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1. Considering the Potential Benefits of Over-the-Counter Naloxone

Author

Evoy KE, Hill LG, and Davis CS

Subjects
opioid, opioid overdose, naloxone, naloxone access law, over-the-counter, Pharmacy and materia medica, RS1-441
Abstract

Kirk E Evoy,1 Lucas G Hill,2 Corey S Davis3 1University Health, Department of Pharmacy, The University of Texas at Austin College of Pharmacy, San Antonio, TX, USA; 2Pharmacy Practice, The University of Texas at Austin College of Pharmacy, Austin, TX, USA; 3Harm Reduction Legal Project, Los Angeles, CA, USACorrespondence: Kirk E Evoy Email evoy@uthscsa.eduAbstract: Since 1999, annual opioid-related overdose (ORO) mortality has increased more than six-fold. In response to this crisis, the US Department of Health and Human Services outlined a 5-point strategy to reduce ORO mortality which included the widespread distribution of naloxone, an opioid antagonist that can rapidly reverse an opioid overdose. Increased distribution has been facilitated by the implementation of naloxone access laws in each US state aimed at increasing community access to naloxone. While these laws differ from state-to-state, most contain mechanisms to enable pharmacists to dispense naloxone without a patient-specific prescription. These laws have enhanced community naloxone distribution, both from pharmacies and overdose education and naloxone distribution programs, and produced positive effects on ORO mortality. However, a growing body of evidence has revealed that significant barriers to naloxone access from pharmacies remain, and annual ORO deaths have continued to climb. Given these concerns, there has been a push among some clinicians and policymakers for the US Food and Drug Administration to re-classify naloxone as an over-the-counter (OTC) medication as a means to further increase its accessibility. If an OTC transition occurs, educational outreach and funding for clinical innovations will continue to be crucial given the important role of health professionals in recommending naloxone to people at risk for experiencing or witnessing an ORO. Recognizing the severity of the ORO public health crisis, we believe transitioning formulations of naloxone approved for layperson use to OTC status would result in a net benefit through increased access. However, such a change should be combined with measures to ensure affordability.Keywords: opioid, opioid overdose, naloxone, naloxone access law, over-the-counter

Published
2021

2. Reply to Letter to the Editor Regarding Article: “Considering the Potential Benefits of Over-The-Counter Naloxone” [Response To Letter]

Author

Evou KE, Hill LG, and Davis CS

Subjects
Pharmacy and materia medica, RS1-441
Abstract

Kirk E Evoy,1,2 Lucas G Hill,3 Corey S Davis4 1Division of Pharmacotherapy, The University of Texas at Austin College of Pharmacy, San Antonio, TX, USA; 2Department of Pharmacy, University Health, San Antonio, TX, USA; 3Division of Pharmacy Practice, The University of Texas at Austin College of Pharmacy, Austin, TX, USA; 4Harm Reduction Legal Project, Los Angeles, CA, USACorrespondence: Kirk E Evoy Email evoy@uthscsa.edu View the original paper by Dr Evoy and colleagues This is in response to the Letter to the Editor

Published
2021

3. Fixed-dose combinations in type 2 diabetes – role of the canagliflozin metformin combination

Author

Fleming JW, Fleming LW, and Davis CS

Subjects
Specialties of internal medicine, RC581-951
Abstract

Joshua W Fleming, Laurie W Fleming, Courtney S Davis Department of Pharmacy Practice, The University of Mississippi School of Pharmacy, Jackson, MS, USA Abstract: Canagliflozin–metformin is one of the newest combination therapies available for the treatment of type 2 diabetes mellitus (T2DM). Canagliflozin is an inhibitor of the sodium–glucose co-transporter 2 which causes an increase in the urinary excretion of glucose. In the present article, we review the safety and efficacy of canagliflozin and metformin from data obtained from Phase III metformin add-on therapy clinical trials as there are no studies to date that specifically evaluate the combination of metformin and canagliflozin. Trials included in this review were dual-therapy trials of subjects who were already taking background metformin and were assigned to receive canagliflozin, glimepiride, or sitagliptin. The addition of canagliflozin to metformin resulted in a decrease in HbA1c of 0.73%–0.93%. Canagliflozin 100 mg was considered to be non-inferior to glimepiride and sitagliptin 100 mg with the canagliflozin 300 mg dose being statistically superior to sitagliptin and glimepiride. Other advantages of the use of canagliflozin are reduction in weight (3.3–4.0 kg) and systolic blood pressure (3.3–4.7 mmHg). The primary disadvantages are potential genital mycotic infections, hypotension, and gastrointestinal side effects from metformin. All things considered, this combination appears to be safe and effective in clinical trials and represents a promising option for the treatment of T2DM. Keywords: type 2 diabetes, fixed-dose combination (FDC), canagliflozin metformin

Published
2015

4. Climate impacts on zooplankton population dynamics in coastal marine ecosystems

Author

Batchelder, HP, Daly, KL, Davis, CS, Ji, R, Ohman, MD, Peterson, WT, and Runge, JA

Subjects
Oceanography
Abstract

The 20-year US GLOBEC (Global Ocean Ecosystem Dynamics) program examined zooplankton populations and their predators in four coastal marine ecosystems. Program scientists learned that environmental controls on zooplankton vital rates, especially the timing and magnitude of reproduction, growth, life-cycle progression, and mortality, determine species population dynamics, seasonal and spatial distributions, and abundances. Improved knowledge of spatialtemporal abundance and distribution of individual zooplankton taxa coupled with new information linking higher trophic level predators (salmon, cod, haddock, penguins, seals) to their prey yielded mechanistic descriptions of how climate variation impacts regionally important marine resources. Coupled ecological models driven by improved regional-scale climate scenario models developed during GLOBEC enable forecasts of plausible future conditions in coastal ecosystems, and will aid and inform decision makers and communities as they assess, respond, and adapt to the effects of environmental change. Multi-region synthesis revealed that conditions in winter, before upwelling, or seasonal stratification, or ice melt (depending on region) had significant and important effects that primed the systems for greater zooplankton population abundance and productivity the following spring summer, with effects that propagated to higher trophic levels. © 2013 by The Oceanography Society. All rights reserved.

Published
2013

6. A double-blind, placebo-controlled multicenter study of tacrine for Alzheimer's disease. The Tacrine Collaborative Study Group.

Author

Davis, KL, Thal, LJ, Gamzu, ER, Davis, CS, Woolson, RF, Gracon, SI, Drachman, DA, Schneider, LS, Whitehouse, PJ, and Hoover, TM

Subjects
Humans, Alzheimer Disease, Tacrine, Activities of Daily Living, Double-Blind Method, Psychological Tests, Middle Aged, Dementia, Clinical Trials and Supportive Activities, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias, Neurodegenerative, Aging, Brain Disorders, Alzheimer's Disease, Acquired Cognitive Impairment, Clinical Research, Behavioral and Social Science, Mental Health, 6.1 Pharmaceuticals, Neurological, General & Internal Medicine, Medical and Health Sciences
Abstract

BackgroundIn Alzheimer's disease, there is a marked decline in the function of cholinergic neurons in the brain. However, studies of treatment with cholinesterase inhibitors have produced conflicting results. We conducted a multicenter trial to evaluate whether the cholinesterase inhibitor tacrine (1,2,3,4-tetrahydro-9-acridinamine monohydrochloride monohydrate) could improve cognition in patients with Alzheimer's disease.MethodsOf 632 eligible patients with probable Alzheimer's disease, 215 improved while receiving tacrine during a preliminary crossover phase to determine responsiveness and the best dose. The 215 patients were randomly assigned to receive either placebo or their best dose of tacrine (10 or 20 mg four times a day) in a six-week, double-blind trial. The primary measures of efficacy were the cognitive subscale of the Alzheimer's Disease Assessment Scale and the Clinical Global Impression of Change scale; the secondary measures included the Mini-Mental State Examination and the assessment of the activities of daily living.ResultsAt the end of the six-week trial, the patients receiving tacrine had a mean adjusted cognitive-subscale score of 30.3 (Alzheimer's Disease Assessment Scale) as compared with 32.7 in patients receiving placebo. This represents a smaller decline (by 2.4 points) in cognitive performance in the tacrine group (P < 0.001). There were no differences between the groups in their global-rating scores. The tacrine group had a significantly smaller decline in the activities of daily living. The results of the Mini-Mental State Examination favored tacrine, but the differences were small and not statistically significant (a score of 16.0 with tacrine vs. 15.3 with placebo; P = 0.08). Gastrointestinal symptoms, elevation of aminotransferase levels, and headache were the most frequent side effects; all could be reversed by reducing the dose or discontinuing treatment.ConclusionsIn this short-term study in patients with Alzheimer's disease who were selected for apparent responsiveness to tacrine, treatment with tacrine resulted in a statistically significant reduction in the decline of cognitive function, although this reduction was not large enough to be detected by the study physicians' global assessments of the patients.

Published
1992

8. Observation of interfacial damage in a silk‐epoxy composite, using hyperspectral and fluorescence lifetime imaging of a simple mechanoresponsive fluorescent probe

Author

Woodcock, JW, Beams, R, Davis, CS, Chen, N, Stranick, SJ, Shah, DU, Vollrath, F, and Gilman, JW

Abstract

Polymer composites are found throughout the world both natural and artificial in origin. In the vast majority of applications, composites serve as structural support or reinforcement roles. Demand for lightweight tough composites is growing in multiple application spaces such as areospace, biomaterials, and infrastructure with physical properties as diverse as the applications. The unifying component in all composites is the presence of an interphase. Many measurement techniques and measurement tools have been developed for the study of this crucial region in composite materials. Many of these methods are great for the measurment and study of bulk properties or model systems. However, development of methods that permit the direct observation of interactions at the interphase during applied stress are needed. Here we employ fluorescence lifetime imaging and hyperspectral imaging to observe activation of a fluorogenic dye at the composite interface as a result of applied stress. The advantages of this sytem include commercial availability of the dye precursor, and simple one-pot functionalization. The attachment of the dye at the interface is easily monitored through emission wavelength shifts and fluorescence lifetime variations. Interfacial mechano-responsive dyes have potential for both fundamental studies as well as industrial use as a structural health monitoring tool.

Published
2017

10. Nusinersen versus sham control in infantile-onset spinal muscular atrophy

Author

Finkel, RS, Mercuri, E, Darras, BT, Connolly, AM, Kuntz, NL, Kirschner, J, Chiriboga, CA, Saito, K, Servais, L, Tizzano, E, Topaloglu, H, Tulinius, M, Montes, J, Glanzman, AM, Bishop, K, Zhong, ZJ, Gheuens, S, Bennett, CF, Schneider, E, Farwell, W, De Vivo, DC, Bradley, WG, Schroth, MK, Bodensteriner, JB, Davis, CS, Shell, R, Hen, J, Austin, ED, Aziz-Zaman, S, Cappell, J, Constantinescu, A, Cruz, R, Dastgir, J, Dunaway, S, Engelstad, K, Gormley, M, Holuba La Marca, N, Khandji, A, Kramer, S, Marra, J, Ortiz-Miller, C, Popolizio, M, Salazar, R, Sanabria, L, Weimer, L, Anand, P, Gadeken, R, Golumbek, PT, Siener, C, Zaidman, CM, Al-Ghamdi, F, Berde, C, Ghosh, P, Graham, R, Harrington, T, Koka, A, Laine, R, Liew, W, Mirek, E, Ordonez, G, Pasternak, A, Quigley, J, Sethna, N, Souris, M, Szelag, H, Wand, L, Day, JW, D'Souza, G, Duong, TT, Gee, R, Kitsuwa-Lowe, J, McFall, D, Patnaik, S, Paulose, S, Perez, J, Proud, C, Purse, B, Ramamurthi, RJ, Sakamuri, S, Sampson, J, Sanjanwala, B, Tesi Rocha, AC, Watson, K, Welsh, L, Pena, LDM, Case, L, Coates, J, DeArmey, S, Homi, MM, Milleson, C, Nelson, N, Ross, A, Smith, E, Taicher, B, Wootton, J, Finanger, E, Benjamin, D, Frank, A, Roberts, C, Russman, B, Finkel, RS, Mercuri, E, Darras, BT, Connolly, AM, Kuntz, NL, Kirschner, J, Chiriboga, CA, Saito, K, Servais, L, Tizzano, E, Topaloglu, H, Tulinius, M, Montes, J, Glanzman, AM, Bishop, K, Zhong, ZJ, Gheuens, S, Bennett, CF, Schneider, E, Farwell, W, De Vivo, DC, Bradley, WG, Schroth, MK, Bodensteriner, JB, Davis, CS, Shell, R, Hen, J, Austin, ED, Aziz-Zaman, S, Cappell, J, Constantinescu, A, Cruz, R, Dastgir, J, Dunaway, S, Engelstad, K, Gormley, M, Holuba La Marca, N, Khandji, A, Kramer, S, Marra, J, Ortiz-Miller, C, Popolizio, M, Salazar, R, Sanabria, L, Weimer, L, Anand, P, Gadeken, R, Golumbek, PT, Siener, C, Zaidman, CM, Al-Ghamdi, F, Berde, C, Ghosh, P, Graham, R, Harrington, T, Koka, A, Laine, R, Liew, W, Mirek, E, Ordonez, G, Pasternak, A, Quigley, J, Sethna, N, Souris, M, Szelag, H, Wand, L, Day, JW, D'Souza, G, Duong, TT, Gee, R, Kitsuwa-Lowe, J, McFall, D, Patnaik, S, Paulose, S, Perez, J, Proud, C, Purse, B, Ramamurthi, RJ, Sakamuri, S, Sampson, J, Sanjanwala, B, Tesi Rocha, AC, Watson, K, Welsh, L, Pena, LDM, Case, L, Coates, J, DeArmey, S, Homi, MM, Milleson, C, Nelson, N, Ross, A, Smith, E, Taicher, B, Wootton, J, Finanger, E, Benjamin, D, Frank, A, Roberts, C, and Russman, B

Abstract

BACKGROUND: Spinal muscular atrophy is an autosomal recessive neuromuscular disorder that is caused by an insufficient level of survival motor neuron (SMN) protein. Nusinersen is an antisense oligonucleotide drug that modifies pre–messenger RNA splicing of the SMN2 gene and thus promotes increased production of full-length SMN protein. METHODS: We conducted a randomized, double-blind, sham-controlled, phase 3 efficacy and safety trial of nusinersen in infants with spinal muscular atrophy. The primary end points were a motor-milestone response (defined according to results on the Hammersmith Infant Neurological Examination) and event-free survival (time to death or the use of permanent assisted ventilation). Secondary end points included overall survival and subgroup analyses of event-free survival according to disease duration at screening. Only the first primary end point was tested in a prespecified interim analysis. To control the overall type I error rate at 0.05, a hierarchical testing strategy was used for the second primary end point and the secondary end points in the final analysis. RESULTS: In the interim analysis, a significantly higher percentage of infants in the nusinersen group than in the control group had a motor-milestone response (21 of 51 infants [41%] vs. 0 of 27 [0%], P<0.001), and this result prompted early termination of the trial. In the final analysis, a significantly higher percentage of infants in the nusinersen group than in the control group had a motor-milestone response (37 of 73 infants [51%] vs. 0 of 37 [0%]), and the likelihood of event-free survival was higher in the nusinersen group than in the control group (hazard ratio for death or the use of permanent assisted ventilation, 0.53; P=0.005). The likelihood of overall survival was higher in the nusinersen group than in the control group (hazard ratio for death, 0.37; P=0.004), and infants with a shorter disease duration at screening were more likely than those with a longer disea

Published
2017

11. Salp grazing:effects on phytoplankton abundance, vertical distribution and taxonomic composition in a coastal habitat

Author

Ballara Sl, Zeldis, Chang Fh, Davis Cs, James Mr, and Booth We

Subjects
Ecology, biology, business.industry, Distribution (economics), Aquatic Science, biology.organism_classification, Taxonomic composition, Oceanography, Habitat, Abundance (ecology), Phytoplankton, Grazing, Environmental science, business, Ecology, Evolution, Behavior and Systematics, Salp
Published
1995

14. Genetic linkage map of a wild genome: genomic structure, recombination and sexual dimorphism in bighorn sheep

Author

Poissant, J, Hogg, JT, Davis, CS, Miller, JM, Maddox, JF, Coltman, DW, Poissant, J, Hogg, JT, Davis, CS, Miller, JM, Maddox, JF, and Coltman, DW

Abstract

BACKGROUND: The construction of genetic linkage maps in free-living populations is a promising tool for the study of evolution. However, such maps are rare because it is difficult to develop both wild pedigrees and corresponding sets of molecular markers that are sufficiently large. We took advantage of two long-term field studies of pedigreed individuals and genomic resources originally developed for domestic sheep (Ovis aries) to construct a linkage map for bighorn sheep, Ovis canadensis. We then assessed variability in genomic structure and recombination rates between bighorn sheep populations and sheep species. RESULTS: Bighorn sheep population-specific maps differed slightly in contiguity but were otherwise very similar in terms of genomic structure and recombination rates. The joint analysis of the two pedigrees resulted in a highly contiguous map composed of 247 microsatellite markers distributed along all 26 autosomes and the X chromosome. The map is estimated to cover about 84% of the bighorn sheep genome and contains 240 unique positions spanning a sex-averaged distance of 3051 cM with an average inter-marker distance of 14.3 cM. Marker synteny, order, sex-averaged interval lengths and sex-averaged total map lengths were all very similar between sheep species. However, in contrast to domestic sheep, but consistent with the usual pattern for a placental mammal, recombination rates in bighorn sheep were significantly greater in females than in males (~12% difference), resulting in an autosomal female map of 3166 cM and an autosomal male map of 2831 cM. Despite differing genome-wide patterns of heterochiasmy between the sheep species, sexual dimorphism in recombination rates was correlated between orthologous intervals. CONCLUSIONS: We have developed a first-generation bighorn sheep linkage map that will facilitate future studies of the genetic architecture of trait variation in this species. While domestication has been hypothesized to be responsible for the

Published
2010

27. The aging of elite male athletes: age-related changes in performance and skeletal muscle structure and function.

Author

Faulkner JA, Davis CS, Mendias CL, and Brooks SV

Abstract

OBJECTIVE:: The paper addresses the degree to which the attainment of the status as an elite athlete in different sports ameliorates the known age-related losses in skeletal muscle structure and function. DESIGN:: The retrospective design, based on comparisons of published data on former elite and masters athletes and data on control subjects, assessed the degree to which the attainment of elite and masters athlete status ameliorated the known age-related changes in skeletal muscle structure and function. SETTING:: Institutional. PARTICIPANTS:: Elite male athletes. INTERVENTIONS:: Participation in selected individual and team sports. MAIN OUTCOME MEASUREMENTS:: Strength, power, VO2max, and performance. RESULTS:: For elite athletes in all sports, as for the general population, age-related muscle atrophy begins at about 50 years of age. Despite the loss of muscle mass, elite athletes who maintain an active lifestyle age gracefully with few health problems. Conversely, those who lapse into inactivity regress toward general population norms for fitness, weight control, and health problems. Elite athletes in the dual and team sports have careers that rarely extend into their 30s. CONCLUSIONS:: Lifelong physical activity does not appear to have any impact on the loss in fiber number. The loss of fibers can be buffered to some degree by hypertrophy of fibers that remain. It is surprising that the performance of elite athletes in all sports appears to be impaired before the onset of the fiber loss. Even with major losses in physical capacity and muscle mass, the performance of elite and masters athletes is remarkable. [ABSTRACT FROM AUTHOR]

Published
2008
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28. Expressive, research and reflective poetry as qualitative inquiry: a study of adolescent identity.

Author

Furman R, Langer CL, Davis CS, Gallardo HP, and Kulkarni S

Subjects
POETRY (Literary form), DEVELOPMENTAL psychology, QUALITATIVE research, SOCIAL sciences, ARTS & society, LITERATURE
Abstract

This article explores the uses of poetry in qualitative research. In this study of adolescent identity and development, poetry is used as data, as a means of data representation, and as a process of inquiry. The authors explore the nature of poetry as a tool of qualitative research for investigating human phenomena. Autobiographical poems are used as data which are analysed through thematic analysis. From this analysis, research poems in the form of Japanese tankas are created. Finally, the third and fourth authors respond to the original poems and the 'findings' from the grounded theory analysis as responsive poems. [ABSTRACT FROM AUTHOR]

Published
2007
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31. Occupational injuries among workers with disabilities: the National Health Interview Survey, 1985-1994.

Author

Zwerling C, Whitten PS, Davis CS, Sprince NL, Zwerling, C, Whitten, P S, Davis, C S, and Sprince, N L

Abstract

Context: As the baby boom generation ages, more people will be working with disabilities, but we have little information regarding how disabilities affect risk for occupational injury.Objective: To test the hypothesis that work-limiting disabilities in general and hearing and visual impairments in particular are risk factors for occupational injuries.Design: Retrospective cohort study.Setting: The National Health Interview Survey (NHIS), 1985 to 1994.Participants: The 459827 participants in the NHIS from 1985 to 1994 who listed "working" as their primary activity, who were not farmers, and who were between 18 and 65 years of age.Main Outcome Measure: Occupational injuries in the year preceding the interview causing a residual impairment at the time of interview.Results: After adjusting for occupation, self-employment, and age, occupational injury was associated with preceding work disability (odds ratio [OR], 1.36; 95% confidence interval [CI], 1.19-1.56); blindness (OR, 3.21; 95% CI, 1.32-7.85); deafness (OR, 2.19; 95% CI, 1.17-4.12); hearing impairment (OR,1.55; 95% CI, 1.29-1.87); upper extremity impairment (OR, 1.46; 95% CI, 1.05-2.05); and arthritis (OR, 1.34; 95% CI, 1.07-1.68). Visual impairment was not associated with a significantly increased risk (OR, 1.37; 95% CI, 0.87-2.17).Conclusions: Workers with disabilities, especially sensory impairments, appear to have an elevated risk for occupational injury. Further research in the design and evaluation of improved workplace accommodations for workers with these disabilities is needed. [ABSTRACT FROM AUTHOR]

Published
1997
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32. Survival of patients surgically treated for Stage I lung cancer

Author

Peter C. Pairolero, Robert S. Fontana, Uhlenhopp Ma, W S Payne, David E. Williams, Davis Cs, Taylor Wf, and Philip E. Bernatz

Subjects
Pulmonary and Respiratory Medicine, medicine.medical_specialty, Stage I Lung Cancer, business.industry, TNM staging system, medicine.disease, Bronchogenic carcinoma, Internal medicine, Adjuvant therapy, Medicine, Surgery, Cardiology and Cardiovascular Medicine, business, Lung cancer, Pathological, Survival analysis, Cancer staging
Abstract

When the TNM staging system of the American Joint Committee (AJC) for Cancer Staging and End-Results Reporting was applied to 3,912 patients seen during a 6 year period at the Mayo Clinic, 624 (16%) fulfilled the criteria for postsurgical pathological Stage I non-small cell bronchogenic carcinoma. Of these 624 patients, 129 were excluded from further survival analysis for various reasons. The remaining 495 consisted of two groups: 350 patients who were enrolled within 30 days into a prospective postoperative 4 monthly follow-up program and 145 patients who were enrolled later or were followed less frequently. Because no significant difference was noted in survival rates between these groups, data were pooled. Of the combined group of 495 patients, 84% survived lung cancer for 2 years and 69% of 5 years (actuarial estimation). The survival of patients classified T1 N0 M0 (91% alive at 2 years and 80% at 5 years) is so good that it seems unlikely that adjuvant therapy in this group could demonstrate improved survival. In addition to TNM classification, age at operation, sex, and extent of operation were important determinants of survival.

Published
1981

35. Stable evaluation of 3D Zernike moments for surface meshes

Author

Patrice Koehl, Jérôme Houdayer, Institut de Physique Théorique - UMR CNRS 3681 (IPHT), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California [Davis] (UC Davis), and University of California (UC)-University of California (UC)

Subjects
Computational Mathematics, Numerical Analysis, Zernike moments, Computational Theory and Mathematics, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], Zernike polynomials, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], shape signatures, Theoretical Computer Science
Abstract

Special Issue Computational Methods and Optimization for Numerical Analysis; International audience; The 3D Zernike polynomials form an orthonormal basis of the unit ball. The associated 3D Zernike moments have been successfully applied for 3D shape recognition; they are popular in structural biology for comparing protein structures and properties. Many algorithms have been proposed for computing those moments, starting from a voxel-based representation or from a surface based geometric mesh of the shape. As the order of the 3D Zernike moments increases, however, those algorithms suffer from decrease in computational efficiency and more importantly from numerical accuracy. In this paper, new algorithms are proposed to compute the 3D Zernike moments of a homogeneous shape defined by an unstructured triangulation of its surface that remove those numerical inaccuracies. These algorithms rely on the analytical integration of the moments on tetrahedra defined by the surface triangles and a central point and on a set of novel recurrent relationships between the corresponding integrals. The mathematical basis and implementation details of the algorithms are presented and their numerical stability is evaluated.

Published
2022

36. LOTVS: A global collection of permanent vegetation plots

Author

Marta Gaia Sperandii, Francesco de Bello, Enrique Valencia, Lars Götzenberger, Manuele Bazzichetto, Thomas Galland, Anna E‐Vojtkó, Luisa Conti, Peter B. Adler, Hannah Buckley, Jiří Danihelka, Nicola J. Day, Jürgen Dengler, David J. Eldridge, Marc Estiarte, Ricardo García‐González, Eric Garnier, Daniel Gómez‐García, Lauren Hallett, Susan Harrison, Tomas Herben, Ricardo Ibáñez, Anke Jentsch, Norbert Juergens, Miklós Kertész, Duncan M. Kimuyu, Katja Klumpp, Mike Le Duc, Frédérique Louault, Rob H. Marrs, Gábor Ónodi, Robin J. Pakeman, Meelis Pärtel, Begoña Peco, Josep Peñuelas, Marta Rueda, Wolfgang Schmidt, Ute Schmiedel, Martin Schuetz, Hana Skalova, Petr Šmilauer, Marie Šmilauerová, Christian Smit, Ming‐Hua Song, Martin Stock, James Val, Vigdis Vandvik, Karsten Wesche, Susan K. Wiser, Ben A. Woodcock, Truman P. Young, Fei‐Hai Yu, Amelia A. Wolf, Martin Zobel, Jan Lepš, Centro de Investigaciones sobre Desertificacion (CIDE), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Universidad Rey Juan Carlos [Madrid] (URJC), Institute of Botany of the Czech Academy of Sciences (IB / CAS), Czech Academy of Sciences [Prague] (CAS), UNIVERSITY OF SOUTH BOHEMIA CESKE BUDEJOVICE CZE, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Czech University of Life Sciences Prague (CZU), Utah State University (USU), Auckland University of Technology (AUT), Masaryk University [Brno] (MUNI), Victoria University of Wellington, Zürich University of Applied Sciences (ZHAW), University of New South Wales [Kensington], CREAF - Centre for Ecological Research and Applied Forestries, Instituto Pirenaico de Ecologìa = Pyrenean Institute of Ecology [Zaragoza] (IPE - CSIC), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), University of Oregon, Eugene, OR 97403, United States, University of California (UC), Department of Zoology, Charles University in Prague, Faculty of Science, Viniicna 7, 128 43 Praha 2, Universidad Pública de Navarra [Espagne] = Public University of Navarra (UPNA), University of Hamburg, Hungarian Academy of Sciences (MTA), University of Liverpool, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), The James Hutton Institute, University of Tartu, Autonomous University of Madrid, Faculty of Sciences, Department of Ecology, 28049 Madrid, Spain, Universidad de Sevilla / University of Sevilla, Centre for Biodiversity and Sustainable Land-use [University of Göttingen] (CBL), Georg-August-University = Georg-August-Universität Göttingen, Hamburg University of Applied Sciences [Hamburg], Swiss Federal Institute for Forest, Snow and Landscape Research WSL, University of South Bohemia, Groningen Institute for Evolutionary Life Sciences [Groningen] (GELIFES), University of Groningen [Groningen], Chinese Academy of Agricultural Sciences (CAAS), Wadden Sea National Park of Schleswig-Holstein, University of Bergen (UiB), Senckenberg Museum of Natural History Görlitz, Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, Manaaki Whenua – Landcare Research [Lincoln], Center for Ecology and Hydrology, Taizhou University, University of Texas-Pan, Smit group, Royal Society of New Zealand, Czech Science Foundation, Academy of Sciences of the Czech Republic, Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), Institut National de la Recherche Agronomique (France), Federal Ministry of Education and Research (Germany), Oberfranken Stiftung, Agence Nationale de la Recherche (France), Scottish Government's Rural and Environment Science and Analytical Services, Estonian Research Council, European Commission, Fundación Ramón Areces, Generalitat de Catalunya, European Research Council, Dresden University of Technology, Ministry of Business, Innovation, and Employment (New Zealand), Natural Environment Research Council (UK), Biotechnology and Biological Sciences Research Council (UK), Comunidad de Madrid, Universidad Rey Juan Carlos, National Science Foundation (US), South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses [University of South Bohemia] (CENAKVA), Faculty of Fisheries and Protection of Waters [University of South Bohemia], University of South Bohemia -University of South Bohemia, Desertification Research Centre (CIDE), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Universitat de València (UV), University of Bayreuth, German Centre for Integrative Biodiversity Research (iDiv), University of New South Wales [Sydney] (UNSW), Centre for Ecological Research and Forestry Applications (CREAF), Unit CREAF-CSIC-UABB, Global Ecology Unit (CREAF-CSIC-UAB), Université de Montpellier (UM), Institut de Recherche pour le Développement (IRD), Department of Mathematics, University of Oregon [Eugene], University of Oregon [Eugene], Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), Charles University [Prague] (CU), Distributed Events Analysis Research Group (MTA SZTAKI Hungarian Academy of Sciences), Mpala Research Centre, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Université Clermont Auvergne (UCA), Institute of Computer Science [University of Tartu, Estonie], Centre de Recerca Ecològica i Aplicacions Forestals - Centre for Ecological Research and Forestry Applications, Partenaires INRAE, University of Chinese Academy of Sciences [Beijing] (UCAS), Lake Ecosystems Group [Lancaster, U.K.] (Centre for Ecology & Hydrology), Lancaster Environment Centre [Lancaster, U.K.], Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, Taizhou University, Taizhou, China, Department of Electrical and Computer Engineering - University of Texas (ECE), University of Texas at Austin [Austin], ANR-11-INBS-0001,ANAEE-FR,ANAEE-Services(2011), Sperandii, M. G., de Bello, F., Valencia, E., Gotzenberger, L., Bazzichetto, M., Galland, T., E-Vojtko, A., Conti, L., Adler, P. B., Buckley, H., Danihelka, J., Day, N. J., Dengler, J., Eldridge, D. J., Estiarte, M., Garcia-Gonzalez, R., Garnier, E., Gomez-Garcia, D., Hallett, L., Harrison, S., Herben, T., Ibanez, R., Jentsch, A., Juergens, N., Kertesz, M., Kimuyu, D. M., Klumpp, K., Le Duc, M., Louault, F., Marrs, R. H., Onodi, G., Pakeman, R. J., Partel, M., Peco, B., Penuelas, J., Rueda, M., Schmidt, W., Schmiedel, U., Schuetz, M., Skalova, H., Smilauer, P., Smilauerova, M., Smit, C., Song, M. -H., Stock, M., Val, J., Vandvik, V., Wesche, K., Wiser, S. K., Woodcock, B. A., Young, T. P., Yu, F. -H., Wolf, A. A., Zobel, M., and Leps, J.

Subjects
Plant communities, temporal analysis, Plant community, Plant Science, ecological succession, Permanent plot, ecoinformatic, plant communitie, Ecology and Environment, ecoinformatics, vegetation, Ecological succession, Ecoinformatics, Global scale, 577: Ökologie, time-serie, Vegetation, ecosystem stability, Ecology, time-series, Temporal analysis, permanent plot, plant diversity, plant communities, temporal analysi, 580: Pflanzen (Botanik), Plant diversity, global scale, Ecosystem stability, Permanent plots, Time-series, permanent plots, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology., The authors acknowledge institutional support as follows. Nicola J. Day: Te Apārangi Royal Society of New Zealand (Rutherford Postdoctoral Fellowship). Jiří Danihelka: Czech Science Foundation (project no. 19-28491X) and Czech Academy of Sciences (project no. RVO 67985939). Francesco de Bello: Spanish Plan Nacional de I+D+i (project PGC2018-099027-B-I00). Eric Garnier: La Fage INRA experimental station. Tomáš Herben: GAČR grant 20-02901S. Anke Jentsch: German Federal Ministry of Education and Research (grant 031B0516C - SUSALPS) and Oberfrankenstiftung (grant OFS FP00237). Norbert Juergens: German Federal Ministry of Education and Research (grant 01LG1201N - SASSCAL ABC). Frédérique Louault and Katja Klumpp: AnaEE-France (ANR-11-INBS-0001). Robin J. Pakeman: Strategic Research Programme of the Scottish Government's Rural and Environment Science and Analytical Services Division. Meelis Pärtel: Estonian Research Council (PRG609) and European Regional Development Fund (Centre of Excellence EcolChange). Josep Peñuelas: Spanish Government (grant PID2019-110521GB-I00), Fundación Ramon Areces (grant ELEMENTAL-CLIMATE), Catalan Government (grant SGR 2017-1005), and European Research Council (Synergy grant ERC-SyG-2013-610028, IMBALANCE-P). Ute Schmiedel: German Federal Ministry of Education and Research (Promotion numbers 01LC0024, 01LC0024A, 01LC0624A2, 01LG1201A, 01LG1201N). Hana Skálová: GAČR grant 20-02901S. Karsten Wesche: International Institute Zittau, Technische Universität Dresden. Susan K. Wiser: New Zealand Ministry for Business, Innovation and Employment’s Strategic Science Investment Fund. Ben A. Woodcock: NERC and BBSRC (NE/N018125/1 LTS-M ASSIST - Achieving Sustainable Agricultural Systems). Enrique Valencia: Program for attracting and retaining talent of Comunidad de Madrid (no. 2017-T2/AMB-5406) and Community of Madrid and Rey Juan Carlos University (Young Researchers R&D Project. Ref. M2165 – INTRANESTI). Truman P. Young: National Science Foundation (LTREB DEB 19-31224).

Published
2022

37. Using ChemCam LIBS data to constrain grain size in rocks on Mars: Proof of concept and application to rocks at Yellowknife Bay and Pahrump Hills, Gale crater

Author

Olivier Forni, Sylvestre Maurice, Amy J. Williams, Nicolas Mangold, Kathryn M. Stack, Horton E. Newsom, Marion Nachon, Jonas L'Haridon, Dawn Y. Sumner, Olivier Gasnault, Roger C. Wiens, Frances Rivera-Hernandez, University of California [Davis] (UC Davis), University of California, Laboratoire de Planétologie et Géodynamique [UMR 6112] (LPG), Université d'Angers (UA)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Institut de recherche en astrophysique et planétologie (IRAP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Davis] (UC Davis), University of California-University of California, Los Alamos National Laboratory (LANL), Department of Earth and Planetary Sciences [Davis], Université d'Angers (UA)-Université de Nantes - Faculté des Sciences et des Techniques, Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Météo France-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Météo France-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS), Institute of Meteoritics [Albuquerque] (IOM), The University of New Mexico [Albuquerque], Department of Physics, Astronomy, and Geosciences [Towson], Towson University [Towson, MD, United States], University of Maryland System-University of Maryland System, University of California (UC), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Univ California Davis] (CS - UC Davis), and University of California (UC)-University of California (UC)

Subjects
Martian, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Bedrock, Mineralogy, Astronomy and Astrophysics, Mars Exploration Program, Exploration of Mars, 01 natural sciences, Grain size, Sedimentary depositional environment, [SDU.STU.PL]Sciences of the Universe [physics]/Earth Sciences/Planetology, [SDU]Sciences of the Universe [physics], 13. Climate action, Space and Planetary Science, 0103 physical sciences, Sedimentary rock, Laser-induced breakdown spectroscopy, 010303 astronomy & astrophysics, ComputingMilieux_MISCELLANEOUS, Geology, 0105 earth and related environmental sciences
Abstract

Grain size in martian sedimentary rocks can be constrained using point-to-point chemical variabilities in Laser Induced Breakdown Spectroscopy (LIBS) data from the ChemCam instrument on the Mars Science Laboratory (MSL) Curiosity rover. The diameter of each point ablated by the ChemCam laser is in the range of medium to coarse sand in size. Thus, rocks with grains significantly smaller than the laser spot size produce bulk rock compositions at each LIBS point and low point-to-point chemical variability among LIBS points. In contrast, analyses of rocks with grains about the size of the spot or larger contain contributions from individual grains at each point and often have high point-to-point chemical variability. The Gini index, a statistical parameter, was used to calculate the point-to-point chemical variability in major-element oxide compositions derived from the ChemCam LIBS data. First, the total range of each LIBS major-element oxide composition was normalized from 0 to 1 across all LIBS observations. Then the Gini index was calculated for each oxide in each LIBS observation. Finally, the Gini indices of each oxide were averaged to derive a Gini index mean score, G MEAN , for each LIBS observation. A correlation between G MEAN and grain size was validated using sedimentary rocks of various grain sizes from the Yellowknife Bay formation and the Pahrump Hills member of the Murray formation in Gale crater. Overall, finer-grained rocks had smaller G MEAN than coarser-grained rocks. To calibrate G MEAN to grain size, grain size estimates based on visual assessment of high-resolution images were compared to G MEAN values for the same targets to create a calibrated scale. This calibrated scale was used to infer the grain size of rocks with unknown grain size. Overall, the grain sizes predicted for rocks with unknown grain size overlapped with those of known grain size from the same units and/or bedrock targets. The grain sizes inferred using the G MEAN based on ChemCam LIBS data are complimentary to those determined from images and both techniques can be used to improve interpretations of the depositional environments of rocks analyzed by Curiosity and future Mars missions with LIBS, such as the Mars 2020 rover.

Published
2019

38. The gem5 Simulator: Version 20.0+

Author

Lowe-Power, Jason, Ahmad, Abdul, Armejach, Adria, Herrera, Adrian, Roelke, Alec, Farmahini-Farahani, Amin, Mondelli, Andrea, Hansson, Andreas, Sandberg, Andreas, Gutierrez, Anthony, Harris, Austin, Akram, Ayaz, Hanindhito, Bagus, Pham, Binh, Bruce, Bobby, Shingarov, Boris, Beckmann, Brad, Escuin, Carlos, Menard, Christian, Weis, Christian, Rodrigues Carvalho, Daniel, Wood, David, Gope, Dibakar, Zulian, Éder, Black, Gabe, Bloom, Gedare, Travaglini, Giacomo, Khaleghzadeh, Hamidreza, Jang, Hanhwi, Nguyen, Hoa, Yoon, Hongil, Vougioukas, Ilias, Setoain, Javier, Gandhi, Jayneel, Castrillon, Jeronimo, Nathella, Krishnendra, Olson, Lena, Chen, Lizhong, Samani, Mahyar, Orr, Marc, Fariborz, Marjan, Andreozzi, Matteo, Sinclair, Matthew, Horsnell, Matthew, Jung, Matthias, Upton, Michael, Moreto, Miquel, Alian, Mohammad, Derumigny, Nicolas, Nikoleris, Nikos, Vaish, Nilay, Asmussen, Nils, Wehn, Norbert, Naji, Omar, Prieto, Pablo, Fotouhi, Pouya, Jagtap, Radhika, Thakur, Rahul, Jafri, Raza, Jeyapaul, Reiley, Amslinger, Rico, Gambord, Ryan, Bharadwaj, Srikant, Diestelhorst, Stephan, Kannoth, Subash, Haria, Swapnil, Ali, Syed, Grass, Thomas, Mück, Tiago, Hayes, Timothy, Jones, Timothy, Marinelli, Tommaso, Reddy, Trivikram, Ta, Tuan, Krishna, Tushar, Elsasser, Wendy, Wang, William, Kodama, Yuetsu, Wang, Zhengrong, University of California [Davis] (UC Davis), University of California (UC), University of Kaiserslautern [Kaiserslautern], Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), University of Virginia, ARM Ltd [Cambridge] (ARM), Western Michigan University [Kalamazoo], Institut Teknologi Bandung (ITB), Institute of Materials Science, Vietnam Academy of Science and Technology, Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California (UC)-University of California (UC), Technische Universität Dresden = Dresden University of Technology (TU Dresden), Technische Universität Kaiserslautern (TU Kaiserslautern), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Pushing Architecture and Compilation for Application Performance (PACAP), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-ARCHITECTURE (IRISA-D3), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Fraunhofer Institute for Experimental Software Engineering (Fraunhofer IESE), Fraunhofer (Fraunhofer-Gesellschaft), University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, Uppsala University, Rheinisch-Westfälische Technische Hochschule Aachen University (RWTH), Georgia Institute of Technology [Atlanta], Rodrigues Carvalho, Daniel, University of California, University of Virginia [Charlottesville], Bandung Institute of Technology [Indonesia], Department of Computer Science [Davis] (UC Davis), University of California-University of California, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and RWTH Aachen University

Subjects
[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR], [INFO.INFO-AR] Computer Science [cs]/Hardware Architecture [cs.AR], [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
Abstract

The open-source and community-supported gem5 simulator is one of the most popular tools for computer architecture research. This simulation infrastructure allows researchers to model modern computer hardware at the cycle level, and it has enough fidelity to boot unmodified Linux-based operating systems and run full applications for multiple architectures including x86, Arm®, and RISC-V. The gem5 simulator has been under active development over the last nine years since the original gem5 release. In this time, there have been over 7000 commits to the codebase from over 250 unique contributors which have improved the simulator by adding new features, fixing bugs, and increasing the code quality. In this paper, we give an overview of gem5's usage and features, describe the current state of the gem5 simulator, and enumerate the major changes since the initial release of gem5. We also discuss how the gem5 simulator has transitioned to a formal governance model to enable continued improvement and community support for the next 20 years of computer architecture research.

Published
2021

39. Overview of BirdCLEF 2020: Bird Sound Recognition in Complex Acoustic Environments

Author

Stefan Kahl, Mary Clapp, Alec Hopping, Hervé Goëau, Hervé Glotin, Robert Planqué, Willem-Pier Vellinga, Alexis Joly, Cornell University [New York], Department of Computer Science [University of California, Davis], University of California [Davis] (UC Davis), University of California-University of California, Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Toulon - Faculté de Droit de Toulon (UTLN UFR Droit), Université de Toulon (UTLN), Xeno-canto foundation, Scientific Data Management (ZENITH), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), ANR-18-CE40-0014,SMILES,Modélisation et Inférence Statistique pour l'Apprentissage non-supervisé à partir de Données Massives(2018), ANR-16-CE04-0014,BACTERIEAU,Capteurs innovants pour la surveillance des Escherichia coli dans leau(2016), Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California (UC)-University of California (UC), and Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM)

Subjects
bird, evaluation, call, [INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM], species, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], eco- logical monitoring, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDE.ES]Environmental Sciences/Environmental and Society, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], bioacoustics, benchmark, iden- tification, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], audio, collection, song, LifeCLEF, fine-grained classification, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, retrieval
Abstract

International audience; Passive acoustic monitoring is a cornerstone of the assessment of ecosystem health and the improvement of automated assessment systems has the potential to have a transformative impact on global biodiversity monitoring, at a scale and level of detail that is impossible with manual annotation or other more traditional methods. The BirdCLEF challenge-as part of the 2020 LifeCLEF Lab [12]-focuses on the development of reliable detection systems for avian vocalizations in continuous soundscape data. The goal of the task is to localize and identify all audible birds within the provided soundscape test set. This paper describes the methodology of the conducted evaluation as well as the synthesis of the main results and lessons learned.

Published
2020

40. Assessment of chemical-crosslink-assisted protein structure modeling in CASP13

Author

Bohdan Monastyrskyy, Juri Rappsilber, Krzysztof Fidelis, J. Eduardo Fajardo, Mikhail Karasikov, Alexander Leitner, Agnieszka S. Karczyńska, Andras Fiser, Adam Belsom, Silvia Crivelli, Emilia A. Lubecka, Celina Sikorska, Andriy Kryshtafovych, Nelson Gil, Cezary Czaplewski, Rojan Shrestha, Esben Trabjerg, Sergei Grudinin, Guillaume Pagès, Adam Liwo, Adam K. Sieradzan, Department of Systems & Computational Biology [New York], Albert Einstein College of Medicine [New York], Department of Biochemistry [New York], Institut für Biotechnologie [berlin], Technische Universität Berlin (TU), Department of Computer Science [Davis] (UC Davis), University of California [Davis] (UC Davis), University of California-University of California, Department of Environmental Analytics [Univ Gdańsk], Faculty of Chemistry [Univ Gdańsk], University of Gdańsk (UG)-University of Gdańsk (UG), Genome Center [UC Davis], Algorithms for Modeling and Simulation of Nanosystems (NANO-D), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Moscow Institute of Physics and Technology [Moscow] (MIPT), Skolkovo Institute of Science and Technology [Moscow] (Skoltech), Department of Computer Science [ETH Zürich] (D-INFK), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Institute of Molecular Systems Biology [Zurich], Korea Institute for Advanced Study (KIAS), Institute of Mathematics [Univ Gdańsk], University of Gdańsk (UG), Wellcome Trust Centre for Cell Biology, University of Edinburgh, Technical University of Berlin / Technische Universität Berlin (TU), Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California (UC)-University of California (UC), Algorithms for Modeling and Simulating Nanosystems [2018-...] (NANO-D-POST [2018-2020]), and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
CASP13, Models, Molecular, Computer science, Protein Conformation, Context (language use), Computational biology, Routine practice, 010402 general chemistry, Mass spectrometry, Machine learning, computer.software_genre, 01 natural sciences, Biochemistry, Article, [PHYS.PHYS.PHYS-COMP-PH]Physics [physics]/Physics [physics]/Computational Physics [physics.comp-ph], 03 medical and health sciences, Protein structure, chemical-crosslink-assisted protein structure modeling, Structural Biology, Tandem Mass Spectrometry, Molecular Biology, 030304 developmental biology, 0303 health sciences, Chemistry, business.industry, 030302 biochemistry & molecular biology, Model protein, Computational Biology, Proteins, Reproducibility of Results, 0104 chemical sciences, [SDV.BBM.BP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biophysics, Workflow, Cross-Linking Reagents, Models, Chemical, chemical crosslinking/mass spectrometry, Critical assessment, Artificial intelligence, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], business, Protein structure modeling, computer, Function (biology), Algorithms, Chromatography, Liquid
Abstract

International audience; With the advance of experimental procedures obtaining chemical crosslinking information is becoming a fast and routine practice. Information on crosslinks can greatly enhance the accuracy of protein structure modeling. Here, we review the current state of the art in modeling protein structures with the assistance of experimentally determined chemical crosslinks within the framework of the 13th meeting of Critical Assessment of Structure Prediction approaches. This largest‐to‐date blind assessment reveals benefits of using data assistance in difficult to model protein structure prediction cases. However, in a broader context, it also suggests that with the unprecedented advance in accuracy to predict contacts in recent years, experimental crosslinks will be useful only if their specificity and accuracy further improved and they are better integrated into computational workflows.

Published
2019

41. Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

Author

John Hardy, Nick C. Fox, Lena Lilius, Christine Van Broeckhoven, Mindy J. Katz, Carlos Cruchaga, Joshua W. Miller, Carol Brayne, Letizia Concari, Christopher Shaw, Minerva M. Carrasquillo, Richard Mayeux, Anne Boland, Charles DeCarli, Helena C. Chui, Laura B. Cantwell, Yoland Aladro Benito, Chuang Kuo Wu, Elaine R. Peskind, Andrew McDavid, M. Ilyas Kamboh, Amanda Smith, Pascual Sánchez-Juan, Jean-François Deleuze, Jayanadra J. Himali, Thomas H. Mosley, Thomas J. Montine, Chuanhai Cao, Andreas J. Forstner, Thomas G. Beach, Robert Barber, Miquel Aguilar, Liming Qu, Jerome I. Rotter, Matthew J. Huentelman, Christiane Reitz, Christopher J. O'Donnell, Steven G. Younkin, Bradley T. Hyman, Bruce L. Miller, Rachelle S. Doody, Eric B. Larson, Ronald L. Hamilton, Todd E. Golde, Steven E. Arnold, Melissa E. Garcia, Rachel Raybould, Lena Kilander, Mark A. Sager, Kevin Morgan, Kathryn L. Lunetta, William Perry, Joseph D. Buxbaum, Craig S. Atwood, Thomas D. Bird, Michael Conlon O'Donovan, Robert Olaso, Juan Fortea, Susanne Moebus, Lisa L. Barnes, Rachel Marshall, Huntington Potter, Mercè Boada, Shahzad Ahmad, Paolo Caffarra, Daniel C. Marson, Jonathan L. Haines, Perrie M. Adams, John M Olichney, Lars Lannfelt, Stefanie Heilmann-Heimbach, Markus M. Nöthen, Shubhabrata Mukherjee, John Malamon, Xue Wang, Christopher S. Carlson, Karen Ritchie, Roger N. Rosenberg, Paul K. Crane, Alexa S. Beiser, Céline Bellenguez, Robert C. Green, Maria Urbano, Petra Proitsi, John Powell, Elisa Majounie, Ammar Al-Chalabi, Hakon Hakonarson, Yogen Patel, Martin Scherer, Julie Williams, Richard B. Lipton, Vincent Dermecourt, Adam L. Boxer, Gerard D. Schellenberg, David G. Clark, Anita L. DeStefano, Joel H. Kramer, Victoria Alvarez, Nandini Badarinarayan, Oscar L. Lopez, Chris Corcoran, Ubaldo Bonuccelli, Donald R. Royall, James Bowen, Monica Diez Fairen, Tricia A. Thornton-Wells, Nilufer Ertekin-Taner, Florence Pasquier, Martin Ingelsson, Yi Zhao, John R. Gilbert, Valentina Escott-Price, Amanda B. Kuzma, Fabienne Garzia, Reinhard Heun, Otto Valladares, Andrew J. Saykin, Sara Ortega-Cubero, Liana G. Apostolova, Henry L. Paulson, John K Kauwe, Imelda Barber, Carolina Ceballos Diaz, Douglas Galasko, M. Arfan Ikram, Lluís Tárraga, Carlo Caltagirone, Joan S. Reisch, Wolfgang Maier, Bruno Vellas, Rebecca Sims, Angela Hodges, Matthew P. Frosch, Isabel Henández, Annakaisa Haapasalo, Thor Aspelund, Håkan Thonberg, Aimee Pierce, Roger L. Albin, Wayne W. Poon, Rebecca Sussams, Amy Braddel, Ranjan Duara, Albert V. Smith, Kirk C. Wilhelmsen, Gianfranco Spalletta, Simon Lovestone, Peter Passmore, Ana Frank-García, Cynthia M. Carlsson, Jade Chapman, Nathan D. Price, Philip L. De Jager, John M. Ringman, Seung Hoan Choi, Nicola Denning, Michael John Owen, Clinton T. Baldwin, Amalia C. Bruni, Denis A. Evans, Rudolph E. Tanzi, Dominique Campion, Laura Fratiglioni, Alberto Lleó, Per Hoffmann, Carole Dufouil, Charlotte Forsell, Alun Meggy, Charlene Thomas, Robert S. Stern, James B. Leverenz, Tatiana Foroud, William W. Seeley, James J. Lah, Brian A. Lawlor, Kenneth B. Fallon, Matthias Riemenschneider, Ryan M. Huebinger, Regina M. Carney, Clinton B. Wright, Didier Hannequin, Deborah Blacker, Anne Kinhult-Ståhlbom, Ekaterina Rogaeva, Andrew P. Lieberman, Bernardino Ghetti, Linda J. Van Eldik, Bernadette McGuinness, Thomas Fairchild, Margaret A. Pericak-Vance, Ashok Raj, Reinhold Schmidt, Ronald C. Petersen, Harald Hampel, María J. Bullido, Steven L. Carroll, Maria Candida Deniz Naranjo, Kathleen A. Welsh-Bohmer, Myriam Fornage, Joseph F. Quinn, Caroline Graff, Claudia L. Satizabal, Patrice L. Whitehead, David Wallon, Christopher Medway, Lindsay A. Farrer, Vilmundur Gudnason, Peter St George-Hyslop, Pau Pastor, Frank Jessen, Erin L. Abner, Johanna Jakobsdottir, Hieab H.H. Adams, Roberta Cecchetti, Walter A. Kukull, Thomas S. Wingo, Michelle K. Lupton, Valur Emilsson, Susan M. McCurry, Simon Mead, Hilkka Soininen, Sandra Weintraub, Amy Gerrish, Lindy E. Harrell, Lina Keller, Jean-Charles Lambert, Denise Harold, Stephen Todd, Wei Gu, Maura Gallo, Najaf Amin, Lenore J. Launer, Eleonora Sacchinelli, Mikko Hiltunen, Cécile Dulary, Eliecer Coto, Xueqiu Jian, Nathalie Fievet, Patrizia Mecocci, Sarah Taylor, Eric Boerwinkle, Maria Serpente, Ronald G. Munger, Ina Giegling, Carlo Masullo, Aoibhinn Lynch, Eliezer Masliah, Anne M. Koivisto, Chang En Yu, Qiong Yang, Benedetta Nacmias, Wayne C. McCormick, Kristelle Brown, Alessio Squassina, Deborah C. Mash, Brian W. Kunkle, Makrina Daniilidou, Alison Goate, David Carrell, Kara L. Hamilton-Nelson, Sandra Barral, Vincent Chouraki, Kristel Sleegers, Frank J. Wolters, Joseph E. Parisi, Iwona Kłoszewska, Ronald C. Kim, Sonia Moreno-Grau, Marina Arcaro, Carmen Muñoz Fernadez, Vernon S. Pankratz, Duane Beekly, Sabrina Pichler, Gislain Septier, Delphine Bacq, Amanda J. Myers, Adam C. Naj, Frank Martiniuk, Sudha Seshadri, Badri N. Vardarajan, Joshua A. Sonnen, M.-Marsel Mesulam, Howard J. Rosen, James T. Becker, Chiara Fenoglio, Ge Li, Alberto Pilotto, Mary Sano, Olivier Hanon, Honghuang Lin, Jean Paul G. Vonsattel, W. T. Longstreth, Daniela Galimberti, David C. Rubinsztein, RoseMarie Brundin, Vilmantas Giedraitis, Christine M. Hulette, Peter Holmans, Martin Dichgans, Maria Vronskaya, Céline Derbois, Michelangelo Mancuso, Constantine G. Lyketsos, Christophe Tzourio, Jacques Epelbaum, Raffaele Maletta, Mariet Allen, Hong-Dong Li, James R. Burke, Rik Vandenberghe, David G. Mann, Bruce M. Psaty, Lawrence S. Honig, Beth A. Dombroski, Erik D. Roberson, Cornelia M. van Duijn, Benjamin Grenier-Boley, Seppo Helisalmi, Jean-François Dartigues, Russell H. Swerdlow, Paola Bossù, Ashley R. Winslow, Elio Scarpini, Lesley Jones, Sebastien Engelborghs, John Q. Trojanowski, Jeffrey Kaye, Jenny Lord, Chiara Cupidi, Janet A. Johnston, Dan Rujescu, Feroze Golamaully, Anne Braae, Rafael Blesa, L. Adrienne Cupples, Dennis W. Dickson, Gail P. Jarvik, David W. Fardo, David H. Cribbs, Michael Gill, Jose Bras, Allan I. Levey, Jennifer Williamson, Rhodri Thomas, John C. Morris, Lei Yu, Debby W. Tsuang, Annette M. Hartmann, John H. Growdon, John Collinge, Claudine Berr, Fernando Rivadeneira, Oliver Peters, Albert Hofman, Frank M. LaFerla, Vivianna M. Van Deerlin, James Uphill, David A. Bennett, Onofre Combarros, Gudny Eiriksdottir, Jeremy D. Burgess, Melanie L. Dunstan, Elizabeth Crocco, Keeley J. Brookes, Robert R. Graham, Lon S. Schneider, Eden R. Martin, Matt Hill, Neill R. Graff-Radford, Joseph T. Hughes, Vincenzo Solfrizzi, Taniesha Morgan, Antonio Ciaramella, Bruno Dubois, Juan C. Troncoso, Paolo Bosco, Jordi Clarimón, Daniel H. Geschwind, Virginia Boccardi, Barry Reisberg, Timothy W. Behrens, Annette L. Fitzpatrick, Salvatore Spina, Alexis Brice, Eileen H. Bigio, Marla Gearing, Jeffrey M. Burns, Carol A. Miller, Marilyn S. Albert, Sven J. van der Lee, Sandro Sorbi, C. Dirk Keene, Daniel Levy, Antonio Daniele, Eric M. Reiman, Paramita Chakrabarty, Oscar Sotolongo-Grau, Helena Schmidt, Francesco Panza, Murray A. Raskind, Rita Guerreiro, Gyungah Jun, Anna Karydas, Markus Leber, Harry V. Vinters, Cory C. Funk, Charles C. White, Jill R. Murrell, Sid E. O'Bryant, Nigel J. Cairns, Josée Dupuis, Ann C. McKee, Julie A. Schneider, Megan L. Grove, Malcolm B. Dick, Bradley F. Boeve, Jennifer A. Brody, Sanjay Asthana, Agustín Ruiz, Stefan Herms, Yuning Chen, David Craig, Neil W. Kowall, Maria Donata Orfei, JoAnn T. Tschanz, Florentino Sanchez Garcia, Manuel Mayhaus, Alfredo Ramirez, James Turton, André G. Uitterlinden, Davide Seripa, Lee-Way Jin, Kelley Faber, Maria C. Norton, Shuo Li, Steven H. Ferris, Steffi G. Riedel-Heller, Joshua C. Bis, Li-San Wang, Johannes Kornhuber, Peter Paul De Deyn, Martin R. Farlow, Randall L. Woltjer, Gary W. Beecham, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Hospital of the University of Pennsylvania (HUP), Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia], Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Icelandic Heart Association [Kopavogur, Iceland] (IHA), John P. Hussman Institute for Human Genomics [Miami, FL, USA], University of Miami [Coral Gables], Institut de Biologie François JACOB (JACOB), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Department of Medicine, University of Washington [Seattle], Dr. John T. Macdonald Foundation [Miami, FL, USA] (Department of Human Genetics), Epidémiologie des maladies chroniques : impact des interactions gène environnement sur la santé des populations, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé, Department of Genomics [Bonn, Germany] (Institute of Human Genetics), University of Bonn-Institute of Human Genetics [Bonn, Germany], Department of Molecular Genetics, Institut Català de Neurociències Aplicades [Barcelona, Spain], Well Advanced Solutions, Centre National de Génotypage (CNG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Translational Centre for Regenerative Medicine (TRM), Department of Cell Therapy, Universität Leipzig [Leipzig]-Universität Leipzig [Leipzig], The University of Texas Health Science Center at Houston (UTHealth), Columbia University [New York], University of Eastern Finland, Life & Brain Center - Department of Genomics, Rheinische Friedrich-Wilhelms-Universität Bonn, Génétique, Reproduction et Développement (GReD), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de la Santé et de la Recherche Médicale (INSERM), John P. Hussman Institute for Human Genomics, Neurobiologie de la Croissance et de la Senescence, Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Emmy Noether Project (SFB 833), Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen, Boston University [Boston] (BU), Department of Genomics, Institute for Systems Biology [Seattle, WA, USA], Universitätsklinikum Bonn (UKB), Centre of Excellence for Robotic Vision [Canberra], Australian Research Council [Canberra] (ARC), Neuroscience and Mental Health Research Institute [Cardiff, UK] (School of Medicine), Boston University School of Medicine (BUSM), Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, University of Pennsylvania [Philadelphia], Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Department of Epidemiology and Biostatistics, ERASMUS, Hospital Universitario Doctor Negrín [Las Palmas de Gran Canaria, Spain], Department of Neurodegenerative Diseases, University of Mississippi Medical Center (UMMC), Pathology and Laboratory Medicine [Philadelphia, PA, USA] (Penn Neurodegeneration Genomics Center), UNIROUEN - UFR Santé (UNIROUEN UFR Santé), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Génétique du cancer et des maladies neuropsychiatriques (GMFC), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bioinformatics, GlaxoSmithKline, Aging Research Center [Karolinska Institutet] (ARC ), Stockholm University-Karolinska Institutet [Stockholm], University of Nottingham, UK (UON), University of Texas Health Science Center, Department of Neurobiology, Caring Sciences and Society (NVS), University of Bari Aldo Moro (UNIBA), Ageing Group, Centre for Public Health, Queen's University [Belfast] (QUB), Mayo Clinic [Jacksonville], Maurice Wohl Clinical Neuroscience Institut, King‘s College London, Istituto di Ricovero e Cura a Carattere Scientifico, Ospedale Casa Sollievo della Sofferenza [San Giovanni Rotondo] (IRCCS), Università degli Studi di Perugia (UNIPG), Framingham Heart Study, Boston University [Boston] (BU)-National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), CHU Rouen, Normandie Université (NU), Universidad Autonoma de Madrid (UAM), Centro de Investigacion Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III [Madrid] (ISC), National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), University of Florida [Gainesville] (UF), University of Parma = Università degli studi di Parma [Parme, Italie], Center for Cognitive Disorders AUSL [Parma, Italy], School of Public Health [Boston], Uppsala University, Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC), National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Xi'an Jiaotong University (Xjtu), Department of Public health and Caring Sciences, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden, Institute of Gerontology and Geriatrics, Troubles cognitifs dégénératifs et vasculaires - U 1171 (TCDV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Geriatric Medicine and Metabolic Diseases, Departments of Nuclear Medicine, University Medical Centre Hamburg-Eppendorf [Hamburg, Germany], University of Texas Southwestern Medical Center [Dallas], University of Cologne, Laboratoire d'Etudes et de Recherche en Informatique d'Angers (LERIA), Université d'Angers (UA), Johns Hopkins University (JHU), Universität Leipzig [Leipzig], University of Iceland [Reykjavik], Metacohorts Consortium, Harvard School of Public Health, Catholic University of Rome, Medical University Graz, Baylor College of Medicine (BCM), Baylor University, University of North Texas Health Science Center [Fort Worth], Santa Lucia Foundation (IRCCS), Nextel S.A. [Bilbao], Massachusetts General Hospital [Boston], Department of Pathology and Laboratory Medicine and Indiana Alzheimer disease Center, Indiana University School of Medicine, Indiana University System-Indiana University System, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), Beijing University of Technology, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Saul B. Korey Department of Neurology, Albert Einstein College of Medicine [New York]-Yeshiva University, Utah State University (USU), Fundació per la Recerca Biomèdica i Social Mútua Terrassa [Barcelona, Spain], Hospital Universitario Mutua de Terrassa, Département de neurologie [Montpellier], Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [Montpellier]-Université de Montpellier (UM), Department of neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland, Department of neurology, University of Eastern Finland-University Hospital of Kuopio-University of Eastern Finland-University Hospital of Kuopio, Medical University of Łódź (MUL), University of Leicester, MRC Prion Unit, Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, University of Milan, Fondazione Istituto di Ricerca e Cura Carattere Scientifico [Rome], Università degli Studi di Roma Tor Vergata [Roma], Saarland University Hospital, Universitat Autònoma de Barcelona (UAB), Regional Neurogenetic Centre [Lamezia Terme, Italy] (CRN - ASP Catanzaro), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Universidade do Porto, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Experimental and Clinical Pharmacology, St. James Hospital and Trinity College [Dublin, Ireland], School of Medicine [Dublin], Trinity College Dublin, University of Sheffield [Sheffield], Lancaster University, University of Michigan [Ann Arbor], University of Michigan System, David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California, University of Wisconsin-Madison, Rush Alzheimer Disease Center [Chicago, IL, États-Unis], Rush University Medical Center [Chicago], Institute for Advanced Biosciences / Institut pour l'Avancée des Biosciences (Grenoble) (IAB), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), School of Engineering [Cardiff], Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), Northwestern University Feinberg School of Medicine, Mayo Clinic [Rochester], Swedish Medical Center [Seattle, WA, USA], University of California [San Francisco] (UCSF), University of California, Duke University [Durham], University of Kansas Medical Center [Lawrence], Laboratory of Molecular Neuropsychiatry, Icahn School of Medicine at Mount Sinai [New York] (MSSM), Washington University in Saint Louis (WUSTL), University of South Florida [Tampa] (USF), Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), Medical University of South Carolina [Charleston] (MUSC), University of Southern California (USC), Los Alamos National Laboratory (LANL), Centre de biologie du développement (CBD), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre de Biologie Intégrative (CBI), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Neurology Department, University of California, Davis (UCDavis-Neuro), University of California [Davis] (UC Davis), University of California [Irvine] (UCI), Mount Sinai Medical Center, Indiana State University, University of Alabama at Birmingham [ Birmingham] (UAB), University of Kentucky, New York University [New York] (NYU), NYU System (NYU), Department of Medical and Molecular Genetics, Department of Epidemiology and biostatistics, VU University Medical Center [Amsterdam], Emory University [Atlanta, GA], Department of Neurology, University of California-University of California-David Geffen School of Medicine [Los Angeles], Brigham & Women’s Hospital [Boston] (BWH), Harvard Medical School [Boston] (HMS), Department of Medical Genetics, HMNC Brain Health, Alzheimer Disease Research Laboratory, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Oregon Health and Science University [Portland] (OHSU), Cleveland Clinic, Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Department of Psychiatry, School of Medicine-Johns Hopkins University and Johns Hopkins Bayview Medical Center, Douglas Mental Health University Institute [Montréal], McGill University = Université McGill [Montréal, Canada], Department of neurosciences, University of California [San Diego] (UC San Diego), Department of Physics and Astronomy [Fort Worth], Texas Christian University (TCU), Department of Computer Science [University of California, Davis], Indiana University System, Institute for Aging and Alzheimer’s Disease Research [Fort Worth] (IAADR), Department of Laboratory Medicine and Pathology, Mayo Clinic, Institute for Memory Impairments and Neurological Disorders [Irvine], University of Colorado Anschutz [Aurora], Tanz Center Research in Neurodegenerative Diseases [Toronto], University of Toronto, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Keck School of Medicine [Los Angeles], Indiana University [South Bend], Massachusetts General Hospital, Novartis Institutes for Biomedical Research [Cambridge, MA, USA], Departments of Pathology and Laboratory Medicine (Neuropathology) and Neurology, UCLA Medical Center-David Geffen School of Medicine [Los Angeles], University of California-University of California-University of California [Los Angeles] (UCLA), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Institut de Génomique d'Evry (IG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, University of Antwerp (UA), Institute Born-Bunge, Karolinska Institutet [Stockholm], Karolinska University Hospital [Stockholm], University of Kuopio, Centre Mémoire de Ressources et de Recherche [Lille-Bailleul] (CMRR), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Hôpital Roger Salengro [Lille], Laboratoire d'Analyse Génomique, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Inserm-U1167, Dpt Gériatrie [CHU Broca], AP-HP - Hôpital Cochin Broca Hôtel Dieu [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Neuroépidémiologie, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Department of Epidemiology, University of Washington, School of Medicine [Los Angeles], Albert Einstein College of Medicine [New York], IdiPAZ - Instituto de Investigación La Paz [Madrid, Spain], Instituto de Física Teórica UAM/CSIC (IFT), Universidad Autonoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Department of Internal Medicine, University of Central Asturias [Oviedo, Spain], Human Genome Sequencing Center, Baylor College of Medicine, Baylor University-Baylor University, Department of Epidemiology, Erasmus Medical Centre, Translational Genomics Research Institute [Phoenix, AZ, USA], University of Arizona, Banner Alzheimer's Institute [Phoenix, AZ, États-Unis], University of Texas Health Science Center at San Antonio [San Antonio], Mount Sinai School of Medicine, Department of Psychiatry-Icahn School of Medicine at Mount Sinai [New York] (MSSM), Department. of Neurological Sciences, University of Milan, IRCCS Ospedale Maggiore Policlinico, Centre for Research in Neurodegenerative Diseases, VA Puget Sound Health Care System/GRECC [Seattle, WA, USA], University of Pisa - Università di Pisa, Pfizer Worldwide Research and Development [Cambridge, MA, USA], Università cattolica del Sacro Cuore [Piacenza e Cremona] (Unicatt), Texas Tech University Health Sciences Center, Texas Tech University [Lubbock] (TTU), Saarland University [Saarbrücken], University of Bonn, Department of Public Health and Primary Care, University of Cambridge [UK] (CAM), Cambridge Institute for Medical Research (CIMR), Department of Molecular Neurosciences, Institute of Neurology, UCL, Institute of Psychiatry, Institute of psychiatry, University of British Columbia (UBC), the Clinical Neuroscience Research Group, University of Manchester [Manchester]-Greater Manchester Neurosciences Centre, Aristotle University of Thessaloniki, Memory and Dementia Centre, 3rd Department of Neurology, G. Pa, University of Barcelona, University of Southampton, Department of Psychiatry [Oxford] (POWIC), University of Oxford [Oxford]-The Warneford Hospital, School of Psychology [Cardiff University], Department of Medical Sciences, UCL, Institute of Neurology [London], Washington University School of Medicine, Netherlands Genomics Initiative, Netherlands Consortium for Healthy Aging [Leiden, Netherlands] (NCHA), School of Medecine, Center for Translational and Computational Neuroimmunology [New York, NY, États-Unis] (CTCN), Department of Neurology [New York, NY, États-Unis], Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York]-Columbia University Medical Center (CUMC), Columbia University [New York]-Columbia University [New York], School of Life Sciences, Department of Neuroscience, Mayo Clinic Jacksonville, Icelandic Heart Association, Heart Preventive Clinic and Research Institute, Klinik für Psychiatrie, Martin-Luther-University Halle-Wittenberg, Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), The Center for Applied Genomics, Children’s Hospital of Philadelphia (CHOP ), Clínica Universidad de Navarra [Pamplona], Neurodegenerative Brain Diseases Group, VIB, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University-Medical Research Council, Brigham Young University (BYU), Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, The Gertrude H Sergivesky Center, Columbia University College of Physicians and Surgeons, Genetic Epidemiology Unit, Section of Clinical and Molecular Neurogenetics, Universität zu Lübeck [Lübeck], University of Pennsylvania - Department of Pathology & Laboratory Medecine, Framingham Heart Study [Framingham, MA, USA], ANR-10-IAHU-0006,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2010), European Project: 29845,LSH-ACC-MENTOR, University of Pennsylvania-University of Pennsylvania, Universität Bonn = University of Bonn-Institute of Human Genetics [Bonn, Germany], Universität Leipzig-Universität Leipzig, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania, Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Università degli Studi di Perugia = University of Perugia (UNIPG), Universidad Autónoma de Madrid (UAM), Università degli studi di Parma = University of Parma (UNIPR), Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC)-CHU Pitié-Salpêtrière [AP-HP], Troubles cognitifs dégénératifs et vasculaires - U 1171 - EA 1046 (TCDV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Universität Leipzig, Università cattolica del Sacro Cuore = Catholic University of the Sacred Heart [Roma] (Unicatt), Yeshiva University- Albert Einstein College of Medicine [New York], Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [CHU Montpellier], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Université de Montpellier (UM), Università degli Studi di Milano = University of Milan (UNIMI), Saarland University Hospital (UKS), Università degli Studi di Firenze = University of Florence (UniFI), Universidade do Porto = University of Porto, University of California (UC)-University of California (UC), University of California [San Francisco] (UC San Francisco), University of California (UC), University of Kansas Medical Center [Kansas City, KS, USA], Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), University of California [Irvine] (UC Irvine), University of Kentucky (UK), University of California (UC)-University of California (UC)-David Geffen School of Medicine [Los Angeles], Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California (UC)-University of California (UC)-University of California [Los Angeles] (UCLA), Université Paris-Saclay-Institut de Biologie François JACOB (JACOB), Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Groupe de recherche clinique Alzheimer Precision Medicine (GRC 21 - APM), Sorbonne Université (SU), Universidad Autónoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), University of Texas Health Science Center at San Antonio [San Antonio, Tx, USA], Universität Bonn = University of Bonn, University of Oxford-The Warneford Hospital, Medical Research Council-Cardiff University, Universität zu Lübeck = University of Lübeck [Lübeck], Epidemiology, Neurology, Gastroenterology & Hepatology, Internal Medicine, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement (Inserm U1167 - RID-AGE - Institut Pasteur), Génétique, Reproduction et Développement - Clermont Auvergne (GReD), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Eberhard Karls Universität Tübingen, IRCCS 'Casa Sollievo della Sofferenza', Centro de Investigación Biomédica en Red para Enfermedades Neurodegenerativas (Ciberned), University of Florida [Gainesville], University of Parma, Troubles cognitifs dégénératifs et vasculaires (U1171), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-INSERM, Yeshiva University- Albert Einstein College of Medicine, Institut d’Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520 (IEMN), Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Université Polytechnique Hauts-de-France (UPHF)-Ecole Centrale de Lille-Université Polytechnique Hauts-de-France (UPHF)-Institut supérieur de l'électronique et du numérique (ISEN), Autonomous University of Barcelona (UAB), Università degli Studi di Firenze [Firenze], Universidade do Porto [Porto], Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Washington University in St Louis, University of South Florida (USF), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, McGill University, Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Centre National de la Recherche Scientifique (CNRS), Neuropsychiatrie : recherche épidémiologique et clinique, Alzheimer Precision Medicine GRC n°21 (APM), CHU Pitié-Salpêtrière [APHP], Albert Einstein College of Medicine, Universidad Autonoma de Madrid (UAM)-Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Università Cattolica del S. Cuore - Catholic University of the Sacred Hearth, University of Florence (UNIFI), CIBER de Enfermedades Neurodegenerativas (CIBERNED), Universität zu Lübeck [Lübeck] - University of Lübeck [Lübeck], [ANR-10-IAIHU-06],« Investissements d'avenir » ,Agence nationale de la recherche (ANR), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Icahn School of Medicine at Mount Sinai [New York] (MSSM)-Department of Psychiatry, van der Lee, Sven J [0000-0003-1606-8643], Naj, Adam C [0000-0002-9621-2942], Badarinarayan, Nandini [0000-0002-6944-748X], Chouraki, Vincent [0000-0002-4698-1794], Graham, Robert R [0000-0001-7151-4277], Hoffmann, Per [0000-0002-6573-983X], Smith, Albert V [0000-0003-1942-5845], Satizabal, Claudia L [0000-0002-1115-4430], Brody, Jennifer A [0000-0001-8509-148X], Wolters, Frank J [0000-0003-2226-4050], Lupton, Michelle K [0000-0002-7274-7299], Lin, Honghuang [0000-0003-3043-3942], Adams, Hieab H [0000-0003-3687-2508], Giedraitis, Vilmantas [0000-0003-3423-2021], Pasquier, Florence [0000-0001-9880-9788], Chen, Yuning [0000-0002-7358-7055], Bossù, Paola [0000-0002-1432-0078], Ghetti, Bernardino [0000-0002-1842-8019], Yang, Qiong [0000-0002-3658-1375], Aspelund, Thor [0000-0002-7998-5433], Bullido, María J [0000-0002-6477-1117], Rivadeneira, Fernando [0000-0001-9435-9441], Rubinsztein, David C [0000-0001-5002-5263], Al-Chalabi, Ammar [0000-0002-4924-7712], Tsolaki, Magda [0000-0002-2072-8010], De Jager, Philip L [0000-0002-8057-2505], Dickson, Dennis W [0000-0001-7189-7917], Van Broeckhoven, Christine [0000-0003-0183-7665], Ikram, M Arfan [0000-0003-0372-8585], Amouyel, Philippe [0000-0001-9088-234X], Lambert, Jean-Charles [0000-0003-0829-7817], Apollo - University of Cambridge Repository, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre de Biologie Intégrative (CBI), Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 APM), Berr, Claudine, Institut de Neurosciences Translationnelles de Paris - - IHU-A-ICM2010 - ANR-10-IAHU-0006 - IAHU - VALID, and Mentoring of LifeSciHealth-Multipliers in the Accession Candidate Countries - LSH-ACC-MENTOR - 29845 - OLD

Subjects
0301 basic medicine, Linkage disequilibrium, [SDV]Life Sciences [q-bio], Medizin, Sequence Homology, Genome-wide association study, genetics [Alzheimer Disease], metabolism [Microglia], Linkage Disequilibrium, 0302 clinical medicine, genetics [Protein Interaction Maps], genetics [Membrane Glycoproteins], Gene Frequency, Immunologic, genetics [Adaptor Proteins, Signal Transducing], Receptors, genetics [Exome], Odds Ratio, Innate, genetics [Receptors, Immunologic], Exome, Protein Interaction Maps, genetics [Genetic Predisposition to Disease], Receptors, Immunologic, ABI3 protein, human, Genetics, Adaptor Proteins, Signal Transducing, Alzheimer Disease, Amino Acid Sequence, Case-Control Studies, Gene Expression Profiling, Genetic Predisposition to Disease, Genotype, Humans, Immunity, Innate, Membrane Glycoproteins, Microglia, Phospholipase C gamma, Sequence Homology, Amino Acid, Polymorphism, Single Nucleotide, Adaptor Proteins, Single Nucleotide, 3. Good health, [SDV] Life Sciences [q-bio], Amino Acid, Settore MED/26 - NEUROLOGIA, genetics [Phospholipase C gamma], [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Alzheimer's disease, Common disease-common variant, Biology, Article, 03 medical and health sciences, ddc:570, medicine, Journal Article, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Polymorphism, Allele frequency, TREM2 protein, human, TREM2, Case-control study, Signal Transducing, Immunity, medicine.disease, R1, Minor allele frequency, genetics [Immunity, Innate], 030104 developmental biology, Human medicine, 030217 neurology & neurosurgery
Abstract

International audience; We identified rare coding variants associated with Alzheimer's disease in a three-stage case-control study of 85,133 subjects. In stage 1, we genotyped 34,174 samples using a whole-exome microarray. In stage 2, we tested associated variants (P < 1 × 10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, we used an additional 14,997 samples to test the most significant stage 2 associations (P < 5 × 10-8) using imputed genotypes. We observed three new genome-wide significant nonsynonymous variants associated with Alzheimer's disease: a protective variant in PLCG2 (rs72824905: p.Pro522Arg, P = 5.38 × 10-10, odds ratio (OR) = 0.68, minor allele frequency (MAF)cases = 0.0059, MAFcontrols = 0.0093), a risk variant in ABI3 (rs616338: p.Ser209Phe, P = 4.56 × 10-10, OR = 1.43, MAFcases = 0.011, MAFcontrols = 0.008), and a new genome-wide significant variant in TREM2 (rs143332484: p.Arg62His, P = 1.55 × 10-14, OR = 1.67, MAFcases = 0.0143, MAFcontrols = 0.0089), a known susceptibility gene for Alzheimer's disease. These protein-altering changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified risk genes in Alzheimer's disease. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to the development of Alzheimer's disease.

Published
2017

42. Blind prediction of homo- and hetero- protein complexes: The CASP13-CAPRI experiment

Author

Lensink, Marc F., Brysbaert, Guillaume, Nadzirin, Nurul, Velankar, Sameer, Chaleil, Raphaël A. G., Gerguri, Tereza, Bates, Paul A., Laine, Elodie, Carbone, Alessandra, Grudinin, Sergei, Kong, Ren, Liu, Ran-Ran, Xu, Xi-Ming, Shi, Hang, Chang, Shan, Eisenstein, Miriam, Karczynska, Agnieszka, Czaplewski, Cezary, Lubecka, Emilia, Lipska, Agnieszka, Krupa, Paweł, Mozolewska, Magdalena, Golon, Łukasz, Samsonov, Sergey, Liwo, Adam, Crivelli, Silvia, Pagès, Guillaume, Karasikov, Mikhail, Kadukova, Maria, Yan, Yumeng, Huang, Sheng-You, Rosell, Mireia, Rodríguez-Lumbreras, Luis A., Romero-Durana, Miguel, Díaz-Bueno, Lucía, Fernandez-Recio, Juan, Christoffer, Charles, Terashi, Genki, Shin, Woong-Hee, Aderinwale, Tunde, Maddhuri Venkata Subraman, Sai Raghavendra, Kihara, Daisuke, Kozakov, Dima, Vajda, Sandor, Porter, Kathryn, Padhorny, Dzmitry, Desta, Israel, Beglov, Dmitri, Ignatov, Mikhail, Kotelnikov, Sergey, Moal, Iain H., Ritchie, David W., Chauvot de Beauchêne, Isaure, Maigret, Bernard, Devignes, Marie-Dominique, Ruiz Echartea, Maria E., Barradas-Bautista, Didier, Cao, Zhen, Cavallo, Luigi, Oliva, Romina, Cao, Yue, Shen, Yang, Baek, Minkyung, Park, Taeyong, Woo, Hyeonuk, Seok, Chaok, Braitbard, Merav, Bitton, Lirane, Scheidman-Duhovny, Dina, Dapkūnas, Justas, Olechnovič, Kliment, Venclovas, Česlovas, Kundrotas, Petras J., Belkin, Saveliy, Chakravarty, Devlina, Badal, Varsha D., Vakser, Ilya A., Vreven, Thom, Vangaveti, Sweta, Borrman, Tyler, Weng, Zhiping, Guest, Johnathan D., Gowthaman, Ragul, Pierce, Brian G., Xu, Xianjin, Duan, Rui, Qiu, Liming, Hou, Jie, Ryan Merideth, Benjamin, Ma, Zhiwei, Cheng, Jianlin, Zou, Xiaoqin, Koukos, Panagiotis I., Roel-Touris, Jorge, Ambrosetti, Francesco, Geng, Cunliang, Schaarschmidt, Jörg, Trellet, Mikael E., Melquiond, Adrien S. J., Xue, Li, Jiménez-García, Brian, van Noort, Charlotte W., Honorato, Rodrigo V., Bonvin, Alexandre M. J. J., Wodak, Shoshana J., 0000-0003-3957-9470, 0000-0003-2759-2088, 0000-0003-0621-0925, 0000-0003-2098-5743, 0000-0001-7169-9398, 0000-0002-0294-3403, 0000-0002-4209-4565, 0000-0002-7787-8896, 0000-0002-3986-7686, 0000-0002-6163-6323, 0000-0003-4091-6614, 0000-0003-0464-4500, 0000-0002-4960-5487, 0000-0002-7035-3042, 0000-0002-1703-7796, 0000-0002-1419-9888, 0000-0002-0496-6107, 0000-0002-4215-0213, 0000-0002-5743-2934, 0000-0003-3413-806X, 0000-0002-3032-7966, 0000-0002-1409-8358, 0000-0001-7369-1322, 0000-0002-0701-6545, Unité de Glycobiologie Structurale et Fonctionnelle UMR 8576 (UGSF), Institut National de la Recherche Agronomique (INRA)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, The Francis Crick Institute [London], School of Geographical Sciences [Bristol], University of Bristol [Bristol], Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology (LCQB), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), Algorithms for Modeling and Simulation of Nanosystems (NANO-D), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), JiangSu University, Chemical Research Support [Rehovot], Weizmann Institute of Science [Rehovot, Israël], University of Gdańsk (UG), Department of Environmental Analytics [Univ Gdańsk], Faculty of Chemistry [Univ Gdańsk], University of Gdańsk (UG)-University of Gdańsk (UG), Institute of Physics [Warsaw] (IFPAN), Polish Academy of Sciences (PAN), Department of Computer Science [Davis] (UC Davis), University of California [Davis] (UC Davis), University of California-University of California, Moscow Institute of Physics and Technology [Moscow] (MIPT), Huazhong University of Science and Technology [Wuhan] (HUST), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Purdue University [West Lafayette], Kitasato University, Stony Brook University [SUNY] (SBU), State University of New York (SUNY), Department of Biomedical Engineering [Boston], Boston University [Boston] (BU), Computational Algorithms for Protein Structures and Interactions (CAPSID), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), King Abdullah University of Science and Technology (KAUST), University of Naples Federico II, Service des Recherches Métallurgiques Appliquées (SRMA), Département des Matériaux pour le Nucléaire (DMN), CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Department of Chemistry, Seoul National University [Seoul] (SNU), The Hebrew University of Jerusalem (HUJ), Vilnius University [Vilnius], Department of Molecular Biosciences [Lawrence], University of Kansas [Lawrence] (KU), University of Kansas [Kansas City], University of Massachusetts Medical School [Worcester] (UMASS), University of Massachusetts System (UMASS), Program in Bioinformatics and Integrative Biology [Worcester], University of Massachusetts System (UMASS)-University of Massachusetts System (UMASS), University of Maryland [Baltimore], Beijing University of Technology, University of Missouri [Columbia] (Mizzou), University of Missouri System, Bijvoet Center for Biomolecular Research [Utrecht], Utrecht University [Utrecht], Dalton Cardiovascular Research Center [Columbia], University of Missouri System-University of Missouri System, Shandong University, Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI), Université Paris-Sud - Paris 11 (UP11)-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE), University of California [Santa Cruz] (UCSC), University of California, The Hospital for sick children [Toronto] (SickKids), Unité de Glycobiologie Structurale et Fonctionnelle - UMR 8576 (UGSF), Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA), Institut des Hautes Etudes Scientifiques (IHES), IHES, The Francis Crick Institute, Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut National Polytechnique de Grenoble (INPG), Weizmann Institute of Science, University of Gdańsk, Department of Environmental Analytics [Gdańsk], Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Technische Universität München [München] (TUM), CEA-Direction de l'Energie Nucléaire (CEA-DEN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-CEA-Direction de l'Energie Nucléaire (CEA-DEN), University of Missouri [Columbia], Université Paris-Sud - Paris 11 (UP11)-Université Paris-Saclay-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE), Université de Lille, CNRS, Unité de Glycobiologie Structurale et Fonctionnelle UMR 8576 [UGSF], Agence Nationale de la Recherche (France), Cancer Research UK, European Commission, Medical Research Council (UK), National Institutes of Health (US), National Natural Science Foundation of China, National Research Foundation of Korea, National Science Foundation (US), Ministerio de Economía y Competitividad (España), Università degli Studi di Napoli PARTHENOPE, Wellcome Trust, Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Algorithms for Modeling and Simulating Nanosystems [2018-...] (NANO-D-POST [2018-2020]), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California (UC)-University of California (UC), University of Naples Federico II = Università degli studi di Napoli Federico II, University of California [Santa Cruz] (UC Santa Cruz), University of California (UC), and Grudinin, Sergei

Subjects
Models, Molecular, Computer science, Protein Conformation, Protein complexes, Template‐based modeling, Oligomeric state, Biochemistry, Docking, protein-protein interaction, Structural Biology, Protein Interaction Mapping, Taverne, Blind prediction, Protein assemblies, Databases, Protein, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], 0303 health sciences, oligomeric state, 030302 biochemistry & molecular biology, protein assemblies, computer.file_format, 3. Good health, CASP, docking, blind prediction, Protein‐protein interaction, CAPRI, proteincomplexes, Algorithms, Protein Binding, protein complexes, template-based modeling, Computational biology, Article, Protein–protein interaction, 03 medical and health sciences, protein‐protein interaction, template‐based modeling, Molecular Biology, 030304 developmental biology, Binding Sites, Computational Biology, Proteins, Protein Data Bank, Docking (molecular), Structural Homology, Protein, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], computer, Software
Abstract

We present the results for CAPRI Round 46, the third joint CASP‐CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo‐oligomers and 6 heterocomplexes. Eight of the homo‐oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher‐order assemblies. These were more difficult to model, as their prediction mainly involved “ab‐initio” docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance “gap” was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template‐based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements., Agence Nationale de la Recherche, Grant/Award Number: ANR‐15‐CE11‐0029‐03; Cancer Research UK, Grant/Award Number: FC001003; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Lietuvos Mokslo Taryba, Grant/Award Number: S‐MIP‐17‐60; Medical Research Council, Grant/Award Number: FC001003; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM123055, R35GM124952; National Natural Science Foundation of China, Grant/Award Number: 31670724; National Research Foundation of Korea, Grant/Award Number: 2016M3C4A7952630; National Science Foundation, Grant/Award Number: DBI1565107; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award Number: 718.015.001; Spanish >Programma Estatal I+D+i>, Grant/Award Number: BIO2016‐79930‐R; University Parthenope, Grant/Award Number: Finanziamento per il Sostegno alla Ricerca Individ; Wellcome Trust, Grant/Award Number: FC001003

Published
2019

43. Inferring user relationship from hidden information in WLANs

Author

Prasant Mohapatra, Ningning Cheng, Roksana Boreli, Srikanth V. Krishnamurthy, Mohamed Ali Kaafar, Mathieu Cunche, Department of Computer Science [Univ California Davis] (CS - UC Davis), University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), National ICT Australia [Sydney] (NICTA), Protocols and applications for the Internet (PLANETE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria), Department of Computer Science and Engineering [Univ California San Diego] (CSE - UC San Diego), and University of California [San Diego] (UC San Diego)

Subjects
Wi-Fi array, Computer science, relationship inference, Wireless LAN controller, law.invention, [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR], law, co-occurrence, Wireless lan, Wireless, Wi-Fi, Fixed wireless, Network detector, Hidden node problem, Wireless network, Service set, business.industry, location proximity, Wireless WAN, CAPWAP, WLAN, Key distribution in wireless sensor networks, Wireless site survey, behavior pattern, SSID, business, Mobile device, Heterogeneous network, Municipal wireless network, Computer network
Abstract

International audience; With ever increasing usage of handheld devices and vast deployment of wireless networks, we observe that it is possible to collect data from mobile devices and reveal personal relationships of their owners. In the paper, we exploit the hidden information collected from WLAN devices and infer individual relationships between device pairs based on three observation dimensions: network association history, physical proximity and spatio-temporal behavior. By measuring WLAN data, we demonstrate that device owners with social relationship tend to share access points, or show similar behavior patterns in wireless communications (e.g. go to the same place periodically to access the same WLAN network). These results can be exploited for various network analytic purposes.

Published
2012

44. Visualizing fiber end geometry effects on stress distribution in composites using mechanophores.

Author

Haque N, Chang HC, Chang CC, and Davis CS

Abstract

Localized stress concentrations at fiber ends in short fiber-reinforced polymer composites (SFRCs) significantly affect their mechanical properties. Our research targets these stress concentrations by embedding nitro-spiropyran (SPN) mechanophores into the polymer matrix. SPN mechanophores change color under mechanical stress, allowing us to visualize and quantify stress distributions at the fiber ends. We utilize glass fibers as the reinforcing material and employ confocal fluorescence microscopy to detect color changes in the SPN mechanophores, providing real-time insights into the stress distribution. By combining this mechanophore-based stress sensing with finite element analysis (FEA), we evaluate localized stresses that develop during a single fiber pull-out test near different fiber end geometries-flat, cone, round, and sharp. This method precisely quantifies stress distributions for each fiber end geometry. The mechanophore activation intensity varies with fiber end geometry and pull-out displacement. Our results indicate that round fiber ends exhibit more gradual stress transfer into the matrix, promoting effective stress distribution. Also, different fiber end geometries lead to distinct failure mechanisms. These findings demonstrate that fiber end geometry plays a crucial role in stress distribution management, critical for optimizing composite design and enhancing the reliability of SFRCs in practical applications. By integrating mechanophores for real-time stress visualization, we can accurately map quantified stress distributions that arise during loading and identify failure mechanisms in polymer composites, offering a comprehensive approach to enhancing their durability and performance.

Published
2024
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45. Impact of California's naloxone co-prescription law on emergency department visits, 30-day mortality, and prescription patterns.

Author

Ghobadi A, Hanna M, Tovar S, Do DH, Duan L, Lee MS, Samuels EA, Davis CS, and Sharp AL

Abstract

Objective: Opioid overdose is a public health epidemic adversely impacting individuals and communities. To combat this, California passed a law mandating that prescribers offer a naloxone prescription in certain circumstances. Our objective was to evaluate associations with California's naloxone prescription mandate and emergency department (ED) overdose visits/hospitalizations, opioid and naloxone prescribing, and 30-day mortality., Methods: This retrospective cohort study included data from January 1, 2018, to December 31, 2019, and included all Kaiser Permanente Southern California (KPSC) members aged >10 years across 15 KPSC EDs. Exposure was defined as presentation to the ED within the study period. The primary outcome was ED visits for opioid overdose pre- and post-implementation of California's naloxone prescription mandate., Results: A total of 1.1 million ED visits (534K pre/576K post) were included in the study population. ED opioid overdose visits were 344 (6.4/10,000) pre-policy and 351 (6.1/10,000) post-policy implementation, while non-opioid overdose visits were 309 (5.8/10,000) pre-implementation and 411 (7.1/10,000) post-implementation. The unadjusted rate of visits with opioid prescriptions decreased significantly (14.9% pre to 13.5% post) after implementation. ED naloxone prescriptions increased substantially (104 pre vs. 6031 post). Primary adjusted interrupted time series analysis found no statistical difference between monthly opioid overdose visits pre versus post (odds ratio 1.02, 95% confidence interval [CI] 0.98‒1.07). Difference-in-differences analysis revealed no significant changes in hospitalization (coefficient [CE] = ‒0.05, 95% CI = ‒0.11 to 0.02) or 30-day mortality (CE = ‒0.01, 95% CI = ‒0.03 to 0.01)., Conclusion: This study revealed that the implementation of California's naloxone prescription mandate was associated with significantly increased naloxone prescribing and decreased opioid prescribing, but no significant change in ED opioid overdose visits, hospitalizations, or 30-day mortality. This indicates that increasing naloxone prescribing alone may not be sufficient to lower opioid overdose rates., Competing Interests: The authors declare they have no conflicts of interest., (© 2024 The Author(s). Journal of the American College of Emergency Physicians Open published by Wiley Periodicals LLC on behalf of American College of Emergency Physicians.)

Published
2024
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46. The Combined Relationship of Prescription Drug Monitoring Program Enactment and Medical Cannabis Laws with Chronic Pain-Related Healthcare Visits.

Author

Mannes ZL, Nowels M, Mauro C, Cook S, Wheeler-Martin K, Gutkind S, Bruzelius E, Doonan SM, Crystal S, Davis CS, Samples H, Hasin DS, Keyes KM, Rudolph KE, Cerdá M, and Martins SS

Abstract

Background: U.S. state electronic prescription drug monitoring programs (PDMPs) are associated with reduced opioid dispensing among people with chronic pain and may impact use of other chronic pain treatments. In states with medical cannabis laws (MCLs), patients can use cannabis for chronic pain management, reducing their need for chronic-pain related treatment visits and moderating effects of PDMP laws., Objective: Given high rates of chronic pain among Medicaid enrollees, we examined associations between PDMP enactment in the presence or absence of MCL on chronic pain-related outpatient and emergency department (ED) visits., Design: We created annual cohorts of Medicaid enrollees with chronic pain diagnoses using national Medicaid claims data from 2002-2013 and 2016. Negative binomial hurdle models produced adjusted odds ratios (aOR) for the likelihood of any chronic pain-related outpatient or ED visit and incident rate ratios (IRR) for the rate of visits among patients with ≥ 1 visit., Participants: Medicaid enrollees aged 18-64 years with chronic pain (N = 4,878,462)., Main Measures: A 3-level state-year variable with the following categories: 1) no PDMP, 2) PDMP enactment in the absence of MCL, or 3) PDMP enactment in the presence of MCL. Healthcare codes for chronic pain-related outpatient and ED visits each year., Key Results: The sample was primarily female (67.2%), non-Hispanic White (51.2%), and ages 40-55 years (37.2%). Compared to no-PDMP states, PDMP enactment in the absence of MCL was not associated with chronic pain-related outpatient visits but PDMP enactment in the presence of MCL was associated with lower odds of chronic pain-related outpatient visits (aOR = 0.81, 95% CI:0.71-0.92). PDMP enactment was not associated with ED visits, irrespective of MCL., Conclusions: During a period of PDMP and MCL expansion, our findings suggest treatment shifts for persons with chronic pain away from outpatient settings, potentially related to increased use of cannabis for chronic pain management., (© 2024. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Published
2024
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47. Investigating the complexity of naloxone distribution: Which policies matter for pharmacies and potential recipients.

Author

Smart R, Powell D, Pacula RL, Peet E, Abouk R, and Davis CS

Subjects
Humans, United States, Pharmacies, Health Policy, Naloxone supply & distribution, Naloxone therapeutic use, Narcotic Antagonists supply & distribution, Narcotic Antagonists therapeutic use
Abstract

Despite efforts to expand naloxone access, opioid-related overdoses remain a significant contributor to mortality. We study state efforts to expand naloxone distribution through pharmacies by reducing the non-monetary costs to prescribers, dispensers, and/or potential recipients of naloxone. We find that laws that only address liability costs have small and insignificant effects on the volume of naloxone dispensed through pharmacies. In contrast, we estimate large effects of laws removing the need for patients to obtain prescriptions from traditional prescribers (e.g., primary care physicians): laws authorizing non-patient-specific prescription distribution and laws granting pharmacists prescriptive authority. We test whether areas designated as primary care shortage areas-where it would be costlier to obtain a prescription-were disproportionately impacted. Shortage areas experienced sharper growth in pharmacy naloxone dispensing in states adopting prescriptive authority policies. These gains were primarily due to those facing low out-of-pocket costs, suggesting that price barriers also must be addressed to increase naloxone purchases., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest., (Copyright © 2024 RAND Corporation. Published by Elsevier B.V. All rights reserved.)

Published
2024
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48. The role of prescription opioid and cannabis supply policies on opioid overdose deaths.

Author

Cerdá M, Wheeler-Martin K, Bruzelius E, Mauro CM, Crystal S, Davis CS, Adhikari S, Santaella-Tenorio J, Keyes KM, Rudolph KE, Hasin D, and Martins SS

Abstract

Mandatory prescription drug monitoring programs and cannabis legalization have been hypothesized to reduce overdose deaths. We examined associations between prescription monitoring programs with access mandates ("must-query PDMPs"), legalization of medical and recreational cannabis supply, and opioid overdose deaths in United States counties in 2013-2020. Using data on overdose deaths from the National Vital Statistics System, we fit Bayesian spatiotemporal models to estimate risk differences and 95% credible intervals (CrI) in county-level opioid overdose deaths associated with enactment of these state policies. Must-query PDMPs were independently associated with on average 0.8 (95% CrI: 0.5, 1.0) additional opioid-involved overdose deaths per 100,000 person-years. Legal cannabis supply was not independently associated with opioid overdose deaths in this time period. Must-query PDMPs enacted in the presence of legal (medical or recreational) cannabis supply were associated with 0.7 (95% CrI: 0.4, 0.9) more opioid-involved deaths, relative to must-query PDMPs without any legal cannabis supply. In a time when overdoses are driven mostly by non-prescribed opioids, stricter opioid prescribing policies and more expansive cannabis legalization were not associated with reduced overdose death rates., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Published
2024
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49. Thrombospondin-1 promotes fibro-adipogenic stromal expansion and contractile dysfunction of the diaphragm in obesity.

Author

Buras ED, Woo MS, Kaul Verma R, Kondisetti SH, Davis CS, Claflin DR, Converso-Baran K, Michele DE, Brooks SV, and Chun TH

Subjects
Animals, Mice, Muscle Contraction physiology, Male, Adipogenesis, Adipocytes metabolism, Adipocytes pathology, Diet, High-Fat adverse effects, Fibroblasts metabolism, Extracellular Matrix metabolism, Mesenchymal Stem Cells metabolism, Mice, Inbred C57BL, Cell Differentiation, Thrombospondin 1 metabolism, Thrombospondin 1 genetics, Diaphragm physiopathology, Diaphragm metabolism, Diaphragm pathology, Obesity metabolism, Mice, Knockout
Abstract

Pulmonary disorders affect 40%-80% of individuals with obesity. Respiratory muscle dysfunction is linked to these conditions; however, its pathophysiology remains largely undefined. Mice subjected to diet-induced obesity (DIO) develop diaphragm muscle weakness. Increased intradiaphragmatic adiposity and extracellular matrix (ECM) content correlate with reductions in contractile force. Thrombospondin-1 (THBS1) is an obesity-associated matricellular protein linked with muscular damage in genetic myopathies. THBS1 induces proliferation of fibro-adipogenic progenitors (FAPs) - mesenchymal cells that differentiate into adipocytes and fibroblasts. We hypothesized that THBS1 drives FAP-mediated diaphragm remodeling and contractile dysfunction in DIO. We tested this by comparing the effects of dietary challenge on diaphragms of wild-type (WT) and Thbs1-knockout (Thbs1-/-) mice. Bulk and single-cell transcriptomics demonstrated DIO-induced stromal expansion in WT diaphragms. Diaphragm FAPs displayed upregulation of ECM and TGF-β-related expression signatures and augmentation of a Thy1-expressing subpopulation previously linked to type 2 diabetes. Despite similar weight gain, Thbs1-/- mice were protected from these transcriptomic changes and from obesity-induced increases in diaphragm adiposity and ECM deposition. Unlike WT controls, Thbs1-/- diaphragms maintained normal contractile force and motion after DIO challenge. THBS1 is therefore a necessary mediator of diaphragm stromal remodeling and contractile dysfunction in overnutrition and a potential therapeutic target in obesity-associated respiratory dysfunction.

Published
2024
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50. Drug-related physician continuing medical education requirements, 2010-2020.

Author

Davis CS, Carr DH, and Stein BD

Subjects
Humans, United States, Practice Patterns, Physicians' standards, Analgesics, Opioid adverse effects, Analgesics, Opioid therapeutic use, Physicians, Pain Management methods, Substance-Related Disorders epidemiology, Substance-Related Disorders prevention & control, Substance-Related Disorders therapy, Education, Medical, Continuing
Abstract

Introduction: The crisis of drug-related harm in the United States continues to worsen. While prescription-related overdoses have fallen dramatically, they are still far above pre-2010 levels. Physicians can reduce the risk of overdose and other drug-related harms by improving opioid prescribing practices and ensuring that patients are able to easily access medications for substance use disorder treatment. Most physicians received little or no training in those subjects in medical school. It is possible that continuing medical education can improve physician knowledge of appropriate prescribing and substance use disorder treatment and patient outcomes., Methods: Descriptive legal review. Laws in all 50 states and the District of Columbia were searched for provisions that require all or most physicians to receive either one-time or continuing medical education regarding controlled substance prescribing, pain management, or substance use disorder treatment., Results: There has been a rapid increase in the number of states with relevant requirements, from three states at the end of 2010 to 42 at the end of 2020. The frequency and duration of required education varied substantially across states. In all states, the number of hours required in relevant topics is a small fraction of overall required continuing education, an average of 1 h per year. Despite recent shifts in the substances driving overdose, most requirements remain focused on opioids., Conclusion: While most states have now adopted continuing education requirements regarding controlled substance prescribing, pain management, or substance use disorder treatment, these requirements comprise a small component of the required post-training education requirements. Research is needed to determine whether this training translates into reductions in drug-related harm., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Published
2024
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