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9,481 results on '"Miller Christopher A"'

1. Bottom-Up and Top-Down Analysis of Values, Agendas, and Observations in Corpora and LLMs

Author

Friedman, Scott E., Benkler, Noam, Mosaphir, Drisana, Rye, Jeffrey, Schmer-Galunder, Sonja M., Goldwater, Micah, McLure, Matthew, Wheelock, Ruta, Gottlieb, Jeremy, Goldman, Robert P., and Miller, Christopher

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Large language models (LLMs) generate diverse, situated, persuasive texts from a plurality of potential perspectives, influenced heavily by their prompts and training data. As part of LLM adoption, we seek to characterize - and ideally, manage - the socio-cultural values that they express, for reasons of safety, accuracy, inclusion, and cultural fidelity. We present a validated approach to automatically (1) extracting heterogeneous latent value propositions from texts, (2) assessing resonance and conflict of values with texts, and (3) combining these operations to characterize the pluralistic value alignment of human-sourced and LLM-sourced textual data.

Published
2024

2. Two Dimensional Magnetic Current Imaging Via L1-Curl Regularized Divergence Free Wavelet Reconstruction

Author

Miller, Christopher, Mariano, Adrian, Oliver, Sean, Lenz, Jacob, and Martynowych, Dmitro

Subjects
Electrical Engineering and Systems Science - Image and Video Processing
Abstract

The reconstruction of current distributions from samples of their induced magnetic field is a challenging problem due to multiple factors. First, the problem of reconstructing general three dimensional current distributions is ill-posed. Second, the current-to-field operator performs a low-pass filter that dampens high-spatial frequency information, so that even in situations where the inversion is formally possible, attempting to employ the formal inverse will result in solutions with unacceptable noise. Most contemporary methods for reconstructing current distributions in two dimensions are based on Fourier techniques and apply a low pass filter to the $B$-field data, which prevents excessive noise amplification during reconstruction at the cost of admitting blurring in the reconstructed solution. In this report, we present a method of current recovery based on penalizing the $L1$ norm of the curl of the current distribution. The utility of this method is based on the observation that in microelectronics settings, the conductivity is piecewise constant. We also reconstruct the current fields using a divergence-free wavelet basis. This has the advantage of automatically enforcing current continuity and halving the number of unknowns that must be solved for. Additionally, the curl operator can be computed exactly and analytically in this wavelet expansion, which simplifies the application of the $L1-\textrm{curl}$ regularizer. We demonstrate improved reconstruction quality relative to Fourier-based techniques on both simulated and laboratory-acquired magnetic field data., Comment: 22 pages, 10 figures, submitted to SIAM Journal on Imaging Sciences

Published
2024

3. pVACview: an interactive visualization tool for efficient neoantigen prioritization and selection

Author

Xia, Huiming, Hoang, My, Schmidt, Evelyn, Kiwala, Susanna, McMichael, Joshua, Skidmore, Zachary L., Fisk, Bryan, Song, Jonathan J., Hundal, Jasreet, Mooney, Thomas, Walker, Jason R., Goedegebuure, S. Peter, Miller, Christopher A., Gillanders, William E., Griffith, Obi L., and Griffith, Malachi

Subjects
Quantitative Biology - Genomics
Abstract

Neoantigen targeting therapies including personalized vaccines have shown promise in the treatment of cancers. Accurate identification/prioritization of neoantigens is highly relevant to designing clinical trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel sequencing technologies, it is now possible to predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. While computational tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address. We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies. pVACview has a user-friendly and intuitive interface where users can upload, explore, select and export their neoantigen candidates. The tool allows users to visualize candidates using variant, transcript and peptide information. pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings. The application is available as part of the pVACtools pipeline at pvactools.org and as an online server at pvacview.org., Comment: Supplemental tables available at 10.5281/zenodo.11534338

Published
2024

4. Escape Velocity Mass of Abell S1063

Author

Rodriguez, Alexander, Miller, Christopher J., Halenka, Vitali, and Kremin, Anthony

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We measure the radius-velocity phase-space edge profile for Abell S1063 using galaxy redshifts from arXiv:1409.3507 and arXiv:2109.03305. Combined with a cosmological model and after accounting for interlopers and sampling effects, we infer the escape velocity profile. Using the Poisson equation, we then directly constrain the gravitational potential profile and find excellent agreement between three different density models. For the NFW profile, we find log$_{10}$(M$_{200},{\rm crit}$)= $15.40^{+0.06}_{-0.12}$M$_{\odot}$, consistent to within $1\sigma$ of six recently published lensing masses. We argue that this consistency is due to the fact that the escape technique shares no common systematics with lensing other than radial binning. These masses are 2-4$\sigma$ lower than estimates using X-ray data, in addition to earlier velocity dispersion estimates. We measure the 1D velocity dispersion within r$_{200}$ to be $\sigma_{v} = 1477^{+87}_{-99}$ km/s, which combined with our escape velocity mass, brings the dispersion for AS1063 in-line with hydrodynamic cosmological simulations for the first time.

Published
2024

5. Bounds on Distinguishing Separated Wires Using Magnetic Field Measurements

Author

Mariano, Adrian, Lenz, Jacob, Martynowych, Dmitro, Miller, Christopher, and Oliver, Sean

Subjects
Physics - Instrumentation and Detectors
Abstract

Magnetic current imaging (MCI) is useful for non-destructive characterization of microelectronics, including both security analysis and failure analysis, because magnetic fields penetrate the materials that comprise these components to enable through-package imaging of chip activity. Of particular interest are new capabilities offered by emerging magnetic field imagers, such as the Quantum Diamond Microscope, which provide simultaneous wide field-of-view, high spatial resolution vector magnetic field imaging capabilities under ambient conditions. While MCI offers several advantages for non-destructive measurement of microelectronics functional activity, there are many limitations of the technique due to rapid falloff of magnetic fields and loss of high frequency spatial information at large sensor standoff distances. To understand spatial resolution as a function of standoff distance, we consider the problem of using magnetic fields to distinguish (1) between a single wire carrying current $I$ and a pair of wires carrying current $I/2$ in the same direction and (2) between no currents and a pair of wires carrying current $I/2$ in opposite directions. In both cases, we compare performance for a single point measurement, representative of typical magnetometers, to performance for an array of measurements found in emerging magnetic imaging devices. Additionally, we examine the advantage provided by measurement of the full vector magnetic field compared to measurement of a single component. We establish and compare for the first time the theoretical lower bounds on separability based on the wire separation and sensor standoff distance of the magnetic field measurements obtained from traditional and new microelectronics reliability tools.

Published
2024

7. A functional microbiome catalogue crowdsourced from North American rivers

Author

Borton, Mikayla A., McGivern, Bridget B., Willi, Kathryn R., Woodcroft, Ben J., Mosier, Annika C., Singleton, Derick M., Bambakidis, Ted, Pelly, Aaron, Daly, Rebecca A., Liu, Filipe, Freiburger, Andrew, Edirisinghe, Janaka N., Faria, José P., Danczak, Robert, Leleiwi, Ikaia, Goldman, Amy E., Wilkins, Michael J., Hall, Ed K., Pennacchio, Christa, Roux, Simon, Eloe-Fadrosh, Emiley A., Good, Stephen P., Sullivan, Matthew B., Wood-Charlson, Elisha M., Miller, Christopher S., Ross, Matthew R. V., Henry, Christopher S., Crump, Byron C., Stegen, James C., and Wrighton, Kelly C.

Published
2024
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8. Optimizing NILC Extractions of the Thermal Sunyaev-Zeldovich Effect with Deep Learning

Author

Pratt, Cameron T., Qu, Zhijie, Bregman, Joel N., and Miller, Christopher J.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

All-sky maps of the thermal Sunyaev-Zel'dovich effect (SZ) tend to suffer from systematic features arising from the component separation techniques used to extract the signal. In this work, we investigate one of these methods known as needlet internal linear combination (NILC) and test its performance on simulated data. We show that NILC estimates are strongly affected by the choice of the spatial localization parameter ($\Gamma$), which controls a bias-variance trade-off. Typically, NILC extractions assume a fixed value of $\Gamma$ over the entire sky, but we show there exists an optimal $\Gamma$ that depends on the SZ signal strength and local contamination properties. Then we calculate the NILC solutions for multiple values of $\Gamma$ and feed the results into a neural network to predict the SZ signal. This extraction method, which we call Deep-NILC, is tested against a set of validation data, including recovered radial profiles of resolved systems. Our main result is that Deep-NILC offers significant improvements over choosing fixed values of $\Gamma$., Comment: 18 pages, 9 figures, 2 Tables, Accepted by ApJ

Published
2024

9. Neoantigen DNA vaccines are safe, feasible, and induce neoantigen-specific immune responses in triple-negative breast cancer patients

Author

Zhang, Xiuli, Goedegebuure, S. Peter, Chen, Michael Y., Mishra, Rashmi, Zhang, Felicia, Yu, Yik Yeung, Singhal, Kartik, Li, Lijin, Gao, Feng, Myers, Nancy B., Vickery, Tammi, Hundal, Jasreet, McLellan, Michael D., Sturmoski, Mark A., Kim, Samuel W., Chen, Ina, Davidson, 4th, Jesse T., Sankpal, Narendra V., Myles, Stephanie, Suresh, Rama, Ma, Cynthia X., Foluso, Ademuyiwa, Wang-Gillam, Andrea, Davies, Sherri, Hagemann, Ian S., Mardis, Elaine R., Griffith, Obi, Griffith, Malachi, Miller, Christopher A., Hansen, Ted H., Fleming, Timothy P., Schreiber, Robert D., and Gillanders, William E.

Published
2024
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12. Phenogrouping heart failure with preserved or mildly reduced ejection fraction using electronic health record data

Author

Soltani, Fardad, Jenkins, David A., Kaura, Amit, Bradley, Joshua, Black, Nicholas, Farrant, John P., Williams, Simon G., Mulla, Abdulrahim, Glampson, Benjamin, Davies, Jim, Papadimitriou, Dimitri, Woods, Kerrie, Shah, Anoop D., Thursz, Mark R., Williams, Bryan, Asselbergs, Folkert W., Mayer, Erik K., Herbert, Christopher, Grant, Stuart, Curzen, Nick, Squire, Iain, Johnson, Thomas, O’Gallagher, Kevin, Shah, Ajay M., Perera, Divaka, Kharbanda, Rajesh, Patel, Riyaz S., Channon, Keith M., Lee, Richard, Peek, Niels, Mayet, Jamil, and Miller, Christopher A.

Published
2024
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16. Mitigating Bias in Deep Learning: Training Unbiased Models on Biased Data for the Morphological Classification of Galaxies

Author

Medina-Rosales, Esteban, Cabrera-Vives, Guillermo, and Miller, Christopher J.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Galaxy morphologies and their relation with physical properties have been a relevant subject of study in the past. Most galaxy morphology catalogs have been labelled by human annotators or by machine learning models trained on human labelled data. Human generated labels have been shown to contain biases in terms of the observational properties of the data, such as image resolution. These biases are independent of the annotators, that is, are present even in catalogs labelled by experts. In this work, we demonstrate that training deep learning models on biased galaxy data produce biased models, meaning that the biases in the training data are transferred to the predictions of the new models. We also propose a method to train deep learning models that considers this inherent labelling bias, to obtain a de-biased model even when training on biased data. We show that models trained using our deep de-biasing method are capable of reducing the bias of human labelled datasets.

Published
2023

17. Methane point source quantification using MethaneAIR: a new airborne imaging spectrometer

Author

Chulakadabba, Apisada, Sargent, Maryann, Lauvaux, Thomas, Benmergui, Joshua S, Franklin, Jonathan E, Miller, Christopher Chan, Wilzewski, Jonas S, Roche, Sébastien, Conway, Eamon, Souri, Amir H, Sun, Kang, Luo, Bingkun, Hawthrone, Jacob, Samra, Jenna, Daube, Bruce C, Liu, Xiong, Chance, Kelly, Li, Yang, Gautam, Ritesh, Omara, Mark, Rutherford, Jeff S, Sherwin, Evan D, Brandt, Adam, and Wofsy, Steven C

Subjects
Earth Sciences, Atmospheric Sciences, Bioengineering, Climate Action, Meteorology & Atmospheric Sciences, Atmospheric sciences
Abstract

The MethaneSAT satellite instrument and its aircraft precursor, MethaneAIR, are imaging spectrometers designed to measure methane concentrations with wide spatial coverage, fine spatial resolution, and high precision compared to currently deployed remote sensing instruments. At 12 960 m cruise altitude above ground (13 850 m above sea level), MethaneAIR datasets have a 4.5 km swath gridded to 10 m × 10 m pixels with 17-20 ppb standard deviation on a flat scene. MethaneAIR was deployed in the summer of 2021 in the Permian Basin to test the accuracy of the retrieved methane concentrations and emission rates using the algorithms developed for MethaneSAT. We report here point source emissions obtained during a single-blind volume-controlled release experiment, using two methods. (1) The modified integrated mass enhancement (mIME) method estimates emission rates using the total mass enhancement of methane in an observed plume combined with winds obtained from Weather Research Forecast driven by High-Resolution Rapid Refresh meteorological data in Large Eddy Simulations mode (WRF-LES-HRRR). WRF-LES-HRRR simulates winds in stochastic eddy-scale (100-1000 m) variability, which is particularly important for low-wind conditions and informing the error budget. The mIME can estimate emission rates of plumes of any size that are detectable by MethaneAIR. (2) The divergence integral (DI) method applies Gauss's theorem to estimate the flux divergence fields through a series of closed surfaces enclosing the sources. The set of boxes grows from the upwind side of the plume through the core of each plume and downwind. No selection of inflow concentration, as used in the mIME, is required. The DI approach can efï¬ ciently determine ï¬ uxes from large sources and clusters of sources but cannot resolve small point emissions. These methods account for the effects of eddy-scale variation in different ways: The DI averages across many eddies, whereas the mIME re-samples many eddies from the LES simulation. The DI directly uses HRRR winds, while mIME uses WRF-LES-HRRR wind products. Emissions estimates from both the mIME and DI methods agreed closely with the single-blind volume-controlled experiments (N Combining double low line 21). The York regression between the estimated emissions and the released emissions has a slope of 0.96 [0.84, 1.08], R Combining double low line 0.83 and N Combining double low line 21, with 30 % mean percentage error for the whole dataset, which indicates that MethaneAIR can quantify point sources emitting more than 200 kg h-1 for the mIME and 500 kg h-1 for the DI method. The two methods also agreed on methane emission estimates from various uncontrolled sources in the Permian Basin. The experiment thus demonstrates the powerful potential of the MethaneAIR instrument and suggests that the quantification method should be transferable to MethaneSAT if it meets the design specifications.

Published
2023

21. Clinical Significance of Myocardial Injury in Patients Hospitalized for COVID-19: A Prospective, Multicenter, Cohort Study

Author

Greenwood, J.P., McCann, G.P., Berry, C., Dweck, M., Miller, C.M., Chiribiri, A., Prasad, S., Ferreira, V.M., Bucciarelli-Ducci, C., Dawson, D., Moon, James C., Artico, Jessica, Shiwani, Hunain, Davies, Rhodri, Dweck, Marc, Berry, Colin, Roditi, Giles, Young, Robin, McConnachie, Alex, Kelly, Bernard, Macfarlane, Peter W., Miller, Christopher A., Levelt, Eylem, Goreka, Miroslawa, Somers, Kathryn, Byrom-Goulthorp, Roo J., Anderson, Michelle, Britton, Laura, Richards, Fiona, Jones, Laura M., Arnold, Ranjit, Moss, Alastair, Fisher, Jude, Wormleighton, Joanne, Parke, Kelly, Wright, Rachel, Yeo, Jian, Dawson, Dana, Falconer, Judith, Harries, Valerie, Henderson, Paula, Singh, Trisha, Newby, David, Piechnik, Stefan, Popescu, Iulia, Lukaschuk, Elena, Zhang, Qiang, Shanmuganathan, Mayooran, Neubauer, Stefan, Raman, Betty, Channon, Keith, Krasopoulos, Catherine, Nunes, Claudia, Da Silva Rodrigues, Liliana, Nixon, Harriet, Panopoulou, Athanasia, Fletcher, Alison, Manley, Peter, Mangion, Kenneth, Morrow, Andrew, Sykes, Robert, Fallon, Kirsty, Brown, Ammani, Kelly, Laura, McGinley, Christopher, Briscoe, Michael, Woodward, Rosemary, Hopkins, Tracey, McLennan, Evonne, Tynan, Nicola, Dymock, Laura, Swoboda, Peter, Wright, Judith, Exley, Donna, Steeds, Richard, Hutton, Kady, MacDonald, Sonia, Treibel, Thomas, Shetye, Abhishek, Miller, Christopher M., Orsborne, Christopher, Woodville-Jones, William, Ferguson, Susan, Bratis, Konstantinos, Fairbairn, Timothy, Sionas, Michail, Widdows, Peris, Chew, Pei Gee, Marsden, Christian, Collins, Tom, George, Linsha, Kearney, Lisa, Flett, Andrew, Smith, Simon, Zhenge, Alice, Harvey, Jake, Inacio, Liliana, Hanam-Penfold, Tomas, Gruner, Lucy, Fontana, Marianna, Razvi, Yousuf S.K., Crause, Jacolene, Davies, Nina M., Brown, James T., Chaco, Liza, Patel, Rishi, Kotecha, Tushar, Knight, Dan S., Green, Thomas, Ripley, David, Thompson, Maria, Chiribiri, Amedeo, Akerele, Ugochi, Cifra, Elna, Alskaf, Ebraham, Crawley, Richard, Villa, Adriana, Bucciarelli-Ducci, Chiara, Nightingale, Angus K., Wright, Kim, Bonnick, Esther D., Hopkins, Emma, George, Jessy, Joseph, Linta, Cole, Graham, Vimalesvaran, Kavitha, Ali, Nadine, Carr, Caitlin R., Ross, Alexandra A.R., King, Clara, Prasad, Sanjay, Farzad, Zohreh, Salmi, Sara A., Kirby, Kevin, McDiarmid, Adam, Stevenson, Hannah J., Matsvimbo, Pamela S., Joji, Lency, Fearby, Margaret, Brown, Benjamin, Bunce, Nicholas, Jennings, Robert, Sookhoo, Vennessa, Joshi, Shatabdi, Kanagala, Prathap, Fullalove, Sandra, Toohey, Catherine, Fenlon, Kate, Bellenger, Nicholas, He, Jingzhou, Statton, Sarah, Pamphilon, Nicola, Steele, Anna, Ball, Claire, McGahey, Ann, Balma, Silvia, Wilkes, Lynsey, Lewis, Katy, Walter, Michelle, Ionescu, Adrian, Ninan, Tishi, Richards, Suzanne, Williams, Marie, Alfakih, Khaled, Pilgrim, Samia, Joy, George, Manisty, Charlotte H., Hussain, Ifza, Gorecka, Miroslawa, McCann, Gerry P., Alzahir, Mohammed, Ramirez, Sara, Lin, Andrew, Swoboda, Peter P., McDiarmid, Adam K., Manisty, Charlotte, Treibel, Thomas A., Piechnik, Stefan K., Davies, Rhodri H., Ferreira, Vanessa M., Dweck, Marc R., and Greenwood, John P.

Published
2024
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23. A functional microbiome catalog crowdsourced from North American rivers.

Author

Borton, Mikayla A, McGivern, Bridget B, Willi, Kathryn R, Woodcroft, Ben J, Mosier, Annika C, Singleton, Derick M, Bambakidis, Ted, Pelly, Aaron, Liu, Filipe, Edirisinghe, Janaka N, Faria, José P, Leleiwi, Ikaia, Daly, Rebecca A, Goldman, Amy E, Wilkins, Michael J, Hall, Ed K, Pennacchio, Christa, Roux, Simon, Eloe-Fadrosh, Emiley A, Good, Stephen P, Sullivan, Matthew B, Henry, Christopher S, Wood-Charlson, Elisha M, Ross, Matthew RV, Miller, Christopher S, Crump, Byron C, Stegen, James C, and Wrighton, Kelly C

Subjects
Microbiology, Environmental Sciences, Biological Sciences, Ecology, Human Genome, Genetics
Abstract

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. Specifically, GROWdb encompasses 1,469 microbial species from 27 phyla, including novel lineages from 10 families and 128 genera, and defines the core river microbiome for the first time at genome level. GROWdb analyses coupled to extensive geospatial information revealed local and regional drivers of microbial community structuring, while also presenting a myriad of foundational hypotheses about ecosystem function. Building upon the previously conceived River Continuum Concept 1 , we layer on microbial functional trait expression, which suggests the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures 2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.

Published
2023

24. Genetic characterization of primary and metastatic high-grade serous ovarian cancer tumors reveals distinct features associated with survival.

Author

Kotnik, Emilee N, Mullen, Mary M, Spies, Nicholas C, Li, Tiandao, Inkman, Matthew, Zhang, Jin, Martins-Rodrigues, Fernanda, Hagemann, Ian S, McCourt, Carolyn K, Thaker, Premal H, Hagemann, Andrea R, Powell, Matthew A, Mutch, David G, Khabele, Dineo, Longmore, Gregory D, Mardis, Elaine R, Maher, Christopher A, Miller, Christopher A, and Fuh, Katherine C

Subjects
Humans, Ovarian Neoplasms, Prognosis, Female, DNA Copy Number Variations, Rare Diseases, Cancer, Genetics, Human Genome, Prevention, Biotechnology, Clinical Research, Ovarian Cancer, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being
Abstract

High-grade serous ovarian cancer (HGSC) is the most lethal histotype of ovarian cancer and the majority of cases present with metastasis and late-stage disease. Over the last few decades, the overall survival for patients has not significantly improved, and there are limited targeted treatment options. We aimed to better characterize the distinctions between primary and metastatic tumors based on short- or long-term survival. We characterized 39 matched primary and metastatic tumors by whole exome and RNA sequencing. Of these, 23 were short-term (ST) survivors (overall survival (OS)  5 years). We compared somatic mutations, copy number alterations, mutational burden, differential gene expression, immune cell infiltration, and gene fusion predictions between the primary and metastatic tumors and between ST and LT survivor cohorts. There were few differences in RNA expression between paired primary and metastatic tumors, but significant differences between the transcriptomes of LT and ST survivors in both their primary and metastatic tumors. These findings will improve the understanding of the genetic variation in HGSC that exist between patients with different prognoses and better inform treatments by identifying new targets for drug development.

Published
2023

25. Developing Relational Coordination: A Qualitative Study of Outpatient Mental Health Teams

Author

Spitzer, Elizabeth G, Kaitz, Jenesse, Fix, Gemmae M, Harvey, Kimberly LL, Stadnick, Nicole A, Sullivan, Jennifer L, Williamson, Alicia K, and Miller, Christopher J

Subjects
Health Services and Systems, Nursing, Health Sciences, Mental Health, Clinical Research, Clinical Trials and Supportive Activities, Good Health and Well Being, Humans, Patient Care Team, Outpatients, Qualitative Research, Leadership, Relational Coordination, Mental health, Outpatient, Team functioning, Teamwork, Clinical Sciences, Public Health and Health Services, Psychology, Psychiatry, Health services and systems, Applied and developmental psychology, Clinical and health psychology
Abstract

Previous studies have shown Relational Coordination improves team functioning in healthcare settings. The aim of this study was to examine the relational factors needed to support team functioning in outpatient mental health care teams with low staffing ratios. We interviewed interdisciplinary mental health teams that had achieved high team functioning despite low staffing ratios in U.S. Department of Veterans Affairs medical centers. We conducted qualitative interviews with 21 interdisciplinary team members across three teams within two medical centers. We used directed content analysis to code the transcripts with a priori codes based on the Relational Coordination dimensions, while also being attentive to emergent themes. We found that all seven dimensions of Relational Coordination were relevant to improved team functioning: frequent communication, timely communication, accurate communication, problem-solving communication, shared goals, shared knowledge, and mutual respect. Participants also described these dimensions as reciprocal processes that influenced each other. In conclusion, relational Coordination dimensions can play pivotal roles in improving team functioning both individually and in combination. Communication dimensions were a catalyst for developing relationship dimensions; once relationships were developed, there was a mutually reinforcing cycle between communication and relationship dimensions. Our results suggest that establishing high-functioning mental health care teams, even in low-staffed settings, requires encouraging frequent communication within teams. Moreover, attention should be given to ensuring appropriate representation of disciplines among leadership and defining roles of team members when teams are formed.

Published
2023

27. Severe Acute Respiratory Syndrome Coronavirus 2 Vasculopathy in a Syrian Golden Hamster Model

Author

Ball, Erin E, Weiss, Christopher M, Liu, Hongwei, Jackson, Kenneth, Keel, M Kevin, Miller, Christopher J, Van Rompay, Koen KA, Coffey, Lark L, and Pesavento, Patricia A

Subjects
Biomedical and Clinical Sciences, Emerging Infectious Diseases, Coronaviruses, Infectious Diseases, Lung, 2.1 Biological and endogenous factors, Cardiovascular, Good Health and Well Being, Cricetinae, Animals, Humans, Mesocricetus, SARS-CoV-2, COVID-19, Vascular Diseases, Disease Models, Animal, Medical and Health Sciences, Pathology, Biomedical and clinical sciences, Health sciences
Abstract

Clinical evidence of vascular dysfunction and hypercoagulability as well as pulmonary vascular damage and microthrombosis are frequently reported in severe cases of human coronavirus disease 2019 (COVID-19). Syrian golden hamsters recapitulate histopathologic pulmonary vascular lesions reported in patients with COVID-19. Herein, special staining techniques and transmission electron microscopy further define vascular pathologies in a Syrian golden hamster model of human COVID-19. The results show that regions of active pulmonary inflammation in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are characterized by ultrastructural evidence of endothelial damage with platelet marginalization and both perivascular and subendothelial macrophage infiltration. SARS-CoV-2 antigen/RNA was not detectable within affected blood vessels. Taken together, these findings suggest that the prominent microscopic vascular lesions in SARS-CoV-2-inoculated hamsters likely occur due to endothelial damage followed by platelet and macrophage infiltration.

Published
2023

28. Computational prediction of MHC anchor locations guides neoantigen identification and prioritization

Author

Xia, Huiming, McMichael, Joshua, Becker-Hapak, Michelle, Onyeador, Onyinyechi C, Buchli, Rico, McClain, Ethan, Pence, Patrick, Supabphol, Suangson, Richters, Megan M, Basu, Anamika, Ramirez, Cody A, Puig-Saus, Cristina, Cotto, Kelsy C, Freshour, Sharon L, Hundal, Jasreet, Kiwala, Susanna, Goedegebuure, S Peter, Johanns, Tanner M, Dunn, Gavin P, Ribas, Antoni, Miller, Christopher A, Gillanders, William E, Fehniger, Todd A, Griffith, Obi L, and Griffith, Malachi

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Immunology, Vaccine Related, Genetics, Immunization, Humans, Antigens, Neoplasm, T-Lymphocytes, Mutation, Peptides, Neoplasms, Clinical sciences
Abstract

Neoantigens are tumor-specific peptide sequences resulting from sources such as somatic DNA mutations. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Accurate neoantigen identification is thus critical for both designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly predicting whether the presenting peptide sequence can successfully induce an immune response. Because most somatic mutations are single-nucleotide variants, changes between wild-type and mutated peptides are typically subtle and require cautious interpretation. A potentially underappreciated variable in neoantigen prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient's specific MHC molecules. Whereas a subset of peptide positions are presented to the T cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T cell responses. We computationally predicted anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6 to 38% of neoantigen candidates are potentially misclassified and can be rescued using allele-specific knowledge of anchor positions. A subset of anchor results were orthogonally validated using protein crystallography structures. Representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, we hope to formalize, streamline, and improve the identification process for relevant clinical studies.

Published
2023

29. kb_DRAM: annotation and metabolic profiling of genomes with DRAM in KBase

Author

Shaffer, Michael, Borton, Mikayla A, Bolduc, Ben, Faria, José P, Flynn, Rory M, Ghadermazi, Parsa, Edirisinghe, Janaka N, Wood-Charlson, Elisha M, Miller, Christopher S, Chan, Siu Hung Joshua, Sullivan, Matthew B, Henry, Christopher S, and Wrighton, Kelly C

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Human Genome, Networking and Information Technology R&D (NITRD), Genetics, Molecular Sequence Annotation, Software, Bacteria, Archaea, Metabolomics, Mathematical Sciences, Information and Computing Sciences, Bioinformatics, Biological sciences, Information and computing sciences, Mathematical sciences
Abstract

Microbial genome annotation is the process of identifying structural and functional elements in DNA sequences and subsequently attaching biological information to those elements. DRAM is a tool developed to annotate bacterial, archaeal, and viral genomes derived from pure cultures or metagenomes. DRAM goes beyond traditional annotation tools by distilling multiple gene annotations to genome level summaries of functional potential. Despite these benefits, a downside of DRAM is the requirement of large computational resources, which limits its accessibility. Further, it did not integrate with downstream metabolic modeling tools that require genome annotation. To alleviate these constraints, DRAM and the viral counterpart, DRAM-v, are now available and integrated with the freely accessible KBase cyberinfrastructure. With kb_DRAM users can generate DRAM annotations and functional summaries from microbial or viral genomes in a point-and-click interface, as well as generate genome-scale metabolic models from DRAM annotations.Availability and implementationFor kb_DRAM users, the kb_DRAM apps on KBase can be found in the catalog at https://narrative.kbase.us/#catalog/modules/kb_DRAM. For kb_DRAM users, a tutorial workflow with all documentation is available at https://narrative.kbase.us/narrative/129480. For kb_DRAM developers, software is available at https://github.com/shafferm/kb_DRAM.

Published
2023

31. Temperature Thresholds for Leaf Damage from Two Extreme Freeze Events (2018 and 2021) Near the Northern Range Limit of Black Mangroves (Avicennia germinans) in Southeastern North America

Author

Kaalstad, Simen, Osland, Michael J., Devlin, Donna J., Proffitt, C. Edward, Feher, Laura C., Armitage, Anna R., Day, Richard H., Swanson, Kathleen M., Anderson, Gordon H., Berger, Brigid, Cebrian, Just, Cummins, Karen L., Dunton, Kenneth H., Feller, Ilka C., Fierro-Cabo, Alejandro, Flores, Elena A., From, Andrew S., Hughes, A. Randall, Kaplan, David A., Langston, Amy K., Martinez, Melinda, Martinez, Briana, Miller, Christopher J., Reaver, Nathan G., Sanspree, Colt R., Snyder, Caitlin M., Stetter, Andrew P., Thompson, Jamie E., and Zamora-Tovar, Carlos

Published
2024
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32. Integrating Remote Sensing with Ground-based Observations to Quantify the Effects of an Extreme Freeze Event on Black Mangroves (Avicennia germinans) at the Landscape Scale

Author

Martinez, Melinda, Osland, Michael J., Grace, James B., Enwright, Nicholas M., Stagg, Camille L., Kaalstad, Simen, Anderson, Gordon H., Armitage, Anna R., Cebrian, Just, Cummins, Karen L., Day, Richard H., Devlin, Donna J., Dunton, Kenneth H., Feher, Laura C., Fierro-Cabo, Alejandro, Flores, Elena A., From, Andrew S., Hughes, A. Randall, Kaplan, David A., Langston, Amy K., Miller, Christopher, Proffitt, Charles E., Reaver, Nathan G. F., Sanspree, Colt R., Snyder, Caitlin M., Stetter, Andrew P., Swanson, Kathleen M., Thompson, Jamie E., and Zamora-Tovar, Carlos

Published
2024
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33. The MegaMapper: A Stage-5 Spectroscopic Instrument Concept for the Study of Inflation and Dark Energy

Author

Schlegel, David J., Kollmeier, Juna A., Aldering, Greg, Bailey, Stephen, Baltay, Charles, Bebek, Christopher, BenZvi, Segev, Besuner, Robert, Blanc, Guillermo, Bolton, Adam S., Bonaca, Ana, Bouri, Mohamed, Brooks, David, Buckley-Geer, Elizabeth, Cai, Zheng, Crane, Jeffrey, Demina, Regina, DeRose, Joseph, Dey, Arjun, Doel, Peter, Fan, Xiaohui, Ferraro, Simone, Finkbeiner, Douglas, Font-Ribera, Andreu, Gontcho, Satya Gontcho A, Green, Daniel, Gutierrez, Gaston, Guy, Julien, Heetderks, Henry, Huterer, Dragan, Infante, Leopoldo, Jelinsky, Patrick, Karagiannis, Dionysios, Kent, Stephen M., Kim, Alex G., Kneib, Jean-Paul, Kremin, Anthony, Kronig, Luzius, Konidaris, Nick, Lahav, Ofer, Lampton, Michael L., Landriau, Martin, Lang, Dustin, Leauthaud, Alexie, Levi, Michael E., Liguori, Michele, Linder, Eric V., Magneville, Christophe, Martini, Paul, Mateo, Mario, McDonald, Patrick, Miller, Christopher J., Moustakas, John, Myers, Adam D., Mulchaey, John, Newman, Jeffrey A., Nugent, Peter E., Padmanabhan, Nikhil, Palanque-Delabrouille, Nathalie, Piro, Antonella Palmese Anthony L., Poppett, Claire, Prochaska, Jason X., Pullen, Anthony R., Rabinowitz, David, Raichoor, Anand, Ramirez, Solange, Rix, Hans-Walter, Ross, Ashley J., Samushia, Lado, Schaan, Emmanuel, Schubnell, Michael, Seljak, Uros, Seo, Hee-Jong, Shectman, Stephen A., Schlafly, Edward F., Silber, Joseph, Simon, Joshua D., Slepian, Zachary, Slosar, Anže, Soares-Santos, Marcelle, Tarlé, Greg, Thompson, Ian, Valluri, Monica, Wechsler, Risa H., White, Martin, Wilson, Michael J., Yèche, Christophe, Zaritsky, Dennis, and Zhou, Rongpu

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment
Abstract

In this white paper, we present the MegaMapper concept. The MegaMapper is a proposed ground-based experiment to measure Inflation parameters and Dark Energy from galaxy redshifts at $2

Published
2022

34. A Spectroscopic Road Map for Cosmic Frontier: DESI, DESI-II, Stage-5

Author

Schlegel, David J., Ferraro, Simone, Aldering, Greg, Baltay, Charles, BenZvi, Segev, Besuner, Robert, Blanc, Guillermo A., Bolton, Adam S., Bonaca, Ana, Brooks, David, Buckley-Geer, Elizabeth, Cai, Zheng, DeRose, Joseph, Dey, Arjun, Doel, Peter, Drlica-Wagner, Alex, Fan, Xiaohui, Gutierrez, Gaston, Green, Daniel, Guy, Julien, Huterer, Dragan, Infante, Leopoldo, Jelinsky, Patrick, Karagiannis, Dionysios, Kent, Stephen M., Kim, Alex G., Kneib, Jean-Paul, Kollmeier, Juna A., Kremin, Anthony, Lahav, Ofer, Landriau, Martin, Lang, Dustin, Leauthaud, Alexie, Levi, Michael E., Linder, Eric V., Magneville, Christophe, Martini, Paul, McDonald, Patrick, Miller, Christopher J., Myers, Adam D., Newman, Jeffrey A., Nugent, Peter E., Palanque-Delabrouille, Nathalie, Padmanabhan, Nikhil, Palmese, Antonella, Poppett, Claire, Prochaska, Jason X., Raichoor, Anand, Ramirez, Solange, Sailer, Noah, Schaan, Emmanuel, Schubnell, Michael, Seljak, Uros, Seo, Hee-Jong, Silber, Joseph, Simon, Joshua D., Slepian, Zachary, Soares-Santos, Marcelle, Tarle, Greg, Valluri, Monica, Weaverdyck, Noah J., Wechsler, Risa H., White, Martin, Yeche, Christophe, and Zhou, Rongpu

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Experiment
Abstract

In this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction of the available linear modes up to z=1.2. DESI-II will pilot observations of galaxies both at much higher densities and extending to higher redshifts. A Stage-5 experiment would build out those high-density and high-redshift observations, mapping hundreds of millions of stars and galaxies in three dimensions, to address the problems of inflation, dark energy, light relativistic species, and dark matter. These spectroscopic data will also complement the next generation of weak lensing, line intensity mapping and CMB experiments and allow them to reach their full potential., Comment: Contribution to Snowmass 2021

Published
2022

35. Diagnostic utility of electrocardiogram for screening of cardiac injury on cardiac magnetic resonance in post-hospitalised COVID-19 patients: a prospective multicenter study

Author

Samat, Azlan Helmy Abd, Cassar, Mark P., Akhtar, Abid M., McCracken, Celeste, Ashkir, Zakariye M., Mills, Rebecca, Moss, Alastair J., Finnigan, Lucy E.M., Lewandowski, Adam J., Mahmod, Masliza, Ogbole, Godwin I., Tunnicliffe, Elizabeth M., Lukaschuk, Elena, Piechnik, Stefan K., Ferreira, Vanessa M., Nikolaidou, Chrysovalantou, Rahman, Najib M., Ho, Ling-Pei, Harris, Victoria C., Singapuri, Amisha, Manisty, Charlotte, O'Regan, Declan P., Weir-McCall, Jonathan R., Steeds, Richard P., LLM, Krisnah Poinasamy, Cuthbertson, Dan J., Kemp, Graham J., Horsley, Alexander, Miller, Christopher A., O'Brien, Caitlin, Chiribiri, Amedeo, Francis, Susan T., Chalmers, James D., Plein, Sven, Poener, Ana-Maria, Wild, James M., Treibel, Thomas A., Marks, Michael, Toshner, Mark, Wain, Louise V., Evans, Rachael A., Brightling, Christopher E., Neubauer, Stefan, McCann, Gerry P., and Raman, Betty

Published
2024
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