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Background: Debate continues regarding the usefulness and benefits of wide prescription of antibiotics in patients hospitalized with coronavirus disease 2019 (COVID-19). Methods: All patients hospitalized in the Infectious Diseases Department, Dijon University Hospital, Dijon, France between 27 February and 30 April 2020 with confirmed COVID-19 were included in this study. Clinical, biological and radiological data were collected, as well as treatment and outcome data. An unfavourable outcome was defined as death or transfer to the intensive care unit. Patient characteristics and outcomes were compared between patients who did and did not receive antibiotic therapy using propensity score matching. Findings: Among the 222 patients included, 174 (78%) received antibiotic therapy. The univariate analysis showed that patients who received antibiotic therapy were significantly older, frailer and had more severe presentation at admission compared with patients who did not receive antibiotic therapy. Unfavourable outcomes were more common in patients who received antibiotic therapy [hazard ratio (HR) 2.94, 95% confidence interval (CI) 1.07–8.11; P = 0.04]. Multi-variate analysis and propensity score matching indicated that antibiotic therapy was not significantly associated with outcome (HR 1.612, 95% CI 0.562–4.629; P = 0.37). Conclusion: Antibiotics were frequently prescribed in this study and this was associated with more severe presentation at admission. However, antibiotic therapy was not associated with outcome, even after adjustment. In line with recent publications, such data support the need to streamline antibiotic therapy in patients with COVID-19.

A cornerstone of the management and conservation of archaeological sites is recording their physical characteristics. Documenting and describing the site is an essential step that allows for delineating the components of the site and for collecting and synthesizing information and documentation (Demas, 2012). The information produced by such work assists in the decision-making process for custodians, site managers, public officials, conservators, and other related experts. Rigorous documentation may also serve a broader purpose: over time, it becomes the primary archival and monitoring record. Both scholars and the public use this information and interpret the site, and they can serve as a posterity record in the event of catastrophic or gradual loss of the heritage asset. In May 2018 the Getty Conservation Institute and the Department of Antiquities of Cyprus collaborated with the Carleton Immersive Media Studio in undertaking the documentation of Nea Paphos, a World Heritage site with very important mosaic pavements in the eastern Mediterranean. This contribution outlines the critical components of the documentation project: field study, field measurements, data processing, validation, GIS, and integration of external data. The paper summarizes the digital workflows and procedures used to produce the deliverables, as well as the equipment and technology employed.

The use of photogrammetry and terrestrial laser scanning for building information modelling (BIM) in the documentation and conservation of Cultural Heritage (CH) is now well established. By combining BIM with the latest visualization technologies, powerful, semi-immersive experiences can be developed to enhance the dissemination of CH. In semi-immersive experiences such as Augmented Reality (AR), digital content can be overlapped on to physical spaces, providing a new way to interact with both the physical space and the digital content. This paper discusses the translation of a digital object created using BIM, into a physical object and the utilisation of this physical object as a trigger for an AR experience. The case study looks at one of the neo- Gothic window frames from the House of Commons in the Centre Block of the Parliament Hill National Historic Site, in Ottawa, Canada. The window frame is one in a series that represents a Canadian province or territory with a stained glass feature that includes floral emblems and heraldic symbols from the respective provincial or territorial shield. The frame in this case study corresponds to the stained glass window of five provinces. Using the replica frame as a target, the user can select which stained glass windows they would like to view in the AR application. Through these combined technologies, we argue that CH can be revealed in a more interactive way and therefore more engaging manner – making even inaccessible architectural details readily available to the public.

Abstract Background Veterans of the 1990–1991 Gulf War have experienced excess health problems, most prominently the multisymptom condition Gulf War illness (GWI). The Department of Veterans Affairs (VA) Cooperative Studies Program #2006 “Genomics of Gulf War Illness in Veterans” project was established to address important questions concerning pathobiological and genetic aspects of GWI. The current study evaluated patterns of chronic ill health/GWI in the VA Million Veteran Program (MVP) Gulf War veteran cohort in relation to wartime exposures and key features of deployment, 27–30 years after Gulf War service. Methods MVP participants who served in the 1990–1991 Gulf War completed the MVP Gulf War Era Survey in 2018–2020. Survey responses provided detailed information on veterans’ health, Gulf War exposures, and deployment time periods and locations. Analyses determined associations of three defined GWI/ill health outcomes with Gulf War deployment characteristics and exposures. Results The final cohort included 14,103 veterans; demographic and military characteristics of the sample were similar to the full population of U.S. 1990–1991 Gulf War veterans. Overall, a substantial number of veterans experienced chronic ill health, as indicated by three defined outcomes: 49% reported their health as fair or poor, 31% met Centers for Disease Control and Prevention criteria for severe GWI, and 20% had been diagnosed with GWI by a healthcare provider. Health outcomes varied consistently with veterans’ demographic and military characteristics, and with exposures during deployment. All outcomes were most prevalent among youngest veterans (

Abstract Introduction Heparin binding proteins (HBPs) with roles in extracellular matrix assembly are strongly correlated to β-amyloid (Aβ) and tau pathology in Alzheimer’s disease (AD) brain and cerebrospinal fluid (CSF). However, it remains challenging to detect these proteins in plasma using standard mass spectrometry-based proteomic approaches. Methods We employed heparin-affinity chromatography, followed by off-line fractionation and tandem mass tag mass spectrometry (TMT-MS), to enrich HBPs from plasma obtained from AD (n = 62) and control (n = 47) samples. These profiles were then correlated to Aβ, tau and phosphorylated tau (pTau) CSF biomarkers and plasma pTau181 from the same individuals, as well as a consensus brain proteome network to assess the overlap with AD brain pathophysiology. Results Heparin enrichment from plasma was highly reproducible, enriched well-known HBPs like APOE and thrombin, and depleted high-abundant proteins such as albumin. A total of 2865 proteins, spanning 10 orders of magnitude in abundance, were measured across 109 samples. Compared to the consensus AD brain protein co-expression network, we observed that specific plasma proteins exhibited consistent direction of change in both brain and plasma, whereas others displayed divergent changes, highlighting the complex interplay between the two compartments. Elevated proteins in AD plasma, when compared to controls, included members of the matrisome module in brain that accumulate with Aβ deposits, such as SMOC1, SMOC2, SPON1, MDK, OLFML3, FRZB, GPNMB, and the APOE4 proteoform. Additionally, heparin-enriched proteins in plasma demonstrated significant correlations with conventional AD CSF biomarkers, including Aβ, total tau, pTau, and plasma pTau181. A panel of five plasma proteins classified AD from control individuals with an area under the curve (AUC) of 0.85. When combined with plasma pTau181, the panel significantly improved the classification performance of pTau181 alone, increasing the AUC from 0.93 to 0.98. This suggests that the heparin-enriched plasma proteome captures additional variance in cognitive dementia beyond what is explained by pTau181. Conclusion These findings support the utility of a heparin-affinity approach coupled with TMT-MS for enriching amyloid-associated proteins, as well as a wide spectrum of plasma biomarkers that reflect pathological changes in the AD brain.

Abstract Preventative treatment for Alzheimer’s Disease (AD) is dire, yet mechanisms underlying early regional vulnerability remain unknown. In AD, one of the earliest pathophysiological correlates to cognitive decline is hyperexcitability, which is observed first in the entorhinal cortex. Why hyperexcitability preferentially emerges in specific regions in AD is unclear. Using regional, cell-type-specific proteomics and electrophysiology in wild-type mice, we uncovered a unique susceptibility of the entorhinal cortex to human amyloid precursor protein (hAPP). Entorhinal hyperexcitability resulted from selective vulnerability of parvalbumin (PV) interneurons, with respect to surrounding excitatory neurons. This effect was partially replicated with an APP chimera containing a humanized amyloid-beta sequence. EC hyperexcitability could be ameliorated by co-expression of human Tau with hAPP at the expense of increased pathological tau species, or by enhancing PV interneuron excitability in vivo. This study suggests early interventions targeting inhibitory neurons may protect vulnerable regions from the effects of APP/amyloid and tau pathology.

Abstract Objective To define tauopathy‐associated changes in the human gray and white matter proteome. Method We applied tandem mass tagged labeling and mass spectrometry, consensus, and ratio weighted gene correlation network analysis (WGCNA) to gray and white matter sampled from postmortem human dorsolateral prefrontal cortex. The sampled tissues included control as well as Alzheimer's disease, corticobasal degeneration, progressive supranuclear palsy, frontotemporal degeneration with tau pathology, and chronic traumatic encephalopathy. Results Only eight proteins were unique to gray matter while six were unique to white matter. Comparison of the gray and white matter proteome revealed an enrichment of microglial proteins in the white matter. Consensus WGCNA sorted over 6700 protein isoforms into 46 consensus modules across the gray and white matter proteomic networks. Consensus network modules demonstrated unique and shared disease‐associated microglial and endothelial protein changes. Ratio WGCNA sorted over 6500 protein ratios (white:gray) into 33 modules. Modules associated with mitochondrial proteins and processes demonstrated higher white:gray ratios in diseased tissues relative to control, driven by mitochondrial protein downregulation in gray and upregulation in white. Interpretation The dataset is a valuable resource for understanding proteomic changes in human tauopathy gray and white matter. The identification of unique and shared disease‐associated changes across gray and white matter emphasizes the utility of examining both tissue types. Future studies of microglial, endothelial, and mitochondrial changes in white matter may provide novel insights into tauopathy‐associated changes in human brain.

Abstract Lewy body dementia (LBD), a class of disorders comprising Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB), features substantial clinical and pathological overlap with Alzheimer’s disease (AD). The identification of biomarkers unique to LBD pathophysiology could meaningfully advance its diagnosis, monitoring, and treatment. Using quantitative mass spectrometry (MS), we measured over 9,000 proteins across 138 dorsolateral prefrontal cortex (DLPFC) tissues from a University of Pennsylvania autopsy collection comprising control, Parkinson’s disease (PD), PDD, and DLB diagnoses. We then analyzed co-expression network protein alterations in those with LBD, validated these disease signatures in two independent LBD datasets, and compared these findings to those observed in network analyses of AD cases. The LBD network revealed numerous groups or “modules” of co-expressed proteins significantly altered in PDD and DLB, representing synaptic, metabolic, and inflammatory pathophysiology. A comparison of validated LBD signatures to those of AD identified distinct differences between the two diseases. Notably, synuclein-associated presynaptic modules were elevated in LBD but decreased in AD relative to controls. We also found that glial-associated matrisome signatures consistently elevated in AD were more variably altered in LBD, ultimately stratifying those LBD cases with low versus high burdens of concurrent beta-amyloid deposition. In conclusion, unbiased network proteomic analysis revealed diverse pathophysiological changes in the LBD frontal cortex distinct from alterations in AD. These results highlight the LBD brain network proteome as a promising source of biomarkers that could enhance clinical recognition and management.

Abstract Early detection of liver malignancy based on medical image analysis plays a crucial role in patient prognosis and personalized treatment. This task, however, is challenging due to several factors, including medical data scarcity and limited training samples. This paper presents a study of three important aspects of radiomics feature from multiphase computed tomography (CT) for classifying hepatocellular carcinoma (HCC) and other focal liver lesions: wavelet-transformed feature extraction, relevant feature selection, and radiomics features-based classification under the inadequate training samples. Our analysis shows that combining radiomics features extracted from the wavelet and original CT domains enhance the classification performance significantly, compared with using those extracted from the wavelet or original domain only. To facilitate the multi-domain and multiphase radiomics feature combination, we introduce a logistic sparsity-based model for feature selection with Bayesian optimization and find that the proposed model yields more discriminative and relevant features than several existing methods, including filter-based, wrapper-based, or other model-based techniques. In addition, we present analysis and performance comparison with several recent deep convolutional neural network (CNN)-based feature models proposed for hepatic lesion diagnosis. The results show that under the inadequate data scenario, the proposed wavelet radiomics feature model produces comparable, if not higher, performance metrics than the CNN-based feature models in terms of area under the curve.

Abstract Background Despite being twice as likely to get Alzheimer’s disease (AD), African Americans have been grossly underrepresented in AD research. While emerging evidence indicates that African Americans with AD have lower cerebrospinal fluid (CSF) levels of Tau compared to Caucasians, other differences in AD CSF biomarkers have not been fully elucidated. Here, we performed unbiased proteomic profiling of CSF from African Americans and Caucasians with and without AD to identify both common and divergent AD CSF biomarkers. Methods Multiplex tandem mass tag-based mass spectrometry (TMT-MS) quantified 1,840 proteins from 105 control and 98 AD patients of which 100 identified as Caucasian while 103 identified as African American. We used differential protein expression and co-expression approaches to assess how changes in the CSF proteome are related to race and AD. Co-expression network analysis organized the CSF proteome into 14 modules associated with brain cell-types and biological pathways. A targeted mass spectrometry method, selected reaction monitoring (SRM), with heavy labeled internal standards was used to measure a panel of CSF module proteins across a subset of African Americans and Caucasians with or without AD. A receiver operating characteristic (ROC) curve analysis assessed the performance of each protein biomarker in differentiating controls and AD by race. Results Consistent with previous findings, the increase of Tau levels in AD was greater in Caucasians than in African Americans by both immunoassay and TMT-MS measurements. CSF modules which included 14–3-3 proteins (YWHAZ and YWHAG) demonstrated equivalent disease-related elevations in both African Americans and Caucasians with AD, whereas other modules demonstrated more profound disease changes within race. Modules enriched with proteins involved with glycolysis and neuronal/cytoskeletal proteins, including Tau, were more increased in Caucasians than in African Americans with AD. In contrast, a module enriched with synaptic proteins including VGF, SCG2, and NPTX2 was significantly lower in African Americans than Caucasians with AD. Following SRM and ROC analysis, VGF, SCG2, and NPTX2 were significantly better at classifying African Americans than Caucasians with AD. Conclusions Our findings provide insight into additional protein biomarkers and pathways reflecting underlying brain pathology that are shared or differ by race.

Abstract Background The Million Veteran Program (MVP) participants represent 100 years of US history, including significant social and demographic changes over time. Our study assessed two aspects of the MVP: (i) longitudinal changes in population diversity and (ii) how these changes can be accounted for in genome-wide association studies (GWAS). To investigate these aspects, we divided MVP participants into five birth cohorts (N-range = 123,888 [born from 1943 to 1947] to 136,699 [born from 1948 to 1953]). Results Ancestry groups were defined by (i) HARE (harmonized ancestry and race/ethnicity) and (ii) a random-forest clustering approach using the 1000 Genomes Project and the Human Genome Diversity Project (1kGP + HGDP) reference panels (77 world populations representing six continental groups). In these groups, we performed GWASs of height, a trait potentially affected by population stratification. Birth cohorts demonstrate important trends in ancestry diversity over time. More recent HARE-assigned Europeans, Africans, and Hispanics had lower European ancestry proportions than older birth cohorts (0.010

Abstract Alzheimer’s disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) β-amyloid (Aβ), total Tau, and phosphorylated Tau (pTau) providing the most sensitive and specific biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the complex changes in AD brain beyond amyloid (A) and Tau (T) pathologies. Here, we report a selected reaction monitoring mass spectrometry (SRM-MS) method with isotopically labeled standards for relative protein quantification in CSF. Biomarker positive (AT+) and negative (AT−) CSF pools were used as quality controls (QCs) to assess assay precision. We detected 62 peptides (51 proteins) with an average coefficient of variation (CV) of ~13% across 30 QCs and 133 controls (cognitively normal, AT−), 127 asymptomatic (cognitively normal, AT+) and 130 symptomatic AD (cognitively impaired, AT+). Proteins that could distinguish AT+ from AT− individuals included SMOC1, GDA, 14-3-3 proteins, and those involved in glycolysis. Proteins that could distinguish cognitive impairment were mainly neuronal proteins (VGF, NPTX2, NPTXR, and SCG2). This demonstrates the utility of SRM-MS to quantify CSF protein biomarkers across stages of AD.

Cognitive impairment in the elderly features complex molecular pathophysiology extending beyond the hallmark pathologies of traditional disease classification. Molecular subtyping using large-scale -omic strategies can help resolve this biological heterogeneity. Using quantitative mass spectrometry, we measured ∼8000 proteins across >600 dorsolateral prefrontal cortex tissues with clinical diagnoses of no cognitive impairment (NCI), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia. Unbiased classification of MCI and AD cases based on individual proteomic profiles resolved three classes with expression differences across numerous cell types and biological ontologies. Two classes displayed molecular signatures atypical of AD neurodegeneration, such as elevated synaptic and decreased inflammatory markers. In one class, these atypical proteomic features were associated with clinical and pathological hallmarks of cognitive resilience. We were able to replicate these classes and their clinicopathological phenotypes across two additional tissue cohorts. These results promise to better define the molecular heterogeneity of cognitive impairment and meaningfully impact its diagnostic and therapeutic precision.

There is an urgent need to improve the translational validity of Alzheimer's disease (AD) mouse models. Introducing genetic background diversity in AD mouse models has been proposed as a way to increase validity and enable the discovery of previously uncharacterized genetic contributions to AD susceptibility or resilience. However, the extent to which genetic background influences the mouse brain proteome and its perturbation in AD mouse models is unknown. In this study, we crossed the 5XFAD AD mouse model on a C57BL/6J (B6) inbred background with the DBA/2J (D2) inbred background and analyzed the effects of genetic background variation on the brain proteome in F1 progeny. Both genetic background and 5XFAD transgene insertion strongly affected protein variance in the hippocampus and cortex (n = 3,368 proteins). Protein co-expression network analysis identified 16 modules of highly co-expressed proteins common across the hippocampus and cortex in 5XFAD and non-transgenic mice. Among the modules strongly influenced by genetic background were those related to small molecule metabolism and ion transport. Modules strongly influenced by the 5XFAD transgene were related to lysosome/stress responses and neuronal synapse/signaling. The modules with the strongest relationship to human disease—neuronal synapse/signaling and lysosome/stress response—were not significantly influenced by genetic background. However, other modules in 5XFAD that were related to human disease, such as GABA synaptic signaling and mitochondrial membrane modules, were influenced by genetic background. Most disease-related modules were more strongly correlated with AD genotype in the hippocampus compared with the cortex. Our findings suggest that the genetic diversity introduced by crossing B6 and D2 inbred backgrounds influences proteomic changes related to disease in the 5XFAD model, and that proteomic analysis of other genetic backgrounds in transgenic and knock-in AD mouse models is warranted to capture the full range of molecular heterogeneity in genetically diverse models of AD.

SAMHD1 has a dNTPase-independent resection function in genome maintenance. Here the authors show that SAMHD1 is deacetylated at conserved K354 by SIRT1 to facilitate direct binding with ssDNA to promote DNA end resection and homologous recombination.

Abstract Robust and accessible biomarkers that can capture the heterogeneity of Alzheimer’s disease and its diverse pathological processes are urgently needed. Here, we undertook an investigation of Alzheimer’s disease cerebrospinal fluid (CSF) and plasma from the same subjects (n=18 control, n=18 AD) using three different proteomic platforms—SomaLogic SomaScan, Olink proximity extension assay, and tandem mass tag-based mass spectrometry—to assess which protein markers in these two biofluids may serve as reliable biomarkers of AD pathophysiology observed from unbiased brain proteomics studies. Median correlation of overlapping protein measurements across platforms in CSF (r~0.7) and plasma (r~0.6) was good, with more variability in plasma. The SomaScan technology provided the most measurements in plasma. Surprisingly, many proteins altered in AD CSF were found to be altered in the opposite direction in plasma, including important members of AD brain co-expression modules. An exception was SMOC1, a key member of the brain matrisome module associated with amyloid-β deposition in AD, which was found to be elevated in both CSF and plasma. Protein co-expression analysis on greater than 7000 protein measurements in CSF and 9500 protein measurements in plasma across all proteomic platforms revealed strong changes in modules related to autophagy, ubiquitination, and sugar metabolism in CSF, and endocytosis and the matrisome in plasma. Cross-platform and cross-biofluid proteomics represents a promising approach for AD biomarker development.

Abstract Background Alzheimer’s Disease (AD) affects millions globally, but therapy development is lagging. New experimental systems that monitor neuronal functions in conditions approximating the AD brain may be beneficial for identifying new therapeutic strategies. Methods We expose cultured neurons to aqueous-soluble human brain extract from 43 individuals across a spectrum of AD pathology. Multi-electrode arrays (MEAs) and live-cell imaging were used to assess neuronal firing and neurite integrity (NI), respectively, following treatments of rat cortical neurons (MEA) and human iPSC-derived neurons (iN) with human brain extracts. Results We observe associations between spontaneous activity and Aβ42:40 levels, between neurite integrity and oligomeric Aβ, and between neurite integrity and tau levels present in the brain extracts. However, these associations with Aβ and tau do not fully account for the effects observed. Proteomic profiling of the brain extracts revealed additional candidates correlated with neuronal structure and activity. Neurotoxicity in MEA and NI assays was associated with proteins implicated in lysosomal storage disorders, while neuroprotection was associated with proteins of the WAVE regulatory complex controlling actin cytoskeleton dynamics. Elevated ganglioside GM2 activator (GM2A) associates with reductions in both NI and MEA activity, and cell-derived GM2A alone is sufficient to induce a loss of neurite integrity and a reduction in neuronal firing. Conclusions The techniques and data herein introduce a system for modeling neuronal vulnerability in response to factors in the human brain and provide insights into proteins potentially contributing to AD pathogenesis.

Summary: SORL1 is implicated in the pathogenesis of Alzheimer’s disease (AD) through genetic studies. To interrogate the roles of SORL1 in human brain cells, SORL1-null induced pluripotent stem cells (iPSCs) were differentiated to neuron, astrocyte, microglial, and endothelial cell fates. Loss of SORL1 leads to alterations in both overlapping and distinct pathways across cell types, with the greatest effects in neurons and astrocytes. SORL1 loss induces a neuron-specific reduction in apolipoprotein E (APOE) and clusterin (CLU) and altered lipid profiles. Analyses of iPSCs derived from a large cohort reveal a neuron-specific association between SORL1, APOE, and CLU levels, a finding validated in postmortem brain. Enhancement of retromer-mediated trafficking rescues tau phenotypes observed in SORL1-null neurons but does not rescue APOE levels. Pathway analyses implicate transforming growth factor β (TGF-β)/SMAD signaling in SORL1 function, and modulating SMAD signaling in neurons alters APOE RNA levels in a SORL1-dependent manner. Taken together, these data provide a mechanistic link between strong genetic risk factors for AD.

The practical application of single atom catalyst (SAC) in liquid-phase heterogeneous catalysis is hampered by the productivity bottleneck as well as catalyst leaching. Here, a bench-top, fast-flow reactor integrated with Pt1-MoS2 SAC was fabricated for continuous production of multifunctional anilines (28 examples) at a record productivity of 5.8 g h-1.

Current isolation-based approaches for cell type-specific proteomics pose several challenges. Here, the authors present an approach for in vivo cell type-specific protein labeling to characterize proteomic differences between neurons and astrocytes in their native state in adult mouse brain.

Mitochondria influence cellular function through both cell-autonomous and non-cell autonomous mechanisms, such as production of paracrine and endocrine factors. Here, we demonstrate that mitochondrial regulation of the secretome is more extensive than previously appreciated, as both genetic and pharmacological disruption of the electron transport chain caused upregulation of the Alzheimer’s disease risk factor apolipoprotein E (APOE) and other secretome components. Indirect disruption of the electron transport chain by gene editing of SLC25A mitochondrial membrane transporters as well as direct genetic and pharmacological disruption of either complexes I, III, or the copper-containing complex IV of the electron transport chain elicited upregulation of APOE transcript, protein, and secretion, up to 49-fold. These APOE phenotypes were robustly expressed in diverse cell types and iPSC-derived human astrocytes as part of an inflammatory gene expression program. Moreover, age- and genotype-dependent decline in brain levels of respiratory complex I preceded an increase in APOE in the 5xFAD mouse model. We propose that mitochondria act as novel upstream regulators of APOE-dependent cellular processes in health and disease.

The Delft3D hydrodynamic and wave model is used to hindcast the storm surge and waves that impacted La Rochelle, France, and the surrounding area (Aytré, Châtelaillon-Plage, Yves, Fouras, and Île de Ré) during storm Xynthia. These models are validated against tide and wave measurements. The models then estimate the footprint of flow depth, speed, unit discharge, flow momentum flux, significant wave height, wave energy flux, total water depth (flow depth plus wave height), and total (flow plus wave) force at the locations of damaged buildings for which insurance claims data are available. Correlation of the hydrodynamic and wave results with the claims data generates building damage functions. These damage functions are shown to be sensitive to the topography data used in the simulation, as well as the hydrodynamic or wave forcing parameter chosen for the correlation. The most robust damage functions result from highly accurate topographic data and are correlated with water depth or total (flow plus wave) force.

Accurate alignment of multi-session medical imaging is essential to the analysis of disease progression. By comparing the magnetic resonance imaging (MRI) data captured before and after a course of neoadjuvant chemoradiation (nCRT) treatment, physicians are able to evaluate the tumor response for further treatment of the disease. However, rectal MRI data captured in multi-session are often misaligned and not guaranteed to have one-to-one correspondence, making it challenging for physicians to observe the treatment response of tumor. To address this issue, we propose an unsupervised learning based volume registration framework, which enables accurate alignment even under a high degree of deformation between multi-session rectal data. Moreover, it works without the assumption of one-to-one correspondence between multi-session data, and hence is a general solution to rectal MRI volume registration. The experimental results show that the proposed registration framework accurately aligns rectal cancer images and outperforms other state-of-the-art methods in medical image registration. By providing accurate registration, it can potentially increase the efficiency and reduce the workload for physicians to evaluate the rectal tumor response to nCRT.

In-depth and reliable characterization of advanced nanoparticles is crucial for revealing the origin of their unique features and for designing novel functional materials with tailored properties. Due to their small size, characterization beyond nanometric resolution, notably, by transmission electron microscopy (TEM) and associated techniques, is essential to provide meaningful information. Nevertheless, nanoparticles, especially those containing volatile elements or organic components, are sensitive to radiation damage. Here, using CsPbBr3 perovskite nanocrystals as an example, strategies to preserve the native structure of radiation-sensitive nanocrystals in high-resolution electron microscopy studies are presented. Atomic-resolution images obtained using graphene support films allow for a clear comparison with simulation results, showing that most CsPbBr3 nanocrystals are orthorhombic. Low-dose TEM reveals faceted nanocrystals with no in situ formed Pb crystallites, a feature observed in previous TEM studies that has been attributed to radiation damage. Cryo-electron microscopy further delays observable effects of radiation damage. Powder electron diffraction with a hybrid pixel direct electron detector confirms the domination of orthorhombic crystals. These results emphasize the importance of optimizing TEM grid preparation and of exploiting data collection strategies that impart minimum electron dose for revealing the true structure of radiation-sensitive nanocrystals.

In recent years, an international consortium of research organizations conducted investigations at the Chicxulub Crater in Yucatan, Mexico, to better understand the crater’s formation mechanisms and the effects produced by the impact of the asteroid that is hypothesized to have caused one of the major life extinctions on Earth. This study aims to reproduce the asteroid’s impact mechanics by matching computer simulations obtained with the use of the distinct element method (DEM) against the latest topographic data observed across the crater footprint. A 2D model was formulated using ITASCA’s PFC2D software to reproduce the asteroid’s impact on Earth. The model ground conditions prior to impact were replicated based on available geological and geophysical field information. Also, the proposed DEM model configuration was designed to reproduce a far-field effect to ascertain the energy dissipation of the asteroid’s impact at the model’s boundaries. Impact conditions of the asteroid were defined based on previous asteroid impact investigations. A parametric analysis including the asteroid’s impact angle and the asteroid’s impact velocity was conducted to assess their influence on the crater formation process. Results of the simulations included the final crater topography and stratigraphy, stress profiles, contact force chains, and velocity fields. Numerical simulations showed that both the asteroid velocity and impact inclination play a major role in the crater formation process, and that the use of DEM provides interesting insights into impact crater formation.

Metal-based aerogels have attracted numerous studies due to their unique physical, structural, thermal, and chemical properties. Utilizing aluminum waste, a novel, facile, environmentally friendly approach to aluminum-based aerogels is proposed. In this work, the aluminum-based aerogels produced do not use toxic chemicals unlike conventional aerogel production. Aluminum powder, with poly(acrylic acid) and carboxymethyl cellulose as binders, is converted into aluminum-based aerogels using the freeze-drying method. The aluminum-based aerogels have low density (0.08–0.12 g/cm3) and high porosity (93.83–95.68%). The thermal conductivity of the aerogels obtained is very low (0.038–0.045 W/m·K), comparable to other types of aerogels and commercial heat insulation materials. Additionally, the aerogels can withstand temperatures up to 1000 °C with less than 40% decomposition. The aerogels exhibited promising oil absorption properties with their absorption capacity of 9.8 g/g and 0.784 g/cm3. The Young’s modulus of the aerogels ranged from 70.6 kPa to 330.2 kPa. This study suggests that aluminum-based aerogels have potential in thermal insulation and oil absorption applications.

Abstract Background Baby boomers are at increased risk for hepatitis C virus (HCV) infection and related cancer; therefore, one‐time HCV screening is recommended. Methods To assess prevalence of, and factors associated with providers ordering HCV screening, we examined a retrospective cohort of electronic medical records for patient visits from 01 August 2015 until 31 July 2017 in a large health system. HCV screening ordered was examined by patient age, gender, race/ethnicity, provider specialty, and number of clinical visits, stratified by birth cohort: born ≤1945, 1945‐1965 (baby boomers), 1966‐1985, and ≥1985. Multivariable regression identified factors independently associated with HCV screening ordered among average risk baby boomers. Results A total of 65 114 patients ages ≥18 years were evaluated. Among baby boomers HCV screening test order increased threefold between the two study years (4.0%‐12.9%). Odds of screening test ordered were significantly higher for non‐Hispanic Blacks (multivariable adjusted odds ratio [aOR]=1.36; 95% CI = 1.19‐1.55), males (aOR = 1.44; 95% CI = 1.33‐1.57), and having a clinic visit with a primary care provider alone or with specialty care (aOR = 3.25‐4.16). Medicare (aOR = 0.89; 95% CI = 0.80‐0.99), Medicaid (aOR 0.89; 95% CI 0.80‐0.99), and an unknown provider type (aOR = 0.16; 95% CI = 0.08‐0.33), were associated with lower odds of screening tests ordered. Conclusions While the proportion of baby boomers with an HCV screening test ordered increased during the study, the rate of screening remains far below national goals. Data from this study indicate that providers are not ordering HCV screening universally for all of their baby boomer patients. Continued efforts to increase HCV screening are needed to reduce the incidence of HCV‐related morbidity and mortality.

Cognitive abilities tend to decline over time in advanced age, yet some individuals experience stable abilities or rapid decline. Here the authors present a proteome-wide association study of cognitive trajectory, and identify 38 proteins associated with cognitive resilience.

Introduction: Considering the need for information regarding approaches to prevention and treatment of coronavirus disease 2019 (COVID-19), we sought to determine publication lag times of COVID-19-related original research articles published in top general medicine and emergency medicine (EM) journals. We further sought to characterize the types of COVID-19 publications within these journals. Methods: We reviewed 125 top-ranked general medicine journals and 20 top-ranked EM-specific journals for COVID-19-related publications. We abstracted article titles and manuscript details for each COVID-19-related article published between January 1–June 30, 2020, and categorized articles as one of the following: original research; case report; review; or commentary. We abstracted data for preprint publications over the same time period and determined whether articles from the general medicine and EM journals had been previously published as preprint articles. Our primary outcomes were the following: 1) lag time (days) between global cumulative World Health Organization (WHO)-confirmed cases of COVID-19 and publications; 2) lag times between preprint article publication and peer-reviewed journal publication; and 3) lag times between submission and publication in peer-reviewed journals. Our secondary outcome was to characterize COVID-19-related publications. Results: The first original research publications appeared in a general medicine journal 20 days and in an EM journal 58 days after the first WHO-confirmed case of COVID-19. We found median and mean lag times between preprint publications and journal publications of 32 days (19, 49) and 36 days (22) for general medicine journals, and 26 days (16, 36) and 25 days (13) for EM journals. Median and mean lag times between submission and publication were 30 days (19, 45) and 35 days (13) for general medicine journals, and 23 days (11, 39) and 27 days (19) for EM journals. Of 2530 general medicine journal articles and 351 EM journal articles, 28% and 23.6% were original research. We noted substantial closing of the preprint to peer-reviewed publication (160 days pre-pandemic) and peer-reviewed journal submission to publication (194 days pre-pandemic) lag times for COVID-19 manuscripts. Conclusion: We found a rapid and robust response with shortened publication lag times to meet the need for the publication of original research and other vital medical information related to COVID-19 during the first six months of 2020.

Neurofibrillary tangles composed of hyperphosphorylated tau and synaptic dysfunction are characteristics of Alzheimer’s disease (AD). However, the underlying molecular mechanisms remain poorly understood. Here, we identified Amphiphysin I mediates both tau phosphorylation and synaptic dysfunction in AD. Amphiphysin I is cleaved by a cysteine proteinase asparagine endopeptidase (AEP) at N278 in the brains of AD patients. The amount of AEP-generated N-terminal fragment of Amphiphysin I (1-278) is increased with aging. Amphiphysin I (1-278) inhibits clathrin-mediated endocytosis and induces synaptic dysfunction. Furthermore, Amphiphysin I (1-278) binds p35 and promotes its transition to p25, thus activates CDK5 and enhances tau hyperphosphorylation. Overexpression of Amphiphysin I (1-278) in the hippocampus of Tau P301S mice induces synaptic dysfunction, tau hyperphosphorylation, and cognitive deficits. However, overexpression of the N278A mutant Amphiphysin I, which resists the AEP-mediated cleavage, alleviates the pathological and behavioral defects. These findings suggest a mechanism of tau hyperphosphorylation and synaptic dysfunction in AD.

Microbiome data are undergoing exponential growth powered by rapid technological advancement. As the scope and depth of microbiome research increases, cross-disciplinary research is urgently needed for interpreting and harnessing the unprecedented data output. However, conventional research settings pose challenges to much-needed interdisciplinary research efforts due to barriers in scientific terminologies, methodology and research-culture. To breach these barriers, our University of South Florida OneHealth Codeathon was designed to be an interactive, hands-on event that solves real-world data problems. The format brought together students, postdocs, faculty, researchers, and clinicians in a uniquely cross-disciplinary, team-focused setting. Teams were formed to encourage equitable distribution of diverse domain-experts and proficient programmers, with beginners to experts on each team. To unify the intellectual framework, we set the focus on the topics of microbiome interactions at different scales from clinical to environmental sciences, leveraging local expertise in the fields of genetics, genomics, clinical data, and social and geospatial sciences. As a result, teams developed working methods and pipelines to face major challenges in current microbiome research, including data integration, experimental power calculations, geospatial mapping, and machine-learning classifiers. This broad, transdisciplinary and efficient workflow will be an example for future workshops to deliver useful data-science products.

Abstract Background Disease-associated-microglia (DAM) represent transcriptionally-distinct and neurodegeneration-specific microglial profiles with unclear significance in Alzheimer’s disease (AD). An understanding of heterogeneity within DAM and their key regulators may guide pre-clinical experimentation and drug discovery. Methods Weighted co-expression network analysis (WGCNA) was applied to existing microglial transcriptomic datasets from neuroinflammatory and neurodegenerative disease mouse models to identify modules of highly co-expressed genes. These modules were contrasted with known signatures of homeostatic microglia and DAM to reveal novel molecular heterogeneity within DAM. Flow cytometric validation studies were performed to confirm existence of distinct DAM sub-populations in AD mouse models predicted by WGCNA. Gene ontology analyses coupled with bioinformatics approaches revealed drug targets and transcriptional regulators of microglial modules predicted to favorably modulate neuroinflammation in AD. These guided in-vivo and in-vitro studies in mouse models of neuroinflammation and neurodegeneration (5xFAD) to determine whether inhibition of pro-inflammatory gene expression and promotion of amyloid clearance was feasible. We determined the human relevance of these findings by integrating our results with AD genome-wide association studies and human AD and non-disease post-mortem brain proteomes. Results WGCNA applied to microglial gene expression data revealed a transcriptomic framework of microglial activation that predicted distinct pro-inflammatory and anti-inflammatory phenotypes within DAM, which we confirmed in AD and aging models by flow cytometry. Pro-inflammatory DAM emerged earlier in mouse models of AD and were characterized by pro-inflammatory genes (Tlr2, Ptgs2, Il12b, Il1b), surface marker CD44, potassium channel Kv1.3 and regulators (NFkb, Stat1, RelA) while anti-inflammatory DAM expressed phagocytic genes (Igf1, Apoe, Myo1e), surface marker CXCR4 with distinct regulators (LXRα/β, Atf1). As neuro-immunomodulatory strategies, we validated LXRα/β agonism and Kv1.3 blockade by ShK-223 peptide that promoted anti-inflammatory DAM, inhibited pro-inflammatory DAM and augmented Aβ clearance in AD models. Human AD-risk genes were highly represented within homeostatic microglia suggesting causal roles for early microglial dysregulation in AD. Pro-inflammatory DAM proteins were positively associated with neuropathology and preceded cognitive decline confirming the therapeutic relevance of inhibiting pro-inflammatory DAM in AD. Conclusions We provide a predictive transcriptomic framework of microglial activation in neurodegeneration that can guide pre-clinical studies to characterize and therapeutically modulate neuroinflammation in AD.

Background: Basic and clinical scientific research at the University of South Florida (USF) have intersected to support a multi-faceted approach around a common focus on rare iron-related diseases. We proposed a modified version of the National Center for Biotechnology Information’s (NCBI) Hackathon-model to take full advantage of local expertise in building “Iron Hack”, a rare disease-focused hackathon. As the collaborative, problem-solving nature of hackathons tends to attract participants of highly-diverse backgrounds, organizers facilitated a symposium on rare iron-related diseases, specifically porphyrias and Friedreich’s ataxia, pitched at general audiences. Methods: The hackathon was structured to begin each day with presentations by expert clinicians, genetic counselors, researchers focused on molecular and cellular biology, public health/global health, genetics/genomics, computational biology, bioinformatics, biomolecular science, bioengineering, and computer science, as well as guest speakers from the American Porphyria Foundation (APF) and Friedreich’s Ataxia Research Alliance (FARA) to inform participants as to the human impact of these diseases. Results: As a result of this hackathon, we developed resources that are relevant not only to these specific disease-models, but also to other rare diseases and general bioinformatics problems. Within two and a half days, “Iron Hack” participants successfully built collaborative projects to visualize data, build databases, improve rare disease diagnosis, and study rare-disease inheritance. Conclusions: The purpose of this manuscript is to demonstrate the utility of a hackathon model to generate prototypes of generalizable tools for a given disease and train clinicians and data scientists to interact more effectively.

Abstract Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are neurodegenerative diseases with overlap in clinical presentation, neuropathology, and genetic underpinnings. The molecular basis for the overlap of these disorders is not well established. We performed a comparative unbiased mass spectrometry‐based proteomic analysis of frontal cortical tissues from postmortem cases clinically defined as ALS, FTD, ALS and FTD (ALS/FTD), and controls. We also included a subset of patients with the C9orf72 expansion mutation, the most common genetic cause of both ALS and FTD. Our systems‐level analysis of the brain proteome integrated both differential expression and co‐expression approaches to assess the relationship of these differences to clinical and pathological phenotypes. Weighted co‐expression network analysis revealed 15 modules of co‐expressed proteins, eight of which were significantly different across the ALS‐FTD disease spectrum. These included modules associated with RNA binding proteins, synaptic transmission, and inflammation with cell‐type specificity that showed correlation with TDP‐43 pathology and cognitive dysfunction. Modules were also examined for their overlap with TDP‐43 protein–protein interactions, revealing one module enriched with RNA‐binding proteins and other causal ALS genes that increased in FTD/ALS and FTD cases. A module enriched with astrocyte and microglia proteins was significantly increased in ALS cases carrying the C9orf72 mutation compared to sporadic ALS cases, suggesting that the genetic expansion is associated with inflammation in the brain even without clinical evidence of dementia. Together, these findings highlight the utility of integrative systems‐level proteomic approaches to resolve clinical phenotypes and genetic mechanisms underlying the ALS‐FTD disease spectrum in human brain.

The clinical management of metastatic melanoma requires predictors of the response to checkpoint blockade. Here, the authors use immunological assays to identify potential prognostic/predictive biomarkers in circulating blood cells and in tumor-infiltrating lymphocytes from patients with resected stage III melanoma.

Echo planar imaging (EPI), a fast magnetic resonance imaging technique, is a powerful tool in functional neuroimaging studies. However, susceptibility artifacts, which cause misinterpretations of brain functions, are unavoidable distortions in EPI. This paper proposes an end-to-end deep learning framework, named TS-Net, for susceptibility artifact correction (SAC) in a pair of 3D EPI images with reversed phase-encoding directions. The proposed TS-Net comprises a deep convolutional network to predict a displacement field in three dimensions to overcome the limitation of existing methods, which only estimate the displacement field along the dominant-distortion direction. In the training phase, anatomical T1-weighted images are leveraged to regularize the correction, but they are not required during the inference phase to make TS-Net more flexible for general use. The experimental results show that TS-Net achieves favorable accuracy and speed trade-off when compared with the state-of-the-art SAC methods, i.e., TOPUP, TISAC, and S-Net. The fast inference speed (less than a second) of TS-Net makes real-time SAC during EPI image acquisition feasible and accelerates the medical image-processing pipelines.

GPRC5A is a retinoic acid inducible gene that is preferentially expressed in lung tissue. Here the authors report that GPRC5A suppresses the translation of EGFR by interfering with the eIF4F complex assembly, thereby limiting lung tumorigenesis, particularly radiation-induced lung tumorigenesis.