The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling.

Force fields are a key component of physics-based molecular modeling, describing the energies and forces in a molecular system as a function of the positions of the atoms and molecules involved. Here, we provide a review and scientific status report on the work of the Open Force Field (OpenFF) Initiative, which focuses on the science, infrastructure and data required to build the next generation of biomolecular force fields. We introduce the OpenFF Initiative and the related OpenFF Consortium, describe its approach to force field development and software, and discuss accomplishments to date as well as future plans. OpenFF releases both software and data under open and permissive licensing agreements to enable rapid application, validation, extension, and modification of its force fields and software tools. We discuss lessons learned to date in this new approach to force field development. We also highlight ways that other force field researchers can get involved, as well as some recent successes of outside researchers taking advantage of OpenFF tools and data.

MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease.

Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledgebase containing manually curated summary statistics from 98 published tables in 38 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels-at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD. Database URL: https://miami-ad.org/.

High-resolution reconstruction of April-September precipitation and major extreme droughts in China over the past ∼530 years.

Extreme drought events have increased, causing serious losses and damage to the social economy under current warming conditions. However, short-term meteorological data limit our understanding and projection of these extremes. With the accumulation of proxy data, especially tree-ring data, large-scale precipitation field reconstruction has provided opportunities to explore underlying mechanisms further. Using point-by-point regression, we reconstructed the April-September precipitation field in China for the past ∼530 years on the basis of 590 proxy records, including 470 tree-ring width chronologies and 120 drought/flood indices. Our regression models explained average 50% of the variance in precipitation. In the statistical test on calibration and verification, our models passed the significance level that assured reconstruction quality. The reconstruction data performed well, showing consistency and better quality than previously reported reconstructions. The first three leading modes of variability in the reconstruction revealed the main distribution modes of precipitation over China. Wet/drought and extremely wet/drought years accounted for 12.81%/10.92% (68 years/58 years) and 1.69%/3.20% (9 years/17 years) of the past ∼530 years in China, respectively. Major extreme drought events can be identified explicitly in our reconstruction. The detailed features of the Chongzhen Great Drought (1637-1643), the Wanli Great Drought (1585-1590), and the Ding-Wu Great Famine (1874-1879), indicated the existence of potentially different underlying mechanisms that need further exploration. Although further improvements can be made for remote uninhabited areas and large deserts, our gridded reconstruction of April-September precipitation in China over the past ∼530 years can provide a solid database for studies on the attribution of climate change and the mechanism of extreme drought events.

ACR Appropriateness Criteria® Dizziness and Ataxia: 2023 Update.

Diagnostic evaluation of a patient with dizziness or vertigo is complicated by a lack of standardized nomenclature, significant overlap in symptom descriptions, and the subjective nature of the patient's symptoms. Although dizziness is an imprecise term often used by patients to describe a feeling of being off-balance, in many cases dizziness can be subcategorized based on symptomatology as vertigo (false sense of motion or spinning), disequilibrium (imbalance with gait instability), presyncope (nearly fainting or blacking out), or lightheadedness (nonspecific). As such, current diagnostic paradigms focus on timing, triggers, and associated symptoms rather than subjective descriptions of dizziness type. Regardless, these factors complicate the selection of appropriate diagnostic imaging in patients presenting with dizziness or vertigo. This document serves to aid providers in this selection by using a framework of definable clinical variants. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

ACR Appropriateness Criteria® Cerebrovascular Diseases-Stroke and Stroke-Related Conditions.

Cerebrovascular disease encompasses a vast array of conditions. The imaging recommendations for stroke-related conditions involving noninflammatory steno-occlusive arterial and venous cerebrovascular disease including carotid stenosis, carotid dissection, intracranial large vessel occlusion, and cerebral venous sinus thrombosis are encompassed by this document. Additional imaging recommendations regarding complications of these conditions including intraparenchymal hemorrhage and completed ischemic strokes are also discussed. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Systematic Studies on the Anti-SARS-CoV-2 Mechanisms of Tea Polyphenol-Related Natural Products.

The causative pathogen of COVID-19, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), utilizes the receptor-binding domain (RBD) of the spike protein to bind to human receptor angiotensin-converting enzyme 2 (ACE2). Further cleavage of spike by human proteases furin, TMPRSS2, and/or cathepsin L facilitates viral entry into the host cells for replication, where the maturation of polyproteins by 3C-like protease (3CLpro) and papain-like protease (PLpro) yields functional nonstructural proteins (NSPs) such as RNA-dependent RNA polymerase (RdRp) to synthesize mRNA of structural proteins. By testing the tea polyphenol-related natural products through various assays, we found that the active antivirals prevented SARS-CoV-2 entry by blocking the RBD/ACE2 interaction and inhibiting the relevant human proteases, although some also inhibited the viral enzymes essential for replication. Due to their multitargeting properties, these compounds were often misinterpreted for their antiviral mechanisms. In this study, we provide a systematic protocol to check and clarify their anti-SARS-CoV-2 mechanisms, which should be applicable for all of the antivirals.

Cep57 regulates human centrosomes through multivalent interactions.

Human Cep57 is a coiled-coil scaffold at the pericentriolar matrix (PCM), controlling centriole duplication and centrosome maturation for faithful cell division. Genetic truncation mutations of Cep57 are associated with the mosaic-variegated aneuploidy (MVA) syndrome. During interphase, Cep57 forms a complex with Cep63 and Cep152, serving as regulators for centrosome maturation. However, the molecular interplay of Cep57 with these essential scaffolding proteins remains unclear. Here, we demonstrate that Cep57 undergoes liquid-liquid phase separation (LLPS) driven by three critical domains (NTD, CTD, and polybasic LMN). In vitro Cep57 condensates catalyze microtubule nucleation via the LMN motif-mediated tubulin concentration. In cells, the LMN motif is required for centrosomal microtubule aster formation. Moreover, Cep63 restricts Cep57 assembly, expansion, and microtubule polymerization activity. Overexpression of competitive constructs for multivalent interactions, including an MVA mutation, leads to excessive centrosome duplication. In Cep57-depleted cells, self-assembly mutants failed to rescue centriole disengagement and PCM disorganization. Thus, Cep57's multivalent interactions are pivotal for maintaining the accurate structural and functional integrity of human centrosomes.

Exploring heterogeneity and dynamics of meteorological influences on US PM2.5: A distributed learning approach with spatiotemporal varying coefficient models.

Particulate matter (PM) has emerged as a primary air quality concern due to its substantial impact on human health. Many recent research works suggest that PM2.5 concentrations depend on meteorological conditions. Enhancing current pollution control strategies necessitates a more holistic comprehension of PM2.5 dynamics and the precise quantification of spatiotemporal heterogeneity in the relationship between meteorological factors and PM2.5 levels. The spatiotemporal varying coefficient model stands as a prominent spatial regression technique adept at addressing this heterogeneity. Amidst the challenges posed by the substantial scale of modern spatiotemporal datasets, we propose a pioneering distributed estimation method (DEM) founded on multivariate spline smoothing across a domain's triangulation. This DEM algorithm ensures an easily implementable, highly scalable, and communication-efficient strategy, demonstrating almost linear speedup potential. We validate the effectiveness of our proposed DEM through extensive simulation studies, demonstrating that it achieves coefficient estimations akin to those of global estimators derived from complete datasets. Applying the proposed model and method to the US daily PM2.5 and meteorological data, we investigate the influence of meteorological variables on PM2.5 concentrations, revealing both spatial and seasonal variations in this relationship.

Health literacy of patients eligible for cochlear implants.

BACKGROUND: Hearing loss is known to be an independent risk factor for inadequate health literacy. The objective of this study was to assess the level of health literacy among patients undergoing cochlear implantation to determine areas for improvement in delivery of patient information. METHODS: A cross-sectional survey was conducted at the otology-neurotology clinic at Sunnybrook Health Sciences Centre. Patients eligible for cochlear implantation completed two health literacy screening tools: The Short Test of Functional Health Literacy in Adults (S-TOFHLA) and Brief Health Literacy Screen (BHLS). RESULTS: Thirty seven patients were included (41% female, 59% male, mean age: 55 years). Most patients had adequate health literacy through BHLS (76%) and S-TOFHLA (98%) scoring. Over 80% of patients were not able to correctly recount all the operative risks associated with cochlear implant surgery and one third of patients did not correctly recount any risks associated with a cochlear implant surgery. Female sex was associated with higher scores (p=0.03) and low income (<$35,000) was associated with lower scores (p=0.05). CONCLUSION: Patients eligible for cochlear implants have adequate health literacy, but most are not able to recount operative risks. Educational tools are required to improve patient retention, understand, and perioperative health information delivery.

EspalomaCharge: Machine Learning-Enabled Ultrafast Partial Charge Assignment.

Atomic partial charges are crucial parameters in molecular dynamics simulation, dictating the electrostatic contributions to intermolecular energies and thereby the potential energy landscape. Traditionally, the assignment of partial charges has relied on surrogates of ab initio semiempirical quantum chemical methods such as AM1-BCC and is expensive for large systems or large numbers of molecules. We propose a hybrid physical/graph neural network-based approximation to the widely popular AM1-BCC charge model that is orders of magnitude faster while maintaining accuracy comparable to differences in AM1-BCC implementations. Our hybrid approach couples a graph neural network to a streamlined charge equilibration approach in order to predict molecule-specific atomic electronegativity and hardness parameters, followed by analytical determination of optimal charge-equilibrated parameters that preserve total molecular charge. This hybrid approach scales linearly with the number of atoms, enabling for the first time the use of fully consistent charge models for small molecules and biopolymers for the construction of next-generation self-consistent biomolecular force fields. Implemented in the free and open source package EspalomaCharge, this approach provides drop-in replacements for both AmberTools antechamber and the Open Force Field Toolkit charging workflows, in addition to stand-alone charge generation interfaces. Source code is available at https://github.com/choderalab/espaloma-charge.

Challenges of COVID-19 Case Forecasting in the US, 2020-2021.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

The landscape of regional missense mutational intolerance quantified from 125,748 exomes.

Missense variants can have a range of functional impacts depending on factors such as the specific amino acid substitution and location within the gene. To interpret their deleteriousness, studies have sought to identify regions within genes that are specifically intolerant of missense variation 1-12 . Here, we leverage the patterns of rare missense variation in 125,748 individuals in the Genome Aggregation Database (gnomAD) 13 against a null mutational model to identify transcripts that display regional differences in missense constraint. Missense-depleted regions are enriched for ClinVar 14 pathogenic variants, de novo missense variants from individuals with neurodevelopmental disorders (NDDs) 15,16 , and complex trait heritability. Following ClinGen calibration recommendations for the ACMG/AMP guidelines, we establish that regions with less than 20% of their expected missense variation achieve moderate support for pathogenicity. We create a missense deleteriousness metric (MPC) that incorporates regional constraint and outperforms other deleteriousness scores at stratifying case and control de novo missense variation, with a strong enrichment in NDDs. These results provide additional tools to aid in missense variant interpretation.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays.

DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer's Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.

SERBP1 interacts with PARP1 and is present in PARylation-dependent protein complexes regulating splicing, cell division, and ribosome biogenesis.

RNA binding proteins (RBPs) containing intrinsically disordered regions (IDRs) are present in diverse molecular complexes where they function as dynamic regulators. Their characteristics promote liquid-liquid phase separation (LLPS) and the formation of membraneless organelles such as stress granules and nucleoli. IDR-RBPs are particularly relevant in the nervous system and their dysfunction is associated with neurodegenerative diseases and brain tumor development. SERBP1 is a unique member of this group, being mostly disordered and lacking canonical RNA-binding domains. Using a proteomics approach followed by functional analysis, we defined SERBP1's interactome. We uncovered novel SERBP1 roles in splicing, cell division, and ribosomal biogenesis and showed its participation in pathological stress granules and Tau aggregates in Alzheimer's disease brains. SERBP1 preferentially interacts with other G-quadruplex (G4) binders, implicated in different stages of gene expression, suggesting that G4 binding is a critical component of SERBP1 function in different settings. Similarly, we identified important associations between SERBP1 and PARP1/polyADP-ribosylation (PARylation). SERBP1 interacts with PARP1 and its associated factors and influences PARylation. Moreover, protein complexes in which SERBP1 participates contain mostly PARylated proteins and PAR binders. Based on these results, we propose a feedback regulatory model in which SERBP1 influences PARP1 function and PARylation, while PARylation modulates SERBP1 functions and participation in regulatory complexes.

Development of a Novel Endometrial Signature Based on Endometrial microRNA for Determining the Optimal Timing for Embryo Transfer.

Though tremendous advances have been made in the field of in vitro fertilization (IVF), a portion of patients are still affected by embryo implantation failure issues. One of the most significant factors contributing to implantation failure is a uterine condition called displaced window of implantation (WOI), which refers to an unsynchronized endometrium and embryo transfer time for IVF patients. Previous studies have shown that microRNAs (miRNAs) can be important biomarkers in the reproductive process. In this study, we aim to develop a miRNA-based classifier to identify the WOI for optimal time for embryo transfer. A reproductive-related PanelChip® was used to obtain the miRNA expression profiles from the 200 patients who underwent IVF treatment. In total, 143 out of the 167 miRNAs with amplification signals across 90% of the expression profiles were utilized to build a miRNA-based classifier. The microRNA-based classifier identified the optimal timing for embryo transfer with an accuracy of 93.9%, a sensitivity of 85.3%, and a specificity of 92.4% in the training set, and an accuracy of 88.5% in the testing set, showing high promise in accurately identifying the WOI for the optimal timing for embryo transfer.

The Mediating Role of Cortical Atrophy on the Relationship between the Resilience Index and Cognitive Function: Findings from the Healthy Brain Initiative.

Background: Lifestyle factors are linked to differences in brain aging and risk for Alzheimer's disease, underscored by concepts like 'cognitive reserve' and 'brain maintenance'. The Resilience Index (RI), a composite of 6 factors (cognitive reserve, physical and cognitive activities, social engagement, diet, and mindfulness) provides such a holistic measure. Objective: This study aims to examine the association of RI scores with cognitive function and assess the mediating role of cortical atrophy. Methods: Baseline data from 113 participants (aged 45+, 68% female) from the Healthy Brain Initiative were included. Life course resilience was estimated with the RI, cognitive performance with Cognivue®, and brain health using a machine learning derived Cortical Atrophy Score (CAS). Mediation analysis probed the relationship between RI, cognitive outcomes, and cortical atrophy. Results: In age and sex adjusted models, the RI was significantly associated with CAS (ß= -0.25, p = 0.006) and Cognivue® scores (ß= 0.32, p < 0.001). The RI-Cognivue® association was partially mediated by CAS (ß= 0.07; 95% CI [0.02, 0.14]). Conclusions: Findings revealed that the collective effect of early and late-life lifestyle resilience factors on cognition are partially explained by their association with less brain atrophy. These findings underscore the value of comprehensive lifestyle assessments in understanding the risk and progression of cognitive decline and Alzheimer's disease in an aging population.

Enhancing Chemotherapy Response Prediction via Matched Colorectal Tumor-Organoid Gene Expression Analysis and Network-Based Biomarker Selection.

Colorectal cancer (CRC) poses significant challenges in chemotherapy response prediction due to its molecular heterogeneity. This study introduces an innovative methodology that leverages gene expression data generated from matched colorectal tumor and organoid samples to enhance prediction accuracy. By applying Consensus Weighted Gene Co-expression Network Analysis (WGCNA) across multiple datasets, we identify critical gene modules and hub genes that correlate with patient responses, particularly to 5-fluorouracil (5-FU). This integrative approach advances precision medicine by refining chemotherapy regimen selection based on individual tumor profiles. Our predictive model demonstrates superior accuracy over traditional methods on independent datasets, illustrating significant potential in addressing the complexities of high-dimensional genomic data for cancer biomarker research.

Neutrophils bearing adhesive polymer micropatches as a drug-free cancer immunotherapy.

Tumour-associated neutrophils can exert antitumour effects but can also assume a pro-tumoural phenotype in the immunosuppressive tumour microenvironment. Here we show that neutrophils can be polarized towards the antitumour phenotype by discoidal polymer micrometric 'patches' that adhere to the neutrophils' surfaces without being internalized. Intravenously administered micropatch-loaded neutrophils accumulated in the spleen and in tumour-draining lymph nodes, and activated splenic natural killer cells and T cells, increasing the accumulation of dendritic cells and natural killer cells. In mice bearing subcutaneous B16F10 tumours or orthotopic 4T1 tumours, intravenous injection of the micropatch-loaded neutrophils led to robust systemic immune responses, a reduction in tumour burden and improvements in survival rates. Micropatch-activated neutrophils combined with the checkpoint inhibitor anti-cytotoxic T-lymphocyte-associated protein 4 resulted in strong inhibition of the growth of B16F10 tumours, and in complete tumour regression in one-third of the treated mice. Micropatch-loaded neutrophils could provide a potent, scalable and drug-free approach for neutrophil-based cancer immunotherapy.

Heterozygous loss-of-function SMC3 variants are associated with variable growth and developmental features.

Heterozygous missense variants and in-frame indels in SMC3 are a cause of Cornelia de Lange syndrome (CdLS), marked by intellectual disability, growth deficiency, and dysmorphism, via an apparent dominant-negative mechanism. However, the spectrum of manifestations associated with SMC3 loss-of-function variants has not been reported, leading to hypotheses of alternative phenotypes or even developmental lethality. We used matchmaking servers, patient registries, and other resources to identify individuals with heterozygous, predicted loss-of-function (pLoF) variants in SMC3, and analyzed population databases to characterize mutational intolerance in this gene. Here, we show that SMC3 behaves as an archetypal haploinsufficient gene: it is highly constrained against pLoF variants, strongly depleted for missense variants, and pLoF variants are associated with a range of developmental phenotypes. Among 14 individuals with SMC3 pLoF variants, phenotypes were variable but coalesced on low growth parameters, developmental delay/intellectual disability, and dysmorphism, reminiscent of atypical CdLS. Comparisons to individuals with SMC3 missense/in-frame indel variants demonstrated an overall milder presentation in pLoF carriers. Furthermore, several individuals harboring pLoF variants in SMC3 were nonpenetrant for growth, developmental, and/or dysmorphic features, and some had alternative symptomatologies with rational biological links to SMC3. Analyses of tumor and model system transcriptomic data and epigenetic data in a subset of cases suggest that SMC3 pLoF variants reduce SMC3 expression but do not strongly support clustering with functional genomic signatures of typical CdLS. Our finding of substantial population-scale LoF intolerance in concert with variable growth and developmental features in subjects with SMC3 pLoF variants expands the scope of cohesinopathies, informs on their allelic architecture, and suggests the existence of additional clearly LoF-constrained genes whose disease links will be confirmed only by multilayered genomic data paired with careful phenotyping.