bluuebunny/crossref_metadata_2025_split huggingface dataset:
EpiPAMPAS: Rapid detection of intra-protein epistasis via parsimonious ancestral state reconstruction and counting mutations
Authors: Dabbaghie Fawaz , Thedinga Kristina , Bazykin Georgii A , Marschall Tobias , Kalinina Olga 
Published: December 2024

MotivationAn epistatic interaction is a non-linear combination of effects of individual mutations on fitness. This type of interaction is a known driver for evolution, as they alter the organism’s fitness and adaptability. In this work we introduce EpiPAMPAS, a statistical method that is based on multiple sequence alignments (MSA) and detecting mutations in the same direction on a dendrogram instead of a phylogenetic tree using the Sankoff algorithm.ResultsWe tested EpiPAMPAS on both simulated and real sequencing data. On the simulated data, our method was able to detect the simulated epistatic pairs with very low p-value. In a real-world application, we tested the influenza proteins N1, N2, H1, H3 and HIV-1 envelope protein subtypes A, B and C. We observe that EpiPAMPAS detects fewer interacting pairs than comparable statistical approaches, although the overlap between detected positions is good. Moreover, some of the amino acids from the detected pairs are known to be deleterious for viral fitness.AvailabilityEpiPAMPAS is available under MIT license athttps://github.com/kalininalab/EpiPAMPAS
Comparative mapping of single-cell transcriptomic landscapes in neurodegenerative diseases
Authors: Shwab E. Keats , Man Zhaohui , Gingerich Daniel C. , Gamache Julia , Garrett Melanie E. , Serrano Geidy E. , Beach Thomas G. , Crawford Gregory E. , Ashley-Koch Allison E. , Chiba-Falek Ornit 
Published: December 2024

ABSTRACTINTRODUCTIONAlzheimer’s disease (AD), Dementia with Lewy bodies (DLB), and Parkinson’s disease (PD) represent a spectrum of neurodegenerative disorders (NDDs). Here, we performed the first direct comparison of their transcriptomic landscapes.METHODSWe profiled the whole transcriptomes of NDD cortical tissue by snRNA-seq. We used computational analyses to identify common and distinct differentially expressed genes (DEGs), biological pathways, vulnerable and disease-driver cell subtypes, and alteration in cell-to-cell interactions.RESULTSThe same vulnerable inhibitory neuron subtype was depleted in both AD and DLB. Potentially disease-driving neuronal cell subtypes were present in both PD and DLB. Cell-cell communication was predicted to be increased in AD but decreased in DLB and PD. DEGs were most commonly shared across NDDs within inhibitory neuron subtypes. Overall, we observed the greatest transcriptomic divergence between AD and PD, while DLB exhibited an intermediate transcriptomic signature.DISCUSSIONThese results help explain the clinicopathological spectrum of this group of NDDs and provide unique insights into the shared and distinct molecular mechanisms underlying the pathogenesis of NDDs.
Hepatic Inactivation of Carnitine Palmitoyltransferase 1a Lowers Apolipoprotein B Containing Lipoproteins in Mice
Authors: Helsley Robert N. , Zelows Mikala M. , Noffsinger Victoria P. , Anspach Garrett B. , Dharanipragada Nikitha , Mead Anna E. , Cobo Isidoro , Carter Abigail , Wu Qinglin , Shalaurova Irina , Saito Kai , Morganti Josh M. , Gordon Scott M. , Graf Gregory A. 
Published: December 2024

SUMMARYGenome- and epigenome-wide association studies have associated variants and methylation status of carnitine palmitoyltransferase 1a (CPT1a) to reductions in very low-density lipoprotein (VLDL) cholesterol and triglyceride levels. We report significant associations between the presence ofCPT1aSNPs and reductions in plasma cholesterol, as well as positive associations between hepatic Cpt1a expression and plasma cholesterol levels across inbred mouse strains. Mechanistic studies show that both wild type and human apolipoprotein B100 (apoB)-transgenic mice with liver-specific deletion ofCpt1a(LKO) display lower circulating apoB levels consistent with reduced LDL-cholesterol (LDL-C) and LDL particle number. Despite a reduction in steady-state plasma lipids, VLDL-triglyceride (VLDL-TG) and cholesterol (VLDL-C) secretion rates are increased, suggesting accelerated clearance of apoB-containing lipoproteins (apoB-LPs) in LKO mice. Mechanistic approaches show greater peroxisome proliferator activated receptor α (PPARα) signaling which favors enhanced lipoprotein lipase-mediated metabolism of apoB-LPs, including increases in ApoCII and ApoAIV and reductions in ApoCIII & Angptl3. These studies provide mechanistic insight linking genetic variants and methylation status ofCPT1ato reductions in circulating apoB-LPs in humans.HIGHLIGHTSLoss-of-function SNPs inCPT1aassociate with reductions in plasma cholesterol in humansHepatic Cpt1a expression positively associates with plasma cholesterol levels across inbred strains of miceLiver-specific Cpt1a deficiency lowers circulating apoB, plasma cholesterol, LDL-C, and LDL particle numberCpt1a ablation activates PPARα and favors clearance of apoB-containing lipoproteins
Headwaters to Valley: Water quality in rivers transitioning from forest to agricultural bottomland
Authors: Neufeld Doug Graber , Alderfer Isaac , Bauman Zachary , Buckwalter Micah 
Published: December 2024

AbstractMany waterways flow out of forestlands, which tend to maintain higher water quality, into agricultural lands, which tend to degrade water quality. The roles of these two types of land cover in impacting key water quality parameters (phosphorus as orthophosphate, nitrogen as nitrate, total suspended sediment (TSS), and indicator bacteria) were investigated for the watershed of the North and South Fork of the Shenandoah River, Virginia. This area has a particularly sharp boundary between heavily forested and heavily agricultural regions. Two datasets were analyzed: 1) a large number of datapoints spanning a 20-year range in the Water Quality Portal (WQP) database, and 2) transects along three representative rivers systems over the span of a 4-year period. Overall nutrient levels were significantly better in forested regions than agricultural regions; while TSS and indicator bacteria showed some trends, but less consistently, of higher water quality in forested regions. All parameters had significant variation in both forested and agricultural areas. Transects showed that waterways flowing out of forestland maintained higher water quality for approximately the first 8 km in agricultural land. Both transect and WQP data indicated higher water quality when the percent of forested land cover in a drainage basin was about 70-80%. Thus, forestland does mitigate the impacts of agriculture on water quality to some degree, but this effect rapidly diminishes as forest cover of the watershed lessens. Furthermore, forests themselves have degraded water quality at certain times and places; for instance, nutrients level were in the medium to high stress level for aquatic life in approximately 15% of samples. This study illustrates general trends of land cover effects on water quality, while also highlighting both site-specific variability, and the dynamics of water quality as water flows out of forested areas into agricultural areas.
Restoring Oscillatory Dynamics in Alzheimer’s Disease: A Laminar Whole-Brain Model of Serotonergic Psychedelic Effects
Authors: Gendra Jan C. , Lopez-Sola Edmundo , Castaldo Francesca , Lleal-Custey Èlia , Sanchez-Todo Roser , Vohryzek Jakub , Salvador Ricardo , Andrzejak Ralph G. , Ruffini Giulio ,   Alzheimer’s Disease Neuroimaging Initiative
Published: December 2024

AbstractClassical serotonergic psychedelics show promise in addressing neurodegenerative disorders such as Alzheimer’s disease by modulating pathological brain dynamics. However, the precise neurobiological mechanisms underlying their effects remain elusive. This study introduces a personalized whole-brain model built upon a laminar neural mass framework to elucidate these effects. Using multimodal neuroimaging data from thirty subjects diagnosed with Alzheimer’s disease, we simulate the impact of serotonin 2A receptor activation, characteristic of psychedelics, on cortical dynamics. By modulating the excitability of layer 5 pyramidal neurons, our models reproduce hallmark changes in EEG power spectra observed under psychedelics, including alpha power suppression and gamma power enhancement. These spectral shifts are shown to correlate strongly with the regional distribution of serotonin 2A receptors. Furthermore, simulated EEG reveals increased complexity and entropy, suggesting restored network function. These findings underscore the potential of serotonergic psychedelics to reestablish healthy oscillatory dynamics in the prodromal and early phases of Alzheimer’s disease and offer mechanistic insights into their potential therapeutic effects in neurodegenerative disorders.
Evaluating Enhanced LLMs for Precise Mental Health Diagnosis from Clinical Notes
Authors: Boggavarapu Lokesh , Srivastava Vineet , Varanasi Amit Maheswar , Lu Yingda , Bhaumik Runa 
Published: December 2024

AbstractAnxiety, depression, and other mental health conditions are affecting millions of people worldwide each year. However, limited access to mental health professionals and the stigma surrounding mental illness often deter individuals from seeking help. Many areas, especially rural and underserved communities, face a significant shortage of mental health professionals, making it difficult for individuals to access timely support and treatment. Traditional therapy can be expensive, time-consuming, and intimidating, discouraging individuals from seeking care and delaying essential treatment. The goal of this project is to harness the power of large language modelsIn the medical domain, large language models (LLMs) have the potential to significantly enhance clinical practice by assisting with tasks such as diagnostic support, therapeutic interventions, and summarization. However, these models often generate inaccurate responses, or “hallucinations,” when faced with queries they cannot effectively handle, raising concerns in the medical community. To address the limitations of LLMs, Retrieval-Augmented Generation (RAG) was leveraged to enhance their performance. By integrating external knowledge sources such as ICD-10-CM guidelines and psychiatric diagnostic manuals, RAG enables LLMs to retrieve relevant information in real time to support their predictions. This study examines whether LLMs can understand and accurately predict mental health-related medical codes from clinical notes. These codes are crucial for clinical documentation and treatment planning. We tested several LLMs (e.g., GPT, LLaMA, Gemini-Pro) enhanced with reliable resources like ICD-10-CM guidelines to evaluate their ability to identify and understand mental health terms and ICD-10-CM codes in psychiatric clinical notes. Our findings reveal that current models lack a robust understanding of the meaning and nuances of these codes, limiting their reliability for mental health applications. This underscores the need for improved strategies to represent and integrate these complex alphanumeric codes within LLMs. Enhancing their capability to accurately process mental health terminologies would make LLMs more reliable and trustworthy tools for mental health professionals, ultimately supporting better care and outcomes for patients.
An atypical phenotype is a risk factor for higher mortality in Alzheimer’s disease
Authors: Bader Ilse , Groot Colin , van der Flier Wiesje M. , Pijnenburg Yolande A.L. , Ossenkoppele Rik 
Published: December 2024

ABSTRACTBackgroundSurvival estimates for individuals with Alzheimer’s disease (AD) are informative to understand the full disease trajectory, but precise estimates for atypical AD variants are scarce. Atypical AD variants are characterized by non-amnestic phenotypes, an early-onset and lower prevalence ofAPOEε4-carriership, which are all possible modulators of clinical trajectories. We aimed to provide survival estimates for posterior cortical atrophy (PCA; “visual-AD”), logopenic variant primary progressive aphasia (lvPPA; “language-AD”) and behavioral-AD (bvAD), and to evaluate the effect of phenotypical atypicality beyond known mortality-determinants.MethodsThis observational study included 2081 amyloid-positive patients (age 65±8 years) from the Amsterdam Dementia Cohort classified as typical AD (n=1801) or atypical AD (n=280; PCA [n=112], lvPPA [n=86], and bvAD [n=82]). Survival estimates from first-visit (∼time-of-diagnosis) to death/censoring (Central Public Administration) were determined (Kaplan-Meier analysis) and compared (Log-Rank tests) across diagnostic groups. To assess effects of atypical AD on mortality, cox proportional-hazard models were performed including age, sex, education, MMSE-score andAPOEε4-carriership (model-1), followed by adding the atypical AD group (model-2) or atypical AD variants individually (model-3), while using typical AD as reference. A likelihood ratio test was performed between model-1 and 2 to assess whether atypical AD improved the model-fit.ResultsThe estimated median survival time for atypical AD of 6.3 years (95%CI: [5.8-6.9]) was shorter than for typical AD (7.2[7.0-7.5], p=0.02). Median survival times across the atypical AD variants were consistently shorter (PCA: 6.3[5.5-7.3], p=0.055); lvPPA: 6.6[5.7-7.7], p=0.110; bvAD: 6.3[5.0-9.1], p=0.121, 48% deceased). In cox proportional-hazards model-1, male sex (HR=1.46[1.30-1.64], p<0.001), age (HR=1.02[1.01-1.03], p<0.001), and MMSE (HR=0.94[0.93-0.96], p<0.001) were associated with increased mortality risk.APOEε4heterozygosity was associated with reduced mortality risk compared to non-carriers (HR=0.85[0.74-0.97], p=0.015). In model-2, atypical AD improved the model fit (model 2; χ²=8.88, p=0.003) and was associated with 31% increased mortality risk compared to typical AD (HR=1.31[1.10-1.56], p=0.002). In model-3, contributions of the variants were: HRPCA=1.35[1.05-1.73], p=0.019; HRlvPPA=1.27[0.94-1.69], p=0.114; HRbvAD=1.31[0.94-1.83], p=0.105].ConclusionsSurvival in atypical AD was shorter compared to typical AD. Atypicality appears an important risk factor for mortality beyond age, sex, education,APOEε4-carriership and disease severity.Trial registration informationNA.
Parkinson’s Disease Pathogenic Variants: Cross-Ancestry Analysis and Microarray Data Validation
Authors: Hong Samantha , Koretsky Mathew J. , Lichtenberg Jens , Leonard Hampton , Pitz Vanessa ,   the Global Parkinson’s Genetics Program (GP2)
Published: December 2024

ABSTRACTBackgroundKnown pathogenic variants in Parkinson’s disease (PD) contribute to disease development but have yet to be fully explored by arrays at scale.ObjectivesThis study evaluated genotyping success of the NeuroBooster array (NBA) and determined the frequencies of pathogenic variants across ancestries.MethodWe analyzed the presence and allele frequency of 34 pathogenic variants in 28,710 PD cases, 9,614 other neurodegenerative disorder cases, and 15,821 controls across 11 ancestries within the Global Parkinson’s Genetics Program dataset. Of these, 25 were genotyped on NBA and cluster plots were used to assess their quality.ResultsGenes previously predicted to have high or very high confidence of causing PD tend to have more pathogenic variants and are present across ancestry groups. Twenty-five of the 34 pathogenic variants were typed by the NBA array and classified “good” (n=12), “medium” (n=4), and “bad” (n=9) variants.ConclusionOur results confirm the likelihood that established PD genes are pathogenic and highlight the importance of ancestrally diverse research in PD. We also show the usefulness of the NBA as a reliable tool for genotyping of rare variants for PD.
Representation learning based on proteomic profiles uncovers key cell types and biological processes contributing to the plasma proteome
Authors: Zhuang Jiali , Smith Erin N. , Diogo Dorothée 
Published: December 2024

AbstractThe plasma proteome is a potential source of information on health status and physiological condition and holds great potential as candidate biomarkers for diagnosis, prognosis, intervention response monitoring, and patient stratification. As proteins in the plasma can be derived from numerous cellular and tissue sources, and their levels influenced by diverse mechanisms, a comprehensive assessment of patterns of protein variation could provide insight into mechanisms driving health and disease. By applying neural network-based representation learning and unsupervised clustering to the plasma proteomic profiles of 51,180 participants in the UK biobank, we identified 36 protein modules representing major cell types and biological processes present in the plasma proteome. We discovered that the overall abundances of proteins belonging to certain modules are associated with disease status and genetic variants. Those associations reflect complex and multi-faceted mechanisms that regulate protein abundances in circulation. An investigation into the protein modules associated with disease variants uncovered both known disease biology and novel findings that may translate into testable hypotheses. Our approach generates biologically relevant groupings of plasma proteins that can be deployed to inform the design of more predictive biomarker panels and shed new light on the effects of disease-associated genetic variants.
Gene-by-environment interactions involving maternal exposures with orofacial cleft risk in Filipinos
Authors: Erdogan-Yildirim Zeynep , Carlson Jenna C. , Mukhopadhyay Nandita , Leslie Elizabeth J. , Padilla Carmencita , Murray Jeffrey C. , Beaty Terri H. , Weinberg Seth M. , Marazita Mary L. , Shaffer John R. 
Published: December 2024

AbstractMaternal exposures are known to influence the risk of isolated cleft lip with or without cleft palate (CL/P) – a common and highly heritable birth defect with a multifactorial etiology. To identify new CL/P risk loci, we conducted a genome-wide gene-environment interaction (GEI) analysis of CL/P on a sample of 540 cases and 260 controls recruited from the Philippines, incorporating the interaction effects of genetic variants with maternal smoking and vitamin use. As GEI analyses are typically low in power and the results can be difficult to interpret, we used multiple testing frameworks to evaluate potential GEI effects: 1 degree-of-freedom (1df) GxE test, the 3df joint test, and the two-step EDGE approach. While we did not detect any genome-wide significant interactions, we detected 12 suggestive GEI with smoking and 25 suggestive GEI with vitamin use between all testing frameworks. Several of these loci showed biological plausibility. Notable interactions with smoking include loci nearFEZF1,TWIST2,andNET1.WhileFEZF1is involved in early neuronal development,TWIST2andNET1regulate epithelial-mesenchymal transition which is required for proper lip and palate fusion. Interactions with vitamins encompassCECR2— a chromatin remodeling protein required for neural tube closure—andFURIN,a critical protease during early embryogenesis that activates various growth factor and extracellular-matrix protein. The activity of both proteins is influenced by folic acid. Our findings highlight the critical role of maternal exposures in identifying genes associated with structural birth defects such as CL/P and provide new paths to explore for CL/P genetics.
Sensor Fusion Algorithm to Improve Accuracy of Robotic Superposition Testing using 6-DOF Position Sensors
Authors: Gillespie Callan M. , Arant Lesley R. , Roth Joshua D. , Colbrunn Robb W. 
Published: December 2024

ABSTRACTTo quantify the contributions of specific ligaments to overall joint biomechanics, the principle of superposition has been used for nearly 30 years. This principle relies on a robotic test system to move a biological joint to the same pose before and after transecting a ligament. The magnitude of the vector difference in joint forces before and after transecting the ligament is assumed to be the transected ligament’s tension. However, the robotic test system’s ability to accurately return the joint to the commanded pose is dependent on the compliance of the system’s various components, which is often neglected. An alternative approach to superposition testing is to use additional sensors attached directly to the joint to inform robot motion. Accordingly, there are two objectives in this manuscript: (1)Describea testing methodology with 6-DOF position sensors to correct for system compliance, and (2)Demonstratethe effectiveness of this methodology to reduce uncertainty of in-situ forces determined using superposition. A Sensor Fusion algorithm fuses 6-DOF position sensors with robot pose measurements to compensate for system compliance. Using a surrogate knee joint with the Traditional testing method, errors in pose of approximately 100 microns resulted in a 23% underestimation of computed ligament tension. With the Sensor Fusion algorithm, errors in pose fell below the noise floor of the 6-DOF position sensors, and errors in computed ligament tension were reduced to 3%. Thus, this Sensor Fusion algorithm is a promising approach to minimize errors in superposition testing caused by compliance in a robotic test system.
Responses to temperature shocks inZymoseptoria triticireveal specific transcriptional reprogramming and novel candidate genes for thermal adaptation
Authors: Minana-Posada Silvia , Feurtey Alice , Alassimone Julien , McDonald Bruce A. , Lorrain Cécile 
Published: December 2024

AbstractPathogens’ responses to sudden temperature fluctuations, spanning various temporal scales, are critical determinants of their survival, growth, reproduction, and homeostasis. Here, we combined phenotyping, transcriptomics, and genome-wide association approaches to investigate how the wheat pathogenZymoseptoria triticiresponds to and recovers from temperature shocks. Survival emerged as the most significantly affected trait immediately following temperature shocks across 122 geographically diverse strains. In contrast, post-recovery phenotypic traits, including growth rate and melanization, showed no significant deviations from control conditions. Transcriptomic analyses of a reference strain revealed temperature stress-specific gene expression patterns, with genes involved in protein folding, redox homeostasis, membrane stabilization, and cell-wall remodeling playing central roles in the response. A multi-reference k-mer genome-wide association study (GWAS) identified six loci significantly associated with cold shock responses. Among these, two loci emerged as strong candidates for near-freezing temperature adaptation, including a 60S ribosomal protein gene involved in protein synthesis and stress recovery, and an NADH oxidoreductase gene implicated in redox homeostasis and oxidative stress tolerance. These findings shed light on the distinct molecular strategiesZ. triticiemploys to adapt to temperature stress and provide novel insights into fungal resilience under dynamic environmental conditions.Author summaryTemperature fluctuations, an inherent aspect of natural environments, are increasingly exacerbated by climate change, intensifying challenges for organisms to maintain homeostasis amid more frequent and severe extreme weather events. This study reveals distinct phenotypic, transcriptomic, and genetic mechanisms underlyingZ. tritici’s responses to short-term temperature shocks. Survival-related phenotypic traits were significantly reduced by heat and cold shocks, while other traits measured after a recovery period demonstrated the resilience ofZ. triticistrains to temperature stress, reflecting efficient recovery mechanisms. Transcriptomic analyses uncovered temperature-specific gene expression patterns, emphasizing unique regulatory strategies, which mostly return to baseline levels after a recovery period. The discovery of novel loci associated with cold shock responses provides valuable insights into the genetic basis of resilience to short-term temperature stress, offering a foundation for future research on pathogen adaptation to fluctuating environments.