bluuebunny/crossref_metadata_2025_split huggingface dataset:
CLONALITY AND POLYPLOIDY CONTRIBUTE TO THE SPREAD OFAVRAINVILLEA LACERATA(BRYOPSIDALES, CHLOROPHYTA) IN HAWAIʻI
Authors: Thornton Brinkley M. , Spalding Heather L. , Stoeckel Solenn , Harris Melissa L. , Wade Rachael M. , Krueger-Hadfield Stacy A. 
Published: May 2024

ABSTRACTThe relative rates of sexual versus asexual reproduction influence the partitioning of genetic diversity within and among populations. During range expansions, uniparental reproduction often facilitates colonization and establishment. The arrival of the green algaAvrainvillea laceratahas caused shifts in habitat structure and community assemblages since its discovery in 1981 offshore of west Oʻahu, Hawai‘i. Field observations suggest this species is spreading via vegetative reproduction. To characterize the reproductive system ofA. laceratain Hawai‘i, we developed seven microsatellite loci and genotyped 321 blades collected between 2018 and 2023 from two intertidal sites at Maunalua Bay and ʻEwa Beach. We found one to four alleles at multiple loci, suggestingA. laceratais tetraploid. Each site was characterized by high genotypic richness (R > 0.8). However, clonal rates were also high at both sites, suggesting vegetative spread ofA. lacerataplays a significant role. The importance of clonal reproduction for the persistence ofA. laceratain Hawai‘i is consistent with the ecological data collected for this species, and observations of other abundant macroalgal invaders in Hawaiʻi and other regions of the world. These data demonstrate the necessity for implementing appropriate population genetic methods and provide insights into the biology of this alga that will contribute to future studies on effective management strategies incorporating its reproductive system. This study represents one of the few investigating green algal population genetic patterns and contributes to our understanding of algal reproductive system evolution.
The Peruvian Genome Project: expanding the global pool of genome diversity from South America
Authors: Guio Heinner , Caceres Omar , Sanchez Cesar , Padilla Carlos , Trujillo Omar , Borda Victor , Jaramillo-Valverde Luis , Poterico Julio A. , Silva-Carvalho Carolina , Horton Mary , Lanata Cristina M , Carnevale Alessandra , Romero-Hidalgo Sandra , Canizales-Quinteros Samuel , Acuña-Alonzo Víctor , Machacuay-Romero Marco , Novoa Pedro , Frisancho Roberto , Shady Ruth , Flores-Villanueva Pedro , O’Connor Timothy D. , Corpas Manuel , Tarazona-Santos Eduardo 
Published: May 2024

SUMMARYThe process of inhabiting the Americas by ancestral native American populations involved many individuals settling in the Peruvian Andes and Amazonian regions. Due to Latin American countries representing less than 1% of the human genome data available in public reference databases, the evolution and migration processes involved in adapting to this unique geography have not yet been fully explained. The Peruvian Genome Project is an initiative, started in 2011, to address the underrepresentation of genomic data from native South American populations. This project has collected 1,149 samples from 17 traditional native and 13 mestizo (mixed of native, African, and European ancestry) communities. Currently, 150 whole genomes and 873 array-genotyped individuals have been sequenced from across the geography of Western South America, including coastal, Andes, and Amazonian regions. We discovered 1.6 million novel genetic variants with varying frequencies, indicative of local environmental adaptations and population drift. These novel variants allow us to infer local evolutionary traits and population-specific allele frequencies for people living at different altitudes, as well as varying adaptations to pathogens and living conditions. The Peruvian Genome Project is the result of over a decade of work in sample selection, logistics, and approved regulatory community engagement, designed to enhance the human genome pool of diversity of native Americans. The data collected here enable the targeted characterization of endemic diseases, trait adaptations, and new variants of clinical significance in South America. The Peruvian Genome Project represents a step forward in international and multidisciplinary efforts to make precision medicine more inclusive and accessible for underrepresented communities in Latin America, offering significant potential for drug development and diagnostics in a neglected continent.
Assessing the subarachnoid space anatomy on clinical imaging: utilizing normal and pathology to understand compartmentalization of the subarachnoid space
Authors: Almohaimede Khaled , Alibrahim Yusuf , Butt Abu Bakar , Maralani Pejman , Heyn Chris , Kapadia Anish 
Published: May 2024

BACKGROUNDThe goad of the study is to use CT imaging in patients with aSAH to evaluate the anatomic distribution of hemorrhage and compartmentalization of subarachnoid space to investigate potential in vivo visualization of recently discovered layer named subarachnoid lymphatic-like membrane (SLYM).METHODSWe conducted a retrospective cohort study of cases with aneurysmal SAH (aSAH) at our institution between January 2015 and June 2022. Subarachnoid hemorrhage distribution into superficial and deep subarachnoid spaces was classified based on proximity to the dural or pial surfaces, respectively, as seen on multiplanar CT head.RESULTSA total of 97 patients with aSAH were included. Patients with lower modified Fisher score (MFS) of 1-2 were more likely to have SAH compartmentalizing in the “deep” pial-adjacent subarachnoid space. Patients with higher MFS of 3-4 were more likely to have SAH in both “superficial” and “deep” compartments along the brainstem. There is a significant association between the severity of aSAH - quantified by the MFS - and the distribution of the blood. Patients with higher MFS scores were roughly 7.6 times (p-value = 0.049) more likely to have hemorrhage at the “Superficial” juxta-dural subarachnoid compartment when compared to those with lower MFS scores.CONCLUSIONThis study suggests an imaging correlate to the recently discovered “SLYM”, potentially influencing aSAH compartmentalization, particularly in low-grade bleeds. While compartmentalization is limited in high-grade cases, these findings warrant further investigation with advanced imaging techniques to validate this membrane’s role and potential impact on CSF flow and aSAH pathophysiology.
Distances from ligands as main predictive features for pathogenicity and functional effect of variants in NMDA receptors
Authors: Montanucci Ludovica , Brünger Tobias , Bhattarai Nisha , Boßelmann Christian M , Kim Sukhan , Allen James P. , Zhang Jing , Klöckner Chiara , Fariselli Piero , May Patrick , Lemke Johannes R. , Myers Scott J. , Yuan Hongjie , Traynelis Stephen F. , Lal Dennis 
Published: May 2024

AbstractGenetic variants in genesGRIN1,GRIN2A,GRIN2B, andGRIN2D, which encode subunits of the N-methyl-D-aspartate receptor (NMDAR), have been associated with severe and heterogeneous neurologic diseases. Missense variants in these genes can result in gain or loss of the NMDAR function, requiring opposite therapeutic treatments. Computational methods that predict pathogenicity and molecular functional effects are therefore crucial for accurate diagnosis and therapeutic applications. We assembled missense variants: 201 from patients, 631 from general population, and 159 characterized by electrophysiological readouts showing whether they can enhance or reduce the receptor function. This includes new functional data from 47 variants reported here, for the first time. We found that pathogenic/benign variants and variants that increase/decrease the channel function were distributed unevenly on the protein structure, with spatial proximity to ligands bound to the agonist and antagonist binding sites being key predictive features. Leveraging distances from ligands, we developed two independent machine learning-based predictors for NMDAR missense variants: a pathogenicity predictor which outperforms currently available predictors (AUC=0.945, MCC=0.726), and the first binary predictor of molecular function (increase or decrease) (AUC=0.809, MCC=0.523). Using these, we reclassified variants of uncertain significance in the ClinVar database and refined a previous genome-informed epidemiological model to estimate the birth incidence of molecular mechanism-defined GRIN disorders. Our findings demonstrate that distance from ligands is an important feature in NMDARs that can enhance variant pathogenicity prediction and enable functional prediction. Further studies with larger numbers of phenotypically and functionally characterized variants will enhance the potential clinical utility of this method.
Multi-Organ System Metabolic Stress and Sex-Divergent Vascular Associations
Authors: Kwan Alan C. , Wang Minhao , Ji Hongwei , Claggett Brian , Ouyang David , Trivedi Hirsh , Sharma Sonia , Shyy John , Velazquez Amanda , Ebinger Joseph E. , Cheng Susan 
Published: May 2024

ABSTRACTIntroductionWomen experience excess cardiovascular risk compared to men in the setting of similar metabolic disease burden. This consistent finding could be related to sex differences in the vascular response to various forms of metabolic stress. In this study we examine the association of both systemic and organ-specific metabolic stress with vascular health in women and men.MethodsWe conducted an observational study of 4,299 adult participants (52% women, aged 59±13 years) of the National Health and Nutrition Examination Survey (NHANES) 2017-2018 cohort and 110,225 adult outpatients (55% women, aged 64±16 years) of the Cedars-Sinai Medical Center (CSMC) 2019 cohort. We used natural splines to examine the association of systemic and organ-specific measures of metabolic stress including body mass index (BMI), hemoglobin A1c (HbA1c), hepatic FIB-4 score, and CKD-EPI estimated glomerular filtration rate (eGFR) on systolic blood pressure (SBP). Piecewise linear models were generated using normal value thresholds (BMI <25 kg/m2, HbA1c <5.7%, FIB-4 <1.3, and eGFR ≥90 ml/min), which approximated observed spline breakpoints. The primary outcome was increase in SBP (relative to a sex-specific physiologic baseline SBP) in association with increase in level of each metabolic measure.ResultsWomen compared to men demonstrated larger magnitudes and an earlier onset of increase in SBP per increment increase across all metabolic stress measures. The slope of SBP increase per increment of each metabolic measure was greater for women than men particularly for metabolic measures within the normal range, with slope differences of 1.71 mmHg per kg/m2 of BMI, 9.61 mmHg per %HbA1c, 6.45 mmHg per FIB-4 unit, and 0.37 mmHg per ml/min decrement of eGFR in the NHANES cohort (P difference <0.05 for all). Overall results were consistent in the CSMC cohort.ConclusionsWomen exhibited greater vascular sensitivity in the setting of multiple types of metabolic stress, particularly in periods representing the transition from metabolic health to disease. These findings underscore the importance of involving early metabolic health interventions as part of efforts to mitigate vascular risks in both women and men.
CLINICAL IMPLEMENTATION OF PREEMPTIVE PHARMACOGENOMICS TESTING FOR PERSONALIZED MEDICINE AT AN ACADEMIC MEDICAL CENTER
Authors: Tamraz Bani , Shin Jaekyu , Khanna Raman , Van Ziffle Jessica , Knowles Susan , Stregowski Susan , Wan Eunice , Kamath Rajesh , Collins Christopher , Phunsur Choeying , Tsai Benjamin , Kong Patsy , Calanoc Clari , Pollard Aleta , Sawhney Rajeev , Pleiman Jennifer , Devine Walter Patrick , Croci Rhiannon , Sashikanth Aparna , Kroon Lisa , Cucina Russ , Rajkovic Aleks 
Published: May 2024

ABSTRACTObjectiveThis paper describes the implementation of preemptive clinical pharmacogenomics (PGx) testing linked to an automated electronic clinical decision support (CDS) system delivering clinically actionable PGx information to clinicians at the point of care at UCSF Health, a large Academic Medical Center.MethodsA multidisciplinary team developed the strategic vision for the PGx program. The drug-gene interactions of interest were compiled, and actionable alleles were identified. A genotyping platform was selected and validated at the in-house laboratory. Following HIPAA protocols, genotype results were electronically transferred and stored in EPIC. CDS was developed and integrated with electronic prescribing.ResultsWe developed a customized clinical PGx program for 56 medications and 15 genes. 233 MWs and 15 BPAs, approved by clinicians, were built into EPIC to deliver actionable clinical PGx information to clinicians.ConclusionsOur multidisciplinary team successfully implemented preemptive PGx testing linked to point-of-care electronic CDS to guide clinicians with precise medication decision-making.
ShapeMed-Knee: A Dataset and Neural Shape Model Benchmark for Modeling 3D Femurs
Authors: Gatti Anthony A. , Blankemeier Louis , Van Veen Dave , Hargreaves Brian , Delp Scott L. , Gold Garry E. , Kogan Feliks , Chaudhari Akshay S. 
Published: May 2024

AbstractAnalyzing anatomic shapes of tissues and organs is pivotal for accurate disease diagnostics and clinical decision-making. One prominent disease that depends on anatomic shape analysis is osteoarthritis, which affects 30 million Americans. To advance osteoarthritis diagnostics and prognostics, we introduceShapeMed-Knee, a 3D shape dataset with 9,376 high-resolution, medicalimaging-based 3D shapes of both femur bone and cartilage. Besides data, ShapeMed-Knee includes two benchmarks for assessing reconstruction accuracy and five clinical prediction tasks that assess the utility of learned shape representations. Leveraging ShapeMed-Knee, we develop and evaluate a novel hybrid explicit-implicit neural shape model which achieves up to 40% better reconstruction accuracy than a statistical shape model and two implicit neural shape models. Our hybrid models achieve state-of-the-art performance for preserving cartilage biomarkers (root mean squared error ≤ 0.05 vs. ≤ 0.07, 0.10, and 0.14). Our models are also the first to successfully predict localized structural features of osteoarthritis, outperforming shape models and convolutional neural networks applied to raw magnetic resonance images and segmentations (e.g., osteophyte size and localization 63% accuracy vs. 49-61%). The ShapeMed-Knee dataset provides medical evaluations to reconstruct multiple anatomic surfaces and embed meaningful disease-specific information. ShapeMed-Knee reduces barriers to applying 3D modeling in medicine, and our benchmarks highlight that advancements in 3D modeling can enhance the diagnosis and risk stratification for complex diseases. The dataset, code, and benchmarks are freely accessible.
Integrated surveillance of sandflies as vectors of leishmaniasis reveals the presence of a newLeishmaniaspecies with possible implication in human health in Europe
Authors: Ruiz-Arrondo Ignacio , Cervera-Acedo Cristina , Villa-López María Inés , Muelas Eva María , Méndez Manuel , Oteo José Antonio , Collantes Francisco 
Published: May 2024

AbstractLeishmaniasis, endemic in Spain, displays rising incidence rates, notably in the Region of Murcia. Sandfly surveillance andLeishmaniascreening in 2021 uncoveredLeishmania infantumandL. adleri. While currentLeishmaniadiagnostic methods primarily targetL. infantum, our study underscores the importance of broaderLeishmaniaspecies surveillance for accurate diagnosis and understanding of disease dynamics. The detection ofL. adleri, previously undescribed in Europe, highlights the need for expanded research to investigate its presence and implications for human and animal health.
Automatic parameter estimation and detection of Saimaa ringed seal knocking vocalizations
Authors: Solana Adrià , Houegnigan Ludwig , Nadeu Climent , Young Mairi , Kunnasranta Mervi 
Published: May 2024

ABSTRACTThe Saimaa ringed seal (Pusa hispida saimensis) is an endangered subspecies of ringed seal that inhabits Finland’s Lake Saimaa. Many efforts have been put into studying their ecology; however, these initiatives heavily rely on human intervention, making them costly. This study first analyzes an extensive dataset of acoustic recordings from Lake Saimaa with a focus on “knocking” vocalizations, the most commonly found Saimaa ringed seal call type. Then, the dataset is used to train and test a binary deep learning classification system to detect these vocalizations. Out of the 8996 annotated knocking events, the model is trained and tuned with 8096 samples and tested with the remaining 900 events. The system achieves a 97% F1-Score in the test set, demonstrating its capacity to identify knocking segments from noise and other events.
Theca cell mechanics and tissue pressure regulate mammalian ovarian folliculogenesis
Authors: Biswas Arikta , Lou Yuting , Ng Boon Heng , Tomida Kosei , Darpe Sukhada , Wu Zihao , Lu Thong Beng , Bonne Isabelle , Chan Chii Jou 
Published: May 2024

SummaryThe maturation of functional eggs within the ovaries is essential for successful reproduction and organismal functions in mammals. Yet, despite its biological and clinical importance, the underlying mechanisms regulating folliculogenesis remain enigmatic. Here, we report a novel role of the surface-anchoring theca cells (TCs) in regulating follicle growth through mechanical signalling. Direct mechanical measurements reveal that these TCs are highly contractile and exert compressive stress to the follicular interior, potentially through active assembly of fibronectin scaffold around the follicles. Abolishing TC contractility disrupts fibronectin assembly, increases follicle size, and decreases intrafollicular pressure and viscosity. We further reveal that the granulosa cells (GCs) within the follicles exhibit spatial patterns of YAP signalling and proliferation, which appear to be decoupled. Transient manipulation of tissue pressure through bulk follicle compression, laser ablation or pharmacological perturbation of TC contractility leads to changes in GC YAP signalling, proliferation, and oocyte-GC communications, while long term abrogation of TC contractility leads to impaired follicle growth. Altogether, our study unveils the unique role of TC-mediated tissue pressure in ensuring robust mammalian ovarian folliculogenesis.
A multivariate approach to joint testing of main genetic and gene-environment interaction effects
Authors: Mishra Saurabh , Majumdar Arunabha 
Published: May 2024

AbstractGene-environment (GxE) interactions crucially contribute to complex phenotypes. The statistical power of a GxE interaction study is limited mainly due to weak GxE interaction effect sizes. To utilize the individually weak GxE effects to improve the discovery of associated genetic loci, Kraft et al. [1] proposed a joint test of the main genetic and GxE effects for a univariate phenotype. We develop a testing procedure to evaluate combined genetic and GxE effects on a multivariate phenotype to enhance the power by merging pleiotropy in the main genetic and GxE effects. We base the approach on a general linear hypothesis testing framework for a multivariate regression for continuous phenotypes. We implement the generalized estimating equations (GEE) technique under the seemingly unrelated regressions (SUR) setup for binary or mixed phenotypes. We use extensive simulations to show that the test for joint multivariate genetic and GxE effects outperforms the univariate joint test of genetic and GxE effects and the test for multivariate GxE effect concerning power when there is pleiotropy. The test produces a higher power than the test for multivariate main genetic effect for a weak genetic and substantial GxE effect. For more prominent genetic effects, the latter performs better with a limited increase in power. Overall, the multivariate joint approach offers high power across diverse simulation scenarios. We apply the methods to lipid phenotypes with sleep duration as an environmental factor in the UK Biobank. The proposed approach identified six independent associated genetic loci missed by other competing methods.
Chromatin condensates tune nuclear mechano-sensing in Kabuki Syndrome by constraining cGAS activation
Authors: D’Annunzio Sarah , Santomaso Lucia , Michelatti Daniela , Bernardis Chiara , Vitali Giulia , Lago Sara , Testi Claudia , Pontecorvo Emanuele , Poli Alessandro , Pennacchio Fabrizio , Maiuri Paolo , Sanchez Elodie , Genevieve David , Petrolli Lorenzo , Tarenzi Thomas , Menichetti Roberto , Potestio Raffaello , Ruocco Giancarlo , Zippo Alessio 
Published: May 2024

AbstractCells and tissue integrity is constantly challenged by the necessity to adapt and respond to mechanical loads. Among the cellular components, the nucleus possesses mechano-sensing and mechanotransduction capabilities, yet the molecular mechanisms involved remain poorly defined. We postulated that the mechanical properties of the chromatin and its compartmentalization into condensates contribute to the nuclear adaptation to external forces, while preserving its integrity. By interrogating the effects of MLL4 loss-of-function in Kabuki Syndrome, we found that the balancing of transcriptional and Polycomb condensates tunes the nuclear responsiveness to external mechanical forces. We showed that MLL4 acts as a chromatin mechano-sensor by clustering into condensates through its Prion-like domain, and its response was regulated by the chromatin context. Furthermore, the mechano-sensing activity of MLL4 condensates is instrumental to withstand the physical challenges that nuclei experience during cell confinement and migration by preserving their integrity. In Kabuki Syndrome persistent rupture of nuclear envelope triggers cGAS-STING activation, which leads to programmed cell death. Ultimately, these results demonstrate the critical role chromatin compartments play in mechano-responses and how they impact pathological conditions by stimulating cGAS-STING signaling.
Ligand Gaussian accelerated Molecular Dynamics 3 (LiGaMD3): Improved Calculations of Binding Thermodynamics and Kinetics of Both Small Molecules and Flexible Peptides
Authors: Wang Jinan , Miao Yinglong 
Published: May 2024

AbstractBinding thermodynamics and kinetics play critical roles in drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics of small molecules and flexible peptides using conventional Molecular Dynamics (cMD), due to limited simulation timescales. Based on our previously developed Ligand Gaussian accelerated Molecular Dynamics (LiGaMD) method, we present a new approach, termed “LiGaMD3”, in which we introduce triple boosts into three individual energy terms that play important roles in small-molecule/peptide dissociation, rebinding and system conformational changes to improve the sampling efficiency of small-molecule/peptide interactions with target proteins. To validate the performance of LiGaMD3, MDM2 bound by a small molecule (Nutlin 3) and two highly flexible peptides (PMI and P53) were chosen as model systems. LiGaMD3 could efficiently capture repetitive small-molecule/peptide dissociation and binding events within 2 microsecond simulations. The predicted binding kinetic constant rates and free energies from LiGaMD3 agreed with available experimental values and previous simulation results. Therefore, LiGaMD3 provides a more general and efficient approach to capture dissociation and binding of both small-molecule ligand and flexible peptides, allowing for accurate prediction of their binding thermodynamics and kinetics.