bluuebunny/crossref_metadata_2025_split huggingface dataset:
Benchmarking commercial healthcare claims data
Authors: Dahlen Alex , Deng Yaowei , Charu Vivek 
Published: August 2024

AbstractImportanceCommercial healthcare claims datasets represent a sample of the US population that is biased along socioeconomic/demographic lines; depending on the target population of interest, results derived from these datasets may not generalize. Rigorous comparisons of claims-derived results to ground-truth data that quantify this bias are lacking.Objectives(1) To quantify the extent and variation of the bias associated with commercial healthcare claims data with respect to different target populations; (2) To evaluate how socioeconomic/demographic factors may explain the magnitude of the bias.DesignThis is a retrospective observational study. Healthcare claims data come from the Merative™ MarketScan® Commercial Database; reference data for comparison come from the State Inpatient Databases (SID) and the US Census. We considered three target populations, aged 18-64 years: (1) all Americans; (2) Americans with health insurance; (3) Americans with commercial health insurance.ParticipantsWe analyzed inpatient discharge records of patients aged 18-64 years, occurring between 01/01/2019 to 12/31/2019 in five states: California, Iowa, Maryland, Massachusetts, and New Jersey.OutcomesWe estimated rates of the 250 most common inpatient procedures, using claims data and using reference data for each target population, and we compared the two estimates.ResultsThe average rate of inpatient discharges per 100 person-years was 5.39 in the claims data (95% CI: [5.37, 5.40]) and 7.003 (95% CI: [7.002, 7.004]) in the reference data for all Americans, corresponding to a 23.1% underestimate from claims. We found large variation in the extent of relative bias across inpatient procedures, including 22.8% of procedures that were underestimated by more than a factor of 2. There was a significant relationship between socioeconomic/demographic factors and the magnitude of bias: procedures that disproportionately occur in disadvantaged neighborhoods were more underestimated in claims data (R2= 51.6%, p < 0.001). When the target population was restricted to commercially insured Americans, the bias decreased substantially (3.2% of procedures were biased by more than factor of 2), but some variation across procedures remained.Conclusions and relevanceNaïve use of healthcare claims data to derive estimates for the underlying US population can be severely biased. The extent of bias is at least partially explained by neighborhood-level socioeconomic factors.
Protocol for Systematic Review and Meta-Analysis of Prehospital Large Vessel Occlusion Screening Scales
Authors: Suzuki Hidetaka , Okada Yohei , Hiroshi Yamagami , Hayakawa Mikito , Takeshi Yoshimoto , Kobata Hitoshi 
Published: August 2024

AbstractBackgroundLarge Vessel Occlusion (LVO) is a serious condition that causes approximately 24-46% of acute ischemic strokes (AIS). LVO strokes tend to have higher mortality rates and result in more severe longterm disabilities compared to non LVO ischemic strokes. Early intervention with endovascular therapy (EVT) is recommended; however, EVT is limited to tertiary care hospitals with specialized facilities. Therefore, identifying patients with a high probability of LVO in prehospital settings and ensuring their rapid transfer to appropriate hospitals is crucial. While LVO diagnosis typically requires advanced imaging like MRI or CT scans, various scoring systems based on neurological symptoms have been developed for prehospital use. Although previous systematic reviews have addressed some of these scales, recent studies have introduced new scales and additional data on their accuracy. This systematic review and meta-analysis aim to summarize the current evidence on the diagnostic accuracy of these prehospital LVO screening scales.MethodsThis systematic review and meta-analysis will be conducted in accordance with the PRISMA-DTA Statement and the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy. We will include observational studies and randomized controlled trials that assess the utility of LVO scales in suspected stroke patients in prehospital settings. Eligible studies must provide sufficient data to calculate sensitivity and specificity, and those lacking such data or being case reports will be excluded. The literature search will cover CENTRAL, MEDLINE, and Ichushi databases, including studies in English and Japanese. Bias will be assessed using QUADAS-2, and meta-analysis will be conducted using a random effects model, with subgroup and sensitivity analyses to explore heterogeneity.
De Novo Genome Assembly and Annotation for the Webbing Clothes Moth (Tineola bisselliella): A Globally Distributed, Economically Important Pest
Authors: Alqassar Jasmine D , Aichelman Hannah E , Novick Isabel A , Mullen Sean P 
Published: August 2024

AbstractTineola bisselliella, the webbing clothes moth, is an economically important, globally distributed synanthropic pest species and member of the basal moth lineage Tineidae.Tineola bisselliellais facultatively keratinophagous. Therefore, their larvae can cause extensive damage, particularly to clothing, textiles, and museum specimens. Despite the economic and phylogenetic importance ofTineola bisselliella, there is a lack of quality genomic resources for this species, or for others within the Tineidae family. TheTineola bisselliellagenome presented here consists of 30 pseudochromosomes (29 autosomes and 1 Z chromosome) produced using synteny alignment to a closely related species,Tinea pellionella. The resulting final pseudochromosome-level assembly is 243.630 Mb and has an N50 length of 8.708 Mb. The assembly is highly contiguous and has similar or improved quality compared to other available Tineidae genomes, with 93.1% of lepidopteran orthologs complete and present. Annotation of the pseudochromosome-level genome assembly with the transcriptome we produced ultimately yielded 11,267 annotated genes. Synteny alignments between theTineola bisselliellagenome assembly and other Tineidae genomes found evidence for numerous small rearrangements with high synteny conservation. In contrast, synteny alignments performed betweenTineola bisselliellaand the more distantly relatedBombyx moriandMelitea cinxiarevealed more frequent small and large rearrangements as predicted by their evolutionary divergence. The reference quality annotated genome forTineola bisselliellapresented here will advance our understanding of the evolution of the lepidopteran karyotype by providing a chromosome-level genome for this basal moth lineage and provide future insights into the mechanisms underlying keratin digestion inTineola bisselliella.Significance StatementTineola bisselliella, the webbing clothes moth, is a globally distributed synanthropic pest species that feeds on both keratin-based materials and detritus. This dietary habit can cause substantial damage to clothing, textiles, rugs, taxidermy, and museum specimens. In fact, keratinophagous organisms cause an estimated $1 billion worth of damage annually in the United States. However, the lack of a high-quality annotated reference genome for this basal moth species has thus far limited our understanding of the mechanisms underlying keratin digestion relevant to pest control efforts and has hampered efforts to investigate the broader phylogenetic relationships the Tineidae family necessary to reveal patterns of lepidopteran chromosome evolution. Here, we present the first reference quality genome forTineola bisselliellaand the first annotated genome for any member of the Tineidae family, providing a critical resource for the lepidopteran genomics and pest management communities.
Developmental variability in cotton fiber cell wall properties linked to important agronomic traits
Authors: Wilson Michael C. , Howell Alexander H. , Sood Anika , Lee Youngwoo , Yang Pengcheng , Yu Elena , Rani Heena , Mallery Eileen L. , Swaminathan Sivakumar , Grover Corrinne E. , Wendel Jonathan F. , Zabotina Olga A. , Xie Jun , Davis Chelsea S. , Szymanski Daniel B. 
Published: August 2024

ABSTRACTThe economic value of cotton is based on its long, thin, strong, and twisted trichoblasts that emerge from the ovule epidermis. The mature dried fiber cell reflects the outcome of a rapid tapering of the nascent trichoblast, weeks of polarized diffuse growth, followed by a transition to persistent secondary cell wall synthesis. Highly conserved and dynamic microtubule and cellulose microfibril-based anisotropic growth control modules are central to all of these phases. In this paper, we developed novel quantitative phenotyping and computational modeling pipelines to analyze fiber growth behaviors at a daily resolution. We uncovered unexpected variability in growth rate, cell wall properties, and cell geometry across a critical window of fiber development. Finite element computational modeling of fiber growth was used to analyze the instability of cell diameter control and predict how spatial gradients of fiber and matrix material properties can interact to dictate the patterns of shape change. As an initial step toward gaining insight into the molecular orchestration of cellulose biosynthesis, expression profiles of a broad set of relevant genes were quantified across the same developmental timeline and correlated with fiber phenotypes. This analysis identified specific candidate genes that may serve as targets for fiber quality improvement.
Functional mapping of epigenetic regulators uncovers coordinated tumor suppression by the HBO1 and MLL1 complexes
Authors: Tang Yuning J. , Xu Haiqing , Hughes Nicholas W. , Kim Samuel H. , Ruiz Paloma , Shuldiner Emily G. , Lopez Steven S. , Hebert Jess D. , Karmakar Saswati , Andrejka Laura , Dolcen D. Nesli , Boross Gabor , Chu Pauline , Detrick Colin , Pierce Sarah , Ashkin Emily L. , Greenleaf William J. , Voss Anne K. , Thomas Tim , van de Rijn Matt , Petrov Dmitri A. , Winslow Monte M. 
Published: August 2024

AbstractEpigenetic dysregulation is widespread in cancer. However, the specific epigenetic regulators and the processes they control to drive cancer phenotypes are poorly understood. Here, we employed a novel, scalable and high-throughputin vivomethod to perform iterative functional screens of over 250 epigenetic regulatory genes within autochthonous oncogenic KRAS-driven lung tumors. We identified multiple novel epigenetic tumor suppressor and tumor dependency genes. We show that a specific HBO1 complex and the MLL1 complex are among the most impactful tumor suppressive epigenetic regulators in lung. The histone modifications generated by the HBO1 complex are frequently absent or reduced in human lung adenocarcinomas. The HBO1 and MLL1 complexes regulate chromatin accessibility of shared genomic regions, lineage fidelity and the expression of canonical tumor suppressor genes. The HBO1 and MLL1 complexes are epistatic during lung tumorigenesis, and their functional correlation is conserved in human cancer cell lines. Together, these results demonstrate the value of quantitative methods to generate a phenotypic roadmap of epigenetic regulatory genes in tumorigenesisin vivo.
Coping switches stress–evoked network disconnection to a new forebrain network state
Authors: Durieux Laura , Herbeaux Karine , Totah Nelson K , Lecourtier Lucas 
Published: August 2024

AbstractCoping with stress is critical to maintaining mental and physical health. Acute stress is associated with changes in neuronal activity across many brain regions and with the reorganization of cross– region correlations in neurovascular coupling. How neuronal activity itself is coordinated across regions during stress, and how neuronal networks are modified during coping, are unknown. We recorded in rats local field potentials (LFPs) simultaneously from five stress–responsive regions during stress and stress–coping behavior. We characterized network activity by computing cross– region coherence, Granger causality, and phase–amplitude coupling on bipolar derivatives of LFPs in the lateral habenula, basolateral amygdala, dorsal hippocampus, prelimbic cortex, and anterior cingulate cortex. First, we established a stress–coping model in rats. We showed that the behavioral response to acute 10–minute restraint stress returned to baseline after a second restraint 3 hours later. The pre–stress state was characterized by robust global network interactions in the theta (6– 9 Hz) and gamma (45–65 Hz) bands. Stress exposure led to nearly complete loss of connectivity. During coping, the robust connectivity reemerged, but in a new pattern compared to the pre–stress state. Finally, we found that baseline, stressed, and coping states can be predicted with high accuracy (> 90 %) from network activity. Overall, we showed that the acutely stressed brain state was primarily a state of network disconnection, while coping was a new network state rather than a return to baseline.
Enhancing Variant Calling in Whole Exome Sequencing (WES) Data Using Population-Matched Reference Genomes
Authors: Guo Shuming , Huang Zhuo , Zhang Yanming , He Yukun , Chen Xiangju , Wang Wenjuan , Li Lansheng , Kang Yu , Gao Zhancheng , Yu Jun , Du Zhenglin , Chu Yanan 
Published: August 2024

AbstractWhole exon sequencing (WES) data are frequently used for cancer diagnosis and genome-wide association studies (GWAS), hinging upon high-coverage read mapping, informative variant calling, and high-quality reference genomes. The center position of the currently used genome assembly, GRCh38, is now challenged by two newly publicized telomere-to-telomere or T2T genomes, T2T-CHM13 and T2T-YAO, and it becomes urgent to have a comparative study to test population specificity using the three reference genomes based on real case WES data. We here report our analysis along this line for 19 tumor samples collected from Chinese patients. The primary comparison of the exon regions among the three references reveals that the sequences in up to ∼1% target regions in YAO are widely diversified from GRCh38 and may lead to off-target in sequence capture. However, YAO still outperforms GRCh38 genomes by obtaining 7.41% more mapped reads. Due to more reliable read-mapping and closer phylogenetic relationship with the samples than GRCh38, YAO reduces half of variant calls of clinical significance which are mostly benign while keeping sensitivity in identifying pathogenic variants. YAO also outperforms CHM13 in reducing calls of Chinese-specific variants. Our findings highlight the critical need for employing population-specific reference genomes in genomic analysis to ensure accurate variant analysis and the significant benefits of tailoring these approaches to the unique genetic backgrounds of each ethnic group.
Phylogeographic Insights into Lion Evolution: Unraveling the Genetic Diversity and Lineage Divergence ofPanthera leo
Authors: Afzali Yaser Amir 
Published: August 2024

ABSTRACTThis study investigates the genetic diversity and phylogeographic structure of lion populations (Panthera leo) across Africa and Asia, revealing significant insights into their evolutionary history. Our analysis identifies two primary clades: the North Clade comprising Asian and northern African populations identified asPanthera leo leo, and the South Clade containing East and southern African populations identified asPanthera leo melanochaita. We estimate that the lion’s modern lineage originated approximately 320–280 Kya, with a divergence into the North Clade around 170–130 Kya. The South Clade exhibits a deeper divergence about 290–180 Kya, suggesting a longer history of geographic isolation driven by environmental changes. These dates are older than earlier estimates, owing to new information on the time of divergence betweenP. leoandP. spelaea. Most famous and referenced studies used 0.55 Mya as the split time betweenP. leoandP.spelaeaas the calibration point for their time calibrated trees but new studies demonstrated that split time betweenP. leoandP.spelaeais circa 1.89 Mya. Also, our findings indicate that the Indian lineage (Asian haplogroup) represents a genetically distinct group that should not be classified as a separate subspecies, as its genetic differentiation is trivial compared to that betweenP. l. leoandP. l. melanochaita. The results also indicate higher genetic diversity withinP. l. melanochaita, suggesting a stable population structure influenced by historical environmental conditions. In contrast,P. l. leoexhibits lower genetic variability, likely due to recent anthropogenic pressures, including habitat loss and fragmentation. Demographic analyses illustrate a dramatic decline in effective population size starting in the mid-20th century, correlating with the well-documented reduction in lion range. Phylogeographic patterns in lions reflect broader trends in savannah mammals, underscoring the role of historical climatic fluctuations in shaping modern populations. Crucially, our results contest the hypothesis that the Indian lion population was bolstered by sub-Saharan lion introductions, indicating its ancient lineage. These findings highlight the necessity for targeted conservation strategies that consider the genetic and evolutionary context of lion populations, as well as the unique challenges they face in a changing landscape. Overall, this research underscores the importance of integrating genetic data into lion conservation efforts to ensure the long-term survival of this iconic species.
The developing hippocampus: Microstructural evolution through childhood and adolescence
Authors: Karat Bradley G. , Genc Sila , Raven Erika P. , Palombo Marco , Khan Ali R. , Jones Derek K. 
Published: August 2024

AbstractThe hippocampus is a structure in the medial temporal lobe which serves multiple cognitive functions. While important, the development of the hippocampus in the formative period of childhood and adolescence has not been extensively investigated, with most contemporary research focusing on macrostructural measures of volume. Thus, there has been little research on the development of the micron-scale structures (i.e., microstructure) of the hippocampus, which engender its cognitive functions. The current study examined age-related changes of hippocampal microstructure using diffusion MRI data acquired with an ultra-strong gradient (300 mT/m) MRI scanner in a sample of children and adolescents (N=88; 8-19 years). Surface-based hippocampal modelling was combined with established microstructural approaches, such as Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion Density Imaging (NODDI), and a more advanced gray matter diffusion model Soma And Neurite Density Imaging (SANDI). No significant changes in macrostructural measures (volume, gyrification, and thickness) were found between 8-19 years, while significant changes in microstructure measures related to neurites (from NODDI and SANDI), soma (from SANDI), and mean diffusivity (from DTI) were found. In particular, there was a significant increase across age in neurite MR signal fraction and a significant decrease in extracellular MR signal fraction and mean diffusivity across the hippocampal subfields and long-axis. A significant negative correlation between age and MR apparent soma radius was found in the subiculum and CA1 throughout the anterior and body of the hippocampus. Further surface-based analyses uncovered variability in age-related microstructural changes between the subfields and long-axis, which may reflect ostensible developmental differences along these two axes. Finally, correlation of hippocampal surfaces representing age-related changes of microstructure with maps derived from histology allowed for postulation of the potential underlying microstructure that diffusion changes across age may be capturing. Overall, distinct neurite and soma developmental profiles in the human hippocampus during late childhood and adolescence are reported for the first time.
Discovering uncertainty: Bayesian constitutive artificial neural networks
Authors: Linka Kevin , Holzapfel Gerhard A , Kuhl Ellen 
Published: August 2024

AbstractUnderstanding uncertainty is critical, especially when data are sparse and variations are large. Bayesian neural networks offer a powerful strategy to build predictable models from sparse data, and inherently quantify both, aleatoric uncertainties of the data and epistemic uncertainties of the model. Yet, classical Bayesian neural networks ignore the fundamental laws of physics, they are non-interpretable, and their parameters have no physical meaning. Here we integrate concepts of Bayesian learning and constitutive neural networks to discover interpretable models, parameters, and uncertainties that best explain soft matter systems. Instead of training an individual constitutive neural network and learning point values of the network weights, we train an ensemble of networks and learn probability distributions of the weights, along with their means, standard deviations, and credible intervals. We use variational Bayesian inference and adopt an efficient backpropagation-compatible algorithm that approximates the true probability distributions by simpler distributions and minimizes their divergence through variational learning. When trained on synthetic data, our Bayesian constitutive neural network successfully rediscovers the initial model, even in the presence of noise, and robustly discovers uncertainties, even from incomplete data. When trained on real data from healthy and aneurysmal human arteries, our network discovers a model with more stretch stiffening, more anisotropy, and more uncertainty for diseased than for healthy arteries. Our results demonstrate that Bayesian constitutive neural networks can successfully discriminate between healthy and diseased arteries, robustly discover interpretable models and parameters for both, and efficiently quantify uncertainties in model discovery. We anticipate our approach to generalize to other soft biomedical systems for which real-world data are rare and inter-personal variations are large. Ultimately, our calculated uncertainties will help enhance model robustness, promote personalized predictions, enable informed decision-making, and build confidence in automated model discovery and simulation.Our source code, data, and examples are available athttps://github.com/LivingMatterLab/CANN.