bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of Medicaid Expansion on Access to Anti-incontinence Surgery
Authors: Roberts Brittany , Ata Ashar , Deverdis Erin C. , Randle Helena , Husk Katherine , Jacobs Bradley , Wolff Gillian , Rogers Rebecca 
Published: October 2024

Importance
Medicaid expansion broadened access to care; however, limited data about the effect on access to anti-incontinence surgical procedures exist.

Objective
Since the Affordable Care Act (ACA) Medicaid expansion in 2014, some regions have had more states adopt expansion (NE—Northeast, W—West) than other regions (S—South, MW—Midwest). We aimed to determine if the proportion of Medicaid funded anti-incontinence procedures increased after Medicaid expansion and whether increases were different by U.S. region.

Study Design
This was a retrospective cohort study.

Results
The 2012–2018 Healthcare Cost and Utilization Project National Inpatient Sample was reviewed for anti-incontinence surgical procedures. Medicaid supported surgical procedures were compared by region and year, and among marginalized populations. During the study period 66,510 surgical procedures were performed. Medicaid as a primary payer for anti-incontinence procedures increased from 10% to 12% (P = <0.001) between 2012 and 2018. The percentage of Medicaid supported procedures performed in the NE (13%) and W (17%) were greater than MW (9%) and S (8%). Procedures among Black, Hispanic or lowest income quartile patients were lowest in the S and did not increase after expansion during the study period (2012 vs 2018, all P = NS). When controlling for confounders, the MW (odds ratio [OR] 0.58; 95% CI 0.46–0.74) and S (OR 0.33; 95% CI 0.26–0.42) were less likely to have Medicaid covered surgical procedures compared to the NE and W (OR 1.04; 95% CI 0.84–1.29).

Conclusions
Nationally, the percentage of Medicaid-supported anti-incontinence procedures increased after expansion. Northeast and W access to procedures increased, and access by marginalized populations broadened, while the S and MW had the most limited proportion of anti-incontinence surgical procedures covered by Medicaid.
Rapid promoter evolution of male accessory gland genes is accompanied by divergent expression in closely relatedDrosophilaspecies
Authors: McQuarrie David W. J. , Stephens Frannie H. S. , Ferguson Alexander D. , Arnold Roland , Civetta Alberto , Soller Matthias 
Published: October 2024

AbstractSeminal fluid proteins (Sfps) are essential for reproductive success and evolve fast, possibly driven by post-copulatory sexual selection (PCSS) originating from sperm competition and cryptic female choice. Counterintuitively, however, the coding region only in few Sfps evolves adaptively. Hence, additional genomic and functional factors must play a role in Sfp evolution independent of the protein coding region. To shed light on drivers of Sfp evolution we focus on those Sfps predominantly expressed in male accessory glands, because this allows examination of their evolution in the tissue which produces the majority of Sfps. Moreover, accessory glands develop normally in hybrids in contrast to testis allowing to control for changes in cellular environment arising during speciation. Here, we discover that Acp promoters contain hot spots for rapid evolution from accumulation of sequence changes and insertions/deletions (indels). We further show that changes in promoter sequences are accompanied by gene expression divergence among closely relatedDrosophilaspecies. We then validate these observations inDrosophilahybrids to show that species-specific expression divergence of Acps with rapidly evolving promoters are maintained in hybrids for some Acps, while others show dominance of one allele, a phenomenon termed transvection. These results indicate thatcis-regulatory evolution, rather than genome background variation, drives Acp expression changes and promotes their rapid evolution.
Fluor NMR study of amino acid derived ligand to study TSPO
Authors: Duma Luminita , Schneider Severine , Martinez Agathe , Hachet Cathy , Bihel Frederic , Lacapere Jean-Jacques 
Published: October 2024

AbstractTranslocator protein (TSPO, 18 kDa), previously known as peripheral-type benzodiazepine receptor, is an evolutionarily conserved membrane protein involved in various physiological processes and patho-physiological conditions. The endogeneous TSPO ligand is a polypeptide of 9 kDa, but dipeptides with biological activity have been previously synthesized and characterized. Herein, we synthesized a phenyl alanine derived ligand with a19F labelling which opens prospective for19F-MRI and potential18F-PET applications. We characterized the coexistence of two conformers that are not equally sensitive to the media used for membrane protein studies. Interaction studies with the recombinant mouse TSPO (mTSPO) in different membrane-mimicking environments are presented using19F NMR enabling structure/function characterizations. A change in the mTSPO environment from pure detergent to lipid/detergent mixture reveals different exchange rates between bound and free ligand forms. Competition experiments with the high-affinity drug ligand (R)-PK 11195 suggests that phenyl alanine derived ligand binds in the same protein cavity.HighlightsFluor labelling of ligands easily reveals the presence of conformersFluorinated phenyl alanine derived ligand interacts with TSPOFluor NMR enables characterization of TSPO ligand interactionsFluor NMR facilitates exchange rate studies between free and bound ligand statesGraphical Abstract
Improving inference in wastewater-based epidemiology by modelling the statistical features of digital PCR
Authors: Lison Adrian , Julian Timothy R. , Stadler Tanja 
Published: October 2024

AbstractThe growing field of wastewater-based infectious disease surveillance relies on the quantification of pathogen concentrations in wastewater using polymerase chain reaction (PCR) techniques. However, existing models for monitoring pathogen spread using wastewater have often been adapted from methods for case count data and neglect the statistical features of PCR techniques. In this paper, we seek to overcome the widespread simplistic modelling of wastewater PCR measurements as normally or log-normally distributed by proposing an appropriate model for digital PCR (dPCR). Building on established statistical theory of dPCR, we derive approximations for the coefficient of variation of measurements and the probability of non-detection and propose a hurdle model-based likelihood for estimating concentrations from dPCR measurements. Using simulations and real-world data, we show that simple likelihoods based on normal or log-normal distributions are misspecified, affecting the estimation of pathogen concentrations and infection trends over time. In contrast, the proposed dPCR-specific likelihood accurately models the distribution of dPCR measurements, improving epidemiological estimates and forecasts even if details of the laboratory protocol are unknown. The method has been implemented in the open-source R package “EpiSewer” to improve wastewater-based monitoring of pathogens.
Assessing the Validity of Leucine Zipper Constructs Predicted in AlphaFold2
Authors: Mitic Isobel , Michie Katharine A. , Jacques David A. 
Published: October 2024

AbstractAP-1 transcription factors are a network of cellular regulators, that combine in different dimer pairs to control a range of pathways involved in differentiation, growth, and cell death. They dimerise via leucine zipper coiled-coil domains, that are preceded by a basic DNA binding domain. Depending on which AP-1 transcription factors dimerise, different DNA sequences will be recognised resulting in differential gene expression. The affinity of AP-1 transcription factors for each other dictates which dimers form. The relative concentration of AP-1 transcription factors varies with tissue type and environment, adding another layer of control to this integral network of cellular regulation. The development of artificial intelligence (AI) protein structure prediction programs gives us a new technique to investigate or predict how dimerization effects combinatorial control. AlphaFold2 and AlphaFold-Multimer are AI programs that predict 3D structures of proteins using primary sequence as their only input, even if there is no homologous model available. To fully realise the potential of AI for structural biology, it is essential to understand its current capabilities and limitations. In this study we used the classical example of an AP-1 dimer: Fos and Jun, to interrogate how AlphaFold2 and AlphaFold-Multimer model leucine zipper domains, and if AlphaFold-Multimer can be used to differentiate between probable and improbable dimer interfaces. We found that AlphaFold-Multimer predicts highly confident leucine zipper dimers, even for dimer pairs, such as the FosB homodimer, for which electrostatics are known to prevent their formation in vivo. This is an important case study concerning high-confidence, but low-accuracy protein structure prediction.statementArtificial intelligence (AI) programs that predict protein structures, like AlphaFold, could transform structural biology by speeding up the experimental process. However, it is important to grasp the capabilities and limitations of these AI tools. This study examines how AlphaFold identifies structural features, specifically a leucine zipper, while not considering other factors like electrostatic interactions, using the well-studied transcription factors Fos and Jun as a case study.
Lower left ventricular ejection time inMYBPC3variant carriers with overt or subclinical hypertrophic cardiomyopathy
Authors: Yan Isabell , Möhring Zoe , Reichart Daniel , Münch Julia , Woitschach Rixa , Kirchhof Paulus , Carrier Lucie , Ho Carolyn Y. , Eschenhagen Thomas , Patten Monica 
Published: October 2024

AbstractAimsHypertrophic cardiomyopathy (HCM) is an inherited cardiomyopathy mainly caused by pathogenic variants inMYBPC3andMYH7,encoding myosin binding protein C3 and myosin heavy chain 7, respectively. These variants can cause increased actin-myosin crossbridge cycling resulting in ventricular hypercontractility. Little is known about genotype-specific differences. Mice lackingMybpc3exhibited reduced left ventricular ejection time (LVET). In this study we tested whether LVET is specifically altered in patients carryingMYBPC3variants by retrospective echocardiographic analysis in two genotype-defined HCM cohorts.Methods and resultsLVET was measured by echocardiography and adjusted for heart rate (LVET index, LVETI) in 173 patients carryingMYBPC3orMYH7pathogenic variant. There was a discovery cohort (Hamburg; 46MYBPC3,31MYH7)and a validation cohort (“Valsartan in Attenuating Disease Evolution in Early Sarcomeric HCM”; 55MYBPC3, 41MYH7). Data were compared with 44 healthy controls from Hamburg. Variant carriers were stratified for overt (G+LVH+) or subclinical left ventricular hypertrophy (G+LVH-). LVETI was lower inMYBPC3and higher inMYH7G+LVH+ patients than in controls in the discovery, validation and pooled cohorts (pooled: 385 ± 23 msMYBPC3, 436 ± 38 msMYH7,411 ± 15 ms controls). Similar findings were seen in G+LVH-.ConclusionThe data suggest that variants inMYBPC3andMYH7result in distinct biophysical consequences, which can be detected by measuring LVETI in patients. The findings may have implications for potential genotype-specific differences in response to therapies targeting sarcomere function.
Cell-free DNA Fragmentomics Assay to Discriminate the Malignancy of Breast Nodules and Evaluate Treatment Response
Authors: Liu Jiaqi , Li Yalun , Tang Wanxiangfu , Dai Lijun , Jia Ziqi , Cao Heng , Li Chenghao , Liu Yuchen , Huang Yansong , Wu Jiang , Ma Dongxu , Qiao Guangdong , Bao Hua , Chang Shuang , Zhu Dongqin , Yang Shanshan , Wu Xuxiaochen , Wu Xue , Xu Hengyi , Chen Hongyan , Shao Yang , Wang Xiang , Liu Zhihua , Su Jianzhong 
Published: October 2024

AbstractThe fragmentomics-based cell-free DNA (cfDNA) assays have recently illustrated prominent abilities to identify various cancers from non-conditional healthy controls, while their accuracy for identifying early-stage cancers from benign lesions with inconclusive imaging results remains uncertain. Especially for breast cancer, current imaging-based screening methods suffer from high false-positive rates for women with breast nodules, leading to unnecessary biopsies, which add to discomfort and healthcare burden. Here, we enroll 560 female participants in this multi-center study and demonstrate that cfDNA fragmentomics is a robust non-invasive biomarker for breast cancer using whole-genome sequencing. Among the multimodal cfDNA fragmentomics profiles, the fragment size ratio (FSR), fragment size distribution (FSD), and copy number variation (CNV) show more distinguishing ability than Griffin, motif breakpoint (MBP), and neomer. The cfDNA fragmentomics (cfFrag) model using the optimal three fragmentomics features discriminated early-stage breast cancers from benign nodules, even at a low sequencing depth (3×). Notably, it demonstrated a specificity of 94.1% in asymptomatic healthy women at a 90% sensitivity for breast cancers. Moreover, we comprehensively showcase the clinical utilities of the cfFrag model in predicting patient responses to neoadjuvant chemotherapy (NAC) and in combining with multimodal features, including radiological results and cfDNA methylation features (with AUC values of 0.93 – 0.94 and 0.96, respectively).
Safety and implementation of a phase 1 randomized GLA-SE-adjuvanted CH505TF gp120 HIV vaccine trial in newborns
Authors: Violari Avy , Otwombe Kennedy , Hahn William , Chen Shiyu , Josipovic Deirdre , Baba Vuyelwa , Angelidou Asimenia , Smolen Kinga K. , Levy Ofer , Mkhize Nonhlanhla N , Woodward Amanda S , Martin Troy M. , Haynes Bart , Williams Wilton B. , Sagawa Zachary K. , Kublin James , Polakowski Laura , Brewinski Isaacs Margaret , Yen Catherine , Tomaras Georgia , Corey Lawrence , Janes Holly , Gray Glenda 
Published: October 2024

AbstractBackgroundThe neonatal immune system is uniquely poised to generate broadly neutralizing antibodies (bnAbs) and thus infants are ideal for evaluating HIV vaccine candidates. We present the design and safety of a novel glucopyranosyl lipid A (GLA)-stable emulsion (SE) adjuvant admixed with a first-in-infant CH505 transmitter-founder (CH505TF) gp120 immunogen designed to induce precursors for bnAbs against HIV.MethodsHVTN 135 is a phase I randomized, placebo-controlled trial of CH505TF+GLA-SE or placebo. Healthy infants in South Africa aged ≤5 days, born to mothers living with HIV but HIV nucleic acid negative at birth were randomized to five doses of CH505TF + GLA-SE or placebo at birth and 8, 16, 32, and 54 weeks.Results38 infants (median age = 4 days; interquartile range 4, 4.75 days) were enrolled November 2020 to January 2022. Among 28 (10) infants assigned to receive CH505TF + GLA-SE (placebo), most (32/38) completed the 5-dose immunization series and follow-up (35/38). Solicited local and systemic reactions were more frequent in vaccine (8, 28.6% local; 16, 57.1% systemic) vs. placebo recipients (1, 10% local, p = 0.25; 4, 40.0% systemic, p = 0.38). All events were Grade 1 except two Grade 2 events (pain, lethargy). Serious vaccine-related adverse events were not recorded.ConclusionsThis study illustrates the feasibility of conducting trials of novel adjuvanted HIV vaccines in HIV-exposed infants receiving standard infant vaccinations. The safety profile of the CH505TF + GLA-SE vaccine was reassuring.Trial registrationClinicalTrials.govNCT04607408FundingNational Institute of Allergy and Infectious Diseases (NIAID) at the National Institutes of Health (NIH)Brief summaryThis paper summarizes the phase 1 trial design and safety profile of an experimental CH505TF immunogen + GLA-SE HIV vaccine in infants born to mothers living with HIV.
Suppressing PDGFRβ Signaling Enhances Myocyte Fusion to Promote Skeletal Muscle Regeneration
Authors: Xue Siwen , Benvie Abigail M. , Blum Jamie E. , Kolba Nikolai J , Cosgrove Benjamin D. , Thalacker-Mercer Anna , Berry Daniel C. 
Published: October 2024

AbstractMuscle cell fusion is critical for forming and maintaining multinucleated myotubes during skeletal muscle development and regeneration. However, the molecular mechanisms directing cell-cell fusion are not fully understood. Here, we identify platelet-derived growth factor receptor beta (PDGFRβ) signaling as a key modulator of myocyte fusion in adult muscle cells. Our findings demonstrate that genetic deletion ofPdgfrβenhances muscle regeneration and increases myofiber size, whereas PDGFRβ activation impairs muscle repair. Inhibition of PDGFRβ activity promotes myonuclear accretion in both mouse and human myotubes, whereas PDGFRβ activation stalls myotube development by preventing cell spreading to limit fusion potential. Transcriptomics analysis show that PDGFRβ signaling cooperates with TGFβ signaling to direct myocyte size and fusion. Mechanistically, PDGFRβ signaling requires STAT1 activation, and blocking STAT1 phosphorylation enhances myofiber repair and size during regeneration. Collectively, PDGFRβ signaling acts as a regenerative checkpoint and represents a potential clinical target to rapidly boost skeletal muscle repair.
Differential reconfiguration of brain networks in children in response to standard versus rewarded go/no-go task demands
Authors: Mitchell Mackenzie E , Henry Teague R , Fogleman Nicholas D , Michael Cleanthis , Nugiel Tehila , Cohen Jessica R 
Published: October 2024

AbstractResponse inhibition and sustained attention are critical for higher-order cognition and rely upon specific patterns of functional brain network organization. This study investigated how functional brain networks reconfigure to execute these cognitive processes during a go/no-go task with and without the presence of rewards in 26 children between the ages of 8 and 12 years. First, we compared task performance between standard and rewarded versions of a go/no-go task. We found that the presence of rewards reduced commission error rate, a measure considered to indicate improved response inhibition. Tau, thought to index sustained attention, did not change across task conditions. Next, changes in functional brain network organization were assessed between the resting state, the standard go/no-go task, and the rewarded go/no-go task. Relative to the resting state, integration decreased and segregation increased during the standard go/no-go task. A further decrease in integration and increase in segregation was observed when rewards were introduced. These patterns of reconfiguration were present globally and across several key brain networks of interest, as well as in individual regions implicated in the processes of response inhibition, attention, and reward processing. These findings align with patterns of brain network organization found to support the cognitive strategy of sustained attention, rather than response inhibition, during go/no-go task performance and suggest that rewards enhance this organization. Overall, this study used large-scale brain network organization and a within-subjects multi-task design to examine different cognitive strategies and the influence of rewards on response inhibition and sustained attention in late childhood.
KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks
Authors: Scheuer Dominik , Runge Frederic , Franke Jörg K.H. , Wolfinger Michael T. , Flamm Christoph , Hutter Frank 
Published: October 2024

AbstractRNA is a dynamic biomolecule crucial for cellular regulation, with its function largely determined by its folding into complex structures, while misfolding can lead to multifaceted biological sequelae. During the folding process, RNA traverses through a series of intermediate structural states, with each transition occurring at variable rates that collectively influence the time required to reach the functional form. Understanding these folding kinetics is vital for predicting RNA behavior and optimizing applications in synthetic biology and drug discovery. Whilein silicokinetic RNA folding simulators are often computationally intensive and time-consuming, accurate approximations of the folding times can already be very informative to assess the efficiency of the folding process. In this work, we presentKinPFN, a novel approach that leverages prior-data fitted networks to directly model the posterior predictive distribution of RNA folding times. By training on synthetic data representing arbitrary prior folding times,KinPFNefficiently approximates the cumulative distribution function of RNA folding times in a single forward pass, given only a few initial folding time examples. Our method offers a modular extension to existing RNA kinetics algorithms, promising significant computational speed-ups orders of magnitude faster, while achieving comparable results. We showcase the effectiveness ofKinPFNthrough extensive evaluations and real-world case studies, demonstrating its potential for RNA folding kinetics analysis, its practical relevance, and generalization to other biological data.
Automatic Detection and Extraction of Key Resources from Tables in Biomedical Papers
Authors: Ozyurt Ibrahim Burak , Bandrowski Anita 
Published: October 2024

AbstractTables are useful information artifacts that allow easy detection of data “missingness” by humans and have been deployed by several publishers to improve the amount of information present for key resources and reagents such as antibodies, cell lines, and other tools that constitute the inputs to a study. The STAR*Methods tables, specifically, have increased the “findability” of these key resources, but they have not been commonly available outside of the Cell Press journal family. To improve the availability of these tables in the broader biomedical literature, we have attempted to automatically process BioRxiv preprints to create tables from text or to recognize tables already created by authors and structure them for later use by publishers and search systems, to improve “findability” of resources in a larger amount of the scientific literature. The extraction of key resource tables in PDF files by the best in class tools resulted in Grid Table Similarity (GriTS) score of 0.12, so we have created several multimodal pipelines employing machine learning approaches for key resource table page identification, Table Transformer models for table detection and table structure recognition and a new table-specific language model for row over-segmentation to improve the extraction of text in tables created by biomedical authors and published on BioRxiv to around GriTS score of 0.90 enabling the deployment of automated research resource extraction tools onto BioRxiv.Author summaryTables are useful information artifacts that allow for easy detection of data “missingness” by humans and have been implemented by several publishers to improve the amount of information present for key resources and reagents such as antibodies, cell lines, and other tools that constitute the inputs to a study. To improve the availability of these tables in the broader biomedical literature, we introduced four pipelines for key resource table extraction from biomedical documents in PDF format. Our approach reconstructs key resource tables using image level table detection and structure detection generated table boundary, column (and row) bounding box information together with PDF text alignment. To remedy row over-segmentation resulting from overflowing table cell contents, we introduced a language modeling (LM) based row merging solution where a character-level generative pre-trained transformer (GPT) model was pre-trained on more than 11 million scientific table contents from PubMed Central Open Access Subset (PMC OAS). All introduced pipelines significantly outperformed GROBID baseline while our Table LM based row merging based pipeline, significantly outperformed all other pipelines including our OCR based pipeline.