bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automated stenosis estimation of coronary angiographies using end-to-end learning
Authors: Eschen Christian Kim , Banasik Karina , Dahl Anders Bjorholm , Chmura Piotr Jaroslaw , Bruun-Rasmussen Peter , Pedersen Frants , Køber Lars , Engstrøm Thomas , Bøttcher Morten , Winther Simon , Christensen Alex Hørby , Bundgaard Henning , Brunak Søren 
Published: October 2024

AbstractBackgroundThe initial evaluation of coronary stenosis during coronary angiography is typically performed by visual assessment. The visual assessment of coronary angiographies has limited accuracy compared to quantitative methods like fractional flow reserve and quantitative coronary angiography. Quantitative methods are also more time-consuming and costly.ObjectivesTo test whether applying deep-learning-based image analysis to coronary angiographies might yield a faster and more accurate stenosis estimation than visual assessment.MethodsWe developed deep learning models for predicting coronary artery stenosis using 332,582 multi-frame x-ray images (cine loops) from 19,414 patients undergoing coronary angiography. The curated dataset for model development included 13,840 patients, with 62,165 cine loops of the left coronary artery and 31,161 cine loops of the right coronary artery.ResultsFor identification of significant coronary stenosis (visual assessment of diameter stenosis >70%), our model obtained a receiver operator characteristic (ROC) area under the curve (ROC-AUC) of 0.903 (95% CI: 0.900-0.906) on the internal test set with 5,056 patients. The performance was evaluated on an external test set with 608 patients against visual assessment, 3D quantitative coronary angiography, and fractional flow reserve (≤ 0.80), obtaining ROC AUC values of 0.833 (95% CI: 0.814-0.852), 0.798 (95% CI: 0.741-0.842, and 0.780 (95% CI: 0.743-0.817), respectively.ConclusionFor assessment of coronary stenosis during invasive coronary angiography a deep-learning-based model showed promising results for predicting visual assessment (ROC AUC of 0.903). Compared to previous work, our approach demonstrates performance increase, includes all 16 segments, does not exclude revascularized patients, is externally tested, and is simpler using fewer steps and fewer models.
Transferability and accuracy of electronic health record-based predictors compared to polygenic scores
Authors: Detrois Kira E. , Hartonen Tuomo , Teder-Laving Maris , Jermy Bradley , Läll Kristi , Yang Zhiyu ,   Estonian Biobank research team, FinnGen, Mägi Reedik , Ripatti Samuli , Ganna Andrea 
Published: October 2024

AbstractElectronic health record (EHR)-based phenotype risk scores (PheRS) leverage individuals’ health trajectories to infer disease risk. Similarly, polygenic scores (PGS) use genetic information to estimate disease risk. While PGS generalizability has been previously studied, less is known about PheRS transferability across healthcare systems and whether PheRS provide complementary risk information to PGS.We trained PheRS to predict the onset of 13 common diseases with high health burden in a total of 845,929 individuals (age 32-70) from 3 biobank-based studies from Finland (FinnGen), the UK (UKB) and Estonia (EstB). The PheRS were based on elastic-net models, incorporating up to 242 diagnoses captured in the EHR up to 10 years before baseline. Individuals were followed up for a maximum of 8 years, during which disease incidence was observed. PGS were calculated for each disease using recent publicly available results from genome-wide association studies.All 13 PheRS were significantly associated with the diseases of interest. The PheRS trained in different biobanks utilized partially distinct diagnoses, reflecting differences in medical code usage across the countries. Even with the large variability in the prevalence of various diagnoses, most PheRS trained in the UKB or EstB transferred well to FinnGen without re-training. PheRS and PGS were only moderately correlated (Pearson’srranging from 0.00 to 0.08), and models including both PheRS and PGS improved onset prediction compared to PGS alone for 8/13 diseases. PheRS was able to identify a subset of individuals at high-risk better than PGS for 8/13 disease.Our results indicate that EHR-based risk scores and PGS capture largely independent information and provide additive benefits for disease risk prediction. Furthermore, for many diseases the PheRS models transfer well between different EHRs. Given the large availability of EHR, PheRS can provide a complementary tool to PGS for risk stratification.
Establishing laboratory reference ranges for adults and children in Kilifi, Kenya
Authors: Downs Louise O , Orindi Benedict , Hamaluba Mainga , Bejon Philip , Ochola-Oyier Lynette Isabella , Ngetsa Caroline 
Published: October 2024

AbstractAccurate laboratory reference ranges (RR) are essential for diagnosis and management of patients in routine clinical care and clinical trials. RRs vary between geographical location due to differences in population demographics and blood analysis equipment, so locally derived RRs are essential. Here we establish adult and paediatric RRs for a rural population in Kilifi, Kenya using clinical trial data from KEMRI-Wellcome Trust Research Programme (KWTRP).Data from healthy, non-pregnant participants from six clinical trials conducted between 2016 and 2020 were used. Coulter ACT 5 Diff and Ilab Aries were used for haematological and biochemical analysis respectively. Quality control was undertaken daily prior to sample analysis. Derived RRs were compared with RRs from other African countries and further afield. All analyses were performed using R version 3.6.1 (Reference Intervals package).2338 adults and 2054 children were included, 52% of adults and 51% of children were male, median adult age was 32.5 years. Haemoglobin range was lower in women compared to men (9.5–14.2g/dL and 11.5–16.6g/dL respectively), platelet upper limit of normal (ULN) was higher in women compared to men (397 × 103/μL vs 358 × 103/ μL). Biochemistry values were higher in men (ALT ULN 57 U/L in men and 35 U/L in women, creatinine ULN 113umol/L in men and 91umol/L in women). Paediatric RRs showed differences in multiple parameters depending on the age of the child.In both adults and children, many parameters in 2023 Kilifi RRs differed from those in other countries. There was however little difference between 2023 and 2017 Kilifi paediatric RRs.This study provides RRs for adults and children in Kilifi, and the most extensive RRs available for much of East and Southern Africa. We show the need for locally derived reference ranges, highlighting differences between sex, age and geographical location.
Glycemic Fluctuations, Fatigue, and Sleep Disturbances in Type 2 Diabetes During Ramadan Fasting: A Cross-Sectional Study
Authors: Pratama Satwika Arya , Kurniawan Rudy , Chiu Hsiao-Yean , Kuo Hsuan-Ju , Ekpor Emmanuel , Al-Baqi Safiruddin , Hasan Faizul , Romadlon Debby Syahru 
Published: October 2024

ABSTRACTBackgroundThis study aimed to assess the prevalence of glycemic fluctuations, fatigue, and sleep disturbances during Ramadan, and to identify factors associated with hypoglycemia and hyperglycemia events in this period.MethodsA cross-sectional study of 88 individuals with type 2 diabetes during Ramadan fasting (March-April 2024) was conducted. HbA1c levels before Ramadan were obtained from medical records. Participants monitored blood glucose twice daily (during the day and two hours after breaking fast). Blood glucose under 70 mg/dl was considered hypoglycemia, and over 200 mg/dl was hyperglycemia. Fatigue and sleep quality were assessed using the Indonesian Multidimensional Fatigue Inventory-20 (IMFI-20) and the Pittsburgh Sleep Quality Index (PSQI).ResultsA total of 88 patients with type 2 diabetes (mean age, 52.7 years) participated, predominantly female (68.2%) and married (63.6%). The study found a prevalence of 21.6% for hypoglycemia and 30.6% for hyperglycemia. Additionally, 30.7% of participants experienced fatigue, and 40.9% reported poor sleep quality. HbA1c levels before Ramadan and fatigue were significantly associated with both hypoglycemia and hyperglycemia (p < 0.05). Sleep quality was also significantly associated with hyperglycemia events (p < 0.05).ConclusionThe study found that hypoglycemia and hyperglycemia are common in individuals with type 2 diabetes during Ramadan. Fatigue and poor sleep quality were also prevalent.Significant factors linked to both glycemic events included pre-Ramadan HbA1c levels and fatigue, while sleep quality was associated with hyperglycemia. These findings emphasize the need for targeted interventions and personalized management to reduce glycemic fluctuations and improve well-being during Ramadan fasting.
The acceptability of being trained to deliver online, group-based Acceptance and Commitment Therapy to stroke survivors: the experience of third-sector practitioners
Authors: Foote Hannah , Bowen Audrey , Cotterill Sarah , Patchwood Emma 
Published: October 2024

AbstractPurposeThe Wellbeing After Stroke study (WAterS) co-developed a nine-week, online, group-based intervention for stroke survivors, informed by Acceptance and Commitment Therapy (ACT), to be delivered by third sector practitioners. This study explored practitioners’ perceptions of the acceptability of the training and their views on delivering the intervention.Materials and methodsSemi-structured interviews completed with practitioners after training, but before intervention delivery had begun. Interview schedule guided by the Theoretical Framework of Acceptability. Template Analysis used to inductively and deductively interpret the data.ResultsAll eight WAterS-trained practitioners were interviewed. Five main themes were generated. Practitioners were motivated to deliver a stroke-specific therapy. Practitioners reported that training was understandable and that experiencing ACT during training benefitted practitioners’ own wellbeing and increased their preparedness for intervention delivery. Previous experience affected their confidence to deliver. Practitioners expected the therapy to be acceptable to many stroke survivors. The online group context was expected to be beneficial, although they foresaw challenges in remotely facilitating groups with diverse accessibility needs.ConclusionIt is acceptable to upskill a third-sector workforce to deliver a protocolised ACT-informed intervention to stroke survivors, potentially enabling greater reach of much needed psychological support.
A dataset for evaluating clinical research claims in large language models
Authors: Zhang Boya , Yazdani Anthony , Bornet Alban , Khlebnikov Philipp , Milutinovic Marija , Rouhizadeh Hossein , Amini Poorya , Teodoro Douglas 
Published: October 2024

AbstractLarge language models (LLMs) have the potential to enhance the verification of health claims. However, issues with hallucination and comprehension of logical statements require these models to be closely scrutinized in healthcare applications. We introduce CliniFact, a scientific claim dataset created from hypothesis testing results in clinical research, covering 992 unique interventions for 22 disease categories. The dataset used study arms and interventions, primary outcome measures, and results from clinical trials to derive and label clinical research claims. These claims were then linked to supporting information describing clinical trial results in scientific publications. CliniFact contains 1,970 scientific claims from 992 unique clinical trials related to 1,540 unique publications. Intrinsic evaluation yields a Cohen’s Kappa score of 0.83, indicating strong inter-annotator agreement. In extrinsic evaluations, discriminative LLMs, such as PubMedBERT, achieved 81% accuracy and 79% F1-score, outperforming generative LLMs, such as Llama3-70B, which reached 52% accuracy and 39% F1-score. Our results demonstrate the potential of CliniFact as a benchmark for evaluating LLM performance in clinical research claim verification.
Spatial mutual nearest neighbors for spatial transcriptomics data
Authors: Zhou Haowen , Panwar Pratibha , Guo Boyi , Hallinan Caleb , Ghazanfar Shila , Hicks Stephanie C. 
Published: October 2024

AbstractMutual nearest neighbors (MNN) is a widely used computational tool to perform batch correction for single-cell RNA-sequencing data. However, in applications such as spatial transcriptomics, it fails to take into account the 2D spatial information. Here, we presentspatialMNN, an algorithm that integrates multiple spatial transcriptomic samples and identifies spatial domains. Our approach begins by building ak-Nearest Neighbors (kNN) graph based on the spatial coordinates, prunes noisy edges, and identifies niches to act as anchor points for each sample. Next, we construct a MNN graph across the samples to identify similar niches. Finally, the spatialMNN graph can be partitioned using existing algorithms, such as the Louvain algorithm to predict spatial domains across the tissue samples. We demonstrate the performance of spatialMNN using large datasets, including one withN=36 10x Genomics Visium samples. We also evaluate the computing performance of spatialMNN to other popular spatial clustering methods. Our software package is available at (https://github.com/Pixel-Dream/spatialMNN).
Automated model-free analysis of cryo-EM volume ensembles with SIREn
Authors: Kinman Laurel F. , Carreira Maria V. , Powell Barrett M. , Davis Joseph H. 
Published: October 2024

ABSTRACTCryogenic electron microscopy (cryo-EM) has the potential to capture snapshots of proteins in motion and generate hypotheses linking conformational states to biological function. This potential has been increasingly realized by the advent of machine learning models that allow 100s-1,000s of 3D density maps to be generated from a single dataset. How to identify distinct structural states within these volume ensembles and quantify their relative occupancies remain open questions. Here, we present an approach to inferring variable regions directly from a volume ensemble based on the statistical co-occupancy of voxels, as well as a 3D-convolutional neural network that predicts binarization thresholds for volumes in an unbiased and automated manner. We show that these tools recapitulate known heterogeneity in a variety of simulated and real cryo-EM datasets, and highlight how integrating these tools with existing data processing pipelines enables improved particle curation and the construction of quantitative conformational landscapes.
Transcriptomic and Biochemical analysis ofProcambarus clarkiiupon exposure to Pesticides: Population-Specific responses as a sign of pollutant resistance?
Authors: Diana Martínez-Alarcón , Reisser Celine , Solé Montserrat , Lignot Jehan-Hervé , Rivera-Ingraham Georgina 
Published: October 2024

AbstractThe effects that anthropogenic stressors may have on modulating species plasticity has been relatively unexplored; however, it represents a scientific frontier that may offer insights into their ability to colonize new habitats. To explore the advantage that inhabiting polluted environments may offer to invasive species, we selected the crayfishProcambarus clarkii, a species that can colonize and thrive in a wide range of aquatic environments, including heavily polluted ones. Here, we studied the molecular and physiological responses of crayfish when experimentally exposed to a pesticide mix of azoxystrobin and oxadiazon at sublethal concentrations. We compared these responses in three isolated crayfish populations in Southern France that are established in areas with different pollution levels: a) Camargue, seasonally affected by pesticide pollution; b) Bages-Sigean, impacted all year-round by domestic effluents and; c) Salagou, a more pristine site. Gene expression analyses revealed that the response to the pesticide mix was the strongest in the Camargue crayfish. In this population, a total of 88 differentially expressed genes (DEGs) were identified in hepatopancreas and 78 in gills between exposed and control laboratory groups. Among genes that were differentially expressed and successfully annotated, those involved in stress, DNA repair, immune response, and translation and transcription processes stand out. Interestingly, the hepatopancreas responded mainly with upregulation, but with downregulation in the gills. This suggests that compared to naïve individuals, when exposed to these biocides in their natural habitat crayfish respond with different mechanistic strategies that may confer them adaptability at the population level. Responses in terms of antioxidant and detoxification enzymes also corroborate differences to biocide inputs according to the origin of the crayfish.
Annulate Lamellae biogenesis is essential for nuclear pore function
Authors: Lin Junyan , Agote-Arán Arantxa , Liao Yongrong , Schoch Rafael , Ronchi Paolo , Cochard Victor , Zhu Rui , Kleiss Charlotte , Ruff Marc , Chevreux Guillaume , Schwab Yannick , Klaholz Bruno P. , Sumara Izabela 
Published: October 2024

AbstractNuclear pore complexes (NPCs), large protein assemblies embedded into the nuclear envelope (NE), are crucial for bidirectional transport between the nucleus and cytoplasm, a process often disrupted in human diseases. Besides their presence within the NE, NPCs are also found in stacked cytoplasmic endoplasmic reticulum (ER) membranes called annulate lamellae (AL)1,2. Despite being discovered in the mid-20th century3, the function and biogenesis mechanisms of AL have remained largely mysterious. While AL were thought to be restricted to germ, embryonic and malignant cells4–12, we find that AL also exist in the cytoplasm of somatic cells under normal physiological conditions and that they can expand upon specific stimuli. We show that AL merge with the NE, supplying the nucleus with new pores which maintains nuclear pore function and nuclear growth during early interphase. NPC protein RanBP2 (Nup358) and ER-associated Climp63 (CKAP4) trigger AL assembly and their NE-integration. The N-terminal phenylalanine-glycine (FG) repeats of RanBP2 drive the oligomerization of Y-complexes (the NPC outer ring units), and AL-NPCs formation and Climp63 ensures the localization of AL-NPCs to ER sheets and their fusion with the nucleus. These findings uncover a fundamental mechanism of AL biogenesis and highlight the critical role of cytosolic NPCs in the nuclear function and mammalian cellular homeostasis.
Cryo-EM structures of theE. coliTon and Tol motor complexes
Authors: Celia Herve , Botos Istvan , Ghirlando Rodolfo , Beach Bridgette M. , Lloubes Roland , Buchanan Susan K. 
Published: October 2024

AbstractThe Ton and Tol motor proteins use the proton gradient at the inner membrane of Gram-negative bacteria as an energy source. The generated force is transmitted through the periplasmic space to protein components associated with the outer membrane, either to maintain the outer membrane integrity for the Tol system, or to allow essential nutrients to enter the cell for Ton. We have solved the high-resolution structures of theE. coliTonB-ExbB- ExbD andTolA-TolQ-TolR complexes, revealing the inner membrane embedded engine parts of the Ton and Tol systems, and showing how TonB and TolA interact with the ExbBD and TolQR subcomplexes. Structural similarities between the two motor complexes suggest a common mechanism for the opening of the proton channel and the propagation of the proton motive force into movement of the TonB and TolA subunits. Because TonB and TolA bind at preferential ExbB or TolQ subunits, we propose a new mechanism of assembly of TonB and TolA with their respective ExbBD and TolQR subcomplexes and discuss its impact on the mechanism of action for the Ton and Tol systems.
DNA/polysome phase separation and cell width confinement couple nucleoid segregation to cell growth inEscherichia coli
Authors: Papagiannakis Alexandros , Yu Qiwei , Govers Sander K. , Lin Wei-Hsiang , Wingreen Ned S. , Jacobs-Wagner Christine 
Published: October 2024

ABSTRACTChromosome segregation is essential for cellular proliferation. Unlike eukaryotes, bacteria lack cytoskeleton-based machinery to segregate their chromosomal DNA (nucleoid). The bacterial ParABS system segregates the duplicated chromosomal regions near the origin of replication. However, this function does not explain how bacterial cells partition the rest (bulk) of the chromosomal material. Furthermore, some bacteria, includingEscherichia coli, lack a ParABS system. Yet,E. colifaithfully segregates nucleoids across various growth rates. Here, we provide theoretical and experimental evidence that polysome production during chromosomal gene expression helps compact, split, segregate, and position nucleoids inE. colithrough phase separation, inherently coupling these processes to biomass growth across nutritional conditions. Halting polysome formation immediately stops sister nucleoid migration while ensuing polysome depletion gradually reverses nucleoid segregation. Redirecting gene expression away from the chromosome and toward plasmids arrests nucleoid segregation and causes ectopic polysome accumulations that drive aberrant nucleoid dynamics. Cell width perturbations show that radial confinement of polysomes and nucleoids spatially controls their phase separation to ensure that nucleoids split along the cell width and segregate along the cell length. Our findings suggest a built-in mechanism for coupling chromosome segregation to cell growth and highlight the importance of cell width regulation in nucleoid segregation.
An Autonomous Microbial Sensor Enables Long-term Detection of TNT Explosive in Natural Soil
Authors: Essington Erin A. , Vezeau Grace E. , Cetnar Daniel P. , Grandinette Emily , Bell Terrence H. , Salis Howard M. 
Published: October 2024

ABSTRACTMicrobes can be engineered to detect target chemicals, but when they operate in real-world environments, it remains unclear how competition with natural microbes affect their performance over long time periods. We engineered sensors and memory-storing genetic circuits insideBacillus subtilisto sense and respond to the TNT explosive, using predictive models for rational design. We characterized their ability to detect TNT in a natural soil system, measuring single-cell and population-level behavior over a 28-day period. The autonomous microbial sensor activated its response by 14-fold when exposed to low TNT concentrations and maintained stable activation for over 21 days, exhibiting exponential decay dynamics at the population-level with a half-life of about 5 days. Our results show that engineered soil bacteria can carry out long-term detection of an important chemical in natural soil with competitive growth dynamics serving as additional biocontainment.