bluuebunny/crossref_metadata_2025_split huggingface dataset:
Psychoactive cocktail consumption on Reunion Island: a case report
Authors: Guyon Joris , Maillot Adrien , Bastard Sophie , Weisse Flore , Daveluy Amélie , Mété David 
Published: February 2025

Abstract
Reunion Island is a French department located in the southwestern Indian Ocean, with distinct trends in drug use, drug diversion, and intoxication compared with metropolitan France (e.g. the misuse of drugs—clonazepam and trihexyphenidyl—combined with cannabis or cocaine, which is not observed in metropolitan France). The authors report a case of atypical intoxication in a 16-year-old female who consumed cannabis in conjunction with an unusual powdered mixture containing psychotropic substances. The intoxication led to confusion, hallucinations, sinus tachycardia, and hospitalization. A comprehensive high-resolution mass spectrometry and liquid-chromatography mass spectrometry analysis of her plasma, her urine and a powder found in her possession revealed the presence of the same five medicines: citalopram/escitalopram, paroxetine, sertraline, venlafaxine, and trihexyphenidyl. This case underscores the intricate interactions between psychoactive substances that are never prescribed together in clinical settings, along with the issue of diverted prescription drugs like trihexyphenidyl. It also emphasizes the potential circulation and use of crushed mixtures of medication for recreational purpose. Fortunately, powder analysis provided crucial insight to understand the intoxication.
Enhancing Thermal Stability in Prismatic Lithium-ion Battery Pack in Electric Vehicle through Optimization for an Indirect Liquid-cooling System
Authors: Park Cheonha , Lee Jun , Lee Hamin , Chang HyukKyun , Kim Chang-Wan 
Published: February 2025

Abstract
In an electric vehicle battery pack, thermal stability degradation due to temperature differences is the cause of performance degradation and thermal runaway. Therefore, an effective battery cooling system design is essential to increase the thermal stability of the battery pack. In this study, surrogate model-based optimization is used to minimize the maximum temperature difference of a prismatic lithium-ion battery pack with an indirect cooling system. In the optimization process, the cooling system mass is constrained along with the maximum temperature of the battery and pumping power. Design of experiments is utilized to identify significant design variables, analyze influence of design variables on responses, and generate a surrogate model. The optimization results showed a 14.48% reduction in the maximum temperature difference, from 8.21 K to 7.02 K, relative to the initial cooling system design.
Divergence-Free Finite Volume WENO Scheme for Relativistic Magnetohydrodynamics Preserving Positivity and Subluminal Velocity
Authors: Ding Shengrong , Wu Kailiang , Yuan Caiyou 
Published: February 2025

Abstract
This paper presents a high-order, locally divergence-free finite volume weighted essentially non-oscillatory (WENO) scheme for special relativistic magnetohydrodynamics (RMHD) with a general equation of state. The scheme rigorously enforces essential physical bounds, including positivity of density and pressure and the subluminal constraint on fluid velocity, achieving bound-preserving (BP) properties. Maintaining BP properties in RMHD simulations requires a discrete divergence-free magnetic field. To address this, we introduce a local projection technique tailored for WENO schemes, without reconstructing approximation polynomials and solving additional equations, thus enhancing computational efficiency and ease of implementation. We also develop a simplified BP limiter for the WENO reconstructed point values and a precondition for BP properties of updated cell averages, maintaining the discretely divergence-free property enforced by the projection. We provide a theoretical proof of BP properties for the updated cell averages in the proposed scheme, overcoming challenges posed by RMHD’s nonlinear couplings, complex variable transformations, and nonlinear physical constraints. Our approach uses geometric quasilinearization to reformulate these nonlinear constraints into equivalent linear forms relative to the conserved variables. Additionally, a provably convergent Newton–Raphson method robustly recovers primitive variables from conserved quantities, ensuring physical validity. Extensive numerical experiments validate the robustness of our method across challenging RMHD scenarios, including those with strong shocks, high Lorentz factors, and conditions of low density, low pressure, and low plasma beta.
Yes to Koch, No to Woke: Public Opinion, Free Markets, and Business Involvement in Politics
Authors: Goidel Spencer , Madsen Bradley , Freeman Craig , Goidel Kirby 
Published: February 2025

Abstract
In this paper, we use data from the 2022 Cooperative Election Study to explore the relationship between partisanship, attitudes toward free markets, and corporate social responsibility. We find that while Republicans continue to express abstract support for free markets and business involvement in politics, they respond negatively to more specific descriptions of CEO activism, particularly when that activism is directed toward environmental, social, and governance (ESG) issues. Overall, individual support for business involvement in politics depends on the noneconomic impact of corporate behavior. In this respect, our findings echo the literature on political tolerance: abstract support for free markets slips when applied to specific environmental, social, and governance contexts. Within this context, “business involvement in politics,” which Republicans support, translates into “corporate political activity,” which Republicans oppose.
UnFATE: A Comprehensive Probe Set and Bioinformatics Pipeline for Phylogeny Reconstruction and Multilocus Barcoding of Filamentous Ascomycetes (Ascomycota, Pezizomycotina)
Authors: Ametrano Claudio G , Jensen Jacob , Lumbsch H Thorsten , Grewe Felix 
Published: February 2025

Abstract
The subphylum Pezizomycotina (filamentous ascomycetes) is the largest clade within Ascomycota. Despite the importance of this group of fungi, our understanding of their evolution is still limited due to insufficient taxon sampling. Although next-generation sequencing technology allows us to obtain complete genomes for phylogenetic analyses, generating complete genomes of fungal species can be challenging, especially when fungi occur in symbiotic relationships or when the DNA of rare herbarium specimens is degraded or contaminated. Additionally, assembly, annotation, and gene extraction of whole-genome sequencing data require bioinformatics skills and computational power, resulting in a substantial data burden. To overcome these obstacles, we designed a universal target enrichment probe set to reconstruct the phylogenetic relationships of filamentous ascomycetes at different phylogenetic levels. From a pool of single-copy orthologous genes extracted from available Pezizomycotina genomes, we identified the smallest subset of genetic markers that can reliably reconstruct a robust phylogeny. We used a clustering approach to identify a sequence set that could provide an optimal trade-off between potential missing data and probe set cost. We incorporated this probe set into a user-friendly wrapper script named UnFATE (https://github.com/claudioametrano/UnFATE) that allows phylogenomic inferences without requiring expert bioinformatics knowledge. In addition to phylogenetic results, the software provides a powerful multilocus alternative to ITS-based barcoding. Phylogeny and barcoding approaches can be complemented by an integrated, pre-processed, and periodically updated database of all publicly available Pezizomycotina genomes. The UnFATE pipeline, using the 195 selected marker genes, consistently performed well across various phylogenetic depths, generating trees consistent with the reference phylogenomic inferences. The topological distance between the reference trees from literature and the best tree produced by UnFATE ranged between 0.10 and 0.14 (nRF) for phylogenies from family to subphylum level. We also tested the in vitro success of the universal baits set in a target capture approach on 25 herbarium specimens from ten representative classes in Pezizomycotina, which recovered a topology congruent with recent phylogenomic inferences for this group of fungi. The discriminating power of our gene set was also assessed by the multilocus barcoding approach, which outperformed the barcoding approach based on ITS. With these tools, we aim to provide a framework for a collaborative approach to build robust, conclusive phylogenies of this important fungal clade.
Comparison of Rubber Band Ligation and Hemorrhoidectomy in Patients With Symptomatic Hemorrhoids Grade III: A Multicenter, Open-Label, Randomized Controlled, Non-Inferiority Trial
Authors: van Oostendorp Justin Y. , Dekker Lisette , van Dieren Susan , Veldkamp Ruben , Bemelman Willem A. , Han-Geurts Ingrid J.M. ,   The HollAND study group
Published: February 2025

BACKGROUND:
The optimal management strategy for grade III hemorrhoids remains a subject of ongoing debate. Hemorrhoidectomy is the gold standard, but rubber band ligation offers a less invasive outpatient alternative. Treatment variability persists due to a lack of consensus on the preferred strategy.

OBJECTIVE:
To directly compare the effectiveness of rubber band ligation and hemorrhoidectomy in the treatment of grade III hemorrhoids.

DESIGN:
Open-label, parallel-group, randomized controlled non-inferiority trial.

SETTINGS:
Multicenter study across 10 Dutch hospitals from October 2019 to September 2022.

PATIENTS:
Patients (≥18 years) with symptomatic grade III (Goligher) hemorrhoids. Exclusions: prior rectal/anal surgery, >1 rubber band ligation/injection within the preceding three years, rectal radiation, preexisting sphincter injury, inflammatory bowel disease, medical unfitness for surgery (ASA >3), pregnancy, or hypercoagulability disorders.

INTERVENTIONS:
Randomized 1:1 to rubber band ligation or hemorrhoidectomy, with up to two banding sessions allowed.

MAIN OUTCOME MEASURES:
Primary: 12-month health-related quality of life and recurrence rate. Secondary: complications, pain, work resumption, and patient-reported outcome measures.

RESULTS:
Eighty-seven patients were randomized (47 rubber band ligation vs 40 hemorrhoidectomy). Rubber band ligation was not non-inferior to hemorrhoidectomy in quality adjusted life years (-0.045, 95% confidence interval -0.087 to -0.004). Recurrence rate was worse in the rubber band ligation group (47.5% vs 6.1%), with an absolute risk difference of 41% (95% confidence interval 24%–59%). Complication rates were comparable. Post-hemorrhoidectomy pain scores were higher during the first week (visual analogue scale 4 vs 1; p = 0.002). Rubber band ligation group returned to work sooner (1 vs 9 days; p = 0.021). Patient-reported hemorrhoidal symptom scores favored hemorrhoidectomy.

LIMITATIONS:
The study’s primary limitation was its early termination due to funding constraints, resulting in a relatively small sample size and limited statistical power. Patient recruitment was hindered by significant treatment preferences and the COVID-19 pandemic.

CONCLUSIONS:
Hemorrhoidectomy may benefit patients with grade III hemorrhoids in terms of quality of life, recurrence risk, and symptom burden, while Rubber Band Ligation allows faster recovery with less pain. These findings can guide clinical decision-making. See Video Abstract.

Clinical trial registration number:
NCT04621695.
A Machine-Learning Approach to Finding Gene Target Treatment Options for Long COVID
Authors: Lopez-Rincon Alejandro 
Published: February 2025

AbstractLong COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), encompasses a range of symptoms persisting for weeks or months after the acute phase of COVID-19. These symptoms, affecting multiple organ systems, significantly impact the quality of life. This study employs a machine-learning approach to identify gene targets for treating Long COVID. Using datasets GSE275334, GSE270045, and GSE157103, Recursive Ensemble Feature Selection (REFS) was applied to identify key genes associated with Long COVID. The study highlights the therapeutic potential of targeting genes such as PPP2CB, SOCS3, ARG1, IL6R, and ECHS1. Clinical trials and pharmacological interventions, including dual antiplatelet therapy and anticoagulants, are explored for their efficacy in managing COVID-19-related complications. The findings suggest that machine learning can effectively identify biomarkers and potential therapeutic targets, offering a promising avenue for personalized treatment strategies in Long COVID patients.
Amyloid-β precursor protein promotes tumor growth by establishing an immune-exclusive tumor microenvironment
Authors: Yin Tao , Wang Guoping , Ma Zhehao , Wang Liuyang , Chen Rui , Xiang Kun , Tan Lianmei , Wang Yan , Chong Mengyang , Liang Yaosi , Pan Christopher C. , Alexander Peter B. , Lim Bryan Jian Wei , Wang Ergang , Liu Bushangqing , Yan Chengsong , Li Qi-Jing , Wang Xiao-Fan 
Published: February 2025

AbstractDuring initiation and progression, cancerous tissue hijacks a series of elaborate tissue homeostatic mechanisms to avoid immune surveillance, including neuro-immune interactions. Here, we show that amyloid-β precursor protein (APP) and its β-cleavage product amyloid-β1-42 (Aβ1-42), well-known in the pathogenesis of Alzheimer’s disease (AD), are expressed in multiple cancer tissues. However, the oncogenic activity of APP is due to its E1 domain, instead of Aβ1-42. Mechanistically, APP restricts immune cells influx into tumor microenvironment (TME) and impairs CD8+ T cell and NK cell-based immunity, by dampening type I interferon (IFN) response in TME. We also provide proof-of-concept that vaccination targeting APP is effective for cancer prevention. Our current study reveals a previously unrecognized role of APP in cancer immune surveillance, and provides a new strategy for cancer prevention and treatment by targeting APP.
Accurate Somatic SV detection via sequence graph model-based local pan-genome optimization
Authors: Tu Kailing , Zhang Qilin , Li Yang , Li Yucong , Yuan Lanfang , Tang Jie , Xia Lin , Wang Jing , Huang Wei , Xie Dan 
Published: February 2025

AbstractSomatic structural variations (Somatic SVs) are critical genomic alterations with significant implications in cancer genomics. Although long-read sequencing (LRS) theoretically provides optimal resolution for detecting these variants due to its ability to span large genomic segments, current LRS - based methods, which are derived from short - read - based somatic SV detection algorithms, mainly rely on split - read information. The high error rate of long - read sequencing and the errors introduced by the seed-and-chaining strategy of mainstream alignment algorithms affect the accuracy of these split-reads, making precise detection of somatic SVs still a challenge. To address this issue, we propose the TDScope algorithm, which uses the complete sequence information of local genomic regions provided by long-read sequencing to construct a local graph genome and combines random forest technology to achieve precise detection of somatic structural variations. TDScope outperforms state-of-the-art somatic SV detection methods on paired long-read whole-genome sequencing (WGS) benchmark cell lines, with an average F1-score improvement of 20%. It also demonstrates superior performance in detecting somatic SVs and resolving heterogeneous genomes in tandem repeat-like simulated somatic SV datasets. We also provide the ScopeVIZ tool to offer users visualization evidence of local graph genomes and somatic SV sequences. All code implementations are publicly available on GitHub (https://github.com/Goatofmountain/TDScope).
Leveraging Comparative Phylogenetics for Evolutionary Medicine: Applications to Comparative Oncology
Authors: Mellon Walker J. , Sterner Beckett , Ågren J. Arvid , Vincze Orsolya , Marx Matthew T. , Kapsetaki Stefania E. , Huang Ping-Han , Yavari Bryan , McCollum Hunter W. , Natterson-Horowitz Barbara , Human Hannah , Baciu Cristina , Richker Harley , Mallo Diego , Maley Carlo , Harmon Luke J. , Compton Zachary T. 
Published: February 2025

AbstractComparative phylogenetics provides a wealth of computational tools to understand evolutionary processes and their outcomes. Advances in these methodologies have occurred in parallel with a surge in cross-species genomic and phenotypic data. To date, however, the majority of published studies have focused on classical questions in evolutionary biology, such as speciation and the ecological drivers of trait evolution. Here, we argue that evolutionary medicine in general, and our understanding of the origin and diversification of disease traits in particular, would be greatly expanded by a wider integration of phylogenetic comparative methods (PCMs). We use comparative oncology – the study of cancer across the tree of life – as a case study to demonstrate the power of the approach and show that implementing PCMs can highlight the mode and tempo of the evolutionary changes in intrinsic, species-level disease vulnerabilities.
Highly efficient genome editing inBacillus subtilisvia miniature DNA nucleases IscB
Authors: Gao Jie , Tang Hongjie , Yang Yuhan , Wang Hengyi , Li Qi 
Published: February 2025

ABSTRACTExisting CRISPR-based genome editing tools are limited inBacillus subtilisdue to the largecasgene. The recently reported DNA nuclease IscB has the potential to be developed into a novel genome editing tool due to its size being one-third of Cas9, while its application inB. subtilisremains unexplored. In this study, genome editing tools pBsuIscB/pBsuenIscB based on IscB and enIscB (enhanced IscB) were established inB. subtilisSCK6, and successfully deleted 0.6 kb to 4.3 kb genes with efficiencies up to 100%. Subsequently, the pBsuenIscB with higher deletion efficiency was used, whereby the large genomic fragment of 37.7 kb or 169.9 kb was deleted with only one ωRNA. Additionally, single-copy or multi-copymCherrygenes was integrated by using pBsuenIscB. Finally, the editing plasmid was eliminated and the second round of genome editing was completed. Overall, this study has successfully applied IscB toB.subtilis, expanded the genome editing toolbox ofB. subtilis, and will help to constructB. subtilischassis for production of a variety of biomolecules.
Alternative approaches to single-cell trajectory inference using a commute time matrix
Authors: Houston Douglas W. 
Published: February 2025

AbstractSingle-cell technology has enhanced the high-resolution analysis of dynamic developmental cell fate decisions. A number of elegant mathematical and computational approaches have been developed for using single-cell genomics data to identify gene regulatory events and cell state changes during embryonic development and related processes. These approaches are typically used in combination to model dynamic cell differentiation trajectories but have different underlying mathematical foundations. The extent to which commonly used algorithms for trajectory modeling, such as data imputation, pseudotemporal ordering, and cell fate probability modeling, might be derived from the same underlying approach has not been widely explored. This work describes the use of a matrix based on the commute time of a graph as a single consistent kernel for cell fate trajectory modeling. The commute time kernel is derived from significant eigenvectors of the pseudo-inverse of the graph Laplacian in a manner that preserves commute time. This kernel matrix is used directly in trajectory inference methods and recapitulates the results obtained using different algorithms using three benchmark datasets. Additionally, a comparison of commute time kernels between spliced and unspliced counts was effective for identifying populations of circadian-cycling progenitor cells in differentiating pancreatic endocrine cells. Overall, this work identifies the commute time kernel as a potential parsimonious measure for multiple aspects of trajectory inference.
Genetic targeting of astrocytes associated with specific neuronal circuit in adultDrosophila
Authors: Dopp Joana , Hobin Frederik , Mastroianni Sofia , Yan Jiekun , van Ninhuys Lisa , Liu Sha 
Published: February 2025

SummaryAstrocytes are the major glial population of the brain and have been associated with a vast number of functions. To probe this diversity and to reach a similar level of understanding about astrocyte physiology that we have about neurons, we need genetic tools to target specific astrocytic subpopulations. InDrosophila, we are restricted to using driver lines that drive expression in astrocytes throughout the brain. To target specific astrocytes, we have optimized the genetic tool TRACT (and refer to it as astro-TRACT), allowing effector expression specifically in local astrocytes of a given neuronal circuit. We analyzed specificity, sensitivity and reproducibility of the tool across various MB split-Gal4 drivers. We found that the number of pre-synapses correlates positively with the success of the tool. Applying the tool to characterize morphology of individual astrocytes revealed that local astrocytes around MB medial compartments project into the ellipsoid body. Astro-TRACT will be a valuable resource to investigate both mechanistic astrocyte-neuron signaling and functional and structural astrocytic diversity across the adultDrosophilabrain.
TGIF2 is a major regulator of neural stem cell fate and neurogenic priming
Authors: Li Yiling , Krontira Anthi C. , Vierl Franziska , Richter Maria L. , Wang Weixu , Merl-Pham Juliane , Theis Fabian J. , Hauck Stefanie M. , Götz Magdalena 
Published: February 2025

AbstractDuring brain development, neural stem cells (NSCs) must balance self-renewal with differentiation and ensure lineage progression. To identify novel regulators of NSCs during neurogenesis, we isolated NSCs by FACS from the mouse cerebral cortex and ganglionic eminence at mid-neurogenesis, and at birth, when gliogenesis starts in both, but neurogenesis only continues in the latter region. RNA-seq and ATAC-seq revealed major transcriptional and chromatin changes between these stages and identified TGFB-Induced Homeobox Factor 2 (TGIF2) as a key candidate factor in neurogenic NSCs.In vitroandin vivoexperiments demonstrated a potent role of TGIF2 controlling NSC fate maintenance mediated by its interaction with the SIN3A/HDAC repressor complex suppressing neuronal differentiation genes. Multiomic comparison of NSC and neuron gene expression allowed the comprehensive analysis of neurogenic priming in cortical NSCs, identifying TGIF2 as its major regulator by restraining neuronal differentiation gene activation in NSCs.