bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diminished spinal cord perfusion despite distal aortic perfusion: an acute translational large animal experiment with occluded segmental arteries
Authors: Haunschild Josephina , Dietze Zara , Ossmann Susann , Von Aspern Konstantin , Naumann Jörg , Borger Michael A , Etz Christian D 
Published: December 2024

Abstract

OBJECTIVES
Neuroprotective measures have been established in open thoraco-abdominal aortic aneurysm repair to reduce the incidence of postoperative paraplegia. Distal aortic perfusion (DaP) is meant to increase blood flow to the abdominal organs and the spinal cord. Cerebrospinal fluid (CSF) drainage is part of peri- and postoperative clinical routine. We aimed to investigate the effect of both techniques on spinal cord perfusion in an acute large animal model with segmental artery occlusion.

METHODS
Eight pigs underwent minimally invasive segmental artery coil embolization prior to establishment of cardiopulmonary bypass with DaP. After initiation of DaP, CSF pressure was increased 3-fold by infusion of blood plasma. Collateral network near-infrared spectroscopy was used as an additional real-time monitoring method for indirect perfusion monitoring. Microspheres were injected for post-mortem regional spinal cord blood flow analysis.

RESULTS
DaP led to an increase in spinal cord perfusion limited to the very lower spinal cord (L3–S, up to 400% of baseline) and the corresponding paraspinous muscle area. The most vulnerable region between T8 and L2 was not reached by DaP (between 14% and 46% of baseline). After initiation of DaP, a 10% increase in oxygenation via collateral network near-infrared spectroscopy was observed for the low lumbar region. The increase in CSF pressure counteracted enhanced perfusion inflow leading to a decrease in net tissue perfusion.

CONCLUSIONS
DaP is effective in increasing blood flow to the distal spinal cord (effectively counteracting CSF pressure increase) and paraspinous muscles, despite occluded segmental arteries, resulting in hyperperfusion potentially leading to spinal cord oedema and delayed paraplegia postoperatively.
COCOA: A Framework for Fine-scale Mapping Cell-type-specific Chromatin Compartments with Epigenomic Information
Authors: Li Kai , Zhang Ping , Xu Jinsheng , Wen Zi , Zhang Junying , Zi Zhike , Li Li 
Published: December 2024

Abstract
Chromatin compartmentalization and epigenomic modification are crucial in cell differentiation and diseases development. However, precise mapping of chromatin compartmental patterns requires Hi-C or Micro-C data at high sequencing depth. Exploring the systematic relationship between epigenomic modifications and compartmental patterns remains challenging. To address these issues, we present COCOA, a deep neural network framework using convolution and attention mechanisms to infer fine-scale chromatin compartment patterns from six histone modification signals. COCOA extracts 1-D track features through bi-directional feature reconstruction after resolution-specific binning epigenomic signals. These track features are then cross-fused with contact features using an attention mechanism and transformed into chromatin compartment patterns through residual feature reduction. COCOA demonstrates accurate inference of chromatin compartmentalization at a fine-scale resolution and exhibits stable performance on test sets. Additionally, we explored the impact of histone modifications on chromatin compartmentalization prediction through in silico epigenomic perturbation experiments. Unlike obscure compartments observed with 1 kb resolution high-depth experimental data, COCOA generates clear and detailed compartmental patterns, highlighting its superior performance. Finally, we demonstrated that COCOA enables cell-type-specific prediction of unrevealed chromatin compartment patterns in various biological processes, making it an effective tool for gaining chromatin compartmentalization insights from epigenomics in diverse biological scenarios. The COCOA python code is publicly available at https://github.com/onlybugs/COCOA.
SCREEN: A Graph-based Contrastive Learning Tool to Infer Catalytic Residues and Assess Enzyme Mutations
Authors: Pan Tong , Bi Yue , Wang Xiaoyu , Zhang Ying , Webb Geoffrey I , Gasser Robin B , Kurgan Lukasz , Song Jiangning 
Published: December 2024

Abstract
The accurate identification of catalytic residues contributes to our understanding of enzyme functions in biological processes and pathways. The increasing number of protein sequences necessitates computational tools for the automated prediction of catalytic residues in enzymes. Here, we introduce SCREEN, a graph neural network for the high-throughput prediction of catalytic residues via the integration of enzyme functional and structural information. SCREEN constructs residue representations based on spatial arrangements and incorporates enzyme function priors into such representations through contrastive learning. We demonstrate that SCREEN (i) consistently outperforms currently-available predictors; (ii) provides accurate results when applied to inferred enzyme structures; and (iii) generalizes well to enzymes dissimilar from those in the training set. We also show that the putative catalytic residues predicted by SCREEN mimic key structural and biophysical characteristics of native catalytic residues. Moreover, using experimental data sets, we show that SCREEN’s predictions can be used to distinguish residues with a high mutation tolerance from those likely to cause functional loss when mutated, indicating that this tool might be used to infer disease-associated mutations. SCREEN is publicly available at https://github.com/BioColLab/SCREEN and https://ngdc.cncb.ac.cn/biocode/tool/7580.
Development of a core outcome set of quality indicators for enhanced recovery after surgery in minimally invasive cardiac heart valve surgery by interprofessional Delphi consensus
Authors: Klotz Susanne G R , Begerow Anke , Girdauskas Evaldas 
Published: December 2024

Abstract

OBJECTIVES
A core outcome set (COS) giving indicators of the quality of the process for minimally invasive valve surgery embedded into enhanced recovery after surgery (ERAS) protocols should be developed.

METHODS
Using web-based questionnaires, a Delphi process with three rounds was conducted from January to December 2022. Prior to the rounds, a systematic database search was performed identifying potential quality parameters. Experts for the panel were selected reflecting the interprofessional nature of the ERAS protocol. In the first round, participants could make suggestions of indicators in the pre-, intra- or postoperative and rehabilitative phase. These suggestions form together with the indicators of the literature a first indicator list. In the second round, participants could rate the relevance of the indicators resulting in a condensed indicator list. The third round was performed for further condensation based on importance ranking of the remaining indicators.

RESULTS
Three studies could be included in the systematic literature search providing a list of 22 indicators. Twenty-one experts participated in the Delphi survey. The experts named 315 indicators in the first round. After condensation in two further rounds, the final COS consisted of 24 indicators in the categories structure, process, outcome and complications.

CONCLUSIONS
A consensual minimum set of quality measurements during pre-, intra- and postoperative and rehabilitation phase for patients with minimally invasive heart surgery is now available for enhancing the quality of clinical practice and facilitating comparisons across different ERAS programs.
Parametric finite-element discretization of the surface Stokes equations: inf-sup stability and discretization error analysis
Authors: Hardering Hanne , Praetorius Simon 
Published: December 2024

Abstract
We study a higher-order surface finite-element penalty-based discretization of the tangential surface Stokes problem. Several discrete formulations are investigated, which are equivalent in the continuous setting. The impact of the choice of discretization of the diffusion term and of the divergence term on numerical accuracy and convergence, as well as on implementation advantages, is discussed. We analyse the inf-sup stability of the discrete scheme in a generic approach by lifting stable finite-element pairs known from the literature. A discretization error analysis in tangential norms then shows optimal order convergence of an isogeometric setting that requires only geometric knowledge of the discrete surface.
Plasma Neurofilament Light Chain and Glial Fibrillary Acidic Protein as Biomarkers of Cognitive Decline in People With Human Immunodeficiency Virus
Authors: Mukerji Shibani S , Bachanová Petra , Park Hemi , Rosen Linzy V , Kashlan Rommi , Kivisäkk Pia , Anderson Albert M , Chow Felicia C , Wu Kunling , Dastgheyb Raha M , Rubin Leah H , Tassiopoulos Katherine , Parker Robert A , Hyle Emily P 
Published: December 2024

Abstract

Background
We examined the relationship between neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) and cognition in people with human immunodeficiency virus (HIV) at baseline and longitudinally.

Methods
Plasma and clinical data were available from virally suppressed people with HIV (PWH) aged ≥45 years in the AIDS Clinical Trials Group HAILO study. Four neuropsychological assessments standardized and averaged (NPZ-4) represented cognition. Plasma collection date marked baseline; slope summarized longitudinal NPZ-4 changes. Linear regressions examined biomarkers associations with baseline NPZ-4 and longitudinal change.

Results
The study included 503 participants with a median age of 52 (interquartile range [IQR, 48–57]) years and observation of 6 (IQR, 5–7) years, and 26% had baseline cognitive impairment defined by HAILO. Cross-sectionally, higher NfL (β = −.76, P &lt; .01) and GFAP (β = −.44, P = .02) were associated with worse NPZ-4. Longitudinally, the median NPZ-4 slope was 0.003 (IQR, −0.06 to 0.06) units/year with 48% demonstrating cognitive decline. Higher NfL (β = −.08, P &lt; .01), but not GFAP (β = −.03, P = .08), was associated with cognitive decline.

Conclusions
NfL and GFAP were associated with worse cognition cross-sectionally; only NfL was associated with cognitive decline. Their clinical utility remains uncertain given small effect sizes and should be studied in populations with more rapid decline.
Pharmacokinetic/pharmacodynamic analysis of meropenem and fosfomycin combinations in in vitro time–kill and hollow-fibre infection models against multidrug-resistant and carbapenemase-producing Klebsiella pneumoniae
Authors: Farooq Aneeq , Martens Miklas , Kroemer Niklas , Pfaffendorf Christoph , Decousser Jean-Winoc , Nordmann Patrice , Wicha Sebastian G 
Published: December 2024

Abstract

Background
MDR Gram-negative bacteria, such as ESBL-producing and carbapenemase-producing Klebsiella pneumoniae, represent major global health threats. Treatment options are limited due to increasing resistance and slowed development of novel antimicrobials, making it necessary to apply effective combination therapies based on approved antibiotics.

Objectives
To quantitatively evaluate the synergistic potential of meropenem and fosfomycin against carbapenem-resistant K. pneumoniae strains isolated from clinics.

Methods
We evaluated four MDR K. pneumoniae strains, each expressing KPC-2 or KPC-3, using static time–kill assays that accounted for measured meropenem degradation. This was followed by pharmacokinetic/pharmacodynamic (PK/PD) interaction modelling, which estimated meropenem degradation rate constants and identified perpetrator–victim relationships in PD interactions. Dynamic hollow-fibre infection model (HFIM) experiments were used to confirm synergy.

Results
Static time–kill assays demonstrated high killing effects and suppressed regrowth for the combination of meropenem and fosfomycin, compared with the failure of monotherapy. Meropenem degradation was significantly higher in the presence of bacteria, attributable to carbapenemase activity. Pharmacometric models indicated a synergistic interaction primarily driven by meropenem as the perpetrator, enhancing the potency of fosfomycin. HFIM experiments confirmed in vitro synergy, demonstrating continuous bacterial suppression of the combination therapy.

Conclusions
Meropenem and fosfomycin exhibited additive or synergistic potential against carbapenemase-expressing single- or double-resistant K. pneumoniae at clinically achievable concentrations. This combination therapy may offer a strategy against MDR infections, possibly improving clinical treatment outcomes. Further in vivo research is needed to translate these findings into clinical practice, emphasizing the importance of PK/PD modelling in rationalizing antibiotic use.
Analysis of eligibility criteria clusters based on large language models for clinical trial design
Authors: Bornet Alban , Khlebnikov Philipp , Meer Florian , Haas Quentin , Yazdani Anthony , Zhang Boya , Amini Poorya , Teodoro Douglas 
Published: December 2024

Abstract

Objectives
Clinical trials (CTs) are essential for improving patient care by evaluating new treatments’ safety and efficacy. A key component in CT protocols is the study population defined by the eligibility criteria. This study aims to evaluate the effectiveness of large language models (LLMs) in encoding eligibility criterion information to support CT-protocol design.

Materials and Methods
We extracted eligibility criterion sections, phases, conditions, and interventions from CT protocols available in the ClinicalTrials.gov registry. Eligibility sections were split into individual rules using a criterion tokenizer and embedded using LLMs. The obtained representations were clustered. The quality and relevance of the clusters for protocol design was evaluated through 3 experiments: intrinsic alignment with protocol information and human expert cluster coherence assessment, extrinsic evaluation through CT-level classification tasks, and eligibility section generation.

Results
Sentence embeddings fine-tuned using biomedical corpora produce clusters with the highest alignment to CT-level information. Human expert evaluation confirms that clusters are well structured and coherent. Despite the high information compression, clusters retain significant CT information, up to 97% of the classification performance obtained with raw embeddings. Finally, eligibility sections automatically generated using clusters achieve 95% of the ROUGE scores obtained with a generative LLM prompted with CT-protocol details, suggesting that clusters encapsulate information useful to CT-protocol design.

Discussion
Clusters derived from sentence-level LLM embeddings effectively summarize complex eligibility criterion data while retaining relevant CT-protocol details. Clustering-based approaches provide a scalable enhancement in CT design that balances information compression with accuracy.

Conclusions
Clustering eligibility criteria using LLM embeddings provides a practical and efficient method to summarize critical protocol information. We provide an interactive visualization of the pipeline here.
Morphological and biological characterization of Spermophagus niger (Motschulsky, 1866) (Coleoptera: Chrysomelidae) from four West African countries
Authors: Kabore Emmanuel , Koussoube Jean Christophe , Kam Koï Wenceslas , Sanon Antoine , Ilboudo Zakaria 
Published: December 2024

Abstract
In Burkina Faso and many West African countries, Spermophagus niger (L.) is the main insect pest of Hibiscus sabdariffa seeds stored with considerable damage. Variations in bioclimatic conditions can lead to significant changes in the morphology and biology of populations of the same insect species, leading to strains that are morphologically and biologically different and that would react differently to a given control method. In this study, strains of S. niger from Niger (Niamey), Ghana (Navrongo), Benin (Parakou) and five localities in Burkina Faso (Diébougou, Banfora, Saaba, Mani, and Manga) are studied under controlled conditions (32 °C ± 0.1, 43% ± 1 r.h., L: D 12:12). The results showed that males from Niamey and Parakou lived longer, while females from Niamey and Diébougou had a statistically high longevity.
The larval survival rate of the Niamey strain was significantly lower than Manga, Parakou, and Navrongo. The Niamey strain recorded adults compared to the other strains. In terms of weight, the females and males from Banfora and Niamey were statistically heavier than other strains. At the end of the study, S. niger’ strains showed different morphologies in terms of weight. Furthermore, adult longevity, larval survival rate, and emergence rate were strain dependent.
The p-Frobenius number for the triple of certain quadratic numbers
Authors: Komatsu Takao , Yilmaz Fatih 
Published: December 2024

Abstract
In this paper, we give closed-form expressions of the $p$-Frobenius number for the triple of the numbers $a n(n-1)+r$ for an integer $a\ge 4$ and $r$ is odd. For the set of given positive integers $A:=\{a_{1},a_{2},\dots ,a_{k}\}$, the $p$-Frobenius number is the largest integer whose nonnegative integral linear combinations of given positive integers in $A$ are expressed in at most $p$ ways. When $p=0$, the $0$-Frobenius number is the classical Frobenius number, which is the central topic of the famous linear Diophantine problem of Frobenius.
Insights into the emerging immune checkpoint NR2F6 in cancer immunity
Authors: Miftah Hayat , Benthami Hamza , Badou Abdallah 
Published: December 2024

Abstract
NR2F6 has emerged as a key player in immune regulation, especially in cancer immunity. It has indeed been reported that NR2F6 could suppress the anti-tumor immune response, and has therefore been suggested as possible target in cancer immunotherapy. In this review, we will start by describing the complex structure of the NR2F6 gene and its multifaceted biological functions. Then we will examine its expression in distinct immune cells and cancer cells, elucidating its role in cancer progression. Subsequently, we will highlight the predictive significance of NR2F6 for cancer patient outcome, suggesting its possible use as a prognostic biomarker. Finally, we will discuss the emerging potential of NR2F6 as a therapeutic target, presenting novel opportunities for the development of effective cancer immunotherapy strategies.
A machine learning approach to automate microinfarct and microhemorrhage screening in hematoxylin and eosin-stained human brain tissues
Authors: Cerny Oliveira Luca , Chauhan Joohi , Chaudhari Ajinkya , Cheung Sen-ching S , Patel Viharkumar , Villablanca Amparo C , Jin Lee-Way , DeCarli Charles , Chuah Chen-Nee , Dugger Brittany N 
Published: December 2024

Abstract
Microinfarcts and microhemorrhages are characteristic lesions of cerebrovascular disease. Although multiple studies have been published, there is no one universal standard criteria for the neuropathological assessment of cerebrovascular disease. In this study, we propose a novel application of machine learning in the automated screening of microinfarcts and microhemorrhages. Utilizing whole slide images (WSIs) from postmortem human brain samples, we adapted a patch-based pipeline with convolutional neural networks. Our cohort consisted of 22 cases from the University of California Davis Alzheimer’s Disease Research Center brain bank with hematoxylin and eosin-stained formalin-fixed, paraffin-embedded sections across 3 anatomical areas: frontal, parietal, and occipital lobes (40 WSIs with microinfarcts and/or microhemorrhages, 26 without). We propose a multiple field-of-view prediction step to mitigate false positives. We report screening performance (ie, the ability to distinguish microinfarct/microhemorrhage-positive from microinfarct/microhemorrhage-negative WSIs), and detection performance (ie, the ability to localize the affected regions within a WSI). Our proposed approach improved detection precision and screening accuracy by reducing false positives thereby achieving 100% screening accuracy. Although this sample size is small, this pipeline provides a proof-of-concept for high efficacy in screening for characteristic brain changes of cerebrovascular disease to aid in screening of microinfarcts/microhemorrhages at the WSI level.
REMEDIES IN EU ANTITRUST LAW
Authors: Ibáñez Colomo Pablo 
Published: December 2024

Abstract
Remedies are central in contemporary EU antitrust enforcement. However, they remain relatively misunderstood. Against this background, this article has three main objectives. It seeks, first, to shed light on the nature and purpose of remedial action under Articles 101 and 102 TFEU, with a focus on the European Commission’s activity. The point of intervention, the case law shows, is to bring an infringement effectively to an end. As a matter of positive law, it is unclear that there is room for restorative remedies (that is, remedies that seek to recreate the conditions of competition as they would have existed in the absence of the practice). Second, the article takes a critical perspective on the practice of the past decade. It appears, in particular, that a ‘principles-based approach’ to the administration of remedies is likely to lead to suboptimal outcomes. Finally, some recommendations are outlined so that the letter of the law matches the demands and ambitions of the sort of regulatory-like intervention that is necessary in digital markets and other industries presenting similar features.
Spatiotemporal modelling with dynamic deformation for nonstationary covariance structures
Authors: Morales Fidel Ernesto Castro , Paez Marina Silva 
Published: December 2024

Abstract
In this paper, we present an innovative spatiotemporal model that allows dynamic variation in the spatial correlation structure over time through dynamic deformation. We propose that temporal deformation occurs smoothly relative to that in the original region. To incorporate this idea, we employ state space models to model dynamic deformation. Generalizing this class of models based on spatial deformation was driven by the need to model monthly average temperature data in the southern region of Brazil. The distinctive traits of this region, characterized by plateaus and mountain ranges and close proximity to the Atlantic Ocean, provide notable geographic diversity. This diversity, in addition to different meteorological phenomena over time, may influence the spatial correlation function. The model parameters are estimated via a Bayesian approach, which requires the use of Markov chain Monte Carlo methods to approximate the posterior distributions of parameters. The model is applied to 15 years of monthly average temperature data from the southern region of Brazil. The primary result of this analysis reveals a significant improvement in temperature modelling when the proposed model is used compared with that when versions that employ static deformation are used.