bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nanopore sequencing as a cutting-edge technology for medulloblastoma classification
Authors: Filser Mathilde , Torrejon Jacob , Merchadou Kevin , Dufour Christelle , Girard Elodie , Bourneix Christine , Lemaître Elisa , Gharsalli Tarek , Brillet Riwan , Wong Jennifer , Gentien David , Rapinat Audrey , Servant Nicolas , Vasiljevic Alexandre , Bertozzi Anne Isabelle , Raimbault Sandra , Tauziede Espariat Arnault , Lhermitte Benoit , Faure-Conter Cécile , Icher Céline , Berger Claire , Maurage Claude Alain , Bodet Damien , Meyronet David , Uro-Coste Emmanuelle , De Carli Emilie , Forest Fabien , Palenzuela Gilles , Chotard Guillaume , Gauchotte Guillaume , Sudour Helene , Mansuy Ludovic , Deparis Marianna , Tallegas Matthias , Faisant Maxime , Entz-Werle Natacha , Varlet Pascale , Leblond Pierre , Michalak-Provost Sophie , Proust Houdemont Stéphanie , Rigau Valérie , Doz François , Delattre Olivier , Bourdeaut Franck , Ayrault Olivier , Masliah-Planchon Julien 
Published: December 2024

Abstract

Background
Medulloblastoma (MB) is one of the most prevalent embryonal malignant brain tumors. Current classification organizes these tumors into 4 molecular subgroups (WNT, SHH, Group 3, and Group 4 MB). Recently, a comprehensive classification has been established, identifying numerous subtypes, some of which exhibit a poor prognosis. It is critical to establish effective subtyping methods for accurate diagnosis and patient’s management that strikes a delicate balance between improving outcomes and minimizing the risk of comorbidities.

Methods
We evaluated the ability of Nanopore sequencing to provide clinically relevant methylation and copy number profiles of MB. Nanopore sequencing was applied to an EPIC cohort of 44 frozen MB, benchmarked against the gold standard EPIC array, and further evaluated on an integrated diagnosis cohort of 116 MB.

Results
Most MB of both cohorts (42/44; 95.5% and 106/116; 91.4%, respectively) were accurately subgrouped by Nanopore sequencing. Employing Flongle flow cells for 18 MB allowed a more rapid and cost-effective analysis, with 94.4% (17/18) being correctly classified. Nanopore sequencing enabled us to accurately subtype 28/30 (93.3%) MB.

Conclusion
This study, conducted on the largest cohort of MB analyzed with Nanopore sequencing to date, establishes the proof of concept that this modern and innovative technology is well-suited for MB classification. Nanopore sequencing demonstrates a robust capacity for precise subtyping of MB, a critical advancement that holds significant potential for enhancing patient stratification in future clinical trials. Its ability to deliver quick and cost-effective results firmly establishes it as a game-changer in the field of MB classification.
Effects of Prebiotics and Probiotics on Symptoms of Depression and Anxiety in Clinically Diagnosed Samples: Systematic Review and Meta-analysis of Randomized Controlled Trials
Authors: Asad Afrida , Kirk Megan , Zhu Sufen , Dong Xue , Gao Min 
Published: December 2024

Abstract

Context
The use of prebiotics and probiotics as a treatment for psychiatric conditions has gained interest due to their potential to modulate the gut–brain axis. This review aims to assess the effectiveness of these interventions in reducing symptoms of depression and anxiety in psychiatric populations.

Objective
The aim was to comprehensively review and appraise the effectiveness of prebiotic, probiotic, and synbiotic interventions in reducing clinical depression and anxiety symptoms.

Data Sources
Systematic searches were conducted across Embase, Medline, PsycINFO, CINAHL, Cochrane Library, and Science Citation Index from database inception to May 22, 2023.

Data Extraction
Randomized controlled trials investigating prebiotic, probiotic, or synbiotic interventions for treating clinical depression or anxiety symptoms in clinical samples were included. Data were extracted on study characteristics, intervention details, and outcome measures. The Cochrane Collaboration Tool was used to assess the risk of bias.

Data Analysis
The standardized mean difference (SMD) was calculated using Hedge’s g as the metric of effect size. A random-effects model was applied to estimate pooled effect sizes with 95% CIs. Subgroup analyses were performed based on study characteristics, methodological factors, and intervention types. Sensitivity analyses excluded studies with a high risk of bias.

Results
Twenty-three RCTs involving 1401 patients met the inclusion criteria, with 20 trials providing sufficient data for meta-analysis. Of these, 18 trials investigated probiotics for depression, 9 trials assessed probiotics for anxiety, and 3 trials examined prebiotics for depression. Probiotics demonstrated a significant reduction in depression symptoms (SMD: –0.96; 95% CI: –1.31, –0.61) and a moderate reduction in anxiety symptoms (SMD: –0.59; 95% CI: –0.98, –0.19). Prebiotics did not show a significant effect on depression (SMD: –0.28; 95% CI: –0.61, 0.04). High heterogeneity was observed across studies, and subgroup analyses indicated that study duration and probiotic formulations contributed to the variation in effect sizes.

Conclusion
Probiotics showed substantial reductions in depression symptoms and moderate reductions in anxiety symptoms. Prebiotics showed a nonsignificant trend toward reducing depression. An adjunctive mental health treatment approach that diagnoses, monitors, and treats the gut microbiome alongside traditional pharmacological treatment holds promise for clinical practice.

Systematic Review Registration
PROSPERO registration no. CRD42023424136.
Exploring the interplay between catastrophizing and endometriosis pain through 2-wave and intensive longitudinal data
Authors: Moreira Marcelo França , Oliveira Marco Aurelio Pinho 
Published: December 2024

Abstract

Background
Endometriosis, characterized by the presence of endometrial-like tissue outside the uterus, results in chronic pelvic pain. However, lesion characteristics alone cannot fully explain the complexity of endometriosis-related pain. Pain catastrophizing, a cognitive process that influences pain perception, has traditionally been studied through cross-sectional or 2-wave designs, which struggle to capture its dynamic interplay with endometriosis pain. To address these gaps, our study explores the bidirectional relationship between pain catastrophizing and pain outcomes—including intensity, frequency, and flares—over a detailed 4-week period and an aggregated 30-day time frame and across sensory and affective dimensions.

Methods
A latent growth curve model assessed the relationship between pain catastrophizing, initial pain levels, and endometriosis pain trajectories over 4 weeks. Additionally, 4 mediator models explored how baseline pain catastrophizing affects various pain aspects, including sensory and affective dimensions, and its subsequent influence on pain catastrophizing.

Results
Results indicate that high levels of pain catastrophizing significantly escalate endometriosis pain over 4 weeks, affecting average pain intensity, episode frequency, and flares over 30 days. Pain catastrophizing also adversely impacts sensory and affective dimensions. These elements partially mediate baseline pain catastrophizing’s effect on week 5 levels, revealing a bidirectional relationship. Notably, whereas the affective dimension amplifies subsequent pain catastrophizing, the sensory dimension exerts a contrasting negative association.

Conclusion
The study highlights the bidirectional influence between pain catastrophizing and several aspects of endometriosis-related pain. Sensory and affective dimensions play distinct roles, with implications for personalized interventions. Limitations and clinical relevance are discussed.

Trial registration
Brazilian Registry of Clinical Trials ID: U1111-1233-4802.
Inverted EEMD: a robust method to identify narrow absorption features form spectral data and cubes
Authors: He Zhen-Zhen , Li Guang-Xing 
Published: December 2024

ABSTRACT
Extracting information from complex data is a challenge shared by multiple frontiers of modern astrophysical research. Among those, analysing spectra cubes, where the emission is mapped in the position–position–velocity space is a difficult task given the vast amount of information contained within. The cubes often contain a superposition of emissions and absorptions, where extracting absorption signatures is often necessary. One example is the extraction of narrow absorption structures in H i 21 cm emission spectra. These H i self-absorption (HISA) clouds trace the cold H i gas in interstellar space. We introduce an automatic and robust method called the inverted ensemble empirical mode decomposition (EEMD) method to extract narrow features from spectral cubes. Our method is based on the EEMD method, an established method to decompose 1d signals. The method is robust and parameter-free, making it useful in analysing spectral cubes containing localized absorption signals of different types. The inverted-EEMD method is suitable for the analysis of spectral cubes where it can produce a cube containing the absorption signal and one containing the unabsorbed signal, where cold clouds can be identified as coherent regions in the absorption map.
Building a low budget planeterella for auroral outreach incorporating physics student co-creation principles
Authors: Whittaker Ian C , Elkan Ethan , Toms Ryan 
Published: December 2024

ABSTRACT
A planeterella (an auroral simulator) has been built at Nottingham Trent University within the cost of a student postgraduate Masters project budget (£100). This instrument is currently only the third working planeterella in the UK, and while not as sophisticated as it’s two older cousins, it still demonstrates the space physics principles at the same time as providing an educational and inspirational benefit. The final equipment has proved successful in engaging students, stakeholders, and the public with ‘seeing’ magnetic fields and auroral processes. The build requirements and method are provided to allow other higher education institutions to be able to create their own planeterella as scientific demonstrations and student projects; only requiring small budgets and common equipment borrowed from physics teaching and research laboratories.
Motherhood Penalty—Beyond Bias? From Stereotypes to Substitutability Structures
Authors: Halrynjo Sigtona , Mangset Marte 
Published: December 2024

Abstract
Mothers continue to experience lower wages and slower career progression than fathers. Are mothers penalized due to prejudice or due to the costs of family-friendly work conditions? Our review of experimental studies on motherhood bias reveals a paradox: implicit bias against mothers is evident in many US and European studies, but absent in Scandinavian experimental studies; yet, mothers still face a wage and career gap. We revisit explanations related to social structures and gendered work–family specialization, including Goldin’s theory of exponential rewards for time and availability. By reviewing longitudinal Scandinavian studies and exploring the role of individual competition in particular job markets, we offer a nuanced understanding of flexibility and substitutability. Finally, we outline a shift in the theoretical lens for examining and challenging the wage and career gap—from stereotypes to substitutability structures—and introduce a model predicting the relation between individualized versus collective substitutability structures and the degree of individual and/or gendered costs.
Inorganic arsenic modulates cell apoptosis by regulating Argonaute 2 expression via the p53 pathway
Authors: Du Kunyu , Shu Jingkui , Wu Jintao , Liu Na , Ma He , Jiang Jinyun , He Yuefeng , Wu Xinan 
Published: December 2024

Abstract
This study explores the role of Argonaute 2 (AGO2) in the induction of apoptosis by arsenic in 16HBE cells and investigates the association between AGO2 expression and arsenic exposure in a human population. By silencing AGO2 with siRNA, we examined its impact on cell viability and apoptosis using CCK-8, HO-PI, and JC-1 assays, complemented by qRT-PCR and Western blot analyses for gene and protein expressions. Our findings revealed a significant correlation between AGO2 expression and levels of exposure to inorganic arsenic (iAs), which was more pronounced than with other arsenic forms such as monomethylarsonic (MMA) and dimethylarsinic acids (DMA). The results showed that silencing AGO2 not only reduced cell viability but also intensified apoptosis, highlighting its role in activating the p53 pathway. This was further supported by increased phosphorylation of p53 at Ser392 and Thr55, reinforcing AGO2’s involvement in apoptotic processes. The study underscores the potential of AGO2 as a therapeutic target in arsenic-related pathologies and highlights the critical need for managing occupational exposure to arsenic.
Anti-M2-pyruvate kinase autoantibodies are correlated with digestive damage in human Chagas disease
Authors: da Silva Denis Dantas , Pereira Nathalie de Sena , Nunes Daniela Ferreira , Brito Ramayana Morais de Medeiros , Pereira Luanderson Cardoso , da Silva Andressa Noronha Barbosa , Brito Carlos Ramon do Nascimento , Andrade Cléber de Mesquita , Galvão Lúcia Maria da Cunha , da Câmara Antonia Claudia Jácome , Nascimento Manuela Sales Lima , Guedes Paulo Marcos Matta 
Published: December 2024

Abstract

Background
Determining esophageal and colon involvement in patients with Chagas disease occurs through invasive and uncomfortable examinations, which in most cases are not performed. The objective of this study was to assess the involvement of anti-M2-pyruvate kinase (M2-PK) autoantibodies in the development of digestive alterations and/or in the diagnosis of the digestive form of human Chagas disease.

Methods
The total IgG and isotype (IgG1, IgG2, IgG3, IgG4) production was quantified using the antigen of Trypanosoma cruzi and the human M2-PK recombinant protein via the ELISA technique. The tests were conducted with serum samples from patients with indeterminate, cardiac, digestive and cardiodigestive clinical forms of Chagas disease, and the results were correlated with the dilatation degree of the esophagus and colon.

Results
Patients with the digestive form of Chagas disease had higher IgG4 anti-M2-PK autoantibody production compared with patients with the indeterminate and cardiac forms and the healthy control group. Furthermore, a positive correlation was observed between sigmoid and rectum size with IgG4 anti-M2-PK autoantibody production.

Conclusions
These results demonstrate that IgG4 anti-M2-PK autoantibodies correlate with digestive damage in human Chagas disease, and their presence may also be implicated in the development of digestive lesions.
T-stage diagnosis of lung cancer based on deep learning in CT images
Authors: Fan Rutao , Chen Jincheng , Xu Shanshan , Wu Wei , Yi Jian , Zhang Nuoyu , Chang Miaoyi , Dong Xuanxuan , Chen Xizhu , Zou Yuxin , Li Xinwei , Wu Yi 
Published: December 2024

Objective:
To explore the advantages of Swin-Transformer (SwinT) network in T-staging diagnosis of lung cancer computed tomography (CT) images by comparing it with Res-Net, Vgg-Net, and Mobile-Net networks.

Methods:
CT images of a total of 176 patients with lung cancer confirmed by pathological biopsy were collected from the First Affiliated Hospital of Army Medical University between 2021 and 2023. Based on the patients’ pathological T-staging reports, the patients’ images were classified into 4 categories: T1, T2, T3, and T4, and all the patients were simply randomly divided into a training set (n = 123), a validation set (n = 18), and a test set (n = 35) in the ratio of 7∶1∶2 for training the intelligent T-staging diagnostic model, which was used for training the intelligent T-staging diagnostic model by using the accuracy, precision, confusion matrix, recall rate, F1 score (F1- Score), receiver operating haracteristic (ROC) curve, and area under the ROC curve (AUC) parameters to assess the diagnostic efficacy of the network.

Results:
In the four classifications of T1, T2, T3, and T4, the accuracy in the training set of Res-Net, Vgg-Net, Mobile-Net, and SwinT network models were 0.5278, 0.6111, 0.6389, and 0.7222, as well as the AUC was 0.7275, 0.7850, 0.7275, and 0.8650.the SwinT network model had the best combined results.

Conclusion:
Compared with Res-Net, Vgg-Net and Mobile-Net networks, SwinT network achieves the optimal prediction performance in the lung cancer CT image classification task, and can be used for the smart T-staging of lung cancer to be able to diagnose, to improve the diagnosis and treatment efficiency, to shorten the diagnosis time, and to save medical resources.
Comparable results for the Femoral Neck System and three-screw fixation in femoral neck fracture treatment
Authors: Honkanen Jukka , Forsbacka Nora , Strengell Ida , Laaksonen Inari , Mäkelä Keijo , Koivisto Mari , Huovinen Ville , Ekman Elina 
Published: December 2024

Abstract

Objectives:
To report outcomes of femoral neck fractures (FNFs) treated with Femoral Neck System (FNS) and to compare the risks of later conversion to arthroplasty for FNS and fixation with cannulated screws (CNSs).

Design:
A retrospective study.

Setting:
A single-center study (Turku University Hospital, Finland).

Patients:
Data on 51 patients with FNFs treated with FNS between January 1, 2019, and May 31, 2021, were retrospectively reviewed. In addition, data on 301 patients treated with cannulated screws were collected and analyzed in a previous study.

Intervention:
Patients with FNFs underwent osteosynthesis with FNS.

Main Outcome Measurements:
Patients' preoperative and postoperative radiographs were analyzed and measured to determine preoperative displacement, preoperative posterior tilt, and quality of reduction. Later conversion to arthroplasty and other reoperations were recorded. The risk of later conversion to arthroplasty was compared between the FNS group and CNS group.

Results:
The overall reoperation rate in the FNS group was 20%, and 16% of the patients treated with FNS underwent later conversion to arthroplasty. In the multivariate analysis, age, sex, and fracture displacement were not associated with increased risk of later conversion to arthroplasty. In comparison with fixation with cannulated screws, there was no statistically significant difference in the probability of later conversion to arthroplasty between the groups.

Conclusion:
FNS seems to have a comparable reoperation rate and conversion-to-arthroplasty rate compared with the gold standard treatment.

Level of Evidence:
III.
Toward Digital Twins in the Intensive Care Unit: A Medication Management Case Study
Authors: Eslami Behnaz , Afshar Majid , Tootooni M. Samie , Miller Timothy , Churpek Matthew , Gao Yanjun , Dligach Dmitriy 
Published: December 2024

ABSTRACTDigital twins, computational representations of individuals or systems, offer promising applications in the intensive care unit (ICU) by enhancing decision-making and reducing cognitive load. We developed digital twins using a large language model (LLM), LLaMA-3, fine-tuned with Low-Rank Adapters (LoRA) on physician notes from different ICU specialties in the MIMIC-III dataset. This study hypothesizes that specialty-specific training improves treatment recommendation accuracy compared to training on other ICU specialties. Additionally, we evaluated a zero-shot baseline model, which relied solely on contextual instructions without training. Discharge summaries were analyzed, and medications were masked to create datasets for model training and testing. The medical ICU dataset (1,000 notes) was used for evaluation, and performance was measured using BERTScore and ROUGE-L. LLMs trained on medical ICU notes achieved the highest BERTScore (0.842), outperforming models trained on other specialties or mixed datasets, while untrained zero-shot models showed the lowest performance. These results underscore the value of context-specific training for digital twins, offering foundational insights into LLMs for personalized clinical decision support.
A population model of age and gender specific cardiac troponin levels
Authors: Corlan Alexandru Dan 
Published: December 2024

AbstractThe range of the high-sensitivity cardiac troponin (HSCTN) values in the gen-eral population increases progressively with age, being several times higher in older patients, beyond 70 years old, than in younger ones, below 40.More accurate normal limits for HSCTN, taking into account age and gender, are needed for the differential diagnosis and evaluation of the prognostic signif-icance of increases that do not reach the vendor-supplied upper reference limits (URL).We performed an analysis of the high sensitivity cardiac troponin (HSCTN) of 21743 individuals, representative for the general US population, that were studied in the NHANES survey performed by the Center for Disease Control of the USA. The vendor supplied URL values are typically several times higher than the actual upper limit in subjects under 40 and correspond to the URL at ages between 51 and 84 for specific vendors and genders.For each HSCTN test variant, we considered each one year age group between 1 and 85 and either gender. The distribution of the logarithmed HSCTN for a given test variant and gender, in each subsamplei, is relatively close to Gaussian (N (µi, σi)). Two quadratic models, for the 1–15 and the 16–85 age ranges, were found to fit well with theµi, while theσifollow a linear model. These theoretical distributions can be used used to estimate any quantiles of the HSCTN distribution as functions of age and gender, including the upper reference limit (URL) for the HSCTN I and T in the general population.Consequently, it is possible to construct a calculated HSCTN indicator that represents the estimated age and gender specific centile in which a measurement with a specific test kit falls, or the percentual distance above the 99th centile. This indicator would be independent of age, gender and kit-vendor, and thus more accurate and easier to employ in clinical practice.
Dorsolateral prefrontal cortex TMS evokes responses in the subgenual anterior cingulate cortex: Evidence from human intracranial EEG
Authors: Trapp Nicholas T. , Liu Xianqing , Li Zhuoran , Bruss Joel , Keller Corey J. , Boes Aaron D. , Jiang Jing 
Published: December 2024

AbstractTranscranial magnetic stimulation combined with intracranial local field potential recordings in humans (TMS-iEEG) represents a new method for investigating electrophysiologic effects of TMS with spatiotemporal precision. We applied TMS-iEEG to the dorsolateral prefrontal cortex (dlPFC) in two subjects and demonstrate evoked activity in the subgenual anterior cingulate cortex (sgACC). This study provides direct electrophysiologic evidence that dlPFC TMS, as targeted for depression treatment, can modulate brain activity in the sgACC.