bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional MRI reveals regional changes of brain activity after five days of focal high-density theta burst stimulation (hdTBS) of the rat brain
Authors: Li Charlotte Qiong , Hoffman Samantha , Nguyen Hieu , Carney Aidan , Duan Ying , Ma Zilu , Zhang Nanyin , Yang Yihong , Lu Hanbing 
Published: September 2024

AbstractBackgroundThe therapeutic effects of transcranial magnetic stimulation (TMS) likely stem from neuroplasticity induced by repeated sessions over time. While animal models offer insights into TMS-induced plasticity, a rodent model that faithfully replicates prolonged TMS conditions in humans is still lacking.Objective/HypothesisDevelop a rat model that mimics the spatial and temporal patterns of TMS in humans.MethodsExperiments were conducted on two cohorts of healthy adult rats (N=33). In cohort 1, rats underwent surgical implantation of microelectrodes for motor evoked potential (MEP) recording. With a rodent-specific coil and the high-density theta burst stimulation (hdTBS) paradigm, under awake condition, rats received daily TMS at 100% motor threshold for five days (days 1-5) to the hindlimb motor cortex. Cortical excitability was measured by input-output (I-O) curves on Day 0 (pre-hdTBS baseline) and Day 6 (post-hdTBS). The second cohort received identical TMS and underwent fMRI to map cerebral blood volume (CBV) on Days 0 and 6.ResultsDaily hdTBS session for 5 days significantly up-shifted I-O curves only in the TMS group (N=9), not in the sham group (N=7), indicating enhanced cortical excitability. fMRI data showed that, compared to sham group (N=9), rats receiving hdTBS (N=8) had increased basal CBV in several brain regions proximal and distal to the stimulation site, suggesting enhanced basal metabolism.Conclusion(s)Daily hdTBS session for 5 days focally delivered to the motor cortex of naïve rats significantly altered basal brain activity in a network of brain regions, opening a novel platform for further investigating TMS-induced plasticity.
DuReS: An R package for denoising experimental tandem mass spectrometry-based metabolomics data
Authors: Banerjee Shayantan , Nakrani Prajval , Singh Aviral , Wangikar Pramod P. 
Published: September 2024

AbstractMass spectrometry-based untargeted metabolomics is a powerful technique for profiling small molecules in biological samples, yet accurate metabolite identification remains challenging. One of the primary obstacles in processing tandem mass spectrometry data is the prevalence of random noise peaks, which can result in false annotations and necessitate labor-intensive verification. A common method for removing noise from MS/MS spectra is intensity thresholding, where low-intensity peaks are discarded based on a user-defined cutoff or by analyzing the top “N” most intense peaks. However, determining an optimal threshold is often dataset-specific and may retain many noisy peaks. In this study, we hypothesize that true signal peaks consistently recur across replicate MS/MS spectra generated from the same precursor ion, unlike random noise. An optimal recurrence frequency of 0.12 (95% CI: 0.087-0.15) was derived using an open-source metabolomics dataset, which enhanced the dot product score between the experimental and library spectra by 66% post-denoising and resulted in a median signal and noise reduction of 5.83% and 99.07%, respectively. Validated across multiple metabolomics datasets, our denoising workflow significantly improved spectral matching metrics, leading to more accurate annotations and fewer false positives. Available freely as an R package, Denoising Using Replicate Spectra (DuReS) (https://github.com/BiosystemEngineeringLab-IITB/dures) is designed to remove noise while retaining diagnostically significant peaks efficiently. It accepts mzML files and feature lists from standard global untargeted metabolomics analysis software as input, enabling users to seamlessly integrate the denoising pipeline into their workflow without additional data manipulation.
Whole Genome Sequencing and single-cell transcriptomics identifyKMT2Das a potential new driver for pituitary adenomas
Authors: Brunner Maxime , Meylan-Merlini Jenny , Muriset Maude , Oreshkov Sergey , Messina Andrea , Messerer Mahmoud , Daniel Roy , Hewer Ekkehard , Brouland Jean Phillipe , Santoni Federico 
Published: September 2024

AbstractThe pituitary gland is a main component of the endocrine system and a master controller of hormone production and secretion. Unlike neoplastic formation in other organs, Pituitary Neuroendocrine Tumors (PitNETs) are frequent in the population (16%) and, for unknown reasons, almost exclusively benign. So far, few genes have been identified as drivers for PitNETs, such asGNASin somatotroph tumors andUSP8in corticotroph tumors. Using whole genome sequencing, we uncover a potential novel driver, the histone methyltransferaseKMT2D, in a patient in his 50s suffering from a mixed somato-lactotroph tumor. Coverage ratio between germline and tumor revealed extensive chromosomal alterations. Single-cell RNA sequencing of the tumor shows up-regulation of known tumorigenic pathways compared to a healthy reference, as well as a different immune infiltration profile compared to other PitNETs, more closely resembling the profile of carcinomas than adenomas. Genome-wide DNA methylation analysis identified 792 differentially methylated regions, including notable hypomethylation in the promoter ofSPON2, an immune-related gene. Our results show that tumors considered as quiet and non-aggressive can share drivers, features, and epigenetic alterations with metastatic forms of cancer, raising questions about the biological mechanisms controlling their homeostasis.
Acute Viral Infection Accelerates Neurodegeneration in a Mouse Model of ALS
Authors: Marzok Art , Mapletoft Jonathan P. , Cowbrough Braeden , Celeste Daniel B. , D’Agostino Michael R. , Ang Jann C. , Chen Andrew T. , Surendran Vithushan , Dvorkin-Gheva Anna , Zhang Ali , Stacey Hannah D. , Lam Mannie , Kollar Yasmine , Milnes Kevin R. , Afkhami Sam , Miller Matthew S. 
Published: September 2024

SummaryWhile several viral infections have been associated with amyotrophic lateral sclerosis (ALS), the mechanism(s) through which they promote disease has remained almost entirely elusive. This study investigated the impact of common, acute viral infections prior to disease onset on ALS progression in the SOD1G93Amouse model. A single sublethal infection prior to onset of ALS clinical signs was associated with markedly accelerated ALS disease progression characterized by rapid loss of hindlimb function. Prior infection resulted in gliosis in the lumbar spine and upregulation of transcriptional pathways involved in inflammatory responses, metabolic dysregulation, and muscular dysfunction. Therapeutic suppression of gliosis with an anti-inflammatory small molecule, or administration of a direct-acting antiviral, was associated with significantly improved ALS clinical signs, akin to what was observed in uninfected animals. This study provides causal and mechanistic evidence that the immune response elicited by acute viral infections may be an important etiological factor that alters ALS disease trajectory, and provides insight into novel therapeutic and preventative strategies for ALS.One Sentence SummaryAcute viral infection with influenza A virus and SARS-CoV-2 accelerates the progression of ALS in SOD1G93Amice.
Obstetric anal sphincter injuries detection by digital rectal examination and impedance spectroscopy: post-hoc analysis of the results from a prospective, comparative, multicentre clinical study
Authors: Salvatore Stefano , Borycka Katarzyna , Ruffolo Alessandro , Młyńczak Marcel , Rosoł Maciej , Korzeniewski Kacper , Iwanowski Piotr , Spinelli Antonino , de Tayrac Renaud , Ratto Carlo , Athanasiou Stavros , Rizk Diaa Essameldin Ali , Stuart Andrea , Baekelandt Jan , Heřman Hynek , Janku Petr , Rosenblat Peter , Franco Rita , Grzesiak Mariusz , Dziki Adam , Fernando Ruwan 
Published: September 2024

AbstractObjectiveTo evaluate the clinical performance of digital rectal examination (DRE) and machine learning-assisted impedance spectroscopy (ONIRY) for detecting obstetric anal sphincter injuries (OASI) compared to three-dimensional endoanal ultrasound (EAUS).DesignA post-hoc analysis of data from a prospective, comparative, multicentre, international study (NCT04903977).SettingPoland, Czech Republic, Slovakia, and Spain.Population152 vaginally delivered women to 8 weeks post-partum.MethodsParticipants were divided into two groups based on EAUS results: Group I (no OASI, including 1st and 2nd degree perineal tears per OASIS classification) and Group II (OASI, including 3rd and 4th-degree tears per OASIS classification). DRE and impedance measurements using the ONIRY system were performed. The machine learning (ML) model for ONIRY was trained and validated. The diagnostic outcomes of ONIRY and DRE were compared to EAUS.Main Outcome MeasuresAccuracy, sensitivity, and specificity.ResultsDRE’s performance versus EAUS was 67.8% for accuracy, 44.3% for sensitivity, and 83.5% for specificity. After completion of ML model training, impedance spectroscopy’s accuracy, sensitivity, and specificity were 87.0%, 90.6%, and 84.6%, respectively, compared with EAUS.ConclusionDRE is insufficient for OASI detection. The ML-assisted impedance spectroscopy demonstrated higher accuracy and could facilitate rapid OASI detection post-delivery.FundingThe study was financed by the European Union’s Fast Track program through the Polish National Centre for Research and Development (POIR.01.01.01-00-0726/18)
Evaluating and Reducing Subgroup Disparity in AI Models: An Analysis of Pediatric COVID-19 Test Outcomes
Authors: Libin Alexander , Treitler Jonah T. , Vasaitis Tadas , Shao Yijun 
Published: September 2024

AbstractArtificial Intelligence (AI) fairness in healthcare settings has attracted significant attention due to the concerns to propagate existing health disparities. Despite ongoing research, the frequency and extent of subgroup fairness have not been sufficiently studied. In this study, we extracted a nationally representative pediatric dataset (ages 0-17, n=9,935) from the US National Health Interview Survey (NHIS) concerning COVID-19 test outcomes. For subgroup disparity assessment, we trained 50 models using five machine learning algorithms. We assessed the models’ area under the curve (AUC) on 12 small (<15% of the total n) subgroups defined using social economic factors versus the on the overall population. Our results show that subgroup disparities were prevalent (50.7%) in the models. Subgroup AUCs were generally lower, with a mean difference of 0.01, ranging from -0.29 to +0.41. Notably, the disparities were not always statistically significant, with four out of 12 subgroups having statistically significant disparities across models. Additionally, we explored the efficacy of synthetic data in mitigating identified disparities. The introduction of synthetic data enhanced subgroup disparity in 57.7% of the models. The mean AUC disparities for models with synthetic data decreased on average by 0.03 via resampling and 0.04 via generative adverbial network methods.
DNFE: Directed-network flow entropy for detecting the tipping points during biological processes
Authors: Peng Xueqing , Li Peiluan , Luonan Chen 
Published: September 2024

ABSTRACTThere generally exists a critical state or tipping point from a stable state to another in dynamic biological processes, beyond which a significant qualitative transition occurs. Identifying this tipping point and its driving network is essential to prevent or delay catastrophic consequences. However, most traditional approaches based on undirected networks still suffer from the problem of the robustness and effectiveness when applied to high-dimensional small sample data, especially for single-cell data. To address this challenge, we developed a directed-network flow entropy (DNFE) method which can transform measured omics data into a directed network. This method is applicable to both single-cell RNA-sequencing (scRNA-seq) and bulk data. By applying this method to five real datasets, including three single-cell datasets and two bulk tumor datasets, the method can not only successfully detect the critical states as well as their dynamic network biomarkers, but also help explore regulatory relationships between genes. Numerical simulation indicates that the DNFE method is robust and superior to existing methods. Furthermore, DNFE has predicted active transcription factors (TFs), and further identified ‘dark genes’, which are usually overlooked by traditional methods.
Impact of the inoculum size on thein vivoactivity of the aztreonam-avibactam combination in a murine model of peritonitis due toEscherichia coliexpressing CTX-M-15 and NDM-1
Authors: Benchetrit Laura , Amoura Ariane , Chosidow Samuel , Menestrel Alice Le , de Lastours Victoire , Chau Françoise , Dion Sara , Massias Laurent , Fantin Bruno , Lefort Agnès 
Published: September 2024

AbstractBackgroundThe combination of aztreonam (ATM) and avibactam (AVI) is an attractive option to treat infections caused by extended spectrumβ-lactamase plus NDM-1-producingEnterobacteriaceae. Since ATM activity was shown to be severely impacted by an increase in the inoculum sizein vitro, we wondered whether ATM-AVI activity could be impaired in high-inoculum infections.MethodsWe analyzed the impact of the inoculum size on ATM-AVI activityin vitroand in a murine model of peritonitis due to susceptibleE. coliCFT073-pTOPO and its isogenic derivatives producing NDM-1 (E. coliCFT073-NDM1) and CTX-M-15 plus NDM-1 (E. coliCFT073-CTXM15-NDM1). The impact of the inoculum size on bacterial morphology was studied by microscopic examination.ResultsIn vitro, at standard (105) inoculum,E. coliCFT073-CTXM15-NDM1 was resistant to ATM but susceptible to the ATM-AVI combination. At high (107) inoculum, MICs of ATM alone and of the ATM-AVI combination reached > 512 and 64 mg/L respectively, against all tested strains. ATM led to bacterial filamentation when active against the bacteria, i.e., in monotherapy or in combination with AVI against susceptibleE. coliCFT073-pTOPO, and only in combination with AVI againstE. coliCFT073-CTXM15-NDM1.In vivo, increase in the inoculum led to a drastic decrease in the activity of ATM alone againstE. coliCFT073-pTOPO, and of ATM-AVI againstE. coliCFT073-CTXM15-NDM1.ConclusionOur results suggest a highin vivoimpact of the inoculum increase on the activity of ATM alone against ATM-susceptibleE. coli, and of ATM-AVI against CTX-M-15 plus NDM-1 producingE. coli. Clinicians must be aware of the risk of failures when using AZT-AVI in high inoculum infections.
DNA-templated spatially controlled proteolysis targeting chimeras for CyclinD1-CDK4/6 complex protein degradation
Authors: Zheng Rong , Prasad Abhay , Satyabola Deeksha , Xu Yang , Yan Hao 
Published: September 2024

AbstractConstraining proximity-based drugs, such as proteolysis-targeting chimeras (PROTACs), into its bioactive conformation can significantly impact their selectivity and potency. However, traditional methods for achieving this often involve complex and time-consuming synthetic procedures. Here, we introduced an alternative approach by demonstrating DNA-templated spatially controlled PROTACs (DTACs), which leverage the programmability of nucleic-acid based self-assembly for efficient synthesis, providing precise control over inhibitors’ spacing and orientation. The resulting constructs revealed distance- and orientation-dependent selectivity and degradation potency for the CyclinD1-CDK4/6 protein complex in cancer cells. Notably, an optimal construct DTAC-V1 demonstrated the unprecedented synchronous degradation of entire CyclinD1-CDK4/6 complex. This resulted in the effective cell cycle arrest in G1 phase, and further therapeutic studies showed its potent anti-tumor effects compared to inhibitors alone. These findings present a novel framework for PROTACs design, offering critical insights that may inform the development of other proximity-induced therapeutic modalities.
Addiction recovery stories: Dylan Suttie in conversation with Lisa Ogilvie
Authors: Suttie Dylan , Ogilvie Lisa 
Published: September 2024

Purpose
The purpose of this paper is to examine recovery through lived experience. It is part of a series that explores candid accounts of addiction and recovery to identify important components in the recovery process.

Design/methodology/approach
The G-CHIME model comprises six elements important to addiction recovery (growth, connectedness, hope, identity, meaning in life and empowerment). It provides a standard against which to consider addiction recovery. It has been used in this series, as well as in the design of interventions that improve well-being and strengthen recovery. In this paper, a first-hand account is presented, followed by a semi-structured e-interview with the author of the account. Narrative analysis is used to explore the account and interview through the G-CHIME model.

Findings
This paper shows that addiction recovery is a remarkable process that can be effectively explained using the G-CHIME model. The significance of each component in the model is apparent from the account and e-interview presented.

Originality/value
Each account of recovery in this series is unique, and as yet, untold.
Stability analysis of flying wing layout aircraft based on radial basis function neural network model
Authors: Zhang Wenqi , Liu Zhenbao , Wang Xiao , Wang Luyao 
Published: September 2024

Purpose
To ensure the stability of the flying wing layout unmanned aerial vehicle (UAV) during flight, this paper uses the radial basis function neural network model to analyse the stability of the aforementioned aircraft.

Design/methodology/approach
This paper uses a linear sliding mode control algorithm to analyse the stability of the UAV's attitude in a level flight state. In addition, a wind-resistant control algorithm based on the estimation of wind disturbance with a radial basis function neural network is proposed. Through the modelling of the flying wing layout UAV, the stability characteristics of a sample UAV are analysed based on the simulation data. The stability characteristics of the sample UAV are analysed based on the simulation data.

Findings
The simulation results indicate that the UAV with a flying wing layout has a short fuselage, no tail with a horizontal stabilising surface and the aerodynamic focus of the fuselage and the centre of gravity is nearby, which is indicative of longitudinal static instability. In addition, the absence of a drogue tail and the reliance on ailerons and a swept-back angle for stability result in a lack of stability in the transverse direction, whereas the presence of stability in the transverse direction is observed.

Originality/value
The analysis of the stability characteristics of the sample aircraft provides the foundation for the subsequent establishment of the control model for the flying wing layout UAV.
Supply chain risk management (SCRM) process: an analysis in the aerospace industry
Authors: Guerra João Henrique Lopes , Bernardi de Souza Fernando , Pires Silvio R. I. , Salgado Manoel Henrique , Sá Anderson Luiz Ribeiro de 
Published: September 2024

PurposeThe study analysed the aerospace industry, a traditionally important sector for the topic of risk management, from three complementary perspectives: the supply chain risks present in the sector, the mitigation strategies adopted to face them, and the characteristics (dimensions) observed in the SCRM process of aerospace companies.Design/methodology/approachThe research employed a quali–quantitative method: a survey was carried out, followed by interviews with professionals from companies belonging to different tiers of aerospace supply chains. Interviews helped to interpret the survey data and understand in more detail risk management in aerospace companies.FindingsThe study presents a panorama of the aerospace industry in terms of risk management. The sector’s turbulent environment is described as well as the strategies to prevent, minimise or postpone the impact of supply chain risks. In particular, ten dimensions that have been identified in the SCRM process of aerospace firms are discussed. These characteristics influence the objectives of this process and are related to resources, roles and responsibilities, incentives, development of competences and skills, scope (internal and external) and approaches to integrate decisions and actions in the context of the supply chain.Originality/valueArticles that address the SCRM process usually focus on the process steps, whereas this study investigated dimensions that transcend these steps but whose discussion in the literature is still fragmented. It also analysed a reference sector for the topic from a broader perspective than others available in the literature (supply chain risks, mitigation strategies and characteristics of the SCRM process). Supply chain members with relationships with each other were investigated, a desirable approach for SCRM but still under-explored. The study also answers calls for industry-specific studies and research on emerging countries.
How knowledge-based HRM practices affects aspects of innovation capability through knowledge management: the moderating role of innovative culture
Authors: Nguyen Lien Thi , Le Phong Ba 
Published: September 2024

Purpose
Given the important of knowledge resource and human capital for improving innovation competence, the purpose of this study is to examine the influence of knowledge-based HRM practices on product and process innovation of firms via the mediating role of knowledge management capability and moderating role of innovative culture.

Design/methodology/approach
The paper used structural equation modeling and empirical data collected from 271 participants in 156 manufacturing and service firms to examine the level of how knowledge-based HRM practices and knowledge management affect product and process innovation under the moderating role of innovative culture.

Findings
The research findings confirm the mediating roles of knowledge management between knowledge-based HRM practices and two specific types of innovation namely product and process innovation. It also firstly reveals the positive moderating role of innovative culture in enhancing the effects of knowledge management on product innovation. The results underline the necessity of building an innovative climate and knowledge-based HRM practices to stimulate knowledge management for improving innovation capability of firms in the developing and emerging markets.

Research limitations/implications
The paper helps bring deeper insights to leaders and practitioners about the new knowledge-based approach that enhances innovation competence for organizations.

Originality/value
The paper significantly contributed to theoretical and practical initiatives on theory of HRM practices and knowledge management by showing different moderating and mediating mechanism thereby firms can follow to enhance innovation capability of firms in developing and emerging markets.