bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of exercise training on cognitive function in patients with COPD: a systematic review and meta-analysis of randomised controlled trials
Authors: Ding Kexin , Song Feiyun , Sun Wen , Sun Mingyun , Xia Rui 
Published: February 2025

ObjectiveThe aim of this study was to describe the characteristics of exercise therapies in randomised controlled trials (RCTs) targeted at improving cognitive function and to assess their efficacy in COPD.MethodsWe conducted a comprehensive search of eight databases, namely PubMed, Web of Science, Embase, Cochrane Library, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Wanfang and Weipu, covering the period from database construction to 23 April 2024. Our search specifically targeted RCTs studying the effects of exercise on cognitive functioning in COPD patients. Trials consisted of one or more exercise training interventions along with at least one cognitive outcome study. Two reviewers independently reviewed papers, extracted data and evaluated the research literature's quality using the Cochrane risk-of-bias assessment tool RoB 2.0 and the modified Jadad scale. Meta-analysis of Montreal Cognitive Assessment (MoCA) scores in the groups with and without exercise intervention was performed and subgroup analyses were undertaken to identify potential causes of heterogeneity.ResultsWe included a total of nine studies that included 578 COPD patients (69% male). Each study demonstrated that patients improved significantly in at least one cognitive component following training. All current research focuses on attention, executive function, motor ability, mental capacity, verbal fluency, visuoconstructive abilities and memory. The results revealed that exercise significantly improved MoCA scores in COPD patients (standardised mean difference (SMD) 0.576 (95% CI 0.054–1.097); p=0.029). A subgroup analysis of the duration of each intervention revealed that exercise training with an intervention duration of >30 min significantly improved overall cognitive performance in COPD patients (SMD 0.499 (95% CI −0.165–1.163); p=0.000, I2=0.0%). A subgroup analysis of varied intervention durations revealed that 4 weeks of exercise training significantly improved overall cognitive performance in COPD patients (SMD 0.202 (95% CI −0.238–0.641); p=0.000, I2=0.0%). In addition, just one study had a year-long follow-up period.ConclusionParticipation in exercise training, whether aerobic exercise alone or in combination with resistance or muscular strength, healthy qigong, dance or breathing exercises, can improve cognitive performance to varying degrees in people with COPD. Nonetheless, the findings should be regarded with caution due to the limitations of the included studies.
Nitidine chloride inhibits the progression of hepatocellular carcinoma by suppressing IGF2BP3 and modulates metabolic pathways in an m6A-dependent manner
Authors: Xiong Dan-dan , Chen Zhen-dong , Li Jian-di , Deng Yu-long , He Rong-quan , Huang Zhi-guang , An San-qi , Dang Yi-wu , Chen Gang 
Published: February 2025

Abstract

Background
Hepatocellular carcinoma (HCC) stands as a major health concern due to its significant morbidity and mortality. Among potential botanical therapeutics, nitidine chloride (NC) has garnered attention for its potential anti-HCC properties. However, the underlying mechanisms, especially the possible involvement of the m6A pathway, remain to be elucidated.

Methods
HCC cell and zebrafish xenograft models were utilized to validate the anti-HCC effects of NC. RNA-seq and MeRIP-seq analyses were performed to explore the potential targets and mechanisms of NC against HCC. The target effect of NC on IGF2BP3 was verified through RT-qPCR, WB, molecular docking, molecular dynamics (MD) simulation, surface plasmon resonance (SPR), and CCK8 off-target assays. Downstream target genes were confirmed using RNA stability assays.

Results
In this study, utilizing HCC cell and zebrafish xenograft models, we validated NC’s ability to inhibit the growth, metastasis, and angiogenesis of HCC. Subsequently, employing RNA sequencing, RT-qPCR, WB, molecular docking, MD simulation, SPR, and CCK8 off-target assays, we pinpointed IGF2BP3 as a direct target of NC. IGF2BP3 is highly expressed in HCC, and IGF2BP3 knockdown significantly inhibited the proliferation, migration and invasion of HCC cells. Further MeRIP-seq and RIP-seq revealed 197 genes interacting with IGF2BP3, downregulated at mRNA and m6A levels after NC treatment, primarily associated with multiple metabolism-related pathways. Through intersection analysis, we pinpointed 30 potential metabolic target genes regulated by NC through IGF2BP3. Based on the expression of these genes, the metabolic scores for each HCC patient were calculated. Our findings suggest that patients with high metabolic scores have poorer prognoses, and the metabolic score serves as an independent prognostic factor. Finally, RNA stability experiments confirmed CKB, RRM2, NME1, PKM, and UXS1 as specific metabolic target genes affected by NC/IGF2BP3, displaying reduced RNA half-life post IGF2BP3 downregulation.

Conclusion
Our study suggest that NC may exert its anti-HCC effects by downregulating IGF2BP3, inhibiting the m6A modification levels of metabolic-related genes, thereby reducing their stability and expression. Such insights provide a new direction in the study of NC’s anti-HCC mechanisms and offer novel perspectives for the treatment of HCC patients, focusing on both metabolic levels and m6A modification levels.
ROITP: Road Obstacle-Involved Trajectory Planner for Autonomous Trucks
Authors: Qin Yechen , Huang Yiwei , Yu Wenhao , Wang Hong 
Published: February 2025

Abstract
Autonomous trucks have the potential to enhance both safety and convenience in intelligent transportation. However, their maximum speed and ability to navigate a variety of driving conditions, particularly uneven roads, are limited by a high center of gravity, which increases the risk of rollover. Road bulges, sinkholes, and unexpected debris all present additional challenges for autonomous trucks' operational design, which current perception and decision-making algorithms often overlook. To mitigate rollover risks and improve adaptability to damaged roads, this paper presents a novel Road Obstacle-Involved Trajectory Planner (ROITP). The planner categorizes road obstacles using a learning-based algorithm. A discrete optimization algorithm selects a multi-objective optimal trajectory while taking into account constraints and objective functions derived from truck dynamics. Validation across various scenarios on a hardware-in-loop platform demonstrates that the proposed planner is effective and feasible for real-time implementation.
AMEND 2.0: module identification and multi-omic data integration with multiplex-heterogeneous graphs
Authors: Boyd Samuel S. , Slawson Chad , Thompson Jeffrey A. 
Published: February 2025

Abstract

Background
Multi-omic studies provide comprehensive insight into biological systems by evaluating cellular changes between normal and pathological conditions at multiple levels of measurement. Biological networks, which represent interactions or associations between biomolecules, have been highly effective in facilitating omic analysis. However, current network-based methods lack generalizability to accommodate multiple data types across a range of diverse experiments.

Results
We present AMEND 2.0, an updated active module identification method which can analyze multiplex and/or heterogeneous networks integrated with multi-omic data in a highly generalizable framework, in contrast to existing methods, which are mostly appropriate for at most two specific omic types. It is powered by Random Walk with Restart for multiplex-heterogeneous networks, with additional capabilities including degree bias adjustment and biased random walk for multi-objective module identification. AMEND was applied to two real-world multi-omic datasets: renal cell carcinoma data from The cancer genome atlas and an O-GlcNAc Transferase knockout study. Additional analyses investigate the performance of various subroutines of AMEND on tasks of node ranking and degree bias adjustment.

Conclusions
While the analysis of multi-omic datasets in a network context is poised to provide deeper understanding of health and disease, new methods are required to fully take advantage of this increasingly complex data. The current study combines several network analysis techniques into a single versatile method for analyzing biological networks with multi-omic data that can be applied in many diverse scenarios. Software is freely available in the R programming language at https://github.com/samboyd0/AMEND.
Fine-tuning GBS data with comparison of reference and mock genome approaches for advancing genomic selection in less studied farmed species
Authors: Fischer Daniel , Tapio Miika , Bitz Oliver , Iso-Touru Terhi , Kause Antti , Tapio Ilma 
Published: February 2025

Abstract

Background
Diversifying animal cultivation demands efficient genotyping for enabling genomic selection, but non-model species lack efficient genotyping solutions. The aim of this study was to optimize a genotyping-by-sequencing (GBS) double-digest RAD-sequencing (ddRAD) pipeline. Bovine data was used to automate the bioinformatic analysis. The application of the optimization was demonstrated on non-model European whitefish data.

Results
DdRAD data generation was designed for a reliable estimation of relatedness and is scalable to up to 384 samples. The GBS sequencing yielded approximately one million reads for each of the around 100 assessed samples. Optimizing various strategies to create a de-novo reference genome for variant calling (mock reference) showed that using three samples outperformed other building strategies with single or very large number of samples. Adjustments to most pipeline tuning parameters had limited impact on high-quality data, except for the identity criterion for merging mock reference genome clusters. For each species, over 15k GBS variants based on the mock reference were obtained and showed comparable results with the ones called using an existing reference genome. Repeatability analysis showed high concordance over replicates, particularly in bovine while in European whitefish data repeatability did not exceed earlier observations.

Conclusions
The proposed cost-effective ddRAD strategy, coupled with an efficient bioinformatics workflow, enables broad adoption of ddRAD GBS across diverse farmed species. While beneficial, a reference genome is not obligatory. The integration of Snakemake streamlines the pipeline usage on computer clusters and supports customization. This user-friendly solution facilitates genotyping for both model and non-model species.
A sarcopenia prediction model based on the calf maximum muscle circumference measured by ultrasound
Authors: Wei An , Zou Yan , Tang Zhen-Hua , Guo Feng , Zhou Yan 
Published: February 2025

Abstract

Background
The correlation between calf circumference（CC）and sarcopenia has been demonstrated, but the correlation between calf maximum muscle circumference (CMMC) measured by ultrasound and sarcopenia has not been reported. We aims to construct a predictive model for sarcopenia based on CMMC in hospitalized older patients.

Methods
This was a retrospective controlled study of patients > 60 years of age hospitalized in the geriatric department of Hunan Provincial People’s Hospital. The patients were thoroughly evaluated by questionnaires, laboratory, and ultrasound examinations, including measuring muscle thickness and calf muscle maximum circumference using ultrasound. Patients were categorized into sarcopenia and non-sarcopenia groups according to the consensus for diagnosis of sarcopenia recommended by the Asian Working Group on Sarcopenia 2019 (AWGS2). Independent predictors of sarcopenia were identified by univariate and multivariate logistic regression analyses, and a predictive model was developed and simplified. The prediction performance of the models was assessed using sensitivity, specificity, and area under the curve (AUC) and compared with independent predictors.

Results
We found that patient age, albumin level (ALB), brachioradialis muscle thickness (BRMT), gastrocnemius lateral head muscle thickness (Glh MT), and calf maximum muscle circumference (CMMC) were independent predictors of sarcopenia in hospitalized older patients. The prediction model was established and simplified to Logistic P = -4.5 + 1.4 × age + 1.3 × ALB + 1.6 × BR MT + 3.7 × CMMC + 1.8 × Glh MT, and the best cut-off value of the model was 0.485. The sensitivity, specificity, and AUC of the model were 0.884 (0.807–0.962), 0.837 (0.762–0.911), and 0.927 (0.890–0.963), respectively. The kappa coefficient between this model and the diagnostic criteria recommended by AWGS2 was 0.709.

Conclusion
We constructed a sarcopenia prediction model with five variables: age, ALB level, BR MT, Glh MT, and CMMC. The model could quickly predict sarcopenia in older hospitalized patients.
Case report of glomerular histiocytosis associated with non-crystalline IgG-kappa paraproteinemia
Authors: Kishore Aditya , McRae Susanna A. , Telio David , Beaulieu Monica C. 
Published: February 2025

Abstract

Background
Monoclonal gammopathy of renal significance (MGRS) represents a range of disease processes arising from monoclonal proteins depositing in the kidney. These deposits vary and can be broadly grouped as containing a substructure or being non-organised. Their clinical phenotype can include proteinuria, haematuria, kidney injury and tubulopathies resulting in electrolyte changes.

Case presentation
Crystal storing histiocytosis (CSH) is a rare form of MGRS that typically deposits in the interstitium but rarely in the glomerulus to cause progressive kidney disease. We report a case of a male with known monoclonal protein and progressive proteinuria, whose biopsy showed glomerular histiocytosis with non-crystallizing IgG kappa inclusions.

Conclusion
This case reviews an unusual case of a glomerular histiocytosis with non-crystallizing IgG kappa inclusions.
Prevalence of mental disorders and work ability among unemployed individuals in Germany: a register-based analysis of socio-medical assessments by the Federal Employment Agency between 2016 and 2021
Authors: Roser Patrik , Manz Kirsi , Scherbaum Norbert , Lotz-Metz Gabriele , Franke Andreas G. 
Published: February 2025

Abstract

Background
The interactions between unemployment and mental health are complex. However, broad and current epidemiological data about the mental health status of unemployed individuals in Germany are scarce. This study aimed to evaluate the prevalence rates of mental disorders and work ability among all unemployed people who underwent socio-medical assessment by the Federal Employment Agency (FEA).

Methods
Socio-medical assessments between 2016 and 2021 were taken from the FEA database and analyzed regarding sociodemographic characteristics, mental disorders and work ability. Standard descriptive statistics were used to analyze the data.

Results
A total of 4,249,028 unemployed individuals were assessed. Of these, 2,213,048 persons (52.1%) had at least one psychiatric diagnosis (mean age 40.6 ± 13.5 years, 51.7% female). Mood disorders (53.9%), neurotic, stress-related and somatoform disorders (43.9%), as well as substance use disorders (15.3%) showed the highest prevalence rates among mental disorders and accounted for about 80% of all psychiatric diagnoses. About 40% of them were evaluated to be able to work full time.

Conclusions
Psychiatric morbidity among unemployed people is high. However, a significant proportion of them was assessed to be able to return to the labor market. Therefore, close collaborations between unemployment agencies and mental health care institutions as well as specific re-integration programs including supported job placement and vocational training, long-term job coaching as well as integrated mental health care are required in order to improve mental health status, prevent further chronification, avoid labor market exit, and increase employment rate.
Patients’ preferences on atopic dermatitis skincare and social media use: a qualitative study
Authors: Mazilu Roxana , Ziehfreund Stefanie , Traidl Stephan , Zink Alexander 
Published: February 2025

Abstract

Background
Atopic dermatitis (AD) is a chronic inflammatory disease with a complex pathophysiology, necessitating strict therapeutic management. Over-the-counter products play a crucial role in AD treatment. The emergence of social media (SM) as a vast information source for skincare and healthy lifestyle has transformed its role from mere entertainment. This study aimed to explore the attitudes of AD patients towards SM as an information source for their AD products, understand their purchase behavior, and identify unmet needs.

Methods
Qualitative semi-structured interviews were conducted with AD patients recruited from a university hospital in Southern Germany and social media networks. The interviews took place between November 2022 and January 2023. The recorded interviews were transcribed verbatim and analyzed using Mayring’s qualitative content analysis.

Results
A total of ten patients (3 men, 7 women) aged 23–42 years were interviewed. Participants reported new perspectives in four categories: opportunities and advantages of SM as information source for AD products, risks and disadvantages, important aspects for patients’ choice of AD products, and extent and purpose of SM use in selecting AD skincare.

Conclusions
Patients exhibit diverse patterns of SM use when selecting daily products and critically evaluate the online content, demonstrating a greater trust in healthcare professionals or familial connections. Electronic word-of-mouth, disease severity and prior product experiences emerge as prevalent factors influencing patients’ product selection. Furthermore, female patients express interest in complementary and alternative therapies as part of an integrative therapeutical approach. Understanding patients’ needs and preferences regarding AD skincare can inform physicians in recommending more personalized therapies. Additionally, educational interventions on SM, addressing patients’ questions and concerns with evidence-based information, hold the potential for beneficial outcomes.
Association of ambient temperatures with suicide attempts and violence with the future projections under climate change scenarios: a nationwide time-stratified case-crossover study in South Korea
Authors: Park Jiwoo , Oh Jieun , Lee Whanhee , Kim Yeonsu , Park Jeong Ho , Kim Ho , Hwang Seungsik 
Published: February 2025

Abstract

Background
Both climate change and intentional injuries (suicide attempts and violence) are recognized as crucial factors that affect human health. Previous studies revealed the association between ambient temperatures and deaths due to intentional injuries but mostly about the consequences of severe events. Our study aimed to examine suicide attempts and violence incidence including mild and moderate cases with future projections, using each injury’s burden about climate change scenarios.

Methods
We collected nationally representative cases of suicide attempts (8,512 cases) and violence (9,742 cases) from the Korea National Hospital Discharge In-depth Injury Survey from 2005 to 2019. We performed a two-stage analysis with a time-stratified case-crossover design to evaluate the associations of outdoor temperatures with suicide attempts and violence using historical data (2005–2019). Based on the estimated associations in the historical period, we projected the excess suicide attempts and violence attributable to ambient temperatures in the future (2020–2099) using the three shared socioeconomic pathway (SSP) scenarios.

Results
We found positive associations between outdoor temperatures with suicide attempts and violence individually, and the association with violence was more linear. The excess suicide attempts attributable to temperatures in the historical period were around 11%, and it was expected to increase in all SSP scenarios (up to 14.35%). For violence, the excess risk of violence attributable to temperatures in the historical period was around 3.5%, and it was also estimated to increase in the future (up to 7.92%).

Conclusions
The nationwide study about South Korea shows that there are associations between an increase in outdoor temperatures and increased risks of suicide attempts and violence, and each excess injury related to temperature is projected to grow under the SSP scenarios. Our findings might provide informative evidence for relevant action plans against climate change and intentional injuries.
A ribodepletion and tagging protocol to multiplex samples for RNA-seq based virus detection: application to the cassava virome
Authors: Otron Daniel H. , Pita Justin S. , Hoareau Murielle , Tiendrébéogo Fidèle , Lett Jean-Michel , Lefeuvre Pierre 
Published: February 2025

Abstract

Background
Cassava (Manihot esculenta, Crantz), is a staple food and the main source of calories for many populations in Africa, but the plant is beset by several damaging viruses. So far, eight families of virus infecting cassava have been identified; the Geminiviridae (ssDNA viruses responsible for cassava mosaic disease, CMD) and Potyviridae (ssRNA + viruses responsible for cassava brown streak disease, CBSD) families being the most damaging to cassava in Africa. In several cassava-growing regions, the co-existence of species and strains from these two families results in a complex epidemiological situation making it difficult to correctly identify the viruses in circulation and delaying the implementation of disease management schemes. Nevertheless, the development of next generation sequencing (NGS) methods has revolutionized plant virus detection and identification. One NGS method that has been successfully used in virus detection and identification is ribodepleted RNA sequencing. Unfortunately, the relatively high cost makes it difficult to upscale this method to large epidemiological surveys and limits its adoption as a diagnostic tool.

Results
Here, we develop a high-throughput sequencing protocol, named Ribo-M-Seq, that combines plant rRNA ribodepletion, cDNA synthesis, tagging with a 96 multiplexing scheme and Illumina sequencing. We evaluated the protocol on a series of cassava samples with a known assemblage of viruses. After confirming that the protocol was suitable for ribodepletion, we demonstrated it was possible to detect RNA and DNA viruses via identification of near full-size genomes. Additional phylogenetic analyses confirmed the presence of begomoviruses and ipomoviruses responsible for CMD and CBSD, respectively. We also detected a recently described ampelovirus (Manihot esculenta-associated virus) that was not detected in previous analyses.

Conclusions
The use of the Ribo-M-Seq protocol will pave the way for large-scale sample analyses of collections with potentially complex viromes, such as those collected in the West African cassava integrated pest management program.