bluuebunny/crossref_metadata_2025_split huggingface dataset:
DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure
Authors: Tang Wenwu , Wang Zhixin , Yuan Xinzhu , Chen Liping , Guo Haiyang , Qi Zhirui , Zhang Ying , Xie Xisheng 
Published: January 2025

IntroductionHeart failure (HF) has a very high prevalence in patients with maintenance hemodialysis (MHD). However, there is still a lack of effective and reliable HF diagnostic markers and therapeutic targets for patients with MHD.MethodsIn this study, we analyzed transcriptome profiles of 30 patients with MHD by high-throughput sequencing. Firstly, the differential genes between HF group and control group of patients with MHD were screened. Secondly, HF-related genes were screened by WGCNA, and finally the genes intersecting the two were selected as candidate genes. Machine learning was used to identify hub gene and construct a nomogram model, which was verified by ROC curve and RT-qPCR. In addition, we further explored potential mechanism and function of hub genes in HF of patients with MHD through GSEA, immune cell infiltration analysis, drug analysis and establishment of molecular regulatory network.ResultsTotally 23 candidate genes were screened out by overlapping 673 differentially expressed genes (DEGs) and 147 key module genes, of which four hub genes (DEPDC1B, CDCA2, APOBEC3B and TYMS) were obtained by two machine learning algorithms. Through GSEA analysis, it was found that the four genes were closely related to ribosome, cell cycle, ubiquitin-mediated proteolysis. We constructed a ceRNA regulatory network, and found that 4 hub genes (TYMS, CDCA2 and DEPDC1B) might be regulated by 4 miRNAs (hsa-miR-1297, hsa-miR-4465, hsa-miR-27a-3p, hsa-miR-129-5p) and 21 lncRNAs (such as HCP5, CAS5, MEG3, HCG18). 24 small molecule drugs were predicted based on TYMS through DrugBank website. Finally, qRT-PCR experiments showed that the expression trend of biomarkers was consistent with the results of transcriptome sequencing.DiscussionOverall, our results reveal the molecular mechanism of HF in patients with MHD and provide insights into potential diagnostic markers and therapeutic targets.
Surface movement and crack development laws of super-long working faces in medium-depth coal seam mining
Authors: Hou Pengfei , Wang Shuangming , Feng Dong , Xie Xiaoshen , Hou Enke 
Published: January 2025

IntroductionWith the increased application of super-long working faces in coal mining, the surface movement and crack development laws of super-long working faces present an urgent problem to be studied and solved. This study aimed to determine the surface movement and crack development laws of super-long working faces when mining medium-depth buried coal seams.MethodsThe research area in Xiaobaodang No. 2 coal mine, China, was the adjacent working faces 01, 02 and 03, with inclination widths of 300 m and 450 m, respectively. The laws were determined by applying methods such as manual surface movement observation, GNSS automatic surface movement observation, surface crack observation, and crack morphology tracing.ResultsCompared to the working face with an inclination width of 300 m, the maximum subsidence, maximum horizontal movement value, and maximum subsidence coefficient of the super-long working face with an inclination width of 450 m increased by 15.31%, 4.56%, and 16.13%, respectively. Under the influence of mining the 02 working face, the maximum subsidence of the 01 working face increased by 15% and the surface subsidence patterns of the 01 and 02 working face inclination observation lines showed an asymmetric W shape.DiscussionThe widths of the cracks parallel to the open-off cut followed the dynamic development law of opening first, then closing or semi-closing. The widths of the cracks parallel to grooves followed the dynamic development law of opening first, then remaining open. The study results are important to protect mining buildings and the ecological environment.
Integration of single-cell transcriptomics and bulk transcriptomics to explore prognostic and immunotherapeutic characteristics of nucleotide metabolism in lung adenocarcinoma
Authors: Zhang Kai , Wang Luyao , Chen Huili , Deng Lili , Hu Mengling , Wang Ziqiang , Xie Yiluo , Lian Chaoqun , Wang Xiaojing , Zhang Jing 
Published: January 2025

BackgroundLung adenocarcinoma (LUAD) is a highly aggressive tumor with one of the highest morbidity and mortality rates in the world. Nucleotide metabolic processes are critical for cancer development, progression, and alteration of the tumor microenvironment. However, the effect of nucleotide metabolism on LUAD remains to be thoroughly investigated.MethodsTranscriptomic and clinical data of LUAD were downloaded and organized from TCGA and GEO databases. Genes related to nucleotide metabolism were downloaded from the Msigdb database. Genes associated with LUAD prognosis were identified using univariate COX analysis, and a prognostic risk model was constructed using the machine learning combination of Lasso + Stepcox. The model’s predictive validity was evaluated using KM survival and timeROC curves. Based on the prognostic model, LUAD patients were classified into different nucleotide metabolism subtypes, and the differences between patients of different subtypes were explored in terms of genomic mutations, functional enrichment, tumor immune characteristics, and immunotherapy responses. Finally, the key gene SNRPA was screened, and a series of in vitro experiments were performed on LUAD cell lines to explore the role of SNRPA in LUAD.ResultLUAD patients could be accurately categorized into subtypes based on the nucleotide metabolism-related prognostic risk score (NMBRS). There were significant differences in prognosis between patients of different subtypes, and the NMBRS showed high accuracy in predicting the prognosis of LUAD patients. In addition, patients of different subtypes showed significant differences in genomic mutation and functional enrichment and exhibited different anti-tumor immune profiles. Importantly, NMBRS can be used to predict the responsiveness of LUAD patients to immunotherapy. The results of in vitro cellular experiments indicate that SNRPA plays an important role in the development and progression of lung adenocarcinoma.ConclusionThis study comprehensively reveals the prognostic value and clinical application of nucleotide metabolism in LUAD. A prognostic signature constructed based on genes related to nucleotide metabolism accurately predicted the prognosis of LUAD patients, and this signature can be used as a guide for LUAD immunotherapy.
Changes in health related quality of life in mothers with inflammatory joint disease from year 2000 to 2020 – a comparative cross-sectional study
Authors: Koksvik Hege Svean , Nilssen Ingrid , Jakobsen Bente , Bjørngaard Hilde , Wallenius Marianne , Grønning Kjersti 
Published: January 2025

ObjectivesMore knowledge about health related quality of life (HRQoL) among mothers with inflammatory joint disease (IJD) is needed to understand the complex challenges for this group of patients. The overall aim of this study was to investigate changes in HRQoL among mothers with IJD from year 2000 to year 2020.MethodsThis study had a comparative cross-sectional design with two study groups 20 years apart, year 2000 (n = 77) and year 2020 (n = 197). Patients were identified from RevNatus, a Norwegian nationwide medical quality register (2020 cohort) and from a national centre for pregnancy and rheumatic disease (2000 cohort). Mothers with the diagnoses of rheumatoid arthritis, juvenile idiopathic arthritis, axial spondyloarthritis and psoriatic arthritis with children aged 0–6 were included. Data on HRQoL were self-reported and assessed by the RAND-36 (SF-36) questionnaire, along with data on educational status, number of children, months since last childbirth and eight questions on experienced motherhood limitations and experienced anxiety and distress for the children. Descriptive statistics were performed using the Mann-Whitney U-test, the Pearson chi-squared test and independent samples t-test. Multivariable linear regression were used to investigate changes and association between the RAND36 (SF-36) scores and the two study groups and possible confouders.ResultsThe 2020 cohort had significantly higher scores on bodily pain (p &lt; 0.001), physical function (p &lt; 0.001), and role physical (p = 0.01) scales compared to the 2000 cohort, indicating better health. There were no significant differences between the two cohorts in the mental health (MH) (p = 0.81), vitality (p = 0.09), general health (p = 0.06), social function (p = 0.83), and role emotional (p = 0.93) scales. Compared to the calculated norm scores, the 2020 cohort had significantly lower scores on all scales (p &lt; 0.01) except on the MH scale (p = 0.37).ConclusionMothers with IJD were affected in most dimensions of RAND-36 (SF-36) both in year 2000 and year 2020. The findings emphasize the importance of understanding the intrusiveness of being a mother with IJD despite the improved medical treatment options over the last 20 years.
Col1A1 as a new decoder of clinical features and immune microenvironment in ovarian cancer
Authors: Xiao Xiao , Long Fangyi , Yu Shaolan , Wu Wengjuan , Nie Dayan , Ren Xiaoyan , Li Wen , Wang Xujuan , Yu Ling , Wang Pinghan , Wang Gang 
Published: January 2025

BackgroundsCollagen type I alpha 1 chain (COL1A1) is a key protein encoding fibrillar collagen, playing a crucial role in the tumor microenvironment (TME) due to its complex functions and close association with tumor invasiveness. This has made COL1A1 a focal point in cancer biology research. However, studies investigating the relationship between COL1A1 expression levels and clinical characteristics of ovarian cancer (OC) remain limited.MethodsThis study integrated resources from publicly available online databases and immunohistochemistry (IHC) techniques to analyze and validate COL1A1 expression in OC tissues, and evaluated its potential association with clinical features in OC patients. The prognostic value of COL1A1 was assessed using Kaplan-Meier (KM) survival curve analysis. The TIMER and TISIDB databases to explore the potential relationship between COL1A1 expression and immune microenvironment in OC tissues. The LinkedOmics and INPUT2 databases were used to analyze differential gene expression in OC, This was followed by enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) annotations to identify and predict potential signaling pathways associated with COL1A1.ResultsOur study demonstrated that COL1A1 expression was significantly elevated in OC tissues compared to normal ovarian tissues. This elevated expression was closely associated with tumor metastasis, poor prognosis, and advanced pathological stages in OC patients. Moreover, COL1A1 expression showed a significant correlation with immune cell infiltration and the expression of immune-related genes within the TME.Further analyses revealed that COL1A1 and its co-expressed genes were primarily enriched in key signaling pathways involved in OC invasion, metastasis, and angiogenesis, indicating its potential role in driving OC progression.ConclusionsOur study found that upregulation of COL1A1 expression is significantly associated with lymph node metastasis of OC and can affect the immune microenvironment. Based on this, COL1A1 could serve as a promising biomarker for OC prognosis and provide a new perspective for the development of potential immunotherapies for patients with OC.
Bibliometric analysis of metformin as an immunomodulator (2013–2024)
Authors: Zhou Tongyi , Yu Yunfeng , Li Liu , Liu Xiu , Xiang Qin , Yu Rong 
Published: January 2025

BackgroundMetformin, the frontline treatment for diabetes, has considerable potential as an immunomodulator; however, detailed bibliometric analyses on this subject are limited.MethodsThis study extracted 640 relevant articles from the Web of Science (WOS) Core Collection and conducted visual analyses using Microsoft Excel, VOSviewer, and CiteSpace.ResultsThe findings showed that research on the immunomodulatory function of metformin has grown steadily since 2017, with China and the United States being the leading contributors. These studies have mostly been published in journals such as the International Journal of Molecular Sciences, Cancers, Frontiers in Immunology, and Scientific Reports. Keyword co-occurrence analysis highlighted metformin’s role as an immunomodulator, particularly in the context of the tumor immune microenvironment, immunosuppressive checkpoints, and metformin derivatives. Recent research has highlighted metformin’s application in aging, autoimmune diseases, COVID-19, and tuberculosis. Additionally, its role in regulating inflammation and gut microbiota is also being investigated.ConclusionOverall, the immunomodulatory effects of metformin were investigated in anti-tumor, antiviral, anti-aging, and autoimmune disease research. This highlights the scope of metformin use in these fields, while also significantly enhancing its clinical value as a repurposed drug.
Strongyloides stercoralis combined with concurrent multiple pathogens infections in an immunosuppressed patient: a case report
Authors: Fang Jingchun , Fang Huimin , Guo Penghao , Peng Yaqin , Chen Peisong 
Published: January 2025

BackgroundStrongyloides stercoralis is an opportunistic pathogenic parasite. Most individuals with normal immune function may not exhibit significant symptoms, and the signs are atypical, which can easily lead to missed diagnoses and delayed treatment. People with underlying diseases and weakened immunity are prone to develop severe conditions after infection with Strongyloides stercoralis.Case presentationWe report an immunocompromised patient in whom the pathogen was initially not detectable using traditional parasitic detection techniques. However, Strongyloides stercoralis was identified in both the alveolar lavage fluid and blood through metagenomic next-generation sequencing. Subsequently, Strongyloides stercoralis was detected in the alveolar lavage fluid after multiple rounds of testing using traditional microscopic examination techniques. Based on the mNGS results and other examination findings, the patient was diagnosed with Strongyloides stercoralis in combination with concurrent multiple pathogens infections. After the combined drug therapy of Meropenem, Vancomycin, and Albendazole, the patient’s condition was gradually brought under control.ConclusionThis case demonstrates the advantage of integrating traditional detection methods with metagenomics next-generation sequencing technology in the etiological diagnosis of immunocompromised individuals. It is conducive to clarifying the etiological diagnosis of patients and thereby facilitating the timely initiation of corresponding treatments.
Artificial intelligence in healthcare: transforming patient safety with intelligent systems—A systematic review
Authors: De Micco Francesco , Di Palma Gianmarco , Ferorelli Davide , De Benedictis Anna , Tomassini Luca , Tambone Vittoradolfo , Cingolani Mariano , Scendoni Roberto 
Published: January 2025

IntroductionAdverse events in hospitals significantly compromise patient safety and trust in healthcare systems, with medical errors being a leading cause of death globally. Despite efforts to reduce these errors, reporting remains low, and effective system changes are rare. This systematic review explores the potential of artificial intelligence (AI) in clinical risk management.MethodsThe systematic review was conducted using the PRISMA Statement 2020 guidelines to ensure a comprehensive and transparent approach. We utilized the online tool Rayyan for efficient screening and selection of relevant studies from three different online bibliographic.ResultsAI systems, including machine learning and natural language processing, show promise in detecting adverse events, predicting medication errors, assessing fall risks, and preventing pressure injuries. Studies reveal that AI can improve incident reporting accuracy, identify high-risk incidents, and automate classification processes. However, challenges such as socio-technical issues, implementation barriers, and the need for standardization persist.DiscussionThe review highlights the effectiveness of AI in various applications but underscores the necessity for further research to ensure safe and consistent integration into clinical practices. Future directions involve refining AI tools through continuous feedback and addressing regulatory standards to enhance patient safety and care quality.
Revolutionizing diagnosis of pulmonary Mycobacterium tuberculosis based on CT: a systematic review of imaging analysis through deep learning
Authors: Zhang Fei , Han Hui , Li Minglin , Tian Tian , Zhang Guilei , Yang Zhenrong , Guo Feng , Li Maomao , Wang Yuting , Wang Jiahe , Liu Ying 
Published: January 2025

IntroductionThe mortality rate associated with Mycobacterium tuberculosis (MTB) has seen a significant rise in regions heavily affected by the disease over the past few decades. The traditional methods for diagnosing and differentiating tuberculosis (TB) remain thorny issues, particularly in areas with a high TB epidemic and inadequate resources. Processing numerous images can be time-consuming and tedious. Therefore, there is a need for automatic segmentation and classification technologies based on lung computed tomography (CT) scans to expedite and enhance the diagnosis of TB, enabling the rapid and secure identification of the condition. Deep learning (DL) offers a promising solution for automatically segmenting and classifying lung CT scans, expediting and enhancing TB diagnosis.MethodsThis review evaluates the diagnostic accuracy of DL modalities for diagnosing pulmonary tuberculosis (PTB) after searching the PubMed and Web of Science databases using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines.ResultsSeven articles were found and included in the review. While DL has been widely used and achieved great success in CT-based PTB diagnosis, there are still challenges to be addressed and opportunities to be explored, including data scarcity, model generalization, interpretability, and ethical concerns. Addressing these challenges requires data augmentation, interpretable models, moral frameworks, and clinical validation.ConclusionFurther research should focus on developing robust and generalizable DL models, enhancing model interpretability, establishing ethical guidelines, and conducting clinical validation studies. DL holds great promise for transforming PTB diagnosis and improving patient outcomes.
An artificial transcription factor that activates potent interferon-γ expression in human Jurkat T Cells
Authors: King Ashley , Noblitt Davis , Sherron Olivia , Kjerfve Clara , Pless Lydia , Truex Nicholas L. 
Published: January 2025

Interferon (IFN)-γ is a central regulator of cell-mediated immunity in human health and disease, but reduced expression of the target receptors impairs signaling activity and leads to immunotherapy resistance. Although intracellular expression of IFN-γ restores the signaling and downstream functions, we lack the tools to activate the IFNG gene instead of cell surface receptors. This paper introduces the design and characterization of an artificial transcription factor (ATF) protein that recognizes the IFNG gene with six zinc finger domains, which are dovetailed to a VP64 signaling domain that promotes gene transcription and translation. Biological studies with human Jurkat T cells reveal that the ATF amplifies IFNG gene transcription and translation, and also stimulates gene transcription for multiple class I and II HLA alleles and interferon-stimulated genes (ISGs). Biophysical characterization showed the recombinant ATF protein recognizes the human IFNG gene with nanomolar affinity (KD = 5.27 ± 0.3 nM), adopts a protein secondary structure associated with the ββα-fold of zinc finger domains, and is resistant to thermal denaturation. These studies demonstrate that transcriptional targeting of cytokine genes, rather than surface receptors, activates cytokine expression and shows significant potential for directing immune function.
Correlations among lymphocyte count, white matter hyperintensity and brain atrophy in patients with ischemic stroke
Authors: Liu Chenchen , Shi Dai , Ni Xiaoqiong , You Shoujiang , Wu Xiaofen , Zhuang Sheng , Cai Wu , Xu Liang 
Published: January 2025

BackgroundWhite matter hyperintensity (WMH) and brain atrophy, as imaging marker of cerebral small-vessel diseases (CSVD), have a high prevalence and strong prognostic value in stroke. We aimed to explore the association between lymphocyte count, a maker of inflammation, and WMH and brain atrophy in patients with acute ischemic stroke (AIS).MethodsA total of 727 AIS patients with lymphocyte count and brain magnetic resonance imaging data were enrolled. Participants were divided into four groups according to the quartiles of baseline lymphocyte counts. WMH is frequently divided into periventricular hyperintensity (PVH) and deep white matter hyperintensity (DWMH). WMH was defined as Fazekas scale score ≥ 3; PVH was defined as periventricular Fazekas scale ≥2; DWMH was defined as deep Fazekas scale ≥2. Brain atrophy was defined as global cortical atrophy score ≥ 1. Multivariable logistic regression models were used to assess the association between lymphocyte count and WMH and brain atrophy.ResultsAmong 727 AIS, 517 (71.1%), 442 (60.8%), 459 (63.1%), 583 (80.2%) had WMH, PVH, DWMH and brain atrophy, respectively. After adjustment for potential covariates, the highest quartiles of lymphocyte counts were significantly associated with lower risk of WMH (adjusted odds ratio [aOR] 0.57, 95% confidence intervals [CI] 0.32–0.99), PVH (aOR 0.52, 95% CI 0.31–0.87), DWMH (aOR 0.53 95% CI 0.32–0.90) as well as brain atrophy (aOR 0.46, 95% CI 0.23–0.92) compared with the lowest quartiles of lymphocyte counts, respectively. Furthermore, a notable inverse association was observed between continuous lymphocyte counts and WMH, PVH, DWMH, and brain atrophy. Additionally, we found that the inverse association between baseline lymphocyte count and WMH was significant only in individuals with mild stroke.ConclusionIn patients with AIS, there was an independent and inverse association between the baseline lymphocyte count and both WMH and brain atrophy.