bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrated Bioinformatics and Machine Learning Algorithms of Identify Novel Diagnostic Biomarkers and Chinese Medicine Targets in Chronic Atrophic Gastritis
Authors: Weng Jiao , Wu Xiu-fang , Shao Peng , Liu Xing-pu , Wang Cai-xia 
Published: October 2023

Abstract
Chronic atrophic gastritis (CAG) serves as one of the warning signals for gastric cancer, and the utilization of traditional Chinese medicinal herbs brings hope for patients' recovery. In this study, a combination of bioinformatics and machine learning algorithms was employed to explore the precise targeting of CAG diagnostic biomarkers based on meta-analysis of key Chinese herbal formulas. Firstly, through integrating transcriptomic samples from normal gastric tissue and CAG tissue from three datasets (GSE116312, GSE27411, and GSE54129), differentially expressed genes (DEGs) were identified. Further functional and pathway analysis of the DEGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Twelve Chinese herbal formulas were obtained through meta-analysis, and seven hub herbs were identified through association rule mining, namely, White Peony Root (Baishao), Largehead Atractylodes Rhizome (Baizhu), Pinellia Tuber (Banxia), Tangerine Peel (Chenpi), Root of Pilose Asiabell (Dangshen), Danshen Root (Danshen), and Coptis Root (Huanglian). A total of 248 target genes were associated with these medicinal herbs. Among the 905 CAG-related disease genes retrieved from five databases, 90 target genes of Chinese medicine (TCMTGs) were found to be shared with hub genes that are both pivotal and CAG-related. The regulatory network of Chinese medicine target genes and protein-protein interaction (PPI) network of target genes were constructed to observe the underlying mechanisms. Ten hub genes (BCL2L1, MAPK3, RASSF1, GSTP1, CCND1, CAT, MET, MMP3, THBD, and MAPK1) were identified from the intersection of DEGs and TCMTGs. Through gene correlation, sample expression levels, chromosomal positions, transcription factors, PPI networks, GO, and KEGG enrichment analysis, the characteristics of these hub genes were explored. By utilizing four machine learning algorithms – support vector machine (SVM), generalized linear model (GLM), decision tree model, and K-Nearest Neighbors model – diagnostic biomarkers for CAG (MET, MAPK1, and GSTP1) were obtained. The receiver operating characteristic (ROC) curves, nomogram plots, calibration curves, and clinical decision curves were constructed to evaluate the models. Finally, molecular docking was conducted between three protein receptors (MET-P08581, MAPK1-Q9H706, and GSTP1-P09211) and four active small molecular ligands of Chinese herbs (luteolin, naringenin, quercetin and kaempferol). In summary, the integration of machine learning models with bioinformatics methods for screening drug-targeting gene markers not only elucidated the mechanisms of active compounds in traditional Chinese medicine but also provided support for new drug development, thus increasing the potential to interrupt the progression of CAG into gastric cancer.
Comprehensive analysis of the distinct nano environments characteristics containing the different secondary structure elements: α- helices, β-sheets, and turns
Authors: Mazoni Ivan , Salim José Augusto , Moraes Fabio Rogerio , Correa Jorge Luiz , Borro Luiz , Neshich Goran 
Published: October 2023

Abstract
This work is the third part of our initiative to fully describe the internal protein nano environments (NEs) for the three existing types of secondary structure elements (SSE). In our previous work, the NE of both the α-helix and the β-sheet were analysed. The knowledge acquired in this research is important considering that secondary structure element formation is a crucial step in protein folding and an important phase that precedes the final 3D protein structure. In the current paper, STING´s database of physical-chemical and structural descriptors was used to gather the necessary information to characterize the NE of loops, or, as they are often called, turns. Given that approximately 20% of all protein-type residues form turns, research in this field is essential, and analysis of the obtained results will further contribute to our comprehension of how proteins fold. In addition, the results in this paper will contribute to the better training of algorithms that evaluate the degree of overall protein structure quality and, consequently, structure prediction. This is currently very important given we are witnessing a revolution in algorithms employing artificial intelligence for protein structure prediction. Powered by the STING’s database (wide-ranging protein structure information source), statistical testing was used to retrieve a set of descriptors that fully delineate the NE of turns. By collecting such data, it is then possible to list the variances with respect to the NE of α-helices and β-sheets and, by doing so, establish the most relevant NE descriptors (MRND) for each of the three SSEs. The results show that the α-helical and β-sheet Nes, as well as the amino acid residue composition, all behave in a similar fashion as a “key and lock” system. In other words, it is necessary for a set of specific descriptors to assume respective specific values (within the bounds of a very definite value region) to construct the specific secondary structure element NE at a certain protein location. Consequently, there is a set of descriptors that act together that are required to satisfy specific conditions for secondary structure element occurrences. The very same requirement, we found, occurs in the case of turns.
Anti-tumor Efficacy and Potential Mechanism of Pyrotinib in Locally Advanced Oral Squamous Cell Carcinoma
Authors: Zhou Liang , Wang Huiming , Chen Qianming , Le Kehao 
Published: October 2023

Abstract

Background
The resistance to epidermal growth factor receptor (EGFR) target therapy is common in advanced oral squamous cell carcinoma (OSCC). Meanwhile human epidermal growth factor receptor 2 (HER2) plays an important role in the progression of multiple solid tumors and induces resistance to EGFR target treatment. However, the expression status and the clinical significance of HER2 in OSCC is still controversial. Pyrotinib has shown promising activity as a novel EGFR/HER2 dual inhibitor, in many advanced cancers, but its efficacy in OSCC has not been determined.
Methods
57 locally advanced de novo OSCC patients admitted into a single tertiary referral hospital were enrolled in this study with the approval of the ethics committee. Through tissue microarray analysis of the primary tumors and paired para-tumor oral mucosa, the relationship between the expression levels of HER2 and the prognosis of OSCC patients had been investigated. To complement these findings, the antitumor efficacy of pyrotinib in OSCC was retrieved in vitro and in vivo. The main downstream of HER2 was evaluated by western blotting in OSCC cell lines and xenograft tumors to explore the potential mechanism of pyrotinib.
Results
This study revealed the primary tumor of OSCC had higher HER2 expression levels. Through Kaplan-Meier analysis, OSCC patients with high HER2 expression had poor overall survival (P < 0.014) and poor disease free survival (P < 0.042). In vitro, pyrotinib suppressed the proliferation, colony formation and migration of OSCC cells. Pyrotinib also promoted apoptosis of OSCC cells and induced cell cycle arrest. This study also confirmed that pyrotinib was able to inhibit the occurrence and development of OSCC effectively in vivo. Furthermore, western blotting revealed that pyrotinib suppressed OSCC by inhibiting the phosphorylation of HER2, AKT and ERK in vitro and in vivo.
Conclusions
This is the first study to exhibit the anti-OSCC effects of pyrotinib in vitro and in vivo, and demonstrated pyrotinib inhibited OSCC cells by inducing apoptosis via the HER2/ AKT and ERK pathway. The result of this study also indicated locally advanced OSCC patients might benefit from HER2 assay and EGFR/HER2 dual inhibit treatment.
Evaluating the Salivary Levels of Vitamins A, B12, C, D3, E in Oral Lichen Planus Patients in Southwest of Iran
Authors: Rezazadeh Fahimeh , Abedi Fatemeh , Ranjbar Zahra , Khorami Elham Tayebi , Tabesh Amir 
Published: October 2023

Abstract
Background
The present study aims to assess salivary levels of vitamins A, B12, C, D3 and E and compare them with a healthy group.
Methods
58 individuals, attending Shiraz Dental School, Iran, were enrolled in this cross-sectional study (28 OLP patients and 30 healthy controls, age and sex matched.) saliva samples were collected and levels of A, B12, C, D3 and E vitamins were measured. HPLC was used for measuring vitamins A, B12 and E and ELISA kits for vitamins C and D.
Results
Our study population’s mean age was 44.964 ± 10.32, including 67% female. Levels of vitamins A, C, D3 and E were lower in the saliva of OLP patients (P = 0.000, 0.000, 0.013 and 0.000 respectively), but that wasn’t the case for vitamin B12 (P = 0.699). Vitamins A, C and E were interrelated to the erosive type of OLP (P = 0.003, 0.000 and 0.000 respectively). OLP occurrence was significantly correlated with the female population, but not with the age of participants.
Conclusion
Salivary levels of vitamins A, C, D3 and E were significantly lower in OLP patients. There was no statistical difference in vitamin B12 levels in the saliva of OLP patients and the healthy control population.
Using ChatGPT to Develop the Statistical Analysis Plan for a Randomized Controlled Trial: A Case Report
Authors: Evans Richard , Pozzi Antonio 
Published: October 2023

Abstract
Background
Statistical analysis plans (SAPs) outline the way data will be collected, preprocessed and analyzed, and should be developed during the design phase of the study. However, veterinary researchers often have limited access to biostatistical resources to develop statistical analysis plans. That access can be improved using natural language artificial intelligence chat services (chatbots), such as ChatGPT, which provide ways to access biostatistical expertise that can be understood by nonstatistician researchers. The aim of this study was to demonstrate a ChatGPT query protocol that produced a statistical analysis plan for randomized controlled trial comparing orthopedic surgical methods.
Implementation
Our overall approach was to interact with the chatbot ChapGPT as we would with a biostatistician planning a clinical trial’s data preprocessing and statistical analysis. Collaborations with biostatisticians are iterative, where the investigator initiates the statistical conversation with an overview of the project, and then the biostatistician and investigator go back and forth to refine the SAP with a series of more detailed questions and responses. Similarly, we iteratively queried ChatGPT after reviewing its responses.
Results
A good SAP was developed after four queries, which took 15 minutes. Researchers with less statistical experience may require more queries and time. ChatGPT produced an acceptable SAP that could be understood by nonstatistician researchers.
Discussion
ChatGPT 3.5 is free, fast, and interactive. Chatbot-generated SAPs might improve the reproducibility of veterinary research because they could be included as supplementary material. Additionally, SAPs are useful for responding to statistical reviewers because SAPs anticipate reviewer questions. Moreover, key analysis elements are often missing from study reports, and SAPs could serve as checklists to ensure that all statistical steps are performed. Finally, even when biostatistical support is available, a chatbot-generated SAP could provide a framework for a biostatistician, and speed up the research process by weeks.
Conclusions
When used iteratively, ChatGPT provides a sound framework for the steps in the statistical analysis of randomized controlled trials. We anticipate that it would be useful for other common study designs, such as risk factor studies, survival analyses, systematic reviews, and observational cohort studies.
Identification and immune landscape of sarcopenia-related molecular clusters in inflammatory bowel disease by machine learning
Authors: Yue Chongkang , Xue Huiping 
Published: October 2023

Abstract
Sarcopenia, a prevalent comorbidity of inflammatory bowel disease(IBD), is characterized by diminished skeletal muscle mass and strength, and it has garnered increasing attention. Nevertheless, the underlying interconnected mechanisms remain elusive. This study pioneered the identification of distinct expression patterns within sarcopenia-related genes (SRGs) across individuals with IBD and in samples of normal tissue. By analyzing various SRG expression profiles, we effectively segregated 860 IBD samples into two distinct clusters, each marked by its unique immune landscape. To unravel the transcriptional disruptions underlying these clusters, the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm was employed to spotlight key genes linked to each cluster. Leveraging machine learning, namely RF, LASSO, and SVM-RFE algorithms, we established a diagnostic model grounded in 13 key genes (LYN, IFITM2, ACSL4, CLEC4E, SOCS3, PLAU, TIMP1, NCF2, MNDA, IL1B, CXCL1, MMP1, and S100A8). Moreover, the GSE112366 dataset facilitated the exploration of gene expression dynamics within the ileum mucosa of UC patients pre- and post-Ustekinumab treatment. Additionally, insights into the intricate relationship between immune cells and these pivotal genes were gleaned from the single-cell RNA (scRNA) dataset GSE162335. In conclusion, our findings collectively underscored the pivotal role of sarcopenia-related genes in the pathogenesis of IBD. Their potential as robust biomarkers for future diagnostic and therapeutic strategies is particularly promising, opening avenues for a deeper understanding and improved management of these interconnected conditions.
Work Pressure, Coping Styles and Occupational Burnout Among Chinese Police Officers: A Meta-analytic Review
Authors: Zhou Senlin , Li Miaomiao , Chen Siru , Jiang Daokui , Qu Ying 
Published: October 2023

Abstract
The present study conducted a comprehensive meta-analysis to systematically review the relationship between occupational burnout and work pressure among Chinese police officers. Additionally, the study explored the mediating role of coping styles using a meta-analytic structural equation model. The investigation involved a thorough search of CNKI, PubMed, PsychInfo, Web of Science, and Google Scholar databases, resulting in the identification of a total of 39 studies with 124 effect sizes and 14089 police officers. The findings revealed a positive correlation between work pressure and occupational burnout among Chinese police officers (r = 0.410, 95% CI = [0.347, 0.469]). Furthermore, negative coping styles mediate the relationship between work pressure and occupational burnout. Importantly, these conclusions held true across various work regions for police officers. These results provide insights into the relationship magnitude between work pressure and occupational burnout in Chinese police work and shed light on the underlying mechanisms. Based on these findings, it is recommended that interventions focusing on reducing work pressure and fostering positive coping styles be implemented to mitigate occupational burnout among police officers.
Decorating phenylalanine side-chains with triple labeled 13 C/ 19 F/ 2 H isotope patterns
Authors: Toscano Giorgia , Holzinger Julian , Nagl Benjamin , Kontaxis Georg , Kählig Hanspeter , Konrat Robert , Lichtenecker Roman J. 
Published: October 2023

Abstract
We present an economic and straightforward method to introduce 13C-19F spin systems into the deuterated aromatic side chains of phenylalanine as reporters for various protein NMR applications. The method is based on the synthesis of [4-13C, 2,3,5,6-2H4] 4-fluorophenylalanine from the commercially available isotope sources [2-13C] acetone and deuterium oxide. This compound is readily metabolized by standard E. coli overexpression in a glyphosate-containing minimal medium, which results in high incorporation rates in the corresponding target proteins.
CD72 Downregulation on CD5+ B Cells Promotes CD5-associated B Cell Proliferation and IL-10 expression during HBV Infection
Authors: Li Bingjie , Zhu Qingfeng , Zhang Yan , Ju Mabaike , Song Ying , Xie Songsong 
Published: October 2023

Abstract

Backgroud:B cells play an important role in HBV infection. CD72 is expressed on B cells, and negatively regulates B cell activation. And the effects of CD72 on B cell proliferation associated with CD5 expression have not yet been studied. The aim was to assess the impact of CD72 expression on CD5+ B cells during HBV infection.
Method: Peripheral blood mononuclear cells with HBV infection and healthy donors were collected, and CD72 on B cells were examined. The correlation between CD72 and CD5 expression on B cells was analysed by flow cytometry. The effect of CD72 expression on signal transduction and B cell proliferation were assessed by western blotting and BrdU assays.
Results: CD72 expression was significantly lower on CD5+ B cells of patients with HBV infection than those of healthy donors (P < 0.001). A negative correlation was found between CD72 and CD5 expression on B cells (P <0.01 in cells%; P = 0.033, in mean fluorescence intensity). CD5+ B cell proliferation was significantly increased after CD72 suppression. CD5+ B cell proliferation was associated with ERK and Syk activation in patients with HBV infection. And the CD72 downregulation in CD5+ B cell induced IL-10 upregulation.
Conclusion: CD72 expression was downregulated in CD5+ B cells of patients with HBV infection. Downregulation of CD72 in CD5+ B cells promotes CD5-associated B cell proliferation and IL-10 expression in an ERK and Syk signalling-dependent manner.
Development of a CRISPR/Cas12a-based fluorescent detection system of Senecavirus A
Authors: He Wei , Liao Kai , Li Ruixue , Peng wanqing , Qian Bingxu , Zeng Dexin , Tang Fang , Xue Feng , Jung Yong sam , Dai jianjun 
Published: October 2023

Abstract
Background Senecavirus A (SVA) was found in 2002 and could cause porcine idiopathic vesicular disease (PIVD) which symptoms were similar to vesicular diseases resulting in increased difficulty of a field diagnosis. However, traditional molecular diagnosis failed to reconcile cost, instrument, sensitivity, and efficiency.
Methods In this study, we integrated pre-amplification and three kinds of sensor systems with CRISPR and therefore established an SVA diagnosis platform with highly adaptable and ultra-sensitive advantages. This diagnosis which the whole process should not exceed four hours consisted of three steps: nucleic acid extraction, pre-amplification, and fluorescent signal capture.
Results This method showed no cross-reaction with other 10 swine viruses; its limit of detection was as low as one copy/reaction of SVA; its accuracy for clinical sample diagnosis was 100%.
Conclusions In addition, this diagnosis used common instruments which would be beneficial to remote testing sites or poorly equipped laboratories to promote a large-scale screening of this epidemic. Overall, this diagnosis enlarged diagnostic tools of SVA and had the potential to play a positive role in the control of PIVD.
The identification of novel biomarkers offers potential avenues for therapeutic interventions in lung adenocarcinoma
Authors: Meng Lifei , Bo Xue , Jun Zhao , Zhou Chengwei , Li Chenwei 
Published: October 2023

Abstract
Background: Lung cancer stands as a prominent contributor to cancer-related fatalities, with lung adenocarcinoma emerging as one of its primary histological subtypes. Regrettably, the 5-year survival rate for patients afflicted by this condition remains below 20%. Mitochondria, being indispensable organelles responsible for upholding cellular functionality, are susceptible to malfunctioning and can consequently give rise to diverse diseases. Henceforth, the objective of this study is to scrutinize the correlation between genes associated with mitochondria and the onset and progression of lung adenocarcinoma tumors .
Method: The lung adenocarcinoma gene expression dataset was obtained from the TCGA database for conducting differential gene expression analysis. Subsequently, Kaplan-Meier survival analysis, univariate and multivariate Cox regression analyses were performed on the differentially expressed genes (DEGs), leading to the construction of a nomogram based on these analytical results. Additionally, GO, KEGG, and GSEA enrichment analyses were carried out on the DEGs.
Results: Differential gene expression analysis revealed the presence of 13 upregulated genes related to mitochondrial fission in lung adenocarcinoma tissues, which were found to be associated with prognosis. After excluding one unfavorable prognostic gene, survival analysis was conducted on the remaining 12 genes. Univariate and multivariate Cox regression analyses demonstrated that N stage, T stage, risk score, and age significantly influenced the prognosis of lung adenocarcinoma. Based on these findings, a nomogram was developed for predicting the survival probability of patients with lung adenocarcinoma at different time points (1 year, 3 years, 5 years, and 10 years). Furthermore, GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes), and GSEA (Gene Set Enrichment Analysis) enrichment analyses indicated that the differentially expressed genes were predominantly enriched in pathways associated with cellular senescence and cell cycle regulation. These results suggest their potential relevance to tumor development in lung adenocarcinoma.
Conclusion: This study identified 12 differentially expressed genes, namely BIRC5, BRCA1, CA9, CDK1, CERS1, FOXM1, GAPDH, GPI, MTFR2, PPIF, RACGAP1 and S100A9. These genes hold promising potential as prognostic biomarkers for lung adenocarcinoma.
Group Brief Cognitive Behavioral Therapy for Suicide Prevention Compared to Dialectal Behavior Therapy Skills Group for Military Service Members: A Study Protocol of a Randomized Controlled Trial
Authors: Baker Justin C. , Grover Shawna , Gunn Laura H. , Charles Cindy , Rikli Heather , Franks Michael J. , Khazem Lauren R. , Williams Sean , Ammendola Ennio , Washington Cherita , Bennette Marquita , Starkey Austin , Schnecke Kelly , Cain Shannon , Bryan Craig J. , Cramer Robert J. 
Published: October 2023

Abstract
Background
Suicide is a pressing matter for the military. Not only does it pose a health risk, but suicide also compromises operational readiness. Despite provision of suicide prevention clinical best practices, the Department of Defense suffers several challenges (e.g., clinician shortages) limiting the agency’s ability to effectively respond to service member suicide. Implementation of evidence-based suicide-specific group therapy is a possible solution to service member well-being needs and system challenges. Service members can also gain coping skills useful beyond managing suicidal thoughts and behaviors.
Methods
This 2-arm non-inferiority randomized controlled trial compares a group therapy format of Brief Cognitive Behavioral Therapy (i.e., G-BCBT) with Dialectical Behavior Therapy (DBT) Skills Group. Both therapies are delivered in-person at a United States Naval Medical Center. Participants (N = 136) are active-duty service members with recent suicidal thoughts or suicidal behavior. Evaluation features electronically delivered questionnaires at baseline, after each treatment session, and at 3- and 6-month follow-up.
Discussion
The primary outcome concerns G-BCBT impacts on suicidal ideation. Secondary outcomes of interest are suicide attempt, psychological distress (e.g., symptoms of depression, anxiety), and self-regulatory skills (e.g., emotion regulation). We also examine self-regulatory skills as treatment moderators. Clinical trial strengths and limitations are reviewed.
Trial registration
This study was registered at Clinicaltrials.gov (protocol NCT05401838).