syedzayyan/paper_mill_benchmark huggingface dataset:
Identification of Therapeutic Targets and Prognostic Biomarkers among Genes from the Mediator Complex Family in the Hepatocellular Carcinoma Tumour-Immune Microenvironment

Hepatocellular carcinoma (hcc) is predominant among all types of primary liver cancers characterised by high morbidity and mortality.Genes in the mediator complex (med) family are engaged in the tumour-immune microenvironment and function as regulatory hubs mediating carcinogenesis and progression across diverse cancer types.Whereas research studies have been conducted to examine the mechanisms in several cancers, studies that systematically focused on the therapeutic and prognostic values of med in patients with hcc are limited.Methods.The online databases oncomine, gepia, ualcan, gene mania, c bio portal, omic studio, sting, metascape, and timer were used in this study.Results.The transcriptional levels of all members of the med family in hcc presented an aberrant high expression pattern.Significant correlations were found between the med1, med6, med8, med10, med12, med15, med17, med19, med20, med21, med22, med23, med24, med25, med26, and med27 expression levels and the pathological stage in the patients with hcc.The patients with high expression levels of med6, med8, med10, med17, med19, med20, med21, med22, med24, and med25 were significantly associated with poor prognosis.Functional enrichment analysis revealed that the members of the med family were mainly enriched in the nucleobase-containing compound catabolic process, regulation of chromosome organisation, and transcriptional regulation by tp53.Significant correlations were found between the med6, med8, med10, med17, med19, med20, med21, med22, med24, and med25 expression levels and all types of immune cells (b cells, cd8+ t cells, cd4+ t cells, macrophages, neutrophils, and dendritic cells).B cells and med8 were independent predictors of overall survival.We found significant correlations between the somatic copy number alterations of the med6, med8, med10, med20, med21, med22, med24, and med25 molecules and the abundance of immune infiltrates.Conclusions.Our study delineated a thorough landscape to investigate the therapeutic and prognostic potentials of the med family for hcc cases, which yielded promising results for the development of immunotherapeutic drugs and construction of a prognostic stratification model.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Identification of Prognostic Signature of Necroptosis-Related lncRNAs and Molecular Subtypes in Glioma

In tumor progression and epigenetic regulation, long non-coding rna (lnc rna) and necroptosis are crucial regulators.However, in glioma microenvironment, the role of necroptosis-related lnc rnas (nrls) remains unknown.Method.In this study, the rna-seq and clinical annotation of glioma patients were analyzed using the cancer genome atlas (tcga) and chinese glioma genome atlas (cgga) databases.To investigate prognosis and tumor microenvironment of nrls in gliomas, we conducted a prediction model based on the training cohort.The accuracy of the model was verified in the verification cohort.Results.A signature composed of 13 nrls was identified, and all glioma patients were divided into two groups.We found that each group has unique survival outcomes, biological behaviors, and immune infiltrating status.The necroptosis-related lnc rna signature (nrls) model was found to be an independent risk factor in multivariate cox analysis.Immunosuppressive microenvironment was positively correlated with the high-risk group.Due to significantly different ic50 between risk groups, nrls could be used as a guide for chemotherapeutic treatment.Further, the entire cohort was divided into two clusters depending on nrls.Consensus clustering method and the risk scoring system were basically similar.Survival probability was higher in cluster 2, while cluster 1 has stronger immunologic infiltration.Conclusion.The predictive signature could be a prognostic factor independently and serve to detect the role of nrls in glioma immunotherapy response.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Identification of Potential Key Biomarkers of Atrial Fibrillation and Their Correlation with Immune Infiltration in Atrial Tissue

To identify potential key biomarkers and characterize immune infiltration in atrial tissue of patients with atrial fibrillation (af) through bioinformatics analysis.Methods.Differentially expressed genes (degs) were identified by the limma package in bioconductor, and functional and pathway enrichment analyses were undertaken using go and kegg.The lasso logistic regression and boruta algorithm were employed to screen for potential novel key markers of af from all degs.Gene set variation analysis was also performed.Single-sample gene set enrichment analysis was employed to quantify the infiltration levels for each immune cell type, and the correlation between hub genes and infiltrating immune cells was analyzed.Results.A total of 52 degs were identified, including of 26 downregulated degs and 26 upregulated degs.Degs were primarily enriched in the major histocompatibility complex class ii protein complex, glucose homeostasis, protein tetramerization, regulation of synapse organization, cytokine activity, heart morphogenesis, and blood circulation.Three downregulated genes and three upregulated genes were screened by lasso logistic regression and the boruta algorithm.Finally, immune infiltration analysis indicated that the atrial tissue of af patients contained significant infiltration of apc_co_inhibition, mast_cell, neutrophils, p dcs, t_cell_costimulation, and th1_cells compared with paired sinus rhythm (sr) atrial tissue, and the three downregulated genes were negatively correlated with the six kinds of immune cells mentioned above.Conclusion.The hub genes identified in this study and the differences in immune infiltration of atrial tissue observed between af and sr tissue might help to characterize the occurrence and progression of af.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Identification of Novel Biomarkers Related to Lung Squamous Cell Carcinoma Using Integrated Bioinformatics Analysis

Lung squamous cell carcinoma (lusc) is one of the most common types of lung carcinoma and has specific clinicopathologic characteristics.In this study, we screened novel molecular biomarkers relevant to the prognosis of lusc to explore new diagnostic and treatment approaches for this disease.Methods.We downloaded gse73402 from the gene expression omnibus (geo) database.Gse73402 contains 62 samples, which could be classified as four subtypes according to their pathology and stages.Via weighted gene coexpression network analysis (wgcna), the main module was identified and was further analyzed using differentially expressed genes (degs) analysis.Then, by protein-protein interaction (ppi) network and gene expression profiling interactive analysis (gepia), hub genes were screened for potential biomarkers of lusc.Results.Via wgcna, the yellow module containing 349 genes was identified, and it is strongly related to the subtype of cis (carcinoma in situ).Degs analysis detected 180 genes that expressed differentially between the subtype of cis and subtype of early-stage carcinoma (stage i and stage ii).A ppi network of degs was constructed, and the top 20 genes with the highest correlations were selected for gepia database to explore their effect on lusc survival prognosis.Finally, itga5, tubb3, scnn1b, and serpine1 were screened as hub genes in lusc.Conclusions.Itga5, tubb3, scnn1b, and serpine1 may have great diagnostic and prognostic significance for lusc and have great potential to be new treatment targets for lusc.

Journal: Computational and Mathematical Methods in Medicine (2021)
Publication types: Research Article;
Identification of Molecular Targets and Underlying Mechanisms of Xiaoji Recipe against Pancreatic Cancer Based on Network Pharmacology

Traditional chinese medicine (tcm) is applied in the anticancer adjuvant therapy of various malignancies and pancreatic cancer included.Xiaoji recipe consists several tcm materials with anticancer activities.In our work, we intended to analyze the molecular targets as well as the underlying mechanisms of xiaoji recipe against pancreatic cancer.A total of 32 active components and 522 potential targets of xiaoji recipe were selected using the tcmsp and swiss target prediction databases.The potential target gene prediction in pancreatic cancer was performed using omim, disgenet, and genecards databases, and totally, 998 target genes were obtained.The component-disease network was constructed using the cytoscape software, and 116 shared targets of pancreatic cancer and xiaoji recipe were screened out.As shown in the protein–protein interaction (ppi) network, the top 20 hub genes such as tp53, hras, akt1, vegfa, stat3, egfr, and src were further selected by degree.Go and kegg functional enrichment analysis revealed that xiaoji recipe may affect pancreatic cancer progression by targeting the pi3k/akt and mapk signaling pathways.Moreover, we performed in vitro assays to explore the effect of xiaoji recipe on pancreatic cancer cells.The results revealed that xiaoji recipe suppressed the viability and migration and promoted the apoptosis of pancreatic cancer cells via the inactivation of pi3k/akt, mapk, and stat3 pathways.The findings of our study suggested the potential of xiaoji recipe in the targeting therapy of pancreatic cancer.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Identification of an m6A RNA Methylation Regulator Risk Score Model for Prediction of Clinical Prognosis in Astrocytoma

Astrocytoma (as) is the most ubiquitous primary malignancy of the central nervous system (cns).The vital involvement of the n6-methyladenosine (m6a) rna modification in the growth of multiple human tumors is known.This study entailed probing m6a regulators with as prognosis to construct a risk prediction model (rs) for potential clinical use.A total of 579 as patients’ (of the chinese glioma genome atlas,cgga) data and the expression of 12 published m6a-related genes were included in this study.Cox and selection operator (lasso) regression analyses for independent prognostic factors and multifactor cox analysis established an r.s.Model to predict the as patient prognosis.This was subject to verification employing 331 samples from the tcga data set followed by gene ontology and pathway enrichment study with gene set enrichment analysis (gsea).The r.s.Constructed with three m6a genes inclusive of wtap, rbm15, and ythdf2 emerged as independent prognostic factors in as patients with vital involvement in the advancement and development of the malignancy.In a nutshell, this work reported an m6a-related gene risk model to predict the prognosis of as patients to pave the way for discerning diagnostic and prognostic biomarkers.Further corroboration employing relevant wet-lab assays of this model is warranted.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Identification and Potential Mechanisms of a 7-MicroRNA Signature That Predicts Prognosis in Patients with Lower-Grade Glioma

Lower-grade glioma is an intracranial cancer that may develop into glioblastoma with high mortality.The main objective of our study is to develop micro rna for lgg patients which will provide novel prognostic biomarkers along with therapeutic targets.Methods.Clinicopathological data of lgg patients and their rna expression profile were downloaded through the cancer genome atlas relevant expression profiles of rna, and clinicopathological data of the lgg patients had been extracted from the database of “the cancer genome atlas.” differential expression analysis had been conducted for identification of the differentially expressed micro rnas as well as m rnas in lgg samples and normal ones.Roc curves and k–m plots were plotted to confirm performance and for predictive accuracy.For the confirmation of micro rnas as an independent prognostic factor, an independent prognosis analysis was conducted.Moreover, target differentially expressed genes of these identified prognostic micro rnas that were extracted and protein-protein interaction networks were developed.Moreover, the biological functions of signature were determined through genome ontology analysis, genome pathway analysis, and kyoto encyclopedia of genes.Results.7-micro rna signature was identified that has the ability of categorization of individuals with lgg into high- and low-risk groups on the basis of significant difference in survival during training and testing cohorts (p &lt; 0.001).The 7-micro rna signature had appeared to be robust in predictive accuracy (all auc&gt; 0.65).It was also approved with multivariate cox regression along with some traditional clinical practices that we can use 7-micro rna signature for therapeutic purposes as a self-regulating predictive os factor (p &lt; 0.001).Kegg and gene ontology (go) analyses reported that 7-micro rnas had mainly developed in important pathways related with glioma, e.g., the “c amp signaling pathway,” “glutamatergic synapses,” and “calcium signaling pathway”.Conclusion.A newly discovered 7-micro rna signature could be a potential target for the diagnosis and treatment for lgg patients.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
CASC1 Expression in Bladder Cancer Is Regulated by Exosomal miRNA-150: A Comprehensive Pan-Cancer and Bioinformatics Study

This study explored the role of cancer susceptibility 1 (casc1) in tumorigenesis and development as well as the key pathways affecting bladder cancer progression.Casc1 was examined in various normal tissues in humans using the hpa database to quantify its expression level and subcellular localization.Casc1 is abundantly expressed in tumor tissues, primarily in cytoplasmic vesicles and stroma.Timer2 was used to analyze the correlation between casc1 expression levels and the types of infiltrates associated with immune cells and immunosuppressive cells.Mdsc, treg, m2, and caf were significantly correlated with casc1 expression in various tumors.Comparing patients with and without casc1 mutation, those with casc1 mutation had worse overall survival, progression-free survival, and disease-free survival.The correlation between has-mi r-150 and casc1 (for the case of bladder cancer) was then analyzed, and the related ce rna network was mapped.A negative relationship between casc1 expression and has-mi r-150 expression was found in cases of bladder cancer.And the presence of mi r-150-targeted casc1 may be associated with bladder cancer progression.Casc1 is expressed at elevated levels in various tumor tissues, and it is associated with tumorigenesis and development.Exosomes containing mi r-150-targeted casc1 may affect the progression of bladder cancer.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Hypoxia Tumor Microenvironment Activates GLI2 through HIF-1α and TGF-β2 to Promote Chemotherapy Resistance of Colorectal Cancer

A majority of relapse cases have been reported in colorectal cancer patients due to cancer stem cell progenitors.The factors responsible for chemoresistance have yet to be discovered and investigated as cscs have reported escaping from chemotherapy’s killing action.Objective.In this study, we have investigated the effects of hif-1α and tgf-β2 in hypoxia conditions on the expression of gli2, which is a potential factor for causing chemoresistance.Material and methods.Colorectal samples of treated patients were collected from the hospital biological sample library.Culture of patient-derived tss and fibroblasts was performed.The collected patient samples and cells were used for immunohistochemistry, quantitative pcr, and western blotting studies which were performed.Results.It was reported that hif-1α (hypoxia-inducible factor) and tgf-β2 secreted from cancer-associated fibroblasts (cafs) synergistically work to express gli2 in cancer stem cells.Hence, it increased the stemness as well as resistance to chemotherapy.Conclusion.The hif-1α/tgf-β2-mediated gli2 signaling was responsible for causing chemoresistance in the hypoxia environment.High expressions of hif1α/tgf-β2/gli2 cause the relapsing of colorectal cancer, thus making this a potential biomarker for identifying the relapse and resistance in patients.The study uncovers the mechanism involved in sternness and chemotherapy resistance which will help in targeted treatment.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Hydroxyethyl Starch Improves the Prognosis of Rats with Traumatic Shock via Activation of the ERK Signaling Pathway in Lymphocytes

Severe traumatic shock is one of the leading causes of death in young adults.A large number of studies have shown that effective volumetry resuscitation on the basis of controlled injury can not only increase the success rate of early resuscitation but also reduce systemic inflammatory response and improve the cure rate of severe traumatic shock.The study explored the effects of hydroxyethyl starch (hes) on the survival rate, lymphocyte function and proliferation of rats with traumatic shock, and the potential mechanisms.Methods.Traumatic shock was constructed in rats as experimental model, and liquid resuscitation was performed using hes and lactated ringer’s (lr).24-h mortality was recorded, and lymphocytes were isolated.The expressions of signaling pathway factors was detected by q pcr and western blot.Elisa was performed to determine the expression of interleukin 6 (il-6) and tumor necrosis factor-α (tnf-α) in cell supernatant.Results.Hes for fluid resuscitation augmented the survival of traumatic shock rats, upregulated the expressions of mek and erk1/2, and downregulated the expressions of il-6 and tnf-α.However, inhibition of erk signaling pathway reversed the effect of hes on the immune improvement and the 24-h survival rate of the traumatic shock rats ( p &lt; 0.05 ).Conclusion.Hes could exert the anti-inflammatory effects on lymphocytes by mediating the phosphorylation of proteins of the erk signaling pathway.Hse demonstrated a high efficacy in effectively treating traumatic shock, thus could be used in clinical practice.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Hippocampus Segmentation Method Based on Subspace Patch-Sparsity Clustering in Noisy Brain MRI

Since the hippocampus is of small size, low contrast, and irregular shape, a novel hippocampus segmentation method based on subspace patch-sparsity clustering in brain mri is proposed to improve the segmentation accuracy, which requires that the representation coefficients in different subspaces should be as sparse as possible, while the representation coefficients in the same subspace should be as average as possible.By restraining the coefficient matrix with the patch-sparse constraint, the coefficient matrix contains a patch-sparse structure, which is helpful to the hippocampus segmentation.The experimental results show that our proposed method is effective in the noisy brain mri data, which can well deal with hippocampus segmentation problem.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Heart Disease Prediction Based on the Embedded Feature Selection Method and Deep Neural Network

In recent decades, heart disease threatens people’s health seriously because of its prevalence and high risk of death.Therefore, predicting heart disease through some simple physical indicators obtained from the regular physical examination at an early stage has become a valuable subject.Clinically, it is essential to be sensitive to these indicators related to heart disease to make predictions and provide a reliable basis for further diagnosis.However, the large amount of data makes manual analysis and prediction taxing and arduous.Our research aims to predict heart disease both accurately and quickly through various indicators of the body.In this paper, a novel heart disease prediction model is given.We propose a heart disease prediction algorithm that combines the embedded feature selection method and deep neural networks.This embedded feature selection method is based on the linear svc algorithm, using the l1 norm as a penalty item to choose a subset of features significantly associated with heart disease.These features are fed into the deep neural network we built.The weight of the network is initialized with the he initializer to prevent gradient varnishing or explosion so that the predictor can have a better performance.Our model is tested on the heart disease dataset obtained from kaggle.Some indicators including accuracy, recall, precision, and f1-score are calculated to evaluate the predictor, and the results show that our model achieves 98.56%, 99.35%, 97.84%, and 0.983, respectively, and the average auc score of the model reaches 0.983, confirming that the method we proposed is efficient and reliable for predicting heart disease.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Healthcare and Scientific Treatment of Knee Osteoarthritis

Knee osteoarthritis is a chronic degenerative disease companied with chronic knee pain and dysfunction.However, the etiology and pathogenesis of knee osteoarthritis were unclear.Currently, age, diet, trauma, obesity, and inheritance are the main risk factors.The major pathological hallmarks of knee osteoarthritis included subchondral bone sclerosis, articular cartilage degeneration, arthrosynovitis, and osteophyte.With the acceleration of the aging process in china, the treatment of knee arthritis and the methods to improve the quality of life have become the focus of medical staff.Currently, therapies in clinical practice include surgery and nonoperative treatment; however, the clinical effects of different individuals at different stages will still be very different.This article reviews the recent advances in the treatment of knee osteoarthritis from three aspects: nonsurgical treatment, surgical treatment, and modern new medical means.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Review Article;
GIP Evaluation and Path Improvement of Technological SMEs Based on Digital Information Technology

Small and medium-sized technology-based smes also play a certain role in promoting the economic development and social progress of a country and can provide relative social resources.However, under the wave of green development, green technology innovation for smes is also important, which is of great significance to the sustainable development of enterprises.This paper summarizes the situation of a certain stage of chinese enterprises’ green technology innovation and builds a gip evaluation index system suitable for small and medium-sized technology-based enterprises.This paper selects z province for analysis and uses data envelopment analysis and malmquist index analysis to analyze the gi situation of 11 cities in z province.And this paper proposes a green innovation performance (gip) evaluation path for technology-based smes.The results show that the overall green innovation (gi) level of z province shows an upward and progressive trend from 2016 to 2020, and the total factor productivity change index (tpf) in the overall period from 2018 to 2020 is 0.913.The overall gip of enterprises in cities c and d in z province is insufficient and needs to be further expanded.

Journal: Mobile Information Systems (2022)
Publication types: Research Article;