Identification of diagnostic signatures for ischemic stroke by machine learning algorithm.

OBJECTIVE: Ischemic stroke (IS) is one of the major diseases threatening human health and survival and a leading cause of acquired mortality and disability in adults. The aim of this study was to screen diagnostic features of IS and to explore the characteristics of immune cell infiltration in IS pathogenesis. METHODS: The microarray data of IS (GSE16561, GSE58294, GSE37587, and GSE124026) in the GEO database were merged after removing the batch effect. Then integrated bioinformatic analysis and machine-learning strategies were adopted to analyze the functional correlation and select diagnostic signatures. The WGCNA was used to identify the co-expression modules related to IS. The CIBERSORT algorithm was performed to assess the inflammatory state of IS and to investigate the correlation between diagnostic signatures and infiltrating immune cells. RESULTS: Functional analysis of dysregulated genes showed that immune response-regulating signaling pathway and pattern recognition receptor activity were enriched in the pathophysiology of IS. The turquoise module was identified as the significant module with IS. By using Lasso and SVM-RFE learning methods, we finally obtained four diagnostic genes, including LAMP2, CR1, CLEC4E, and F5. The corresponding results of AUC of ROC prediction model in training and validation cohort were 0.954 and 0.862, respectively. The immune cell infiltration analysis suggested that plasma cells, resting and activated NK cells, activated dendritic cells, memory B cells, CD8+ T cells, naïve CD4+ T cells, and resting mast cells may be involved in the development of IS. Additionally, these diagnostic signatures might be correlated with multiple immune cells in varying degrees. CONCLUSION: We identified four biologically relevant genes (LAMP2, CR1, CLEC4E, and F5) with diagnostic effects for IS, our results further provide novel insights regarding molecular mechanisms associated with various immune cells that related to IS for future investigations.

Efficacy of the sphingosine-1-phosphate receptor agonist fingolimod in animal models of stroke: an updated meta-analysis.

Objective: Neuroinflammation is a central part of cerebral ischemia/reperfusion injury. The novel immune suppressant, fingolimod, is a promising candidate to ameliorate stroke-induced damage. Fingolimod is efficacious in experimental ischemic models, but a rigorous meta-analysis is lacking that considers how different experiment variables affect outcomes.Methods: We conducted a systematic literature review of fingolimod in stroke models, with the aim of rigorously evaluating fingolimod's effects on reducing infarct volume improving neurological outcomes. Seventeen variables were evaluated as covariates for the source of heterogeneity, and effect sizes were combined by using normalized mean difference meta-analysis to evaluate efficacy. Study quality was evaluated by the CAMARADES ten-item checklist, and publication bias was evaluated by funnel plots and Egger's tests.Results: About 123 unduplicated articles were identified in the literature research. Of these papers, 118 articles were excluded after reading titles and abstracts. Another 17 articles were selected in this study. Study quality was moderate (median = 6; interquartile range = 4), and publication bias was statistically insignificant. fingolimod reduced infarct volume by 30.4% (95% CI 22.4%-38.3%; n = 24; I2 = 90.0%; p < 0.0001) and consistently enhanced neurobehavioral outcome by 34.2% (95% CI 23.1%-45.2%; n = 14; I2 = 76.5%; p < 0.0001). No single factors accounted for heterogeneity.Conclusions: Our rigorous statistical evaluation confirmed the neuroprotective properties of fingolimod. New data can be used in designing future clinical trials.

Chinese herbal medicines for the treatment of depression: a systematic review and network meta-analysis.

Objectives: Amidst rising global burden of depression and the associated challenges with conventional antidepressant therapies, there is a growing interest in exploring the efficacy and safety of alternative treatments. This study uses a Bayesian network meta-analysis to rigorously evaluate the therapeutic potential of Chinese herbal medicines in the treatment of depression, focusing on their comparative efficacy and safety against standard pharmacological interventions. Methods: Five databases (PubMed, Wanfang Data, EMBASE, CNKI, and the Cochrane Library) and grey literature were searched from inception to end of July 2023 to identify studies that assessed the efficacy and safety of Chinese herbal medicines in treating depression. The response rate, Hamilton Depression Scale (HAMD) scores, and rates of adverse events were assessed through both direct and indirect comparisons. Data extraction and risk of bias assessment were meticulously performed. Statistical analysis used Markov chain Monte Carlo methods, with effect size estimates provided as odd ratios and their 95% confidence intervals. Results: A total of 198 RCTs involving 8,923 patients were analyzed, assessing 17 Chinese herbal medicines. Surface Under the Cumulative Ranking results indicated that the top three treatments with the best response rate were possibly Guipiwan, Ease Pill, and Chaihu Jia Longgu Muli Decoction; the top three treatments on the reduction of HAMD scores were Chai Hu Shu Gan San, Xingnao Jieyu Decoction, and Xiaoyao Powder; and the top three treatments with the lowest adverse effects rates were Xiaoyao Powder, Alprazolam, and Xingnao Jieyu Decoction. Interestingly, commonly used synthetic drugs such as Fluoxetine, Escitalopram, Amitriptyline, Sertraline, Flupentixol and Melitracen, and Venlafaxine, not only appeared to be less effective than specific Chinese herbal medicines (Gan Mai Da Zao Decoction, Chaihu Jia Longgu Muli Decoction, Chai Hu Shu Gan San, Danzhi-Xiaoyao-San, and Xingnao Jieyu Decoction), but they were also related to substantially higher risk of adverse events. Conclusion: Our findings elucidate the promising therapeutic potential of Chinese herbal medicines as viable alternatives in the treatment of depression, with certain herbs demonstrating enhanced efficacy and safety profiles. The outcomes of this study advocate for the integration of these alternative modalities into contemporary depression management paradigms. However, it underscores the necessity for larger, methodologically robust trials to further validate and refine these preliminary findings. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023452109.

Pharmacological treatments for vascular dementia: a systematic review and Bayesian network meta-analysis.

Background: Vascular dementia (VaD) is one of the most prevalent, burdensome, and costly forms of dementia. Pharmacological treatment is often the first-line choice for clinicians; however, there is a paucity of comparative information regarding the multiple available drug options. Methods and Analysis: A systematic review and network meta-analysis were conducted on randomized trials involving adult patients with VaD, sourced from PubMed, the Cochrane Library, EMBASE, Web of Science, OPENGREY, ClinicalTrials.gov, Wanfang Data, and CNKI. The primary outcomes included changes in Mini-Mental State Examination (MMSE) scores, activities of daily living (ADL) scores, and the incidence of adverse reactions. Efficacy and safety of intervention strategies were comprehensively analyzed using forest plots, cumulative ranking probability curves (SUCRA), and funnel plots, all generated with R software. Results: A total of 194 RCTs comparing 21 different anti-VaD drugs with placebos or no treatment were analysed. Regarding MMSE scores, the five most effective drugs were Butylphthalide, Huperzine A, Edaravone, Rivastigmine, and Memantine. For ADL scores, the top five drugs in efficacy were Huperzine A, Butylphthalide, Tianzhi granule, Nicergoline, and Idebenone. In terms of the incidence of adverse drug reactions, Co-dergocrine Mesylate, Tongxinluo capsule, Butylphthalide, Piracetam, and Oxiracetam demonstrated favourable safety profiles. Conclusion: This study enhances the understanding of the relative benefits and risks associated with various VaD treatments, providing a valuable reference for clinical decision-making. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier registration number.

Neuroimaging modalities in the detection of Alzheimer's disease-associated biomarkers.

Alzheimer's disease (AD) is the most common cause of dementia. Neuropathological changes in AD patients occur up to 10-20 years before the emergence of clinical symptoms. Specific diagnosis and appropriate intervention strategies are crucial during the phase of mild cognitive impairment (MCI) and AD. The detection of biomarkers has emerged as a promising tool for tracking the efficacy of potential therapies, making an early disease diagnosis, and prejudging treatment prognosis. Specifically, multiple neuroimaging modalities, including magnetic resonance imaging (MRI), positron emission tomography, optical imaging, and single photon emission-computed tomography, have provided a few potential biomarkers for clinical application. The MRI modalities described in this review include structural MRI, functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy, and arterial spin labelling. These techniques allow the detection of presymptomatic diagnostic biomarkers in the brains of cognitively normal elderly people and might also be used to monitor AD disease progression after the onset of clinical symptoms. This review highlights potential biomarkers, merits, and demerits of different neuroimaging modalities and their clinical value in MCI and AD patients. Further studies are necessary to explore more biomarkers and overcome the limitations of multiple neuroimaging modalities for inclusion in diagnostic criteria for AD.

Identification of diagnostic signatures associated with immune infiltration in Alzheimer's disease by integrating bioinformatic analysis and machine-learning strategies.

Objective: As a chronic neurodegenerative disorder, Alzheimer's disease (AD) is the most common form of progressive dementia. The purpose of this study was to identify diagnostic signatures of AD and the effect of immune cell infiltration in this pathology. Methods: The expression profiles of GSE109887, GSE122063, GSE28146, and GSE1297 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between AD and control brain samples. Functional enrichment analysis was performed to reveal AD-associated biological functions and key pathways. Besides, we applied the Least Absolute Shrinkage Selection Operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) analysis to screen potential diagnostic feature genes in AD, which were further tested in AD brains of the validation cohort (GSE5281). The discriminatory ability was then assessed by the area under the receiver operating characteristic curves (AUC). Finally, the CIBERSORT algorithm and immune cell infiltration analysis were employed to assess the inflammatory state of AD. Results: A total of 49 DEGs were identified. The functional enrichment analysis revealed that leukocyte transendothelial migration, cytokine receptor interaction, and JAK-STAT signaling pathway were enriched in the AD group. MAF basic leucine zipper transcription factor F (MAFF), ADCYAP1, and ZFP36L1 were identified as the diagnostic biomarkers of AD with high discriminatory ability (AUC = 0.850) and validated in AD brains (AUC = 0.935). As indicated from the immune cell infiltration analysis, naive B cells, plasma cells, activated/resting NK cells, M0 macrophages, M1 macrophages, resting CD4+ T memory cells, resting mast cells, memory B cells, and resting/activated dendritic cells may participate in the development of AD. Additionally, all diagnostic signatures presented different degrees of correlation with different infiltrating immune cells. Conclusion: MAFF, ADCYAP1, and ZFP36L1 may become new candidate biomarkers of AD, which were closely related to the pathogenesis of AD. Moreover, the immune cells mentioned above may play crucial roles in disease occurrence and progression.

Baricitinib Ameliorates Experimental Autoimmune Encephalomyelitis by Modulating the Janus Kinase/Signal Transducer and Activator of Transcription Signaling Pathway.

Experimental autoimmune encephalomyelitis (EAE) is an animal model of multiple sclerosis (MS) and a CD4+ T cell-mediated autoimmune disease. The Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway is recognized as the major mechanism that regulates the differentiation and function of T helper (Th) 1 and Th17 cells, which are recognized as pivotal effector cells responsible for the development of EAE. We used baricitinib, a JAK 1/2 inhibitor, to investigate the therapeutic efficacy of inhibiting the JAK/STAT pathway in EAE mice. Our results showed that baricitinib significantly delayed the onset time, decreased the severity of clinical symptoms, shortened the duration of EAE, and alleviated demyelination and immune cell infiltration in the spinal cord. In addition, baricitinib treatment downregulated the proportion of interferon-γ+CD4+ Th1 and interleukin-17+CD4+ Th17 cells, decreased the levels of retinoic acid-related orphan receptor γ t and T-bet mRNA, inhibited lymphocyte proliferation, and decreased the expression of proinflammatory cytokines and chemokines in the spleen of mice with EAE. Furthermore, our results showed the role of baricitinib in suppressing the phosphorylation of STATs 1, 3, and 4 in the spleen of EAE mice. Therefore, our study demonstrates that baricitinib could potentially alleviate inflammation in mice with EAE and may be a promising candidate for treating MS.

MicroRNA-424 regulates cisplatin resistance of gastric cancer by targeting SMURF1 based on GEO database and primary validation in human gastric cancer tissues.

PURPOSE: Cisplatin (DDP) based chemotherapy regimens are widely used in advanced gastric cancer (GC). Drug resistance often limited the clinical benefits of cisplatin regimen. The mechanisms of cisplatin resistance have not been fully revealed. Therefore, further exploration of the relevant molecular mechanisms is urgently needed. PATIENTS AND METHODS: DDP resistance associated miRNA of GC microarray dataset GSE86195 was obtained from the National Center for Biotechnology Information (NCBI) GEO database, GEO2R was applied to compare the samples in two different groups under the same experimental conditions. |log2(Fold Change) | (log2(FC)) was selected as the criteria to screen the statistically significant DE-miRNAs. StarBaseV3.0 was used to predict the target genes of the DE-miRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of target genes of DE-miRNAs were carried out using DAVID. The STRING database was applied to estimate the correlations between target genes. Analysis of hubgenes by coremine and The Human Protein Atlas (THPA). Initial expression validations of miR-424 and miR-491-5p, SMURF1 and BCL2L1 were carried out using clinical pathological specimens by RT-PCR. RESULTS: A total of 13 Differential expression-miRNAs (DE-miRNAs) were identified in DDP chemoresistant cells, including 9 upregulated miRNAs and 4 downregulated miRNAs. SMURF1 and BCL2L1 were screened as the critical genes in DDP-resistant GC, which were regulated by miR-424 and miR-491-5p respectively. The results of validation of hub genes expression in GC tissues indicated that in DFS<1-year group, the expression of miR-424 decreased significantly, notably upregulated expression of SMURF1 was also detected. CONCLUSION: Our results implied that miR-424, as a tumor suppressor, could deregulate SMURF1 in DDP-resistant GC cells.

Safety and efficacy of combining capecitabine and temozolomide (CAPTEM) to treat advanced neuroendocrine neoplasms: A meta-analysis.

Retrospective studies have suggested that capecitabine combined with temozolomide (CAPTEM) is effective for treating patients with advanced neuroendocrine neoplasms (NENs); however, the efficacy and safety of this regimen needs to be verified by high-quality evidence or results of randomized controlled trials.We carried out a meta-analysis to evaluate the safety and effectiveness of a CAPTEM protocol for patients with advanced NENs. Systematic electronic literature searches were conducted using PubMed, EMBASE, and the Cochrane Library, and among meeting abstracts of the American Society of Clinical Oncology, European Society for Medical Oncology, European Neuroendocrine Tumor Society, and North American Neuroendocrine Tumor Society, up to June 30, 2017. We selected studies describing CAPTEM regimens for treating advanced NENs and reported on tumor response and/or toxicities according to clear World Health Organization (WHO) grading of patients. Three reviewers independently and repeatedly identified studies, extracted data, and assessed the quality of the literature. A single-proportion meta-analysis was applied to included articles.Fifteen studies with a total of 384 individuals were included. Medium overall survival in most studies was more than 12 months, whereas medium progression-free survival was similar or slightly higher than that in studies using other treatment regimes. Disease control rate of CAPTEM administration for patients with NENs was 72.89% (95% confidence interval, 64.04-81.73%; I = 82.4%; P < .01). WHO grade 3 to 4 toxicities, such as thrombocytopenia (3.36%), neutropenia (0.69%), lymphopenia (0.65%), anemia (0.59%), mucositis (0.57%), fatigue (0.54%), diarrhea (0.49%), nausea (0.39%), and transaminase elevation (0.13%) were reported in the trials included.CAPTEM is effective and relatively safe for treating patients with advanced NENs.