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This article explores the foundational research, Chinese medicine theories, and clinical applications of the “heart adjusting acupuncture method” developed by Professor Guanhu Yang to prevent and treat atherosclerotic cardiovascular disease (ASCVD). Professor Yang established this method based on experimental studies involving electroacupuncture along the horizontal umbilical line, which demonstrated a reduction in infarct area in the myocardial infarction mice model. This method was formulated using acupoints on the horizontal umbilical line: Daimai (GB 26), Tianshu (ST 25), and Daheng (SP 15). Clinical application has shown that it could effectively improve cardiac function and manage various cardiovascular conditions and proposed a new hypothesis for the treatment of myocardial infarction. Further research is required to determine if electroacupuncture stimulation at the site of myocardial infarction or during transportation can extend the critical treatment window, preserve myocardial tissue, and enhance reperfusion therapy prognosis. Professor Yang advocates that, when combined with active Western medicine treatments, the “heart adjusting acupuncture method” offers an effective measure to prevent and treat ASCVD.

Abstract Background We aimed to pinpoint biomarkers, create a diagnostic model for ulcerative colitis (UC), and delve into its immune features to better understand this autoimmune condition. Methods The sequencing data for both the UC and the control groups were obtained from GEO, including both bulk and single-cell data. Using GSE87466 as training group, we applied differential analysis, WGCNA, PPI, LASSO, RF, and SVM-RFE for biomarker selection. A neural network shaped our diagnostic model, corroborated by GSE92415 as the validation cohort with ROC assessment. Immune cell profiling was conducted using CIBERSORT. Results 53 disease-associated genes were screened. Enrichment analysis highlighted roles in complement cascades and cell adhesion. Eight biomarkers were finally identified through multiple machine learning and PPI: B4GALNT2, PDZK1IP1, FAM195A, REG4, MTMR11, FLJ35024, CD55, and CD44. The diagnostic model had AUCs of 0.984 (training group) and 0.957 (validation group). UC tissues revealed heightened plasma cells, CD8 T cells, and other immune cells. Two unique UC immune patterns emerged, with certain T and NK cells central to immune modulation. Conclusion We identified eight biomarkers of UC by various methods, constructed a diagnostic model through neural networks, and explored the immune complexity of the disease, which contributes to the diagnosis and treatment of UC.

BackgroundAtherosclerosis, a complex chronic vascular disorder with multifactorial etiology, stands as the primary culprit behind consequential cardiovascular events, imposing a substantial societal and economic burden. Nevertheless, our current understanding of its pathogenesis remains imprecise. In this investigation, our objective is to establish computational models elucidating molecular-level markers associated with atherosclerosis. This endeavor involves the integration of advanced machine learning techniques and comprehensive bioinformatics analyses.Materials and methodsOur analysis incorporated data from three publicly available the Gene Expression Omnibus (GEO) datasets: GSE100927 (104 samples, 30,558 genes), which includes atherosclerotic lesions and control arteries from carotid, femoral, and infra-popliteal arteries of deceased organ donors; GSE43292 (64 samples, 23,307 genes), consisting of paired carotid endarterectomy samples from 32 hypertensive patients, comparing atheroma plaques and intact tissues; and GSE159677 (30,498 single cells, 33,538 genes), examining single-cell transcriptomes of calcified atherosclerotic core plaques and adjacent carotid artery tissues from patients undergoing carotid endarterectomy. Utilizing single-cell sequencing, highly variable atherosclerotic monocyte subpopulations were systematically identified. We analyzed cellular communication patterns with temporal dynamics. The bioinformatics approach Weighted Gene Co—expression Network Analysis (WGCNA) identified key modules, constructing a Protein-Protein Interaction (PPI) network from module-associated genes. Three machine-learning models derived marker genes, formulated through logistic regression and validated via convolutional neural network(CNN) modeling. Subtypes were clustered based on Gene Set Variation Analysis (GSVA) scores, validated through immunoassays.ResultsThree pivotal atherosclerosis-associated genes—CD36, S100A10, CSNK1A1—were unveiled, offering valuable clinical insights. Profiling based on these genes delineated two distinct isoforms: C2 demonstrated potent microbicidal activity, while C1 engaged in inflammation regulation, tissue repair, and immune homeostasis. Molecular docking analyses explored therapeutic potential for Estradiol, Zidovudine, Indinavir, and Dronabinol for clinical applications.ConclusionThis study introduces three signature genes for atherosclerosis, shaping a novel paradigm for investigating clinical immunological medications. It distinguishes the high biocidal C2 subtype from the inflammation-modulating C1 subtype, utilizing identified signature gene as crucial targets.

Abstract Alzheimer’s disease (AD) is a serious brain disorder characterized by the presence of beta-amyloid plaques, tau pathology, inflammation, neurodegeneration, and cerebrovascular dysfunction. The presence of chronic neuroinflammation, breaches in the blood-brain barrier (BBB), and increased levels of inflammatory mediators are central to the pathogenesis of AD. These factors promote the penetration of immune cells into the brain, potentially exacerbating clinical symptoms and neuronal death in AD patients. While microglia, the resident immune cells of the central nervous system (CNS), play a crucial role in AD, recent evidence suggests the infiltration of cerebral vessels and parenchyma by peripheral immune cells, including neutrophils, T lymphocytes, B lymphocytes, NK cells, and monocytes in AD. These cells participate in the regulation of immunity and inflammation, which is expected to play a huge role in future immunotherapy. Given the crucial role of peripheral immune cells in AD, this article seeks to offer a comprehensive overview of their contributions to neuroinflammation in the disease. Understanding the role of these cells in the neuroinflammatory response is vital for developing new diagnostic markers and therapeutic targets to enhance the diagnosis and treatment of AD patients.

Objective: To assess the efficacy and safety of combining traditional Chinese medicine (TCM), specifically Chinese herbal medicine (CHM), with Western medicine (WM), compared to WM alone to treat breast cancer endocrine therapy-related osteoporosis (BCET-OP) by meta-analysis. Methods: Thirty-eight randomized controlled trials involving 2170 participants were analyzed. Eight databases were searched for articles published between inception and December 2023. Quality assessment was performed using the Risk of Bias 2 tool. Results: Significant increases were observed in the TCM-WM group in lumbar vertebrae bone mineral density (BMD) (P

BackgroundThe COVID-19 pandemic and its economic impact have heightened the risk of mental health and pain-related issues. The integration of acupuncture with conventional medicine shows promise in improving treatment outcomes for these conditions. The Alberta Complementary Health Integration Project (ABCHIP) aimed to provide acupuncture to youth (aged 24 and under) and seniors (aged 55 and above) experiencing chronic pain, pain management issues, mental health issues, and/or related conditions. The program aimed to promote integrative care, assess the effectiveness and cost-effectiveness of these therapies, and deliver patient-centered care.DesignABCHIP provided acupuncture to address pain, mental health, and addiction issues at no cost to two vulnerable populations in Alberta: youth and the older adult. A total of 606 patients aged 14–65 received 5,424 acupuncture treatments. Outcome measures included pain interference, pain severity, sleep quality, depression, anxiety, fatigue, anger, and quality of life. Short-term outcomes were assessed through questionnaires completed at the beginning and completion of the treatments, while long-term benefits were estimated using these outcome indicators and existing literature on the economic cost of illnesses.ResultThe cost-effectiveness analysis revealed the following ratios per Quality-Adjusted Life Year (QALY): CND12,171 for the overall sample, CND10,766 for patients with pain, CND9,331 for individuals with depression, and CND9,030 for those with anxiety. The cost–benefit analysis demonstrated annual cost savings ranging from CND1,487 to CND5,255, with an average of CND3,371.ConclusionThe study findings indicate that ABCHIP’s treatment for pain, depression, anxiety, and sleep issues is cost-effective, leading to substantial cost savings and improved quality of life for patients. The program’s cost per Quality-Adjusted Life Year (QALY) is significantly lower than benchmarks used in other countries, demonstrating high cost-effectiveness and value. Patients receiving 12 treatments experienced significant improvements across all measures, with estimated economic benefits surpassing treatment costs. In summary, ABCHIP offers a cost-effective and economically efficient therapy choice for individuals dealing with pain and mental health issues.

BackgroundColorectal cancer (CRC) poses a global health threat, with the oral microbiome increasingly implicated in its pathogenesis. This study leverages Mendelian Randomization (MR) to explore causal links between oral microbiota and CRC using data from the China National GeneBank and Biobank Japan. By integrating multi-omics approaches, we aim to uncover mechanisms by which the microbiome influences cellular metabolism and cancer development.MethodsWe analyzed microbiome profiles from 2017 tongue and 1915 saliva samples, and GWAS data for 6692 CRC cases and 27178 controls. Significant bacterial taxa were identified via MR analysis. Single-cell RNA sequencing and enrichment analyses elucidated underlying pathways, and drug predictions identified potential therapeutics.ResultsMR identified 19 bacterial taxa significantly associated with CRC. Protective effects were observed in taxa like RUG343 and Streptococcus_umgs_2425, while HOT-345_umgs_976 and W5053_sp000467935_mgs_712 increased CRC risk. Single-cell RNA sequencing revealed key pathways, including JAK-STAT signaling and tyrosine metabolism. Drug prediction highlighted potential therapeutics like Menadione Sodium Bisulfite and Raloxifene.ConclusionThis study establishes the critical role of the oral microbiome in colorectal cancer development, identifying specific microbial taxa linked to CRC risk. Single-cell RNA sequencing and drug prediction analyses further elucidate key pathways and potential therapeutics, providing novel insights and personalized treatment strategies for CRC.

BackgroundThis study presents real-world evidence on the clinical outcomes of the Alberta Complementary Health Integration Project (ABCHIP), which utilized acupuncture to address pain and mental health issues in two vulnerable populations in Alberta: youth (aged 24 and below) and elderly (aged 55 and above).MethodsOver 282 days, a total of 606 patients received 5,424 acupuncture treatments. Tailored to each patients’ specific pain and mental health concerns, an individualized treatment plan was selected, following a standard treatment protocol lasting 1 to 3 months. Patients were evaluated at least twice: initially and upon completing therapy. Primary treatment outcomes were assessed using various measures, including the Brief Pain Inventory (BPI), Pittsburgh Sleep Quality Index (PSQI), Patient Health Questionnaire 9 (PHQ9), PROMIS Anxiety 8a and its pediatric form PROMIS Anxiety-Pediatric, PROMIS Short Form v1.0 Fatigue 8a and its pediatric counterpart PROMIS Pediatric Short Form v2.0 Fatigue 10a, PROMIS Short Form v1.1 Anger 5a and its version PROMIS SF v2.0 5a, and EQ-5D-5L. These measures gauged pain reduction, improved sleep quality, reduced depression, anxiety, fatigue, anger, and quality of life, respectively.ResultsAnalysis of data from 500 patients who received at least 6 acupuncture sessions through ABCHIP showed statistically significant improvements in clinical outcomes. Among this group, the subgroup of 235 patients who received at least 12 sessions demonstrated the most favorable treatment outcomes, including an 75.5% reduction in pain severity, a 53.1% improvement in sleep quality, a 78.4% drop in depression, a 41.1% decline in anxiety, a 43.7% decrease in fatigue, a 38.2% decrease in anger, and a 42.6% improvement in overall quality of life.ConclusionIntegrating acupuncture with usual care demonstrates promise in enhancing mental health, alleviating chronic and general pain, and improving overall quality of life. The findings suggest that integrative programs, such as ABCHIP, present an effective approach to addressing pain and mental health concerns in vulnerable populations, providing valuable insights for future healthcare interventions.

Backgroundpancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with a very poor prognosis and a complex tumor microenvironment, which plays a key role in tumor progression and treatment resistance. Glycosylation plays an important role in processes such as cell signaling, immune response and protein stability.Materials and methodssingle-cell RNA sequencing data and spatial transcriptome data were obtained from GSE197177 and GSE224411, respectively, and RNA-seq data and survival information were obtained from UCSC Xena and TCGA. Multiple transcriptomic data were comprehensively analyzed to explore the role of glycosylation processes in tumor progression, and functional experiments were performed to assess the effects of MGAT1 overexpression on PDAC cell proliferation and migration.ResultsIn PDAC tumor samples, the glycosylation level of macrophages was significantly higher than that of normal samples. MGAT1 was identified as a key glycosylation-related gene, and its high expression was associated with better patient prognosis. Overexpression of MGAT1 significantly inhibited the proliferation and migration of PDAC cells and affected intercellular interactions in the tumor microenvironment.ConclusionMGAT1 plays an important role in PDAC by regulating glycosylation levels in macrophages, influencing tumor progression and improving prognosis.MGAT1 is a potential therapeutic target for PDAC and further studies are needed to develop targeted therapeutic strategies against MGAT1 to improve clinical outcomes.

Breast cancer (BC) is one of the most common and fatal malignancies among women worldwide. Circadian rhythms have emerged in recent studies as being involved in the pathogenesis of breast cancer. In this paper, we reviewed the molecular mechanisms by which the dysregulation of the circadian genes impacts the development of BC, focusing on the critical clock genes, brain and muscle ARNT-like protein 1 (BMAL1) and circadian locomotor output cycles kaput (CLOCK). We discussed how the circadian rhythm disruption (CRD) changes the tumor microenvironment (TME), immune responses, inflammation, and angiogenesis. The CRD compromises immune surveillance and features and activities of immune effectors, including CD8+ T cells and tumor-associated macrophages, that are important in an effective anti-tumor response. Meanwhile, in this review, we discuss bidirectional interactions: age and circadian rhythms, aging further increases the risk of breast cancer through reduced vasoactive intestinal polypeptide (VIP), affecting suprachiasmatic nucleus (SCN) synchronization, reduced ability to repair damaged DNA, and weakened immunity. These complex interplays open new avenues toward targeted therapies by the combination of clock drugs with chronotherapy to potentiate the immune response while reducing tumor progression for better breast cancer outcomes. This review tries to cover the broad area of emerging knowledge on the tumor-immune nexus affected by the circadian rhythm in breast cancer.

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease with a complex pathological mechanism involving autoimmune response, local inflammation and bone destruction. Metabolic pathways play an important role in immune-related diseases and their immune responses. The pathogenesis of rheumatoid arthritis may be related to its metabolic dysregulation. Moreover, histological techniques, including genomics, transcriptomics, proteomics and metabolomics, provide powerful tools for comprehensive analysis of molecular changes in biological systems. The present study explores the molecular and metabolic mechanisms of RA, emphasizing the central role of metabolic dysregulation in the RA disease process and highlighting the complexity of metabolic pathways, particularly metabolic remodeling in synovial tissues and its association with cytokine-mediated inflammation. This paper reveals the potential of histological techniques in identifying metabolically relevant therapeutic targets in RA; specifically, we summarize the genetic basis of RA and the dysregulated metabolic pathways, and explore their functional significance in the context of immune cell activation and differentiation. This study demonstrates the critical role of histological techniques in decoding the complex metabolic network of RA and discusses the integration of histological data with other types of biological data.

Breast cancer, due to resistance to standard therapies such as endocrine therapy, anti-HER2 therapy and chemotherapy, continues to pose a major health challenge. A growing body of research emphasizes the heterogeneity and plasticity of metabolism in breast cancer. Because differences in subtypes exhibit a bias toward metabolic pathways, targeting mitochondrial inhibitors shows great potential as stand-alone or adjuvant cancer therapies. Multiple therapeutic candidates are currently in various stages of preclinical studies and clinical openings. However, specific inhibitors have been shown to face multiple challenges (e.g., single metabolic therapies, mitochondrial structure and enzymes, etc.), and combining with standard therapies or targeting multiple metabolic pathways may be necessary. In this paper, we review the critical role of mitochondrial metabolic functions, including oxidative phosphorylation (OXPHOS), the tricarboxylic acid cycle, and fatty acid and amino acid metabolism, in metabolic reprogramming of breast cancer cells. In addition, we outline the impact of mitochondrial dysfunction on metabolic pathways in different subtypes of breast cancer and mitochondrial inhibitors targeting different metabolic pathways, aiming to provide additional ideas for the development of mitochondrial inhibitors and to improve the efficacy of existing therapies for breast cancer.

Melanoma, a malignant skin cancer arising from melanocytes, exhibits rapid metastasis and a high mortality rate, especially in advanced stages. Current treatment modalities, including surgery, radiation, and immunotherapy, offer limited success, with immunotherapy using immune checkpoint inhibitors (ICIs) being the most promising. However, the high mortality rate underscores the urgent need for robust, non-invasive biomarkers to predict patient response to adjuvant therapies. The immune microenvironment of melanoma comprises various immune cells, which influence tumor growth and immune response. Melanoma cells employ multiple mechanisms for immune escape, including defects in immune recognition and epithelial-mesenchymal transition (EMT), which collectively impact treatment efficacy. Single-cell analysis technologies, such as single-cell RNA sequencing (scRNA-seq), have revolutionized the understanding of tumor heterogeneity and immune microenvironment dynamics. These technologies facilitate the identification of rare cell populations, co-expression patterns, and regulatory networks, offering deep insights into tumor progression, immune response, and therapy resistance. In the realm of biomarker discovery for melanoma, single-cell analysis has demonstrated significant potential. It aids in uncovering cellular composition, gene profiles, and novel markers, thus advancing diagnosis, treatment, and prognosis. Additionally, tumor-associated antibodies and specific genetic and cellular markers identified through single-cell analysis hold promise as predictive biomarkers. Despite these advancements, challenges such as RNA-protein expression discrepancies and tumor heterogeneity persist, necessitating further research. Nonetheless, single-cell analysis remains a powerful tool in elucidating the mechanisms underlying therapy response and resistance, ultimately contributing to the development of personalized melanoma therapies and improved patient outcomes.

BackgroundClear Cell Renal Cell Carcinoma (ccRCC) is the most common type of kidney cancer, characterized by high heterogeneity and complexity. Recent studies have identified mitochondrial defects and autophagy as key players in the development of ccRCC. This study aims to delve into the changes in mitophagic activity within ccRCC and its impact on the tumor microenvironment, revealing its role in tumor cell metabolism, development, and survival strategies.MethodsComprehensive analysis of ccRCC tumor tissues using single cell sequencing and spatial transcriptomics to reveal the role of mitophagy in ccRCC. Mitophagy was determined to be altered among renal clear cells by gene set scoring. Key mitophagy cell populations and key prognostic genes were identified using NMF analysis and survival analysis approaches. The role of UBB in ccRCC was also demonstrated by in vitro experiments.ResultsCompared to normal kidney tissue, various cell types within ccRCC tumor tissues exhibited significantly increased levels of mitophagy, especially renal clear cells. Key genes associated with increased mitophagy levels, such as UBC, UBA52, TOMM7, UBB, MAP1LC3B, and CSNK2B, were identified, with their high expression closely linked to poor patient prognosis. Particularly, the ubiquitination process involving the UBB gene was found to be crucial for mitophagy and its quality control.ConclusionThis study highlights the central role of mitophagy and its regulatory factors in the development of ccRCC, revealing the significance of the UBB gene and its associated ubiquitination process in disease progression.

This review systematically examines gender differences in hepatocellular carcinoma (HCC), identifying the influence of sex hormones, genetic variance, and environmental factors on the disease’s epidemiology and treatment outcomes. Recognizing the liver as a sexually dimorphic organ, we highlight how gender-specific risk factors, such as alcohol consumption and obesity, contribute differently to hepatocarcinogenesis in men and women. We explore molecular mechanisms, including the differential expression of androgen and estrogen receptors, which mediate diverse pathways in tumor biology such as cell proliferation, apoptosis, and DNA repair. Our analysis underscores the critical need for gender-specific research in liver cancer, from molecular studies to clinical trials, to improve diagnostic accuracy and therapeutic effectiveness. By incorporating a gender perspective into all facets of liver cancer research, we advocate for a more precise and personalized approach to cancer treatment that acknowledges gender as a significant factor in both the progression of HCC and its response to treatment. This review aims to foster a deeper understanding of the biological and molecular bases of gender differences in HCC and to promote the development of tailored interventions that enhance outcomes for all patients.

Cancer remains a significant global challenge, with escalating incidence rates and a substantial burden on healthcare systems worldwide. Herein, we present an in-depth exploration of the intricate interplay between cancer cell death pathways and tumor immunity within the tumor microenvironment (TME). We begin by elucidating the epidemiological landscape of cancer, highlighting its pervasive impact on premature mortality and the pronounced burden in regions such as Asia and Africa. Our analysis centers on the pivotal concept of immunogenic cell death (ICD), whereby cancer cells succumbing to specific stimuli undergo a transformation that elicits robust anti-tumor immune responses. We scrutinize the mechanisms underpinning ICD induction, emphasizing the release of damage-associated molecular patterns (DAMPs) and tumor-associated antigens (TAAs) as key triggers for dendritic cell (DC) activation and subsequent T cell priming. Moreover, we explore the contributions of non-apoptotic RCD pathways, including necroptosis, ferroptosis, and pyroptosis, to tumor immunity within the TME. Emerging evidence suggests that these alternative cell death modalities possess immunogenic properties and can synergize with conventional treatments to bolster anti-tumor immune responses. Furthermore, we discuss the therapeutic implications of targeting the TME for cancer treatment, highlighting strategies to harness immunogenic cell death and manipulate non-apoptotic cell death pathways for therapeutic benefit. By elucidating the intricate crosstalk between cancer cell death and immune modulation within the TME, this review aims to pave the way for the development of novel cancer therapies that exploit the interplay between cell death mechanisms and tumor immunity and overcome Challenges in the Development and implementation of Novel Therapies.

This comprehensive review delves into the complex interplay between mitochondrial gene defects and pancreatic cancer pathogenesis through a multiomics approach. By amalgamating data from genomic, transcriptomic, proteomic, and metabolomic studies, we dissected the mechanisms by which mitochondrial genetic variations dictate cancer progression. Emphasis has been placed on the roles of these genes in altering cellular metabolic processes, signal transduction pathways, and immune system interactions. We further explored how these findings could refine therapeutic interventions, with a particular focus on precision medicine applications. This analysis not only fills pivotal knowledge gaps about mitochondrial anomalies in pancreatic cancer but also paves the way for future investigations into personalized therapy options. This finding underscores the crucial nexus between mitochondrial genetics and oncological immunology, opening new avenues for targeted cancer treatment strategies.

Extracellular vesicles (EVs) have been proven to play a significant immunoregulatory role in many chronic diseases, such as cancer and immune disorders. Among them, EVs derived from NK cells are an essential component of the immune cell functions. These EVs have been demonstrated to carry a variety of toxic proteins and nucleic acids derived from NK cells and play a therapeutic role in diseases like malignancies, liver fibrosis, and lung injury. However, natural NK-derived EVs (NKEVs) have certain limitations in disease treatment, such as low yield and poor targeting. Concurrently, NK cells exhibit characteristics of memory-like NK cells, which have stronger proliferative capacity, increased IFN-γ production, and enhanced cytotoxicity, making them more advantageous for disease treatment. Recent research has shifted its focus towards engineered extracellular vesicles and their potential to improve the efficiency, specificity, and safety of disease treatments. In this review, we will discuss the characteristics of NK-derived EVs and the latest advancements in disease therapy. Specifically, we will compare different cellular sources of NKEVs and explore the current status and prospects of memory-like NK cell-derived EVs and engineered NKEVs.

Abstract Previous studies have shown that peripheral nerve injury can lead to abnormal dendritic spine remodeling in spinal dorsal horn neurons. Inhibition of abnormal dendritic spine remodeling can relieve neuropathic pain. Electroacupuncture (EA) has a beneficial effect on the treatment of neuropathic pain, but the specific mechanism remains unclear. Evidence has shown that slit-robo GTPase activating protein 3 (srGAP3) and Rho GTPase (Rac1) play very important roles in dendritic spine remodeling. Here, we used srGAP3 siRNA and Rac1 activator CN04 to confirm the relationship between SrGAP3 and Rac1 and their roles in improving neuropathic pain with EA. Spinal nerve ligation (SNL) was used as the experimental model, and thermal withdrawal latency (TWL), mechanical withdrawal threshold (MWT), Western blotting, immunohistochemistry and Golgi-Cox staining were used to examine changes in behavioral performance, protein expression and dendritic spines. More dendritic spines and higher expression levels of srGAP3 were found in the initial phase of neuropathic pain. During the maintenance phase, dendritic spines were more mature, which was consistent with lower expression levels of srGAP3 and higher expression levels of Rac1-GTP. EA during the maintenance phase reduced the density and maturity of dendritic spines of rats with SNL, increased the levels of srGAP3 and reduced the levels of Rac1-GTP, while srGAP3 siRNA and CN04 reversed the therapeutic effects of EA. These results suggest that dendritic spines have different manifestations in different stages of neuropathic pain and that EA may inhibit the abnormal dendritic spine remodeling by regulating the srGAP3/Rac1 signaling pathway to alleviate neuropathic pain.

BackgroundClear cell renal carcinoma (ccRCC) stands as the prevailing subtype among kidney cancers, making it one of the most prevalent malignancies characterized by significant mortality rates. Notably,mitochondrial permeability transition drives necrosis (MPT-Driven Necrosis) emerges as a form of cell death triggered by alterations in the intracellular microenvironment. MPT-Driven Necrosis, recognized as a distinctive type of programmed cell death. Despite the association of MPT-Driven Necrosis programmed-cell-death-related lncRNAs (MPTDNLs) with ccRCC, their precise functions within the tumor microenvironment and prognostic implications remain poorly understood. Therefore, this study aimed to develop a novel prognostic model that enhances prognostic predictions for ccRCC.MethodsEmploying both univariate Cox proportional hazards and Lasso regression methodologies, this investigation distinguished genes with differential expression that are intimately linked to prognosis.Furthermore, a comprehensive prognostic risk assessment model was established using multiple Cox proportional hazards regression. Additionally, a thorough evaluation was conducted to explore the associations between the characteristics of MPTDNLs and clinicopathological features, tumor microenvironment, and chemotherapy sensitivity, thereby providing insights into their interconnectedness.The model constructed based on the signatures of MPTDNLs was verified to exhibit excellent prediction performance by Cell Culture and Transient Transfection, Transwell and other experiments.ResultsBy analyzing relevant studies, we identified risk scores derived from MPTDNLs as an independent prognostic determinant for ccRCC, and subsequently we developed a Nomogram prediction model that combines clinical features and associated risk assessment. Finally, the application of experimental techniques such as qRT-PCR helped to compare the expression of MPTDNLs in healthy tissues and tumor samples, as well as their role in the proliferation and migration of renal clear cell carcinoma cells. It was found that there was a significant correlation between CDK6-AS1 and ccRCC results, and CDK6-AS1 plays a key role in the proliferation and migration of ccRCC cells. Impressive predictive results were generated using marker constructs based on these MPTDNLs.ConclusionsIn this research, we formulated a new prognostic framework for ccRCC, integrating mitochondrial permeability transition-induced necrosis. This model holds significant potential for enhancing prognostic predictions in ccRCC patients and establishing a foundation for optimizing therapeutic strategies.

HBV infection profoundly escalates hepatocellular carcinoma (HCC) susceptibility, responsible for a majority of HCC cases. HBV-driven immune-mediated hepatocyte impairment significantly fuels HCC progression. Regrettably, inconspicuous early HCC symptoms often culminate in belated diagnoses. Nevertheless, surgically treated early-stage HCC patients relish augmented five-year survival rates. In contrast, advanced HCC exhibits feeble responses to conventional interventions like radiotherapy, chemotherapy, and surgery, leading to diminished survival rates. This investigation endeavors to unearth diagnostic hallmark genes for HBV-HCC leveraging a bioinformatics framework, thus refining early HBV-HCC detection. Candidate genes were sieved via differential analysis and Weighted Gene Co-Expression Network Analysis (WGCNA). Employing three distinct machine learning algorithms unearthed three feature genes (HHIP, CXCL14, and CDHR2). Melding these genes yielded an innovative Artificial Neural Network (ANN) diagnostic blueprint, portending to alleviate patient encumbrance and elevate life quality. Immunoassay scrutiny unveiled accentuated immune damage in HBV-HCC patients relative to solitary HCC. Through consensus clustering, HBV-HCC was stratified into two subtypes (C1 and C2), the latter potentially indicating milder immune impairment. The diagnostic model grounded in these feature genes showcased robust and transferrable prognostic potentialities, introducing a novel outlook for early HBV-HCC diagnosis. This exhaustive immunological odyssey stands poised to expedite immunotherapeutic curatives' emergence for HBV-HCC.

Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD).Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments.Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells.Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.

Head and neck squamous cell carcinoma (HNSCC), as a complex and variable malignancy, poses a significant threat to human health. Since the intricate association between HPV and HNSCC emerged, its role within the TME has garnered extensive attention. HPV+HNSCC exhibits distinct immunological characteristics within the TME, intricately intertwined with mechanisms of immune evasion. HPV employs multifaceted pathways to intervene in metabolic regulation within the TME, exerting influence over immune cell functionality and neoplastic cell genesis. Furthermore, the heightened immune reactivity exhibited by HPV+HNSCC within the TME augments responses to immune interventions such as immune checkpoint inhibitors. Therefore, amidst the current limitations of therapeutic approaches, immunotherapy stands as a promising strategy to overcome the conventional confines of treating HNSCC. This article comprehensively outlines the impact of HPV on the inception and progression of HNSCC while discussing the amalgamation of metabolic regulation within the TME and immunotherapeutic strategies. By intervening in the reciprocal interactions between HPV and HNSCC within the TME, the potential to modulate the efficacy of immune-based treatments becomes evident. Concurrently, a synthesis of pertinent biomarker development is summarized. Such endeavors hold paramount significance for personalized therapeutic approaches and the more effective management of HNSCC patients.

Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients’ visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment.Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay.Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments.Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.

Background: Hepatitis B-related liver cirrhosis (HBV-LC) is a common clinical disease that evolves from chronic hepatitis B (CHB). The development of cirrhosis can be suppressed by pharmacological treatment. When CHB progresses to HBV-LC, the patient’s quality of life decreases dramatically and drug therapy is ineffective. Liver transplantation is the most effective treatment, but the lack of donor required for transplantation, the high cost of the procedure and post-transplant rejection make this method unsuitable for most patients.Methods: The aim of this study was to find potential diagnostic biomarkers associated with HBV-LC by bioinformatics analysis and to classify HBV-LC into specific subtypes by consensus clustering. This will provide a new perspective for early diagnosis, clinical treatment and prevention of HCC in HBV-LC patients. Two study-relevant datasets, GSE114783 and GSE84044, were retrieved from the GEO database. We screened HBV-LC for feature genes using differential analysis, weighted gene co-expression network analysis (WGCNA), and three machine learning algorithms including least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) for a total of five methods. After that, we constructed an artificial neural network (ANN) model. A cohort consisting of GSE123932, GSE121248 and GSE119322 was used for external validation. To better predict the risk of HBV-LC development, we also built a nomogram model. And multiple enrichment analyses of genes and samples were performed to understand the biological processes in which they were significantly enriched. And the different subtypes of HBV-LC were analyzed using the Immune infiltration approach.Results: Using the data downloaded from GEO, we developed an ANN model and nomogram based on six feature genes. And consensus clustering of HBV-LC classified them into two subtypes, C1 and C2, and it was hypothesized that patients with subtype C2 might have milder clinical symptoms by immune infiltration analysis.Conclusion: The ANN model and column line graphs constructed with six feature genes showed excellent predictive power, providing a new perspective for early diagnosis and possible treatment of HBV-LC. The delineation of HBV-LC subtypes will facilitate the development of future clinical treatment of HBV-LC.

Vascular cognitive impairment (VCI) is the initial stage of vascular dementia (VaD). Early diagnosis and treatment of VCI are crucial to prevent the progression of VaD. In order to gain a better understanding of VCI, this study aimed to investigate the use of advanced imaging techniques such as structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI). These techniques allow researchers to observe the structural and functional changes in the brain that are associated with VCI. Functional magnetic resonance imaging (fMRI) and sMRI techniques have been widely used in studies focusing on gray matter, brain networks, and functional abnormalities during rest. By searching and summarizing recent literature, this study has provided valuable evidence on the use of advanced imaging techniques in understanding and treating VCI. The findings from this study can aid in the development of early intervention strategies for patients with VCI, potentially slowing down or even halting the progression of VCI to full-blown VaD.

Subjective cognitive decline (SCD) is the initial stage of Alzheimer’s disease (AD). Early identification of SCD and its risk factors is of great importance for targeted interventions and for delaying the onset of AD. We reviewed the relevant literature on structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), functional magnetic resonance imaging (fMRI), and other techniques regarding SCD research in recent years. This study applied sMRI and fMRI techniques to explore abnormal brain structures and functions, which may help provide a basis for SCD diagnosis.

BackgroundAmnestic mild cognitive impairment (aMCI) is an early stage of Alzheimer’s disease (AD). Regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) are employed to explore spontaneous brain function in patients with aMCI. This study applied ALFF and ReHo indicators to analyze the neural mechanism of aMCI by resting-state functional magnetic resonance imaging (rs-fMRI).MethodsTwenty-six patients with aMCI were included and assigned to the aMCI group. The other 26 healthy subjects were included as a healthy control (HC) group. Rs-fMRI was performed for all participants in both groups. Between-group comparisons of demographic data and neuropsychological scores were analyzed using SPSS 25.0. Functional imaging data were analyzed using DPARSF and SPM12 software based on MATLAB 2017a. Gender, age, and years of education were used as covariates to obtain ALFF and ReHo indices.ResultsCompared with HC group, ALFF decreased in the left fusiform gyrus, left superior temporal gyrus, and increased in the left cerebellum 8, left inferior temporal gyrus, left superior frontal gyrus (BA11), and right inferior temporal gyrus (BA20) in the aMCI group (p

BackgroundPancreatic cancer (PC) is a lethal malignancy that ranks seventh in terms of global cancer-related mortality. Despite advancements in treatment, the five-year survival rate remains low, emphasizing the urgent need for reliable early detection methods. MicroRNAs (miRNAs), a group of non-coding RNAs involved in critical gene regulatory mechanisms, have garnered significant attention as potential diagnostic and prognostic biomarkers for pancreatic cancer (PC). Their suitability stems from their accessibility and stability in blood, making them particularly appealing for clinical applications.MethodsIn this study, we analyzed serum miRNA expression profiles from three independent PC datasets obtained from the Gene Expression Omnibus (GEO) database. To identify serum miRNAs associated with PC incidence, we employed three machine learning algorithms: Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. We developed an artificial neural network model to assess the accuracy of the identified PC-related serum miRNAs (PCRSMs) and create a nomogram. These findings were further validated through qPCR experiments. Additionally, patient samples with PC were classified using the consensus clustering method.ResultsOur analysis revealed three PCRSMs, namely hsa-miR-4648, hsa-miR-125b-1-3p, and hsa-miR-3201, using the three machine learning algorithms. The artificial neural network model demonstrated high accuracy in distinguishing between normal and pancreatic cancer samples, with verification and training groups exhibiting AUC values of 0.935 and 0.926, respectively. We also utilized the consensus clustering method to classify PC samples into two optimal subtypes. Furthermore, our investigation into the expression of PCRSMs unveiled a significant negative correlation between the expression of hsa-miR-125b-1-3p and age.ConclusionOur study introduces a novel artificial neural network model for early diagnosis of pancreatic cancer, carrying significant clinical implications. Furthermore, our findings provide valuable insights into the pathogenesis of pancreatic cancer and offer potential avenues for drug screening, personalized treatment, and immunotherapy against this lethal disease.

BackgroundThe primary pathogenic cause of tooth loss in adults is periodontitis, although few reliable diagnostic methods are available in the early stages. One pathological factor that defines periodontitis pathology has previously been believed to be the equilibrium between inflammatory defense mechanisms and oxidative stress. Therefore, it is necessary to construct a model of oxidative stress-related periodontitis diagnostic markers through machine learning and bioinformatic analysis.MethodsWe used LASSO, SVM-RFE, and Random Forest techniques to screen for periodontitis-related oxidative stress variables and construct a diagnostic model by logistic regression, followed by a biological approach to build a Protein-Protein interaction network (PPI) based on modelled genes while using modelled genes. Unsupervised clustering analysis was performed to screen for oxidative stress subtypes of periodontitis. we used WGCNA to explore the pathways correlated with oxidative stress in periodontitis patients. Networks. Finally, we used single-cell data to screen the cellular subpopulations with the highest correlation by scoring oxidative stress genes and performed a proposed temporal analysis of the subpopulations.ResultsWe discovered 3 periodontitis-associated genes (CASP3, IL-1β, and TXN). A characteristic line graph based on these genes can be helpful for patients. The primary hub gene screened by the PPI was constructed, where immune-related and cellular metabolism-related pathways were significantly enriched. Consistent clustering analysis found two oxidative stress categories, with the C2 subtype showing higher immune cell infiltration and immune function ratings. Therefore, we hypothesized that the high expression of oxidative stress genes was correlated with the formation of the immune environment in patients with periodontitis. Using the WGCNA approach, we examined the co-expressed gene modules related to the various subtypes of oxidative stress. Finally, we selected monocytes for mimetic time series analysis and analyzed the expression changes of oxidative stress genes with the mimetic time series axis, in which the expression of JUN, TXN, and IL-1β differed with the change of cell status.ConclusionThis study identifies a diagnostic model of 3-OSRGs from which patients can benefit and explores the importance of oxidative stress genes in building an immune environment in patients with periodontitis.

Background: The study on Head and Neck Squamous Cell Carcinoma (HNSCC), a prevalent and aggressive form of head and neck cancer, focuses on the often-overlooked role of soluble mediators. The objective is to leverage a transcriptome-based risk analysis utilizing soluble mediator-related genes (SMRGs) to provide novel insights into prognosis and immunotherapy efficacy in HNSCC patients. Methods: We analyzed the expression and prognostic significance of 10,859 SMRGs using 502 HNSCC and 44 normal samples from the TCGA-HNSC cohort in The Cancer Genome Atlas (TCGA). The samples were divided into training and test sets in a 7:3 ratio, with an additional external validation using 40 tumor samples from the International Cancer Genome Consortium (ICGC). Key differentially expressed genes (DEGs) with prognostic significance were identified through univariate and Lasso-Cox regression analyses. A prognostic model based on 20 SMRGs was developed using Lasso and multivariate Cox regression. We assessed the clinical outcomes and immune status in high-risk (HR) and low-risk (LR) HNSCC patients utilizing the BEST databases and single-sample Gene Set Enrichment Analysis (ssGSEA). Results: The 20 SMRGs were crucial in predicting the prognosis of HNSCC, with the SMRG signature emerging as an independent prognostic indicator. Patients classified in the HR group exhibited poorer outcomes compared to those in the LR group. A nomogram, integrating clinical characteristics and risk scores, demonstrated substantial prognostic value. Immunotherapy appeared to be more effective in the LR group, possibly attributed to enhanced immune infiltration and expression of immune checkpoints. Conclusions: The model based on soluble mediator-associated genes offers a fresh perspective for assessing the pre-immune efficacy and showcases robust predictive capabilities. This innovative approach holds significant promise in advancing the field of precision immuno-oncology research, providing valuable insights for personalized treatment strategies in HNSCC.

B cells occupy a vital role in the functioning of the immune system, working in tandem with T cells to either suppress or promote tumor growth within the tumor microenvironment(TME). In addition to direct cell-to-cell communication, B cells and other cells release exosomes, small membrane vesicles ranging in size from 30-150 nm, that facilitate intercellular signaling. Exosome research is an important development in cancer research, as they have been shown to carry various molecules such as major histocompatibility complex(MHC) molecules and integrins, which regulate the TME. Given the close association between TME and cancer development, targeting substances within the TME has emerged as a promising strategy for cancer therapy. This review aims to present a comprehensive overview of the contributions made by B cells and exosomes to the tumor microenvironment (TME). Additionally, we delve into the potential role of B cell-derived exosomes in the progression of cancer.

BackgroundAlzheimer's disease (AD) is a common, progressive, irreversible, and fatal neurodegenerative disorder with rapidly increasing worldwide incidence. Although much research on magnetic resonance imaging (MRI) of the white matter (WM) in AD has been published, no bibliometric analysis study has investigated this issue. Thus, this study aimed to provide an overview of the current status, hotspots, and trends in MRI of WM in AD.MethodsWe searched for records related to MRI studies of WM in AD from 1990 to 2022 in the Web of Science Core Collection (WOSCC) database. CiteSpace (version 5.1.R8) and VOSviewer (version 1.6.19) software were used for bibliometric analyses.ResultsA total of 2,199 articles were obtained from this study. From 1990 to 2022, the number of published articles showed exponential growth of y = 4.1374e0.1294x, with an average of 17.9 articles per year. The top country and institutions were the United States and the University of California Davis, accounting for 44.52 and 5.32% of the total studies, respectively. The most productive journal was Neurology, and the most co-cited journal was Lancet Neurology. Decarli C was the most productive author. The current research frontier trend focuses on the association between small vessel disease and AD, the clinical application and exploration of diffusion MRI, and related markers.ConclusionThis study provides an in-depth overview of publications on MRI of WM in AD, identifying the current research status, hotspots, and frontier trends in the field.

Background: Endometrial cancer (UCEC) is a highly heterogeneous gynecologic malignancy that exhibits variable prognostic outcomes and responses to immunotherapy. The Familial sequence similarity (FAM) gene family is known to contribute to the pathogenesis of various malignancies, but the extent of their involvement in UCEC has not been systematically studied. This investigation aimed to develop a robust risk profile based on FAM family genes (FFGs) to predict the prognosis and suitability for immunotherapy in UCEC patients.Methods: Using the TCGA-UCEC cohort from The Cancer Genome Atlas (TCGA) database, we obtained expression profiles of FFGs from 552 UCEC and 35 normal samples, and analyzed the expression patterns and prognostic relevance of 363 FAM family genes. The UCEC samples were randomly divided into training and test sets (1:1), and univariate Cox regression analysis and Lasso Cox regression analysis were conducted to identify the differentially expressed genes (FAM13C, FAM110B, and FAM72A) that were significantly associated with prognosis. A prognostic risk scoring system was constructed based on these three gene characteristics using multivariate Cox proportional risk regression. The clinical potential and immune status of FFGs were analyzed using CiberSort, SSGSEA, and tumor immune dysfunction and rejection (TIDE) algorithms. qRT-PCR and IHC for detecting the expression levels of 3-FFGs.Results: Three FFGs, namely, FAM13C, FAM110B, and FAM72A, were identified as strongly associated with the prognosis of UCEC and effective predictors of UCEC prognosis. Multivariate analysis demonstrated that the developed model was an independent predictor of UCEC, and that patients in the low-risk group had better overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores exhibited good prognostic power. Patients in the low-risk group exhibited a higher tumor mutational load (TMB) and were more likely to benefit from immunotherapy.Conclusion: This study successfully developed and validated novel biomarkers based on FFGs for predicting the prognosis and immune status of UCEC patients. The identified FFGs can accurately assess the prognosis of UCEC patients and facilitate the identification of specific subgroups of patients who may benefit from personalized treatment with immunotherapy and chemotherapy.

Electroacupuncture (EA) has both anti-inflammatory and cardio-protective effects. Activation of calpain pathway is involved in several myocardiopathy. In sepsis, the role of calpain-2-regulated STAT3 in cardio-protective mechanism of electroacupuncture remains unclear. In this study, we aimed to elucidate the mechanism by which electroacupuncture reduces cardiac inflammation and apoptosis and improves cardiac function during sepsis. Electroacupuncture pretreatment for 7 days was applied in septic cardiomyopathy model induced by lipopolysaccharide (LPS). lipopolysaccharide-induced sepsis was associated with a dramatically systemic inflammation and cardiac dysfunction, which was alleviated by electroacupuncture pre-treatment. Lipopolysaccharide resulted in increases of pro-inflammatory factors (TNF-α,IL1βand IL-6) and apoptosis (TUNEL staining and BAX/Bcl2) via activation of calpain-2/STAT3 pathway.Electroacupuncture pre-treatment inhibited LPS-induced activation of cardiac calpain-2/STAT3 signalling and ameliorated inflammatory and apoptosis. Additionally, inhibition of calpain-2 expression using the corresponding siRNA decreased the Phosphorylation of STAT3,pro-inflammatory factors and apoptosis in lipopolysaccharide- treated cardiomyocytes, confirming that calpain-2 activated p-STAT3 participate in septic cardiomyopathy. Furthermore, suppression of STAT3 by stattic enhanced anti-inflammatory and anti-apoptosis effects of electroacupuncture. These findings reveal mechanisms of electroacupuncture preconditioning protection against cardiac inflammation and apoptosis in sepsis mouse via calpain-2/STAT3 pathway and may provide novel targets for clinical treatments of the sepsis-induced cardiac dysfunction.

Abstract Background The permeability of the blood-spinal cord barrier (BSCB) is mainly determined by junction complexes between adjacent endothelial cells (ECs), including tight junctions (TJs) and adherens junctions (AJs), which can be severely damaged after spinal cord injury (SCI). Exercise training is a recognized method for the treatment of SCI. The destruction of the BSCB mediated by matrix metalloproteinases (MMPs) leads to inflammation, neurotoxin production, and neuronal apoptosis. The failure of new blood vessels to effectively regenerate is also an important cause of delayed recovery after SCI. For the first time, we introduced water treadmill training (TT) to help SCI rats successfully exercise and measured the effects of TT in promoting recovery after SCI and the possible mechanisms involved. Methods Sprague-Dawley (200–250 g) rats were randomly divided into the following three groups: sham operated, SCI, and SCI + TT. Animals were sacrificed at 7 or 14 days post-surgery. The degree of neurological deficit, tissue morphology and BSCB permeability were assessed by the Basso-Beattie-Bresnahan (BBB) motor function scale and appropriate staining protocols, and apoptosis, protein expression and vascular EC ultrastructure were assessed by TUNEL staining, Western blotting, immunofluorescence and transmission electron microscopy (TEM). Results Our experiments showed that TT reduced permeability of the BSCB and decreased structural tissue damage. TT significantly improved functional recovery when compared with that in the SCI group; TJ and AJ proteins expression increased significantly after TT, and training reduced apoptosis induced by SCI. TT could promote angiogenesis, and MMP-2 and MMP-9 expression was significantly inhibited by TT. Conclusions The results of this study indicate that TT promotes functional recovery for the following reasons: TT (1) protects residual BSCB structure from further damage, (2) promotes vascular regeneration, and (3) inhibits MMP-2/9 expression to mitigate BSCB damage.

Abstract Background Acupoint application therapy (AAT) has been widely used to treat allergic inflammation induced by allergic rhinitis (AR). The therapeutic effect of acupoint application is obvious. But the underlying therapeutic mechanism is still indistinct. Nerve growth factor (NGF) expression showed a dramatic rise in nasal mucosa tissue after AR, and allergic inflammation also increased significantly. To demonstrate how AAT can improve allergic inflammation by down-regulating the expression of NGF, AR rat models were established by intraperitoneal injection of ovalbumin (OVA) and nasal drops in SD rats. The number of nasal rubbing, sneezing and the degree of runny nose were observed and the symptoms were scored by behavioral symptom scoring method within 3 min. The expression levels of NGF and its downstream key proteins, such as IL-4, IL-5, IL-13, IgE and IFN-γ were determined by q-PCR, Western blot analysis, ELISA and immunofluorescence staining. Furthermore, H&E staining and toluidine blue staining were used to observe the pathological structure of nasal mucosa and mast cells in nasal mucosa, and the ultrastructure of nasal mucosa was observed by electron microscopy. Results Our data demonstrated that acupoint application significantly reduced the score of behavioral symptoms, and decreased the expression levels of NGF and its downstream key proteins, including IL-4, IL-5, IL-13, IgE, as well as promoting the expression level of IFN-γ in nasal mucosa tissue in AR rats. Thus, the activation of IgE and viability of mast cells was inhibited. Conclusion Our findings suggest that AAT can attenuate allergic inflammation by inhibiting the expression of NGF and its downstream pathway.

Background. Electroacupuncture (EA) has benefits for neuropathic pain. However, the underlying mechanisms are still unknown. The current study explores the underlying mechanisms of EA in neuropathic pain of chronic constriction injury (CCI) rats. Material/Methods. Overall, 126 Sprague-Dawley (200-250 g) rats were divided into nine groups randomly: the sham-operated, CCI, CCI+EA, CCI+sham EA, CCI+NS, CCI+AAV-NC, CCI+AAV-miR-206-3p, CCI+EA+NS, and CCI+EA+AAV-miR-206-3p groups. The animals were sacrificed 14 days postsurgery. Mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) tests were used to determine differences in neurobehavioral manifestations. qPCR, western blotting, and immunofluorescence (IF) were carried out to detect the expression levels of miR-206-3p, BDNF, BAX/Bcl-2, TNF-α, and IL-6. Nissl staining was measured to observe morphological changes in neurons. Transmission electron microscopy (TEM) was employed to evaluate microscopic changes in dorsal horn synapses. Results. Hyperalgesia was reduced markedly by EA in the CCI model. The expression level of miR-206-3p was elevated, whereas the expression levels of BDNF, BAX/Bcl-2, TNF-α, and IL-6 were decreased in EA-treated CCI rats. However, a miR-206-3p inhibitor partially abrogated the analgesic effect of EA and resulted in poor behavioral performance and the BDNF, BAX/Bcl-2, TNF-α, and IL-6 expression was elevated as well. Conclusions. EA can relieve neuropathic pain by regulating the miR-206-3p/BDNF pathway, thus exerting anti-inflammatory and antiapoptotic effect.

Background: Neuroinflammation plays a major role in the development of ischemic stroke, and regulation of the proinflammatory TLR4 signaling pathway in microglia stands to be a promising therapeutic strategy for stroke intervention. Recently, the homeostasis of mitochondrial dynamics has also been raised as a vital component in maintaining neuronal health, but its relevance in microglia hasn't been investigated. Schaftoside, a natural flavonoid compound and a promising treatment for inflammation, has demonstrated potency against LPS-induced lung inflammation in mice; however, its action on TLR4-induced neuroinflammation and mitochondrial dynamics in microglia is still unknown. Methods: The effects of schaftoside in regulating inflammation and mitochondrial dynamics were investigated in vitro in oxygen glucose deprivation (OGD)-stimulated BV2 microglia cells. Results: Schaftoside inhibited mRNA and protein expressions of proinflammatory cytokines (IL-1β, TNF-α, and IL-6) after 4 h in OGD-stimulated BV2 microglia cells, similar to the effect of TAK242, an inhibitor of TLR4. TLR4/Myd88 signaling pathway was effectively suppressed by schaftoside. In addition, both schaftoside and TAK242 treatments significantly decreased Drp1 expression, phosphorylation, translocation and mitochondrial fission in OGD-stimulated BV2 cells. Conclusions: Our study suggested that schaftoside was able to reduce neuroinflammation, which is mediated in part by reducing TLR4/Myd88/Drp1-related mitochondrial fission in BV2 microglia cells. Keywords: Mitochondrial fission, Microglia, TLR4, Stroke, Schaftoside

Traditional Chinese Medicine (TCM) has a rich history spanning thousands of years, with its applications ranging from treating female infertility and recurrent pregnancy loss to managing nausea and vomiting of pregnancy. Yet the safety of pregnant women consuming Chinese herbal medicine (CHM) still lacks sufficient modern clinical research data. On April 19, the journal Acta Obstetricia et Gynecologica Scandinavica published a research article titled "Maternal traditional Chinese medicine exposure and risk of congenital malformations: a multicenter prospective cohort study." The study claimed that "Periconceptional TCM exposure is associated with an increased risk of congenital malformation," drawing attention from both English and Chinese media outlets, which extensively reported and commented on the findings. In response, various TCM organizations contested the research, asserting that it failed to adhere to fundamental standards of academic rigor, statistical analysis, and necessary methodologies to draw conclusions. International TCM practitioners and scholars thoroughly examined the article, uncovering multiple errors and arguing that these misleading conclusions significantly undermined the reputation of CHM. These scholars communicated their doubts directly to the corresponding author and the journal's chief editor, emphasizing that the article's conclusion was derived from secondary data analysis of another clinical research project and funding sources, therefore, called for withdrawal of the article. Eventually, the article was retracted due to flaws with the study design in collecting data on exposure to TCM in pregnant women, which affects the validity of the data to support the conclusions of the study. This article conducts a comprehensive academic inquiry into the article, meticulously outlining the identified errors, discusses the reproductive toxicity of CHM, and provides suggestions for future research to evaluate the safety of pregnant women using CHM rigorously, emphasizing evaluation on teratogenicity research of CHM should not only be based on study using healthy animals, but also incorporate clinical epidemiological research and disease-syndrome-based toxicology. [ABSTRACT FROM AUTHOR]