ObjectiveTo elucidate the effects of autonomic neuromodulators [calcium chloride (CaCl₂)-acetylcholine (ACh)] on atrial electrical remodeling and histopathological changes in rats, thereby providing evidence for further investigation into the pathological mechanisms by which autonomic imbalance induces atrial fibrillation (AF). MethodsTen 8-week-old male Sprague-Dawley (SD) rats were randomly divided into experimental and control groups, with 5 rats in each group. The experimental group received daily tail vein injections of a CaCl₂-ACh mixed solution for 28 days, while the control group received an equal volume of saline. Surface electrocardiograms were recorded before and after daily administration. On day 28 of administration, under isoflurane inhalation anesthesia, echocardiography was performed, and then the rats were euthanized by exsanguination under isoflurane anesthesia for tissue collection. Body weight and heart weight of rats were measured, and electrophysiological parameters including AF inducibility, conduction velocity, and conduction dispersion in isolated rat hearts were monitored using the MappingLab multichannel electrophysiological mapping system. HE staining was performed to evaluate atrial tissue architecture and inflammatory cell infiltration. The expression levels of matrix metalloproteinase 9 (MMP-9) and interleukin-1 beta (IL-1β) were analyzed by Western blotting. Masson staining was used to quantitatively analyze the proportional distribution of collagen fibers and myocardial fibers, and to calculate the area of collagen deposition, thereby evaluating the degree of myocardial fibrosis. Wheat germ agglutinin (WGA) staining was used to evaluate morphological changes of cardiomyocytes. Dihydroethidium (DHE) staining was used to detect the level of oxidative stress in atrial myocytes. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining was used to detect atrial cell apoptosis. ResultsCompared with the control group, the experimental group showed obvious arrhythmias on electrocardiograms. Echocardiography after 28 days of administration revealed significant structural remodeling in the experimental group, with a marked increase in left atrial anteroposterior diameter (P < 0.05), and also showed cardiac dysfunction, with significant decreases in left ventricular ejection fraction and left ventricular fractional shortening (P < 0.01). Compared with the control group, the experimental group showed a significantly increased heart weight-to-body weight ratio (P < 0.05), a markedly higher AF inducibility (P < 0.001), a significantly slowed atrial conduction velocity (P < 0.05), an uneven isochronal map with irregular directions, and a significantly increased conduction dispersion (P < 0.01). HE staining showed that atrial myocytes in the experimental group were disorganized, with slight inflammatory cell infiltration. Western blotting showed that the expression levels of MMP-9 and IL-1β in the atrial tissue of the experimental group were significantly upregulated (P < 0.05). Masson staining showed a significant increase in collagen deposition and a significant increase in fibrosis area in the atrial tissue of the experimental group (P < 0.001). WGA staining showed that cardiomyocytes in the experimental group were significantly hypertrophied compared with the control group (P < 0.05). DHE staining and TUNEL staining revealed that the level of oxidative stress in atrial myocytes (P < 0.001) and the apoptotic rate (P < 0.01) were both significantly increased. Conclusion Daily tail vein injections of the autonomic neuromodulator CaCl₂-ACh mixed solution for 28 days can successfully induce AF in rats, accompanied by significant atrial structural remodeling, electrical remodeling, and oxidative stress.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Exosomal circular RNA(circRNAs)are pivotal in cancer biology,and tumor pathophysiology.These stable,non-coding RNAs encapsulated in exosomes participated in cancer progression,tumor growth,metas-tasis,drug sensitivity and the tumor microenvironment(TME).Their presence in bodily fluids positions them as potential non-invasive biomarkers,revealing the molecular dynamics of cancers.Research in exosomal circRNAs is reshaping our understanding of neoplastic intercellular communication.Exploiting the natural properties of exosomes for targeted drug delivery and disrupting circRNA-mediated pro-tumorigenic signaling can develop new treatment modalities.Therefore,ongoing exploration of exoso-mal circRNAs in cancer research is poised to revolutionize clinical management of cancer.This emerging field offers hope for significant breakthroughs in cancer care.This review underscores the critical role of exosomal circRNAs in cancer biology and drug resistance,highlighting their potential as non-invasive biomarkers and therapeutic targets that could transform the clinical management of cancer.

Objective To observe the value of CT angiography(CTA)radiomics for evaluating the risk of basilar tip aneurysm(BTA)rupture.Methods Totally 133 BTA patients were retrospectively enrolled and divided into ruptured group(n=39)and unruptured group(n=94)based on BT A ruptured or not,also divided into training set(n=93)and test set(n=40)at the ratio of 7∶3.CTA radiomics features of BTA were extracted,the best radiomics features were screened,and the radiomics score(Radscore)was calculated.Then machine learning(ML)models were established with logistic regression(LR),random forest(RF),decision tree(DT)and K-nearest neighbor(KNN)algorithms,respectively.Radscore model was also established,and finally a combined model was constructed based on clinical data,routine imaging findings and Radscore.The efficacy of the above models for evaluating the risk of BTA rupture were comparatively analyzed.Results Finally 4 radiomics features of BTA were obtained.The area under the curve(AUC)of LR,RF,DT and KNN radiomics models for differentiating ruptured and unruptured BTA in training set was 0.770,0.816,0.817 and 0.795,respectively,while that in test set was 0.795,0.793,0.786 and 0.824,respectively,both being not significant different(both P＞0.05).Patient's gender,alcohol consumption history,BTA morphology and Radscore were all independent impact factors of BT A rupture(all P＜0.05),which were used to establish a clinical-routine imaging model.For all 133 cases,AUC of the combination model for differentiating ruptured and unruptured BTA was 0.877,of Radscore model was 0.775,while that of clinical-routine imaging model was 0.677,of the former was significantly higher than of the last two(both P＜0.05).Conclusion CTA radiomics was helpful for evaluating the risk of BTA rupture.Combining with clinical data and routine imaging findings could further improve the value of CTA radiomics.

Ferroptosis has received great attention as an iron-dependent programmed cell death for efficient cancer therapy. However, with the accumulation of iron in tumor cells, the antioxidant system is activated by reducing glutathione (GSH) with glutathione peroxidase 4 (GPX4), which critically limits the ferroptosis therapeutic effect. Herein, an iron and GPX4 silencing siRNA (siGPX4) co-encapsulated ferritin nanocage (HFn@Fe/siGPX4) was developed to enhance ferroptosis by disruption of redox homeostasis and inhibition of antioxidant enzyme synergistically. The siGPX4 were loaded into the nanocages by pre-incubated with iron, which could significantly improve the loading efficiency of the gene drugs when compared with the reported gene drug loading strategy by ferritin nanocages. And more iron was overloaded into the ferritin through the diffusion method. When HFn@Fe/siGPX4 was taken up by human breast cancer cell MCF-7 in a TfR1-mediated pathway, the excess iron ions in the drug delivery system could for one thing induce ferroptosis by the production of reactive oxygen species (ROS), for another promote siGPX4 escaping from the lysosome to exert gene silencing effect more effectively. Both the in vitro and in vivo results demonstrated that HFn@Fe/siGPX4 could significantly inhibit tumor growth by synergistical ferroptosis. Thus, the developed HFn@Fe/siGPX4 afforded a combined ferroptosis strategy for ferroptosis-based antitumor as well as a novel and efficient gene drug delivery system.

Exosomal circular RNA (circRNAs) are pivotal in cancer biology, and tumor pathophysiology. These stable, non-coding RNAs encapsulated in exosomes participated in cancer progression, tumor growth, metastasis, drug sensitivity and the tumor microenvironment (TME). Their presence in bodily fluids positions them as potential non-invasive biomarkers, revealing the molecular dynamics of cancers. Research in exosomal circRNAs is reshaping our understanding of neoplastic intercellular communication. Exploiting the natural properties of exosomes for targeted drug delivery and disrupting circRNA-mediated pro-tumorigenic signaling can develop new treatment modalities. Therefore, ongoing exploration of exosomal circRNAs in cancer research is poised to revolutionize clinical management of cancer. This emerging field offers hope for significant breakthroughs in cancer care. This review underscores the critical role of exosomal circRNAs in cancer biology and drug resistance, highlighting their potential as non-invasive biomarkers and therapeutic targets that could transform the clinical management of cancer.

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

Objective:To analyze the characteristics of cardiovascular and cerebrovascular diseases in patients with primary aldosteronism (PA) and compare them with age-, sex-, and blood pressure-matched patients with essential hypertension (EH).Methods:This cross-sectional study was conducted at the West China Hospital of Sichuan University. Patients with PA and EH between December 2018 and December 2021 were included. Demographic characteristics, stroke events, coronary artery diseases, peripheral vascular diseases, and cardiac structure and function indicators were analyzed. Propensity score matching (PSM) was used to balance non-study data. The t-test, chi-square test, and Wilcoxon signed-rank test were used for data comparison. The cardiovascular and cerebrovascular damage in the patients with unilateral and bilateral PA were also compared. Results:A total of 336 and 369 patients with PA and EH, respectively, were enrolled in this study. One hundred and ninety-eight patients from each group were included after PSM; no significant differences were found in terms of age, gender, and blood pressure. The prevalence of stroke in the PA group was considerably higher than that in the EH group [12.6% (25/198) vs. 5.6% (11/198), P=0.014], due to the significantly greater risk of ischemic stroke [10.0% (20/198) vs. 4.5% (9/198), P=0.029]. The prevalence of hemorrhagic stroke, coronary artery disease, peripheral arterial stenosis, aorta atherosclerosis, and aneurysm in the PA group were also higher than those in the EH group, but there was no statistical significance (all P>0.05). More patients with PA had concurrent left ventricular hypertrophy [22.2% (44/198) vs. 9.1% (18/198)], left atrial enlargement [40.4% (80/198) vs. 30.3% (60/198)], ventricular septal thickening [50.0% (99/198) vs. 36.9% (73/198)], and aortic widening [21.7% (43/198) vs. 13.1% (26/198)] than those with EH (all P<0.05). Compared with the bilateral PA group, the unilateral PA group had higher prevalence of left ventricular hypertrophy [28.3% (51/180) vs. 13.4% (11/82), P=0.013]. Conclusions:Compared with well-matched patients with EH, patients with PA have significantly higher risks of cardiovascular and cerebrovascular diseases, which are mainly manifested in increased prevalence of stroke and severe damage to the cardiac structure. Patients with unilateral PA may suffer more severe cardiac damage than those with bilateral PA.