Alzheimer's disease (AD), a prototypical neurodegenerative disorder, encompasses multifaceted pathological processes. As pivotal cellular structures within the central nervous system, ion channels play critical roles in regulating neuronal excitability, synaptic transmission, and neurotransmitter release. Extensive research has revealed significant alterations in the expression and function of ion channels in AD, implicating an important role of ion channels in the pathogenesis of abnormal Aβ deposition, neuroinflammation, oxidative stress, and disruptions in calcium homeostasis and neural network functionality. This review systematically summarizes the crucial roles and underlying mechanisms of ion channels in the onset and progression of AD, highlighting how these channel abnormalities contribute to AD pathophysiology. We also discuss the therapeutic potential of ion channel modulation in AD treatment, emphasizing the importance of addressing multifactorial nature and heterogeneity of AD. The development of multi-target drugs and precision therapies is proposed as a future direction of scientific research.
Alzheimer Disease/therapy* ; Humans ; Ion Channels/physiology* ; Oxidative Stress ; Animals ; Amyloid beta-Peptides/metabolism* ; Synaptic Transmission ; Calcium/metabolism*

OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

Objective:To evaluate the value of a combined model based on primary lesion 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT radiomics for predicting lymph node metastasis in non-small cell lung cancer (NSCLC) . Methods:A retrospective analysis was conducted on the clinical data of 203 NSCLC patients who underwent pre-treatment PET/CT imaging at Nanjing Drum Tower Hospital from June 2013 to July 2023. Patients were randomly assigned to the training set ( n=142) and the validation set ( n=61) at a ratio of 7∶3. A predictive model was developed in the training set, and its predictive performance and clinical application value were assessed in both the training and validation sets. Traditional PET/CT parameters and PET/CT radiomics features of the primary lesion were obtained by 3D-slicer software. Least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting were performed to extract features. Support vector machine was used to construct a radiomics score (Radscore). Univariate and multivariate logistic regression analysis was used to predict the influencing factors of lymph node metastasis in NSCLC patients and to establish models. Predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves and clinical application value was assessed by calibration curves and decision curve analysis (DCA) . Results:Among 203 NSCLC patients, 116 had lymph node metastasis, with 64 cases in the training set and 52 cases in the validation set. Three complementary classical machine learning methods were used for feature screening, and finally 10 radiomics features were obtained. The optimal threshold for Radscore-PET was 0.43 and the optimal threshold for Radscore-CT was 0.39. Univariate analysis showed that, sex ( OR=0.48, 95% CI: 0.24-0.95, P=0.036), tumor marker levels ( OR=3.81, 95% CI: 1.84-7.91, P<0.001), long diameter of tumor ( OR=2.56, 95% CI: 1.27-5.16, P=0.009), short diameter of tumor ( OR=3.73, 95% CI: 1.75-7.92, P=0.001), vacuolar sign ( OR=0.32, 95% CI: 0.12-0.86, P=0.024), ring-like metabolism ( OR=3.67, 95% CI: 1.33-10.13, P=0.012), maximum standardized uptake value (SUV max) ( OR=6.57, 95% CI: 3.03-14.25, P<0.001), metabolic tumor volume (MTV) ( OR=2.91, 95% CI: 1.43-5.92, P=0.003), total lesion glycolysis (TLG) ( OR=4.23, 95% CI: 2.08-8.59, P<0.001), Radscore-PET ( OR=21.93, 95% CI: 9.04-53.20, P<0.001) and Radscore-CT ( OR=13.72, 95% CI: 6.12-30.76, P<0.001) were all influencing factors for predicting lymph node metastasis in NSCLC patients. Multivariate analysis showed that, tumor marker levels ( OR=2.55, 95% CI: 1.11-5.90, P=0.028), vacuolar sign ( OR=0.26, 95% CI: 0.08-0.83, P=0.023), SUV max ( OR=5.94, 95% CI: 1.99-17.75, P=0.001), Radscore-PET ( OR=25.51, 95% CI: 5.92-110.22, P<0.001), and Radscore-CT ( OR=8.68, 95% CI: 2.73-27.61, P<0.001) were independent influencing factors for predicting lymph node metastasis in patients with NSCLC. Based on the above independent influencing factors, models were constructed: the traditional model (tumor marker levels, vacuolar sign, SUV max), the PET model (SUV max, Radscore-PET), the CT model (vacuolar sign, Radscore-CT), and the combined model (tumor marker levels, vacuolar sign, SUV max, Radscore-PET, Radscore-CT). ROC curve analysis showed that, the area under curve (AUC) of the traditional, PET, CT, and combined models in the training set were 0.75 (95% CI: 0.67-0.82), 0.90 (95% CI: 0.84-0.95), 0.85 (95% CI: 0.78-0.90), and 0.94 (95% CI: 0.88-0.97), respectively. The predictive value of the combined model was higher than that of the traditional model ( Z=5.01, P<0.001), the PET model ( Z=1.99, P=0.047), and the CT model ( Z=3.25, P=0.001). In the validation set, the AUCs for the traditional model, PET model, CT model, and combined model were 0.65 (95% CI: 0.52-0.77), 0.86 (95% CI: 0.74-0.93), 0.85 (95% CI: 0.73-0.93), and 0.90 (95% CI: 0.80-0.96), respectively. The predictive value of the combined model was superior to that of the traditional model ( Z=3.23, P=0.001). The sensitivity and specificity of the combined model in the training set were 84.37% and 91.03%, while in the validation set, the sensitivity and specificity were 82.61% and 94.74%, respectively. Calibration curves showed a good agreement between the predicted and actual probabilities in both the training and validation sets. DCA showed that the combined models had good discriminative ability in both the training and validation sets. Conclusions:Tumor marker levels, vacuolar sign, SUV max, Radscore-PET, and Radscore-CT are all independent influencing factors for predicting lymph node metastasis in patients with NSCLC. The combined model based on these factors demonstrates excellent predictive performance and clinical application value for predicting lymph node metastasis in NSCLC.

This review delves into the pivotal role of necrotic apoptosis in Alzheimer's disease(AD),with a focus on treatment strategies,drug development,prospects,and challenges,highlighting its significance in the progression of the disease.Firstly,necrotic apoptosis plays a crucial role in the pathogenesis of AD,particularly in association with the abnormal metabolism of β-amyloid(Aβ)and Tau proteins.The primary focus of drug design is to regulate the metabolism pathways of these two proteins to slow down or inhibit the progression of necrotic apoptosis.Secondly,the progress in drug development further emphasizes the importance of necrotic apoptosis in treating AD.Current research mainly focuses on drugs that affect the metabolism of Aβ and Tau proteins,such as lecanemab.Still,inconsistent result underscore the necessity for a more comprehensive understanding of the molecular mechanisms of necrotic apoptosis.Finally,the prospects and challenges of necrotic apoptosis research in AD are thoroughly discussed.A deeper understanding of necrotic apoptosis contributes to a better comprehension of the pathological mechanisms of AD but also may reveal new therapeutic targets.However,challenges such as multifactorial influences and the selection of treatment timing necessitate further in-depth research in the future.In conclusion,this review advocates for future research to deepen the understanding of the molecular mechanisms of necrotic apoptosis,enhance research on treatment strategies,gain a deeper understanding of its cross-regulation with other cell death pathways,and promote collaboration between basic research and clinical practice to advance the comprehensive understanding and treatment of Alzheimer's disease and necrotic apoptosis.

With the improvement of China's socioeconomic status,the issue of aging has become increasingly prominent,making cerebral infarction a common disease among the elderly.In recent years,research on cerebral infarction has gradually deepened,shifting focus from merely protecting and repairing neurons to emphasizing the complex interplay between inflammatory response and autophagy in the brain vascular unit,covering various aspects such as the blood-brain barrier,astrocytes,microglia,and autophagy.This shift in research direction has provided us with a profound understanding of the mechanisms underlying cerebral infarction,offering strong support for innovative future treatment strategies.In this review,we delved into the importance of the interplay between inflammatory response and autophagy in the pathogenesis of cerebral infarction,emphasized the intricate interactions among these biological components,which might lay the groundwork for more effective managements and treatments of cerebral infarction.By comprehensively reviewing existing literatures,we proposed future research directions,aiming to provide more scientific and systematic guidance for the clinical management and treatment of cerebral infarction.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective:To investigate the effects of CP-31398 on proliferation and metastasis of gallbladder carcinoma cell lines expressing mutant P53GBC-SD and wild-type p53NOZ.Meth-ods:The effects of CP-31398 on the proliferation of wild-type and mutant p53 gallbladder carci-noma cells were detected by CCK8 cell proliferation assay and clonal formation assay.The effect of CP-31398 on cell cycle and apoptosis of gallbladder carcinoma was detected by flow cytometry.The effects of CP-31398 on the migration and invasion of gallbladder carcinoma cells were detected by scratch,cytoskeleton and Transwell assay.The effect of CP-31398 on the expression of p53 protein was detected by Western blot and the related mechanism was discussed.Results:In mutant P53GBC-SD cells,the proliferation of CCK8 cells showed that the proliferation rate of gallbladder cancer cells in CP-31398 treatment group was slower than that in control group(P＜0.01).The cycle experiment showed that compared with the control group,the proportion of cells in S phase in-creased in CP-31398 treatment group,and the proportion of cells in G0 and G1 phase decreased,so the cells were blocked in S phase(P＜0.001).Apoptosis experiment showed that the apoptosis rate of control group was lower than CP-31398 treatment group(P＜0.05).Transwell experiment showed that the number of cells passing through the cell compartment in the control group was higher than that in the CP-31398 treatment group.Western blot analysis showed that the expression of p53 pro-tein in CP-31398 treatment group was increased(P＜0.05).In wild-type p53NOZ cells,the prolifera-tion of CCK8 cells showed that the proliferation rate of gallbladder cancer cells in CP-31398 treat-ment group was slower than that in control group.The number of cell clones in the control group was higher than that in the CP-31398 treatment group(P＜0.001).The cycle test showed that the propor-tion of cells in G2 and M phases increased significantly,while the proportion of cells in G0 and G1 phases decreased,and the cells were blocked in G2 and M phases(P＜0.001).Apoptosis experiment showed that the apoptosis rate of control group was(14.04±3.08)％,and that of CP-31398 treat-ment group was(34.55±3.30)％(P＜0.01).Transwell experiment showed that the number of cells passing through the cell compartment in the control group was higher than that in the CP-31398 treatment group.Western blot analysis showed that the expression of p53 protein in CP-31398 treatment group was increased(P＜0.01).Conclusion:CP-31398 can effectively inhibit the prolif-eration and metastasis of gallbladder cancer cells,and is independent of p53 mutation,and CP-31398 has a good effect on NOZ gallbladder cancer cell lines expressing wild-type p53,which can be used as a new drug treatment for gallbladder cancer.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

BACKGROUND: The benefits of healthy lifestyles are well recognized. However, the extent to which improving unhealthy lifestyles reduces cardiovascular disease (CVD) risk needs to be discussed. We evaluated the impact of lifestyle improvement on CVD incidence using data from the China-PAR project (Prediction for Atherosclerotic Cardiovascular Disease Risk in China). METHODS: A total of 12,588 participants free of CVD were followed up for three visits after the baseline examination. Changes in four lifestyle factors (LFs) (smoking, diet, physical activity, and alcohol consumption) were assessed through questionnaires from the baseline to the first follow-up visit. Cox proportional hazard models were used to estimate hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). The risk advancement periods (RAPs: the age difference between exposed and unexposed participants reaching the same incident CVD risk) and population-attributable risk percentage (PAR%) were also calculated. RESULTS: A total of 909 incident CVD cases occurred over a median follow-up of 11.14 years. Compared with maintaining 0-1 healthy LFs, maintaining 3-4 healthy LFs was associated with a 40% risk reduction of incident CVD (HR = 0.60, 95% CI: 0.45-0.79) and delayed CVD risk by 6.31 years (RAP: -6.31 [-9.92, -2.70] years). The PAR% of maintaining 3-4 unhealthy LFs was 22.0% compared to maintaining 0-1 unhealthy LFs. Besides, compared with maintaining two healthy LFs, improving healthy LFs from 2 to 3-4 was associated with a 23% lower risk of CVD (HR = 0.77, 95% CI: 0.60-0.98). CONCLUSIONS Long-term sustenance of healthy lifestyles or improving unhealthy lifestyles can reduce and delay CVD risk.

Liver fibrosis is a pathological condition characterized by replacement of normal liver tissue with scar tissue, and also the leading cause of liver-related death worldwide. During the treatment of liver fibrosis, in addition to antiviral therapy or removal of inducers, there remains a lack of specific and effective treatment strategies. For thousands of years, Chinese herbal medicines (CHMs) have been widely used to treat liver fibrosis in clinical setting. CHMs are effective for liver fibrosis, though its mechanisms of action are unclear. In recent years, many studies have attempted to determine the possible mechanisms of action of CHMs in treating liver fibrosis. There have been substantial improvements in the experimental investigation of CHMs which have greatly promoted the understanding of anti-liver fibrosis mechanisms. In this review, the role of CHMs in the treatment of liver fibrosis is described, based on studies over the past decade, which has addressed the various mechanisms and signaling pathways that mediate therapeutic efficacy. Among them, inhibition of stellate cell activation is identified as the most common mechanism. This article provides insights into the research direction of CHMs, in order to expand its clinical application range and improve its effectiveness.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Fibrosis ; Liver Diseases/drug therapy* ; Treatment Outcome ; Liver Cirrhosis/drug therapy*