Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Aim To investigate the therapeutic effect of newly formulated Tadalafil tablets on liver fibrosis in mice induced by carbon tetrachloride(CCl4)and its impact on the activation of hepatic stellate cells(HSCs).Methods Liver fibrosis model was estab-lished by intraperitoneally injecting 20％CCl4 corn oil solution twice a week for eight weeks.After four weeks of modeling,the treatment group was administered ei-ther the newly formulated Tadalafil tablets(1.0 mg·kg-1)or the Cialis(2.5 mg·kg-1)via gavage for the remaining four weeks.We assessed the effects of Tadalafil on collagen deposition,tissue structural dam-age,and HSCs activation markers in the fibrotic liver of mice using serum biochemical analysis,histopathologi-cal staining,and Western blotting following the treat-ment period.LX-2 cells were cultured and treated with tadalafil after TGF β1 stimulation,and the effects of tadalafil on LX-2 cell activation were assessed via Western blot.Results Compared to the normal mice,the model group mice exhibited a significantly higher liver-specific index,increased liver function indicators,and notable hepatocyte necrosis.Additionally,liver lobules were damaged,accompanied by severe infiltra-tion of inflammatory cells.Both smooth muscle actin(α-SMA)and fibronectin(Fn)were elevated,serving as markers of HSCs activation.As a result of treatment with the newly formulated Tadalafil tablets,liver tissue damage was significantly reduced,transaminase levels decreased,necrosis and inflammatory cell infiltration were reduced,and collagen fiber deposition was allevia-ted,and α-SMA and Fn expression was reduced.It was worth noting that low-dose newly formulated Tadalafil tablets were found to be as effective as high-dose Cia-lis.In a cellular model,Tadalafil significantly inhibited the activation of LX-2 cells and reduced the expression of proteins related to cell activation.Conclusions The newly formulated Tadalafil tablets can significantly inhibit HSCs activation,reduce extracellular matrix(ECM)deposition,improve liver fibrosis and liver function damage caused by CCl4.This new formulation offers a significant advantage over Cialis in terms of ef-fectiveness,with a lower effective dose.

Objective To investigate the effects of ischemia time and storage periods on RNA quality in fresh-frozen breast cancer(BC)and esophageal cancer(EC)tissue samples in order to establish evidence-based protocols for biobank sample management.Methods The tumor(T)and paired normal(N)tissue samples from 6 cases of BC and 6 cases of EC were collected and cryopreserved in Biobank,Shantou Central Hospital.Mirror paraffin-embedded tissues were simultaneously prepared into sections for morphological analysis.The samples were divided into two groups of<15 min and 15-30 min according to ischemia time,and RNA quality was analyzed at 4 storage periods of 8-10 months(T1),14-16 months(T2),26-28 months(T3)and 38-40 months(T4).Results In 96 analyzed samples,93.8%(90/96)exhibited high quality(RIN≥6),with 89.6%(43/48)in BC and 97.9%(47/48)in EC.Significant differences in RIN were observed between BC group and EC group(8.050 vs.8.600,P=0.009).In EC group,RIN value was significantly negatively correlated with RNA yield(P<0.001).Moreover,RIN values of tumor-normal pairs exhibited markedly significant differences(7.550 vs.9.000,P<0.001).In contrast,no significant difference was detected in BC group(8.200 vs.7.700,P=0.348).Statistical analysis showed that RIN value was positively correlated with 28S/18S(P<0.001),but had no correlation with tumor content(P=0.676)and necrotic content(P=0.055).Neither ischemia time(<15 min vs.15-30 min:8.200 vs.8.300,P=0.932)nor storage periods(T1-T4:8.400,7.700,8.450,8.600,P=0.163)compromised RNA quality.Conclusion Organ origin and tissue type could influence RNA quality of fresh-frozen tissue samples.However,limited ischemia time(≤30 min)and long-term storage period(38-40 months)do not adversely affect RNA quality in fresh-frozen breast cancer and esophageal cancer tissue samples.

To analyze the ethnic differences in the genotype distribution of thalassemia between the Han and Li ethnic groups in the Qiongnan region (southern Hainan). A cross-sectional study employing a stratified multistage sampling method was conducted from January 2019 to December 2023. A total of 4 493 high-risk individuals (2 734 Han and 1 759 Li) from southern Hainan (including Sanya, Ledong, Baoting, Lingshui, and other counties) underwent thalassemia genetic testing. The genotype distribution was statistically analyzed. Inter-group comparisons were performed using χ2 test or Fisher′s exact test. The results showed an overall thalassemia positivity rate of 66.70% (2 997/4 493), with carrier, intermediate and major thalassemia rates of 62.01% (2 786/4 493), 3.98% (179/4 493) and 0.71% (32/4 493), respectively. The positivity rates for thalassemia were 87.83% (1 545/1 759) in the Li ethnic group and 53.11% (1 452/2 734) in the Han ethnic group. Among them, the Li ethnic group exhibited significantly higher positivity rates for α-thalassemia (71.12% vs. 40.64%, χ2=398.90, P<0.001) and α/β-compound thalassemia (13.36% vs. 3.33%, χ2=160.06, P<0.001) compared to the Han ethnic group, whereas the Han ethnic group had a higher β-thalassemia rate (9.14% vs. 3.35%, χ2=56.03, P<0.001). Both ethnic groups shared common α-thalassemia alleles (-α 3.7 and -α 4.2), but the -- SEA allele proportion was significantly higher in Han (21.33% vs. 4.34%, χ2=231.45, P<0.001). Six rare -α 21.9 mutations (0.26%) were exclusively identified in the Li ethnic group, whereas none were found in Han. For β-thalassemia, the β CD41-42 allele was predominant in Li (96.60% vs. 71.01%, χ2=77.24, P<0.001), whereas other alleles (β IVS-II-654, β CD71-72, β CD17, and β -28) were more prevalent in Han (11.01%, 6.96%, 4.64%, and 3.19% vs. 1.54%, 0.00%, 0.31%, and 0.62%, respectively),all P<0.05. In conclusion, distinct ethnic disparities in thalassemia genotype distribution are observed in southern Hainan. The Li ethnic group is predominantly characterized by α-thalassemia and α/β-compound genotypes with a predominant β CD41-42 mutation. In contrast, the Han ethnic group displays higher -- SEA proportion and heterogeneous β-thalassemia genotypes.

Objective To investigate the association of insulin resistance(IR)and its related indices,including triacylglycerol-glucose(TyG)index and metabolic score of insulin resistance(Mets-IR),with the occurrence of early neurological deterioration(END)in patients with branch atheromatous disease(BAD),and develop a risk prediction model based on these factors.Methods A total of 189 BAD patients were consecutively recruited from the Department of Neurology of the Second Affiliated Hospital of Zhengzhou University between March 2020 and August 2024.Based on the occurrence of END within 7 d after admission,the participants were stratified into END(75 cases)and non-END(114 cases)groups.Demographic characteristics,clinical parameters,TyG index and Mets-IR values were systematically collected and analyzed.Multivariate logistic regression analysis was performed to identify independent risk factors for END in BAD-related stroke.Receiver operating characteristic curve(ROC)analysis was subsequently conducted to evaluate the predictive performance of significant variables,followed by construction of a nomogram prediction model.Results The END group exhibited significantly elevated fasting blood glucose[6.47(5.74,7.86)mmol/L vs 5.83(5.14,6.70)mmol/L]and triacylglycerol[1.65(1.21,2.04)mmol/L vs 1.27(0.99,1.57)mmol/L]levels,higher body mass index[25.02(23.88,26.67)kg/m2 vs 23.71(22.66,25.27)kg/m2]and TyG index(9.03±0.41 vs 8.71±0.45),and increased Mets-IR(39.98±4.23 vs 36.85±4.38)and NIHSS score[5.00(3.00,7.00)vs 3.00(2.00,5.00)]at admission when compared with the non-END group(P＜0.05).Multivariate logistic regression analysis showed that high TyG index(OR=3.751,95％CI:1.592-9.202,P＜0.01),Mets-IR(OR=1.146,95％CI:1.049-1.252,P＜0.01),and NIHSS score at admission(OR=1.279,95％CI:1.128-1.451,P＜0.01)were risk factors for the occurrence of END in BAD patients(P＜0.05).ROC curve indicated that the AUC value of TyG index,Mets-IR,and NIHSS score at admission in predicting END occurrence was 0.698(95％CI:0.623-0.774,P＜0.01),0.698(95％CI:0.620-0.775,P＜0.01),and 0.666(95％CI:0.586-0.745,P＜0.01),respectively.The nomogram prediction model based on these factors demonstrated significant clinical benefits by decision curve analysis and goodness of fit in internal calibration analysis.Conclusion IR shows significant association with END in BAD patients.The IR related indices,TyG index and Mets-IR,have certain predictive efficiency for occurrence and progression of END.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective:To detect the expression of autophagy-related genes (ATGs) involved in the late stage of autophagy in peripheral blood mononuclear cells (PBMCs) of patients with ankylosing spondylitis (AS), analyze the difference and explore its possible clinical significance.Methods:① Peripheral blood specimens and clinical data were collected from 90 AS patients (AS group) who attended the outpatient clinic of the Department of Rheumatology and Immunology of the Affiliated Hospital of North Sichuan Medical College from March 2022 to August 2023, among which 30 patients were treated with secukinumab monoclonal antibody for 24 weeks (the treatment group), and clinical data and peripheral blood specimens from 45 healthy individuals (the HC group) who had medical checkups in the Affiliated Hospital of Chuanbei Medical College during the same period were used as the control group. As the control group, the mRNA expression levels of six ATGs (ATG5, ATG7, LC3-Ⅱ, ATG4B, ATG2A, ATG10) involved in the late autophagy stage were detected in PBMCs of peripheral blood specimens by RT-qPCR, and were compared among different groups, and the measured data conformed to the normal distribution were analyzed using the paired t-test, and the abnormal distribution date were analyzed using the Wilcoxon signed-rank test. Wilcoxon signed-rank test was used for measurement data, and Spearman correlation analysis was used for correlation analysis. ② Receiver operating curve (ROC) was used to verify the difference in the expression of ATGs in the late stage of autophagy between AS group and HC group to evaluate its value in the diagnosis of AS and the inflammatory state of the disease. Results:① Compared with the HC group, ATG2A [2.00(1.10, 2.70)×10 -3, 7.50(4.60, 10.0)×10 -3, Z=-6.67, P<0.001], ATG5 [3.60 (2.30, 5.30)×10 -3, 7.20(5.50, 9.20)×10 -3, Z=-3.63, P=0.001], LC3Ⅱ[25.70(8.50, 35.00)×10 -3, 52.20(45.00, 69.10)×10 -3, Z=-5.87, P<0.001] and ATG7[5.50(3.20, 8.10)×10 -3, 8.30(5.20, 9.80)×10 -3, Z=-2.38, P=0.017] the mRNA expressions were significantly decreased in the AS group. ②ATG5 mRNA expression was negatively correlated with platelet count ( r=-0.35, P=0.008), LC3-Ⅱ was negatively correlated with estimated glomerular filtration rate ( r=-0.33, P=0.017), ATG7 was positively correlated with absolute basophil count ( r=0.33, P=0.011),ATG10 was negatively correlated with estimated glomerular filtration rate and C-reactive protein (CRP) was negatively correlated ( r=-0.30, P=0.032). ③ The area under the ROC curve (AUC) of ATG2A mRNA expression level for predicting AS was 0.910, and the sensitivity and specificity were 94.6% and 83.8% respectively. ④ After 24 weeks of treatment with secukinumab, the mRNA expression levels of ATG2A[2.00(1.20, 2.90)×10 -3, 4.90(0.10, 7.40)×10 -3, Z=-3.75, P<0.001] and LC3-Ⅱ[2.00(1.20, 2.90)×10 -3, 4.90(0.10, 7.40)×10 -3, Z=-3.75, P<0.001]were elevated in the AS patients. Conclusion:Late autophagy-related genes ATG2A, ATG5, LC3II, ATG7 may be involved in AS development.The AUC of ATG2A in AS is 0.91, suggesting that ATG2a is expected to be a biological indicator for early diagnosis of AS. Secukinumab may be involved in the regulation of autophagy by affecting the expression of late autophagy genes, but the specific mechanism needs to be further explored.

OBJECTIVE: To evaluate the clinical efficacy and safety of Yangxue Qingnao Pills (YXQNP) combined with amlodipine in treating patients with grade 1 hypertension. METHODS: This is a multicenter, randomized, double-blind, and placebo-controlled study. Adult patients with grade 1 hypertension of blood deficiency and Gan (Liver)-yang hyperactivity syndrome were randomly divided into the treatment or the control groups at a 1:1 ratio. The treatment group received YXQNP and amlodipine besylate, while the control group received YXQNP's placebo and amlodipine besylate. The treatment duration lasted for 180 days. Outcomes assessed included changes in blood pressure, Chinese medicine (CM) syndrome scores, symptoms and target organ functions before and after treatment in both groups. Additionally, adverse events, such as nausea, vomiting, rash, itching, and diarrhea, were recorded in both groups. RESULTS: A total of 662 subjects were enrolled, of whom 608 (91.8%) completed the trial (306 in the treatment and 302 in the control groups). After 180 days of treatment, the standard deviations and coefficients of variation of systolic and diastolic blood pressure levels were lower in the treatment group compared with the control group. The improvement rates of dizziness, headache, insomnia, and waist soreness were significantly higher in the treatment group compared with the control group (P<0.05). After 30 days of treatment, the overall therapeutic effects on CM clinical syndromes were significantly increased in the treatment group as compared with the control group (P<0.05). After 180 days of treatment, brachial-ankle pulse wave velocity, ankle brachial index and albumin-to-creatinine ratio were improved in both groups, with no statistically significant differences (P>0.05). No serious treatment-related adverse events occurred during the study period. CONCLUSIONS Combination therapy of YXQNP with amlodipine significantly improved symptoms such as dizziness and headache, reduced blood pressure variability, and showed a trend toward lowering urinary microalbumin in hypertensive patients. These findings suggest that this regimen has good clinical efficacy and safety. (Registration No. ChiCTR1900022470).
Humans ; Amlodipine/adverse effects* ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Hypertension/complications* ; Middle Aged ; Treatment Outcome ; Drug Therapy, Combination ; Adult ; Blood Pressure/drug effects* ; Double-Blind Method ; Aged ; Antihypertensive Agents/adverse effects*