BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

A quantitative method for the analysis of the multi-component contents in Marsdenia tenacissimae was established, and the quality differences were evaluated by principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), factor analysis (FA) and weighted technique for order preference by similarity to ideal solution (TOPSIS) method. The contents of chlorogenic acid, cryptochlorogenic acid, sinapic acid, tenacigenoside A, tenacissoside G, tenacissoside I, tenacissoside H, drevogenin A, betulinic acid and lupeol were determined by HPLC wavelength switching method. At the same time, the contents of alcohol-soluble extract and total ash were detected. PCA, OPLS-DA and FA methods were used to identify the origin of M. tenacissimae from different producing areas. According to the OPLS-DA model, the index weight was determined to construct the weighted TOPSIS evaluation model. The qualities of M. tenacissimae from different producing areas were analyzed by model scoring results. The contents of 12 indexes in 18 batches of M. tenacissimae varied to different degrees, and the repeatability and accuracy of the test method were satisfactory. PCA analysis divided 18 batches of M. tenacissimae into three categories. OPLS-DA identified five main potential quality markers, including tenacissoside A, tenacissoside I, lupeol, tenacissoside H and chlorogenic acid. The evaluation results of FA and weighted TOPSIS method were consistent, which showed that the quality of M. tenacissimae from Yunnan and Guizhou was better. The established multi-component quantitative analysis method is accurate and reliable, the chemometrics model has strong predictive ability, and the evaluation results of FA and weighted TOPSIS method are scientific and objective. The combination of the four methods can clearly determine the qualities of M. tenacissimae from different producing areas.

Objective To investigate the significance of modified Seoul National University Renal Stone Complexity score (S-ReSC), renal stone complexity score (R.I.R.S.), and Clinical Research Office of the Endourological Society Nephrolithometric Nomogram (CROES) score in predicting the stone-clearance rate (SFR) after ureteroscopy combined with flexible negative pressure suction sheath in the treatment of kidney stones. Methods A total of 200 patients with kidney stones treated in our hospital during Dec.2022 and Apr.2024 were selected.According to abdominal CT evaluation 1 month after surgery, the patients were divided into the residual group (n=38) and the non-residual group (n=162).The relationship between the scores was assessed with Pearson correlation, the independent risk factors were identified with binary logistic regression, the predictive efficacy was evaluated with the receiver operating characteristic (ROC) curves, and the difference in the area under the ROC curves (AUCs) was compared with the Delong test. Results Compared with the non-residual group, the residual group had significantly higher modified S-ReSC and R.I.R.S., but significantly lower CROES score (P＜0.05). Modified S-ReSC was positively correlated with R.I.R.S. (P＜0.05), while CROES score was negatively correlated with S-ReSC and R.I.R.S.Staghorn stones, maximum stone diameter, elevated CT values, increased S-ReSC and R.I.R.S., and decreased CROES score were independent risk factors for postoperative stone residual (P＜0.05).ROC curves showed the optimal AUC of R.I.R.S.was 0.855, and the optimal AUC of combined prediction was 0.950.Conclusion The R.I.R.S.has the best efficacy in predicting postoperative stone residual, especially for complex stones.The combination of stone characteristics and the three scoring systems can improve the prediction efficiency, and provide reference for preoperative evaluation and individualized treatment.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

The Chinese Pharmacopoeia is the legal technical standard which should be followed during the research, production, use, and administration of drugs. At present, the new edition of the Chinese Pharmacopoeia is planned to be promulgated and implemented. This article summarizes and analyzes the main characteristics and the content of updates and amendments of the Chinese Pharmacopoeia 2025 Edition(Volume Ⅰ), to provide a reference for the correct understanding and accurate implementation the new edition of the pharmacopoeia.

To introduce and analyze guideline terminology related to clinical question formulation, evidence retrieval and appraisal, and recommendation development.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

BACKGROUND: Recent studies have shown that sodium-glucose cotransporters-2 (SGLT2) inhibitors significantly improve major adverse cardiovascular events in heart failure with preserved ejection fraction (HFpEF) patients, but the exact mechanism is unknown. Ferritinophagy is a special form of selective autophagy that participates in ferroptosis. In this study, we aimed to investigate whether ferritinophagy was activated during the occurrence of HFpEF, and whether canagliflozin (CANA) could inhibite ferritinophagy. METHODS: We reared Dahl salt-sensitive (DSS) rats on a high-salt diet to construct a hypertensive HFpEF model, and simultaneously administered CANA intervention. Then we detected indicators related to ferritinophagy. RESULTS: The expression of nuclear receptor coactivator 4 (NCOA4), as well as microtubule-associated proteins light chain 3 (LC3), Bcl-2 interacting protein 1 (Beclin-1) and p62, were upregulated in HFpEF rats, accompanied by the downregulation of ferritin heavy chain 1 (FTH1), upregulation of mitochondrial iron transporter sideroflexin1 (SFXN1) and increased reactive oxygen species (ROS) production. Above changes were diminished by CANA. CONCLUSION Ferritinophagy is activated in HFpEF rats and then inhibited by CANA, leading to HFpEF benefits. The inhibition of ferritinophagy could provide new prospective targets for the prevention and treatment of HFpEF, and provide new ideas for investigating the mechanism of cardiovascular benefit of SGLT2 inhibitors.

Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.