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）］

Childhood primary renal tubular diseases are chronic kidney diseases characterized by impaired renal tubular reabsorption. Primary renal tubular disease has diverse clinical manifestations and lacks of specificity. Laboratory tests are limited，making it prone to missed diagnosis and misdiagnosis. Based on the current knowledge of renal tubular diseases，authors propose early warning signals of renal tubular diseases such as family history of primary tubular diseases，unexplained polyhydramnios during pregnancy，polydipsia，polyuria，delayed growth and development or rickets，decreased muscle strength and tone，unexplained electrolyte disturbance，hyperuricemia，acid-base disturbance，positive urine sugar test，renal tubular proteinuria，urinary imaging examination suggesting kidney stones，calcium deposition，renal cysts and early onset of eye，ear，joint and neuron injury.Meanwhile，some universal management strategies for primary renal tubular disease are proposed，emphasizing the importance of multidisciplinary collaboration，genetic testing and individualized intervention to improve the long-term prognosis of childhood primary renal tubular diseases.

Osteoporosis is a common senile bone metabolism disease， clinically characterized by decreased bone mass， destruction of bone microstructure， increased bone fragility， and easy fracture. It tends to occur in the elderly and postmenopausal women， seriously threatening the quality of life and physical and mental health of the elderly. At present， the treatment of osteoporosis is mainly based on oral western medicines， such as calcium， Vitamin D， and bisphosphonates. Still， there are drawbacks such as a long medication cycle and many adverse reactions. In recent years， due to the advantages of multi-component， multi-pathway， and multi-target， some traditional Chinese medicines and effective ingredients can regulate the osteogenic and osteoclastic differentiation process in both directions and are widely used in the prevention and treatment of osteoporosis. Hippophae rhamnoides is a commonly used herbal medicine， and its fruits are rich in flavonoids， polyphenols， fatty acids， vitamins， and trace elements， which have been proven to have a good anti-osteoporosis effect. Isorhamnetin is the main effective ingredient of Hippophae rhamnoides fruits， which has many pharmacological effects such as anti-inflammation， anti-oxidative stress， anti-aging， and anti-tumor. Studies have shown that isorhamnetin can participate in the regulation of bone metabolism and has a good anti-osteoporosis effect. However， the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis have not been systematically summarized. Therefore， this paper reviewed the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis by referring to relevant literature to provide more basis for the development and application of isorhamnetin.

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment

Osteoarthritis (OA) causes chronic pain that significantly impairs quality of life, with current treatments often proving insufficient and accompanied by adverse effects. Recent research has identified the dorsal root ganglion (DRG) and its resident macrophages as crucial mediators of chronic OA pain through neuroinflammation driven by macrophage polarization. We present a novel injectable thermo-sensitive hydrogel system, KAF@PLEL, designed to deliver an anti-inflammatory peptide (KAF) specifically to the DRG. This biodegradable hydrogel enables sustained KAF release, promoting the reprogramming of DRG macrophages from pro-inflammatory to anti-inflammatory phenotypes. Through comprehensive in vitro and in vivo studies, we evaluated the hydrogel's biocompatibility, effects on macrophage polarization, and therapeutic efficacy in chronic OA pain management. The system demonstrated significant capabilities in preserving macrophage mitochondrial function, suppressing neuroinflammation, alleviating chronic OA pain, reducing cartilage degradation, and improving motor function in OA rat models. The sustained-release properties of KAF@PLEL enabled prolonged therapeutic effects while minimizing systemic exposure and side effects. These findings suggest that KAF@PLEL represents a promising therapeutic approach for improving outcomes in OA patients through targeted, sustained treatment.

Local anesthetics (LAs), such as articaine (AT), exhibit limited efficacy in inflammatory environments, which constitutes a significant limitation in their clinical application within oral medicine. In our prior research, we developed AT-17, which demonstrated effective properties in chronic inflammatory conditions and appears to function as a novel oral LA that could address this challenge. In the present study, we further elucidated the beneficial effects of AT-17 in acute inflammation, particularly in oral acute inflammation, where mitochondrial-related apoptosis played a crucial role. Our findings indicated that AT-17 effectively inhibited lipopolysaccharide (LPS)-induced nerve cell apoptosis by ameliorating mitochondrial dysfunction in vitro. This process involved the inhibition of mitochondrial reactive oxygen species (mtROS) production and the subsequent activation of the NRF2 pathway. Most notably, improvements in mitochondria-related apoptosis were key contributors to AT-17's inhibition of voltage-gated sodium channels. Additionally, AT-17 was shown to reduce mtROS production in nerve cells through the Na⁺/NCLX/ETC signaling axis. In conclusion, we have developed a novel local anesthetic that exhibits pronounced anesthetic functionality under inflammatory conditions by enhancing mitochondria-related apoptosis. This advancement holds considerable promise for future drug development and deepening our understanding of the underlying mechanisms of action.

Objective To retrospectively analyze the clinical risk factors and prognosis of perioperative myocardial injury(MINS)in non-cardiac surgery patients admitted to the intensive care unit(ICU).Methods A total of 478 postoperative patients admitted to the Department of Intensive Medicine,Minhang Hospital,Fudan University from Jan 2020 to Dec 2023 were selected.They were divided into MINS group(n=302)and normal group(n=176)based on whether myocardial injury occurred within 7 days after surgery.The differences in clinical characteristics between the two groups were compared,and risk factors for perioperative myocardial injury were identified.Risk factors for mortality in the MINS group were analyzed with 30-day mortality as the clinical endpoint.Results The prevalence of acute physiology and chronic health evaluation Ⅱ(Apache Ⅱ)score,coronary artery disease,and chronic kidney disease were all higher in the MINS group than those in the normal group,with statistically significant differences(P<0.05).The proportion of emergency surgeries,co-infection,and perioperative hypotension were significantly different between the MINS group and the normal group(P<0.05).Multivariate logistic regression analysis revealed that chronic kidney disease,emergency surgery,co-infection,and intraoperative and postoperative hypotension were risk factors for MINS occurrence.Prognostic analysis indicated that perioperative hypotension was a risk factor for 30-day mortality in MINS patients.Conclusion MINS is closely associated with patients'underlying conditions,timing of surgery,and perioperative hypotension status,and especially perioperative hypotension affects the final outcomes.

Objective To explore the predictive value of MRI parameters of carotid artery plaque combined with low density lipoprotein cholesterol/high density lipoprotein cholesterol(LDL-C/HDL-C)ratio for predicting ischemic stroke in young patients with carotid atherosclerosis.Methods Totally 125 young patients with carotid atherosclerosis were prospectively included and divided into stroke group and non-stroke group based on whether ischemic stroke occurred within 3 months.Clinical data,laboratory indicators and carotid plaque-related MRI parameters were compared between groups.Based on carotid plaque-related MRI parameters being statistically different between groups,combined model 1 was constructed using multivariable logistic regression analysis,while combined model 2 was constructed combined with LDL-C/HDL-C ratio.The efficacy of each parameter and model for predicting ischemic stroke in young adults was analyzed.Results There were 48 cases in stroke group and 77 cases in non-stroke group.The levels of glycosylated hemoglobin,LDL-C,LDL-C/HDL-C ratio,carotid artery stenosis rate,plaque eccentricity index and plaque enhancement rate in stroke group were all higher than those in non-stroke group(all P＜0.05).The area under the curve(AUC)of LDL-C/HDL-C ratio,carotid artery stenosis rate,plaque eccentricity index,plaque enhancement rate,combined model 1 and 2 for predicting ischemic stroke in young adults was 0.816,0.757,0.768,0.805,0.883 and 0.936,respectively,of combined model 1 was higher than those of single parameter(all P＜0.05),while of combined model 2 was higher than that of combined model 1(Z=2.336,P=0.020).Conclusion MRI parameters of carotid artery plaque combined with LDL-C/HDL-C ratio could effectively predict ischemic stroke in young patients with carotid atherosclerosis.

Objective To establish a risk factor model for intracranial artery stenosis in young patients with acute ischemic stroke(AIS)based on high-resolution magnetic resonance vascular wall imaging(HR-VWI).Methods Young patients with AIS(n=290)treated at Hengshui People's Hospital between January 2021 and January 2023 were retrospectively analyzed and randomly divided into a modeling set(203 cases)and a validation set(n=87)at a ratio of 7∶3.Patients in the modeling set were divided into the stenosis and non-ste-nosis groups according to whether they had intracranial artery stenosis.Multivariate logistic regression was used to analyze the clinical data and HR-VWI characteristics of the patients in the modeling set to screen for factors influencing intracranial artery stenosis in young patients with AIS.R software was used to construct and verify the risk factor model.Results Among the 290 patients,88 had intracranial artery stenosis(30.34％).The proportions of low-density lipoprotein cholesterol(LDL-C),plaque load,smoking history,hypertension,and eccentric plaques were higher in the stenosis group than in the non-stenosis group(P＜0.05),and the minimum lumen area and remode-ling index were lower in the stenosis group than in the non-stenosis group(P＜0.05).Multivariate logistic regression analysis showed that smoking history,hypertension,LDL-C level,plaque load,plaque morphology,and remodeling index were all factors influencing intracra-nial artery stenosis in young patients with AIS(P＜0.05).Based on the above risk factors,R was used to build a nomogram early warning model.The ROC results showed that the AUC of the nomogram model for predicting intracranial artery stenosis in the modelling and vali-dation sets were 0.872(95％CI:0.815-0.902)and 0.850(95％CI:0.789-0.891),respectively.The Hosmer-Lemeshow test results of the modeling and validation sets were x2=0.589,P=0.571 and x2=0.602,P=0.558,respectively.The calibration curves of the two groups were consistent with the standard curves.Conclusion The risk factor model for intracranial artery stenosis in young patients built in this study based on HR-VWI features exhibits good predictive efficacy,providing a new method for clinical prevention and treatment.