To analyze the disease burden of acute lymphoid leukemia(ALL) and its changing trends in China and globally from 1990 to 2021, aiming to provide a theoretical basis for disease prevention, treatment, and policy formulation.

Objective To investigate the effects of dapagliflozin on inflammatory factors and prognosis in patients with type 2 diabetes mellitus (T2DM) and acute myocardial infarction (AMI). Methods In a randomized, double-blind trial, 146 patients with T2DM and AMI (within 7 days of onset) were divided into dapagliflozin (dapagliflozin 10 mg/d combining AMI standard therapy) and control (AMI standard therapy) groups, and were followed up for 12 months. Serum levels of interleukin-1β (IL-1β), IL-6, high-sensitivity C reactive protein (hs-CRP) at baseline, 1, 3, 6, and 12 months, and left ventricular ejection fraction (LVEF), brain natriuretic peptide (BNP), and major adverse cardiovascular events (MACE) rate at 12 months were compared between the two groups. Kaplan-Meier curves were used to analyze the cumulative incidences of MACE in the two groups. Results Three patients were withdrawn or dropped out. At 12 months, IL-1β, IL-6, and hs-CRP levels were significantly lower in dapagliflozin group (n＝71) than those in control group (n＝72, P＜0.01), approaching normal levels. Compared with the control group, LVEF was higher (P＜0.01), BNP was lower (P＜0.01), MACE incidence was lower (P＝0.047) in dapagliflozin group at 12 months. Generalized linear mixed models showed significant group-time interactions in IL-1β, IL-6, and hs-CRP (P＜0.001), and these factors declined faster in the dapagliflozin group. Kaplan-Meier curve showed the cumulative incidences of MACE and heart failure were lower in dapagliflozin group than those in non-dapagliflozin group (P＜0.05). Conclusions For patients with T2DM patients and AMI, dapagliflozin has good anti-inflammatory and cardioprotective effects.

In the context of global warming, protecting outdoor workers from occupational heat exposure has become an important public health concern. This review summarized the principle, applicability, and limitation of three categories of wet bulb globe temperature (WBGT) prediction models: empirical regression models, heat-balance models, and machine-learning models. Drawing on international experience from the United States, Europe, and Japan, this review further examined the technical challenges of applying WBGT-based prediction models to large-scale occupational heat stress early warning systems. In response to gaps in occupational heat stress management in China, WBGT should be considered a core assessment indicator to support a transition from passive response to proactive intervention. A localized implementation pathway is proposed, incorporating mechanism-based model calibration, regional parameter adaptation, and multi-source data fusion. Strengthening collaboration between public health and meteorological departments and developing platform-based flexible intervention strategies for workers in new forms of employment may improve the targeting of occupational heat stress early warning and health protection. Future research should focus on physics-constrained machine learning, refined microenvironmental prediction, and individualized risk assessment to support the development of a digitally enabled occupational heat-health protection framework.

Addressing the current clinical problems of conventional antidepressants， such as delayed onset of action and prominent adverse reactions， this paper explores the theoretical basis， mechanism of action， and application prospects of nasal administration as a novel rapid antidepressant strategy. By clarifying the conceptual connotation of rapid antidepressants， elucidating their clinical demands and application advantages， and explaining the physiological basis of nasal-to-brain delivery， it is proposed that the olfactory and trigeminal nerve pathways can bypass the blood-brain barrier to achieve rapid targeted delivery of drugs to brain tissue. On this basis， combined with the theory of opening orifices with aromatic medicinals in traditional Chinese medicine （TCM） as well as related research in modern aromatherapy， the ancient and modern clinical evidence of nasal administration in regulating emotions was systematically reviewed. Furthermore， this article discusses the application advantages of nasal administration in special populations such as the elderly， children， and pregnant women， and analyzes the practical bottlenecks such as mucosal clearance， limited formulation volume， and safety evaluation. Nasal administration is expected to become an important supplementary means for rapid antidepressants， and the integrated model of "TCM aromatic medicinals plus nanopreparations plus nasal administration" can provide new ideas for research on the integration of TCM and western medicine in treating depression.

Cerebral blood flow directly affects the metabolism of substances and neural activity in the brain, and is closely associated with the occurrence and development of cerebral small vessel disease (CSVD). Multiple studies have revealed that various imaging biomarkers in patients with CSVD, such as lacunar infarction, enlarged perivascular spaces, cerebral microbleeds, cerebral atrophy, and white matter hyperintensities, are closely associated with cerebral autoregulation (CA) function. Therefore, understanding the regulatory mechanism of CA in patients with CSVD is of great significance for delaying the further development of CSVD, improving cerebral ischemia and cognitive impairment. This article reviews the correlation and mechanism between CA and CSVD.

Objective:To identify independent risk factors for chronic critical illness (CCI) secondary to severe pneumonia and to develop and validate a clinical prediction model.Methods:A retrospective cohort study was conducted using electronic medical records from 415 patients with severe pneumonia admitted between January 2023 and March 2024. Patients were randomly divided into a training set ( n = 290) and a validation set ( n = 125) at a 7:3 ratio. Univariate and multivariate logistic regression analyses were used to identify independent risk factors, and a nomogram was constructed. The model’s discriminative ability, calibration, and clinical utility were assessed using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results:The overall incidence of CCI was 23.13% (96/415). Multivariate analysis identified five independent predictors: virus infection ( OR = 13.00, 95% CI: 5.07–33.35, P < 0.001), mechanical ventilation ≥72 hours ( OR = 8.06, 95% CI: 3.68–20.09, P < 0.001), neutrophil-to-albumin ratio (NAR) ( OR = 27848, 95% CI: 193.93–5542274.11, P < 0.001), oxygenation index ( OR =1.09, 95% CI: 1.01–1.09, P < 0.001), and age ( OR = 0.94, 95% CI: 0.91–0.97, P < 0.001). The model demonstrated excellent performance in both sets: training set AUC = 0.96 (95% CI: 0.94–0.98), sensitivity 0.93, specificity 0.89, Brier score 0.09; validation set AUC = 0.93 (95% CI: 0.88–0.98), sensitivity 0.89, specificity 0.64, Brier score 0.13. Calibration curves showed high consistency between predicted and observed risks (mean absolute error < 3%), and DCA indicated significant net clinical benefit within the threshold probability range of 15–60%. Conclusions:The developed prediction model integrates etiological, inflammatory, metabolic, and respiratory support parameters and demonstrates outstanding predictive performance (AUC > 0.90). It may serve as a quantitative tool for early risk stratification and intervention in patients with severe pneumonia. Further multicenter external validation and exploration of integrating dynamic biomarker monitoring are recommended.

To analyze the disease burden and trends of motor neuron disease(MND) in China and globally from 1990 to 2021, providing evidence for the formulation of relevant health strategies inChina.

Objective To investigate the risk factors of the infarct growth rate(IGR)in patients with acute anterior circulation large vessel occlusion.Methods This is a retrospective analysis of consecutive patients having acute anterior circulation large-vessel occlusion and being admitted to the Department of Neurointerventional Intervention,Central Hospital affiliated to Dalian University of Technology between September 2021 and July 2023.Patients were dichotomized into rapid and slow growth groups based on the median value of IGR,with 145 cases in each group.Univariate and multivariate Logistic regression models were used to analyze the risk factors of preoperative IGR.Results Multivariable Logistic regression analysis,after univariate screening,showed that hypertension(OR=2.27,95%CI:1.39-3.71),atrial fibrillation(OR=1.95,95%CI:1.22-3.12),and intracranial internal carotid artery occlusion(OR=1.98,95%CI:1.19-3.28)were risk factors of preoperative IGR(P<0.05).Hypertension,atrial fibrillation,and internal carotid artery occlusion all exhibited relatively low predictive value for IGR(P<0.05).The area under the curve for predicting IGR by combining these three factors was 0.642(95%CI:0.579-0.704),indicating a slight improvement in predictive performance,yet it remained relatively low.Conclusion Hypertension,atrial fibrillation,and proximal occlusion are risk factors of IGR in patients having acute anterior circulation large vessel occlusion.

Objective To investigate the risk factors of the infarct growth rate(IGR)in patients with acute anterior circulation large vessel occlusion.Methods This is a retrospective analysis of consecutive patients having acute anterior circulation large-vessel occlusion and being admitted to the Department of Neurointerventional Intervention,Central Hospital affiliated to Dalian University of Technology between September 2021 and July 2023.Patients were dichotomized into rapid and slow growth groups based on the median value of IGR,with 145 cases in each group.Univariate and multivariate Logistic regression models were used to analyze the risk factors of preoperative IGR.Results Multivariable Logistic regression analysis,after univariate screening,showed that hypertension(OR=2.27,95%CI:1.39-3.71),atrial fibrillation(OR=1.95,95%CI:1.22-3.12),and intracranial internal carotid artery occlusion(OR=1.98,95%CI:1.19-3.28)were risk factors of preoperative IGR(P<0.05).Hypertension,atrial fibrillation,and internal carotid artery occlusion all exhibited relatively low predictive value for IGR(P<0.05).The area under the curve for predicting IGR by combining these three factors was 0.642(95%CI:0.579-0.704),indicating a slight improvement in predictive performance,yet it remained relatively low.Conclusion Hypertension,atrial fibrillation,and proximal occlusion are risk factors of IGR in patients having acute anterior circulation large vessel occlusion.

Purpose To explore the feasibility and validity of radiomics combined with blind/referenceless image spatial quality evaluator(Brisque)for automated assessment of arterial-phase image quality in hepatic gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)dynamic enhanced MRI examinations.Materials and Methods A total of 326 arterial phase images from January 2020 to March 2024 in the First Affiliated Hospital of Henan University of Chinese Medicine for liver Gd-EOB-DTPA dynamic enhancement MRI examination were retrospectively collected.A 4-level(1-4 points)Likert scale was used for subjective image quality scoring,and then binary classification was used to divide the images into clinically acceptable group(166 images with a score of 2-4)and clinically unacceptable group(160 images with a score of 1).All images were randomly divided into a training set(227 images)and a test set(99 images)in a 7∶3 ratio.Brisque images were created based on arterial-phase images,and subsequently Brisque image features,image histologic features of the original arterial-phase images and combined features of the two were extracted.The extracted data were reduced in dimension and the optimal features of radiomics were selected.Based on the Logistic regression algorithm,radiomics models,Brisque models and combined models of the two were constructed.The receiver operating characteristic curve was drawn for each subject,and the area under the curve(AUC),threshold,sensitivity,specificity,accuracy,negative predictive value and positive predictive value were calculated to analyze the diagnostic performance of each model,and the net benefit of the models was evaluated by decision curve analysis.Results The AUC values of the radiomics model,Brisque model and combined model in the training set were 0.942(95%CI 0.914-0.969),0.722(95%CI 0.655-0.788)and 0.967(95%CI 0.947-0.987),respectively.In the test set,the AUC values were 0.904(95%CI 0.848-0.960),0.684(95%CI 0.579-0.789)and 0.920(95%CI 0.866-0.972),respectively.There was statistically significant difference between two of the three models in the training set(Z=6.493,3.397,7.427;all P<0.05);in the test set,there was statistically significant difference between the combined model and the Brisque model,and between the radiomics model and the Brisque model(Z=4.137,3.740,both P<0.05),but no statistically significant difference between the combined model and the radiomics model(P>0.05).The diagnostic performance was higher in the combined model in both the training set and the test set.The decision curve analysis curve suggested that the net benefit of the combined model was greater than that of the other two models.Conclusion Radiomics combined with Brisque can be applied in the assessment of the quality of arterial-phase images in Gd-EOB-DTPA dynamic-enhanced MRI examinations of the liver to automatically detect clinically unacceptable arterial-phase images of the liver with high diagnostic efficacy,which contributes to the improvement of the quality of the images at the time of acquisition,leading to a reduction in the number of duplicate scans and an increase in the accuracy of the diagnosis.