BACKGROUND: High temperatures are known to be associated with an increased risk of self-harm, but the influence of demographic changes and country-level indicators on the burden of heat-related self-harm remains unclear. This study examined the key factors driving changes in self-harm mortality linked to high temperatures and explored their impact at the country level. METHODS: This is an ecological study that analyzes data from the 2021 Global Burden of Disease (GBD) study, the World Bank, and the Climate Research Unit (CRU) were analyzed. Decomposition analyses were used to identify key factors driving changes in high temperature-related self-harm mortality between 1990 and 2021. A panel data model assessed the impact of national indicators on heat-related self-harm mortality. RESULTS: In 2021, 14,885 deaths globally were attributed to heat-related self-harm, a 41.94% increase from 1990, with low-middle SDI regions accounting for 47.84% of these deaths. While the global death rate from heat-related self-harm declined slightly over this period, South Asia and low-middle SDI regions contributed most to the decline. However, population aging exacerbated mortality rates. Demographic and meteorological factors were also linked to heat-related self-harm. CONCLUSION The global decline in heat-related self-harm mortality is largely driven by reductions in females, low-middle SDI regions, and South Asia. However, population aging and growth in these regions have added to the mortality burden, slowing the overall decline. Factors such as population density are also associated with heat-related self-harm. Targeted measures are needed to mitigate heat-induced self-harm more effectively in future.
Humans ; Self-Injurious Behavior/etiology* ; Hot Temperature/adverse effects* ; Global Health/statistics & numerical data* ; Female ; Male ; Adult ; Middle Aged ; Aged ; Young Adult ; Adolescent

Protein liquid-liquid phase separation (LLPS), a pivotal phenomenon intricately linked to cellular processes, is regulated by various other proteins. However, there is still a lack of high-throughput methods for screening protein regulators of LLPS in target proteins. Here, we developed a CRISPR/Cas9-based screening method to identify protein phase separation regulators by integrating bimolecular fluorescence complementation (BiFC) and fluorescence-activated cell sorting (FACS). Using this newly developed method, we screened the RNA-binding proteins that regulate PABPN1 phase separation and identified the tumor suppressor QKI as a promoter of PABPN1 phase separation. Furthermore, QKI exhibits decreased expression levels and diminished nuclear localization in colorectal cancer cells, resulting in reduced PABPN1 phase separation, which, in turn, promotes alternative polyadenylation (APA), cell proliferation, and migration in colorectal cancer.
Humans ; Colorectal Neoplasms/genetics* ; RNA-Binding Proteins/genetics* ; Poly(A)-Binding Protein I/genetics* ; CRISPR-Cas Systems ; Flow Cytometry ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement

Purpose To evaluate the predictive performance of mean apparent propagator-magnetic resonance imaging(MAP-MRI)combined with habitat analysis for determining O6-methylguanine-DNA methyltransferase(MGMT)promoter methylation status in glioma.Materials and Methods This retrospective study analyzed MRI and clinical data from 55 patients with surgically confirmed glioma at Fujian Medical University Union Hospital from January 2019 to December 2023.All patients underwent structural and diffusion-weighted imaging.Three-dimensional volumes of interest were delineated in the tumor solid region using ImageJ software.The nn-FAE tool was used to segment the tumor solid region into two habitat subregions based on mean diffusivity(MD)maps:high-MD and low-MD habitats.Average diffusion parameter values were extracted from the entire tumor solid region and each habitat subregion.Differences in parameters between methylated and unmethylated groups were compared,and the area under the curve was calculated.Results Among 55 patients,significant differences were observed in all MAP-MRI parameters and MD in the tumor solid region and low-MD habitat,as well as all parameters in the high-MD habitat between methylated and unmethylated groups(t/Z=-3.780-3.153,all P<0.05).The return-to-origin probability(RTOP)in the low-MD habitat demonstrated the highest diagnostic performance,with the area under the curve improving from 0.771 before habitat analysis to 0.827 after habitat analysis.In the high-grade subgroup,significant differences were observed in return-to-axis probability(RTAP)and RTOP in the tumor solid region;RTOP,non-Gaussianity,non-Gaussianity axial,and RTAP in the low-MD habitat;and non-Gaussianity in the high-MD habitat(t/Z=-2.820--1.976,all P<0.05).RTOP in the low-MD habitat again showed optimal diagnostic efficacy(the area under the curve 0.725 before habitat analysis,0.798 after).Multivariate analysis identified RTAP and RTOP in the tumor solid region and low-MD habitat as independent predictors of MGMT methylation.Conclusion MAP-MRI diffusion parameters demonstrate the ability to predict MGMT promoter methylation status in glioma,with superior performance compared with diffusion tensor imaging.Habitat imaging further enhances the predictive efficacy of MAP-MRI parameters for MGMT promoter methylation.

Objective:To provide a scoping review of domestic and international studies on the influencing factors of frailty in stroke inpatients, and to provide guidance for interventional studies on debility in stroke inpatients in China.Methods:A systematic search of domestic and international literature databases, including China National Knowledge Infrastructure, WanFang, VIP, China Biomedical Literature Database, PubMed, Web of Science, Embase, Cochrane Library, CINAHL was conducted about the status and its influencing factors of frailty in stroke inpatients. The retrieval time limit was from database establishment to November 23, 2023. The included literature was extracted, analyzed, and summarized according to the reporting specifications of the scope review guidelines.Results:Thirty-six articles were included, all of the 36 papers reported the prevalence of frailty in patients with stroke. The top three countries with the highest prevalence were China (15.3%-86.9%), the United Kingdom (28%-78%), and Italy (31.37%). The risk factors of stroke frailty were categorized mainly into 4 themes: social demographic factors, physical health factors, disease-related factors, and psychological and social background factors.Conclusions:The confidence of frailty in stroke patients of a higher level at home and abroad, and the risk factors involved are complex and diverse. It is suggested that future studies need to conduct large-sample, multicenter longitudinal studies to clarify the causal relationship, strengthen the exploration of controversial factors of stroke debility, and carry out more targeted intervention studies, so as to reduce the incidence of frailty and improve the recovery process of patients.

Objective:To examine the effect of cumulative hemoglobin A 1c (HbA 1c) levels and insulin dosage on insulin resistance (IR)-related metabolic disturbances in newly diagnosed patients with type 1 diabetes (T1D). Methods:This retrospective cohort study included T1D patients admitted to the Second Xiangya Hospital of Central South University from November 2015 to March 2023. Clinical data collected comprised age, sex, disease duration, insulin dosage, body mass index, waist circumference, blood pressure, HbA 1c levels, islet autoantibodies, and fasting blood lipid profiles. IR-related metabolic disturbances assessed were overweight, obesity, central obesity, hypertension, and dyslipidemia. Cox regression and cluster analyses were applied to assess the influence of cumulative HbA 1c and insulin dosage on these metabolic disturbances. Results:A total of 235 patients were included, with 97 males (41.3%) and 138 females (58.7%). The median age was 19.8 (13.3, 31.1) years, and the median follow-up duration was 30.8 (20.8, 45.6) months. During follow-up, 41.6% (72/173) of patients developed IR-related metabolic disturbances. Multivariate Cox regression analysis revealed that a cumulative HbA 1c ≥60 mmol/mol was an independent risk factor for any IR-related metabolic disturbance [ HR (95% CI): 1.739 (1.067-2.835) ] and for triglyceride abnormalities [ HR (95% CI): 3.277 (1.176-9.127)]. Additionally, a cumulative insulin dosage ≥0.5 U·kg -1·d -1 was identified as an independent risk factor for overweight, obesity, or central obesity [ HR (95% CI): 2.374 (1.059-5.323)]. Cluster analysis further identified that patients with higher levels of cumulative HbA 1c and insulin dosage, particularly those with adolescent-onset diabetes, had the highest likelihood of developing hypertension ( HR=2.460, 95% CI 1.008-6.005), overweight/obesity/central obesity ( HR=2.707, 95% CI 1.062-6.900), triglyceride abnormalities ( HR=5.495, 95% CI 1.842-16.391), high-density lipoprotein cholesterol abnormalities ( HR=11.054, 95% CI 4.107-29.751), and any IR-related metabolic disturbance ( HR=5.833, 95% CI 2.602-13.077). Conclusions:Elevated cumulative HbA 1c and insulin dosage levels in T1D patients are associated with an increased risk of developing IR-related metabolic disturbances. These findings underscore the urgent need for novel therapeutic strategies tailored to this population.

Purpose To evaluate the predictive performance of mean apparent propagator-magnetic resonance imaging(MAP-MRI)combined with habitat analysis for determining O6-methylguanine-DNA methyltransferase(MGMT)promoter methylation status in glioma.Materials and Methods This retrospective study analyzed MRI and clinical data from 55 patients with surgically confirmed glioma at Fujian Medical University Union Hospital from January 2019 to December 2023.All patients underwent structural and diffusion-weighted imaging.Three-dimensional volumes of interest were delineated in the tumor solid region using ImageJ software.The nn-FAE tool was used to segment the tumor solid region into two habitat subregions based on mean diffusivity(MD)maps:high-MD and low-MD habitats.Average diffusion parameter values were extracted from the entire tumor solid region and each habitat subregion.Differences in parameters between methylated and unmethylated groups were compared,and the area under the curve was calculated.Results Among 55 patients,significant differences were observed in all MAP-MRI parameters and MD in the tumor solid region and low-MD habitat,as well as all parameters in the high-MD habitat between methylated and unmethylated groups(t/Z=-3.780-3.153,all P<0.05).The return-to-origin probability(RTOP)in the low-MD habitat demonstrated the highest diagnostic performance,with the area under the curve improving from 0.771 before habitat analysis to 0.827 after habitat analysis.In the high-grade subgroup,significant differences were observed in return-to-axis probability(RTAP)and RTOP in the tumor solid region;RTOP,non-Gaussianity,non-Gaussianity axial,and RTAP in the low-MD habitat;and non-Gaussianity in the high-MD habitat(t/Z=-2.820--1.976,all P<0.05).RTOP in the low-MD habitat again showed optimal diagnostic efficacy(the area under the curve 0.725 before habitat analysis,0.798 after).Multivariate analysis identified RTAP and RTOP in the tumor solid region and low-MD habitat as independent predictors of MGMT methylation.Conclusion MAP-MRI diffusion parameters demonstrate the ability to predict MGMT promoter methylation status in glioma,with superior performance compared with diffusion tensor imaging.Habitat imaging further enhances the predictive efficacy of MAP-MRI parameters for MGMT promoter methylation.

Objective:To provide a scoping review of domestic and international studies on the influencing factors of frailty in stroke inpatients, and to provide guidance for interventional studies on debility in stroke inpatients in China.Methods:A systematic search of domestic and international literature databases, including China National Knowledge Infrastructure, WanFang, VIP, China Biomedical Literature Database, PubMed, Web of Science, Embase, Cochrane Library, CINAHL was conducted about the status and its influencing factors of frailty in stroke inpatients. The retrieval time limit was from database establishment to November 23, 2023. The included literature was extracted, analyzed, and summarized according to the reporting specifications of the scope review guidelines.Results:Thirty-six articles were included, all of the 36 papers reported the prevalence of frailty in patients with stroke. The top three countries with the highest prevalence were China (15.3%-86.9%), the United Kingdom (28%-78%), and Italy (31.37%). The risk factors of stroke frailty were categorized mainly into 4 themes: social demographic factors, physical health factors, disease-related factors, and psychological and social background factors.Conclusions:The confidence of frailty in stroke patients of a higher level at home and abroad, and the risk factors involved are complex and diverse. It is suggested that future studies need to conduct large-sample, multicenter longitudinal studies to clarify the causal relationship, strengthen the exploration of controversial factors of stroke debility, and carry out more targeted intervention studies, so as to reduce the incidence of frailty and improve the recovery process of patients.

Objective:To examine the effect of cumulative hemoglobin A 1c (HbA 1c) levels and insulin dosage on insulin resistance (IR)-related metabolic disturbances in newly diagnosed patients with type 1 diabetes (T1D). Methods:This retrospective cohort study included T1D patients admitted to the Second Xiangya Hospital of Central South University from November 2015 to March 2023. Clinical data collected comprised age, sex, disease duration, insulin dosage, body mass index, waist circumference, blood pressure, HbA 1c levels, islet autoantibodies, and fasting blood lipid profiles. IR-related metabolic disturbances assessed were overweight, obesity, central obesity, hypertension, and dyslipidemia. Cox regression and cluster analyses were applied to assess the influence of cumulative HbA 1c and insulin dosage on these metabolic disturbances. Results:A total of 235 patients were included, with 97 males (41.3%) and 138 females (58.7%). The median age was 19.8 (13.3, 31.1) years, and the median follow-up duration was 30.8 (20.8, 45.6) months. During follow-up, 41.6% (72/173) of patients developed IR-related metabolic disturbances. Multivariate Cox regression analysis revealed that a cumulative HbA 1c ≥60 mmol/mol was an independent risk factor for any IR-related metabolic disturbance [ HR (95% CI): 1.739 (1.067-2.835) ] and for triglyceride abnormalities [ HR (95% CI): 3.277 (1.176-9.127)]. Additionally, a cumulative insulin dosage ≥0.5 U·kg -1·d -1 was identified as an independent risk factor for overweight, obesity, or central obesity [ HR (95% CI): 2.374 (1.059-5.323)]. Cluster analysis further identified that patients with higher levels of cumulative HbA 1c and insulin dosage, particularly those with adolescent-onset diabetes, had the highest likelihood of developing hypertension ( HR=2.460, 95% CI 1.008-6.005), overweight/obesity/central obesity ( HR=2.707, 95% CI 1.062-6.900), triglyceride abnormalities ( HR=5.495, 95% CI 1.842-16.391), high-density lipoprotein cholesterol abnormalities ( HR=11.054, 95% CI 4.107-29.751), and any IR-related metabolic disturbance ( HR=5.833, 95% CI 2.602-13.077). Conclusions:Elevated cumulative HbA 1c and insulin dosage levels in T1D patients are associated with an increased risk of developing IR-related metabolic disturbances. These findings underscore the urgent need for novel therapeutic strategies tailored to this population.

Objective To analyze the radiomic and clinical features extracted from 2D ultrasound images of thyroid tumors in patients with Hashimoto's thyroiditis(HT)combined with papillary thyroid carcinoma(PTC)using machine learning(ML)models,and to explore the diagnostic performance of the method in making preoperative noninvasive identification of cervical lymph node metastasis(LNM).Methods A total of 528 patients with HT combined with PTC were enrolled and divided into two groups based on their pathological results of the presence or absence of LNM.The groups were subsequently designated the With LNM Group and the Without LNM Group.Three ultrasound doctors independently delineated the regions of interest and extracted radiomic features.Two modes,radiomic features and radiomics-clinical features,were used to construct random forest(RF),support vector machine(SVM),LightGBM,K-nearest neighbor(KNN),and XGBoost models.The performance of these five ML models in the two modes was evaluated by the receiver operating characteristic(ROC)curves on the test dataset,and SHapley Additive exPlanations(SHAP)was used for model visualization.Results All five ML models showed good performance,with area under the ROC curve(AUC)ranging from 0.798 to 0.921.LightGBM and XGBoost demonstrated the best performance,outperforming the other models(P＜0.05).The ML models constructed with radiomics-clinical features performed better than those constructed using only radiomic features(P＜0.05).The SHAP visualization of the best-performing models indicated that the anteroposterior diameter,superoinferior diameter,original_shape_VoxelVolume,age,wavelet-LHL_firstorder_10Percentile,and left-to-right diameter had the most significant effect on the LightGBM model.On the other hand,the superoinferior diameter,anteroposterior diameter,left-to-right diameter,original_shape_VoxelVolume,original_firstorder_InterquartileRange,and age had the most significant effect on the XGBoost model.Conclusion ML models based on radiomics and clinical features can accurately evaluate the cervical lymph node status in patients with HT combined with PTC.Among the 5 ML models,LightGBM and XGBoost demonstrate the best evaluation performance.

Humans ; Glycated Hemoglobin ; Diabetes Mellitus, Type 1 ; Blood Glucose ; Diabetes Mellitus, Type 2