Objective: To explore the effect of different obesity indicators in predicting cardiovascular and cerebrovascular diseases (CVD) risk among patients with type 2 diabetes mellitus (T2DM), so as to provide the evidence for the early identification of CVD risk among T2DM patients. Methods: The patients with T2DM under community management in Qingpu District, Shanghai Municipality were selected as the study subjects in January 2025. Basic information such as gender, age, and blood glucose control status were collected through the Shanghai Chronic Disease Information Management System, while history of CVD were obtained from residents' electronic health records and the Shanghai Disease Control Information Platform. Obesity was assessed using body mass index (BMI), waist circumference (WC), BMI combined with WC, waist-to-height ratio (WHtR), and triglyceride (TG) combined with WC indicators. The association between obesity and CVD was analyzed using multivariable logistic regression models. The predictive effect of each obesity indicators for CVD was evaluated using the area under the receiver operating characteristic curve (AUC). Results: A total of 4 367 patients with T2DM were included, including 2 121 males (48.57%) and 2 246 females (51.43%). The average age was (68.71±8.05) years. The prevalence of CVD was 44.49%. Multivariable logistic regression analysis showed that after adjusting for age, education level, history of hypertension, duration of T2DM, use of glucose-lowering medications, renal function, and blood glucose control status, obese T2DM patients had a 389.4% increased risk of CVD compared to those with normal BMI; centrally obese T2DM patients had a 100.4% increased risk compared to those with normal WC; T2DM patients with isolated general obesity and compound obesity had 161.0% and 241.1% increased risks of CVD, respectively, compared to those with normal BMI and WC; centrally obese T2DM patients had a 100.4% increased risk compared to those with normal WHtR; T2DM patients with normal TG-high WC and high TG-high WC phenotypes had 83.1% and 68.8% increased risks of CVD, respectively, compared to those with normal TG and normal WC (all P<0.05). BMI had the highest AUC, at 0.714, with sensitivity and specificity of 0.675 and 0.642, respectively. This was followed by BMI combined with WC, which had an AUC of 0.707, with sensitivity and specificity of 0.635 and 0.679, respectively. Conclusions Obesity defined by BMI, WC, BMI combined with WC, WHtR, and TG combined with WC increases the risk of CVD among patients with T2DM. BMI and BMI combined with WC have better predictive effect in predicting CVD risk among patients with T2DM, and can be used as the primary obesity indicators for CVD risk screening.

Objective: To analyze the occupational health literacy (OHL) level and its influencing factors among key populations in the tertiary industry in Lu'an City, Anhui Province, so as to provide a basis for developing targeted health interventions and improving regional occupational health policies. Methods: A stratified cluster random sampling method was employed to select five categories of key populations from the tertiary industry in Lu'an City as study subjects from August to September 2024. Data on gender, age, education level, and OHL were collected through the National OHL Monitoring Questionnaire for Key Populations. The OHL levels were analyzed, and influencing factors of OHL levels among key populations were analyzed using a multivariable logistic regression model. Results: A total of 1 243 individuals were surveyed, comprising 700 (56.32%) males and 543 (43.68%) females. The median age was 42.00 (interquartile range, 17.00) years. There were 609 individuals with OHL, and the OHL level was 48.99%. The OHL levels in fundamental knowledge of occupational health protection, healthy work styles and behaviors, knowledge of occupational health laws, and basic skills for occupational health protection were 84.71%, 60.34%, 43.93%, and 37.09%, respectively. Multivariable logistic regression analysis showed that educational level (primary school and below, OR=0.149, 95%CI: 0.064-0.344; junior high school, OR=0.340, 95%CI: 0.184-0.629; high school, OR=0.408, 95%CI: 0.230-0.723), average monthly personal income (3 000-<5 000 yuan, OR=1.655, 95%CI: 1.092-2.508; 5 000-<7 000 yuan, OR=2.195, 95%CI: 1.302-3.699; ≥7 000 yuan, OR=2.062, 95%CI: 1.016-4.183), employer nature (private enterprises, OR=2.992, 95%CI: 1.569-5.443), and industry category (education, OR=3.423, 95%CI: 1.407-8.327; courier / food delivery services, OR=0.459, 95%CI: 0.268-0.787; healthcare, OR=7.539, 95%CI: 3.255-17.461) were statistically associated with the OHL level among key population. Conclusion The OHL level among key population in the tertiary industry of Lu'an City can be further enhanced, with educational level, average monthly personal income, employer nature, and industry category identified as the primary influencing factors.

Electrical impedance tomography (EIT) is a technique that uses an array of electrodes to deliver safe stimulating currents and measures the boundary voltages between adjacent electrode pairs in the array in sequence. Subsequently, it reconstructs the impedance distribution in all or part of the tissue using reconstruction algorithms to achieve structural and functional imaging. Lung EIT technology features continuity, being radiation-free and non-invasive, and it can be used for real-time dynamic monitoring of the lungs in critically ill patients. This paper introduces the basic principles of lung EIT, analyzes the research progress and existing problems of the technology from the perspectives of hardware systems, imaging algorithms, and clinical applications (such as lung ventilation, lung perfusion, and lung function assessment), and discusses the development direction to provide ideas for expanding the clinical application of lung EIT.
Electric Impedance ; Humans ; Tomography/methods* ; Lung Diseases/therapy* ; Algorithms

Dendritic cells (DCs) serve as the primary antigen-presenting cells in autoimmune diseases, like rheumatoid arthritis (RA), and exhibit distinct signaling profiles due to antigenic diversity. Type II collagen (CII) has been recognized as an RA-specific antigen; however, little is known about CII-stimulated DCs, limiting the development of RA-specific therapeutic interventions. In this study, we show that CII-stimulated DCs display a preferential gene expression profile associated with migration, offering a new perspective for targeting DC migration in RA treatment. Then, saikosaponin D (SSD) was identified as a compound capable of blocking CII-induced DC migration and effectively ameliorating arthritis. Optineurin (OPTN) is further revealed as a potential SSD target, with Optn deletion impairing CII-pulsed DC migration without affecting maturation. Function analyses uncover that OPTN prevents the proteasomal transport and ubiquitin-dependent degradation of C-C chemokine receptor 7 (CCR7), a pivotal chemokine receptor in DC migration. Optn-deficient DCs exhibit reduced CCR7 expression, leading to slower migration in CII-surrounded environment, thus alleviating arthritis progression. Our findings underscore the significance of antigen-specific DC activation in RA and suggest OPTN is a crucial regulator of CII-specific DC migration. OPTN emerges as a promising drug target for RA, potentially offering significant value for the therapeutic management of RA.

The anterior cingulate cortex (ACC) has recently been proposed as a key player in the representation of itch stimuli. However, to date, little is known about the contribution of specific ACC interneuron populations to itch processing. Using c-Fos immunolabeling and in vivo Ca²⁺ imaging, we reported that both histamine and chloroquine stimuli-induced acute itch caused a marked enhancement of vasoactive intestinal peptide (VIP)-expressing interneuron activity in the ACC. Behavioral data indicated that optogenetic and chemogenetic activation of these neurons reduced scratching responses related to histaminergic and non-histaminergic acute itch. Similar neural activity and modulatory role of these neurons were seen in mice with chronic itch induced by contact dermatitis. Together, this study highlights the importance of ACC VIP⁺ neurons in modulating itch-related affect and behavior, which may help us to develop novel mechanism-based strategies to treat refractory chronic itch in the clinic.
Animals ; Pruritus/physiopathology* ; Vasoactive Intestinal Peptide/metabolism* ; Interneurons/metabolism* ; Gyrus Cinguli/metabolism* ; Mice ; Male ; Mice, Inbred C57BL ; Histamine ; Chloroquine ; Optogenetics ; Mice, Transgenic

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

Objective:To analyze the characteristics of patients with chronic rhinosinusitis (CRS) in the South China region based on pathological tissue biomarkers for regional comparison.Methods:The study population consisted of CRS in-patients in the First Affiliated Hospital of Sun Yat-sen University from October 2019 to June 2022. Among all the 181 cases, 123 of them were male and 58 were female, with an average age of 40. Retrospectively collected clinical data included demographic information, preoperative symptom scores, preoperative endoscopic images, preoperative paranasal sinus computed tomography scanning images, and inflammatory serological features. In addition, 52 variables of pathological tissue biomarkers including cytokines, chemokines and remodeling factors were collected for analysis. Cluster analysis was performed on the integrated data of training set through centroid-based clustering algorithm, and the inflammatory characteristics, post-operation control status, and airway diseases comorbidity of each endotype were analyzed. R project (version 4.2.2) was used in statistical analysis.Results:Cluster analysis divided 181 patients with CRS into 4 endotypes. Cluster 1 ( n=101, 55.80%) showed a locally low inflammatory status. Cluster 2 ( n=23, 12.71%) showed a mixed type of inflammation with predominantly neutrophilic inflammation and tissue remodeling. Cluster 3 ( n=11, 6.08%) was characterized by type Ⅱ inflammation without tissue remodeling. Cluster 4 ( n=46, 25.41%) was mainly characterized by type Ⅱ inflammation with tissue remodeling, showing higher comorbidity rate of asthma and allergic rhinitis. This cluster presented more severe symptoms, significant olfactory dysfunction, extensive overall inflammation based on objective examination results, a notable increase in total eosinophil count and proportion in peripheral blood, and the highest uncontrolled rate observed one year post-surgery. In comparison to other regions, the endotype classification of CRS in Southern China was characterized by a predominant pattern of locally low inflammatory status, a moderate level of type Ⅱ inflammation with tissue remodeling, and a lesser presence of neutrophilic inflammation. Conclusion:CRS distribution in Southern China is mainly characterized by low inflammatory endotype and type Ⅱ inflammation with tissue remodeling. The latter shows more severe clinical manifestations and higher uncontrol rate after surgery.

BACKGROUND:Proximal humerus internal locking system locking plate is the most commonly used fixation method for proximal humeral fractures,but its failure rate is still high in clinical practice.Reasonable screw placement is an important factor affecting the stability of internal fixation. OBJECTIVE:To investigate the distribution of humeral head screws in the treatment of proximal humeral fractures with proximal humerus internal locking system plate and its influence on internal fixation failure. METHODS:From January 2017 to December 2021,data from patients with proximal humeral fractures undergoing proximal humerus internal locking system plate in Third Affiliated Hospital of Guangzhou University of Chinese Medicine were retrospectively analyzed.A total of 124 patients were enrolled,including 16 males and 108 females,at the age of≥60 years.According to whether there was internal fixation failure after operation,they were divided into normal group(n=101)and internal fixation failure group(n=23).The patient's age,gender,fracture type,the integrity of the medial column,plate height,neck-shaft angle,whether the talus screw was inserted,and the number of humeral head screws,were collected.The humeral head was divided into eight zones according to the postoperative digital radiography anteroposterior film,and the distribution characteristics of the screws in each zone were collected,and the heat map of the screw distribution was drawn. RESULTS AND CONCLUSION:(1)There were no significant differences between the two groups in age,gender,fracture type,the integrity of the medial column,plate height,neck-shaft angle,whether to insert talus screws,and the number of humeral head screws(P>0.05).(2)The heat map showed that the humeral head screws were evenly distributed in the normal group,mainly scattered in zones 4,6,and 7.However,the screw distribution in the internal fixation failure group was not uniform,mainly concentrated in zones 4 and 6.In addition,in the ideal area of talus screws(7/8 zone),there were significantly more screws in the normal group than in the internal fixation failure group.(3)It is indicated that in the treatment of proximal humeral fractures with proximal humerus internal locking system plate,the uniform distribution of humeral head screws is the key to ensuring the internal fixation effect.A reasonable distribution of humeral head screws helps to improve the treatment effect and the success rate of internal fixation.

Objective To understand the characteristics and temporal trends of stroke incidence in the household population of Shanghai's Qingpu District and to provide a basis for the development of comprehensive prevention and control strategies. Methods The stroke case database for Qingpu District from 2017-2022 was obtained from the Shanghai Stroke and Acute Myocardial Infarction Registry and Reporting Information System. The average age of onset, incidence rate, standardised incidence rate, and constitutive ratio were calculated. Independent samples t-tests were used for comparisons between groups, 2-tests and 2-trend tests for comparisons of rates, and the Joinpoint regression model for calculating the annual percentage change (APC) to analyse the temporal trend of rates. Results Between 2017 and 2022, the average age of stroke onset in the household population of Shanghai's Qingpu District was 73.69±11.60 years. The average annual incidence rate was 556.62/100 000, with an average annual standardised incidence rate of 333.76/100000. There was an increasing trend in the incidence and standardised incidence of stroke in males (APC=7.06%, t=3.44, P=0.03, APC=5.32%, t=3.04, P=0.04). The incidence of stroke increases with age, with cases mainly concentrated in those aged 65 years and above, accounting for 79.47%. Ischemic stroke dominates the stroke typology, accounting for 91.08% of cases, while the incidence of hemorrhagic stroke shows an increasing trend (APC=4.64%, t=4.59, P=0.01). Conclusion The occurrence of stroke in the general population of Shanghai’s Qingpu District is concerning. The study indicates that males, individuals aged 65 years and above, and ischaemic stroke are significant factors that require attention for stroke prevention and control.