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 assess the effects of low-dose esketamine on the median effective dose(ED50)of ciprofol for anesthesia induction in painless gastrointestinal endoscopy.Methods Fifty-nine pa-tients underwent elective painless gastrointestinal endoscopy,26 males and 33 females,aged 18-64 years,BMI 18-30 kg/m2,ASA physical status Ⅰ or Ⅱ,were divided into two groups by random number table method:esketamine combined with ciprofol group(group EC,n = 29)and ciprofol group(group C,n = 30).Group EC received intravenous injection of esketamine 0.3 mg/kg and group C received the same amount of normal saline 2 minutes before administration of ciprofol.The initial anesthesia induction dose of ciprofol was 0.4 mg/kg.If a positive reaction occurs during the examination,the next patient will receive an increase dose of propofol 0.04 mg/kg,otherwise will decrease by propofol 0.04 mg/kg.The positive reaction was defined that the patient's BIS can not be decreased to 60 2 minutes after anesthesia induction,or the cough or body movement reaction occur at level 2 or above when entering the mirror.The dosage of ciprofol,recovery time,discharge time,the occurrence of intraoperative and postoperative adverse reactions were recorded.The ED50,95%effective dose(ED95)and 95%confidence interval(CI)of the two groups were calculated by Probit probability regression analysis.Results Compared with group C,the dosage of ciprofol,the incidence of hypotension and frequency of administration of vasoactive drugs during the exami-nation process in group EC were significantly reduced(P＜0.05).The ED50 of ciprofol for anesthesia in-duction in painless gastrointestinal endoscopy in group EC was 0.21 mg/kg(95%CI 0.12-0.25 mg/kg)and the ED95 was 0.32 mg/kg(95%CI 0.26-0.39 mg/kg).The ED50 of ciprofol for anesthesia induction in painless gastrointestinal endoscopy in group C was 0.37 mg/kg(95%CI 0.32-0.40 mg/kg)and the ED95 was 0.48 mg/kg(95%CI 0.43-0.54 mg/kg).The ED50 and ED95 of ciprofol for anesthesia induction in painless gastrointestinal endoscopy in group EC was significantly lower than that in group C(P＜0.05).There was no significant difference in other frequency of adverse events between the two groups.Conclusion Esketamine 0.3 mg/kg can reduce the ED50 of ciprofol in painless gastrointestinal endoscopy and reduce the dosage of ciprofol during the examination process,which is safe for painless gastrointestinal endoscopy with stable intraoperative circulation.

Objective·To construct and verify the mouse model that can mimic the vitamin A deficiency(VAD)-like craniofacial skeletal deformity and do not cause embryonic death.Methods·Based on the Cre-LoxP system,the OsxCre;Rosa26dn/dn mice expressing osteoblast-specific dominant-negative retinoid acid receptor α(dnRARα)mutation were obtained by hybridization through OsxCre and Rosa26dnRARa/ddnRARa mice,to achieve the conditional inhibition of retinoic acid signaling to simulate VAD disease.Femur bone mesenchymal stem cells(BMSCs)and parietal bone cells of OsxCre;Rosa26dn/dn mice and their control littermates were isolated and underwent osteogenic induction,to assess the expression of retinoid acid receptor α(RARα)protein through Western blotting.Osteoblasts induced from parietal bone cells of OsxCre;Rosa26dn/dn mice and their control littermates were isolated and the effect of retinoic acid signaling inhibition was verified through dual luciferase gene reporter assay.Meanwhile,Ad-eGFP or Ad-Cre adenovirus-infected femur BMSCs and parietal bone cells of Rosa26dn/dnmice underwent osteogenic induction to assess the expression of dominant-negative mutant protein and the inhibition of the retinoic acid signaling pathway in vitro by Western blotting and dual luciferase gene reporter assay.Moreover,the skulls of 6-week-old OsxCre;Rosa26dn/dn mice were collected,and Micro-CT scanning and three-dimensional(3D)reconstruction were performed to verify the craniofacial skeletal deformities of the mouse model.Results·Western blotting results demonstrated that the level of RARα protein increased in the femur and parietal osteoblasts of OsxCre;Rosa26dn/dn mice compared to that of their control littermates,and also increased in the Ad-Cre-infected femur and parietal osteoblasts of Rosa26dn/dn mice compared to that in the Ad-eGFP-infected group(P＜0.05).Dualluciferase gene reporter assay results indicated that the activity of retinoid acid response element(RARE)was inhibited in the osteoblasts of OsxCre;Rosa26dn/dn mice compared to their control littermates,and was also inhibited in the Ad-Cre-infected group compared to the Ad-eGFP-infected group(P＜0.05).Micro-CT and 3D reconstruction suggested that the skull of 6-week-old OsxCre;Rosa26dn/dn mice exhibited VAD-like craniofacial skeletal deformities,including smaller size of the skull and osteogenesis imperfecta compared to their control littermates.Conclusion·An osteoblast-specific dnRARα expressing mouse model that can mimic VAD-like craniofacial skeletal deformity is successfully constructed,therefore providing a new model for exploring the pathogenesis and therapeutic targets of VAD-like craniofacial skeletal deformity in the future.

Tumor microenvironment(TME)is a complex cellular environment where tumor cells reside,along with various types of cells and extracellular components surrounding the tumor cells.Immune cells are key components of TME,including tumor-associated macrophages(TAMs),myeloid-derived suppressor cells(MDSCs),lymphocytes,regulatory T cells(Tregs),natural killer cells(NK cells),dendritic cells(DCs),and many others.It is worth noting that drug resistance is currently a major factor limiting the efficacy of cancer treatment methods such as chemotherapy,radiotherapy,targeted therapy,and immunotherapy,and a leading cause of treatment failure.Research has found that the development of drug resistance in tumor cells is the result of interactions between tumor cells and TME.Consequently,overcoming drug resistance in tumors caused by TME is considered a significant challenge in cancer treatment.In recent years,with in-depth research into immune cells within TME,significant progress has been made in understanding the specific mechanisms by which immune cells regulate drug resistance in tumor cells.Furthermore,therapeutic strategies that target these immune cells,signaling pathways,or cytokines have been shown to effectively combat tumor drug resistance and enhance the therapeutic outcomes of cancer treatment.This article reviews the research advancements regarding the roles of TAMs,MDSCs,Tregs,and NK cells in tumor drug resistance within TME and discusses the development of targeting strategies to overcome this resistance.Additionally,we explore the relationship of tumor-associated neutrophils(TANs)and B regulatory cells(Bregs)with tumor drug resistance.It is hoped that this review will offer insights and serve as reference for reducing tumor drug resistance and improving the efficacy of anti-tumor therapies.