BACKGROUND:The formation of postoperative abdominal adhesions is a complicated process,and the prevention of postoperative adhesions is an urgent problem in clinic. OBJECTIVE:To analyze the mechanism of adhesion at cellular and molecular levels,and to provide theoretical basis for the prevention and treatment of adhesion by mesenchymal stem cell exosomes. METHODS:"Abdominal adhesion,pelvic adhesion,postoperative adhesion,epithelial mesenchymal transformation,mesenchymal stem cells,stem cell exosomes,mesenchymal stem cell exosomes"were selected as Chinese and English search terms.We searched PubMed,CNKI,and Chinese biomedical literature and screened relevant articles on postoperative abdominal adhesion and mesenchymal stem cell exosomal intervention published from inception to August 2023.After systematic analysis,54 articles were finally included for the review. RESULTS AND CONCLUSION:(1)Any pathological factors such as peritoneal inflammation,mechanical injury,tissue ischemia,and foreign body implantation cause peritoneal surface injury,resulting in postoperative abdominal adhesion.The formation process of adhesion includes the interaction of peritoneal mesothelial cell repair,inflammatory response,fibrinolytic system,coagulation pathway and other processes,involving a variety of cytokines and signaling pathways.Wnt/β-catenin pathway can induce fibrosis and angiogenesis,and cooperate with transforming growth factor-β/Smads signaling pathway to stimulate fibroblast proliferation and cause peritoneal fibrosis.Meanwhile,nuclear factor-κB signaling pathway up-regulates the expression of cellular inflammatory factors,promotes fibroblast proliferation,and plays a key role in the process of tissue fibrosis.(2)The paracrine function of stem cells is an important direction of molecular intervention in abdominal adhesions based on regenerative medicine.It can participate in a variety of complex cytokines and signaling pathways involved in abdominal adhesions.(3)Compared with traditional methods for treating abdominal adhesions,mesenchymal stem cell exosome has biological activity and is safe to use.Mesenchymal stem cell exosomes without special culture and expansion have lower immunogenicity,longer stability and other advantages,can guide a normal repair and healing through a variety of ways.(4)Mesenchymal stem cell exosome has been proven to be involved in regulating the above processes of adhesion formation in previous studies,showing potential application prospects in clinical studies.However,further clinical studies are needed to explore appropriate treatment options for mesenchymal stem cell exosomes to address the problem of clinical translation.

Objective: To investigate the prevalence and associated factors of spinal curvature abnormalities among primary and secondary school students in the Guangxi Zhuang Autonomous Region, so as to provide a scientific basis for the prevention and control of such abnormalities. Methods: From September to November 2023, adopting a stratified cluster random sampling method, spinal curvature screenings and questionnaire surveys were conducted among 168 931 students from grade 4 of primary school to grade 12 of high school in 111 districts and counties across 14 cities in Guangxi. Chi square tests and binary Logistic regression analysis were used to analyze influencing factors of spinal curvature abnormalities. Results: In 2023, the detection rate of poor posture among students above grade 4 in Guangxi was 4.24% , and the detection rate of spinal curvature abnormalities was 2.13%. The detection rate was higher among urban students (2.84%) than rural students (1.66%), boarding students (2.61%) than non-boarding students (1.60%), and high school students (3.16%) than junior high (2.45%) and primary school students (1.15%), and the differences were statistically significant ( χ 2=269.85, 221.44, 565.10, P <0.01). A trend of increasing detection rates with higher grade levels was observed ( χ 2 trend =617.63, P <0.01). Binary Logistic regression analysis indicated that students without boarding at school ( OR =0.82, 95% CI =0.75-0.90), engaging in high-intensity physical activity for over 60 min per day ≥5 days per week ( OR =0.90, 95% CI =0.82-0.98), and adequate sleep ( OR =0.87, 95% CI =0.81-0.94) had lower risks of detecting spinal curvature abnormalities ( P <0.05). Conclusions The prevalence of spinal curvature abnormalities increases with grade level among primary and secondary school students in Guangxi. Regular moderate-to-vigorous physical activity demonstrates protective effects against spinal abnormalities.

Objective To investigate dynamic changes in myocardial protein phosphorylation during the acute phase of myocardial infarction (MI) in mice. Methods Six 8-week-old C57BL/6J mice were randomly assigned to MI model (n＝3) or sham-operated control (n＝3) groups. Cardiac tissues were harvested 72 hours post-intervention for proteomic analysis. Phosphorylation modifications were systematically characterized using liquid chromatography-mass spectrometry (LC-MS). Bioinformatics analyses included differential phosphorylation screening, functional enrichment, hierarchical clustering, and protein-protein interaction network. Results LC-MS identified 1 921 differentially phosphorylated sites (20 tyrosine and 1 901 serine/threonine sites) across 851 proteins. Compared with controls, MI hearts exhibited significant phosphorylation upregulation at 1 545 sites and downregulation at 376 sites (P＜0.05). Conclusions This study delineates MI-associated phosphorylation dynamics, providing mechanistic insights and potential therapeutic targets for acute MI intervention.

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.

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

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

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

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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