ObjectiveTo observe the effects of Xiere Xingpi Yin （XRXPY） on the body mass and body fat distribution in patients with simple obesity， and to preliminarily explore whether the mechanism involves the regulation of specific obesity-related microRNAs （miRNAs）. MethodsA randomized controlled trial design was employed to recruit patients with simple obesity diagnosed with the traditional Chinese medicine （TCM） syndrome of dampness-heat accumulating in the spleen. Using a randomized controlled trial design， 95 patients with simple obesity of dampness-heat encumbering the Spleen syndrome were recruited， after 3 were excluded， 92 were randomly assigned in a 1∶1 ratio by means of a random number table. On the basis of lifestyle intervention， the observation group received XRXPY granules， while the control group received a placebo. Serum samples and TCM symptom scores were collected before and after the 12-week observation period. Differences in body mass loss， body composition， lipid metabolism， and TCM symptom scores were compared between the groups. An obesity-related miRNA dataset was constructed by searching the Human MicroRNA Disease Database. Library construction， sequencing， and quality control were performed on 6 selected patients from each group to screen the differentially expressed miRNAs. The intersection of these miRNAs with the obesity-related miRNAs was verified by bioinformatics and correlation analysis. ResultsBaseline characteristics were comparable between the two groups before treatment. A total of 86 patients completed the study （42 cases in the observation group and 44 cases in the control group）. The proportion of patients achieving ≥5% body weight reduction was significantly higher in the observation group than in the control group 81.0% （34/42） vs. 43.2% （19/44） （χ²=12.963， P<0.01）. Compared with baseline within the observation group， body weight， waist circumference， and TCM syndrome score were significantly decreased （P<0.01）， as were body fat percentage （P<0.01） and serum triglyceride level （P<0.05）. Compared with the control group after treatment， waist circumference and TCM syndrome score were significantly lower in the observation group （P<0.01）， and body weight showed a trend toward reduction. When changes from baseline were compared between the two groups， the magnitudes of decrease in body weight， waist circumference， and TCM syndrome score were all significantly greater in the observation group than in the control group （P<0.01）. With respect to safety， no serious adverse events occurred in either group and no participant discontinued the study because of adverse events. Compared with baseline， alanine aminotransferase levels decreased significantly in both the control and observation groups （P<0.01）， and urea decreased significantly in the observation group （P<0.01）， indicating a favorable safety profile. Sequencing identified nine differentially expressed miRNAs. After intersecting with the obesity-related miRNA dataset （187 miRNAs）， 3 miRNAs were identified： miR-221 （log₂FC=-6.62， P=0.009）， miR-29a （log₂FC=6.33， P=0.016）， and miR-10b （log₂FC=-5.91， P=0.029）. A total of 262 target genes of the 3 miRNAs were identified， which were significantly enriched in 67 pathways， including the lysine degradation pathway （P=0.001）. Correlation analysis revealed a positive correlation between miR-221 and triglycerides （r=0.46， P=0.027）， a negative correlation between miR-29a and waist-to-hip ratio （r=-0.41， P=0.047）， and positive correlations of miR-10b with body fat percentage （r=0.49， P=0.014） and waist circumference （r=0.44， P=0.032）. ConclusionXRXPY combined with lifestyle intervention can effectively reduce the body mass and improve body composition. The underlying mechanism may involve the regulation of the lysine degradation pathway via miR-221， miR-29a， and miR-10b， though further verification is required.

ObjectiveTo observe the effects of Xiere Xingpi Yin （XRXPY） on the body mass and body fat distribution in patients with simple obesity， and to preliminarily explore whether the mechanism involves the regulation of specific obesity-related microRNAs （miRNAs）. MethodsA randomized controlled trial design was employed to recruit patients with simple obesity diagnosed with the traditional Chinese medicine （TCM） syndrome of dampness-heat accumulating in the spleen. Using a randomized controlled trial design， 95 patients with simple obesity of dampness-heat encumbering the Spleen syndrome were recruited， after 3 were excluded， 92 were randomly assigned in a 1∶1 ratio by means of a random number table. On the basis of lifestyle intervention， the observation group received XRXPY granules， while the control group received a placebo. Serum samples and TCM symptom scores were collected before and after the 12-week observation period. Differences in body mass loss， body composition， lipid metabolism， and TCM symptom scores were compared between the groups. An obesity-related miRNA dataset was constructed by searching the Human MicroRNA Disease Database. Library construction， sequencing， and quality control were performed on 6 selected patients from each group to screen the differentially expressed miRNAs. The intersection of these miRNAs with the obesity-related miRNAs was verified by bioinformatics and correlation analysis. ResultsBaseline characteristics were comparable between the two groups before treatment. A total of 86 patients completed the study （42 cases in the observation group and 44 cases in the control group）. The proportion of patients achieving ≥5% body weight reduction was significantly higher in the observation group than in the control group 81.0% （34/42） vs. 43.2% （19/44） （χ²=12.963， P<0.01）. Compared with baseline within the observation group， body weight， waist circumference， and TCM syndrome score were significantly decreased （P<0.01）， as were body fat percentage （P<0.01） and serum triglyceride level （P<0.05）. Compared with the control group after treatment， waist circumference and TCM syndrome score were significantly lower in the observation group （P<0.01）， and body weight showed a trend toward reduction. When changes from baseline were compared between the two groups， the magnitudes of decrease in body weight， waist circumference， and TCM syndrome score were all significantly greater in the observation group than in the control group （P<0.01）. With respect to safety， no serious adverse events occurred in either group and no participant discontinued the study because of adverse events. Compared with baseline， alanine aminotransferase levels decreased significantly in both the control and observation groups （P<0.01）， and urea decreased significantly in the observation group （P<0.01）， indicating a favorable safety profile. Sequencing identified nine differentially expressed miRNAs. After intersecting with the obesity-related miRNA dataset （187 miRNAs）， 3 miRNAs were identified： miR-221 （log₂FC=-6.62， P=0.009）， miR-29a （log₂FC=6.33， P=0.016）， and miR-10b （log₂FC=-5.91， P=0.029）. A total of 262 target genes of the 3 miRNAs were identified， which were significantly enriched in 67 pathways， including the lysine degradation pathway （P=0.001）. Correlation analysis revealed a positive correlation between miR-221 and triglycerides （r=0.46， P=0.027）， a negative correlation between miR-29a and waist-to-hip ratio （r=-0.41， P=0.047）， and positive correlations of miR-10b with body fat percentage （r=0.49， P=0.014） and waist circumference （r=0.44， P=0.032）. ConclusionXRXPY combined with lifestyle intervention can effectively reduce the body mass and improve body composition. The underlying mechanism may involve the regulation of the lysine degradation pathway via miR-221， miR-29a， and miR-10b， though further verification is required.

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.

Objective To investigate the effects of chronic restraint stress for 28 days(day and night)on mood and cognitive-like behavior in male and female ICR mice,to provide a basis for the selection of sex and restraint period in chronic restraint stress model animals.Methods A total of 72 male and female(1∶1)ICR mice were divided into six groups:male control,daytime restraint,and nighttime restraint groups,and female control,daytime restraint,and nighttime restraint groups.Mice in all but the control groups were bound for 10 h/d and restrained continuously for 28 days to establish a chronic restraint stress model.The emotional and cognitive behaviors induced by restraint in male and female mice at different times were observed by open field,Y maze,novel inhibition feeding,elevated cross maze,tail suspension,forced swimming,and dark-avoidance experiments.Results In the tail suspension experiment,the immobility time of male mice in the daytime restraint group was significantly increased compared with that in the control group(P＜0.05),and the immobility times of male mice in the daytime and nighttime restraint groups were also significantly increased in the forced swimming experiment,compared with those in the control group(P＜0.05).There was no significant difference between the female daytime restraint and female control groups in the novelty inhibition feeding experiment,but the feeding latency of the nighttime restraint group was significantly longer than that of the control group(P＜0.05)and the daytime restraint group(P＜0.05).The feeding latency of female mice was significantly longer than that of males during nighttime restraint(P＜0.05).In the open field test,compared with the male control group,the female control group showed a significant decrease in central area time and the ratio of central area time to peripheral area time(P＜0.05).Compared with the female control group,the female daytime restraint group exhibited a significant decrease in central area time and the ratio of central area time to peripheral area time(P＜0.05).There was no significant difference between the groups in the elevated cross maze and Y maze experiments.There was no significant difference in dark latency between the daytime restraint group and the control group,but darkness latency was significantly shorter in the nighttime restraint group compared with those in the control group(P＜0.05).When male and female mice were combined,the immobility time in the daytime restraint group was significantly increased in the tail suspension experiment(P＜0.05),the immobility times of mice in the daytime and nighttime restraint groups were significantly increased in the forced swimming experiment(P＜0.01,P＜0.05),and the central zone time and the ratio of central area time to peripheral area time of daytime restraint mice were significantly shorter compared with those in the control group(P＜0.05,P＜0.01).There was no significant difference in the central zone time and the ratio of central area time to peripheral area time in the nighttime restraint groups,and no significant difference in average speed or total distance between the daytime and nighttime restraint groups.Conclusions Male mice exhibited depression after 28 d of chronic restraint stress during the daytime,while female mice were prone to anxiety after 28 d of chronic restraint stress.Male mice experienced learning and memory impairment after 28 d of chronic restraint stress during the night.

Objective To explore the correlation between the test panel of serum CC chemokine ligand 3(CCL3),soluble podoplanin(sPDPN),fatty acid-binding protein 5(FABP5)and the severity of lung injury and clinical outcomes in children with severe pneumonia.Methods A total of 168 children with severe pneumonia who visited our hospital from January 2022 to January 2023 were included in this study as severe group.The patients were assigned to good outcome group(137 cases)or poor outcome group(31 cases)based on their prognosis.Additional 80 children with mild or moderate pneumonia were treated as non-severe group.In addition,80 children who underwent health checkup were included as control group.Baseline data such as body mass index and duration of disease were observed and recorded for all children.Enzyme linked immunosorbent assay(ELISA)was applied to detect the expression levels of C-reactive protein(CRP),procalcitonin(PCT),interleukin-6(IL-6),tumor necrosis factor-α(TNF-α),CCL3,sPDPN,and FABP5 in the serum of all children.The Acute Physiology and Chronic Health Evaluation Ⅱ(APACHEⅡ)score and Lung Injury Prediction(LIPS)score were rated to evaluate the degree of lung injury.Multivariate logistic regression was used to analyze the impact of various factors on the poor outcome of children with severe pneumonia.Spearman correlation was applied to analyze the correlation between the expression levels of CCL3,sPDPN,FABP5 and poor outcome,the severity of lung injury,APACHE Ⅱ score,and LIPS score in children with severe pneumoniae.Receiver operating characteristic(ROC)curve was applied to analyze the diagnostic value of CCL3,sPDPN,and FABP5 expression levels for poor outcome in children with severe pneumonia.Z-test was used to compare the differences in area under the curve(AUC).Results The baseline data such as duration of disease,body mass index,age,and sex did not show significant differences among the control group,non-severe group,and severe group(P＞0.05).The levels of serum CRP,PCT,IL-6,TNF-α,CCL3,sPDPN increased,while the level of FABP5 decreased gradually from the control group to non-severe group,and severe group(P＜0.05).The patients with poor outcomes showed higher serum levels of CRP,PCT,IL-6,TNF-α,CCL3,sPDPN,APACHE Ⅱ score,and LIPS score but lower FABP5 level compared to the patients with good outcomes(P＜0.05).TNF-α,CCL3,sPDPN,APACHE Ⅱ,and LIPS scores were independent risk factors for poor outcomes in children with severe pneumonia,while FABP5 level was independent protective factor for poor outcomes in children with severe pneumonia(P＜0.05).The levels of CCL3 and sPDPN were positively correlated with APACHE Ⅱ score and LIPS score,while FABP5 was negatively correlated with APACHE Ⅱ score and LIPS score(P＜0.05).The AUC of CCL3,sPDPN,and FABP5 alone was 0.802,0.864,and 0.859 respectively for predicting poor prognosis in children with severe pneumonia.The test panel of CCL3+sPDPN+FABP5 was superior to CCL3,sPDPN,or FABP5 alone(Zcombination-CCL3=3.842,Zcombination-sPDPN=2.585,Zcombination-FABP5=2.957,P＜0.05).Conclusions The serum levels of CCL3 and sPDPN are positively correlated with the severity of lung injury,while FABP5 is negatively correlated with the severity of lung injury in children with severe pneumonia.The test panel of CCL3+sPDPN+FABP5 is valuable for predicting poor outcomes in children with severe pneumonia.

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

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.

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