OBJECTIVE: To compare the clinical efficacy of electroacupuncture (EA) at neuro-arterial stimulation points with topical western medication in treating post-stroke shoulder-hand syndrome (SHS). METHODS: A total of 72 patients with post-stroke SHS were randomly assigned to an observation group (n=36, 2 cases dropped out) and a control group (n=36, 3 cases dropped out). Both groups received standard neurological treatment, comprehensive rehabilitation, and physical therapy. The observation group received EA at neuro-arterial stimulation points, including the ipsilateral stellate ganglion point, vagus nerve trunk and auricular branch (left side), and stimulation points of the radial and ulnar arteries, radial nerve, ulnar nerve, and median nerve, once daily for 4 weeks. The control group was treated with topical diclofenac diethylamine emulgel, and mucopolysaccharide polysulfate cream was added for patients with pronounced early-stage edema, twice a day for 4 weeks. The VAS pain score and hand edema volume were recorded before treatment, at 2 and 4 weeks during treatment, and 2 weeks after treatment completion (follow-up). Musculoskeletal ultrasound was used to measure the thickness of the dorsal hand and middle finger skin on the affected side before and after 4 weeks of treatment. RESULTS: Compared before treatment, the VAS pain scores and edema volume of the affected hand in both groups were decreased at week 2, week 4, and follow-up (P<0.05). At week 4, both groups showed lower VAS pain scores and edema volume than those at week 2 (P<0.05); during follow-up, both VAS pain scores and edema volume were further reduced compared to those at week 4 (P<0.05). At week 2, week 4, and follow-up, the VAS scores and edema volume of the affected hand in the observation group were lower than those in the control group (P<0.05). Compared before treatment, the dorsal hand skin thickness and middle finger skin thickness on the affected side were decreased in both groups after 4 weeks of treatment (P<0.05). Compared with the control group, the observation group showed thinner dorsal hand and middle finger skin thickness after 4 weeks of treatment (P<0.05). CONCLUSION EA at neuro-arterial stimulation points effectively alleviates pain and edema in patients with post-stroke SHS, and demonstrates superior efficacy compared to topical western medication.
Humans ; Male ; Female ; Middle Aged ; Electroacupuncture ; Aged ; Stroke/complications* ; Acupuncture Points ; Adult ; Reflex Sympathetic Dystrophy/physiopathology* ; Treatment Outcome ; Hand

During the operation of warm needling, the needle may be tilted and bent to a large degree, which will cause high temperature of moxibustion on the skin surface around, and even burns in patients. To solve this problem, the team developed a balance fixator for acupuncture needle that can be used at acupoints in various parts of the body, such as on the abdomen, waist, limbs and face. The device is composed of 3 parts, including three (or more)-bifurcated sleeve, cushion pad, and circular fixed base-plate, forming an integrated structure. The three (or more)-bifurcated sleeve increases the contact area with the filiform needle body, which can quickly and easily reduce the curvature of the needle body and fix the filiform needle. According to the different locations of acupoints in clinical practice, the cushion pad is designed as three types, i.e. rectangle, large circle, and small circle. It can not only balance needle body, but also prevent skin burns to a certain extent. This device is simple to manufacture, lightweight in material, and environmental friendly; and is applicable to a simple and safe operation in clinical practice.
Humans ; Acupuncture Therapy/methods* ; Acupuncture Points ; Needles ; Equipment Design

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

Background Psychological disturbances such as work-family conflict and depressive mood are prevalent among occupational groups and are closely related to eating behavior. Therefore, investigating the influencing factors of eating behavior is of great significance for promoting the health behaviors of occupational populations. Objective To clarify the current situation of eating behavior among the occupational populations aged 18 to 60 years in China, and to explore the relationship between work-family conflict, depressive mood, and eating behavior, and to test the mediating role of depressive mood in the relationship. Methods The study used a data set containing occupational populations aged 18 to 60 years extracted from the 2021 Psychology and Behavior Investigation of Chinese Residents. The Work-Family Conflict Scale, the Chinese version of the Sakata Eating Behavior Scale Short Form, and the Patient Health Questionnaire-Depression Scale were used. Potential influencing factors of eating behavior of the occupational populations were evaluated by multiple linear regression. Structural equation modeling was used to analyze the relationships between work-family conflict, depressive mood, and eating behavior, and the Bootstrap method was used to test the mediating effect of depressive mood on the relationship of work-family conflict and eating behavior. Results Among the occupational populations, the proportion of reporting high work-family conflict was 48.4%, and the proportion of reporting mild depression and above was 48.7%. The total score of eating behavior was (16.16±4.64), and the proportion of high abnormal eating behavior tendency was 39.1%. There were significant differences in eating behavior score among different age, educational level, marital status, number of offspring, occupation, smoking, and drinking groups (P<0.05). The partial correlation analysis showed that work-family conflict and depressive mood were positively correlated with abnormal eating behavior (r=0.367, 0.386, P<0.001); work-family conflict was positively correlated with depressive mood (r=0.466, P<0.001). The results of the multiple linear regression showed that depressive mood, work-family conflict, age, smoking, drinking, and education level were associated with eating behavior (P<0.05). The structural equation modeling indicated that work-family conflict positively associated with depressive mood (b=0.529, P<0.001), depressive mood positively associated with abnormal eating behavior (b=0.292, P<0.001), and work-family conflict positively associated with abnormal eating behavior (b=0.270, P<0.001). Depressive mood played a partial mediating role in the relationship between work-family conflict and eating behavior, and the effect value was 0.154 (95%CI: 0.132, 0.179) that accounted for 36.32% of the total effect. Conclusion Work-family conflict could directly affect the eating behavior among occupational populations, and also indirectly affect eating behavior through a mediating effect of depressive mood. Therefore, optimizing the allocation of tasks between work and family, providing psychological support in need, alleviating work-family conflict and depressive mood may improve the eating behavior and mental health of working populations.

Objective:To clarify the changes in incidence and mortality of various cancers based on analysis on registration data of malignant tumor incidence and mortality from Dehui City and Yanji City in Jilin Province.Methods:The incidence and mortality data of malignant tumors from 2009 to 2016 in Dehui City and Yanji City in Jilin Province,were collected from the Chinese Cancer Registry Annual Report published by the National Cancer Center.The number of cases,deaths,crude incidence rate,crude mortality rate,age-standardized incidence rate(ASIR),age-standardized mortality rate(ASMR),and annual percentage change(APC)of the malignant tumors were analyzed by cancer sites and genders.Results:From 2009 to 2016,the CIR of malignant tumors in Dehui City(APC=1.2%,P=0.019)and Yanji City(APC=3.6%,P=0.058)showed an increasing trend.After standard population age adjustment,the ASIR in males in Dehui City showed a significant decline(APC=-5.7%,P=0.021),while the ASIR in females exhibited an overall downward trend,but the difference was not significant(APC=-2.2%,P=0.111).In Yanji City,the ASIR in males(APC=-1.4%,P=0.535)and females(APC=0.0%,P=0.988)showed no significant changes.The CMR of malignant tumors in Dehui City(APC=1.9%,P=0.001)and Yanji City(APC=5.9%,P=0.001)showed a continuous upward trend.After age-standardization,the ASMR in males(APC=-3.1%,P=0.100)and females(APC=-4.2%,P=0.053)in Dehui City,as well as in males(APC=-1.3%,P=0.438)in Yanji City,showed a slight downward trend.Although the ASMR in females in Yanji City showed a slight increase,the difference was not statistically significant(APC=0.5%,P=0.838).In 2016,the most common malignant tumor in terms of both incidence and mortality in Dehui City was lung cancer,with a CIR of 60.76/100 000 and a CMR of 46.96/100 000.In Yanji City,the most common malignant tumor was liver cancer,with a CIR of 49.04/100 000 and a CMR of 51.09/100 000.Conclusion:Lung cancer,liver cancer,and gastric cancer are the major malignant tumors threatening residents in Dehui City,Yanji City,and even the entire Jilin Province,and should be prioritized in cancer prevention and control efforts.Early diagnosis and treatment should be strengthened.

Hypoxic-ischemic brain damage(HIBD)is a leading cause of neonatal mortality and neurological dysfunction in the infants,and it remains a focal point of research in neonatology.MicroRNA(miRNA)is involved in neural development,and its alterations is closely associated with the pathological progression of HIBD.However,there is a lack of effective integration of studies on the specific roles and mechanisms of miRNAs at different pathological stages of the disease.This review summarized the recent researches on miRNA in various stages of HIBD.During the hypoxic-ischemic phase,abnormal expression of certain hypoxia-related miRNA can serve as novel biological diagnostic markers.In the cerebral edema phase,miRNA may maintain the integrity of the blood-brain barrier,alleviating neuronal swelling and structural changes.In the cerebral infarction phase,miRNA can inhibit the expression of apoptotic proteins,enhance the neuronal survival rates,reduce the infarct size,and improve neurological behavior.Further research into the mechanisms of miRNA in HIBD will provide new insights for the development of diagnostic and therapeutic strategies for HIBD.

Objective To evaluate the efficacy and safety of dupilumab combined with 2％cleboride ointment in the treatment of moderate to severe atopic dermatitis,as well as its impact on serological indica-tors.Methods A retrospective analysis was conducted on the clinical data of 67 patients with moderate to se-vere atopic dermatitis(AD)admitted to the Department of Dermatology of Shaoxing University Affiliated Hospital from March 2021 to December 2024.The study subjects were divided into an experimental group(n=35)and a control group(n=32)according to the treatment method.The experimental group was treated with Dupilumab injection and 2％Cleboride ointment,while the control group was treated with ebastine tab-lets and 2％cleboride ointment.Clinical and related serological indicators of patients after 16 weeks of treat-ment were collected,and the itch digital scale score,eczema area and severity(EASI)score,IL-4,IL-13 levels,and incidence of local skin adverse reactions were analyzed before and after treatment in both groups.Results The total effective rate of the experimental group after treatment was 94.29％(33/35),which was higher than the control group[53.13％(17/32)],and the difference was statistically significant(x2=12.862,P＜0.001).There was no statistically significant difference in symptom scores,IL-4,and IL-13 levels between the two groups before treatment(P＞0.05).After treatment,the symptom scores of the experimental group were lower than those of the control group,and the difference was statistically significant(P＜0.05).The lev-els of IL-4 and IL-13 in the experimental group were lower than those in the control group,and the difference was statistically significant(P＜0.05).The incidence of adverse reactions in the experimental group was 2.86％(1/35),significantly lower than the 34.38％(11/32)in the control group,and the difference was sta-tistically significant(x2=9.252,P=0.002).Conclusion The combination of dupilumab injection and 2％cleboride ointment is effective in relieving skin symptoms,regulating cellular immune function,reducing in-flammatory reactions,and minimizing local skin adverse reactions in patients with moderate to severe AD.It is worthy of clinical promotion and use.

The cellular and molecular components of the tumor immune microenvironment (TIME) and their information exchange processes significantly influence the trends of anti-tumor immunity. In recent years, numerous studies have begun to evaluate TIME in the context of previous cancer treatment strategies. This review will systematically summarize the compositional characteristics of TIME and, based on this foundation, explore the impact of current cancer therapies on the remodeling of TIME, aiming to provide new insights for the development of innovative immune combination therapies that can convert TIME into an anti-tumor profile.
Tumor Microenvironment/immunology* ; Humans ; Neoplasms/therapy* ; Immunotherapy/methods* ; Animals

BackgroundThe issue of school absenteeism due to school refusal in adolescents has become increasingly prominent. Acceptance and Commitment Therapy （ACT） has been applied successfully to improve depression， anxiety， and psychological flexibility in adolescents， while few studies have tested the effect of ACT intervention on above-mentioned psychological aspects and return-to-school rate in adolescents with school absenteeism. ObjectiveTo explore the effect of ACT on depression， anxiety， psychological flexibility and return-to-school rate in school absenteeism adolescents， and to provide a broader evidence base for clinical interventions. MethodsFrom May to June 2024， a sample of 50 adolescents with Shenzhen school registration who had been suspended from school for more than a consecutive month for school refusal were recruited based on Wechat official account platform. The adolescents were divided into study group and control group by random number table method. Both groups received psychological education with the theme of 'Causes and Coping Strategies of School Refusal'， and study group added a 6-week ACT intervention with weekly 1-hour sessions. At baseline and after treatment， Patients’ Health Questionnaire Depression Scale-9 item （PHQ-9）， Generalized Anxiety Disorder Scale-7 item （GAD-7） and Comprehensive assessment of Acceptance and Commitment Therapy processes （CompACT） were used for the clinical evaluation. ResultsA total of 45 （90.00%）adolescents completed the study， including 25 in study group and 20 in control group. Analysis revealed that study group scored higher on PHQ-9 and GAD-7， while lower on total CompACT score， openness dimension and awareness dimension compared with control group， with statistical significance （F=7.786， 10.334， 12.922， 14.374， 3.075， P<0.05 or 0.01）. After intervention， the rate of return-to-school was higher in study group than in control group （40.00% vs 10.00%， χ²=5.114， P<0.05）. ConclusionACT intervention for adolescents with school absenteeism may alleviate depression and anxiety， improve their psychological flexibility and increase return-to-school rate.［Funded by the "14^th Five Year Plan" for Social Sciences Project in Jiangxi Province （number， 24JY41D）； Science and Technology Planning Project of Shenzhen Municipality （number， 20210617155253001）］

Objective To explore the feasibility of applying artificial intelligence (AI) technology in chromosomal aberration (CA) analysis for occupational health surveillance of radiation workers and in biological dose estimation during nuclear emergency responses. Methods Peripheral blood samples from healthy volunteers were irradiated in vitro with X-rays and cobalt-60 (⁶⁰Co) γ rays. Chromosome slides were prepared using an automated harvesting and dropping device. The data training and outcome evaluation of CA analysis was performed on the AI software using chromosome images from occupational medical examination of radiation workers from the current lab or chromosome slides from blood samples irradiated with X-rays. The trained AI software was then used to assist in CA analysis and biological dose estimation among occupational medical examination of radiation workers, with results compared with manual reading and actual exposure doses. Results The trained AI software achieved a CA recognition accuracy of 95.11%. In the occupational health examination of radiation workers, the positive CA detection rate using AI + manual review was 2.25% higher than that in manual reviewing alone. The errors in biological dose estimation for ⁶⁰Co γ rays and X-rays using AI + manual review analysis were 11.86% and 7.33%, respectively, both within the acceptable 20.00% error margin. Conclusion AI + manual review can be effectively applied in CA analysis for occupational health examination and biological dose estimation during nuclear emergencies, significantly improving analysis efficiency.