Numerous studies have shown that depression is main-ly associated with the abnormal expression of connexin 43(Cx43)in astrocytes(Astro)and its mediated dysfunction of gap junction(GJ).However,the molecular mechanism of post-translational modifications targeting Cx43 to regulate neuroin-flammation-associated depression is still unclear.Post-transla-tional modifications of Cx43 mainly include phosphorylation of specific amino acid sites by PKC,PKA,PKG,MAPK and PTK,and protein degradation of Cx43 through the K48/K63 polyubiq-uitylation and deubiquitination pathways,which ultimately lead to protein degradation through K48/K63 polyubiquitination and deubiquitination.These modifications are ultimately involved in the regulation of neuroinflammatory responses through the associ-ation of GJ function.In this paper,we systematically review the role of Cx43 post-translational modifications in neuroinflamma-tion,with the aim of further exploring the potential application of targeting these modifications to modulate the inflammatory re-sponse mechanism in improving depressive symptoms.

Objective To propose a lightweight deep learning network-based segmentation method for automatic segmenta-tion of the skeletal muscle at the third cervical spine(C3)level.Methods Firstly,121 patients with head and neck tumors admitted to the Department of Oncology of Zigong First People's Hospital from January 2019 to December 2022 were selected and randomly divided into a training set,a validation set and a test set in the ratio of 7∶1∶2.Secondly,a lightweight Mamba architecture was introduced into the UNet network and an attention gate(AG)mechanism was added to the skip connection path to construct a MB-UNet network model.Finally,the trained network models were evaluated for segmentation performance on the test set,the MB-UNet network model was compared with manual segmentation over the results of determination of skeletal muscle area(SMA),and with classical network models in terms of parameter scale and computation effort including UNet,Deeplab V3+,U2Net,VMUNet and UltraLight-VMUNet models.The time required by the MB-UNet network model for predicting SMA and that by the physician with the assistance of the model was summarized.Results When used for segmenting the skeletal muscle at C3 level the constructued MB-UNet network model gained advantages over the classical models,with a Dice similarity coefficient of 88.23%,an intersection over union(IoU)ratio of 78.94%,a sensitivity of 91.27%and a 95%Hausdorff distance of 7.13 mm;the SMA determined by manual segementation was basically close to that by the MB-UNet network model;the MB-UNet network model behaved generally better than the classical network models,with the computation effort being 1.88 GFLOPS and the parameter scale being 0.77M;it took the MB-UNet network model 1.93 s for the prediction on the test set,and only 2 min for the physician to obtain satisfactory results with the assistance of the MB-UNet network model,which was significantly shorter than that by munual segmentation(20 min).Conclusion The proposed method contributes to segmenting the skeletal muscle at C3 level precisely and rapidly and calculating SMA accurately,which helps clinicians to quickly diagnose sarcopenia in patients with head and neck tumors and improves the diagnostic efficiency.[Chinese Medical Equipment Journal,2025,46(8):11-17]

Objective To investigate the value of patient data-based real-time quality control(PBRTQC)in internal quality control(IQC)for blood cells analysis based on the data from patients.Methods The data of patients'blood cells,including white blood cell count(WBC),hemoglobin(Hb),red blood cell count(RBC),hematocrit(HCT),mean corpuscular volume(MCV),mean cor-puscular hemoglobin(MCH),mean corpuscular hemoglobin concentration(MCHC),and platelet(PLT)were collected from August 1,2023 to February 26,2024,and the extracted patient data were analyzed on the AI-based real-time quality control intelligent moni-toring platform.The corresponding IQC data for this period were reviewed,and the results of PBRTQC and IQC were compared and an-alyzed.The causes of the emerging warning or alarm prompts were checked and analyzed to explore the application value of PBRTQC in the IQC process of blood cell analysis.Results It is found that when the quality control product was unstable due to overlong opening time of the reagent or improper storage conditions,and the performance changes of the operating system during the detection process,the PBRTQC intelligent monitoring platform was able to issue risk warning or alarm prompt in advance.PBRTQC may have certain limi-tations,such as the error of red blood cell count,which need to be identified.Conclusion PBRTQC is superior to IQC in blood cell analysis and may play a complementary role in IQC.Meanwhile,it is necessary to exclude the possibility that PBRTQC is significantly influenced by the patient population in medical laboratories.

Objective To evaluate the medical service performance of the cardiovascular department in a tertiary hospital in Hunan Province using Diagnosis Related Groups(DRGs)and Entropy Weighted TOPSIS methods,providing suggestions for discipline construction and development.Methods Data from the front pages of hospitalization cases in the Department of Cardi-ovascular Medicine from 2018 to 2023 were collected.Both traditional indicators and DRG(Diagnosis-Related Group)indicators were utilized to analyze the department's overall performance,the structure of treated disease groups,and the comparative per-formance across different wards.Results The number of discharged cases and the Case Mix Index(CMI)in the cardiovascular medicine department of the sample hospital exhibited a fluctuating upward trend,while the number of DRG groups remained rela-tively stable,reflecting ideal professional coverage.Certain key disease groups demonstrated higher time and cost consumption in-dices,and variations in medical service performance were observed across different wards.Furthermore,in the Entropy Weighted TOPSIS comprehensive evaluation,the rankings of the four wards aligned with their actual developmental positioning within the discipline.Conclusion The DRG method and Entropy Weighted TOPSIS provide an effective framework for evaluating medical service performance in hospital disciplinary development,utilizing reasonable evaluation indicators.These methods offer valuable insights for guiding the development of key clinical specialties and enhancing the overall level of disciplinary capability.

Objective To propose a lightweight deep learning network-based segmentation method for automatic segmenta-tion of the skeletal muscle at the third cervical spine(C3)level.Methods Firstly,121 patients with head and neck tumors admitted to the Department of Oncology of Zigong First People's Hospital from January 2019 to December 2022 were selected and randomly divided into a training set,a validation set and a test set in the ratio of 7∶1∶2.Secondly,a lightweight Mamba architecture was introduced into the UNet network and an attention gate(AG)mechanism was added to the skip connection path to construct a MB-UNet network model.Finally,the trained network models were evaluated for segmentation performance on the test set,the MB-UNet network model was compared with manual segmentation over the results of determination of skeletal muscle area(SMA),and with classical network models in terms of parameter scale and computation effort including UNet,Deeplab V3+,U2Net,VMUNet and UltraLight-VMUNet models.The time required by the MB-UNet network model for predicting SMA and that by the physician with the assistance of the model was summarized.Results When used for segmenting the skeletal muscle at C3 level the constructued MB-UNet network model gained advantages over the classical models,with a Dice similarity coefficient of 88.23%,an intersection over union(IoU)ratio of 78.94%,a sensitivity of 91.27%and a 95%Hausdorff distance of 7.13 mm;the SMA determined by manual segementation was basically close to that by the MB-UNet network model;the MB-UNet network model behaved generally better than the classical network models,with the computation effort being 1.88 GFLOPS and the parameter scale being 0.77M;it took the MB-UNet network model 1.93 s for the prediction on the test set,and only 2 min for the physician to obtain satisfactory results with the assistance of the MB-UNet network model,which was significantly shorter than that by munual segmentation(20 min).Conclusion The proposed method contributes to segmenting the skeletal muscle at C3 level precisely and rapidly and calculating SMA accurately,which helps clinicians to quickly diagnose sarcopenia in patients with head and neck tumors and improves the diagnostic efficiency.[Chinese Medical Equipment Journal,2025,46(8):11-17]

Objective:To investigate the incidence of shoulder work-related musculoskeletal disorders (WMSDs) among occupational population in China, and to explore their intrinsic association with personal and work-related factors.Methods:In April 2024, 73497 valid questionnaires of the Chinese version of the Musculoskeletal Disorders Electronic Questionnaire were retrospectively analyzed from June 2018 to December 2023 in 22 provinces and 29 key industries in China, and the general information, occurrence of WMSDs and related risk factors of key occupational populations in different regions in China were collected. By using Chi-square test and confirmatory factor analysis, the relationship between shoulder fatigue and pain in key occupational groups and individual factors, work type, work posture and work organization was discussed, and the internal relationship was analyzed based on structural equation model.Results:Higher incidence of shoulder fatigue and pain were associated with female, lack of physical exercise, uncomfortable working posture and neck leaning forward ( P<0.05). Structural equation model analysis showed that work type, work posture and work organization were strongly correlated ( r=0.58, 0.55). Work organization and work type were strongly correlated with shoulder fatigue ( r=0.65) and moderately correlated with shoulder fatigue ( r=0.21). Shoulder fatigue was moderately associated with shoulder pain ( r=0.40). Individual factors, work type, work posture and shoulder fatigue could directly affect shoulder pain ( OR=0.07, -0.09, 0.17 and 0.40), and work type and work posture could also indirectly affect shoulder pain through shoulder fatigue ( OR=0.08, 0.03). Work organization only indirectly affected shoulder pain through shoulder fatigue ( OR=0.26) . Conclusion:The main influencing factor of shoulder pain is shoulder fatigue, followed by work posture and individual factors. Structural equation model can better reflect the complex relationship between work type, work posture and work organization and shoulder WMSDs. Improving work posture and work organization may be an effective way to control the influence of shoulder fatigue on shoulder pain.

Objective:To explore the structural equation model to explore the levels of work-related musculoskeletal disorders (WMSDs) and various risk factors in the feet and ankle of China's occupational population, providing scientific basis for for preventing WMSDs in feet and ankles.Methods:Data of 73497 national occupational epidemiological cases were selected from June 2018 to December 2023 used the Chinese version of the Electronic Questionnaire on Musculoskeletal Disorders. The adverse ergonomic factors and their source classification standard and confirmatory factor analysis were used to investigate foot and ankle WMSDs and their related risk factors (including individual factors, work organization, work posture, work type, fatigue, etc.) in key occupational groups in China, and structural equation model hypothesis, fitting, verification, and path and intermediary effect analysis were carried out. The model fit evaluation indexes included Chi-square specific degrees of freedom ( χ2/ df), gauge fit index (NFI), Tucker Lewis index (TLI), goodness of Fit index (GFI), adjusted Goodness of Fit index (AGFI) and approximate root mean square error (RMSEA) . Results:A total of 73497 occupational workers were surveyed, with local muscle fatigue and WMSDs incidence rates in the feet and ankles being 17.17% and 12.06%, respectively. The fitting index of the adjusted structural equation model basically meets the standard (GFI=1, AGFI=1, RMESA=0.042, NFI=0.716, TLI=0.663). The top three factors affecting feet and ankle WMSDs are feet and ankle muscle fatigue, work type, and work organization, with standardized path coefficients of 0.221, 0.105, and 0.095, respectively. The top two factors affecting feet and ankle muscle fatigue are work organization and work type, with standardized path coefficients of 0.548 and 0.383, respectively. Feet and ankle muscle fatigue, work type, work organization, and work posture have a direct effect on feet and ankle WMSDs, with effect values of 0.221, 0.105, 0.095, and 0.077, respectively. The organization and type of work can also have indirect effects through feet and ankle muscle fatigue, with effect values of 0.121 and 0.084, respectively.Conclusion:Feet and ankle muscle fatigue has a direct impact on WMSDs, and plays a mediating role between ankle and ankle WMSDs caused by work organization and work type. Feet and ankle muscle fatigue is an important pathway leading to feet and ankle WMSDs. It is recommended that employers and managers detect job fatigue early and take corresponding prevention and intervention measures, which can play a key role in preventing feet and ankle WMSDs.

Objective:To explore the structural relationship between WMSDs in the upper limbs and various risk factors in the occupational population in China, based on a large sample epidemiological survey and structural equation analysis, and to establish a structural equation model, so as to lay a foundation for the prevention and control of such diseases.Methods:The Chinese version of the Musculoskeletal Disorders Electronic Questionnaire was used to conduct a nationwide survey on the prevalence of WMSDs in the upper extremity. Six factors related to WMSDs in the upper extremity were extracted by the classification standard of adverse ergonomic factors and their source and confirmatory factor analysis, including work organization, work type, upper extremity work posture, individual factors, upper extremity fatigue and upper extremity WMSDs. The structural equation analysis was carried out and the structural equation model was established.Results:The incidence of WMSDs and fatigue in the upper limbs was 24.44% and 43.76%, respectively. The adjusted structural equation model fitting indicators were generally up to the standard (GFI=1.000, AGFI=1.000, RMSEA=0.043, NFI=0.808, TLI=0.784) . The four exogenous latent variables of work organization, work type, upper limb work posture and individual factors were correlated. There was a strong positive correlation between job type and upper limb work posture ( r=0.865) , a moderate positive correlation between work organization and job type and upper limb work posture ( r=0.570, 0.490) , and a weak negative correlation between individual factors and the other three exogenous latent variables. Upper limb work posture and individual factors had direct effects on upper limb WMSDs, and the effect coefficients were 0.10 and 0.06, respectively. Upper limb fatigue played a mediating role between work organization, work type, upper limb work posture and upper limb WMSDs. The effect coefficient was 0.46, and the composition ratios of indirect effects were 100.0%, 100.0%, and 38.3%, respectively. The direct path effect of upper limb work posture, individual factors and upper limb WMSDs was weaker than the mediating path through upper limb fatigue. Conclusion:When carrying out the prevention and control of upper limbWMSDs, it is necessary to comprehensively consider the pathogenesis path of upper limb muscle fatigue and upper limb WMSDs caused by work organization, work type, and upper limb work posture, so as to provide theoretical reference for improving the prevention and control level of such diseases.

Objective:To observe any effect of oscillating positive expiratory pressure training on the airway clearing ability of postoperative esophageal cancer patients after neoadjuvant chemotherapy.Methods:Forty postoperative esophageal cancer patients undergoing neoadjuvant chemotherapy were enrolled and randomized into a control group and an experimental group, each of 20. Both groups received conventional postoperative rehabilitation starting on the first postoperative day, while the experimental group additionally underwent oscillating positive expiratory pressure training (3 sets/day, 30 breaths/set) for five consecutive days. Peak cough flow was measured using a peak flow meter before and 1, 3 and 5 days after the operation. Forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), and peak expiratory flow (PEF) were also measured on the 5th day after the operation using spirometry. Any postoperative pulmonary complications were recorded.Results:On the 1st day after the operation, peak cough flow had decreased significantly in both groups compared to preoperative levels. However, it had increased significantly on days 3 and 5 in both groups, with the average increase in the experimental group significantly greater than in the control group. On day 5 the average FEV1, forced vital capacity and PEF in both groups were significantly lower than the preoperative values, while the experimental group demonstrated significantly higher average FEV1s (2.22±0.51L) and PEFs (5.09±1.26L/s) compared to the control group.Conclusions:Early postoperative oscillating positive expiratory pressure training can improve the peak cough flow and airway clearing ability of esophageal cancer patients after neoadjuvant chemotherapy, promoting the recovery of their lung function.

Objective To evaluate the medical service performance of the cardiovascular department in a tertiary hospital in Hunan Province using Diagnosis Related Groups(DRGs)and Entropy Weighted TOPSIS methods,providing suggestions for discipline construction and development.Methods Data from the front pages of hospitalization cases in the Department of Cardi-ovascular Medicine from 2018 to 2023 were collected.Both traditional indicators and DRG(Diagnosis-Related Group)indicators were utilized to analyze the department's overall performance,the structure of treated disease groups,and the comparative per-formance across different wards.Results The number of discharged cases and the Case Mix Index(CMI)in the cardiovascular medicine department of the sample hospital exhibited a fluctuating upward trend,while the number of DRG groups remained rela-tively stable,reflecting ideal professional coverage.Certain key disease groups demonstrated higher time and cost consumption in-dices,and variations in medical service performance were observed across different wards.Furthermore,in the Entropy Weighted TOPSIS comprehensive evaluation,the rankings of the four wards aligned with their actual developmental positioning within the discipline.Conclusion The DRG method and Entropy Weighted TOPSIS provide an effective framework for evaluating medical service performance in hospital disciplinary development,utilizing reasonable evaluation indicators.These methods offer valuable insights for guiding the development of key clinical specialties and enhancing the overall level of disciplinary capability.