Objective To analyze the status and its influencing factors of high-frequency hearing loss (HFHL) among occupational noise-exposed workers. Methods A total of 6 764 noise-exposed workers who participated in occupational medical examinations during their employment were selected as the study subjects using the judgmental sampling method. Their pure-tone audiometry results were analyzed. Results The detection rate of HFHL among the study subjects was 10.3%. Binary logistic regression analysis result revealed that males had a higher risk of HFHL than females (P<0.05). The HFHL risk of workers increased with age (all P<0.01). Workers with longer noise exposure durations had a higher risk of HFHL (all P<0.01). Smokers had a higher detection rate of HFHL than non-smokers (P<0.01). Workers in the mining industry, electricity/heat/gas and water production and supply industry, and other industries had a higher HFHL detection rate compared with manufacturing workers (all P<0.05). Medium-sized enterprise workers had a lower HFHL detection rate compared with micro-sized enterprise workers (P<0.05), while workers in private enterprises had a higher HFHL detection rate compared with those in state-owned enterprises (P<0.05). Workers who exposed to noise combined with dust, lead, high temperature, or multiple factors had a higher HFHL risk than those only exposed to noise (all P<0.05). Conclusion Gender, age, noise exposure duration, smoking, industry, and exposure to noise combined with other occupational hazard factors are all influencing factors for HFHL among noise-exposed workers. Targeted occupational health education on noise hazard prevention and occupational medical surveillance should be strengthened for key populations in priority industries, including male workers, older employees, individuals with prolonged noise exposure, smokers, and those concurrently exposed to noise and one of the following: dust, lead, high temperatures, or multiple occupational factors.

Objective To observe CT manifestations of Fitz-Hugh-Curtis syndrome(FHCS).Methods Data of 23 patients with FHCS were retrospectively analyzed,and non-enhanced and enhanced abdominal and pelvic CT manifestations were observed.Results All 23 cases were found with pelvic inflammation,peritonitis,perihepatic inflammation,as well as abdominal and pelvic adhesion.The main manifestations of pelvic inflammation included pelvic effusion(23/23,100％),inflammatory changes of uterus and accessories(17/23,73.91％),and the latter presented as tubal thickening(8/17,47.06％)or tubal cystic dilatation and effusion(9/17,52.94％),with ovarian enlargement(8/9,88.89％)or nodules on uterine surface(1/9,11.11％).The main CT manifestations of peritonitis were peritoneal thickening(23/23,100％)and peritoneal nodules(15/23,65.22％),of perihepatic inflammation were mainly liver capsule enhancement(23/23,100％),subcapsular transient perfusion abnormality(16/23,69.57％),perihepatic effusion(20/23,86.96％)and perihepatic"violin-string sign"(16/23,69.57％).No inflammation in the bare area of liver was noticed.Among 23 cases,3 cases(3/23,13.04％)complicated with mechanical ileus,19 cases(19/23,82.61％)were accompanied by mesenteric or retroperitoneal lymph nodes enlargement with uniform or circular enhancement.Conclusion The main CT manifestations of FHCS included pelvic inflammation,peritonitis,perihepatic inflammation,as well as abdominal and pelvic adhesion,having certain characteristics.

Objective To observe CT manifestations of Fitz-Hugh-Curtis syndrome(FHCS).Methods Data of 23 patients with FHCS were retrospectively analyzed,and non-enhanced and enhanced abdominal and pelvic CT manifestations were observed.Results All 23 cases were found with pelvic inflammation,peritonitis,perihepatic inflammation,as well as abdominal and pelvic adhesion.The main manifestations of pelvic inflammation included pelvic effusion(23/23,100％),inflammatory changes of uterus and accessories(17/23,73.91％),and the latter presented as tubal thickening(8/17,47.06％)or tubal cystic dilatation and effusion(9/17,52.94％),with ovarian enlargement(8/9,88.89％)or nodules on uterine surface(1/9,11.11％).The main CT manifestations of peritonitis were peritoneal thickening(23/23,100％)and peritoneal nodules(15/23,65.22％),of perihepatic inflammation were mainly liver capsule enhancement(23/23,100％),subcapsular transient perfusion abnormality(16/23,69.57％),perihepatic effusion(20/23,86.96％)and perihepatic"violin-string sign"(16/23,69.57％).No inflammation in the bare area of liver was noticed.Among 23 cases,3 cases(3/23,13.04％)complicated with mechanical ileus,19 cases(19/23,82.61％)were accompanied by mesenteric or retroperitoneal lymph nodes enlargement with uniform or circular enhancement.Conclusion The main CT manifestations of FHCS included pelvic inflammation,peritonitis,perihepatic inflammation,as well as abdominal and pelvic adhesion,having certain characteristics.

Objectives:To develop a novel prediction model for mitral valve repair failure based on machine learning algorithms.Methods:Clinical and echocardiographic data were analyzed on patients,who underwent mitral valve repair in Fuwai Hospital from 2009 January 1st to 2022 December 31st.End points included immediate mitral valve repair failure (mitral replacement secondary to mitral repair failure) and recurrence regurgitation (moderate or severe mitral regurgitation before discharge).Risk factors of mitral valve repair failure were analyzed by XGBoost and shapley additive explanation (SHAP),and a machine learning model was established based on mixture of experts (MoE) as a risk prediction model and compared with conventional mitral valve repair complexity scores.Results:A total of 2314 patients were included in this study.Mitral repair was unsuccessful in 4.2％ (98 of 2314) of patients.Patient factors such as tricuspid regurgitation pressure gradient,A3 and A3P3 lesions,left ventricular end-systolic volume,and left atrium anterior and posterior diameter are associated with mitral valve repair failure;in addition,surgeon factors,such as cumulative repair failure rate,cumulative repair volume,and surgeon seniority,are also risk factors for mitral valve repair failure.The MoE model has an AUC value of 0.79,and the prediction performance is significantly better than traditional complexity scores.Conclusions:The MoE based machine learning model can predict the risk of mitral valve repair failure well.This evaluation system can effectively assist surgeons in assessing the risk of mitral valve repair failure and in selecting suitable treatment options for patients.

Objective:To investigate impacts of usnic acid(UA)on malignant behavior of gastric cancer cells by regulating the chemokine(C-C motif)ligand 2(CCL2)-CCL2 receptor(CCR2)signal axis.Methods:SGC-7901 cells,a well growing human gastric cancer cell line,were treated with different concentrations of UA,which were grouped into low concentration(UA-L)group(62.5 μmol/L UA),medium concentration(UA-M)group(125 μmol/L UA)and high concentration(UA-H)group(250 μmol/L UA);meantime,the cells were transfected with CCL2 overexpression vector(pc DNA3.1 CCL2),empty vector(pc DNA3.1),silenced CCL2(si CCL2)and negative control(si control),and SGC-7901 cells were treated with 250 μmol/L UA,labeled as UA-H+pc DNA3.1 CCL2 group,UA-H+pc DNA3.1 group,UA-H+si control group and UA-H+si CCL2 group,another untreated SGC-7901 cells were taken as the control group.Flow cytometry,MTT and qRT-PCR were applied to detect cell apoptosis,proliferation,and expres-sion levels of CCL2 and CCR2 mRNA;Western blot was applied to detect expression levels of PD-L1,apoptotic protein(Bax),proli-ferative protein(CyclinD1,CCL2,CCR2)and immune escape related protein(B7H1);after co-culturing with CD8+T cells isolated and cultured in vitro,ELISA was applied to detect levels of IL-4,IFN-γ and IL-10 in the supernatant.Gastric cancer cells in each group were co-cultured with activated peripheral blood mononuclear cell(PBMC)1∶1 for 72 hours,and the sensitivity of gastric can-cer cells in each group to T-cell-mediated killing was compared.Results:Compared with control group,cell proliferation rate,IL-10 level,CyclinD1,PD-L1,CCL2,CCR2 and B7H1 protein and mRNA expressions,cell counts after co-culturing with activated PBMC 1∶1 for 72 hours in UA-L group,UA-M group and UA-H group were obviously reduced,while apoptosis rate,IL-4 and IFN-γ levels,Bax protein expression were obviously increased(P<0.05);compared with UA-H+pc DNA3.1 group,cell proliferation rate,IL-10 level,CyclinD1,PD-L1,CCL2,CCR2 protein and mRNA expressions,cell counts after co-culturing with activated PBMC 1∶1 for 72 hours in UA-H+pc DNA3.1 CCL2 group were obviously increased,while apoptosis rate,IL-4 and IFN-γ levels,and Bax protein ex-pression were obviously reduced(P<0.05);compared with UA-H+si control group,cell proliferation rate,IL-10 level,CyclinD1,PD-L1,CCL2,CCR2 and B7H1 protein and mRNA expressions,cell counts after co-culturing with activated PBMC 1∶1 for 72 hours in UA-H+si CCL2 group were obviously reduced,while apoptosis rate,IL-4 and IFN-γ levels and Bax protein expression were obviously increased(P<0.05).Conclusion:UA can inhibit gastric cancer cells proliferation,immune escape,and induce apoptosis,which may be related to the inhibition of the CCL2-CCR2 signaling axis.

ObjectiveTo explore the application effect of Jianpi Huoxue prescription combined with acupuncture in patients with chronic atrophic gastritis （CAG） of gastric blood stasis type. MethodA total of 86 patients with CAG admitted to Wuhan First Hospital from November 2021 to March 2023 were selected and randomly divided into two groups. The control group was treated with conventional Western medicine， while the observation group was treated with Jianpi Huoxue prescription combined with acupuncture. The clinical efficacy， traditional Chinese medicine （TCM） syndrome score， pathological score， negative conversion rate of Helicobacter pylori （Hp）， inflammatory indicators ［neutrophils/lymphocytes （NLR） and interleukin （IL）-1β］， changes in levels of gastric protease （PG） Ⅰ， PG Ⅰ/PG Ⅱ， and gastrin-17 （G-17）， and drug safety during treatment were observed after treatment in both groups. ResultAfter treatment， the total effective rate of the observation group ［95.35% （41/43）］ was significantly better than that of the control group ［79.07% （34/43）］， and the difference was statistically significant （χ²=5.108， P<0.05）. After treatment， the scores of the primary and secondary TCM syndromes in the observation group and the control group were significantly decreased （P<0.05）. After treatment， the scores of primary and secondary TCM syndromes in the observation group were significantly lower than those in the control group （P<0.05）. After treatment， the pathological scores of gastric mucosa atrophy， activity， chronic inflammation， intestinal metaplasia， and dysplasia were significantly lower in the observation group and control group （P<0.05）. After treatment， the pathological scores of gastric mucosa atrophy， activity， chronic inflammation， intestinal metaplasia， and dysplasia in the observation group were significantly lower than those in the control group （P<0.05）. After treatment， the Hp conversion rate in the observation group was significantly increased compared with the control group （P<0.05）. After treatment， the levels of inflammatory indicators NLR and IL-1β in the observation group and control group were significantly lower （P<0.05）， and the levels of inflammatory indicators NLR and IL-1β in the observation group were significantly lower than those in the control group （P<0.05）. After treatment， the levels of PGI and PGⅠ/PGⅡ in the observation group and control group were significantly higher （P<0.05）， and the levels of PGI and PGⅠ/PGⅡ in the observation group were significantly higher than those in the control group （P<0.05）. After treatment， the G-17 level of the observation group and the control group was different at different time points （P<0.05）， and the G-17 level of the observation group was higher at different time points than that of the control group （P<0.05）. The G-17 level of the observation group had an increasing trend compared with the control group （P<0.05）. There was no significant difference in the risk of adverse reactions between the two groups. ConclusionThe combination of Jianpi Huoxue prescription and acupuncture can effectively alleviate symptoms， increase Hp negative conversion rate， inhibit inflammation， and regulate PG and G-17 levels in CAG patients， thus controlling or even reversing gastric mucosal atrophy and reducing the probability of its progression to gastric cancer.

Objective: We used polysomnography (PSG) monitoring and neuropsychological scales to explore the characteristics of coronavirus disease-2019 (COVID-19) patients diagnosed with post-traumatic stress disorder (PTSD) in Wuhan, two years after the onset of the COVID-19 pandemic. Methods: A total of 42 patients in the Sleep Medicine Center were diagnosed with insomnia between December 2021 and May 2022; they were divided into the PTSD group (patients with PTSD diagnosed with insomnia after COVID-19 infection) and the non-PTSD group (patients with insomnia without PTSD). A healthy control group was simultaneously included. Results: The PTSD group was more significant than the non-PTSD group in partial manifestations of sleep disorders, neuropsychological clinical symptoms, and partial PSG data. Patients with different COVID-19 subtypes showed significant differences in the course of disease, sleep disorders, neuropsychological clinical symptoms, relevant scale scores, and PSG data analysis. Conclusion The emotional anxiety and depression of COVID-19 patients diagnosed with PTSD two years after the COVID-19 pandemic in Wuhan are more significant, and will not be self-alleviated with the passage of time. It is necessary to continue to pay attention to the PTSD symptoms and sleep psychology of COVID-19 infected patients, and take appropriate measures. Patients with severe and critical COVID-19 have more severe sleep and mental disorders, and there is a significant correlation between the duration of the disease and the severity of mental and mental disorders and sleep disorders after recovery.

Objectives:To develop a novel prediction model for mitral valve repair failure based on machine learning algorithms.Methods:Clinical and echocardiographic data were analyzed on patients,who underwent mitral valve repair in Fuwai Hospital from 2009 January 1st to 2022 December 31st.End points included immediate mitral valve repair failure (mitral replacement secondary to mitral repair failure) and recurrence regurgitation (moderate or severe mitral regurgitation before discharge).Risk factors of mitral valve repair failure were analyzed by XGBoost and shapley additive explanation (SHAP),and a machine learning model was established based on mixture of experts (MoE) as a risk prediction model and compared with conventional mitral valve repair complexity scores.Results:A total of 2314 patients were included in this study.Mitral repair was unsuccessful in 4.2％ (98 of 2314) of patients.Patient factors such as tricuspid regurgitation pressure gradient,A3 and A3P3 lesions,left ventricular end-systolic volume,and left atrium anterior and posterior diameter are associated with mitral valve repair failure;in addition,surgeon factors,such as cumulative repair failure rate,cumulative repair volume,and surgeon seniority,are also risk factors for mitral valve repair failure.The MoE model has an AUC value of 0.79,and the prediction performance is significantly better than traditional complexity scores.Conclusions:The MoE based machine learning model can predict the risk of mitral valve repair failure well.This evaluation system can effectively assist surgeons in assessing the risk of mitral valve repair failure and in selecting suitable treatment options for patients.

Objective:To investigate the predictive value of diffusion tensor imaging (DTI) parameters in upper extremity motor function recovery after surgery in patients with acute cervical spinal cord injury (CSCI).Methods:Twenty-three patients with acute CSCI who received postoperative systemic rehabilitation therapy in Department of Neurosurgery, 900 th Hospital of Joint Logistics Team of People's Liberation Army from May 2019 to July 2021 were selected as an experimental group, and 22 healthy subjects (healthy control group) matched with age and gender were selected from Physical Examination Center of the same hospital at the same period. Routine MRI sequence and DTI scan of the cervical spinal cord, scale of American Association for Spinal Cord Injury (ASIA) and modified Barthe index (mBI) were performed in patients of the experimental group 1 d and 3 months after surgery. Routine MRI sequence and DTI scan of the cervical spinal cord were performed in healthy subjects after enrollment. The DTI parameters in different regions between the two groups were compared, and the differences in DTI parameters, ASIA scores and mBI in patients of the experimental group before and after surgery were compared. Correlations of preoperative DTI parameters with preoperative upper extremity motor ASIA scores and upper extremity motor recovery rate 3 months after surgery were analyzed by Pearson correlation analysis. Receiver operating characteristic (ROC) curve was used to analyze the predictive efficacy of preoperative fractional anisotropy (FA) in upper extremity motor function recovery in CSCI patients 3 months after surgery. Results:As compared with the healthy control group, the experimental group had significantly lower preoperative FA in the injury area and distal injury area, and statistically higher preoperative apparent diffusion coefficient (ADC, P<0.05). In patients of the experimental group, preoperative FA in the injury area was significantly lower and ADC in the injury area was significantly higher as compared with those in the distal injury area ( P<0.05); patients of the experimental group had significantly higher FA in these two regions, upper extremity motor ASIA scores and mBI, and significantly lower ADC 3 months after surgery as compared with those 1 d before surgery ( P<0.05). The preoperative FA in the injury area and distal injury area in CSCI patients were positively correlated with preoperative upper extremity motor ASIA scores and upper extremity motor recovery rate 3 months after surgery ( P<0.05). ROC curve results showed that the area under the curve (AUC) of preoperative FA in injury area in predicting upper extremity motor function recovery 3 months after surgery was 0.912 ( 95%CI: 0.783-1.000, P<0.001); that of preoperative FA in the distal injury area was 0.842 ( 95%CI: 0.682-1.000, P<0.001). Conclusion:DTI parameters FA and ADC are sensitive indicators for detecting CSCI; preoperative FA in the injury area and distal injury area can be used to predict the upper extremity motor function recovery, but the efficacy of the former is superior to that of the later.

Surface electromyography (sEMG) is a weak signal which is non-stationary and non-periodic. The sEMG classification methods based on time domain and frequency domain features have low recognition rate and poor stability. Based on the modeling and analysis of sEMG energy kernel, this paper proposes a new method to recognize human gestures utilizing convolutional neural network (CNN) and phase portrait of sEMG energy kernel. Firstly, the matrix counting method is used to process the sEMG energy kernel phase portrait into a grayscale image. Secondly, the grayscale image is preprocessed by moving average method. Finally, CNN is used to recognize sEMG of gestures. Experiments on gesture sEMG signal data set show that the effectiveness of the recognition framework and the recognition method of CNN combined with the energy kernel phase portrait have obvious advantages in recognition accuracy and computational efficiency over the area extraction methods. The algorithm in this paper provides a new feasible method for sEMG signal modeling analysis and real-time identification.
Algorithms ; Electromyography ; Gestures ; Humans ; Neural Networks, Computer ; Signal Processing, Computer-Assisted