Objective To analyze the infection status and epidemic trends of soil-borne nematode infections in Yubei, Chongqing City, in 2010,2021, and 2022. Methods The local populations from four survey sites of four towns in 2010 and five sites of five towns in 2021 and 2022 were surveyed regarding their basic information using a unified form. Fecal samples of the participants were collected and tested for soil-borne nematode infections using the modified Kato-Katz thick smear method. Results In 2010, 2 049 participants were surveyed, followed by 1 000 participants in 2021 and 2022. The overall prevalence of parasitic infections declined significantly from 3.86% to 0.20%. In 2010, soil-transmitted nematode included hookworms(3.81%) and roundworms(0.29%). In 2021, the infection rates of roundworms and hookworms were 1.70% and 0.10% respectively. Notably, only Ascaris was identified in 2022(0.20%). The≥60 age group consistently exhibited the highest infection rates across all surveys, followed by the 40-59 age group. The infection rates of males in the three surveys were 3.31%,1.92%, and 0.20% respectively, and those of females were 4.37%, 1.46%, and 0.20% respectively. There was no statistically significant difference in the infection rates between males and females. Educational attainment was inversely associated with infection; in 2010, the highest prevalence was observed among those with primary education or below, whereas in 2021, illiterate or semi-literate individuals showed the highest susceptibility. The occupational distribution of infections in 2010 indicated that retirees (8.33%), farmers(4.86%), and homemakers or unemployed individuals(3.45%)were the most affected. However, in 2021 and 2022, farmers emerged as the predominant occupational group with soil-transmitted nematode infections. Conclusions The infection rate of soil-borne nematodes showed a decreasing trend in Yubei, and the infection species changed from hookworms in 2010 to Ascaris in 2022. Farmers, the elderly, and people with low education levels should continue to be the focus of preventive and control efforts.

PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

OBJECTIVE: To investigate the clinical features, treatment and prognosis of extranodal NK/T-cell lymphoma, nasal type (ENKTL) with skin lesions as initial symptom. METHODS: The clinical data of 11 ENKTL patients with skin lesions as initial symptom were retrospectively analyzed from August 2016 to January 2023 in Wuhan First Hospital and Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. RESULTS: Among the 11 patients, there were 6 males and 5 females, with a median age of 50(32-80) years. All patients had different forms of skin lesions as initial clinical symptom, including rash, ulcerative mass, painful skin nodules, infiltrating macula, etc. Most of the skin lesions were involved in the limbs and trunk but also appeared in the lower limbs alone. Five patients had hemophagocytic lymphohistiocytosis (HLH) at initial diagnosis, and 8 patients had B symptoms. All patients were diagnosed with advanced clinical staging (Lugano staging IV), and classified as high risk (PINK-E score ≥3). Immunohistochemical examination revealed that the positive rates of CD56 and EBER were both 100%, and the median Ki-67 index was 75%(50%-80%). Plasma EBV-DNA tests were all positive (≥5×10² copies/ml). Most of the induction chemotherapy regimens were combination chemotherapy (MESA, p-Gemox, SMILE) containing pegaspargase or L-asparaginase, or combined with PD-1 monoclonal immunotherapy, or HLH regimens (HLH-04 regimen, L-DEP). The median follow-up time and overall survival (OS) time were both 4.5(0.5-27) months. During the follow-up period, all 8 patients who did not receive autologous hematopoietic stem cell transplantation (ASCT) died, most of whom died of rapid disease progression. Three patients received ASCT, one died of central nervous system recurrence after transplantation, and two survived. The OS of three patients who underwent ASCT was 21, 27, and 19 months, and PFS was 11, 20, and 13 months, respectively. The plasma EBV-DNA copy number was monitored irregularly after transplantation, and the load of EBV was consistent with the changes of the disease. CONCLUSIONS Early clinical symptoms of ENKTL patients with skin lesions as initial symptom are more atypical, and early diagnosis is particularly difficult. The disease progresses rapidly and the prognosis is poor. There is still no uniform standard for the best treatment strategy. The survival of patients can be significantly prolonged by applying ASCT as soon as possible after complete remission obtained by high-dose induction chemotherapy.
Humans ; Male ; Female ; Lymphoma, Extranodal NK-T-Cell/diagnosis* ; Middle Aged ; Adult ; Retrospective Studies ; Aged ; Prognosis ; Aged, 80 and over

Hypertrophic cardiomyopathy (HCM) is a major contributor to cardiovascular diseases (CVD), the leading cause of death globally. HCM can precipitate heart failure (HF) by causing the cardiac tissue to weaken and stretch, thereby impairing its pumping efficiency. Moreover, HCM increases the risk of atrial fibrillation, which in turn elevates the likelihood of thrombus formation and stroke. Given these significant clinical ramifications, research into the etiology and pathogenesis of HCM is intensifying at multiple levels. In this review, we discuss and synthesize the latest findings on HCM pathogenesis, drawing on key experimental studies conducted both in vitro and in vivo. We also offer our insights and perspectives on these mechanisms, while highlighting the limitations of current research. Advancing fundamental research in this area is essential for developing effective therapeutic interventions and enhancing the clinical management of HCM.
Cardiomyopathy, Hypertrophic/physiopathology* ; Humans ; Animals

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

Hypertensive nephropathy is one of the common chronic kidney diseases in China,the morbidity and mortality are increasing year by year,which seriously endangers the physical and mental health of patients.Traditional Chinese medicine believes that human is an organic whole,the five viscera and six organs are closely related in physiology and pathology,based on the theory of"holistic concept",the application of Chinese medicine in the treatment of hypertensive nephropathy can effectively improve kidney function and reduce the occurrence of adverse reactions.Therefore,based on the theory of"five viscera in one",this paper summarizes the etiology and pathogenesis of hypertensive nephropathy and the treatment of hypertensive nephropathy from the five aspects of liver,heart,spleen,lung and kidney,aiming to provide new ideas for the prevention and treatment of kidney disease by traditional Chinese medicine.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Objective To propose a low-dose CT image denoising method based on an improved Corediff model to recover the detailed features of the image and enhance the image quality.Methods An RS-Corediff model was established by modifying the key component U-Net network of the Corediff model.Firstly,the residual module was introduced in the network input stage for feature extraction;secondly,a new downsampling module was designed in the U-Net network encoder,which learned the semantic information of the feature map by convolution and maintained the learning state during the downsampling process so as to fully extract the image features;thirdly,the feature splicing processing was used to further enhance the learning effect during the upsampling process of the U-Net network decoder;finally,the convolutional kernel size was modified to adjust the sensory field during the convolutional process of the whole U-Net network structure so as to obtain rich features.The RS-Corediff model was compared with the residual encoder-decoder convolutional neural network(RED-CNN)model and the Corediff model on the public dataset AAPM 2016 in order to verify its effectiveness for low-dose CT image denoising.Results The RS-Corediff model gained advantages over the RED-CNN and Corediff models with a peak signal-to-noise ratio(PSNR)of 41.269 8,structural similarity(SSIM)of 0.953 4 and root mean square error(RMSE)of 17.568 7.Conclusion The proposed method effectively preserves the texture and details of low-dose CT images during the denoising process to improve the overall quality of the images.[Chinese Medical Equipment Journal,2025,46(5):9-13]

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Hypertensive nephropathy is one of the common chronic kidney diseases in China,the morbidity and mortality are increasing year by year,which seriously endangers the physical and mental health of patients.Traditional Chinese medicine believes that human is an organic whole,the five viscera and six organs are closely related in physiology and pathology,based on the theory of"holistic concept",the application of Chinese medicine in the treatment of hypertensive nephropathy can effectively improve kidney function and reduce the occurrence of adverse reactions.Therefore,based on the theory of"five viscera in one",this paper summarizes the etiology and pathogenesis of hypertensive nephropathy and the treatment of hypertensive nephropathy from the five aspects of liver,heart,spleen,lung and kidney,aiming to provide new ideas for the prevention and treatment of kidney disease by traditional Chinese medicine.