Objectives:To explore the relationship between carboxymethyl lysine (CML) and type 2 diabetes (T2DM) with myopenia, so as to provide some clinical reference for clinical prevention and early intervention of myopenia.Methods:A case-control study was conducted, selecting 142 T2DM patients admitted to the Endocrinology Department of the Affiliated Hospital of North China University of Science and Technology from November 2022 to November 2023. According to the diagnostic criteria of the 2019 consensus of experts on the diagnosis and treatment of sarcopenia, the patients were divided into a case group (T2DM with sarcopenia, 58 cases) and a control group (T2DM without sarcopenia, 84 cases). Collect and compare general information, serological data, and body composition data of two groups of patients. Two independent sample t-test is used for inter group comparison of metric data that conforms to normal distribution; Non parametric tests are used for inter group comparisons of non normally distributed quantitative data; The comparison of count data between groups is conducted using χ2 test. Multivariate logistic regression analysis was used to analyze the relationship between carboxymethyl lysine and type 2 diabetes with myopenia. Draw receiver operating characteristic (ROC) curves and analyze the efficacy of carboxymethyllysine in diagnosing T2DM with muscle atrophy. Results:Univariate analysis showed the BMI ((21.59±3.04) kg/m 2), FINS (4.49 (1.85,9.03) U/L), and FCP ((1.45±0.96) mg/L) levels of the patients in the case group were lower than those in the control group(27.32±3.74) kg/m 2, 6.91 (3.74, 11.99) U/L, (2.64±1.23) mg/L), while age, ((64.67±6.75) years old) of disease duration(12.16±6.69) years, and CML (5.70±2.14 μg/L) were higher than those in the control group ((62.23±7.33) years old, (8.70±8.01) years, (2.38±0.73) μg/L), and the differences were statistically significant (Statistical values were t=9.66, Z=2.86, t=6.46, t=2.02, t=2.70, t=13.17; P values were <0.001, 0.004, <0.001, 0.046, 0.008, <0.001). Multifactorial binary logistic regression analysis showed that CML ( OR(95%CI):3.242 (1.933-5.437)) and BMI ( OR(95%CI):0.636 (0.505-0.801)) were associated with T2DM combined with sarcopenia (all P<0.001). The results of the ROC curve showed that the area under the curve (AUC) of CML was 0.934, and the corresponding optimal cut-off value was 3.038 μg/L. The diagnostic efficacy of CML for the diagnosis of T2DM combined with myasthenia gravis was high, and the diagnostic results were in good agreement with the actual results. Conclusions:Carboxymethyl lysine is associated with T2DM combined with muscle atrophy. CML has a high diagnostic efficacy in diagnosing T2DM combined with muscle atrophy, and it has certain practical value in diagnosing T2DM combined with muscle atrophy.

Azvudine and nirmatrelvir/ritonavir (Paxlovid) are recommended for COVID-19 treatment in China, but their safety and efficacy in the elderly population are not fully known. In this multicenter, retrospective, cohort study, we identified 5131 elderly hospitalized COVID-19 patients from 32,864 COVID-19 patients admitted to nine hospitals in Henan Province, China, from December 5, 2022, to January 31, 2023. The primary outcome was all-cause death, and the secondary outcome was composite disease progression. Propensity score matching (PSM) was performed to control for confounding factors, including demographics, vaccination status, comorbidities, and laboratory tests. After 2:1 PSM, 1786 elderly patients receiving azvudine and 893 elderly patients receiving Paxlovid were included. Kaplan-Meier and Cox regression analyses revealed that compared with Paxlovid group, azvudine could significantly reduce the risk of all-cause death (log-rank P = 0.002; HR: 0.71, 95% CI: 0.573-0.883, P = 0.002), but there was no difference in composite disease progression (log-rank P = 0.52; HR: 1.05, 95% CI: 0.877-1.260, P = 0.588). Four sensitivity analyses verified the robustness of above results. Subgroup analysis suggested that a greater benefit of azvudine over Paxlovid was observed in elderly patients with primary malignant tumors (P for interaction = 0.005, HR: 0.32, 95% CI: 0.18-0.57) compared to patients without primary malignant tumors. Safety analysis revealed that azvudine treatment had a lower incidence of adverse events and higher lymphocyte levels than Paxlovid treatment. In conclusion, azvudine treatment is not inferior to Paxlovid treatment in terms of all-cause death, composite disease progression and adverse events in elderly hospitalized COVID-19 patients.

BACKGROUND:Neuregulin 1 has been shown to be characterized in cell proliferation,differentiation,and vascular growth.Human amniotic mesenchymal stem cells are important seed cells in the field of tissue engineering,and have been shown to be involved in tissue repair and regeneration. OBJECTIVE:To construct human amniotic mesenchymal stem cells overexpressing neuregulin 1 and investigate their proliferation and migration abilities,as well as their effects on wound healing. METHODS:(1)Human amniotic mesenchymal stem cells were in vitro isolated and cultured and identified.(2)A lentivirus overexpressing neuregulin 1 was constructed.Human amniotic mesenchymal stem cells were divided into empty group,neuregulin 1 group,and control group,and transfected with empty lentivirus and lentivirus overexpressing neuregulin 1,or not transfected,respectively.(3)Edu assay was used to detect the proliferation ability of the cells of each group,and Transwell assay was used to detect the migration ability of the cells.(4)The C57 BL/6 mouse trauma models were constructed and randomly divided into control group,empty group,neuregulin 1 group,with 8 mice in each group.Human amniotic mesenchymal stem cells transfected with empty lentivirus or lentivirus overexpressing neuregulin-1 were uniformly injected with 1 mL at multiple local wound sites.The control group was injected with an equal amount of saline.(5)The healing of the trauma was observed at 1,7,and 14 days after model establishment.Histological changes of the healing of the trauma were observed by hematoxylin-eosin staining.The expression of CD31 on the trauma was observed by immunohistochemistry. RESULTS AND CONCLUSION:(1)Human amniotic mesenchymal stem cells overexpressing neuregulin-1 were successfully constructed.The mRNA and protein expression of intracellular neuregulin 1 was significantly up-regulated compared with the empty group(P<0.05).(2)The overexpression of neuregulin 1 promoted the migratory ability(P<0.01)and proliferative ability of human amniotic mesenchymal stem cells(P<0.05).(3)Human amniotic mesenchymal stem cells overexpressing neuregulin 1 promoted wound healing in mice(P<0.05)and wound angiogenesis(P<0.05).The results showed that overexpression of neuregulin 1 resulted in an increase in the proliferative and migratory capacities of human amniotic mesenchymal stem cells,significantly promoting wound healing and angiogenesis.

Objectives:To explore the relationship between carboxymethyl lysine (CML) and type 2 diabetes (T2DM) with myopenia, so as to provide some clinical reference for clinical prevention and early intervention of myopenia.Methods:A case-control study was conducted, selecting 142 T2DM patients admitted to the Endocrinology Department of the Affiliated Hospital of North China University of Science and Technology from November 2022 to November 2023. According to the diagnostic criteria of the 2019 consensus of experts on the diagnosis and treatment of sarcopenia, the patients were divided into a case group (T2DM with sarcopenia, 58 cases) and a control group (T2DM without sarcopenia, 84 cases). Collect and compare general information, serological data, and body composition data of two groups of patients. Two independent sample t-test is used for inter group comparison of metric data that conforms to normal distribution; Non parametric tests are used for inter group comparisons of non normally distributed quantitative data; The comparison of count data between groups is conducted using χ2 test. Multivariate logistic regression analysis was used to analyze the relationship between carboxymethyl lysine and type 2 diabetes with myopenia. Draw receiver operating characteristic (ROC) curves and analyze the efficacy of carboxymethyllysine in diagnosing T2DM with muscle atrophy. Results:Univariate analysis showed the BMI ((21.59±3.04) kg/m 2), FINS (4.49 (1.85,9.03) U/L), and FCP ((1.45±0.96) mg/L) levels of the patients in the case group were lower than those in the control group(27.32±3.74) kg/m 2, 6.91 (3.74, 11.99) U/L, (2.64±1.23) mg/L), while age, ((64.67±6.75) years old) of disease duration(12.16±6.69) years, and CML (5.70±2.14 μg/L) were higher than those in the control group ((62.23±7.33) years old, (8.70±8.01) years, (2.38±0.73) μg/L), and the differences were statistically significant (Statistical values were t=9.66, Z=2.86, t=6.46, t=2.02, t=2.70, t=13.17; P values were <0.001, 0.004, <0.001, 0.046, 0.008, <0.001). Multifactorial binary logistic regression analysis showed that CML ( OR(95%CI):3.242 (1.933-5.437)) and BMI ( OR(95%CI):0.636 (0.505-0.801)) were associated with T2DM combined with sarcopenia (all P<0.001). The results of the ROC curve showed that the area under the curve (AUC) of CML was 0.934, and the corresponding optimal cut-off value was 3.038 μg/L. The diagnostic efficacy of CML for the diagnosis of T2DM combined with myasthenia gravis was high, and the diagnostic results were in good agreement with the actual results. Conclusions:Carboxymethyl lysine is associated with T2DM combined with muscle atrophy. CML has a high diagnostic efficacy in diagnosing T2DM combined with muscle atrophy, and it has certain practical value in diagnosing T2DM combined with muscle atrophy.

Objective:To predict suicidal behaviors in patients with bipolar disorder by constructing a machine learning model based on random forest and backpropagation neural network, and provide clinical decision support for the prevention and intervention of patient suicide.Methods:From January 2020 to August 2023, 1 005 patients with bipolar disorder were enrolled.The general clinical data and social dysfunction, anxiety, depression scores of all patients were collected.The random forest algorithm was applied for feature selection, and backpropagation neural network model was constructed for evaluating the model's fitting effect and predictive performance.Results:There were statistically significant differences in sociodemographic characteristics and physiological and psychological factors among the suicide attempt group ( n=293), suicide ideation group ( n=332) and non-suicidal group ( n=380) of patients with bipolar disorder( P<0.05).Using the random forest algorithm identified six main predictive variables: educational level, age, free triiodothyronine (FT3), cognitive impairment, hopelessness and psychogenic anxiety.The developed backpropagation neural network model achieved a precision rate of 79.3%, a recall rate of 79.6%, an F1 score of 79.4%, and an AUC of 0.89 on the test set, indicating that the model predictive performance has high accuracy and discriminative power. Conclusion:This study developed a machine learning model for predicting suicide in patients with bipolar disorder, which possesses high accuracy and discriminative ability, providing a decision-making basis for the prevention and intervention of suicidal behaviors in patients with bipolar disorder.

Objective:To predict suicidal behaviors in patients with bipolar disorder by constructing a machine learning model based on random forest and backpropagation neural network, and provide clinical decision support for the prevention and intervention of patient suicide.Methods:From January 2020 to August 2023, 1 005 patients with bipolar disorder were enrolled.The general clinical data and social dysfunction, anxiety, depression scores of all patients were collected.The random forest algorithm was applied for feature selection, and backpropagation neural network model was constructed for evaluating the model's fitting effect and predictive performance.Results:There were statistically significant differences in sociodemographic characteristics and physiological and psychological factors among the suicide attempt group ( n=293), suicide ideation group ( n=332) and non-suicidal group ( n=380) of patients with bipolar disorder( P<0.05).Using the random forest algorithm identified six main predictive variables: educational level, age, free triiodothyronine (FT3), cognitive impairment, hopelessness and psychogenic anxiety.The developed backpropagation neural network model achieved a precision rate of 79.3%, a recall rate of 79.6%, an F1 score of 79.4%, and an AUC of 0.89 on the test set, indicating that the model predictive performance has high accuracy and discriminative power. Conclusion:This study developed a machine learning model for predicting suicide in patients with bipolar disorder, which possesses high accuracy and discriminative ability, providing a decision-making basis for the prevention and intervention of suicidal behaviors in patients with bipolar disorder.

Objective:To investigate the changes of thyroid hormones and the flow velocity of superior thyroid artery in patients with Graves' disease and Hashimoto's thyrotoxicosis before and after treatment with methimazole.Methods:A case-control study was conducted to select 45 cases of Graves' disease and 45 cases of Hashimoto's thyroiditis from October 2021 to December 2022 in the Department of Endocrinology, North China University of Science and Technology Affiliated Hospital. The changes of thyroid hormone and blood flow velocity of superior thyroid artery in patients with Graves' disease and Hashimoto's thyroiditis before and after treatment with methimazole were analyzed. Measurement data satisfying normal distribution were expressed by xˉ±s, and the mean between two groups was compared by t test. Measurement data not satisfying normal distribution were expressed by M( Q1, Q3), and the median between two groups was compared by Wilcoxon rank sum test. χ 2 test was used to compare the constituent ratio of enumeration data among groups. Results:There was no significant difference in thyroid stimulating hormone (TSH) between the two groups before treatment, and there was no significant difference in TSH between the two groups after 1 month and 3 months of treatment (all P>0.05). The levels of free triiodothyronine (FT3) were (24.09±9.29) pmol/L and (17.41±9.36) pmol/L in Graves' disease group and Hashimoto's thyroiditis group respectively before treatment. FT4 were (60.23±20.82) and (43.47±21.71) pmol/L, respectively, and the peak stolie vloiy (PSV) were (69.53±5.70) and (52.65±4.64) cm/s, respectively in Graves' disease group and Hashimoto's thyroiditis group respectively before treatment. There were significant differences between the two groups ( t values wrere 3.39 and 3.74, Z=13.83, all P<0.001). The difference of FT3 between one month after treatment and before treatment was (-6.36±5.32) and (-12.64±9.08) pmol/L ( t=4.02, P<0.001) and the difference in FT3 between 3 months of treatment and before treatment was (-10.14±9.50) and (-17.80±11.17) pmol/L, respectively ( t=3.51, P<0.001) between the Graves disease group and the Hashimoto's thyroiditis group. The difference in FT4 between the Graves disease group and the Hashimoto's thyroiditis group after 1 month of treatment and before treatment was (-28.47±10.09) and (-20.57±14.48) pmol/L ( t=7.01, P<0.001), and the difference of FT4 was (-47.06±20.57) and (-30.17±20.54) pmol/L ( t=3.91, P<0.001) between the Graves disease group and the Hashimoto toxin group. The difference between one month after treatment and before treatment was (-13.10(-34.10,-2.60)) and (-10.50(-27.5,-0.20)) cm/s ( Z=2.63, P=0.009), respectively. The difference between 3 months and before treatment was (-31.40(-53.20,-12.70)) and (-19.90(-46.00,-4.70)cm/s ( Z=4.40, P<0.001)) between the Graves disease group and the Hashimoto's thyroiditis group, and the difference was statistically significant. Conclusion:Thyroid hormone levels were decreased after treatment with methimazole in patients with diffuse toxic goiter and Hashimoto toxemia, but the difference was not statistically significant. The PSV level of superior thyroid artery in patients with diffuse toxic goiter was significantly lower than that in patients with Hashimoto's thyrotoxicosis.

Objective To explore the professionalization model of nursing management team in an international medical center in a provincial public tertiary hospital.Methods Through literature research and Delphi method,a three-person nursing management team was established respectively in three nursing units:outpatient,first-ward,and second-ward of the center,and then trained professionally to define management boundaries and responsibilities.The training effect was verified by applying the professionalization management in the international medical center.The three nursing teams(nine nurses totally)were compared in terms of leadership,patient satisfaction,and nursing discipline construction before and after the training.Results Following the training,the three teams all exhibited a significant improvement in leadership as well as its dimensions(P＜0.05),and pa-tient satisfaction(P＜0.05).Additionally,care quality,scientific research capacity,and innovation ability were all elevated across the three groups.Conclusion The establishment of a nursing management team and performance of professional training can effectively promote the concept of professionalization management,improve the leadership of nurses,cultivate talent eche-lons,drive the overall development of disciplines and teams,and expand the connotation of nursing culture.For all these bene-fits,this model is suitable for promotion and application among clinical departments.

Idiopathic pulmonary fibrosis (IPF) is a terminal disease of the lung. Its pathogenesis mechanism and pathogenesis evolution are very complex, which is closely related to epithelial-mesenchymal transformation (EMT). Under the guidance of the theory of "deficient-qi induced stagnation", this article elaborated on the relationship between IPF, "deficient-qi induced stagnation", and EMT from the perspective of TCM and Western medicine. It is believed that "deficient-qi induced stagnation" is the macroscopic pathogenesis of IPF, and EMT is the microscopic mechanism of IPF. The micro-mechanism was to inhibit EMT as the treatment target to prevent epithelial cell injury and apoptosis, thus reducing the release of inflammatory factors, pro-fibrosis factors and other factors that damage lung tissue and the transformation of damaged epithelial cells into fibroblasts and produce a large number of ECM deposition; the occurrence and development process of IPF was summarized in the macro pathogenesis. It was highly condensed that IPF was based on "deficiency-qi", "stagnation" as the standard, and the basic pathogenesis characteristics of "stagnation" due to deficiency, as well as the pathogenesis development characteristics of the vicious cycle of "deficiency leads to stagnation, and from stagnation to deficiency". Based on the theory of "deficient-qi induced stagnation", it should be used to tonify deficiency and clear stagnation; tonifying deficiency includes replenishing lung qi, benefiting qi and nourishing yin, and mutual generation between metal and water; clearing stagnation includes circulating qi and blood, drying the wetness and eliminating phlegm, and promoting blood circulation for removing obstruction in collaterals, etc. In clinical application, attention should be paid to the fact that tonifying deficiency and clearing stagnation should be used in parallel.

Objectives: Telemedicine is firmly established in the healthcare landscape of many countries. Acute respiratory infections are the most common reason for telemedicine consultations. A throat examination is important for diagnosing bacterial pharyngitis, but this is challenging for doctors during a telemedicine consultation. A solution could be for patients to upload images of their throat to a web application. This study aimed to develop a deep learning model for the automated diagnosis of exudative pharyngitis. Thereafter, the model will be deployed online. Methods: We used 343 throat images (139 with exudative pharyngitis and 204 without pharyngitis) in the study. ImageDataGenerator was used to augment the training data. The convolutional neural network models of MobileNetV3, ResNet50, and EfficientNetB0 were implemented to train the dataset, with hyperparameter tuning. Results: All three models were trained successfully; with successive epochs, the loss and training loss decreased, and accuracy and training accuracy increased. The EfficientNetB0 model achieved the highest accuracy (95.5%), compared to MobileNetV3 (82.1%) and ResNet50 (88.1%). The EfficientNetB0 model also achieved high precision (1.00), recall (0.89) and F1-score (0.94). Conclusions We trained a deep learning model based on EfficientNetB0 that can diagnose exudative pharyngitis. Our model was able to achieve the highest accuracy, at 95.5%, out of all previous studies that used machine learning for the diagnosis of exudative pharyngitis. We have deployed the model on a web application that can be used to augment the doctor’s diagnosis of exudative pharyngitis.