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.

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.

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.

Rheumatoid arthritis(RA)is an autoimmune disease with the basic pathological manifestation of synovial inflammation.Symmetric poly-articular pain and swelling are the main symptoms in clinical practice,and even extra-articular manifestations and comorbidities such as interstitial fibrosis and coronary artery disease are triggered,which seriously affect the quality of life of patients.Traditional Chinese medicine(TCM)has achieved good clinical efficacy in the prevention and treatment of RA with the advantages of multi-pathway,multi-target,multi-component,and less toxic side effects,and plays an important role in the treatment of RA.Recently,many studies have demonstrated that Chinese medicine monomers and Chinese herbal compound can control inflammation,reduce angiogenesis,induce apoptosis of synovial fibroblasts,and inhibit their proliferation,invasion and migration by regulating the PI3K/Akt signaling pathway,so as to play a key role in the treatment of RA.For this reason,the article summarizes current knowledge regarding the PI3K/Akt signaling pathway and its role in RA,as well as summarizes the current research progress of TCM in the treatment of RA by regulating the PI3K/Akt signaling pathway.The aim of this review is to provide theoretical bases for the prevention and treatment of RA and the development of new drugs.

Ankylosing spondylitis(AS)is a chronic inflammatory autoimmune disease characterized by inflammatory back pain.Its pathological features mainly include inflammation,bone destruction,and pathologic new bone formation.The etiology of AS is complex,and it may be related to genetics,infections,the environment,and intestinal flora.Its pathogenesis has not yet been clarified.In recent years,osteoimmunology,as a new theme in the study of inflammatory arthritis,plays an important role in the pathogenesis and development of AS,which was embodied in the inflammatory response and imbalance of bone metabolism.Traditional Chinese medicine(TCM)has the characteristics of multiple pathways,multiple components,multiple targets and multiple levels.TCM can improve the inflammatory response and bone metabolism imbalance of AS by regulating the osteoblasts of the skeletal system and the related factors of the immune system,thus to prevent and control AS.For this reason,the paper summarizes the role of bone immunology in the pathogenesis of AS,and reviews the current status of research on the intervention of TCM in bone immunology for the treatment of AS,with a view to providing certain references for the future clinical application of TCM in the prevention and treatment of AS.

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.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.