BACKGROUND:In recent years,numerous studies have shown that autophagy and mitophagy play an important role in the regulation of bone metabolism.Under non-physiological conditions,mitophagy breaks the balance of bone metabolism and triggers metabolism disorders,which affect osteoblasts,osteoclasts,osteocytes,chondrocytes,bone marrow mesenchymal stem cells,etc. OBJECTIVE:To summarize the mechanism of mitophagy in regulating bone metabolic diseases and its application in clinical treatment. METHODS:PubMed,Web of Science,CNKI,WanFang and VIP databases were searched by computer using the keywords of"mitophagy,bone metabolism,osteoblasts,osteoclasts,osteocytes,chondrocytes,bone marrow mesenchymal stem cells"in English and Chinese.The search time was from 2008 to 2023.According to the inclusion criteria,90 articles were finally included for review and analysis. RESULTS AND CONCLUSION:Mitophagy promotes the generation of osteoblasts through SIRT1,PINK1/Parkin,FOXO3 and PI3K signaling pathways,while inhibiting osteoclast function through PINK1/Parkin and SIRT1 signaling pathways.Mitophagy leads to bone loss by increasing calcium phosphate particles and tissue protein kinase K in bone tissue.Mitophagy improves the function of chondrocytes through PINK1/Parkin,PI3K/AKT/mTOR and AMPK signaling pathways.Modulation of mitophagy shows great potential in the treatment of bone diseases,but there are still some issues to be further explored,such as different stages of drug-activated mitophagy,and the regulatory mechanisms of different signaling pathways.

Purpose To analyze the value of a deep learning(DL)radiomics model based on dynamic contrast-enhanced MRI images in predicting the expression of Ki-67 status in breast cancer.Materials and Methods A retrospective analysis of 152 breast cancer patients confirmed by pathological results at Guangdong Women and Children Hospital,MRI images and clinical pathological data were reviewed,and based on postoperative immunohistochemistry results,the images of the high and low expression groups of Ki-67 were randomly sampled in a ratio of 8∶2 to form a training set of 122 cases and a validation set of 30 cases.Single-factor and multi-factor Logistic regression analyses of clinical data were performed to select independent predictors of breast cancer expressing Ki-67 status.The ResNet-18 model was used as the basic model for DL feature extraction.Hand-crafted radiomic features and DL features were extracted.Eight machine learning models were constructed based on clinical features,hand-crafted radiomic features,DL features,and their combinations.The area under the receiver operating characteristic curve was used to evaluate the predictive performance of the models,and the best model was determined as the output model.Results The progesterone receptor status(OR=0.764,P=0.040)and human epidermal growth factor receptor-2 status(OR=1.187,P=0.046)were independent clinical predictors of breast cancer expressing Ki-67 status.The combined feature models demonstrated superior performance over the individual feature models,and the support vector machine algorithm had the highest prediction performance in the validation set,with an area under the curve of 0.847.Conclusion The DL radiomics model based on dynamic contrast-enhanced MRI images can effectively predict the expression of Ki-67 status in breast cancer.The support vector machine algorithm combined with feature model is the best,which can help the clinical diagnosis and treatment of breast cancer and prognosis evaluation.

Purpose To analyze the value of a deep learning(DL)radiomics model based on dynamic contrast-enhanced MRI images in predicting the expression of Ki-67 status in breast cancer.Materials and Methods A retrospective analysis of 152 breast cancer patients confirmed by pathological results at Guangdong Women and Children Hospital,MRI images and clinical pathological data were reviewed,and based on postoperative immunohistochemistry results,the images of the high and low expression groups of Ki-67 were randomly sampled in a ratio of 8∶2 to form a training set of 122 cases and a validation set of 30 cases.Single-factor and multi-factor Logistic regression analyses of clinical data were performed to select independent predictors of breast cancer expressing Ki-67 status.The ResNet-18 model was used as the basic model for DL feature extraction.Hand-crafted radiomic features and DL features were extracted.Eight machine learning models were constructed based on clinical features,hand-crafted radiomic features,DL features,and their combinations.The area under the receiver operating characteristic curve was used to evaluate the predictive performance of the models,and the best model was determined as the output model.Results The progesterone receptor status(OR=0.764,P=0.040)and human epidermal growth factor receptor-2 status(OR=1.187,P=0.046)were independent clinical predictors of breast cancer expressing Ki-67 status.The combined feature models demonstrated superior performance over the individual feature models,and the support vector machine algorithm had the highest prediction performance in the validation set,with an area under the curve of 0.847.Conclusion The DL radiomics model based on dynamic contrast-enhanced MRI images can effectively predict the expression of Ki-67 status in breast cancer.The support vector machine algorithm combined with feature model is the best,which can help the clinical diagnosis and treatment of breast cancer and prognosis evaluation.

Objective:To gain insight into the multidimensional needs of adults with moderate-to-severe psoriasis at different stages of disease progression diagnostic and treatment dynamics based on patient journey maps, providing a basis for developing precise intervention strategies and optimizing care throughout the journey.Methods:From September to October 2024, 14 adult patients with moderate-to-severe psoriasis admitted to the Department of Dermatology of the First Hospital of Shanxi Medical University were selected by purposive sampling method for semi-structured interviews. Content analysis was used to analyze the data, drawing on theory of "timing it right" to depict a patient journey map that was reviewed and improved by the research team and patients.Results:Patient journey map was developed and condensed into four themes of experiences and challenges from pre-diagnosis to adaptation, complex emotional experiences, experiential pain points at each stage of the diagnosis and treatment, and opportunity points to improve the experience and quality of the diagnosis and treatment.Conclusions:At different stages of disease progression, the diagnosis and treatment needs of adults with moderate-to-severe psoriasis are characterized by dynamic evolution and multidimensional integration. The journey map can accurately identify patients' differentiated experiences and needs, and can provide a reference for healthcare professionals and policy makers to optimize patients' diagnostic and treatment experiences and focus on patients' health management.

Objective:To gain insight into the multidimensional needs of adults with moderate-to-severe psoriasis at different stages of disease progression diagnostic and treatment dynamics based on patient journey maps, providing a basis for developing precise intervention strategies and optimizing care throughout the journey.Methods:From September to October 2024, 14 adult patients with moderate-to-severe psoriasis admitted to the Department of Dermatology of the First Hospital of Shanxi Medical University were selected by purposive sampling method for semi-structured interviews. Content analysis was used to analyze the data, drawing on theory of "timing it right" to depict a patient journey map that was reviewed and improved by the research team and patients.Results:Patient journey map was developed and condensed into four themes of experiences and challenges from pre-diagnosis to adaptation, complex emotional experiences, experiential pain points at each stage of the diagnosis and treatment, and opportunity points to improve the experience and quality of the diagnosis and treatment.Conclusions:At different stages of disease progression, the diagnosis and treatment needs of adults with moderate-to-severe psoriasis are characterized by dynamic evolution and multidimensional integration. The journey map can accurately identify patients' differentiated experiences and needs, and can provide a reference for healthcare professionals and policy makers to optimize patients' diagnostic and treatment experiences and focus on patients' health management.

Objective:To analyze the status of respiratory pathogen detection and the clinical features in children with Mycoplasma pneumoniae pneumonia (MPP). Methods:A prospective, multicenter study was conducted to collect clinical data, including medical history, laboratory examinations and multiplex PCR tests of children diagnosed with MPP from 4 hospitals in China between November 15 th and December 20 th, 2023. The multiplex PCR results and clinical characteristics of MPP children in different regions were analyzed. The children were divided into severe and mild groups according to the severity of the disease. Patients in the severe group were further divided into Mycoplasma pneumoniae (MP) alone and Multi-pathogen co-detection groups based on whether other pathogens were detected besides MP, to analyze the influence of respiratory pathogen co-detection rate on the severity of the disease. Mann-Whitney rank sum test and Chi-square test were used to compare data between independent groups. Results:A total of 298 children, 136 males and 162 females, were enrolled in this study, including 204 children in the severe group with an onset age of 7.0 (6.0, 8.0) years, and 94 children in the mild group with an onset age of 6.5 (4.0, 7.8) years. The level of C-reactive protein, D-dimer, lactic dehydrogenase (LDH) were significantly higher (10.0 (5.0, 18.0) vs. 5.0 (5.0, 7.5) mg/L, 0.6 (0.4, 1.1) vs. 0.5 (0.3, 0.6) mg/L, 337 (286, 431) vs. 314 (271, 393) U/L, Z=2.02, 2.50, 3.05, all P<0.05), and the length of hospitalization was significantly longer in the severe group compared with those in mild group (6.0 (6.0, 7.0) vs. 5.0 (4.0, 6.0) d, Z=4.37, P<0.05). The time from onset to admission in severe MPP children was significantly shorter than that in mild MPP children (6.0 (5.0, 9.5) vs. 9.0 (7.0, 13.0) d, Z=2.23, P=0.026). All patients completed the multiplex PCR test, with 142 cases (47.7%) MPP children detected with 21 pathogens including adenovirus 25 cases (8.4%), human coronavirus 23 cases (7.7%), rhinovirus 21 cases (7.0%), Streptococcus pneumoniae 21 cases (7.0%), influenza A virus 18 cases (6.0%). The pathogens with the highest detection rates in Tianjin, Shanghai, Wenzhou and Chengdu were Staphylococcus aureus at 10.7% (8/75), adenovirus at 13.0% (10/77), adenovirus at 15.3% (9/59), and both rhinovirus and Haemophilus influenzae at 11.5% (10/87) each. The multi-pathogen co-detection rate in severe MPP children was significantly higher than that in mild MPP group (52.9% (108/204) vs. 36.2% (34/94), χ2=10.62, P=0.005). Among severe MPP children, there are 89 cases in the multi-pathogen co-detection group and 73 cases in the simple MPP group. The levels of LDH, D-dimer and neutrophil counts in the multi-pathogen co-detection group were significantly higher than those in the simple MPP group (348 (284, 422) vs. 307 (270, 358) U/L, 0.8 (0.5, 1.5) vs. 0.6 (0.4, 1.0) mg/L, 4.99 (3.66, 6.89)×10 9vs. 4.06 (2.91, 5.65)×10 9/L, Z=5.17, 4.99, 6.11, all P<0.05). Conclusions:The co-detection rate of respiratory pathogens, LDH and D-dimer in children with severe MPP were higher than those with mild MPP. Among severe MPP children the stress response of children in co-detection group was more serious than that of children with simple MPP.

Medical mutual aid is an important component of multi-level medical security system. West China Second University Hospital of Sichuan University led the establishment of the pediatric specialty alliance " West China Women and Children Alliance". Based on customized and inclusive mutual insurance product " Family Doctor Mutual Aid Plan", the alliance implemented key links such as mutual aid product forms, patient risk protection, institutional financing and hematopoiesis, and distribution of benefits to all parties, explored innovative mutual aid funding, payment, and incentive mechanisms, forming a closed-loop pediatric tiered diagnosis and treatment service system with the Mutual Aid Plan as the core. This system operated continuously under the " Four-in-One" framework, stimulating the integration of medical insurance and service supply systems while enhancing the synergistic effect between mutual insurance and social security. It has formed a distinctive health-centered multi-level medical security system within the alliance, and could provide reference for the construction and exploration of hierarchical diagnosis and treatment system.

ObjectiveTo explore the syndrome elements and evolving patterns of patients with hepatitis B virus-related acute on chronic liver failure （HBV-ACLF） at different stages. MethodsClinical information of 1,058 hospitalized HBV-ACLF patients， including 618 in the early stage， 355 in the middle stage， and 85 in the late stage， were collected from 18 clinical centers across 12 regions nationwide from January 1， 2012 to February 28， 2015. The “Hepatitis B-related Chronic and Acute Liver Failure Chinese Medicine Clinical Questionnaire” were designed to investigate the basic information of the patients， like the four diagnostic information （including symptoms， tongue， pulse） of traditional Chinese medicine （TCM）， and to count the frequency of the appearance of the four diagnostic information. Factor analysis and cluster analysis were employed to determine and statistically analyze the syndrome elements and patterns of HBV-ACLF patients at different stages. ResultsThere were 76 four diagnostic information from 1058 HBV-ACLF patients， and 53 four diagnostic information with a frequency of occurrence ≥ 5% were used as factor analysis entries， including 36 symptom information， 12 tongue information， and 5 pulse information. Four types of TCM patterns were identified in HBV-ACLF， which were liver-gallbladder damp-heat pattern， qi deficiency and blood stasis pattern， liver-kidney yin deficiency pattern， and spleen-kidney yang-deficiency pattern. In the early stage， heat （39.4%， 359/912） and dampness （27.5%， 251/912） were most common， and the pattern of the disease was dominated by liver-gallbladder damp-heat pattern （74.6%， 461/618）； in the middle stage， dampness （30.2%， 187/619） and blood stasis （20.7%， 128/619） were most common， and the patterns of the disease were dominated by liver-gallbladder damp-heat pattern （53.2%， 189/355）， and qi deficiency and blood stasis pattern （27.6%， 98/355）； and in the late stage， the pattern of the disease was dominated by qi deficiency （26.3%， 40/152） and yin deficiency （20.4%， 31/152）， and the patterns were dominated by qi deficiency and blood stasis pattern （36.5%， 31/85）， and liver-gallbladder damp-heat pattern （25.9%， 22/85）. ConclusionThere are significant differences in the distribution of syndrome elements and patterns at different stages of HBV-ACLF， presenting an overall trend of evolving patterns as "from excess to deficiency， transforming from excess to deficiency"， which is damp-heat → blood stasis → qi-blood yin-yang deficiency.

Objective: To examine the relationship between 24 hour movement behavior and physical fitness of pupils by using compositional analyses, so as to provide a theoretical basis for physical activity promotion and physical fitness improvement. Methods: By random cluster sampling method, 120 students of grade 4 and 5 from the Second Experimental Primary School of Yingze District of Taiyuan were selected. Physical fitness was evaluated by the indicators of the Protocol of National Physical Training Standard and 20 meter shuttle run. The movement behavior was measured by accelerometer. The relationship between each behavior and physical fitness was analysed by component multiple linear regression, and the effect of replacement of components on physical fitness was discussed. Results: Girls 1minute situps were lower than boys（24.79±7.77，28.21±6.52），and sitting forward flexion was higher than boys[9.00（5.00，14.00），5.20（1.00，9.75）cm]（ t/Z =2.60，-3.15， P ＜0.05）. Boys showed higher light physical activity(LPA), moderate to vigorous physical activity(MVPA) and lower sedentary behavior(SB), while girls showed lower LPA, MVPA and higher SB. MVPA was positively correlated with the performance of 30 second rope skipping and 20 meter shuttle run ( β= 13.19, 7.90, P <0.05). Sleep(SLP), SB, and LPA were not significantly correlated with physical fitness. After re allocating 10 min MVPA to SB and SLP，the performance of 30 second rope skipping and 20 meter shuttle run increased by 2.25，2.28 and 1.28 ,1.34 times，respectively，while significantly decreased after reverse reallocation ( P <0.05). MVPA replaced LPA，the 20 meter shuttle run performance increased 1.46 times，while decreased significantly in reverses ( P <0.05). Conclusion MVPA is positively correlated with the speed and endurance of pupils. There are gender differences in movement behavior patterns and physical fitness. Children, especially girls, should be encouraged to raise exercise awareness and increase PA, especially MVPA.

Acute respiratory tract infection is the most common infectious disease in children, which seriously threatens children′s health.Rapid and accurate etiological diagnosis is of great significance for the clinical treatment and control of these diseases.Pathogen nucleic acid test was applied and became the main method of respiratory tract infection diagnosis for its high sensitivity and specificity.To regulate the application of pathogen nucleic acid amplification test in respiratory tract infection in children, improve the diagnosis level, expert consensus on nucleic acid amplification test of respiratory pathogens in children was prepared to guide the application and promote pathogens diagnosis ability.