Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

Acupuncture, a therapeutic treatment defined as the insertion of needles into the body at specific points (ie, acupoints), has growing in popularity world-wide to treat various diseases effectively, especially acute and chronic pain. In parallel, interest in the physiological mechanisms underlying acupuncture analgesia, particularly the neural mechanisms have been increasing. Over the past decades, our understanding of how the central nervous system and peripheral nervous system process signals induced by acupuncture has developed rapidly by using electrophysiological methods. However, with the development of neuroscience, electrophysiology is being challenged by calcium imaging in view field, neuron population and visualization in vivo. Owing to the outstanding spatial resolution, the novel imaging approaches provide opportunities to enrich our knowledge about the neurophysiological mechanisms of acupuncture analgesia at subcellular, cellular, and circuit levels in combination with new labeling, genetic and circuit tracing techniques. Therefore, this review will introduce the principle and the method of calcium imaging applied to acupuncture research. We will also review the current findings in pain research using calcium imaging from in vitro to in vivo experiments and discuss the potential methodological considerations in studying acupuncture analgesia.
Calcium ; Acupuncture Therapy ; Acupuncture ; Acupuncture Analgesia/methods* ; Acupuncture Points ; Technology

Objective: To analyze the incidence and related factors of drug resistance in HIV-infected pregnant and postpartum women in some areas of three western provinces of China from 2017 to 2019. Methods: From April 2017 to April 2019, face-to-face questionnaires and blood sample testing were conducted in all health care institutions providing maternal and perinatal care and midwifery-assisted services in 7 prevention of mother-to-child transmissi project areas in Xinjiang, Yunnan and Guangxi provinces/autonomous regions. Information was collected during the perinatal period and viral load, CD4⁺T lymphocytes and drug resistance genes were detected at the same time. The multivariate logistic regression model was used to analyze the relationship between different factors and drug resistance in HIV-infected pregnant and postpartum women. Results: A total of 655 HIV-infected pregnant and postpartum women were included in this study. The incidence of drug resistance was 3.4% (22/655), all of whom were cross-drug resistant. The rate of low, moderate and high drug resistance was 2.1% (14/655), 1.2% (8/655) and 0.8% (5/655), respectively. The drug resistance rate in the people who had previously used antiviral drugs was 1.9% (8/418), and the drug resistance rate in the people who had not used drugs was 5.9% (14/237). The NNRTI drug resistance accounted for 2.8% (18/655) and the NRTI drug resistance rate was 2.5% (16/655). The multivariate logistic regression model showed that the risk of HIV resistance was lower in pregnant women who had previously used antiviral drugs (OR=0.32, 95%CI: 0.11-0.76). Conclusion: Strengthening the management of antiviral drug use and focusing on pregnant and postpartum women who have not previously used antiviral drugs can help reduce the occurrence of drug-resistant mutations. Personalized antiviral therapy should be considered to achieve viral inhibition effects in clinical practice.
Female ; Humans ; Pregnancy ; HIV Infections/drug therapy* ; Incidence ; China/epidemiology* ; Infectious Disease Transmission, Vertical/prevention & control* ; Postpartum Period ; Drug Resistance, Viral/genetics* ; Antiviral Agents/therapeutic use*

Objective: To analyze the incidence and related factors of drug resistance in HIV-infected pregnant and postpartum women in some areas of three western provinces of China from 2017 to 2019. Methods: From April 2017 to April 2019, face-to-face questionnaires and blood sample testing were conducted in all health care institutions providing maternal and perinatal care and midwifery-assisted services in 7 prevention of mother-to-child transmissi project areas in Xinjiang, Yunnan and Guangxi provinces/autonomous regions. Information was collected during the perinatal period and viral load, CD4⁺T lymphocytes and drug resistance genes were detected at the same time. The multivariate logistic regression model was used to analyze the relationship between different factors and drug resistance in HIV-infected pregnant and postpartum women. Results: A total of 655 HIV-infected pregnant and postpartum women were included in this study. The incidence of drug resistance was 3.4% (22/655), all of whom were cross-drug resistant. The rate of low, moderate and high drug resistance was 2.1% (14/655), 1.2% (8/655) and 0.8% (5/655), respectively. The drug resistance rate in the people who had previously used antiviral drugs was 1.9% (8/418), and the drug resistance rate in the people who had not used drugs was 5.9% (14/237). The NNRTI drug resistance accounted for 2.8% (18/655) and the NRTI drug resistance rate was 2.5% (16/655). The multivariate logistic regression model showed that the risk of HIV resistance was lower in pregnant women who had previously used antiviral drugs (OR=0.32, 95%CI: 0.11-0.76). Conclusion: Strengthening the management of antiviral drug use and focusing on pregnant and postpartum women who have not previously used antiviral drugs can help reduce the occurrence of drug-resistant mutations. Personalized antiviral therapy should be considered to achieve viral inhibition effects in clinical practice.
Female ; Humans ; Pregnancy ; HIV Infections/drug therapy* ; Incidence ; China/epidemiology* ; Infectious Disease Transmission, Vertical/prevention & control* ; Postpartum Period ; Drug Resistance, Viral/genetics* ; Antiviral Agents/therapeutic use*

Objective To establish the three-dimensional finite element model of lumbar spine(L) 3-5 segments of the normal spine of 14-year-old adolescents to analyze the biomechanical changes of the lumbar spine after different degrees of lumbar foraminal plasty, and to provide reference for improvement of adolescent foraminoplasty. Methods A14-year-old female volunteer with no previous history of lumbar spine was selected to collect lumbar CT image data and we imported it into Mimics 16.0 software for modeling. ABAQUS software was used to conduct finite element model force analysis. Models M

Objective:To explore the accuracy of artificial intelligence (AI) system based on deep learning in evaluating bone age of children with abnormal growth and development.Methods:The positive X-ray films of the left wrist of children with abnormal growth and development who were treated at the Affiliated Hospital of Guizhou Medical University from January 2020 to December 2021 were collected retrospectively. A total of 717 children were collected, including 266 males and 451 females, aged 2-18 (11±3) years. Based on Tanner Whitehouse 3 (TW 3)-RUS (radius, ulna, short bone) and TW3-Carpal (carpal bone) method, bone age was measured by 3 senior radiologists, and the mean value was taken as reference standard. The bone ages were independently evaluated by the AI system (Dr.Wise bone age prediction software) and two junior radiologists (physicians 1 and 2). The accuracy within 0.5 year, the accuracy within 1 year, the mean absolute error (MAE) and the root mean square error (RMSE) between the evaluation results and the reference standard were analyzed. Paired sample t-test was used to compare MAE between AI system and junior physicians. Intraclass correlation coefficient (ICC) was used to evaluate the consistency between AI system, junior physician and reference standard. The Bland-Altman diagram was drawn and the 95% consistency limit was calculated between AI system and reference standard. Results:For TW3-RUS bone age, compared with the reference standard, the accuracy within 0.5 year of AI system, physician 1 and physician 2 was 75.3% (540/717), 62.1% (445/717) and 66.2% (475/717), respectively. The accuracy within 1 year was 96.9% (695/717), 86.3% (619/717) and 89.1% (639/717), respectively. MAE was 0.360, 0.565 and 0.496 years, and RMSE was 0.469, 0.634 and 0.572 years, respectively. For TW3-Carpal bone age, compared with the reference standard, the accuracy within 0.5 year of AI system, physician 1 and physician 2 was 80.9% (580/717), 65.1% (467/717) and 71.7% (514/717), respectively. The accuracy within 1 year was 96.0% (688/717), 87.3% (626/717) and 90.4% (648/717), respectively. MAE was 0.330, 0.527 and 0.455 years, and RMSE was 0.458, 0.612, 0.538 years, respectively. Based on TW3-RUS and TW3-Carpal bone age, the MAE of AI system were lower than those of physician 1 and physician 2, and the differences were statistically significant ( P all<0.001). The evaluation results of AI, physician 1 and physician 2 were in good agreement with the reference standard (ICC all>0.950). The Bland-Altman analysis showed that the 95% agreement limits of AI system for assessing TW3-RUS and TW3-Carpal bone age were -0.75-1.02 years and-0.86-0.91 years, respectively. Conclusion:The accuracy of AI system in evaluating the bone age of children with abnormal growth and development is close to that of senior doctors, better than that of junior doctors, and in good agreement with senior doctors.

The latest epidemiological data suggests that the situation of adult diabetes in China is severe, and metabolic diseases have become significant chronic illnesses that have a serious impact on public health and social development. After more than six years of practice, the National Metabolic Management Center(MMC) has developed distinctive approaches to manage metabolic patients and has achieved a series of positive outcomes, continuously advancing the standardized diagnosis and treatment model. In order to further improve the efficiency, based on the first edition, the second edition guideline was composed by incorporating experience of the past six years in conjunction with the latest international and domestic guidelines.

OBJECTIVES: To develop a risk prediction model for severe adenovirus pneumonia (AVP) in children, and to explore the appropriate timing for intravenous immunoglobulin (IVIG) therapy for severe AVP. METHODS: Medical data of 1 046 children with AVP were retrospectively analyzed, and a risk prediction model for severe AVP was established using multivariate logistic regression. The model was validated with 102 children with AVP. Then, 75 children aged ≤14 years who were considered at risk of developing severe AVP by the model were prospectively enrolled and divided into three groups (A, B and C) in order of visit, with 25 children in each group. Group A received symptomatic supportive therapy only. With the exception of symptomatic supportive therapy, group B received IVIG treatment at a dose of 1g/(kg·d) for 2 consecutive days, before progressing to severe AVP. With the exception of symptomatic supportive therapy, group C received IVIG treatment at a dose of 1 g/(kg·d) for 2 consecutive days after progressing to severe AVP. Efficacy and related laboratory indicators were compared among the three groups after treatment. RESULTS: Age<18.5 months, underlying diseases, fever duration >6.5 days, hemoglobin level <84.5 g/L, alanine transaminase level >113.5 U/L, and co-infection with bacteria were the six variables that entered into the risk prediction model for severe AVP. The model had an area under the receiver operating characteristic curve of 0.862, sensitivity of 0.878, and specificity of 0.848. The Hosmer-Lemeshow test showed good consistency between the predicted values and the actual observations (P>0.05). After treatment, group B had the shortest fever duration and hospital stay, the lowest hospitalization costs, the highest effective rate of treatment, the lowest incidence of complications, the lowest white blood cell count and interleukin (IL)-1, IL-2, IL-6, IL-8, IL-10 levels, and the highest level of tumor necrosis factor alpha (P<0.05). CONCLUSIONS The risk model for severe AVP established in this study has good value in predicting the development of severe AVP. IVIG therapy before progression to severe AVP is more effective in treating AVP in children.
Child ; Humans ; Immunoglobulins, Intravenous/therapeutic use* ; Prospective Studies ; Retrospective Studies ; Adenoviridae Infections/drug therapy* ; Pneumonia, Viral/drug therapy* ; Adenoviridae

The purpose of this study was to investigate how Zuogui pills from the Kidney-tonifying and Nourishing Yin formula, in combination with the gonadotrophin-releasing hormone antagonist cetrorelix, affected the ovarian local oxidative stress response in decreasing ovarian reserve (DOR) mice. All animal experiments were carried out in accordance with the guidelines and standards established by Jinan University's Experimental Animal Management Committee. Cyclophosphamide (CTX)-treated DOR mice were given Zuogui pills, cetrorelix, or a combination of the two drugs intragastrically. After treatment, there were changes in the estrous cycle, serum sex hormone levels, oxidative stress-related indexes, growth biochemical factor levels, and SIRT1/P53/P21 expression. In comparison to the model group, the Zuogui pills and the cetrorelix+Zuogui pills group had significantly prolonged estrous periods and shortened interestrous periods, and the cetrorelix+Zuogui pills group had a significantly shortened cycle length. Follicle-stimulating hormone (FSH) decreased and estradiol (E₂) increased in all treatment groups compared to the model group, oxidative stress indexes nitric oxide synthase (NOS), nitric oxide (NO), and reactive oxygen species (ROS) decreased, growth biochemical factors brain derived neurotrophic factor (BDNF) and growth differentiation factor 9 (GDF-9) concentrations increased significantly, and leukemia inhibitory factor (LIF) showed no significant change. SIRT1/P53/P21 immunohistochemical results revealed that, when compared to the model group, the expression of SIRT1 increased while the expression of P53 and P21 proteins decreased in all treatment groups, with the cetrorelix+Zuogui pills group having the largest decrease, with significant differences in all indicators. We conclude that cetrorelix combined with Zuogui pills for kidney nourishing and Yin recipe improved the oxidative stress response in the follicle by regulating the SIRT1/P53/P21 pathway, reducing peroxide product production, protecting ovarian function, and regulating ovarian hormone secretion, and its efficacy is superior to that of cetrorelix or Zuogui pills alone.

Objective: To understand levels of various foods and nutrients in school lunch based on digital platform and to provide reference for food preparation and serving. Methods: A total of 13 018 school lunch recipes in Binhai New Area of 96 schools in Tianjin from November 2020 to April 2021 were collected by using digital management platform for food safety and nutritional health.Food types including cereals and tubers, vegetables, fruits, livestock and poultry meat, fish and shrimp, eggs, milk and dairy products, legumes and their products/nuts and others energy, and nutrients including protein, fat, carbohydrate, calcium, iron, zinc, selenium, vitamin A, vitamin B 1, vitamin B 2, vitamin C and dietary fiber were evaluated. Results: The qualified rate of all kinds of food for students lunch from high to low were 96.8% (116.4 g) of livestock and poultry meat, 92.3% (179.5 g) of cereal and potato, 65.0% (170.6 g) of vegetables, 47.7% (21.4 g) of soybeans and their products/nuts, 33.4% (18.0 g) of eggs, 14.4% (8.5 g) of fish and shrimp, 14.1% (19.6 g) of fruits, 0.3% (35.4 g) of milk and dairy products. There were significant differences in the qualified rate of various food intake among different grades( P <0.05). The qualified rate of students lunch energy was 76.9%(932.6 kcal). The qualified rates of various nutrients from high to low were iron 96.9%(9.7 mg), zinc 96.8%(5.9 mg), protein 96.4%(43.8 g), carbohydrate 87.6%(130.8 g) and selenium 82.9%(23.5 μg), vitamin C 78.5%(48.8 mg), vitamin B 1 75.9%(0.5 mg), fat 74.3%(28.5 g), vitamin A 74.1%(327.1 μ g) vitamin B 2 49.9%(0.5 mg), dietary fiber 19.5%(5.9 g) and calcium 13.4%(246.1 mg). There were significant differences in the qualified rates of energy and nutrients among different grades( P <0.05). Conclusion The digital platform basically meets school lunch requirments on food types and nutrients, but still with problems regarding insufficient fish and shrimp, fruits, milk and dairy products, vitamin B 2, dietary fiber and calcium. It is suggested to optimize school lunch recipes or increase corresponding nutrients content in other meals.