Objective:To investigate the incidence, risk factors, and outcomes of falls among the elderly community population in Beijing.Methods:A cross-sectional survey was conducted using stratified multistage random sampling to select urban and rural residents aged 65 years and older in Beijing. Mortality data was collected after the baseline survey for 5 years. The incidence of falls was weighted based on the composition ratios of age and gender from the 2010 Nation-wide Population Census of Beijing. A logistic regression model was used to analyze the impacts of demographic sociology of common chronic diseases on fall occurrence. The Cox proportional hazards regression model was used to analyze the fall and 5-year survival association.Results:A total of 2 968 participants completed the questionnaire, at cross-sectional survey, with an average age of (73.2±6.0) years, and 1 581 (53.8%) participants were female. Three hundred and sixty-one individuals experienced a fall within the past year. Among those who fell, 64 (17.7%) fell twice, and 95 (26.6%) fell three or more times. Of them, 14.4% (52) had post-fall fractures, with the wrist, knee, and hip being the most common fracture sites, accounting for 25.0%, 17.3%, and 15.4%, respectively. The weighted fall incidence was 12.4% (95% CI: 11.2%-13.5%). Aging, being female, and living in rural areas were more likely to fall. Logistic regression analysis showed that after adjusting for age, gender, and urban-rural status, the risk of falls for those living alone ( OR=1.48, 95% CI: 1.08-2.04) or living with children/grandchildren ( OR=1.51, 95% CI: 1.15-1.97) were significantly higher than those living with their spouse. In addition, the risk of falls was elevated significantly among the elderly with hypertension, diabetes, stroke, dementia, depression status, urinary incontinence, arthritis, insomnia, vision, and hearing loss, dependence on activities of daily living (ADL), general and poor self-rated health (SRH). The Cox proportional hazard regression model revealed that the 5-year risk of death increased by 65% ( HR=1.65, 95% CI: 1.29-2.11) for those who experienced a fall, which increased with fall frequency. This elevated risk persisted after adjusting for chronic conditions, ADL, and SRH. Conclusions:Ageing, female, living in rural regions, having common chronic diseases, dependence on ADL, general and poor SRH, living alone or living with children/grandchildren were associated with the elevated fall risk. The occurrence of fall was seasonal. The most common short-term adverse consequence after a fall was fractures, while the long-term effect was an increased risk of death.

This article summarizes Professor Tan Yong's approach to the treatment of polycystic ovary syndrome(PCOS)based on the lipid turbidity theory.It is believed that multiple factors such as improper diet,emotional injury,insufficient endowment,and im-proper work and rest lead to dysfunction of spleen and stomach,which cannot normally transport and transform water and grain essence and body fluid,and lipids cannot be effectively transformed and utilized,thus accumulating in the body to form lipid turbidity.Lipid turbidity is not only a pathological product but also an independent pathogenic factor,characterized by stickiness,concealment,heavy turbidity,lodging in collaterals,combined pathogenicity,and obstruction of qi and blood.Based on this theory,the etiology and patho-genesis of PCOS are explored,with its pathological progression divided into three stages:spleen deficiency and liver depression,phlegm and blood stasis,and kidney deficiency with lipid turbidity.In the early stage,impaired spleen transportation and liver disper-sion functions lead to lipid metabolism disorders,forming lipid turbidity.In the middle stage,lipid stagnation and obstruction of the meridians affect the circulation of qi and blood,leading to internal stasis and the formation of a pathological pattern of phlegm and blood stasis.In the later stage,prolonged illness affects the kidney,resulting in kidney qi deficiency,unresolved lipid turbidity,and imbal-ance of qi,blood,yin and yang,which leads to long-term metabolic and reproductive dysfunction.In terms of treatment,emphasis is placed on strengthening the spleen and eliminating turbidity,soothing the liver and nourishing blood in the early stage;eliminating phlegm and blood stasis,unblocking the collaterals and eliminating lipid in the middle stage;nourishing the kidney and replenishing essence,and regulating yin and yang in the late stage,providing new insights and theoretical basis for the integrated diagnosis and treatment of PCOS with traditional Chinese and Western medicine.

Recently, intelligent care is gradually changing the traditional care way, and artificial intelligence (AI) application is gradually broadening in the field of assisted reproduction. This review systematically analyzes the AI application in multiple aspects of reproductive health care. It also indicates the challenge during the process, including data privacy, technical reliability, ethics and legal provisions, and humanistic care. Both the opportunities of AI in assisted reproduction are highlighted and the ensuing problems are analyzed in depth. The purpose is to provide ideas for future studies to ensure that AI technology can be safely, efficiently and responsibly integrated with the field of reproductive health care.

Oocyte maturation disorders and fertilization failures are caused by a variety of factors, including complex factors such as chromosomal abnormalities and poor oocyte quality. With the widespread use of high-throughput sequencing technology, more and more genetic mutations have been found to be associated with oocyte maturation and fertilization process in infertile patients. This paper summarizes and discusses 11 key genes ( TRIP13, TBPL2, LHX8, PATL2, TUBB8, CDC20, WEE2, ZP, ASTL, JUNO and CD9) related to oocyte maturation and fertilization-related disorders in females, providing a basis for research on the prevention of diseases associated with oocyte maturation blockage and fertilization failure and the development of targeted therapies.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*

Non-classical congenital adrenal hyperplasia (NCCAH), an autosomal recessive disorder, stems from genetic mutations affecting the enzymes and cofactors integral to adrenal steroidogenesis. These mutations may result in diminished activity or a complete loss of function for critical enzymes, such as 21-hydroxylase, 11β-hydroxylase, 3β-hydroxysteroid dehydrogenase, 17α-hydroxylase, and the steroidogenic acute regulatory protein (StAR). The impairment of these enzymatic processes has profound implications for reproductive health in females, mediated through both genetic and endocrine pathways. This review aims to explore the pathogenesis of various enzyme defects in different types of NCCAH, their clinical features, and their impact on female fertility. It is hoped that this will help refine the diagnostic strategies for infertility associated with NCCAH, thereby enhancing fertility of patients and providing new directions and opportunities for further research in this field.

Objective:To investigate the incidence, risk factors, and outcomes of falls among the elderly community population in Beijing.Methods:A cross-sectional survey was conducted using stratified multistage random sampling to select urban and rural residents aged 65 years and older in Beijing. Mortality data was collected after the baseline survey for 5 years. The incidence of falls was weighted based on the composition ratios of age and gender from the 2010 Nation-wide Population Census of Beijing. A logistic regression model was used to analyze the impacts of demographic sociology of common chronic diseases on fall occurrence. The Cox proportional hazards regression model was used to analyze the fall and 5-year survival association.Results:A total of 2 968 participants completed the questionnaire, at cross-sectional survey, with an average age of (73.2±6.0) years, and 1 581 (53.8%) participants were female. Three hundred and sixty-one individuals experienced a fall within the past year. Among those who fell, 64 (17.7%) fell twice, and 95 (26.6%) fell three or more times. Of them, 14.4% (52) had post-fall fractures, with the wrist, knee, and hip being the most common fracture sites, accounting for 25.0%, 17.3%, and 15.4%, respectively. The weighted fall incidence was 12.4% (95% CI: 11.2%-13.5%). Aging, being female, and living in rural areas were more likely to fall. Logistic regression analysis showed that after adjusting for age, gender, and urban-rural status, the risk of falls for those living alone ( OR=1.48, 95% CI: 1.08-2.04) or living with children/grandchildren ( OR=1.51, 95% CI: 1.15-1.97) were significantly higher than those living with their spouse. In addition, the risk of falls was elevated significantly among the elderly with hypertension, diabetes, stroke, dementia, depression status, urinary incontinence, arthritis, insomnia, vision, and hearing loss, dependence on activities of daily living (ADL), general and poor self-rated health (SRH). The Cox proportional hazard regression model revealed that the 5-year risk of death increased by 65% ( HR=1.65, 95% CI: 1.29-2.11) for those who experienced a fall, which increased with fall frequency. This elevated risk persisted after adjusting for chronic conditions, ADL, and SRH. Conclusions:Ageing, female, living in rural regions, having common chronic diseases, dependence on ADL, general and poor SRH, living alone or living with children/grandchildren were associated with the elevated fall risk. The occurrence of fall was seasonal. The most common short-term adverse consequence after a fall was fractures, while the long-term effect was an increased risk of death.

Non-classical congenital adrenal hyperplasia (NCCAH), an autosomal recessive disorder, stems from genetic mutations affecting the enzymes and cofactors integral to adrenal steroidogenesis. These mutations may result in diminished activity or a complete loss of function for critical enzymes, such as 21-hydroxylase, 11β-hydroxylase, 3β-hydroxysteroid dehydrogenase, 17α-hydroxylase, and the steroidogenic acute regulatory protein (StAR). The impairment of these enzymatic processes has profound implications for reproductive health in females, mediated through both genetic and endocrine pathways. This review aims to explore the pathogenesis of various enzyme defects in different types of NCCAH, their clinical features, and their impact on female fertility. It is hoped that this will help refine the diagnostic strategies for infertility associated with NCCAH, thereby enhancing fertility of patients and providing new directions and opportunities for further research in this field.

Recently, intelligent care is gradually changing the traditional care way, and artificial intelligence (AI) application is gradually broadening in the field of assisted reproduction. This review systematically analyzes the AI application in multiple aspects of reproductive health care. It also indicates the challenge during the process, including data privacy, technical reliability, ethics and legal provisions, and humanistic care. Both the opportunities of AI in assisted reproduction are highlighted and the ensuing problems are analyzed in depth. The purpose is to provide ideas for future studies to ensure that AI technology can be safely, efficiently and responsibly integrated with the field of reproductive health care.

Oocyte maturation disorders and fertilization failures are caused by a variety of factors, including complex factors such as chromosomal abnormalities and poor oocyte quality. With the widespread use of high-throughput sequencing technology, more and more genetic mutations have been found to be associated with oocyte maturation and fertilization process in infertile patients. This paper summarizes and discusses 11 key genes ( TRIP13, TBPL2, LHX8, PATL2, TUBB8, CDC20, WEE2, ZP, ASTL, JUNO and CD9) related to oocyte maturation and fertilization-related disorders in females, providing a basis for research on the prevention of diseases associated with oocyte maturation blockage and fertilization failure and the development of targeted therapies.