Osteoporosis is a systemic disease, and epidemiological projections indicate that by 2050, approximately 23.43% of the Chinese population over 50 years of age will be affected. Given the poor prognosis associated with osteoporosis, the exploration of safe and effective natural products is of considerable significance. Studies investigating the chemical constituents of traditional Chinese medicine in cellular and/or animal models have demonstrated bone-protective effects. Although most of these compounds lack clinical data, they hold considerable potential as lead candidates for drug development. In-depth study of the structure-activity relationship of these natural products not only contributes to elucidating the mechanisms of action but also provides a theoretical basis for the development of novel antiosteoporosis therapies. This review summarizes natural products with potential antiosteoporotic effects reported between 2020 and 2024. Overall, plant-derived natural compounds exhibit antiosteoporotic effects by regulating bone remodeling, inflammation, and oxidative stress, highlighting their promise as multitarget therapeutic candidates.

This paper introduces professor WU Rongzu's clinical experience in using Fuyang Tongmi Decoction （扶阳通秘汤， FTD） to treat irritable bowel syndrome with constipation （IBS-C）. It is believed that yang qi depletion， water cold， earth dampness， and wood constraint are the key pathogenesis.The treatment principle is warming water， drying the earth and venting wood， with the basic formula FTD adjusted according to the symptoms. This approach aims to transport the qi movement of the middle jiao （焦） and support the recovery of intestinal function of directing turbidity downward， providing a treatment strategy for IBS-C caused by yang deficiency.

Triclosan (TCS) and triclocarban (TCC) are widely used synthetic broad-spectrum antibacterial agents that can enter the human body through the skin, gastrointestinal tract, and other pathways. More and more studies have found that exposure to TCS and TCC can affect human health, but currently, review reports on the health effects of human exposure to TCS and TCC are limited. Therefore, this study reviewed population studies on the relationship between TCS and TCC exposure and health effects by searching the PubMed database, summarized the associated health outcomes, and elucidated the biological mechanisms. A total of 56 studies were retrieved, among which cross-sectional studies (25 studies, 44.64%) and cohort studies (25 studies, 44.64%) accounted for a relatively large proportion, while case-control studies (6 studies, 10.72%) were relatively few. Studies on TCS exposure (48 studies, 85.71%) were far more prevalent than those on TCC exposure (2 studies, 3.57%). The remaining 6 studies involved both TCS and TCC exposure. The research results revealed that TCS exposure was associated with male and female abnormal reproductive functions, fetal growth restriction, abnormal behavior development in children, obesity, gestational diabetes mellitus (GDM), and immune-related diseases. Although the results of different studies show significant differences, they have indicated that exposure to TCS is a potential risk factor for these health problems. Due to the limited number of studies, the evidence for the relationship between TCC exposure and most of the aforementioned health effects is insufficient. Population studies and in vitro and in vivo studies have shown that exposure to TCS and TCC can interfere with the microbial homeostasis, the endocrine system, oxidative stress and immune function of the body, which are potential mechanisms causing adverse health effects. In the future, large-scale prospective cohort studies, as well as in vivo and in vitro studies, are still needed to further clarify the associations between TCS and TCC exposure and health effects, and to deeply explore its mechanism of action. These efforts will provide references for clarifying the human health hazards of TCS and TCC exposure and formulating targeted prevention and control strategies.

ObjectiveTo analyze the risk factors for long-term cardiovascular events in patients undergoing long-term peritoneal dialysis （PD）， and to construct and validate a visual nomogram prediction model based on multiple parameters. MethodsA prospective cohort study was conducted， consecutively enrolling 248 maintenance PD patients （dialysis duration ≥ 3 months）. Demographic characteristics， clinical indicators， laboratory parameters， and echocardiographic indices （including left ventricular ejection fraction ［LVEF］， ratio of early diastolic mitral inflow velocity to early diastolic mitral annular velocity （E/e’）， etc.） were collected. The composite endpoint was defined as the occurrence of cardiovascular events or cardiovascular death， with non-cardiovascular death as the competing risk and loss to follow-up or the end of follow-up as censoring events. Fine-Gray competing risks model was used to screen independent predictors， based on which a nomogram model was constructed. Internal validation was performed using the Bootstrap method （1 000 resamplings）， and the concordance index （C-index） and time-dependent receiver operating characteristic （time-dependent ROC） curve were calculated to evaluate the model performance. ResultsWith a median follow-up of 29 months （interquartile range： 24–35 months）， 88 patients （35.48%） reached the composite endpoint， including 80 cases of cardiovascular events and 8 cases of cardiovascular death， and 4 patients died of non-cardiovascular causes. Multivariate Fine-Gray analysis revealed that age， diabetes mellitus， hemoglobin （HGB） level and E/e' ratio were independent influencing factors of the composite endpoint. Specifically， each 1-year increase in age was associated with a 3.0% increase in the risk of the composite endpoint （HR=1.030， P=0.006）； patients with diabetes mellitus had a 167.9% higher risk compared with non-diabetic patients （HR=2.679， P=0.007）； each 1g/L increase in HGB level contributed to a 1.5% reduction in the risk （HR=0.985， P=0.003）； and each 0.1 increase in E/e' ratio led to a 7.2% increase in the risk （HR=1.072， P=0.045）. The nomogram model had a C-index of 0.76 （95% CI： 0.698–0.820）， and the AUC of the time-dependent ROC curve reached 0.849 at 23 months of follow-up. ConclusionIncreased age， complicated with diabetes mellitus， decreased HGB， and elevated E/e' ratio are independent risk factors of long-term occurrence of cardiovascular events and cardiovascular death in patients undergoing long-term PD. The nomogram model constructed based on the above variables has good predictive value and clinical applicability， which can provide a reference for cardiovascular risk stratification and individualized intervention in long-term PD patients.

The disease-syndrome combination animal model in traditional Chinese medicine （TCM） andrology serves as an important bridge linking TCM theory with modern medical research， providing a key experimental platform for elucidating the 'syndrome-disease' correlation mechanism in male-specific diseases and for screening effective prescriptions. This article reviews recent progress in animal model research on common TCM andrological diseases， including prostatic diseases， sexual dysfunction， and male infertility， with a focus on analyzing the application， advantages， and disadvantages of various modeling strategies， such as immune induction， hormonal intervention， and multi-factor combination across different syndrome types. However， despite breakthroughs in model construction techniques， current research still faces several challenges， including insufficient standardization of syndrome differentiation and difficulties in quantifying TCM-specific indicators. Future studies need to optimize model evaluation systems by integrating modern technologies， in order to promote the standardization and internationalization of TCM andrology research.

Metabolic dysfunction-associated fatty liver disease （MAFLD） has become one of the most prevalent chronic liver diseases worldwide， posing a serious challenge to public health. In this context， the integration of artificial intelligence （AI）， especially intelligent diagnosis and treatment and digital health interventions based on machine learning， can break through the limitations of traditional methods， realize efficient screening of multi-dimensional data such as key genes， biomarkers， and biochemical metabolites， and achieve revolutionary breakthroughs in risk prediction， subtype identification， and therapeutic effect assessment for MAFLD. This article systematically reviews the ground-breaking application of machine learning models in driving the innovation of clinical diagnosis and precise risk prediction of MAFLD， conducts a comprehensive comparative analysis of digital health practice cases of MAFLD in China and globally， and deeply analyzes their advantages and limitations in terms of research subjects， interventions， and management team. Studies have shown that the deep integration of digital health and long-term management of MAFLD is becoming the key engine driving the transformation of disease management modes towards an intelligent， individualized， and precise era， but there are various ethical and technical issues that need to be addressed urgently.

Objective To investigate the distribution characteristics of Oncomelania hupensis snails in Yunnan Province fol-lowing interruption of schistosomiasis transmission, so as to provide the evidence for assessing the risk of schistosomiasis transmission and scientifically formulating the schistosomiasis surveillance program. Methods According to the requirements of the National Schistosomiasis Surveillance Scheme (2020 Edition), O. hupensis snail surveillance data were collected from 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province from 2020 to 2024, including area of snail survey, area of snail habitats, area of re-emerging snail habitats, number of frames surveyed, number of frames with O. hupensis snails, number of O. hupensis snails captured, and number of living snails, and the occurrence of frames with snails and mean density of living snails were calculated. Changes in snail status over the 5-year period from 2020 to 2024 and the differences in snail distributions specified by epidemic intensity, environmental type, and vegetation type were analyzed. Results The areas of snail survey increased from 1 727.96 hm² in 2020 to 3 894.45 hm² in 2024 (peak) across 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province during the period from 2020 through 2024. The areas of snail habitats increased from 70.36 hm² in 2020 to a peak in 2023 (172.04 hm²), followed by a reduction to 132.36 hm² in 2024, and the areas of re-emerging snail habitats increased from 42.71 hm² in 2020 to a peak in 2022 (78.43 hm²), followed by a reduction to 40.21 hm² in 2024. The occurrence of frames with snails and mean density of living snails increased from 1.24% (3 025/244 404) and (0.033 2 ± 0.038 7) snails/0.1 m² in 2020 to peaks at 2.03% (6 231/307 563) and (0.066 9 ± 0.068 4) snails/0.1 m² in 2023, followed by reductions to 1.04% (5 829/559 941) and (0.032 6 ± 0.057 7) snails/0.1 m² in 2024, respectively. There was a significant difference in the occurrence of frames with snails over the 5-year study period (χ² = 1 962.95, P < 0.05), and the occurrence of frames with snails reduced by 48.71% in 2024 relative to in 2023 (χ² = 1 411.05, P < 0.005); however, there was no significant difference in the mean density of living snails over the 5 years (H = 5.310, P > 0.05). There were significant differences in the occurrence of frames with snails (χ² = 481.27, P < 0.05) and mean density of living snails (H = 6.872, P < 0.05) in schistosomiasis-endemic areas with different epidemic intensities. The occurrence of frames with snails (χ² = 25.32 and 38.70, both P values < 0.017) and mean density of living snails (Z = 28.55 and 49.96, both P values < 0.017) were higher in schistosomiasis transmission-interrupted and eliminated areas with snails than in schistosomiasis-eliminated areas without snails, and the occurrence of frames with snails (χ² = 453.54, P < 0.017) and mean density of living snails (Z = −56.97, P < 0.017) were higher in schistosomiasis-eliminated areas with snails than in schistosomiasis transmission-interrupted areas with snails. O. hupensis snails were mainly distributed in paddy fields, dry farmlands and ditches; however, the occurrence of frames with snails (13.40%, 424/3 164) and mean density of living snails [(0.252 8 ± 0.158 7) snails/0.1 m²] were higher in ponds/weirs than in other types of environments (both P values < 0.05). Rice, dry farmland crops and weeds were main vegetations in which O. hupensis snails were distributed, and the occurrence of frames with snails (2.29%, 7 111/310 140) and mean density of living snails [(0.072 3 ± 0.018 9) snails/0.1 m²] were higher in weeds than in other types of environments (both P values < 0.05). Conclusions O. hupensis snails have been effectively controlled in Yunnan Province following implementation of integrated schistosomiasis control measures; however, there are still risk factors for schistosomiasis transmission, including reduced attention to schistosomiasis control and snail re-emergence. Improved control efforts and surveillance system construction and timely identification of risk factors of snail status and timely management are recommended to ensure the achievement of the target of schistosomiasis elimination as scheduled.

To evaluate the clinical value of nebulized indocyanine green(ICG) combined with near-infrared fluorescence imaging for intraoperative detection of air leaks during pulmonary resection.

At present， the systematic excavation of the clinical experience and academic thought of the Sichuan school of Chinese medicine vis-à-vis its dominant disease entities remains fragmentary， and replicable paradigms are scarce. Confronted with empirical fragmentation， data heterogeneity and decision-making subjectivity， the standardised distillation， inheritance and clinical translation of these distinctive experiences has become a critical bottleneck constraining the development of the Sichuan school. The integration of artificial-intelligence technologies in data processing， pattern recognition and intelligent decision-making has rendered deep mining of traditional Chinese medicine（TCM） clinical knowledge and patterns imperative. Constructing an intelligent modern TCM diagnostic-therapeutic-evaluative system is now the obligatory route for inheritance and innovation in Chinese medicine， and simultaneously provides a technological breakthrough for intelligent decision paradigms in the dominant diseases of the Sichuan school. Accordingly， this study adopts the regional academic school as its point of entry， focuses on the dominant diseases of the Sichuan school， and proposes an innovative pathway of "four-dimensional data-multi-modal fusion-multi-agent decision-making". Specifically， four data dimensions are defined and instantiated： （Ⅰ） knowledge from classical medical literature and historical case records. （Ⅱ） objective four-diagnosis phenotypic data. （Ⅲ） master physicians' prescribing regularities. （Ⅳ） characteristic mechanisms of renowned formulae. Leveraging multi-modal data fusion and generative artificial intelligence， the entire causal chain of Famous Physicians and Renowned Formulas is explicated to reconstruct the diagnostic-therapeutic cognitive logic of the regional school. Finally， a multi-agent collective-decision model is established and refined for the dominant diseases of the Sichuan school， capable of generating precise， individualised treatment regimens and thereby advancing an intelligent diagnostic-therapeutic paradigm that delivers more efficient and accurate clinical decision support.

The chronicity of infectious diseases is an important field in the collaborative research of traditional Chinese and Western medicine. The warm disease theory of pathogen invading nutrient and blood aspects in traditional Chinese medicine （TCM） takes the struggle between healthy Qi and pathogenic Qi and cementation of Yin as the core pathogenesis， providing a unique theoretical framework for explaining the common pathology of infectious chronic diseases. This theory originated from Yin-Yang interaction in the Internal Classic and was enriched with WU Youke's theory of intruding pathogen interacting and lingering in blood vessels and YE Tianshi's theory of long-term illness entering collaterals. Combining the theory with modern medical knowledge， our team has condensed the dynamic pathogenesis model of deficiency （nutrient and blood aspects） and excess （pathogen） interacting in the blood collaterals of Yin aspect， the core feature of which is the four-dimensional interactions of cause （pathogen characteristics）， location （three Yin locations of diseases）， nature （deficiency and excess）， and potential （transmission trend）. The common pathology of infectious chronic diseases is reflected in interactions. That is， the interactions between nutrient and blood deficiency （immune exhaustion and metabolic disorder） and pathogen excess （pathogen persistence and fibrous hyperplasia） in the liver collaterals （Jueyin）， kidney collaterals （Shaoyin）， lung collaterals （Taiyin） and other blood collaterals of Yin aspect form the pathological damage characterized by immune inflammatory response-continuous tissue damage with excessive repair. Taking the inheritance and innovative development of classics as the main line， this paper systematically discusses the scientific connotation of the theory of pathogen invading nutrient and blood aspects and the paths of inheritance and innovation and clarifies the original significance of this theory in the chronic development of infectious diseases. Furthermore， taking clinical diseases as an example， this paper reflects the guiding value of this classical theory in the modern diagnosis and treatment of infectious diseases with integrated traditional Chinese and Western medicine and the application potential of this theory in solving complex medical problems through the construction of the innovative paradigm of precise diagnosis and treatment with integrated traditional Chinese and Western medicine.