Bone metastases are a common and serious complication of solid tumors such as breast cancer, prostate cancer, lung cancer, and kidney cancer, and occur at a high rate in patients with advanced cancer. This pathological process not only frequently leads to skeletal-related events such as severe bone pain, pathological fractures, spinal cord compression, and hypercalcemia—conditions that severely impact patients’ quality of life—but may also significantly increase the risk of death. Cancer bone metastasis is a complex, multistage cascade involving key steps such as the detachment of tumor cells from the primary tumor, their invasion and entry into the bloodstream, and their colonization, dormancy, and reactivation within the bone microenvironment. In recent years, exercise—as a safe and easily implementable non-pharmacological intervention—has demonstrated significant potential in inhibiting bone metastasis, improving the bone microenvironment, and alleviating related clinical symptoms. Its mechanisms of action may involve multiple levels. First, at the mechanical load level, mechanical signals generated by exercise can directly act on bone cells, inhibiting tumor cell infiltration and colonization by regulating endothelial cell permeability and osteoclast activity. Second, at the endocrine and paracrine levels, exercise can alter the expression profiles of microRNAs (such as miR-486 and miR-34b) carried by extracellular vesicles and particles (EVPs) in the circulation, thereby inhibiting tumor cell proliferation and migration by targeting cell cycle-related genes. Furthermore, exercise can remodel the immune microenvironment, enhance the cytotoxic activity of antitumor immune cells, and improve oxygen supply to tumor tissues, thereby alleviating hypoxia-induced immunosuppression. Finally, at the metabolic intervention level, exercise can induce systemic metabolic reprogramming, increasing the nutritional demands of normal tissues, thereby competing with tumor cells for nutrients and forming a “metabolic barrier” in distal organs such as bones. This article reviews the pathogenesis and classification of bone metastases, including osteolytic, osteogenic, and mixed types, and elaborates in detail on the complex processes by which tumor cells undergo colonization, dormancy, and reactivation within the bone microenvironment. Furthermore, based on a comprehensive analysis of human and animal studies on exercise interventions for bone metastases, this paper highlights the mechanisms by which exercise inhibits tumor formation, growth, and spread through the regulation of mechanical loading, extracellular vesicles and granules, as well as via immune and metabolic pathways, thereby interfering with bone metastasis. However, the array of exercise modalities and intensities available for patients grappling with the challenges of cancer-related bone metastases remains markedly constrained, and the formulation of tailored exercise prescriptions continues to be devoid of robust, evidence-based medical backing. This review aims to explore the effects of exercise on bone health in patients with bone metastases, analyze the factors and considerations that should be taken into account in exercise prescriptions, and provide new theoretical support and insights for developing personalized exercise programs for these patients and further advancing relevant clinical research. Future research directions should include the development of evidence-based, personalized exercise prescriptions and further clarification of the safety boundaries and best practice standards for exercise interventions, thereby promoting the advancement of relevant clinical research and ultimately improving patients’ clinical outcomes and quality of life.

Developing an intelligent agent for integrated traditional Chinese and western medicine diagnosis and treatment based on clinical practice guidelines is a key approach to advancing the standardization and intelligent deve-lopment of traditional Chinese medicine （TCM） and to supporting clinical decision-making. This paper argues for the necessity of building a knowledge base using guidelines as the sole data source， systematically identifies five core methodological challenges across the entire process， and proposes corresponding solutions. An ontology framework capable of distinguishing between TCM and western medicine concepts should be designed to address the difficulty of knowledge integration. A closed-loop "algorithm-based extraction-expert review" model is adopted to reduce data extraction errors. Expert consensus is incorporated to address decision gaps in specific clinical scenarios outlined in the guidelines， while a multi-stage， standardized output process for the AI system is established to eliminate model hallucinations. Furthermore， an evaluation framework reflecting clinical applicability is developed to enhance the AI system's accuracy and stability. Throughout the research process， it is essential to ensure the in-depth and continuous participation of multidisciplinary experts， strictly control the selection and quality evaluation of guidelines， and rely on the expert consensus method to address decision gaps in the knowledge base. Additionally， continuous validation and iterative optimization of intelligent agents are required to ensure the accuracy and stability of generated outputs. Limitations remain in the mechanisms for real-time knowledge synchronization in intelligent diagnostic and treatment systems， and further validation through large-scale real-world studies is warranted.

ObjectiveTo explore the therapeutic effect of Xuebijing injection （XBJ） on severe acute pancreatitis induced acute lung injury （SAP-ALI） by regulating formyl peptide receptors （FPRs）/nucleotide-binding oligomerization domain-like receptor 3 （NLRP3） inflammatory pathway. MethodsSixty rats were randomly divided into a sham group， a SAP-ALI model group， low-， medium-， and high-dose XBJ groups （4， 8， and 12 mL·kg^-1）， and a positive drug （BOC2， 0.2 mg·kg^-1） group. For the sham group， the pancreas of rats was only gently flipped after laparotomy， and then the abdomen was closed， while for the remaining five groups， SAP-ALI rat models were established by retrograde injection of 5% sodium taurocholate （Na-Tc） via the biliopancreatic duct. XBJ and BOC2 were administered via intraperitoneal injection once daily for 3 d prior to modeling and 0.5 h after modeling. Blood was collected from the abdominal aorta 6 h after the completion of modeling， and the expression of interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） in plasma was measured by enzyme-linked immunosorbent assay （ELISA）. The amount of ascites was measured， and the dry-wet weight ratios of pancreatic and lung tissue were determined. Pancreatic and lung tissue was taken for hematoxylin-eosin （HE） staining to observe pathological changes and then scored. The protein expression levels of FPR1， FPR2， and NLRP3 in lung tissue were detected by the immunohistochemical method. Western blot was used to detect the expression of FPR1， FPR2， and NLRP3 in lung tissue. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of FPR1， FPR2， and NLRP3 in lung tissue. ResultsCompared with the sham group， the SAP-ALI model group showed significantly decreased dry-wet weight ratio of lung tissue （P<0.01）， serious pathological changes of lung tissue， a significantly increased pathological score （P<0.01）， and significantly increased protein and mRNA expression levels of FPR1， FPR2， and NLRP3 in lung tissue （P<0.01）. After BOC2 intervention， the above detection indicators were significantly reversed （P<0.01）. After treatment with XBJ， the groups of different XBJ doses achieved results consistent with BOC2 intervention. ConclusionXBJ can effectively improve the inflammatory response of the lungs in SAP-ALI rats and reduce damage. The mechanism may be related to inhibiting the expression of FPRs and NLRP3 in lung tissue， which thereby reduces IL-1β and simultaneously antagonize the release of inflammatory factors IL-6 and TNF-α.

ObjectiveBased on functional near-infrared spectroscopy (fNIRS), we investigated the brain activity characteristics of gross motor tasks in children with autism spectrum disorder (ASD) and motor dysfunctions (MDs) to provide a theoretical basis for further understanding the mechanism of MDs in children with ASD and designing targeted intervention programs from a central perspective. MethodsAccording to the inclusion and exclusion criteria, 48 children with ASD accompanied by MDs were recruited into the ASD group and 40 children with typically developing (TD) into the TD group. The fNIRS device was used to collect the information of blood oxygen changes in the cortical motor-related brain regions during single-handed bag throwing and tiptoe walking, and the differences in brain activation and functional connectivity between the two groups of children were analyzed from the perspective of brain activation and functional connectivity. ResultsCompared to the TD group, in the object manipulative motor task (one-handed bag throwing), the ASD group showed significantly reduced activation in both left sensorimotor cortex (SMC) and right secondary visual cortex (V2) (P<0.05), whereas the right pre-motor and supplementary motor cortex (PMC&SMA) had significantly higher activation (P<0.01) and showed bilateral brain region activity; in terms of brain functional integration, there was a significant decrease in the strength of brain functional connectivity (P<0.05) and was mainly associated with dorsolateral prefrontal cortex (DLPFC) and V2. In the body stability motor task (tiptoe walking), the ASD group had significantly higher activation in motor-related brain regions such as the DLPFC, SMC, and PMC&SMA (P<0.05) and showed bilateral brain region activity; in terms of brain functional integration, the ASD group had lower strength of brain functional connectivity (P<0.05) and was mainly associated with PMC&SMA and V2. ConclusionChildren with ASD exhibit abnormal brain functional activity characteristics specific to different gross motor tasks in object manipulative and body stability, reflecting insufficient or excessive compensatory activation of local brain regions and impaired cross-regions integration, which may be a potential reason for the poorer gross motor performance of children with ASD, and meanwhile provides data support for further unraveling the mechanisms underlying the occurrence of MDs in the context of ASD and designing targeted intervention programs from a central perspective.

Ganoderic acid is a class of lanostane-type triterpenoids found in Ganoderma species, and is one of the most important pharmacologically active components in G. lucidum, exhibiting antioxidant, anti-neuropsychiatric, anti-tumor, and immune-enhancing properties. The content of ganoderic acid in G. lucidum is very low, and the traditional extraction process is complex, yielding minimal amounts at high cost. The biosynthetic pathway of G. lucidum triterpenoids(GLTs), including the synthesis of different structural forms of ganoderic acid from lanosterol, as well as the molecular regulatory mechanisms involving key regulatory enzyme genes and their functions, are not yet fully understood. With the continuous development of synthetic biology technologies, there has been a deeper understanding of the biosynthesis and metabolic regulation pathways of ganoderic acid and its derivatives at the molecular level. Research has explored the key regulatory enzyme genes related to ganoderic acid biosynthesis and their functions. Moreover, through the optimization of synthetic biology and culture conditions, large-scale production and preparation of GLTs at the cellular level have been achieved. This paper reviews and analyzes the latest research progress on the biosynthesis pathways and metabolic regulation of GLTs, focusing on the configuration of ganoderic acid and its derivatives, the biosynthetic pathways, key enzyme genes, transcription factors related to ganoderic acid biosynthesis, signal transduction mechanisms, and factors affecting triterpenoid biotransformation. This review is expected to provide a theoretical basis and technical reference for improving the efficient production of triterpenoid pharmacological components and the exploitation and utilization of G. lucidum resources.
Triterpenes/chemistry* ; Reishi/chemistry* ; Biosynthetic Pathways ; Lanosterol

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To analyze the clinical characteristics and cytokines expression characteristics in infants with mild and severe respiratory syncytial virus (RSV) infection.Methods:From May 2023 to December 2023, plasma samples and clinical information were collected from 16 infants with RSV infection and 14 control infants. Cytek Aurora flow cytometry (Cytek, America) and Enzyme linked immunosorbent assay (ELISA) were used to detect the expression levels of 25 cytokines after mild and severe RSV infection.Results:Cough and nasal obstruction were the main clinical manifestations in infants with mild RSV infection, accompanied by polypnea, wheezing and other symptoms. The main symptoms of severe RSV infection were cough and rales, accompanied by fever and polypnea. In comparison with the control group, the expression levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-13, IL-22, TNF-α, IFN-α, IFN-β, MIP-1β, I-TAC, ENA-78, GROα, Eotaxin, and MCP-1 in the RSV infection group all exhibited an upregulation trend. Both IP-10 and MIP-3α demonstrated a downward trend in the RSV infection group; however, there was no statistically significant difference ( P>0.05). The levels of IL-10, IFN-γ, MIP-1α, and IL-8 in the RSV infection group were significantly higher than those in the control group, whereas the levels of MIG, TARC, and RANTES in the RSV infection group were significantly lower than those in the control group ( P<0.05). The levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-13, IL-22, IFN-β, IFN-γ, TNF-α, IL-8, I-TAC, MIP-1β, Eotaxin, and MCP-1 in the mild RSV infection group were significantly higher than those in the severe RSV infection group ( P>0.05). Among these, the levels of MIG, RANTES, TARC, MIP-3α, and ENA-78 in the mild infection group were all lower than those in the severe infection group. The expressions of ENA-78 and MIP-1α in the severe infection group were significantly higher than those in the mild infection group and also higher than those in the control group. There was no significant difference in IP-10 and GROα between the mild and severe RSV infection groups ( P>0.05). Conclusions:The differences in clinical features and cytokines between infants with mild and severe RSV infection provide important data support for the prevention and treatment of RSV infection in infants.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

This study was aimed at developing an in vitro fluorescent substrate assay for the activity of leucyl aminopeptid-ase(LAP)from Echinococcus multilocularis and comparing it with the chemical chromogenic substrate enzyme activity assay.Through the establishment of reaction conditions for the fluorescent substrate-based in vitro enzyme activity assay,we com-pared the differences between the fluorescent substrate L-Leucine-7-amido-4-methylocoumarin(Leu-AMC)and the chemical chromogenic substrate L-Leucine-4-nitroanilide(Leu-pNA)through molecular docking,inhibition rates,and precision measures.Molecular docking revealed that the fluorescent substrate Leu-AMC had higher affinity for the protein than the chemical chromogenic substrate Leu-pNA.Through analysis of the effects of varying reaction conditions on fluorescence intensi-ty,we optimized the fluorescent substrate enzyme activity assay to demonstrate favorable performance at a reaction temperature of 37℃,a pH of 9.0,a protein concentration of 800 nmol/L,and a reaction duration of 60 minutes.Leu-AMC exhibited significant and distinct responses at a 5 μmol/L substrate concentration,under varying substrate conditions.The fluo-rescent substrate assay demonstrated more significant intergroup differences than the chemical chromogenic substrate assay when various inhibitors were added.This study established a fluorescence-based enzyme activity assay for leucyl aminopeptidase from Echinococcus multilocularis by using Leu-AMC as the substrate;this method demonstrated a more significant intergroup difference and sensitivity than the chemical chromogenic substrate assay.