This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

OBJECTIVE To investigate the effects and mechanisms of Lycium ruthenicum Murr. in improving sleep. METHODS Network pharmacology was employed to identify the active components of L. ruthenicum and their associated disease targets， followed by enrichment analysis. A caffeine‑induced zebrafish model of sleep deprivation was established ， and the zebrafish were treated with L. ruthenicum Murr. extract （LRME） at concentrations of 0.1， 0.2 and 0.4 mg/mL， respectively； 24 h later， behavioral changes of zebrafish and pathological alterations in brain neurons were subsequently observed. The levels of inflammatory factors [interleukin-6 （IL-6）， IL-1β， IL-10， tumor necrosis factor-α （TNF-α）]， oxidative stress markers [superoxide dismutase （SOD）， malondialdehyde （MDA）， glutathione peroxidase （GSH-Px）， catalase （CAT）]， and neurotransmitters [5- hydroxytryptamine （5-HT）， γ-aminobutyric acid （GABA）， glutamic acid （Glu）， dopamine （DA）， and norepinephrine （NE）] were measured. The protein expression levels of protein kinase B1 （AKT1）， phosphorylated AKT1 （p-AKT1）， epidermal growth factor receptor （EGFR）， B-cell lymphoma 2 （Bcl-2）， sarcoma proto-oncogene，non-receptor tyrosine kinase （SRC）， and heat shock protein 90α family class A member 1 （HSP90AA1） in the zebrafish were also determined. RESULTS A total of 12 active components and 176 intersecting disease targets were identified through network pharmacology analysis. Among these， apigenin， naringenin and others were recognized as core active compounds， while AKT1， EGFR and others served as key targets； EGFR tyrosine kinase inhibitor resistance signaling pathway was identified as the critical pathway. The sleep improvement rates in zebrafish of LRME low-， medium-， and high-dose groups were 54.60%， 69.03% and 77.97%， 开发。E-mail：hjp_yft@163.com respectively， while the inhibition ratios of locomotor distance were 0.57， 0.83 and 0.95， respectively. Compared with the model group， the number of resting counts， resting time and resting distance were significantly increased/extended in LRME medium- and high-dose groups （P＜0.05）. Neuronal damage in the brain was alleviated. Additionally， the levels of IL-6， IL-1β， TNF-α， MDA， Glu， DA and NE， as well as the protein expression levels of AKT1， p-AKT1， EGFR， SRC and HSP90AA1， were markedly reduced （P＜0.05）， while the levels of IL-10， SOD， GSH-Px， CAT， 5-HT and GABA， as well as Bcl-2 protein expression， were significantly elevated （P＜0.05）. CONCLUSIONS L. ruthenicum Murr. demonstrates sleep-improving effects， and its specific mechanism may be related to the regulation of inflammatory responses， oxidative stress， neurotransmitter balance， and the EGFR tyrosine kinase inhibitor resistance signaling pathway.

Collagen is a major structural protein in the matrix of animal cells and the most widely distributed and abundant functional protein in mammals. Collagen’s good biocompatibility, biodegradability and biological activity make it a very valuable biomaterial. According to the source of collagen, it can be broadly categorized into two types: one is animal collagen; the other is recombinant collagen. Animal collagen is mainly extracted and purified from animal connective tissues by chemical methods, such as acid, alkali and enzyme methods, etc. Recombinant collagen refers to collagen produced by gene splicing technology, where the amino acid sequence is first designed and improved according to one’s own needs, and the gene sequence of improved recombinant collagen is highly consistent with that of human beings, and then the designed gene sequence is cloned into the appropriate vector, and then transferred to the appropriate expression vector. The designed gene sequence is cloned into a suitable vector, and then transferred to a suitable expression system for full expression, and finally the target protein is obtained by extraction and purification technology. Recombinant collagen has excellent histocompatibility and water solubility, can be directly absorbed by the human body and participate in the construction of collagen, remodeling of the extracellular matrix, cell growth, wound healing and site filling, etc., which has demonstrated significant effects, and has become the focus of the development of modern biomedical materials. This paper firstly elaborates the structure, type, and tissue distribution of human collagen, as well as the associated genetic diseases of different types of collagen, then introduces the specific process of producing animal source collagen and recombinant collagen, explains the advantages of recombinant collagen production method, and then introduces the various systems of expressing recombinant collagen, as well as their advantages and disadvantages, and finally briefly introduces the application of animal collagen, focusing on the use of animal collagen in the development of biopharmaceutical materials. In terms of application, it focuses on the use of animal disease models exploring the application effects of recombinant collagen in wound hemostasis, wound repair, corneal therapy, female pelvic floor dysfunction (FPFD), vaginal atrophy (VA) and vaginal dryness, thin endometritis (TE), chronic endometritis (CE), bone tissue regeneration in vivo, cardiovascular diseases, breast cancer (BC) and anti-aging. The mechanism of action of recombinant collagen in the treatment of FPFD and CE was introduced, and the clinical application and curative effect of recombinant collagen in skin burn, skin wound, dermatitis, acne and menopausal urogenital syndrome (GSM) were summarized. From the exploratory studies and clinical applications, it is evident that recombinant collagen has demonstrated surprising effects in the treatment of all types of diseases, such as reducing inflammation, promoting cell proliferation, migration and adhesion, increasing collagen deposition, and remodeling the extracellular matrix. At the end of the review, the challenges faced by recombinant collagen are summarized: to develop new recombinant collagen types and dosage forms, to explore the mechanism of action of recombinant collagen, and to provide an outlook for the future development and application of recombinant collagen.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

ObjectiveTo explore the effectiveness of health information dissemination and its influencing factors using the "Shanghai CDC" WeChat public account as a case study, providing references for public health institutions to optimize the use of official new media platforms for effective publicity. MethodsA total of 1 030 headline articles published on the "Shanghai CDC" WeChat public account between 2016 and 2019 were analyzed using content analysis and non-parametric tests to examine the impact of factors such as titles and content categories. ResultsFrom 2016 to 2019, the number of WeChat public account followers increased by 280 000, with the articles accumulating over 8.8 million views. The median (P₂₅, P₇₅) open rate of articles was 5.90% (3.69%, 10.31%), and the median (P₂₅, P₇₅) sharing and forwarding rate was 6.60% (4.25%, 9.17%). Factors such as the use of first- and second-person pronouns, degree adverbs, negative adverbs, explicit viewpoints, and title length all significantly affected the open rate of articles, with OR (95%CI) values of 0.175 (0.041‒0.756), 32.606 (2.350‒452.432), 4.079 (1.093‒15.230), 0.106 (0.028‒0.409), and 1.184 (1.063‒1.319),respectively (all P<0.05). In terms of content, statistical significant differences in dissemination effectiveness were observed across article categories and themes (P<0.05). In terms of article categories, articles related to news hotspots and service information had higher open rates of 9.58% and 14.00%, respectively. These two types of articles also obtained higher sharing and forwarding rates of 7.65% and 9.16%, respectively. In terms of article topics, compared with healthy life and health products, among the top four topics in terms of publication volume, the open rates of articles about infectious diseases and disease-causing biology and immunization programs were higher, accounting for 7.88% and 6.88%, respectively, with no significant difference in sharing and forwarding rates. ConclusionThe "Shanghai CDC" WeChat public account demonstrated good dissemination effectiveness. Enhancing article titles by increasing informational content and degree adverbs (e.g., "highly," "most," and "extremely") and negative adverbs (e.g., "no") can improve dissemination reach. Public health WeChat accounts should incorporate news hotspots or service information in their articles. While maintaining their strengths in disseminating knowledge on infectious diseases and immunization programs, they should also enhance public education in other professional fields within their scope of responsibility to improve the overall dissemination impact of health information.

The worksite survey of occupational disease diagnosis is a series of occupational health investigations in the workplace initiated by the occupational disease diagnosis institution or the public health administrative department in order to understand whether there is a causal relationship between the workers' diseases and the workplace in the process of occupational disease diagnosis and verification. The main purpose of the worksite survey is to find out whether there are occupational hazards that cause health damage to workers in the workplace, and to analyze whether there is a causal relationship between the exposure to occupational hazards at the corresponding concentration (intensity) and the diseases suffered by workers. In actual work, it is necessary to determine whether it is necessary to organize worksite survey according to the legal situation and actual work of occupational disease diagnosis. The mainly works of worksite survey includes three aspects: preliminary preparation, survey implementation and survey report writing. It is necessary to pay attention to the key and difficult tasks such as preparation before survey, survey plan and questionnaire, complexity and uncertainty of worksite survey and sampling and detection of occupational hazard factors in workplace. After the worksite survey,it is necessary to write a written occupational disease on-site investigation report to provide objective, reliable and scientific evidence for occupational disease diagnosis.

Background: This study aimed to estimate temporal trends in metabolically unhealthy obesity (MUO) among United States (US) adults by age, sex, race/ethnicity, and income from 1999 to 2018. Methods: We included 17,230 non-pregnant adults from a nationally representative cross-sectional study, the National Health and Nutrition Examination Survey (NHANES). MUO was defined as body mass index ≥30 kg/m2 with any metabolic disorders in blood pressure, blood glucose, and blood lipids. The age-adjusted percentage of MUO was calculated, and linear regression models estimated trends in MUO. Results: The weighted mean age of adults was 47.28 years; 51.02% were male, 74.64% were non-Hispanic White. The age-adjusted percentage of MUO continuously increased in adults across all subgroups during 1999–2018, although with different magnitudes (all P<0.05 for linear trend). Adults aged 45 to 64 years consistently had higher percentages of MUO from 1999–2000 (34.25%; 95% confidence interval [CI], 25.85% to 42.66%) to 2017–2018 (42.03%; 95% CI, 35.09% to 48.97%) than the other two age subgroups (P<0.05 for group differences). The age-adjusted percentage of MUO was the highest among non-Hispanic Blacks while the lowest among non-Hispanic Whites in most cycles. Adults with high-income levels generally had lower MUO percentages from 1999–2000 (22.63%; 95% CI, 17.00% to 28.26%) to 2017–2018 (32.36%; 95% CI, 23.87% to 40.85%) compared with the other two subgroups. Conclusion This study detected a continuous linear increasing trend in MUO among US adults from 1999 to 2018. The persistence of disparities by age, race/ethnicity, and income is a cause for concern. This calls for implementing evidence-based, structural, and effective MUO prevention programs.

Background: and Purpose Limited evidence exists on the effectiveness of endovascular treatment (EVT) for acute posterior circulation tandem lesion (PCTL). This study aimed to explore the role of extracranial vertebral artery (VA) stenting in patients with PCTL stroke undergoing EVT. Methods: Individual patient data were pooled from the BASILAR (EVT for Acute Basilar Artery Occlusion Study) and PERSIST (Posterior Circulation Ischemic Stroke) registries. Patients with PCTLs who underwent EVT were included in the present cohort and divided into the stenting and nonstenting groups based on the placement of extracranial VA stents. The primary efficacy outcome was the modified Rankin Scale (mRS) scores at 90 days and 1 year. Safety outcomes included 24-hour symptomatic intracranial hemorrhage (sICH) and all-cause mortality at 90 days and 1 year post-surgery. Results: A combined dataset of 1,320 patients with posterior circulation artery occlusion, including 263 (19.9%) with tandem lesions, of whom 217 (median age, 65 years; 82.9% male) met the inclusion criteria for the analysis. The stenting group had 84 (38.7%) patients, while the non-stenting group had 133 (61.3%). After adjustment for the potential confounders, extracranial VA stenting was associated with favorable shifts in mRS scores at both 90 days (adjusted common odds ratio [OR], 2.30; 95% confidence interval [CI], 1.23–4.28; P<0.01) and 1 year (adjusted OR [aOR], 2.04; 95% CI [1.05–3.97]; P=0.04), along with lower rate of mortality at both 90 days (aOR, 0.45; 95% CI [0.21–0.93]; P=0.01) and 1 year (aOR, 0.36; 95% CI [0.16–0.79]; P=0.01), with no significant difference in sICH incidence (aOR, 0.35; 95% CI [0.06–1.98]; P=0.24). Conclusion Extracranial VA stenting during EVT may improve functional outcomes and reduce mortality in patients with PCTL strokes.

Background: This study aimed to estimate temporal trends in metabolically unhealthy obesity (MUO) among United States (US) adults by age, sex, race/ethnicity, and income from 1999 to 2018. Methods: We included 17,230 non-pregnant adults from a nationally representative cross-sectional study, the National Health and Nutrition Examination Survey (NHANES). MUO was defined as body mass index ≥30 kg/m2 with any metabolic disorders in blood pressure, blood glucose, and blood lipids. The age-adjusted percentage of MUO was calculated, and linear regression models estimated trends in MUO. Results: The weighted mean age of adults was 47.28 years; 51.02% were male, 74.64% were non-Hispanic White. The age-adjusted percentage of MUO continuously increased in adults across all subgroups during 1999–2018, although with different magnitudes (all P<0.05 for linear trend). Adults aged 45 to 64 years consistently had higher percentages of MUO from 1999–2000 (34.25%; 95% confidence interval [CI], 25.85% to 42.66%) to 2017–2018 (42.03%; 95% CI, 35.09% to 48.97%) than the other two age subgroups (P<0.05 for group differences). The age-adjusted percentage of MUO was the highest among non-Hispanic Blacks while the lowest among non-Hispanic Whites in most cycles. Adults with high-income levels generally had lower MUO percentages from 1999–2000 (22.63%; 95% CI, 17.00% to 28.26%) to 2017–2018 (32.36%; 95% CI, 23.87% to 40.85%) compared with the other two subgroups. Conclusion This study detected a continuous linear increasing trend in MUO among US adults from 1999 to 2018. The persistence of disparities by age, race/ethnicity, and income is a cause for concern. This calls for implementing evidence-based, structural, and effective MUO prevention programs.