ObjectiveTo address the limitations of the current quality standard for Polygalae Radix（PR）， which relies on a single component for quality assessment and struggles to holistically control its intrinsic quality， by constructing a comprehensive quality evaluation system integrating "macro-characterization of chemical profile， synchronous quantification of multiple index components， and quantitative analysis of multi-components by single marker（QAMS） for key component groups". This study aims to facilitate the scientific revision of the quality standard for PR. MethodsHigh performance liquid chromatography（HPLC） characteristic chromatograms were established for 11 batches of PR medicinal materials（YZ）， 10 batches of PR decoction pieces（YP）， and 10 batches of licorice-processed PR decoction pieces（ZYZ）， followed by similarity evaluation and identification of common peaks. HPLC-QAMS was developed for xanthones（sibiricaxanthone B， polygalaxanthone Ⅺ， polygalaxanthone Ⅲ） in the characteristic chromatograms. Simultaneously， the external standard method（ESM） was used to determine the contents of the corresponding xanthones and 3，6'-disinapoyl sucrose in YZ， YP， and ZYZ， followed by multivariate statistical analysis and Spearman correlation analysis. ResultsThe similarity between the characteristic chromatograms of 31 batches of PR samples and the reference chromatogram was>0.9. A total of 13 common peaks were identified， and 10 of these peaks were characterized through reference standard comparison. The successfully constructed QAMS method showed that the relative correction factors（RCFs） of sibiricaxanthone B and polygalaxanthone Ⅺ to polygalaxanthone Ⅲ were 0.76 and 0.88， and their relative retention times（RRTs） were 0.85 and 0.97， respectively. The results calculated by the QAMS method showed no significant difference from those obtained by the ESM. According to the limit standard for polygalaxanthone Ⅲ in the 2020 edition of the Pharmacopoeia of the People's Republic of China（hereinafter referred to as the Chinese Pharmacopoeia）， the pass rate of 31 batches of samples was only 19.35%. Multivariate statistical analysis indicated certain compositional differences between different batches of YZ and YP， as well as between YP and ZYZ， with 3，6'-disinapoyl sucrose identified as the main differentiating component. Furthermore， correlation analysis revealed that the content of polygalaxanthone Ⅲ was positively correlated with the contents of sibiricaxanthone B and polygalaxanthone Ⅺ， but showed no association with the content of 3，6'-disinapoyl sucrose. ConclusionIt is recommended that the content limit for polygalaxanthone Ⅲ in YZ，YP and ZYZ be revised to not less than 0.07%， or the total content of polygalaxanthone Ⅲ， sibiricaxanthone B and polygalaxanthone Ⅺ be not less than 0.18%. The newly established triple quality control model of "holistic control via characteristic chromatograms， precise quantification of oligosaccharide esters， and efficient detection of xanthones by QAMS" provides a systematic and precise solution for quality evaluation of PR and similar Chinese herbal medicines.

Background The quality of occupational health technical services is directly linked to the protection of workers' health rights and the efficacy of occupational disease prevention and control. However, the industry still faces critical challenges: sporadic instances of institutional non-compliance and persistent irregularities in professional practice continue to undermine overall service performance. Objective To assess the current quality status of occupational health technical services in Zhejiang Province and propose countermeasures for quality improvement, providing a scientific basis for policy optimization and service delivery quality enhancement. Methods A total of 69 occupational health technical service institutions in Zhejiang Province that obtained formal accreditation as of April 30, 2024, were sampled, including 3 public institutions and 66 private institutions (comprising 3 formerly Class-A, 28 formerly Class-B, 11 formerly Class-C, and 24 newly certified institutions). Following the Technical Protocol for Quality Monitoring of Occupational Health Technical Service in Zhejiang Province and the Technical Protocol for Proficiency Testing of Occupational Health Detection in Zhejiang Province, a quality assessment task force comprising national and provincial experts was established. Evaluation was conducted across four dimensions: qualification maintenance and compliance, standardization of technical services, authenticity of technical services, and proficiency testing, utilizing a combination of document review, on-site inspections, and technical skill assessments. Results The occupational health technical service institutions in Zhejiang Province were predominantly private entities (82.5%), with significant disparities in overall service quality. The pass rates for qualification maintenance and compliance, technical service standardization, technical service authenticity, and the excellence rate for laboratory proficiency testing were 81.5%, 80.7%, 97.3%, and 90.4%, respectively. Regarding qualification maintenance, the pass rates for "environmental conditions" (49.8%, 56.7%) and "instrumentation and equipment" (58.2%、65.6%) were significantly lower for formerly Class-C and newly certified institutions compared to other categories. In terms of technical standardization, "standardized on-site inspections" recorded the lowest pass rate (67.4%), with newly certified institutions at only 48.0%. Regarding technical service authenticity, formerly Class-C institutions exhibited issues such as missing raw chromatograms for blank samples (85.7% pass rate). In laboratory proficiency testing, public and formerly Class-A institutions achieved 100% excellence rates, but the performance of formerly Class-C and newly certified institutions was comparatively weak; specifically, the failure rate for organic analysis in formerly Class-C institutions reached 20%; the failure rate for dust testing items in newly certified institutions was 10.3%. Conclusion The overall quality of occupational health technical services in Zhejiang Province still requires significant improvement, particularly in basic institutional conditions, the standardization of on-site inspections, and laboratory proficiency in organic and dust analysis. Formerly Class-C and newly certified institutions should be the primary focus of quality management efforts. Differentiated regulatory strategies are recommended, alongside strengthening interim and ex-post supervision to gradually enhance the quality of occupational health technical services across all institutions.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

Preeclampsia (PE) is a severe gestational disorder characterized by hypertension and proteinuria, with a subset of cases exhibiting an immune-driven phenotype marked by placental overexpression of proinflammatory cytokines and chronic inflammatory damage, profoundly impacting fetal development. To elucidate the pathophysiology of this PE subtype, we established an inflammation-driven PE mouse model via lipopolysaccharide (LPS) intraperitoneal injection, systematically evaluating histopathological changes in maternal heart, liver, lung, kidney, and placenta, and integrating transcriptomic profiling to uncover molecular mechanisms. LPS administration robustly induced maternal hypertension and proteinuria, hallmarks of PE, without significantly altering organ or fetal weights. Histological analyses revealed pronounced inflammatory damage in the maternal lung, kidney, and placenta, with the lung exhibiting the most severe pathology, characterized by inflammatory cell infiltration, alveolar wall thickening, and interstitial edema-challenging the conventional focus on placental and renal primacy in PE. Placental labyrinth and junctional zones displayed extensive structural disruption and necrosis, indicating functional impairment. Transcriptomic analysis identified 27 inflammation-related genes consistently upregulated across tissues, with protein-protein interaction networks pinpointing Il1β, Il6, Ccl5, Ccl2, Cxcl10, Tlr2, and Icam1 as hub genes. Quantitative PCR validation confirmed Tlr2 as a central regulator, evidenced by significant upregulation of Tlr2 in lung, kidney, and placenta of LPS-induced PE mice, while Cxcl10 exhibited placenta-specific upregulation, suggesting a synergistic inflammatory axis in placental pathology. These findings highlight the lung as a critical, yet underappreciated, target in inflammation-driven PE, reframe the multi-organ inflammatory landscape of the disease, and nominate Tlr2 and Cxcl10 as potential diagnostic biomarkers and therapeutic targets, offering new avenues for precision intervention in PE.
Animals ; Female ; Pregnancy ; Mice ; Pre-Eclampsia/genetics* ; Inflammation ; Lipopolysaccharides/adverse effects* ; Disease Models, Animal ; Transcriptome ; Placenta/pathology* ; Phenotype

Moringa oleifera, widely utilized in Ayurvedic medicine, is recognized for its leaves, seeds, and velamen possessing traditional effects such as vātahara(wind alleviation), sirovirecaka(brain clearing), and hridya(mental nourishment). This study aims to identify the medicinal part of ■ in the Sārasvata ghee formulation as described in the Bower Manuscript, while investigating the ameliorative effects of different medicinal parts of M. oleifera on learning and memory deficits in mice and elucidating the underlying molecular mechanisms. A total of 144 male ICR mice were randomly assigned to the following groups: control, model(scopolamine hydrobromide, Sco, 2 mg·kg~(-1)), donepezil(donepezil hydrochloride, Don, 3 mg·kg~(-1)), M. oleifera leaf low-, medium-, and high-dose groups(0.5, 1, 2 g·kg~(-1)), M. oleifera seeds low-, medium-, and high-dose groups(0.25, 0.5, 1 g·kg~(-1)), and M. oleifera velamen low-, medium-, and high-dose groups(0.31, 0.62, 1.24 g·kg~(-1)). Learning and memory abilities were assessed using the passive avoidance test and Morris water maze. Nissl and HE staining were employed to examine histopathological changes in the hippocampus. Transcriptomics and targeted metabolomics were used to screen differential genes and metabolites, with MetaboAnalyst 6.0 and O2PLS methods applied to identify key disease-related targets and pathways. RESULTS:: demonstrated that M. oleifera leaf(1 g·kg~(-1)) significantly ameliorated Sco-induced learning and memory deficits, outperforming M. oleifera seeds(0.25 g·kg~(-1)) and M. oleifera velamen(1.24 g·kg~(-1)). This was evidenced by improved behavioral performance, reversal of neuronal damage, and reduced acetylcholinesterase(AChE) activity. Multi-omics analysis revealed that M. oleifera leaf upregulated Tuba1c gene expression through the synaptic vesicle cycle, enhancing glutamate(Glu), dopamine(DA), and acetylcholine(ACh) release via Tuba1c-Glu associations for neuroprotection. M. oleifera seeds targeted the dopaminergic synapse pathway, promoting memory consolidation through Drd2-ACh associations. M. oleifera velamen was associated with the cocaine addiction pathway, modulating dopamine metabolism via Adora2a-DOPAC, with limited relevance to learning and memory. In conclusion, M. oleifera leaf exhibits superior efficacy and mechanistic advantages over M. oleifera seeds and velamen, suggesting that the ■ in the Sārasvata ghee formulation is likely M. oleifera leaf, providing scientific evidence for its identification in ancient texts.
Animals ; Moringa oleifera/chemistry* ; Male ; Mice ; Seeds/chemistry* ; Plant Leaves/chemistry* ; Mice, Inbred ICR ; Memory Disorders/psychology* ; Transcriptome/drug effects* ; Memory/drug effects* ; Learning/drug effects* ; Metabolomics ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Maze Learning/drug effects*

Microbial detection and control of traditional Chinese medicine(TCM) decoction pieces are crucial for the quality control of TCM preparations. It is also a key area of research in the measurement technology and equipment development for TCM manufacturing. Guided by TCM manufacturing measurement methodologies, this study presented a design of a novel portable microbial detection device, using Atractylodis Macrocephalae Rhizoma decoction pieces as a demonstration. Immunomagnetic separation technology was employed for specific isolation and labeling of target microorganisms. Enzymatic signal amplification was utilized to convert weak biological signals into colorimetric signals, constructing an optical biosensor. A self-developed smartphone APP was further applied to analyze the colorimetric signals and quantify target concentrations. A portable and automated detection system based on Arduino microcontroller was developed to automatically perform target microbial separation/extraction, as well as mimetic enzyme labeling and catalytic reactions. The developed equipment specifically focuses on the rapid and quantitative microbial analysis of TCM active pharmaceutical ingredients, intermediates in TCM manufacturing, and final TCM products. Experimental results demonstrate that the equipment could detect Salmonella in samples within 2 h, with a detection limit as low as 5.1 × 10~3 CFU·mL~(-1). The equipment enables the rapid detection of microorganisms in TCM decoction pieces, providing a potential technical solution for on-site rapid screening of microbial contamination indicators in TCM. It has broad application prospects in measurement technology for TCM manufacturing and offers strong technical support for the modernization, industrialization, and intelligent development of TCM.
Drugs, Chinese Herbal/analysis* ; Atractylodes/microbiology* ; Rhizome/microbiology* ; Biosensing Techniques/methods* ; Medicine, Chinese Traditional ; Colorimetry/instrumentation* ; Quality Control

OBJECTIVE: To explore the co-morbid influencing factors of postmenopausal osteoporosis(PMOP) and dyslipidemia, and to provide evidence-based basis for clinical co-morbidity management. METHODS: Based on the 2017 to 2018 Beijing community cross-sectional survey data, PMOP patients were included and divided into the dyslipidemia group and the uncomplicated dyslipidemia group according to whether they were comorbid with dyslipidemia. Demographic characteristics, living habits and disease history were collected through questionnaires, and bone mineral density and bone metabolism biomarkers (osteocalcin, blood calcium, serum typeⅠprocollagen N-terminal prepeptide, etc.) were detected on site. Co-morbidity risk factors were analyzed using binary logistic regression. RESULTS: Three hundred and twenty patients with PMOP were included, including the comorbid group (75 patients) and the uncomplicated group (245 patients). The results showed that history of cardiovascular disease [OR=1.801, 95%CI(1.003, 3.236), P=0.049], history of cerebrovascular disease [OR=2.923, 95%CI(1.460, 5.854), P=0.002], frying and cooking methods[OR=5.388, 95%CI(1.632, 17.793), P=0.006], OST results[OR=0.910, 95%CI(0.843, 0.983), P=0.016], and blood Ca results [OR=60.249, 95%CI(1.862, 1 949.926), P=0.021] were the influencing factors of PMOP complicated with dyslipidemia. CONCLUSION Focus should be placed on the influencing factors of PMOP and dyslipidemia co-morbidities, with emphasis on multidimensional assessment, combining lifestyle interventions with bone metabolism marker monitoring to optimize co-morbidity management.
Humans ; Dyslipidemias/epidemiology* ; Female ; Middle Aged ; Osteoporosis, Postmenopausal/metabolism* ; Aged ; Cross-Sectional Studies ; Risk Factors ; Bone Density