ObjectiveBased on traditional quality evaluation of Gardeniae Fructus（GF） recorded in historical materia medica， this study systematically compared the quality differences between wild and cultivated GF from morphological characteristics， microscopic features， and contents of primary and secondary metabolites. MethodsVernier calipers and analytical balances were used to measure the length， diameter and individual fruit weight of wild and cultivated GF， and the aspect ratio was calculated. A colorimeter was used to determine the chromaticity value of wild and cultivated GF， and the paraffin sections of them were prepared by safranin-fast green staining and examined under an optical microscope to observe their microstructure. Subsequently， the contents of water-soluble and alcohol-soluble extracts of wild and cultivated GF were detected by hot immersion method under the general rule 2201 in volume Ⅳ of the 2020 edition of the Pharmacopoeia of the People's Republic of China， the starch content was measured by anthrone colorimetric method， the content of total polysaccharides was determined by phenol-sulfuric acid colorimetric method， the sucrose content was determined by high performance liquid chromatography coupled with evaporative light scattering detection（HPLC-ELSD）， and the contents of representative components in them were measured by ultra-performance liquid chromatography（UPLC）. Finally， correlation analysis was conducted between quality traits and phenotypic traits， combined with multivariate statistical analysis methods such as principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， key differential components between wild and cultivated GF were screened. ResultsIn terms of traits， the wild GF fruits were smaller， exhibiting reddish yellow or brownish red hues with significant variation between batches. While the cultivated GF fruits are larger， displaying deeper orange-red or brownish red. The diameter and individual fruit weight of cultivated GF were significantly greater than those of wild GF， while the blue-yellow value（b^*） of wild GF was significantly higher than that of cultivated GF. In the microstructure， the mesocarp of wild GF contained numerous scattered calcium oxalate cluster crystals， while the endocarp contained stone cell class round， polygonal or tangential prolongation， undeveloped seeds were visible within the fruit. In contrast， the mesocarp of cultivated GF contained few calcium oxalate cluster crystals， or some batches exhibited extremely numerous cluster crystals. The stone cells in the endocarp were predominantly round-like， with the innermost layer arranged in a grid pattern. Seeds were basically mature， and only a few immature seeds existed in some batches. Regarding primary metabolite content， wild GF exhibited significantly higher total polysaccharide level than cultivated GF（P<0.01）. In category-specific component content， wild GF exhibited significantly higher levels of total flavonoids and total polyphenols compared to cultivated GF（P<0.01）. Analysis of 12 secondary metabolites revealed that wild GF exhibited significantly higher levels of Shanzhiside， deacetyl asperulosidic acid methyl ester， gardenoside and chlorogenic acid compared to cultivated GF（P<0.01）. Conversely， the contents of genipin 1-gentiobioside， geniposide and genipin were significantly lower in wild GF（P<0.01）. ConclusionThere are significant differences between wild and cultivated GF in terms of traits， microstructure， and contents of primary and secondary metabolites. At present， the quality evaluation system of cultivated GF remains incomplete， and this study provides a reference for guiding the production of high-quality GF medicinal materials.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

[Objective] To study the molecular biological mechanism for a case of ABO blood group B subtype, and perform three-dimensional modeling of the mutant enzyme. [Methods] The ABO phenotype was identified by the tube method and microcolumn gel method; the ABO gene of the proband was detected by sequence-specific primer polymerase chain reaction (PCR-SSP), and the exon 6 and 7 of the ABO gene were sequenced and analyzed. Homologous modeling of Bw.03 glycosyltransferase (GT) was carried out by Modeller and analyzed by PyMOL2.5.0 software. [Results] The weakening B antigen was detected in the proband sample by forward typing, and anti-B antibody was detected by reverse typing. PCR-SSP detection showed B, O gene, and the sequencing results showed c.721 C>T mutation in exon 7 of the B gene, resulting in p. Arg 241 Trp. Compared with the wild type, the structure of Bw.03GT was partially changed, and the intermolecular force analysis showed that the original three hydrogen bonds at 241 position disappeared. [Conclusion] Blood group molecular biology examination is helpful for the accurate identification of ambiguous blood group. Homologous modeling more intuitively shows the key site for the weakening of Bw.03 GT activity. The intermolecular force analysis can explain the root cause of enzyme activity weakening.

Many triterpenoid compounds have been successfully heterologously synthesized in Saccharomyces cerevisiae. To increase the yield of triterpenoids, various metabolic engineering strategies have been developed. One commonly applied strategy is to enhance the supply of precursors, which has been widely used by researchers. Squalene, as a precursor to triterpenoid biosynthesis, plays a crucial role in the synthesis of these compounds. This study primarily investigates the effect of different squalene levels in chassis strains on the synthesis of triterpenoids(oleanolic acid and ursolic acid), and the underlying mechanisms are further explored using real-time quantitative PCR(qPCR) analysis. The results demonstrate that the chassis strain CB-9-5, which produces high levels of squalene, inhibits the synthesis of oleanolic acid and ursolic acid. In contrast, chassis strains with moderate to low squalene production, such as Y8-1 and CNPK, are more conducive to the synthesis of oleanolic acid and ursolic acid. The qPCR analysis reveals that the expression levels of ERG1, βAS, and CrCYP716A154 in the oleanolic acid-producing strain CB-OA are significantly lower than those in the control strains C-OA and Y-OA, suggesting that high squalene production in the chassis strains suppresses the transcription of certain genes, leading to a reduced yield of triterpenoids. Our findings indicate that when constructing S. cerevisiae strains for triterpenoid production, chassis strains with high squalene content may suppress the expression of certain genes, ultimately lowering their production, whereas chassis strains with moderate squalene levels are more favorable for triterpenoid biosynthesis.
Squalene/analysis* ; Saccharomyces cerevisiae/genetics* ; Triterpenes/metabolism* ; Metabolic Engineering ; Oleanolic Acid/biosynthesis* ; Ursolic Acid

Macroporous resin adsorption column chromatography, silica gel column chromatography, ODS column chromatography, and semi-preparative high-performance liquid chromatography, combined with analytical methods such as NMR and MS, were employed to separate and identify compounds from the 70% ethanol extract of Ajania purpurea. A total of 30 compounds were isolated and identified, including 13 phenolic acids, 7 coumarins, 2 lignans, 1 flavonoid, 2 sesquiterpenes, 1 steroid, and 4 others. Among them, compounds 1 and 2 were newly discovered compounds, and compounds 4, 6, 8, 12, 14-23, 25, 28, and 30 were isolated from Ajania plants for the first time. Bioactivity screening showed that multiple compounds significantly inhibited the production of nitric oxide in lipopolysaccharide-stimulated RAW264.7 cells in a dose-dependent manner. Furthermore, compound 2 elevated the levels of glutathione in LPS-induced BEAS-2B cells, reduced the expression of pro-inflammatory cytokines such as tumor necrosis factor(TNF)-α, interleukin(IL)-6, and IL-1β, enhanced the mRNA of GPX4, HMOX1, NFE2L2, and enhanced protein levels of GPX4, HO-1, Nrf2, and SLC7A11, demonstrating potential anti-ferroptotic effect.
Mice ; Animals ; Lignans/isolation & purification* ; RAW 264.7 Cells ; Humans ; Nitric Oxide ; Tumor Necrosis Factor-alpha/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; NF-E2-Related Factor 2/metabolism* ; Macrophages/metabolism* ; Interleukin-6/immunology*

Based on the interleukin-17(IL-17) signaling pathway, this study explores the effect and mechanism of Bufei Decoction on Klebsiella pneumoniae pneumonia in rats. SD rats were randomly divided into the control group, model group, Bufei Decoction low-dose group(6.68 g·kg~(-1)·d~(-1)), Bufei Decoction high-dose group(13.36 g·kg~(-1)·d~(-1)), and dexamethasone group(1.04 mg·kg~(-1)·d~(-1)), with 10 rats in each group. A pneumonia model was established by tracheal drip injection of K. pneumoniae. After successful model establishment, the improvement in lung tissue damage was observed following drug administration. Core targets and signaling pathways were screened using transcriptomics techniques. Real-time fluorescence quantitative polymerase chain reaction was used to detect the mRNA expression of core targets interleukin-6(IL-6), interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and chemokine CXC ligand 6(CXCL6). Western blot was used to assess key proteins in the IL-17 signaling pathway, including interleukin-17A(IL-17A), nuclear transcription factor-κB activator 1(Act1), tumor necrosis factor receptor-associated factor 6(TRAF6), and downstream phosphorylated p38 mitogen-activated protein kinase(p-p38 MAPK), and phosphorylated nuclear factor-κB p65(p-NF-κB p65). Apoptosis of lung tissue cells was detected by terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling(TUNEL). The results showed that, compared with the control group, the model group exhibited significant pathological damage in lung tissue. The mRNA expression of IL-6, IL-1β, TNF-α, and CXCL6, as well as the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly increased, and the number of apoptotic cells was notably higher, indicating successful model establishment. Compared with the model group, both low-and high-dose groups of Bufei Decoction showed reduced pathological damage in lung tissue. The mRNA expression levels of IL-6, IL-1β, TNF-α, and CXCL6, and the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly decreased, with a significant reduction in apoptotic cells in the high-dose group. In conclusion, Bufei Decoction can effectively improve lung tissue damage and reduce inflammation in rats with K. pneumoniae. The mechanism may involve the regulation of the IL-17 signaling pathway and the reduction of apoptosis.
Animals ; Interleukin-17/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Rats ; Male ; Klebsiella pneumoniae/physiology* ; Klebsiella Infections/immunology* ; Humans ; Lung/drug effects*

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

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*