ObjectiveTo address the challenges of unstructured classical Chinese expressions， nested entity relationships， and limited annotated data in famous traditional Chinese medicine（TCM） case records， this study proposes a joint relation extraction framework that integrates data augmentation and entity mapping， aiming to support the construction of TCM diagnostic knowledge graphs and clinical pattern mining. MethodsWe developed an annotation structure for entities and their relationships in TCM case texts and applied a data augmentation strategy by incorporating multiple ancient texts to expand the relation extraction dataset. A cascade binary tagging framework for relation triple extraction（CasRel） model for TCM semantics was designed， integrating a pre-trained bidirectional encoder representations from transformers（BERT） layer for classical TCM texts to enhance semantic representation， and using a head entity-relation-tail entity mapping mechanism to address entity nesting and relation overlapping issues. ResultsExperimental results showed that the CasRel model， combining data augmentation and entity mapping， outperformed the pipeline-based Bert-Radical-Lexicon（BRL）-bidirectional long short-term memory（BiLSTM）-Attention model. The overall precision， recall， and F₁-score across 12 relation types reached 65.73%， 64.03%， and 64.87%， which represent improvements of 14.26%， 7.98%， and 11.21% compared to the BRL-BiLSTM-Attention model， respectively. Notably， the F₁-score for tongue syndrome relations increased by 22.68%（69.32%）， and the prescription-syndrome relations performed the best with the F₁-score of 70.10%. ConclusionThe proposed framework significantly improves the semantic representation and complex dependencies in TCM texts， offering a reusable technical framework for structured mining of TCM case records. The constructed knowledge graph can support clinical syndrome differentiation， prescription optimization， and drug compatibility， providing a methodological reference for TCM artificial intelligence research.

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.

AIM: To delineate the specific mutation responsible for retinitis pigmentosa(RP)in a Yi pedigree, and to analyze the correlation of RHO gene mutation with clinical phenotype.METHODS:A comprehensive clinical evaluation was conducted on the proband diagnosed with RP and other familial members, complemented by a thorough ophthalmic examination. Peripheral blood samples were obtained from the proband and familial members, from which genomic DNA was extracte. Subsequent whole exome sequencing(WES)was employed to identify the variant genes in the proband. The identified variant gene was validated through Sanger sequencing, then an in-depth analysis of the mutation genes was carried out using genetic databases to ascertain the pathogenic mutation sites. Furthermore, an exhaustive analysis was performed to delineate the genotype and phenotype characteristics.RESULTS:The RP pedigree encompasses 5 generations with 42 members, including 19 males and 23 females. A total of 13 cases of RP were identified, consisting of 4 males and 9 females, which conforms to the autosomal dominant inheritance pattern. The clinical features of this family include an early onset age, rapid progression, and a more severe condition. The patients were found to have night blindness around 6 years old, representing the earliest reported case of night blindness in RP families. The retina was manifested by progressive osteocytoid pigmentation of the fundus, a reduced visual field, and significantly decreased or even vanished a and b amplitudes of ERG. The combined results of WES and Sanger sequencing indicated that the proband had a heterozygous missense mutation of the RHO gene c.1040C>T:p.P347L, where the 1 040 base C of cDNA was replaced by T, causing codon 347 to encode leucine instead of proline. Interestingly, this mutation has not been reported in the Chinese population.CONCLUSION:This study confirmed that the mutant gene of RP in a Yi nationality pedigree was RHO(c.1040C>T). This variant leads to the change of codon 347 from encoding proline to encoding leucine, resulting in a severe clinical phenotype among family members. This study provides a certain molecular, clinical, and genetic basis for genetic counseling and gene diagnosis of RHO.

AIM: To delineate the specific mutation responsible for retinitis pigmentosa(RP)in a Yi pedigree, and to analyze the correlation of RHO gene mutation with clinical phenotype.METHODS:A comprehensive clinical evaluation was conducted on the proband diagnosed with RP and other familial members, complemented by a thorough ophthalmic examination. Peripheral blood samples were obtained from the proband and familial members, from which genomic DNA was extracte. Subsequent whole exome sequencing(WES)was employed to identify the variant genes in the proband. The identified variant gene was validated through Sanger sequencing, then an in-depth analysis of the mutation genes was carried out using genetic databases to ascertain the pathogenic mutation sites. Furthermore, an exhaustive analysis was performed to delineate the genotype and phenotype characteristics.RESULTS:The RP pedigree encompasses 5 generations with 42 members, including 19 males and 23 females. A total of 13 cases of RP were identified, consisting of 4 males and 9 females, which conforms to the autosomal dominant inheritance pattern. The clinical features of this family include an early onset age, rapid progression, and a more severe condition. The patients were found to have night blindness around 6 years old, representing the earliest reported case of night blindness in RP families. The retina was manifested by progressive osteocytoid pigmentation of the fundus, a reduced visual field, and significantly decreased or even vanished a and b amplitudes of ERG. The combined results of WES and Sanger sequencing indicated that the proband had a heterozygous missense mutation of the RHO gene c.1040C>T:p.P347L, where the 1 040 base C of cDNA was replaced by T, causing codon 347 to encode leucine instead of proline. Interestingly, this mutation has not been reported in the Chinese population.CONCLUSION:This study confirmed that the mutant gene of RP in a Yi nationality pedigree was RHO(c.1040C>T). This variant leads to the change of codon 347 from encoding proline to encoding leucine, resulting in a severe clinical phenotype among family members. This study provides a certain molecular, clinical, and genetic basis for genetic counseling and gene diagnosis of RHO.

BACKGROUND:Primary osteoporosis has a high incidence,but the pathogenesis is not fully understood.Currently,there is a lack of effective early screening indicators and treatment programs. OBJECTIVE:To further explore the mechanism of primary osteoporosis through comprehensive bioinformatics analysis. METHODS:The primary osteoporosis data were obtained from the gene expression omnibus(GEO)database,and the differentially expressed genes were screened for Gene Ontology(GO)function and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis.In addition,the differentially expressed genes were subjected to protein-protein interaction network to determine the core genes related to primary osteoporosis,and the least absolute shrinkage and selection operator algorithm was used to identify and verify the primary osteoporosis-related biomarkers.Immune cell correlation analysis,gene enrichment analysis and drug target network analysis were performed.Finally,the biomarkers were validated using qPCR assay. RESULTS AND CONCLUSION:A total of 126 differentially expressed genes and 5 biomarkers including prostaglandins,epidermal growth factor receptor,mitogen-activated protein kinase 3,transforming growth factor B1,and retinoblastoma gene 1 were obtained in this study.GO analysis showed that differentially expressed genes were mainly concentrated in the cellular response to oxidative stress and the regulation of autophagy.KEGG analysis showed that autophagy and senescence pathways were mainly involved.Immunoassay of biomarkers showed that prostaglandins,retinoblastoma gene 1,and mitogen-activated protein kinase 3 were closely related to immune cells.Gene enrichment analysis showed that biomarkers were associated with immune-related pathways.Drug target network analysis showed that the five biomarkers were associated with primary osteoporosis drugs.The results of qPCR showed that the expression of prostaglandins,epidermal growth factor receptor,mitogen-activated protein kinase 3,and transforming growth factor B1 in the primary osteoporosis sample was significantly increased compared with the control sample(P<0.001),while the expression of retinoblastoma gene 1 in the primary osteoporosis sample was significantly decreased compared with the control sample(P<0.001).Overall,the study screened and validated five potential biomarkers of primary osteoporosis,providing a reference basis for further in-depth investigation of the pathogenesis,early screening and diagnosis,and targeted treatment of primary osteoporosis.

ObjectiveTo investigate the therapeutic effects of direct-acting antiviral agents (DAAs) combined regimens for hepatitis C virus (HCV) patients in Dehong Prefecture, Yunnan Province from 2022 to 2024, to analyze the characteristics of treatment failure patients, so as to provide a basis for discovering more effective treatment regimens in the future. MethodsData on HCV prevention and treatment in Dehong Prefecture was extracted from the China Disease Control and Prevention Information System. A total of 617 patients with HCV antiviral therapy were included, and the differences in variable characteristics among patients with different genotypes were analyzed using comparative statistical tests, including basic socio-demographic characteristics, biochemical testing indicators, and information on previous treatment and current treatment. In addition, the cure rate of HCV patients with diverse characteristics was compared, and the potential causes of treatment failure were explored simultaneously. ResultsThe cure rate of HCV was 96.8%, and statistically significant differences were observed in aspartate transaminase (AST) and alanine transaminase (ALT) levels, previous antiviral therapy history and initial treatment regimens among patients with different HCV genotypes (all P<0.05). Among the multi-type combination regimens, the cure rate of sofosbuvir (SOF)-containing regimens was 97.00%, that of velpatasvir (VEL)-containing regimens was 95.45%, and the cure rate of other treatment regimens, including the regimens with ribavirin (RIB) intervention, was 93.10%. Among the patients with treatment failure, 45.00% had genotype 3, 40.00% had abnormal abdominal ultrasound results, and all presented with elevated baseline AST test levels. ConclusionThe clinical treatment of HCV patients should consider the differences in genotype and biochemical test results. DAAs combined regimens for HCV have achieved a high cure rate in Dehong Prefecture and are applicable to HCV patients with diverse clinical characteristics, providing research evidence for wider application.

Piezo1, a mechanosensitive nonselective cation channel characterized by multiple transmembrane domains, plays a critical role intransducing mechanical stimuli at the cellular membrane and participates in various physiological and pathological processes. Recent studies have established a significant association between Piezo1 and the occurrence and development of multiple ophthalmic disorders. Substantial evidence demonstrates that Piezo1 contributes to ocular disease progression by regulating fundamental cellular processes including proliferation, differentiation, apoptosis, and inflammatory responses, with particular relevance to glaucoma, corneal diseases, retinal disorders, and dry eye syndrome. Piezo1 has made rapid progress in ophthalmology, and has been established as an important mechanosensor in the eye, widely involved in intraocular pressure regulation, retinal function maintenance, corneal homeostasis and repair, and ocular development, and its dysfunction is closely related to the pathological mechanisms of many important blinding eye diseases. Consequently, Piezo1 is not only a key molecule for understanding ocular mechanobiology, but also represents a highly promising therapeutic target. Its study offers new perspectives for the development of novel therapeutic strategies against ocular diseases. This review systematically summarizes current research advances regarding Piezo1 channels in ophthalmology, analyzes their mechanistic involvement in disease processes, and evaluates their potential therapeutic value, thereby offering innovative perspectives for the clinical management of ocular diseases.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

Under the background of carbon peaking and carbon neutrality goals, the Ministry of Ecology and Environment, together with 15 national ministries and commissions, has formulated the Implementation Plan on Establishing a Carbon Footprint Management System, and it is urgent for traditional Chinese medicine(TCM) pharmaceutical enterprises to carry out research on carbon footprint accounting methods of related products. Based on the life cycle assessment(LCA) theory, taking mulberry leaf extract produced by a certain enterprise as an example, this study analyzed the carbon footprint of TCM extracts during the life cycle. The results show that for every 1 kg of product produced, the carbon emissions from the stages of raw material acquisition, transportation, and extract production are-20.569, 1.205, and 173.577 kgCO_2eq(CO_2 equivalent), respectively. The carbon footprint of the product is 154.213 kgCO_2eq·kg~(-1). In addition, the carbon emission is the highest in the production stage, in which the consumption of ethanol solvents makes the greatest contribution to the carbon footprint, accounting for 25.71%, more than one-fourth of the total carbon footprint. The second contribution was from the treatment process of TCM residues, accounting for 19.67%, closely followed by wastewater treatment(17.71%), the consumption of hot steam(17.43%), and drinking water(16.90%). The consumption of electric power and packaging materials has a smaller carbon emission of 2.58%. In particular, the carbon emission caused by the consumption of packaging materials is only 0.04%, which is negligible. The results of the study are expected to provide a reference for TCM enterprises to carry out research on the carbon footprint of products, offer ideas for collaborative innovation in reducing pollution and carbon emissions throughout the entire industry chain of TCM, and develop new quality productivity of modern TCM industry based on green and low-carbon manufacturing.
Morus/chemistry* ; Plant Leaves/chemistry* ; Carbon Footprint ; Drugs, Chinese Herbal/chemistry* ; Plant Extracts/analysis* ; Medicine, Chinese Traditional