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 elucidate the molecular mechanism of sirtuin-3 (SIRT3) in regulating mitochondrial biogenesis in human renal tubular epithelial cells. Methods Cells were stimulated with different concentrations of H₂O₂ and divided into four groups: control (NC), 50 μmol/L H₂O₂, 110 μmol/L H₂O₂ and 150 μmol/L H₂O₂. SIRT3 protein expression was then measured. SIRT3 was knocked down with siRNA, and cells were further assigned to five groups: control (NC), negative-control siRNA (NCsi), SIRT3-siRNA (siSIRT3), NCsi+H₂O₂, and siSIRT3+H₂O₂. After 24 h, cellular adenosine triphosphate (ATP) and mitochondrial superoxide anion (O₂•⁻) levels were determined, together with mitochondrial expression of SIRT3, peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α), nuclear respiratory factor 1 (NRF1), mitochondrial transcription factor A (TFAM), superoxide dismutase 2 (SOD2), acetylated-SOD2 and adenosine monophosphate activated protein kinase α1 (AMPKα1). Results The 110 and 150 μmol/L H₂O₂ decreased SIRT3 protein (both P<0.05). ATP and mitochondrial O₂•⁻ did not differ between NC and NCsi groups (both P>0.05). Compared to the NCsi group, the siSIRT3 group exhibited elevated O₂•⁻ level, decreased SIRT3 protein and increased expression levels of SOD2 and acetylated SOD2 protein (all P<0.05). Compared to the NCsi group, the NCsi+H₂O₂ group exhibited decreased cellular ATP levels, elevated mitochondrial O₂•⁻ levels, and reduced protein expression levels of SIRT3, SOD2, TFAM, AMPKα1, PGC-1α and NRF1 (all P<0.05). Compared with the siSIRT3 group, the siSIRT3+H₂O₂ group showed a decrease in cellular ATP levels, an increase in mitochondrial O₂•⁻ levels, a decrease in SIRT3, SOD2, TFAM, AMPKα1, PGC-1α and NRF1 protein expression levels and a decrease in acetylated SOD2 protein expression levels (all P<0.05). Compared with the NCsi+H₂O₂ group, the siSIRT3+H₂O₂ group showed a decrease in cellular ATP levels, an increase in mitochondrial O₂•⁻ levels, a decrease in SIRT3, AMPKα1, PGC-1α and NRF1, TFAM protein expression levels, and an increase in SOD2 and acetylated SOD2 protein expression levels (all P<0.05). Conclusions SIRT3 promotes mitochondrial biogenesis in tubular epithelial cells via the AMPK/PGC-1α/NRF1/TFAM axis, representing a key mechanism through which SIRT3 ameliorates oxidative stress-induced mitochondrial dysfunction.

BACKGROUND:Studies have shown that metformin has anti-inflammatory,anti-tumor,anti-aging and vasoprotective effects,and can inhibit the progression of osteoarthritis,but its specific mechanism of action remains unclear. OBJECTIVE:To investigate the mechanism of metformin on cartilage protection in a rat model of osteoarthritis. METHODS:Forty male Sprague-Dawley rats were randomly divided into four groups(n=10 per group):blank,control,sham-operated,and metformin groups.The blank group did not undergo any surgery.In the sham-operated group,the joint cavity was exposed.In the model group and the metformin group,the modified Hulth method was used to establish the osteoarthritis model.At 1 day after modeling,the rats in the metformin group were given 200 mg/kg/d metformin by gavage,and the model,blank,and sham-operated groups were given normal saline by gavage.Administration in each group was given for 4 weeks consecutively.Hematoxylin-eosin staining,toluidine blue staining,and safranin O-fast green staining were used to observe the morphological structure of rat knee joints.Immunohistochemical staining and western blot were used to detect the protein expression of SOX9,type Ⅱ collagen,a disintegrin and metalloproteinase with thrombospondin motifs 5(ADAMTS5),Beclin1,P62,phosphatidylinositol 3-kinase(PI3K),p-PI3K,protein kinase B(AKT),p-AKT,mammalian target of rapamycin(Mtor),and p-Mtor in rat cartilage tissue. RESULTS AND CONCLUSION:The results of hematoxylin-eosin,toluidine blue and safranin O-fast green staining showed smooth cartilage surface of the knee joints and normal histomorphology in the blank group and the sham-operated group,while in the model group,there was irregular cartilage surface of the knee joint and cartilage damage,with a decrease in the number of chondrocytes and the content of proteoglycans in the cartilage matrix.In the metformin group,there was a significant improvement in the damage to the structure of the cartilage in the knee joints of the rats,and the cartilage surface tended to be smooth,with an increase in the number of chondrocytes and the content of proteoglycans in the cartilage matrix.Immunohistochemistry staining and western blot results showed that compared with the control and sham-operated groups,the expression of SOX9,type Ⅱ collagen,and Beclin1 proteins in the cartilage tissue of rats in the model group was significantly decreased(P<0.05).Conversely,the expression of ADAMTS5,P62,as well as p-PI3K,p-AKT,and p-Mtor proteins was significantly increased(P<0.05).Furthermore,compared with the model group,the expression of SOX9,type Ⅱ collagen,and Beclin1 proteins in the cartilage tissue of rats in the metformin group was significantly increased(P<0.05),while the expression of ADAMTS5,P62,as well as p-PI3K,p-AKT,and p-Mtor proteins was significantly decreased(P<0.05).To conclude,Metformin can improve the autophagy activity of chondrocytes and reduce the degradation of cartilage matrix in osteoarthritis rats by inhibiting the activation of PI3K/AKT/Mtor signaling pathway,thus exerting a protective effect on articular cartilage.

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.

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.

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.

The study aims to elucidate the existence forms(original constituents and metabolites) of Notoginseng Radix et Rhizoma in rats and reveal its metabolic pathways. After Notoginseng Radix et Rhizoma was administered orally once a day for seven consecutive days to rats, all urine and feces samples were collected for seven days, while the blood samples were obtained 6 h after the last administration. Using the ultra high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technique, this study identified 6, 73, and 156 existence forms of Notoginseng Radix et Rhizoma in the rat plasma, urine, and feces samples, respectively. Among them, 101 compounds were identified as new existence forms, and 13 original constituents were identified by comparing with reference compounds. The metabolic reactions of constituents from Notoginseng Radix et Rhizoma were mainly deglycosylation, dehydration, hydroxylation, hydrogenation, dehydrogenation, acetylation, and amino acid conjugation. Furthermore, the possible in vivo metabolic pathways of protopanaxatriol(PPT) in rats were proposed. Through comprehensive analysis of the liquid chromatography-mass spectrometry(LC-MS) data, isomeric compounds were discriminated, and the planar chemical structures of 32 metabolites were clearly identified. According to the literature, 48 original constituents possess antitumor and cardiovascular protective bioactivities. Additionally, 32 metabolites were predicted to have similar bioactivities by SuperPred. This research lays the foundation for further exploring the in vivo effective forms of Notoginseng Radix et Rhizoma.
Animals ; Rats ; Drugs, Chinese Herbal/pharmacokinetics* ; Rhizome/metabolism* ; Male ; Rats, Sprague-Dawley ; Chromatography, High Pressure Liquid ; Panax notoginseng/chemistry* ; Tandem Mass Spectrometry ; Feces/chemistry*

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

OBJECTIVE: To investigate the distribution of GP.Mur antigen in blood donors in Jiangsu Province. METHODS: Genomic DNA was extracted from 1 114 blood donors in Jiangsu region. PCR-SSP was performed to amplify GP.Mur, and gene analysis was conducted by direct sequencing of the PCR products. The frequency of GP.Mur in the blood donor population of Jiangsu region was calculated. RESULTS: Out of 1 114 randomly selected blood samples, 11 positive bands were detected during amplification. Direct sequencing analysis revealed that among the 11 positive samples, 4 were homozygous for GYP .Mur genotype, 3 were heterozygous for GYP .Mur genotype, and the remaining 4 samples were identified as GYP .HF genotype. CONCLUSION This study analyzed the distribution of the GP.Mur antigen and preliminary obtained the frequency data in the blood donor population in Jiangsu region. Further in-depth research on this blood group is of great importance in guiding clinical blood transfusion practices and ensuring transfusion safety.
Humans ; Blood Donors ; China ; Genotype ; Blood Group Antigens/genetics* ; Polymerase Chain Reaction ; Glycophorins/genetics* ; Gene Frequency