ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.

OBJECTIVE: To assess the value of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) score combined with PSA density (PSAD) in the diagnosis of clinically significant prostate cancer (CSPCa) in the PSA grey zone by MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy. METHODS: This retrospective study included 327 male patients with total PSA (tPSA) levels of 4-10 μg/L undergoing MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy in our hospital between January 2021 and December 2023. According to the pathological results, we divided the patients into a CSPCa (n = 44) and a non-CSPCa group (n = 283), collected their clinical and imaging data, and subjected them to statistical analysis. RESULTS: The age, tPSA level, PSAD and PI-RADS score were significantly higher, while the free PSA (fPSA) level, f/tPSA ratio and prostate volume remarkably lower in the CSPCa than in the non-CSPCa group (P<0.05). The areas under the curve (AUCs) of PSAD, PI-RADS score and their combination were 0.772, 0.730 and 0.801, with sensitivities of 63.63%, 70.45% and 72.73%, and specificities of 84.10%, 75.62% and 83.75%, respectively (P<0.01). With PSAD 0.2 μg/(ml·cm3) as the best cut-off value and based on the PI-RADS scores, the patients were divided into two groups for analysis. In the patients with PI-RADS scores 2 and 5, the AUCs were 0.534 and 0.643, with sensitivities of 16.67% and 63.64%, and specificities of 85.14% and 64.29%, with no statistically significant differences (P= 0.784, P= 0.228), and in those with PI-RADS scores 3 and 4, the AUCs were 0.794 and 0.843, with sensitivities of 57.14% and 80.00%, and specificities of 87.14% and 81.82%, with statistically significant differences (P= 0.009, P<0.001). CONCLUSION PI-RADS v2.1 score combined with PSAD can effectively improve the diagnostic efficiency of CSPCa in the PSA grey zone by MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy and serve as a guide for selection of prostate biopsy.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Retrospective Studies ; Prostate-Specific Antigen ; Magnetic Resonance Imaging ; Image-Guided Biopsy ; Prostate/pathology* ; Aged ; Middle Aged

Idiopathic pulmonary fibrosis (IPF), a chronic interstitial lung disease, is characterized by aberrant wound healing, excessive scarring and the formation of myofibroblastic foci. Although the role of alternative splicing (AS) in the pathogenesis of organ fibrosis has garnered increasing attention, its specific contribution to pulmonary fibrosis remains incompletely understood. In this study, we identified an up-regulation of serine/arginine-rich splicing factor 7 (SRSF7) in lung fibroblasts derived from IPF patients and a bleomycin (BLM)-induced mouse model, and further characterized its functional role in both human fetal lung fibroblasts and mice. We demonstrated that enhanced expression of Srsf7 in mice spontaneously induced alveolar collagen accumulation. Mechanistically, we investigated alternative splicing events and revealed that SRSF7 modulates the alternative splicing of pyruvate kinase (PKM), leading to metabolic dysregulation and fibroblast activation. In vivo studies showed that fibroblast-specific knockout of Srsf7 in conditional knockout mice conferred resistance to bleomycin-induced pulmonary fibrosis. Importantly, through drug screening, we identified lomitapide as a novel modulator of SRSF7, which effectively mitigated experimental pulmonary fibrosis. Collectively, our findings elucidate a molecular pathway by which SRSF7 drives fibroblast metabolic dysregulation and propose a potential therapeutic strategy for pulmonary fibrosis.

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

Chirality is not only a natural phenomenon but also a bridge between chemistry and life sciences. An effective way to obtain a single enantiomer is through racemates resolution. Recent literature shows that chiral metal-organic frameworks (CMOFs) have many applications in various fields because of their diverse topologies and functionalities. This review outlines the design idea and summarizes the latest synthesis strategies and applications of CMOFs. It highlights key advances and issues in the separation domain. In conclusion, the review provides perspectives on the challenges and prospective advancements of CMOFs materials and CMOFs-based separation technologies.

ObjectiveTo explore the efficacy-driving mechanism of Danhong injection （DHI） in the treatment of stable angina pectoris （SAP） based on the composition-activity relationship of target modules and clarify the pharmacological effects of DHI. MethodAccording to the angina frequency （AF） in the Seattle Angina Questionnaire （SAQ） that was obtained in the previous clinical trial， the patients before and after DHI treatment were grouped based on efficacy. The transcriptomic data of the patients before treatment and in the best efficacy group 30 days post-treatment were selected as the data source， and then weighted gene co-expression network analysis （WGCNA） was employed to construct the co-expression network. Relevant modules in the network were identified and associated with clinical features. In addition， the On-modules （Z value below 0） were identified by Zsummary. The topological indicators such as density， centrality， and clustering coefficient were adopted to explore the dynamics of DHI efficacy at the network level and module level， respectively. In addition， the driver genes were screened by the personalized network control （PNC） algorithm. Finally， rat H9C2 cells were used to establish the model of hypoxia/reoxygenation （H/R）， which was used to confirm the potential therapeutic target of DHI for SAP and provide a scientific basis for revealing the therapeutic mechanism of DHI. ResultWe identified 19 modules in the best efficacy group of DHI for SAP， and the comparison between day 0 and day 30 revealed 12 On-modules. The changes of network topological indicators at the network and module levels confirmed the correlation between the best efficacy of DHI treatment and topological dynamics. Finally， the driver genes， Klotho and fibroblast growth factor 22 （FGF22）， in DHI treatment of SAP were verified by the H9C2 cell model of H/R. ConclusionBased on clinical transcriptome data， this study determined the composition-activity relationship of target modules of DHI for SAP， which provided a scientific basis for deciphering the efficacy-driven mechanism of DHI for SAP.

Abstract Fangjiomics is a promising paradigm that enhances research on multi-omics-based pharmacological mechanisms of Fangji from holistic and systematic perspective. We reviewed recent advances in Fangjiomics, focusing on database and analysis platform development, methodological innovations, and translational applications. Through the integration of Fangji and multi-omics data, multi-level system analysis approaches were developed, encompassing single-target analysis, signaling pathways, multi-targeted network and modules. Fangjiomics has emerged as a key strategy in various areas of Fangji research. To support the high quality development of Fangjiomics, we propose principles and perspectives from the integrated, macro-level, and practical viewpoints.

Objective To explore the effects of different fractionation doses,fractionation methods,and other related parameters on the peripheral blood lymphocyte count of patients with liver cancer receiving CyberKnife radiotherapy.Methods The clinical data of 90 patients with liver cancer receiving CyberKnife radiotherapy in our hospital were retrospectively analyzed.The peripheral blood lymphocyte counts of patients 1 week before CyberKnife radiotherapy and 1 week,1 month and 3 months after treatment were determined.The effects of different prescribed doses,fractionation doses and numbers of fractionations on the peripheral blood lymphocyte count were analyzed.Results The peripheral blood lymphocyte counts of patients with different prescribed doses,fractionation doses and fractionation methods after CyberKnife treatment decreased to varying degrees compared with those 1 week before treatment(P<0.05).The peripheral blood lymphocyte counts of patients in the groups with≤5 fractionations and fractionation dose>7 Gy were significantly higher than those of patients in the groups with>5 fractionations and the fractionation dose≤7 Gy,respectively(P<0.05).There was no significant difference in peripheral blood lymphocyte counts between patients with different prescribed doses before and after CyberKnife treatment(P>0.05).Conclusion CyberKnife in the treatment of liver cancer with≤5 ractionations and a fractionation dose of>7 Gy is more beneficial to alleviate the decrease of lymphocyte count caused by Cyberknife treatment.

Objective To investigate the association of 13 single nucleotide polymorphism(SNP)sites in 6 phalange-bone development related genes[fibroblast growth factor receptor 2(FGFR2),indian hedgehog signaling molecule(IHH),Msh homeobox 1(MSX1),Runx family transcription factor 2(RUNX2),SRY-box transcription factor 9(SOX9),Wnt family member 5A(WNT5A)]with human index-ring finger length ratio(2D∶4D).Methods Digital cameras were used to take frontal photographs of the hands of 731 college students(358 males and 373 females)in Ningxia,and image analysis software was used to mark anatomical points and measure finger lengths of index(2th)and ring(4th);genotyping of 13 SNP sites(rs1047057,rs755793,rs41258305,rs3731881,rs3100776,rs12532,rs3821949,rs45585135,rs3749863,rs1042667,rs12601701,rs1829556,rs3732750)for 6 genes by multiplex PCR;One-Way ANOVA or independent sample t-test indirectly assessed the association between 2D∶4D and 13 SNP sites.Results Both left and right hand 2D∶4D were significantly higher in females than males in Ningxia college students(all P<0.01);no statistically significant differences in genotype and allele frequencies of the 13 SNP sites among different sexes(all P>0.05);among different sexes,male left hand 2D∶4D was significantly associated with the genotype of SOX9 gene rs12601701 site(P<0.05)and right hand 2D∶4D was significantly associated with the genotype of WNT5A gene rs1829556 site(P<0.05);the female right hand 2D∶4D was significantly associated with the MSX1 gene rs12532(P<0.01)and rs3821949(P<0.05)sites genotypes.Conclusion SOX9(rs12601701),WNT5A(rs1829556)and MSX1(rs12532 and rs3821949)gene polymorphisms may be associated with the formation of 2D∶4D in Ningxia population.