OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

OBJECTIVE: To analyze the significance of total vitamin D (tVD), total procollagen type I amino-terminal propeptide (tPINP) and β-CrossLaps (β-CTx) in the staging and prognosis of patients with multiple myeloma (MM). METHODS: A total of 54 patients with newly diagnosed MM admitted to the Second Affiliated Hospital of Fujian Medical University from 2020 to 2022 were selected as the observation group (MM group), and 50 healthy persons who underwent physical examinations in our hospital were selected as the control group. The expression levels of tVD, tPINP and β-CTx in the two groups were detected by chemiluminescence method. The differences in the expression levels of tVD, tPINP and β-CTx among MM patients at different ISS stages were analyzed. The expression levels of tVD, tPINP and β-CTx in MM patients with different levels of hemoglobin (Hb), serum calcium (Ca), creatinine (Crea), albumin (ALB), β₂-microglobulin (β₂-MG) and lactate dehydrogenase (LDH) were compared. The correlations between the expression levels of tVD, tPINP, β-CTx and the aforementioned clinical parameters were analyzed, respectively. The relationship between the expression levels of tVD, tPINP, β-CTx and the progression-free survival (PFS) of MM patients was analyzed. RESULTS: The expression level of tVD in the MM group was significantly lower than that in the control group (21.73±14.45 ng/ml vs 30.78±9.94 ng/ml, P =0.022). The expression level of β-CTx in the MM group was significantly higher than that in the control group (1.43±0.99 ng/ml vs 0.53±0.29 ng/ml, P =0.013). The tVD level in MM patients with ISS stage I-II was significantly higher than that of MM patients with ISS stage III (29.50±14.59 ng/ml vs 12.62±7.73 ng/ml, P =0.028), indicating that the higher the ISS stage, the lower the tVD level. The tPINP and β-CTx levels in MM patients with high Ca levels (>2.65 mmol/L) were significantly higher than those in patients with low Ca levels (≤2.65 mmol/L) (P =0.016, P =0.021). The tVD level of MM patients was positively correlated with the ALB level (r =0.570), tPINP was positively correlated with Ca and β₂-MG levels (r =0.791,r =0.673), and β-CTx was positively correlated with tPINP level (r =0.616). The PFS of the low tVD expression group was significantly lower than that of the high tVD expression group (P =0.041). CONCLUSION The expression level of tVD is decreased in MM patients, which can be used as an indicator to evaluate the disease stage and prognosis of the patients. The β-CTx expression level is increased in MM patients. tPINP and β-CTx may be correlated with clinical symptoms such as osteolytic lesions and renal function changes in MM patients.
Humans ; Multiple Myeloma/pathology* ; Procollagen/blood* ; Vitamin D/blood* ; Prognosis ; Peptide Fragments/blood* ; Collagen Type I/blood* ; Female ; Male ; Middle Aged ; Aged ; Neoplasm Staging

OBJECTIVE: To explore the expression regulation of lipid metabolism gene ABHD5 in testes. METHODS: Differential gene analysis was performed by integrating databases of TCGA and GTEx to identify the target gene ABHD5. The expression trends of ABHD5 gene in testicular carcinoma tissue were analyzed. Human testis single-cell atlases were obtained from the Human Protein Atlas and Male Health Atlas databases to determine the expression distribution of ABHD5 across different testicular cell types. Additionally, the GTEx database was utilized to visualize the expression pattern of ABHD5 in the testis, thereby enhancing the understanding of its transcriptional profile. The relationship between ABHD5 expression and age was assessed through integrated database analysis. Western blotting and immunofluorescence were performed to detect differential expressions of ABHD5 in testicular tissues of young and aged mice respectively. RESULTS: The TCGA database indicated that the expression of ABHD5 in human testicular carcinoma tissue was significantly lower than that in normal testicular tissue which showed a negative correlation with patient survival. ABHD5 was highly expressed in germ cells of the testis reveaked from Human Protein Atlas and Male Health Atlas databases. The stability of ABHD5 protein was crucial for testicular tissue, and its expression decreased with age. Furthermore, Western blot and immunofluorescence staining demonstrated that ABHD5 expression in the testicular tissue of aged mice was significantly lower than that in young mice. CONCLUSION ABHD5 plays an important role in testicular tissue, and may be inseparable from testicular tumors and reproductive aging. However, its mechanism of action remains to be further studied.
Male ; Animals ; Mice ; Testis/metabolism* ; Humans ; Lipid Metabolism/genetics* ; 1-Acylglycerol-3-Phosphate O-Acyltransferase/metabolism* ; Testicular Neoplasms/metabolism*

The current production of Chinese herbal decoction pieces faces several issues including strong subjectivity,unstable quality,low production efficiency,and a lack of intelligent systems.In order to expedite the intelligent transformation and upgrading of Chinese medicine processing,this paper delves deeply into the problems and challenges encountered in establishing a digital and intel-ligent production model for Chinese herbal pieces.Addressing the slow progress in fundamental research on traditional Chinese medi-cine processing mechanisms,the absence of online digital quality characterization techniques,the low level of production equipment in-telligence,and the lack of evaluation standards for high-quality decoction pieces,this paper proposes a"New Quality Productive Forces"formation approach driven by technological innovation.Through interdisciplinary integration methods,the paper explores the mechanisms of Chinese medicine processing in depth,clarifies the correlation between the processing procedures and the"medicinal properties-quality"relationship,and employs bionic sensing and artificial intelligence to achieve a holistic quality characterization of decoction pieces.Additionally,the use of cloud-edge collaborative big data systems is proposed to enhance intelligent upgrades of the production lines.The paper also aims to establish a high-quality decoction piece evaluation system integrating"physical-chemical-bio-logical"multimodal data fusion.This approach aims to steer the Chinese medicine processing towards becoming more efficient,precise,and sustainable,thereby promoting high-quality sustainable development of the Chinese herbal decoction industry and providing both theoretical and practical support for the modernization of traditional Chinese medicine.

Objective To establish a model of long-term atrazine(ATR)-induced liver injury in mice and to evaluate the hepatotoxic effects induced by ATR.Methods C57BL/6-N male mice were randomly divided into a control group and 1.5 mg/L and 150 mg/L ATR dose(ATR-L,ATR-H)groups.After 35 and 63 days,serum liver function biochemical indexes and inflammatory factors were detected,the hepatosomatic ratio was calculated,and the histopathology and ultrastructure of the liver were observed.Lipid peroxidation levels and antioxidant capacity,the activities of major phase I metabolic enzymes and phase Ⅱ detoxification enzymes,and the expression of related proteins in liver tissues were detected.Results Compared with the control group,the ATR groups showed significant changes in the AST/ALT ratio,levels of pro-inflammatory factors CCL2,TNF-α and IL-6,H2O2 content and activities of the metabolic enzymes NCR,CYTb5,and UDPGT(P＜0.05).In the 150 mg/L ATR group,GGT content,peroxide levels(as indicated by malondialdehyde),and CYP1A2 expression were significantly increased(P＜0.01),while GSH content was significantly decreased(P＜0.05),and hepatocyte injury and mitochondrial vacuolation were more serious when compared to control and 1.5 mg/L groups.Conclusions In a mouse model of low-dose ATR liver injury,both 1.5 mg/L and 150 mg/L ATR exposure induced liver injury in mice,with 150 mg/L ATR inducing the maximum metabolic toxicity in the liver after 63 days.

Objective:This study utilizes a hybrid research design,integrating interviews with experimental surveys,to investigate the variances in patient trust models between tertiary hospitals and primary healthcare institutions.Methods:Thirty-eight residents participated in semi-structured interviews,which were then analyzed using content analysis.The experimental survey segment divided participants into two groups:"Tertiary Hospitals"and"Primary Healthcare Institutions,"resulting in 648 valid questionnaires.These questionnaires were subjected to variance analysis to assess differences.Results:Patients exhibit greater systemic trust in tertiary hospitals than in primary healthcare facilities,while interpersonal trust is stronger in primary healthcare settings.Suggestions:Therefore,strategies should be developed to bolster systemic trust at the primary level and emphasize the advantages of interpersonal trust.Moreover,specific measures are required to reshape patients'interpersonal trust in tertiary hospitals.

Aim To investigate the role and mecha-nism of CXC chemokine receptor 3(CXCR3)in hepa-toblastoma(HB).Methods The expression of CX-CR3 was detected by immunohistochemical and West-ern blot in 16 cases of HB tissue and adjacent normal liver tissue.The HB cells(Huh-6 and HepT1)were transfected with Con-shRNA,CXCR3-shRNA1,and CXCR3-shRNA2,respectively,and then divided into the Con-shRNA group,CXCR3-shRNA1 group,and CXCR3-shRNA2 group.Cell proliferation was detected by CCK-8 assay and EdU staining.Cell migration and invasion were detected by scratch and Transwell as-says.The expressions of β-catenin,c-Myc,cyclin D1,MMP-7 and MMP-9 were detected by Western blot.The tumor formation and tumor volume in each group were assessed using nude mouse xenograft tumor model,while the expressions of MMP-9 and Ki67 in tumor tissue were examined by immunohistochemistry.Results The expression of CXCR3 was up-regulated in HB tissue(P＜0.01).Compared to the Con-shR-NA group,the viability,proliferation,migration and invasion of Huh-6 and HepT1 cells in the CXCR3-shR-NA1 and CXCR3-shRNA2 groups were reduced(P＜0.01),the expressions of the Wnt/β-catenin signaling pathway related proteins were attenuated(P＜0.01),the tumor grew slowly and the volume was significantly reduced(P＜0.01),and the expressions of MMP-9 and Ki67 in tumor tissue decreased(P＜0.01).Con-clusions Downregulation of CXCR3 hinders the pro-liferation and migration of HB cells,potentially as-cribed to the attenuation of Wnt/β-catenin signaling regulation.

Endodontic diseases are a kind of chronic infectious oral disease.Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha.However,it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy(RCT).Recent research,encompassing bacterial etiology and advanced imaging techniques,contributes to our understanding of the root canal system's anatomy intricacies and the technique sensitivity of RCT.Success in RCT hinges on factors like patients,infection severity,root canal anatomy,and treatment techniques.Therefore,improving disease management is a key issue to combat endodontic diseases and cure periapical lesions.The clinical difficulty assessment system of RCT is established based on patient conditions,tooth conditions,root canal configuration,and root canal needing retreatment,and emphasizes pre-treatment risk assessment for optimal outcomes.The findings suggest that the presence of risk factors may correlate with the challenge of achieving the high standard required for RCT.These insights contribute not only to improve education but also aid practitioners in treatment planning and referral decision-making within the field of endodontics.