Objective To explore the clinical efficacy of plasma exchange (PE) and double-filtration plasmapheresis (DFPP) pretreatment regimens for high-titer ABO-incompatible kidney transplantation (ABOi-KT). Methods A retrospective analysis was conducted on 31 cases of ABOi-KT with a follow-up period ≥1 year admitted to Zhongshan Hospital Affiliated to Fudan University from April 2016 to August 2025. The efficacy differences between the PE combined with rituximab (RTX) + oral triple immunosuppressive regimen and the DFPP combined with RTX + oral triple immunosuppressive regimen were compared and analyzed. The titers of blood group antibodies and serum creatinine levels before and after the operation were monitored. The survival curves and cumulative risk occurrence curves were plotted using the Kaplan-Meier method. The survival rates of recipients and transplanted kidneys and the occurrence of complications were analyzed. Results Both the PE regimen and the DFPP regimen may effectively reduce the preoperative blood group antibody titer of the recipients to ≤1∶16. The one-year survival rate of the recipients and the transplanted kidneys both reached 100% after the operation. The postoperative serum creatinine levels of recipients who received the DFPP regimen were lower and more stable. There was no statistically significant difference in the incidence of complications between the two regimens during the same follow-up period. Conclusions Both the PE and DFPP regimens are effective pretreatment regimens for ABOi-KT. The DFPP regimen has more advantages in reducing treatment operations, lowering drug dosage and maintaining the stability of postoperative renal function. For recipients with a high initial antibody titer (≥ 1∶32), individualized determination of the number and frequency of plasma processing for pretreatment may achieve ideal therapeutic effects.

ObjectiveTo investigate the protective effect of α-ketoglutarate （α-KG） on hepatic lipid deposition in offspring caused by arsenic exposure during pregnancy. Methods8-week-old institute of cancer research （ICR） mice were mated in a ratio of 2∶1 between females and males， and the detection of vaginal plugs confirmed pregnant. A total of 32 pregnant mice were randomly divided into four groups： control group， arsenic group， α-KG group， arsenic+α-KG group. On gestational day 0-16 （GD0-GD16）， the arsenic and arsenic+α-KG groups were exposed to sodium arsenite （NaAsO₂ ，15 mg/L） in drinking water everyday， and the α-KG and arsenic+α-KG groups were gavaged with α-KG （2 g/kg） everyday. On GD16， pregnant mice were euthanized to collect fetal liver， and fetal body weight and crown-rump length were measured. Gene expression differences between the control group and the arsenic group were analyzed by transcriptome. The total triglycerides （TGs） and subtypes in fetal liver were detected by liquid chromatography tandem mass spectrometry （LC-MS/MS）. Oil red O staining was used to observe the histopathological changes in the liver. Quantitative polymerase chain reaction （qPCR） was used to detect the expression level of genes related to lipid synthesis， transport， and degradation， and phosphatidylinositol 3' -kinase/ protein kinase B （PI3K/AKT） in the liver of fetus. ResultsTranscriptomics analysis showed that 2 144 genes were downregulated and 1 675 genes were upregulated in the arsenic exposed fetal liver； body weight and crown-rump length were reduced （P_TuKey<0.05）； the level of hepatic TGs was elevated in arsenic group （P_TuKey<0.05）； oil-red O staining showed a significant increase in lipid droplets in arsenic group （P_TuKey<0.01）； the expression of lipid synthesis-related genes were significantly upregulated （P_TuKey<0.05）； the expression of β-oxidation-related genes and lipid degradation-related genes were downregulated （P_TuKey<0.05）； the expression of PI3K， AKT decreased（P_TuKey<0.05）. Compared with the arsenic group， the body weight and crown-rump length of fetus increased in the arsenic+α-KG group （P_TuKey<0.05）； the level of hepatic TGs decreased in the arsenic+α-KG group （P_TuKey<0.05）； oil red O staining showed lipid droplets significantly decreased （P_TuKey<0.01）； the expression of lipid synthesis-related genes were downregulated （P_TuKey<0.05）， the expression of β-oxidation-related genes and lipid degradation-related genes were upregulated （P_TuKey<0.05）； the expression levels of PI3K and AKT increased （P_TuKey<0.05）. Conclusionα-KG alleviated hepatic lipid deposition in offspring exposed to arsenic during pregnancy through activating PI3K/AKT signaling pathway.

Early caries confined to the enamel layer represent a critical window for achieving noninvasive intervention in caries management. Caries management has shifted from the traditional “drill-and-fill” model toward a modern paradigm centered on caries risk and lesion management. Based on contemporary concepts, this review systematically summarizes recent advances in early caries management, including caries risk assessment, early diagnosis, treatment strategy selection, and follow-up monitoring, while highlighting the major challenges currently being faced, and further reviewing and discussing the application of artificial intelligence (AI) in early caries management. In terms of risk management, conventional systems including the American Dental Association, Caries Management by Risk Assessment, Cariogram, and the Caries-Risk Assessment Tool remain mainstays in clinical practice. However, AI offers predictive capability through higher-dimensional data processing and the integration of numerous influencing factors, with the potential to improve the accuracy of risk stratification. For diagnosis, visual inspection, tactile examination, and bitewing radiography remain fundamental methods, yet their sensitivity for early caries—particularly proximal lesions—is limited. The application of optical technologies, including quantitative light-induced fluorescence, optical coherence tomography, near-infrared light transillumination, fiber-optic transillumination, and laser-induced fluorescence, enables digital characterization of caries lesions, providing a data foundation for demineralization assessment, lesion activity evaluation, and AI model development. The management of early caries primarily relies on noninvasive and minimally invasive approaches. Remineralization therapy is suitable for superficial lesions, resin infiltration offers the dual advantages of inhibiting lesion progression and improving aesthetics, and microabrasion and bleaching may serve as adjunctive aesthetic treatments. Emerging modalities such as laser, ozone, and photodynamic therapy have also demonstrated potential. Treatment decision-making should comprehensively consider lesion activity, patient caries risk status, demineralization depth, patient compliance, and treatment preferences. However, precise quantification of demineralization depth remains challenging, and standardized decision-making criteria are still lacking. Follow-up management should be individualized based on risk stratification, with attention to lesion changes, patient compliance, and the risk of recurrence. In summary, intelligent and precision-based approaches are expected to define the future of early caries management, and the application of AI in risk prediction, image analysis, and clinical decision support is anticipated to further enhance the efficiency and effectiveness of early caries diagnosis and treatment.

Objective To explore the potential causal relationship between occupational pneumoconiosis (hereinafter referred to as "pneumoconiosis") and five mental disorders (depression, bipolar disorder, schizophrenia, insomnia and anxiety) using the two-sample Mendelian randomization (MR) method. Methods Single nucleotide polymorphisms (SNPs) loci associated with pneumoconiosis and five mental disorders were screened from Genome-Wide Association Studies. Inverse variance weighting (IVW), weighted median (WM) and MR-Egger regression methods were used to evaluate the significance of the causal relationship between pneumoconiosis and five mental disorders. Sensitivity analysis was used to evaluate the accuracy and reliability of the research results. Results After matching data of pneumoconiosis and the five mental disorders, 16 SNPs were ultimately included as instrumental variables in this study. The result of MR analysis revealed a positive causal relationship between pneumoconiosis and both depression [IVW: odds ratio (OR) and 95% confidence interval (CI) was 1.017 (1.000-1.035), P<0.05] and bipolar disorder [IVW: OR(95%CI)was 1.046(1.009-1.083), P<0.05; WM: OR (95%CI) was 1.055(1.007-1.105), P<0.05]. Result of sensitivity analysis indicated there was no heterogeneity and horizontal pleiotropy in the above results. There was no causal association observed between pneumoconiosis and schizophrenia, insomnia, or anxiety disorders (all P>0.05). Conclusion This study provides genetic evidence supporting a positive causal relationship between pneumoconiosis and both depression and bipolar disorder.

Acute Gelsemium poisoning is a systemic disease primarily affecting the central nervous system and respiratory symptoms caused by the ingestion of a substantial amount of Gelsemium within a short period. It manifests as sudden onset and rapid progression, primarily caused by accidental ingestion due to misidentification, and posing significant health risks. The compilation of the Technical Plan for Emergency Health Response to Acute Gelsemium Poisoning describes in detail the specialized practice and technical requirements in the process of handling acute Gelsemium poisoning, including accident investigation and management, laboratory testing and identification, in-hospital treatment, and health monitoring. The guidelines clarify key procedures and requirements such as personal protection, investigation elements, etiology determination, medical rescue, and health education. The key to acute Gelsemium poisoning investigation lies in promptly identifying the toxin through exposure history, clinical manifestations, and sample testing. Because there is no specific antidote for Gelsemium poisoning, immediate removal from exposure, rapid elimination of the toxin, and respiratory monitoring are critical on-site rescue measures. Visual identification of food or herbal materials, followed by laboratory testing to determine Gelsemium alkaloids in samples is a rapid effective screening method. These guidelines offer a scientific, objective, and practical framework to support effective emergency responses to acute Gelsemium poisoning incidences.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis

This study established a high performance liquid chromatography(HPLC) fingerprint of Chuanxiong Rhizoma from different producing areas and screened its potential differential components for producing areas by chemometrics. Furthermore, the content of the above differential components in Chuanxiong Rhizoma from different producing areas was measured and compared. Then, the geoherbalism markers(geo-markers) that can be used to distinguish Dao-di and non-Dao-di Chuanxiong Rhizoma were excavated by chemometrics. In fingerprint studies, a total of 27 common peaks were determined, and the fingerprint similarity for 37 batches of Chuanxiong Rhizoma samples from different producing areas was above 0.968. The orthogonal partial least squares-discriminant analysis(OPLS-DA) was capable of distinguishing Chuanxiong Rhizoma from Sichuan and from three other provinces, as well as Dao-di Chuanxiong Rhizoma(from Dujiangyan) and non-Dao-di Chuanxiong Rhizoma(from other producing areas) in Sichuan province. Meanwhile, 14 potential differential components in Chuanxiong Rhizoma from different provinces and 16 potential differential components in Chuanxiong Rhizoma from different producing areas in Sichuan were screened by the variable importance in projection(VIP) analysis under OPLS-DA. The reference standards were used to identify 10 potential differential components in the common peaks, and subsequent content determination verified that the content of the above 10 potential differential components was different among different producing areas. Then, the OPLS-DA and VIP analysis were performed with the content of the 10 potential differential components as variables. The results showed that Z-ligustilide, chlorogenic acid, and the ratio of butylidenephthalide/senkyunolide A were the geo-markers that can distinguish Chuanxiong Rhizoma from Sichuan and Chuanxiong Rhizoma from Shaanxi, Hebei, and Jiangxi, while Z-ligustilide, n-butylphthalide, and the ratios of Z-ligustilide/senkyunolide A and butylidenephthalide/senkyunolide A were the geo-markers that can distinguish Dao-di Chuanxiong Rhizoma(from Dujiangyan) and non-Dao-di Chuanxiong Rhizoma(from other producing areas) in Sichuan province. This study elucidated the differences in material basis of Dao-di and non-Dao-di Chuanxiong Rhizoma based on fingerprinting and content determination combined with chemometrics, which provides a reference for the study of material basis of Dao-di traditional Chinese medicine.
Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Chemometrics/methods* ; Quality Control