ObjectiveTo investigate the mechanism of Xiezhuo Jiedu prescription in the treatment of ulcerative colitis （UC） by inhibiting ferroptosis and alleviating intestinal mucosal injury based on the nuclear factor E₂ related factor 2/solute carrier family 7 member/glutathione peroxidase 4 （Nrf2/SLC7A11/GPX4） signaling pathway. MethodsA total of 60 male SD rats were divided into a normal group， a model group， high- and low-dose Xiezhuo Jiedu prescription groups （26.64 and 13.32 g·kg^-1， respectively）， a ferroptosis inhibitor group （Ferrostatin-1， 0.005 g·kg^-1）， and a mesalazine group （0.27 g·kg^-1）， with 10 rats in each group. A UC rat model was established by intrarectal administration of trinitrobenzene sulfonic acid （TNBS）-ethanol. The normal group and the model group were intragastrically administered normal saline. The other groups were given intragastric administration according to the corresponding dosage for 7 d. The general condition， disease activity index （DAI） score， colon length， and mucosal injury index （CDMI） score were observed in each group. The pathological changes of colon tissue in each group were observed by hematoxylin-eosin （HE） staining. The intestinal mucosa and mitochondrial morphology in each group were observed by transmission electron microscopy. The expression levels of Occludin， Claudin-1， mucin 2 （MUC2）， and E-cadherin in intestinal tissue were detected by immunofluorescence （IF）. Enzyme-linked immunosorbent assay （ELISA） was used to detect the expression levels of serum tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and interleukin-10 （IL-10） in each group， and a lactic acid assay kit or ELISA was employed to detect the expression levels of reactive oxygen species （ROS）， ferrous ions （Fe²⁺）， glutathione （GSH）， malondialdehyde （MDA）， 4-hydroxynonenal （4-HNE）， diamine oxidase （DAO）， and D-lactate （D-LA）. Real-time quantitative polymerase chain reaction （Real-time PCR） was applied to detect the mRNA expression levels of Nrf2， SLC7A11， GPX4， Occludin， Claudin-1， MUC2， and E-cadherin in each group， and Western blot was adopted to detect the protein expression levels of Nrf2， p-Nrf2， SLC7A11， and GPX4 in each group. ResultsCompared with the normal group， rats in the model group exhibited listlessness， sluggish response， and mucopurulent and bloody stools. The model group also showed significantly increased DAI score， colon length， CDMI score， and expression levels of TNF-α， IL-6， ROS， Fe²⁺， MDA， 4-HNE， DAO， and D-LA （P<0.01）. In addition， it presented significantly decreased IF values of Occludin， Claudin-1， MUC2， and E-cadherin and mRNA and protein expression levels of IL-10， GSH， Nrf2， p-Nrf2， SLC7A11， and GPX4 （P<0.01）. There were different degrees of improvement in each administration group after treatment， and the improvement was the most significant in the high-dose Xiezhuo Jiedu prescription group （P<0.01）. ConclusionXiezhuo Jiedu prescription may alleviate intestinal mucosal injury by inhibiting ferroptosis of intestinal epithelial cells via regulating the Nrf2/SLC7A11/GPX4 signaling pathway， thereby exhibiting efficacy in the treatment of UC.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

ObjectiveThis study aims to explore the potential mechanism of the Xiezhuo Jiedu formula in regulating pyroptosis for the treatment of ulcerative colitis （UC） using bioinformatics and in vivo animal experiments. MethodsDifferentially expressed genes （DEGs） in colon tissues of UC patients were retrieved from the Gene Expression Omnibus （GEO） database. Pyroptosis-related genes were obtained from the GEO and GeneCards databases. The intersection of these datasets yielded pyroptosis-related DEGs （Pyro-DEGs）. Pyro-DEGs were subjected to Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis using the Metascape database. A protein-protein interaction （PPI） network was constructed using the STRING database. Least absolute shrinkage and selection operator （LASSO） prediction model and receiver operating characteristic （ROC） analysis were conducted to identify core Pyro-DEGs with diagnostic and therapeutic potential. Immune infiltration analysis of the UC datasets was performed using the deconvolution method （CIBERSORT）， along with correlation analysis with core Pyro-DEGs. Sixty male Sprague-Dawley （SD） rats were randomly divided into a control group， a model group， high-， medium-， and low-dose groups of Xiezhuo Jiedu formula （26.64， 13.32， 6.66 g·kg^-1）， and a mesalazine group （0.27 g·kg^-1）， with 10 rats in each group. UC was established by intrarectal administration of 3，5-trinitrobenzenesulfonic acid （TNBS） dissolved in ethanol. The control and model groups were given distilled water by gavage， while the treatment groups were administered the corresponding drugs for 7 consecutive days. Hematoxylin-eosin （HE） staining was used to observe the colon histopathology. Enzyme-linked immunosorbent assay （ELISA） was used to detect the levels of inflammatory factors such as interleukin-1β （IL-1β）， IL-10， IL-18， and transforming growth factor-β （TGF-β）. Immunohistochemistry （IHC） and Western blot were applied to detect the expression of Caspase-1， gap junction alpha-1 protein （GJA1）， peroxisome proliferator-activated receptor gamma （PPARG）， and S100 calcium-binding protein A8 （S100A8）. Real-time quantitative polymerase chain reaction （Real-time PCR） was utilized to measure mRNA expression of Caspase-1， GJA1， PPARG， and S100A8. Western blot was performed to assess protein expression levels of Caspase-1， GJA1， PPARG， and S100A8. ResultsGEO datasets GSE87466 and GSE87473 yielded 64 Pyro-DEGs. KEGG analysis indicated that these genes were enriched in the NOD-like receptor signaling pathway， tumor necrosis factor （TNF） signaling pathway， and hypoxia-inducible factor 1 （HIF-1） signaling pathway. Four core Pyro-DEGs （Caspase-1， GJA1， PPARG， and S100A8） were identified. Immune infiltration analysis showed that expression of these genes was positively correlated with mast cells， neutrophils， M0 macrophages， M1 macrophages， and dendritic cells. Animal experimental results indicated that compared with the control group， the model group had significantly increased levels of IL-1β and IL-18， significantly decreased levels of IL-10 and TGF-β. The model group showed enhanced Caspase-1， GJA1， and S100A8 staining， and significantly increased mRNA and protein expression of Caspase-1， GJA1， and S100A8 （P<0.01）. In contrast， the expression of PPARG was reduced in the model group （P<0.01）. After treatment， all dosage groups showed varying degrees of improvement （P<0.05， P<0.01）， with the high-dose group showing the most significant improvement （P<0.01）. ConclusionCaspase-1， GJA1， PPARG， and S100A8 are core Pyro-DEGs closely associated with the pathogenesis of UC. These genes may collaborate with immune cells such as mast cells， neutrophils， and M0 macrophages to mediate disease development. The Xiezhuo Jiedu formula may regulate the expression of core Pyro-DEGs through the NOD-like receptor， TNF， and HIF-1 core signaling pathways， thereby modulating immune homeostasis in UC rats and effectively alleviating UC.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Based on ultra-performance liquid chromatography-quadrupole-electrostatic field Orbitrap high-resolution mass spectrometry(UPLC-Q-Orbitrap HRMS) technology and molecular docking, the bitter-tasting substances(hereafter referred to as "bitter substances") in Cistanche deserticola extract were investigated, and the bitter taste and efficacy relationship was explored to lay the foundation for future research on de-bittering and taste correction. Firstly, UPLC-Q-Orbitrap HRMS was used for the qualitative analysis of the constituents of C. deserticola, and 69 chemical components were identified. These chemical components were then subjected to molecular docking with the bitter taste receptor, leading to the screening of 20 bitter substances, including 6 phenylethanol glycosides, 5 flavonoids, 3 phenolic acids, 2 cycloalkenyl ether terpenes, 2 alkaloids, and 2 other components. Nine batches of fresh C. deserticola samples were collected from the same origin but harvested at different months. These samples were divided into groups based on harvest month and plant part. The bitterness was quantified using an electronic tongue, and the content of six potential bitter-active compounds(pineconotyloside, trichothecene glycoside, tubulin A, iso-trichothecene glycoside, jinshihuaoside, and jingnipinoside) was determined by high-performance liquid chromatography(HPLC). The total content of phenylethanol glycosides, polysaccharides, alkaloids, flavonoids, and phenolic acids was determined using UV-visible spectrophotometry. Chemometric analyses were then conducted, including Pearson's correlation analysis, gray correlation analysis, and orthogonal partial least squares discriminant analysis(OPLS-DA), to identify the bitter components in C. deserticola. The results were consistent with the molecular docking findings, and the two methods mutually supported each other. Finally, network pharmacological predictions and analyses were performed to explore the relationship between the targets of bitter substances and their efficacy. The results indicated that key targets of the bitter substances included EGFR, PIK3CB, and PTK2. These substances may exert their bitter effects by acting on relevant disease targets, confirming that the bitter substances in C. deserticola are the material basis of its bitter taste efficacy. In conclusion, this study suggests that the phenylethanol glycosides, primarily pineconotyloside, mauritiana glycoside, and gibberellin, are the material basis for the "bitter taste" of C. deserticola. The molecular docking technique plays a guiding role in the screening of bitter substances in traditional Chinese medicine(TCM). The bitter substances in C. deserticola not only contribute to its bitter taste but also support the concept of the "taste-efficacy" relationship in TCM, providing valuable insights and references for future research in this area.
Molecular Docking Simulation ; Taste ; Chromatography, High Pressure Liquid ; Cistanche/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Humans ; Mass Spectrometry

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

Diabetic kidney disease (DKD) with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression. Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials. In this study, we integrated large-scale plasma proteomics, genetic-driven causal inference, and experimental validation to identify prioritized targets for DKD using the UK Biobank (UKB) and FinnGen cohorts. Among 2844 diabetic patients (528 with DKD), we identified 37 targets significantly associated with incident DKD, supported by both observational and causal evidence. Of these, 22% (8/37) of the potential targets are currently under investigation for DKD or other diseases. Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4 (IGFBP4), family with sequence similarity 3 member C (FAM3C), and prostaglandin D2 synthase (PTGDS)-were associated with a 4.35, 3.51, and 3.57-fold increased likelihood of developing DKD, respectively. In addition, population-level protein-altering variants (PAVs) analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD, through the classic NLR family pyrin domain containing 3 (NLRP3)-caspase-1-gasdermin D (GSDMD) apoptotic axis. Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.

[Objective] To study on the genotyping of a sample with inconsistent forward and reverse serological tests, and to conduct a pedigree investigation and molecular biological mechanism study. [Methods] The ABO blood group of the proband and his family members were identified using blood group serological method. The ABO gene exon 1-7 of samples of the proband and his family were sequenced by Sanger and single molecule real-time sequencing (SMRT). DeepTMHMM was used to predict and analyze the transmembrane region of proteins before and after mutation. [Results] The proband and his mother have the Bw phenotype, while his maternal grandfather has ABw phenotype. The blood group results of forward and reverse typing of other family members were consistent. ABO gene sequencing results showed that there was B new mutation of c.3 G>C in exon 1 of ABO gene in the proband, his mother and grandfather, leading to a shift in translation start site. DeepTMHMM analysis indicated that the shift in the translation start site altered the protein topology. [Conclusion] The c.3G>C mutation in the first exon of the ABO gene leads to a shift in the translation start site, altering the protein topology from an α-transmembrane region to a spherical signaling peptide, reducing enzyme activity and resulting in the Bw serological phenotype.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.