Esophageal cancer is a prevalent malignant tumor of the digestive tract in China, and radical surgery remains the cornerstone of its comprehensive treatment. However, multifactorial challenges such as postoperative gastrointestinal tract reconstruction, traumatic stress, and tumor-related metabolic disturbances render esophageal cancer patients highly susceptible to malnutrition. Perioperative nutritional support therapy plays a crucial role in enhancing surgical safety, improving clinical outcomes, and elevating patients' quality of life by regulating metabolic homeostasis, preserving organ function, and optimizing the immune microenvironment. This article reviews the mechanisms underlying malnutrition in esophageal cancer, methods for nutritional status assessment, and precision intervention pathways based on multi-omics evaluations. The aim is to strengthen clinicians' awareness of standardized perioperative nutritional management for esophageal cancer patients and promote its clinical implementation, thereby facilitating postoperative recovery and improving long-term quality of life.

Lung cancer remains one of the leading causes of cancer-related morbidity and mortality worldwide, and its treatment continues to face major challenges such as therapeutic resistance and tumor recurrence. Pyroptosis, a newly characterized form of programmed cell death, induces tumor cell death through gasdermin-mediated membrane pore formation and is accompanied by the release of inflammatory mediators, thereby playing complex roles in lung cancer initiation, progression, and modulation of the tumor microenvironment. Active components and herbal formulas derived from traditional Chinese medicine can modulate pyroptosis-related signaling pathways through multi-target mechanisms, showing potential advantages in inducing lung cancer cell death, inhibiting proliferation and migration, and reversing chemoresistance. This review systematically summarizes relevant studies from domestic and international sources, focusing on the molecular mechanisms of pyroptosis, its roles in lung cancer development and tumor microenvironment remodeling, and the current research progress on traditional Chinese medicine-based interventions targeting pyroptosis, with the aim of providing references for the prevention and treatment of lung cancer using traditional Chinese medicine.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

BACKGROUND: Disease-modifying therapies have been approved for the treatment of relapsing multiple sclerosis (RMS). The present study aims to examine the safety of teriflunomide in Chinese patients with RMS. METHODS: This non-randomized, multi-center, 24-week, prospective study enrolled RMS patients with variant (c.421C>A) or wild type ABCG2 who received once-daily oral teriflunomide 14 mg. The primary endpoint was the relationship between ABCG2 polymorphisms and teriflunomide exposure over 24 weeks. Safety was assessed over the 24-week treatment with teriflunomide. RESULTS: Eighty-two patients were assigned to variant ( n  = 42) and wild type groups ( n  = 40), respectively. Geometric mean and geometric standard deviation (SD) of pre-dose concentration (variant, 54.9 [38.0] μg/mL; wild type, 49.1 [32.0] μg/mL) and area under plasma concentration-time curve over a dosing interval (AUC tau ) (variant, 1731.3 [769.0] μg∙h/mL; wild type, 1564.5 [1053.0] μg∙h/mL) values at steady state were approximately similar between the two groups. Safety profile was similar and well tolerated across variant and wild type groups in terms of rates of treatment emergent adverse events (TEAE), treatment-related TEAE, grade ≥3 TEAE, and serious adverse events (AEs). No new specific safety concerns or deaths were reported in the study. CONCLUSION: ABCG2 polymorphisms did not affect the steady-state exposure of teriflunomide, suggesting a similar efficacy and safety profile between variant and wild type RMS patients. REGISTRATION NCT04410965, https://clinicaltrials.gov .
Humans ; Crotonates/adverse effects* ; Toluidines/adverse effects* ; Nitriles ; Hydroxybutyrates ; Female ; Male ; Adult ; ATP Binding Cassette Transporter, Subfamily G, Member 2/genetics* ; Middle Aged ; Multiple Sclerosis, Relapsing-Remitting/genetics* ; Prospective Studies ; Young Adult ; Neoplasm Proteins/genetics* ; East Asian People

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective To analyze the nonlinear relationship between hypothermic machine perfusion (HMP) parameters and delayed graft function (DGF) and optimize the construction of a predictive model for DGF. Methods The data of 923 recipients who underwent kidney transplantation from deceased donors were retrospectively analyzed. According to the occurrence of DGF, the recipients were divided into DGF group (n=823) and non-DGF group (n=100). Donor data, HMP parameters and recipient data were analyzed for both groups. The nonlinear relationship between HMP parameters and the occurrence of DGF was explored based on restricted cubic splines (RCS). Over-sampling, under-sampling and balanced sampling were used to address the imbalance in the proportion of DGF to construct logistic regression predictive models. The area under the curve (AUC) of each model was compared in the validation set, and a nomogram model was constructed. Results Donor BMI, cold ischemia time of the donor kidney, and HMP parameters (initial and final pressures, resistance, and perfusion time) were significantly different between the DGF and non-DGF groups (all P<0.05). The RCS analysis revealed a threshold-like nonlinear relationship between HMP parameters and the risk of DGF. Among the models constructed using different sampling methods, the balanced sampling model had the highest AUC. Using this model, a nomogram was constructed to stratify recipients based on risk scores. Recipients in the high-risk group had higher serum creatinine levels at 1, 6, and 12 months after kidney transplantation compared to those in the low-risk group (all P<0.05). Conclusions There is a nonlinear relationship between HMP parameters and the risk of DGF, and the threshold is helpful for organ quality assessment and monitoring of graft function after transplantation. The predictive model for DGF constructed on the base of balanced sampling algorithms helps perioperative decision-making and postoperative graft function monitoring of kidney transplantation.

ObjectiveTo establish the quality standards for Sennae Folium（Cassia angustifolia） dispensing granules based on standard decoctions. MethodsHigh performance liquid chromatography（HPLC） specific chromatograms were established for 15 batches of Sennae Folium（C. angustifolia） standard decoctions and 10 of Sennae Folium（C. angustifolia） dispensing granules from different manufacturers， and the similarity evaluation， hierarchical cluster analysis（HCA） and principal component analysis（PCA） were performed. Linear calibration with two reference substances（LCTRS） and quantitative analysis of multi-components by single-marker（QAMS） were established for the common peaks in the specific chromatograms to determine the contents of main components in the decoction pieces， standard decoctions and dispensing granules， and to calculate their transfer rates from decoction pieces to standard decoctions and dispensing granules. ResultsThe similarities of specific chromatograms of 15 batches of Sennae Folium（C. angustifolia） standard decoctions and 10 batches of Sennae Folium（C. angustifolia） dispensing granules were all greater than 0.95， and a total of 8 characteristic peaks were calibrated， and five of them were identified， including kaempferol-3，7-O-diglucoside， apigenin-6，8-di-C-glucoside， quercetin-3-O-gentianoside， sennoside B and sennoside A. HCA and PCA results showed that there were certain differences in the composition of different batches of standard decoctions， but no clustering was observed in the production area. As the standard decoctions， the extract rate of 15 batches of samples was 26.54%-45.38%， the contents of kaempferol-3，7-O-diglucoside， apigenin-6，8-di-C-glucoside， quercetin-3-O-gentianoside， sennoside B and sennoside A were 12.16-19.26， 2.57-4.94， 3.27-5.11， 6.75-11.39， 4.69-7.79 mg·g^-1， and their transfer rates from decoction pieces to standard decoctions were 45.41%-79.02%， 29.12%-55.07%， 40.52%-67.90%， 24.72%-49.12%， 27.54%-49.34%， respectively. The extract rates of Sennae Folium（C. angustifolia） dispensing granules（C8-C10） were 38.10%-39.50%， the transfer rates of the above five components from decoction pieces to dispensing granules were 72.85%-73.58%， 53.43%-53.94%， 40.19%-40.74%， 24.62%-25.00%， 28.65%-29.11%， respectively， which were generally consistent with the transfer rates from decoction pieces to standard decoctions. ConclusionCompared with the relative retention time method， LCTRS has higher prediction accuracy and is more suitable for chromatographic columns. The established quality control standard of Sennae Folium（C. angustifolia） dispensing granules based on standard decoction is reasonable and reliable， and all indicators of samples from different manufacturers are within the range specified based on the standard decoction， which can provide reference for the quality control and process research of this dispensing granules.

ObjectiveTo establish the specific chromatogram of Chuanxiong Rhizoma dispensing granules（CRdg）， and to evaluate its quality by chemometrics and two reference substances for determination of multiple components（TRSDMC）. MethodsHigh performance liquid chromatography（HPLC） specific chromatograms were established using 13 batches of CRdg from 7 manufacturers， and preliminary quality evaluation was performed by similarity evaluation and chemometrics analysis. Eight characteristic peaks in the specific chromatogram of CRdg were measured on 22 different types of C₁₈ columns， and the actual retention times were recorded. Taking chlorogenic acid（peak 1） and senkyunolide A（peak 8） as double standard compounds， the retention times of the eight characteristic peaks were predicted by linear calibration using two reference substances（LCTRS）， and the method was validated on three other columns of different brands. Taking chlorogenic acid as reference peak， the relative correction factor method（RCFM） was used to quantify cryptochlorogenic acid， caffeic acid， ferulic acid， senkyunolide I and senkyunolide A， and the results were compared with the external standard method（ESM）. ResultsThe similarities of specific chromatograms of 13 batches of CRdg were all >0.90， and a total of 8 characteristic peaks were calibrated， and six of them were identified， including chlorogenic acid（peak 1）， cryptochlorogenic acid（peak 2）， caffeic acid（peak 3）， ferulic acid（peak 5）， senkyunolide I（peak 6） and senkyunolide A（peak 8）. Through chemometric analysis， it was found that ferulic acid， chlorogenic acid， senkyunolide I and cryptochlorogenic acid were the main components causing quality difference in CRdg， and the accuracy of LCTRS in predicting the retention time of 8 characteristic peaks was superior to that of the relative retention time method（RRT）. Further comparison of the results obtained from RCFM and ESM showed that there was no statistically significant difference between the two methods. ConclusionA quality evaluation method for CRdg based on HPLC specific chromatogram and TRSDMC is established， its qualitative accuracy is better than that of RRT， the quantitative accuracy is similar to that of ESM， and 4 quality-differentiated components among different manufacturers are found. This method is stable and reliable， and has reference value for the quality evaluation of other dispensing granules.