Fibrosis, the pathological scarring of vital organs, is a severe and often irreversible condition that leads to progressive organ dysfunction. It is particularly pronounced in organs like the liver, kidneys, lungs, and heart. Despite its clinical significance, the full understanding of its etiology and complex pathogenesis remains incomplete, posing substantial challenges to diagnosing, treating, and preventing the progression of fibrosis. Among the various molecular players involved, platelet-derived growth factor-C (PDGF-C) has emerged as a crucial factor in fibrotic diseases, contributing to the pathological transformation of tissues in several key organs. PDGF-C is a member of the PDGFs family of growth factors and is synthesized and secreted by various cell types, including fibroblasts, smooth muscle cells, and endothelial cells. It acts through both autocrine and paracrine mechanisms, exerting its biological effects by binding to and activating the PDGF receptors (PDGFRs), specifically PDGFRα and PDGFRβ. This binding triggers multiple intracellular signaling pathways, such as JAK/STAT, PI3K/AKT and Ras-MAPK pathways. which are integral to the regulation of cell proliferation, survival, migration, and fibrosis. Notably, PDGF-C has been shown to promote the proliferation and migration of fibroblasts, key effector cells in the fibrotic process, thus accelerating the accumulation of extracellular matrix components and the formation of fibrotic tissue. Numerous studies have documented an upregulation of PDGF-C expression in various fibrotic diseases, suggesting its significant role in the initiation and progression of fibrosis. For instance, in liver fibrosis, PDGF-C stimulates hepatic stellate cell activation, contributing to the excessive deposition of collagen and other extracellular matrix proteins. Similarly, in pulmonary fibrosis, PDGF-C enhances the migration of fibroblasts into the damaged areas of lungs, thereby worsening the pathological process. Such findings highlight the pivotal role of PDGF-C in fibrotic diseases and underscore its potential as a therapeutic target for these conditions. Given its central role in the pathogenesis of fibrosis, PDGF-C has become an attractive target for therapeutic intervention. Several studies have focused on developing inhibitors that block the PDGF-C/PDGFR signaling pathway. These inhibitors aim to reduce fibroblast activation, prevent the excessive accumulation of extracellular matrix components, and halt the progression of fibrosis. Preclinical studies have demonstrated the efficacy of such inhibitors in animal models of liver, kidney, and lung fibrosis, with promising results in reducing fibrotic lesions and improving organ function. Furthermore, several clinical inhibitors, such as Olaratumab and Seralutinib, are ongoing to assess the safety and efficacy of these inhibitors in human patients, offering hope for novel therapeutic options in the treatment of fibrotic diseases. In conclusion, PDGF-C plays a critical role in the development and progression of fibrosis in vital organs. Its ability to regulate fibroblast activity and influence key signaling pathways makes it a promising target for therapeutic strategies aiming at combating fibrosis. Ongoing research into the regulation of PDGF-C expression and the development of PDGF-C/PDGFR inhibitors holds the potential to offer new insights and approaches for the diagnosis, treatment, and prevention of fibrotic diseases. Ultimately, these efforts may lead to the development of more effective and targeted therapies that can mitigate the impact of fibrosis and improve patient outcomes.

Systemic lupus erythematosus （SLE）， a refractory autoimmune disease， is among the dominant diseases where traditional Chinese medicine （TCM） shows advantages in the field of rheumatology and immunology. The China-Japan Friendship Hospital hosted the "46^th Youth Salon on Dominant Diseases （Systemic Lupus Erythematosus）" organized by the China Association of Chinese Medicine， which led to a consensus on "the advantages， challenges， interdisciplinary approaches， and translational achievements of integrated TCM and Western medical approaches in the diagnosis and treatment of SLE." The diagnosis and treatment of SLE currently face several challenges， such as frequent misdiagnosis and missed diagnosis in the early stages， difficulty in achieving treatment targets， multiple side effects from pharmacotherapy， and the lack of management strategies for special populations， all of which hinder the fulfillment of the clinical needs of patients. Integrated TCM and Western medical approaches can improve clinical symptoms such as skin erythema， aversion to cold and cold limbs， fatigue， dry mouth， restlessness， and heat sensation in the palms and soles， thereby improving patients' quality of life. The approaches also help consolidate the efficacy of conventional Western medicine， slow disease progression， reduce relapse rates， address multi-organ involvement， and prevent or treat complications. Additionally， they enhance efficacy and reduce toxicity， prevent the side effects of Western medications， help reduce hormone use， and offer distinct advantages in the individualized intervention of special populations， contributing to the whole-process management of the disease. However， evidence-based medical support for this integrated approach remains limited， and the quality of available evidence is generally low. Common evaluation systems and modern research methodologies should be adopted to clarify the efficacy of TCM in SLE treatment. Efforts should be made to carry out high-quality evidence-based medical research， strengthen the development of fundamental and pharmacological research， and further explain the distinct advantages of TCM in the diagnosis and treatment of SLE. Future efforts should focus on advancing the integration of TCM and modern medicine， incorporating multi-omics technologies， individualized stratification， and other precision medicine concepts， in combination with artificial intelligence. Moreover， interdisciplinary collaboration should be promoted to utilize modern technology in exploring the essence of TCM theories and screening effective formulae， thereby comprehensively improving the diagnosis and treatment of SLE through integrated TCM and Western medical approaches.

Systemic lupus erythematosus （SLE）， a refractory autoimmune disease， is among the dominant diseases where traditional Chinese medicine （TCM） shows advantages in the field of rheumatology and immunology. The China-Japan Friendship Hospital hosted the "46^th Youth Salon on Dominant Diseases （Systemic Lupus Erythematosus）" organized by the China Association of Chinese Medicine， which led to a consensus on "the advantages， challenges， interdisciplinary approaches， and translational achievements of integrated TCM and Western medical approaches in the diagnosis and treatment of SLE." The diagnosis and treatment of SLE currently face several challenges， such as frequent misdiagnosis and missed diagnosis in the early stages， difficulty in achieving treatment targets， multiple side effects from pharmacotherapy， and the lack of management strategies for special populations， all of which hinder the fulfillment of the clinical needs of patients. Integrated TCM and Western medical approaches can improve clinical symptoms such as skin erythema， aversion to cold and cold limbs， fatigue， dry mouth， restlessness， and heat sensation in the palms and soles， thereby improving patients' quality of life. The approaches also help consolidate the efficacy of conventional Western medicine， slow disease progression， reduce relapse rates， address multi-organ involvement， and prevent or treat complications. Additionally， they enhance efficacy and reduce toxicity， prevent the side effects of Western medications， help reduce hormone use， and offer distinct advantages in the individualized intervention of special populations， contributing to the whole-process management of the disease. However， evidence-based medical support for this integrated approach remains limited， and the quality of available evidence is generally low. Common evaluation systems and modern research methodologies should be adopted to clarify the efficacy of TCM in SLE treatment. Efforts should be made to carry out high-quality evidence-based medical research， strengthen the development of fundamental and pharmacological research， and further explain the distinct advantages of TCM in the diagnosis and treatment of SLE. Future efforts should focus on advancing the integration of TCM and modern medicine， incorporating multi-omics technologies， individualized stratification， and other precision medicine concepts， in combination with artificial intelligence. Moreover， interdisciplinary collaboration should be promoted to utilize modern technology in exploring the essence of TCM theories and screening effective formulae， thereby comprehensively improving the diagnosis and treatment of SLE through integrated TCM and Western medical approaches.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

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.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Background::Hypertension and non-alcoholic fatty liver disease (NAFLD) share several pathophysiologic risk factors, and the exact relationship between the two remains unclear. Our study aims to provide evidence concerning the relationship between hypertension and NAFLD by analyzing data from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 and Mendelian randomization (MR) analyses.Methods::Weighted multivariable-adjusted logistic regression was applied to assess the relationship between hypertension and NAFLD risk by using data from the NHANES 2017-2018. Subsequently, a two-sample MR study was performed using the genome-wide association study (GWAS) summary statistics to identify the causal association between hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), and NAFLD. The primary inverse variance weighted (IVW) and other supplementary MR approaches were conducted to verify the causal association between hypertension and NAFLD. Sensitivity analyses were adopted to confirm the robustness of the results.Results::A total of 3144 participants were enrolled for our observational study in NHANES. Weighted multivariable-adjusted logistic regression analysis suggested that hypertension was positively related to NAFLD risk (odds ratio [OR] = 1.677; 95% confidence interval [CI], 1.159-2.423). SBP ≥130 mmHg and DBP ≥80 mmHg were also significantly positively correlated with NAFLD. Moreover, hypertension was independently connected with liver steatosis ( β = 7.836 [95% CI, 2.334-13.338]). The results of MR analysis also supported a causal association between hypertension (OR = 7.203 [95% CI, 2.297-22.587]) and NAFLD. Similar results were observed for the causal exploration between SBP (OR = 1.024 [95% CI, 1.003-1.046]), DBP (OR = 1.047 [95% CI, 1.005-1.090]), and NAFLD. The sensitive analysis further confirmed the robustness and reliability of these findings (all P >0.05). Conclusion::Hypertension was associated with an increased risk of NAFLD.

Background::Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients’ recovery.Methods::This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group ( n = 665) and fasting group ( n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results::The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P <0.001) and 20 h (2.4 ± 2.1 vs. 3.4 ± 2.4, t= 7.94, P <0.001) in the CFD group, with least-squares mean differences of 0.48 (95% confidence interval [CI]: 0.26–0.71, P <0.001) and 0.76 (95% CI: 0.57–0.95, P <0.001), respectively. The 4-h pain scores (2.1 ± 1.7 vs. 2.2 ± 1.7, t = 2.60, P = 0.009, with a least-squares mean difference of 0.21 [95% CI: 0.05–0.37]) and positive urine ketone levels (7.7% [39/509] vs. 15.4% [82/533], χ2 = 15.13, P <0.001) were lower in the CFD group. The CFD group had significantly less cholangitis (2.1% [13/634] vs. 4.0% [26/658], χ2 = 3.99, P = 0.046) but not pancreatitis (5.5% [35/634] vs. 6.5% [43/658], χ2 = 0.59, P = 0.444). Subgroup analysis revealed that CFD reduced the incidence of complications in patients with native papilla (odds ratio [OR]: 0.61, 95% CI: 0.39–0.95, P = 0.028) in the multivariable models. Conclusion::Ingesting 400 mL of CFD 2 h before ERCP is safe, with a reduction in post-ERCP fatigue, abdominal pain, and cholangitis during recovery.Trail Registration::ClinicalTrials.gov, No. NCT03075280.

Cancer stem cell(CSC)are the"seed"cells in the occurrence,development,metastasis and recurrence of colorectal cancer.Targeted killing of CSC provides a new target for anti-colorectal cancer therapy.Ferroptosis is an iron-dependent cell death mode due to the abnormal accumulation of intracellular i-ron ions,which results in the massive reactive oxygen species(ROS)and lipid peroxides,leading to cell death.Studies have shown that cancer stem cells are more enriched in iron ions than non-CSC,which provides a new perspective for targeting ferropto-sis in cancer stem cells against colorectal cancer.This article re-views the research progress of inducing CSC ferroptosis in the treatment of colorectal cancer,such as targeted regulation of SLC7A11 expression in CSC,chelating iron in CSC lysosomes,targeting CSC phenotypic plasticity,reversing CSC iron homeo-stasis,and targeting CSC lipid droplet metabolism induce CSC ferroptosis,which provides new ideas for anti-tumor therapy.

Coronary atherosclerotic heart disease(CHD)is an ischemic cardiovascular condition caused by the narrowing or blockage of the vascular lumen due to coronary atherosclerosis.Clinically,it presents as angina pectoris,heart failure,or sud-den cardiac death,and stands as one of the primary causes of mortality among both urban and rural populations in China.Cir-cRNA,classified as non-coding RNAs,can function as upstream regulatory molecules for miRNA or RNA-binding proteins.They actively participate in various pathological processes associated with CHD,including endothelial cell dysfunction,smooth mus-cle cell migration,macrophage-derived foam cell formation,an-giogenesis,myocardial injury,and repair,as well as post-in-farction heart failure.The expression pattern of these molecules is highly specific to the illness and tissue,indicating their poten-tial as therapeutic targets for disease management and as biomar-kers.Furthermore,they also open up new avenues for drug tar-get development in the field of traditional Chinese medicine.This article aims to provide an overview of the recent research progress on circRNA in the regulation of coronary heart disease,as well as the mechanisms involved in traditional Chinese medi-cine.It serves as a valuable reference for future research on cor-onary heart disease.