Diabetic nephropathy (DN) remains a leading cause of end-stage renal disease (ESRD), driven by chronic inflammation, oxidative stress, and apoptosis. Current therapies targeting glycemic and blood pressure control fail to address the underlying molecular mechanisms of DN. This study investigates the therapeutic potential of andrographolide (AD), a diterpenoid lactone from Andrographis paniculata, in mitigating DN by modulating key molecular pathways. Through integrative network pharmacology, molecular docking, and in vivo/in vitro experiments, 107 overlapping DN-related targets were identified, with STAT3, PI3K, and AKT1 emerging as core nodes. Molecular docking revealed high binding affinities between AD and these targets, supporting its modulatory potential. In vivo, AD significantly improved renal function in streptozotocin-induced DN rats, reducing proteinuria, glomerular hypertrophy, and renal fibrosis. AD also attenuated oxidative stress, decreased pro-inflammatory cytokine levels, and enhanced antioxidant enzyme activities, demonstrating systemic anti-inflammatory and antioxidative effects. In vitro studies further confirmed that AD alleviates podocyte oxidative stress and apoptosis under high glucose conditions by suppressing the RAGE-NF-κB and STAT3/PI3K/Akt pathways. Histological analyses revealed substantial improvements in renal architecture, including reductions in fibrosis and mesangial expansion. These results underscore AD’s multi-target mechanism, directly addressing DN’s core pathological drivers, including inflammation, oxidative stress, and apoptosis. As a natural compound with notable safety and efficacy, AD holds promise as an adjunct or standalone therapeutic agent for DN. This study establishes a robust preclinical foundation for AD, warranting further exploration in clinical trials and its potential application in other diabetic complications.

Diabetic nephropathy (DN) remains a leading cause of end-stage renal disease (ESRD), driven by chronic inflammation, oxidative stress, and apoptosis. Current therapies targeting glycemic and blood pressure control fail to address the underlying molecular mechanisms of DN. This study investigates the therapeutic potential of andrographolide (AD), a diterpenoid lactone from Andrographis paniculata, in mitigating DN by modulating key molecular pathways. Through integrative network pharmacology, molecular docking, and in vivo/in vitro experiments, 107 overlapping DN-related targets were identified, with STAT3, PI3K, and AKT1 emerging as core nodes. Molecular docking revealed high binding affinities between AD and these targets, supporting its modulatory potential. In vivo, AD significantly improved renal function in streptozotocin-induced DN rats, reducing proteinuria, glomerular hypertrophy, and renal fibrosis. AD also attenuated oxidative stress, decreased pro-inflammatory cytokine levels, and enhanced antioxidant enzyme activities, demonstrating systemic anti-inflammatory and antioxidative effects. In vitro studies further confirmed that AD alleviates podocyte oxidative stress and apoptosis under high glucose conditions by suppressing the RAGE-NF-κB and STAT3/PI3K/Akt pathways. Histological analyses revealed substantial improvements in renal architecture, including reductions in fibrosis and mesangial expansion. These results underscore AD’s multi-target mechanism, directly addressing DN’s core pathological drivers, including inflammation, oxidative stress, and apoptosis. As a natural compound with notable safety and efficacy, AD holds promise as an adjunct or standalone therapeutic agent for DN. This study establishes a robust preclinical foundation for AD, warranting further exploration in clinical trials and its potential application in other diabetic complications.

Objective To explore the research hotspots and development trends in the field of cancer treatment in the past decade. Methods The CNKI and Web of Science Core Collection databases were searched for Chinese and English articles related to cancer treatment published over the last 10 years. Bibliometric research methods were employed, including keyword cluster analysis of published literature. Results A total of 45 455 Chinese articles and 866 958 English articles were retrieved. Combining the visualization analysis results and the current research dilemma of tumor treatment revealed that the current research hotspots of tumor treatment domestically and internationally can primarily focus on four key areas. In the realm of targeted therapy, efforts are directed towards the discovery of new drug targets, overcoming resistance to targeted therapy, and the development of monoclonal antibodies and antibody–drug conjugates. In the field of immunotherapy, the emphasis lies in enhancing the response rate to immune checkpoint inhibitors, determining the mechanisms behind resistance to immunotherapy, and improving the safety of treatment. The research in traditional Chinese medicine (TCM) covers evidence-based evaluation studies on TCM treatment, the identification of populations that can gain the most benefit from TCM, and strategies for improving the quality of life. In the area of novel drug development, cutting-edge technologies, such as organoid-based screening for anticancer drugs, synthetic biology, and artificial intelligence, are under investigation. Conclusion New targeted drugs, immune efficacy improvement, multidisciplinary integration, nano-delivery, and TCM innovation are the key research directions in the field of tumor therapy in the future.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

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.

OBJECTIVE To sort out the evaluation mechanism and methodology of published cases of comprehensive clinical evaluation of drugs in China， and provide a reference for promoting standardized comprehensive clinical evaluation of drugs and strengthening policy transformation in China. METHODS Clinical comprehensive evaluation cases of drugs published in China from CNKI， Wanfang Data， PubMed and Web of Science were systematically searched， and the retrieval time was from the inception to December 31st， 2023. The summary and analysis were performed from the aspects of theme selection， indicator system construction， evaluation methods， comprehensive decision-making， quality control， etc. RESULTS A total of 143 pieces of literature were ultimately included from 2014 to 2023. The number of publications has shown a rapid upward trend since 2019. The subjects of the evaluation cases were mainly pediatric drugs， Chinese patent medicines， cardiovascular drugs and anti-tumor drugs. The evaluation dimensions were between 3-8， all involving safety and effectiveness dimensions. Most cases adopted rapid evaluation methods based on literature review and expert interviews/questionnaire surveys with less emphasis on real-world research. Most cases did not involve comprehensive decision-making， quality control， or policy transformation. CONCLUSIONS The clinical comprehensive evaluation of drugs in China has made rapid progress under the guidance of national policies. However， there are still issues and challenges such as incomplete evaluation methods and standards， few cases of evaluation results being converted into decision-making， and a lack of quality control mechanisms. It is suggested that standardized evaluation paths and quality control mechanisms should be explored； when the evidence-based basis is insufficient， real-world research should be conducted as much as possible， so as to accelerate the policy transformation of evaluation results.

OBJECTIVE To sort out the evaluation mechanism and methodology of published cases of comprehensive clinical evaluation of drugs in China， and provide a reference for promoting standardized comprehensive clinical evaluation of drugs and strengthening policy transformation in China. METHODS Clinical comprehensive evaluation cases of drugs published in China from CNKI， Wanfang Data， PubMed and Web of Science were systematically searched， and the retrieval time was from the inception to December 31st， 2023. The summary and analysis were performed from the aspects of theme selection， indicator system construction， evaluation methods， comprehensive decision-making， quality control， etc. RESULTS A total of 143 pieces of literature were ultimately included from 2014 to 2023. The number of publications has shown a rapid upward trend since 2019. The subjects of the evaluation cases were mainly pediatric drugs， Chinese patent medicines， cardiovascular drugs and anti-tumor drugs. The evaluation dimensions were between 3-8， all involving safety and effectiveness dimensions. Most cases adopted rapid evaluation methods based on literature review and expert interviews/questionnaire surveys with less emphasis on real-world research. Most cases did not involve comprehensive decision-making， quality control， or policy transformation. CONCLUSIONS The clinical comprehensive evaluation of drugs in China has made rapid progress under the guidance of national policies. However， there are still issues and challenges such as incomplete evaluation methods and standards， few cases of evaluation results being converted into decision-making， and a lack of quality control mechanisms. It is suggested that standardized evaluation paths and quality control mechanisms should be explored； when the evidence-based basis is insufficient， real-world research should be conducted as much as possible， so as to accelerate the policy transformation of evaluation results.

Diabetic nephropathy (DN) remains a leading cause of end-stage renal disease (ESRD), driven by chronic inflammation, oxidative stress, and apoptosis. Current therapies targeting glycemic and blood pressure control fail to address the underlying molecular mechanisms of DN. This study investigates the therapeutic potential of andrographolide (AD), a diterpenoid lactone from Andrographis paniculata, in mitigating DN by modulating key molecular pathways. Through integrative network pharmacology, molecular docking, and in vivo/in vitro experiments, 107 overlapping DN-related targets were identified, with STAT3, PI3K, and AKT1 emerging as core nodes. Molecular docking revealed high binding affinities between AD and these targets, supporting its modulatory potential. In vivo, AD significantly improved renal function in streptozotocin-induced DN rats, reducing proteinuria, glomerular hypertrophy, and renal fibrosis. AD also attenuated oxidative stress, decreased pro-inflammatory cytokine levels, and enhanced antioxidant enzyme activities, demonstrating systemic anti-inflammatory and antioxidative effects. In vitro studies further confirmed that AD alleviates podocyte oxidative stress and apoptosis under high glucose conditions by suppressing the RAGE-NF-κB and STAT3/PI3K/Akt pathways. Histological analyses revealed substantial improvements in renal architecture, including reductions in fibrosis and mesangial expansion. These results underscore AD’s multi-target mechanism, directly addressing DN’s core pathological drivers, including inflammation, oxidative stress, and apoptosis. As a natural compound with notable safety and efficacy, AD holds promise as an adjunct or standalone therapeutic agent for DN. This study establishes a robust preclinical foundation for AD, warranting further exploration in clinical trials and its potential application in other diabetic complications.

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 investigate the value of soluble interleukin-6 (IL-6) receptor (sIL-6R) level in predicting ultrafiltration insufficiency in peritoneal dialysis (PD) patients.Methods:It was a prospective cohort study. The patients who received continuous ambulatory PD and regular follow-up between November 2016 and July 2018 in the PD Center of Renji Hospital, School of Medicine, Shanghai Jiao Tong University were enrolled. Enzyme-linked immunosorbent assay was used to determine dialysate sIL-6R and its appearance rate (AR) was calculated. Patients were divided into high sIL-6R AR group and low sIL-6R AR group according to median value of sIL-6R AR and prospectively followed up until death, PD cessation, or the end of the study (December 31, 2022). Multiple linear regression was used to analyze the related factors of sIL-6R AR. Kaplan-Meier method and log-rank test were used to compare the survival rate difference of ultrafiltration insufficiency between high sIL-6R AR group and low sIL-6R AR group. Multivariate Cox regression and multivariate competing risk models were used to assess the risk factors associated with occurrence of ultrafiltration insufficiency.Results:A total of 198 PD patients were enrolled, including 115 (58.1%) males, with age of (54.9±13.7) years old and PD duration of 22.5 (6.6, 65.0) months. The sIL-6R AR of the cohort was 2 094.7 (1 672.4, 2 920.9) pg/min. Compared with low sIL-6R AR（<2 094.7 pg/min）group, high sIL-6R AR（>2 094.7 pg/min）group had older age ( t=-3.269, P=0.001), higher body mass index ( t=-3.248, P=0.001), proportion of combined diabetes mellitus ( χ2=8.890, P=0.003), 24 h glucose exposure ( Z=-2.257, P=0.024), 24 h ultrafiltration capacity ( Z=-2.515, P=0.012), 4 h dialysate creatinine to serum creatinine ratio ( t=-2.609, P=0.010), mass transfer area coefficient of creatinine ( Z=-2.308, P=0.021), IL-6 AR ( Z=-3.533, P<0.001) and solute glycoprotein 130 AR ( Z=-8.670, P<0.001), and lower serum albumin ( t=2.595, P=0.010) and residual renal function ( t=2.133, P=0.033). Multiple linear regression analysis showed that body mass index ( β=0.194, P=0.005), serum albumin ( β=-0.215, P=0.002) and dialysate lg[IL-6 AR] ( β=0.197, P=0.011) were independently correlated with sIL-6R AR. By the end of the study, 57 (28.8%) patients developed ultrafiltration insufficiency. Kaplan-Meier analysis showed that high sIL-6R AR group had a significantly inferior ultrafiltration insufficiency-free survival rate than that in low sIL-6R AR group (log-rank χ 2=5.375, P=0.020). Multivariate Cox regression analysis and multivariate competing risk models showed that high dialysate sIL-6R AR (>2 094.7 pg/min) was an independent influencing factor of ultrafiltration insufficiency ( HR=2.286 , 95% CI 1.254-4.165 , P=0.007 ; SHR=2.074, 95% CI 1.124-3.828, P=0.020) in PD patients. Conclusions:Dialysate sIL-6R level was associated with body mass index, serum albumin and dialysate IL-6 level. Dialysate sIL-6R may be a predictive factor of ultrafiltration insufficiency in PD patients.