Oxidative stress is a pivotal factor in the onset and progression of diabetic kidney disease （DKD）， and it plays an essential role in the prevention and treatment of DKD. The "Gaozhuo" pathogenesis posits that DKD is characterized by the invasion of Gaozhuo and damage to the kidney collaterals， with the underlying cause being the insufficiency of spleen Qi and the internal formation of Gaozhuo， which provides valuable guidance on oxidative stress. The insufficiency of spleen Qi and the internal formation of Gaozhuo represent a dynamic， evolving process. Gaozhuo invades the kidney collaterals， impairs kidney Qi， and progressively leads to the congealing and stagnation of Gaozhuo and blood， ultimately resulting in the failure of both the spleen and kidneys. The damage caused by Gaozhuo to the kidney collaterals and kidney Qi is analogous to the organ and functional damage of the kidneys induced by excessive reactive oxygen species and oxidative stress. Damage to the kidney collaterals means organic injuries to the glomeruli， renal tubules， and renal interstitium， and the depletion of kidney Qi refers to damage to glomerular filtration and renal tubular reabsorption. The congealing and stagnation of Gaozhuo and blood in the kidney collaterals is similar to oxidative stress-induced thickening of the glomerular basement membrane and fibrosis. The interaction between spleen and kidney Qi deficiency and the congealing and stagnation of Gaozhuo and blood creates a vicious cycle that exacerbates the condition， ultimately evolving into the failure of both the spleen and kidneys. The failure of the spleen and kidneys is analogous to renal failure， and its extreme manifestation is end-stage renal disease and uremia. The treatment of oxidative stress in DKD with traditional Chinese medicine （TCM） is based on the principles of strengthening the spleen and tonifying the kidneys， and dispelling turbidity and removing blood stasis. According to the syndrome type， it is recommended to use methods such as strengthening the spleen and tonifying Qi while dispelling dampness and removing turbidity， strengthening the spleen and tonifying the kidneys while dispelling dampness and removing turbidity， strengthening the spleen and tonifying the kidneys while dispelling turbidity and removing blood stasis， or consolidating the spleen and kidneys while clearing away turbidity and blood stasis.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective To explore the differences in heartbeat-evoked response (HER) under drug-related cues and neutral cues in individuals with heroin use disorder (HUD), and analyze the correlation between HER potentials and immediate cue-induced craving scores. Methods Fifty HUD participants were recruited from the Chang’an Compulsory Isolation Drug Rehabilitation Center in Shaanxi Province from June to September 2024. Simultaneous acquisition of 64-channel electroencephalography (EEG) and electrocardiogram signals was performed. Twenty alternating segments of drug-related and neutral cue videos were presented, and participants rated their subjective craving after each segment using visual analogue scale (VAS) scores. Scalp EEG data were source analyzed to obtain cortical EEG signals and corresponding HER. Short-time Fourier transform was used to calculate the power spectral density (PSD) of EEG within a time window from 100 ms before the R-peak to 500 ms after it, using the R-peak as the time zero point. Cluster-based permutation testing was used to analyze PSD differences between drug-related and neutral cues in the HUD individuals. Pearson correlation analysis was performed to evaluate the correlation between HER potentials and VAS scores. Results In the 350–420 ms time window, HER potentials in the left posterior parietal, temporal, and posterior cingulate cortices were significantly lower under drug-related cues compared to neutral cues (P＜0.01); in the 140–210 ms time window, HER potentials in the right prefrontal cortex were significantly higher under drug-related cues compared to neutral cues (P＜0.01). Correlation analysis showed that HER potentials in the left temporal and left posterior cingulate cortices were significantly negatively correlated with VAS scores (P＜0.05). Drug-related cues enhanced PSD of γ power (30–100 Hz) in salience network (fronto-insular), parietal and occipital regions (P＜0.05). PSD integrations of low-γ power (40–60 Hz) in parietal region (350–400 ms) and high-γ power (70–100 Hz) in left salience network (fronto-parietal) and occipital regions (300–350 ms) were positively correlated with VAS scores (P＜0.05). Conclusions Drug-related cues may modulate cortical activity related to heartbeat perception in HUD individuals, and such dynamic changes in both time and frequency domains are stably associated with subjective craving.

AIM: To investigate the effects of Conbercept on various optical coherence tomography(OCT)biomarkers in patients with retinal vein occlusion-related macular edema(RVO-ME), and to analyze the correlation of these biomarker changes with visual prognosis.METHODS: Retrospective study. A total of 57 patients(57 eyes)with RVO-ME, including 25 patients(25 eyes)with central retinal vein occlusion(CRVO)and 32 patients(32 eyes)with branch retinal vein occlusion(BRVO), were enrolled in this study. All the patients received intravitreal injection of conbercept once a month, three times in total. The preoperative and postoperative best-corrected visual acuity(BCVA), and changes in OCT biomarkers, including central macular thickness(CMT), the length of disorganization of the retinal inner layers(DRIL), the number of hyperreflective dots(HRD), the area of intraretinal fluid(IRF), the area of subretinal fluid(SRF), and the length of ellipsoid zone(EZ)disruption were compared. Furthermore, the relationship of these changes with BCVA was analyzed.RESULTS:Compared with the baseline, at 3 mo post-treatment, BCVA(LogMAR)was improved, CMT was decreased, the length of DRIL was shortened, the number of HRD was reduced, the area of IRF was decreased, the area of SRF was reduced, and the length of EZ disruption was shortened(all P<0.05). Spearman correlation analysis showed that there was no correlation between the changes in CMT, the length of DRIL, the number of HRD, the area of IRF, the area of SRF and the change in BCVA before and after treatment(P>0.05). However, the change in the length of EZ disruption was positively correlated with the change in BCVA(rs=0.34, P=0.011), and the R2 value of the fitting curve between the change in the length of EZ disruption and the change in BCVA was 0.113(P=0.011). When comparing the pre- and post-treatment changes in BCVA, the length of DRIL, the number of HRD, the area of IRF, the area of SRF, and the length of EZ disruption between patients in the CRVO group and BRVO group, no significant differences were observed(all P>0.05). In contrast, a significant difference was found in the change in CMT between the two groups(P=0.002).CONCLUSION:Conbercept effectively improves multiple OCT biomarkers in patients with RVO-ME. Repair of EZ disruption is a key driver of visual recovery, and its stability may serve as a novel indicator for personalized decision-making in anti-vascular endothelial growth factor therapy.

Lipid droplets (LDs) are dynamic organelles that are ubiquitous across most organisms, including animals, plants, protists, and microorganisms. Their core consists of neutral lipids, surrounded by a phospholipid monolayer adorned with a specific set of proteins. As critical intracellular hubs of metabolic regulation, lipid droplets play essential roles in maintaining physiological homeostasis and contributing to the progression of various pathological processes. They store neutral lipids for energy production during periods of starvation or for membrane biosynthesis, and they sequester fatty acids to mitigate lipotoxicity. Clinically, dysregulation of lipid droplet function is associated with a wide range of diseases, including metabolic dysfunction-associated steatotic liver disease (MASLD), obesity, type 2 diabetes mellitus (T2DM), neurodegenerative disorders, and cancer. Research into the biological functions of lipid droplets—as dynamic organelles and their links to multiple diseases—has emerged as a cutting-edge focus in cell biology. In recent years, significant advances have been made in understanding lipid droplet biogenesis. Researchers have developed a more refined framework that elucidates how LDs are assembled in the endoplasmic reticulum (ER). Triacylglycerols and sterol esters are synthesized between the inner and outer leaflets of the ER bilayer, and when they exceed the critical nucleation concentration (CNC), they coalesce to form neutral lipid lenses. These then bud from the ER under the coordinated action of key proteins such as Seipin, fat storage-inducing transmembrane protein 2 (FIT2), and the peroxisomal membrane protein Pex30. This budding process is driven by changes in membrane curvature and surface tension, induced by the asymmetric distribution of phospholipids. Nascent lipid droplets recruit lipid-synthesizing enzymes via ER-LD bridging structures, enabling localized lipid production and surface expansion, ultimately resulting in the formation of mature LDs. Biochemical and biophysical approaches have revealed important features of this process, underscoring the critical roles of ER membrane biophysical properties and specific phospholipids. Structural biology and proteomic studies have identified key regulators—particularly Seipin and FIT2—as central players in LD biogenesis. This review systematically summarizes recent advances in the molecular mechanisms of LD biogenesis. It delves into the processes of LD nucleation, membrane budding, and expansion in eukaryotic cells, with a special focus on how core factors such as Seipin and FIT2 dynamically regulate LD morphology. In addition, it examines the mechanisms and pathways by which class I and class II proteins are targeted to LDs, compares LD biogenesis involving different neutral lipid cores, and discusses the disease relevance of specific regulatory proteins. Finally, the review outlines critical unresolved questions in the field of LD biogenesis, offering clear directions for future research and providing a comprehensive framework for deepening our understanding of LD formation and its implications for disease intervention.

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 understand the incidence risk and risk factors of tuberculosis (TB) among middle school students in Chongqing, so as to provide a basis for formulating TB prevention and control strategies. Methods: From September to December 2022, 32 181 middle school students were selected as the study cohort from 15 administrative districts in Chongqing by using the stratified cluster random sampling method. All cohort members were screened with the tuberculin skin test (TST), and relevant information was collected from January 1, 2023 to December 31, 2024. On the basis of active screening, the follow up data of the participants were compared with the National Tuberculosis Management Information System to obtain the incidence status of the study subjects. The Log rank test was used to compare the TB incidence rates among students with different characteristics, and a Cox proportional hazards model was established to analyze the incidence risk and risk factors of TB. Results: The TST screening rate of the cohort members was 93.0%. During the 2 year follow up period, a total of 36 TB cases occurred, with a cumulative incidence rate of 111.87/100 000 and an incidence density of 55.95/100 000. Among them, the cumulative incidence rate of students from public schools (170.44/ 100 000 ) was higher than that of students from private schools (41.16/100 000), the cumulative incidence rate of students in schools located in high epidemic areas (153.95/100 000) was higher than that in medium epidemic areas (69.00/100 000), and the difference was statistically significant ( χ 2=11.49, 4.73, both P <0.05). The Log-rank test for different TST results showed that the difference in TB comulative incidence rate between students with strongly positive TST results (216.55/ 100 000 ) and those with negative TST results (81.40/100 000) was statistically significant ( χ 2=5.85, P <0.05). Univariate analysis using the Cox proportional hazards model revealed that the risk of TB was lower in students from private schools ( HR=0.25, 95% CI = 0.10-0.59) and students in medium epidemic areas ( HR=0.46, 95%CI =0.23-0.94); whereas the risk of TB was increased in students with strongly positive TST results ( HR=1.39, 95%CI =1.05-1.84) (all P <0.05). Multivariate Cox regression analysis showed that the risk of TB in students from private schools was lower than that of students from public schools ( HR=0.23, 95%CI=0.08-0.62, P <0.05). Conclusions The annual average incidence rate of TB among middle school students in Chongqing is at a relatively high level. It is necessary to strengthen the management and intervention for student groups, including those in public schools, those in schools located in high epidemic areas, and those with strongly positive TST results, so as to reduce the incidence rate of TB.

ObjectiveTo characterize the seasonal patterns of influenza in Kunming City, Yunnan Province before, during, and after the COVID-19 pandemic, and provide scientific evidence for optimizing influenza prevention and control strategies. MethodsInfluenza-like illness (ILI) and etiological surveillance data for influenza from the 14^th week of 2010 to the 13^th week of 2024 in Kunming City of Yunnan Province were collected. Harmonic regression models were constructed to analyze the epidemic characteristics and seasonal patterns of influenza before (2010/2011‒2019/2020 influenza seasons), during (2020/2021‒2022/2023 influenza seasons), and after (2023/2024 influenza season) the COVID-19 pandemic. ResultsBefore the COVID-19 pandemic, influenza in Kunming City mainly exhibited an annual cyclic pattern without a significant semi-annual periodicity, peaking from December to February of the next year, with an epidemic duration of 20‒30 weeks. During the pandemic, influenza seasonality shifted, with an increase in semi-annual periodicity and an approximate one month delay in annual peaks. However, after the pandemic, the annual amplitude of influenza increased compared with that before the pandemic, and the epidemic duration extended by about one month. Although the annual peak largely reverted to the pre-pandemic levels, the annual peaks for different influenza subtypes/lineages had not fully recovered. ConclusionInfluenza seasonality in Kunming City underwent substantial alterations following the COVID-19 pandemic and has not yet fully reverted to pre-pandemic levels. Continuous surveillance on different subtypes/lineages of influenza viruses remains essential, and prevention and control strategies should be adjusted and optimized in a timely manner based on current epidemic trends.

Ferroptosis, an iron-dependent programmed cell death process driven by reactive oxygen species-mediated lipid peroxidation, is regulated by several metabolic processes, including iron metabolism, lipid metabolism, and redox system. Macrophages are a group of innate immune cells that are widely distributed throughout the body, and play pivotal roles in maintaining metabolic balance by its phagocytic and efferocytotic effects. There is a profound association between the biological functions of macrophage and ferroptosis. Therefore, this review aims to elucidate three key aspects of the unique relationship between macrophages and ferroptosis, including macrophage metabolism and their regulation of cellular ferroptosis; ferroptotic stress that modulates functions of macrophage and promotion of inflammation; and the effects of macrophage ferroptosis and its role in diseases. Finally, we also summarize the possible mechanisms of macrophages in regulating the ferroptosis process at the global and local levels, as well as the role of ferroptosis in the macrophage-mediated inflammatory process, to provide new therapeutic insights for a variety of diseases.
Ferroptosis/physiology* ; Macrophages/metabolism* ; Humans ; Animals ; Iron/metabolism* ; Reactive Oxygen Species/metabolism* ; Lipid Peroxidation/physiology* ; Inflammation/metabolism*