Indobufen is a new generation of antiplatelet agents and has been shown to have antithrombotic effects in animal models. However, its therapeutic potential and mechanisms against cerebral ischemia/reperfusion (I/R) injury remain unclear. In this study, we evaluated the in vivo neuroprotective effects of indobufen through both pretreatment and posttreatment regimens in a rat model of middle cerebral artery occlusion/reperfusion (MCAO/R). In vitro, human umbilical vein endothelial cells (HUVECs) subjected to oxygen-glucose deprivation/reoxygenation (OGD/R) were employed to investigate the relationship between indobufen and the pyroptosis-associated NF-κB/Caspase-1/GSDMD pathway. The pharmacodynamic tests revealed that indobufen ameliorated I/R injury by decreasing the level of thromboxane B2 (TXB2), infarct size, brain edema and neurological impairment in rats and rescuing cell pyroptosis in HUVECs. The underlying mechanisms were probably related to pyroptosis suppression by regulating the NF-κB/Caspase-1/GSDMD pathway. Overall, these studies indicate that indobufen exerts protective and therapeutic effects against I/R injury by pyroptosis suppression via downregulating NF-κB/Caspase-1/GSDMD pathway.

Optical microscopy is essential for exploring biological and material structures, with resolution determining the level of observable detail. The advent of super-resolution fluorescence microscopy has broken the diffraction limit, achieving nanoscale resolution. However, traditional assessment methods, such as the Rayleigh criterion and point spread function (PSF) width measurement, rely on empirical judgments and diffraction-limited models, rendering them inadequate for modern super-resolution imaging. This review systematically traces the evolution of resolution assessment methodologies, from classical criteria to advanced strategies tailored for various super-resolution modalities. We first discuss Fourier-based quantitative methods. Fourier ring correlation (FRC) and its 3D counterpart, Fourier shell correlation (FSC), objectively determine resolution by evaluating the statistical correlation of two independent image reconstructions in frequency space. These methods offer robustness against noise and provide a global resolution metric, but they require data independence and are computationally intensive. They have become the prevailing standards in electron and super-resolution microscopy. Subsequently, we examine adaptations for specific super-resolution techniques. For single-molecule localization microscopy (SMLM) techniques such as PALM and STORM, the Fourier image resolution (FIRE) method extends FRC by incorporating a physical model that accounts for localization precision and labeling density. For stimulated emission depletion (STED) microscopy and other nonlinear techniques, assessment strategies differ. While PSF shrinkage measurements using fluorescent beads are useful for system calibration, evaluating the effective resolution directly on biological samples is more practical. This is typically performed via linewidth analysis of known structures (e.g., microtubules) or edge-spread function measurements, capturing the effects of photobleaching and sample-induced aberrations. A major paradigm shift is parameter-free resolution estimation based on decorrelation analysis. This method analyzes the autocorrelation decay of a single image’s Fourier spectrum to identify the cutoff spatial frequency without requiring dual datasets or user-defined thresholds. Its high efficiency and broad applicability have been validated across widefield, confocal, STED, SIM, and SMLM modalities. Optimized rendering strategies for SMLM data further enhance its accuracy, and it is emerging as a tool for real-time optimization of experimental parameters. The review also addresses the “gold standard” of resolution validation using well-defined nanostructures, such as DNA origami and nuclear pore complexes, which provide ground truth for verifying resolution claims and detecting artifacts. In the era of artificial intelligence, deep learning plays a dual role: it powerfully enhances image resolution but also introduces challenges, as models may generate “hallucinations” or false details. This underscores the need for new validation metrics to verify the physical fidelity of AI-generated content. Finally, we outline future directions: developing unified cross-modality standards, enabling real-time dynamic resolution monitoring for live-cell imaging, creating techniques for generating local resolution maps to capture sample heterogeneity, and integrating intelligent error correction to ensure data veracity. By providing a comprehensive overview of resolution assessment progress and challenges, this review aims to equip researchers with the knowledge to select appropriate tools, thereby fostering rigorous quantitative imaging in the life and material sciences.

ObjectiveThe present study aimed to investigate alterations in white matter microstructure and spontaneous neural activity in male college smokers, and to further explore their associations with nicotine dependence. Given that adolescence and early adulthood represent critical periods for brain maturation, particularly for white matter development, understanding the neural correlates of smoking behavior during this stage is of substantial importance for both neuroscience and public health. MethodsA total of 115 male undergraduate students were initially recruited for this study. After quality control and exclusion procedures, 52 male college smokers and 42 demographically matched healthy non-smokers were included in the final analysis. All participants underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI). White matter fiber tracts were reconstructed using the automated fiber quantification (AFQ) method, which enables precise identification and quantification of major fiber bundles. Eighteen major white matter tracts were segmented for each participant. Along the core trajectory of each tract, 100 equidistant nodes were sampled. Fractional anisotropy (FA) was calculated at each node to assess white matter microstructural integrity, while amplitude of low-frequency fluctuation (ALFF) was computed to evaluate spontaneous neural activity within white matter tracts. Between-group differences in FA and ALFF were assessed using two-sample t-tests, with appropriate corrections applied for multiple comparisons. Furthermore, Pearson correlation analyses were conducted to examine the relationships between imaging-derived metrics (FA and ALFF values in regions showing significant group differences) and nicotine dependence severity, as measured by the Fagerström test for nicotine dependence (FTND). ResultsCompared with healthy non-smokers, male college smokers exhibited significantly increased FA values in several white matter tracts, including the left thalamic radiation, right corticospinal tract, forceps major of the corpus callosum, left uncinate fasciculus, and right arcuate fasciculus. These findings suggest altered microstructural organization or increased directional coherence within these pathways. In addition, smokers demonstrated significantly elevated ALFF values in the forceps major, right uncinate fasciculus, and left arcuate fasciculus, indicating enhanced spontaneous neural activity in these white matter regions. Correlation analyses revealed that FA values in the left thalamic radiation and right corticospinal tract were negatively correlated with FTND scores, suggesting that higher levels of nicotine dependence were associated with reduced microstructural integrity or altered fiber organization in these regions. In contrast, ALFF values in the forceps major and right uncinate fasciculus were positively correlated with FTND scores, indicating that greater nicotine dependence was associated with increased spontaneous neural activity in specific white matter pathways. ConclusionThe present study provides evidence that male college smokers exhibit distinct alterations in both white matter microstructure and functional activity. These abnormalities are not uniformly distributed but rather localized to specific fiber tracts implicated in sensorimotor processing, interhemispheric communication, and higher-order cognitive and emotional regulation. Importantly, the observed associations between imaging metrics and nicotine dependence severity suggest that these structural and functional alterations may reflect neurobiological mechanisms underlying addiction. The combination of AFQ-based tract profiling and multimodal MRI offers a sensitive approach for detecting subtle changes along white matter pathways, highlighting its potential utility in identifying neuroimaging biomarkers of nicotine dependence. Overall, these findings indicate that smoking during early adulthood may disrupt ongoing white matter maturation, potentially leading to long-term consequences for brain function. This study provides novel insights into the neural basis of nicotine dependence and underscores the importance of early intervention and prevention strategies targeting young smokers.

ObjectiveTo investigate the protective effect of liver-targeted fibroblast growth factor 21 （FGF21） overexpression against CCl₄-induced acute liver injury （ALI） and its association with silent information regulator 1/glutathione peroxidase 4 （SIRT1/GPX4） expression and ferroptosis-related markers. MethodsFemale ICR mice （8 weeks old） were randomly divided into Control， CCl₄， adeno-associated virus （AAV）-FGF21， and AAV-FGF21 + CCl₄ groups. Liver-targeted FGF21 overexpression was achieved via tail vein injection of AAV8-FGF21 virus with green fluorescent protein （GFP） labeling. ALI was induced by intraperitoneal injection of CCl₄ （0.3 mL/kg）， with sample collection at 12 hours. Body weight and liver weight were recorded to calculate the liver weight/body weight. Alanine aminotransferase （ALT） and aspartate aminotransferase （AST） levels were measured using a biochemical analyzer. FGF21 expression in liver tissues was detected by immunofluorescence. Hepatic histopathology was evaluated by HE staining. RT-qPCR was performed to assess mRNA expression of ferroptosis and iron metabolism-related genes （ACSL4， PTGS2， HJV， FPN， GPX4）， FGF21， and SIRT1. Protein expression of FGF21， SIRT1， and GPX4 were determined by Western blot. Iron content， malondialdehyde （MDA）， glutathione （GSH）， and superoxide dismutase （SOD） activity in liver homogenate were quantified using assay kits. ResultsCompared with the Control group， the FGF21 mRNA and protein expression elevated in CCl₄ group； serum ALT/AST levels and liver weight/body weigh increased. The HE staining results showed that the liver cell membranes were ruptured. The mRNA levels of ACSL4 and PTGS2， the iron content and MDA levels all increased （P<0.01）. The mRNA levels of SIRT1， GPX4， HJV， and FPN， the GSH level and SOD activity all decreased （P<0.05）， and the protein levels of SIRT1 and GPX4 both decreased （P<0.05）. Compared with the CCl₄ group， the serum levels of ALT and AST in the AAV-FGF21 + CCl4 group were decreased （P<0.01）， and the liver/body ratio of mice decreased （P<0.01）. The results of HE staining showed that the degree of liver injury was alleviated. The mRNA levels of ACSL4 and PTGS2， iron content and MDA level all decreased （P<0.01）， while the mRNA levels of SIRT1， GPX4， HJV， FPN， GSH level and SOD activity all increased （P<0.05）. The protein levels of SIRT1 and GPX4 both increased （P<0.05）. ConclusionFGF21 overexpression is associated with enhanced SIRT1/GPX4 expression and suppression of ferroptosis features， thereby contributing to the alleviation of CCl₄-induced ALI.

Objective To summarize the clinical features and treatment strategies of acute mercury poisoning caused by intramuscular injection of metallic mercury. Methods The clinical data of a patient with acute mercury poisoning following intramuscular injection of metallic mercury were collected, and a retrospective analysis of the diagnosis and treatment process was conducted. Results The patient was a 14-year-old boy who self-injected 20 g of metallic mercury into the left upper arm muscle. Clinical manifestations included fever, chest tightness, cough, and a painful mass at the injection site. Laboratory tests of the patient indicated that blood mercury level was 4.160 μmol/L, urinary mercury level was 6 545.50 μg/g creatinine, urinary retinol-binding protein was 6 556 μg/L, urinary β₂-microglobulin was 8 726.48 μg/g creatinine, and urinary α1-microglobulin was 41.60 mg/L at day 11 after injection. Thoracoabdominal imaging revealed mercury deposition in the lungs, heart, liver, kidneys, and other organs. The patient's clinical symptoms were markedly relieved after one course of treatment with sodium dimercaptopropanesulfonate for mercury chelation. Subsequent treatment included continued mercury chelation therapy, debridement of muscle tissue at the injection site, removal of retained foreign bodies, and other supportive measures. Reexamination showed a blood mercury level of 2.810 μmol/L and urinary mercury level of 5 280 μg/L at day 127 after injection. Conclusion The clinical manifestations of intramuscular injection of metallic mercury poisoning differ from those of occupational mercury poisoning. Debridement of the injection site combined with sodium dimercaptopropanesulfonate chelation therapy can alleviate systemic symptoms and reduce mercury levels in such patients.

Objective To investigate the relationship between brain white matter lesions (WML) and triglyceride glucose (TyG) index in non-diabetic elderly individuals based on magnetic resonance imaging. Methods A total of 523 non-diabetic elderly individuals aged ≥ 60 years were selected from Jinan, Shandong Province, China from June 2018 to December 2019. According to the quartiles of TyG index, there were 133 participants in the first quartile (Q1) group, 127 in the second quartile (Q2) group, 132 in the third quartile (Q3) group, and 131 in the fourth quartile (Q4) group. All participants underwent brain magnetic resonance imaging to evaluate paraventricular, deep, and total WML volumes, as well as Fazekas scores. Results Compared with Q1, Q2, and Q3 groups, Q4 group showed significant increase in periventricular, deep, and total WML volumes (P < 0.05). The proportion of participants with a Fazekas score ≥ 2 in the periventricular, deep, and total WML was higher in the Q4 group compared with the Q1 and Q2 groups (P < 0.05). The proportion of participants with a Fazekas score ≥ 2 in deep WML was higher in Q4 group than in Q3 group (P < 0.05). TyG index was significantly positively correlated with periventricular, deep, and total WML volumes (r = 0.401, 0.405, and 0.445, P < 0.001). After adjusting for confounding factors, TyG index was still significantly positively correlated with periventricular, deep, and total WML volumes (P < 0.001). Logistic regression analysis showed that compared with Q1 group, the risk of Fazekas score ≥ 2 in periventricular WML was 1.950-fold (95% confidence interval [CI]: 1.154-3.294, P = 0.013) in Q3 group and 3.411-fold (95% CI: 1.984-5.863, P < 0.001) in Q4 group, the risk of Fazekas score ≥ 2 in total WML was 2.529-fold (95%CI: 1.444-4.430, P = 0.001) in Q3 group and 4.486-fold (95%CI: 2.314-8.696, P < 0.001) in Q4 group. The risk of Fazekas score ≥ 2 in deep WML was 2.953-fold (95%CI: 1.708-5.106, P < 0.001) in Q4 group compared with Q1 group. Conclusion Increased TyG index is an independent risk factor for WML in non-diabetic elderly individuals.

OBJECTIVE: To preliminarily investigate the effect of buccal acupuncture therapy on ameliorating postoperative pain and enhancing recovery quality among patients undergoing radical resection of gastrointestinal cancers. METHODS: Fifty-two participants were randomized at a 1:1 ratio to either the buccal acupuncture or the control group. The acupuncture protocol entailed targeting 5 predetermined acupoints [CA-2 (Upper jiao), CA-3 (Middle jiao), CA-4 (Lower jiao), CA-6 (back), and CA-7 (waist) and two adjustable acupoints [CA-1 (head) and CA-8 (sacrum)] on each side of the face. The outcomes included the Numeric Rating Scale (NRS) scores for each day within 7 days postoperatively, 15-Item Quality of Recovery Scale (QoR-15) scores, analgesics consumption during and after surgery, incidences of postoperative nausea and vomiting, and perioperative levels of interleukin-6 and glucose. Adverse events related to acupuncture were recorded. RESULTS: Of the initial 52 participants, 46 completed the study and were included in the analysis. Findings indicated that the buccal acupuncture group experienced significantly reduced resting NRS scores in post-anesthesia care unit and throughout the postoperative phase (P=0.001 and P=0.003, respectively), along with enhanced QoR-15 scores on the 3rd postoperative day (P=0.008), compared to the control group. No notable differences were identified in the remaining indicators (P>0.05). CONCLUSION Buccal acupuncture therapy demonstrated significant effectiveness in reducing postoperative pain and improving recovery quality for patients undergoing radical resection of gastrointestinal cancers, presenting a viable intervention without associated adverse outcomes. (Trial registration No. ChiCTR2200060441).
Humans ; Male ; Pilot Projects ; Female ; Acupuncture Therapy/methods* ; Pain, Postoperative/therapy* ; Middle Aged ; Gastrointestinal Neoplasms/surgery* ; Aged ; Acupuncture Points ; Adult

OBJECTIVE: To explore the mechanism of colon dialysis with Yishen Decoction (YS) in improving the autophagy disorder of intestinal epithelial cells in chronic renal failure (CRF) in vivo and in vitro. METHODS: Thirty male SD rats were randomly divided into normal, CRF, and colonic dialysis with YS groups by a random number table method (n=10). The CRF model was established by orally gavage of adenine 200 mg/(kg•d) for 4 weeks. CRF rats in the YS group were treated with colonic dialysis using YS 20 g/(kg•d) for 14 consecutive days. The serum creatinine (SCr) and urea nitrogen (BUN) levels were detected by enzyme-linked immunosorbent assay. Pathological changes of kidney and colon tissues were observed by hematoxylin and eosin staining. Autophagosome changes in colonic epithelial cells was observed with electron microscopy. In vitro experiments, human colon cancer epithelial cells (T84) were cultured and divided into normal, urea model (74U), YS colon dialysis, autophagy activator rapamycin (Ra), autophagy inhibitor 3-methyladenine (3-MA), and SIRT1 activator resveratrol (Re) groups. RT-PCR and Western blot were used to detect the mRNA and protein expressions of zonula occludens-1 (ZO-1), Claudin-1, silent information regulator sirtuin 1 (SIRT1), LC3, and Beclin-1 both in vitro and in vivo. RESULTS: Colonic dialysis with YS decreased SCr and BUN levels in CRF rats (P<0.05), and alleviated the pathological changes of renal and colon tissues. Expressions of SIRT1, ZO-1, Claudin-1, Beclin-1, and LC3II/I were increased in the YS group compared with the CRF group in vivo (P<0.05). In in vitro study, compared with normal group, the expressions of SIRT1, ZO-1, and Claudin-1 were decreased, and expressions of Beclin-1, and LC3II/I were increased in the 74U group (P<0.05). Compared with the 74U group, expressions of SIRT1, ZO-1, and Claudin-1 were increased, whereas Beclin-1, and LC3II/I were decreased in the YS group (P<0.05). The treatment of 3-MA and rapamycin regulated autophagy and the expression of SIRT1. SIRT1 activator intervention up-regulated autophagy as well as the expressions of ZO-1 and Claudin-1 compared with the 74U group (P<0.05). CONCLUSION Colonic dialysis with YS could improve autophagy disorder and repair CRF intestinal mucosal barrier injury by regulating SIRT1 expression in intestinal epithelial cells.
Animals ; Sirtuin 1/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Autophagy/drug effects* ; Male ; Intestinal Mucosa/drug effects* ; Rats, Sprague-Dawley ; Epithelial Cells/metabolism* ; Colon/drug effects* ; Humans ; Kidney Failure, Chronic/drug therapy* ; Signal Transduction/drug effects* ; Renal Dialysis ; Rats ; Kidney/drug effects*

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

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.