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.

During orthodontic treatment, clinical monitoring of patients is a crucial factor in determining treatment success. It aids in timely problem detection and resolution, ensuring adherence to the intended treatment plan. In recent years, digital technology has increasingly permeated orthodontic clinical diagnosis and treatment, facilitating clinical decision-making, treatment planning, and follow-up monitoring. This review summarizes recent advancements in digital technology for monitoring orthodontic tooth movement, related complications, and appliance-wearing compliance. It aims to provide insights for researchers and clinicians to enhance the application of digital technology in orthodontics, improve treatment outcomes, and optimize patient experience. The digitization of diagnostic data and the visualization of dental models make chair-side follow-up monitoring more convenient, accurate, and efficient. At the same time, the emergence of remote monitoring technology allows orthodontists to promptly identify oral health issues in patients and take corresponding measures. Furthermore, the multimodal data fusion method offers valuable insights into the monitoring of the root-alveolar relationship. Artificial intelligence technology has made initial strides in automating the identification of orthodontic tooth movement, associated complications, and patient compliance evaluation. Sensors are effective tools for monitoring patient adherence and providing data-driven support for clinical decision-making. The application of digital technology in orthodontic monitoring holds great promise. However, challenges like technical bottlenecks, ethical considerations, and patient acceptance remain.

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.

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

OBJECTIVE: High-altitude hypoxia exposure often damages hippocampus-dependent learning and memory. Nogo-A is an important axonal growth inhibitory factor. However, its function in high-altitude hypoxia and its mechanism of action remain unclear. METHODS: In an in vivo study, a low-pressure oxygen chamber was used to simulate high-altitude hypoxia, and genetic or pharmacological intervention was used to block the Nogo-A/NgR1 signaling pathway. Contextual fear conditioning and Morris water maze behavioral tests were used to assess learning and memory in rats, and synaptic damage in the hippocampus and changes in oxidative stress levels were observed. In vitro, SH-SY5Y cells were used to assess oxidative stress and mitochondrial function with or without Nogo-A knockdown in Oxygen Glucose-Deprivation/Reperfusion (OGD/R) models. RESULTS: Exposure to acute high-altitude hypoxia for 3 or 7 days impaired learning and memory in rats, triggered oxidative stress in the hippocampal tissue, and reduced the dendritic spine density of hippocampal neurons. Blocking the Nogo-A/NgR1 pathway ameliorated oxidative stress, synaptic damage, and the learning and memory impairment induced by high-altitude exposure. CONCLUSION: Our results demonstrate the detrimental role of Nogo-A protein in mediating learning and memory impairment under high-altitude hypoxia and suggest the potential of the Nogo-A/NgR1 signaling pathway as a crucial therapeutic target for alleviating learning and memory dysfunction induced by high-altitude exposure. GRAPHICAL ABSTRACT available in www.besjournal.com.
Animals ; Oxidative Stress ; Hippocampus/metabolism* ; Rats ; Nogo Proteins/genetics* ; Male ; Rats, Sprague-Dawley ; Hypoxia/metabolism* ; Altitude ; Synapses ; Humans ; Altitude Sickness/metabolism*

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.