ObjectiveTo investigate whether Huanglian Jiedutang can inhibit neutrophil infiltration in the brains of middle cerebral artery occlusion （MCAO） mice by regulating the expression of neutrophil-related chemokines in exosomes， thereby achieving therapeutic effects. MethodsA total of 130 male specific pathogen-free （SPF） C57BL/6J mice were randomly divided into four groups： Sham-operated group， MCAO model group， Huanglian Jiedutang group （6 g·kg^-1）， and Ginaton group （21.6 mg·kg^-1）， with 10 mice in the Ginaton group and 40 mice in each of the remaining three groups. Mice in the Huanglian Jiedutang group and the Ginaton group were administered the corresponding drugs by oral gavage once daily at a volume of 0.15 mL·（10 g）^-1 for 7 consecutive days， while the sham-operated and model groups received an equal volume of saline via the same route. After 7 days， MCAO surgery was performed. The distal and proximal ends of the right common carotid artery （CCA） were ligated， a small incision was made between the two ligatures， and a silicone rubber-coated monofilament with a rounded tip was inserted into the lumen to occlude the CCA. The filament was left in place for 1 h to establish a focal cerebral ischemia model. At 24 h after modeling， mice were evaluated. Neurological function was assessed using the Longa score. Cerebral infarct volume was measured by 2，3，5-triphenyltetrazolium chloride （TTC） staining. Cerebral blood flow was observed by laser speckle imaging. Hematoxylin and eosin （HE） staining and Nissl staining were used to observe pathological changes in brain tissues. Exosomes were isolated from mouse plasma and brain tissues by ultracentrifugation and molecular size exclusion and identified by electron microscopy， particle size analysis， and protein blotting. Long-chain RNA libraries of exosomes were constructed and sequenced. Real-time quantitative reverse transcription polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of inflammatory factors and neutrophil-related chemokines in exosomes from plasma and brain tissues of each group. Enzyme-linked immunosorbent assay （ELISA） was used to detect the protein expression of inflammatory factors and neutrophil-related chemokines in exosomes from brain tissues of each group. Immunohistochemistry was used to detect the expression of the neutrophil-specific protein myeloperoxidase （MPO） in the brains of mice in each group. ResultsCompared with the sham-operated group， the model group showed decreased neurological function scores （P<0.01）， obvious cerebral infarction （P<0.01）， reduced cerebral blood flow （P<0.01）， neuronal necrosis in the brain， and decreased numbers of Nissl bodies （P<0.01）. The mRNA expression levels of IL-1β， MPO， CXCL1， CXCL2， CXCL3， CXCL10， CCL2， and CCL3 in exosomes from plasma and brain tissues were significantly increased （P<0.05， P<0.01）. The protein expression levels of IL-1β， MPO， CXCL2， and CXCL10 in exosomes from brain tissues were increased （P<0.05， P<0.01）， and MPO-positive rates and mean optical density values in brain tissues were elevated （P<0.01）. Compared with the model group， the Huanglian Jiedutang group and the Ginaton group showed increased neurological function scores （P<0.05）， reduced cerebral infarct volume （P<0.01）， restored cerebral blood flow （P<0.01）， reduced necrotic cells in the brain， and increased numbers of Nissl bodies （P<0.01）. In the Huanglian Jiedutang group， the mRNA expression levels of IL-1β， MPO， CXCL1， CXCL2， CXCL3， CXCL10， CCL2， and CCL3 in exosomes from plasma and brain tissues were decreased （P<0.05， P<0.01）. The protein expression levels of IL-1β， MPO， CXCL2， and CXCL10 in exosomes from brain tissues were reduced （P<0.05， P<0.01）， and MPO-positive rates and mean optical density values in brain tissues were decreased （P<0.01）. ConclusionHuanglian Jiedutang can effectively regulate the expression of neutrophil-related chemokines in exosomes from plasma and brain tissues of MCAO mice， thereby reducing neutrophil infiltration in the brain and achieving therapeutic effects.

ObjectiveTo investigate whether Huanglian Jiedutang can inhibit neutrophil infiltration in the brains of middle cerebral artery occlusion （MCAO） mice by regulating the expression of neutrophil-related chemokines in exosomes， thereby achieving therapeutic effects. MethodsA total of 130 male specific pathogen-free （SPF） C57BL/6J mice were randomly divided into four groups： Sham-operated group， MCAO model group， Huanglian Jiedutang group （6 g·kg^-1）， and Ginaton group （21.6 mg·kg^-1）， with 10 mice in the Ginaton group and 40 mice in each of the remaining three groups. Mice in the Huanglian Jiedutang group and the Ginaton group were administered the corresponding drugs by oral gavage once daily at a volume of 0.15 mL·（10 g）^-1 for 7 consecutive days， while the sham-operated and model groups received an equal volume of saline via the same route. After 7 days， MCAO surgery was performed. The distal and proximal ends of the right common carotid artery （CCA） were ligated， a small incision was made between the two ligatures， and a silicone rubber-coated monofilament with a rounded tip was inserted into the lumen to occlude the CCA. The filament was left in place for 1 h to establish a focal cerebral ischemia model. At 24 h after modeling， mice were evaluated. Neurological function was assessed using the Longa score. Cerebral infarct volume was measured by 2，3，5-triphenyltetrazolium chloride （TTC） staining. Cerebral blood flow was observed by laser speckle imaging. Hematoxylin and eosin （HE） staining and Nissl staining were used to observe pathological changes in brain tissues. Exosomes were isolated from mouse plasma and brain tissues by ultracentrifugation and molecular size exclusion and identified by electron microscopy， particle size analysis， and protein blotting. Long-chain RNA libraries of exosomes were constructed and sequenced. Real-time quantitative reverse transcription polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of inflammatory factors and neutrophil-related chemokines in exosomes from plasma and brain tissues of each group. Enzyme-linked immunosorbent assay （ELISA） was used to detect the protein expression of inflammatory factors and neutrophil-related chemokines in exosomes from brain tissues of each group. Immunohistochemistry was used to detect the expression of the neutrophil-specific protein myeloperoxidase （MPO） in the brains of mice in each group. ResultsCompared with the sham-operated group， the model group showed decreased neurological function scores （P<0.01）， obvious cerebral infarction （P<0.01）， reduced cerebral blood flow （P<0.01）， neuronal necrosis in the brain， and decreased numbers of Nissl bodies （P<0.01）. The mRNA expression levels of IL-1β， MPO， CXCL1， CXCL2， CXCL3， CXCL10， CCL2， and CCL3 in exosomes from plasma and brain tissues were significantly increased （P<0.05， P<0.01）. The protein expression levels of IL-1β， MPO， CXCL2， and CXCL10 in exosomes from brain tissues were increased （P<0.05， P<0.01）， and MPO-positive rates and mean optical density values in brain tissues were elevated （P<0.01）. Compared with the model group， the Huanglian Jiedutang group and the Ginaton group showed increased neurological function scores （P<0.05）， reduced cerebral infarct volume （P<0.01）， restored cerebral blood flow （P<0.01）， reduced necrotic cells in the brain， and increased numbers of Nissl bodies （P<0.01）. In the Huanglian Jiedutang group， the mRNA expression levels of IL-1β， MPO， CXCL1， CXCL2， CXCL3， CXCL10， CCL2， and CCL3 in exosomes from plasma and brain tissues were decreased （P<0.05， P<0.01）. The protein expression levels of IL-1β， MPO， CXCL2， and CXCL10 in exosomes from brain tissues were reduced （P<0.05， P<0.01）， and MPO-positive rates and mean optical density values in brain tissues were decreased （P<0.01）. ConclusionHuanglian Jiedutang can effectively regulate the expression of neutrophil-related chemokines in exosomes from plasma and brain tissues of MCAO mice， thereby reducing neutrophil infiltration in the brain and achieving therapeutic effects.

Objective: To explore the impact of adverse childhood experiences (ACEs) on health risk behaviors (HRBs) among college students and the mediating role of psychological symptoms, so as to provide a basis for developing intervention strategies. Methods: From March to April 2023, a convenience cluster sample of 1 801 students from 12 universities in Nanning, Liuzhou, Guilin, Wuzhou of Guangxi completed an online survey. A self designed questionnaire, Adverse Childhood Experiences-International Questionnaire (ACE-IQ) and Symptom Checklist-90 (SCL-90) were used for evaluation tools. Binary Logistic regression, structural equation modeling (SEM) and Bootstrap methods were used to analyze the associations and mediating effects. Results: Overall, 71.2% of college students experienced at least one type of ACE, with emotional neglect (40.3%) and emotional abuse ( 25.2 %) having the highest detection rates. The top three HRBs were unhealthy diet (77.8%), physical inactivity (54.1%), and smoking/alcohol use (18.5%). Logistic regression showed that poor family functioning, abuse, and extra familial violence were each associated with an increased risk of smoking/alcohol use ( OR =1.14, 1.11, 1.18) and deliberate self harm ( OR =1.26, 1.19,1.30) (all P <0.05). Experience of abuse increased the risk of high risk sexual behavior and family dysfunction increaded the risk of physical inactivity, respectively ( OR = 1.07 , 1.04, both P <0.05). Mediation analysis revealed that anxiety ( β =0.20) and depression ( β = 0.09 ) partially mediated the pathway from poor family functioning to deliberate self harm; paranoia ( β =0.02) partially mediated the pathway from abuse to high risk sexual behavior; and obsessive-compulsive symptoms ( β =0.26) and depression ( β =0.10) partially mediated the pathway from extra familial violence to deliberate self harm (all P <0.05). Conclusion Psychological symptoms play a mediating role in the association between ACEs and HRBs, and mental health interventions may reduce the risk of HRBs among college students.

Infection-related glomerulonephritis (IRGN) is an immune-mediated glomerular injury triggered by infectious agents. This article reports a case of immune complex-mediated glomerulonephritis following acute hepatitis B virus infection, which continued to progress despite standard antiviral and immunosuppressive therapy. Given the significant elevation of soluble complement membrane attack complex (sC5b-9), an indicator of terminal complement pathway activation, the patient was treated with eculizumab. Following treatment, the patient's urine protein-to-creatinine ratio significantly decreased, hypoalbuminemia and hematuria markedly improved, and sC5b-9 levels declined. This case suggests that abnormal complement system activation may be a key mechanism driving disease persistence in some patients with IRGN. For those unresponsive to conventional therapy, complement function screening and targeted terminal complement pathway inhibition may represent an effective salvage strategy.

OBJECTIVE To study the protective effect and potential mechanism of chikusetsu saponin Ⅳ a （chsⅣ） on renal function in diabetic nephropathy （DN） model rats. METHODS DN rat model was established by high-fat diet combined with streptozotocin injection. Thirty-six model rats were randomly divided into model group （i.g. administration of normal saline， high-fat diet）， chsⅣ low-dose and high-dose groups （i.g. administration of 90， 180 mg/kg chsⅣ， high-fat diet）， with 12 rats in each group. Additionally， 10 normal rats were set as the control group （i.g. administration of normal saline， regular diet）. From the 5th to the 12th week after streptozotocin injection， they were given intragastric administration of relevant drug or normal saline， once a day. After the last medication， the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine and urine protein as well as the levels of reduced glutathione （GSH）， superoxide dismutase （SOD） and malondialdehyde （MDA） in renal tissues were measured. Additionally， the insulin resistance index was calculated. Hematoxylin-eosin， periodic acid-Schiff， and Masson staining techniques were employed to examine the histopathological alterations in the renal tissue. The expressions of Notch signaling pathway-related proteins in renal tissue were detected by immunohistochemical staining and Western blot methods. RESULTS Compared with model group， the histomorphological of renal tissues in the chsⅣ low- and high-dose groups were significantly improved， with significant decreases in renal histological scores， mesangial expansion index， and glomerulosclerosis scores （ P ＜0.05）； the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine， urine protein and homeostasis model assessment for insulin resistance， as well as MDA content， the expression levels of Notch1， Notch intracellular domain， hairy and enhancer of Split 1 and Delta-like protein 1 in renal tissue were all significantly decreased （ P ＜0.05）. The levels of GSH and SOD in renal tissue were significantly elevated （ P ＜0.05）. Moreover， the improvement in these indicators was significantly more pronounced in the chsⅣ high-dose group compared to the chsⅣ low-dose group （ P ＜0.05）. CONCLUSIONS ChsⅣ can ameliorate renal pathological damage and functional impairment in DN rats. Its underlying mechanisms include restoration of glucose homeostasis and insulin sensitivity， attenuation of renal oxidative stress， and suppression of aberrant Notch signaling pathway activation.

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.

At present， the systematic excavation of the clinical experience and academic thought of the Sichuan school of Chinese medicine vis-à-vis its dominant disease entities remains fragmentary， and replicable paradigms are scarce. Confronted with empirical fragmentation， data heterogeneity and decision-making subjectivity， the standardised distillation， inheritance and clinical translation of these distinctive experiences has become a critical bottleneck constraining the development of the Sichuan school. The integration of artificial-intelligence technologies in data processing， pattern recognition and intelligent decision-making has rendered deep mining of traditional Chinese medicine（TCM） clinical knowledge and patterns imperative. Constructing an intelligent modern TCM diagnostic-therapeutic-evaluative system is now the obligatory route for inheritance and innovation in Chinese medicine， and simultaneously provides a technological breakthrough for intelligent decision paradigms in the dominant diseases of the Sichuan school. Accordingly， this study adopts the regional academic school as its point of entry， focuses on the dominant diseases of the Sichuan school， and proposes an innovative pathway of "four-dimensional data-multi-modal fusion-multi-agent decision-making". Specifically， four data dimensions are defined and instantiated： （Ⅰ） knowledge from classical medical literature and historical case records. （Ⅱ） objective four-diagnosis phenotypic data. （Ⅲ） master physicians' prescribing regularities. （Ⅳ） characteristic mechanisms of renowned formulae. Leveraging multi-modal data fusion and generative artificial intelligence， the entire causal chain of Famous Physicians and Renowned Formulas is explicated to reconstruct the diagnostic-therapeutic cognitive logic of the regional school. Finally， a multi-agent collective-decision model is established and refined for the dominant diseases of the Sichuan school， capable of generating precise， individualised treatment regimens and thereby advancing an intelligent diagnostic-therapeutic paradigm that delivers more efficient and accurate clinical decision support.

OBJECTIVE To screen a single matrix， prepare dissolving microneedles of Pterocarya hupehensis total flavonoids（PHTF-MN）， and characterize it while evaluating its analgesic effects.METHODS Using microneedle morphology and puncture rate as evaluation indicators， the matrix was screened from polyvinyl alcohol （PVA）， polyvinylpyrrolidone K30 （PVP K30）， PVP K90， and sodium hyaluronate with relative molecular weights of 15 000 and 60 000 （HA 1.5w and HA 6w ）. PHTF-MN was prepared by the layer-by-layer casting method with the selected matrix， and the appearance and morphology， total flavonoid content， mechanical properties， puncture performance， dissolution properties， and drug release behavior of the obtained PHTF-MN were characterized. Using male BALB/c mice as test subjects and aspirin （ASA） as a positive control， the analgesic effects of the microneedles were evaluated using a formalin-induced pain model.RESULTS Blank microneedles prepared with 30% HA 1.5w exhibited optimal surface flatness and the membrane puncture rate （through 4 layers of parafilm membrane） reaching 78%. The PHTF-MNs （with PHTF contents of 10， 20， 30， 40， and 50 mg/g in the matrix） exhibited uniform arrays and intact tips， with RSDs for total flavonoid contents all below 7% （ n ＝8）. The single-needle puncture forces were 1.46 and 1.07 N （with PHTF contents of 30 and 50 mg/g in the matrix， respectively）. The skin penetration rate approached 100%， with visible puncture marks in the stratum corneum and drug residue （with a PHTF content of 50 mg/g in the matrix）. After 30 min of fixation， the needles had almost completely dissolved， and the skin retention rates all exceeded 90% （with PHTF contents of 10， 30， and 50 mg/g in the matrix， respectively）. The cumulative release within 8 h was （134.64±2.03） μg/cm 2 ， and the fit to the first-order kinetic equation （ R 2 ＝0.950 1） was highest （with a PHTF content of 50 mg/g in the matrix）. Low- and high-dose PHTF-MN （containing 85.26 and 145.03 μg of total flavonoids per patch， respectively； 1 patch/day） significantly shortened the cumulative time of phase Ⅱ pain response in mice （ P ＜0.05）， with pain inhibition rates （43.67% and 59.78%） comparable to those of ASA （53.70%）.CONCLUSIONS PHTF-MN using HA 1.5w as a single matrix was successfully prepared. This formulation features a simplified preparation process， uniform drug loading， favorable mechanical properties， resistance to fracture， and rapid dissolution. Its drug release behavior conforms to a first-order kinetic model， and its analgesic effect is comparable to that of ASA.

It is considered that although meibomian gland dysfunction （MGD）-associated dry eye is mainly manifested by signs of dryness such as ocular dryness and burning sensation， it may also be accompanied by signs of dampness， including thick meibomian secretions， epigastric and abdominal fullness， and a greasy tongue coating， thus presenting a pattern characterized by the coexistence of dryness and dampness. Based on LIU Wansu's theory of "promoting the flow of dampness to moisten dryness"， this disease is understood from the perspectives of an imbalance between dryness and dampness in the middle jiao （焦） and abnormal distribution of body fluids. For dampness and turbidity constraint and stagnation， treatment should focus on diffusing the lung， fortifying the spleen， promoting the flow of dampness， and resolving turbidity， with modified Sanren Decoction （三仁汤） combined with Shenling Baizhu Powder （参苓白术散） commonly used. For steaming of dampness-heat， treatment should focus on clearing heat， draining dampness， and moistening dryness with sweet and cool medicinals， with modified Jinzhi Qingmu Formula （金栀清目方） combined with Shashen Maidong Decoction （沙参麦冬汤） commonly used. For dryness-toxin damaging the physical form， treatment should focus on nourishing yin and blood， unblocking the collaterals， and resolving toxins， with modified Qiju Dihuang Pill （杞菊地黄丸） combined with Taohong Siwu Decoction （桃红四物汤） commonly used.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.