Idiopathic pulmonary fibrosis （IPF） is a chronic and fibrotic lethal interstitial lung disease with poor prognosis. It is mainly treated by organ transplantation and administration of chemical drugs， which have poor efficacy and induce side effects， failing to meet the clinical needs. Therefore， it is urgent to develop more safe and effective drugs to treat IPF. Traditional Chinese medicine （TCM） has garnered increasing attention in recent years in the treatment of IPF due to its unique advantages. Increasing studies have shown that TCM has remarkable therapeutic effects on IPF and thus demonstrate broad application prospects. Modern medical research shows that the pathogenesis of IPF can be discussed from inflammation （macrophage polarization）， oxidative stress， epithelial-mesenchymal transition （EMT）， autophagy inhibition and other related signaling pathways， while few studies systematically explain the relationship between the signaling pathways and TCM theory. According to the theory of TCM， lung collateral obstruction is the basic pathogenesis of IPF. Therefore， according to the principle of dredging and replenishing lung collaterals， IPF can be treated with the methods of reinforcing healthy qi and eliminating pathogen， replenishing qi and activating blood， and detoxifying and dredging collaterals， which demonstrate definite curative effect and can effectively relieve clinical symptoms， restore the lung function and blood oxygen partial pressure， improve the quality of life of patients， and reduce adverse reactions. Experimental studies have found that dredging and replenishing lung collaterals have significant effects on IPF inflammation （macrophage polarization）， oxidative stress， EMT， autophagy inhibition and other signaling pathways. Therefore， from the perspective of impediment， this article reviews pathogenesis of IPF， the research progress in TCM treatment of IPF， and the treatment of IPF from active components， single herbs， and compound prescriptions of TCM， with the aim of revealing the scientific connotation of the treatment of IPF from impediment and providing a new theoretical basis for enriching the TCM methods of treating IPF.

OBJECTIVE To investigate the neuroprotective effect and mechanism of eleutheroside B （ELB） on Parkinson’s disease （PD） model mice by regulating the IκB kinase β （IKKβ）/nuclear factor-κB （NF-κB） signaling pathway. METHODS Fifty mice were randomly divided into normal control group， model group， positive control group （selegiline hydrochloride， 10 mg/kg）， and ELB low-dose and high-dose groups （80， 160 mg/kg）， with 10 mice in each group. Each group was given relevant medicine or normal saline intragastrically for 14 consecutive days. Starting from the 10th day of administration， the model group and all administration groups were intraperitoneally injected with 1-methyl-4-phenyl-1，2，3，6-tetrahydropyridine （MPTP） 30 mg/kg， for five consecutive days to establish the chronic PD model. After the last administration for 24 h， six mice were randomly selected from each group to test their behavioral abilities； detect the levels of interleukin-1β （IL-1β）， IL-10， tumor necrosis factor-α （TNF-α） in brain tissue and their mRNA expressions were measured， and positive expression of tyrosine hydroxylase （TH）， protein expressions of TH， α -synuclein （ α -syn）， ionized calcium-binding adaptor molecule 1 （Iba-1）， as well as phosphorylation levels of IKKβ and NF-κB p65 proteins in the brain tissue were detected. The ultrastructure of neurons in substantia nigra was observed. RESULTS Compared with the model group， rotarod endurance time and climbing score of each administration group （except for the ELB low-dose group） were increased significantly （ P ＜0.05）， while the levels and mRNA expressions of IL-1β， TNF-α， α -syn， and Iba-1， as well as phosphorylation levels of IKKβ and NF-κB p65 proteins in brain tissue were decreased significantly （except for TNF-α in the ELB low-dose group）. Conversely， the level and mRNA expression of IL-10 （except for the ELB low-dose group）， TH positive expression and protein expressions were significantly increased （ P ＜0.05）. Typical neurodegenerative pathological changes， such as neuronal karyopyknosis， mitochondrial swelling and vacuolization， and endoplasmic reticulum dilation， all showed varying degrees of improvement. CONCLUSIONS ELB may exert neuroprotective effects by inhibiting the activation of the IKKβ/NF-κB signaling pathway， alleviating inflammatory responses， reducing abnormal α -syn aggregation and neuronal loss， and further improving motor dysfunction in PD mice.

OBJECTIVE To investigate the mechanism of Huangqin decoction in improving ulcerative colitis （UC） through the gut microbiota-tryptophan metabolism-aryl hydrocarbon receptor （AhR） axis. METHODS Mice were randomly divided into normal group （normal saline）， model group （normal saline）， microbiota depletion-model group （normal saline）， microbiota depletion-Huangqin decoction group （9.1 g/kg， by crude drug， similarly hereinafter）， Huangqin decoction group and mesalazine group （positive control group， 0.4 g/kg）， with 6 mice in each group. Microbiota depletion was achieved by providing free access to a mixed antibiotics for 10 days. The UC model was induced by administering 2.5% dextran sulfate sodium solution for 7 days. After successful modeling， each treatment group received corresponding drugs or normal saline intragastrically once daily for 10 days. After the final administration， body weight change ratio， disease activity index （DAI） score， and colon length were evaluated； colon pathological changes were observed； serum levels of interleukin-6 （IL-6）， IL-10， IL-22， and tumor necrosis factor-α （TNF-α） were measured； the expressions of Occludin， zonula occluden-1 （ZO-1）， and AhR in colon tissue were detected； fecal samples were subjected to high-throughput sequencing to analyze targeted tryptophan metabolomics. RESULTS Compared with the model group， Huangqin decoction group showed reduced infiltration of inflammatory cells in the colon tissue and restoration of the intestinal mucosal structure. Body weight change ratio， colon length， serum content of IL-10， the expressions of Occludin， ZO-1 and AhR in colon tissue and the contents of tryptophan metabolites indole-3-propionic acid （IPA）， N -acetylserotonin （NAS） and indole-3-acetic acid （IAA） were all significantly increased （ P ＜0.05）； DAI score， serum levels of IL-6， TNF-α， and IL-22 and the content of tryptophan metabolite indole-3-ethanol were significantly decreased （ P ＜0.05）； gut microbiota structure was improved， with increased relative abundances of beneficial bacteria such as Lactobacillus ， and decreased relative abundances of pathogenic bacteria such as Escherichia-Shigella . However， after antibiotic-induced microbiota depletion， although Huangqin decoction significantly increased the content of NAS in the feces of mice， the expression of AhR protein in colon tissue did not increase concurrently. CONCLUSIONS Huangqin decoction can repair the intestinal mucosal barrier in UC mice by regulating the gut microbiota and promoting the production of IPA and IAA， thereby activating AhR. This suggests that an intact gut microbiota is an important prerequisite for Huangqin decoction to exert its AhR-regulating effects.

Lung cancer remains one of the leading causes of cancer-related morbidity and mortality worldwide, and its treatment continues to face major challenges such as therapeutic resistance and tumor recurrence. Pyroptosis, a newly characterized form of programmed cell death, induces tumor cell death through gasdermin-mediated membrane pore formation and is accompanied by the release of inflammatory mediators, thereby playing complex roles in lung cancer initiation, progression, and modulation of the tumor microenvironment. Active components and herbal formulas derived from traditional Chinese medicine can modulate pyroptosis-related signaling pathways through multi-target mechanisms, showing potential advantages in inducing lung cancer cell death, inhibiting proliferation and migration, and reversing chemoresistance. This review systematically summarizes relevant studies from domestic and international sources, focusing on the molecular mechanisms of pyroptosis, its roles in lung cancer development and tumor microenvironment remodeling, and the current research progress on traditional Chinese medicine-based interventions targeting pyroptosis, with the aim of providing references for the prevention and treatment of lung cancer using traditional Chinese medicine.

Diabetic macular edema(DME), a serious complication of diabetic retinopathy(DR), is a chronic condition caused by multiple factors. Throughout its progression, inflammatory factors and vascular endothelial growth factor(VEGF)play a critical role. Anti-VEGF drugs have shown significant effectiveness in the treatment of DME; however, some patients may experience persistent DME after injection or require frequent injections. Dexamethasone intravitreal implants(DEX implants)serve as a sustained-release implant characterized by a reasonable release profile and high bioavailability. They offer safe, effective, and prolonged anti-inflammatory effects, aiding in the repair of retinal barrier and reduction of exudation. To further enhance patients' visual quality, exploring the efficacy of DEX implants in combination with existing treatment regimens has great clinical significance. This review primarily discusses the research advancements in DEX implants, focusing on their pharmacological properties, indications for use, and their combination with existing drugs and treatment methods. It also evaluates the advantages and disadvantages of combination therapy or switching to DEX implants compared to current standard treatments, aiming to provide guidance for personalized treatment options for patients with DME.

Objective To develop a machine learning model integrating preoperative chest CT radiomic features with clinical data for predicting 5-year postoperative recurrence risk in stage Ⅰ non-small cell lung cancer(NSCLC)patients undergoing surgical resection.Methods A total of 217 patients with pathologically confirmed stage Ⅰ NSCLC(selected from 778 initially screened cases based on our inclusion and exclusion criteria)treated in Army Medical Center of PLA between January 2014 and December 2019 were retrospectively enrolled,including 53 recurrence cases and 164 non-recurrence cases within 5-year follow-up.They were randomly divided into a training set(n=173)and a validation set(n=44)in a ratio of 8:2.Radiomic models were established based on extracted features from tumor-dominant regions of interest(ROI)on CT images,while clinical models were developed using demographic characteristics and preoperative laboratory examinations.A combined model was further constructed by integrating both feature sets,and model performance was compared to identify the optimal predictive model.Results This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model.Among 6 machine learning algorithms,the adaptive boosting(Adaboost)model demonstrated the best overall predictive performance,with an area under the curve(AUC)of 0.866(95%CI:0.808～0.923;accuracy:0.832,specificity:0.884)in the training set and of 0.806(95%CI:0.630～0.983;accuracy:0.795,specificity:0.971)in the validation set.Univariate and multivariate logistic regression analyses identified 4 clinical features for clinical model construction.The clinical model achieved an AUC value of 0.874(95%CI:0.821～0.928;accuracy:0.827,specificity:0.891)in the training set and 0.813(95%CI:0.677～0.948;accuracy:0.636,specificity:0.600)in the validation set.By integrating the 7 radiomic features and 4 clinical features using a feature-level fusion strategy,the combined model exhibited further improved predictive performance,with an AUC value of 0.953(95%CI:0.924～0.983;accuracy:0.884,specificity:0.860)and 0.852(95%CI:0.729～0.976;accuracy:0.682,specificity:0.629),respectively in the training set and the validation set.Conclusion The combined model integrating preoperative CT radiomic features with clinical risk factors may provide an evidence-based framework for evaluating 5-year postoperative recurrence risk in stage Ⅰ NSCLC patients.

A deep learning-based method for recognizing the minutiae in fingerprint,as well as a Python programming-based evaluation system for quantifying the evidence value of fingerprint was proposed.Firstly,latent fingerprints,which were developed using a series of fluorescent nanomaterials synthesized by chemical methods,were used as unknown fingerprint(UKFP),while ink impressed fingerprints were used as known fingerprint(KFP).Then,the bifurcations and terminations in minutiae were recognized using the improved YOLOv8 deep learning model.After that,the similarity index(Sim.)of UKFP vs KFP were calculated by analyzing the angle similarity factor(α)and the curve similarity factor(β)between UKFP and KFP,meanwhile,the sensitivity index(Sen.)were calculated by analyzing the fineness factor(γ)between UKFP and KFP.The evidence value(EV)of fingerprint was thus obtained by the combination of Sim.and Sen..The calculation formulas for above evaluation factors(i.e.α,β and γ),evaluation indexes(i.e.Sim.and Sen.),and EV were also put forward.Finally,the evaluation system for quantifying the evidence value of fingerprint was established,the feasibility and reliability of this system were verified,and the external factors that impacted on Sim.,Sen.,and EV were investigated in detail.The Python-based evaluation system for quantifying the evidence value of fingerprint could achieve the goals objectively,comprehensively,accurately and efficiently,exhibiting easy operability,high efficiency,responsiveness and reliability.This research was expected to provide beneficial references for quantitatively evaluating and thoroughly developing the evidence value.

The influence of material properties on fingerprint development effects were systematically studied.Firstly,carbon dots/NaYF4 and Cu nanoclusters/starch nanocomposites respectively possessing different fluorescent intensities and dual fluorescent colors,as well as NaYF4 micro-/nano-materials exhibiting different morphologies,sizes,and surface properties were chemically synthesized and further used for latent fingerprint development.Then,the developing effects were comprehensively evaluated by visual analysis combining with spectral characterization and Python-based calculation.Finally,the influences of material properties on latent fingerprint development were quantitatively evaluated from three dimensions including contrast,sensitivity,and selectivity.The fluorescence properties of developing materials and substrates could significantly affect the developing contrast,namely,the stronger the developing signal,the higher the contrast;the weaker the background noise,the higher the contrast.The sizes and morphologies of the developing materials could respectively influence the quantity and quality of developed minutiae,and significantly affect the developing sensitivity,namely,the smaller the particle size of developing materials,the more the quantity of developed minutiae and the higher the sensitivity;the smaller the surface area of developing materials,the higher the quality of developed minutiae and the higher the sensitivity.The surface properties together with the sizes and morphologies of developing materials could influence their adsorption performances,and significantly affect the developing selectivity,namely,the stronger the specific adsorption of developing materials with fingerprint substance,and the weaker the non-specific adsorption of developing materials with substrate,the higher the selectivity.Moreover,the fingerprint development using the materials with suitable surface area and appropriate mass would have a high selectivity.

Nano/microplastics(NMPs),due to their environmental persistence and resistance to degradation,have emerged as a major contributor to global pollution.NMPs are capable of adsorbing various hazardous chemicals and heavy metals,thereby posing threats to aquatic ecosystem health,which may ultimately cause potential risks to human health.Conventional analytical methods suffered from limited resolution,insufficient chemical information,or destruction of sample,invalidating these assays for on-site detection of NMPs.Surface-enhanced Raman scattering(SERS)offers distinct advantages such as high sensitivity,superior specificity,rich fingerprint information,and non-destructive analysis,thus facilitating the on-site analysis of NMPs in complex matrices.This review summarized recent advances in SERS substrates for detection of NMPs,discussed the construction and applications of SERS-based multimodal detection strategies,and introduced the research progress of SERS detection of NMPs in food safety,environmental pollution,and bioanalysis.Moreover,the main challenges and future directions of SERS-based NMP detection were outlined.

Under the background of forensic medicine becoming a first-level discipline,the opportuni-ties and challenges of discipline development coexist.Starting from the actual situation and characteris-tics of local medical colleges and universities,this paper discusses the problems and solutions for the development of forensic medicine discipline from the perspective of building a regional high-level medical university.Combined with the experiences of carrying out forensic medicine education in our college,this paper supplies our thoughts and practices on improving the discipline system,enhancing the ability to serve society,perfecting the talent cultivation model and promoting forensic culture,to provide reference and inspiration for the development of forensic medicine in other universities,jointly promote the advancement of forensic medicine in China to a new stage,and contribute the wisdom and strength of forensic medical experts to the construction of a law-based China,a safe China and a healthy China.