ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

ObjectiveFlavonoids are clinically significant natural products, yet their oxygen-glycosylation in aqueous environments relies heavily on expensive nucleotide-activated sugar donors such as UDP-glucose. Liquid-liquid phase separation (LLPS) creates specialized, membraneless physicochemical microenvironments capable of modulating enzymatic functions and overcoming mass transfer limitations. This study aims to investigate whether the gut microbiota-derived DgpB/C complex—a multienzyme system traditionally recognized for cleaving stable C-glycosidic bonds and facilitating isomerization—can undergo functional remodeling within phase-separated condensates. Our core objective is to elucidate the role of phase separation in expanding enzymatic catalytic plasticity and to provide a non-canonical, highly cost-effective biocatalytic mechanism for the direct utilization of free sugars in the synthesis of O-glycosylated natural products. MethodsAn artificial phase-separation platform was constructed utilizing the multivalent arginine-glycine-glycine motif (RGG)-repeat domain derived from the Caenorhabditis elegans LAF-1 protein. To ensure precise spatial compartmentalization, the DgpB/C complex was specifically recruited into the RGG condensates via a high-affinity SZ1/SZ2 heterodimerization tag system. Condensate formation and substrate partitioning were visualized using light and confocal fluorescence microscopy. The chemical structures and regioselectivity of the reaction products were rigorously characterized using high-performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS)/MS systems. Furthermore, molecular docking and 20-ns molecular dynamics (MD) simulations were performed via the Hermite platform and Uni-GBSA pipeline to elucidate the structural and thermodynamic basis underlying the phase-transition-induced functional shift. ResultsWe observed that the condensates formed by RGG proteins selectively recruited and significantly enriched hydrophobic flavonoid substrates. Strikingly, within the LLPS microenvironment, the DgpB/C complex—which typically exhibits only degradative or isomerase activities—underwent a profound functional remodeling, transforming into an efficientO-glycosyltransferase. Diverging from canonical pathways that require high-energy donors, the sequestered DgpB/C complex directly utilized unactivated free glucose to catalyze the formation of new O-glycosidic bonds. This remodeled activity was found to be evolutionarily conserved across DgpB/C homologs from diverse gut microbiota strains, such as P581a and W974-1. LC-MS/MS analysis further revealed that the phase-separated environment reduced the regioselectivity constraints of the enzyme, enabling catalytic action on multiple hydroxyl positions of the flavonoid scaffold. MD simulations further indicated that the low-water-activity microenvironment of the condensates reconfigured the conformational dynamics of the catalytic pocket, favoring a spatial orientation highly conducive to dehydration condensation. ConclusionThis study demonstrates that LLPS drives the functional remodeling of the gut microbiota enzyme DgpB/C through the reconfiguration of the physicochemical microenvironment. These findings challenge traditional perceptions regarding the functional boundaries of metabolic enzymes and reveal a novel biocatalytic pathway that bypasses the requirement for nucleotide-activated sugars. Consequently, this provides a highly promising artificial compartmentalization strategy for the green manufacturing of complex, high-value-added natural products.

Objective To analyze the factors affecting the prognosis of patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) undergoing immunotherapy and construct an individualized prognostic nomogram prediction model. Methods A retrospective analysis was conducted on the clinical data of 385 patients with driver gene-negative, locally advanced or metastatic NSCLC who received first-line immune checkpoint inhibitors. Univariate and multivariate Cox regression analyses were used to identify prognostic risk factors, and a prognostic nomogram model was established. The predictive performance of the model was evaluated using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves and area under the curve (AUC), and calibration curves. The cutoff value of the nomogram was calculated to stratify patients by risk. Survival curves were calculated by Kaplan-Meier analysis. Results Age (HR=1.775, 95%CI: 1.265-2.490), degree of differentiation (HR=0.365, 95%CI: 0.257-0.519), low PD-L1 expression (HR=0.661, 95%CI: 0.455-0.960), high PD-L1 expression (HR=0.423, 95%CI: 0.297-0.603), SCC-Ag (HR=1.549, 95%CI: 1.109-2.163), and CONUT score (HR=2.527, 95%CI: 1.797-3.554) were independent risk factors affecting overall survival (OS) of patients with NSCLC undergoing immunotherapy. The nomogram prediction model constructed on the basis of these factors had a C-index of 0.767. Time-dependent ROC curves for survival showed that the AUCs for 1-, 2-, and 3-year OS were 0.830, 0.853, and 0.886, respectively. Calibration curves indicated that the nomogram-predicted survival rates were in good agreement with the actual outcomes. The cutoff value for the study’s nomogram prediction model was 136.60 points, and survival curves showed statistically significant differences between different risk groups (P<0.05). Conclusion The nomogram model established in this study can effectively predict the prognosis of patients with driver gene-negative locally advanced or metastatic NSCLC treated with first-line immunosuppressive therapy. It provides a new tool for assessing prognosis and aids clinicians in formulating individualized treatment plans.

ObjectiveTo investigate the effects of paeoniflorin （PF） on neuroinflammation and cognitive impairment in the rat model of Alzheimer's disease （AD） and to clarify whether its mechanism is associated with regulation of the Janus kinase 2 （JAK2）/signal transducer and activator of transcription 3 （STAT3） signaling pathway. MethodsGlycosides related to AD-associated neuroinflammation were screened through bibliometric analysis， and the potential targets of PF were predicted through network pharmacology and molecular docking. A rat model of AD was established by intraperitoneal injection of D-galactose （100 mg·kg^-1·d^-1）. Rats were assigned into a control group， a model group， a PF （200 mg·kg^-1） group， and a donepezil （0.5 mg·kg^-1·d^-1） group， and drugs were administered by gavage for 21 days. The learning and memory abilities were evaluated by the Morris water maze （MWM）. Hematoxylin-eosin （HE） staining and Nissl staining were performed to observe hippocampal neuronal morphology. The mRNA levels of inflammatory factors were determined by Real-time quantitative polymerase chain reaction （Real-time PCR）， and the protein levels of molecules in the JAK2/STAT3 signaling pathway were determined by Western blot. ResultsCompared with the control group， the model group showed prolonged escape latency and decreased platform crossings and time spent in the target quadrant （P<0.05， P<0.01）， accompanied by increased expression of interleukin-1β （IL-1β） and tumor necrosis factor-α （TNF-α）， as well as elevated ratios of phosphorylated （p）-JAK2/JAK2 and p-STAT3/STAT3 （P<0.01）. Compared with the model group， the PF group and donepezil group exhibited shortened escape latency and increased platform crossings and time spent in the target quadrant （P<0.05， P<0.01）， decreased expression levels of IL-1β and TNF-α， upregulated mRNA levels of interleukin-4 （IL-4） and interleukin-10 （IL-10）， and reduced ratios of p-JAK2/JAK2 and p-STAT3/STAT3 （P<0.05， P<0.01）. ConclusionPaeoniflorin can alleviate cognitive impairment and neuroinflammation in the rat model of AD by inhibiting the JAK2/STAT3 signaling pathway.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

Objective Inflammation and fibrosis are key features of diabetic nephropathy(DN).Triptolide(TP)exhibits anti-inflammatory and anti-fibrotic properties,though its mechanisms of action in DN remain unclear.CREKA(Cys-Arg-Glu-Lys-Ala)is a pentapeptide that specifically binds to fibronectin(FN),and the CREKA-modified liposome(CREKA-Lip)represents a novel FN-targeted drug delivery system.This study aimed to investigate the role of TP in diabetic db/db mice and determine whether encapsulation within CREKA-Lip enhances therapeutic efficacy while reducing the multi-organ toxicity of TP.Methods Eight-week-old diabetic db/db mice received tail vein injections twice weekly with vehicle,free TP,or CREKA-Lip/TP for 10 weeks.Urine and serum parameters were measured,and kidney,heart,liver,and testis tissues were collected for pathological evaluation.Protein-protein interaction networks were constructed using Cytoscape and its plug-ins to identify core targets and elucidate the therapeutic mechanism of TP against DN.Inflammatory,fibrotic,apoptotic,and lipid metabolism markers were evaluated in the kidneys of diabetic mice with DN and in high glucose-treated mouse mesangial cells and podocytes using qPCR,Western blot,immunohistochemistry,and immunofluorescence assays.Results TP administration reduced fasting blood glucose levels and glomerular mesangial expansion in diabetic mice.TP significantly suppressed renal inflammation,fibrosis,and apoptosis while enhancing lipid metabolism.Integration of network pharmacology,molecular docking,and transcriptomics revealed that TP ameliorated DN by inhibiting the JAK2-STAT1 signaling pathway.In vitro,TP inhibited high glucose-induced phosphorylation of JAK2 and STAT1,reduced collagen production in mesangial cells,decreased apoptosis,and improved lipid metabolism in podocytes.Moreover,CREKA-Lip/TP exhibited superior efficacy compared with free TP,with a more sustained reduction in urine albumin-to-creatinine ratio and greater inhibition of mesangial expansion.Notably,CREKA-Lip/TP treatment did not induce systemic toxicity.Conclusion TP improves renal inflammation,fibrosis,apoptosis,and lipid homeostasis,thereby ameliorating DN by inhibiting JAK2-STAT1 activation.Targeted delivery of TP via FN-binding CREKA-Lip enhances therapeutic efficacy while minimizing multi-organ toxicity.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

Objective:To investigate the current status and influencing factors of barriers to going out among elderly patients with chronic obstructive pulmonary disease (COPD), and to provide a reference for implementing targeted preventive measures.Methods:Elderly COPD patients from the People's Hospital of Xinjiang Uygur Autonomous Region were selected between January and May 2024 by convenience sampling. A cross-sectional survey was conducted using a general information questionnaire, Scale on Barriers to Going Out for the Elderly, Perceived Isolation Scale and COPD Assessment Test (CAT).Results:A total of 270 questionnaires were distributed, with 250 valid responses, the effective response rate was 92.6%. Among the 250 elderly COPD patients, there were 124 males and 126 females, with age distributions: 116 patients aged 60-69 years, 94 aged 70-79 years, and 40 aged ≥80 years. The total score for Scale on Barriers to Going Out for the Elderly was (20.01 ± 4.09). The score on barriers to going out in elderly COPD patients were positively correlated with the Perceived Isolation Scale and CAT scores ( r = 0.456 and 0.625, both P <0.05). Multiple linear regression analysis revealed that age, oxygen therapy, exercise habits,Perceived Isolation Scale, and CAT score classification were the main influencing factors for barriers to going out ( t values were -2.85 to 8.93, all P<0.05), explaining 63.0% of the total variance. Conclusions:The level of barriers to going out in elderly COPD patients is moderate-to-high level. Healthcare professionals should emphasize the assessment of barriers to going out, closely monitor high-risk groups, and develop and implement interventions to prevent such barriers.

Objective To explore the application effect of multimodal somatosensory exercise based on artificial intelligence technology in home rehabilitation exercise for elderly patients with chronic obstructive pulmonary dis-ease(COPD),so as to promote COPD patients to participate in home rehabilitation exercise.Methods Using the convenient sampling method,80 elderly patients with COPD admitted to the Department of Respiratory Medicine of a tertiary A hospital in Urumqi from November 2023 to February 2024 were selected as the research subjects.Ac-cording to the random number table method,they were divided into a control group and an experimental group,with 40 cases in each group.The control group adopted the traditional exercise training method,and the experimental group adopted the multi-modal somatosensory movement based on artificial intelligence technology for exercise in-tervention,with 5 times a week,and the intervention was implemented for 12 weeks.The pulmonary function index,modified Medical Research Council scale score,physical fitness level,Chronic Obstructive Pulmonary Disease As-sessment Test scale score and exercise compliance of the 2 groups were compared before intervention and 12 weeks after intervention.Results 77 patients completed the study,with 39 in the experimental group and 38 in the control group.The forced vital capacity,forced expiratory volume in one second,forced expiratory volume in one second to forced vital capacity ratio,physical fitness level and exercise compliance of the experimental group were higher than those of the control group,while the modified British Medical Research Council scale score and Chron-ic Obstructive Pulmonary Disease Assessment Test score were lower than those of the control group.The differences were statistically significant(P＜0.05).Conclusion Somatosensory exercise based on artificial intelligence technology can improve the lung function of the patients with COPD,improve the exercise compliance and physical fitness in-dicators of elderly patients and improve the quality of life of the patients.

Time-of-flight secondary ion mass spectrometer(TOF-SIMS)is a highly sensitive surface analysis instrument with high spatial resolution.Traditional TOF-SIMS instruments for sample targets use high field extraction methods.Although the ion collection efficiency is high,it is prone to issues such as low-energy ion beam defocusing,sample morphology sensitivity,and organic molecule ion dissociation.This study aimed to develope an efficient low-field ion extraction system suitable for TOF-SIMS with a continuous beam source.The SIMION simulation software was used to construct a model of the secondary ion optical extraction system.The key factors affecting the extraction efficiency were studied,and the structural parameters of the extraction cone were optimized.Using an indium target as the sample,an experimental test of the performance of the ion extraction system was carried out on the TOF-SIMS instrument.The influences of the voltages of the ion extraction cone and the single lens on the ion extraction efficiency were consistent with the simulation results.By adopting the technology of deflection and coaxial dynamic compensation,the imaging field of view of the ion extraction system was increased to 500 μm×500 μm.The energy window of the ion extraction system reached 10 eV,and the large imaging depth of field of 400 μm was achieved.In the test of a 5 mg/L cholesterol thin film sample,the signal-to-noise ratio of the characteristic peak[M-OH]+reached 4453.The results showed that this low-field secondary ion extraction system effectively improved the performance of the continuous beam TOF-SIMS instrument.