Aging has emerged as a cutting edge and hotspot in global life science field， with anti-aging and geriatric disease prevention and treatment becoming critical issues urgently demanding solutions in international medical communities. In the face of the challenge of accelerating global population aging， in-depth exploration of aging mechanisms and the development of effective intervention strategies hold significant scientific and clinical value. This study supported by the national key research and development program of China， employed the essence-Qi-spirit theory of Qiluo doctrine as its guiding framework， focusing on the key scientific issue of the core traditional Chinese pathogenesis of aging， namely "depletion of kidney essence， deficiency of primordial Qi， and impairment of body and spirit". The treatment principle of "tonifying the kidney to replenish essence， harmonizing Yin and Yang， warming and invigorating primordial Qi， and nourishing the body and spirit" was established. Centered on holistic aging， systemic aging， and aging-related diseases， the research integrated multidisciplinary research approaches to construct multi-modal aging models and a multi-dimensional evaluation system， and it utilized multi-omics technologies to deeply analyze aging mechanisms. By systematically reviewing historical kidney-tonifying and anti-aging formulas and combining big data with artificial intelligence technologies， an information database of anti-aging traditional Chinese medicine substance was developed to reveal the differences and synergistic effects of various treatment methods and formulas on anti-aging. Based on this treatment method， the research integrated two millennia of kidney-tonifying medicinal experience to develop the innovative anti-aging traditional Chinese medicine， namely Bazhi Bushen capsules. It was validated that this capsule can delay holistic and systemic aging through multiple targets and mechanisms， thereby elucidating the scientific connotation of the essence-Qi-spirit theory of Qiluo doctrine in guiding anti-aging research from multiple dimensions and providing robust support for leveraging the advantages of traditional Chinese medicine to occupy the commanding heights of international anti-aging research.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

Objective: To develop and compare multiple machine learning models for identifying high-risk college students exhibiting phubbing behavior and to determine key predictive factors, so as to provide evidence for precise screening and early intervention strategies. Methods: In December 2025, 1 828 undergraduate students, selected from three universities in Wuhan by using convenience sampling method, were surveyed via online qustionnaire for sociodemographic characteristics, phubbing behavior, family cohesion index, mature happiness, fear of negative evaluation, multidimensional state boredom, and psychological vulnerability. Four machine learning algorithms, including multilayer perceptron (MLP), extreme gradient booting (XGBoost), K-nearest neighbors (KNN), and gradient boosting decision tree (GBDT), were applied. The dataset was randomly split into a training set and a test set at a ratio of 7∶3. Model performance was evaluated using accuracy, recall, F1-score, and area under the receiver operating characteristic curve (AUC). The best performing model was further interpreted using shapley additive explanation (SHAP) analysis to assess feature importance. Results: In the training set,955 participants were classified as having low level phubbing behavior, and 325 participants were classified as having high level phubbing behavior. Significant differences were observed in psychological vulnerability, multidimensional state boredom, family cohesion index, and mature happiness between groups ( Z =-10.29, -11.72, -8.17, -7.83, all P <0.05). Significant differences were also found in the detection rate of high level phubbing behavior according to family residence, family status, left behind experience,interpersonal relationships,exercise frequency,physical flexibility,and sleep status ( χ 2=12.22, 38.93, 16.90, 44.64, 58.17, 82.14, 37.89, all P <0.05). Among the four machine learning models (MLP, KNN, GBDT, XGBoost),all showed good discrimination ability, with XGBoost performing best (accuracy 79%, recall 71%, F1-score=0.70, AUC=0.78), while GBDT achieved the highest precision (78%). Feature importance analysis showed that multidimensional state boredom was the most important predictor of phubbing behavior, followed by psychological vulnerability, family cohesion, mature happiness, and fear of negative evaluation. SHAP analysis indicated that multidimensional state boredom, psychological vulnerability, and fear of negative evaluation had positive risk effects, while family cohesion and hedonic well being had protective effects for high risk of phubbing behavior. Conclusions Multidimensional state boredom is the core predictor of phubbing behavior among college students. The XGBoost model demonstrates good predictive performance and can provide a reference for identifying high risk individuals and implementing targeted interventions.

Detection of poor-water-soluble substances typically requires an organic solvent containing solution,and therefore,the biosensors that can operate in such conditions are highly promising for practical applications.However,most existing biosensors have been developed in aqueous solution and it is hard to work effectively in organic solvent systems.In this work,we uncovered that the G-quadruplex(G4)/hemin DNAzyme(G4HD)could be strongly reactivated by NH4 in organic solvents at concentration up to 30％,and the activity was significantly higher than that in aqueous solutions containing K+.Based on this discovery,a biosensing system was developed for small molecule in 40％methanol by coupling G4HD with our previously identified RNA-cleaving DNAzyme(E3).This system comprised an ATP-activated aptazyme that was made of E3 and a G4HD that was activated by the cleavage product of the aptazyme.By using a manmade pipette tip filter to separate the reaction products,the subsequent colorimetric reaction of the G4HD could be triggered.This biosensing system enabled the visualization of target molecules in organic cosolvents without any other instruments.The activable DNAzyme-cascade sensing system had potential in point-of-care detection of poor-water-soluble pollutants,thereby enhancing the practical values of functional nucleic acid-based biosensors in real-world detection conditions.

Early screening of tumors is crucial for prevention and treatment of cancer,thus identifying effective biomarkers is of great importance for early diagnosis of tumors.In recent years,tumor-secreted exosomes(Exos)have attracted widespread attention as a novel biomarker for tumor liquid biopsy.Especially,some specific proteins contained in Exos play important roles in the occurrence,development,metastasis and microenvironment regulation of tumors,indicating their enormous potential as potential diagnostic biomarkers for tumors.Compared to traditional biopsy sample testing,exosome-based protein detection methods exhibit significant advantages in liquid biopsy,including rapid sampling,easy operation,non-invasiveness,and feasibility for early detection,holding important application value for clinical diagnosis of tumors.This review aimed to comprehensively summarize and discuss various detection strategies for exosomal proteins in liquid biopsy for tumors,while comprehensively evaluating the analytical performance of these methods.Meanwhile,new perspectives and strategies for early diagnosis and treatment of tumors were discussed.Additionally,the unique advantages of exosomal proteins as a new generation of non-invasive diagnostic biomarkers and insights into their promising prospects for future clinical applications were emphasized.

Nitrofurantoin(NFT)is a nitrofuran antibiotic commonly used as a veterinary drug to treat bacterial infections in animals.However,due to the low solubility and bioaccumulation properties,NFT is prone to leave excessive residues in animal-derived foods and water systems,posing serious threats to human health and ecosystems.Therefore,there is an urgent need to develop an efficient and rapid detection method for NFT.In this work,nitrogen-doped carbon nanomaterials with unique bowl-like structures(N-CNBs)were synthesized via a hydrothermal-carbonization method.The morphology,surface structure,and specific surface area of N-CNBs were characterized using transmission electron microscopy(TEM),scanning electron microscopy(SEM),and X-ray photoelectron spectroscopy(XPS).The N-CNB modified glassy carbon electrode(N-CNB/GCE)was prepared,and the electrochemical test revealed that the N-CNB/GCE exhibited higher conductivity and larger electrochemical active surface area compared to bare GCE and nitrogen-doped hollow carbon nanosphere-modified electrode(N-HCNS/GCE).Additionally,the N-CNB/GCE demonstrated superior electrocatalytic activity toward NFT.An NFT electrochemical sensor was constructed based on N-CNB/GCE.The detection conditions of the sensor were optimized,and differential pulse voltammetry(DPV)was employed for NFT detection under optimal experimental conditions.The established NFT electrochemical sensor had a wide linear range of 0.4-500 μmol/L,a low detection limit(S/N=3)of 0.015 μmol/L and high selectivity,with excellent stability and reproducibility.The practical feasibility of this sensor was confirmed by analysis of NFT in milk and tap water samples,with spiked recoveries ranging from 94.2%to 108.9%.

Aim To investigate the effect of Huangqi injection(HI)and Huangqi oral solution(HO)on cisplatin-induced nephrotoxicity(CIN)based on un-targeted metabolomics technology and the underlying mechanisms.Methods Sprague Dawley(SD)rats were randomly divided into the blank group,cisplatin(CDDP)model group,HI treatment group,and HO treatment group,then the CIN model was built with low dose multiple intraperitoneal injections of CDDP.Pre-liminary evaluation of the renal protective efficacy of HI and HO was performed by measuring serum creatinine(Scr),blood urea nitrogen(BUN),and organ indi-ces.Further screening and identification of potential biomarkers(PBs)related to CIN and HI/HO pharma-cological effects were attained through metabolomics studies of renal tissues,and pathway enrichment analy-sis was conducted.Results HI and HO significantly restored the abnormal increase in renal function indica-tors and abnormal decrease in organ indices caused by CDDP,as well as significantly improved the abnormal renal metabolic profile induced by CDDP,indicating that both HI and HO had good alleviating effects on CIN.HI significantly reversed 47 out of 54 CIN related PBs,mainly involving metabolic pathways such as glycerophospholipid metabolism,tryptophan metabo-lism,pantothenate and CoA biosynthesis;HO signifi-cantly reversed 18 out of 54 CIN related PBs,mainly involving metabolic pathways such as taurine and hypo-taurine metabolism,ascorbate and aldarate metabo-lism,pentose and glucuronate interconversions.Con-clusions Both HI and HO have significant alleviating effects on CIN.In the short term,HI salleviating effect is superior to that of HO.Overall,the mechanisms by which both alleviate CIN are mainly related to regula-ting lipid metabolism,amino acid metabolism.

Aim To investigate the effect of high-fat diet on the tight junction function injury of Sertoli cells through the NF-κB/NLRP3 signaling pathway in mice and to explore the underlying mechanism.Methods Male C57BL/6J mice were fed with high-fat or normal diet for five months.The body and gonadal organ weight of mice were measured,and their indices were calculated.The sperm concentration,the sperm viabili-ty,the testicular histomorphology and the expression levels of tight junction proteins ZO-1,Occludin and Claudin-11 were measured.TM4 cells were treated with palmitic acid(PA)for 24 h.Cell viability was detected by CCK-8 method.Then,TM4 cells were di-vided into different groups treated with PA(0,50,100,200 and 300 μmnol·L-1),and the expression lev-els of tight junction proteins ZO-1,Occludin and Clau-din-11 were detected by Western blot.The tight junc-tion permeability of TM4 cells were detected by transepithelial electrical resistance(TEER)and FITC-dextran.The expression levels of mRNA and proteins for the NF-κB/NLRP3 pathway-related factors were de-tected by RT-qPCR and Western blot.Results The results from animal experiments showed that high-fat diet increased body weight and seminal vesicle weight of mice,and decreased testicular index,epididymal in-dex,sperm concentration and sperm motility of mice.High-fat diet also caused testicular tissue structure damage and down-regulated the expression levels of tight junction proteins ZO-1 and Occludin,without af-fecting the expression of Claudin-11.In vitro,PA sig-nificantly down-regulated the expression levels of ZO-1,Occludin and Claudin-11 in TM4 cells,increased the cell permeability,as well as up-regulated the mRNA and protein expression levels of NLRP3/NF-κB signa-ling pathway-related factors in TM4 cells.Conclusions High-fat diet can impair the function of tight junction of testicualr Sertoli cells,and the machanism may be related to the activation of the NF-κB/NLRP3 signaling pathway,resulting in Sertoli cell inflammation in mice.

Objective:To analyze the influencing factors of severe dengue fever patients in the early stage, construct a early prediction model for severe dengue fever, and evaluate it.Methods:A retrospective analysis was conducted to collect early clinical data of dengue fever patients admitted to the People's Hospital of Mengla County and the Third People's Hospital of Kunming in Yunnan Province from July to December 2023. The multifactor logistic regression was used to analyze the factors affecting the severe dengue fever patients, and Nomogram prediction model was used for visualization. Receiver operating characteristic (ROC) curve and calibration curve analysis were used to evaluate the model.Results:A total of 534 dengue fever patients were included, including 291 males and 243 females, aged (39.95 ± 15.69) years. Among them, there were 59 cases (11.05%) of severe dengue fever. The results of multifactor logistic regression analysis showed that age ( OR = 1.05, 95% CI: 1.02 - 1.08, P < 0.001), cardiovascular disease ( OR = 5.28, 95% CI: 2.08 - 13.40, P < 0.001), serous effusion ( OR = 4.34, 95% CI: 1.63 - 11.57, P = 0.003), aspartate aminotransferase ( OR = 1.03, 95% CI: 1.02 - 1.04, P < 0.001), lactate dehydrogenase ( OR = 1.00, 95% CI: 1.00 - 1.01, P = 0.001), and fibrinogen ( OR = 0.46, 95% CI: 0.28 - 0.76, P = 0.003) were independent influencing factors in the early stage of severe dengue fever. The area under the ROC curve of the Nomogram prediction model constructed from the above six variables was 0.96 (0.93 - 0.98). The calibration curve analysis results showed that the mean absolute error between the predicted values of the Nomogram prediction model and the actual observed values was 0.014. Conclusions:Age, cardiovascular disease, serous effusion, aspartate aminotransferase, lactate dehydrogenase, and fibrinogen are independent influencing factors in the early stage of severe dengue fever. The Nomogram prediction model established based on these variables has good predictive ability for severe dengue fever.