Objective To establish an HPLC method to determine the concentration of inositol nicotinate（IN） in rat skin, and study the pharmacokinetic characteristics of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats. Methods HPLC method was used to establish a simple and rapid analytical method for the determination of IN concentration in the skin of rats at different time points after administration. The established method was used to study the pharmacokinetics of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats, and the pharmacokinetic parameters were fitted with DAS software. Results The linearity of the analytical method was good in the concentration range of 0.25-20 μg/ml, the quantitative limit was 0.25 μg/ml, and the average recovery rate was 96.18%. The pharmacokinetic parameters of IN after transdermal administration of heparin sodium inositol nicotinate cream in rats were as follows: t_1/2 was （4.555±2.054） h, T_max was （6±0）h, C_max was （16.929±2.153）mg/L, AUC_0−t was （150.665±16.568） mg·h /L ,AUC_0−∞ was （161.074±23.917） mg·h /L, MRT_（0−t） was （9.044±0.618）h, MRT_{（0−∞）} was （10.444±1.91） h, CLz/F was （0.19±0.03） L/（h·kg）, and Vz/F was （1.19±0.437） L/（h·kg）. Conclusion IN could quickly penetrate the skin and accumulate in the skin for a long time, which was beneficial to the pharmacological action of drugs on the lesion site for a long time. The method is simple, rapid, specific and reproducible, which could be successfully applied to the pharmacokinetic study of IN after transdermal administration in rats.

A UHPLC-Q-Orbitrap/MS method was developed to identify the related substances in apixaban tablets. Complete separation was accomplished with a Waters Xbridge C18 (250 mm×4.6 mm, 5 μm) column by linear gradient elution using a mobile phase consisting of 30 mmol/L ammonium acetate buffer solution (pH 4.50) and acetonitrile. The related substances were successfully characterized through the accurate mass and elemental composition of the parent ions and their product ions determined by electrospray positive ionization high-resolution Q-Orbitrap/MS methods. Under the established analytical condition, apixaban and its related substances were well separated, and 30 related substances were detected and identified by hyphenated techniques in apixaban tablets and their stressed samples. Among them, 11 were known impurities and the rest 19 were unknown related substances identified for the first time in this study. The results obtained are valuable for apixaban manufacturing process optimization and quality control.

Allergen-specific immunotherapy（AIT） remains the only therapeutic approach with the potential to modify the natural course of allergic rhinitis（AR）. Nevertheless, considerable inter-individual variability exists in patients'responses to AIT. To facilitate more reliable assessment of treatment efficacy, the China Rhinopathy Research Cooperation Group（CRRCG） convened young and middle-aged nasal experts in China to formulate the present consensus. The recommended subjective outcome measures for AIT comprise symptom scores, medication scores, combined symptom and medication scores, quality-of-life assessments, evaluation of disease control, and assessment of comorbidities. Objective indicators may supplement these measures. Currently available objective approaches include skin prick testing, nasal provocation testing, and allergen exposure chambers. However, these methods remain constrained by practical limitations and are not yet appropriate for routine implementation in clinical efficacy evaluation. In addition, several biomarkers, including sIgE and the sIgE/tIgE ratio, sIgG4, serum IgE-blocking activity, IgA, cytokines and chemokines, as well as immune cell surface molecules and their functional activity, have been shown to have associations with AIT outcomes. While these biomarkers may complement subjective assessments, they are subject to significant limitations. Consequently, large-scale multicenter trials and real-world evidence are required to strengthen the evidence base. The present consensus underscores the necessity of integrating patients'subjective experiences with objective testing throughout the treatment process, thereby providing a more comprehensive and accurate framework for efficacy evaluation. Looking forward, future investigations should prioritize the incorporation of multi-omics data and artificial intelligence methodologies, which hold promise for overcoming current limitations in assessment strategies and for advancing both the standardization and personalization of AIT.
Humans ; Allergens/immunology* ; China ; Consensus ; Desensitization, Immunologic ; Immunoglobulin E ; Quality of Life ; Rhinitis, Allergic/therapy* ; Treatment Outcome ; East Asian People

Glucose-6-phosphate dehydrogenase (G6PD), the first rate-limiting enzyme of the pentose phosphate pathway (PPP), is aberrantly activated in multiple types of human cancers, governing the progression of tumor cells as well as the efficacy of anticancer therapy. Here, we discovered that cyclin-dependent kinase 5 (CDK5) rewired glucose metabolism from glycolysis to PPP in breast cancer (BC) cells by activating G6PD to keep intracellular redox homeostasis under oxidative stress. Mechanistically, CDK5-phosphorylated G6PD at Thr-91 facilitated the assembly of inactive monomers of G6PD into active dimers. More importantly, CDK5-induced pho-G6PD was explicitly observed specifically in tumor tissues in human BC specimens. Pharmacological inhibition of CDK5 remarkably abrogated G6PD phosphorylation, attenuated tumor growth and metastasis, and synergistically sensitized BC cells to poly-ADP-ribose polymerase (PARP) inhibitor Olaparib, in xenograft mouse models. Collectively, our results establish the crucial role of CDK5-mediated phosphorylation of G6PD in BC growth and metastasis and provide a therapeutic regimen for BC treatment.

The iridoid glycosides from Veronica anagallis-aquatica L. alleviate heart failure by modulating the gut microbiota and influencing the production of two metabolites with potential antihypertrophic effects, HVA and 2OH-VA.Image 1.

A method was developed for determination of dilauryl thiodipropionate(DLTDP)in fried foods by coupling solid-phase extraction(SPE)pretreatment with reverse-phase liquid chromatography-tandem mass spectrometry(RPLC-MS/MS)detection.Samples were extracted with n-hexane as the solvent,purified using a neutral alumina SPE cartridge,and finally analyzed by RPLC-MS/MS.Quantitative analysis was performed using matrix-matched calibration curves combined with an external standard method under optimal experimental conditions.The results showed that DLTDP exhibited good linearity in the range of 2.0-50.0 μg/L,with a correlation coefficient(R2)≥0.999.The limit of detection(LOD)and the limit of quantification(LOQ)of the method were 0.15 mg/kg and 0.5 mg/kg,respectively.The mean recoveries at three fortification levels(0.5,1.0,and 200 mg/kg)in different samples ranged from 84.8%to 96.8%,with the relative standard deviations(RSDs)all less than 8.0%.The developed method was highly sensitive,accurate and reliable,and easy to operate,making it well suited for the routine quantitative analysis of DLTDP in fried foods.

Objective To explore the pathogenesis of Alzheimer's disease by examining the effects of dihydroartemisinin(DHA)on cognitive behavior,hippocampal,cerebral cortex and retinal cell morphology,β-amyloid(Aβ)and autophagy-related proteins in 5×FAD mice.Methods Twenty 5×FAD mice and 5 wild type(WT)mice were selected,all of which were female.The 5×FAD mice were randomly divided into model(M)group,donepezil(D)group,low-dose DHA(DHA-L)group,and high-dose DHA(DHA-H)group.The WT and M groups were not treated,and the D group was given donepezil 0.1 mg/kg per day.DHA-L group and DHA-H group were given 10 mg/kg and 20 mg/kg DHA per day,respectively.Group D,group DHA-L and group DHA-H were given intragastric administration once a day for 3 months.The changes of in cognitive behavior were measured by Morris experiment.HE staining was used to observe the arrangement and morphology of nerve cells in cerebral cortex,hippocampus and retina.The expressions of Aβ protein in cerebral cortex,hippocampus and retina were detected by immunohistochemistry.Western blotting detected the expression of autophagy related proteins(LC3-Ⅰ,LC3-Ⅱ,Beclin-1,P62,β-actin).Results The DHA-H group and the D group exhibited more frequent adoption of both linear and trending exploration routes.Compared to the model group,significant differences in the contents of Aβ in the hippocampal CA1,cerebral cortex S1,and retinal were observed(P＜0.0001)in the other four groups.The analysis also showed significant differences in autophagy-associated proteins between the DHA-L,DHA-H,and model groups(P＜0.01).Conclusion DHA improves cognitive function and increases the number of nerve cells in mice.It also reduces Aβ content in the cerebral cortex,hippocampus,and retina,along with improving autophagy-associated protein deposition in mice.

Objective To develop and validate risk prediction models utilizing five machine learning algorithms for assessing postoperative pulmonary infection(PPI)risk in lung cancer patients undergoing grade Ⅳ thoracoscopic surgery.Methods A retrospective cohort study included 2,380 lung cancer patients who underwent grade Ⅳ thoracoscopic surgery at a tertiary hospital in Shanghai(January 2022 to June 2024).Patients were stratified into training(n=1,665)and validation(n=715)cohorts.Five machine learning algorithms—Logistic regression(LR),artificial neural network(ANN),support vector machine(S VM),random forest(RF),and extreme gradient boosting(XGB)—were employed to construct predictive models.A nomogram was developed for clinical utility.Results Among 2,380 patients,226(9.5％)developed PPI.The Least Absolute Shrinkage and Se-lection Operator(LASSO)regression identified eight predictive variables:daily cigarette consumption,diabetes history,preoperative diffusing capacity,maximal tumor diameter,24-hour postoperative chest drainage volume,perioperative oral nutritional supplementation(ONS),postoperative urinary cathe-terization,and intraoperative pleural adhesion severity.All models demonstrated robust discrimina-tion,with area under the curve(AUC)values ranging from 0.862 to 0.947.The XGB model a-chieved superior performance(AUC=0.947,95％CI,0.937 to 0.962),followed closely by the LR model(AUC=0.926,95％CI,0.918 to 0.933).Conclusion Machine learning-based algo-rithms models effectively stratify PPI risk in lung cancer patients following grade Ⅳ thoracoscopic surgery.The derived nomogram provides a practical tool for perioperative risk management by healthcare providers.

Objective To investigate the effect of quercetin on HCE-2 injury of human corneal epithelial cells induced by high osmotic pressure and its mechanism.Methods HCE-2 cells were randomly divided into control group(normal osmotic pressure),model group(high osmotic pressure),experimental-L group(high osmotic pressure+31.25 pg·mL-1 quercetin),experimental-M group(high osmotic pressure+62.50 μg·mL-1 quercetin),experimental-H group(high osmotic pressure+125.00 μg·mL-1 quercetin),erastin group(high osmotic pressure+125.00 μg·mL-1 quercetin+30.00 μmol·L-1 iron death inducer erastin).Cell survival rate was detected by cell counting kit 8;reactive oxygen species(ROS)levels was detected by C11-BODIPY 581/591 probe staining;glutathione(GSH)and malondialdehyde(MDA)levels were determined by kit method;the expression levels of glutathione peroxidase 4(GPX4),dihydrolactate dehydrogenase(DHODH)and ferroptosis suppressor protein 1(FSP1)were detected by real-time quantitative polymerase chain reaction and Western blot.Results The cell survival rates of control group,model group,experimental-H group and erastin group were(100.00±3.97)％,(50.05±5.83)％,(86.35±7.35)％and(58.32±4.66)％,respectively;ROS levels were 1.00±0.09,2.45±0.16,1.19±0.05 and 2.09±0.30,respectively;GPX4 protein levels were 1.09±0.11,0.34±0.03,0.91±0.12 and 0.30±0.04,respectively;FSP1 protein levels were 0.92±0.06,0.25±0.03,0.89±0.07 and 0.39±0.07,respectively;DHODH protein levels were 0.89±0.11,0.31±0.04,0.86±0.11,0.41±0.04,respectively.Compared with model group,the above indexes in control group were statistically significant(all P＜0.05);the differences between experimental-H group and model group were statistically significant(all P＜0.05);the above indexes in erastin group were significantly different from those in experimental-H group(all P＜0.05).Conclusion Quercetin can ameliorate HCE-2 cell damage induced by high osmotic pressure by inhibiting iron death pathway.

Objective To construct machine learning models that can be used to predict AUC fold change(FC)using a database of existing pharmacokinetic(PK)and drug-drug interaction(DDI)information,which can be used to explore the possibility of predicting existing drug interactions and to provide certain rational recommendations for clinical drug use.Methods PK data of DDIs and AUC fold change data were extracted from FDA-approved drug labels.Peptide and pharmacodynamic(PD)information related to drug interactions were retrieved through DrugBank,and PPDT identification of relevant peptide IDs was performed using Protein Resource(UniProt),and a matrix normalization code was used to generate multidimensional vector data that were easy to analysis.The effect of PPDT on the AUC,and the resulting multiplicity change was used as the dependent variable for machine learning model construction.The model with the smallest root mean square error(RMES)value was used for model construction to train a bagged decision tree(Bagged)prediction model.The models were tested using the trained models for some of the drug tests.The models were evaluated by reviewing the available literature findings on detection of drug interaction pairs and analyzing and comparing the predicted values.Results A total of 16 pairs of model drug pairs were tested for the effects of 16 drugs on tacrolimus,and it was found that the accuracy of the prediction of the presence or absence of drug interactions was 81.25％;the prediction results were classified according to the FDA standard classification of the strong and weak for the strength of drug interactions,and the results showed that the prediction of the strength of drug interactions,with a large deviation from the larger prediction was less.Conclusion The evaluation of the model to predict the presence or absence of drug interactions was general;however,after classifying the strengths and weaknesses of drug interactions,the prediction of drug interactions was better,and the prediction results indicated that the model prediction performance has a certain reference value for potential DDI assessment before clinical trials.