Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

BACKGROUND:Kaempferol has anti-osteoporotic effects,but the mechanisms by which kaempferol regulates gut microbiota and metabolites to prevent and treat osteoporosis remain unclear.OBJECTIVE:To exploring the potential mechanisms by which kaempferol inhibit osteoporosis based on gut microbiota and comprehensive targeted metabolomics.METHODS:Eighteen female Sprague-Dawley rats were randomly divided into three groups:sham operation group,model group,and kaempferol group,with 6 rats in each group.Animal models of osteoporosis were made in the latter two groups through removal of bilateral ovaries.Eight weeks after modeling,the sham operation and model groups were gavaged with distilled water,and the kaempferol group was gavaged with 40 mg/kg kaempferol.Continuous administration in each group was carried out for 12 weeks.Rat fecal samples were collected for 16S rDNA amplicon sequencing to observe changes in the gut microbiota structure.Serum samples were subjected to comprehensive targeted metabolomics analysis using ultra-high performance liquid chromatography-tandem mass spectrometry technology,along with a proprietary database and multivariate statistical analysis.RESULTS AND CONCLUSION:After 12 weeks of continuous intervention,the results of 16S rDNA amplicon sequencing showed that compared with the sham operation group,the abundance of gut microbiota increased in the model group.Compared with the model group,kaempferol group exhibited a statistically significant increase in the abundance of the genus Latilactobacillus(P=0.021),while the abundances of Pantoea(P=0.034),Enterorhabdus(P=0.000),Monoglobus(P=0.024),Butyricimonas(P=0.034),Rothia(P=0.043),and Clostridia(P=0.004)were significantly downregulated.After 12 weeks of continuous intervention,the results of the serum samples analyzed by broad-targeted metabolomics revealed that 120 and 79 metabolites were identified between the sham operation and model groups and between the model and kaempferol groups,respectively.Among the three groups,there were 17 overlapping differentially expressed metabolites,including Cis-aconitic acid,barbituric acid,L-homocitrulline,3,4,5-trimethoxycinnamic acid,L-3-phenyllactic acid,cyclo(pro-pro),L-phenylalanine-L-serine,proline-isoleucine,L-donoraminoacetic acid-L-phenylalanineacetic acid,and phenylalanine-aspartic acid.Most of them belong to amino acids and their metabolites,glycerophospholipids and fatty acyls.The Kyoto Encyclopedia of Genes and Genomes pathways involved in the differential metabolites were mainly enriched in D-amino acid metabolism,histidine metabolism,propionate metabolism,lysine degradation,fatty acid metabolism and sphingolipid metabolism.After 12 weeks of continuous intervention,combined analysis revealed that genera such as Enterorhabdus,Latilactobacillus,Rothia,and Ruminococcus were closely associated with differential serum metabolites.To conclude,kaempferol may exert its anti-osteoporotic effects by modulating the abundance,diversity,and structure of gut microbiota,thereby regulating the metabolism of amino acids,their metabolites,and fatty acids.

AIM To study the chemical constituents from Commelina communis L.METHODS The 95％ethanol extract from C.Communis was isolated and purified by activated charcoal,silica gel,Sephadex LH-20,and HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Seventeen compounds were isolated and identified as p-hydroxyl ethyl cinnamate(1),p-hydroxybenzaldehyde(2),vanillin(3),4-hydroxy-2,3-dimethyl-2-nonen-4-olide(4),hemeratrol A(5),chakyunglupulin B(6),chakyunglupulin A(7),2-(2-hydroxyethyl)-3-methylfumaric acid(8),N-cis-feruloyl tyramine(9),N-trans-coumaroyltyramine(10),5,6,7,3',4',5'-hexamethoxyflavone(11),N-trans-sinapoyltyramine(12),dihydro-feruloyltyramine(13),N-trans-feruloyltyramine(14),2-phenylethanol-β-D-glucoside(15),quercetin-3-O-β-D-glucoside(16),and isorhamnetin-3-O-β-D-glucopyranoside(17).CONCLUSION Compounds 4-8,10 and 11 are isolated from Commelina genus for the first time,and 1,9,12-15 are first isolated from this plant.

Natural products are an important source for innovative drugs,but unclear molecular targets and mechanisms limit their further development and application.The authors proposed a new method for the target identification of natural products based on proteolysis-targeting chimera(PROTAC)technology and quantitative proteomics,and established the targeted degradomics(TGDO) technology for the identification of weak-affinity tar-gets.This article summarizes the standardized workflow and the application of TGDO for target identification of natural products.

Objective:To investigate the influencing factors of secondary type 2 diabetes in young obesity patients, and construct and validate a risk prediction model.Methods:The retrospective cohort study was conducted. The clinical data of 847 young obesity patients who were admitted to The First Affiliated Hospital of Nanjing Medical University from January 2022 to July 2024 were collected. There were 382 males and 465 females, aged (29.4±3.8)years. Patients were randomly divided into a training set of 593 cases and a validation set of 254 cases based on a random number table method of 7∶3 ratio. The training set was used to construct the prediction model, and the validation set was used to validate prediction model. Observation indicators: (1) analysis of influencing factors of secondary type 2 diabetes in young obesity patients; (2) construc-tion and validation of a prediction model for secondary type 2 diabetes in young obesity patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate analysis was performed using the corresponding statistical methods based on data types. Multivariate analysis was performed using the Logistic regression model, and the area under the curve (AUC) of receiver operating characteristic (ROC) curve, the Hosmer-Lemeshow test, the calibration curve and decision curve were used to evaluate the predictive performance of the model. Results:(1) Analysis of influencing factors of secondary type 2 diabetes in young obesity patients. Of the 847 young obesity patients, there were 238 patients with secondary type 2 diabetes, including 161 cases in the training set and 77 cases in the validation set, 609 patients of simple obesity, including 432 cases in the training set and 177 cases in the validation set. Results of multivariate analysis showed that family history of diabetes, hypertension, high-sugar diet, exercise habits, triglyceride (TG), homeostasis model assessment of insulin resistance (HOMA-IR) and neutrophil-to-lymphocyte ratio (NLR) were independent factors influencing secondary type 2 diabetes in young obesity patients [ odds ratio=9.476, 2.420, 3.219, 0.272, 2.137, 26.759, 41.535, 95% confidence interval ( CI) as 3.242-27.696, 1.159-5.052, 1.525-6.796, 0.117-0.632, 1.019-4.481, 12.907-55.476, 16.085-107.251, P<0.05]. (2) Construction and validation of a prediction model for secondary type 2 diabetes in young obesity patients. A nomogram prediction model for secondary type 2 diabetes in young obesity patients was constructed based on the results of multivariate analysis. Results of ROC curve analysis showed that the AUC of prediction model for the training set was 0.963(95% CI as 0.946-0.980), with sensitivity of 89.6% and specificity of 93.2%, respectively, and the AUC of prediction model for the validation set was 0.966(95% CI as 0.944-0.988), with sensitivity of 92.7% and specificity of 88.3%, respectively. Results of Hosmer-Lemeshow test showed that the P-values for both the training set and validation set were >0.05, indicating good model fit. The calibration curves for both the training set and validation set closely matched the actual curve, demonstrating the prediction model with a good fit. The decision curve analysis showed high practical value of the model. Conclusions:Family history of diabetes, hypertension, high-sugar diet, exercise habits, TG, HOMA-IR and NLR are independent factors influencing secondary type 2 diabetes in young obesity patients. The prediction model constructed based on these factors demons-trates good predictive performance.

Natural products are an important source for innovative drugs,but unclear molecular targets and mechanisms limit their further development and application.The authors proposed a new method for the target identification of natural products based on proteolysis-targeting chimera(PROTAC)technology and quantitative proteomics,and established the targeted degradomics(TGDO) technology for the identification of weak-affinity tar-gets.This article summarizes the standardized workflow and the application of TGDO for target identification of natural products.

In view of the characteristics of H5N6 subtype avian influenza virus(AIV)that it has both high pathogenicity and the risk of cross-species transmission,posing a serious threat to the poultry farming industry and public health security,in order to effectively prevent and control the spread of H5N6 avian influenza,a rapid,sensitive and specific detection technolo-gy was established in this study.The specific monoclonal antibodies against the neuraminidase N6 protein of avian influenza A virus subtype H5N6 were obtained through hybridoma and monoclonal antibody technology.These antibodies were coupled and labeled with carboxyl-functionalized fluorescent quantum dots,along with previously prepared specific antibodies against the hemagglutinin H5 protein.A rapid fluorescence immunochromatographic detection method for the H5N6 subtype of avian influ-enza virus was established according to the principle of double-antibody sandwich immunochromatography.This method a-chieved a detection sensitivity of 1 ng/mL for recombinant hemagglutinin H5 subtype protein and 0.1 ng/mL for recombinant neuraminidase N6 subtype protein.Moreover,the method exhibited no cross-reactivity with other influenza subtypes or patho-gens,such as Newcastle disease(ND),infectious bronchitis(IB),and infectious laryngotracheitis(ILT),thus demonstrating good specificity.The method effectively identified the highly pathogenic avian influenza virus H5 subtype and directly distin-guished the H5N6 subtype with good accuracy.The fluorescent quantum dot immunochromatographic typing detection method established herein met the sensitivity,specificity,and accuracy requirements for H5N6 subtype detection,and can be further used for rapid detection of the H5 and H5N6 subtypes of avian influenza virus.

BACKGROUND:Kaempferol has anti-osteoporotic effects,but the mechanisms by which kaempferol regulates gut microbiota and metabolites to prevent and treat osteoporosis remain unclear.OBJECTIVE:To exploring the potential mechanisms by which kaempferol inhibit osteoporosis based on gut microbiota and comprehensive targeted metabolomics.METHODS:Eighteen female Sprague-Dawley rats were randomly divided into three groups:sham operation group,model group,and kaempferol group,with 6 rats in each group.Animal models of osteoporosis were made in the latter two groups through removal of bilateral ovaries.Eight weeks after modeling,the sham operation and model groups were gavaged with distilled water,and the kaempferol group was gavaged with 40 mg/kg kaempferol.Continuous administration in each group was carried out for 12 weeks.Rat fecal samples were collected for 16S rDNA amplicon sequencing to observe changes in the gut microbiota structure.Serum samples were subjected to comprehensive targeted metabolomics analysis using ultra-high performance liquid chromatography-tandem mass spectrometry technology,along with a proprietary database and multivariate statistical analysis.RESULTS AND CONCLUSION:After 12 weeks of continuous intervention,the results of 16S rDNA amplicon sequencing showed that compared with the sham operation group,the abundance of gut microbiota increased in the model group.Compared with the model group,kaempferol group exhibited a statistically significant increase in the abundance of the genus Latilactobacillus(P=0.021),while the abundances of Pantoea(P=0.034),Enterorhabdus(P=0.000),Monoglobus(P=0.024),Butyricimonas(P=0.034),Rothia(P=0.043),and Clostridia(P=0.004)were significantly downregulated.After 12 weeks of continuous intervention,the results of the serum samples analyzed by broad-targeted metabolomics revealed that 120 and 79 metabolites were identified between the sham operation and model groups and between the model and kaempferol groups,respectively.Among the three groups,there were 17 overlapping differentially expressed metabolites,including Cis-aconitic acid,barbituric acid,L-homocitrulline,3,4,5-trimethoxycinnamic acid,L-3-phenyllactic acid,cyclo(pro-pro),L-phenylalanine-L-serine,proline-isoleucine,L-donoraminoacetic acid-L-phenylalanineacetic acid,and phenylalanine-aspartic acid.Most of them belong to amino acids and their metabolites,glycerophospholipids and fatty acyls.The Kyoto Encyclopedia of Genes and Genomes pathways involved in the differential metabolites were mainly enriched in D-amino acid metabolism,histidine metabolism,propionate metabolism,lysine degradation,fatty acid metabolism and sphingolipid metabolism.After 12 weeks of continuous intervention,combined analysis revealed that genera such as Enterorhabdus,Latilactobacillus,Rothia,and Ruminococcus were closely associated with differential serum metabolites.To conclude,kaempferol may exert its anti-osteoporotic effects by modulating the abundance,diversity,and structure of gut microbiota,thereby regulating the metabolism of amino acids,their metabolites,and fatty acids.

Objective:To explore the factors associated with the efficacy of high-frequency repetitive transcranial magnetic stimulation (rTMS) in the treatment of neuropathic pain (NP) following spinal cord injury (SCI).Methods:This was a retrospective study of 89 SCI survivors with NP receiving high-frequency rTMS. Those with a ≥30% reduction in their Numeric Rating Scales (NRS) scores after 2 weeks of treatment were termed Responders ( n=36), with the others classified as non-responders ( n=53). Demographic data (gender, education level, age), SCI characteristics (injury etiology, injury severity, neurological injury level, injury duration), NP characteristics (pain type, pain intensity, analgesic use), functional assessment (Modified Ashworth Scale score, Spinal Cord Independence Measure score, Modified Barthel Index score, American Spinal Injury Association motor/sensory score) were collected. Least absolute shrinkage and selection operator (LASSO) regression was used for variable selection, followed by binary logistic regression to identify factors associated with treatment efficacy. Results:Among the 89 patients, 36 (40.4%) were Responders to high-frequency rTMS. Binary logistic regression revealed that those with a cervical spinal cord injury and/or spasticity and women were more likely to respond to high-frequency rTMS.Conclusions:Female gender, cervical spinal cord injury, and spasticity are independent factors predicting rTMS efficacy in treating SCI, with spasticity demonstrating the strongest association.