Allergic rhinitis (AR), a globally prevalent immune-mediated inflammatory condition, is still an incurable disease. In the present study, we have validated the impact of the Kelch-like ECH associated protein 1 (Keap1)-related oxidative stress and inflammatory response in clinical AR patient peripheral blood and nasal swab samples, emphasizing the biological relevance of Keap1 and AR. Targeting Keap1 -nuclear factor erythroid 2-related factor 2 (Nrf2) related anti-oxidative stress may be effective for AR intervention. Drawing inspiration from the Keap1 homodimerization and the E3 ligase characteristics, we herein present a design of novel bivalent molecules for chemical knockdown of Keap1. For the first time, we characterized ternary complexes of Keap1 dimer and one molecule of bivalent compounds. The best bivalent molecule 8 encompasses robust capacity to degrade Keap1 as a homoPROTAC^KEAP1. It efficaciously suppresses inflammatory cytokines in extensively different cells, including human nasal epithelial cells. Moreover, in an AR mouse model, we confirmed that the chemical degradation induced by homoPROTAC^KEAP1 led to therapeutic benefits in managing AR symptoms, oxidative stress and inflammation. In summary, our findings underscore the efficacy of targeting the Keap1 system through the homoPROTAC-ing technology as an innovative and promising treatment strategy for the incurable allergic disorders.

Numerous research conducted in recent years has revealed that gut microbial dysbiosis, such as modifications in composition and activity, might influence lung tissue homeostasis through specific pathways, thereby promoting susceptibility to lung diseases. The development and progression of lung cancer, as well as the effectiveness of immunotherapy are closely associated with gut flora and metabolites, which influence immunological and inflammatory responses. During abnormal proliferation, non-small cell lung cancer cells acquire more substances and energy by altering their own metabolic pathways. Glucose and amino acid metabolism reprogramming provide tumor cells with abundant ATP, carbon, and nitrogen sources, respectively, providing optimal conditions for tumor cell proliferation, invasion, and immune escape. This article reviews the relationship of immune response with gut flora and metabolic reprogramming in non-small cell lung cancer, and discusses the potential mechanisms by which gut flora and metabolic reprogramming affect the occurrence, development, and immunotherapy of non-small cell lung cancer, in order to provide new ideas for precision treatment of lung cancer patients.
Humans ; Gastrointestinal Microbiome/immunology* ; Carcinoma, Non-Small-Cell Lung/therapy* ; Lung Neoplasms/therapy* ; Immunotherapy ; Metabolic Reprogramming

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Objective:Integrating genes and GEO database related cuproptosis chips,to analyze connection between cupropto-sis genes,immune infiltration and myocardial infarction(MI),construct risk prediction model,predict Western medicine and Chi-nese medicine,analyze miRNA-mRNA regulatory network,and to provides a new research direction for the future study of MI-related cuproptosis mechanism and immune infiltration.Methods:By GEO database retrieval of MI related chips,standardized processing and MI-related cuproptosis genes screening were performed,and immunoinfiltration analysis and quantification were performed based on the treated gene expression matrix,correlation between immune infiltrating cells and function was analyzed,as well as their differ-ences in MI group and the control group.Cuproptosis genes that most related to MI in immune infiltration were screened out,and the risk model was constructed to analyze the risk probability of cuproptosis genes in MI.The Enrichr website and Coremine Medical data-base were used to predict cuproptosis-related genes in MI in Western medicine and traditional Chinese medicine.Finally,the up-stream mirnas of FDX1 and SLC31A1 were predicted by miRTarBase,Starbase and Targetscan databases,and miRNA-mRNA regula-tory networks were constructed.Results:Correlation of immune infiltration showed that Tfh cells and B cells had the strongest positive correlation(r=0.68),while regulatory T cells and iDC had the strongest negative correlation(r=-0.63);the difference analysis of im-mune infiltration showed that the differences among mast cells,NK cells and Th1 cells in the MI group at the cellular level were the most significant(P<0.001);and the differences in APC co-inhibition and MHCⅠ at the functional level were the most significant(P<0.001).Six genes with the highest correlation between immune cells and immune function were screened out:ATP7A,DLD,FDX1,LIAS,LIPT1 and SLC31A1.Results of the risk model showed that the high levels of FDX1 and SLC31A1 were negatively correlated with the risk prediction of MI.A total of 21 Western medicines and 30 traditional medicines were predicted by database comparison.miRTarBase,Starbase and Targetscan databases predicted 9 upstream miRNAs of cuproptosis-related genes in MI,including has-miR-122-5p.Conclusion:Tfh cells,B cells,para-inflammatory,typeⅠinterferon response and other related immune cells and functions may play important roles in pathogenesis and prognosis of MI.FDX1 and SLC31A1 as the key genes of cuproptosis process,are negatively correlated with MI.A total of 30 kinds of traditional Chinese medicines including Spirulina,sheep liver,Wen ezhu,Pian jianghuang and Yujin may have potential value in treatment of MI.Finally,9 miRNAs including has-miR-122-5p may play an important role in the regulation of cuproptosis in myocardial infarction.

Objective To investigate the effect and mechanism of Liraglutide on the spatial learning and memory function in type 2 diabetes mellitus(T2DM)rats.Methods SD rats were randomly divided into control group(NC),T2DM group(T2DM)and Liraglutide group(Lir).The ability of learning and memory was evaluated by Morris water maze method.Apoptosis of hippocampal neuron was tested by TUNEL staining.The mRNA expression levels of inflammatory cytokines TNF-α,IL-1β and IL-6 were measured by real time-PCR.The protein expressions of heme oxygenase-1(HO-1),NADPH oxidase 1(NOX1),protein B-cell lymphoma-2(Bcl-2)and Bcl2-associated X(Bax)in hippocampus tissues were determined by Western blot.Results Compared with T2DM group,the percent time in target quadrant was increased in Lir group(P<0.05),while the escape latency of day 3 to day 5 was significantly decreased in Lir group(P<0.05).The apoptosis of hippocampal neurons was reduced in Lir group,and the morphological changes,including hyperchromatic cytoplasm and karyopyknosis were alleviated.Compared with T2DM group,MDA content,mRNA level of TNF-α,IL-1β and IL-6,and protein expression of NOX1 and Bax were decreased(P<0.05),while T-AOC,SOD,HO-1 and Bcl-2 protein expression were increased in Lir group(P<0.05).Conclusions Liraglutide ameliorates diabetes-related learning and memory impairment by regulating antioxidant,anti-inflammatory and anti-apoptotic effects in hippocampus.

Objective:To evaluate the right atrial volume and function abnormalities in patients with pulmonary hypertension (PH) by four-dimensional automatic quantitation technique, and to explore the application value of this technique in evaluating the risk stratification and World Health Organization functional class(WHO-FC) of PH patients.Methods:Eighty-four adult patients with PH diagnosed by right heart catheterization from April to October 2022 in Fuwai Central China Cardiovascular Hospital were consecutively enrolled as the PH group. All cases were divided into 3 groups according to the mean pulmonary arterial pressure (mPAP): mild PH group ( n=28), moderate PH group ( n=28), severe PH group ( n=28). Twenty-eight healthy volunteers matched by gender and age were included in the same period as the control group. The volume and strain parameters of the right atrium were obtained by analyzing the four-dimensional image of the right atrium using four-dimensional automatic quantitation technique, including right atrial minimum volume index (RAVImin), right atrial maximum volume index (RAVImax), right atrial presystolic volume index (RAVIpreA), right atrial ejection fraction (RAEF), right atrial passive ejection fraction (RAPEF), right atrial active ejection fraction, RAAEF, longitudinal strains of right atrial reserve, conduit and systolic period (RASr, RAScd, RASct), circumferential strains of right atrial reserve, conduit and systolic period (RASr-c, RAScd-c, RASct-c). The differences in right atrial parameters among four groups were compared.ROC curve was used to analyze the diagnostic efficiency of right atrial four-dimensional strain parameters for PH patients with WHO-FC≥Ⅲ. Pearson linear correlation analysis was used to investigate the relationships between RASr and right atrial area (RAA), NT-proBNP and tricuspid annular plane systolic excursion to pulmonary arterial systolic pressure ratio (TAPSE/sPAP). Results:①Compared with the control group, RAEF, RAPEF, RASr, RAScd, RASr-c, RAScd-c were significantly decreased in mild, moderate and severe PH groups; while RAAEF, RASct, RASct-c were significantly increased in mild PH group and significantly decreased in moderate and severe PH groups, and the differences were statistically significant (all P<0.05). RAVImin, RAVImax, RAVIpreA gradually increased among the control, mild PH, moderate PH and severe PH groups, and the differences were statistically significant (all P<0.05). RAEF, RAPEF, RAAEF, RASr, RAScd, RASct, RASr-c, RAScd-c, RASct-c were decreased successively among mild, moderate and severe PH groups, and the differences were statistically significant (all P<0.05). ②ROC curve showed that RASr had the highest diagnostic efficiency in PH patients with WHO-FC ≥Ⅲ, and the cut-off value was 20.5% (AUC=0.914, P<0.001). ③Correlation analysis showed that RASr was correlated with RAA, NT-proBNP and TAPSE/sPAP ( r=-0.803, -0.621, 0.739; all P<0.001). Conclusions:The degree of right atrial function impairment increased in patients with mild, moderate and severe PH in turn. RASr is the best predictor of WHO-FC ≥Ⅲ in patients with pulmonary hypertension and is a potential parameter for risk stratification in patients with PH.

Aiming at the hysteresis and destructiveness of off-line static detection of critical quality attribute of the moisture content of the raw material unit of the traditional Chinese medicine manufacturing process, honey-processed Tussilago farfara, honey-processed Astragalus and honey-processed Glycyrrhiza uralensis were used as the research carriers, and the drying method was used to measure the moisture content as a reference value. The moving stage was used to simulate the movement process of samples on the conveyor belt in the actual on-site production process, and near-infrared (NIR) spectra were collected, combined with machine learning, to establish NIR on-site dynamic detection model of moisture content in multi-variety honey-processed Chinese herbal slice. The results show that the second derivative method is used to preprocess the spectrum. The number of decision trees (ntree), the number of random features (max feature), and the minimum number of samples for generating leaf nodes (node size) are selected: 46, 76, and 8, respectively. The quantitative analysis model of moisture content has the best effect. The prediction coefficient of determination (the prediction coefficient of determination, R²_pre) and the root mean square error of prediction (root mean square error of prediction, RMSEP) of the model were 0.903 2 and 0.330 2, respectively. The NIR quantitative model for the moisture content of multi-variety honey-processed Chinese herbal slice established in this study has good predictive performance, and can achieve rapid, accurate and non-destructive quantitative analysis of the moisture content of honey-processed Tussilago farfara, honey-processed Astragalus and honey-processed Glycyrrhiza uralensis at the same time, and provides a method for determining the moisture content of honey-processed Chinese herbal slice of the raw material unit of the traditional Chinese medicine manufacturing process.

Aim To investigate the mechanism through which liraglutide (LRG) inhibited high glucose (HG)-induced cardiomyocyte hypertrophy. Methods Cultured H9c2 were divided into control (CON) group, HG group, low-, middle- and high-dose LRG (LRG-L, LRG-M and LRG-H) groups, LRG-H + autophagy inhibitor trimethyladenine (3-MA) group. The relative cell surface change was assessed phalloidin staining. Membrane bound Na, K