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Abstract Background The role of circular RNAs (circRNAs) as biomarkers of coronary artery disease (CAD) remains poorly explored. This study aimed to identify and validate potential circulating circRNAs as biomarkers for the diagnosis of CAD. Methods The expression profile of circRNAs associated with CAD was obtained from Gene Expression Omnibus (GEO) database. Differential expression analysis, weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operation (LASSO) were employed to identify CAD-related hub circRNAs. The expression levels of these hub circRNAs were validated using qRT-PCR in blood samples from 100 CAD patients and 100 controls. The diagnostic performance of these circRNAs was evaluated through logistic regression analysis, receiver operator characteristic (ROC) analysis, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Functional enrichment analyses were performed to predict the possible mechanisms of circRNAs in CAD. Results A total of ten CAD-related hub circRNAs were identified through WGCNA and LASSO analysis. Among them, hsa_circ_0069972 and hsa_circ_0021509 were highly expressed in blood samples of CAD patients, and they were identified as independent predictors after adjustment for relevant confounders. The area under the ROC curve for hsa_circ_0069972 and hsa_circ_0021509 was 0.760 and 0.717, respectively. The classification of patients was improved with the incorporation of circRNAs into the clinical model composed of conventional cardiovascular risk factors, showing an IDI of 0.131 and NRI of 0.170 for hsa_circ_0069972, and an IDI of 0.111 and NRI of 0.150 for hsa_circ_0021509. Functional enrichment analyses revealed that the hsa_circ_0069972-miRNA-mRNA network was enriched in TGF-β、FoxO and Hippo signaling pathways, while the hsa_circ_0021509-miRNA-mRNA network was enriched in PI3K/Akt and MAPK signaling pathways. Conclusion Hsa_circ_0069972 and hsa_circ_0021509 were identified by integrated analysis, and they are highly expressed in CAD patients. They may serve as novel biomarkers for CAD.

Abstract Background Ethyl acetate extracts from Tetrastigma hemsleyanum (Sanyeqing) (EFT), a member of the Vitaceae plant family, have been shown to exhibit efficacy against a variety of cancers. In this light, our current study seeks to examine the mechanism of efficacy between EFT extracts and human pancreatic cancer PANC-1 cells. Methods The chemical components of EFT were analyzed by gas chromatography–mass spectrometry. The cytotoxicity of EFT on PANC-1 cells was measured using an MTT assay. In order to investigate EFT induction of cell cycle arrest, changes in cell-cycle distribution were monitored by flow cytometry. Wound healing and transwell assays were employed to investigate whether migration and invasion of PANC-1 cells were inhibited by EFT. Relative protein expression was detected using Western blot. Results GC-MS analysis of the chemical composition of EFT revealed that the majority of constituents were organic acids and their corresponding esters. EFT exhibits measurable cytotoxicity and inhibition of PANC-1 invasion. Growth inhibition was primarily attributed to downregulation of CDK2 which induces cell cycle arrest in the S-phase. Inhibition of metastasis is achieved through downregulation of mesenchymal-associated genes/activators, including ZEB1, N-cadherin, Vimentin, and Fibronectin. Meanwhile, the expression of E-cadherin was significantly increased by EFT treatment. Furthermore, downregulation of MMP-2 and MMP-9 were observed. Conclusion Treatment of PANC-1 with EFT demonstrated measurable cytotoxic effects. Furthermore, EFT evoked S phase arrest while inhibiting the migration and invasion of PANC-1 cells. Additionally, EFT inhibited the epithelial to mesenchymal transition and MMPs expression in PANC-1 cells. This study serves to confirm the strong therapeutic potential of EFT while identifying the mechanisms of action.

Abstract Background Kawasaki disease (KD) is a systemic vasculitis accompanied by many systemic physiological and biochemical changes. Elucidating its molecular mechanisms is crucial for diagnosing and developing effective treatments. NLR Family CARD Domain Containing 4 (NLRC4) encodes the key components of inflammasomes that function as pattern recognition receptors. The purpose of this study was to investigate the potential of NLRC4 methylation as a biomarker for KD. Methods In this study, pyrosequencing was utilized to analyze NLRC4 promoter methylation in blood samples from 44 children with initial complete KD and 51 matched healthy controls. Methylation at five CpG sites within the NLRC4 promoter region was evaluated. Results Compared to controls, NLRC4 methylation significantly decreased in KD patients (CpG1: p = 2.93E-06; CpG2: p = 2.35E-05; CpG3: p = 6.46E-06; CpG4: p = 2.47E-06; CpG5: p = 1.26E-05; average methylation: p = 5.42E-06). These changes were significantly reversed after intravenous immunoglobulin (IVIG) treatment. ROC curve analysis demonstrated remarkable diagnostic capability of mean NLRC4 gene methylation for KD (areas under ROC curve = 0.844, sensitivity = 0.75, p = 9.61E-06, 95% confidence intervals were 0.762–0.926 for mean NLRC4 methylation). In addition, NLRC4 promoter methylation was shown to be significantly negatively correlated with the levels of central granulocyte percentage, age, mean haemoglobin quantity and mean erythrocyte volume. Besides, NLRC4 promoter methylation was positively correlated with lymphocyte percentage, lymphocyte absolute value. Conclusions Our work revealed the role of peripheral NLRC4 hypomethylation in KD pathogenesis and IVIG treatment response, could potentially serve as a treatment monitoring biomarker, although its precise functions remain to be elucidated.

Background: Gastric cancer (GC) is a typical malignant tumor and the main cause of cancer-related deaths. Its pathogenesis involves multiple steps, including pyroptosis, although these steps are still uncertain. Pyroptosis, also known as gasdermin-mediated programmed necrosis, participates in various pathological processes in tumors, including GC. ELANE, which encodes neutrophil elastase, is closely associated with GC. Additionally, ELANE has been implicated in GC cell pyroptosis, but this has not been confirmed. Therefore, investigating the link between ELANE and pyroptosis in GC is warranted. This research uses bioinformatics and experiments to examine the relationship between ELANE, pyroptosis, and GC prognosis. Methods: The GEO and TCGA databases, along with pyroptosis-related genes, were applied to identify pyroptosis-related differentially expressed genes (DEGs). ELANE was selected via primary screening. Using the median expression level of ELANE as the threshold, pyroptosis-related DEGs were divided into low- and high-ELANE groups. Based on the DEGs in these two groups, GO, KEGG and GSEA analyses were conducted to elucidate the mechanisms of ELANE in GC. Furthermore, we plotted ROC and Kaplan–Meier curves to analyze the clinical and pathological features of ELANE expression. The Nomograms tool was applied to calculate the predictive value of ELANE for the clinical outcomes of GC cases. Immunohistochemical analysis was performed to detect the level of ELANE in GC tissues and to validate whether ELANE was involved in pyroptosis in GC cells through cell experiments. Finally, the immune infiltration of ELANE was investigated, and interaction networks (proteins-ELANE, microRNA-ELANE, and small-molecule drug-ELANE) were constructed. Results: We aimed to investigate the expression of the ELANE gene in GC and study the relationship among ELANE, pyroptosis, and the prognosis of patients with GC. Differential expression analysis of gene-expression datasets from TCGA-STAD and GSE49051 revealed that the expression of the ELANE gene was significantly up-regulated in GC. Using STRING network analysis, we identified multiple proteins involved in the occurrence and development of GC, including interactions between ELANE and GSDMC, a member of the gasdermin protein family. Survival analysis showed that ELANE expression levels significantly affected overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS) in patients with GC. Additionally, ROC analysis demonstrated that ELANE was effective in distinguishing GC patients from normal controls (AUC = 0.812). Immunohistochemical analysis showed that ELANE was highly expressed in gastric cancer tissues and was closely related to age, tumor grade, and stage. The cell experiments further confirmed that the high expression of ELANE in gastric cancer cells was associated with pyroptosis. Comprehensive analysis indicated that ELANE could be used as a potential prognostic marker for GC and plays an important role in pyroptosis. Conclusion: High ELANE expression is related to poor survival and prognosis of patients with GC. It participates in pyroptosis and immune infiltration in GC. Therefore, ELANE is a promising prognostic biomarker for pyroptosis in GC.

Consider a simple undirected connected graph G, with D(G) and A(G) representing its degree and adjacency matrices, respectively. Furthermore, L(G)=D(G)−A(G) is the Laplacian matrix of G, and Ht=exp⁡(−tL(G)) is the heat kernel (HK) of G, with t>0 denoting the time variable. For a vertex u∈V(G), the uth element of the diagonal of the HK is defined as Ht(u,u)=(exp⁡(−tL(G)))uu=∑k=0∞((−tL(G))k)uuk!, and HE(G)=∑i=1ne−tλi=∑u=1nHt(u,u) is the HK trace of G, where λ1,λ2,⋯,λn denote the eigenvalues of L(G). This study provides new computational formulas for the HK diagonal entries of graphs using an almost equitable partition and the Schur complement technique. We also provide bounds for the HK trace of the graphs.

ObjectivesTo develop and validate various ultrasomics models based on endoscopic ultrasonography (EUS) for retrospective differentiating pancreatic neuroendocrine tumors (PNET) from pancreatic cancer.MethodsA total of 231 patients, comprising 127 with pancreatic cancer and 104 with PNET, were retrospectively enrolled. These patients were randomly divided into either a training or test cohort at a ratio of 7:3. Ultrasomics features were extracted from conventional EUS images, focusing on delineating the region of interest (ROI) for pancreatic lesions. Subsequently, dimensionality reduction of the ultrasomics features was performed by applying the Mann-Whitney test and least absolute shrinkage and selection operator (LASSO) algorithm. Eight machine learning algorithms, namely logistic regression (LR), light gradient boosting machine (LightGBM), multilayer perceptron (MLP), random forest (RF), extra trees, k nearest neighbors (KNN), support vector machine (SVM), and extreme gradient boosting (XGBoost), were employed to train prediction models using nonzero coefficient features. The optimal ultrasomics model was determined using a ROC curve and utilized for subsequent analysis. Clinical-ultrasonic features were assessed using both univariate and multivariate logistic regression. An ultrasomics nomogram model, integrating both ultrasomics and clinical-ultrasonic features, was developed.ResultsA total of 107 EUS-based ultrasomics features were extracted, and 6 features with nonzero coefficients were ultimately retained. Among the eight ultrasomics models based on machine learning algorithms, the RF model exhibited superior performance with an AUC= 0.999 (95% CI 0.9977 - 1.0000) in the training cohort and an AUC= 0.649 (95% CI 0.5215 - 0.7760) in the test cohort. A clinical-ultrasonic model was established and evaluated, yielding an AUC of 0.999 (95% CI 0.9961 - 1.0000) in the training cohort and 0.847 (95% CI 0.7543 - 0.9391) in the test cohort. Subsequently, the ultrasomics nomogram demonstrated a significant improvement in prediction accuracy in the test cohort, as evidenced by an AUC of 0.884 (95% CI 0.8047 - 0.9635) and confirmed by the Delong test. The calibration curve and decision curve analysis (DCA) depicted this ultrasomics nomogram demonstrated superior accuracy. They also yielded the highest net benefit for clinical decision-making compared to alternative models.ConclusionsA novel ultrasomics nomogram was proposed and validated, that integrated clinical-ultrasonic and ultrasomics features obtained through EUS, aiming to accurately and efficiently identify pancreatic cancer and PNET.

Oilseed rape (Brassica napus) is a crucial global oil crop. It is generally cultivated in rotation with rice in southern China’s Yangtze River Basin, where the wet soil and residue retention after rice harvest significantly hinder its seedling establishment. Hence, this study developed a strip-tillage seeder for oilseed rape seeding following rice harvest. Additionally, seedling establishment, soil infiltration and evaporation post-seeding, soil moisture change, oilseed yield, and weed occurrence under strip tillage (ST) were compared with conventional shallow rotary-tillage (SR) and deep rotary-tillage (DR) seeding practices. Compared to SR and DR, the results demonstrated that ST had a higher seeding efficiency and 53.8% and 80.2% lower energy consumption, respectively. ST also enhanced seedling growth and oilseed yield formation more effectively than the competitor tillage treatments, with an oilseed yield increase exceeding 6%. Additionally, ST improved water infiltration and reduced soil water evaporation, resulting in higher topsoil (0–20 cm) moisture during the critical growth stages. Furthermore, ST reduced soil disturbance, significantly decreasing the density of the dominant weed, Polypogon fugax. Overall, ST seeding technology has the potential to improve the productivity of oilseed rape in rice–oilseed rape rotation systems, and its yield superiority is mainly due to seedling establishment improvement and soil moisture adjustment.

Background: The stability, efficacy, and safety of omalizumab at different doses and regimens for chronic spontaneous urticaria (CSU) are yet to be studied. Objective: A systematic review (SR) with meta-analysis (MA) and trial sequential analysis (TSA) was performed to assess the efficacy and safety of omalizumab in CSU. Methods: Randomised controlled trials (RCTs) of administering omalizumab versus placebo for CSU were searched. Random-effects MAs were performed using planned subgroup analyses. TSA was performed to control for the risk of random errors and assess the stability of our MA results. Publication bias was visually assessed using a contour-enhanced funnel plot and the trim-and-fill method. The quality of RCTs was assessed using the Cochrane Risk of Bias Tool 2. Results: Twelve studies met the inclusion criteria. Omalizumab had remarkable effects on the patient percentage of the weekly urticaria activity score is zero (UAS = 0) [RR 4.64, 95% CI (3.38, 6.37)], percentage of no angioedema-burdened days [MD 3.15, 95% CI (0.10, 6.19], patient percentage of UAS ≤6 [RR 3.05, 95% CI (2.46, 3.78)], and patient percentage of the weekly itch severity score minimally important difference (ISS7 MID) [RR 1.50, 95% CI (1.36, 1.66)]. Omalizumab was well tolerated across studies [RR 0.98, 95% CI (0.90, 1.08)]. TSA confirmed the above results, except for “the percentage of no angioedema-burdened day”. Conclusion: Among the different doses and courses assessed, omalizumab (300 mg, 12 weeks) can be recommended as an effective treatment for patients with CSU. However, whether omalizumab improves angioedema requires further investigation. The clinical management of angioedema accompanying CSU requires further attention.

Exosomes are small extracellular vesicles secreted by cells, ranging in size from 30 to 150 nm. They contain proteins, nucleic acids, lipids, and other bioactive molecules, which play a crucial role in intercellular communication and material transfer. In tumor immunity, exosomes present various functions while the following two are of great importance: regulating the immune response and serving as delivery carriers. This review starts with the introduction of the formation, compositions, functions, isolation, characterization, and applications of exosomes, and subsequently discusses the current status of exosomes in tumor immunotherapy, and the recent applications of exosome-based tumor immunity regulation and antitumor drug delivery. Finally, current challenge and future prospects are proposed and hope to demonstrate inspiration for targeted readers in the field.

The study of functional traits and their relationship to trade-offs has provided valuable insights into how plants adapt to environmental changes. Nonetheless, further research is necessary to fully comprehend the subtropical montane trade-off patterns in moss functional traits and the impact of environmental gradients on the correlation of these traits. To address this gap, we conducted a study of 11 moss species (7 families, 9 genera) in 54 patches from two subtropical mountain ranges, examining 40 functional traits related to photosynthesis, nutrients, water retention, and architecture. Through principal component analysis (PCA) and bi-variate correlation analysis, our findings reveal a strong correlation between light capture and nutrient assimilation strategies, as evidenced by the coordination between the traits of light capture and nutrient per area along a main principal component. Interestingly, we observed a trend towards smaller leaves and leaf cells in species with higher capacity for photosynthesis and metabolism, consistent with global trait spectra in vascular plants. However, we found that the trade-off between light capture and nutrient assimilation strategies was independent of water-holding capacity at shoot levels. Instead, we found that water-holding capacity was closely associated with nutrient utilization, energy metabolism, chlorophyll synthesis, and the primary process of photosynthesis. Our results highlight the multiple dimensions of functional traits in subtropical montane mosses and demonstrate that variation in these traits is driven by water availability, slope, and canopy density. Overall, our study provides valuable insights into the co-variation of moss traits and how environmental changes may impact mosses and ecosystem function.