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Background Severe acute respiratory syndrome (SARS)-CoV-2-induced coronavirus disease-2019 (COVID-19) is a pandemic disease that affects > 2.8 million people worldwide, with numbers increasing dramatically daily. However, there is no specific treatment for COVID-19 and much remains unknown about this disease. Angiotensin-converting enzyme (ACE)2 is a cellular receptor of SARS-CoV-2. It is cleaved by type II transmembrane serine protease (TMPRSS)2 and disintegrin and metallopeptidase domain (ADAM)17 to assist viral entry into host cells. Clinically, SARS-CoV-2 infection may result in acute lung injury and lung fibrosis, but the underlying mechanisms of COVID-19 induced lung fibrosis are not fully understood. Methods The networks of ACE2 and its interacting molecules were identified using bioinformatic methods. Their gene and protein expressions were measured in human epithelial cells after 24 h SARS-CoV-2 infection, or in existing datasets of lung fibrosis patients. Results We confirmed the binding of SARS-CoV-2 and ACE2 by bioinformatic analysis. TMPRSS2, ADAM17, tissue inhibitor of metalloproteinase (TIMP)3, angiotensinogen (AGT), transformation growth factor beta (TGFB1), connective tissue growth factor (CTGF), vascular endothelial growth factor (VEGF) A and fibronectin (FN) were interacted with ACE2, and the mRNA and protein of these molecules were expressed in lung epithelial cells. SARS-CoV-2 infection increased ACE2 , TGFB1 , CTGF and FN1 mRNA that were drivers of lung fibrosis. These changes were also found in lung tissues from lung fibrosis patients. Conclusions Therefore, SARS-CoV-2 binds with ACE2 and activates fibrosis-related genes and processes to induce lung fibrosis.

Background Colorectal cancer (CRC) is the most common cancer and a leading cause of death worldwide. Extracellular matrix (ECM) proteins regulate tumor growth and development in CRC. Elastin (ELN) is a component of ECM proteins involved in the tumor microenvironment. However, the role of ELN in CRC remains unclear. Methods In this study, we analyzed ELN gene expression in tumors from CRC patients and adjacent non-tumor colon tissues and healthy controls from two existing microarray datasets. ELN protein was measured in human normal colon cells and colon cancer epithelial cells and tumor development was assessed in colon epithelial cells cultured in medium with or without ELN peptide on plates coated with ELN recombinant protein. Control plates were coated with PBS only. Results We found ELN gene expression was increased in tumors from CRC patients compared to adjacent non-tumor tissues and healthy controls. ELN protein was increased in cancer cells compared to normal colon epithelial cells. Transforming growth factor beta (TGF-β) was a key cytokine to induce production of ECM proteins, but it did not induce ELN expression in colon cancer cells. Matrix metalloproteinase 9 ( MMP9 ) gene expression was increased, but that of MMP12 (elastase) did not change between CRC patients and control. Tissue inhibitor of metalloproteinases 3 ( TIMP3 ) gene expression was decreased in colon tissues from CRC patients compared to healthy controls. However, MMP9, MMP12 and TIMP3 proteins were increased in colon cancer cells. ELN recombinant protein increased proliferation and wound healing in colon cancer epithelial cells. This had further increased in cancer cells incubated in plates coated with recombinant ELN coated plate and in culture media containing ELN peptide. A potential mechanism was that ELN induced epithelial mesenchymal transition with increased alpha-smooth muscle actin and vimentin proteins but decreased E-cadherin protein. Tumor necrosis factor alpha ( TNF ) mRNA was also increased in CRC patients compared to controls. ELN recombinant protein induced further increases in TNF protein in mouse bone marrow derived macrophages after lipopolysaccharide stimulation. Conclusions These data suggest ELN regulates tumor development and the microenvironment in CRC.

Background The antioxidant system of periodontal tissue is unbalanced in periodontitis, and appropriate supplementation of antioxidants can effectively prevent or alleviate periodontal tissue damage. However, a dearth of research exists on the association between dietary antioxidant intake and the prevalence of periodontitis. Methods Six dietary antioxidants (vitamins A, C, and E, zinc, selenium, and carotenoids) were extracted from two 24-h recall interviews utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2009 and 2014. The composite dietary antioxidant index (CDAI) made calculations using data on the intake of these six dietary antioxidants. Periodontitis severity was categorized into mild, moderate, and severe classifications based on established consensus criteria. Additionally, a restricted cubic spline (RCS) regression model was applied to evaluate the potential non-linear dose–response relationship between CDAI and periodontitis prevalence. Results A total of 9,378 adults were included in this analysis, of which 4,755 had periodontitis. Individuals within the highest CDAI quartile demonstrated a diminished prevalence of total periodontitis compared to those in the lowest quartile (OR = 0.70 [0.53–0.93], P trend  = 0.012). When moderate/severe periodontitis served as the outcome variable, those within the fourth CDAI quartile exhibited a 32% reduced prevalence compared to those in the first quartile (OR = 0.68 [0.52–0.88], P trend  = 0.006). RCS regression showed that CDAI was linearly and negatively related to the prevalence of periodontitis (both total and moderate/severe periodontitis). In subgroup analysis by gender, a significant association between CDAI and total periodontitis was discerned solely among females (OR = 0.60 [0.42–0.85], P interaction  = 0.015). Conclusion Elevated dietary antioxidant intake is associated with a diminished prevalence of periodontitis. These findings underscore the potential role of antioxidants in periodontal health.

The application of microsphere molecularly imprinted materials for the targeted extraction and purification of flavonoids derived from agricultural waste has emerged as a prominent area of investigation. An innovative boronate affinity imprinted microsphere (MC-CD@BA-MIP) was successfully synthesized using the Pickering emulsion interfacial assembly strategy for the selective separation of naringin (NRG). The double-bond functionalized covalent organic framework (COF)-based microspheres were synthesized through Schiff–base reaction and secondary interfacial emulsion polymerization. Then, the synthetic mono-(6-mercapto-6-deoxy)-β-cyclodextrin (SH-β-CD) was grafted onto the surface of the microspheres (MC) using click chemistry. The 1-allylpyridine-3-boronic acid (APBA) as a functional monomer was grafted onto the initiator (ABIB) through atom transfer radical polymerization (ATRP). Ultimately, the synthesized boronic acid-imprinted ABIB-BA-MIPs were immobilized onto the COFs microsphere surface through host–guest interactions. As expected, under neutral conditions, the MC-CD@BA-MIPs still exhibited a significant adsorption capacity (38.78 μmol g−1 at 308 K) for NRG. The regenerated MC-CD@BA-MIPs maintained 92.56% of their initial adsorption capacity through six consecutive cycles.

Text classification has been a fundamental problem in the realm of Natural Language Processing (NLP), and a variety of approaches have been proposed with the development of deep learning. Despite recent progress, most existing approaches deal with the problem of multi-class text classification in a flat way, assuming that text labels are semantically independent. This assumption doesn’t always hold in realistic settings, since there usually exist hierarchical or within-layer dependencies in the latent label space, especially when we consider larger label sets. In this paper, we propose a label clustering algorithm to exploit the underlying structure of label relations, and express the stacked concept relationships in the form of a two-layer label space. Next, we present two different neural network structures to capture inter-layer and intra-layer label relations. The first model HSNN organizes a group of local classifiers in a hierarchical way according to the exploited label space, while the second model LSNN takes advantages of text representations in different granularity levels and the bidirectional inferences with recurrent connections to make predictions. Finally, we evaluate our methods on three benchmark datasets. The results empirically demonstrate that both models are capable of leveraging the exploited label relations to improve text classification performance.

In recent years, attention toward oral health issues has increased with economic development and improvements in quality of life. Biochemical testing technologies offer an efficient method for identifying insidious pathological changes in the oral cavity. Frequent home-based self-screening can enable early identification of dental disease risks, thus facilitating timely interventions. Convenient home-based biochemical testing methods must be user-friendly, cost-effective, and operable without specialized equipment or extensive training. This review summarizes recent advances in convenient biochemical testing methods for the detection and diagnosis of oral diseases, focusing on their reliability, user compliance, and practicality for home-based applications. This review highlights the significance of biomarker distribution imaging for simultaneously identifying multiple lesions and provides perspectives on future research directions. By promoting interdisciplinary collaboration in biochemical diagnostics, this review outlines pathways toward personalized oral healthcare, precision dentistry, and enhanced overall health outcomes.

Background/Aims Arsenic trioxide (ATO) is the first-line therapeutic drug for acute promyelocytic leukemia. However, the cardiotoxicity of ATO limits its clinical application. This study aims to explore the long noncoding RNA (lncRNA) involved molecular mechanism in ATO-induced cardiotoxicity and to identify available prevention strategies. Methods ATO was administered to mice or primary cultured mouse cardiomyocytes. Small interfering RNA targeting lncRNA Kcnq1ot1 (si-Kcnq1ot1) was used to knockdown lncRNA Kcnq1ot1. MiR-34a-5p mimic and antisense morpholino oligonucleotide targeting miR-34a-5p (AMO-34a-5p) were used to upregulate and downregulate the expression of miR-34a-5p, respectively. TUNEL staining was conducted to detect cell DNA damage. Flow cytometry assay was used to detect cell apoptosis. Western blot was conducted to detect Bcl-2, Bax and Sirt1 protein expression. Real-time PCR was used to detect lncRNA Kcnq1ot1, miR-34a-5p, and Sirt1 mRNA expression. Dual-luciferase reporter assay was performed to validate the predicted binding site. Results ATO induced apoptosis in cardiomyocytes both in vivo and in vitro. Simultaneously, the expression of lncRNA Kcnq1ot1 and Sirt1 was downregulated, and miR-34a-5p was upregulated. MiR-34a-5p has binding sites with lncRNA Kcnq1ot1 and Sirt1. Knockdown of lncRNA Kcnq1ot1 induced apoptosis of cardiomyocytes, with increased miR-34a-5p and decreased Sirt1 expression. Inhibition of miR-34a-5p attenuated si-Kcnq1ot1-induced apoptosis in cardiomyocytes. Therefore, the lncRNA Kcnq1ot1/miR-34a-5p/Sirt1 signaling pathway is involved in ATO-induced cardiotoxicity. Propranolol alleviated ATO-induced apoptosis in cardiomyocytes both in vivo and in vitro, which was related to the lncRNA Kcnq1ot1/miR-34a-5p/Sirt1 signaling pathway. Conclusion The lncRNA Kcnq1ot1/miR-34a-5p/Sirt1 pathway is involved in ATO-induced cardiotoxicity. Propranolol can attenuate ATO-induced cardiotoxicity at least partially through the lncRNA Kcnq1ot1/miR-34a-5p/Sirt1 pathway. Combined administration with propranolol may be a new strategy for alleviating the cardiotoxicity of ATO.

Background This study aimed to evaluate the prognostic value of the newly revised International Association for the Study of Lung Cancer (IASLC) grading system (2020) on the 5-year overall survival (OS) and recurrence-free survival (RFS) in patients with lung adenocarcinoma (LADC). Methods Clinical studies that investigated the prognostic value of revised IASLC staging system in patients with LADC were retrieved from the PubMed, Web of Science, ScienceDirect, and Cochrane Library databases. This study was conducted in accordance to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and checklists. Results Based on inclusion and exclusion criteria, we included 12 studies for analysis. The grade of LADC was assessed by revised IASLC system, which included three grades. Compared to Grade 3 LADC, grade 1 (total [95% CI]: 1.38 [1.19, 1.60]) and grade 2 (total [95% CI]: 1.29 [1.15, 1.44]) LADC had higher 5-year OS rates. Similarly, Grade 1 (total [95% CI]: 1.76 [1.42, 2.18]) and Grade 2 (total [95% CI]: 1.51 [1.28, 1.77]) had higher 5-year RFS rates Grade 3 LADC. However, 5-year OS and RFS had no significant difference between Grade 1 and Grade 2 patients. Conclusion This systematic review and meta-analysis provides evidence that the newly revised IASLC grading system is significantly associated with the prognosis of patients with LADC, where Grade 3 indicated unfavorable prognosis.

Phenotyping technologies are essential for modern aquaculture, particularly for precise analysis of individual morphological traits. This study focuses on critical phenotype segmentation tasks for fish carcass and fins, which have significant applications in phenotypic assessment and breeding. In high-density underwater environments, fish frequently exhibit structural overlap and indistinct boundaries, making it difficult for conventional segmentation methods to obtain complete and accurate phenotypic regions. To address these challenges, a double-branch segmentation network is proposed for fish phenotype segmentation in high-density underwater scenes. An auxiliary saliency object detection (SOD) branch is introduced alongside the primary segmentation branch to localize structurally complete targets and suppress interference from overlapping or incomplete fish while inter-branch skip connections further enhance the model’s focus on salient targets and their boundaries. The network is trained under a multi-task learning framework, allowing the branches to specialize in edge detection and accurate region segmentation. Experiments on large yellow croaker (Larimichthys crocea) images collected under real farming conditions show that the proposed method achieves Dice scores of 97.58% for carcass segmentation and 88.88% for fin segmentation. The corresponding ASD values are 0.590 and 0.364 pixels, and the HD95 values are 3.521 and 1.222 pixels. The method outperforms nine existing algorithms across key metrics, confirming its effectiveness and reliability for practical aquaculture phenotyping.

Background The correlation between central airway anatomical parameters and demographic factors, such as sex, age, weight, height, body mass index (BMI), and cardiac factors, remains unclear. This study examined the correlation between these factors and central airway anatomical parameters in adult patients. Methods All consecutive patients who underwent lung mass surgery at our hospital between December 2020 and December 2023 were included in this study. DeepInsight software was used to analyze high-resolution chest computed tomography (HRCT) images and to measure various central airway anatomical parameters, including tracheal diameter (TD), tracheal length (TL), left main bronchus diameter (LBD), left main bronchus length (LBL), right main bronchus diameter (RBD), right main bronchus length (RBL), and subcarinal angle (SCA). A multivariate linear regression analysis was performed to evaluate the independent effects of sex, age, weight, height, BMI, left atrial diameter, and diastolic left ventricular internal diameter (LVIDd) on these anatomical parameters. Results Among the 391 patients included in this study, all were over 18 years old, with 192 male and 199 female. The multivariate linear regression analysis indicated that in male patients with lung masses, TD exhibited a negative correlation with age (β =  − 0.032, P  = 0.015) and a positive correlation with height (β = 0.099, P  < 0.001). Furthermore, TL exhibited a positive correlation with height (β = 0.311, P  = 0.004). LBL was substantially influenced by age (β =  − 0.098, P  = 0.011), height (β = 0.204, P  = 0.003), and BMI (β = 0.311, P  = 0.026). Conversely, RBD exhibited notable correlations with height (β = 0.062, P  = 0.02), BMI (β =  − 0.113, P  = 0.039), and left atrial size (β = 0.111, P  = 0.007). In female patients, TD and TL exhibited positive correlations with height (β = 0.065, P  = 0.01; β = 0.337, P  = 0.01, respectively). LBL was significantly correlated only with height (β = 0.171, P  = 0.045), whereas LBD exhibited an inverse correlation with age (β =  − 0.024, P  = 0.014). In addition, changes in SCA were positively associated with left atrial size (β = 0.65, P  = 0.042), indicating a potential anatomical correlation. Conclusion This study innovatively examined the impact of cardiac factors on central airway anatomical parameters in adult patients with lung masses. Notably, age, as an important factor in airway development, was found to have significant associations with tracheal characteristics along with height in males, while tracheal features exhibited a particularly strong relationship with height in females. Furthermore, the study identified associations between right bronchial diameter (RBD) in males and subcarinal angle (SCA) in females with left atrial size, although these findings require further validation in larger and more diverse populations.