RESUMEN

BACKGROUND: Liver cirrhosis is a progressive hepatic disease whose immunological basis has attracted increasing attention. However, it remains unclear whether a concrete causal association exists between immunocyte phenotypes and liver cirrhosis. AIM: To explore the concrete causal relationships between immunocyte phenotypes and liver cirrhosis through a mendelian randomization (MR) study. METHODS: Data on 731 immunocyte phenotypes were obtained from genome-wide association studies. Liver cirrhosis data were derived from the Finn Gen dataset, which included 214403 individuals of European ancestry. We used inverse variable weighting as the primary analysis method to assess the causal relationship. Sensitivity analyses were conducted to evaluate heterogeneity and horizontal pleiotropy. RESULTS: The MR analysis demonstrated that 11 immune cell phenotypes have a positive association with liver cirrhosis [P < 0.05, odds ratio (OR) > 1] and that 9 immunocyte phenotypes were negatively correlated with liver cirrhosis (P < 0.05, OR < 1). Liver cirrhosis was positively linked to 9 immune cell phenotypes (P < 0.05, OR > 1) and negatively linked to 10 immune cell phenotypes (P < 0.05; OR < 1). None of these associations showed heterogeneity or horizontally pleiotropy (P > 0.05). CONCLUSION: This bidirectional two-sample MR study demonstrated a concrete causal association between immunocyte phenotypes and liver cirrhosis. These findings offer new directions for the treatment of liver cirrhosis.

RESUMEN

The concept of 'brain age', derived from neuroimaging data, serves as a crucial biomarker reflecting cognitive vitality and neurodegenerative trajectories. In the past decade, machine learning (ML) and deep learning (DL) integration has transformed the field, providing advanced models for brain age estimation. However, achieving precise brain age prediction across all ages remains a significant analytical challenge. This comprehensive review scrutinizes advancements in ML- and DL-based brain age prediction, analyzing 52 peer-reviewed studies from 2020 to 2024. It assesses various model architectures, highlighting their effectiveness and nuances in lifespan brain age studies. By comparing ML and DL, strengths in forecasting and methodological limitations are revealed. Finally, key findings from the reviewed articles are summarized and a number of major issues related to ML/DL-based lifespan brain age prediction are discussed. Through this study, we aim at the synthesis of the current state of brain age prediction, emphasizing both advancements and persistent challenges, guiding future research, technological advancements, and improving early intervention strategies for neurodegenerative diseases.

Asunto(s)

RESUMEN

BACKGROUND: The association between psoriasis and pulmonary fibrosis has been reported in observational studies. However, the association is vulnerable to bias from using immunosuppressants such as methotrexate, which can cause fibrosis in multiple organs. The present study is to investigate whether psoriasis could independently increase the risk of idiopathic pulmonary fibrosis (IPF). METHODS: We conducted a two-sample Mendelian randomization (MR) study using summary statistics from genome-wide association studies. The random-effects inverse variance weighted analysis was used as the primary method. Some secondary analyses were further performed, including a sensitivity analysis using a genetic instrument that excluded extended single nucleotide polymorphisms (SNPs) in the major histocompatibility complex (MHC) gene region. RESULTS: Our study included 9267 cases and 364,071 controls for psoriasis, 2018 cases, and 373,064 controls for IPF of European ancestry, respectively. Genetically predicted psoriasis was associated with a higher risk of IPF (odds ratio (OR), 1.14; 95% confidence interval (CI), 1.08-1.22; P < 0.001). Sensitivity analyses did not uncover any statistically significant evidence of bias resulting from pleiotropy or the genetic instruments, including SNPs in the MHC gene region. CONCLUSIONS: These MR analyses support that genetically predicted psoriasis was associated with the risk of IPF, implying that pulmonary fibrosis in patients with psoriasis should not be neglected, even if they are not receiving immunosuppressant therapy.

RESUMEN

Ubiquitin modification and alternative polyadenylation play crucial roles in the onset and progression of cancer. Hence, this study aims to comprehensively and deeply understand gene regulation and associated biological processes in lung adenocarcinoma (LUAD) by integrating both mechanisms. Alternative polyadenylation (APA)-related E3 ubiquitin ligases in LUAD were identified through multiple databases, and the association between selected genetic loci influencing gene expression (apaQTL-SNPs) and LUAD risk were evaluated through the GWAS database of the Female Lung Cancer Consortium in Asia (FLCCA). Subsequently, the interaction between RNF213 and ZBTB20, as well as their functional mechanisms in LUAD, were investigated using bioinformatics analysis, Western blot, co-immunoprecipitation, and colony formation experiments. A total of five apaQTL-SNPs (rs41301932, rs4494603, rs9890400, rs56066320, and rs41301932), located on RNF213, were significantly associated with LUAD risk (p < 0.05), and they inhibit tumor growth through ubiquitin-mediated degradation of ZBTB20.

Asunto(s)

RESUMEN

Although most source apportionments of VOCs use mixing ratios, about 23 % of published studies use mass concentrations. Thus, systematically exploring the changes in VOC source apportioned results caused by metric differences is important to assess the differences in key precursor apportionment results given the observed increases in O3 pollution situation. Different monitoring instruments measured hourly VOC volumetric concentrations in three typical Chinese cities (i.e., Qingdao, Shijiazhuang, and Zhumadian). Converting volumetric to mass concentrations under standard and/or actual temperature-pressure conditions, VOC values with different metrics were obtained. The impacts of different metrics on the source apportionments were then investigated. Compared to the positive matrix factorization of the volumetric data (VC-PMF), the VOC species concentrations with low relative molecular mass (RMM) in the factor profiles substantially decreased in mass data analyses (MC-PMF). However, those species with high RMM substantially increased. There were no substantial differences in the apportioned source contributions based on standard and actual condition mass concentrations. However, the high-low rankings of percent contributions apportioned using the volumetric and mass data produced substantial differences. Compared with the VC-PMF results, the percent contributions of sources dominated by species with low RMM (e.g., natural gas usage and mixed sources containing natural gas usage) apportioned by MC-PMF decreased, while those of sources that emitted high RMM species (e.g., solvent usage and mixed sources containing solvent usage) increased. Source apportionments based on the volumetric concentration data had more practical significance compared to the mass concentration data results for control strategy development since the mass data analyses created issues.

Asunto(s)

RESUMEN

Glioma is the most common brain tumor, accounting for a large majority of cancer-related deaths. ß-galactoside α2, 6 sialyltranferase 1 (ST6Gal1), the primary enzyme responsible for the conjugation of α2, 6 sialic acids to protein and lipid targets, is strongly associated with the occurrence and development of several brain tumor types. Still, the expression, targets, and functions of ST6Gal1 in glioma patients remain undetermined. As sialylation of the Ig-like cell adhesion family molecules have prominent roles in the latter's regulation in other biological contexts, we screened for members that have potential to be regulated by ST6Gal1 in silico and examined co-expressed protein modules using data derived from the Cancer Genome Atlas (TCGA) database, and we identified neural cell adhesion molecule (NCAM1) as a major ST6Gal1-interacting target. Bioinformatic binding analysis confirmed the interaction of ST6Gal1 and NCAM1. Immunohistochemistry was then used to evaluate post-operative samples from 156 patients with gliomas. ST6Gal1 and NCAM1 were co-expressed in gliomas, and their expression correlated significantly (p = 0.002) by univariate analysis. Our study also found that the expression levels of both ST6Gal1 and NCAM1 corresponded negatively with glioma grade, isocitrate dehydrogenase (IDH) mutation, and proliferation index (Ki67). Consistently, Kaplan-Meier survival curves showed that lower ST6Gal1 and NCAM1 protein levels are linked to unfavorable outcomes in glioma patients (p = 0.018 and p < 0.001, respectively). Our data indicate that ST6Gal1 may participate in the inhibition of oncogenesis and malignant progression via interacting with and targeting NCAM1 in glioma, thus presenting a novel strategy for intervention.

Asunto(s)

RESUMEN

The mammalian intestine harbors abundant T cells with high motility, where these cells can affect both intestinal and extraintestinal disorders. Growing evidence shows that gut-derived T cells migrate to extraintestinal organs, contributing to the pathogenesis of certain autoimmune diseases, including type 1 diabetes (T1D) and multiple sclerosis (MS). However, three key questions require further elucidation. First, how do intestinal T cells egress from the intestine? Second, how do gut-derived T cells enter organs outside the gut? Third, what is the pathogenicity of gut-derived T cells and their correlation with the gut microenvironment? In this Opinion, we propose answers to these questions. Understanding the migration and functional regulation of gut-derived T cells might inform precise targeting for achieving safe and effective approaches to treat certain extraintestinal autoimmune diseases.

Asunto(s)

RESUMEN

Bromine (Br2) and related species removal from water systems are rather complicated due to the complicated chemistry instability, and materials with high Br2 removal rate and efficiency, along with stimuli/apparatus suitable for highly corrosive environments, are necessary. Ultrasonication as a non-destructive process is especially suitable in scenarios where conventional stir apparatus is not applicable, such as highly corrosive environments. Considering the validity nature of Br2 and combining the advantages of ultrasonic with a highly stable Br2 fixation method through aromatic polymer nanoparticles, we demonstrate highly efficient acoustic-aided Br2 removal in aqueous solutions with two times capacity compared to the non-treated sample. Related aquatic applications are also proposed for the materials to be cost-effective, including silver (Ag) recovery, recyclable MnO2-mediated Br2 deep removal, and aqueous zinc anode modification. The coupled novel-material-based processes motivate the strategic design of water purification with high-safety and sustainable industrial procedures and post-value-added utilizations.

RESUMEN

Background: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by inflammatory cell infiltration, which can lead to chronic disability, joint destruction and loss of function. At present, the pathogenesis of RA is still unclear. The purpose of this study is to explore the potential biomarkers and immune molecular mechanisms of rheumatoid arthritis through machine learning-assisted bioinformatics analysis, in order to provide reference for the early diagnosis and treatment of RA disease. Methods: RA gene chips were screened from the public gene GEO database, and batch correction of different groups of RA gene chips was performed using Strawberry Perl. DEGs were obtained using the limma package of R software, and functional enrichment analysis such as gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), disease ontology (DO), and gene set (GSEA) were performed. Three machine learning methods, least absolute shrinkage and selection operator regression (LASSO), support vector machine recursive feature elimination (SVM-RFE) and random forest tree (Random Forest), were used to identify potential biomarkers of RA. The validation group data set was used to verify and further confirm its expression and diagnostic value. In addition, CIBERSORT algorithm was used to evaluate the infiltration of immune cells in RA and control samples, and the correlation between confirmed RA diagnostic biomarkers and immune cells was analyzed. Results: Through feature screening, 79 key DEGs were obtained, mainly involving virus response, Parkinson's pathway, dermatitis and cell junction components. A total of 29 hub genes were screened by LASSO regression, 34 hub genes were screened by SVM-RFE, and 39 hub genes were screened by Random Forest. Combined with the three algorithms, a total of 12 hub genes were obtained. Through the expression and diagnostic value verification in the validation group data set, 7 genes that can be used as diagnostic biomarkers for RA were preliminarily confirmed. At the same time, the correlation analysis of immune cells found that γδT cells, CD4+ memory activated T cells, activated dendritic cells and other immune cells were positively correlated with multiple RA diagnostic biomarkers, CD4+ naive T cells, regulatory T cells and other immune cells were negatively correlated with multiple RA diagnostic biomarkers. Conclusions: The results of novel characteristic gene analysis of RA showed that KYNU, EVI2A, CD52, C1QB, BATF, AIM2 and NDC80 had good diagnostic and clinical value for the diagnosis of RA, and were closely related to immune cells. Therefore, these seven DEGs may become new diagnostic markers and immunotherapy markers for RA.

RESUMEN

Duck enteritis virus (DEV) may lead to vascular injury, gastrointestinal mucosal erosion, lymphoid organ injury, and Polyinosinic-polycytidylic acid (Poly I:C) has an antiviral effect by inducing low levels of interferon. The purpose of this study was to explore the pathogenesis of DEV-induced intestinal injury in ducks and to verify the therapeutic effects of different concentrations of Poly I:C. In this study, duck enteritis model was established by infecting healthy Pekin ducks with DEV. Duck intestinal tissues were extracted from normal control group, model group, and treatment group with different doses of Poly I:C. In vivo, HE and TUNEL staining were used to observe the morphological changes and apoptosis. In vitro, the proliferation and apoptosis of duck intestinal epithelial cells were evaluated by MTT assay, TUNEL staining, and flow cytometry. The results showed that Poly I:C protected ducks from DEV toxicity by improving intestinal morphology and inhibiting apoptosis. In addition, the antiviral effect of Poly I:C on DEV was found in a dose-dependent manner, with a more relatively obvious effect at a high dose of Poly I:C. All in all, these results demonstrated that Poly I:C played a vital role in the apoptosis induced by DEV in ducks and modest dose of Poly I:C treatment worked well and may provide important reference for the development of new antiviral drugs in the future.

Asunto(s)

RESUMEN

The aim of this study was to explore potential novel plasma protein biomarkers for lung adenocarcinoma (LUAD). A plasma proteomics analysis was carried out and candidate protein biomarkers were validated in 102 LUAD cases and 102 matched healthy controls. The same LUAD tumor tissues were detected to explore the correlation between the expression of candidate proteins in tissues and plasma and vascular normalization. A LUAD active metastasis mice model was constructed to explore the role of candidate proteins for lung metastasis. GPI and PGD were verified to be upregulated in plasma from LUAD patients, and the expression of GPI in tumor tissue was positively correlated with the expression of GPI in plasma and negatively correlated with the normalization of tumor blood vessels. Meanwhile, a negative correlation between the expression of GPI and PGD in plasma and tumor vascular normalization was discovered. In the LUAD active metastasis model, the lowest levels of vascular normalization and the highest expression of GPI and PGD were found in mice with lung metastases. This study found that GPI and PGD may be potential plasma biomarkers for LUAD, and monitoring those may infer the risk of metastasis and malignancy of the tumor. SIGNIFICANT: We identified GPI and PGD as potential novel diagnostic and prognostic biomarkers for LUAD. PGD and GPI can be used as diagnostic biomarkers in combination with other available strategies to assist in the screening and diagnosis of LUAD, and as prognostic biomarkers aid in predict the risk of tumor metastasis and malignancy in patients with LUAD.

Asunto(s)

RESUMEN

OBJECTIVE: To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm. MATERIALS AND METHODS: A fine-tuned, domain-specific, transformer-based clinical text deep learning model was used to interpret free-text nursing assessments in the electronic medical records of 235,789 adult presentations to the ED over a three-year period. The model classified presentations according to whether the patient had pain on arrival at the ED. Interrupted time series analysis was used to determine the incidence of pain in patients on arrival over time. We described the changes in the population characteristics and incidence of patients with pain on arrival occurring with the start of the Covid-19 pandemic. RESULTS: 55.16% (95%CI 54.95%-55.36%) of all patients presenting to this ED had pain on arrival. There were differences in demographics and arrival and departure patterns between patients with and without pain. The Covid-19 pandemic initially precipitated a decrease followed by a sharp, sustained rise in pain on arrival, with concurrent changes to the population arriving in pain and their treatment. DISCUSSION: Applying a clinical text deep learning model has successfully identified the incidence of pain on arrival. It represents an automated, reproducible mechanism to identify pain from routinely collected medical records. The description of this population and their treatment forms the basis of intervention to improve care for patients with pain. The combination of the clinical text deep learning models and interrupted time series analysis has reported on the effects of the Covid-19 pandemic on pain care in the ED, outlining a methodology to assess the impact of significant events or interventions on pain care in the ED. CONCLUSION: Applying a novel deep learning approach to identifying pain guides methodological approaches to evaluating pain care interventions in the ED, giving previously unavailable population-level insights.

Asunto(s)

RESUMEN

A 36-year-old unmarried male chef was incidentally diagnosed with hypokalemia during an evaluation for an acute perianal abscess. Despite potassium supplementation, he developed progressive weakness in his lower limbs, culminating in an inability to stand. Investigations confirmed severe hypokalemia, metabolic alkalosis, hypomagnesemia, secondary hyperaldosteronism, and low urinary calcium excretion, with normotension. The patient's long-standing stunted growth and lean physique since childhood were noted. Biochemical assays further identified type 2 diabetes mellitus and metabolic syndrome. Genetic analysis revealed three heterozygous SLC12A3 mutations (M1: c.421G>A: p.G141R, M2: c.509T>A:p.L170Q, and M3: c.704C>A: p.T235K), compound heterozygo us and derived from both parents, with M1 and M3 reported here for the first time. Treatment with spironolactone and oral potassium chloride stabilized his potassium levels. Following the administration of SGLT2 inhibitors in patients receiving hypoglycemic therapy, we observed a mild decrease in serum sodium levels. This case highlights the criticality of vigilant metabolic surveillance in Gitelman syndrome and advises prudence with SGLT2 inhibitors in those with concurrent type 2 diabetes, given the risk of potentially aggravate sodium loss.

RESUMEN

The intricate dynamics of brain aging, especially the neurodegenerative mechanisms driving accelerated (ABA) and resilient brain aging (RBA), are pivotal in neuroscience. Understanding the temporal dynamics of these phenotypes is crucial for identifying vulnerabilities to cognitive decline and neurodegenerative diseases. Currently, there is a lack of comprehensive understanding of the temporal dynamics and neuroimaging biomarkers linked to ABA and RBA. This study addressed this gap by utilizing a large-scale UK Biobank (UKB) cohort, with the aim to elucidate brain aging heterogeneity and establish the foundation for targeted interventions. Employing Lasso regression on multimodal neuroimaging data, structural MRI (sMRI), diffusion MRI (dMRI), and resting-state functional MRI (rsfMRI), we predicted the brain age and classified individuals into ABA and RBA cohorts. Our findings identified 1949 subjects (6.2%) as representative of the ABA subpopulation and 3203 subjects (10.1%) as representative of the RBA subpopulation. Additionally, the Discriminative Event-Based Model (DEBM) was applied to estimate the sequence of biomarker changes across aging trajectories. Our analysis unveiled distinct central ordering patterns between the ABA and RBA cohorts, with profound implications for understanding cognitive decline and vulnerability to neurodegenerative disorders. Specifically, the ABA cohort exhibited early degeneration in four functional networks and two cognitive domains, with cortical thinning initially observed in the right hemisphere, followed by the temporal lobe. In contrast, the RBA cohort demonstrated initial degeneration in the three functional networks, with cortical thinning predominantly in the left hemisphere and white matter microstructural degeneration occurring at more advanced stages. The detailed aging progression timeline constructed through our DEBM analysis positioned subjects according to their estimated stage of aging, offering a nuanced view of the aging brain's alterations. This study holds promise for the development of targeted interventions aimed at mitigating age-related cognitive decline.

RESUMEN

This study developed a UPLC-PDA wavelength switching method to simultaneously determine the content of maltol and seventeen saponins in red and black ginseng and compared the quality differences of two different processed products of red and black ginseng. A Waters HSS T3 column(2. 1 mm×100 mm, 1. 8 µm) at 30 ℃ was adopted, with the mobile phase of acetonitrile(A) and water containing 0. 1% phosphoric acid(B) under gradient elution, the flow rate of 0. 3 m L·min~(-1), and the injection volume of 2 µL.The wavelength switching was set at 273 nm within 0-11 min and 203 nm within 11-60 min. The content results of multiple batches of red and black ginseng samples were analyzed by the hierarchical cluster analysis(HCA) and principal component analysis(PCA) to evaluate the quality difference. The results showed that the 18 constituents exhibited good linear relationships within certain concentration ranges, with the correlation coefficients(r) greater than 0. 999 1. The relative standard deviations(RSDs) of precision,repeatability, and stability were all less than 5. 0%. The average recoveries ranged from 95. 93% to 104. 2%, with an RSD of 1. 8%-4. 2%. The content determination results showed that the quality of red and black ginseng samples was different, and the two types of processed products were intuitively distinguished by HCA and PCA. The method is accurate, reliable, and reproducible. It can be used to determine the content of maltol and seventeen saponins in red and black ginseng and provide basic information for the quality evaluation and comprehensive utilization of red and black ginseng.

Asunto(s)

RESUMEN

Alternative polyadenylation (APA) plays a crucial role in cancer biology. Here, we used data from the 3'aQTL-atlas, GTEx, and the China Nanjing Lung Cancer GWAS database to explore the association between apaQTL/eQTL-SNPs and the risk of lung adenocarcinoma (LUAD). The variant T allele of rs277646 in NIT2 is associated with an increased risk of LUAD (OR = 1.12, P = 0.015), lower PDUI values, and higher NIT2 expression. The 3'RACE experiment showed multiple poly (A) sites in NIT2, with the rs277646-T allele causing preferential use of the proximal poly (A) site, resulting in a shorter 3'UTR transcript. This leads to the loss of the hsa-miR-650 binding site, thereby affecting LUAD malignant phenotypes by regulating the expression level of NIT2. Our findings may provide new insights into understanding and exploring APA events in LUAD carcinogenesis.

Asunto(s)

RESUMEN

Solid-state batteries (SSBs) have garnered significant attention in the critical field of sustainable energy storage due to their potential benefits in safety, energy density, and cycle life. The large-scale, cost-effective production of SSBs necessitates the development of high-performance solid-state electrolytes. However, the manufacturing of SSBs relies heavily on the advancement of suitable solid-state electrolytes. Composite polymer electrolytes (CPEs), which combine the advantages of ordered microporous materials (OMMs) and polymer electrolytes, meet the requirements for high ionic conductivity/transference number, stability with respect to electrodes, compatibility with established manufacturing processes, and cost-effectiveness, making them particularly well-suited for mass production of SSBs. This review delineates how structural ordering dictates the fundamental physicochemical properties of OMMs, including ion transport, thermal transfer, and mechanical stability. The applications of prominent OMMs are critically examined, such as metal-organic frameworks, covalent organic frameworks, and zeolites, in CPEs, highlighting how structural ordering facilitates the fulfillment of property requirements. Finally, an outlook on the field is provided, exploring how the properties of CPEs can be enhanced through the dimensional design of OMMs, and the importance of uncovering the underlying "feature-function" mechanisms of various CPE types is underscored.

RESUMEN

Fibroblasts are crucial components of the skin structure. They were traditionally believed to maintain the skin's structure by producing extracellular matrix and other elements. Recent research illuminated that fibroblasts can respond to external stimuli and exhibit diverse functions, such as the secretion of pro-inflammatory factors, adipogenesis, and antigen presentation, exhibiting remarkable heterogeneity and plasticity. This revelation positions fibroblasts as active contributors to the pathogenesis of skin diseases, challenging the traditional perspective that views fibroblasts solely as structural entities. Based on their diverse functions, fibroblasts can be categorized into six subtypes: pro-inflammatory fibroblasts, myofibroblasts, adipogenic fibroblasts, angiogenic fibroblasts, mesenchymal fibroblasts, and antigen-presenting fibroblasts. Cytokines, metabolism, and epigenetics regulate functional abnormalities in fibroblasts. The dynamic changes fibroblasts exhibit in different diseases and disease states warrant a comprehensive discussion. We focus on dermal fibroblasts' aberrant manifestations and pivotal roles in inflammatory and autoimmune skin diseases, including psoriasis, vitiligo, lupus erythematosus, scleroderma, and atopic dermatitis, and propose targeting aberrantly activated fibroblasts as a potential therapeutic strategy for inflammatory and autoimmune skin diseases.

RESUMEN

Laccase (LAC) is a diverse group of genes found throughout the plant genome essential for plant growth and the response to stress by converting monolignin into intricate lignin formations. However, a comprehensive investigation of maize laccase has not yet been documented. A bioinformatics approach was utilized in this research to conduct a thorough examination of maize (Zea mays L.), resulting in the identification and categorization of 22 laccase genes (ZmLAC) into six subfamilies. The gene structure and motifs of each subgroup were largely consistent. The distribution of the 22 LAC genes was uneven among the maize chromosomes, with the exception of chromosome 9. The differentiation of the genes was based on fragment replication, and the differentiation time was about 33.37 million years ago. ZmLAC proteins are primarily acidic proteins. There are 18 cis-acting elements in the promoter sequences of the maize LAC gene family associated with growth and development, stress, hormones, light response, and stress response. The analysis of tissue-specific expression revealed a high expression of the maize LAC gene family prior to the V9 stage, with minimal expression at post-V9. Upon reviewing the RNA-seq information from the publicly available transcriptome, it was discovered that ZmLAC5, ZmLAC10, and ZmLAC17 exhibited significant expression levels when exposed to various biotic and abiotic stress factors, suggesting their crucial involvement in stress responses and potential value for further research. This study offers an understanding of the functions of the LAC genes in maize's response to biotic and abiotic stress, along with a theoretical basis for comprehending the molecular processes at play.

Asunto(s)

RESUMEN

The ubiquitination-mediated protein degradation exerts a vital role in the progression of multiple tumors. NEDD4L, which belongs to the E3 ubiquitin ligase NEDD4 family, is related to tumor genesis, metastasis and drug resistance. However, the anti-tumor role of NEDD4L in esophageal carcinoma, and the potential specific recognition substrate remain unclear. Based on public esophageal carcinoma database and clinical sample data, it was discovered in this study that the expression of NEDD4L in esophageal carcinoma was apparently lower than that in atypical hyperplastic esophageal tissue and esophageal squamous epithelium. Besides, patients with high expression of NEDD4L in esophageal carcinoma tissue had longer progression-free survival than those with low expression. Experiments in vivo and in vitro also verified that NEDD4L suppressed the growth and metastasis of esophageal carcinoma. Based on co-immunoprecipitation and proteome analysis, the NEDD4L ubiquitination-degraded protein ITGB4 was obtained. In terms of the mechanism, the HECT domain of NEDD4L specifically bound to the Galx-ß domain of ITGB4, which modified the K915 site of ITGB4 in an ubiquitination manner, and promoted the ubiquitination degradation of ITGB4, thus suppressing the malignant phenotype of esophageal carcinoma.

Asunto(s)