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BACKGROUND: COVID-19 infection shows variant symptoms apart from respiratory symptoms, including the orofacial pain. We aim to research the morbidity, characteristics and potential risk factors of orofacial pain associated with COVID-19 pandemic in China from December 2022 to early 2023. METHODS: A cross-sectional survey was conducted in Fujian Province, China. The demographic and characteristic data of the subjects were collected and analysed. RESULTS: A total of 1526 subjects responded to the survey. The morbidity of orofacial pain increased significantly before and after COVID-19 infection. (42.26% vs. 46.52%, P < .001) A total of 217 (14.22%) subjects with orofacial pain before COVID-19 infection reported the phenomenon of "COVID-19 infection with orofacial pain" (CIOP). Univariate and multivariate logistic regression showed that male (OR = 1.761, P < .001) and other symptoms of COVID-19 (OR = 1.494, P < .001) may be the risk factors for the aggravation of CIOP, while the time of first infection (OR = 0.580, P = .004) and preference for drinking tea or coffee (OR = 0.610, P = .003) may be the protective factors for the aggravation of CIOP. While, the subjects who did not concern about the spread of COVID-19 in oral treatment (OR = 0.639, P = .001), female (OR = 0.749, P = .03), education level (OR = 1.687, P < .001) and income level (OR = 1.796, P < .001), higher PSS-10 score (OR = 1.076, P < .001), and more drugs taken for infection (OR = 1.330, P < .001) were more willing to seek medical treatment. CONCLUSION: The morbidity of orofacial pain appears to have increased significantly due to the COVID-19 epidemic; a number of factors can influence the CIOP including gender, infection period, and beverage preference' psychological factors, gender, education and income level can also influence the intent to seek a dentist.
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Drug resistance poses a high risk to human health. Extensive use of non-antibiotic drugs contributes to antibiotic resistance genes (ARGs) transfer. However, how they affect the spread of broad-host plasmids in complex biological systems remains unknown. This study investigated the effect of metoprolol on the transfer frequency and host range of ARGs in both intrageneric and intergeneric pure culture systems, as well as in anammox microbiome. The results showed that environmental concentrations of metoprolol significantly promoted the intrageneric and intergeneric conjugative transfer. Initially, metoprolol induced excessive oxidative stress, resulting in high cell membrane permeability and bacterial SOS response. Meanwhile, more pili formation increased the adhesion and contact between bacteria, and the abundance of conjugation-related genes also increased significantly. Activation of the electron transport chain provided more ATP for this energy-consuming process. The underlying mechanism was further verified in the complex anammox conjugative system. Metoprolol induced the enrichment of ARGs and mobile genetic elements. The enhanced bacterial interaction and energy generation facilitated the high conjugative transfer frequency of ARGs. In addition, plasmid-borne ARGs tended to transfer to opportunistic pathogens. This work raises public concerns about the health and ecological risks of non-antibiotic drugs.
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The antioxidant activities of lycopene (LY), lutein (LU), chlorogenic acid (CA), and delphinidin (DP) were tested in vitro on H9c2 cell-based models. Some indicators, such as the generation of reactive oxygen (ROS), the quantification of cell antioxidant activity (CAA), and the expressions of SOD, GSH-Px, and CAT, were calculated to examine their antioxidant interactions. From our results, the phytochemical mixtures (M1: CA-LU: F3/10, M2: DP-CA: F7/10, M3: DP-LY: F5/10) displayed strong synergistic effects based on the generation of ROS and the quantification of CAA. However, great antagonistic bioactivities were seen in the combinations of LY-LU: F5/10 (M4), CA-LU: F9/10 (M5), and DP-LY: F7/10 (M6). Western blotting analysis indicated that the possible mechanism underlying the synergistic antioxidant interactions among phytochemical combinations was to enhance the accumulation of Nrf2 in the nucleus and the expression of its downstream antioxidant enzymes, HO-1 and GCLC. The combinations (M1-M3 groups) showed significant protection against the loss of mitochondrial membrane potential than individual groups to avoid excessive ROS production. The M4-M6 groups exerted antagonistic protective effects compared with the individual groups. In addition, lutein and lycopene absorption was improved more because of the presence of chlorogenic acid and delphinidin in the M1 and M3 groups, respectively. However, delphinidin significantly reduced the cellular uptake of lycopene in the M6 group. It appeared that antioxidant interactions of phytochemical combinations may contribute to the restoration of cellular redox homeostasis and lead to an improvement in diet quality and collocation.
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Hydrological models are vital tools in environmental management. Weaknesses in model robustness for hydrological parameters transfer uncertainties to the model outputs. For streamflow, the optimized parameters are the primary source of uncertainty. A reliable calibration approach that reduces prediction uncertainty in model simulations is crucial for enhancing model robustness and reliability. The optimization of parameter ranges is a key aspect of parameter calibration, yet there is a lack of literature addressing the optimization of parameter ranges in hydrological models. In this paper, we introduce a parameter calibration strategy that applies a clustering technique, specifically the Self-Organizing Map (SM), to intelligently navigate the parameter space during the calibration of the Soil and Water Assessment Tool (SWAT) model for monthly streamflow simulation in the Baishan Basin, Jilin Province, China. We selected the representative algorithm, the Sequential Uncertainty Fitting version 2 (SUFI-2), from the commonly used SWAT Calibration and Uncertainty Programs for comparison. We developed three schemes: SUFI-2, SUFI-2-Narrowing Down (SUFI-2-ND), and SM. Multiple diagnostic error metrics were used to compare simulation accuracy and prediction uncertainty. Among all schemes, SM outperformed the others in describing watershed streamflow, particularly excelling in the simulation of spring snowmelt runoff (baseflow period). Additionally, the prediction uncertainty was effectively controlled, demonstrating the SM's adaptability and reliability in the interval optimization process. This provides managers with more credible prediction results, highlighting its potential as a valuable calibration tool in hydrological modeling.
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Purpose: Diffuse large B-cell lymphoma (DLBCL) is a prevalent malignant condition with a dismal prognosis. LncRNA PGM5 antisense RNA 1 (PGM5-AS1) appears to be intricately involved in the progression of DLBCL, yet the modulatory mechanism remains unclear. The purpose of this study was to explore the expression of lncRNA PGM5-AS1 in DLBCL and its effect on the disease progression of DLBCL, as well as to explore its mechanisms. Patients and Methods: A total of 35 patients were included in the study. The expression levels of PGM5-AS1 and miR-503-5p in DLBCL tumor tissues and cell lines were detected by RT-qPCR. Cell proliferation was assessed using CCK8. Apoptosis rate was determined by flow cytometry. Cell invasion was examined by transwell assays. The specific interaction between PGM5-AS1 and miR-503-5p was verified through dual luciferase reporter gene assays. The immune related factors were detected by ELASA kits. The CD8+ T cells cytotoxicity was evaluated by LDH cytotoxicity kit. Results: In DLBCL tumor tissues and cells, upregulated PGM5-AS1 expression, downregulated miR-503-5p expression, and elevated PD-L1 expression were observed. PGM5-AS1 functioned as a regulator in controlling DLBCL cell proliferation, apoptosis, and invasion by downregulating miR-503-5p expression. When CD8+ T cells were co-cultured with cells transfected with si-PGM5-AS1, the secretion of immunoregulatory factors increased, and the cytotoxicity of CD8+ T cells increased. These effects were mitigated by miR-503-5p inhibitors. Conclusion: PGM5-AS1 accelerated DLBCL development and facilitated tumor immune escape through the miR-503-5p. Our discoveries offered an insight into lncRNA PGM5-AS1 serving as a prospective therapeutic target for DLBCL.
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Purpose: Major depressive disorder (MDD) and venous thromboembolism (VTE) may be linked in observational studies. However, the causal association remains ambiguous. Therefore, this study investigates the causal associations between them. Methods: We performed a two-sample univariable and multivariable bidirectional Mendelian randomization (MR) analysis to evaluate the associations between MDD and VTE. The summary genetic associations of MDD statistics were obtained from the Psychiatric Genomics Consortium and UK Biobank. Information on VTE, deep vein thrombosis (DVT), and pulmonary embolism (PE) were obtained from the FinnGen Biobank. Inverse-variance weighting was used as the main analysis method. Other methods include weighted median, MR-Egger, Simple mode, and Weighted mode. Results: Univariable MR analysis revealed no significant associations between MDD and VTE risk (odds ratio (OR): 0.936, 95% confidence interval (CI): 0.736-1.190, p = 0.590); however, after adjusting the potential relevant polymorphisms of body mass index and education, the multivariable MR analysis showed suggestive evidence of association between them (OR: 1.163, 95% CI: 1.004-1.346, p = 0.044). Univariable MR analysis also revealed significant associations between MDD and PE risk (OR: 1.310, 95% CI: 1.073-1.598, p = 0.008), but the association between them was no longer significant in MVMR analysis (p = 0.072). We found no significant causal effects between MDD and DVT risk in univariable or multivariable MR analyses. There was also no clear evidence showing the causal effects between VTE, PE, or DVT and MDD risk. Conclusion: We provide suggestive genetic evidence to support the causal association between MDD and VTE risk. No causal associations were observed between VTE, PE, or DVT and MDD risk. Further validation of these associations and investigations of potential mechanisms are required.
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Depression is a prevalent mental disorder that significantly diminishes quality of life and longevity, ranking as one of the primary causes of disability globally. Contemporary research has explored the potential pathogenesis of depression from various angles, encompassing genetics, neurotransmitter systems, neurotrophic factors, the hypothalamic-pituitary-adrenal axis, inflammation, and intestinal flora, among other contributing factors. In addition, conventional chemical medications are plagued by delayed onset of action, persistent adverse effects, and restricted therapeutic efficacy. In light of these limitations, the therapeutic approach of traditional Chinese medicine (TCM) has gained increasing recognition for its superior effectiveness. Numerous pharmacological and clinical studies have substantiated TCM's capacity to mitigate depressive symptoms through diverse mechanisms. This article attempts to summarize the mechanisms involved in the pathogenesis of depression and to describe the characteristics of herbal medicines (including compounded formulas and active ingredients) for the treatment of depression. It further evaluates their effectiveness by correlating with the multifaceted pathogenesis of depression, thereby furnishing a reference for future research endeavors.
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Metals are essential for human health and play a crucial role in numerous biological processes and pathways. Gaining a deeper insight into these biological events will facilitate novel strategies for disease prevention, early detection, and personalized treatment. In recent years, there has been significant progress in the development of metal-detection based techniques from single cell metallome and proteome profiling to multiplex imaging, which greatly enhance our comprehension of the intricate roles played by metals in complex biological systems. This perspective summarizes the recent progress in advanced metal-detection based techniques and highlights successful applications in elucidating the roles of metals in biology and medicine. Technologies including machine learning that couple with single-cell analysis such as mass cytometry and their application in metallobiology, cancer biology and immunology are also emphasized. Finally, we provide insights into future prospects and challenges involved in metal-detection based techniques, with the aim of inspiring further methodological advancements and applications that are accessible to chemists, biologists, and clinicians.
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Lung cancer persistently leads as the primary cause of morbidity and mortality among malignancies. A notable increase in the prevalence of lung adenocarcinoma has become evident in recent years. Although targeted therapies have shown in treating certain subsets of non-small cell lung cancers (NSCLC), a significant proportion of patients still face suboptimal therapeutic outcomes. Neuregulin-1 (NRG1), a critical member of the NRG gene family, initially drew interest due to its distribution within the nascent ventricular endocardium, showcasing an exclusive presence in the endocardium and myocardial microvessels. Recent research has highlighted NRG1's pivotal role in the genesis and progression across a spectrum of tumors, influencing molecular perturbations across various tumor-associated signaling pathways. This review provides a concise overview of NRG1, including its expression patterns, configuration, and fusion partners. Additionally, we explore the unique features and potential therapeutic strategies for NRG1 fusion-positive occurrences within the context of NSCLC.
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Due to the similarity and diversity among kinases, small molecule kinase inhibitors (SMKIs) often display multi-target effects or selectivity, which have a strong correlation with the efficacy and safety of these inhibitors. However, due to the limited number of well-known popular databases and their restricted data mining capabilities, along with the significant scarcity of databases focusing on the pharmacological similarity and diversity of SMIKIs, researchers find it challenging to quickly access relevant information. The KLIFS database is representative of specialized application databases in the field, focusing on kinase structure and co-crystallised kinase-ligand interactions, whereas the KLSD database in this paper emphasizes the analysis of SMKIs among all reported kinase targets. To solve the current problem of the lack of professional application databases in kinase research and to provide centralized, standardized, reliable and efficient data resources for kinase researchers, this paper proposes a research program based on the ChEMBL database. It focuses on kinase ligands activities comparisons. This scheme extracts kinase data and standardizes and normalizes them, then performs kinase target difference analysis to achieve kinase activity threshold judgement. It then constructs a specialized and personalized kinase database platform, adopts the front-end and back-end separation technology of SpringBoot architecture, constructs an extensible WEB application, handles the storage, retrieval and analysis of the data, ultimately realizing data visualization and interaction. This study aims to develop a kinase database platform to collect, organize, and provide standardized data related to kinases. By offering essential resources and tools, it supports kinase research and drug development, thereby advancing scientific research and innovation in kinase-related fields. It is freely accessible at: http://ai.njucm.edu.cn:8080.
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The COVID-19 pandemic caused by SARS-CoV-2 resulted in a global public health crisis. In addition to vaccines, the development of effective therapy is highly desirable. Targeting a protein that plays a critical role in virus replication may allow pan-spectrum antiviral drugs to be developed. Among SARS-CoV-2 proteins, helicase (i.e., non-structural protein 13) is considered as a promising antiviral drug target due to its highly conserved sequence, unique structure and function. Herein, we demonstrate SARS-CoV-2 helicase as a target of bismuth-based antivirals in virus-infected mammalian cells by a metal-tagged antibody approach. To search for more potent bismuth-based antivirals, we further screened a panel of bismuth compounds towards inhibition of ATPase and DNA unwinding activity of nsp13 and identified a highly potent bismuth compound Bi(5-aminotropolonate)3, namely Bi(Tro-NH2)3 with an IC50 of 30 nM for ATPase. We show that bismuth-based compounds inhibited nsp13 unwinding activity via disrupting the binding of ATP and the DNA substrate to viral helicase. Binding of Bi(iii) to nsp13 also abolished the interaction between nsp12 and nsp13 as evidenced by immunofluorescence and co-immunoprecipitation assays. Finally, we validate our in vitro data in SARS-CoV-2 infected mammalian cells. Notably, Bi(6-TG)3 exhibited an EC50 of 1.18 ± 0.09 µM with a selective index of 847 in VeroE6-TMPRSS2 infected cells. This study highlights the important role of helicase for the development of more effective antiviral drugs to combat SARS-CoV-2 infection.
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This study evaluated the treatment efficiency of two selected fillers and their combination for improving the water quality of aquaculture wastewater using a packed bed biofilm reactor (PBBR) under various process conditions. The fillers used were nanosheet (NS), activated carbon (AC), and a combination of both. The results indicated that the use of combined fillers and the hydraulic retention time (HRT) of 4 h significantly enhanced water quality in the PBBR. The removal rates of chemical oxygen demand, NO2-âN, total suspended solidsï¼TSSï¼, and chlorophyll a were 63.55%, 74.25%, 62.75%, and 92.85%, respectively. The microbiota analysis revealed that the presence of NS increased the abundance of microbial phyla associated with nitrogen removal, such as Nitrospirae and Proteobacteria. The difference between the M1 and M2 communities was minimal. Additionally, the microbiota in different PBBR samples displayed similar preferences for carbon sources, and carbohydrates and amino acids were the most commonly utilized carbon sources by microbiota. These results indicated that the combination of NS and AC fillers in a PBBR effectively enhanced the treatment efficiency of aquaculture wastewater when operated at an HRT of 4 h. The findings provide valuable insights into optimizing the design of aquaculture wastewater treatment systems.
Subject(s)
Aquaculture , Biofilms , Bioreactors , Wastewater , Water Purification , Biofilms/growth & development , Bioreactors/microbiology , Water Purification/methods , Wastewater/microbiology , Wastewater/chemistry , Nitrogen/metabolism , Charcoal/chemistry , Bacteria/genetics , Bacteria/isolation & purification , Bacteria/metabolism , Bacteria/growth & development , Biological Oxygen Demand Analysis , Microbiota , Waste Disposal, Fluid/methods , Water QualityABSTRACT
BACKGROUND: The current understanding of the prognostic significance of B cells and their role in the tumor microenvironment (TME) in esophageal carcinoma (ESCA) is limited. METHODS: We conducted a screening for B-cell-related genes through the analysis of single-cell transcriptome data. Subsequently, we developed a B-cell-related gene signature (BRGrisk) using LASSO regression analysis. Patients from The Cancer Genome Atlas cohort were divided into a training cohort and a test cohort. Patients were categorized into high- and low-risk groups based on their median BRGrisk scores. The overall survival was assessed using the Kaplan-Meier method, and a nomogram based on BRGrisk was constructed. Immune infiltration profiles between the risk groups were also compared. RESULTS: The BRGrisk prognostic model indicated significantly worse outcomes for patients with high BRGrisk scores (p < 0.001). The BRGrisk-based nomogram exhibited good prognostic performance. Analysis of immune infiltration revealed that patients in the high-BRGrisk group had notably higher levels of immune cell infiltration and were more likely to be in an immunoresponsive state. Enrichment analysis showed a strong correlation between the prognostic gene signature and cancer-related pathways. IC50 results indicated that patients in the low-BRGrisk group were more responsive to common drugs compared to those in the high-BRGrisk group. CONCLUSIONS: This study presents a novel BRGrisk that can be used to stratify the prognosis of ESCA patients and may offer guidance for personalized treatment strategies aimed at improving prognosis.
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The seeding amplification assay (SAA) has recently emerged as a valuable tool for detecting α-synuclein (αSyn) aggregates in various clinically accessible biospecimens. Despite its efficiency and specificity, optimal tissue-specific conditions for distinguishing Parkinson's disease (PD) from non-PD outside the brain remain underexplored. This study systematically evaluated 150 reaction conditions to identify the one with the highest discriminatory potential between PD and non-synucleinopathy controls using skin samples, resulting in a modified SAA. The streamlined SAA achieved an overall sensitivity of 92.46% and specificity of 93.33% on biopsy skin samples from 332 PD patients and 285 controls within 24 h. Inter-laboratory reproducibility demonstrated a Cohen's kappa value of 0.87 (95% CI 0.69-1.00), indicating nearly perfect agreement. Additionally, αSyn seeds in the skin were stable at -80 °C but were vulnerable to short-term exposure to non-ultra-low temperatures and grinding. This study thoroughly investigated procedures for sample preprocessing, seed amplification, and storage, introducing a well-structured experimental framework for PD diagnosis using skin samples.
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Recent studies increasingly suggest a connection between lipids and idiopathic pulmonary fibrosis (IPF). This study was aimed at exploring potential lipid-related biomarkers for IPF and uncovering the mechanisms underlying pulmonary fibrosis. IPF-related datasets were retrieved from the GEO database, and the ComBat algorithm was used to merge multiple datasets and eliminate batch effects. Weighted gene co-expression network analysis (WGCNA) was utilized to identify modules and genes associated with IPF. Potential hub genes were determined by intersecting these genes with lipid-related genes from the GeneCards database. A machine learning-based integrative approach was developed to construct diagnostic and prognostic signatures, which were validated across several datasets. Additionally, single-cell sequencing data was used to validate the expression differences of core IPF-related genes across various cell types. The effect of ABHD5 on fibroblasts was assessed using the cell counting kit-8, 5-ethynyl-2'-deoxyuridine, and cell scratch assays. The expression levels of fibrotic factors were measured using real-time quantitative polymerase chain reaction and western blot analysis. WGCNA identified a red module potentially related to IPF, and the intersection with lipid-related genes yielded 51 hub genes. These genes were used to build diagnostic and prognostic models that demonstrated robust validation capabilities across multiple datasets. Single-cell sequencing analysis revealed low expression of ABHD5 in the lung tissues of IPF patients, with a higher proportion of fibroblasts exhibiting low ABHD5 expression. Cell experiments showed that under the influence of TGF-ß1, knockdown of ABHD5 slightly promoted fibroblast proliferation. Additionally, fibroblasts with low ABHD5 expression exhibited enhanced migratory capabilities and secreted more fibrotic factors. Lipid-related diagnostic and prognostic models for IPF were developed, and ABHD5 may serve as a potential biomarker. Low ABHD5 expression could potentially accelerate the progression of pulmonary fibrosis.
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Brucellosis is a serious public health problem worldwide and can affect any organ system. Due to brucellosis's variable clinical presentation, ranging from subclinical to fully symptomatic, and limited available information, it poses a diagnostic challenge. In this study, we reported a case series of patients with diverse presentations. In addition, we briefly described the pathophysiology and mechanisms of Brucella in the body. These case presentations will be valuable in increasing the awareness of physicians. A prompt diagnosis is crucial, as detecting some clues of the infection in its early stages can help avoid misdiagnoses.
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Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide, but the underlying molecular mechanisms remain largely unclear. The transcription factor (TF) specificity protein 1 (SP1) plays a crucial role in the development of various cancers, including LUAD. Recent studies have indicated that master TFs may form phase-separated macromolecular condensates to promote super-enhancer (SE) assembly and oncogene expression. In this study, we demonstrated that SP1 undergoes phase separation and that its zinc finger 3 in the DNA-binding domain is essential for this process. Through Cleavage Under Targets & Release Using Nuclease (CUT&RUN) using antibodies against SP1 and H3K27ac, we found a significant correlation between SP1 enrichment and SE elements, identified the regulator of the G protein signaling 20 (RGS20) gene as the most likely target regulated by SP1 through SE mechanisms, and verified this finding using different approaches. The oncogenic activity of SP1 relies on its phase separation ability and RGS20 gene activation, which can be abolished by glycogen synthase kinase J4 (GSK-J4), a demethylase inhibitor. Together, our findings provide evidence that SP1 regulates its target oncogene expression through phase separation and SE mechanisms, thereby promoting LUAD cell progression. This study also revealed an innovative target for LUAD therapies through intervening in SP1-mediated SE formation.
Subject(s)
Adenocarcinoma of Lung , Gene Expression Regulation, Neoplastic , Lung Neoplasms , RGS Proteins , Sp1 Transcription Factor , Sp1 Transcription Factor/metabolism , Sp1 Transcription Factor/genetics , Humans , Adenocarcinoma of Lung/metabolism , Adenocarcinoma of Lung/pathology , Adenocarcinoma of Lung/genetics , Lung Neoplasms/metabolism , Lung Neoplasms/pathology , Lung Neoplasms/genetics , RGS Proteins/metabolism , RGS Proteins/genetics , Cell Line, Tumor , Animals , Enhancer Elements, Genetic , Disease Progression , Mice , Phase SeparationABSTRACT
Rice aroma, one of the most important qualities of rice, was the comprehensive result of volatiles in rice and human sense. In this study, the main volatile compounds in rice were analyzed by using gas chromatography-mass spectrometry and gas chromatography-olfactometry, and their correlations with sensory score were investigated. A total of eighty-five volatiles were found in rice samples. By combining odor activity value and correlation analysis, nine volatiles were considered as potential characteristic volatiles in rice aroma, namely hexanal, 2-pentylfuran, octanal, 2-acetyl-1-pyrroline (2-AP), 1-octen-3-ol, trans-2-octenal, decanal, trans-2-nonenal and trans, trans-2,4-decadienal. It was found that the volatiles negatively correlated with sensory scores were positively correlated with hexanal. It indicated that hexanal might be a representative of the negative volatiles of rice aroma. The effects of the nine potential characteristic volatiles on rice aroma were investigated by using sensory analysis. The results showed that the odor intensity and preference level of 2-AP, hexanal, and 1-octen-3-ol were significantly affected by the content. Furthermore, the aroma of cooked rice was significantly different after adding 2-AP, hexanal or trans, trans-2,4-decadienal. Rice aroma was increased by adding 2-AP and deteriorated by adding hexanal or trans, trans-2,4-decadienal, indicating that 2-AP contributed positively to rice aroma while hexanal and trans, trans-2,4-decadienal contributed negatively to rice aroma. Hexanal, 2-AP, and trans, trans-2,4-decadienal were suggested to be the key characteristic volatiles for future aroma evaluation.
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Multiple myeloma, which is a clonal plasma cell tumor, derives from a postmitotic lymphoid B-cell lineage and remains untreatable. Group XVI phospholipase A2 (PLA2G16) can either be a tumor suppressor or an oncogene in different types of cancer. This study was intended to explore the role of PLA2G16 in multiple myeloma and to reveal the reaction mechanism. The mRNA and protein expressions of PLA2G16 in human bone marrow stromal cell line HS-5 and multiple myeloma cells were assessed using reverse transcription-quantitative PCR and western blot. The transfection efficacy of sh-PLA2G16 and oe-YAP was examined using reverse transcription-quantitative PCR and western blot. Through cell counting kit-8 assay and 5-ethynyl-2'- deoxyuridine staining, multiple myeloma cell viability and proliferation were detected. Flow cytometry was used to measure cell apoptosis and cell cycle distribution. Oxygen consumption rate, the activities of mitochondrial respiratory chain complexes I-V, and the activity of caspase-3 were estimated with Seahorse XF24 analyzer, oxidative phosphorylation activity assay kit, and caspase-3 assay kit, respectively. Lactate production and glucose consumption were evaluated usingcorresponding assay kits. Western blot was employed to meaure proteins associated with cell cycle, glycolysis, pentose phosphate pathway as well as Hippo/YAP signaling pathway. In this study, PLA2G16 expression was greatly increased in multiple myeloma cells and PLA2G16 silence inhibited cell proliferation, promoted cell apoptosis, facilitated cell cycle arrest, and suppressed the reprogramming of glucose metabolism in multiple myeloma. It was also identified that PLA2G16 depletion inhibited the Hippo/YAP signaling pathway. Further experiments revealed that the overexpression of YAP partially reversed the inhibitory effects of PLA2G16 silence on multiple myeloma cell malignant development and the reprogramming of glucose metabolism. Collectively, PLA2G16 silence impeded multiple myeloma progression and inhibited glucose metabolism reprogramming by blocking the Hippo/YAP signaling pathway.
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Nonenzymatic glycosylation of proteins can generate advanced glycosylation end products, which are closely associated with the pathogenesis of certain chronic physiological diseases and aging. In this study, we characterized the covalent binding of cyanidin-3-glucoside (C3G) to bovine serum albumin (BSA) and investigated the mechanism by which this covalent binding inhibits the nonenzymatic glycosylation of BSA. The results indicated that the covalent interaction between C3G and BSA stabilized the protein's secondary structure. Through liquid chromatography-electrospray ionization tandem mass spectrometry analysis, we identified the covalent binding sites of C3G on BSA as lysine, arginine, asparagine, glutamine, and cysteine residues. This covalent interaction significantly suppressed the nonenzymatic glycosylation of BSA, consequently reducing the formation of nonenzymatic glycosylation products. C3G competitively binds to nonenzymatic glycosylation sites (e.g., lysine and arginine) on BSA, thereby impeding the glycosylation process and preventing the misfolding and structural alterations of BSA induced by fructose. Furthermore, the covalent attachment of C3G to BSA preserves the secondary structure of BSA and hinders subsequent nonenzymatic glycosylation events.