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OBJECTIVE: The relationship between gout and osteoporosis is poorly clarified, and the association between gout and fractures incidence remains controversial. Hence, in the present study, we aimed to comprehensively evaluate the available literature to elucidate whether gout is associated with an increased risk of both osteoporosis and fractures. MATERIALS AND METHODS: We conducted an exhaustive search of pertinent literature published until 20 March 2023, in well-recognized databases, namely Medline, Embase and Cochrane Library, focusing on examining the association between gout and the risk of osteoporosis or fracture. Meta-analysis was performed to aggregate the relative risks (RR) using random- or fixed-effects models. Sensitivity analyses were conducted iteratively, whereby each study was removed sequentially to gauge its impact on the overall outcome. Publication bias was assessed using Egger's and Begg's tests. This study was registered with PROSPERO (registry number: CRD42022376822). RESULTS: Herein, we included 10 observational studies comprising a total of 1,606,095 participants. An independent population sample of four studies validated the significant association between gout and osteoporosis (RRâ¯= 1.25, 95% confidence interval [CI] 1.05-1.48), with the results demonstrating robustness. However, our analysis did not detect any association between gout and fracture risk when compared with the control group (RRâ¯= 1.09, 95%CI 0.99-1.19), along with high heterogeneity (p for heterogeneityâ¯= 0.000; I2â¯= 79.7%). Further subgroup analysis revealed that gout is positively associated with fracture risk in the Chinese population (RRâ¯= 1.17, 95%CI 1.14-1.21), with no evidence of heterogeneity (p for heterogeneityâ¯= 0.420; I2â¯= 0.00%). CONCLUSION: Our meticulous evaluation of the available literature indicates that gout has no discernible impact on fracture incidence, although it is positively associated with an enhanced risk of osteoporosis. Therefore, it is imperative to prioritize preventive measures to prevent osteoporotic complications in individuals diagnosed with gout.
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Gota , Osteoporose , Fraturas por Osteoporose , Humanos , Fraturas por Osteoporose/epidemiologia , Osteoporose/epidemiologia , Gota/complicações , Gota/epidemiologiaRESUMO
BACKGROUND: Increasing evidence shows that an elevated homocysteine(Hcy) level is associated with an increased risk of chronic kidney disease (CKD). This study systematically evaluated the correlation between homocysteine level and the incidence of CKD reported in cohort and cross-sectional studies. METHODS: We searched electronic databases and reference lists for relevant articles. 4 cohort studies and 7 cross-sectional studies including 79,416 patients were analyzed in a meta-analysis. Hyperhomocysteinemia was defined as a Hcy level > 15 µmol/L, which was the criterium used in previous studies. Meta-analyses were conducted of literature searches from online databases such as PubMed, Embase, Cochrane and Scopus. Computed pooled adjusted odds ratios with corresponding 95% confidence intervals (95% CI) were used to estimate the risk of new-onset CKD according to Hcy levels in the general population. RESULTS: People with high Hcy levels were more likely to suffer from CKD than people with normal Hcy levels (pooled OR, 2.09; 95% CI, 1.72-2.55). This positive relationship persisted across different study types such as cohort studies (summary OR, 2.2; 95% CI, 1.55-3.13) and cross-sectional studies (summary OR, 2.07; 95% CI, 1.63-2.63). CONCLUSIONS: People with hyperhomocysteinemia have a higher incidence of CKD, Hyperhomocysteinemia may also be an independent risk factor for CKD in the general population.
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Hiper-Homocisteinemia , Insuficiência Renal Crônica , Humanos , Hiper-Homocisteinemia/epidemiologia , Estudos Transversais , Bases de Dados Factuais , Homocisteína , Insuficiência Renal Crônica/epidemiologiaRESUMO
OBJECTIVE: The purpose of this study was to evaluate the impact of COVID-19 outbreaks on emergency patients in a resuscitation room in Nanning, China. METHODS: A single-center cross-sectional retrospective study was conducted in the emergency department of a tertiary public hospital from January 1, 2019, to December 31, 2020, in Nanning, Guangxi, China. We collected the data of patients in the resuscitation room to investigate the number of patients accessing emergency services during the study period. Data in 2020 were compared to the data during the same period in 2019. RESULTS: The number of emergency patients in the resuscitation room during the COVID-19 pandemic has decreased in intrinsic diseases, extrinsic diseases, and pediatric cases, especially in the early stages of the pandemic. Additionally, the length of stay of emergency patients in the resuscitation room was reduced. CONCLUSIONS: The number of emergency patients in the resuscitation room during the pandemic of COVID-19 in 2020 was reduced compared to that in the same period in 2019 in Nanning, China. This situation shows a serious social problem, which should arouse the attention of the medical profession and the government.
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COVID-19/epidemiologia , Serviço Hospitalar de Emergência/estatística & dados numéricos , Ressuscitação/estatística & dados numéricos , Adulto , Idoso , China , Estudos Transversais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , SARS-CoV-2RESUMO
Background: The current 2019 novel coronavirus disease (COVID-19) pandemic is a major threat to global health. It is currently uncertain whether and how liver injury affects the severity of COVID-19. Therefore, we conducted a meta-analysis to determine the association between liver injury and the severity of COVID-19. Methods: A systematic search of the PubMed, Embase, and Cochrane Library databases from inception to August 12, 2022, was performed to analyse the reported liver chemistry data for patients diagnosed with COVID-19. The pooled odds ratio (OR), weighted mean difference (WMD) and 95% confidence interval (95% CI) were assessed using a random-effects model. Furthermore, publication bias and sensitivity were analyzed. Results: Forty-six studies with 28,663 patients were included. The pooled WMDs of alanine aminotransferase (WMD = 12.87 U/L, 95% CI: 10.52-15.23, I 2 = 99.2%), aspartate aminotransferase (WMD = 13.98 U/L, 95% CI: 12.13-15.83, I 2 = 98.2%), gamma-glutamyl transpeptidase (WMD = 20.67 U/L, 95% CI: 14.24-27.10, I 2 = 98.8%), total bilirubin (WMD = 2.98 µmol/L, 95% CI: 1.98-3.99, I 2 = 99.4%), and prothrombin time (WMD = 0.84 s, 95% CI: 0.46-1.23, I 2 = 99.4%) were significantly higher and that of albumin was lower (WMD = -4.52 g/L, 95% CI: -6.28 to -2.75, I 2 = 99.9%) in severe cases. Moreover, the pooled OR of mortality was higher in patients with liver injury (OR = 2.72, 95% CI: 1.18-6.27, I 2 = 71.6%). Conclusions: Hepatocellular injury, liver metabolic, and synthetic function abnormality were observed in severe COVID-19. From a clinical perspective, liver injury has potential as a prognostic biomarker for screening severely affected patients at early disease stages. Systematic review registration: https://www.crd.york.ac.uk/prospero/, Identifier: CRD42022325206.
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COVID-19 , Humanos , Fígado , SARS-CoV-2RESUMO
Purpose: Although the combined photo-thermal (PTT) and photodynamic therapy (PDT) of tumors have demonstrated promise as effective cancer therapy, the hypoxic and insufficient H2O2 supply of tumors seriously limits the efficacy of PDT, and the acidic environment reduces the catalytic activity of nanomaterial in the tumor microenvironment. To develop a platform for efficiently addressing these challenges, we constructed a nanomaterial of Aptamer@dox/GOD-MnO2-SiO2@HGNs-Fc@Ce6 (AMS) for combination tumor therapy. The treatment effects of AMS were evaluated both in vitro and in vivo. Methods: In this work, Ce6 and hemin were loaded on graphene (GO) through π-π conjugation, and Fc was connected to GO via amide bond. The HGNs-Fc@Ce6 was loaded into SiO2, and coated with dopamine. Then, MnO2 was modified on the SiO2. Finally, AS1411-aptamer@dox and GOD were fixed to gain AMS. We characterized the morphology, size, and zeta potential of AMS. The oxygen and reactive oxygen species (ROS) production properties of AMS were analyzed. The cytotoxicity of AMS was detected by MTT and calcein-AM/PI assays. The apoptosis of AMS to a tumor cell was estimated with a JC-1 probe, and the ROS level was detected with a 2',7'-Dichlorodihydrofluorescein diacetate (DCFH-DA) probe. The anticancer efficacy in vivo was analyzed by the changes in the tumor size in different treatment groups. Results: AMS was targeted to the tumor cell and released doxorubicin. It decomposed glucose to produce H2O2 in the GOD-mediated reaction. The generated sufficient H2O2 was catalyzed by MnO2 and HGNs-Fc@Ce6 to produce O2 and free radicals (â¢OH), respectively. The increased oxygen content improved the hypoxic environment of the tumor and effectively reduced the resistance to PDT. The generated â¢OH enhanced the ROS treatment. Moreover, AMS depicted a good photo-thermal effect. Conclusion: The results revealed that AMS had an excellent enhanced therapy effect by combining synergistic PTT and PDT.
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Neoplasias , Fotoquimioterapia , Humanos , Fotoquimioterapia/métodos , Fármacos Fotossensibilizantes/química , Dióxido de Silício/uso terapêutico , Peróxido de Hidrogênio , Espécies Reativas de Oxigênio , Porosidade , Compostos de Manganês/química , Óxidos/química , Oxigênio , Neoplasias/tratamento farmacológico , Doxorrubicina/uso terapêutico , Hipóxia/tratamento farmacológico , Linhagem Celular Tumoral , Microambiente TumoralRESUMO
Introduction: Coronavirus disease 2019 (COVID-19) can lead to acute respiratory distress syndrome (ARDS) and life-threatening multi-organ failure with increased levels of inflammatory mediators and viral load; however, little is known about its pathophysiology. Methods: To better understand the cellular status of COVID-19-induced ARDS, we performed single-cell RNA sequencing on peripheral blood samples from patients with COVID-19-induced ARDS. Single-cell RNA sequencing combined with bioinformatics analysis was used to study dynamic changes in cell composition and transcriptional profiles. Results: The single-cell RNA sequencing data revealed significant phenotypic differences between patients with COVID-19-induced ARDS and controls, mainly in monocytes, and CD8+ T and B cells. B-cell and monocyte abundances were significant in COVID-19-induced ARDS patients compared to controls, while CD8+ T cells were depleted. These data suggest that there is an imbalance between lymphocytes and monocytes in the blood of COVID-19-induced ARDS patients. In addition, cytokine interactions between T cells, monocytes and B cells are enhanced as evidenced by the intercellular communication analysis. In particular, T cell subsets target receptors on other cells via CCL5 and may play an important role in patients with COVID-19-induced ARDS. Conclusion: Our analysis suggested that a dysregulated adaptive immune response exists in patients with COVID-19-induced ARDS. Overall, we provided a cellular picture of the peripheral immune response in patients with COVID-19-induced ARDS.
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Background: Acute respiratory distress syndrome (ARDS) is caused by severe pulmonary inflammation and the leading cause of death in the intensive care unit. Methods: We used single-cell RNA sequencing to compare peripheral blood mononuclear cells from sepsis-induced ARDS (SEP-ARDS) and pneumonic ARDS (PNE-ARDS) patient. Then, we used the GSE152978 and GSE152979 datasets to identify molecular dysregulation mechanisms at the transcriptional level in ARDS. Results: Markedly increased CD14 cells were the predominant immune cell type observed in SEP-ARDS and PNE-ARDS patients. Cytotoxic cells and natural killer (NK) T cells were exclusively identified in patients with PNE-ARDS. An enrichment analysis of differentially expressed genes (DEGs) suggested that Th1 cell differentiation and Th2 cell differentiation were enriched in cytotoxic cells, and that the IL-17 signaling pathway, NOD receptor signaling pathway, and complement and coagulation cascades were enriched in CD14 cells. Furthermore, according to GSE152978 and GSE152979, 1939 DEGs were identified in patients with ARDS and controls; they were mainly enriched in the Kyoto Encyclopedia of Genes and Genomes pathways. RBP7 had the highest area under the curve values among the 12 hub genes and was mainly expressed in CD14 cells. Additionally, hub genes were negatively correlated with NK cells and positively correlated with neutrophils, cytotoxic cells, B cells, and macrophages. Conclusion: A severe imbalance in the proportion of immune cells and immune dysfunction were observed in SEP-ARDS and PNE-ARDS patients. RBP7 may be immunologically associated with CD14 cells and serve as a potential marker of ARDS.
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Introduction: Acute respiratory distress syndrome (ARDS) remains a major clinical challenge for patients in intensive care units. Determining the differential mechanisms underlying ARDS with different etiologies is a key goal to improve the effectiveness of ARDS therapy. Despite growing evidence that different immune cell types are involved in ARDS, the role of altered immune cell subpopulations in disease progression is unelucidated. Methods: In this study, we combined scRNA-seq and bulk-level sequencing to analyze the transcriptomes of peripheral blood mononuclear cells from healthy volunteers and patients with septic ARDS (sep-ARDS) and pneumonic ARDS (PNE-ARDS). Results: Our data revealed differential alterations at the cellular and molecular levels and within biological signaling pathways in ARDS with different etiologies. The dynamics of neutrophils, macrophages (Macs), classical dendritic cells (cDCs), myeloid-derived suppressive cells (MDSCs), and CD8+ T cells varied significantly among groups of different samples, with neutrophils and cDCs at higher, and Macs at significantly lower, amounts in the patients with sep-ARDS. Furthermore, MDSCs were highly enriched only in the sep-ARDS patients, whereas a higher abundance of CD8+ T cells was observed in patients with PNE-ARDS. In addition, these cell subpopulations were found to be significantly involved in apoptosis, inflammatory, and immune-related pathways. In particular, a significant enhancement of the oxidative stress response was observed in the neutrophil subpopulation. Conclusion: Our study shows that the composition of cells involved in the main peripheral circulation differs in patients with ARDS with different etiologies. Studying the role and mechanism of action of these cells during ARDS will provide new opportunities for the treatment of this condition.
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PURPOSE: The goal of this study was to compare the efficacy and tolerability of insulin degludec with those of other long-acting insulin analogues (insulin glargine and insulin detemir) in patients with type 1 or 2 diabetes mellitus (T1D or T2D). METHODS: Those randomized controlled trials comparing insulin degludec with other long-acting insulin analogues in the treatment of patients with T1D or T2D published on or before August 21, 2022, were retrieved from PubMed, Web of Science, the Cochrane Library, and EMBASE. The efficacy end points were the changes from baseline in hemoglobin A1c and fasting plasma glucose (FPG). The tolerability end point was the prevalence of hypoglycemia confirmed throughout the treatment period. FINDINGS: Data from a total of 20 trials (19,048 patients) were included. The differences in the reductions in glycosylated hemoglobin between insulin degludec and other long-acting basal insulin analogues (insulin glargine and insulin detemir) used for the treatment of patients with T1D or T2D were not significant. However, the reduction in FPG was greater with insulin degludec (-0.370 mmol/L; 95% CI, -0.473 to -0.267 mmol/L; P ≤ 0.001). Throughout the treatment periods of all of the available trials, the estimated rate ratios of overall and nocturnal hypoglycemia were significantly decreased with insulin degludec compared with insulin glargine or insulin detemir in patients with T1D or T2D; the differences in the risks for severe hypoglycemia were not significant. IMPLICATIONS: Compared with other long-acting insulin analogues (insulin glargine and insulin detemir), insulin degludec was associated with a significantly decreased FPG, with lower prevalences of overall and nocturnal hypoglycemia.
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Diabetes Mellitus Tipo 1 , Diabetes Mellitus Tipo 2 , Hipoglicemia , Humanos , Diabetes Mellitus Tipo 2/tratamento farmacológico , Insulina Glargina/efeitos adversos , Insulina Detemir/efeitos adversos , Diabetes Mellitus Tipo 1/tratamento farmacológico , Hipoglicemiantes/efeitos adversos , Insulina de Ação Prolongada/efeitos adversos , Hipoglicemia/induzido quimicamente , Hipoglicemia/epidemiologia , Hemoglobinas Glicadas , GlicemiaRESUMO
Deep learning has brought a rapid development in the aspect of molecular representation for various tasks, such as molecular property prediction. The prediction of molecular properties is a crucial task in the field of drug discovery for finding specific drugs with good pharmacological activity and pharmacokinetic properties. SMILES string is always used as a kind of character approach in deep neural network models, inspired by natural language processing techniques. However, the deep learning models are hindered by the nonunique nature of the SMILES string. To efficiently learn molecular features along all message paths, in this paper we encode multiple SMILES for every molecule as an automated data augmentation for the prediction of molecular properties, which alleviates the overfitting problem caused by the small amount of data in the datasets of molecular property prediction. As a result, by using the multiple SMILES-based augmentation, we obtained better molecular representation and showed superior performance in the tasks of predicting molecular properties.
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Aprendizado Profundo , Redes Neurais de ComputaçãoRESUMO
OBJECTIVE: Our study aimed to assess the existing evidence on whether serum uric acid (SUA) levels are associated with diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). METHODS: We conducted a systematic search of articles up to October 2021 in Medline, Embase, The Cochrane Library and Web of Science that estimated DKD by SUA levels in patients with T2DM. Pooled relative risks with 95% CI were calculated using random effects models RESULTS: A total of eight cohort studies involving 25,741 T2DM patients were included. Meta-analysis showed that compared the highest with the lowest category of SUA level, the summary risk ratios were 2.04 (95%CI 1.43-2.92, P < 0.001). The linear dose-response analysis revealed that the risk of DKD increased by 24% for each 1 mg/dl increase of SUA. The non-linear dose-response analysis also showed a significant relevance between SUA and the risk of DKD in patients with type 2 diabetes mellitus (P < 0.001). CONCLUSIONS: Serum uric acid is associated with an increased risk of diabetic kidney disease in patients with type 2 diabetes mellitus. Serum uric acid level could be a good indicator for predicting diabetic kidney disease in patients with type 2 diabetes mellitus.
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Diabetes Mellitus Tipo 2 , Nefropatias Diabéticas , Ácido Úrico , Estudos de Coortes , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/epidemiologia , Nefropatias Diabéticas/diagnóstico , Nefropatias Diabéticas/epidemiologia , Humanos , Fatores de Risco , Ácido Úrico/sangueRESUMO
Objective: Pretreatment with hydrocortisone (prehydrocortisone) has been used to protect against adverse drug reactions (ADRs) following antivenom administration after snakebite. However, controversial results have been reported in studies evaluating its efficacy. Herein, we conducted a meta-analysis to evaluate the effect of prehydrocortisone on the risk of ADRs. Methods: We conducted a systematic search of PubMed, Embase, and Cochrane for relevant studies on the literature published up to December 6, 2020, with no language restrictions. Premedications, including hydrocortisone with or without other drugs, were compared with placebo or no premedication. Our primary end point was the risk of ADRs, which was reported as the number of patients who developed ADRs divided by the total number of snakebite patients administered with antivenom separately for the prehydrocortisone and control groups for each study. We evaluated pooled data using of a random-effects model. Results: Among 831 identified studies, 4 were eligible and included in our analysis (N = 1348 participants). Upon combining all eight comparisons from the four selected studies, the overall pooled odds ratio (OR) for ADRs was 0.47 (95% CI 0.19, 1.17; p=0.11; I 2 = 68%). When the analysis was restricted to only articles using hydrocortisone with other drugs, the pooled OR was 0.19 (95% CI 0.05, 0.75; p=0.02; I 2 = 55%). The result was not statistically significant when the analysis was restricted to studies using prehydrocortisone alone, or randomized controlled designs, or cohorts. Our study was limited by heterogeneity, quality, and a paucity of data. Conclusions: The findings in this study revealed that prehydrocortisone alone was ineffective. However, the substantial beneficial effect of prehydrocortisone combinations with premedications (injectable antihistamines or adrenaline) used against ADRs cannot be excluded. Therefore, the use of prehydrocortisone combinations with premedications (injectable antihistamines or adrenaline) as a prophylaxis may reduce the ADRs to antivenom.
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PURPOSE: Acute respiratory distress syndrome (ARDS) is a rapidly progressive diffuse lung injury that is characterized by high mortality and acute onset. The pathological mechanisms of ARDS are still unclear. But alveolar macrophages have been shown to play an important role in inflammatory responses during ARDS. We aimed to find the biomarkers for ARDS for early diagnosis, to give ARDS patients timely treatment. METHODS: Gene expression profiles were downloaded from Gene Expression Omnibus (GEO) and screened for differentially expressed genes (DEGs). The common upregulated genes in all the datasets were defined as circulating ARDS alveolar macrophage-related genes (cARDSAMGs). We performed a functional enrichment analysis to explore potential biological functions of cARDSAMGs, and we built protein-protein interaction networks. Gene set variation analysis (GSVA) was used to calculate the core gene set variation analysis (CGSVA) score for individual samples. Receiver operating characteristic (ROC) curve analysis was applied on the CGSVA score to evaluate its ability for diagnosis of ARDS. RESULTS: A total of 60 genes were upregulated in all ARDS datasets and were therefore denominated as cARDSAMGs. The cARDSAMGs were significantly involved in multiple inflammation-, immunity- and phagocytosis-related biological processes and pathways. In the protein-protein interaction network associated with host responses to ADRS, eight genes were identified as a core gene set: PTCRA, JAG1, C1QB, ADAM17, C1QA, MMP9, VSIG4 and TNFAIP3. ROC curve analysis showed that the CGSVA score may be considered as a biomarker for ARDS: it was significantly higher in patients with ARDS than those in healthy in both alveolar lavage fluid and whole blood. CONCLUSION: The ARDS alveolar macrophage-related CGSVA score may be useful as a biomarker for ARDS.
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OBJECTIVE: Sepsis is a disease associated with high mortality. We performed bioinformatic analysis to identify key biomarkers associated with sepsis and septic shock. METHODS: The top 20% of genes showing the greatest variance between sepsis and controls in the GSE13904 dataset (children) were screened by co-expression network analysis. The differentially expressed genes (DEGs) were identified through analyzing differential gene expression between sepsis patients and control in the GSE13904 (children) and GSE154918 (adult) data sets. Intersection analysis of module genes and DEGs was performed to identify common DEGs for enrichment analysis, protein-protein interaction network (PPI network) analysis, and Short Time-series Expression Miner (STEM) analysis. The PPI network genes were ranked by degree of connectivity, and the top 100 sepsis-associated genes were identified based on the area under the receiver operating characteristic curve (AUC). In addition, we evaluated differences in immune cell infiltration between sepsis patients and controls in children (GSE13904, GSE25504) and adults (GSE9960, GSE154918). Finally, we analyzed differences in DNA methylation levels between sepsis patients and controls in GSE138074 (adults). RESULTS: The common genes were associated mainly with up-regulated inflammatory and metabolic responses, as well as down-regulated immune responses. Sepsis patients showed lower infiltration by most types of immune cells. Genes in the PPI network with AUC values greater than 0.9 in both GSE13904 (children) and GSE154918 (adults) were screened as key genes for diagnosis. These key genes (MAPK14, FGR, RHOG, LAT, PRKACB, UBE2Q2, ITK, IL2RB, and CD247) were also identified in STEM analysis to be progressively dysregulated across controls, sepsis patients and patients with septic shock. In addition, the expression of MAPK14, FGR, and CD247 was modified by methylation. CONCLUSION: This study identified several potential diagnostic genes and inflammatory and metabolic responses mechanisms associated with the development of sepsis.
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PURPOSE: Early diagnosis of sepsis-induced acute respiratory distress syndrome (ARDS) is critical for effective treatment. We aimed to identify early stage biomarkers. MATERIALS AND METHODS: Differentially expressed genes were identified in whole blood samples from patients with sepsis or ARDS based on the Gene Expression Omnibus (GEO) datasets GSE32707, GSE54514 and GSE10361. Functional enrichment analysis explored the biological characteristics of differentially expressed genes. Genes with high functional connectivity based on a protein-protein interaction network were marked as hub genes, which were validated using the GEO dataset GSE76293, and a gene set variation analysis index (GSVA) was assigned. Diagnostic and predictive ability of the hub genes were assessed by receiver operating characteristic (ROC) curve analysis. DNA methylation levels of hub genes were quantified using the GEO dataset GSE67530. RESULTS: Forty-one differentially expressed genes were shared between sepsis-specific and ARDS-specific datasets. MAP2K2 and IRF7 functional activity was highly connected in sepsis-induced ARDS. Hub genes included RETN, MVP, DEFA4, CTSG, AZU1, FMNL1, RBBP7, POLD4, RIN3, IRF7. ROC curve analysis of the hub gene GSVA index showed good diagnostic ability in sepsis or ARDS. Among genes related to sepsis-induced ARDS, 17 were differentially methylated. Principal component analysis and heatmaps indicated that gene methylation patterns differed significantly between ARDS patients and controls. CONCLUSION: We identified a genetic profile specific to early-stage sepsis-induced ARDS. The abnormal expression of these genes may be caused by hypomethylation, which may serve as a biomarker for early diagnosis of ARDS.
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BACKGROUND: Neighboring gene pairs in the genome of Saccharomyces cerevisiae have a tendency to be expressed at the same time. The distribution of histone modifications along chromatin fibers is suggested to be an important mechanism responsible for such coexpression. However, the extent of the contribution of histone modifications to the coexpression of neighboring genes is unclear. RESULTS: We investigated the similarity of histone modification between neighboring genes using autocorrelation analysis and composite profiles. Our analysis showed that neighboring genes had similar levels or changes of histone modifications, especially those transcribed in the same direction. The similarities, however, were restricted to 1 or 2 neighboring genes. Moreover, the expression of a gene was significantly correlated with histone modification of its neighboring gene(s), but this was limited to only 1 or 2 neighbors. Using a hidden Markov model (HMM), we found more than 2000 chromatin domains with similar acetylation changes as the cultures changed and a considerable number of these domains covered 2-4 genes. Gene pairs within domains exhibited a higher level of coexpression than random pairs and shared similar functions. CONCLUSIONS: The results of this study suggest that similar histone modifications occur within only a small local chromatin region in yeast. The modifications generally have an effect on coexpression with only 1 or 2 neighboring genes. Some blocking mechanism(s) might strictly restrain the distribution of histone modifications in yeast.
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Regulação Fúngica da Expressão Gênica , Genoma Fúngico/genética , Histonas/metabolismo , Processamento de Proteína Pós-Traducional/genética , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Acetilação , Cromatina/metabolismo , Cromossomos Fúngicos/metabolismo , Genes Fúngicos/genética , Lisina/metabolismoRESUMO
BACKGROUND: Recently, a number of high-resolution genome-wide maps of nucleosome locations in S. cerevisiae have been derived experimentally. However, nucleosome positions are determined in vivo by the combined effects of numerous factors. Consequently, nucleosomes are not simple static units, which may explain the discrepancies in reported nucleosome positions as measured by different experiments. In order to more accurately depict the genome-wide nucleosome distribution, we integrated multiple nucleosomal positioning datasets using a multi-angle analysis strategy. RESULTS: To evaluate the contribution of chromatin structure to transcription, we used the vast amount of available nucleosome analyzed data. Analysis of this data allowed for the comprehensive identification of the connections between promoter nucleosome positioning patterns and various transcription-dependent properties. Further, we characterised the function of nucleosome destabilisation in the context of transcription regulation. Our results indicate that genes with similar nucleosome occupancy patterns share general transcription attributes. We identified the local regulatory correlation (LRC) regions for two distinct types of nucleosomes and we assessed their regulatory properties. We also estimated the nucleosome reproducibility and measurement accuracy for high-confidence transcripts. We found that by maintaining a distance of approximately 13 bp between the upstream border of the +1 nucleosome and the transcription start sites (TSSs), the stable +1 nucleosome may form a barrier against the accessibility of the TSS and shape an optimum chromatin conformation for gene regulation. An in-depth analysis of nucleosome positioning in normally growing and heat shock cells suggested that the extent and patterns of nucleosome sliding are associated with gene activation. CONCLUSIONS: Our results, which combine different types of data, suggest that cross-platform information, including discrepancy and consistency, reflects the mechanisms of nucleosome packaging in vivo more faithfully than individual studies. Furthermore, nucleosomes can be divided into two classes according to their stable and dynamic characteristics. We found that two different nucleosome-positioning characteristics may significantly impact transcription programs. Besides, some positioned-nucleosomes are involved in the transition from stable state to dynamic state in response to abrupt environmental changes.
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Biologia Computacional/métodos , Nucleossomos/genética , Saccharomyces cerevisiae/genética , Regulação Fúngica da Expressão Gênica , Genoma Fúngico , Modelos Genéticos , Regiões Promotoras Genéticas , Sítio de Iniciação de TranscriçãoRESUMO
BACKGROUND: The incidence of sepsis has been increasing in recent years. The molecular mechanism of different pathogenic sepsis remains elusive, and biomarkers of sepsis against different pathogens are still lacking. METHODS: The microarray data of bacterial sepsis, fungal sepsis, and mock-treated samples were applied to perform differentially expressed gene (DEG) analysis to identify a bacterial sepsis-specific gene set and a fungal sepsis-specific gene set. Functional enrichment analysis was used to explore the body's response to bacterial sepsis and fungal sepsis. Gene set variation analysis (GSVA) was used to score individual samples against the two pathogen-specific gene sets, and each sample gets a GSVA index. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of sepsis. An independent data set was used to validate the bacterial sepsis-specific GSVA index. RESULTS: The genes differentially expressed only in bacterial sepsis and the genes differentially expressed only in fungal sepsis were significantly involved in different biological processes (BPs) and pathways. This indicated that the body's responses to fungal sepsis and bacterial sepsis are varied. Twenty-two genes were identified as bacterial sepsis-specific genes and upregulated in bacterial sepsis, and 23 genes were identified as fungal sepsis-specific genes and upregulated in fungal sepsis. ROC curve analysis showed that both of the two pathogen sepsis-specific GSVA indexes may be a reliable biomarker for corresponding pathogen-induced sepsis (AUC = 1.000), while the mRNA of CALCA (also known as PCT) have a poor diagnostic value with AUC = 0.512 in bacterial sepsis and AUC = 0.705 in fungi sepsis. In addition, the AUC of the bacterial sepsis-specific GSVA index in the independent data set was 0.762. CONCLUSION: We proposed a bacterial sepsis-specific gene set and a fungal sepsis-specific gene set; the bacterial sepsis GSVA index may be a reliable biomarker for bacterial sepsis.
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Bacteriemia , Fungemia , Transcriptoma , Bacteriemia/genética , Bacteriemia/imunologia , Bacteriemia/metabolismo , Biomarcadores/análise , Biomarcadores/metabolismo , Peptídeo Relacionado com Gene de Calcitonina/análise , Peptídeo Relacionado com Gene de Calcitonina/genética , Peptídeo Relacionado com Gene de Calcitonina/metabolismo , Fungemia/genética , Fungemia/imunologia , Fungemia/metabolismo , Humanos , Curva ROC , Transcriptoma/genética , Transcriptoma/imunologiaRESUMO
Accurate diagnosis of sepsis remains challenging, new markers or combinations of markers are urgently needed. In the present study, we screened differentially expressed genes (DEGs) between sepsis and non-sepsis blood samples across three previously published gene expression data sets. Common upregulated and downregulated DEGs were ranked according to their average functional similarity. The ten genes (OLFM4, ORM1, CEP55, S100A12, S100P, LRG1, CEACAM8, MS4A4A, PLSCR1, and IL1R2) with the largest average functional similarity among the common upregulated genes and another ten genes (THEMIS, IL2RB, CD2, IL7R, CD3E, KLRB1, PVRIG, CCRR3, TGFBR3, and PLEKHA1) with the largest average functional similarity among the common downregulated genes were separately identified as the upregulated crucial gene set and the downregulated crucial gene set. Gene set variation analysis (GSVA) was used to obtain the GSVA index of each sample against the two crucial gene sets. Both the two crucial GSVA indexes may be robust markers for sepsis with high area under ROC curve. The diagnostic utility of the upregulated GSVA index was validated in another independent data set. Functional analyses revealed several sepsis-related pathways. In conclusion, we proposed two sepsis-related gene sets across multiple data sets and created two GSVA indexes with promising diagnostic value.
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BACKGROUND: Nucleosomes regulate DNA accessibility and therefore play a central role in transcription control. Computational methods have been developed to predict static nucleosome positions from DNA sequences, but nucleosomes are dynamic in vivo. RESULTS: Motivated by our observation that transcriptional interaction is discriminative information for nucleosome occupancy, we developed a novel computational approach to identify dynamic nucleosome positions at promoters by combining transcriptional interaction and genomic sequence information. Our approach successfully identified experimentally determined nucleosome positioning dynamics available in three cellular conditions, and significantly improved the prediction accuracy which is based on sequence information alone. We then applied our approach to various cellular conditions and established a comprehensive landscape of dynamic nucleosome positioning in yeast. CONCLUSION: Analysis of this landscape revealed that the majority of nucleosome positions are maintained during most conditions. However, nucleosome occupancy at most promoters fluctuates with the corresponding gene expression level and is reduced specifically at the phase of peak expression. Further investigation into properties of nucleosome occupancy identified two gene groups associated with distinct modes of nucleosome modulation. Our results suggest that both the intrinsic sequence and regulatory proteins modulate nucleosomes in an altered manner.