Deciphering the dynamic changes in antibodies against SARS-CoV-2 is essential for understanding the immune response in COVID-19 patients. Here we analyze the laboratory findings of 1,850 patients to ...describe the dynamic changes of the total antibody, spike protein (S)-, receptor-binding domain (RBD)-, and nucleoprotein (N)-specific immunoglobulin M (IgM) and G (IgG) levels during SARS-CoV-2 infection and recovery. The generation of S-, RBD-, and N-specific IgG occurs one week later in patients with severe/critical COVID-19 compared to patients with mild/moderate disease, while S- and RBD-specific IgG levels are 1.5-fold higher in severe/critical patients during hospitalization. The RBD-specific IgG levels are 4-fold higher in older patients than in younger patients during hospitalization. In addition, the S- and RBD-specific IgG levels are 2-fold higher in the recovered patients who are SARS-CoV-2 RNA negative than those who are RNA positive. Lower S-, RBD-, and N-specific IgG levels are associated with a lower lymphocyte percentage, higher neutrophil percentage, and a longer duration of viral shedding. Patients with low antibody levels on discharge might thereby have a high chance of being tested positive for SARS-CoV-2 RNA after recovery. Our study provides important information for COVID-19 diagnosis, treatment, and vaccine development.
Patients with diabetes mellitus (DM) have a higher incidence of malignant tumors than people without diabetes, but the underlying molecular mechanisms are still unclear.
To investigate the link ...between DM and cancer, we screened publicly available databases for diabetes and cancer-related genes (DCRGs) and constructed a diabetes-based cancer-associated inflammation network (DCIN). We integrated seven DCRGs into the DCIN and analyzed their role in different tumors from various perspectives. We also investigated drug sensitivity and single-cell sequencing data in colon adenocarcinoma as an example. In addition, we performed
experiments to verify the expression of DCRGs and the arachidonic acid metabolic pathway.
Seven identified DCRGs, including
,
,
,
,
,
, and
, were integrated to construct a DCIN. The bioinformatics analysis showed that the expression of the seven DCRGs in different tumors was significantly different, which had varied effects on diverse perspectives. Single-cell sequencing analyzed in colon cancer showed that the activity of the DCRGs was highest in Macrophage and the lowest in B cells among all cell types in adenoma and carcinoma tissue.
experiments showed that the DCRGs verified by western bolt and
verified by ELISA were all highly expressed in COAD epithelial cells stimulated by high glucose.
This study, for the first time, constructed a DCIN, which provides novel insights into the underlying mechanism of how DM increases tumor occurrence and development. Although further research is required, our results offer clues for new potential therapeutic strategies to prevent and treat malignant tumors.
Coronavirus disease 2019 (COVID-19) is a respiratory disorder caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which had rapidly spread all over the world and caused public ...health emergencies in the past two years. Although the diagnosis and treatment for COVID-19 have been well defined, the immune cell characteristics and the key lymphocytes subset alterations in COVID-19 patients have not been thoroughly investigated. The levels of immune cells including T cells, B cells, and natural killer (NK) cells in 548 hospitalized COVID-19 patients, and 30 types of lymphocyte subsets in 125 hospitalized COVID-19 patients admitted to Wuhan Huoshenshan Hospital of China were measured using flow cytometry. The relationship between lymphocytes subsets with the cytokine interleukin-6 (IL-6) and the characteristics of lymphocyte subsets in single-cell RNA sequencing (scRNA-seq) data obtained from peripheral blood mononuclear cells (PBMCs) were also analysed in COVID-19 patients. In this study, we found that patients with critical COVID-19 infection exhibited an overall decline in lymphocytes including CD4.sup.+ T cells, CD8.sup.+ T cells, total T cells, B cells, and NK cells compared to mild and severe patients. However, the number of lymphocyte subsets, such as CD21.sup.low CD38.sup.low B cells, effector T4 cells, and PD1.sup.+ depleted T8 cells, was moderately increased in critical COVID-19 patients compared to mild cases. Notably, except for effector memory T4 cells, plasma blasts and Tregs, the number of all lymphocyte subsets was markedly decreased in COVID-19 patients with IL-6 levels over 30-fold higher than those in healthy cases. Moreover, scRNA-seq data showed obvious differences in the distribution and numbers of lymphocyte subsets between COVID-19 patients and healthy persons, and subsets-specific marker genes of lymphocyte subsets including CD4, CD19, CCR7, and IL7R, were markedly decreased in COVID-19 patients compared with those in healthy cases. A comprehensive decrease in immune cell and lymphocyte subsets in critical COVID-19 patients, and peripheral lymphocyte subset alterations showed a clear association with clinical characteristics.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background Aortic diseases remain a highly perilous macrovascular condition. The relationship between circulating aldosterone and aortic diseases is rarely explored, thus we investigated the ...difference in plasma aldosterone concentration (PAC) between patients with and without aortic disease in hypertensive people. Methods We analyzed 926 patients with hypertension, ranging in age from 18 to 89 years, who had their PAC measured from the hospital's electronic database. The case group and control group were defined based on inclusion and exclusion criteria. The analysis included general information, clinical data, biochemical data, and medical imaging examination results as covariates. To further evaluate the difference in PAC between primary hypertension patients with aortic disease and those without, we used multivariate logistic regression analysis and also employed propensity score matching to minimize the influence of confounding factors. Results In total, 394 participants were included in the analysis, with 66 individuals diagnosed with aortic diseases and 328 in the control group. The participants were predominantly male (64.5%) and over the age of 50 (68.5%), with an average PAC of 19.95 ng/dL. After controlling for confounding factors, the results showed hypertension patients with aortic disease were more likely to have high PAC levels than those without aortic disease (OR = 1.138, 95% CI 1.062 to 1.238). Subgroup analysis revealed consistent relationship between PAC and primary hypertensive patients with aortic disease across the different stratification variables. Additionally, hypertensive patients with aortic disease still have a risk of higher PAC levels than those without aortic disease, even after propensity score matching. Conclusions The results of this study suggest that primary hypertensive patients with aortic diseases have elevated levels of PAC, but the causal relationship between PAC and aortic disease requires further study. Keywords: Aortic diseases, Aldosterone, Hypertension, Aortic dissection
How does SARS-CoV-2 cause lung microenvironment disturbance and inflammatory storm is still obscure. We here performed the single-cell transcriptome sequencing from lung, blood, and bone marrow of ...two dead COVID-19 patients and detected the cellular communication among them. Our results demonstrated that SARS-CoV-2 infection increase the frequency of cellular communication between alveolar type I cells (AT1) or alveolar type II cells (AT2) and myeloid cells triggering immune activation and inflammation microenvironment and then induce the disorder of fibroblasts, club, and ciliated cells, which may cause increased pulmonary fibrosis and mucus accumulation. Further study showed that the increase of T cells in the lungs may be mainly recruited by myeloid cells through ligands/receptors (e.g., ANXA1/FPR1, C5AR1/RPS19, and CCL5/CCR1). Interestingly, we also found that certain ligands/receptors (e.g., ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1) are significantly activated and shared among lungs, blood and bone marrow of COVID-19 patients, implying that the dysregulation of ligands/receptors may lead to immune cell's activation, migration, and the inflammatory storm in different tissues of COVID-19 patients. Collectively, our study revealed a possible mechanism by which the disorder of cell communication caused by SARS-CoV-2 infection results in the lung inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.
Objective:
This study aimed to distinguish the risk variables of nonalcoholic fatty liver disease (NAFLD) and to construct a prediction model of NAFLD in visceral fat obesity in Japanese adults.
...Methods
This study is a historical cohort study that included 1,516 individuals with visceral obesity. All individuals were randomly divided into training group and validation group at 70% (
n
= 1,061) and 30% (
n
= 455), respectively. The LASSO method and multivariate regression analysis were performed for selecting risk factors in the training group. Then, overlapping features were selected to screen the effective and suitable risk variables for NAFLD with visceral fatty obesity, and a nomogram incorporating the selected risk factors in the training group was constructed. Then, we used the C-index, calibration plot, decision curve analysis, and cumulative hazard analysis to test the discrimination, calibration, and clinical meaning of the nomogram. At last, internal validation was used in the validation group.
Results
We contract a nomogram and validated it using easily available and cost-effective parameters to predict the incidence of NAFLD in participants with visceral fatty obesity, including ALT, HbA1c, body weight, FPG, and TG. In training cohort, the area under the ROC was 0.863, with 95% CI: 0.84–0.885. In validation cohort, C-index was 0.887, with 95%CI: 0.857–0.888. The decision curve analysis showed that the model's prediction is more effective. Decision curve analysis of the training cohort and validation cohort showed that the predictive model was more effective in predicting the risk of NAFLD in Japanese patients with visceral fatty obesity. To help researchers and clinicians better use the nomogram, our online version can be accessed at
https://xy2yyjzyxk.shinyapps.io/NAFLD/
.
Conclusions
Most patients with visceral fatty obesity have a risk of NALFD, but some will not develop into it. The presented nomogram can accurately identify these patients at high risk.
OBJECTIVE To identify differentially expressed microRNA (miRNA) in peripheral blood mononuclear cells (PBMCs) of anxiety patients and predict their target genes and function by bioinformatics ...analysis. METHODS The miRNA expression profiles were determined using an Affymetrix array. To validate the results, real-time quantitative polymerase chain reaction (qRT-PCR) analysis in a larger cohort was employed. The targets of the differentially expressed miRNAs were predicted by Target Scan, miRBD, and DIANA-microT-CDS, and the results were analyzed by gene ontology (GO) and KEGG pathway analysis using FunNet. RESULTS MicroRNA microarray chip analysis has identified 7 miRNAs were detected with significant changes in expression in PBMCs of anxiety patients. qRT-PCR analysis has confirmed that the expression levels of 5 miRNAs (has-miR-4484, has-miR-4505, has-miR-4674, has-miR-501-3p and has-miR-663) were up-regulated. Intersecting the genes by Target Scan, miRBD, and DIANA-microT-CDS has predicted 195 targets. GO an
Two case series examining the impact of convalescent plasma on patients with COVID-19 suggest some clinical benefit from early administration and modest impact on parameters of inflammation. Further ...assessment of the impact of this intervention awaits controlled clinical trials.
The determination of biological mechanisms and biomarkers related to intracranial aneurysm (IA) rupture is of utmost significance for the development of effective preventive and therapeutic ...strategies in the clinical field.
GSE122897 and GSE13353 datasets were downloaded from Gene Expression Omnibus. Data extracted from GSE122897 were used for analyzing differential gene expression, and consensus clustering was performed to identify stable molecular subtypes. Clinical characteristics were compared between subgroups, and fast gene set enrichment analysis and weighted gene coexpression network analysis were performed. Hub genes were identified via least absolute shrinkage and selection operator analysis. Predictive models were constructed based on hub genes using the Light Gradient Boosting Machine, eXtreme Gradient Boosting, and logistic regression algorithm. Immune cell infiltration in IA samples was analyzed using Microenvironment Cell Population counter, CIBERSORT, and xCell algorithm. The correlation between hub genes and immune cells was analyzed. The predictive model and immune cell infiltration were validated using data from the GSE13353 dataset.
A total of 43 IA samples were classified into 2 subgroups based on gene expression profiles. Subgroup I had a higher risk of rupture, while 70% of subgroup II remained unruptured. In subgroup I, specific genes were associated with inflammation and immunity, and weighted gene coexpression network analysis revealed that the black module genes were linked to IA rupture. We identified 4 hub genes (spermine synthase, macrophage receptor with collagenous structure, zymogen granule protein 16B, and LIM and calponin-homology domains 1), which constructed predictive models with good diagnostic performance in differentiating between ruptured and unruptured IA samples. Monocytic lineage was found to be a significant factor in IA rupture, and the 4 hub genes were linked to monocytic lineage (P < 0.05).
We reveal a new molecular subtype that can reflect the actual pathological state of IA rupture, and our predictive models constructed by machine learning algorithms can efficiently predict IA rupture.
•Daily step counts showed a significant association with all-cause mortality in patients with CHF.•Patients with CHF who achieve a daily step count of 5581 may reduce the risk of all-cause ...mortality.•A significant association between step counts and all-cause mortality was observed in male patients with CHF.
There is a lack of understanding of how daily step counts differentially affect the risk of all-cause mortality in adult with congestive heart failure (CHF) by sex in the United States (US).
To explore the relationship between daily step counts and all-cause mortality in patients with CHF by sex.
This is a cohort analysis from the National Health and Nutrition Examination Survey from 2005 to 2006. Multiple Cox hazard regression was performed to explore the association of step counts and all-cause mortality in patients with CHF by sex.
In this study, 363 unweighted samples were enrolled from NHANES 2005–2006, representing about 8.4 million of the US population. Further, 46.28% were women, and the average age was 46 years. Patients with CHF in the more than 5581 steps/day group (HR, 0.31 95% CI, 0.16–0.58) had a significantly reduced risk of all-cause mortality compared with the patients in the less 5581 steps/day group after accounting for all covariates. In men, after accounting for all the covariates, there was a significant difference in more than 5581 steps/day group (HR, 0.33 95% CI, 0.14–0.76) on all-cause mortality in men with CHF compared with men in the less than 5581 steps/day group.
Step count is associated with all-cause mortality in patients with CHF. Taking 5581 daily steps was associated with a decreased risk of all-cause mortality in patients with CHF.
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