scholarly journals A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples

2022 ◽  
Vol 9 ◽  
Author(s):  
Shangming Du ◽  
Ulrich Mansmann ◽  
Benjamin P. Geisler ◽  
Yingxia Li ◽  
Roman Hornung
Keyword(s):  
Kawasaki Disease ◽  
Chemokine Receptors ◽  
Immune Cell ◽  
Learning Algorithm ◽  
External Validation ◽  
Cell Types ◽  
Diagnostic Model ◽  
Lasso Regression ◽  
Blood Samples ◽  
Diagnostic Score

Background: Kawasaki disease (KD) is the leading cause of acquired heart disease in children. However, distinguishing KD from febrile infections early in the disease course remains difficult. Our goal was to estimate the immune cell composition in KD patients and febrile controls (FC), and to develop a tool for KD diagnosis.Methods: We used a machine-learning algorithm, CIBERSORT, to estimate the proportions of 22 immune cell types based on blood samples from children with KD and FC. Using these immune cell compositions, a diagnostic score for predicting KD was then constructed based on LASSO regression for binary outcomes.Results: In the training set (n = 496), a model was fit which consisted of eight types of immune cells. The area under the curve (AUC) values for diagnosing KD in a held-out test set (n = 212) and an external validation set (n = 36) were 0.80 and 0.77, respectively. The most common cell types in KD blood samples were monocytes, neutrophils, CD4+-naïve and CD8+ T cells, and M0 macrophages. The diagnostic score was highly correlated to genes that had been previously reported as associated with KD, such as interleukins and chemokine receptors, and enriched in reported pathways, such as IL-6/JAK/STAT3 and TNFα signaling pathways.Conclusion: Altogether, the diagnostic score for predicting KD could potentially serve as a biomarker. Prospective studies could evaluate how incorporating the diagnostic score into a clinical algorithm would improve diagnostic accuracy further.

scholarly journals Krüppel-like Factor 2 (KLF2) in Immune Cell Migration

Vaccines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1171
Author(s):  
Jens Wittner ◽  
Wolfgang Schuh
Keyword(s):  
Transcription Factor ◽  
Cell Migration ◽  
Immune Responses ◽  
Adhesion Molecules ◽  
Chemokine Receptors ◽  
Immune Cell ◽  
Cell Types ◽  
Immune Cell Migration ◽  
Functional Relevance ◽  
And Migration

Krüppel-like factor 2 (KLF2), a transcription factor of the krüppel-like family, is a key regulator of activation, differentiation, and migration processes in various cell types. In this review, we focus on the functional relevance of KLF2 in immune cell migration and homing. We summarize the key functions of KLF2 in the regulation of chemokine receptors and adhesion molecules and discuss the relevance of the KLF2-mediated control of immune cell migration in the context of immune responses, infections, and diseases.

scholarly journals Interleukin-17 and Th17 Lymphocytes Directly Impair Motoneuron Survival of Wildtype and FUS-ALS Mutant Human iPSCs

2021 ◽  
Vol 22 (15) ◽  
pp. 8042
Author(s):  
Mengmeng Jin ◽  
Katja Akgün ◽  
Tjalf Ziemssen ◽  
Markus Kipp ◽  
Rene Günther ◽  
...  
Keyword(s):  
Motor Neurons ◽  
Th17 Cells ◽  
Immune Cell ◽  
Cell Types ◽  
Positive Control ◽  
Interleukin 17 ◽  
Fused In Sarcoma ◽  
Th17 Lymphocytes ◽  
Human Ipscs ◽  
Als Patients

Amyotrophic lateral sclerosis (ALS) is a progressive disease leading to the degeneration of motor neurons (MNs). Neuroinflammation is involved in the pathogenesis of ALS; however, interactions of specific immune cell types and MNs are not well studied. We recently found a shift toward T helper (Th)1/Th17 cell-mediated, pro-inflammatory immune responses in the peripheral immune system of ALS patients, which positively correlated with disease severity and progression. Whether Th17 cells or their central mediator, Interleukin-17 (IL-17), directly affects human motor neuron survival is currently unknown. Here, we evaluated the contribution of Th17 cells and IL-17 on MN degeneration using the co-culture of iPSC-derived MNs of fused in sarcoma (FUS)-ALS patients and isogenic controls with Th17 lymphocytes derived from ALS patients, healthy controls, and multiple sclerosis (MS) patients (positive control). Only Th17 cells from MS patients induced severe MN degeneration in FUS-ALS as well as in wildtype MNs. Their main effector, IL-17A, yielded in a dose-dependent decline of the viability and neurite length of MNs. Surprisingly, IL-17F did not influence MNs. Importantly, neutralizing IL-17A and anti-IL-17 receptor A treatment reverted all effects of IL-17A. Our results offer compelling evidence that Th17 cells and IL-17A do directly contribute to MN degeneration.

scholarly journals Development and Verification of a Deep Learning Algorithm to Evaluate Small-Bowel Preparation Quality

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1127
Author(s):  
Ji Hyung Nam ◽  
Dong Jun Oh ◽  
Sumin Lee ◽  
Hyun Joo Song ◽  
Yun Jeong Lim
Keyword(s):  
Deep Learning ◽  
Small Bowel ◽  
Scoring System ◽  
Operating Characteristic ◽  
Clinical Evidence ◽  
Learning Algorithm ◽  
Characteristic Curve ◽  
External Validation ◽  
Test Results ◽  
Deep Learning Algorithm

Capsule endoscopy (CE) quality control requires an objective scoring system to evaluate the preparation of the small bowel (SB). We propose a deep learning algorithm to calculate SB cleansing scores and verify the algorithm’s performance. A 5-point scoring system based on clarity of mucosal visualization was used to develop the deep learning algorithm (400,000 frames; 280,000 for training and 120,000 for testing). External validation was performed using additional CE cases (n = 50), and average cleansing scores (1.0 to 5.0) calculated using the algorithm were compared to clinical grades (A to C) assigned by clinicians. Test results obtained using 120,000 frames exhibited 93% accuracy. The separate CE case exhibited substantial agreement between the deep learning algorithm scores and clinicians’ assessments (Cohen’s kappa: 0.672). In the external validation, the cleansing score decreased with worsening clinical grade (scores of 3.9, 3.2, and 2.5 for grades A, B, and C, respectively, p < 0.001). Receiver operating characteristic curve analysis revealed that a cleansing score cut-off of 2.95 indicated clinically adequate preparation. This algorithm provides an objective and automated cleansing score for evaluating SB preparation for CE. The results of this study will serve as clinical evidence supporting the practical use of deep learning algorithms for evaluating SB preparation quality.

scholarly journals Single-cell map of diverse immune phenotypes in the acute myeloid leukemia microenvironment

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Rongqun Guo ◽  
Mengdie Lü ◽  
Fujiao Cao ◽  
Guanghua Wu ◽  
Fengcai Gao ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Immune Cell ◽  
Immune Surveillance ◽  
Cell Types ◽  
Developmental Trajectory ◽  
Significant Difference ◽  
Cell Phenotypes ◽  
Acute Myeloid

Abstract Background Knowledge of immune cell phenotypes, function, and developmental trajectory in acute myeloid leukemia (AML) microenvironment is essential for understanding mechanisms of evading immune surveillance and immunotherapy response of targeting special microenvironment components. Methods Using a single-cell RNA sequencing (scRNA-seq) dataset, we analyzed the immune cell phenotypes, function, and developmental trajectory of bone marrow (BM) samples from 16 AML patients and 4 healthy donors, but not AML blasts. Results We observed a significant difference between normal and AML BM immune cells. Here, we defined the diversity of dendritic cells (DC) and macrophages in different AML patients. We also identified several unique immune cell types including T helper cell 17 (TH17)-like intermediate population, cytotoxic CD4+ T subset, T cell: erythrocyte complexes, activated regulatory T cells (Treg), and CD8+ memory-like subset. Emerging AML cells remodels the BM immune microenvironment powerfully, leads to immunosuppression by accumulating exhausted/dysfunctional immune effectors, expending immune-activated types, and promoting the formation of suppressive subsets. Conclusion Our results provide a comprehensive AML BM immune cell census, which can help to select pinpoint targeted drug and predict efficacy of immunotherapy.

scholarly journals Alveolar compartmentalization of inflammatory and immune cell biomarkers in pneumonia-related ARDS

Critical Care ◽  
2021 ◽  
Vol 25 (1) ◽  
Author(s):  
Inès Bendib ◽  
Asma Beldi-Ferchiou ◽  
Frédéric Schlemmer ◽  
Mathieu Surenaud ◽  
Bernard Maitre ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Hospital Mortality ◽  
Distress Syndrome ◽  
Immune Cell ◽  
Routine Care ◽  
Clinical Endpoint ◽  
Blood Samples ◽  
Hla Dr ◽  
Serum Ratio ◽  
Immunocompetent Patients

Abstract Background Biomarkers of disease severity might help individualizing the management of patients with the acute respiratory distress syndrome (ARDS). Whether the alveolar compartmentalization of biomarkers has a clinical significance in patients with pneumonia-related ARDS is unknown. This study aimed at assessing the interrelation of ARDS/sepsis biomarkers in the alveolar and blood compartments and explored their association with clinical outcomes. Methods Immunocompetent patients with pneumonia-related ARDS admitted between 2014 and 2018 were included in a prospective monocentric study. Bronchoalveolar lavage (BAL) fluid and blood samples were obtained within 48 h of admission. Twenty-two biomarkers were quantified in BAL fluid and serum. HLA-DR+ monocytes and CD8+ PD-1+ lymphocytes were quantified using flow cytometry. The primary clinical endpoint of the study was hospital mortality. Patients undergoing a bronchoscopy as part of routine care were included as controls. Results Seventy ARDS patients were included. Hospital mortality was 21.4%. The BAL fluid-to-serum ratio of IL-8 was 20 times higher in ARDS patients than in controls (p < 0.0001). ARDS patients with shock had lower BAL fluid-to-serum ratio of IL-1Ra (p = 0.026), IL-6 (p = 0.002), IP-10/CXCL10 (p = 0.024) and IL-10 (p = 0.023) than others. The BAL fluid-to-serum ratio of IL-1Ra was more elevated in hospital survivors than decedents (p = 0.006), even after adjusting for SOFA and driving pressure (p = 0.036). There was no significant association between alveolar or alveolar/blood monocytic HLA-DR or CD8+ lymphocytes PD-1 expression and hospital mortality. Conclusions IL-8 was the most compartmentalized cytokine and lower BAL fluid-to-serum concentration ratios of IL-1Ra were associated with hospital mortality in patients with pneumonia-associated ARDS.

scholarly journals Implications of hematopoietic stem cells heterogeneity for gene therapies

Gene Therapy ◽  
2021 ◽  
Author(s):  
Jeremy Epah ◽  
Richard Schäfer
Keyword(s):  
Immune Cell ◽  
Ex Vivo ◽  
Bone Marrow Failure ◽  
Cell Types ◽  
Blood Disorders ◽  
Hematopoietic Stem ◽  
Therapeutic Concept ◽  
Gene Therapies ◽  
Bone Marrow Failure Syndromes ◽  
Immunodeficiency Syndrome

AbstractHematopoietic stem cell transplantation (HSCT) is the therapeutic concept to cure the blood/immune system of patients suffering from malignancies, immunodeficiencies, red blood cell disorders, and inherited bone marrow failure syndromes. Yet, allogeneic HSCT bear considerable risks for the patient such as non-engraftment, or graft-versus host disease. Transplanting gene modified autologous HSCs is a promising approach not only for inherited blood/immune cell diseases, but also for the acquired immunodeficiency syndrome. However, there is emerging evidence for substantial heterogeneity of HSCs in situ as well as ex vivo that is also observed after HSCT. Thus, HSC gene modification concepts are suggested to consider that different blood disorders affect specific hematopoietic cell types. We will discuss the relevance of HSC heterogeneity for the development and manufacture of gene therapies and in exemplary diseases with a specific emphasis on the key target HSC types myeloid-biased, lymphoid-biased, and balanced HSCs.

484 Bioturing browser: interactively explore public single cell sequencing data

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A520-A520
Author(s):  
Son Pham ◽  
Tri Le ◽  
Tan Phan ◽  
Minh Pham ◽  
Huy Nguyen ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cell ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Cell Types ◽  
Sequencing Data ◽  
Single Cell Sequencing ◽  
Data Formats ◽  
Cancer Types ◽  
Cell Data

BackgroundSingle-cell sequencing technology has opened an unprecedented ability to interrogate cancer. It reveals significant insights into the intratumoral heterogeneity, metastasis, therapeutic resistance, which facilitates target discovery and validation in cancer treatment. With rapid advancements in throughput and strategies, a particular immuno-oncology study can produce multi-omics profiles for several thousands of individual cells. This overflow of single-cell data poses formidable challenges, including standardizing data formats across studies, performing reanalysis for individual datasets and meta-analysis.MethodsN/AResultsWe present BioTuring Browser, an interactive platform for accessing and reanalyzing published single-cell omics data. The platform is currently hosting a curated database of more than 10 million cells from 247 projects, covering more than 120 immune cell types and subtypes, and 15 different cancer types. All data are processed and annotated with standardized labels of cell types, diseases, therapeutic responses, etc. to be instantly accessed and explored in a uniform visualization and analytics interface. Based on this massive curated database, BioTuring Browser supports searching similar expression profiles, querying a target across datasets and automatic cell type annotation. The platform supports single-cell RNA-seq, CITE-seq and TCR-seq data. BioTuring Browser is now available for download at www.bioturing.com.ConclusionsN/A

Bacterial pore‐forming toxin pneumolysin: Cell membrane structure and microvesicle shedding capacity determines differential survival of immune cell types

2019 ◽  
Vol 34 (1) ◽  
pp. 1665-1678 ◽  
Author(s):  
Yu Larpin ◽  
Hervé Besançon ◽  
Mircea‐Ioan Iacovache ◽  
Victoriia S. Babiychuk ◽  
Eduard B. Babiychuk ◽  
...  
Keyword(s):  
Cell Membrane ◽  
Membrane Structure ◽  
Immune Cell ◽  
Cell Types ◽  
Differential Survival

scholarly journals Increased Density of Human Immunodeficiency Virus Type 1 Coreceptors CCR5 and CXCR4 on the Surfaces of CD4+ T Cells and Monocytes of Patients with Schistosoma mansoni Infection

2003 ◽  
Vol 71 (11) ◽  
pp. 6668-6671 ◽  
Author(s):  
W. Evan Secor ◽  
Amil Shah ◽  
Pauline M. N. Mwinzi ◽  
Bryson A. Ndenga ◽  
Caroline O. Watta ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
T Cells ◽  
Cell Surface ◽  
Human Immunodeficiency Virus Type ◽  
Virus Type ◽  
Peripheral Blood ◽  
Chemokine Receptors ◽  
Blood Samples ◽  
Immunodeficiency Virus

ABSTRACT Distribution of chemokine receptors CCR5 and CXCR4, which are also coreceptors for human immunodeficiency virus type 1 invasion of cells, was measured on the surfaces of CD4+ T cells and monocytes in peripheral blood samples from a group of Kenyan car washers. Patients with active schistosomiasis displayed higher cell surface densities of these receptors than did cured schistosomiasis patients.

scholarly journals Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tracy M. Yamawaki ◽  
Daniel R. Lu ◽  
Daniel C. Ellwanger ◽  
Dev Bhatt ◽  
Paolo Manzanillo ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Immune Cell ◽  
Cell Types ◽  
Data Interpretation ◽  
Detection Sensitivity ◽  
Rna Seq ◽  
Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

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