DNA Methylation signatures underpinning blood neutrophil to lymphocyte ratio during first week of human life.

Understanding of newborn immune ontogeny in the first week of life will enable age-appropriate strategies for safeguarding vulnerable newborns against infectious diseases. Here we conducted an observational study exploring the immunological profile of infants longitudinally throughout their first week of life. Our Expanded Program on Immunization - Human Immunology Project Consortium (EPIC-HIPC) studies the epigenetic regulation of systemic immunity using small volumes of peripheral blood samples collected from West African neonates on days of life (DOL) 0, 1, 3, and 7.

Breastfeeding and Neonatal Age Influence Neutrophil-Driven Ontogeny of Blood Cell Populations in the First Week of Human Life.

The first few days of life are characterized by rapid external and internal changes that require substantial immune system adaptations. Despite growing evidence of the impact of this period on lifelong immune health, this period remains largely uncharted. To identify factors that may impact the trajectory of immune development, we conducted stringently standardized, high-throughput phenotyping of peripheral white blood cell (WBC) populations from 796 newborns across two distinct cohorts (The Gambia, West Africa; Papua New Guinea, Melanesia) in the framework of a Human Immunology Project Consortium (HIPC) study.

MAGIC-DR: An interpretable machine-learning guided approach for acute myeloid leukemia measurable residual disease analysis.

Multiparameter flow cytometry is widely used for acute myeloid leukemia minimal residual disease testing (AML MRD) but is time consuming and demands substantial expertise. Machine learning offers potential advancements in accuracy and efficiency, but has yet to be widely adopted for this application. To explore this, we trained single cell XGBoost classifiers from 98 diagnostic AML cell populations and 30 MRD negative samples.

Recommendations for using artificial intelligence in clinical flow cytometry.

Flow cytometry is a key clinical tool in the diagnosis of many hematologic malignancies and traditionally requires close inspection of digital data by hematopathologists with expert domain knowledge. Advances in artificial intelligence (AI) are transferable to flow cytometry and have the potential to improve efficiency and prioritization of cases, reduce errors, and highlight fundamental, previously unrecognized associations with underlying biological processes. As a multidisciplinary group of stakeholders, we review a range of critical considerations for appropriately applying AI to clinical flow cytometry, including use case identification, low and high risk use cases, validation, revalidation, computational considerations, and the present regulatory frameworks surrounding AI in clinical medicine.

flowSim: Near duplicate detection for flow cytometry data.

The analysis of large amounts of data is important for the development of machine learning (ML) models. flowSim is the first algorithm designed to visualize, detect and remove highly redundant information in flow cytometry (FCM) training sets to decrease the computational time for training and increase the performance of ML algorithms by reducing overfitting. flowSim performs near duplicate image detection by combining community detection algorithms with the density analysis of the marker expression values.

Single-cell profiling reveals a memory B cell-like subtype of follicular lymphoma with increased transformation risk.

Follicular lymphoma (FL) is an indolent cancer of mature B-cells but with ongoing risk of transformation to more aggressive histology over time. Recurrent mutations associated with transformation have been identified; however, prognostic features that can be discerned at diagnosis could be clinically useful. We present here comprehensive profiling of both tumor and immune compartments in 155 diagnostic FL biopsies at single-cell resolution by mass cytometry.

flowCut: An R package for automated removal of outlier events and flagging of files based on time versus fluorescence analysis.

Technical artifacts such as clogging that occur during the data acquisition process of flow cytometry data can cause spurious events and fluorescence intensity shifting that impact the quality of the data and its analysis results. These events should be identified and potentially removed before being passed to the next stage of analysis. flowCut, an R package, automatically detects anomaly events in flow cytometry experiments and flags files for potential review.

Automated identification of maximal differential cell populations in flow cytometry data.

We introduce a new cell population score called SpecEnr (specific enrichment) and describe a method that discovers robust and accurate candidate biomarkers from flow cytometry data. Our approach identifies a new class of candidate biomarkers we define as driver cell populations, whose abundance is associated with a sample class (e.g.

Multi-Omic Data Integration Allows Baseline Immune Signatures to Predict Hepatitis B Vaccine Response in a Small Cohort.

Background: Vaccination remains one of the most effective means of reducing the burden of infectious diseases globally. Improving our understanding of the molecular basis for effective vaccine response is of paramount importance if we are to ensure the success of future vaccine development efforts.

Methods: We applied cutting edge multi-omics approaches to extensively characterize temporal molecular responses following vaccination with hepatitis B virus (HBV) vaccine.

Corrigendum: Clinical Protocol for a Longitudinal Cohort Study Employing Systems Biology to Identify Markers of Vaccine Immunogenicity in Newborn Infants in The Gambia and Papua New Guinea.

[This corrects the article DOI: 10.3389/fped.2020.

"Age Related Differences in the Biology of Chronic Graft-Versus-Host Disease After Hematopoietic Stem Cell Transplantation".

It is established that pediatric hematopoietic stem cell transplant (HSCT) recipients have a lower rate of chronic graft-versus-host disease (cGvHD) compared to adults. Our group has previously published immune profiles changes associated with cGvHD of clinically well-defined adult and pediatric HSCT cohorts. Since all analyses were performed by the same research group and analyzed using identical methodology, we first compared our previous immune profile analyses between adults and children.

Data File Standard for Flow Cytometry, Version FCS 3.2.

FCS 3.2 is a revision of the flow cytometry data standard based on a decade of suggested improvements from the community as well as industry needs to capture instrument conditions and measurement features more precisely. The unchanged goal of the standard is to provide a uniform file format that allows files created by one type of acquisition hardware and software to be analyzed by any other type.

ISAC Probe Tag Dictionary: Standardized Nomenclature for Detection and Visualization Labels Used in Cytometry and Microscopy Imaging.

Since the advent of microscopy imaging and flow cytometry, there has been an explosion in the number of probes, consisting of a component binding to an analyte and a detectable tag, to mark areas of interest in or on cells and tissue. Probe tags have been created to detect and/or visualize probes. Over time, these probe tags have increased in number.

Clinical Protocol for a Longitudinal Cohort Study Employing Systems Biology to Identify Markers of Vaccine Immunogenicity in Newborn Infants in The Gambia and Papua New Guinea.

Infection contributes to significant morbidity and mortality particularly in the very young and in low- and middle-income countries. While vaccines are a highly cost-effective tool against infectious disease little is known regarding the cellular and molecular pathways by which vaccines induce protection at an early age. Immunity is distinct in early life and greater precision is required in our understanding of mechanisms of early life protection to inform development of new pediatric vaccines.

The miR-185/PAK6 axis predicts therapy response and regulates survival of drug-resistant leukemic stem cells in CML.

Overcoming drug resistance and targeting cancer stem cells remain challenges for curative cancer treatment. To investigate the role of microRNAs (miRNAs) in regulating drug resistance and leukemic stem cell (LSC) fate, we performed global transcriptome profiling in treatment-naive chronic myeloid leukemia (CML) stem/progenitor cells and identified that miR-185 levels anticipate their response to ABL tyrosine kinase inhibitors (TKIs). miR-185 functions as a tumor suppressor: its restored expression impaired survival of drug-resistant cells, sensitized them to TKIs in vitro, and markedly eliminated long-term repopulating LSCs and infiltrating blast cells, conferring a survival advantage in preclinical xenotransplantation models.

Coprescription of opioid and naloxone in office-based practice and emergency department settings in the United States.

Objectives: The objective of the study was to estimate the national rates of naloxone coprescribing with opioids in office-based practice and emergency department (ED) settings in the United States (US).

Study Design: This study is a cross-sectional study.

Methods: We used the National Ambulatory Medical Care Survey (NAMCS) and the National Hospital Ambulatory Medical Care Survey (NHAMCS) datasets to estimate the national rates of naloxone coprescribing with opioids for the period 2014-2016.

Single Cell Phenotypic Profiling of 27 DLBCL Cases Reveals Marked Intertumoral and Intratumoral Heterogeneity.

Diffuse large B-cell lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin lymphoma and is notorious for its clinical heterogeneity. Patient outcomes can be predicted by cell-of-origin (COO) classification, demonstrating that the underlying transcriptional signature of malignant B-cells informs biological behavior in the context of standard combination chemotherapy regimens. In the current study, we used mass cytometry (CyTOF) to examine tumor phenotypes at the protein level with single cell resolution in a collection of 27 diagnostic DLBCL biopsy specimens from treatment naïve patients.

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition).

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells.

Performance of a web-based application measuring spot quality in dried blood spot sampling.

Background The dried blood spot (DBS) method allows patients and researchers to collect blood on a sampling card using a skin-prick. An important issue in the application of DBSs is that samples for therapeutic drug monitoring are frequently rejected because of poor spot quality, leading to delayed monitoring or missing data. We describe the development and performance of a web-based application (app), accessible on smartphones, tablets or desktops, capable of assessing DBS quality at the time of sampling by means of analyzing a picture of the DBS.

Improving the Quality and Reproducibility of Flow Cytometry in the Lung. An Official American Thoracic Society Workshop Report.

Defining responses of the structural and immune cells in biologic systems is critically important to understanding disease states and responses to injury. This requires accurate and sensitive methods to define cell types in organ systems. The principal method to delineate the cell populations involved in these processes is flow cytometry.