Publications by authors named "Meysman P"

In a letter critiquing our manuscript, Takefuji highlights general pitfalls in machine learning, without directly engaging with our study. The comments provide generic advice rather than a specific critique of our methods or findings. Despite raising important topics, the concerns reflect standard risks in machine learning, which we were aware of and explicitly addressed in our analyses.

View Article and Find Full Text PDF
Article Synopsis
  • T cells and their receptors (TCRs) are essential for understanding immune responses but are often overlooked in single-cell analysis, which typically focuses on gene expression.
  • The authors created a comprehensive T cell atlas from 12 major studies, involving 500,000 T cells across various diseases, and found challenges in accurately labeling cell types using standard methods.
  • They propose a TCR-first approach, using a semi-supervised method, to better identify T cell characteristics and dynamics, potentially enhancing immunotherapy and diagnostic strategies.
View Article and Find Full Text PDF

Deciphering the specificity of T-cell receptor (TCR) repertoires is crucial for monitoring adaptive immune responses and developing targeted immunotherapies and vaccines. To elucidate the specificity of previously unseen TCRs, many methods employ the BLOSUM62 matrix to find TCRs with similar amino acid (AA) sequences. However, while BLOSUM62 reflects the AA substitutions within conserved regions of proteins with similar functions, the remarkable diversity of TCRs means that both TCRs with similar and dissimilar sequences can bind the same epitope.

View Article and Find Full Text PDF
Article Synopsis
  • There is a problem with both HIV and visceral leishmaniasis (VL) infections in Ethiopia, making it hard to treat VL in people who also have HIV.
  • Researchers found that certain genes (HLA) can help predict who might get sick from VL, especially in people with HIV.
  • In a study of people living in Ethiopia, they found a specific gene (HLA-A*03:01) that is linked to a higher risk of developing VL, which could help improve treatment strategies in the future.
View Article and Find Full Text PDF

The Wilms' tumor protein 1 (WT1) is a well-known and prioritized tumor-associated antigen expressed in numerous solid and blood tumors. Its abundance and immunogenicity have led to the development of different WT1-specific immune therapies. The driving player in these therapies, the WT1-specific T-cell receptor (TCR) repertoire, has received much less attention.

View Article and Find Full Text PDF

Background: Schizophrenia and bipolar disorder frequently face significant delay in diagnosis, leading to being missed or misdiagnosed in early stages. Both disorders have also been associated with trait and state immune abnormalities. Recent machine learning-based studies have shown encouraging results using diagnostic biomarkers in predictive models, but few have focused on immune-based markers.

View Article and Find Full Text PDF

Our study aims to investigate the dynamics of conventional memory T cells (Tconv) and regulatory memory T cells (Treg) following activation, and to explore potential differences between these two cell types. To achieve this, we developed advanced statistical mixed models based on mathematical models of ordinary differential equations (ODE), which allowed us to transform post-vaccination immunological processes into mathematical formulas. These models were applied to in-house data from a de novo Hepatitis B vaccination trial.

View Article and Find Full Text PDF

A large proportion of HIV-coinfected visceral leishmaniasis (VL-HIV) patients exhibit chronic disease with frequent VL recurrence. However, knowledge on immunological determinants underlying the disease course is scarce. We longitudinally profiled the circulatory cellular immunity of an Ethiopian HIV cohort that included VL developers.

View Article and Find Full Text PDF

The role of T cell receptor (TCR) diversity in infectious disease susceptibility is not well understood. We use a systems immunology approach on three cohorts of herpes zoster (HZ) patients and controls to investigate whether TCR diversity against varicella-zoster virus (VZV) influences the risk of HZ. We show that CD4 T cell TCR diversity against VZV glycoprotein E (gE) and immediate early 63 protein (IE63) after 1-week culture is more restricted in HZ patients.

View Article and Find Full Text PDF
Article Synopsis
  • Discovering T-cell receptors (TCRs) for cancer therapies is often slow and costly due to the need for a lot of patient samples.
  • To improve efficiency and reduce the reliance on these samples, researchers are using prediction models to identify TCRs specific to cancer epitopes through computational methods.
  • This chapter outlines a protocol for training a prediction model using the TCRex webtool, focusing on the WT1 antigen, which is commonly overexpressed in various cancers, and provides a method to compile TCR data from healthy donors for model training.
View Article and Find Full Text PDF

The highly diverse T cell receptor (TCR) repertoire is a crucial component of the adaptive immune system that aids in the protection against a wide variety of pathogens. This TCR repertoire, comprising the collection of all TCRs in an individual, is a valuable source of information on both recent and ongoing T cell activation. Cancer cells, like pathogens, have the ability to trigger an adaptive immune response.

View Article and Find Full Text PDF
Article Synopsis
  • * A study analyzed genetic data from UK Biobank patients with shingles, focusing on immune responses and risk factors, uncovering significant links between susceptibility and human leukocyte antigens (HLAs).
  • * Key findings indicate that variations in the major histocompatibility complex play a crucial role in developing shingles, alongside increased immune responses related to type I interferon, offering new insights into how VZV reactivation affects the immune system.
View Article and Find Full Text PDF
Article Synopsis
  • Single-cell RNA sequencing (scRNA-seq) is a powerful technique for analyzing gene expression diversity in cells, particularly useful for studying complex cell populations like T cells.
  • Unlike bulk RNA sequencing, scRNA-seq can identify specific subtypes within these populations and recently enables simultaneous analysis of T-cell receptor (TCR) sequences alongside gene expression.
  • However, the analysis of scRNA-seq data faces challenges due to the lack of reliable methods for accurately annotating T-cell subtypes, as existing tools struggle to differentiate between the various T-cell populations effectively.
View Article and Find Full Text PDF
Article Synopsis
  • Developed an AI software system to predict late-onset sepsis (LOS) and necrotizing enterocolitis (NEC) in premature infants in the NICU using continuous monitoring data.
  • The study used an XGBoost machine learning algorithm on a dataset of 865 preterm infants, achieving a sensitivity of 69% for all episodes and 81% for severe cases, significantly reducing the time to diagnosis.
  • The AI model's predictions can support clinicians' early detection efforts, indicating potential clinical and socioeconomic benefits, with further studies needed to understand the combined impact of AI and clinical expertise on patient outcomes.
View Article and Find Full Text PDF

T-cell-based diagnostic tools identify pathogen exposure but lack differentiation between recent and historical exposures in acute infectious diseases. Here, T-cell receptor (TCR) RNA sequencing was performed on HLA-DR+/CD38+CD8+ T-cell subsets of hospitalized coronavirus disease 2019 (COVID-19) patients (n = 30) and healthy controls (n = 30; 10 of whom had previously been exposed to severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]). CDR3α and CDR3β TCR regions were clustered separately before epitope specificity annotation using a database of SARS-CoV-2-associated CDR3α and CDR3β sequences corresponding to >1000 SARS-CoV-2 epitopes.

View Article and Find Full Text PDF

The immune system acts as an intricate apparatus that is dedicated to mounting a defense and ensures host survival from microbial threats. To engage this faceted immune response and provide protection against infectious diseases, vaccinations are a critical tool to be developed. However, vaccine responses are governed by levels that, when interrogated, separately only explain a fraction of the immune reaction.

View Article and Find Full Text PDF

Despite the general agreement on the significance of T cells during SARS-CoV-2 infection, the clinical impact of specific and cross-reactive T-cell responses remains uncertain. Understanding this aspect could provide insights for adjusting vaccines and maintaining robust long-term protection against continuously emerging variants. To characterize CD8+ T-cell response to SARS-CoV-2 epitopes unique to the virus (SC2-unique) or shared with other coronaviruses (CoV-common), we trained a large number of T-cell receptor (TCR) - epitope recognition models for MHC-I-presented SARS-CoV-2 epitopes from publicly available data.

View Article and Find Full Text PDF

Antimicrobial resistant Salmonella enterica serovar Concord (S. Concord) is known to cause severe gastrointestinal and bloodstream infections in patients from Ethiopia and Ethiopian adoptees, and occasional records exist of S. Concord linked to other countries.

View Article and Find Full Text PDF
Article Synopsis
  • Researchers are using human induced pluripotent stem cell (hiPSC)-derived neural models to study the interactions between the Varicella-Zoster Virus (VZV) and the immune system in neurons.
  • A new study explored whether macrophages could help activate an antiviral response in VZV-infected hiPSC-neurons, but found the macrophages were ineffective in suppressing the infection.
  • RNA sequencing results showed a weak immune response in both infected neurons and co-cultured macrophages, indicating that other immune cells, like T-cells, may be necessary for a strong antiviral response against VZV.
View Article and Find Full Text PDF
Article Synopsis
  • The diversity of T cell receptors (TCRs) plays a key role in the immune response against various pathogens and is vital for the adaptive immune system.
  • When T cells encounter infections, they activate to fight these intruders, making the TCR repertoire a valuable source of information about past and current infections as well as vaccine responses.
  • The study utilizes machine learning techniques to analyze TCR data, specifically focusing on a yellow fever virus vaccination study, to identify specific TCRs that respond to the virus before and after vaccination.
View Article and Find Full Text PDF

Schizophrenia (SCZ) and bipolar disorder (BD) are associated with immunological dysfunctions that have been hypothesized to lead to clinical symptomatology in particular through kynurenine pathway abnormalities. The aim of this study was thus to investigate the impact of serum kynurenine metabolite levels on diagnosis, clinical state, symptom severity and clinical course in a large French transdiagnostic cohort of SCZ and BD patients. Four patient groups (total n = 507) were included in a cross-sectional observational study: 1) hospitalized acute bipolar patients (n = 205); 2) stable bipolar outpatients (n = 116); 3) hospitalized acute schizophrenia patients (n = 111) and 4) stable schizophrenia outpatients (n = 75), in addition to healthy controls (HC) (n = 185).

View Article and Find Full Text PDF
Article Synopsis
  • Varicella-zoster virus (VZV) infection mechanisms in human neurons are not well understood due to a lack of effective models for study.
  • Researchers created a human-induced pluripotent stem cell (hiPSC)-derived neuronal model that allows for realistic VZV infection, demonstrating that these neurons fail to activate an effective interferon-mediated antiviral response.
  • The study reveals that while hiPSC-neurons do not produce interferon-α (IFNα) on their own, they respond well to it when provided externally, suggesting that other cell types in the body may play a crucial role in controlling VZV infection by producing IFNα.
View Article and Find Full Text PDF
Article Synopsis
  • The study focuses on improving the early diagnosis of pediatric rheumatic diseases by analyzing gene expression in blood samples and applying machine learning to develop predictive models.
  • RNA sequencing was performed on blood from children with rheumatic diseases, viral infections, and controls, leading to the development of classification models that successfully distinguished between various disease groups.
  • Results indicated that certain classifiers achieved high accuracy in differentiating rheumatic conditions, highlighting the role of innate immune responses, and suggesting blood transcriptomics combined with machine learning could aid in clinical diagnostics.
View Article and Find Full Text PDF

Aneuploidy causes system-wide disruptions in the stochiometric balances of transcripts, proteins, and metabolites, often resulting in detrimental effects for the organism. The protozoan parasite Leishmania has an unusually high tolerance for aneuploidy, but the molecular and functional consequences for the pathogen remain poorly understood. Here, we addressed this question in vitro and present the first integrated analysis of the genome, transcriptome, proteome, and metabolome of highly aneuploid Leishmania donovani strains.

View Article and Find Full Text PDF