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Record W4282967346 · doi:10.1101/2022.06.13.495867

Human innate lymphoid cell activation by adenoviruses is modified by host defence proteins and neutralizing antibodies

2022· preprint· en· W4282967346 on OpenAlexfundno aff
Océane Paris, Franck J. D. Mennechet, Eric J. Kremer

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsnot available
FundersInstitute of GeneticsCentre National de la Recherche ScientifiqueInstitut National de la Santé et de la Recherche MédicaleEtablissement Français du SangAgence Nationale de la Recherche
KeywordsBiologyInnate lymphoid cellImmune systemImmunologyAcquired immune systemAntibodyInnate immune systemImmunityNeutralizing antibodyVirology

Abstract

fetched live from OpenAlex

Abstract Innate lymphoid cells (ILCs), the complements of diverse CD4 T helper cells, help maintain tissue homeostasis by providing a link between innate and adaptive immune responses. While pioneering studies over the last decade have advanced our understanding how ILCs influence adaptive immune responses to pathogens, far less is known about whether the adaptive immune response feeds back into an ILC response. In this study, we isolated ILCs from blood of healthy donors, fine-tuned culture conditions, and then directly challenged them with human adenoviruses (HAdVs), with HAdVs and host defence proteins (HDPs) or neutralizing antibodies (NAbs), to mimic interactions in a host with pre-existing immunity. Additionally, we developed an ex vivo approach to identify how bystander ILCs respond to the uptake of HAdVs ± neutralizing antibodies by monocyte-derived dendritic cells. We show that ILCs take up HAdVs, which induces phenotypic maturation and cytokine secretion. Moreover, NAbs and HDPs complexes modified the cytokine profile generated by ILCs, consistent with a feedback loop for host antiviral responses and potential to impact adenovirus-based vaccine efficacy. Author Summary Several studies have shown the importance of innate lymphoid cells (ILCs) both from an immune and physiological point of view, in particular for their role in the maintenance of tissue integrity, pathogens clearance, or in the establishment of immune tolerance. Our study focuses on the role of ILCs during direct challenge with prototype vaccines based on human adenoviruses (HAdVs) ± host defence proteins (HDPs) or neutralizing antibodies (NAbs) to mimic interactions in a host with pre-existing immunity. In parallel, through an ex vivo approach we observe how bystander ILCs respond to the uptake of HAdVs ± NAbs by monocyte-derived dendritic cells. We show that ILCs take up HAdVs, which induces pro- inflammatory and antiviral responses through phenotypic maturation and cytokine secretion. Moreover, HAdV-NAb and HAdV-HDP complexes modified the cytokine profile generated by ILCs, consistent with a feedback loop for host antiviral responses and potential to impact HAdV vaccine efficacy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.223
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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