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Record W2914417447 · doi:10.1073/pnas.1817376116

Paneth cell α-defensins HD-5 and HD-6 display differential degradation into active antimicrobial fragments

2019· article· en· W2914417447 on OpenAlexafffund
Dirk Ehmann, Judith Wendler, Louis Koeninger, Ida Larsen, Thomas Klag, J. Berger, André Marette, Martin Schaller, Eduard F. Stange, Nisar P. Malek, Benjamin A. H. Jensen, Jan Wehkamp

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversité Laval
FundersInstitut universitaire de cardiologie et de pneumologie de Québec, Université LavalNovo Nordisk FondenNovo NordiskH. Lundbeck A/SLundbeckfondenUniversité LavalDeutsche ForschungsgemeinschaftEuropean Commission
KeywordsAntimicrobialAntimicrobial peptidesPaneth cellDegradation (telecommunications)Differential (mechanical device)ChemistryDefensinMicrobiologyCell biologyBiologyBiochemistryPhysicsComputer science

Abstract

fetched live from OpenAlex

Significance Paneth cells provide intestinal host defense against pathogens and control the healthy microbiota by secreting antimicrobial peptides. We show that the most abundant secreted Paneth cell products, human defensin HD-5 and HD-6, show a distinct susceptibility to proteolytic digestion by human duodenal fluid. While HD-5 is digested in many fragments, HD-6 is stable and still able to form nanonets. The occurring fragments of HD-5 were antimicrobially active against microorganisms. We provide proof of concept about microbiome modulating capacities in vivo, which includes an increase of Akkermansia sp. Our results indicate that fragmentation of defensins increases antimicrobial diversity and further adds to the complexity of host microbial interaction at interfaces. Fragmentation could lead to new antimicrobial peptides with possible therapeutic usage.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.054
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.249
Teacher spread0.233 · 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 teacher head, 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

Citations112
Published2019
Admission routes2
Has abstractyes

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