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Record W4220787050 · doi:10.1002/bies.202100233

<i>Hydra</i> and the hair follicle – An unconventional comparative biology approach to exploring the human holobiont

2022· article· en· W4220787050 on OpenAlexfundno aff
Marta B. Lousada, Tim Lachnit, Janin Edelkamp, Ralf Paus, Thomas C. G. Bosch

Bibliographic record

VenueBioEssays · 2022
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftCanadian Institute for Advanced Research
KeywordsMicrobiomeHolobiontBiologyLernaean HydraHost (biology)Model organismComputational biologyEvolutionary biologyNeuroscienceEcologyBioinformaticsCell biologyGeneticsSymbiosisBacteria

Abstract

fetched live from OpenAlex

The microbiome of human hair follicles (HFs) has emerged as an important player in different HF and skin pathologies, yet awaits in-depth exploration. This raises questions regarding the tightly linked interactions between host environment, nutrient dependency of host-associated microbes, microbial metabolism, microbe-microbe interactions and host immunity. The use of simple model systems facilitates addressing generally important questions and testing overarching, therapeutically relevant principles that likely transcend obvious interspecies differences. Here, we evaluate the potential of the freshwater polyp Hydra, to dissect fundamental principles of microbiome regulation by the host, that is the human HF. In particular, we focus on therapeutically targetable host-microbiome interactions, such as nutrient dependency, microbial interactions and host defence. Offering a new lens into the study of HF - microbiota interactions, we argue that general principles of how Hydra manages its microbiota can inform the development of novel, microbiome-targeting therapeutic interventions in human skin disease.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.643
Threshold uncertainty score0.555

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 studies0.0010.000
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 head0.101
GPT teacher head0.327
Teacher spread0.226 · 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 designObservational
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

Citations4
Published2022
Admission routes1
Has abstractyes

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