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Record W4388914051 · doi:10.1016/j.cub.2023.10.038

Multiple neuronal populations control the eating behavior in Hydra and are responsive to microbial signals

2023· article· en· W4388914051 on OpenAlexfundno aff
Christoph Giez, Denis Pinkle, Yan Giencke, Jörg Wittlieb, Eva Herbst, Tobias Spratte, Tim Lachnit, Alexander Klimovich, Christine Selhuber‐Unkel, Thomas C. G. Bosch

Bibliographic record

VenueCurrent Biology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Invertebrate Physiology and Ecology
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftCanadian Institute for Advanced Research
KeywordsBiologyLernaean HydraEvolutionary biologyCell biologyNeuroscienceEcologyPhysiology

Abstract

fetched live from OpenAlex

Although recent studies indicate the impact of microbes on the central nervous systems and behavior, it remains unclear how the relationship between the functionality of the nervous system, behavior, and the microbiota evolved. In this work, we analyzed the eating behavior of Hydra, a host that has a simple nervous system and a low-complexity microbiota. To identify the neuronal subpopulations involved, we used a subpopulation-specific cell ablation system and calcium imaging. The role of the microbiota was uncovered by manipulating the diversity of the natural microbiota. We show that different neuronal subpopulations are functioning together to control eating behavior. Animals with a drastically reduced microbiome had severe difficulties in mouth opening due to a significantly increased level of glutamate. This could be reversed by adding a full complement of the microbiota. In summary, we provide a mechanistic explanation of how Hydra's nervous system controls eating behavior and what role microbes play in this.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.551

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 studies0.0000.000
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 head0.053
GPT teacher head0.287
Teacher spread0.234 · 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

Citations28
Published2023
Admission routes1
Has abstractyes

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