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Record W3133719715 · doi:10.1038/s41598-021-84762-0

Amplification of potential thermogenetic mechanisms in cetacean brains compared to artiodactyl brains

2021· article· en· W3133719715 on OpenAlexfundno aff
Paul R. Manger, Nina Patzke, Muhammad A. Spocter, Adhil Bhagwandin, Karl Æ. Karlsson, Mads F. Bertelsen, Abdulaziz N. Alagaili, Nigel C. Bennett, Osama B. Mohammed, Suzana Herculano‐Houzel, Patrick R. Hof, Kjell Fuxé

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersInstitute of Population and Public HealthJames S. McDonnell FoundationVetenskapsrådetDeutscher Akademischer AustauschdienstKing Saud UniversityNational Research Foundation
KeywordsNeuroscienceComputer scienceBiologyEvolutionary biology

Abstract

fetched live from OpenAlex

To elucidate factors underlying the evolution of large brains in cetaceans, we examined 16 brains from 14 cetartiodactyl species, with immunohistochemical techniques, for evidence of non-shivering thermogenesis. We show that, in comparison to the 11 artiodactyl brains studied (from 11 species), the 5 cetacean brains (from 3 species), exhibit an expanded expression of uncoupling protein 1 (UCP1, UCPs being mitochondrial inner membrane proteins that dissipate the proton gradient to generate heat) in cortical neurons, immunolocalization of UCP4 within a substantial proportion of glia throughout the brain, and an increased density of noradrenergic axonal boutons (noradrenaline functioning to control concentrations of and activate UCPs). Thus, cetacean brains studied possess multiple characteristics indicative of intensified thermogenetic functionality that can be related to their current and historical obligatory aquatic niche. These findings necessitate reassessment of our concepts regarding the reasons for large brain evolution and associated functional capacities in cetaceans.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.244
Teacher spread0.225 · 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 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

Citations16
Published2021
Admission routes1
Has abstractyes

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