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Record W2285815731 · doi:10.1038/srep21768

Exploring miniature insect brains using micro-CT scanning techniques

2016· article· en· W2285815731 on OpenAlexafffund
Dylan B. Smith, Galina Bernhardt, Nigel E. Raıne, Richard L. Abel, Dan Sykes, Farah K. Ahmed, Inti Pedroso, Richard J. Gill

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Guelph
FundersNatural Environment Research CouncilComisión Nacional de Investigación Científica y TecnológicaDirectorate for Biological SciencesImperial College LondonDepartment for Environment, Food and Rural Affairs, UK GovernmentBiotechnology and Biological Sciences Research CouncilW. Garfield Weston FoundationWellcome TrustLeverhulme TrustCorporación de Fomento de la Producción
KeywordsBumblebeeComputer scienceBombus terrestrisBrain tissueInsectBrain functionNeuroimaging3D reconstructionProtocol (science)Artificial intelligenceComputed tomographyBiologyComputer visionNeuroscienceEcologyMedicinePathologyPollinatorRadiologyPollination

Abstract

fetched live from OpenAlex

The capacity to explore soft tissue structures in detail is important in understanding animal physiology and how this determines features such as movement, behaviour and the impact of trauma on regular function. Here we use advances in micro-computed tomography (micro-CT) technology to explore the brain of an important insect pollinator and model organism, the bumblebee (Bombus terrestris). Here we present a method for accurate imaging and exploration of insect brains that keeps brain tissue free from trauma and in its natural stereo-geometry, and showcase our 3D reconstructions and analyses of 19 individual brains at high resolution. Development of this protocol allows relatively rapid and cost effective brain reconstructions, making it an accessible methodology to the wider scientific community. The protocol describes the necessary steps for sample preparation, tissue staining, micro-CT scanning and 3D reconstruction, followed by a method for image analysis using the freeware SPIERS. These image analysis methods describe how to virtually extract key composite structures from the insect brain, and we demonstrate the application and precision of this method by calculating structural volumes and investigating the allometric relationships between bumblebee brain structures.

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)0.001
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 score0.248
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.181
GPT teacher head0.248
Teacher spread0.067 · 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

Citations118
Published2016
Admission routes2
Has abstractyes

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