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Record W2053416609 · doi:10.1242/jeb.077594

ATTACK OF THE EXPLODING TERMITES

2012· article· en· W2053416609 on OpenAlexaff
Katie E. Marshall

Bibliographic record

VenueJournal of Experimental Biology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsWestern University
Fundersnot available
KeywordsThorax (insect anatomy)AbdomenWhite (mutation)HymenopteraBlue lightBiologyAnatomyZoologyPhysicsOptics

Abstract

fetched live from OpenAlex

Aging is not always the most graceful of processes in animals. Hair greys, eyesight dims and teeth lose their edge. But perhaps no animal has it as tough as termites. A paper recently published in Science by J. Šobotník and an international team of colleagues shows that as Neocapritermes taracua workers age they develop a backpack stuffed with toxic chemicals that explodes when they are attacked.The researchers had noticed that workers of N. taracua come in two varieties: a regular-looking ‘white’ worker, and one that has two long dark blue markings at the space where the thorax and abdomen join (‘blue’ workers). And when either blue or white workers were attacked by other termite species, they burst, emitting a small amount of fluid. Upon closer inspection, the researchers found that the blue markings appeared to be caused by small groups of dark blue crystals held in pouches between the abdomen and an outgrowth of the thorax.To figure out what was going on, the researchers went to French Guiana and collected several colonies of N. taracua. Based on previous studies, they hypothesized that, as older workers were less useful to the colony – because their mandibles were worn and not as effective at chewing – they would be more likely to have blue crystals, more likely to burst when attacked and, when they burst, produce more toxic fluid. They first compared the mass of blue crystals to the sharpness of the mandibles in N. taracua workers and found that older workers (with duller mandibles) had greater amounts of blue crystal. Then they set up fighting matches where they paired N. taracua workers with other termite species to see how long blue and white workers held out before bursting. They found that blue workers were more aggressive to other species, and burst more quickly than white workers.Šobotník and the other researchers then applied fluid from burst white and blue workers to termites of other species to compare the toxicity of the fluids. In addition, they gently removed the crystals from the blue workers, to see whether they were solely responsible for any differences in toxicity. They found that the fluid emitted by blue workers (complete with blue crystals) was extremely effective at killing other termites, whereas the fluid emitted by white workers was much less potent. However, without their blue crystals the blue workers' fluid was far less toxic. Similarly, if the team added blue crystals to the fluid from a white worker, the toxicity of the mixture was increased (although it was never as toxic as the unaltered mixture from a blue worker).This pointed to the blue crystals being an important component of the toxicity. Using several chemical techniques, the researchers found that the blue crystals contained a 76 kDa protein, likely an oxygen-binding copper protein from the hemocyanin/phenoloxidase family, containing a large amount of copper (which gave the crystals their blue colour). The also found that salivary gland extract (which mixes with the blue crystals during the explosion) from the blue and white workers appeared to differ in composition. This led the researchers to conclude that blue N. taracua workers have a two-component toxin: the crystal protein and salivary gland components mix to produce the toxin.Aging is not exactly a peaceful process in this termite species. Rather than settling down and picking up a hobby as they age, workers of N. taracua develop a hash of toxic chemicals that they carry around in a backpack on their cuticle, ready to burst at any moment in a Kamikaze mission against their enemies.

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)0.001
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.322
Teacher spread0.293 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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