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Record W2485089278 · doi:10.1038/srep30582

Molecular characterization of Tps1 and Treh genes in Drosophila and their role in body water homeostasis

2016· article· en· W2485089278 on OpenAlexfundno aff
Miki Yoshida, Hiroko Matsuda, Hitomi Kubo, Takashi Nishimura

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsnot available
FundersInstitute of GeneticsRIKENMinistry of Education, Culture, Sports, Science and Technology
KeywordsComputational biologyGeneBiologyHomeostasisDrosophila (subgenus)BioinformaticsCell biologyGenetics

Abstract

fetched live from OpenAlex

In insects, trehalose serves as the main sugar component of haemolymph. Trehalose is also recognized as a mediator of desiccation survival due to its proposed ability to stabilize membranes and proteins. Although the physiological role of trehalose in insects has been documented for decades, genetic evidence to support the importance of trehalose metabolism remains incomplete. We here show on the basis of genetic and biochemical evidence that the trehalose synthesis enzyme Tps1 is solely responsible for the de novo synthesis of trehalose in Drosophila. Conversely, a lack of the gene for the trehalose hydrolyzing enzyme Treh causes an accumulation of trehalose that is lethal during the pupal period, as is observed with Tps1 mutants. Lack of either Tps1 or Treh results in a significant reduction in circulating glucose, suggesting that the maintenance of glucose levels requires a continuous turnover of trehalose. Furthermore, changes in trehalose levels are positively correlated with the haemolymph water volume. In addition, both Tps1 and Treh mutant larvae exhibit a high lethality after desiccation stress. These results demonstrate that the regulation of trehalose metabolism is essential for normal development, body water homeostasis, and desiccation tolerance in Drosophila.

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 score0.033
Threshold uncertainty score0.225

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 studies0.0000.001
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 head0.014
GPT teacher head0.245
Teacher spread0.231 · 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

Citations67
Published2016
Admission routes1
Has abstractyes

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