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Record W2994993394 · doi:10.1007/s12192-019-01058-z

Effect of cadmium on essential metals and their impact on lipid metabolism in Saccharomyces cerevisiae

2019· review· en· W2994993394 on OpenAlexaff
Selvaraj Rajakumar, Albert Abhishek, Govindan Sadasivam Selvam, Vasanthi Nachiappan

Bibliographic record

VenueCell Stress and Chaperones · 2019
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Stress Responses and Tolerance
Canadian institutionsHeritage Medical Research ClinicUniversity of Alberta
Fundersnot available
KeywordsLipid metabolismSaccharomyces cerevisiaeLipotoxicityLipid dropletBiochemistryEndoplasmic reticulumBiologyCell biologyYeastCadmiumMetabolismChemistry

Abstract

fetched live from OpenAlex

Cadmium (Cd) is a toxic heavy metal that induces irregularity in numerous lipid metabolic pathways. Saccharomyces cerevisiae, a model to study lipid metabolism, has been used to establish the molecular basis of cellular responses to Cd toxicity in relation to essential minerals and lipid homeostasis. Multiple pathways sense these environmental stresses and trigger the mineral imbalances specifically calcium (Ca) and zinc (Zn). This review is aimed to elucidate the role of Cd toxicity in yeast, in three different perspectives: (1) elucidate stress response and its adaptation to Cd, (2) understand the physiological role of a macromolecule such as lipids, and (3) study the stress rescue mechanism. Here, we explored the impact of Cd interference on the essential minerals such as Zn and Ca and their influence on endoplasmic reticulum stress and lipid metabolism. Cd toxicity contributes to lipid droplet synthesis by activating OLE1 that is essential to alleviate lipotoxicity. In this review, we expanded our current findings about the effect of Cd on lipid metabolism of budding yeast.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.270
Teacher spread0.253 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations39
Published2019
Admission routes1
Has abstractno

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