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Record W4376641476 · doi:10.1038/s41598-023-34789-2

TRPM7 kinase mediates hypomagnesemia-induced seizure-related death

2023· article· en· W4376641476 on OpenAlexfundno aff
Man Liu, Hong Liu, Feng Feng, Esther Krook‐Magnuson, Samuel C. Dudley

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldNursing
TopicMagnesium in Health and Disease
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteUniversity of Toronto ScarboroughNational Institutes of HealthDirectorate for Biological SciencesUniversity of Toronto
KeywordsTRPM7Oxidative stressEndocrinologyInternal medicineInflammationKinaseEpilepsyHypomagnesemiaMedicineGenetically modified mouseBiologyTransgeneTransient receptor potential channelChemistryReceptorCell biologyNeuroscienceBiochemistryGene

Abstract

fetched live from OpenAlex

Abstract Hypomagnesemia (HypoMg) can cause seizures and death, but the mechanism is unknown. Transient receptor potential cation channel subfamily M 7 (TRPM7) is a Mg transporter with both channel and kinase function. In this study, we focused on the kinase role of TRPM7 in HypoMg-induced seizures and death. Wild type C57BL/6J mice and transgenic mice with a global homozygous mutation in the TRPM7 kinase domain (TRPM7K1646R, with no kinase function) were fed with control diet or a HypoMg diet. After 6 weeks of HypoMg diet, mice had significantly decreased serum Mg, elevated brain TRPM7, and a significant rate of death, with females being most susceptible. Deaths were immediately preceded by seizure events. TRPM7K1646R mice showed resistance to seizure-induced death. HypoMg-induced brain inflammation and oxidative stress were suppressed by TRPM7K1646R. Compared to their male counterparts, HypoMg female mice had higher levels of inflammation and oxidative stress in the hippocampus. We concluded that TRPM7 kinase function contributes seizure-induced deaths in HypoMg mice and that inhibiting the kinase reduced inflammation and oxidative stress.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.298
Teacher spread0.270 · 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 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

Citations10
Published2023
Admission routes1
Has abstractyes

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