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Record W2138148792 · doi:10.1139/o07-142

Osmotic water permeability of rat intestinal brush border membrane vesicles: involvement of aquaporin-7 and aquaporin-8 and effect of metal ions

2007· article· en· W2138148792 on OpenAlexvenueno aff
Simona Tritto, Giulia Gastaldi, Sergey Zelenin, Monica Grazioli, M. Orsenigo, Ulderico Ventura, Umberto Laforenza, Marina Zelenina

Bibliographic record

VenueBiochemistry and Cell Biology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon Transport and Channel Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsAquaporinBrush borderApical membraneTransfectionChemistryAquaporin 1VesicleBiophysicsMembraneCell biologyBiochemistryMolecular biologyWater channelBiologyGene

Abstract

fetched live from OpenAlex

Water channels AQP7 and AQP8 may be involved in transcellular water movement in the small intestine. We show that both AQP7 and AQP8 mRNA are expressed in rat small intestine. Immunoblot and immunohistochemistry experiments demonstrate that AQP7 and AQP8 proteins are present in the apical brush border membrane of intestinal epithelial cells. We investigated the effect of several metals and pH on the osmotic water permeability (Pf) of brush border membrane vesicles (BBMVs) and of AQP7 and AQP8 expressed in a cell line. Hg2+, Cu2+, and Zn2+ caused a significant decrease in the BBMV Pf, whereas Ni2+ and Li+ had no effect. AQP8-transfected cells showed a reduction in Pf in the presence of Hg2+ and Cu2+, whereas AQP7-transfected cells were insensitive to all tested metals. The Pf of both BBMVs and cells transfected with AQP7 and AQP8 was not affected by pH changes within the physiological range, and the Pf of BBMVs alone was not affected by phlorizin or amiloride. Our results indicate that AQP7 and AQP8 may play a role in water movement via the apical domain of small intestine epithelial cells. AQP8 may contribute to the water-imbalance-related clinical symptoms apparent after ingestion of high doses of Hg2+ and Cu2+.

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)0.000
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 score0.023
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.006
GPT teacher head0.232
Teacher spread0.226 · 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

Citations29
Published2007
Admission routes1
Has abstractyes

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