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Record W2041368434 · doi:10.1074/jbc.m209933200

Brain-specific Restoration of Angiotensin II Corrects Renal Defects Seen in Angiotensinogen-deficient Mice

2003· article· en· W2041368434 on OpenAlexafffund
Nadheige Lochard, David W. Silversides, Jorge P. van Kats, Chantal Mercure, Timothy L. Reudelhuber

Bibliographic record

VenueJournal of Biological Chemistry · 2003
Typearticle
Languageen
FieldMedicine
TopicRenin-Angiotensin System Studies
Canadian institutionsMontreal Clinical Research Institute
FundersCanadian Institutes of Health Research
KeywordsRenin–angiotensin systemInternal medicineAngiotensin IIEndocrinologyMedicineKidneyHydronephrosisGenetically modified mouseTransgeneBiologyUrinary systemReceptorBlood pressure

Abstract

fetched live from OpenAlex

Mice deficient for angiotensinogen (AGT), or other components of the renin-angiotensin system, show a high rate of neonatal mortality correlated with severe renal abnormalities including hydronephrosis, hypertrophy of renal arteries, and an impaired ability to concentrate urine. Although transgenic replacement of systemic or adipose, but not renal, AGT in AGT-deficient mice has previously been reported to correct some of these renal abnormalities, the tissue target for this complementation has not been defined. In the current study, we have used a novel transgenic strategy to restore the peptide product of the renin-angiotensin system, angiotensin II, exclusively in the brain of AGT-deficient mice and demonstrate that brain-specific angiotensin II can correct the hydronephrosis and partially correct renal dysfunction seen in AGT-deficient mice. Taken together, these results suggest that the renin-angiotensin system affects renal development and function through systemically accessible targets in the brain.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.036
GPT teacher head0.265
Teacher spread0.229 · 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

Citations45
Published2003
Admission routes2
Has abstractyes

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Same venueJournal of Biological ChemistrySame topicRenin-Angiotensin System StudiesFrench-language works237,207