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Record W4365450005 · doi:10.1101/2023.04.11.536476

Kir7.1 is the physiological target for hormones and steroids that regulate uteroplacental function

2023· preprint· en· W4365450005 on OpenAlexfundno aff
Monika Haoui, Citlalli Vergara, Polina V. Lishko

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsnot available
FundersNational Institute on AgingNational Institutes of HealthBuck Institute for Research on AgingEcho Foundation
KeywordsMyometriumEndocrinologyInternal medicineHormonePlacentaEndogenyGestationIn uteroBiologyUterusPregnancyMedicineFetus

Abstract

fetched live from OpenAlex

Summary Preterm birth is a multifactorial syndrome that is detrimental to the well-being of both the mother and the newborn. During normal gestation, the myometrium is maintained in a quiescent state by the action of progesterone. As a steroid hormone, progesterone is thought to modify uterine and placental morphology by altering gene expression, but a nongenomic mode of action has long been suspected. Here we reveal that progesterone activates both human and murine inwardly rectifying potassium channel Kir7.1, which is expressed in mammalian myometrial smooth muscle and placental pericytes during late gestation. Kir7.1 is also activated by compounds used to prevent premature labor, including the progestogens 17-alpha-hydroxyprogesterone caproate and dydrogesterone, revealing an unexpected mode of action for these drugs. Our results reveal that Kir7.1 is the molecular target of a number of endogenous and synthetic steroids that control uterine excitability and placental function, and is therefore a promising therapeutic target to control utero-placental physiology and support healthy pregnancy.

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 score0.004
Threshold uncertainty score0.012

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.032
GPT teacher head0.238
Teacher spread0.206 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicPreterm Birth and ChorioamnionitisFrench-language works237,207