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Record W2080041227 · doi:10.1515/jpm.2006.052

Altered protease expression by periarterial trophoblast cells in severe early-onset preeclampsia with IUGR

2006· article· en· W2080041227 on OpenAlexaff
Frank Reister, John‏ Kingdom, Peter Ruck, K. Marzusch, W. Heyl, Uli Pauer, Peter Kaufmann, Werner Rath, Berthold Huppertz

Bibliographic record

VenueJournal of Perinatal Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsSpiral arteryTrophoblastPreeclampsiaMedicinePlacentaCellular adaptationMatrix metalloproteinaseFetusInternal medicineGestational ageEndocrinologyPregnancyAndrologyImmunologyBiologyGene

Abstract

fetched live from OpenAlex

Adaptation of uteroplacental arteries in patients with early-onset preeclampsia combined with IUGR is compromised due to insufficient invasion of extravillous trophoblast cells (EVT) into the spiral artery wall. The underlying molecular mechanisms are widely unknown. We investigated expression and possible mechanisms of regulation of different matrix-metalloproteases (MMPs) by EVT in placental bed biopsies from patients with early onset preeclampsia combined with IUGR and healthy pregnant women. Expression of MMP-3 and MMP-7 by EVT was markedly reduced in preeclamptic patients, especially close to spiral arteries. In contrast to healthy pregnancies these cells strongly expressed the receptor for leukemia inhibitory factor (LIF). LIF is known to suppress MMP-expression and is produced by uterine natural killer (uNK) cells which we found to be present in higher concentrations in the placental bed of preeclamptic patients, and accumulating aside the spiral arteries. We speculate that in preeclampsia a maternal immune cell network accumulating and interfering in the placental bed leads to an altered cytokine environment, resulting in disturbed trophoblast cell function such as impaired MMP expression and reduced invasiveness.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.008
GPT teacher head0.236
Teacher spread0.228 · 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

Citations61
Published2006
Admission routes1
Has abstractyes

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