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Record W2014087264 · doi:10.1097/mnh.0b013e328326092c

Developmental programming and hypertension

2009· review· en· W2014087264 on OpenAlexaff
Anne Monique Nuyt, Barbara T. Alexander

Bibliographic record

VenueCurrent Opinion in Nephrology & Hypertension · 2009
Typereview
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersNational Institute on Minority Health and Health DisparitiesNational Heart, Lung, and Blood Institute
KeywordsFetal programmingIntrauterine growth restrictionMedicineBlood pressureBioinformaticsPregnancyWindow of opportunityIntensive care medicinePhysiologyFetusBiologyEndocrinologyComputer science

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: There is a growing body of evidence linking adverse events or exposures during early life and adult-onset diseases. After important epidemiological studies from many parts of the world, research now focuses on mechanisms of organ dysfunction and on refining the understanding of the interaction between common elements of adverse perinatal conditions, such as nutrition, oxidants, and toxins exposures. This review will focus on advances in our comprehension of developmental programming of hypertension. RECENT FINDINGS: Recent studies have unraveled important mechanisms of oligonephronia and impaired renal function, altered vascular function and structure as well as sympathetic regulation of the cardiovascular system. Furthermore, interactions between prenatal insults and postnatal conditions are the subject of intensive research. Prematurity vs. intrauterine growth restriction modulate differently programming of high blood pressure. Along with antenatal exposure to glucocorticoids and imbalanced nutrition, a critical role for perinatal oxidative stress is emerging. SUMMARY: While the complexity of the interactions between antenatal and postnatal influences on adult blood pressure is increasingly recognized, the importance of postnatal life in (positively) modulating developmental programming offers the hope of a critical window of opportunity to reverse programming and prevent or reduce related adult-onset diseases.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.142
GPT teacher head0.379
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations158
Published2009
Admission routes1
Has abstractyes

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