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Record W4389244277 · doi:10.1093/humupd/dmad031

Roles of bone morphogenetic proteins in endometrial remodeling during the human menstrual cycle and pregnancy

2023· review· en· W4389244277 on OpenAlexaff
Daimin Wei, Yaxin Su, Peter C. K. Leung, Yan Li, Zi‐Jiang Chen

Bibliographic record

VenueHuman Reproduction Update · 2023
Typereview
Languageen
FieldImmunology and Microbiology
TopicReproductive System and Pregnancy
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersNational Key Research and Development Program of ChinaNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China
KeywordsDecidualizationEndometriumMiscarriageEndometriosisMenstrual cycleMedicineInfertilityBioinformaticsCancer researchPregnancyBiologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: During the human menstrual cycle and pregnancy, the endometrium undergoes a series of dynamic remodeling processes to adapt to physiological changes. Insufficient endometrial remodeling, characterized by inadequate endometrial proliferation, decidualization and spiral artery remodeling, is associated with infertility, endometriosis, dysfunctional uterine bleeding, and pregnancy-related complications such as preeclampsia and miscarriage. Bone morphogenetic proteins (BMPs), a subset of the transforming growth factor-β (TGF-β) superfamily, are multifunctional cytokines that regulate diverse cellular activities, such as differentiation, proliferation, apoptosis, and extracellular matrix synthesis, are now understood as integral to multiple reproductive processes in women. Investigations using human biological samples have shown that BMPs are essential for regulating human endometrial remodeling processes, including endometrial proliferation and decidualization. OBJECTIVE AND RATIONALE: This review summarizes our current knowledge on the known pathophysiological roles of BMPs and their underlying molecular mechanisms in regulating human endometrial proliferation and decidualization, with the goal of promoting the development of innovative strategies for diagnosing, treating and preventing infertility and adverse pregnancy complications associated with dysregulated human endometrial remodeling. SEARCH METHODS: A literature search for original articles published up to June 2023 was conducted in the PubMed, MEDLINE, and Google Scholar databases, identifying studies on the roles of BMPs in endometrial remodeling during the human menstrual cycle and pregnancy. Articles identified were restricted to English language full-text papers. OUTCOMES: BMP ligands and receptors and their transduction molecules are expressed in the endometrium and at the maternal-fetal interface. Along with emerging technologies such as tissue microarrays, 3D organoid cultures and advanced single-cell transcriptomics, and given the clinical availability of recombinant human proteins and ongoing pharmaceutical development, it is now clear that BMPs exert multiple roles in regulating human endometrial remodeling and that these biomolecules (and their receptors) can be targeted for diagnostic and therapeutic purposes. Moreover, dysregulation of these ligands, their receptors, or signaling determinants can impact endometrial remodeling, contributing to infertility or pregnancy-related complications (e.g. preeclampsia and miscarriage). WIDER IMPLICATIONS: Although further clinical trials are needed, recent advancements in the development of recombinant BMP ligands, synthetic BMP inhibitors, receptor antagonists, BMP ligand sequestration tools, and gene therapies have underscored the BMPs as candidate diagnostic biomarkers and positioned the BMP signaling pathway as a promising therapeutic target for addressing infertility and pregnancy complications related to dysregulated human endometrial remodeling.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.010
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.055
GPT teacher head0.315
Teacher spread0.260 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

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