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Record W4387539844 · doi:10.26685/urncst.493

Vitamin K Supplementation for Prevention of Teratogenic Neurological Calcification in Fetuses with Congenital Zika Syndrome: A Research Protocol

2023· article· en· W4387539844 on OpenAlexafffund
Erin A. Ford, Emma C. Griffin, V. J. H. Sharpe, Simon J. Zacharias Bezanson

Bibliographic record

VenueUndergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal · 2023
Typearticle
Languageen
FieldNursing
TopicVitamin K Research Studies
Canadian institutionsQueen's University
FundersUniversity of Ottawa
KeywordsZika virusCalcificationMedicineFetusBone morphogenetic protein 2MicrocephalyPregnancyIn uteroInternal medicineBioinformaticsPediatricsBiologyImmunologyBiochemistry

Abstract

fetched live from OpenAlex

Introduction: Congenital Zika Syndrome (CZS) manifests in infants exposed to the Zika virus (ZIKV) in utero. Recent studies have documented the correlation between bone morphogenetic protein (BMP) and fetal brain calcification in these infants; however, potential treatment avenues remain unaccomplished. Unfortunately, the increase in ZIKV cases has engendered fetal neurodevelopmental defects including brain calcification which permanently impairs neurological function. The dominant pathogenic explanation results from osteogenic factor upregulation. Previous research has identified this underlying factor, highlighting the mechanism to combat the neurodegenerative impacts of ZIKV. Since the correlation between ZIKV and BMP is novel, studies addressing the mitigation of infant brain calcification are limited. Data from established ZIKV research was used to determine the potential utilization of matrix Gla protein (MGP) to inhibit the BMP pathway which calcifies fetal neural tissue. This rationale is founded on evidence showing (a) the efficacy of MGP in combating BMP-dependent calcification, and (b) the activation of MGP with Vitamin K2 (VK2). This study aims to establish a protocol for supplementing pregnant Zika patients with the VK2 derivative menaquinone-4 (MK-4), with the goal of preventing CZS-associated neurological calcification. Methods: A literature search was performed to evaluate the feasibility of VK2 injections for the prevention of neural calcification in CZS patients. The preventative potential of VK2 against CZS-related calcification will be tested using in vivo pregnant mouse (Mus musculus) models. Treatment groups will receive MK-4 administered with propylene glycol, while the control group will receive a placebo. Neurological calcification of fetuses and neonates will be monitored using pelvic ultrasound and micro-CT. Plasma and cerebral MK-4 content will be quantified using liquid chromatography-tandem mass spectrometry. Results: Anticipated results should demonstrate reduced subcortical calcification in the MK-4-treated murine cohort. Discussion: Protocol implementation precipitates the development of preventative CZS treatments. These findings indicate that low-dose maternal VK2 supplementation could provide a potential avenue for prevention of brain calcification in utero after vertical transmission of ZIKV. Conclusion: The proposed treatment would be the first of its kind, providing affected populations with a low-cost intervention for neurological damage caused by CZS, decreasing the burden of disease as ZIKV prevalence grows.

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)0.007
metaresearch head score (Gemma)0.008
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.038
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0380.004

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 head0.141
GPT teacher head0.508
Teacher spread0.367 · 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
GenreProtocol

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

Citations3
Published2023
Admission routes2
Has abstractyes

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