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Record W4313499229 · doi:10.33915/etd.11459

Vaping During Pregnancy: Effects on Vascular and Behavioral Outcomes in Offspring

2022· dissertation· en· W4313499229 on OpenAlexaff
Eiman A Aboaziza

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsCanadian Society for Exercise Physiology
FundersCancer Institute, West Virginia UniversityNational Institutes of HealthDivision of Graduate EducationAmerican Heart Association
KeywordsEnvironmental healthOffspringNicotinePregnancyScarcityStigma (botany)PopulationSAFERPublic healthMedicineElectronic cigaretteCotininePsychologyBusinessPsychiatryEconomicsNursingComputer security

Abstract

fetched live from OpenAlex

Electronic cigarette (e-cig) use is increasing due to aggressive marketing, tempting flavors, and seemingly higher acceptability in the community (lesser perceived social stigma) despite unproven claims of safety. In an alarming trend, pregnant women smokers have turned to novel “modified risk” products, such as e-cigs, in response to heavy marketing of e-cigs as safer alternatives to cigarettes and a tool to help quit smoking. This is despite proven detrimental effects of nicotine on a growing fetus, and scarcity of information regarding toxicity of e-liquid (with and without nicotine) on child development. Moreover, rampant e-cig use among youth (nearly 4 million in 2018, CDC) reflects a growing population of experienced and addicted female users who may become pregnant. This project addresses this emerging public health issue by providing information regarding consequences of maternal e-cig use and its long-term effects on child health outcomes. It is established that both mother and fetus are vulnerable to environmental exposures during pregnancy. Prenatal exposure to nicotine leads to preterm births and is linked to adverse health, behavioral and cognitive outcomes in newborns. E-cigs have been shown to deliver physiologically significant amounts of nicotine to its users. Currently, little is known about the effects of e-cig use on perinatal and developmental outcomes and whether adverse effects can be attributed to nicotine delivery alone. Given the paucity of data, this overall goal project seeks to elucidate the impact of maternal e-cig use during pregnancy using an animal model to test cardiovascular and behavioral outcomes. The first objective of this work was to determine dose-dependent effects of maternal e-cig exposure on functional vascular outcomes in conduit and resistance vessel beds and to investigate potential pathways that lead to this impairment. The second objective is to evaluate the effect of on cognitive development and behavioral deficits in the pups and compare between levels of exposure. The hypothesis is that 1) maternal e-cig exposure will lead to increased arterial stiffness and reduced vascular reactivity in aorta and middle cerebral artery, and this impairment will be at least partially mediated by the nitric oxide pathway; and 2) pups exposed to e-cig aerosol in utero will demonstrate hyperactivity, exploratory behavior, and impaired spatial and aversive learning as well as impaired memory. The specific aims are to (1) determine dose-dependent effect of maternal e-cig vapor exposure (with and without nicotine) on arterial stiffness and vascular reactivity in offspring and (2) evaluate cognitive development

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.334
Teacher spread0.307 · 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 designObservational
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

Citations1
Published2022
Admission routes1
Has abstractyes

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