MétaCan
Menu
Back to cohort
Record W4381619694 · doi:10.1093/humrep/dead093.662

P-304 Does imaging affect embryo health? Comparative analysis of discrete wavelengths of light on the developing embryo

2023· article· en· W4381619694 on OpenAlexaff
Kari Dunning, C A Campugan, M Lim, D. H. Chow, T. Tan, T Li, Anil Kumar Saini, Antony Orth, Philipp Reineck, Erik P. Schartner, Jeremy G. Thompson, Kishan Dholakia

Bibliographic record

VenueHuman Reproduction · 2023
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsEmbryoWavelengthBlastocystOffspringEmbryo transferPregnancyAndrologyBiologyEmbryogenesisMedicineOpticsGeneticsPhysics

Abstract

fetched live from OpenAlex

Abstract Study question What is the effect of exposing the embryo to discrete wavelengths of light on preimplantation development and resultant offspring health? Summary answer Exposure of embryos to red or yellow wavelengths negatively impacted embryo health, pregnancy rate and resulted in offspring that were heavier at weaning. What is known already Previous studies have indicated a potential negative impact of shorter wavelengths of light on embryo health. Red and yellow wavelengths are widely considered benign and utilised clinically in time-lapse equipped incubators within IVF clinics. However previous studies had not uniformly and correctly irradiated embryos to enable a fair comparison between different wavelengths. Study design, size, duration A current aim of the field is to use optical imaging to predict embryo developmental potential. Such approaches use varying wavelengths of light. The impact of irradiating the embryo with discrete wavelengths of light is not fully understood. Here, we assess the impact of various wavelengths on the developing embryo and for the first time, ensured that the energy dose applied was consistent between wavelengths, thus mimicking fluorescence and time-lapse imaging (470 – 620 nm). Participants/materials, setting, methods Preimplantation mouse embryos were exposed daily to blue (470 nm), green (520 nm), yellow (590 nm) or red (620 nm) wavelengths and compared to embryos that were not exposed. We assessed embryo development, DNA damage, and postnatal outcomes following transfer to pseudopregnant recipients. Main results and the role of chance We found exposure to the yellow wavelength significantly impaired embryo development to the blastocyst stage (P < 0.05). While exposure to blue, green and red wavelengths resulted in significantly higher levels of DNA damage when compared to unexposed embryos (P < 0.05). The pregnancy rate was significantly lower when embryos were exposed to the red wavelength (P < 0.05). Interestingly, resultant offspring were significantly heavier when derived from red or yellow light exposed embryos compared to those derived from unexposed embryos (P < 0.01). Towards understanding the effect on offspring weight we assessed intracellular lipid abundance in the embryo. We found lipid abundance to be significantly elevated following exposure to yellow wavelength (1.8-fold, P < 0.0001) but not red. We believe that the role of chance is low as results were collected from multiple independent experimental replicates that were tested using appropriate statistical analyses. Limitations, reasons for caution While we demonstrate the distinct impacts of discrete wavelengths of light on the developing mouse embryos including post-natal effects, confirmation of these results in human embryos is required. Wider implications of the findings Red and yellow wavelengths are utilised clinically in time-lapse equipped incubators within IVF clinics. Our results demonstrate the potential need to re-evaluate these assumptions. Mapping the stress tolerance embryos show for each wavelength may be advantageous in identifying how damage can be mitigated in clinical manipulation and imaging techniques. Trial registration number not applicable

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)0.001
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 score0.601
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.043
GPT teacher head0.351
Teacher spread0.308 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHuman ReproductionSame topicAssisted Reproductive Technology and Twin PregnancyFrench-language works237,207