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Record W2594206110 · doi:10.1093/biolreprod/85.s1.767

Understanding Oxidative Stress in Donor Fibroblasts for Enhancing Reprogramming Efficiency.

2011· article· en· W2594206110 on OpenAlexaffabout
Andrea Hunt, W.A. King, Dean H. Betts, Pavneesh Madan

Bibliographic record

VenueBiology of Reproduction · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsWestern UniversityUniversity of Guelph
Fundersnot available
KeywordsReprogrammingCell biologyBiologyOxidative stressSenescenceSomatic cellReactive oxygen speciesSomatic cell nuclear transferMitochondrionStem cellCellBiochemistry

Abstract

fetched live from OpenAlex

The low success rate of cloning by somatic cell nuclear transfer can be attributed to the remarkable difficulty in reprogramming differentiated donor nuclei. Reports indicate this is largely due to differentiated cells having undergone epigenetic modifications, telomere shortening and oxidative stress accumulation as they age, resulting in a decreased ability to generate induced pluripotent stem cells. Cellular senescence, the irreversible loss of replicative capacity in cells, is a significant barrier to transgenesis and somatic cell nuclear reprogramming in mammals. Cellular senescence can be triggered prematurely by exposure to reactive oxygen species (ROS)-induced oxidative stress. p66shc, a stress sensor that may be linked to ROS-induced senescence, has been suggested to trigger apoptotic responses by generating mitochondrial H2O2 in response to exogenous H2O2 exposure. This interaction increases the amount of oxidative stress experienced within a cell and may contribute to the difficulties of nuclear reprogramming differentiated somatic cells. The purpose of this study was to examine the role of p66Shc in the ROS-mediated somatic cell senescence response. Bovine fibroblasts were treated for two hours with H2O2 concentrations 25 micromol/L, 50 micromol/L, 100 micromol/L, 150 micromol/L and 200 micromol/L in order to determine the effects of ROS on the expression of p66Shc and on the induction of the senescence signaling pathway. Post H2O2 treatment, cells were treated with pharmacological inhibitor Juglone to modulate p66shc activity by inhibiting its translocation into the mitochondria via peptidly propyl isomerase-1 (PIN1). Bongkrekic Acid and Difumarate, pharmacological inhibitors that inhibit the opening of mitochondrial permeability transition pores (MPTP), and interfere with mitochondrial membrane potential, respectively, were used to prevent the subsequent release of mitochondrial ROS into the intracellular environment. Following treatment with pharmacological inhibitors, the number of floating dead cells was quantified using a hemocytometer. Cells sticking to the bottom of the culture dish were then washed with fresh media and cultured for either 24 hours or 72 hours. Senescent cells were detected using a SA-beta-galactosidase staining assay. Real-time PCR was used to quantitatively assess altered expression of critical genes regulating mitochondrial ROS-mediated signaling: p66shc, PIN1, ANT3, Hsp70 and COX. Results indicate that as H2O2 dosage increases, apoptosis increases; however, SA-beta-galactosidase measured senescence decreases. This indicates cells are sensitive to rising levels of H2O2 and make a choice to enter senescence based on the oxidative insult they face. Low levels of p66shc expression are associated with senescence, while high levels are associated with apoptosis. These results indicate that the presence of exogenous H2O2 induces the modulation of p66shc expression, suggesting that p66Shc may serve as an integration point for ROS-mediated senescence signaling. Future studies would focus on alleviating senescence in bovine cultures to enhance reprogramming efficiency. Funding provided by the Canadian Institute of Health Research. (poster)

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.071
GPT teacher head0.280
Teacher spread0.209 · 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
Published2011
Admission routes2
Has abstractyes

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