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MOLECULAR AND CELLULAR MECHANISMS REGULATING EPIGENETIC CELL CONVERSION

2019· dissertation· en· W2979555137 on OpenAlexfundno aff
Elena F. M. Manzoni

Bibliographic record

VenueArchivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) · 2019
Typedissertation
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsnot available
FundersCarraresi FoundationEuropean Foundation for the Study of DiabetesUniversità degli Studi di Milano
KeywordsEpigeneticsComputational biologyBiologyCell biologyGeneticsGene

Abstract

fetched live from OpenAlex

Phenotype definition is controlled by epigenetic regulations that allow cells to acquire their differentiated state. The process is reversible and cells can be driven back to a higher plasticity state with several different approaches, which include the interaction with the epigenetic set up through the use of epigenetic erasers, readers or writers. Among the many epigenetic modifiers presently available, in our previous experiments, we selected 5-azacytidine (5-aza-CR), which is a well-known DNA methyltransferase inhibitor, and has been previously shown to increase cell plasticity and facilitate phenotype changes in different cell types. Beside the epigenetic mechanisms driving cell conversion processes, growing evidences highlight the importance of mechanical forces that directly influence cell plasticity and differentiation. Aims of my PhD were: a) characterization of the molecular and cellular mechanisms regulating cell phenotype b) analysis of the possible relation between mechano-sensing and epigenetic control of cell plasticity and differentiation. The experiments carried out confirmed the global demethylating effect of 5-aza-CR, with a transient upregulation of pluripotency markers. At the same time increased transcription of TET2 and several histones was detected. This was accompanied by changes in enzymes controlling histone acetylation and cell morphological rearrangement. Interestingly, the study of DNA methylation profile and its regulatory genes, revealed that the use of a 3D micro-bioreactor promotes and stabilizes the maintenance of the acquired plasticity for a long period of culture. In particular, the use of an adequate soft substrate increased pancreatic conversion efficiency and induced the acquisition of a mono-hormonal phenotype, which is distinctive of terminally matured cell. Altogether these findings indicate that 5-aza-CR induced somatic cell transition to a higher plasticity state may be the result of multiple regulatory mechanisms that accompany the demethylating effect exerted by the modifier. The results described in my thesis also revealed that mechano-transduction-related responses modulate and maintain 5-aza- CR induced cell plasticity and significantly improve cell differentiation toward the pancreatic lineage.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.435
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.215
Teacher spread0.206 · 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.

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
Published2019
Admission routes1
Has abstractyes

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