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Participação do estresse de retículo endoplasmático no processo de morte celular em neutrófilos de ratos diabéticos.

2013· dissertation· pt· W1486152476 on OpenAlexfundno aff
Wilson Mitsuo Tatagiba Kuwabara

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsnot available
FundersHospital for Sick ChildrenFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsUnfolded protein responseEndoplasmic reticulumATF6ATF4Programmed cell deathCell biologyKinaseBiologyChemistryApoptosisBiochemistry

Abstract

fetched live from OpenAlex

Endoplasmic reticulum (ER) has been gaining evidence when it comes to cell death.This organelle may go under stress conditions due to changes in protein formation, lack of ATP, disturbances in calcium signaling and alterations in the redox state.The accumulation of unfolded proteins initiates the activation of the Unfolded Protein Response (UPR).Currently, it is well established that the ER stress response is due to activation of three ER components: Inositol-Requiring kinase 1α (IRE1α), double-stranded RNA-activated protein kinase-like ER kinase (PERK) and Activating transcription factor 6 (ATF6).The UPR may resolve the ER stress by upregulating genes responsible to maintain the ER homeostasis; or it can activate genes that lead to the cell death when the ER disbalance is not solved.Hyperglycemia, one of many symptoms observed is Diabetes, may cause ER stress in various types of cells, for instance, pancreatic β-cells, osteoblasts and cardiomiocytes.Thus, this study aims to investigate the possible involvement of the ER stress in the process of cell death in neutrophils from diabetic rats.ER stress was evaluated by the expression of key genes: GRP78 (Bip), IRE-1, PERK, ATF-6 by PCR real time; the content of proteins related to the PERK pathway: PERK, eIF2α, peIF2α, ATF4, CHOP and GADD34; the content o pJNK, a protein related to cell death that is activated by IRE1α pathway; the content of ATF6 and sXBP1 resulted from the IRE1α activity.Also, the gene expression of MAM proteins related to the association between ER and mitochondria, Mitofusin 2, GRP75 and PACS2, were evaluated.MAM is related to the ER homeostasis and is very importat for calcium and ATP exechange between these twoorganelles.Finally, activity of caspases 3 by spectrofluorimetry and ROS production by chemoluminescence, using luminol, were measured.We observed higher expression of GRP78 (Bip) in the control group and higher expression of IRE1α in the diabetic and control group when they were stimulated with PMA.However, increase in IRE1α was observed in the non-stimulated state only in the diabetic group.This same pattern was observed in CHOP gene expression.The content of peIF2α was higher in the control group without stimulus and the other proteins of the PERK pathway showed no alteration.Gene expression of the MAM proteins was higher in the control group when neutrophils were stimulated with PMA.CHOP content was increased in the diabetic group.Finally, Caspase 3 activity and the reason Bax/Bcl2 were higher in the diabetic group stimulated with PMA.In summary, our study found that neutrophils from diabetic rats when stimulated with PMA exhibit greater susceptibility to death due to activation of IRE1α and subsequent phosphorylation of JNK, reduced safety in mitochondria-ER interaction in the MAM compartment and increased caspase-3 activation.We also conclude that these changes were not altered by ROS, since the two groups, control and diabetic, have the same profile of these species production when stimulated with PMA.Control group seems to be protect against the ER stress by ROS production by higher expression of GRP78 and MAM proteins.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.260
Teacher spread0.253 · 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 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
Published2013
Admission routes1
Has abstractyes

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