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Record W7062566623

TNF-alpha and hypoxia-induced paracrine secretion of rat bone marrow-mesenchymal stem cells for cardiac repair in Lewis rats post-ml

2017· dissertation· en· W7062566623 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2017
Typedissertation
Languageen
FieldEngineering
TopicThermal Analysis in Power Transmission
Canadian institutionsnot available
FundersMcGill University Health Centre
KeywordsParacrine signallingSecretionHoming (biology)Mesenchymal stem cellStem cellWestern blotImmunocytochemistryHypoxia (environmental)Cell culture
DOInot available

Abstract

fetched live from OpenAlex

Bone-marrow mesenchymal stem cell (BM-MSC) strategies have been suggested to play a crucial role in promoting the reparative process in ischemic hearts following a myocardial infarction (MI). However, poor viability and retention of transplanted cells in the harsh microenvironment remains as an obstacle. The paracrine hypothesis suggests that BM-MSCs secrete paracrine factors consisting of biologically active molecules that may work together to manipulate the microenvironment and trigger angiogenesis, cardioprotective, and homing properties at the site of infarct. The current study aims to understand the regulatory effects of Tumour Necrosis Factor-α (TNF-α) and hypoxia on rat BM-MSCs (rBM-MSC) and the angiogenic, migratory, cardioprotective, and reparative effects of its secretion which may, initiate and sustain the process of cardiac repair post MI. Secretome from rBM-MSC cultures treated/untreated with either conditioned rat cardiomyocyte medium (rCCM), TNF-α, and/or normoxia/hypoxia in various combinations were examined. Immunocytochemistry and western blot analyses confirmed the presence of the TNF-Receptors 1 and 2 (TNFR1/TNFR2) on the surface of rBM-MSCs, which indicates that TNF-α is able to bind to rBM-MSCs and initiate cell survival pathways through the TNFR2 pathway. Western blot analyses on rBM-MSC lysates treated with rCCM, TNF-α and hypoxia showed increased expression of TGF-β, FGF-2, VEGF-1, Myogenin, and Ang-2. Thus, indicating that in hypoxic conditions, TNF-α induces rBM-MSCs to secrete proteins that contribute to neovascularization; MSC/endothelial cell (EC) proliferation, migration or differentiation; and/or decreasing acute pro-inflammatory responses. Furthermore, the trans-well migration assay showed that the TNF-α Hypoxia-Induced secretome exhibits chemotactic properties, which may play a role in the migration of BM-MSCs to the site of infarct. The Annexin V apoptosis assay revealed that the TNF-α Hypoxia-Induced secretome treatment on rCMs under hypoxia does not show a statistically significant difference between the values for the control cells (rCMS with hypoxia only) and itself. Accordingly, there may be no significant difference in the number of apoptotic rCMs, as the presence of the TNF-α cytokine itself may be reducing the pro-survival effect of the secreted secretome. In vivo, induced infarcted Lewis rats treated with TNF-α Hypoxia-Induced secretome had a higher left ventricle fractional shortening (LVFS) than the control secretome (rCCM and hypoxia) treated rats, while trichrome staining revealed a decrease in the size of infarct. Hence, a higher LVFS and the decrease in the size of infarct in the TNF-α hypoxia-induced secretome treated Lewis rats show that myocardial preservation maybe occurring. Lastly, immunohistochemistry revealed increased expression of CD31 and Ki67 proteins near the area of infarct in the TNF-α Hypoxia-Induced secretome treated rats. The presence of the CD31 and Ki67 markers indicate an increase in vessel formation and proliferation at the site of infarct in TNF-α hypoxia-induced secretome treated rats. These findings suggest that the paracrine secretion of TNF-α and hypoxia preconditioned BM-MSCs may play a therapeutic role in cardiac repair post-MI.

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 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 score0.089
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.230
Teacher spread0.217 · 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
Published2017
Admission routes1
Has abstractyes

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