TNF-alpha and hypoxia-induced paracrine secretion of rat bone marrow-mesenchymal stem cells for cardiac repair in Lewis rats post-ml
Bibliographic record
Abstract
Background: Due to the limited regenerative capacity of mammalian cardiomyocytes, following a myocardial infarction (MI) the chronic loss of functional contractile myocardium and continuous inflammation degrade the structure and function of the heart.Although bone-marrow mesenchymal stem cell (BM-MSC) strategies have been suggested to play a crucial role in promoting the repairing process in ischemic hearts, 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.Tumour Necrosis Factor-α (TNF-α) is a pleiotropic proinflammatory cytokine present in ischemic cardiac regions, but the specific roles it plays in cardioprotection and its interaction with BM-MSCs have yet to be established.The current study aims to understand the regulatory effects of TNF-α and hypoxia on rat BM-MSCs (rBM-MSC) and the angiogenic, migratory, cardioprotective, and reparative effects of its secretions which may, initiate and sustain the process of cardiac repair following MI.Methods: Secretome from rBM-MSC cultures treated/untreated with either conditioned rat cardiomyocyte medium (rCCM), TNF-α, and/or normoxia/hypoxia in various combinations were collected.Immunocytochemistry, western blot analyses, trans-well cell migration, and Annexin V apoptosis assays in conjunction with fluorescence-activated cell sorting were conducted.In vivo, echocardiography was performed on induced infarcted rats at three weeks following their treatment with a control (rCCM and hypoxia) or TNF-α Hypoxia-Induced secretome.Histological analyses including Masson's Trichrome staining and immunohistochemistry (IHC) for the CD31 and Ki-67 markers were further conducted.Image J and Prism were used for graphing and statistical analysis.Results: The immunocytochemistry and western blot analyses confirmed the presence of the TNF-Receptors 1 and 2 (TNFR1/TNFR2) on the surface of rBM-MSCs.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, while decreased expression of Ang-1 and FGF-7.The trans-well migration assay showed that TNF-α Hypoxia-Induced secretome exhibits chemotactic properties.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 for providing me with the opportunity to experience the highest level of translational research in the field of cardiology at the MUHC's Myocardial Regeneration Lab.Thank you for your kind support and guidance throughout this journey in helping me fulfill my passion in research and further advancing my knowledge in the field of cardiac research.I would like to extend my sincere thanks to the members of my advisory committee: Dr. Maria Petropavlovskaya, Dr. Fackson Mwale, and Dr. Jacques Lapointe for their time, support, and contributions to furthering my knowledge and for challenging me in successfully understanding and acquiring the skills and knowledge required to excel as a graduate student.I would like to offer my special
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".