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TRANSIENT TELOMERASE EXPRESSION IN NORMAL SOMATIC CELLS LEADS TO TELOMERE EXTENSION AND INCREASED PROLIFERATION IN THE ABSENCE OF MALIGNANT TRANSFORMATION

2004· article· en· W2063862748 on OpenAlexaff
Adrian Young, Jonathan R. T. Lakey, Ronald B. Moore

Bibliographic record

VenueTransplantation · 2004
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTelomeraseTelomereTelomerase reverse transcriptaseTransfectionMalignant transformationBiologyCell growthMolecular biologyCell biologyCancer researchCell cultureDNAGeneticsGene

Abstract

fetched live from OpenAlex

O276* Aims: Progressive loss of telomeres through cell division leads to cell cycle arrest and apoptosis rendering cells incapable of unlimited tissue repair. This limited capacity reduces allograft survival as a result of injury from acute and chronic rejection. In this study, normal endothelial cells were rescued from telomere shortening via the transient expression of human telomerase (hTERT) to reverse replicative senescence. We hypothesized that this transient telomerase activity imparts a growth advantage to these cells via telomere maintenance without causing a malignant phenotype. Methods: Telomerase activity in hTERT-transfected normal human umbilical vein endothelial cells (HUVECs) was assessed using the telomeric repeat amplification protocol (TRAP). Telomere length in HUVECs was examined before and after telomerase transfection with Effectene. A flow-FISH procedure was used with a FITC-labelled telomere-specific PNA probe containing sequence complementary to telomeric DNA. The signal intensity of fluorescence was standardized into molecules of equivalent soluble fluorochrome (MESF) unit (M) that directly correlates to telomere length. HeLa cells was used as controls in the different assays that evaluate telomerase activity, as well as biological function and malignant transformation utilizing standard protocols in soft agar and matrigel respectively. Results: A decline in telomere length, as a function of culture passage, was detected in normal aging HUVECs. HUVECs, at escalating passage numbers (p), showed mean MESF values of 53±16.0 kM (n=4):p5-7, 40±7.8 kM (n=6):p10-13, 28±5.3 kM (n=5):p14-17, 24±3.5 kM (n=4):p18-20 and 20±3.2 kM (n=3):p21-23. Following hTERT transfection, variable telomere extension was found in both young and senescing cultures whose DNA uptake efficiency was not significantly hampered by age (17±2.52% vs 12±1.55%, p>0.05). The net increase in telomere length ranged from 2 to 222 kM for HUVECs between p5 and p23. Telomerase activity peaked on day 2 post-transfection and returned to baseline levels, similar to untransfected and heat-denatured controls, on day 5. Peaked activity was 4% of that observed in HeLa positive controls. Whereas HeLa cells lacked tubule formation, hTERT-expressing HUVECs demonstrated vessel sprouting on matrigel, which was also observed with normal HUVECs. Only HeLa cells formed colonies on soft agar indicative of malignant transformation. Although untransformed, hTERT-transfected HUVECs showed an increase in proliferation. Proliferation index in terms of %S-phase cycling cells in hTERT-transfected cultures displayed a net increase of up to 7% despite in-vitro aging. Such an increase led to a more rapid cell recovery following serum starvation compared to HUVECs transfected with an irrelevant β-galactosidase vector. Conclusions: Transient telomerase expression leads to telomere lengthening in normal somatic cells, which can potentially increase cellular lifespan. While telomerase activity boost cell proliferation, it does not cause malignant transformation rendering it a feasible gene therapeutic strategy to prolong allograft survival.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.001

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 head0.013
GPT teacher head0.249
Teacher spread0.237 · 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

Citations2
Published2004
Admission routes1
Has abstractyes

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