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Record W2100941174 · doi:10.1002/cyto.10053

Telomere length measurement by fluorescence in situ hybridization and flow cytometry: Tips and pitfalls

2002· article· en· W2100941174 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCytometry · 2002
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersNational Institute of Allergy and Infectious DiseasesNational Science FoundationNational Institutes of HealthNational Cancer InstituteBernische KrebsligaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsTelomereFluorescence in situ hybridizationMolecular biologyFlow cytometryBiologyPeptide nucleic acidSouthern blotIn situ hybridizationDNAChemistryChromosomeGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: Telomeres containing noncoding DNA repeats at the end of the chromosomes are essential for chromosomal stability and are implicated in regulating the replication and senescence of cells. The gradual loss of telomere repeats in cells has been linked to aging and tumor development and methods to measure telomere length are of increasing interest. At least three methods for measuring the length of telomere repeats have been described: Southern blot analysis and quantitative fluorescence in situ hybridization using either digital fluorescence microscopy (Q-FISH) or flow cytometry (flow-FISH). Both Southern blot analysis and Q-FISH have specific limitations and are time-consuming, whereas the flow-FISH technique requires relatively few cells (10(5)) and can be completed in a single day. A further advantage of the flow-FISH method is that data on the telomere length from individual cells and subsets of cells (lymphocytes and granulocytes) can be acquired from the same sample. In order to obtain accurate and reproducible results using the flow-FISH technique, we systematically explored the influence of various steps in the protocol on telomere length values and established an acceptable range for the most critical parameters. METHODS: Isolated leukocytes from whole blood are denatured by heat and 70%/75% formamide, then hybridized with or without a telomere-specific fluorescein isothiocyante (FITC)-conjugated peptide nucleic acid probe (PNA). Unbound telomere PNA is washed away, the DNA is counterstained, and telomere fluorescence is measured on a flow cytometer using an argon ion laser (488 nm) to excite FITC. For each sample, duplicates of telomere PNA-stained and unstained tubes are analyzed. RESULTS: Cell counts and flow-FISH telomere length measurements were performed on leukocytes and thymocytes of humans and other species. Leukocyte suspensions were prepared by two red blood cell lysis steps with ammonium chloride. Optimal denaturation of DNA was achieved by heating at 85-87 degrees C for 15 min in a solution containing 70%/75% formamide. Hybridization was performed at room temperature with a 0.3 microg/ml telomere-PNA probe for at least 60-90 min. Unbound telomere-PNA probe was diluted at least 4,000-40,000 times with wash steps containing 70%/75% formamide at room temperature. LDS 751 and DAPI were suitable as DNA counterstains as they did not show significant interference with telomere length measurement. CONCLUSIONS: The use of flow-FISH for telomere length measurements in nucleated blood cells requires tight adherence to an optimized protocol. The method described here can be used to determine rapidly the telomere length in subsets of nucleated blood cells.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.232
Teacher spread0.207 · 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