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Record W1561552992

Technical brief: isolation of total DNA from postmortem human eye tissues and quality comparison between iris and retina.

2012· article· en· W1561552992 on OpenAlexaff
Jay Ching Chieh Wang, Aikun Wang, Jiangyuan Gao, Sijia Cao, Idris Samad, Dean Zhang, Carol Ritland, Jing Cui, Joanne A. Matsubara

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIRIS (biosensor)GenotypingBiologySingle-nucleotide polymorphismgenomic DNARetinaMacular degenerationGenotypeGeneticsComputational biologyDNAGeneOphthalmologyMedicineNeuroscienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Recent genomic technologies have propelled our understanding of the mechanisms underlying complex eye diseases such as age-related macular degeneration (AMD). Genotyping postmortem eye tissues for known single nucleotide polymorphisms (SNPs) associated with AMD may prove valuable, especially when combined with information obtained through other methods such as immunohistochemistry, western blot, enzyme-linked immunosorbent assay (ELISA), and proteomics. Initially intending to genotype postmortem eye tissues for AMD-related SNPs, our group became interested in isolating and comparing the quality of DNA from the iris and retina of postmortem donor eyes. Since there is no previously published protocol in the literature on this topic, we present a protocol suitable for isolating high-quality DNA from postmortem eye tissues for genomic studies. METHODS: DNA from 33 retinal samples and 35 iris samples was extracted using the phenol-chloroform-isoamyl method from postmortem donor eye tissues. The quantity of DNA was measured with a spectrophotometer while the quality was checked using gel electrophoresis. The DNA samples were then amplified with PCR for the complement factor H (CFH) gene. The purified amplified products were then genotyped for the SNPs in the CFH gene. RESULTS: Regarding concentration, the retina yielded 936 ng/μl of DNA, while the iris yielded 78 ng/μl of DNA. Retinal DNA was also purer than iris DNA (260/280=1.78 vs. 1.46, respectively), and produced superior PCR results. Retinal tissue yielded significantly more DNA than the iris tissue per mg of sample (21.7 ng/μl/mg vs. 7.42 ng/μl/mg). Retinal DNA can be readily amplified with PCR, while iris DNA can also be amplified by adding bovine serum albumin. Overall, retinal tissues yielded DNA of superior quality, quantity, and suitability for genotyping and genomic studies. CONCLUSIONS: The protocol presented here provides a clear and reliable method for isolating total DNA from postmortem eye tissues. Retinal tissue provides DNA of excellent quantity and quality for genotyping and downstream genomic studies. However, DNA isolated from iris tissues, and treated with bovine serum albumin, may also be a valuable source of DNA for genotyping and genomic studies.

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)0.003
metaresearch head score (Gemma)0.010
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: Methods · Consensus signal: Methods
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.020

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 head0.029
GPT teacher head0.295
Teacher spread0.266 · 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
GenreMethods

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

Citations7
Published2012
Admission routes1
Has abstractyes

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