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Record W2567319477 · doi:10.1002/jcp.25751

Super‐resolution structure of DNA significantly differs in buccal cells of controls and Alzheimer's patients

2016· article· en· W2567319477 on OpenAlexafffund
Ángeles García, David Huang, Amanda Righolt, Christiaan H. Righolt, Maria Carmela Kalaw, Shubha Mathur, Elizabeth McAvoy, James W. Anderson, Angela Luedke, Justine Itorralba, Sabine Mai

Bibliographic record

VenueJournal of Cellular Physiology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of ManitobaCancerCare ManitobaQueen's University
FundersCanada Foundation for Innovation
KeywordsBuccal administrationDNABuccal swabCell nucleusBiologyNucleusNuclear DNAResolution (logic)Alzheimer's diseaseCell biologyMolecular biologyBiophysicsPathologyDiseaseMedicineGeneticsGeneMitochondrial DNABioinformatics

Abstract

fetched live from OpenAlex

The advent of super-resolution microscopy allowed for new insights into cellular and physiological processes of normal and diseased cells. In this study, we report for the first time on the super-resolved DNA structure of buccal cells from patients with Alzheimer's disease (AD) versus age- and gender-matched healthy, non-caregiver controls. In this super-resolution study cohort of 74 participants, buccal cells were collected and their spatial DNA organization in the nucleus examined by 3D Structured Illumination Microscopy (3D-SIM). Quantitation of the super-resolution DNA structure revealed that the nuclear super-resolution DNA structure of individuals with AD significantly differs from that of their controls (p < 0.05) with an overall increase in the measured DNA-free/poor spaces. This represents a significant increase in the interchromatin compartment. We also find that the DNA structure of AD significantly differs in mild, moderate, and severe disease with respect to the DNA-containing and DNA-free/poor spaces. We conclude that whole genome remodeling is a feature of buccal cells in AD.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.005
GPT teacher head0.222
Teacher spread0.218 · 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.

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

Citations15
Published2016
Admission routes2
Has abstractyes

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