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Record W3134037066 · doi:10.1097/rct.0000000000001141

Quantitative Analysis of Mobile Proteins in Normal Brain Tissue by Amide Proton Transfer Imaging: Age Dependence and Sex Differences

2021· article· en· W3134037066 on OpenAlexaboutno aff
Kazuaki Sugawara, Tosiaki Miyati, Ryo Ueda, Daisuke Yoshimaru, Masanobu Nakamura, Shuhei Komatsu, Kazuchika Hagiwara, Kuniyasu Saigusa

Bibliographic record

VenueJournal of Computer Assisted Tomography · 2021
Typearticle
Languageen
FieldMaterials Science
TopicLanthanide and Transition Metal Complexes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMagnetic resonance imagingNuclear magnetic resonanceNuclear medicineConfidence intervalNeuroimagingInternal medicineRadiology

Abstract

fetched live from OpenAlex

PURPOSE: The aims of this study were to evaluate the relationship between age change and amide proton transfer (APT) signal in each region of the whole brain and to derive the standard value of APT signal in each brain region of normal adults. MATERIALS AND METHODS: Using the mDIXON 3-dimensional-APT sequence of the fast spin echo method, an APT image was obtained. In total, 60 patients (mean age, 49.8 ± 16.9 years) with no abnormal findings on magnetic resonance imaging data were included. For image analysis, registration parameters were created using the FMRIB Software Library 5.0.11, and then a region of interest was set in the Montreal Neurological Institute structural atlas for analysis. Statistical analyses were performed using the age-dependent and sex differences in APT signals from each brain region. RESULTS: No significant correlation was seen between APT signal and age and sex in all brain regions. CONCLUSION: Under the APT imaging parameter conditions used in this study, local brain APT signals in healthy adults are independent of age and sex.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.273
Teacher spread0.258 · 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 designObservational
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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Computer Assisted TomographySame topicLanthanide and Transition Metal ComplexesFrench-language works237,207