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Record W3097829292 · doi:10.1002/jms.4671

A matrix‐assisted laser desorption/ionization imaging mass spectrometric approach to study weight‐related changes within thyroid tissue

2020· article· en· W3097829292 on OpenAlexaff
Assim A. Alfadda, Hicham Benabdelkamel, Amany Fathaddin, Ibrahim O. Alanazi, Nidia Lauzon, Pierre Chaurand, Afshan Masood

Bibliographic record

VenueJournal of Mass Spectrometry · 2020
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversité de MontréalMcGill University Health Centre
Fundersnot available
KeywordsChemistryThyroidReceiver operating characteristicInternal medicineThyroid diseaseBody mass indexEndocrinologyMedicine

Abstract

fetched live from OpenAlex

Obesity is associated with numerous comorbidities along with abnormalities of the endocrine system, more commonly manifesting as dysfunctions of the thyroid gland such as goiter. Changes in weight, especially an increase, could lead to an increase in the incidence of thyroid dysfunction; however, its pathophysiology remains to be elucidated. In the present study, we aimed to interrogate the changes in the protein distribution and abundance between the lean patients and patients with obesity thyroid tissue sections through utilizing this technique. The FFPE-fixed thyroid tissue blocks from the selected cases and controls were identified and targeted for matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) analysis. Patients in the 30 to 75 years age group and undergoing total thyroidectomy for benign thyroid disease were recruited. Patients with thyroid cancers, autoimmune disorders, and other inflammatory conditions were excluded from the study. The selected patients were divided into two groups according to their BMIs: lean (BMI < 25) and obese (BMI > 35). An initial trial set was used as a pilot study for the optimization of the MALDI IMS protocol that was next applied to the selected thyroid tissues. MALDI IMS data from all the samples were aligned and statistical analysis carried out by k-means and linear discriminant analysis (LDA) classification model using principle component analysis (PCA) results were evaluated between the two groups: controls (lean) and cases (obese). Receiver operator characteristic (ROC) curves were alternatively used to calculate the variability of the identified peptides. The discriminating peptides were also independently identified and related to their corresponding proteins by using liquid chromatography and tandem mass spectrometry (LC-MS/MS) analyses. Eight peptides mainly from thyroglobulin were found to be upregulated whereas 10 others were found to be downregulated in the lean compared to the obese group. Through this technique, we will be able to better understand the relationship between the disease entity and obesity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.123
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.007
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.265
Teacher spread0.249 · 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.

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
Published2020
Admission routes1
Has abstractyes

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