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Record W4283316269 · doi:10.1002/jcb.30301

Induction of endoplasmic reticulum stress markers in an acromegaly model

2022· article· en· W4283316269 on OpenAlexaff
Abdalla Elbialy, Kaidiliayi Sulidan, Afsana Bhuiyan, Yoji Igarashi, Kazutoshi Yoshitake, Dai Yamanouchi, Junsu Kang, Shuichi Asakawa, Shugo Watabe, Shigeharu Kinoshita

Bibliographic record

VenueJournal of Cellular Biochemistry · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsSaint Paul University
Fundersnot available
KeywordsAcromegalyUnfolded protein responseXBP1Endoplasmic reticulumSomatic cellRNA splicingInternal medicineEndocrinologyMedicineBiologyHormoneCell biologyGeneGeneticsGrowth hormoneRNA

Abstract

fetched live from OpenAlex

Acromegaly is a growth hormone (GH) excess pathological condition in humans. Acromegaly is associated with somatic disfigurement and a wide range of systemic manifestations such as arthritis, neuropathy, carpal tunnel syndrome, reproductive disorders, metabolic disorders, and gastrointestinal complications. The influence of excess GH on the cellular level could aid in understanding the root causes of acromegaly-related health complications. Previously, we found that GH excess induces DNA damage to somatic cells and reduces the stem cells number and causes premature aging. In this study, an in-depth analysis of the acromegaly RNAseq data revealed the disruption of important biological cellular processes. Gene set enrichment analysis, heatmap, and enrichment analysis of acromegaly RNAseq data revealed induction of endoplasmic reticulum (ER) stress markers in various organs. Interestingly, the induction of ER stress was even more apparent than in aged zebrafish. Splicing of box-binding protein-1 (XBP1) mRNA is a hallmark of ER stress. Therefore, we quantified spliced XBP1 mRNA in different organs of our acromegaly model. Thus, our study emphasizes the importance of ER stress in GH oversecretion, which is important for understanding the health complications of acromegaly.

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 score0.018
Threshold uncertainty score0.717

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 head0.007
GPT teacher head0.230
Teacher spread0.223 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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