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Record W2594324040 · doi:10.14740/jem.v7i1.405

Circulating Betatrophin and Hepatocyte Growth Factor in Type 2 Diabetic Patients: Their Relationship With Disease Prognosis

2017· article· en· W2594324040 on OpenAlexvenueno aff
Abdulrahman Alduraywish

Bibliographic record

VenueJournal of Endocrinology and Metabolism · 2017
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineBody mass indexGlycemicDiabetes mellitusInsulinAnthropometryHepatocyte growth factorRisk factorEndocrinologyGastroenterology

Abstract

fetched live from OpenAlex

Background: In Saudi Arabia, diabetes established itself as an epidemic that necessitates dissection of its predisposing factors and pathogenesis to set appropriate preventive measures. In a cross-sectional study, relationships between plasma betatrophin (BetaT) and hepatocyte growth factor (HGF) on one side, and, glycemic control, lipogram, anthropometric indices, treatment and prognosis on the other side were assessed in Saudi patients with type 2 diabetes mellitus (T2DM) vs. healthy controls. Methods: The study voluntarily enrolled 202 T2DM patients (44 males and 158 females) and socioeconomically, age- and body mass index (BMI)-matched 106 healthy participants (71 males and 35 females). All participants were subgrouped according to gender and BMI ( = 25) and patients were also subgrouped according to disease duration ( 5 years) and treatment (insulin/non-insulin). Demographic and anthropometric data were anonymously collected. EDTA whole blood for HbA1c and its plasma for bioassays were frozen at -80 °C. Standard procedures and specific immunoassays were employed for biomarkers. Results: Plasma insulin paralleled BMI and disease duration and was highly significantly different comparing patients and healthy controls. As expected glycemic control and lipogram indices were also highly significantly different comparing patients and healthy controls. Because of the massive individual variation in the plasma levels of each of betatrophin (except for a higher level in patients with lower BMI) and HGF (except for a higher level in females and those with higher BMI among controls), there were non-significant differences comparing patients and healthy controls. Males were more inclined to have more insulin treatment. Surprisingly, the later doubled the disease severity complication score and correlated negatively with plasma HDL-cholesterol. Betatrophin did not show much correlation among controls but correlated negatively with age and cholesterol and positively with BMI and HbA1c in patients. HGF showed very clear negative correlation with age and plasma insulin in patients. Conclusion: The massive individual variation in plasma content of betatrophin and HGF did allow specific diagnostic/pathogenetic classification for these two hepato-/adipokines. This may reflect gene polymorphism at their gene regulatory sequences and/or resistance correlating insulin resistance. The former is being pursued in our laboratory for patients with distinctly higher and lower levels. J Endocrinol Metab. 2017;7(1):31-43 doi: https://doi.org/10.14740/jem405w

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.266
Teacher spread0.240 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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