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Record W3135594715 · doi:10.29252/wjps.10.1.53

Histological Changes in Adipose Tissue: An Alarm When Methamphetamine Is Targeted for Weight Loss Purposes

2021· article· en· W3135594715 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWORLD JOURNAL OF PLASTIC SURGERY · 2021
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsUniversity of Alberta
FundersShiraz UniversityShiraz University of Medical SciencesIslamic Azad University
KeywordsAdipose tissueMedicineMethamphetamineWeight lossALARMPathologyBioinformaticsPharmacologyInternal medicineObesityBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Methamphetamine (METH) may be administered for weight loss purposes and to understand the METH side-effects more in details, this study aimed at determining the effect of METH on changes in adipose tissue in experimental rats. METHODS: group was the control receiving distilled water, identically. The elevated plus maze test was used to confirm cognitive impairment and distraction as anxiety and to verify addiction to METH by assessing the percent time spent in open arm (OAT), the percent time spent in closed arm (CAT), the percent time spent in central parts and head dipping over the side of the maze. Adipose tissue was assessed histologically 7, 14 and 21-days after interventions. RESULTS: A significant increase in anxiety level, and histologically inflammation, degeneration and necrosis in adipose tissue were visible after METH use. CONCLUSION: METH use resulted in a significant inflammation and necrosis in adipose tissue denoting to the dangers of METH use, when recreationally targeted for weight loss purposes.

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.

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)0.002
metaresearch head score (Gemma)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.083
GPT teacher head0.377
Teacher spread0.294 · 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