Effects of Pharmacological Thermogenic Adipocyte Activation on Metabolism and Atherosclerotic Plaque Regression
Part of the results reproduced; minor but material deviations remained.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Any deviation was negligible
- 🔴Could not use the authors’ exact input data
- 🔴Reported values were only indirectly comparable
- 🟡A deviation arose in the data or preprocessing
- 🔴A deviation was attributed to the published material
- 🟡Reported values were not (fully) derivable from the shared data
- 🟡The central claim did not (fully) hold under reproduction
- 🟡Overall, the reproduction showed a material discrepancy
▸Reproduction agent’s raw note
DROP (non_pipeline). PMID 30813320 (Worthmann et al., Nutrients 2019, 11(2):463, doi:10.3390/nu11020463, PMC6412269) is a purely wet-lab in vivo mouse study: Ldlr-/- mice on Western diet +/- the beta3-agonist CL316,243 for 4 weeks, asking whether pharmacological thermogenic-adipocyte activation regresses atherosclerosis (it does not). All readouts are bench/manual: organ & body weights, food intake, qPCR (TaqMan ddCt vs Tbp), plasma cholesterol/TG enzymatic assays, FPLC lipoprotein profiling, hepatic lipid extraction, and manual Oil-Red-O en-face + aortic-root plaque morphometry; stats = two-tailed Student's t-test, n=7-9. There is NO RNA-seq/microarray/omics, NO GEO/SRA/ENA/figshare/Zenodo accession, NO code repository or computational pipeline, NO Data Availability statement and NO supplementary source-data file (PubMed + PMC full text both checked; MDPI page 403 to bot but PMC mirrors full text). Hence nothing is pipeline-derived and there is no deposited data on which a third-party tool could be run (P16 route impossible too). Not described-well-enough is moot -- there is simply nothing computational to reproduce; this is a text-mining false positive for the study's pipeline-reproduction scope. No «our HPC» compute was spent (correct -- nothing in scope). NOT attempted: any wet-lab measurement (out of scope by design). Dataset profiling: zero deposited datasets (dataset_profile.json datasets=[], no_dataset=true). Honest drop, nothing fabricated.
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Assessment versions
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v1 current initial assessmentassessed: 2026-06-18 ⛓ 0b43b2ff5a61
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Provenance — full disclosure
When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-06-18
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-18no human curator yet
- Last updated
- 2026-08-05
Provisional, curator- or AI-assessed, and independently checkable. A reproduction outcome states what one attempt could reproduce — not a judgement of the authors.
Deep full-text extraction
Model: sonnetThe paper tests whether pharmacological activation of thermogenic adipocytes (via dietary CL316,243) can therapeutically induce regression of established atherosclerotic plaques in LDLR-deficient mice.
- ★ Chronic dietary CL316,243 treatment reduces adiposity and enhances body weight loss independent of food intake in LDLR-deficient mice finding
- ★ CL316,243 treatment pharmacologically activates thermogenic adipocytes, evidenced by BAT activation and browning of ingWAT (reduced lipid droplet size, increased Ucp1/Ppara/Ppargc1a/Lpl expression) finding
- ★ CL treatment alters hepatic lipid metabolism gene expression, reducing Fasn and inducing Cyp7a1 expression finding
- ★ CL treatment reduces plasma triglyceride levels and, non-significantly, plasma cholesterol levels in LDLR-deficient mice finding
- ★ Despite improved adiposity and plasma triglycerides, pharmacologic activation of thermogenic adipocytes does not reduce atherosclerotic plaque burden or lesion severity in LDLR-deficient mice finding
- Dietary switch from HFCS diet to chow diet (with or without CL) itself substantially lowers plasma cholesterol and lipoprotein cholesterol levels finding
- LDLR-deficient mice fed HFCS diet then switched to chow +/- CL316,243 is used as a model of established atherosclerosis regression method
- Thermogenic adipocyte activation clears triglyceride-rich lipoproteins and cholesterol-enriched remnants via intravascular lipolysis and hepatic uptake, contributing to an anti-atherosclerotic lipid phenotype mechanism
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Body weight and food intake monitoring | LDLR-deficient mice (male, 8-week-old, HFCS-fed then chow-switched) | dietary CL316,243 (5 mg/kg chow) vs mock chow | body weight, daily/cumulative food intake, tissue weights (liver, heart, epiWAT, BAT, ingWAT) | — |
| Histology (H&E staining) | BAT and inguinal WAT (ingWAT), LDLR-deficient mice | CL316,243 vs mock | tissue morphology, lipid droplet size | — |
| Quantitative real-time PCR (qPCR) | ingWAT, LDLR-deficient mice | CL316,243 vs mock | expression of Ucp1, Ppara, Ppargc1a, Lpl, Elovl3 | 7900HT sequence detection system, TaqMan Assay-on-Demand |
| Histology (H&E staining) and biochemical lipid quantification | Liver, LDLR-deficient mice | CL316,243 vs mock | liver morphology, liver triglyceride and cholesterol levels | commercial kit (Roche); Amplex Red Cholesterol Assay Kit |
| Quantitative real-time PCR (qPCR) | Liver, LDLR-deficient mice | CL316,243 vs mock | expression of Fasn, Abcg5, Abcg8, Cyp7a1 | 7900HT sequence detection system, TaqMan Assay-on-Demand |
| Plasma lipid analysis and FPLC lipoprotein profiling | Plasma, LDLR-deficient mice | CL316,243 vs mock, over 4 weeks | plasma cholesterol and triglyceride levels; TRL/LDL/HDL fraction cholesterol and triglyceride | Superose 6 10/300 GL column FPLC; Roche kits |
| En face aortic lesion staining and aortic root histology | Aorta and aortic root, LDLR-deficient mice | CL316,243 vs mock | plaque/lesion area (total aorta, abdominal aorta, aortic arch, aortic root), lesion severity classification | Sudan IV staining; ImageJ quantification |
- ▼ CL-treated mice lost significantly more body weight than mock-treated mice despite similar/slightly higher food intake ~7 g weight loss in both groups, greater in CL group
- ▼ EpiWAT weight significantly lower in CL-treated mice; BAT and ingWAT weights trended lower
- ▲ Ucp1, Ppara, and Ppargc1a expression significantly increased in ingWAT of CL-treated mice
- ▲ Lpl expression significantly increased and Elovl3 increased by trend in ingWAT after CL treatment
- – Hepatic Fasn expression modestly reduced and Cyp7a1 expression induced by CL treatment; Abcg5/Abcg8 unchanged
- ▼ Plasma triglycerides diminished starting 2 weeks after CL treatment, unlike mock group which was unchanged by week 4
- ▼ Plasma cholesterol modestly but non-significantly reduced by CL treatment at 4 weeks; TRL cholesterol lower in CL group
- – No difference in lesion area (total aorta, abdominal aorta, aortic arch, aortic root) or lesion severity between CL-treated and control mice
- other 31.3% of global mortality (CVD as proportion of global mortality (background))
- pvalue p < 0.1 (trend reduction in liver triglyceride levels in CL-treated vs mock mice)
- pvalue * p < 0.05, ** p < 0.01, *** p < 0.001 (significance thresholds used for two-tailed Student's t test comparisons)
- mean ~7 g body weight reduction (body weight loss after dietary switch in both mock and CL groups)
- count 12 weeks HFCS feeding followed by 4 weeks chow ± CL (study diet/timeline design)
- count 30 fractions collected at 0.5 mL/min flow rate (FPLC lipoprotein profiling protocol)
Statistical methods review
Model: sonnetA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
The study used a two-group (Mock vs. CL316,243) diet-switch intervention in male LDLR-deficient mice over 4 weeks following 12 weeks of atherogenic diet. All pairwise comparisons between groups across metabolic, histological, and atherosclerosis endpoints were performed with a two-tailed independent Student's t-test. Results were reported as mean ± SEM with threshold-based significance symbols; no multiplicity correction was applied across the many outcomes tested.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Two-tailed independent Student's t-test | Body weight, cumulative food intake, tissue weights (BAT, ingWAT, epiWAT, liver, heart) | — | not stated |
| Two-tailed independent Student's t-test | Gene expression (ΔΔCt qPCR) in ingWAT and liver (Ucp1, Ppara, Ppargc1a, Lpl, Elovl3, Fasn, Abcg5, Abcg8, Cyp7a1) | — | not stated |
| Two-tailed independent Student's t-test | Plasma cholesterol and triglyceride levels at multiple time points (week 0, 1, 2, 4) | — | not stated |
| Two-tailed independent Student's t-test | Liver triglyceride and cholesterol levels | — | not stated |
| Two-tailed independent Student's t-test | En face aortic plaque area (total aorta, abdominal aorta, aortic arch) and aortic root lesion area | — | not stated |
| Two-tailed independent Student's t-test | Aortic root lesion severity classification | — | not stated |
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All group comparisons were made with individual two-tailed t-tests across a large number of endpoints (gene expression panels, lipid time points, plaque metrics, tissue weights)↳ Could also: A false-discovery rate (FDR) correction (e.g., Benjamini-Hochberg) or a Bonferroni adjustment applied across the family of tests could also be used to account for multiple comparisons — When many outcomes are tested simultaneously, some proportion of nominally significant results is expected by chance; FDR or family-wise error rate control makes that proportion explicit and is standard in multi-endpoint preclinical studies
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Repeated plasma lipid measurements (week 0, 1, 2, 4) were analyzed with separate t-tests at each time point↳ Could also: A two-way repeated-measures ANOVA (factors: treatment × time) with a post-hoc correction (e.g., Sidak or Tukey) could also be used for the longitudinal plasma data — Repeated-measures ANOVA accounts for the within-animal correlation across time points and tests the treatment-by-time interaction in a single model, which both increases power and reduces the number of individual tests
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Dispersion was reported as SEM throughout↳ Could also: SD or 95% confidence intervals could also be reported alongside or instead of SEM — SEM describes precision of the mean estimate rather than variability among individual animals; SD or 95% CI communicates biological spread and is often preferred for small-n preclinical studies where between-animal variability is itself informative
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P-values were reported as threshold symbols only (*, **, ***)↳ Could also: Exact p-values (e.g., p = 0.032) could also be reported — Exact p-values allow readers and future meta-analysts to assess effect magnitude more precisely and to apply alternative thresholds, and are now recommended by many journals and reporting guidelines (e.g., Nature journals, APA)
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The lesion severity endpoint was classified into categories (lesion severity score)↳ Could also: An ordinal regression or a non-parametric Mann-Whitney U test could also be applied to ordered categorical lesion severity data — Ordinal or rank-based methods match the measurement scale of categorical severity scores and do not assume the equal-interval spacing that underlies the t-test, which is designed for continuous outcomes
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Sample size and statistical power were not described in the methods↳ Could also: An a priori power calculation based on expected effect sizes from prior studies (e.g., the group's prior APOE3L.CETP atherosclerosis work) could also be reported — A stated power analysis helps readers interpret null results — such as the absence of plaque regression — by making explicit whether the study was adequately powered to detect a biologically meaningful difference in plaque area
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope analysis — PMID 30813320
Title: Effects of Pharmacological Thermogenic Adipocyte Activation on Metabolism and Atherosclerotic Plaque Regression Authors: Worthmann A, Schlein C, Berbée JFP, Rensen PCN, Heeren J, Bartelt A Journal: Nutrients 2019; 11(2):463 · DOI: 10.3390/nu11020463 · PMCID: PMC6412269
What kind of paper is this?
An in vivo wet-lab mouse study. LDLR-deficient (Ldlr⁻/⁻) mice were fed a Western diet ± the β3-adrenergic agonist CL316,243 for 4 weeks to ask whether pharmacological activation of thermogenic (brown/beige) adipocytes can regress established atherosclerosis. Conclusion: it improves adiposity and plasma triglycerides but does not reverse atherosclerosis.
Materials & Methods subsections (from PMC full text)
- Experimental Animals, Housing, Diets, Animal Experiments — wet lab / in vivo
- Plasma Analysis (enzymatic cholesterol/TG kits, FPLC lipoprotein profiling) — wet lab
- Gene Expression Analysis — qPCR (TaqMan Assay-on-Demand, 7900HT, ΔΔCt vs Tbp) — wet lab
- Histology (H&E) — wet lab / manual
- Liver Analysis (lipid extraction/quantification) — wet lab
- Analysis of Atherosclerosis (en face Oil-Red-O aortic plaque area; aortic-root lesion area + severity grading) — wet lab / manual morphometry
- Statistical Analysis — two-tailed independent Student's t-test; mean ± SEM; n = 7–9
In-scope (pipeline-derived computational) results
NONE.
There is no high-throughput / omics component anywhere in the paper:
- No RNA-seq, microarray, ATAC, WGS/WES, proteomics, or any sequencing.
- No GEO / SRA / ENA / ArrayExpress / figshare / Zenodo / dbGaP accession.
- No GitHub / GitLab / code repository, no scripts, no bioinformatic pipeline, no Snakemake/Nextflow/nf-core workflow, no Docker/conda environment.
- No Data Availability statement; no supplementary source-data file.
- Gene expression is bench qPCR (ΔΔCt), not a sequencing pipeline.
- The only "computation" is a Student's t-test on n = 7–9 per group, and the underlying per-animal measurements are not deposited — only summary mean ± SEM bar graphs are published. There is nothing to run a tool against.
Out-of-scope (wet-lab / manual / not attempted)
Every reported result — body/organ weights, food intake, qPCR fold-changes (Ucp1, Ppara, Ppargc1a, Lpl, Elovl3, Fasn, Abcg5/8, Cyp7a1), plasma cholesterol/TG, FPLC profiles, hepatic lipids, en-face plaque area, aortic-root lesion area/severity — derives from physical mouse experiments and manual measurement. None is reproducible from deposited data or code.
Verdict
DROP — non_pipeline. The paper carries no pipeline-derived computational
result and deposits no data on which a third-party tool could be run (the P16
"third-party tool on the paper's own data" route is also impossible: there is no
data to apply a tool to). This is a text-mining false positive for a
computational-reproduction study. No compute was spent on «our HPC» — correctly, per
HARD RULE 1 there was nothing in scope to submit.
No individual results have been recorded for this entry yet.
Assessments & scoring basis
Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.
An automated assessment. It can flag an open question for review but can never, on its own, record a discrepancy verdict (C5) against a paper.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
This is a correct, honest non-pipeline drop. PMID 30813320 (Worthmann et al., Nutrients 2019) is a purely wet-lab in vivo mouse study (Ldlr⁻/⁻ + CL316,243) whose readouts are qPCR, plasma chemistry, FPLC and manual plaque morphometry — there is no computational pipeline, no code, and no deposited data (no accession, no source-data file). The gap is entirely one of data availability/scope (q1/q2 red), not our methodology and not a fabrication signal — so q5 is yellow (derivability simply cannot be tested) and q7 yellow (the central claim was never put to reproduction). Overall yellow: nothing in scope to reproduce and no fabrication concern, so reproduction quality is unassessable rather than critical.
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Reproduction footprint
claude-opus-4-8Measured resources invested to assess this paper — sanitised (machine class only, no job ids/paths). Compute = HPC accounting (SLURM); tokens = the AI agent's session.