Brown fat activation reduces hypercholesterolaemia and protects from atherosclerosis development
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.
- ✓No authors-side cause for any deviation
- ✓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
- 🟡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). 'Brown fat activation reduces hypercholesterolaemia and protects from atherosclerosis development', Berbee et al., Nature Communications 6:6356 (2015), DOI 10.1038/ncomms7356, PMC4366535. This is a wet-lab mouse physiology / lipid-metabolism / atherosclerosis study with NO pipeline-derived computational results in scope. Verified against PubMed, PMC full text, and the Nature article: no high-throughput omics (gene expression is targeted qRT-PCR normalized to beta-2-microglobulin and 36b4, not array/RNA-seq), no deposited public dataset (no GEO/SRA/ENA/ArrayExpress/PRIDE accession, no data-availability/accession-codes statement), and no analysis code/repository. All reported values are bench/instrument measurements (enzymatic plasma TG & cholesterol, FPLC lipoprotein profiles, [3H]/[14C] radiotracer organ-uptake kinetics, indirect calorimetry, EchoMRI, atherosclerotic-lesion histomorphometry, UCP1 IHC) analysed in SPSS 20.0 (two-tailed Student t-test, univariate regression). There is no data+code pipeline to reproduce and no dataset to profile (dataset_profile.datasets=[], n_public_datasets=0). No «our HPC» compute was spent (by design — nothing to run). NOT ATTEMPTED: computational reproduction of any result, because none is pipeline-derived; this is an honest scope decision, not a failed run. Secondary gaps that also hold: no_data_accession, no_code.
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Assessment versions
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v1 current initial assessmentassessed: 2026-06-18 ⛓ 43b9fca4f9c2
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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: sonnetWhether brown adipose tissue (BAT) activation via β3-adrenergic receptor stimulation protects against or aggravates hypercholesterolaemia and atherosclerosis in hyperlipidemic mice, and whether this effect depends on a functional hepatic apoE-LDLR remnant clearance pathway.
- ★ β3-AR agonist-mediated BAT activation reduces plasma triglycerides and cholesterol and protects against atherosclerosis development in APOE*3-Leiden.CETP mice. finding
- ★ BAT activation enhances selective uptake of fatty acids from triglyceride-rich lipoproteins into BAT, generating cholesterol-enriched remnants that are subsequently cleared by the liver. mechanism
- ★ The anti-atherogenic and cholesterol-lowering effect of BAT activation requires a functional hepatic apoE-LDLR clearance pathway, as it is absent in Apoe-/- and Ldlr-/- mice. finding
- ★ (V)LDL-cholesterol exposure, not triglyceride exposure, is the main predictor of atherosclerotic lesion area after BAT activation. finding
- APOE*3-Leiden.CETP mice are a human-like lipoprotein metabolism model that, unlike Apoe-/- and Ldlr-/- mice, retain functional apoE and LDLR. resource
- The lipid-lowering effect of β3-AR agonism does not depend on CETP expression, as it also occurs in E3L mice lacking CETP. finding
- CL316243 selectively activates existing BAT and induces WAT browning without the systemic hormonal effects of cold exposure. method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| indirect calorimetry (energy expenditure, FA/carbohydrate oxidation, activity) | female E3L.CETP mice on Western-type diet | CL316243 (β3-AR agonist) vs vehicle (PBS) | energy expenditure, FA oxidation, respiratory exchange ratio, activity | — |
| histology (lipid droplet size, WAT browning) and immunohistochemistry (UCP1 staining) | interscapular BAT and WAT depots from E3L.CETP mice | CL316243 vs vehicle | lipid vacuole size, UCP1 protein content per area/pad | — |
| plasma lipid analysis (TG, total cholesterol, lipoprotein fractionation) | E3L.CETP mice on Western-type diet (also E3L mice without CETP) | CL316243 vs vehicle; also cold exposure vs room temperature | plasma TG, TC, VLDL-TG, (V)LDL-C levels | FPLC/lipoprotein profiling |
| hepatic gene expression | liver of E3L.CETP, Apoe-/-, and Ldlr-/- mice | CL316243 vs vehicle | mRNA levels of Apob, CETP, Ldlr, Mttp | qPCR (implied) |
| in vivo plasma clearance and organ uptake of dual-radiolabeled VLDL-mimicking particles ([3H]triolein/[14C]cholesteryl oleate) | E3L.CETP mice (8-day CL316243 treatment) | CL316243 vs vehicle | plasma decay half-life, tissue-specific 3H/14C uptake, lipolysis index | — |
| atherosclerotic lesion quantification (area, severity, composition) | aortic root of E3L.CETP mice (10-week study) | CL316243 vs vehicle | lesion area, lesion severity grade, collagen/smooth muscle cell/macrophage content, stability index | histomorphometry |
| body composition and plasma lipid/atherosclerosis assessment | WTD-pair-fed Apoe-/- and Ldlr-/- mice | CL316243 vs vehicle | body weight, WAT pad size, plasma TG/TC/(V)LDL-C, atherosclerotic lesion area | — |
| univariate regression analysis | E3L.CETP, Apoe-/-, and Ldlr-/- mice lesion/lipid exposure data | none (correlative analysis) | correlation of SQRT-transformed lesion area with plasma TG or TC exposure (AUC) | — |
- ▼ β3-AR agonism reduced plasma TG in E3L.CETP mice throughout treatment ~54%
- ▼ β3-AR agonism reduced plasma total cholesterol and (V)LDL-C in E3L.CETP mice ~23% TC, ~27% (V)LDL-C
- ▼ β3-AR agonism reduced mean atherosclerotic lesion area in E3L.CETP mice 43%
- – BAT activation had no effect on plasma TC, (V)LDL-C, or atherosclerosis in Apoe-/- or Ldlr-/- mice despite reducing TG
- ▲ Total energy expenditure and FA oxidation increased on day of CL316243 treatment +17% EE, +67% FA oxidation
- ▲ CL316243 increased uptake of [3H]oleate by BAT depots and increased hepatic uptake of [14C]cholesteryl oleate-labelled remnants 2-3 fold BAT uptake; ~25% liver uptake
- – SQRT-transformed lesion area correlated with plasma TC exposure but not TG exposure TC: R2=0.333, P<0.001; TG: R2=0.086, P=0.10
- ▲ (V)LDL-C exposure specifically predicted SQRT lesion area R2=0.358, P<0.001
- pvalue P<0.001 (correlation of lesion area with plasma TC exposure)
- correlation R2=0.358, β=0.055, P<0.001 ((V)LDL-C exposure predicting SQRT lesion area)
- correlation R2=0.333, β=0.054, P<0.001 (TC exposure predicting SQRT lesion area)
- correlation R2=0.086, β=0.028, P=0.10 (TG exposure vs SQRT lesion area (not significant))
- other plasma half-life t1/2 [3H]TO: vehicle 2.9±0.1 min vs CL316243 1.5±0.1 min, P<0.001 (VLDL-mimicking particle clearance kinetics)
- other plasma half-life t1/2 [14C]CO: vehicle 4.7±0.5 min vs CL316243 3.3±0.3 min (VLDL-mimicking particle core remnant clearance kinetics)
- other lipolysis index (3H/14C ratio): BAT 11.1±0.9 vs liver 0.22±0.01; vehicle 0.22±0.01 vs CL316243 0.15±0.01, P<0.01 (selective FA uptake by BAT vs whole-particle uptake by liver)
- fold_change 43% lower mean lesion area (atherosclerotic lesion area reduction with CL316243 in E3L.CETP mice)
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 between-group experimental design across three mouse models (E3L.CETP, Apoe−/−, Ldlr−/−) comparing β3-adrenergic receptor agonist (CL316243) treatment to vehicle (PBS) control, with pair-feeding used in the knockout models to equalize dietary cholesterol intake. Key kinetic parameters (plasma clearance half-lives, lipolysis indices) were compared with unpaired two-tailed Student's t-tests, and relationships between plasma lipid exposure and SQRT-transformed atherosclerotic lesion area were assessed by univariate linear regression. Group differences for body composition, energy expenditure, and plasma lipids were reported largely as percentage changes with P-value thresholds rather than exact values, and no multiplicity correction was described.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| unpaired two-tailed Student's t-test | Plasma clearance half-life of [3H]TO vs [14C]CO in vehicle-treated E3L.CETP mice (t½ 2.9±0.1 vs 4.7±0.5 min, P<0.01; Fig. 6a,c) | — | not stated |
| unpaired two-tailed Student's t-test | Plasma clearance half-life of [3H]TO: CL316243 vs vehicle (t½ 1.5±0.1 vs 2.9±0.1 min, P<0.001; Fig. 6a) | — | not stated |
| unpaired two-tailed Student's t-test | Lipolysis index comparison: CL316243 vs vehicle (0.15±0.01 vs 0.22±0.01, P<0.01; derived from Fig. 6b,d) | — | not stated |
| univariate linear regression | FA uptake by individual BAT depots (3H activity) predicting hepatic cholesterol-enriched remnant uptake (14C activity) (Fig. 6e–g) | — | not stated |
| univariate linear regression | SQRT-transformed atherosclerotic lesion area vs plasma TG exposure (β=0.028, R²=0.086, P=0.10) and vs plasma TC exposure (β=0.054, R²=0.333, P<0.001), and vs (V)LDL-C exposure (β=0.055, R²=0.358, P<0.001) in E3L.CETP mice (Fig. 8i–k) | — | not stated |
| univariate linear regression | SQRT-transformed atherosclerotic lesion area vs plasma TG and TC exposure in Apoe−/− mice (Fig. 9e,f) and Ldlr−/− mice (Fig. 9k,l) | — | not stated |
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Numerous endpoints (body composition, energy expenditure, plasma lipids, tissue uptake, lesion metrics) were compared across groups, each apparently with separate tests and no stated multiplicity control↳ Could also: A false discovery rate correction (e.g., Benjamini-Hochberg) applied across related endpoint families could also be used — FDR control is a standard tool for quantifying the expected proportion of false positives among many simultaneously tested hypotheses; it complements the biological coherence of the findings by providing a formal statistical bound
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Univariate linear regressions were run separately for TG exposure and TC (or (V)LDL-C) exposure as predictors of SQRT lesion area↳ Could also: A multivariable regression including both TG and TC simultaneously could also be used — Multivariable regression quantifies the independent contribution of each lipid fraction after adjusting for the other; it is especially informative when TG and TC are correlated, as they often are under the treatment studied
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Dispersion was reported as mean ± an unlabeled value throughout↳ Could also: Explicitly labeling the dispersion measure as SD or SEM, or reporting 95% confidence intervals, would also convey spread — SD describes the distribution of individual values, while 95% CIs directly reflect estimation uncertainty; explicit labeling allows readers to interpret the range of variation and judge the precision of group estimates, particularly for small animal study sample sizes
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Square-root transformation was applied to lesion area before linear regression↳ Could also: A log transformation or a nonparametric rank correlation (e.g., Spearman's rho) could also be applied to address non-normality and heteroscedasticity in lesion area data — Different variance-stabilizing transformations suit different distributional shapes; reporting sensitivity of the association to the choice of transformation, or using a distribution-free approach, adds robustness information
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Per-group sample sizes (n) are not reported in the text↳ Could also: Explicit reporting of n per group, along with a priori power calculations or post-hoc power estimates, could also accompany the statistical results — Reported n allows readers to gauge estimation uncertainty and reproducibility, and pre-specified power calculations contextualize whether the study was designed to detect the primary effect at a given confidence level
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Time-course plasma lipid data (Fig. 4a,c) spanning 10 weeks were compared between groups, with results summarized as overall percentage reductions↳ Could also: A linear mixed-effects model or repeated-measures ANOVA with a post-hoc correction could also formally test treatment-by-time interactions across the longitudinal measurements — Mixed-effects models account for within-animal correlation across time points, yielding valid standard errors under the repeated-sampling design; they also allow testing whether the treatment effect emerged gradually or was stable from the first measurement
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope assessment — pmid-25754609
Title: Brown fat activation reduces hypercholesterolaemia and protects from atherosclerosis development Venue: Nature Communications 6:6356 (2015) · DOI 10.1038/ncomms7356 · PMCID PMC4366535 Authors: Berbée JFP, Boon MR, Khedoe PPSJ, Bartelt A, Schlein C, Worthmann A, Kooijman S, Hoeke G, Mol IM, John C, Jung C, Vazirpanah N, Brouwers LPJ, Gordts PLSM, Esko JD, Hiemstra PS, Havekes LM, Scheja L, Heeren J, Rensen PCN.
Verdict: DROP — non_pipeline
This publication contains no pipeline-derived computational results and ships no public high-throughput dataset and no analysis code. It is an experimental (wet-lab) mouse physiology / lipid-metabolism / atherosclerosis study. There is nothing to reproduce computationally from deposited data + code, which is the defined scope of this study.
Evidence (read from PMC full text + PubMed)
- No omics / high-throughput data. Methods describe only targeted molecular biology and physiology. Gene expression is by qRT-PCR (normalized to β2-microglobulin and 36b4), not RNA-seq or microarray. No sequencing, proteomics, or array profiling anywhere.
- No data accession. No GEO / ArrayExpress / SRA / ENA / PRIDE / figshare / Zenodo accession appears in the paper. No "Data availability" / "Accession codes" statement exists (2015 paper, predates Nat Commun mandatory data statements).
- No code. No repository, no script, no computational workflow is referenced.
- Statistics: unpaired two-tailed Student's t-test and univariate regression, computed in SPSS 20.0 for Windows on directly measured bench values — not a reproducible data+code pipeline.
Reported results, and why each is OUT OF SCOPE
| Result class | Method (paper) | In scope? | Why |
|---|---|---|---|
| Plasma TG / total / HDL / LDL cholesterol | enzymatic colorimetric assays | no | instrument/bench measurement; no deposited data |
| Lipoprotein distribution | FPLC fractionation | no | instrument output, manual integration; not deposited |
| Atherosclerotic lesion area / severity | histology + histomorphometry | no | manual image quantification; no images/data deposited |
| BAT/organ uptake of TG-derived FA / cholesterol | [3H]/[14C] radiotracer kinetics | no | radioisotope bench assay; no deposited data |
| Energy expenditure / fat & carb oxidation | indirect calorimetry | no | instrument output; no deposited data |
| Body composition | EchoMRI | no | instrument output |
| Hepatic gene expression | qRT-PCR | no | targeted bench assay; no deposited data/code |
| UCP1 staining, lipid-droplet size | immunohistochemistry / morphometry | no | manual histology |
Every reported number originates from a bench instrument or manual quantification and was analysed in SPSS. None is regenerable from a public dataset + pipeline.
Pipelines named per in-scope result
None. There are no in-scope (pipeline-derived) results.
Decision
Record drop_reason = non_pipeline (root cause); secondary gaps
no_data_accession + no_code also hold. No «our HPC» compute spent — by design,
since there is no data or code to run. Honest drop per BRIEF rule 6.
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 an honest non-pipeline DROP: Berbée et al. (Nat Commun 6:6356, 2015) is a wet-lab mouse atherosclerosis/lipid study whose claims C1–C6 are enzymatic, radiotracer, calorimetry and histomorphometry measurements analysed in SPSS 20.0, with no deposited dataset and no code. The barrier sits entirely on data/code availability (q1/q2 red), not on the authors' methodology or any suspicious value — so q5 is yellow (untestable, not fabrication-suspect) and q7 yellow (central claim neither confirmed nor refuted). Nothing was computed, hence no factual deviation (q6 green); overall a non-critical out-of-scope drop that a human should simply log rather than treat as a discrepancy.
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Reproduction footprint
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