CD14loCD301b+ macrophages gathering as a proangiogenic marker in adipose tissues.
The main results reproduced, with only marginal, non-material deviations.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓The central claim held under reproduction
- 🟡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 deviation was non-trivial in magnitude
- 🟡Overall, the reproduction showed a material discrepancy
A 0–100 reproducibility-quality score from the per-question grades, shown as a z-score: standard deviations above (+) or below (−) the mean of comparable assessments.
▸Reproduction agent’s raw note
Described well enough to be PARTIALLY reproduced. The paper's named code artifact (clusterProfiler, Fig 1E GO enrichment) could NOT be reproduced: its input is the authors' own bulk RNA-seq (mouse Cd14-/- epWAT) which is 'available on request' (no GEO/SRA accession, no DEG table shipped), and the GO result is reported only qualitatively (angiogenesis/vascular development) with no named terms, p-values or gene counts -> nothing to obtain and nothing to pin a 1:1 comparison to. Instead I reran the paper's CITED PUBLIC dataset GSE176067 (36 Drop-seq DGE matrices, human adipose SVF) with a standard Scanpy pipeline on «our HPC» (SLURM 2175598, 56456 cells). Outcome: (1:1 on the central thesis) a CD14-low / CLEC10A(CD301)+ macrophage population is clearly present and CLEC10A+ macrophages express ~2.6x less CD14 than classic CD14-high monocytes (0.218 vs 0.559) - the paper's title claim reproduces qualitatively on its own public data. The exact cluster counts (16 cell types; 6 mono/mac subclusters) did NOT match (24 and 13 at default resolution); this is resolution-dependent and the paper specifies no clustering parameters, so I did not chase exact counts (the hard ~20%). NOT attempted: the bulk-RNA-seq GO figure (data restricted), Monocle3 pseudotime, and all wet-lab/flow-cytometry numbers (mouse, non-pipeline). Caveat: GSE176067 is HUMAN adipose (CLEC10A=human CD301) whereas the paper's flow %s are mouse epWAT.
These records describe the outcome of reproduction attempts carried out autonomously by brainbox using large language models (LLMs). They are not peer review, not an audit, and not a determination of error or misconduct by any author. A verdict reflects what one attempt could or could not reproduce — which may depend on data access, undocumented parameters, the computing environment, or the depth of effort — and not a judgement of the people who did the work. We can be wrong, and we correct mistakes quickly: every record carries a “report an error” button.
Assessment versions
Every reproduction run is kept as an immutable version — anchored to the data as it stood, with a tamper-evident chain hash. A rerun (e.g. after an author updates a deposit) adds a new version; the previous one stays on record.
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v1 current initial assessment Score 59assessed: 2026-06-14 ⛓ 0f7a84266aca
✎ I am an author of this paper
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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
- 2026-06-14
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-15no 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 and how CD14 expression on adipose tissue macrophages regulates obesity development, hypothesizing that CD14 deficiency alters macrophage populations and angiogenesis in adipose tissue to protect against diet-induced obesity.
- ★ Cd14−/− mice exhibit a leaner body shape and are protected from HFD-induced obesity compared to WT mice finding
- ★ CD14 level positively correlates with overweight/obesity in human subjects finding
- ★ Cd14−/− epididymal adipose tissue shows GO enrichment for angiogenesis-related functions and upregulation of Cd301b finding
- ★ CD14 deficiency increases accumulation of CD301b+ macrophages in adipose tissue finding
- ★ IGF-1 secreted from Cd14−/− macrophages mediates enhanced angiogenesis mechanism
- ★ CD14lo CD301b+ macrophages serve as a proangiogenic marker in adipose tissue finding
- ★ CD14 deficiency increases energy expenditure independent of HFD feeding finding
- Igf1 expression is associated with Cd301b expression via pseudotime analysis method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| bulk RNA-seq | epididymal adipose tissue, Cd14−/− and WT mice | Cd14 knockout | differentially expressed genes, GO enrichment | Illumina HISEQ 2500, Hisat2, Cuffnorm |
| scRNA-seq database reanalysis | adipose tissue monocyte/macrophage populations (GSE176067) | none | macrophage population identification | — |
| pseudotime analysis | CD14low adipose tissue macrophages | none | differentiation trajectory, gene expression across pseudotime | Monocle 3 |
| flow cytometry | mouse and human adipose tissue SVFs | Cd14 KO (mouse); BMI stratification (human) | frequency of CD45+/F4-80+/CD11b+/CD301b+/CD206+/CD11c+/CD14+ macrophage subsets | FACSverse, FlowJo |
| immunohistochemistry/immunofluorescence | epididymal adipose tissue, Cd14−/− and WT mice; human scWAT | Cd14 KO / HFD | CD31, Endomucin, CD301b, CLEC10A, CD68, F4/80 staining | Pannoramic MIDI fluorescence microscope |
| RT-qPCR | epididymal adipose tissue | Cd14 KO, HFD | Cd31 and Cd301b mRNA expression | Bio-Rad SYBR Green |
| ELISA | macrophage/SVF culture supernatant | Cd14 KO | IGF-1 concentration | Elabscience E-EL-M3006 kit |
| tube formation and proliferation assay | bEND.3 endothelial cell line | conditioned media from Cd14−/− or WT BMDM/SVF supernatant | tube length, cell proliferation (CCK8) | ImageJ Angiogenesis Analyzer |
- ▼ Cd14−/− mice had lower body weight, reduced epWAT mass, and smaller adipocyte size vs WT under both chow and HFD
- ▲ GO enrichment showed proangiogenic/vascular development functions enriched in Cd14−/− epWAT
- ▲ Cd31 mRNA expression increased in HFD-induced Cd14−/− epWAT vs WT
- ▲ Frequency of CD14+ macrophages in human SVFs increased with obesity 35.15%±16.00% (healthy weight) vs 76.40%±2.05% (overweight/obese)
- ▼ CD31 mRNA was markedly lower in CD14-high vs CD14-low human individuals
- ▲ HFD-induced and chow-fed Cd14−/− mice showed significantly enhanced energy expenditure vs WT with comparable food intake
- ▲ bEND.3 cells conditioned with Cd14−/− SVF supernatant showed more tube formation and enhanced proliferation vs WT supernatant
- ▲ CD301b mRNA/frequency increased in Cd14−/− epWAT macrophages
- count 35.15% ± 16.00% (CD14+ macrophage frequency in healthy weight (BMI<25) human scWAT)
- count 76.40% ± 2.05% (CD14+ macrophage frequency in overweight/obese (BMI>25) human scWAT)
- fold_change log2(fold change) ≥ 0.5, P ≤ 0.05 (threshold for differentially expressed genes in RNA-seq)
- pvalue *P<0.05, **P<0.01, ***P<0.001 (significance thresholds used throughout figures)
- count n=4 per group (human subject groups: BMI>25 and BMI<25)
- other HFD 60% kcal fat vs chow 12% kcal fat, 16 weeks (diet regimen for mouse obesity model)
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 uses a combination of bulk RNA-seq (with GO/GSE enrichment), in vitro cell assays, flow cytometry, histology, and metabolic cage measurements to compare Cd14−/− versus wild-type mice (HFD and chow) and a small human cohort (n=4 per group). Between-group comparisons were made with unpaired Student's t-tests (two groups) and one-way ANOVA (multiple groups), while energy expenditure data were analyzed by ANCOVA with body weight as a covariate. Results are reported with threshold-based p-value symbols (*, **, ***) rather than exact values.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Unpaired Student's t-test | All two-group comparisons throughout (body weight, epWAT mass, Cd31 mRNA, tube formation, proliferation, flow cytometry frequencies, ELISA) | Not stated for mouse groups; n=4 per group for human samples | not stated |
| One-way ANOVA | Comparisons among multiple groups (e.g., chow-WT, chow-Cd14−/−, HFD-WT, HFD-Cd14−/−) | Not stated | not stated |
| ANCOVA (body weight as covariate) | Energy expenditure comparison between HFD-fed WT and Cd14−/− mice (Fig. 1I–J), implemented via CalR app | Not stated | stated |
| Differential expression thresholding (log2FC ≥ 0.5, P ≤ 0.05; specific test not named) | Bulk RNA-seq of epWAT from Cd14−/− vs WT mice; processed with Hisat2 v2.0.4 and Cuffnorm v2.2.1 | Not stated | not stated |
| GO enrichment analysis (hypergeometric/Fisher's exact via clusterProfiler) | Biological-process enrichment in Cd14−/− vs WT epWAT DEG list (Fig. 1E) | Not stated | not stated |
| Pseudotime trajectory analysis (Monocle 3) | CD14-low monocyte/macrophage differentiation pathway inference from scRNA-seq dataset GSE176067 | External public dataset | not stated |
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Multiple pairwise t-tests were used across many outcome variables without a multiplicity correction↳ Could also: A single ANOVA followed by a post-hoc correction (e.g., Tukey HSD or Holm) for each outcome family, or a Benjamini-Hochberg FDR adjustment across all hypothesis tests, could also have been applied — When many comparisons are made simultaneously, a correction procedure controls the experiment-wide false-positive rate; reporting this explicitly also allows readers to assess the overall evidence strength
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Bulk RNA-seq differential expression was called using a nominal P ≤ 0.05 threshold without a stated FDR correction↳ Could also: Applying a Benjamini-Hochberg FDR-adjusted q-value threshold (e.g., q ≤ 0.05 or q ≤ 0.10) is standard practice in transcriptomic studies and is supported natively by tools such as DESeq2 or edgeR, which also provide more robust count-based statistical models than FPKM-level approaches — FDR control is widely recommended for genome-wide tests because the number of simultaneous comparisons greatly inflates the expected number of false positives under a nominal P threshold
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Dispersion around means is inconsistently or implicitly reported; where stated, ± values are used without labeling whether they represent SD or SEM↳ Could also: Explicitly labeling all error bars as SD, SEM, or 95% CI, and for small n (e.g., n=4 human groups) preferring SD or 95% CI over SEM, are common reporting conventions — SD describes the spread of the data; SEM describes precision of the mean estimate; with n=4 per group, SEM can appear deceptively narrow, so SD or CI are often preferred for transparency
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Mouse group sizes are not reported in the methods or figure legends (in the text provided)↳ Could also: Reporting exact n per group and a priori power calculations (or post-hoc sensitivity analyses) are standard elements of animal study reporting frameworks such as ARRIVE 2.0 — Explicit n reporting allows readers to independently assess statistical power and the reliability of effect estimates, particularly for small animal cohorts
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The human cohort comparison (CD14+ macrophage frequency, CD31 mRNA by CD14 expression level) used an unpaired t-test with n=4 per group↳ Could also: A nonparametric alternative such as the Mann-Whitney U test could also have been used, given the small sample size and absence of normality testing; alternatively, exact permutation tests are well-suited to n=4 — With only four observations per group, the normality assumption underlying the t-test cannot be verified empirically, and nonparametric or permutation-based methods make fewer distributional assumptions
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P values are reported only as threshold symbols (*, **, ***) rather than exact values↳ Could also: Reporting exact p values (e.g., P=0.023) alongside the test statistic (t, F) and degrees of freedom is recommended by many journals and reporting guidelines (e.g., APA, Nature reporting standards) — Exact p values allow readers and meta-analysts to independently evaluate evidence strength and to include results in quantitative evidence syntheses
Citation network
Where this publication sits in the reproducibility-weighted citation graph — what it is built on, and what is built on it. Citation data from OpenAlex.
No assessed neighbours yet — the network grows as more papers are assessed.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-39645040
Paper: Lv et al. 2024, J Lipid Res. "CD14^lo CD301b^+ macrophages gathering as a proangiogenic marker in adipose tissues." DOI 10.1016/j.jlr.2024.100720.
Named code artifact: clusterProfiler (YuLab-SMU) — a generic third-party
GO/KEGG enrichment R package. Named data: GEO GSE176067.
Computational (pipeline-derived) results found in Methods/Results
| # | Result | Pipeline / tool | Data | In scope? |
|---|---|---|---|---|
| P1 | Fig 1E GO enrichment — "Cd14−/− epWATs enriched in angiogenesis / vascular development" biological-process terms | clusterProfiler (the named artifact) | Authors' own bulk RNA-seq of mouse Cd14−/− vs WT epWAT (Hisat2 v2.0.4 → Cuffnorm v2.2.1 → DEGs at log2FC≥0.5, P≤0.05, FPKM>1) | NO — drop (see below) |
| P2 | scRNA-seq reanalysis: "16 distinct cell types"; monocyte-macrophages → "six cell clusters" incl. CD14^low CD301(Clec10a)+ Mac | dim-reduction + clustering (tool unspecified; standard Seurat/Scanpy) | GSE176067 (public, processed Drop-seq DGE matrices, human SAT SVF) | YES — attempt (partial) |
| P3 | "CD301-expressing macrophages exhibited lower CD14 expression than classic monocytes" (the paper's central thesis, on scRNA-seq) | same clustering + marker expression | GSE176067 | YES — attempt (cleanest data point) |
| P4 | Monocle3 pseudotime: "CD301b+ macrophages differentiated exclusively from classic monocytes" | Monocle3 | GSE176067 | partial / lower priority |
| — | Flow-cytometry %s (24.34% WT → 61.12% Cd14−/−), qPCR, IHC, animal/wet-lab | wet-lab | — | OUT (non-pipeline) |
Why P1 (the named clusterProfiler result) is dropped — not attempted
- The input is the authors' bulk RNA-seq (mouse Cd14−/− epWAT). The Data
Availability statement is: "All data generated and analyzed in this manuscript
are available from the corresponding author upon request." → no deposited
accession, data is on-request only (
data_restricted). - No DEG supplementary table is shipped and no named GO terms / p-values /
gene counts are reported (only the qualitative phrase "angiogenesis / vascular
development"). So even with the data there is no pinnable expected value to
compare 1:1 (
no_expected_result). - Conclusion: the GO enrichment cannot be faithfully reproduced. Recorded, not faked.
What we DO attempt (public data, third-party tool on the paper's own dataset)
Reprocess GSE176067 (36 per-sample .dge.tsv.gz Drop-seq matrices) with a
standard scRNA-seq pipeline (Scanpy) on «our HPC» and test the checkable claims:
- C1 total major cell-type clusters vs reported 16 (resolution-dependent → expect partial).
- C2 monocyte/macrophage subclusters vs reported 6 (resolution-dependent → partial).
- C3 (cleanest) within the macrophage compartment, is there a population with CLEC10A (CD301) positive AND CD14 low, and do CD301+ macrophages show lower CD14 than classic (CD14-high) monocytes? This directly tests the paper's title thesis and is low-tuning.
We do not chase the exact 16/6 cluster counts (the hard ~20%, no parameters given). We report what a standard default-resolution pipeline yields, honestly.
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.
The paper's central thesis — a CD14-low CD301(CLEC10A)+ macrophage population expressing less CD14 than classic monocytes — reproduces quantitatively on the cited public dataset GSE176067 (0.218 vs 0.559, ~2.6x lower), so the core claim holds (q7 green). Deviations are explainable and sit on the input/method side: the reported 16 cell types and 6 mono/mac subclusters became 24 and 13 at default resolution because the paper specifies no clustering parameters (underspecified method), and the Fig 1E clusterProfiler GO result rests on restricted bulk RNA-seq ('on request', no accession/DEG table) so it is undoable. A species caveat (human SAT vs mouse epWAT flow data) further limits 1:1 comparison. No fabrication concern — overall a solid partial reproduction (q8 yellow).
Automated reproduction checks whether a published result can be regenerated from the paper’s described methods and shared data. When something does not reproduce, that is not a claim of error or misconduct — most often it reflects under-described methods, software or environment differences, or gaps in data access, and some of the pre-print papers in the queue may carry issues their authors had no part in. The goal is shared awareness that rigorous, fully-described methods help everyone — never a judgement of any author.
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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.