Covalent binding of thioredoxin to TXNIP is required for diet-induced insulin resistance in the liver.
The main results reproduced: recomputed values matched the published ones within tolerance.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Same input data as the authors
- ✓Reported values were directly comparable
- ✓Reported values are derivable from the shared data
- ✓The central claim held under reproduction
- 🟡A deviation arose in the data or preprocessing
- 🟡A deviation was attributed to the published material
- 🟡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
Pipeline-derived RNA-seq results of GSE275407 reproduce 1:1 via TWO independent routes. Phase 1 (GEO-deposited transcript count matrix -> gene-level DESeq2) and Phase 2 (full re-quantification from the 15 raw FASTQ with kallisto 0.50.1, 100 bootstraps -> gene-level DESeq2) agree with each other and the paper: all 8 named cholesterol-synthesis genes up & significant in C247S vs WT (C1 exact); Irs1 non-significant (C3 exact); the 'surprisingly restricted' DEG set (C4 within-tol: 139/143 DEGs C247S vs ~2149/2146 KO); cholesterol/steroid biosynthesis the #1 enriched pathway across KEGG/WikiPathways/Reactome via Enrichr (C5 exact). Phase 2 requant concords with the deposited matrix at median Pearson r=0.9928 / Spearman 0.9791 over 115,868 common transcripts, confirming the deposited matrix is faithful and the pipeline reproduces end-to-end (C6 within-tol). The cDNA-only Ensembl GRCm39 r113 index (116,116 tx) matches the deposited 115,911 transcripts at 99.96%, confirming the paper's 'standard kallisto index' = Ensembl cDNA. The only soft spot is Irs2 (C2 partial): up directionally with nominal p=0.025 but does not survive FDR<=0.1 in our re-analysis (the paper likely leans on qPCR validation there). NOT attempted (out of scope, wet-lab / not pipeline-derived): mouse genetics (C247S knock-in / KO generation), metabolic phenotyping (GTT/ITT/clamps/body composition/lipids), Trx-TXNIP covalent-binding mass-spec/biochemistry, histology, and Western blots (Figs 1-3, 6). Caveats: the deposit is transcript-level (Methods describe gene-level tximport), and the gene matrix, DE tables, pathway results and analysis code are not deposited (regenerated here); gene aggregation summed transcript est_counts (tximport length offset not applied; affects normalization, not the tested conclusions). NOTE: one author (Schlein C) is the room operator; grades are provisional and must be independently checked.
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 81assessed: 2026-06-18 ⛓ bf363d20b459
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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
- 2026-06-22
- 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: sonnetBecause TXNIP's redox-sensitive cysteine (C247) enables covalent binding to thioredoxin uniquely in mammals, this single cysteine mediates diet-induced hepatic insulin resistance under a high-fat diet.
- ★ TXNIP Cysteine 247 is required for high-fat diet-induced hepatic and whole-body insulin resistance in mice finding
- ★ The TXNIP-thioredoxin binding motif containing C247 is present only in mammals among vertebrates examined finding
- TXNIP C247S mice generated via CRISPR-Cas9 knock-in (TGC to ATG mutation in exon 5) method
- ★ Tm7sf2 (cholesterol biosynthesis sterol reductase) is upregulated in HFD-fed TXNIP C247S mouse livers and mediates enhanced insulin signaling mechanism
- ★ TM7SF2 increases Akt phosphorylation and suppresses gluconeogenic markers PCK1 and G6Pc under oxidative stress conditions in HepG2 cells finding
- A heterozygous human TXNIP C247 variant is well tolerated finding
- TXNIP C247S mice show altered plasma lipid species (hexosylceramide, LPCs) compared with WT and TXNIP KO mice finding
- Irs2 mRNA expression is upregulated in HFD-fed TXNIP C247S livers, consistent with improved insulin signaling finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Insulin/glucose/pyruvate tolerance tests (ITT/GTT/PTT) | WT, TXNIP C247S, TXNIP KO mice (chow and HFD) | CRISPR C247S knock-in / TXNIP KO; 8-week 60% HFD | blood glucose response to insulin/glucose/pyruvate injection | — |
| Lipidomics (plasma and liver lipid profiling) | plasma/liver from chow- and HFD-fed WT, C247S, KO mice | diet (chow vs HFD), genotype | hexosylceramide and lysophosphatidylcholine species levels | — |
| Hyperinsulinemic-euglycemic clamp with [3-3H]glucose and [1-14C]2-deoxyglucose | 8-week HFD-fed WT, C247S, KO mice | genotype (C247S, KO) under HFD | whole-body glucose turnover, hepatic glucose production, tissue-specific glucose uptake | — |
| Western blot | mouse liver, insulin-stimulated (I.P. insulin 1 U/kg) | genotype, insulin stimulation | Akt Ser473 phosphorylation, total Akt, AMPK and mTOR phosphorylation, TXNIP protein levels | — |
| GSH/GSSG assay | mouse liver (chow and HFD) | genotype, diet | GSH levels and GSH:GSSG ratio (oxidative stress marker) | — |
| Thioredoxin activity assay | mouse liver | genotype (C247S vs WT) | thioredoxin activity | — |
| Bulk RNA-Seq | liver, WT, TXNIP C247S, TXNIP KO mice, HFD | genotype under HFD | differential gene expression, KEGG pathway analysis (cholesterol biosynthesis pathway) | — |
| qPCR | mouse liver (separate validation cohort) | genotype, diet | mRNA expression of cholesterol biosynthesis genes (Tm7sf2 etc.), Irs1/Irs2, Pck1 | — |
| Cell-based signaling assay | HepG2 cells | TM7SF2 manipulation under oxidative stress | Akt phosphorylation, PCK1 and G6Pc gluconeogenic marker expression | — |
- ▲ TXNIP C247S mice show improved insulin tolerance vs WT after 8-week HFD, but not improved glucose or pyruvate tolerance
- ▲ Whole-body glucose infusion and turnover rates elevated in C247S and KO vs WT during hyperinsulinemic-euglycemic clamp on HFD
- ▲ Hepatic insulin action (suppression of hepatic glucose production) increased in C247S and KO vs WT on HFD; basal HGP unchanged
- ▲ Increased Akt Ser473 phosphorylation in livers of insulin-stimulated TXNIP C247S mice vs WT
- ▼ Lower GSH and GSH/GSSG ratio in HFD-fed C247S livers vs HFD-fed WT livers (chow diet: no difference)
- ▲ Cholesterol biosynthesis pathway genes (Idi1, Fdps, Sqle, Cyp51, Tm7sf2, Nsdhl, Hsd7b17, Dhcr7) upregulated in TXNIP C247S livers vs WT
- ▲ Plasma LPC species elevated in chow-fed C247S mice vs WT and KO 23-45% increase across LPC 14:0/16:1/20:2/20:5/22:5
- ▲ Irs2 mRNA upregulated in HFD-fed C247S livers vs WT and KO; no difference in Irs1
- fold_change 23% increase LPC 14:0 (chow-fed plasma LPC C247S vs WT)
- fold_change 37% increase LPC 16:1 (chow-fed plasma LPC C247S vs WT)
- fold_change 23% increase LPC 20:2 (chow-fed plasma LPC C247S vs WT)
- fold_change 45% increase LPC 20:5 (chow-fed plasma LPC C247S vs WT)
- fold_change 36% increase LPC 22:5 (chow-fed plasma LPC C247S vs WT)
- pvalue p = 0.06 (5-h fasted insulin levels, HFD WT vs C247S trend)
- other basal HGP: 15.9 mg/kg/m (WT), 20 mg/kg/m (C247S), 21.5 mg/kg/m (KO) (basal hepatic glucose production during clamp, HFD-fed mice)
- other significance threshold FDR ≤0.1, p < 0.05 (bulk RNA-Seq differential expression criteria, liver, HFD)
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 compared a TXNIP C247S knock-in mouse model with WT and TXNIP KO controls on chow and 8-week 60% high-fat diets, assessing metabolic phenotypes via insulin/glucose/pyruvate tolerance tests, hyperinsulinemic-euglycemic clamps, bulk RNA-seq, and qPCR validation. Group comparisons used one-way and two-way ANOVAs with Tukey and Holm-Sidak post hoc tests, with Kruskal-Wallis used for selected comparisons; RNA-seq differential expression was filtered at FDR ≤ 0.1 and p < 0.05. Results were summarized as mean ± SD and significance was indicated by threshold-based asterisk notation throughout.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Two-way ANOVA with Tukey and Holm-Sidak post hoc tests | Insulin, glucose, and pyruvate tolerance test curves in chow-fed WT, TXNIP C247S, and TXNIP KO mice (Fig 1 C–E) | n = 7–10 (ITT), n = 9–10 (GTT), n = 7–9 (PTT) | not stated |
| Two-way ANOVA with Tukey and Holm-Sidak post hoc tests | Insulin, glucose, and pyruvate tolerance test curves in 8-week HFD-fed mice (Fig 2 G–I) | n = 9–10 | not stated |
| One-way ANOVA with Tukey post hoc test or Kruskal-Wallis test | Hyperinsulinemic-euglycemic clamp parameters, GSH levels, GSH:GSSG ratios, plasma insulin, tissue glucose uptake, Akt phosphorylation (Fig 3 A–J) | n = 7–10 (clamp), n = 5–6 (GSH/GSSG) | not stated |
| One-way ANOVA with Tukey post hoc test | qPCR-validated liver mRNA expression of Tm7sf2, Irs1, Irs2, Pck1, and cholesterol biosynthesis genes (Fig 5 C–I) | n = 6–10 | not stated |
| FDR-controlled differential gene expression analysis | Bulk RNA-seq comparing liver transcriptomes of WT, TXNIP C247S, and TXNIP KO groups (Fig 4 A–D; Fig 5 A) | n = 5 per group | not stated |
| KEGG pathway enrichment analysis | Pathway-level interpretation of RNA-seq differential expression results (Fig 5 A) | n = 5 per group | na |
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Tolerance test curves (ITT, GTT, PTT) measured at multiple time points were analyzed with two-way ANOVA treating time as a fixed between-groups factor↳ Could also: A linear mixed-effects model (e.g., via lme4 or nlme in R) with time as a within-subject repeated factor and mouse as a random effect would also handle the correlated longitudinal structure — Mixed-effects models explicitly account for within-animal correlation across time points, an assumption two-way ANOVA does not make; this can improve power and produce better-calibrated inference for time-series tolerance-test data
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Statistical significance was reported with threshold-based asterisk notation only↳ Could also: Reporting exact p values alongside a standardized effect-size metric (e.g., Cohen's d, eta-squared, or fold change with 95% CI) would also fully characterize each comparison — Exact p values allow readers to apply their own significance thresholds and support meta-analysis; effect sizes separate statistical significance from biological magnitude, which is especially informative for small n studies
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The choice between parametric (ANOVA) and non-parametric (Kruskal-Wallis) tests appears to have been applied selectively across figures without a stated decision rule↳ Could also: Pre-specifying a single decision rule — for example, always using Kruskal-Wallis when n < 8 per group or when a Shapiro-Wilk test rejects normality — would also be an approach used in metabolic phenotyping studies — A pre-specified rule for test selection reduces analytic flexibility and makes the statistical analysis plan reproducible and transparent for readers
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The RNA-seq FDR significance threshold was set at ≤ 0.1↳ Could also: A more stringent FDR threshold of ≤ 0.05 is also widely used for bulk RNA-seq differential expression, particularly when not all hits are independently validated — An FDR of 0.1 permits up to 10% expected false discoveries among significant genes; a 0.05 threshold is often chosen when the significant gene list directly informs downstream biological conclusions, and the authors' qPCR validation in an independent cohort effectively provides that verification for the key genes
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Summary statistics were presented as mean ± SD for groups with n as low as 5↳ Could also: Overlaying individual data points (dot/strip plots) on bar or box plots would also fully represent the distribution at these small sample sizes — With n = 5–6, individual-level plots make outliers and distributional shape visible to readers in a way that mean ± SD alone cannot, which is increasingly expected by journals for small-n animal studies
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No a priori sample-size or power calculation was reported↳ Could also: A power analysis based on expected effect sizes from pilot data or prior literature (e.g., for clamp-derived glucose infusion rates) would also justify the chosen group sizes — Reporting a power calculation helps readers assess whether the study was adequately powered to detect differences of a biologically meaningful magnitude and is increasingly required by funding agencies and journals in metabolic phenotyping research
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-40345590
Paper: Dagdeviren S, et al. "Covalent binding of thioredoxin to TXNIP is required for diet-induced insulin resistance in the liver." J Biol Chem 2025. PMID 40345590 / PMC12180993 / DOI 10.1016/j.jbc.2025.110214.
Note: One author (Schlein C) is a co-author and is the room operator. Reproduction is kept strictly objective; grades are provisional and must be independently checked.
The single pipeline-derived dataset
- GSE275407 — bulk RNA-seq, mouse liver, HFD 8 wk, 3 genotypes × n=5:
WT, TXNIP C247S knock-in, TXNIP KO. 15 paired-end NovaSeq runs (PRJNA1150621,
SRR30334160–74). GEO also deposits a gene-level count matrix
(
GSE275407_sparseCounts.csv.gz) +GSE275407_samplesheet.tsv.gz.
Pipeline (from Methods)
- QC/trim: Trimmomatic v0.39
- Quantification: kallisto v0.50.1, 100 bootstraps, "standard kallisto index" from pachterlab GitHub (github.com/pachterlab/kallisto-transcriptome-indices)
- Gene summarization: tximport v1.0.3
- Differential expression: DESeq2 (pseudogenes + mitochondrial genes removed first)
- Significance: FDR ≤ 0.1, p < 0.05
- Enrichment: KEGG; Reactome + WikiPathways via Enrichr
IN SCOPE (reproduce)
- Downstream DE from the deposited count matrix (Phase 1, quick floor):
DESeq2 on
sparseCounts→ contrasts C247S vs WT and KO vs WT.- Claim C1: cholesterol-synthesis genes (Idi1, Fdps, Sqle, Cyp51, Tm7sf2, Nsdhl, Hsd17b7 [paper "Hsd7b17"], Dhcr7) UP in C247S vs WT.
- Claim C2: Irs2 mRNA UP in C247S vs WT.
- Claim C3: Irs1 mRNA NOT significantly different in C247S vs WT.
- Claim C4: "surprisingly restricted" overall DEG count (qualitative).
- Claim C5: KEGG/enrichment dominated by cholesterol biosynthesis (Fig 5).
- Full quantification from raw FASTQ (Phase 2, harder): kallisto 0.50.1 + tximport on the 15 ENA runs → compare regenerated counts to the deposited matrix, then re-run DESeq2.
OUT OF SCOPE (wet-lab / not pipeline-derived — not attempted)
- Generation of C247S knock-in / KO mice; metabolic phenotyping (GTT/ITT, clamps, body composition, lipids); mass-spec / biochemistry of the Trx–TXNIP covalent adduct; histology; protein/Western blots. These are the paper's core (Figs 1–3, 6) and are experimental, not reproducible from deposited data.
Figures in scope
- Fig 4 (volcano / heatmap of DE, incl. Irs1/Irs2), Fig 5 (KEGG / pathway enrichment).
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 in-scope pipeline-derived RNA-seq results of GSE275407 reproduce strongly from the deposited data: all 8 cholesterol-synthesis genes upregulated in C247S vs WT (C1, padj 2.8e-7..4.9e-4), Irs1 non-significant (C3), the restricted 139-DEG set (C4), and cholesterol/steroid biosynthesis as the #1 enriched term across all three databases (C5, adjp 1e-17..2e-25). The deviations are minor and explainable: Irs2 (C2) is up directionally but fails the paper's FDR<=0.1 (padj=0.43), likely resting on qPCR validation. The main friction is data-availability on the authors' side — the deposit is transcript-level while Methods describe gene-level output, and the gene matrix, DE tables and real analysis code are absent (the cited repo is a generic index), forcing regeneration. No fabrication concern; overall a solid reproduction with explainable deviations.
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
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