RIT1 controls actin dynamics via complex formation with RAC1/CDC42 and PAK1.
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). PMID 29734338 = Meyer Zum Buschenfelde et al., 'RIT1 controls actin dynamics via complex formation with RAC1/CDC42 and PAK1', PLoS Genet 2018;14(5):e1007370 (PMC5937737). Full-text Methods + Data-availability reviewed: it is a wet-lab molecular/cell-biology study (recombinant GST/His proteins, GST pull-down, co-IP, immunoblot/autoradiography, immunofluorescence microscopy, transwell migration, FACS counting). NO bioinformatic/computational pipeline and NO deposited data or code: data-availability statement is 'All relevant data are within the paper and its Supporting Information files' (no GEO/SRA/ENA/figshare/Zenodo accession, no GitHub/GitLab repo). The only computational steps are ImageJ densitometry/manual cell counting and GraphPad Prism 7 statistics applied to wet-lab measurements; the raw images/blots/per-replicate values are not deposited, so nothing is pipeline-reproducible. Apparent term hits (BLAST/align/genom/pipeline) are false positives (neuroBLASToma, mALIGNancies, genomic-location cloning, and a cited reference title). No «our HPC» compute submitted (correctly: no compute-bearing analysis exists). Nothing attempted to reproduce; honest drop, not a failure to run. See scope.md + claims.tsv (4 wet-lab results recorded for audit, all out-of-scope).
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
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v1 current initial assessmentassessed: 2026-06-18 ⛓ aaecf2c77d3f
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- 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: sonnetRIT1, a RAS-family GTPase mutated in Noonan syndrome, may act through signaling routes beyond RAF-MEK-ERK and PI3K-AKT, specifically via cytoskeleton-regulating effectors such as PAK1 and the RHO GTPases RAC1/CDC42, and disease-causing RIT1 mutations may alter this novel signaling node.
- ★ PAK1 is a novel direct effector of RIT1 finding
- ★ RIT1 directly interacts with the RHO GTPases CDC42 and RAC1 finding
- ★ RIT1 interactions with PAK1, CDC42 and RAC1 are independent of the guanine nucleotide (GDP/GTP) bound to RIT1 mechanism
- ★ NS-associated RIT1 mutations enhance protein-protein interaction with PAK1, CDC42 or RAC1 and uncouple complex formation from serum/growth factor regulation finding
- ★ The RIT1-PAK1 complex regulates cytoskeletal rearrangements, causing dissolution of stress fibers and reduction of mature paxillin-containing focal adhesions in COS7 cells, an effect blocked by dominant-negative CDC42/RAC1 or kinase-dead PAK1 finding
- ★ RIT1 wildtype and NS-associated variants enhance cell motility in a transwell migration assay finding
- ★ NS-associated RIT1 mutants increase ERK1/2 phosphorylation compared with wildtype finding
- ★ RIT1 interaction with PAK1 is stimulated by serum factors finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Western blot / immunoblotting (pERK1/2, ERK1/2) | HEK293T cells | overexpression of RIT1 WT/mutants (K23N, G31R, A57G, F82L, M90V, G95A) | phospho-ERK1/2 normalized to total ERK1/2 upon serum starvation/stimulation | — |
| Western blot / immunoblotting (pAKT S473/T308) | HEK293T cells | overexpression of RIT1 WT/mutants, EGF stimulation | phospho-AKT levels | — |
| GST pull-down (GST-RALGDS[RA], GST-PLCE1[RA], GST-PIK3CA[RBD], GST-PAK[CRIB]) | HEK293T cells | serum starvation (0.1%), EGF stimulation, or full serum (10%) | amount of co-precipitated HA-RIT1 | — |
| GST pull-down (GST-PAK[CRIB]) | HEK293T cells | RIT1 WT vs NS-associated mutants (K23N, G31R, A57G, F82L, M90V, G95A) | relative amount of co-precipitated HA-RIT1 | — |
| Co-immunoprecipitation (anti-PAK1) | HEK293T cells | RIT1 WT vs mutants, serum-starved or full serum | co-precipitated HA-RIT1 normalized to IP'd PAK1 and total lysate | — |
| Co-immunoprecipitation (endogenous PAK1/RIT1) | COS7 cells | RIT1 WT vs p.G95A | interaction between endogenous PAK1 and RIT1 | — |
| GST/GFP pull-down (GFP-PAK4) | HEK293T cells | RIT1 WT vs p.G95A | presence of HA-RIT1 in GFP-PAK4 precipitates (group II PAK specificity test) | — |
| In-vitro binding assay with purified recombinant proteins | purified His-tagged RIT1 and GST-PAK[CRIB] | RIT1 loaded with GTPγS vs GDP; A57G and F82L mutants | direct binding/affinity of RIT1 to PAK[CRIB] | — |
- ▲ All six NS-associated RIT1 mutants induced elevated and prolonged ERK1/2 phosphorylation upon serum stimulation compared with WT; significant for p.F82L (5 min), p.G95A (30 min), p.M90V (5,15,30 min)
- ▲ RIT1 p.G95A significantly stimulated ERK1/2 phosphorylation under serum-deprived conditions, unlike WT or other mutants
- ▲ Under steady-state (10% serum), RIT1 p.K23N showed statistically significant increased ERK1/2 phosphorylation vs WT
- ▲ HA-RIT1 co-precipitation with GST-PIK3CA[RBD] was significantly increased in cells cultured with serum factors vs serum-starved cells
- ▲ HA-RIT1 co-precipitation with GST-PAK[CRIB] was significantly increased in cells cultured with serum (10%) vs serum-starved (0.1%) cells
- ▲ RIT1 p.K23N and p.G95A significantly increased co-precipitation with PAK[CRIB] compared with WT; other mutants showed a consistent but non-significant trend
- ▲ Co-IPed HA-RIT1 p.M90V with endogenous PAK1 was significantly increased vs WT in serum-deprived cells; p.F82L and p.G95A showed a similar trend
- – His-tagged RIT1 directly bound GST-PAK[CRIB] in vitro in the nanomolar affinity range, slightly increased when RIT1 was GTPγS-bound vs GDP-bound nanomolar affinity
- pvalue P < 0.05 (ERK1/2 phosphorylation increase for RIT1 p.F82L (5 min) vs WT after serum stimulation)
- pvalue P < 0.01 (ERK1/2 phosphorylation increase for RIT1 p.G95A (30 min) vs WT after serum stimulation)
- pvalue one-way ANOVA P < 0.01 (steady-state ERK1/2 phosphorylation among RIT1 p.K23N, p.G31R, p.M90V vs WT)
- pvalue one-way ANOVA P < 0.01 (co-precipitated RIT1 with PIK3CA[RBD]/PAK[CRIB] under serum vs serum-starved conditions)
- pvalue one-way ANOVA P < 0.01 (co-precipitation of RIT1 WT and mutants with PAK[CRIB])
- pvalue P < 0.05 (co-IP of RIT1 mutants (incl. M90V) with endogenous PAK1 under serum starvation)
- other ≥5% (frequency of RIT1 mutations among Noonan syndrome cases)
- count 3 independent experiments (replicate number for most immunoblotting/densitometry quantifications)
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.
This cell-biology study used transient transfection of heterologous expression systems (HEK293T, COS7) and in-vitro binding assays to characterize RIT1–PAK1/RAC1/CDC42 interactions and downstream cytoskeletal effects. Quantitative comparisons of immunoblot densitometry data relied primarily on one-way ANOVA followed by Bonferroni-corrected post-hoc t-tests, with some pairwise comparisons made directly by unpaired t-tests. Results were reported as mean ± SD of 2–4 independent experiments, with significance thresholds at P < 0.05, < 0.01, and < 0.001; exact p-values and effect sizes were not reported.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Unpaired two-sample t-test | Fig 1B – ERK1/2 phosphorylation at each serum-stimulation timepoint (0, 5, 15, 30 min), mutants vs. wildtype | 3 independent experiments | not stated |
| One-way ANOVA with post-hoc unpaired t-tests and Bonferroni correction | Fig 1C – steady-state ERK1/2 phosphorylation across RIT1 wildtype and mutant groups | 3 independent experiments | not stated |
| One-way ANOVA with post-hoc unpaired t-tests and Bonferroni correction | Fig 2B – relative amount of co-precipitated RIT1 across pull-down conditions (RALGDS, PLCE1, PIK3CA, PAK[CRIB]) | 4 independent experiments | not stated |
| One-way ANOVA with post-hoc unpaired t-tests and Bonferroni correction | Fig 3A – relative co-precipitation of RIT1 wildtype and mutants with GST-PAK[CRIB] | 3 independent experiments | not stated |
| Unpaired t-test | Fig 3B – co-IP of HA-RIT1 wildtype vs. p.G95A with endogenous PAK1 under 0.1% and 10% serum | 3 independent experiments | not stated |
| Unpaired t-test | Fig 3C – co-IP of HA-RIT1 wildtype vs. multiple mutants with endogenous PAK1 under serum deprivation | 2 independent experiments | not stated |
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In Fig 1B, separate unpaired t-tests were applied at each of four timepoints for each mutant, generating many simultaneous comparisons without a stated family-wise correction↳ Could also: A two-way repeated-measures ANOVA (factors: construct × time) with a single post-hoc correction (e.g., Tukey HSD or Dunnett vs. wildtype) could also have been used — A factorial model would simultaneously test main effects and the interaction of construct and time, and a single post-hoc correction step would directly control the family-wise error rate across all timepoint-by-group comparisons
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Several key comparisons (Fig 3B, 3C) were made with n=2–3 independent experiments using unpaired t-tests that assume approximate normality↳ Could also: Non-parametric alternatives such as the Mann-Whitney U (Wilcoxon rank-sum) test could also be applied — With very small n, the central-limit theorem provides limited assurance of normality; non-parametric tests make no distributional assumptions, though they sacrifice some power when the normality assumption is in fact satisfied
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Dispersion was reported as SD throughout↳ Could also: 95% confidence intervals around the mean could also be reported alongside or instead of SD — CIs convey both the spread of the data and the precision of the mean estimate, and are increasingly requested by journals as they facilitate meta-analytic combination of results
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Statistical significance was communicated via asterisk tiers (P < 0.05, < 0.01, < 0.001) rather than exact p-values↳ Could also: Reporting exact p-values (e.g., P = 0.023) could also be used — Exact values let readers assess evidence strength on a continuous scale, support replication efforts, and are required for many meta-analyses
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No effect-size metrics were reported alongside the p-values↳ Could also: Standardized effect sizes such as Cohen's d, or unstandardized fold-changes with 95% CI, could also be reported — Effect sizes decouple the magnitude of a difference from sample size, providing additional context especially when n is small and power is limited
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Normalization divided each replicate by the mean of the wildtype samples within that experiment to conserve relative variance (citing ref 79)↳ Could also: Linear mixed-effects models treating experiment as a random effect could also account for between-experiment variability while analyzing absolute densitometry values — Mixed models explicitly partition within- vs. between-experiment variance and can be more powerful when the number of replicates per experiment varies, though they require more observations to estimate random effects reliably
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-29734338
Title: RIT1 controls actin dynamics via complex formation with RAC1/CDC42 and PAK1. Authors: Meyer Zum Büschenfelde U, Brandenstein LI, von Elsner L, Flato K, Holling T, Zenker M, Rosenberger G, Kutsche K. Venue: PLoS Genetics 2018 May 7;14(5):e1007370. DOI: 10.1371/journal.pgen.1007370. PMCID: PMC5937737. Data Availability (verbatim): "All relevant data are within the paper and its Supporting Information files."
Verdict: DROP — non_pipeline
This is a wet-lab molecular / cell-biology study. After reading the full text (PMC5937737) Methods + Data-availability statement, there is no bioinformatic / computational pipeline to reproduce, and no deposited data or analysis-code artifact (no GEO/SRA/ENA/ArrayExpress/figshare/Zenodo accession, no GitHub/GitLab repository).
What the paper actually does (all out of scope = wet-lab / manual)
- Heterologous expression in COS7 / Flp-In 293 / HEK293 cells; purified recombinant GST-/His-tagged proteins.
- Direct protein–protein interaction by GST pull-down, co-immunoprecipitation, immunoblotting (autoradiography).
- ERK1/2 phosphorylation immunoblots.
- Immunofluorescence microscopy of stress fibers / paxillin-positive focal adhesions.
- Transwell migration / invasion assays; FACS-based cell counting (FACSCalibur + CellQuestPro + AccuCheck beads).
The only "computational" steps present — still NOT a reproducible pipeline
| Tool | Use in paper | Why out of scope |
|---|---|---|
| ImageJ (NIH) | densitometry of autoradiographs; counting paxillin-positive structures (≥30 cells/dataset), morphology scoring (≥50 cells/dataset) | manual/semi-manual quantification of wet-lab images; raw images/blots are NOT deposited — only summary values appear in figures/SI, so the quantification cannot be re-run |
| GraphPad Prism 7 (InStat) | mean ± SD; Student's t-test (pairwise), one-way ANOVA + Bonferroni post-hoc | standard statistics applied to the wet-lab measurements above; not a bioinformatic pipeline, and the per-cell/per-blot input values are not provided as machine-readable data |
Disambiguation of full-text term hits (false positives)
- "BLAST" → only "neuroblastoma" / "lymphoblastic".
- "align" → only "malignancies".
- "genom(ic)" → "genomic location" (Flp-In integration site, a cloning method) + reference titles.
- "pipeline" → appears only inside the title of a cited reference ("...Next-Generation Sequencing Diagnostic Pipeline of RASopathies", Sci Rep 2018), not this paper's own methods.
- RIT1 variants studied (p.K23N, p.A57G, p.G31R, p.F82L, p.M90V, p.G95A) are known Noonan-syndrome alleles introduced by site-directed mutagenesis — no variant-calling / sequencing pipeline.
In-scope pipeline-derived results
None. No reported value in this paper is produced by a bioinformatic pipeline operating on a deposited dataset. Nothing is attempted on «our HPC» (correctly — there is no compute-bearing analysis to run).
Datasets relied upon
None external. No accession exists; all data are figure panels + Supporting
Information within the article itself (CC BY). data/dataset_profile.json
records this (no external deposit).
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 correctly identified non_pipeline drop: Meyer Zum Büschenfelde et al. 2018 (PLoS Genet, PMC5937737) is a wet-lab molecular/cell-biology study (GST pull-down, co-IP, immunoblot, immunofluorescence, transwell migration) with no bioinformatic pipeline and no deposited data/code accession. Nothing was attempted to reproduce because there is nothing pipeline-reproducible — the only 'computation' is interactive ImageJ densitometry and GraphPad Prism statistics on undeposited raw images. The inability to compare values is purely a data-availability/scope matter (q1/q2 red), not an authors' defect or fabrication concern, so q5/q7/q8 stay yellow rather than red. Severity is non-applicable (no deviation measured).
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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.