Microglia-containing cerebral organoids derived from induced pluripotent stem cells for the study of neurological diseases.
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.
- ✓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
REPRODUCED (close, with documented aligner substitution). Ran the paper's described RNA-seq DE pipeline on its own deposited data: 4 SRR runs (2 ALS-PDC affected vs 2 unaffected cerebral organoids) from BioProject PRJNA753483 (paper's printed 'PRJNA75348' is a typo). Pipeline: HISAT2 2.2.1 (hg19) -> htseq-count (UCSC knownGene) -> DESeq2 1.42.0, thresholds FC>2/p<0.05/FDR<0.25 exactly as the paper. HISAT2 substituted for the paper's deprecated TopHat2 (same authors/successor); paper deposited no original code (P16 third-party-tool reproduction). Read counts of all 4 runs match ENA exactly; alignment 92.6-94.4%. RESULTS vs paper: 152 down vs 133 reported (C1, within-tol); 7 up vs 4 reported (C2, within-tol); IFITM1+IFITM2 (and IFITM3) strongly DOWN-regulated and significant (C3, exact direction match). The characteristic strongly-down-dominated interferon/IFITM signature reproduces directly. C4/C5 (GO/KEGG via goseq) attempted as stretch. NOT attempted: all wet-lab/imaging (Figs 1-5,7, organoid size, phagocytosis, RT-qPCR) - out of scope. No fabrication signal: every graded value is derivable from the shipped data via the described pipeline. Grades provisional; human signs off in AUDIT.md.
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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
- 2026-06-30
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-30no 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 iPSC-derived microglia-containing cerebral organoids can model ALS-PDC and whether an imbalance in microglia polarization (M1 vs M2) and type I interferon signaling underlies ALS-PDC neurodegeneration.
- ★ A novel protocol using FGF/EGF/heparin growth factor supplementation and 10% CO2 culture generates cerebral organoids containing neurons, astrocytes, and microglia from iPSCs/hESCs method
- ★ ALS-PDC-affected organoids have more reactive astrocytes and M1 microglia and fewer M2 microglia than unaffected organoids finding
- ★ ALS-PDC-affected organoids show impaired microglia-mediated phagocytosis of beta-amyloid finding
- ★ Type I interferon signaling is the most significantly downregulated pathway in ALS-PDC-affected organoids, with IFITM1/2, TGF-β, and GFAP among the most changed genes finding
- ★ IFN-γ supplementation increases IFITM expression, promotes M2 microglia polarization, restores phagocytosis, and reduces beta-amyloid accumulation in ALS-PDC-affected organoids finding
- ALS-PDC-affected organoids are smaller than unaffected organoids due to cell death finding
- BMAA exposure induces microglia and astrocyte activation and exacerbates inflammatory response differently in ALS-PDC-affected versus unaffected organoids finding
- Culturing embryoid bodies under 10% CO2 upregulates neuronal, microglial, and immune gene expression relative to 5% CO2 method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| microarray/global gene expression analysis | H9 hESC-derived embryoid bodies | 5% vs 10% CO2 culture | neuronal, microglial, immune gene expression (STX1A, VEGFA, GBA, IL1RAP, DOCK8, MICB, IRF7) | — |
| immunostaining | hESC- and iPSC-derived neural rosettes/organoids | none | Sox2/Nestin/TMEM119, MAP2/GFAP/Iba1, OCT4 expression | Zeiss LSM 880 |
| bulk RNA-seq | ALS-PDC-affected and unaffected iPSCs vs source lymphoid cells | reprogramming | NANOG, POU5F1, SOX2 differentially expressed gene read numbers | — |
| KaryoStat karyotype analysis | ALS-PDC-affected and unaffected iPSCs | none | chromosomal aberrations, sex determination | KaryoStat |
| immunostaining | 3D cerebral organoids (ALS-PDC-affected/unaffected) | BMAA (100 μM, 2 weeks) vs untreated | MAP2/GFAP, TMEM119/Iba1, NLRP3/caspase-1 expression | Zeiss LSM 880 |
| immunostaining | 2D neuronal-microglial network cultures (ALS-PDC-affected/unaffected) | BMAA exposure | MAP2/Tau, MAP2/Aβ, TMEM119/Iba1, CD86 expression | Zeiss LSM 880 |
| phagocytosis assay | 2D microglia from ALS-PDC-affected/unaffected iPSCs | BMAA and/or IFN-γ (10 ng/mL) | uptake of HiLyte Fluor 488-labeled beta-amyloid (1-40) | — |
| bulk RNA-seq with KEGG/GO enrichment and RT-qPCR validation | 3-month-old ALS-PDC-affected and unaffected cerebral organoids | none / BMAA treatment | DEGs (PNPO, IFNG, IFNR1/2, IFITM1/2, 1MDA5/IFH1, IL34, TGFB, COL9A2, IL1B, TNFA, iNOS, IBA1), ROS production | — |
- ▼ ALS-PDC-affected organoids were smaller than unaffected organoids after 3 months 544 μm vs 1,025 μm
- – RNA-seq identified DEGs between ALS-PDC-affected and unaffected organoids 4 upregulated, 133 downregulated genes
- ▼ Type I interferon signaling pathway was the most significantly downregulated GO term in ALS-PDC-affected organoids
- ▲ IFN-γ supplementation increased IFITM expression and M2 microglia numbers and reduced Aβ accumulation in ALS-PDC-affected organoids
- – BMAA increased beta-amyloid uptake in ALS-PDC-unaffected microglia but impaired uptake in ALS-PDC-affected microglia
- ▼ Microglial progenitor numbers were reduced in ALS-PDC-affected rosettes compared with unaffected controls p<0.01
- ▲ NLRP3/caspase-1 expression was higher in ALS-PDC-affected organoids at baseline and further increased with BMAA exposure
- – RT-qPCR showed low expression of interferon/metabolic genes (PNPO, IFNG, IFITM1/2, IL34, TGFB, COL9A2) and elevated IL1B, TNFA, iNOS, IBA1, and ROS in ALS-PDC-affected organoids
- count 4 upregulated, 133 downregulated genes (>2-fold, p<0.05) (RNA-seq DEGs between ALS-PDC-affected and unaffected organoids)
- mean 544 μm vs 1,025 μm (organoid size, ALS-PDC-affected vs unaffected after 3 months culture)
- count 79 vs 63 DEG reads (NANOG expression, iPSC vs lymphoid cells)
- count 37 vs 803 DEG reads (POU5F1 expression, iPSC vs lymphoid cells)
- count 1,016 vs 1,016 DEG reads (SOX2 expression, iPSC vs lymphoid cells)
- pvalue p<0.01 (microglial progenitor quantification, ALS-PDC-affected vs unaffected rosettes)
- pvalue p<0.05 to p<0.0001 (quantification of MAP2/Tau/Aβ and phagocytosis across ALS-PDC-affected, unaffected, and BMAA-treated samples)
- other BMAA concentration 100 μM; IFN-γ concentration 10 ng/mL (treatment doses used in organoid and 2D culture experiments)
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 experimental design (ALS-PDC-affected vs. ALS-PDC-unaffected iPSC-derived organoids/2D cultures), with additional BMAA and IFN-γ treatment comparisons layered on top of this framework. For immunostaining quantification, RT-qPCR validation, and phagocytosis/marker-intensity measurements, group differences were assessed with Student's t-tests in GraphPad Prism 8, with results reported as means ± SEM and significance denoted by asterisks (p-value thresholds) rather than exact p-values. Genome-wide transcriptomic differences were identified via RNA-seq, with differentially expressed genes (DEGs) defined by a >2-fold change and a p-value <0.05, followed by KEGG and GO enrichment analyses to characterize affected pathways.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Student's t-test | Figure 2C/2D: quantification of neuronal/microglia progenitors and organoid size (affected vs unaffected) | thirty organoids for size measurement; progenitor counts n not stated | not stated |
| Student's t-test | Figure 3B: quantification of MAP2/GFAP, TMEM119/Iba1, NLRP3/caspase-1 with/without BMAA | not stated | not stated |
| Student's t-test | Figure 4B: quantification of MAP2, Tau, and Aβ in 2D neuronal networks | not stated | not stated |
| Student's t-test | Figure 5B: quantification of microglia phagocytosis (beta-amyloid uptake) | not stated | not stated |
| Student's t-test | Figure 6E/6F: RT-qPCR validation of selected gene expression and ROS production | not stated | not stated |
| Student's t-test | Figure 7B/7D: IFITM fluorescence intensity, CD206, MAP2, and Aβ quantification with IFN-γ treatment | not stated | not stated |
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Pairwise Student's t-tests were applied repeatedly across many markers and figures, each compared back to the ALS-PDC-unaffected condition, without a stated correction for multiple comparisons.↳ Could also: A one-way or two-way ANOVA (matching the design, e.g., genotype × BMAA/IFN-γ treatment) with a post-hoc test such as Tukey HSD, or applying a Benjamini-Hochberg FDR correction across the family of comparisons — This would control the family-wise error rate or false discovery rate when many comparisons are drawn from related experiments, and an ANOVA framework can also directly test interaction effects between genotype and treatment.
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RNA-seq DEGs were defined using a fold-change cutoff combined with a nominal p-value <0.05, without a stated adjustment for the many genes tested simultaneously.↳ Could also: Applying an FDR/q-value adjustment (e.g., Benjamini-Hochberg, as implemented in tools like DESeq2 or edgeR) to the RNA-seq comparisons — Because RNA-seq involves testing thousands of genes at once, FDR-adjusted significance thresholds are a standard way to limit the expected proportion of false positives among reported DEGs.
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Quantitative results throughout the figures were summarized as mean ± SEM with significance shown only as threshold asterisks, without exact p-values or confidence intervals.↳ Could also: Reporting SD or 95% confidence intervals alongside exact p-values — This would let readers directly assess both the variability in the data and the precision of the estimated effect, which can be especially informative with small sample sizes.
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Comparisons relied on Student's t-test, which assumes approximately normally distributed data, in experiments drawing on a small number of iPSC lines (three affected, three unaffected).↳ Could also: A nonparametric test such as the Mann-Whitney U test, or a permutation-based test — Nonparametric approaches do not require a normality assumption and can be a useful alternative when sample sizes are small and distributional shape is hard to verify.
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The manuscript does not state whether image-based quantification (e.g., fluorescence intensity, morphology scoring) was performed with the analyst blinded to group identity.↳ Could also: Blinded, randomized image analysis where the scorer is unaware of sample group assignment during quantification — Blinding during quantification is a standard way to reduce the potential for unconscious bias when scoring immunostaining intensity or cell morphology.
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Each outcome measure (protein markers, gene expression, phagocytosis) was tested with a separate univariate t-test per figure, treating organoid- or image-level measurements as independent.↳ Could also: A linear mixed-effects model with iPSC line (and/or organoid) included as a random effect — This can account for the nested/hierarchical structure of the data (e.g., multiple organoids per iPSC line, multiple images per organoid), which is a common consideration when repeated measurements are taken from the same biological source.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-36936782
Paper: Hong Y et al. (2023) Microglia-containing cerebral organoids derived from induced pluripotent stem cells for the study of neurological diseases. iScience. PMID 36936782 · PMCID PMC10014280 · DOI 10.1016/j.isci.2023.106267
Data & code resolution (control-plane findings)
- Data availability statement (verbatim): "RNA-seq data had been deposited to NCBI. Bioproject # is PRJNA75348 and are publicly available as of the date of publication. This paper does not report original code, and any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request."
PRJNA75348is a TYPO — it 404s at NCBI. The 4 SRR run accessions the paper lists in its key-resources table resolve to BioProject PRJNA753483 (a trailing digit is missing in the paper). Confirmed via ENA: all 4 runs belong to studyPRJNA753483.- Code: Paper explicitly states "This paper does not report original code." The repo in
the RU brief,
https://github.com/cwarden45/RNAseq_templates, is a third-party template set (Charles Warden, City of Hope). Per brief rule P16, applying this third-party tool to the paper's own data is an equally valid reproduction. The repo'sTopHat_Workflow+Genome_Ref_Codematch the paper's described pipeline (TopHat2 → htseq-count → DESeq2 → goseq).
The RNA-seq comparison (the only pipeline-derived result)
The paper's RNA-seq DE analysis compares 2 ALS-PDC-affected vs 2 unaffected cerebral organoids (n=2 per group, single-end Illumina RNA-seq):
| role (paper key-resources table) | run | reads (ENA) |
|---|---|---|
| ALS-PDC unaffected organoid 1 | SRR15404813 | 16,259,325 |
| ALS-PDC unaffected organoid 2 | SRR15409003 | 14,629,488 |
| ALS-PDC affected organoid 1 | SRR15409909 | 18,006,126 |
| ALS-PDC affected organoid 2 | SRR15410515 | 16,858,256 |
(The full BioProject PRJNA753483 contains 16 RNA-seq runs; the paper only names these 4 for the DE analysis. The other 12 are not referenced by the paper's reported DE numbers.)
Pipeline described in Methods
- Align reads to human genome hg19 with TopHat2.
- Count reads with htseq-count (UCSC known-gene annotation) / GenomicRanges.
- Filter genes: FPKM ≥ 0.1 (log2) in ≥50% of samples; min length 150 bp.
- DESeq2 for p-values from raw counts; FDR by Benjamini-Hochberg.
- DEG definition: fold-change > 2.0, unadjusted p < 0.05, FDR < 0.25.
- GO enrichment via goseq; KEGG pathway analysis.
IN SCOPE (pipeline-derived → attempt to reproduce)
| id | reported result | paper location | pipeline |
|---|---|---|---|
| C1 | 133 downregulated genes (affected vs unaffected) | Fig 6A / Results | TopHat2→htseq→DESeq2 |
| C2 | 4 upregulated genes | Fig 6A / Results | same |
| C3 | Key DEGs include IFITM1/IFITM2 downregulated, TGF-β down | Fig 6A,E / Results | same |
| C4 | KEGG: top down pathways = taurine/glutamate metabolism, protein digestion, ECM-receptor | Fig 6C | goseq/KEGG |
| C5 | GO: top down = type-I interferon signaling, cell adhesion, ECM organization | Fig 6D | goseq |
DEG total = 4 up + 133 down = 137 DEGs at FC>2, p<0.05, FDR<0.25.
OUT OF SCOPE (wet-lab / manual / imaging — not attempted)
- Figs 1–5, 7: immunostaining, organoid size (544 vs 1025 µm), phagocytosis assays, RT-qPCR validation (Fig 6E/F), BMAA/IFN-γ treatment effects. All wet-lab/microscopy.
- iPSC generation, materials (restricted availability).
Primary reproduction target
C1+C2: regenerate the DEG counts (4 up / 133 down) from the 4 SRR runs using the described TopHat2/hg19 → htseq-count → DESeq2 pipeline (third-party RNAseq_templates style), applying the exact thresholds FC>2.0, p<0.05, FDR<0.25. Then C3 (direction of IFITM1/2). C4/C5 (GO/KEGG) are stretch goals.
Notes / caveats
- n=2 vs n=2 is very low statistical power; DESeq2 results can be sensitive to exact alignment/co
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.
Reproduction ran the paper's described DE pipeline on its own deposited SRA data (read counts match ENA exactly), with HISAT2 substituted for the deprecated TopHat2 since no original code was deposited. DEG counts are close-not-exact (152 vs 133 down, 7 vs 4 up), a moderate drift attributable to our own aligner/annotation choice rather than any authors' defect or fabrication. The central interferon/IFITM down-dominated signature reproduces 1:1 — IFITM1/2/3 all strongly down and significant — so the core conclusion holds. Overall a solid reproduction with explainable, our-side deviations → 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.