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     Long Response


    SCFA vs IBS symptom change: data availability check

    Critical constraint
    The provided source report is a healthy-adult dietary cross-over study (not IBS patients) and it reports that faecal SCFA/BCFA did not change significantly with dietary FODMAP variation over ~3 weeks, while GI symptoms were not significantly different between arms. However, the excerpted dataset you provided contains no numeric per-participant (or arm-level with dispersion) values for β€œSCFA change” and β€œIBS symptom change”, so a true SCFA-vs-symptom scatter/fit cannot be computed without adding new raw numbers.

    Figure 1 β€” Intended plot, but no plottable numeric endpoints

    What we can say from the supplied data

    • SCFA/BCFA (faecal): reported as not statistically different between dietary arms (so even arm-level Ξ” values are not given in the excerpt).
    • Symptoms: the excerpt indicates no significant differences in GI symptoms between arms. But again, no numeric symptom-change values are provided.
    • Population mismatch: this study is in healthy adults, not IBS patients; therefore, β€œIBS symptom change” is not directly measured in the supplied material.

    What you can provide so I can generate the requested SCFA vs symptom graph

    Minimum needed (no placeholders)
    Provide either:
    1. Per-participant data: baseline and follow-up (or Ξ”) for SCFA (e.g., total acetate/propionate/butyrate or specific SCFAs) and IBS symptom score (e.g., IBS-SSS, diary composite) so we can scatter/fit Ξ”SCFA vs Ξ”symptom.
    2. Or arm-level summary with dispersion: mean Ξ”SCFA Β± SD/SE and mean Ξ”symptom Β± SD/SE for β‰₯2 arms (still limited), ideally with n per arm.
    If you upload a table/CSV (or paste the numeric results), I’ll produce:
    (i) scatter with regression line (or rank-correlation), (ii) confidence/uncertainty depiction, and (iii) sensitivity notes.
    Epistemic humility / skepticism: With only the provided excerpt, any attempt to compute β€œSCFA vs IBS symptom change” would require inventing missing numeric endpoints, which would violate the constraint against hypothetical/simulated data.


    Feedback:    

    Updated: April 28, 2026

     Analysis Wizard



    It would compute per-participant SCFA and IBS symptom delta, then fit correlation/regression and generate a Plotly scatter with uncertainty, using numeric values you provide from the raw tables.



     Science Art


    Create Graphs: Plot SCFA vs IBS symptom change Science Art

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