The Evidence Layer for Scientific AI

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The Evidence Layer for Scientific AI

Ask questions across claims linked to experiments, exact results, limitations, and sources.Know what the science actually supports before you trust the answer.

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3. Sequence-based drug design using transformers [2023]

4. Kinetic fingerprints differentiate anti-Aβ therapies [2019]

5. Amyloid-β modulates the phase separation and aggregation of α-synuclein. [2025]

6. Telomeric DNA damage response mediates neurotoxicity of Aβ42 oligomers in Alzheimer's disease. [2025]

9. The gain-of-function TREM2-T96K mutation increases risk for Alzheimer's disease by impairing microglial function. [2025]

11. An Automated Micro-Immunobeads-Based Electromagnetic Operation System (MEMOs) for Blood Testing of Alzheimer's Disease. [2025]

12. Mild behavioural impairment-apathy and core Alzheimer's disease cerebrospinal fluid biomarkers. [2025]

13. Single-fibril Förster resonance energy transfer imaging and deep learning reveal concentration dependence of amyloid β 42 aggregation pathways. [2025]

14. Baicalein inhibits amyloid-β42 aggregation and promotes disaggregation by binding to the aggregation-prone region, disrupting the Asp23-Lys28 salt bridge, stabilizing non-β-sheet structures, and demonstrating this dual activity through in vitro assays and atomistic simulations. [2025]

15. Longitudinal Blood-Based Biomarkers and Clinical Progression in Subjective Cognitive Decline. [2025]

16. Plasma biomarkers in neuropsychiatric syndromes: A narrative review. [2025]

17. Epigenetic clocks and longitudinal plasma biomarkers of Alzheimer's disease. [2025]

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Upload the original figure or numeric data so I can fit microscopic aggregation models and return kplus k2 kn estimates with uncertainties

Do you want mechanistic fits (primary nucleation, elongation, secondary nucleation) or only nonparametric t1/2 summaries?

Should I compare results across multiple papers and experimental conditions after normalizing buffers and monomer concentrations?

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Digitizing and fitting ThT timecourses, extracting t1/2 and fitting microscopic aggregation models across datasets (Sequence based drug design, Kinetic fingerprints) using provided or digitized data.

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I prioritize mechanistic interpretations and publicly available evidence; limited by lack of raw numeric traces here.

Stay current without chasing every paper.

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