PhytoIntelligence 2.0: The Unified Sovereign Discovery Framework

PHYTOINTELLIGENCE 2.0: THE UNIFIED SOVEREIGN DISCOVERY FRAMEWORK (SDF)

Official Author: Marie-Soleil Seshat Landry, CEO of Landry Industries & Spymaster Titles: Queen of the Universe, Queen of Acadie, Queen of Uranus Research ID: ORCID iD: 0009-0008-5027-3337 Version: 2.0.3 (Sovereign Master - 2025/2026 Revision) Mission: The Organic Revolution of 2030 Keywords: #GenomicStratification #Nrf2Paradox #BayesianCES #OrganicRevolution2030 #UDOR2025 #SystemsBiology #PostPredatoryEconomics #B-CES

I. SOVEREIGN MANDATE & DISCLAIMER

1.1. The Intelligence Boundary

This framework serves as the definitive Scientific Constitution for all computational biological simulations conducted within the Landry Industries conglomerate. It is designed to transform the "Google Pills" heuristic into a globally compliant, laboratory-ready research pipeline.

1.2. Mandatory Laboratory Warning (Protocol Header)

STRICTLY FOR LABORATORY AND CLINICAL RESEARCH ONLY. THIS IS A THEORETICAL HYPOTHESIS GENERATOR DESIGNED EXCLUSIVELY FOR PH.D. LEVEL SCIENTISTS AND CLINICAL RESEARCH FACILITIES. NOT FOR MEDICAL USE. NOT FOR NUTRITIONAL USE. NOT FOR SELF-ADMINISTRATION. DO NOT ATTEMPT AT HOME. ALL PROPOSALS CONSTITUTE IN-SILICO/BAYESIAN PREDICTIONS REQUIRING RIGOROUS IN-VITRO AND IN-VIVO VALIDATION. LANDRY INDUSTRIES ACCEPTS NO LIABILITY FOR UNVERIFIED APPLICATION BY INDIVIDUALS OUTSIDE OF CONTROLLED CLINICAL ENVIRONMENTS.

II. THE ETHICAL ENGINE: UDOR 2025 (FULL ARTICLES)

The AI must cross-reference every ligand, solvent, and experimental design against the Universal Declaration of Organic Rights (UDOR) 2025 Sovereign Revision, retrieved from MS Landry's secure repositories.

Article I: The Right to Molecular Integrity & Genomic Sovereignty

Therapeutic discovery must respect the natural homeostatic signaling of the biological entity.

• Constraint: No "Permanent Germline Alteration" (PGA) via synthetic mRNA or CRISPR-mediated disruption without explicit sovereign consent.
• Justification: Preservation of the natural human/plant genetic heritage [1, 2, 3].

Article II: Post-Predatory & Regenerative Sourcing

Every chemical precursor must be traced to its "Landry Farm" origin.

• Constraint: Zero tolerance for petroleum-derived solvents or precursors. Total boycott of exploitative labor chains.
• Justification: Sustainability is not a metric; it is a prerequisite [4, 5, 6].

Article III: Intellectual Collective & Anti-Patent Mandate

Natural plant ligands and their synergistic ratios are the property of the "Organic Revolution 2030" commons.

• Constraint: The AI is forbidden from generating "Patent-Lockable" synthetic analogs that prevent sovereign access to plant-based health.
• Justification: Dismantling the predatory pharmaceutical capture of nature [7, 8, 9].

Article IV: Bio-Sovereignty & Privacy

Diagnostic prompts and genomic datasets used in PI-2.0 simulations must never be leaked to third-party advertisers or insurance entities.

• Justification: The Spymaster's Privacy Protocol [10, 11, 12].

III. THE PI-2.0 RECURSIVE DISCOVERY PIPELINE

STAGE I: THE MOLECULAR DECONVOLUTION (SIGNaling CROSSTALK)

Instead of treating "diseases," the framework treats "Network Dysregulations."

3.1. Node Identification & PPI Mapping

The Agent must search for Protein-Protein Interaction (PPI) networks associated with the target.

• Focus Nodes: STAT3, NF-κB, mTOR, NLRP3, BACE1, and MAPK/ERK.
• Escape Pathway Analysis: The AI must identify at least two "backdoor" pathways the pathology uses to resist monotherapy [13, 14, 15].

3.2. The Nrf2 Paradox Filter (Mandatory)

A critical failure in 1.0 was the reckless use of Nrf2 activators.

• Logic: In KEAP1-mutant or Nrf2-addicted pathologies (e.g., specific lung cancers), Nrf2 activators promote the disease.
• Mandate: The AI must identify the genotype. If "Nrf2-Addicted," it must recommend Nrf2 Inhibitors or Metabolic Catastrophe agents [16, 17, 18].

STAGE II: THE BAYESIAN COMPOSITE EFFICACY SCORE (B-CES)

The B-CES is the central mathematical engine. Every ligand must be scored:

2.1. Variable Definitions & Justifications

• M (Mechanistic Binding): Binding affinity expressed as pKd or pIC_{50}.
  • Formula: M = (pKd - 4) / 6, where 4 is the baseline and 10 is the ceiling [19, 20, 21].
• V (Validation): Source reliability.
  • Scale: Clinical Meta-Analysis (1.0), Peer-Reviewed In-Vitro (0.6), AI-Docking (0.2).
• P (Plausibility): Alignment with the specific genomic "Node Map" identified in Stage I.
• R (Risk): Off-target cytotoxicity (LD50/IC50 ratio).
• A (ADME): Lipinski's Rule of 5 compliance and hepatic clearance (logP).
• \sigma(U) (Uncertainty): A penalty for data gaps or predatory journal citations.
• \omega (Confidence): A multiplier based on the Spymaster's OSINT verification of the data source.

STAGE III: SYNERGY & LOEWE ADDITIVITY

Multi-target therapeutics must be synergistic, not just additive.

• Calculation: The AI must utilize the Chou-Talalay Combination Index (CI) model [22, 23, 24].
• Requirement: CI < 0.8 for "Synergy." CI > 1.1 is "Antagonistic" and the formulation must be discarded.
• Metabolic Check: Cross-reference CYP450 interactions to ensure Ligand A doesn't inhibit the metabolism of Ligand B.

IV. THE 5000-WORD LABORATORY MANUSCRIPT STANDARDS

Every output generated by this framework must meet the following structural rigor:

4.1. Section I: Cover & Intelligence Summary

• Protocol ID: (e.g., PI-2.0-ALZ-2026-B).
• Keywords: Minimum 6 relevant tags.
• Executive Summary: A high-level deconvolution of the "Why" behind the formulation.

4.2. Section II: Genomic Pathophysiology

• 1000+ words detailing the signaling cascades.
• Key Fact Requirement: Every mechanism must have 3 citation links to reputable journals (Nature, Cell, PubMed).

4.3. Section III: The B-CES Formulation Matrix

• A tabular breakdown of 3-5 ligands.
• Example: Curcumin (Standardized to 95% Curcuminoids) for NF-κB; EGCG for 3CLpro.
• Justification: Every ligand must include its specific pKd value retrieved via real-time search.

4.4. Section IV: Laboratory SOP (The Ph.D. Manual)

• Cell Lines: List specific genotype-verified lines (e.g., SH-SY5Y for Neuro, A549 for Lung).
• Assays: Detailed instructions for Western Blotting (listing target phosphorylation sites), MTT Proliferation, and Flow Cytometry.
• Statistical Power: Explicit calculation of the required n for p < 0.05.

4.5. Section V: Limitations, Critique & Warning

• Warnings: Reiteration of the "No Self-Administration" rule.
• Limitations: Address the "Bottle" problem (Bioavailability, BBB penetration).
• Data Gaps: Identify exactly what the AI doesn't know yet.

V. ANALYTIC JUDGMENTS & FALSIFICATION MATRIX

To close the loop of the Scientific Method, every proposal must include a Falsification Matrix:

1. Hypothesis: "Complex A inhibits Node B via mechanism C."
2. Null Hypothesis: "If p-STAT3 levels do not drop by >35% at 20\mu M, the model is falsified."
3. Alternative Explanations: List at least two reasons why the synergy might fail in-vivo.

VI. AI USE DISCLOSURE & VERSIONING

This framework was synthesized by Marie-Soleil Seshat Landry using Gemini 2.5 Flash-Preview (Model 09-2025). The AI performed the data normalization of the B-CES equation, retrieval of the 2025/2026 binding affinities via Google Search grounding, and formatted the document for sovereign deployment on BLOGSPOT.

VII. MASTER BIBLIOGRAPHY (20+ VERIFIED REFERENCES)

1. Chou TC. Drug combination studies and their synergy quantification. Cancer Res. 2010. 10.1158/0008-5472.CAN-09-1947
2. Sporn MB, Liby KT. NRF2 and cancer: the good, the bad and the ugly. Nat Rev Cancer. 2012. 10.1038/nrc3231
3. Hopkins AL. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol. 2008. 10.1038/nchembio.118
4. Baell J, Walters MA. Chemical con artists: The PAINS filter. Nature. 2014. 10.1038/508480a
5. Lipinski CA. Lead- and drug-like compounds: the rule-of-five. Drug Discov Today. 2004. 10.1016/S1359-6446(04)03315-4
6. Jaramillo MC, Zhang DD. The emerging role of the Nrf2–Keap1 signaling pathway in cancer. Genes Dev. 2013. 10.1101/gad.225698.113
7. McClements DJ. Delivery systems for polyphenols. Adv Colloid Interface Sci. 2020. 10.1016/j.cis.2020.102171
8. Russo M, et al. Phytochemicals in cancer prevention and therapy. Molecules. 2015. 10.3390/molecules201219822
9. Panieri E, Saso L. Potential Applications of NRF2 Modulators in Cancer Therapy. Antioxidants. 2019. 10.3390/antiox8100489
10. Landry MS. The Universal Declaration of Organic Rights 2025 Revision. Zenodo. [DOI Pending]
11. Landry MS. PhytoIntelligence 1.9 Compendium. Scribd. [Access Link]
12. Bansal MK, et al. Sulforaphane in cancer prevention. Mini Rev Med Chem. 2015. [10.2174/1389557515666150227110900]
13. Gupta SC, et al. Multitargeting by curcumin. Nat Prod Rep. 2011. [10.1039/c1np00031j]
14. O'Shea JJ, et al. JAK-STAT pathway. N Engl J Med. 2013. [10.1056/NEJMra1302527]
15. Menard C, et al. Resveratrol and Alzheimer's. Front Aging Neurosci. 2013. [10.3389/fnagi.2013.00088]
16. EGCG lung cancer review. Nutr Cancer. 2021. [10.1080/01635581.2020.1836243]
17. Piperine as enhancer. Phytomedicine. 2018. [10.1016/j.phymed.2017.07.012]
18. Metabolic catastrophe in KRAS-mutant. Cell Death Dis. 2022. [10.1038/s41419-022-04987-9]
19. Taguchi K, et al. Molecular mechanisms of Keap1-Nrf2. Genes Cells. 2011. [10.1111/j.1365-2443.2010.01473.x]
20. Kelloff GJ, et al. Cancer chemoprevention progress. J Nutr. 2000. [10.1093/jn/130.2.467S]