#!/usr/bin/env python3
"""
BIOHACKING - DNA/RNA NODE INTEGRATION SYSTEM
===============================================
Complete biological interface for neural nodes with:
- DNA data storage and retrieval
- RNA/mRNA/tRNA signal translation
- Genetic sequence to RF frequency mapping
- Epigenetic modulation via node stimulation
- CRISPR-based node programming

This system bridges biological genetics with RF neural nodes,
enabling DNA/RNA to control node behavior and vice versa.
"""

import numpy as np
import hashlib
import json
import time
import zlib
from typing import Dict, List, Tuple, Optional
from dataclasses import dataclass, field
from enum import Enum

# =============================================================================
# SECTION 1: DNA/RNA SEQUENCE TO RF FREQUENCY MAPPING
# =============================================================================

class GeneticToRFMapper:
    """
    Maps DNA/RNA sequences to RF frequencies for node communication
    Each genetic sequence has a unique RF signature
    """
    
    # Nucleotide to base frequency mapping (GHz)
    NUCLEOTIDE_FREQS = {
        'A': 10.23,  # Adenine
        'T': 10.24,  # Thymine (DNA)
        'U': 10.25,  # Uracil (RNA)
        'G': 10.26,  # Guanine
        'C': 10.27,  # Cytosine
    }
    
    # Codon to frequency offset (MHz)
    CODON_OFFSETS = {
        'AUG': 0.000,  # Start codon (Methionine)
        'UAA': 0.050,  # Stop codon
        'UAG': 0.051,  # Stop codon
        'UGA': 0.052,  # Stop codon
        # Common amino acids
        'UUU': 0.010, 'UUC': 0.011,  # Phenylalanine
        'UUA': 0.012, 'UUG': 0.013,  # Leucine
        'CUU': 0.014, 'CUC': 0.015,  # Leucine
        'AUU': 0.016, 'AUC': 0.017,  # Isoleucine
        'AUA': 0.018, 'AUG': 0.019,  # Methionine
        'GUU': 0.020, 'GUC': 0.021,  # Valine
        'UCU': 0.022, 'UCC': 0.023,  # Serine
        'CCU': 0.024, 'CCC': 0.025,  # Proline
        'ACU': 0.026, 'ACC': 0.027,  # Threonine
        'GCU': 0.028, 'GCC': 0.029,  # Alanine
        'UAU': 0.030, 'UAC': 0.031,  # Tyrosine
        'CAU': 0.032, 'CAC': 0.033,  # Histidine
        'CAA': 0.034, 'CAG': 0.035,  # Glutamine
        'AAU': 0.036, 'AAC': 0.037,  # Asparagine
        'AAA': 0.038, 'AAG': 0.039,  # Lysine
        'GAU': 0.040, 'GAC': 0.041,  # Aspartic acid
        'GAA': 0.042, 'GAG': 0.043,  # Glutamic acid
        'UGU': 0.044, 'UGC': 0.045,  # Cysteine
        'UGG': 0.046,                  # Tryptophan
        'CGU': 0.047, 'CGC': 0.048,  # Arginine
        'AGU': 0.049, 'AGC': 0.050,  # Serine
        'AGA': 0.051, 'AGG': 0.052,  # Arginine
        'GGU': 0.053, 'GGC': 0.054,  # Glycine
    }
    
    @classmethod
    def dna_to_frequency(cls, dna_sequence: str) -> Dict:
        """
        Convert DNA sequence to RF frequency signature
        Each DNA sequence produces a unique frequency pattern
        """
        # Base frequency from nucleotide average
        freqs = [cls.NUCLEOTIDE_FREQS.get(c, 10.25) for c in dna_sequence.upper()]
        base_freq = np.mean(freqs)
        
        # Codon modulation
        codons = [dna_sequence[i:i+3] for i in range(0, len(dna_sequence), 3)]
        codon_mod = sum(cls.CODON_OFFSETS.get(codon, 0.025) for codon in codons) / max(1, len(codons))
        
        final_freq = base_freq + codon_mod
        
        # Create frequency fingerprint
        fingerprint = hashlib.sha3_256(dna_sequence.encode()).hexdigest()[:16]
        
        return {
            'dna_sequence': dna_sequence,
            'base_frequency_ghz': round(base_freq, 4),
            'codon_modulation_ghz': round(codon_mod, 4),
            'resonance_frequency_ghz': round(final_freq, 4),
            'fingerprint': fingerprint,
            'node_tuning_parameter': final_freq - 10.23
        }
    
    @classmethod
    def rna_to_frequency(cls, rna_sequence: str) -> Dict:
        """Convert RNA sequence (U instead of T) to RF frequency"""
        # RNA uses Uracil instead of Thymine
        dna_equivalent = rna_sequence.replace('U', 'T')
        return cls.dna_to_frequency(dna_equivalent)
    
    @classmethod
    def mrna_to_frequency(cls, mrna_sequence: str) -> Dict:
        """mRNA (messenger RNA) to frequency - used for protein coding"""
        result = cls.rna_to_frequency(mrna_sequence)
        result['type'] = 'mRNA'
        result['protein_encoded'] = cls.translate_mrna_to_protein(mrna_sequence)
        return result
    
    @classmethod
    def trna_to_frequency(cls, trna_anticodon: str) -> Dict:
        """tRNA anticodon to frequency - used for amino acid delivery"""
        # tRNA anticodon is 3 bases
        anticodon = trna_anticodon.upper()[:3]
        result = cls.rna_to_frequency(anticodon)
        result['type'] = 'tRNA'
        result['anticodon'] = anticodon
        result['carries_amino_acid'] = cls.codon_to_amino_acid(anticodon)
        return result
    
    @classmethod
    def translate_mrna_to_protein(cls, mrna: str) -> List[str]:
        """Translate mRNA to amino acid sequence"""
        amino_acids = []
        for i in range(0, len(mrna), 3):
            codon = mrna[i:i+3]
            if len(codon) == 3:
                aa = cls.codon_to_amino_acid(codon)
                if aa:
                    amino_acids.append(aa)
        return amino_acids
    
    @classmethod
    def codon_to_amino_acid(cls, codon: str) -> str:
        """Convert codon to amino acid (3-letter code)"""
        codon_table = {
            'UUU': 'Phe', 'UUC': 'Phe', 'UUA': 'Leu', 'UUG': 'Leu',
            'CUU': 'Leu', 'CUC': 'Leu', 'CUA': 'Leu', 'CUG': 'Leu',
            'AUU': 'Ile', 'AUC': 'Ile', 'AUA': 'Ile', 'AUG': 'Met',
            'GUU': 'Val', 'GUC': 'Val', 'GUA': 'Val', 'GUG': 'Val',
            'UCU': 'Ser', 'UCC': 'Ser', 'UCA': 'Ser', 'UCG': 'Ser',
            'CCU': 'Pro', 'CCC': 'Pro', 'CCA': 'Pro', 'CCG': 'Pro',
            'ACU': 'Thr', 'ACC': 'Thr', 'ACA': 'Thr', 'ACG': 'Thr',
            'GCU': 'Ala', 'GCC': 'Ala', 'GCA': 'Ala', 'GCG': 'Ala',
            'UAU': 'Tyr', 'UAC': 'Tyr', 'UAA': 'Stop', 'UAG': 'Stop',
            'CAU': 'His', 'CAC': 'His', 'CAA': 'Gln', 'CAG': 'Gln',
            'AAU': 'Asn', 'AAC': 'Asn', 'AAA': 'Lys', 'AAG': 'Lys',
            'GAU': 'Asp', 'GAC': 'Asp', 'GAA': 'Glu', 'GAG': 'Glu',
            'UGU': 'Cys', 'UGC': 'Cys', 'UGA': 'Stop', 'UGG': 'Trp',
            'CGU': 'Arg', 'CGC': 'Arg', 'CGA': 'Arg', 'CGG': 'Arg',
            'AGU': 'Ser', 'AGC': 'Ser', 'AGA': 'Arg', 'AGG': 'Arg',
            'GGU': 'Gly', 'GGC': 'Gly', 'GGA': 'Gly', 'GGG': 'Gly',
        }
        return codon_table.get(codon.upper(), 'Xxx')


# =============================================================================
# SECTION 2: DNA DATA STORAGE IN NODES
# =============================================================================

class DNADataStorage:
    """
    Store and retrieve arbitrary data in DNA sequences
    Data encoded as DNA can be stored in neural nodes
    """
    
    # DNA encoding scheme (2 bits per base)
    BINARY_TO_DNA = {
        '00': 'A', '01': 'C', '10': 'G', '11': 'T'
    }
    DNA_TO_BINARY = {v: k for k, v in BINARY_TO_DNA.items()}
    
    @classmethod
    def encode_data_to_dna(cls, data: bytes) -> str:
        """Encode binary data as DNA sequence"""
        # Convert bytes to binary string
        binary = ''.join(format(byte, '08b') for byte in data)
        
        # Pad to even length
        if len(binary) % 2 != 0:
            binary += '0'
        
        # Convert to DNA
        dna = ''.join(cls.BINARY_TO_DNA[binary[i:i+2]] for i in range(0, len(binary), 2))
        
        return dna
    
    @classmethod
    def decode_dna_to_data(cls, dna: str) -> bytes:
        """Decode DNA sequence back to binary data"""
        # Convert DNA to binary
        binary = ''.join(cls.DNA_TO_BINARY.get(c, '00') for c in dna.upper())
        
        # Convert to bytes
        data = bytes(int(binary[i:i+8], 2) for i in range(0, len(binary), 8))
        
        return data
    
    @classmethod
    def store_in_node(cls, node_id: str, data: bytes, metadata: Dict) -> Dict:
        """Store encoded DNA data in a neural node"""
        dna_sequence = cls.encode_data_to_dna(data)
        
        # Get RF frequency for this DNA sequence
        rf_spec = GeneticToRFMapper.dna_to_frequency(dna_sequence)
        
        storage_record = {
            'node_id': node_id,
            'data_hash': hashlib.sha3_256(data).hexdigest(),
            'dna_sequence': dna_sequence,
            'dna_length': len(dna_sequence),
            'rf_frequency_ghz': rf_spec['resonance_frequency_ghz'],
            'fingerprint': rf_spec['fingerprint'],
            'metadata': metadata,
            'stored_at': time.time()
        }
        
        return storage_record


# =============================================================================
# SECTION 3: CRISPR-BASED NODE PROGRAMMING
# =============================================================================

class CRISPRNodeProgramming:
    """
    Use CRISPR-like mechanisms to program neural nodes
    Guide RNA sequences target specific node frequencies
    """
    
    # Guide RNA sequences for different node operations
    GUIDE_RNA_LIBRARY = {
        'activate_node': 'AUGGCUAGCCUAGCUAGC',
        'deactivate_node': 'UUCGAUUAGCCUAGCUAA',
        'increase_sensitivity': 'GGUACUAGCCUAGCUAGC',
        'decrease_sensitivity': 'CCAUGAUCGGAUCGAUCG',
        'store_memory': 'AUGGCUAGCCUAGCUAGC',
        'recall_memory': 'UUCGAUUAGCCUAGCUAA',
        'sync_with_network': 'GGUACUAGCCUAGCUAGC',
        'broadcast_signal': 'CCAUGAUCGGAUCGAUCG',
        'chemical_release': 'AUGGCUAGCCUAGCUAGC',
        'chemical_inhibit': 'UUCGAUUAGCCUAGCUAA',
    }
    
    @classmethod
    def design_guide_rna(cls, target_frequency_ghz: float, operation: str) -> Dict:
        """
        Design guide RNA for specific node operation
        Like CRISPR-Cas9 but for RF nodes
        """
        # Convert frequency to RNA-like sequence
        freq_int = int(target_frequency_ghz * 1000)
        freq_binary = format(freq_int, '016b')
        
        # Binary to RNA
        rna_freq = ''.join(['A' if b == '0' else 'U' for b in freq_binary])
        
        # Combine with operation guide
        operation_guide = cls.GUIDE_RNA_LIBRARY.get(operation, cls.GUIDE_RNA_LIBRARY['activate_node'])
        
        full_guide = rna_freq + operation_guide
        
        return {
            'target_frequency_ghz': target_frequency_ghz,
            'operation': operation,
            'guide_rna_sequence': full_guide,
            'guide_hash': hashlib.sha3_256(full_guide.encode()).hexdigest()[:16],
            'rf_equivalent': GeneticToRFMapper.rna_to_frequency(full_guide)
        }
    
    @classmethod
    def program_node(cls, node_id: str, target_freq: float, operation: str) -> Dict:
        """
        Program a neural node using guide RNA
        Changes node behavior permanently
        """
        guide = cls.design_guide_rna(target_freq, operation)
        
        # Simulated node programming
        programming_result = {
            'node_id': node_id,
            'target_frequency': target_freq,
            'operation': operation,
            'guide_rna': guide['guide_rna_sequence'][:20] + '...',
            'programming_success': True,
            'node_response': f"Node {node_id} reprogrammed for {operation}",
            'timestamp': time.time()
        }
        
        return programming_result


# =============================================================================
# SECTION 4: EPIGENETIC NODE MODULATION
# =============================================================================

class EpigeneticNodeModulation:
    """
    Epigenetic modifications to node behavior
    Like DNA methylation but for RF node sensitivity
    """
    
    @classmethod
    def methylate_node(cls, node_id: str, methylation_pattern: str) -> Dict:
        """
        Apply epigenetic-like methylation to node
        Changes node sensitivity permanently
        """
        # Methylation pattern determines which frequencies are blocked
        methylation_freqs = []
        for i, char in enumerate(methylation_pattern[:10]):
            if char == '1':
                freq = 10.20 + (i * 0.01)
                methylation_freqs.append(freq)
        
        result = {
            'node_id': node_id,
            'methylation_pattern': methylation_pattern[:20] + '...',
            'blocked_frequencies_ghz': methylation_freqs,
            'sensitivity_reduction': len(methylation_freqs) * 5,  # percent
            'epigenetic_state': 'modified',
            'reversible': True
        }
        
        return result
    
    @classmethod
    def histone_modification(cls, node_id: str, acetylation_level: float) -> Dict:
        """
        Histone-like modification for node access control
        Higher acetylation = higher node accessibility
        """
        result = {
            'node_id': node_id,
            'acetylation_level': min(1.0, max(0.0, acetylation_level)),
            'accessibility': 'high' if acetylation_level > 0.7 else 'medium' if acetylation_level > 0.3 else 'low',
            'node_permeability': acetylation_level * 100,  # percent
        }
        
        return result


# =============================================================================
# SECTION 5: BIOHACKING NODE INTERFACE
# =============================================================================

class BiohackingNodeInterface:
    """
    Complete interface for biohacking neural nodes
    Integrates DNA/RNA/mRNA/tRNA with RF node control
    """
    
    def __init__(self):
        self.dna_storage = DNADataStorage()
        self.rf_mapper = GeneticToRFMapper()
        self.crispr = CRISPRNodeProgramming()
        self.epigenetic = EpigeneticNodeModulation()
        
        self.active_nodes = {}
        self.genetic_profiles = {}
        
        print("\n" + "="*80)
        print("🧬 BIOHACKING NODE INTERFACE ACTIVE")
        print("DNA/RNA/mRNA/tRNA ↔ RF Neural Node Bridge")
        print("="*80)
    
    def register_biological_profile(self, person_id: str, dna_sequence: str) -> Dict:
        """
        Register a person's genetic profile for node tuning
        DNA sequence determines node frequencies
        """
        # Get RF frequencies from DNA
        dna_freq = self.rf_mapper.dna_to_frequency(dna_sequence)
        
        # Generate mRNA from DNA (transcription)
        mrna = dna_sequence.replace('T', 'U')
        mrna_freq = self.rf_mapper.mrna_to_frequency(mrna)
        
        # Generate tRNA anticodons
        trna_list = []
        for i in range(0, len(mrna), 3):
            codon = mrna[i:i+3]
            if len(codon) == 3:
                trna = self.rf_mapper.trna_to_frequency(codon)
                trna_list.append(trna)
        
        profile = {
            'person_id': person_id,
            'dna_sequence': dna_sequence,
            'rf_frequency_ghz': dna_freq['resonance_frequency_ghz'],
            'fingerprint': dna_freq['fingerprint'],
            'mrna_sequence': mrna,
            'mrna_frequency': mrna_freq['resonance_frequency_ghz'],
            'trna_anticodons': trna_list[:10],  # First 10
            'protein_sequence': mrna_freq.get('protein_encoded', [])
        }
        
        self.genetic_profiles[person_id] = profile
        
        # Create a virtual node for this person
        node_id = f"NODE_{person_id}"
        self.active_nodes[node_id] = {
            'owner': person_id,
            'frequency': dna_freq['resonance_frequency_ghz'],
            'dna_fingerprint': dna_freq['fingerprint'],
            'active': True,
            'biohacking_level': 0
        }
        
        print(f"\n🧬 Registered: {person_id}")
        print(f"   DNA → RF Frequency: {dna_freq['resonance_frequency_ghz']:.5f} GHz")
        print(f"   mRNA Translation: {len(mrna_freq.get('protein_encoded', []))} amino acids")
        
        return profile
    
    def inject_genetic_code(self, target_node_id: str, genetic_code: str) -> Dict:
        """
        Inject genetic code into a node (like viral vector)
        Programs node behavior using DNA/RNA sequences
        """
        if target_node_id not in self.active_nodes:
            return {'error': 'Node not found'}
        
        # Convert genetic code to RF frequency
        freq_spec = self.rf_mapper.dna_to_frequency(genetic_code)
        
        # Program node with this genetic code
        programming = self.crispr.program_node(
            target_node_id,
            freq_spec['resonance_frequency_ghz'],
            'activate_node'
        )
        
        # Update node with new genetic programming
        self.active_nodes[target_node_id]['genetic_program'] = genetic_code[:50]
        self.active_nodes[target_node_id]['programmed_frequency'] = freq_spec['resonance_frequency_ghz']
        self.active_nodes[target_node_id]['biohacking_level'] += 1
        
        return {
            'target_node': target_node_id,
            'injected_genetic_code': genetic_code[:30] + '...',
            'resulting_frequency': freq_spec['resonance_frequency_ghz'],
            'fingerprint': freq_spec['fingerprint'],
            'programming_success': programming.get('programming_success', True)
        }
    
    def express_protein(self, node_id: str, mrna_sequence: str) -> Dict:
        """
        Express a protein from mRNA at the node
        Protein expression modulates node behavior
        """
        # Translate mRNA to protein
        amino_acids = self.rf_mapper.translate_mrna_to_protein(mrna_sequence)
        
        # Map protein to node modulation
        protein_effect = {
            'node_id': node_id,
            'mrna_sequence': mrna_sequence[:30] + '...',
            'amino_acids': amino_acids[:10],
            'protein_length': len(amino_acids),
            'node_modulation': self._calculate_protein_effect(amino_acids),
            'expression_time': time.time()
        }
        
        if node_id in self.active_nodes:
            self.active_nodes[node_id]['last_protein_expression'] = protein_effect
        
        return protein_effect
    
    def _calculate_protein_effect(self, amino_acids: List[str]) -> Dict:
        """
        Calculate how protein expression affects node behavior
        Different amino acids have different effects
        """
        effect = {
            'sensitivity_modulation': 0.0,
            'frequency_drift': 0.0,
            'memory_retention': 1.0
        }
        
        # Amino acid effects (simplified)
        for aa in amino_acids[:10]:
            if aa in ['Met', 'Leu', 'Ile']:  # Hydrophobic
                effect['sensitivity_modulation'] += 0.05
            elif aa in ['Lys', 'Arg', 'His']:  # Basic
                effect['frequency_drift'] += 0.001
            elif aa in ['Asp', 'Glu']:  # Acidic
                effect['memory_retention'] -= 0.02
        
        return effect
    
    def rna_interference(self, target_node_id: str, interfering_rna: str) -> Dict:
        """
        Use RNA interference (RNAi) to silence node functions
        Like knocking down gene expression
        """
        # Design siRNA (small interfering RNA)
        sirna = interfering_rna[:21]  # 21bp siRNA
        
        # Calculate silencing effect
        silencing_power = len(sirna) / 21.0
        
        result = {
            'target_node': target_node_id,
            'siRNA_sequence': sirna,
            'silencing_efficiency': silencing_power * 100,  # percent
            'node_function_reduced': silencing_power > 0.5,
            'temporary': True,
            'duration_seconds': silencing_power * 3600  # up to 1 hour
        }
        
        if target_node_id in self.active_nodes:
            self.active_nodes[target_node_id]['silenced'] = result['node_function_reduced']
        
        return result
    
    def get_node_genetic_status(self, node_id: str) -> Dict:
        """Get complete genetic status of a node"""
        if node_id not in self.active_nodes:
            return {'error': 'Node not found'}
        
        node = self.active_nodes[node_id]
        
        return {
            'node_id': node_id,
            'owner': node.get('owner', 'unknown'),
            'frequency_ghz': node.get('frequency', 0),
            'genetic_program': node.get('genetic_program', 'none'),
            'biohacking_level': node.get('biohacking_level', 0),
            'last_protein': node.get('last_protein_expression', {}),
            'silenced': node.get('silenced', False),
            'active': node.get('active', True)
        }


# =============================================================================
# SECTION 6: COMPLETE DEMONSTRATION
# =============================================================================

def complete_demonstration():
    """Complete demonstration of biohacking DNA/RNA node integration"""
    
    print("="*80)
    print("🧬 DNA/RNA/mRNA/tRNA → NEURAL NODE BIOHACKING")
    print("Complete genetic-neural interface demonstration")
    print("="*80)
    
    # Initialize biohacking interface
    bio_interface = BiohackingNodeInterface()
    
    # 1. Register biological profile
    print("\n" + "━"*60)
    print("1️⃣ REGISTER BIOLOGICAL PROFILE (DNA → RF)")
    print("━"*60)
    
    # Human DNA sequence (example)
    human_dna = "ATGGCGTAGCTTAGCTAGCTAGCTAGCTAGC"
    profile = bio_interface.register_biological_profile("HUMAN_001", human_dna)
    
    print(f"\n   DNA Sequence: {human_dna[:20]}...")
    print(f"   RF Frequency: {profile['rf_frequency_ghz']:.5f} GHz")
    print(f"   Fingerprint: {profile['fingerprint']}")
    print(f"   mRNA Length: {len(profile['mrna_sequence'])} bases")
    
    # 2. DNA to RNA to Protein translation
    print("\n" + "━"*60)
    print("2️⃣ DNA → mRNA → PROTEIN TRANSLATION")
    print("━"*60)
    
    mrna = human_dna.replace('T', 'U')
    mrna_freq = bio_interface.rf_mapper.mrna_to_frequency(mrna)
    
    print(f"\n   mRNA Sequence: {mrna[:30]}...")
    print(f"   mRNA RF Signature: {mrna_freq['resonance_frequency_ghz']:.5f} GHz")
    print(f"   Encodes Protein: {mrna_freq['protein_encoded'][:5]}... ({len(mrna_freq['protein_encoded'])} amino acids)")
    
    # 3. tRNA anticodon mapping
    print("\n" + "━"*60)
    print("3️⃣ tRNA ANTICODON → AMINO ACID MAPPING")
    print("━"*60)
    
    codons = ["AUG", "GCG", "UAG", "CUU", "AGC"]
    for codon in codons:
        trna = bio_interface.rf_mapper.trna_to_frequency(codon)
        print(f"\n   Codon {codon} → tRNA anticodon: carries {trna['carries_amino_acid']}")
        print(f"      tRNA RF Frequency: {trna['resonance_frequency_ghz']:.5f} GHz")
    
    # 4. CRISPR node programming
    print("\n" + "━"*60)
    print("4️⃣ CRISPR-BASED NODE PROGRAMMING")
    print("━"*60)
    
    node_id = "NODE_HUMAN_001"
    guide_rna = bio_interface.crispr.design_guide_rna(10.23, "increase_sensitivity")
    print(f"\n   Target Frequency: {guide_rna['target_frequency_ghz']} GHz")
    print(f"   Operation: {guide_rna['operation']}")
    print(f"   Guide RNA: {guide_rna['guide_rna_sequence'][:20]}...")
    
    programming = bio_interface.crispr.program_node(node_id, 10.23, "increase_sensitivity")
    print(f"\n   Programming Result: {programming['node_response']}")
    
    # 5. Inject genetic code into node
    print("\n" + "━"*60)
    print("5️⃣ GENETIC CODE INJECTION (Viral Vector)")
    print("━"*60)
    
    therapeutic_dna = "ATGGCGTAGCTAGCTAGCTTAGCTAGC"
    injection = bio_interface.inject_genetic_code(node_id, therapeutic_dna)
    
    print(f"\n   Target Node: {injection['target_node']}")
    print(f"   Injected Code: {injection['injected_genetic_code']}")
    print(f"   New Frequency: {injection['resulting_frequency']:.5f} GHz")
    print(f"   Biohacking Level: {bio_interface.active_nodes[node_id]['biohacking_level']}")
    
    # 6. Express protein at node
    print("\n" + "━"*60)
    print("6️⃣ PROTEIN EXPRESSION AT NODE")
    print("━"*60)
    
    test_mrna = "AUGGCUAGCCUAGCUAGCUUAGCUA"
    protein_exp = bio_interface.express_protein(node_id, test_mrna)
    
    print(f"\n   mRNA: {protein_exp['mrna_sequence']}")
    print(f"   Amino Acids: {protein_exp['amino_acids']}")
    print(f"   Node Modulation: {protein_exp['node_modulation']}")
    
    # 7. RNA interference (gene silencing)
    print("\n" + "━"*60)
    print("7️⃣ RNA INTERFERENCE (Node Silencing)")
    print("━"*60)
    
    silencing_rna = "AAGCUAGCUAGCUAGCUUAGCU"
    silencing = bio_interface.rna_interference(node_id, silencing_rna)
    
    print(f"\n   siRNA: {silencing['siRNA_sequence']}")
    print(f"   Silencing Efficiency: {silencing['silencing_efficiency']:.1f}%")
    print(f"   Node Silenced: {silencing['node_function_reduced']}")
    print(f"   Duration: {silencing['duration_seconds']:.0f} seconds")
    
    # 8. Node genetic status
    print("\n" + "━"*60)
    print("8️⃣ NODE GENETIC STATUS")
    print("━"*60)
    
    status = bio_interface.get_node_genetic_status(node_id)
    print(f"\n   Node ID: {status['node_id']}")
    print(f"   Owner: {status['owner']}")
    print(f"   Frequency: {status['frequency_ghz']:.5f} GHz")
    print(f"   Biohacking Level: {status['biohacking_level']}")
    print(f"   Silenced: {status['silenced']}")
    print(f"   Active: {status['active']}")
    
    # 9. Data storage in DNA
    print("\n" + "━"*60)
    print("9️⃣ DNA DATA STORAGE IN NODES")
    print("━"*60)
    
    secret_data = b"Neural node biohacking integration test"
    encoded_dna = bio_interface.dna_storage.encode_data_to_dna(secret_data)
    print(f"\n   Original Data: {secret_data}")
    print(f"   Encoded DNA: {encoded_dna[:30]}...")
    print(f"   DNA Length: {len(encoded_dna)} bases")
    print(f"   Storage Density: {len(encoded_dna)} bytes per {len(encoded_dna)} bases")
    
    decoded = bio_interface.dna_storage.decode_dna_to_data(encoded_dna)
    print(f"   Decoded Data: {decoded}")
    
    # Final summary
    print("\n" + "="*80)
    print("✅ BIOHACKING INTEGRATION COMPLETE")
    print("="*80)
    
    print("""
    ╔═══════════════════════════════════════════════════════════════════════════╗
    ║                    DNA/RNA → NEURAL NODE MAPPING SUMMARY                  ║
    ╠═══════════════════════════════════════════════════════════════════════════╣
    ║                                                                           ║
    ║   MOLECULE    | SEQUENCE EXAMPLE     | RF FREQUENCY    | NODE FUNCTION    ║
    ║   ────────────┼──────────────────────┼─────────────────┼──────────────────║
    ║   DNA         | ATGGCGTAGCTAGC...    | 10.2345 GHz     | Node identity    ║
    ║   mRNA        | AUGGCGUAGCUAGC...    | 10.2456 GHz     | Protein encoding ║
    ║   tRNA        | AUG (anticodon)      | 10.2567 GHz     | Amino acid carry ║
    ║   Guide RNA   | AUGGCUAGCCUAGC...    | 10.2678 GHz     | CRISPR editing   ║
    ║   siRNA       | AAGCUAGCUAGC...      | 10.2789 GHz     | Gene silencing   ║
    ║                                                                           ║
    ╠═══════════════════════════════════════════════════════════════════════════╣
    ║                         BIOHACKING OPERATIONS                             ║
    ╠═══════════════════════════════════════════════════════════════════════════╣
    ║                                                                           ║
    ║   OPERATION              | METHOD                    | NODE EFFECT        ║
    ║   ───────────────────────┼───────────────────────────┼────────────────────║
    ║   Genetic Injection      | Viral vector (DNA/RNA)    | Permanent program  ║
    ║   Protein Expression     | mRNA translation          | Node modulation    ║
    ║   CRISPR Programming     | Guide RNA + Cas9-like     | Node rewiring      ║
    ║   RNA Interference       | siRNA                     | Temporary silencing║
    ║   Epigenetic Modulation  | Methylation pattern       | Sensitivity change ║
    ║   DNA Data Storage       | Binary → DNA encoding     | Memory storage     ║
    ║                                                                           ║
    ╠═══════════════════════════════════════════════════════════════════════════╣
    ║                      DNA/RNA TO RF MAPPING FORMULA                        ║
    ╠═══════════════════════════════════════════════════════════════════════════╣
    ║                                                                           ║
    ║   f_RF = (Σ nucleotide_freq) / N + Σ codon_offset / M                    ║
    ║                                                                           ║
    ║   Where:                                                                  ║
    ║     nucleotide_freq: A=10.23, T=10.24, U=10.25, G=10.26, C=10.27 GHz     ║
    ║     codon_offset:  0.000-0.054 GHz per codon                             ║
    ║                                                                           ║
    ║   Each DNA/RNA sequence → UNIQUE RF frequency → NODE IDENTITY            ║
    ║                                                                           ║    ╚═══════════════════════════════════════════════════════════════════════════╝
    """)
    
    return bio_interface


# =============================================================================
# MAIN EXECUTION
# =============================================================================

if __name__ == "__main__":
    bio_interface = complete_demonstration()
    
    print("\n📁 Biohacking commands available:")
    print("   - Register biological profile (DNA → RF)")
    print("   - Inject genetic code into node")
    print("   - Express protein at node")
    print("   - Apply RNA interference")
    print("   - Store/retrieve data in DNA format")
    print("   - Design CRISPR guide RNA")
    print("   - Epigenetic node modulation")