from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm, mm
from reportlab.platypus import (
    SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle,
    HRFlowable, KeepTogether
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_RIGHT
from reportlab.platypus import PageBreak

OUTPUT = "/home/daytona/workspace/iat-cheatsheet/IAT_2026_Biology_CheatSheet.pdf"

# ── Colors ──────────────────────────────────────────────────────────────────
C_DARK   = colors.HexColor("#0D1B2A")   # deep navy
C_ACCENT = colors.HexColor("#E63946")   # red accent
C_GREEN  = colors.HexColor("#2DC653")   # correct/formula green
C_BLUE   = colors.HexColor("#1D7FD8")   # section header blue
C_YELLOW = colors.HexColor("#FFD166")   # highlight yellow
C_LIGHT  = colors.HexColor("#F1FAEE")   # light background
C_GRAY   = colors.HexColor("#8D99AE")   # muted text
C_WHITE  = colors.white

# ── Styles ───────────────────────────────────────────────────────────────────
styles = getSampleStyleSheet()

def S(name, **kw):
    return ParagraphStyle(name, **kw)

TITLE = S("Title2", fontName="Helvetica-Bold", fontSize=22,
          textColor=C_WHITE, alignment=TA_CENTER, spaceAfter=4)
SUBTITLE = S("Sub", fontName="Helvetica", fontSize=11,
             textColor=C_YELLOW, alignment=TA_CENTER, spaceAfter=2)
WARN = S("Warn", fontName="Helvetica-Bold", fontSize=9,
         textColor=C_ACCENT, alignment=TA_CENTER, spaceAfter=8)

SEC = S("Sec", fontName="Helvetica-Bold", fontSize=12,
        textColor=C_WHITE, alignment=TA_LEFT, spaceAfter=2)
SUBSEC = S("SubSec", fontName="Helvetica-Bold", fontSize=10,
           textColor=C_YELLOW, alignment=TA_LEFT, spaceAfter=2)
BODY = S("Body2", fontName="Helvetica", fontSize=8.5,
         textColor=C_DARK, leading=13, spaceAfter=2)
BOLD = S("Bold2", fontName="Helvetica-Bold", fontSize=8.5,
         textColor=C_DARK, leading=13, spaceAfter=2)
ANS = S("Ans", fontName="Helvetica-Bold", fontSize=8.5,
        textColor=C_GREEN, leading=13, spaceAfter=1)
FORMULA = S("Formula", fontName="Helvetica-Bold", fontSize=9,
            textColor=C_ACCENT, leading=14, spaceAfter=2)
SMALL = S("Small", fontName="Helvetica", fontSize=7.5,
          textColor=C_GRAY, leading=11, spaceAfter=1)

PAGE_W, PAGE_H = A4
MARGIN = 1.5 * cm

# ── Helpers ──────────────────────────────────────────────────────────────────
def sec_header(text, color=C_BLUE):
    data = [[Paragraph(f"<b>{text}</b>", SEC)]]
    t = Table(data, colWidths=[PAGE_W - 2*MARGIN])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), color),
        ("ROUNDEDCORNERS", [4,4,4,4]),
        ("TOPPADDING",    (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("LEFTPADDING",   (0,0), (-1,-1), 8),
    ]))
    return t

def two_col_table(rows, col_ratio=(0.38, 0.62), hdr_color=C_BLUE):
    w = PAGE_W - 2*MARGIN
    cw = [w * col_ratio[0], w * col_ratio[1]]
    style = TableStyle([
        ("BACKGROUND",    (0,0), (-1,0),  hdr_color),
        ("TEXTCOLOR",     (0,0), (-1,0),  C_WHITE),
        ("FONTNAME",      (0,0), (-1,0),  "Helvetica-Bold"),
        ("FONTSIZE",      (0,0), (-1,-1), 8),
        ("BACKGROUND",    (0,1), (-1,-1), C_LIGHT),
        ("ROWBACKGROUNDS",(0,1), (-1,-1), [C_WHITE, C_LIGHT]),
        ("GRID",          (0,0), (-1,-1), 0.3, C_GRAY),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 6),
        ("VALIGN",        (0,0), (-1,-1), "TOP"),
    ])
    tbl_rows = []
    for i, row in enumerate(rows):
        r = [Paragraph(str(c), BOLD if i==0 else BODY) for c in row]
        tbl_rows.append(r)
    t = Table(tbl_rows, colWidths=cw)
    t.setStyle(style)
    return t

def three_col_table(rows, col_ratio=(0.25, 0.35, 0.40), hdr_color=C_BLUE):
    w = PAGE_W - 2*MARGIN
    cw = [w * r for r in col_ratio]
    style = TableStyle([
        ("BACKGROUND",    (0,0), (-1,0),  hdr_color),
        ("TEXTCOLOR",     (0,0), (-1,0),  C_WHITE),
        ("FONTNAME",      (0,0), (-1,0),  "Helvetica-Bold"),
        ("FONTSIZE",      (0,0), (-1,-1), 8),
        ("BACKGROUND",    (0,1), (-1,-1), C_LIGHT),
        ("ROWBACKGROUNDS",(0,1), (-1,-1), [C_WHITE, C_LIGHT]),
        ("GRID",          (0,0), (-1,-1), 0.3, C_GRAY),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 6),
        ("VALIGN",        (0,0), (-1,-1), "TOP"),
    ])
    tbl_rows = []
    for i, row in enumerate(rows):
        r = [Paragraph(str(c), BOLD if i==0 else BODY) for c in row]
        tbl_rows.append(r)
    t = Table(tbl_rows, colWidths=cw)
    t.setStyle(style)
    return t

def highlight_box(text, bg=C_YELLOW, fg=C_DARK):
    sty = S("hbox", fontName="Helvetica-Bold", fontSize=8.5,
            textColor=fg, leading=13)
    data = [[Paragraph(text, sty)]]
    t = Table(data, colWidths=[PAGE_W - 2*MARGIN])
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), bg),
        ("TOPPADDING",    (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("LEFTPADDING",   (0,0), (-1,-1), 10),
        ("ROUNDEDCORNERS", [4,4,4,4]),
    ]))
    return t

def qa_box(q, a, tip=""):
    """Question / Answer / Tip box"""
    q_sty = S("Q", fontName="Helvetica-Bold", fontSize=8.5, textColor=C_DARK, leading=13)
    a_sty = S("A", fontName="Helvetica-Bold", fontSize=8.5, textColor=C_GREEN, leading=13)
    t_sty = S("T", fontName="Helvetica-Oblique", fontSize=7.5, textColor=C_GRAY, leading=11)
    content = [Paragraph(f"Q: {q}", q_sty), Paragraph(f"Ans: {a}", a_sty)]
    if tip:
        content.append(Paragraph(f"Trick: {tip}", t_sty))
    data = [[c] for c in content]
    inner = Table([[item] for item in content], colWidths=[PAGE_W - 2*MARGIN - 24])
    inner.setStyle(TableStyle([
        ("TOPPADDING",    (0,0), (-1,-1), 1),
        ("BOTTOMPADDING", (0,0), (-1,-1), 1),
        ("LEFTPADDING",   (0,0), (-1,-1), 0),
    ]))
    outer = Table([[inner]], colWidths=[PAGE_W - 2*MARGIN])
    outer.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), colors.HexColor("#EDF6FF")),
        ("BOX",           (0,0), (-1,-1), 0.5, C_BLUE),
        ("LEFTLINE",      (0,0), (0,-1),  3,   C_BLUE),
        ("TOPPADDING",    (0,0), (-1,-1), 6),
        ("BOTTOMPADDING", (0,0), (-1,-1), 6),
        ("LEFTPADDING",   (0,0), (-1,-1), 10),
    ]))
    return outer

def sp(h=4):
    return Spacer(1, h)

def hr():
    return HRFlowable(width="100%", thickness=0.5, color=C_GRAY, spaceAfter=4, spaceBefore=4)

# ══════════════════════════════════════════════════════════════════════════════
# CONTENT
# ══════════════════════════════════════════════════════════════════════════════
story = []

# ── COVER BANNER ─────────────────────────────────────────────────────────────
cover_data = [[
    Paragraph("IAT 2026 Biology", TITLE),
    Paragraph("REVISION CHEAT SHEET", SUBTITLE),
    Paragraph("EXAM: 7 JUNE 2026  |  15 MCQs  |  +4 / -1  |  Target: 12-13/15", WARN),
]]
cover = Table([[Paragraph("IAT 2026 Biology — REVISION CHEAT SHEET", TITLE)],
               [Paragraph("All Formulas, Concepts & Expected PYQs  |  Exam: 7 June 2026", SUBTITLE)],
               [Paragraph("15 MCQs  •  +4 correct  •  -1 wrong  •  Biology is EASIEST section — target 12-13/15", WARN)]],
              colWidths=[PAGE_W - 2*MARGIN])
cover.setStyle(TableStyle([
    ("BACKGROUND",    (0,0), (-1,-1), C_DARK),
    ("TOPPADDING",    (0,0), (-1,-1), 10),
    ("BOTTOMPADDING", (0,0), (-1,-1), 6),
    ("LEFTPADDING",   (0,0), (-1,-1), 12),
]))
story.append(cover)
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# 1. HUMAN PHYSIOLOGY  (3-4 Qs)
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    sec_header("1. HUMAN PHYSIOLOGY  [3-4 Questions — HIGHEST PRIORITY]"),
    sp(4),
]))

# 1a O2-Hb curve
story.append(Paragraph("<b>A. Oxygen-Haemoglobin Dissociation Curve (Bohr Effect)</b>", SUBSEC))
story.append(two_col_table([
    ["Condition", "Effect on Curve → Impact"],
    ["HIGH CO₂ / HIGH H⁺ / HIGH Temp / HIGH 2,3-BPG", "RIGHT SHIFT → Hb releases O₂ (tissues, exercise)"],
    ["LOW CO₂ / LOW H⁺ / LOW Temp / LOW 2,3-BPG",     "LEFT SHIFT → Hb holds O₂ (lungs, O₂ loading)"],
    ["Foetal Hb (HbF)",  "LEFT SHIFT of adult — higher O₂ affinity (pulls O₂ from mother)"],
    ["CO poisoning",     "Left shift + Hb permanently blocked → hypoxia"],
]))
story.append(highlight_box("KEY FORMULA: Bohr Effect — CO₂ ↑ → H⁺ ↑ → pH ↓ → RIGHT shift → O₂ released to active tissues"))
story.append(sp(6))

# 1b Nephron
story.append(Paragraph("<b>B. Nephron — What Happens Where</b>", SUBSEC))
story.append(two_col_table([
    ["Segment", "What is reabsorbed / secreted"],
    ["Glomerulus (Bowman's capsule)", "Ultrafiltration — all small molecules pass (glucose, urea, ions, water)"],
    ["PCT (Proximal Convoluted Tubule)", "~70% Na⁺, K⁺, water, ALL glucose, ALL amino acids, HCO₃⁻"],
    ["Loop of Henle (Descending)", "Water exits (permeable to water, not solutes) → filtrate concentrated"],
    ["Loop of Henle (Ascending)", "Na⁺, Cl⁻, K⁺ exit (impermeable to water) → filtrate diluted"],
    ["DCT (Distal Convoluted Tubule)", "Selective Na⁺/K⁺, HCO₃⁻, H⁺ secretion; aldosterone acts here"],
    ["Collecting Duct", "Water reabsorption by ADH (vasopressin); final urine concentration"],
]))
story.append(highlight_box("TRICK: 'PCT = glucose hotel — ALL glucose absorbed here'. Diabetes → glucose in urine = PCT overloaded"))
story.append(sp(6))

# 1c Hormones
story.append(Paragraph("<b>C. Key Hormones — Quick Reference</b>", SUBSEC))
story.append(three_col_table([
    ["Hormone", "Gland", "Function"],
    ["Insulin",          "Beta cells, Pancreas",     "Lowers blood glucose (glycogenesis, uptake)"],
    ["Glucagon",         "Alpha cells, Pancreas",    "Raises blood glucose (glycogenolysis)"],
    ["ADH (Vasopressin)","Posterior Pituitary",      "Water retention by collecting duct"],
    ["Oxytocin",         "Posterior Pituitary",      "Uterine contractions, milk ejection"],
    ["TSH",              "Anterior Pituitary",       "Stimulates thyroid to secrete T3/T4"],
    ["T3 / T4",          "Thyroid",                  "BMR regulation, growth, brain development"],
    ["PTH",              "Parathyroid",              "Raises blood Ca²⁺ (bone resorption)"],
    ["Calcitonin",       "Thyroid (C-cells)",        "Lowers blood Ca²⁺ (bone deposition)"],
    ["Aldosterone",      "Adrenal Cortex",           "Na⁺ retention → BP increase"],
    ["Adrenaline",       "Adrenal Medulla",          "Fight-or-flight: HR up, glucose up"],
    ["LH",               "Anterior Pituitary",       "Ovulation trigger; testosterone in males"],
    ["FSH",              "Anterior Pituitary",       "Follicle dev (F) / Spermatogenesis (M)"],
    ["Progesterone",     "Corpus Luteum / Placenta", "Maintains uterine lining (luteal phase)"],
    ["Estrogen",         "Ovary / Placenta",         "Secondary sexual characters, follicular phase"],
]))
story.append(sp(6))

# 1d Action Potential
story.append(Paragraph("<b>D. Action Potential — Ion Changes</b>", SUBSEC))
story.append(two_col_table([
    ["Phase", "Ions & Voltage"],
    ["Resting Membrane Potential (RMP)", "-70 mV. K⁺ high INSIDE, Na⁺ high OUTSIDE. K⁺ channels slightly open."],
    ["Depolarization", "Stimulus → Na⁺ channels OPEN → Na⁺ rushes IN → voltage rises to +30 mV"],
    ["Repolarization", "Na⁺ channels close, K⁺ channels OPEN → K⁺ rushes OUT → voltage falls"],
    ["Hyperpolarization (after-potential)", "Voltage overshoots below -70 mV briefly before Na⁺/K⁺ pump restores"],
    ["Refractory Period", "Absolute: no new AP possible. Relative: strong stimulus can trigger AP"],
    ["Na⁺/K⁺ ATPase pump", "Pumps 3 Na⁺ OUT, 2 K⁺ IN per cycle (ATP required) — restores RMP"],
]))
story.append(highlight_box("ALL-OR-NONE LAW: AP either happens fully or not at all. Weak stimulus → no AP. Above threshold → full AP always same amplitude."))
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# 2. GENETICS & MOLECULAR BIOLOGY  (2-3 Qs)
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    sec_header("2. GENETICS & MOLECULAR BIOLOGY  [2-3 Questions]", C_DARK),
    sp(4),
]))

story.append(Paragraph("<b>A. Mendelian Ratios — Must Know</b>", SUBSEC))
story.append(two_col_table([
    ["Cross Type", "Ratio / Result"],
    ["Monohybrid (Aa × Aa)", "3:1 (dominant:recessive) phenotype | 1:2:1 genotype"],
    ["Dihybrid (AaBb × AaBb)", "9:3:3:1 (all combos)"],
    ["Test cross (Aa × aa)", "1:1 (dominant:recessive)"],
    ["Incomplete dominance (Rr × Rr)", "1:2:1 (Red:Pink:White) — NO dominant 3:1"],
    ["Co-dominance (IAIB)", "Both expressed equally — e.g., AB blood group"],
    ["Epistasis (12:3:1 etc.)", "One gene masks another — ratio modified from 9:3:3:1"],
    ["Lethal allele (AA lethal)", "2:1 ratio instead of 3:1 in progeny"],
]))
story.append(highlight_box("PROBABILITY FORMULA: P(AABBcc) from AaBbCc × AaBbCc = P(AA) × P(BB) × P(cc) = 1/4 × 1/4 × 1/4 = 1/64"))
story.append(sp(5))

story.append(Paragraph("<b>B. DNA Replication — Key Enzymes</b>", SUBSEC))
story.append(two_col_table([
    ["Enzyme", "Function"],
    ["Helicase",            "Unwinds double helix (breaks H-bonds between bases)"],
    ["SSB proteins",        "Stabilise single strands, prevent re-annealing"],
    ["Primase",             "Synthesises short RNA primer (needed to start replication)"],
    ["DNA Polymerase III",  "Main enzyme — adds dNTPs in 5'→3' direction ONLY"],
    ["DNA Polymerase I",    "Removes RNA primers, fills gaps with DNA"],
    ["DNA Ligase",          "Joins Okazaki fragments on lagging strand (seals nicks)"],
    ["Topoisomerase",       "Relieves supercoiling ahead of replication fork"],
]))
story.append(highlight_box("Leading strand = continuous synthesis. Lagging strand = discontinuous = Okazaki fragments. Both synthesised 5'→3'."))
story.append(sp(5))

story.append(Paragraph("<b>C. Transcription vs Translation</b>", SUBSEC))
story.append(three_col_table([
    ["Feature", "Transcription", "Translation"],
    ["Product",    "mRNA",                   "Protein (polypeptide)"],
    ["Template",   "DNA (template strand)",  "mRNA (codons)"],
    ["Location",   "Nucleus (eukaryotes)",   "Ribosome (cytoplasm)"],
    ["Enzyme",     "RNA Polymerase",         "Ribosome + aminoacyl-tRNA synthetase"],
    ["Monomer",    "NTPs (ribonucleotides)", "Amino acids (via tRNA)"],
    ["Start",      "Promoter (TATA box)",    "AUG (Met codon)"],
    ["Stop",       "Terminator sequence",    "UAA, UAG, UGA (stop codons)"],
]))
story.append(sp(5))

story.append(Paragraph("<b>D. Lac Operon (E. coli — Inducible System)</b>", SUBSEC))
story.append(two_col_table([
    ["Condition", "What Happens"],
    ["Lactose ABSENT (glucose present)", "Repressor binds operator → structural genes OFF (no transcription)"],
    ["Lactose PRESENT (glucose absent)", "Lactose (allolactose) binds repressor → repressor RELEASED → genes ON → β-galactosidase, permease, transacetylase produced"],
    ["Both glucose + lactose present", "Catabolite repression — glucose preferred, lac operon mostly OFF despite lactose"],
]))
story.append(highlight_box("TRICK: Lac operon = 'lactose = inducer'. Trp operon = 'tryptophan = co-repressor (repressible system)' — OPPOSITE logic!"))
story.append(sp(5))

story.append(Paragraph("<b>E. Genetic Code Properties</b>", SUBSEC))
story.append(two_col_table([
    ["Property", "Meaning"],
    ["Triplet", "3 bases = 1 codon = 1 amino acid"],
    ["Degenerate / Redundant", "Multiple codons can code for same amino acid (e.g., 6 codons for Leu)"],
    ["Non-overlapping", "Each base is read only once"],
    ["Non-ambiguous", "One codon always codes for only ONE amino acid"],
    ["Universal", "Same in almost all organisms (except mitochondria — slight variation)"],
    ["Commaless", "No punctuation between codons — read continuously"],
    ["AUG", "Start codon (codes for Methionine/fMet). ALSO only Met codon."],
    ["UAA, UAG, UGA", "Stop codons (nonsense codons) — no amino acid"],
]))
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# 3. PLANT PHYSIOLOGY  (2 Qs)
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    sec_header("3. PLANT PHYSIOLOGY  [2 Questions]", colors.HexColor("#2D6A4F")),
    sp(4),
]))

story.append(Paragraph("<b>A. Photosynthesis — Light Reactions vs Dark Reactions</b>", SUBSEC))
story.append(two_col_table([
    ["Feature", "Light Reactions (Thylakoid)  vs  Calvin Cycle (Stroma)"],
    ["Location",      "Thylakoid membrane  |  Stroma of chloroplast"],
    ["Input",         "Light, H₂O, ADP+Pi, NADP⁺  |  CO₂, ATP, NADPH"],
    ["Output",        "ATP, NADPH, O₂ (from water splitting)  |  G3P (glucose precursor)"],
    ["PS I (P700)",   "Produces NADPH (by reducing NADP⁺) — cyclic & non-cyclic"],
    ["PS II (P680)",  "Water splitting (photolysis) → O₂ released. Produces ATP."],
    ["Z-scheme",      "Non-cyclic photophosphorylation: PS II → PS I → NADPH"],
    ["Calvin Cycle",  "CO₂ + RuBP → 2× 3-PGA (first stable product in C3 plants)"],
]))
story.append(highlight_box("C3 plants: First product = 3-PGA (3-carbon). C4 plants: First product = OAA/Oxaloacetate (4-carbon) in MESOPHYLL cells."))
story.append(sp(5))

story.append(Paragraph("<b>B. C3 vs C4 vs CAM Plants</b>", SUBSEC))
story.append(three_col_table([
    ["Feature", "C3 Plants", "C4 Plants"],
    ["First product of CO₂ fixation", "3-PGA (3-carbon)", "OAA / Oxaloacetate (4-carbon)"],
    ["CO₂ fixation enzyme", "RuBisCO", "PEP Carboxylase (mesophyll) → RuBisCO (bundle sheath)"],
    ["Site of Calvin Cycle", "Mesophyll cells", "Bundle sheath cells"],
    ["Kranz anatomy", "Absent", "PRESENT (wreath of bundle sheath cells)"],
    ["Photorespiration", "HIGH (wasteful)", "Very LOW (CO₂ concentrated at bundle sheath)"],
    ["Examples", "Wheat, Rice, Sunflower", "Maize, Sugarcane, Sorghum"],
    ["CAM plants", "—", "Crassulacean Acid Metabolism: stomata open at NIGHT, fix CO₂ as malate, release during day. E.g., Cacti, Agave"],
]))
story.append(sp(5))

story.append(Paragraph("<b>C. Plant Hormones — Functions</b>", SUBSEC))
story.append(three_col_table([
    ["Hormone", "Key Functions", "Trick / Mnemonic"],
    ["Auxin (IAA)",     "Cell elongation; apical dominance; root initiation; phototropism",  "Apex boss — suppresses lateral buds"],
    ["Gibberellin (GA)","Stem elongation; seed germination; breaks dormancy; fruit dev",     "Giant GA makes stems TALL"],
    ["Cytokinin",       "Cell division; delays senescence (Richmond-Lang effect); lateral bud growth", "Cytokinin = Cell division"],
    ["Ethylene",        "Fruit ripening; leaf/fruit abscission; epinasty; promotes senescence","Ethylene = End of life (ripening)"],
    ["ABA (Abscisic Acid)", "Stomatal CLOSURE; dormancy; stress response; seed maturation","ABA = Abscission + stress = Bad weather hormone"],
]))
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# 4. ECOLOGY  (2 Qs)
# ══════════════════════════════════════════════════════════════════════════════
story.append(PageBreak())
story.append(KeepTogether([
    sec_header("4. ECOLOGY  [2 Questions — Easy Marks]", colors.HexColor("#6A3D9A")),
    sp(4),
]))

story.append(Paragraph("<b>A. Population Growth Models</b>", SUBSEC))
story.append(two_col_table([
    ["Model", "Formula & Key Points"],
    ["Exponential Growth (J-curve)", "dN/dt = rN   |   N(t) = N₀ · e^(rt)   |   Unlimited resources, no competition"],
    ["Logistic Growth (S-curve / sigmoid)", "dN/dt = rN × (K−N)/K   |   K = Carrying capacity"],
    ["Maximum growth rate (logistic)", "When N = K/2 → dN/dt is MAXIMUM"],
    ["At N = K", "dN/dt = 0 → population stops growing (equilibrium)"],
    ["r-strategists", "High r, many offspring, short life, boom-bust: insects, bacteria"],
    ["K-strategists", "Low r, few offspring, long-lived, stable near K: elephants, humans"],
]))
story.append(highlight_box("KEY FORMULA: dN/dt = rN(K−N)/K   ←   MAX growth at N = K/2. This is asked EVERY YEAR."))
story.append(sp(5))

story.append(Paragraph("<b>B. Ecological Pyramids</b>", SUBSEC))
story.append(three_col_table([
    ["Pyramid Type", "Can be Inverted?", "Example of Inverted"],
    ["Pyramid of Numbers",  "YES", "Tree (1) → insects → birds (inverted at base)"],
    ["Pyramid of Biomass",  "YES", "Aquatic — phytoplankton biomass < zooplankton"],
    ["Pyramid of Energy",   "NEVER — Always Upright", "Energy is lost at each trophic level (10% rule)"],
]))
story.append(highlight_box("10% ENERGY RULE: Only 10% energy transferred to next trophic level. 90% lost as heat. So: Producer → Primary consumer → Secondary... always loses energy."))
story.append(sp(5))

story.append(Paragraph("<b>C. Biotic Interactions</b>", SUBSEC))
story.append(two_col_table([
    ["Interaction", "Species A / Species B"],
    ["Mutualism (+/+)",           "Both benefit — Mycorrhizae-plant, Lichen, Cleaner fish"],
    ["Commensalism (+/0)",        "A benefits, B unaffected — Orchid on tree (epiphyte), Barnacles on whale"],
    ["Predation (+/−)",           "Predator benefits, prey harmed — Lion-zebra, Insectivorous plants"],
    ["Parasitism (+/−)",          "Parasite benefits, host harmed — Plasmodium-human, Cuscuta-host plant"],
    ["Competition (−/−)",         "Both harmed — Interspecific competition, Gause's competitive exclusion"],
    ["Amensalism (0/−)",          "A unaffected, B harmed — Penicillin kills bacteria"],
]))
story.append(sp(5))

story.append(Paragraph("<b>D. Nitrogen Cycle — Key Organisms</b>", SUBSEC))
story.append(two_col_table([
    ["Process", "Key Organisms"],
    ["Nitrogen Fixation (N₂ → NH₃)",     "Rhizobium (legumes), Azotobacter, Cyanobacteria (Anabaena)"],
    ["Nitrification (NH₃ → NO₂ → NO₃⁻)", "Nitrosomonas (NH₃→NO₂), Nitrobacter (NO₂→NO₃⁻)"],
    ["Denitrification (NO₃⁻ → N₂)",       "Pseudomonas, Thiobacillus — anaerobic bacteria"],
    ["Ammonification (org N → NH₃)",       "Decomposers (fungi and bacteria) — decompose dead organic matter"],
]))
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# 5. REPRODUCTION  (1-2 Qs)
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    sec_header("5. REPRODUCTION  [1-2 Questions]", colors.HexColor("#E76F51")),
    sp(4),
]))

story.append(Paragraph("<b>A. Double Fertilization in Angiosperms (IAT FAVOURITE)</b>", SUBSEC))
story.append(two_col_table([
    ["Event", "Details"],
    ["Syngamy (1st fertilization)", "Sperm (n) + Egg (n) = Zygote (2n) → EMBRYO"],
    ["Triple Fusion (2nd fertilization)", "Sperm (n) + 2 Polar Nuclei (n+n) = Primary Endosperm Nucleus (3n) → ENDOSPERM"],
    ["Seed coat (testa)", "From integuments of ovule — MATERNAL tissue — DIPLOID (2n of mother)"],
    ["Ploidy calculation", "If P (2n=20) × Q (2n=30): Embryo = 10+15=25, Endosperm = 10+10+15=35, Seed coat = 20"],
]))
story.append(highlight_box("FORMULA: Embryo ploidy = n(female) + n(male). Endosperm ploidy = 2n(female) + n(male). Seed coat = 2n of mother ONLY."))
story.append(sp(5))

story.append(Paragraph("<b>B. Menstrual Cycle — Hormone Phases</b>", SUBSEC))
story.append(two_col_table([
    ["Phase (Days)", "Hormones & Events"],
    ["Menstruation (1-5)", "Estrogen + Progesterone DROP → uterine lining shed"],
    ["Follicular Phase (1-13)", "FSH rises → Graafian follicle develops → Estrogen rises → LH surge triggered"],
    ["Ovulation (Day 14)", "LH SURGE → mature follicle ruptures → ovum released"],
    ["Luteal Phase (15-28)", "Corpus luteum forms → secretes Progesterone + Estrogen → prepares uterus"],
    ["If no fertilization", "Corpus luteum degenerates → hormones drop → menstruation begins again"],
]))
story.append(sp(5))

story.append(Paragraph("<b>C. Gametogenesis Comparison</b>", SUBSEC))
story.append(three_col_table([
    ["Feature", "Spermatogenesis", "Oogenesis"],
    ["Location",    "Seminiferous tubules",    "Ovarian follicles"],
    ["Products",    "4 functional sperms",     "1 egg + 3 polar bodies (degenerate)"],
    ["When begins", "Puberty — continuous",    "Starts before birth, arrested at Prophase I"],
    ["Completion",  "~74 days",               "Completed only after fertilization (Meiosis II)"],
    ["FSH role",    "Spermatogenesis support", "Follicle development"],
    ["LH role",     "Testosterone production (Leydig)", "Ovulation trigger"],
]))
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# 6. BIOTECHNOLOGY  (1-2 Qs)
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    sec_header("6. BIOTECHNOLOGY  [1-2 Questions — Rising Trend]", colors.HexColor("#1D4E89")),
    sp(4),
]))

story.append(Paragraph("<b>A. PCR (Polymerase Chain Reaction)</b>", SUBSEC))
story.append(two_col_table([
    ["Step", "Temperature & Event"],
    ["1. Denaturation", "94-96°C → DNA double helix melts (H-bonds break) → two single strands"],
    ["2. Annealing", "50-65°C → Primers bind to complementary sequences on template"],
    ["3. Extension", "72°C → Taq polymerase adds dNTPs in 5'→3' direction → new strand made"],
    ["Taq polymerase", "FROM Thermus aquaticus (hot spring bacteria) — HEAT STABLE, works at 72°C"],
    ["Exponential amplification", "After n cycles: 2ⁿ copies of target DNA"],
    ["Primers", "Short, synthetic, single-stranded DNA — define start and end of target region"],
]))
story.append(highlight_box("PCR order: DENATURE (heat) → ANNEAL (cool) → EXTEND (72°C). 30 cycles = ~10⁹ copies from single molecule!"))
story.append(sp(5))

story.append(Paragraph("<b>B. Restriction Enzymes (Molecular Scissors)</b>", SUBSEC))
story.append(two_col_table([
    ["Term", "Explanation"],
    ["Recognition site", "Specific palindromic DNA sequence (reads same both strands 5'→3')"],
    ["EcoRI example", "5'-G↓AATTC-3' / 3'-CTTAA↑G-5' → produces sticky ends (4-base overhang)"],
    ["Sticky ends", "Single-stranded overhangs — easier to ligate with complementary fragments"],
    ["Blunt ends", "Enzyme cuts both strands at same position — no overhang (e.g., SmaI: CCC↓GGG)"],
    ["Isoschizomers", "Different enzymes that recognise same sequence"],
    ["DNA Ligase", "Joins cut DNA fragments — seals phosphodiester bond between sticky ends"],
]))
story.append(sp(5))

story.append(Paragraph("<b>C. Gel Electrophoresis</b>", SUBSEC))
story.append(two_col_table([
    ["Principle", "Details"],
    ["What separates", "DNA/RNA/protein by SIZE (and charge for proteins)"],
    ["Direction of migration", "DNA is negatively charged → moves toward POSITIVE electrode (anode)"],
    ["Smaller fragments", "Travel FARTHER (less resistance in gel matrix)"],
    ["Larger fragments", "Travel SHORTER distance"],
    ["Staining", "Ethidium bromide (EtBr) — intercalates DNA → fluoresces orange under UV"],
    ["Agarose vs Polyacrylamide", "Agarose for DNA. Polyacrylamide (PAGE) for proteins/small DNA"],
]))
story.append(sp(5))

story.append(Paragraph("<b>D. Recombinant DNA & Key Applications</b>", SUBSEC))
story.append(two_col_table([
    ["Topic", "Key Fact"],
    ["Plasmid (vector)", "Circular self-replicating DNA — used to carry foreign gene into host cell"],
    ["Ti plasmid", "From Agrobacterium tumefaciens — natural plant transformation vector"],
    ["Bt cotton", "Gene from Bacillus thuringiensis (cry genes) → Cry proteins → kills bollworm"],
    ["Golden Rice", "Transgenic rice with beta-carotene (Vitamin A precursor) — phytoene synthase gene from daffodil"],
    ["Insulin (Humulin)", "Human insulin gene in E. coli → large-scale production via rDNA tech"],
    ["Selectable marker", "Antibiotic resistance gene (e.g., ampicillin) — used to identify transformants"],
    ["Southern Blotting", "DNA → gel → transfer to membrane → hybridize with probe"],
    ["Northern Blotting", "RNA detection (transcription studies)"],
    ["Western Blotting", "PROTEIN detection (uses antibodies)"],
]))
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# 7. CELL BIOLOGY & BIOMOLECULES  (1-2 Qs)
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    sec_header("7. CELL BIOLOGY & BIOMOLECULES  [1-2 Questions]", colors.HexColor("#264653")),
    sp(4),
]))

story.append(Paragraph("<b>A. Cell Cycle — Phases</b>", SUBSEC))
story.append(two_col_table([
    ["Phase", "What Happens"],
    ["G1 (Gap 1)",              "Cell grows, synthesises proteins, organelles increase"],
    ["S (Synthesis)",           "DNA REPLICATION — chromosomes duplicated (each becomes 2 chromatids)"],
    ["G2 (Gap 2)",              "Cell prepares for division, tubulin synthesised for spindle"],
    ["M (Mitosis)",             "Prophase → Metaphase → Anaphase → Telophase → Cytokinesis"],
    ["G0 (Quiescent phase)",    "Cell exits cycle, no longer dividing (e.g., neurons, muscle)"],
    ["Cyclins + CDKs",          "Regulate transitions: Cyclin D/E (G1→S), Cyclin B/CDK1 (G2→M)"],
    ["p53 tumour suppressor",   "Checks DNA damage; triggers apoptosis or arrest if damage found"],
]))
story.append(sp(5))

story.append(Paragraph("<b>B. Mitosis vs Meiosis</b>", SUBSEC))
story.append(three_col_table([
    ["Feature", "Mitosis", "Meiosis"],
    ["Number of divisions", "1", "2 (Meiosis I + II)"],
    ["Daughter cells", "2 diploid (2n)", "4 haploid (n)"],
    ["Crossing over", "Absent", "Present in Prophase I (chiasmata)"],
    ["Purpose", "Growth, repair, asexual reproduction", "Gamete / spore formation"],
    ["Genetic outcome", "Identical to parent cell", "Genetically diverse"],
    ["Where occurs", "Somatic (body) cells", "Germline cells (gonads)"],
]))
story.append(sp(5))

story.append(Paragraph("<b>C. Cell Organelles — Key Functions</b>", SUBSEC))
story.append(two_col_table([
    ["Organelle", "Key Function"],
    ["Mitochondria",     "ATP production (aerobic respiration) — 'powerhouse'. Double membrane. Has own DNA."],
    ["Chloroplast",      "Photosynthesis. Double membrane. Thylakoids (light rxn) + Stroma (Calvin). Own DNA."],
    ["Ribosome (80S)",   "Protein synthesis in eukaryotes. 60S + 40S subunits. In ER or free in cytoplasm."],
    ["Ribosome (70S)",   "Protein synthesis in prokaryotes, mitochondria, chloroplasts. 50S + 30S."],
    ["Rough ER",         "Protein synthesis and transport (has ribosomes on surface)"],
    ["Smooth ER",        "Lipid/steroid synthesis, detoxification, Ca²⁺ storage"],
    ["Golgi Apparatus",  "Protein modification, packaging, secretion (cis → trans). Produces lysosomes."],
    ["Lysosome",         "Intracellular digestion — contains hydrolytic enzymes at low pH (~5)"],
    ["Peroxisome",       "Oxidation of fatty acids; detoxification of H₂O₂ by catalase"],
    ["Centrosome",       "Forms mitotic spindle; has centrioles (absent in plant cells)"],
    ["Nucleus",          "DNA storage, transcription control. Nuclear envelope has nuclear pores."],
]))
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# 8. EVOLUTION  (1 Q)
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    sec_header("8. EVOLUTION  [1 Question]", colors.HexColor("#6B4226")),
    sp(4),
]))

story.append(two_col_table([
    ["Concept", "Key Points"],
    ["Darwin's Natural Selection", "Variation → Struggle for existence → Survival of fittest → Differential reproduction"],
    ["Lamarck's Theory", "Use and disuse + inheritance of acquired characters — DISPROVEN"],
    ["Hardy-Weinberg Equilibrium", "p² + 2pq + q² = 1 (allele frequencies constant if no evolution)"],
    ["H-W conditions (for NO evolution)", "Large population, random mating, no mutation, no migration, no selection"],
    ["Factors that DISTURB H-W", "Natural selection, mutation, genetic drift, gene flow, non-random mating"],
    ["Genetic Drift", "Random change in allele freq in SMALL population (Founder effect, Bottleneck)"],
    ["Homologous organs", "Same origin, different function → evidence for divergent evolution (e.g., human arm / whale flipper / bat wing)"],
    ["Analogous organs", "Different origin, same function → convergent evolution (e.g., wings of bat vs insect)"],
    ["Vestigial organs", "Remnants of structures that had function in ancestors (e.g., vermiform appendix, coccyx in humans)"],
    ["Molecular clock", "Rate of mutation in DNA used to estimate divergence time between species"],
]))
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# 9. BIOLOGY IN HUMAN WELFARE  (1 Q occasional)
# ══════════════════════════════════════════════════════════════════════════════
story.append(KeepTogether([
    sec_header("9. HUMAN HEALTH, IMMUNITY & MICROBES  [1 Question Occasionally]", colors.HexColor("#457B9D")),
    sp(4),
]))

story.append(three_col_table([
    ["Disease / Topic", "Causative Agent", "Key Fact"],
    ["Malaria",          "Plasmodium (P. falciparum = most deadly)", "Vector: Female Anopheles mosquito"],
    ["Typhoid",          "Salmonella typhi",        "Widal test for diagnosis; faecal-oral route"],
    ["Pneumonia",        "Streptococcus pneumoniae","Alveoli fill with fluid; cough with rust-coloured sputum"],
    ["AIDS",             "HIV (retrovirus)",         "Destroys TH (CD4+) cells; Western blot & ELISA diagnosis"],
    ["Cancer",           "Oncogenes / carcinogens",  "Uncontrolled cell division; contact inhibition lost"],
    ["Innate immunity",  "Non-specific",             "Skin, mucus, NK cells, macrophages, fever, complement"],
    ["Adaptive immunity","Specific (B and T cells)", "Humoral (antibody) + Cell-mediated (cytotoxic T cells)"],
    ["Memory cells",     "B and T memory cells",     "Basis of vaccination — secondary response faster & stronger"],
    ["Antibody structure","Y-shaped glycoprotein",   "2 heavy + 2 light chains; antigen-binding site = Fab region"],
    ["Interferons",      "Antiviral proteins",       "Secreted by virus-infected cells; warn neighbouring cells"],
]))
story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# QUICK REFERENCE FORMULAS BOX
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("MASTER FORMULA SHEET — All Key Formulas at a Glance", C_ACCENT))
story.append(sp(5))

formulas = [
    ["Logistic Growth", "dN/dt = rN × (K−N)/K       Max growth at N = K/2"],
    ["Exponential Growth", "dN/dt = rN     OR     N(t) = N₀ × e^(rt)"],
    ["Hardy-Weinberg", "p + q = 1     |     p² + 2pq + q² = 1     (p = dom allele freq, q = rec allele freq)"],
    ["10% Energy Rule", "Energy at trophic level n+1 = 10% × Energy at level n"],
    ["Double Fertilization Ploidy", "Embryo = n(♀) + n(♂)     |     Endosperm = 2n(♀) + n(♂)     |     Seed coat = 2n(♀ only)"],
    ["PCR Amplification", "After n cycles: 2ⁿ copies of target sequence from 1 template"],
    ["Crossing Over (Meiosis I)", "Occurs in Pachytene of Prophase I. Point of crossing = Chiasma."],
    ["Bohr Effect", "CO₂↑ → H⁺↑ → pH↓ → Hb O₂ affinity↓ → RIGHT shift → O₂ released"],
    ["Monohybrid ratio", "Phenotype = 3:1 | Genotype = 1(AA) : 2(Aa) : 1(aa)"],
    ["Dihybrid ratio", "9 : 3 : 3 : 1  (AaBb × AaBb)"],
    ["Probability of genotype", "P(AABBcc) = P(AA) × P(BB) × P(cc) = 1/4 × 1/4 × 1/4 = 1/64"],
    ["Cardiac Output", "CO = Heart Rate × Stroke Volume   (Normal: ~5 L/min at rest)"],
    ["GFR (Glomerular Filtration Rate)", "Normal = ~125 mL/min or ~180 L/day — 99% reabsorbed"],
]

for name, formula in formulas:
    w = PAGE_W - 2*MARGIN
    row = Table([[
        Paragraph(name, S("fn", fontName="Helvetica-Bold", fontSize=8, textColor=C_WHITE)),
        Paragraph(formula, S("ff", fontName="Helvetica", fontSize=8.5, textColor=C_DARK))
    ]], colWidths=[w*0.28, w*0.72])
    row.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (0,0),  C_DARK),
        ("BACKGROUND",    (1,0), (1,0),  colors.HexColor("#FFF8E7")),
        ("TOPPADDING",    (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("LEFTPADDING",   (0,0), (-1,-1), 8),
        ("GRID",          (0,0), (-1,-1), 0.3, C_GRAY),
    ]))
    story.append(row)

story.append(sp(8))

# ══════════════════════════════════════════════════════════════════════════════
# LAST MINUTE TIPS
# ══════════════════════════════════════════════════════════════════════════════
story.append(sec_header("EXAM DAY STRATEGY — 7 June 2026", C_ACCENT))
story.append(sp(5))
tips = [
    ["Start with Biology", "Attempt biology FIRST — easiest section, builds confidence"],
    ["Skip & return",       "If stuck on a question, skip it. Come back later. Don't waste >2 min per Q."],
    ["Negative marking",    "-1 for wrong. If you can eliminate 2 options, ATTEMPT. If clueless, SKIP."],
    ["Diagram questions",   "Read all options carefully — IAT often asks 'which of these is WRONG'"],
    ["Time budget",         "45 min per subject (3 hours total). Biology = 45 min → 3 min per question."],
    ["NCERT language",      "Answers use NCERT exact terminology. Memorise NCERT definitions."],
    ["Good attempt target", "Biology: attempt 13-14 out of 15. Even 11 correct = 44-3 = 41 marks (out of 60)"],
]
for tip, detail in tips:
    row = Table([[
        Paragraph(f"✓ {tip}", S("tn", fontName="Helvetica-Bold", fontSize=8.5, textColor=C_GREEN)),
        Paragraph(detail, BODY)
    ]], colWidths=[(PAGE_W-2*MARGIN)*0.25, (PAGE_W-2*MARGIN)*0.75])
    row.setStyle(TableStyle([
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 6),
        ("ROWBACKGROUNDS",(0,0), (-1,-1), [C_LIGHT, C_WHITE]),
        ("GRID",          (0,0), (-1,-1), 0.3, C_GRAY),
    ]))
    story.append(row)

story.append(sp(8))
story.append(highlight_box("ALL THE BEST FOR IAT 2026 — 7 JUNE 2026  |  You've got this! Target 12+ in Biology.", bg=C_GREEN, fg=C_WHITE))

# ── BUILD PDF ────────────────────────────────────────────────────────────────
doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=A4,
    leftMargin=MARGIN, rightMargin=MARGIN,
    topMargin=MARGIN, bottomMargin=MARGIN,
    title="IAT 2026 Biology Cheat Sheet",
    author="Orris AI"
)
doc.build(story)
print(f"PDF created: {OUTPUT}")

from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.styles import ParagraphStyle
from reportlab.lib.units import cm
from reportlab.platypus import (
    SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle,
    HRFlowable, KeepTogether, PageBreak
)
from reportlab.lib.enums import TA_CENTER, TA_LEFT

OUTPUT = "/home/daytona/workspace/iat-cheatsheet/IAT_2026_Biology_MockTest.pdf"

# ── Colors ──
C_DARK   = colors.HexColor("#0D1B2A")
C_ACCENT = colors.HexColor("#E63946")
C_GREEN  = colors.HexColor("#2DC653")
C_BLUE   = colors.HexColor("#1D7FD8")
C_YELLOW = colors.HexColor("#FFD166")
C_LIGHT  = colors.HexColor("#F1FAEE")
C_GRAY   = colors.HexColor("#8D99AE")
C_WHITE  = colors.white
C_ORANGE = colors.HexColor("#F4A261")
C_PURPLE = colors.HexColor("#6A3D9A")

PAGE_W, PAGE_H = A4
MARGIN = 1.5 * cm

def S(name, **kw):
    return ParagraphStyle(name, **kw)

TITLE   = S("T", fontName="Helvetica-Bold", fontSize=20, textColor=C_WHITE, alignment=TA_CENTER, spaceAfter=3)
SUBT    = S("ST", fontName="Helvetica", fontSize=10, textColor=C_YELLOW, alignment=TA_CENTER, spaceAfter=2)
WARN    = S("W", fontName="Helvetica-Bold", fontSize=9, textColor=C_ACCENT, alignment=TA_CENTER, spaceAfter=5)
QNUM    = S("QN", fontName="Helvetica-Bold", fontSize=10, textColor=C_WHITE)
QTOPIC  = S("QT", fontName="Helvetica-Oblique", fontSize=8, textColor=C_YELLOW)
QTEXT   = S("QTX", fontName="Helvetica-Bold", fontSize=9.5, textColor=C_DARK, leading=14, spaceAfter=4)
OPT     = S("OP", fontName="Helvetica", fontSize=9, textColor=C_DARK, leading=13)
OPTC    = S("OPC", fontName="Helvetica-Bold", fontSize=9, textColor=C_GREEN, leading=13)  # correct
ANSHDR  = S("AH", fontName="Helvetica-Bold", fontSize=10, textColor=C_WHITE)
ANSTXT  = S("AT", fontName="Helvetica", fontSize=8.5, textColor=C_DARK, leading=13)
ANSANS  = S("AA", fontName="Helvetica-Bold", fontSize=9, textColor=C_GREEN, leading=13)
TRICK   = S("TR", fontName="Helvetica-Oblique", fontSize=8, textColor=C_PURPLE, leading=12)
SECHEAD = S("SH", fontName="Helvetica-Bold", fontSize=11, textColor=C_WHITE, alignment=TA_LEFT)
BODY    = S("BO", fontName="Helvetica", fontSize=8.5, textColor=C_DARK, leading=13)
BOLD    = S("BD", fontName="Helvetica-Bold", fontSize=8.5, textColor=C_DARK, leading=13)

def sp(h=6): return Spacer(1, h)
def hr(): return HRFlowable(width="100%", thickness=0.4, color=C_GRAY, spaceBefore=3, spaceAfter=3)

def banner(lines_styles):
    rows = [[Paragraph(t, s)] for t, s in lines_styles]
    t = Table(rows, colWidths=[PAGE_W - 2*MARGIN])
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), C_DARK),
        ("TOPPADDING",    (0,0), (-1,-1), 8),
        ("BOTTOMPADDING", (0,0), (-1,-1), 6),
        ("LEFTPADDING",   (0,0), (-1,-1), 12),
    ]))
    return t

def sec_hdr(text, color=C_BLUE):
    t = Table([[Paragraph(text, SECHEAD)]], colWidths=[PAGE_W - 2*MARGIN])
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), color),
        ("TOPPADDING",    (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("LEFTPADDING",   (0,0), (-1,-1), 10),
    ]))
    return t

def highlight(text, bg=C_YELLOW, fg=C_DARK):
    sty = S("hl", fontName="Helvetica-Bold", fontSize=8.5, textColor=fg, leading=13)
    t = Table([[Paragraph(text, sty)]], colWidths=[PAGE_W - 2*MARGIN])
    t.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), bg),
        ("TOPPADDING",    (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("LEFTPADDING",   (0,0), (-1,-1), 10),
    ]))
    return t

# ══════════════════════════════════════════════════════
# QUESTIONS DATA
# ══════════════════════════════════════════════════════
# Each Q: (topic, question_text, options_list, correct_index 0-based, explanation, trick)
QUESTIONS = [
    # Q1 — Human Physiology
    (
        "Human Physiology — Nephron",
        "A patient with uncontrolled Type 1 Diabetes mellitus will show glucosuria (glucose in urine). "
        "This occurs primarily because:",
        [
            "(A) Glomerular filtration is completely blocked",
            "(B) The PCT transport maximum (Tm) for glucose is exceeded — reabsorption cannot keep up",
            "(C) ADH secretion increases, diluting urine",
            "(D) Loop of Henle actively secretes glucose into filtrate",
        ],
        1,  # B is correct
        "In normal individuals, all filtered glucose is reabsorbed in the PCT via Na⁺-glucose cotransport. "
        "The transport maximum (Tm) for glucose is ~300 mg/min. In diabetes, blood glucose exceeds the renal "
        "threshold (~180 mg/dL), flooding the PCT with more glucose than transporters can handle → glucose spills into urine.",
        "Trick: PCT = glucose hotel. When guests (glucose) exceed hotel capacity (Tm), overflow = glucosuria."
    ),
    # Q2 — Human Physiology
    (
        "Human Physiology — O₂-Hb Dissociation Curve",
        "In a working muscle during intense exercise, which combination of conditions would cause the "
        "MAXIMUM rightward shift of the oxygen-haemoglobin dissociation curve?",
        [
            "(A) Low CO₂, low temperature, high pH",
            "(B) High CO₂, high temperature, low pH, high 2,3-BPG",
            "(C) High O₂ partial pressure, low H⁺, low 2,3-BPG",
            "(D) Low CO₂, high temperature, low 2,3-BPG",
        ],
        1,  # B
        "The Bohr effect: right shift = decreased Hb-O₂ affinity = O₂ released to tissues. "
        "Right shift is caused by: ↑CO₂, ↑H⁺ (↓pH), ↑temperature, ↑2,3-BPG. "
        "During intense exercise, ALL four factors are elevated in working muscles simultaneously — "
        "maximising O₂ delivery exactly where needed.",
        "Trick: CHAT = CO₂ High, Acid (H⁺ High), Temperature High → Right shift"
    ),
    # Q3 — Genetics
    (
        "Genetics — Dihybrid Cross",
        "In pea plants, Tall (T) is dominant over Dwarf (t), and Round seed (R) is dominant over "
        "Wrinkled (r). A plant heterozygous for both traits (TtRr) is test-crossed. "
        "What fraction of offspring will be TALL with WRINKLED seeds?",
        [
            "(A) 9/16",
            "(B) 1/4",
            "(C) 3/16",
            "(D) 1/2",
        ],
        1,  # B
        "Test cross = TtRr × ttrr. Gametes from TtRr: TR, Tr, tR, tr (each 1/4). "
        "Gametes from ttrr: only tr. Offspring: TtRr : Ttrr : ttRr : ttrr = 1:1:1:1. "
        "Tall + Wrinkled = Ttrr = 1/4 of offspring.",
        "Trick: Test cross always gives 1:1:1:1 for dihybrid → each phenotypic class = 1/4"
    ),
    # Q4 — Molecular Biology
    (
        "Molecular Biology — DNA Replication",
        "During DNA replication, Okazaki fragments are eventually joined into a continuous strand. "
        "Which sequence of enzymatic steps correctly describes this process?",
        [
            "(A) DNA Pol III extends fragment → DNA Pol I replaces primer → Ligase joins nicks",
            "(B) Primase removes primer → DNA Pol III fills gap → Helicase joins nicks",
            "(C) DNA Pol I extends Okazaki fragment → DNA Pol III removes primer → Ligase joins",
            "(D) Helicase removes primer → SSB proteins fill gap → Ligase joins",
        ],
        0,  # A
        "On the lagging strand: (1) DNA Pol III synthesises Okazaki fragment up to the RNA primer of "
        "the previous fragment. (2) DNA Pol I uses its 5'→3' exonuclease activity to remove the RNA primer "
        "while simultaneously filling the gap with DNA (nick translation). (3) DNA Ligase seals the remaining "
        "nick (phosphodiester bond) between fragments.",
        "Trick: Pol III = builder. Pol I = demolish primer + rebuild with DNA. Ligase = glue."
    ),
    # Q5 — Plant Physiology
    (
        "Plant Physiology — C4 Photosynthesis",
        "Sugarcane (a C4 plant) has a competitive advantage over wheat (a C3 plant) in hot, sunny "
        "conditions primarily because:",
        [
            "(A) Sugarcane has more chlorophyll and absorbs more light",
            "(B) PEP carboxylase in mesophyll cells has much higher affinity for CO₂ than RuBisCO, "
                "suppressing photorespiration",
            "(C) Sugarcane undergoes both C3 and C4 cycles simultaneously in the same cell",
            "(D) Bundle sheath cells in sugarcane lack RuBisCO, performing only light reactions",
        ],
        1,  # B
        "In hot conditions stomata close to prevent water loss → internal CO₂ drops → "
        "in C3 plants, RuBisCO fixes O₂ instead of CO₂ (photorespiration, wasteful). "
        "C4 plants use PEP carboxylase in mesophyll cells — it has ~60× higher affinity for CO₂ than RuBisCO "
        "and does NOT fix O₂. It concentrates CO₂ in bundle sheath cells, suppressing photorespiration entirely.",
        "Trick: PEP carboxylase = super-selective CO₂ pump. C4 = CO₂ concentrating mechanism (CCM)"
    ),
    # Q6 — Ecology
    (
        "Ecology — Population Growth",
        "A population of bacteria has r = 0.5 per hour and K = 10,000 cells. "
        "At what population size (N) is the instantaneous growth rate (dN/dt) at its MAXIMUM?",
        [
            "(A) N = 10,000",
            "(B) N = 2,500",
            "(C) N = 5,000",
            "(D) N = 7,500",
        ],
        2,  # C
        "Using logistic growth equation: dN/dt = rN(K−N)/K. "
        "To find maximum, differentiate with respect to N and set = 0. "
        "d²N/dt² = 0 when N = K/2 = 10,000/2 = 5,000. "
        "At N=K/2, growth rate is maximum = rK/4 = 0.5 × 10,000/4 = 1,250 cells/hour.",
        "Formula: Max dN/dt always at N = K/2. This is asked EVERY year in IAT."
    ),
    # Q7 — Reproduction
    (
        "Reproduction — Double Fertilization & Ploidy",
        "In an interspecific cross between Plant A (2n = 16) as the female parent and Plant B (2n = 24) "
        "as the male parent, what will be the chromosome number in the ENDOSPERM of the resulting seed?",
        [
            "(A) 20 chromosomes",
            "(B) 28 chromosomes",
            "(C) 24 chromosomes",
            "(D) 32 chromosomes",
        ],
        1,  # B
        "Endosperm is formed by triple fusion: 2 polar nuclei (from female) + 1 sperm (from male). "
        "Plant A (2n=16): haploid = n=8. Two polar nuclei = 8+8 = 16 chromosomes. "
        "Plant B (2n=24): haploid = n=12. One sperm = 12 chromosomes. "
        "Endosperm = 16 + 12 = 28 chromosomes (triploid = 3n, but chromosomes = 28 here).",
        "Formula: Endosperm chromosomes = 2n(♀)/2 + 2n(♀)/2 + 2n(♂)/2 = n♀ + n♀ + n♂"
    ),
    # Q8 — Biotechnology
    (
        "Biotechnology — PCR",
        "A forensic scientist needs to amplify a specific 500 bp DNA sequence from a crime scene sample. "
        "After 30 cycles of PCR, approximately how many copies of the target sequence will be present "
        "(starting from 1 copy)?",
        [
            "(A) 30 copies",
            "(B) 900 copies",
            "(C) ~10⁶ copies",
            "(D) ~10⁹ copies",
        ],
        3,  # D
        "PCR amplification is exponential: after n cycles, 1 template gives 2ⁿ copies. "
        "After 30 cycles: 2³⁰ = 1,073,741,824 ≈ 10⁹ copies. "
        "This massive amplification from a single molecule is what makes PCR so powerful for forensics, "
        "diagnosis (e.g., COVID RT-PCR), and research.",
        "Formula: copies after n cycles = 2ⁿ. 2¹⁰ ≈ 10³, so 2³⁰ ≈ 10⁹"
    ),
    # Q9 — Cell Biology
    (
        "Cell Biology — Cell Cycle & Cancer",
        "A mutation that INACTIVATES the p53 tumour suppressor gene contributes to cancer development. "
        "Which mechanism best explains this?",
        [
            "(A) p53 normally stimulates cell division; its loss slows division",
            "(B) p53 normally detects DNA damage and triggers cell cycle arrest or apoptosis; "
                "its loss allows damaged cells to proliferate",
            "(C) p53 is a proto-oncogene; mutation converts it to an oncogene",
            "(D) p53 activates telomerase; its inactivation shortens telomeres, causing instability",
        ],
        1,  # B
        "p53 is the 'guardian of the genome' — a tumour SUPPRESSOR protein. "
        "When DNA is damaged, p53 accumulates and: (1) arrests the cell cycle at G1/S checkpoint "
        "(by activating p21 which inhibits CDK), giving time for repair; OR (2) if damage is irreparable, "
        "triggers apoptosis (programmed cell death). Without p53, cells with mutations skip the checkpoint, "
        "accumulate more mutations, and become cancerous.",
        "Trick: p53 = brake pedal of cell division. Lost brake = runaway car = cancer"
    ),
    # Q10 — Genetics (Lac Operon)
    (
        "Molecular Biology — Gene Regulation (Lac Operon)",
        "A mutation in the lacI gene of E. coli produces a repressor protein that can NO LONGER "
        "bind allolactose (the inducer). What would be the phenotype of this mutant?",
        [
            "(A) Constitutive expression of lac genes — always ON even without lactose",
            "(B) Lac genes permanently OFF — cannot be induced even in presence of lactose",
            "(C) Normal regulation — lactose still induces transcription",
            "(D) Overproduction of allolactose causes cell death",
        ],
        1,  # B
        "Normal regulation: Allolactose binds repressor → repressor releases operator → lac genes transcribed. "
        "If the repressor CANNOT bind allolactose (inducer), it remains permanently bound to the operator "
        "even when lactose IS present. The operator stays blocked → structural genes (lacZ, lacY, lacA) "
        "stay permanently OFF. This is called a 'super-repressor' or lacI⁻ dominant mutation.",
        "Trick: Repressor that ignores inducer = super-repressor = always blocks = permanently OFF"
    ),
    # Q11 — Human Physiology (Hormones)
    (
        "Human Physiology — Endocrine System",
        "A patient presents with: goitre (enlarged thyroid gland), low T3/T4 levels, and HIGH TSH. "
        "What is the most likely diagnosis and mechanism?",
        [
            "(A) Hyperthyroidism — thyroid over-secretes T3/T4 despite feedback",
            "(B) Primary hypothyroidism — damaged thyroid fails to produce T3/T4; pituitary keeps "
                "secreting TSH in compensation",
            "(C) Hypopituitarism — low TSH causes low T3/T4 and compensatory thyroid enlargement",
            "(D) Cushing's syndrome — excess cortisol suppresses T3/T4 production",
        ],
        1,  # B
        "Negative feedback axis: Hypothalamus → TRH → Anterior Pituitary → TSH → Thyroid → T3/T4 → "
        "inhibits hypothalamus and pituitary. If the thyroid is damaged (primary hypothyroidism — e.g., "
        "Hashimoto's, iodine deficiency), T3/T4 are low. Low T3/T4 cannot inhibit the pituitary → "
        "TSH rises enormously (compensatory). High TSH constantly stimulates thyroid → goitre (hypertrophy). "
        "Result: HIGH TSH + LOW T3/T4 + goitre = primary hypothyroidism.",
        "Rule: Low T3/T4 + HIGH TSH = PRIMARY hypothyroid. Low T3/T4 + LOW TSH = secondary (pituitary problem)"
    ),
    # Q12 — Evolution
    (
        "Evolution — Hardy-Weinberg Equilibrium",
        "In a population of 1000 individuals, 360 show the recessive phenotype (aa). "
        "Assuming Hardy-Weinberg equilibrium, what is the frequency of HETEROZYGOUS (Aa) individuals?",
        [
            "(A) 0.36",
            "(B) 0.40",
            "(C) 0.48",
            "(D) 0.60",
        ],
        2,  # C
        "Step 1: Frequency of recessive genotype (aa) = q² = 360/1000 = 0.36. "
        "Step 2: q = √0.36 = 0.6. "
        "Step 3: p = 1 − q = 1 − 0.6 = 0.4. "
        "Step 4: Frequency of Aa = 2pq = 2 × 0.4 × 0.6 = 0.48. "
        "Number of heterozygotes = 0.48 × 1000 = 480 individuals.",
        "Formula: p² + 2pq + q² = 1. Always find q first from q² (recessive phenotype frequency), then p = 1-q, then 2pq."
    ),
    # Q13 — Ecology (Interactions)
    (
        "Ecology — Biotic Interactions",
        "Mycorrhizal fungi form associations with the roots of most terrestrial plants. "
        "The fungus receives sugars from the plant, while the plant gains enhanced water and "
        "mineral (especially phosphorus) absorption. This relationship is an example of:",
        [
            "(A) Parasitism — the fungus harms the plant by consuming sugars",
            "(B) Commensalism — only the fungus benefits, plant is unaffected",
            "(C) Mutualism — both organisms benefit from the association",
            "(D) Amensalism — the fungus inhibits competing root organisms, plant is unaffected",
        ],
        2,  # C
        "Mutualism (+/+): Both species benefit. Mycorrhizae are classic mutualism: "
        "Fungus gets photosynthate (sugars) from plant. Plant gets dramatically enhanced nutrient "
        "and water uptake via the extensive hyphal network (much larger surface area than roots alone). "
        "Over 80% of land plant species have mycorrhizal associations — it is not parasitic because "
        "the plant's overall fitness increases.",
        "Other mutualism examples: Rhizobium-legume, cleaner fish-shark, lichen (algae+fungus), pollinator-flower"
    ),
    # Q14 — Reproduction (Menstrual Cycle)
    (
        "Reproduction — Menstrual Cycle",
        "On Day 14 of a 28-day menstrual cycle, a sharp surge in which hormone directly triggers ovulation?",
        [
            "(A) FSH (Follicle Stimulating Hormone)",
            "(B) Progesterone",
            "(C) LH (Luteinising Hormone)",
            "(D) Estrogen",
        ],
        2,  # C
        "The LH surge (mid-cycle spike in Luteinising Hormone from anterior pituitary) is the direct "
        "trigger for ovulation. Mechanism: Rising estrogen from the Graafian follicle — rather than "
        "inhibiting LH (as it normally does) — causes a POSITIVE feedback surge in LH. This surge "
        "causes the mature follicle to rupture and release the secondary oocyte. "
        "After ovulation, LH causes the ruptured follicle to become the corpus luteum (which secretes progesterone).",
        "Sequence: FSH grows follicle → follicle makes Estrogen → LH SURGE → OVULATION → Corpus luteum → Progesterone"
    ),
    # Q15 — Cell Biology (Organelles)
    (
        "Cell Biology — Organelles",
        "Mitochondria and chloroplasts share several features that support the endosymbiotic theory. "
        "Which of the following features is common to BOTH organelles?",
        [
            "(A) They both contain a single circular DNA molecule, 70S ribosomes, and are bounded by a double membrane",
            "(B) Both contain thylakoids and carry out photophosphorylation",
            "(C) Both are found only in plant cells and use the Calvin cycle",
            "(D) Both contain cristae and produce ATP exclusively by substrate-level phosphorylation",
        ],
        0,  # A
        "Endosymbiotic theory (Lynn Margulis): Mitochondria and chloroplasts were once free-living "
        "prokaryotes engulfed by ancestral eukaryotic cells. Evidence — both share: "
        "(1) Circular DNA (like bacteria), (2) 70S ribosomes (prokaryotic type, vs 80S in eukaryotic cytoplasm), "
        "(3) Double membrane (inner from original bacterium, outer from host cell's phagosome), "
        "(4) Binary fission-like division, (5) Similar size to bacteria. "
        "Thylakoids are only in chloroplasts; cristae are only in mitochondria.",
        "Trick: Mito + Chloro = both have: own circular DNA + 70S ribosomes + double membrane = endosymbiont evidence"
    ),
]

# ══════════════════════════════════════════════════════
# BUILD PDF
# ══════════════════════════════════════════════════════
story = []

# ── COVER ──
story.append(banner([
    ("IAT 2026 BIOLOGY — FULL MOCK TEST", TITLE),
    ("15 Questions  •  60 Marks  •  Time: 45 Minutes  •  +4 Correct / -1 Wrong", SUBT),
    ("Exam: 7 June 2026  |  Attempt all questions before checking answers!", WARN),
]))
story.append(sp(8))

# Instructions box
instr = [
    ["Instructions", ""],
    ["Total Questions", "15 MCQs (Single correct answer)"],
    ["Marking Scheme", "+4 for correct, -1 for incorrect, 0 for unattempted"],
    ["Time Limit", "45 minutes (simulate real exam conditions)"],
    ["Difficulty", "Same level as IAT 2024-2025 — Easy to Moderate"],
    ["Topics Covered", "Human Physiology, Genetics, Plant Physiology, Ecology, Reproduction, Biotechnology, Cell Biology, Evolution"],
    ["Answer Key", "At the END of this document with full explanations"],
]
w = PAGE_W - 2*MARGIN
t = Table([[Paragraph(r[0], BOLD), Paragraph(r[1], BODY)] for r in instr],
          colWidths=[w*0.3, w*0.7])
t.setStyle(TableStyle([
    ("BACKGROUND",    (0,0), (-1,0),  C_DARK),
    ("TEXTCOLOR",     (0,0), (-1,0),  C_WHITE),
    ("FONTNAME",      (0,0), (-1,0),  "Helvetica-Bold"),
    ("FONTSIZE",      (0,0), (-1,-1), 9),
    ("BACKGROUND",    (0,1), (-1,-1), C_LIGHT),
    ("ROWBACKGROUNDS",(0,1), (-1,-1), [C_WHITE, C_LIGHT]),
    ("GRID",          (0,0), (-1,-1), 0.3, C_GRAY),
    ("TOPPADDING",    (0,0), (-1,-1), 5),
    ("BOTTOMPADDING", (0,0), (-1,-1), 5),
    ("LEFTPADDING",   (0,0), (-1,-1), 8),
    ("SPAN",          (0,0), (-1,0)),
    ("ALIGN",         (0,0), (-1,0),  "CENTER"),
]))
story.append(t)
story.append(sp(10))

# ── ANSWER GRID (blank) ──
story.append(sec_hdr("YOUR ANSWERS — Fill This Before Checking!", C_ORANGE))
story.append(sp(4))
grid_data = [["Q No.", "Your Answer", "Correct?", "Marks"]] + \
            [[str(i+1), "", "", ""] for i in range(15)] + \
            [["TOTAL", "", "", "/60"]]
wg = PAGE_W - 2*MARGIN
tg = Table(grid_data, colWidths=[wg*0.15, wg*0.35, wg*0.25, wg*0.25])
tg.setStyle(TableStyle([
    ("BACKGROUND",    (0,0), (-1,0),  C_ORANGE),
    ("TEXTCOLOR",     (0,0), (-1,0),  C_WHITE),
    ("FONTNAME",      (0,0), (-1,0),  "Helvetica-Bold"),
    ("FONTSIZE",      (0,0), (-1,-1), 9),
    ("ROWBACKGROUNDS",(0,1), (-1,-2), [C_WHITE, C_LIGHT]),
    ("BACKGROUND",    (0,-1),(-1,-1), C_DARK),
    ("TEXTCOLOR",     (0,-1),(-1,-1), C_WHITE),
    ("FONTNAME",      (0,-1),(-1,-1), "Helvetica-Bold"),
    ("GRID",          (0,0), (-1,-1), 0.4, C_GRAY),
    ("TOPPADDING",    (0,0), (-1,-1), 5),
    ("BOTTOMPADDING", (0,0), (-1,-1), 5),
    ("ALIGN",         (0,0), (-1,-1), "CENTER"),
]))
story.append(tg)
story.append(sp(10))

# ── QUESTIONS ──
story.append(sec_hdr("QUESTIONS — 15 MCQs", C_BLUE))
story.append(sp(6))

for i, (topic, qtext, options, correct_idx, explanation, trick) in enumerate(QUESTIONS):
    qn = i + 1
    # Question number + topic header
    hdr = Table([[
        Paragraph(f"Q{qn}.", QNUM),
        Paragraph(f"[{topic}]", QTOPIC),
    ]], colWidths=[(PAGE_W-2*MARGIN)*0.1, (PAGE_W-2*MARGIN)*0.9])
    hdr.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), C_DARK),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 8),
        ("VALIGN",        (0,0), (-1,-1), "MIDDLE"),
    ]))

    # Question text
    qtbl = Table([[Paragraph(qtext, QTEXT)]], colWidths=[PAGE_W-2*MARGIN])
    qtbl.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), colors.HexColor("#EDF6FF")),
        ("LEFTLINE",      (0,0), (0,-1),  3, C_BLUE),
        ("TOPPADDING",    (0,0), (-1,-1), 8),
        ("BOTTOMPADDING", (0,0), (-1,-1), 6),
        ("LEFTPADDING",   (0,0), (-1,-1), 12),
    ]))

    # Options
    opt_rows = []
    for j, opt in enumerate(options):
        opt_rows.append([Paragraph(opt, OPT)])
    opt_tbl = Table(opt_rows, colWidths=[PAGE_W-2*MARGIN])
    opt_tbl.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), C_WHITE),
        ("ROWBACKGROUNDS",(0,0), (-1,-1), [C_WHITE, C_LIGHT]),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 20),
        ("GRID",          (0,0), (-1,-1), 0.2, C_GRAY),
    ]))

    story.append(KeepTogether([hdr, qtbl, opt_tbl, sp(4)]))
    if qn < 15:
        story.append(hr())
    story.append(sp(4))

# ══════════════════════════════════════════════════════
# ANSWER KEY
# ══════════════════════════════════════════════════════
story.append(PageBreak())
story.append(banner([
    ("DETAILED ANSWER KEY & EXPLANATIONS", TITLE),
    ("Check your answers — understand each concept, not just the correct option", SUBT),
]))
story.append(sp(8))

# Quick answer table
labels = ["A","B","C","D"]
qa_quick = [["Q No.", "Correct Answer", "Topic", "Marks"]]
for i, (topic, qtext, options, correct_idx, explanation, trick) in enumerate(QUESTIONS):
    qa_quick.append([
        str(i+1),
        options[correct_idx][:50] + ("..." if len(options[correct_idx]) > 50 else ""),
        topic.split("—")[0].strip(),
        "+4",
    ])
w = PAGE_W - 2*MARGIN
tqa = Table([[Paragraph(str(c), BOLD if r==0 else BODY) for c in row] for r, row in enumerate(qa_quick)],
            colWidths=[w*0.08, w*0.50, w*0.28, w*0.14])
tqa.setStyle(TableStyle([
    ("BACKGROUND",    (0,0), (-1,0),  C_GREEN),
    ("TEXTCOLOR",     (0,0), (-1,0),  C_WHITE),
    ("FONTNAME",      (0,0), (-1,0),  "Helvetica-Bold"),
    ("FONTSIZE",      (0,0), (-1,-1), 8),
    ("ROWBACKGROUNDS",(0,1), (-1,-1), [C_WHITE, C_LIGHT]),
    ("GRID",          (0,0), (-1,-1), 0.3, C_GRAY),
    ("TOPPADDING",    (0,0), (-1,-1), 4),
    ("BOTTOMPADDING", (0,0), (-1,-1), 4),
    ("LEFTPADDING",   (0,0), (-1,-1), 6),
    ("ALIGN",         (0,0), (0,-1),  "CENTER"),
    ("ALIGN",         (3,0), (3,-1),  "CENTER"),
]))
story.append(tqa)
story.append(sp(10))

# Detailed explanations
story.append(sec_hdr("Detailed Explanations — Read ALL even if you got it right!", C_DARK))
story.append(sp(6))

for i, (topic, qtext, options, correct_idx, explanation, trick) in enumerate(QUESTIONS):
    qn = i + 1
    correct_letter = labels[correct_idx]

    # Header
    hdr2 = Table([[
        Paragraph(f"Q{qn}", ANSHDR),
        Paragraph(f" Correct: ({correct_letter})  |  {topic}", ANSHDR),
    ]], colWidths=[(PAGE_W-2*MARGIN)*0.08, (PAGE_W-2*MARGIN)*0.92])
    hdr2.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), C_GREEN),
        ("TOPPADDING",    (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("LEFTPADDING",   (0,0), (-1,-1), 8),
        ("VALIGN",        (0,0), (-1,-1), "MIDDLE"),
    ]))

    # Options with correct highlighted
    opt_rows2 = []
    for j, opt in enumerate(options):
        sty = OPTC if j == correct_idx else OPT
        marker = "✓ CORRECT → " if j == correct_idx else "      "
        opt_rows2.append([Paragraph(marker + opt, sty)])
    opt_tbl2 = Table(opt_rows2, colWidths=[PAGE_W-2*MARGIN])
    opt_tbl2.setStyle(TableStyle([
        ("BACKGROUND",    (0,0),              (-1,-1), C_WHITE),
        ("BACKGROUND",    (0,correct_idx),    (-1,correct_idx), colors.HexColor("#E8F9EE")),
        ("TOPPADDING",    (0,0), (-1,-1), 3),
        ("BOTTOMPADDING", (0,0), (-1,-1), 3),
        ("LEFTPADDING",   (0,0), (-1,-1), 12),
        ("GRID",          (0,0), (-1,-1), 0.2, C_GRAY),
    ]))

    # Explanation
    exp_tbl = Table([[Paragraph(f"Explanation: {explanation}", ANSTXT)]], colWidths=[PAGE_W-2*MARGIN])
    exp_tbl.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), colors.HexColor("#F0F4FF")),
        ("LEFTLINE",      (0,0), (0,-1),  3, C_BLUE),
        ("TOPPADDING",    (0,0), (-1,-1), 6),
        ("BOTTOMPADDING", (0,0), (-1,-1), 6),
        ("LEFTPADDING",   (0,0), (-1,-1), 10),
    ]))

    # Trick
    trick_tbl = Table([[Paragraph(f"⚡ {trick}", TRICK)]], colWidths=[PAGE_W-2*MARGIN])
    trick_tbl.setStyle(TableStyle([
        ("BACKGROUND",    (0,0), (-1,-1), colors.HexColor("#FFF9E6")),
        ("LEFTLINE",      (0,0), (0,-1),  3, C_YELLOW),
        ("TOPPADDING",    (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING",   (0,0), (-1,-1), 10),
    ]))

    story.append(KeepTogether([hdr2, opt_tbl2, exp_tbl, trick_tbl, sp(6)]))
    if qn < 15:
        story.append(hr())

story.append(sp(8))

# Score interpretation
story.append(sec_hdr("Score Interpretation", C_ACCENT))
story.append(sp(4))
score_data = [
    ["Score Range", "Performance", "Action"],
    ["52-60 (13-15 correct)", "Excellent! IAT ready", "Revise once on exam morning. You're set."],
    ["44-52 (11-13 correct)", "Good",                 "Review wrong questions. Focus on those chapters."],
    ["32-44 (8-11 correct)",  "Average",              "Re-read NCERT for wrong topics. Solve 1 more mock."],
    ["Below 32 (<8 correct)", "Needs improvement",    "Focus on top 3 topics: Physiology, Genetics, Ecology"],
]
ws = PAGE_W - 2*MARGIN
ts = Table([[Paragraph(str(c), BOLD if r==0 else BODY) for c in row] for r, row in enumerate(score_data)],
           colWidths=[ws*0.32, ws*0.22, ws*0.46])
ts.setStyle(TableStyle([
    ("BACKGROUND",    (0,0), (-1,0),  C_ACCENT),
    ("TEXTCOLOR",     (0,0), (-1,0),  C_WHITE),
    ("FONTNAME",      (0,0), (-1,0),  "Helvetica-Bold"),
    ("FONTSIZE",      (0,0), (-1,-1), 8.5),
    ("ROWBACKGROUNDS",(0,1), (-1,-1), [C_WHITE, C_LIGHT]),
    ("GRID",          (0,0), (-1,-1), 0.3, C_GRAY),
    ("TOPPADDING",    (0,0), (-1,-1), 5),
    ("BOTTOMPADDING", (0,0), (-1,-1), 5),
    ("LEFTPADDING",   (0,0), (-1,-1), 8),
    ("VALIGN",        (0,0), (-1,-1), "TOP"),
]))
story.append(ts)
story.append(sp(8))
story.append(highlight("ALL THE BEST FOR IAT 2026  —  7 JUNE 2026  |  Target Biology 12+/15. You've got this!", bg=C_GREEN, fg=C_WHITE))

# ── BUILD ──
doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=A4,
    leftMargin=MARGIN, rightMargin=MARGIN,
    topMargin=MARGIN, bottomMargin=MARGIN,
    title="IAT 2026 Biology Mock Test",
    author="Orris AI"
)
doc.build(story)
print(f"PDF created: {OUTPUT}")

<!DOCTYPE html>
<html lang="en">
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<title>IAT 2026 Biology Mock Test</title>
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<body>

<div class="cover">
  <h1>🧬 IAT 2026 Biology Mock Test</h1>
  <div class="sub">15 Questions &nbsp;•&nbsp; 60 Marks &nbsp;•&nbsp; +4 Correct / &minus;1 Wrong</div>
  <div class="warn">⏱ Exam: 7 June 2026 &nbsp;|&nbsp; Attempt all questions then check score!</div>
</div>

<!-- Sticky Timer -->
<div id="timer-bar">
  ⏱ Time Remaining: <span id="timer-display">45:00</span>
  <button id="timer-btn" onclick="toggleTimer()">Start Timer</button>
</div>

<div class="container">

  <!-- Instructions -->
  <div class="instr-box">
    <h3>📋 Instructions</h3>
    <table>
      <tr><td>Questions</td><td>15 MCQs (one correct answer each)</td></tr>
      <tr><td>Marks</td><td>+4 for correct, −1 for wrong, 0 for skipped</td></tr>
      <tr><td>Time Limit</td><td>45 minutes (use timer above)</td></tr>
      <tr><td>How to use</td><td>Click an option → click <b>"Check Answer"</b> to see explanation</td></tr>
      <tr><td>Final Score</td><td>Click <b>"Submit & See Score"</b> at the bottom</td></tr>
    </table>
  </div>

  <!-- Questions -->
  <div class="sec-hdr">📝 Questions</div>

  <!-- Q1 -->
  <div class="q-card" id="qcard-1">
    <div class="q-header">
      <span class="q-num">Q1</span>
      <span class="q-topic">Human Physiology — Nephron & Diabetes</span>
    </div>
    <div class="q-body">
      <div class="q-text">A patient with uncontrolled Type 1 Diabetes mellitus shows glucosuria (glucose in urine). This occurs primarily because:</div>
      <ul class="options" id="opts-1">
        <li onclick="select_opt(1,0)">A) Glomerular filtration is completely blocked</li>
        <li onclick="select_opt(1,1)">B) The PCT transport maximum (Tm) for glucose is exceeded — reabsorption cannot keep up</li>
        <li onclick="select_opt(1,2)">C) ADH secretion increases, diluting urine and carrying glucose out</li>
        <li onclick="select_opt(1,3)">D) Loop of Henle actively secretes glucose into filtrate</li>
      </ul>
      <div class="ans-box" id="ans-1">
        <div class="ans-correct">✓ Correct Answer: (B)</div>
        <div class="ans-exp">In normal individuals, ALL filtered glucose is reabsorbed in the PCT via Na⁺-glucose cotransport. The transport maximum (Tm) for glucose is ~300 mg/min. In diabetes, blood glucose exceeds the renal threshold (~180 mg/dL), flooding the PCT with more glucose than transporters can handle → glucose spills into urine.</div>
        <div class="ans-trick">⚡ Trick: PCT = glucose hotel. When guests exceed hotel capacity (Tm), overflow = glucosuria.</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(1, 1)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-1">Not attempted</span>
    </div>
  </div>

  <!-- Q2 -->
  <div class="q-card" id="qcard-2">
    <div class="q-header">
      <span class="q-num">Q2</span>
      <span class="q-topic">Human Physiology — O₂-Hb Dissociation Curve (Bohr Effect)</span>
    </div>
    <div class="q-body">
      <div class="q-text">In a working muscle during intense exercise, which combination of conditions would cause the MAXIMUM rightward shift of the oxygen-haemoglobin dissociation curve?</div>
      <ul class="options" id="opts-2">
        <li onclick="select_opt(2,0)">A) Low CO₂, low temperature, high pH</li>
        <li onclick="select_opt(2,1)">B) High CO₂, high temperature, low pH, high 2,3-BPG</li>
        <li onclick="select_opt(2,2)">C) High O₂ partial pressure, low H⁺, low 2,3-BPG</li>
        <li onclick="select_opt(2,3)">D) Low CO₂, high temperature, low 2,3-BPG</li>
      </ul>
      <div class="ans-box" id="ans-2">
        <div class="ans-correct">✓ Correct Answer: (B)</div>
        <div class="ans-exp">Right shift = decreased Hb-O₂ affinity = O₂ released to tissues. Right shift caused by: ↑CO₂, ↑H⁺ (↓pH), ↑temperature, ↑2,3-BPG. During intense exercise, ALL four factors are elevated in working muscles simultaneously — maximising O₂ delivery exactly where needed.</div>
        <div class="ans-trick">⚡ Trick: CHAT = CO₂ High, Acid (H⁺ High), Temperature High, 2,3-BPG High → RIGHT shift</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(2, 1)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-2">Not attempted</span>
    </div>
  </div>

  <!-- Q3 -->
  <div class="q-card" id="qcard-3">
    <div class="q-header">
      <span class="q-num">Q3</span>
      <span class="q-topic">Genetics — Dihybrid Test Cross</span>
    </div>
    <div class="q-body">
      <div class="q-text">In pea plants, Tall (T) is dominant over Dwarf (t), and Round seed (R) is dominant over Wrinkled (r). A plant heterozygous for both traits (TtRr) is test-crossed. What fraction of offspring will be TALL with WRINKLED seeds?</div>
      <ul class="options" id="opts-3">
        <li onclick="select_opt(3,0)">A) 9/16</li>
        <li onclick="select_opt(3,1)">B) 1/4</li>
        <li onclick="select_opt(3,2)">C) 3/16</li>
        <li onclick="select_opt(3,3)">D) 1/2</li>
      </ul>
      <div class="ans-box" id="ans-3">
        <div class="ans-correct">✓ Correct Answer: (B) 1/4</div>
        <div class="ans-exp">Test cross = TtRr × ttrr. Gametes from TtRr: TR, Tr, tR, tr (each 1/4). Gametes from ttrr: only tr. Offspring: TtRr : Ttrr : ttRr : ttrr = 1:1:1:1. Tall + Wrinkled = Ttrr = 1/4 of offspring.</div>
        <div class="ans-trick">⚡ Trick: Test cross of dihybrid ALWAYS gives 1:1:1:1 → each phenotypic class = 1/4</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(3, 1)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-3">Not attempted</span>
    </div>
  </div>

  <!-- Q4 -->
  <div class="q-card" id="qcard-4">
    <div class="q-header">
      <span class="q-num">Q4</span>
      <span class="q-topic">Molecular Biology — DNA Replication Enzymes</span>
    </div>
    <div class="q-body">
      <div class="q-text">During DNA replication, Okazaki fragments are eventually joined into a continuous strand. Which sequence of enzymatic steps correctly describes this process?</div>
      <ul class="options" id="opts-4">
        <li onclick="select_opt(4,0)">A) DNA Pol III extends fragment → DNA Pol I removes primer & fills gap → Ligase joins nicks</li>
        <li onclick="select_opt(4,1)">B) Primase removes primer → DNA Pol III fills gap → Helicase joins nicks</li>
        <li onclick="select_opt(4,2)">C) DNA Pol I extends fragment → DNA Pol III removes primer → Ligase joins</li>
        <li onclick="select_opt(4,3)">D) Helicase removes primer → SSB proteins fill gap → Ligase joins</li>
      </ul>
      <div class="ans-box" id="ans-4">
        <div class="ans-correct">✓ Correct Answer: (A)</div>
        <div class="ans-exp">On lagging strand: (1) DNA Pol III synthesises Okazaki fragment up to the RNA primer of previous fragment. (2) DNA Pol I uses 5'→3' exonuclease to remove RNA primer while filling gap with DNA (nick translation). (3) DNA Ligase seals the remaining nick — joins fragments with phosphodiester bond.</div>
        <div class="ans-trick">⚡ Trick: Pol III = builder. Pol I = demolish primer + rebuild with DNA. Ligase = glue/sealer.</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(4, 0)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-4">Not attempted</span>
    </div>
  </div>

  <!-- Q5 -->
  <div class="q-card" id="qcard-5">
    <div class="q-header">
      <span class="q-num">Q5</span>
      <span class="q-topic">Plant Physiology — C4 Photosynthesis</span>
    </div>
    <div class="q-body">
      <div class="q-text">Sugarcane (C4 plant) has a competitive advantage over wheat (C3 plant) in hot, sunny conditions primarily because:</div>
      <ul class="options" id="opts-5">
        <li onclick="select_opt(5,0)">A) Sugarcane has more chlorophyll and absorbs more light</li>
        <li onclick="select_opt(5,1)">B) PEP carboxylase in mesophyll cells has much higher affinity for CO₂ than RuBisCO, suppressing photorespiration</li>
        <li onclick="select_opt(5,2)">C) Sugarcane undergoes both C3 and C4 cycles simultaneously in the same cell</li>
        <li onclick="select_opt(5,3)">D) Bundle sheath cells in sugarcane lack RuBisCO, performing only light reactions</li>
      </ul>
      <div class="ans-box" id="ans-5">
        <div class="ans-correct">✓ Correct Answer: (B)</div>
        <div class="ans-exp">In hot conditions, stomata close → internal CO₂ drops. In C3 plants, RuBisCO fixes O₂ instead of CO₂ (photorespiration = wasteful). C4 plants use PEP carboxylase in mesophyll — ~60× higher affinity for CO₂ than RuBisCO, does NOT fix O₂. It concentrates CO₂ in bundle sheath cells → suppresses photorespiration entirely.</div>
        <div class="ans-trick">⚡ Trick: PEP carboxylase = super-selective CO₂ pump. C4 = CO₂ Concentrating Mechanism (CCM)</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(5, 1)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-5">Not attempted</span>
    </div>
  </div>

  <!-- Q6 -->
  <div class="q-card" id="qcard-6">
    <div class="q-header">
      <span class="q-num">Q6</span>
      <span class="q-topic">Ecology — Logistic Population Growth</span>
    </div>
    <div class="q-body">
      <div class="q-text">A population has an intrinsic rate of increase r = 0.5/hour and carrying capacity K = 10,000. At what population size (N) is the instantaneous growth rate (dN/dt) at its MAXIMUM?</div>
      <ul class="options" id="opts-6">
        <li onclick="select_opt(6,0)">A) N = 10,000</li>
        <li onclick="select_opt(6,1)">B) N = 2,500</li>
        <li onclick="select_opt(6,2)">C) N = 5,000</li>
        <li onclick="select_opt(6,3)">D) N = 7,500</li>
      </ul>
      <div class="ans-box" id="ans-6">
        <div class="ans-correct">✓ Correct Answer: (C) N = 5,000</div>
        <div class="ans-exp">Formula: dN/dt = rN(K−N)/K. Differentiating with respect to N and setting = 0 gives N = K/2 = 10,000/2 = 5,000. At N = K/2, maximum growth rate = rK/4 = 0.5 × 10,000/4 = 1,250 cells/hour. At N = K, growth rate = 0 (population at equilibrium).</div>
        <div class="ans-trick">⚡ Formula: Max dN/dt ALWAYS at N = K/2. This appears EVERY year in IAT!</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(6, 2)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-6">Not attempted</span>
    </div>
  </div>

  <!-- Q7 -->
  <div class="q-card" id="qcard-7">
    <div class="q-header">
      <span class="q-num">Q7</span>
      <span class="q-topic">Reproduction — Double Fertilization Ploidy</span>
    </div>
    <div class="q-body">
      <div class="q-text">In a cross between Plant A (2n = 16, female) × Plant B (2n = 24, male), what will be the chromosome number in the ENDOSPERM of the resulting seed?</div>
      <ul class="options" id="opts-7">
        <li onclick="select_opt(7,0)">A) 20 chromosomes</li>
        <li onclick="select_opt(7,1)">B) 28 chromosomes</li>
        <li onclick="select_opt(7,2)">C) 24 chromosomes</li>
        <li onclick="select_opt(7,3)">D) 32 chromosomes</li>
      </ul>
      <div class="ans-box" id="ans-7">
        <div class="ans-correct">✓ Correct Answer: (B) 28 chromosomes</div>
        <div class="ans-exp">Endosperm = triple fusion: 2 polar nuclei (from female) + 1 sperm (from male). Plant A (2n=16): n = 8. Two polar nuclei = 8+8 = 16. Plant B (2n=24): n = 12. One sperm = 12. Endosperm = 16 + 12 = 28 chromosomes. [Embryo = 8+12 = 20; Seed coat = 16 (maternal only)]</div>
        <div class="ans-trick">⚡ Formula: Endosperm = n(♀) + n(♀) + n(♂) = 2×n♀ + n♂</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(7, 1)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-7">Not attempted</span>
    </div>
  </div>

  <!-- Q8 -->
  <div class="q-card" id="qcard-8">
    <div class="q-header">
      <span class="q-num">Q8</span>
      <span class="q-topic">Biotechnology — PCR Amplification</span>
    </div>
    <div class="q-body">
      <div class="q-text">A forensic scientist amplifies a DNA sequence from a crime scene sample. After 30 cycles of PCR starting from 1 copy, approximately how many copies will be present?</div>
      <ul class="options" id="opts-8">
        <li onclick="select_opt(8,0)">A) 30 copies</li>
        <li onclick="select_opt(8,1)">B) 900 copies</li>
        <li onclick="select_opt(8,2)">C) ~10⁶ copies</li>
        <li onclick="select_opt(8,3)">D) ~10⁹ copies</li>
      </ul>
      <div class="ans-box" id="ans-8">
        <div class="ans-correct">✓ Correct Answer: (D) ~10⁹ copies</div>
        <div class="ans-exp">PCR amplification is exponential: after n cycles, 1 template gives 2ⁿ copies. After 30 cycles: 2³⁰ = 1,073,741,824 ≈ 10⁹ copies. This massive amplification from a single molecule is why PCR is used in forensics, COVID diagnosis, and genetic research.</div>
        <div class="ans-trick">⚡ Formula: copies = 2ⁿ. Shortcut: 2¹⁰ ≈ 10³, so 2³⁰ = (2¹⁰)³ ≈ (10³)³ = 10⁹</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(8, 3)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-8">Not attempted</span>
    </div>
  </div>

  <!-- Q9 -->
  <div class="q-card" id="qcard-9">
    <div class="q-header">
      <span class="q-num">Q9</span>
      <span class="q-topic">Cell Biology — p53 Tumour Suppressor</span>
    </div>
    <div class="q-body">
      <div class="q-text">A mutation that INACTIVATES the p53 tumour suppressor gene contributes to cancer development. Which mechanism best explains this?</div>
      <ul class="options" id="opts-9">
        <li onclick="select_opt(9,0)">A) p53 normally stimulates cell division; its loss slows division</li>
        <li onclick="select_opt(9,1)">B) p53 normally detects DNA damage and triggers cell cycle arrest or apoptosis; its loss allows damaged cells to proliferate</li>
        <li onclick="select_opt(9,2)">C) p53 is a proto-oncogene; mutation converts it to an oncogene</li>
        <li onclick="select_opt(9,3)">D) p53 activates telomerase; its inactivation shortens telomeres causing instability</li>
      </ul>
      <div class="ans-box" id="ans-9">
        <div class="ans-correct">✓ Correct Answer: (B)</div>
        <div class="ans-exp">p53 is the "guardian of the genome" — a tumour SUPPRESSOR. When DNA is damaged, p53: (1) arrests cell cycle at G1/S checkpoint (activates p21 which inhibits CDK), giving time for repair; OR (2) if damage irreparable, triggers apoptosis. Without p53, cells with mutations skip checkpoint → accumulate more mutations → cancer.</div>
        <div class="ans-trick">⚡ Trick: p53 = brake pedal of cell division. Broken brake = runaway car = cancer</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(9, 1)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-9">Not attempted</span>
    </div>
  </div>

  <!-- Q10 -->
  <div class="q-card" id="qcard-10">
    <div class="q-header">
      <span class="q-num">Q10</span>
      <span class="q-topic">Molecular Biology — Lac Operon Mutation</span>
    </div>
    <div class="q-body">
      <div class="q-text">A mutation in the lacI gene produces a repressor protein that CANNOT bind allolactose (the inducer). What would be the phenotype of this E. coli mutant?</div>
      <ul class="options" id="opts-10">
        <li onclick="select_opt(10,0)">A) Constitutive expression — lac genes always ON even without lactose</li>
        <li onclick="select_opt(10,1)">B) Lac genes permanently OFF — cannot be induced even when lactose is present</li>
        <li onclick="select_opt(10,2)">C) Normal regulation — lactose still induces transcription</li>
        <li onclick="select_opt(10,3)">D) Overproduction of allolactose causes cell toxicity</li>
      </ul>
      <div class="ans-box" id="ans-10">
        <div class="ans-correct">✓ Correct Answer: (B)</div>
        <div class="ans-exp">Normal: Allolactose binds repressor → repressor releases operator → lac genes ON. If repressor CANNOT bind allolactose (inducer), it remains permanently bound to operator even when lactose IS present → structural genes (lacZ, lacY, lacA) permanently OFF. Called "super-repressor" or lacIˢ mutation.</div>
        <div class="ans-trick">⚡ Trick: Repressor that ignores inducer = super-repressor = always blocks = permanently OFF</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(10, 1)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-10">Not attempted</span>
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  <!-- Q11 -->
  <div class="q-card" id="qcard-11">
    <div class="q-header">
      <span class="q-num">Q11</span>
      <span class="q-topic">Human Physiology — Thyroid & Negative Feedback</span>
    </div>
    <div class="q-body">
      <div class="q-text">A patient has: goitre (enlarged thyroid), LOW T3/T4 levels, and HIGH TSH. What is the most likely diagnosis?</div>
      <ul class="options" id="opts-11">
        <li onclick="select_opt(11,0)">A) Hyperthyroidism — thyroid over-secretes T3/T4 despite feedback</li>
        <li onclick="select_opt(11,1)">B) Primary hypothyroidism — damaged thyroid fails to produce T3/T4; pituitary keeps secreting TSH in compensation</li>
        <li onclick="select_opt(11,2)">C) Hypopituitarism — low TSH causes low T3/T4 and compensatory thyroid enlargement</li>
        <li onclick="select_opt(11,3)">D) Cushing's syndrome — excess cortisol suppresses T3/T4 production</li>
      </ul>
      <div class="ans-box" id="ans-11">
        <div class="ans-correct">✓ Correct Answer: (B)</div>
        <div class="ans-exp">Negative feedback axis: Hypothalamus→TRH→Pituitary→TSH→Thyroid→T3/T4→inhibits pituitary. If thyroid is damaged (Primary hypothyroidism), T3/T4 are LOW → cannot inhibit pituitary → TSH rises enormously. High TSH constantly stimulates thyroid → goitre (hypertrophy). Pattern: HIGH TSH + LOW T3/T4 + goitre = Primary Hypothyroidism.</div>
        <div class="ans-trick">⚡ Rule: Low T3/T4 + HIGH TSH = PRIMARY hypothyroid. Low T3/T4 + LOW TSH = pituitary problem (secondary).</div>
      </div>
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    <div class="q-header">
      <span class="q-num">Q12</span>
      <span class="q-topic">Evolution — Hardy-Weinberg Equilibrium</span>
    </div>
    <div class="q-body">
      <div class="q-text">In a population of 1000 individuals, 360 show the recessive phenotype (aa). Assuming Hardy-Weinberg equilibrium, what is the frequency of HETEROZYGOUS (Aa) individuals?</div>
      <ul class="options" id="opts-12">
        <li onclick="select_opt(12,0)">A) 0.36</li>
        <li onclick="select_opt(12,1)">B) 0.40</li>
        <li onclick="select_opt(12,2)">C) 0.48</li>
        <li onclick="select_opt(12,3)">D) 0.60</li>
      </ul>
      <div class="ans-box" id="ans-12">
        <div class="ans-correct">✓ Correct Answer: (C) 0.48</div>
        <div class="ans-exp">Step 1: q² = 360/1000 = 0.36. Step 2: q = √0.36 = 0.6. Step 3: p = 1 − q = 0.4. Step 4: Frequency of Aa = 2pq = 2 × 0.4 × 0.6 = 0.48. Number of heterozygotes = 0.48 × 1000 = 480 individuals.</div>
        <div class="ans-trick">⚡ Always: Find q from q² first (recessive phenotype) → then p = 1−q → then 2pq for heterozygotes.</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(12, 2)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-12">Not attempted</span>
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  <!-- Q13 -->
  <div class="q-card" id="qcard-13">
    <div class="q-header">
      <span class="q-num">Q13</span>
      <span class="q-topic">Ecology — Biotic Interactions</span>
    </div>
    <div class="q-body">
      <div class="q-text">Mycorrhizal fungi live in roots of most terrestrial plants. The fungus receives sugars from the plant; the plant gains enhanced water and phosphorus absorption. This relationship is:</div>
      <ul class="options" id="opts-13">
        <li onclick="select_opt(13,0)">A) Parasitism — fungus harms the plant by consuming sugars</li>
        <li onclick="select_opt(13,1)">B) Commensalism — only the fungus benefits, plant is unaffected</li>
        <li onclick="select_opt(13,2)">C) Mutualism — both organisms benefit from the association</li>
        <li onclick="select_opt(13,3)">D) Amensalism — fungus inhibits competing root organisms, plant unaffected</li>
      </ul>
      <div class="ans-box" id="ans-13">
        <div class="ans-correct">✓ Correct Answer: (C) Mutualism</div>
        <div class="ans-exp">Mutualism (+/+): Both species benefit. Fungus gets photosynthate (sugars) from plant. Plant gets dramatically enhanced nutrient and water uptake via extensive hyphal network (much larger surface area than roots alone). Over 80% of land plants have mycorrhizal associations. The plant's fitness increases — so it is NOT parasitism.</div>
        <div class="ans-trick">⚡ Other mutualism: Rhizobium-legume, cleaner fish-shark, lichen (algae+fungus), bee-flower</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(13, 2)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-13">Not attempted</span>
    </div>
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  <!-- Q14 -->
  <div class="q-card" id="qcard-14">
    <div class="q-header">
      <span class="q-num">Q14</span>
      <span class="q-topic">Reproduction — Menstrual Cycle & Ovulation</span>
    </div>
    <div class="q-body">
      <div class="q-text">On Day 14 of a 28-day menstrual cycle, a sharp surge in which hormone directly TRIGGERS ovulation?</div>
      <ul class="options" id="opts-14">
        <li onclick="select_opt(14,0)">A) FSH (Follicle Stimulating Hormone)</li>
        <li onclick="select_opt(14,1)">B) Progesterone</li>
        <li onclick="select_opt(14,2)">C) LH (Luteinising Hormone)</li>
        <li onclick="select_opt(14,3)">D) Estrogen</li>
      </ul>
      <div class="ans-box" id="ans-14">
        <div class="ans-correct">✓ Correct Answer: (C) LH</div>
        <div class="ans-exp">The LH surge (mid-cycle spike from anterior pituitary) is the direct trigger for ovulation. Mechanism: Rising estrogen from Graafian follicle causes POSITIVE feedback → LH surge → follicle ruptures → secondary oocyte released. After ovulation, LH causes ruptured follicle to become corpus luteum (secretes progesterone).</div>
        <div class="ans-trick">⚡ Sequence: FSH grows follicle → Estrogen → LH SURGE → OVULATION → Corpus luteum → Progesterone</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(14, 2)">Check Answer</button>
      <span class="mark-badge mark-skip" id="mark-14">Not attempted</span>
    </div>
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  <!-- Q15 -->
  <div class="q-card" id="qcard-15">
    <div class="q-header">
      <span class="q-num">Q15</span>
      <span class="q-topic">Cell Biology — Endosymbiotic Theory</span>
    </div>
    <div class="q-body">
      <div class="q-text">Mitochondria and chloroplasts share several features that support the endosymbiotic theory. Which feature is common to BOTH organelles?</div>
      <ul class="options" id="opts-15">
        <li onclick="select_opt(15,0)">A) Both contain circular DNA, 70S ribosomes, and are bounded by a double membrane</li>
        <li onclick="select_opt(15,1)">B) Both contain thylakoids and carry out photophosphorylation</li>
        <li onclick="select_opt(15,2)">C) Both are found only in plant cells and use the Calvin cycle</li>
        <li onclick="select_opt(15,3)">D) Both contain cristae and produce ATP only by substrate-level phosphorylation</li>
      </ul>
      <div class="ans-box" id="ans-15">
        <div class="ans-correct">✓ Correct Answer: (A)</div>
        <div class="ans-exp">Endosymbiotic theory (Lynn Margulis): Both were once free-living prokaryotes. Evidence — BOTH share: (1) Circular DNA (like bacteria), (2) 70S ribosomes (prokaryotic, vs 80S in cytoplasm), (3) Double membrane (inner from original bacterium, outer from host cell's phagosome), (4) Binary fission-like division. Thylakoids are ONLY in chloroplasts; cristae are ONLY in mitochondria.</div>
        <div class="ans-trick">⚡ Mito + Chloro = circular DNA + 70S ribosomes + double membrane = endosymbiont evidence</div>
      </div>
    </div>
    <div class="q-footer">
      <button class="btn-check" onclick="check_ans(15, 0)">Check Answer</button>
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  <!-- Quick Cheat Sheet Accordion -->
  <div class="cheat-section">
    <div class="sec-hdr" style="margin-top:40px">📚 Quick Revision — Key Formulas & Tricks (Tap to expand)</div>

    <div class="cheat-card">
      <div class="cheat-hdr" style="background:#1D4E89" onclick="toggle_cheat(this)">
        🧪 Ecology Formulas <span>▼</span>
      </div>
      <div class="cheat-body">
        <div class="formula-box">dN/dt = rN(K−N)/K &nbsp;|&nbsp; Max growth at N = K/2 &nbsp;|&nbsp; At N=K → dN/dt = 0</div>
        <div class="formula-box">Exponential: dN/dt = rN &nbsp;|&nbsp; N(t) = N₀ × e^(rt)</div>
        <div class="formula-box">10% Energy Rule: Only 10% energy transferred to next trophic level</div>
        <table class="ref">
          <tr><th>Interaction</th><th>Symbol</th><th>Example</th></tr>
          <tr><td>Mutualism</td><td>+/+</td><td>Mycorrhizae, Rhizobium, Lichen</td></tr>
          <tr><td>Commensalism</td><td>+/0</td><td>Epiphytes (orchid on tree), Barnacles on whale</td></tr>
          <tr><td>Parasitism</td><td>+/−</td><td>Plasmodium-human, Cuscuta-host</td></tr>
          <tr><td>Predation</td><td>+/−</td><td>Lion-zebra, insectivorous plants</td></tr>
          <tr><td>Competition</td><td>−/−</td><td>Interspecific competition</td></tr>
          <tr><td>Amensalism</td><td>0/−</td><td>Penicillin kills bacteria</td></tr>
        </table>
      </div>
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    <div class="cheat-card">
      <div class="cheat-hdr" style="background:#2D6A4F" onclick="toggle_cheat(this)">
        🌿 Plant Physiology Tricks <span>▼</span>
      </div>
      <div class="cheat-body">
        <table class="ref">
          <tr><th>Feature</th><th>C3 Plants</th><th>C4 Plants</th></tr>
          <tr><td>First product</td><td>3-PGA</td><td>OAA (Oxaloacetate)</td></tr>
          <tr><td>CO₂ fixation enzyme</td><td>RuBisCO</td><td>PEP Carboxylase</td></tr>
          <tr><td>Calvin cycle site</td><td>Mesophyll</td><td>Bundle sheath</td></tr>
          <tr><td>Kranz anatomy</td><td>Absent</td><td>Present</td></tr>
          <tr><td>Examples</td><td>Wheat, Rice</td><td>Maize, Sugarcane</td></tr>
        </table>
        <div class="formula-box">Plant Hormones: Auxin=elongation | Gibberellin=stem/germination | Cytokinin=division | Ethylene=ripening | ABA=stress/closure</div>
      </div>
    </div>

    <div class="cheat-card">
      <div class="cheat-hdr" style="background:#6A3D9A" onclick="toggle_cheat(this)">
        🧬 Genetics Formulas <span>▼</span>
      </div>
      <div class="cheat-body">
        <div class="formula-box">Hardy-Weinberg: p + q = 1 &nbsp;|&nbsp; p² + 2pq + q² = 1</div>
        <div class="formula-box">Probability of genotype: P(AABBcc) = P(AA)×P(BB)×P(cc) = 1/4×1/4×1/4 = 1/64</div>
        <table class="ref">
          <tr><th>Cross</th><th>Phenotype Ratio</th></tr>
          <tr><td>Aa × Aa (monohybrid)</td><td>3:1</td></tr>
          <tr><td>AaBb × AaBb (dihybrid)</td><td>9:3:3:1</td></tr>
          <tr><td>Aa × aa (test cross)</td><td>1:1</td></tr>
          <tr><td>AaBb × aabb (test cross)</td><td>1:1:1:1</td></tr>
          <tr><td>Incomplete dominance Rr × Rr</td><td>1:2:1</td></tr>
        </table>
      </div>
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    <div class="cheat-card">
      <div class="cheat-hdr" style="background:#E63946" onclick="toggle_cheat(this)">
        ❤️ Human Physiology Quick Reference <span>▼</span>
      </div>
      <div class="cheat-body">
        <div class="formula-box">Bohr Effect: CO₂↑ / H⁺↑ / Temp↑ / 2,3-BPG↑ → RIGHT shift → O₂ released (tissues)</div>
        <div class="formula-box">Nephron: PCT=all glucose | Loop=concentrate | DCT=aldosterone | CD=ADH</div>
        <table class="ref">
          <tr><th>Hormone</th><th>Source</th><th>Function</th></tr>
          <tr><td>Insulin</td><td>Beta cells (Pancreas)</td><td>Lowers blood glucose</td></tr>
          <tr><td>Glucagon</td><td>Alpha cells (Pancreas)</td><td>Raises blood glucose</td></tr>
          <tr><td>ADH</td><td>Post. Pituitary</td><td>Water retention (CD)</td></tr>
          <tr><td>LH</td><td>Ant. Pituitary</td><td>Ovulation trigger</td></tr>
          <tr><td>FSH</td><td>Ant. Pituitary</td><td>Follicle dev / spermatogenesis</td></tr>
          <tr><td>Aldosterone</td><td>Adrenal Cortex</td><td>Na⁺ retention, BP↑</td></tr>
        </table>
      </div>
    </div>

    <div class="cheat-card">
      <div class="cheat-hdr" style="background:#F4A261; color:#1a1a2e" onclick="toggle_cheat(this)">
        🔬 Reproduction & Biotechnology <span>▼</span>
      </div>
      <div class="cheat-body">
        <div class="formula-box">Double Fertilization: Embryo = n♀ + n♂ &nbsp;|&nbsp; Endosperm = 2n♀ + n♂ &nbsp;|&nbsp; Seed coat = 2n (maternal)</div>
        <div class="formula-box">PCR: Denature 94°C → Anneal 50-65°C → Extend 72°C (Taq pol) | Copies = 2ⁿ</div>
        <table class="ref">
          <tr><th>Menstrual Cycle</th><th>Phase/Day</th><th>Key Event</th></tr>
          <tr><td>Menstruation</td><td>Day 1-5</td><td>Estrogen + Progesterone drop → shedding</td></tr>
          <tr><td>Follicular</td><td>Day 1-13</td><td>FSH → follicle grows → Estrogen rises</td></tr>
          <tr><td>Ovulation</td><td>Day 14</td><td>LH SURGE → follicle ruptures</td></tr>
          <tr><td>Luteal</td><td>Day 15-28</td><td>Corpus luteum → Progesterone</td></tr>
        </table>
      </div>
    </div>

  </div><!-- end cheat-section -->
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