SUCRALFATE - Mechanism of Mucosal Cytoprotection & Antacid Interaction

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

OUTPUT = "/home/daytona/workspace/mbbs-study-pdf/MBBS_PYQ_High_Yield_Study_Guide.pdf"

# ─── Colour Palette ───────────────────────────────────────────────
DARK_BLUE   = colors.HexColor("#1a3a5c")
MED_BLUE    = colors.HexColor("#2563EB")
LIGHT_BLUE  = colors.HexColor("#DBEAFE")
RED         = colors.HexColor("#DC2626")
LIGHT_RED   = colors.HexColor("#FEE2E2")
ORANGE      = colors.HexColor("#D97706")
LIGHT_ORANGE= colors.HexColor("#FEF3C7")
GREEN       = colors.HexColor("#16A34A")
LIGHT_GREEN = colors.HexColor("#DCFCE7")
YELLOW      = colors.HexColor("#CA8A04")
LIGHT_YELLOW= colors.HexColor("#FEF9C3")
GREY        = colors.HexColor("#374151")
LIGHT_GREY  = colors.HexColor("#F3F4F6")
MID_GREY    = colors.HexColor("#9CA3AF")
WHITE       = colors.white
BLACK       = colors.black
TEAL        = colors.HexColor("#0D9488")
LIGHT_TEAL  = colors.HexColor("#CCFBF1")
PURPLE      = colors.HexColor("#7C3AED")
LIGHT_PURPLE= colors.HexColor("#EDE9FE")

# ─── Page Setup ───────────────────────────────────────────────────
PAGE_W, PAGE_H = A4
MARGIN = 18 * mm

def build_doc():
    doc = SimpleDocTemplate(
        OUTPUT,
        pagesize=A4,
        leftMargin=MARGIN, rightMargin=MARGIN,
        topMargin=MARGIN,  bottomMargin=15*mm,
        title="MBBS PYQ High-Yield Study Guide 2026",
        author="Orris AI — Senior Examiner Analysis"
    )

    styles = getSampleStyleSheet()

    # ── Custom Styles ──────────────────────────────────────────────
    def S(name, **kw):
        return ParagraphStyle(name, **kw)

    cover_title = S("CoverTitle", fontSize=26, leading=32,
                    textColor=WHITE, alignment=TA_CENTER, fontName="Helvetica-Bold")
    cover_sub   = S("CoverSub",   fontSize=14, leading=20,
                    textColor=colors.HexColor("#BFDBFE"), alignment=TA_CENTER, fontName="Helvetica")
    cover_info  = S("CoverInfo",  fontSize=10, leading=14,
                    textColor=colors.HexColor("#93C5FD"), alignment=TA_CENTER, fontName="Helvetica")

    h1 = S("H1", fontSize=16, leading=20, textColor=WHITE,
           fontName="Helvetica-Bold", alignment=TA_LEFT,
           spaceBefore=6, spaceAfter=4)
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    h3 = S("H3", fontSize=11, leading=15, textColor=MED_BLUE,
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    h4 = S("H4", fontSize=10, leading=13, textColor=GREY,
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    body= S("Body", fontSize=9, leading=13, textColor=GREY,
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    bold= S("Bold", fontSize=9, leading=13, textColor=BLACK,
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    qtxt= S("QTxt", fontSize=9.5, leading=14, textColor=GREY,
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    option  = S("Option",  fontSize=9, leading=13, textColor=GREY,
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    tip_style = S("Tip", fontSize=9, leading=13, textColor=colors.HexColor("#1D4ED8"),
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    center_bold = S("CB", fontSize=10, leading=14, textColor=DARK_BLUE,
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    story = []

    # ═══════════════════════════════════════════════════════════════
    # COVER PAGE
    # ═══════════════════════════════════════════════════════════════
    cover_data = [[
        Paragraph("🎓 II MBBS UNIVERSITY EXAM", cover_sub),
        Paragraph("HIGH-YIELD STUDY GUIDE", cover_title),
        Paragraph("30-Year PYQ Analysis + Predicted Question Papers", cover_sub),
        Paragraph("Pathology Paper I  •  Pharmacology Paper I", cover_sub),
        Spacer(1, 8*mm),
        Paragraph("Prepared by Orris AI Senior Examiner Analysis", cover_info),
        Paragraph(f"Generated: {datetime.date.today().strftime('%B %d, %Y')}  |  NMC/MCI Pattern  |  All Indian Universities", cover_info),
    ]]
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        ("RIGHTPADDING",  (0,0), (-1,-1), 18),
        ("ROUNDEDCORNERS", (0,0), (-1,-1), [8,8,8,8]),
    ]))
    story.append(cover_tbl)
    story.append(Spacer(1, 8*mm))

    # Exam format box
    fmt_data = [
        [Paragraph("<b>EXAM FORMAT</b>", S("ef", fontSize=11, leading=14, textColor=DARK_BLUE, fontName="Helvetica-Bold", alignment=TA_CENTER))],
        [Table([
            [Paragraph("<b>Section</b>", bold), Paragraph("<b>Type</b>", bold),
             Paragraph("<b>Count</b>", bold), Paragraph("<b>Marks</b>", bold),
             Paragraph("<b>Total</b>", bold)],
            [Paragraph("LEQ", body), Paragraph("Long Essay", body),
             Paragraph("1 (choose 1/2)", body), Paragraph("10", body), Paragraph("10", body)],
            [Paragraph("SEQ", body), Paragraph("Short Essay", body),
             Paragraph("14 (choose 10)", body), Paragraph("5", body), Paragraph("70", body)],
            [Paragraph("SN", body), Paragraph("Short Notes", body),
             Paragraph("5", body), Paragraph("3", body), Paragraph("15", body)],
            [Paragraph("MCQ", body), Paragraph("Multiple Choice", body),
             Paragraph("20", body), Paragraph("1", body), Paragraph("20", body)],
            [Paragraph("<b>TOTAL</b>", bold), Paragraph("", body),
             Paragraph("", body), Paragraph("", body), Paragraph("<b>100</b>", bold)],
        ], colWidths=[30*mm, 50*mm, 40*mm, 22*mm, 22*mm],
        style=TableStyle([
            ("BACKGROUND", (0,0), (-1,0), LIGHT_BLUE),
            ("BACKGROUND", (0,5), (-1,5), LIGHT_BLUE),
            ("ROWBACKGROUNDS", (0,1), (-1,4), [WHITE, LIGHT_GREY]),
            ("GRID", (0,0), (-1,-1), 0.4, colors.HexColor("#CBD5E1")),
            ("FONTNAME", (0,0), (-1,0), "Helvetica-Bold"),
            ("ALIGN", (0,0), (-1,-1), "CENTER"),
            ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
            ("TOPPADDING", (0,0), (-1,-1), 4),
            ("BOTTOMPADDING", (0,0), (-1,-1), 4),
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    ]
    fmt_tbl = Table(fmt_data, colWidths=[PAGE_W - 2*MARGIN])
    fmt_tbl.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,0), LIGHT_BLUE),
        ("TOPPADDING",    (0,0), (-1,-1), 6),
        ("BOTTOMPADDING", (0,0), (-1,-1), 6),
        ("LEFTPADDING",   (0,0), (-1,-1), 10),
        ("RIGHTPADDING",  (0,0), (-1,-1), 10),
        ("BOX", (0,0), (-1,-1), 1, MED_BLUE),
    ]))
    story.append(fmt_tbl)
    story.append(PageBreak())

    # ═══════════════════════════════════════════════════════════════
    # TABLE OF CONTENTS
    # ═══════════════════════════════════════════════════════════════
    def section_header(text, bg=DARK_BLUE, fg=WHITE):
        t = Table([[Paragraph(text, h1)]], colWidths=[PAGE_W - 2*MARGIN])
        t.setStyle(TableStyle([
            ("BACKGROUND", (0,0), (-1,-1), bg),
            ("TOPPADDING",    (0,0), (-1,-1), 8),
            ("BOTTOMPADDING", (0,0), (-1,-1), 8),
            ("LEFTPADDING",   (0,0), (-1,-1), 12),
            ("RIGHTPADDING",  (0,0), (-1,-1), 12),
        ]))
        return t

    def colored_box(text, bg, fg=DARK_BLUE, pad=5):
        t = Table([[Paragraph(text, S("cb", fontSize=9, leading=13, textColor=fg,
                                       fontName="Helvetica-Bold"))]],
                  colWidths=[PAGE_W - 2*MARGIN])
        t.setStyle(TableStyle([
            ("BACKGROUND", (0,0), (-1,-1), bg),
            ("TOPPADDING",    (0,0), (-1,-1), pad),
            ("BOTTOMPADDING", (0,0), (-1,-1), pad),
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            ("RIGHTPADDING",  (0,0), (-1,-1), 10),
            ("BOX", (0,0), (-1,-1), 0.5, MID_GREY),
        ]))
        return t

    story.append(section_header("📋  TABLE OF CONTENTS"))
    story.append(Spacer(1, 4*mm))

    toc_items = [
        ("PART 1", "PATHOLOGY PAPER I — High-Yield Topic Map", "3"),
        ("", "  30-Year Frequency Analysis (General Pathology + Haematology)", "3"),
        ("", "  Top 25 Topics with Category Ratings", "3"),
        ("", "  Decadal Trend Analysis (1994–2024)", "4"),
        ("PART 2", "PATHOLOGY — Predicted Model Question Paper", "5"),
        ("", "  Section A: 20 MCQs with Answers", "5"),
        ("", "  Section B: General Pathology (LEQ + SEQ + SN)", "6"),
        ("", "  Section C: Haematology (LEQ + SEQ + SN)", "7"),
        ("PART 3", "PATHOLOGY — Last-Minute Revision Priority List", "8"),
        ("", "  48-Hour Blitz Topics", "8"),
        ("", "  Key Comparison Tables", "8"),
        ("", "  MCQ Goldmine — Must-Know Facts", "9"),
        ("PART 4", "PHARMACOLOGY PAPER I — High-Yield Topic Map", "10"),
        ("", "  30-Year Frequency Analysis (Gen Pharm + ANS + CVS + GIT + Resp)", "10"),
        ("", "  Top 25 Topics with Category Ratings", "10"),
        ("PART 5", "PHARMACOLOGY — Predicted Model Question Paper", "12"),
        ("", "  Section A: 20 MCQs with Answers", "12"),
        ("", "  Section B: SEQ + SN + LEQ", "13"),
        ("PART 6", "PHARMACOLOGY — Last-Minute Revision Priority List", "14"),
        ("", "  Sure-Shot 15 Topics", "14"),
        ("", "  DOC Lists + Comparison Tables", "14"),
        ("PART 7", "10-Day Revision Timetable (Both Subjects)", "15"),
        ("PART 8", "Examiner's Strategic Tips & Diagram Checklist", "15"),
    ]
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            Paragraph(page, S("tpg", fontSize=9, leading=13,
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        ]
        row_tbl = Table([row_data], colWidths=[18*mm, 130*mm, 16*mm])
        row_tbl.setStyle(TableStyle([
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            ("LINEBELOW", (0,0), (-1,-1), 0.3, colors.HexColor("#E5E7EB")),
        ]))
        story.append(row_tbl)

    story.append(PageBreak())

    # ═══════════════════════════════════════════════════════════════
    # PART 1 — PATHOLOGY HIGH-YIELD TOPIC MAP
    # ═══════════════════════════════════════════════════════════════
    story.append(section_header("PART 1 — PATHOLOGY PAPER I: HIGH-YIELD TOPIC MAP", bg=colors.HexColor("#1e3a5f")))
    story.append(Spacer(1, 3*mm))
    story.append(Paragraph("General Pathology + Haematology  |  30-Year PYQ Analysis (1994–2024)  |  NMC/MCI Pattern", note))
    story.append(Spacer(1, 3*mm))

    # Legend
    legend = Table([
        [colored_box("🔴  MUST KNOW — Asked almost every year (20–30/30)", LIGHT_RED, RED),
         colored_box("🟠  HIGH YIELD — Asked 10–20/30 years", LIGHT_ORANGE, ORANGE),
         colored_box("🟡  MODERATE — Asked 5–10/30 years", LIGHT_YELLOW, YELLOW)]
    ], colWidths=[(PAGE_W-2*MARGIN)/3]*3, hAlign="LEFT")
    legend.setStyle(TableStyle([("LEFTPADDING",(0,0),(-1,-1),2), ("RIGHTPADDING",(0,0),(-1,-1),2)]))
    story.append(legend)
    story.append(Spacer(1, 4*mm))

    # Frequency Table
    story.append(Paragraph("TOP 25 HIGH-YIELD TOPICS — FREQUENCY TABLE", h2))

    path_topics = [
        ["Rank", "Topic", "Unit", "Cat", "Freq\n(30yr)", "Format"],
        ["1",  "Acute Inflammation",                "Gen Path",    "🔴", "28/30", "LEQ/SEQ/SN/MCQ"],
        ["2",  "Neoplasia / Carcinogenesis",         "Gen Path",    "🔴", "27/30", "LEQ/SEQ/MCQ"],
        ["3",  "Cell Injury & Necrosis",             "Gen Path",    "🔴", "26/30", "LEQ/SEQ/SN/MCQ"],
        ["4",  "Thrombosis & Embolism",              "Haemo",       "🔴", "25/30", "LEQ/SEQ/SN/MCQ"],
        ["5",  "Iron Deficiency Anaemia",            "Haem",        "🔴", "24/30", "LEQ/SEQ/SN/MCQ"],
        ["6",  "Shock",                              "Haemo",       "🔴", "24/30", "LEQ/SEQ/MCQ"],
        ["7",  "Wound Healing / Repair",             "Gen Path",    "🔴", "23/30", "LEQ/SEQ/SN"],
        ["8",  "Leukaemia (ALL/AML/CML/CLL)",        "Haem",        "🔴", "23/30", "LEQ/SEQ/SN/MCQ"],
        ["9",  "Apoptosis",                          "Gen Path",    "🔴", "22/30", "SEQ/SN/MCQ"],
        ["10", "Thalassaemia",                       "Haem",        "🔴", "21/30", "LEQ/SEQ/SN/MCQ"],
        ["11", "Granulomatous Inflammation",         "Gen Path",    "🟠", "19/30", "SEQ/SN/MCQ"],
        ["12", "Chemical Mediators of Inflammation", "Gen Path",    "🟠", "19/30", "SEQ/SN/MCQ"],
        ["13", "Amyloidosis",                        "Immunopath",  "🟠", "18/30", "SEQ/SN/MCQ"],
        ["14", "DIC",                                "Haem",        "🟠", "17/30", "SEQ/SN/MCQ"],
        ["15", "Megaloblastic Anaemia",              "Haem",        "🟠", "17/30", "LEQ/SEQ/SN"],
        ["16", "Hypersensitivity Reactions",         "Immunopath",  "🟠", "16/30", "LEQ/SEQ/SN/MCQ"],
        ["17", "Sickle Cell Disease",                "Haem",        "🟠", "16/30", "SEQ/SN/MCQ"],
        ["18", "Tumour Markers",                     "Neoplasia",   "🟠", "15/30", "SEQ/SN/MCQ"],
        ["19", "Oedema",                             "Haemo",       "🟠", "15/30", "SEQ/SN"],
        ["20", "ITP",                                "Haem",        "🟠", "14/30", "SEQ/SN/MCQ"],
        ["21", "Free Radical Injury",                "Cell Injury", "🟠", "14/30", "SEQ/SN/MCQ"],
        ["22", "Aplastic Anaemia",                   "Haem",        "🟡", "10/30", "SEQ/SN"],
        ["23", "AIDS / Immunodeficiency",            "Immunopath",  "🟡",  "9/30", "SEQ/SN/MCQ"],
        ["24", "Oncogenes & Tumour Suppressor Genes","Neoplasia",   "🟡",  "9/30", "SEQ/SN/MCQ"],
        ["25", "Haemophilia / Bleeding Disorders",   "Haem",        "🟡",  "8/30", "LEQ/SEQ/SN"],
    ]
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               for row in path_topics], colWidths=col_w)
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        ("TEXTCOLOR",  (0,0), (-1,0), WHITE),
        ("FONTNAME",   (0,0), (-1,0), "Helvetica-Bold"),
        ("GRID",       (0,0), (-1,-1), 0.3, colors.HexColor("#CBD5E1")),
        ("ALIGN",      (0,0), (-1,-1), "CENTER"),
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        ("FONTSIZE",   (0,1), (-1,-1), 8),
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        ("BOTTOMPADDING", (0,0), (-1,-1), 3),
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        row_styles.append(("BACKGROUND", (0,i), (-1,i), bg))
    t.setStyle(TableStyle(row_styles))
    story.append(t)
    story.append(Spacer(1, 4*mm))

    # Decadal Trend
    story.append(Paragraph("DECADAL TREND ANALYSIS", h2))
    trend_data = [
        ["Decade", "LEQ Trend", "Emerging Topics"],
        ["1994–2004", "Cell Injury + Inflammation dominate", "HIV Pathology (new entry)"],
        ["2004–2014", "Neoplasia emerges as LEQ favourite", "Oncogenes, Tumour Markers, Apoptosis"],
        ["2014–2020", "Haematology gets consistent LEQ slot", "Hypersensitivity, Immunopathology"],
        ["2020–2024", "Clinical case-based scenario LEQ format", "JAK2, BCR-ABL, Myeloproliferative disorders"],
    ]
    tw = [30*mm, 80*mm, 54*mm]
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        ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
        ("TOPPADDING", (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING", (0,0), (-1,-1), 5),
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    story.append(tt)
    story.append(PageBreak())

    # ═══════════════════════════════════════════════════════════════
    # PART 2 — PATHOLOGY PREDICTED QUESTION PAPER
    # ═══════════════════════════════════════════════════════════════
    story.append(section_header("PART 2 — PATHOLOGY: PREDICTED MODEL QUESTION PAPER", bg=RED))
    story.append(Spacer(1, 2*mm))

    # Paper header box
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        Paragraph("<b>II MBBS DEGREE EXAMINATION — PATHOLOGY — PAPER I</b>", S("ph", fontSize=11,
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        Paragraph("General Pathology &amp; Haematology  |  Time: 3 Hours  |  Maximum Marks: 100",
                  S("ps", fontSize=9, leading=13, textColor=GREY, alignment=TA_CENTER)),
    ]], colWidths=[PAGE_W - 2*MARGIN])
    hdr.setStyle(TableStyle([
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        ("TOPPADDING", (0,0), (-1,-1), 8),
        ("BOTTOMPADDING", (0,0), (-1,-1), 8),
        ("LEFTPADDING", (0,0), (-1,-1), 10),
    ]))
    story.append(hdr)
    story.append(Spacer(1, 3*mm))

    # Section A MCQs
    story.append(colored_box("SECTION A — MCQs  (20 × 1 = 20 Marks)", LIGHT_BLUE, DARK_BLUE))
    story.append(Spacer(1, 2*mm))

    mcqs_path = [
        ("1", "The MOST characteristic feature of irreversible cell injury is:",
         ["A) Cellular swelling", "B) ★ Flocculent densities in mitochondria",
          "C) Ribosome disaggregation", "D) ER dilation"], 1),
        ("2", "Which is NOT a hallmark of cancer (Hanahan & Weinberg)?",
         ["A) Self-sufficiency in growth signals", "B) Resistance to apoptosis",
          "C) ★ Decreased telomerase activity", "D) Sustained angiogenesis"], 2),
        ("3", "Molecule responsible for leukocyte ROLLING on endothelium:",
         ["A) Integrin", "B) ICAM-1", "C) ★ Selectin", "D) PECAM-1"], 2),
        ("4", "Congo red stain under polarised light in amyloidosis shows:",
         ["A) Red birefringence", "B) Blue birefringence",
          "C) ★ Apple-green birefringence", "D) Yellow birefringence"], 2),
        ("5", "Virchow's triad does NOT include:",
         ["A) Endothelial injury", "B) Stasis of blood flow",
          "C) Hypercoagulability", "D) ★ Thrombocytopenia"], 3),
        ("6", "Philadelphia chromosome t(9;22) produces:",
         ["A) PML-RARα", "B) ★ BCR-ABL", "C) EWS-FLI1", "D) MYC rearrangement"], 1),
        ("7", "Peripheral blood smear in megaloblastic anaemia shows:",
         ["A) Microcytic hypochromic cells", "B) Target cells",
          "C) ★ Macro-ovalocytes + hypersegmented neutrophils", "D) Teardrop cells"], 2),
        ("8", "Type of necrosis in BRAIN infarction:",
         ["A) Coagulative", "B) Caseous", "C) ★ Liquefactive", "D) Fat necrosis"], 2),
        ("9", "Mentzer index >13 suggests:",
         ["A) Beta thalassaemia trait", "B) ★ Iron deficiency anaemia",
          "C) Sickle cell anaemia", "D) Folate deficiency"], 1),
        ("10", "PRIMARY mediator of fever:",
         ["A) IL-4", "B) IL-10", "C) ★ IL-1β / TNF-α", "D) IL-2"], 2),
        ("11", "Reed-Sternberg cells are pathognomonic of:",
         ["A) Non-Hodgkin lymphoma", "B) CML",
          "C) ★ Hodgkin lymphoma", "D) ALL"], 2),
        ("12", "Arachidonic acid via COX pathway produces:",
         ["A) Leukotrienes", "B) ★ Prostaglandins and TXA2",
          "C) PAF", "D) Bradykinin"], 1),
        ("13", "D-dimer is elevated in:",
         ["A) Haemophilia A", "B) ITP", "C) ★ DIC", "D) von Willebrand disease"], 2),
        ("14", "MOST important growth factor in wound healing:",
         ["A) EGF", "B) VEGF", "C) ★ TGF-β", "D) FGF"], 2),
        ("15", "Sago spleen in amyloidosis = deposits in:",
         ["A) Red pulp", "B) ★ White pulp (Malpighian corpuscles)",
          "C) Splenic capsule", "D) Penicillary arterioles"], 1),
        ("16", "Coombs' test is positive in:",
         ["A) Iron deficiency anaemia", "B) Thalassaemia",
          "C) ★ Autoimmune haemolytic anaemia", "D) Aplastic anaemia"], 2),
        ("17", "JAK2 V617F mutation is characteristically seen in:",
         ["A) CML", "B) ALL", "C) ★ Polycythaemia vera", "D) Multiple myeloma"], 2),
        ("18", "Classic cell in chronic granulomatous inflammation:",
         ["A) Neutrophil", "B) Plasma cell", "C) ★ Epithelioid cell", "D) Mast cell"], 2),
        ("19", "p53 mutation is seen in approximately what % of cancers?",
         ["A) ~10%", "B) ~30%", "C) ★ ~50%", "D) ~90%"], 2),
        ("20", "Haemophilia A = deficiency of:",
         ["A) Factor IX", "B) Factor XI", "C) ★ Factor VIII", "D) Factor XII"], 2),
    ]

    for qn, qt, opts, ans_idx in mcqs_path:
        story.append(Paragraph(f"<b>Q{qn}.</b> {qt}", qnum))
        for i, opt in enumerate(opts):
            is_ans = opt.startswith("★")
            clean = opt.replace("★ ", "")
            style = correct if is_ans else option
            prefix = "✓ " if is_ans else "   "
            story.append(Paragraph(f"  {prefix}{clean}", style))
        story.append(Spacer(1, 1.5*mm))

    story.append(PageBreak())

    # Section B General Pathology
    story.append(colored_box("SECTION B — GENERAL PATHOLOGY  (40 Marks)", LIGHT_BLUE, DARK_BLUE))
    story.append(Spacer(1, 2*mm))

    story.append(Paragraph("Q21. LONG ESSAY QUESTION — Answer ANY ONE  (10 Marks)", h3))
    story.append(colored_box("(a) A 55-year-old male, chronic smoker, presents with progressive dysphagia and weight loss. Endoscopy reveals squamous cell carcinoma of the oesophagus.", LIGHT_GREY))
    story.append(Paragraph("(i) Discuss the molecular basis of carcinogenesis in this patient. (5)", qtxt))
    story.append(Paragraph("(ii) Describe mechanisms of invasion and metastasis. (3)", qtxt))
    story.append(Paragraph("(iii) Enumerate relevant tumour markers and paraneoplastic syndromes. (2)", qtxt))
    story.append(Spacer(1, 2*mm))
    story.append(colored_box("OR", LIGHT_BLUE, MED_BLUE, pad=3))
    story.append(colored_box("(b) A 25-year-old presents with painful swelling on the right thumb after thorn injury. Area is red, warm, swollen and tender.", LIGHT_GREY))
    story.append(Paragraph("(i) Define acute inflammation. Describe vascular and cellular events. (6)", qtxt))
    story.append(Paragraph("(ii) Enumerate the chemical mediators and their specific roles. (4)", qtxt))
    story.append(Spacer(1, 3*mm))

    story.append(Paragraph("Q22–Q27. SHORT ESSAY QUESTIONS — Answer ANY FIVE  (5 × 5 = 25 Marks)", h3))
    seq_path = [
        ("Q22", "Discuss apoptosis: intrinsic and extrinsic pathways, morphological features, and differences from necrosis."),
        ("Q23", "Compare coagulative, liquefactive, and caseous necrosis with examples and morphology."),
        ("Q24", "Define oedema. Discuss pathogenesis of generalised oedema. Add a note on pulmonary oedema."),
        ("Q25", "Classify shock. Describe pathogenesis of septic shock. Mention morphological changes in lung and kidney."),
        ("Q26", "Discuss wound healing by secondary intention. Enumerate local and systemic factors affecting healing."),
        ("Q27", "AETCOM — A terminally ill cancer patient refuses further chemotherapy. Discuss ethical principles involved and the pathologist's role in communicating prognosis."),
    ]
    for qn, qt in seq_path:
        story.append(Table([[
            Paragraph(f"<b>{qn})</b>", S("qn2", fontSize=9.5, fontName="Helvetica-Bold", textColor=MED_BLUE)),
            Paragraph(qt, qtxt)
        ]], colWidths=[14*mm, PAGE_W-2*MARGIN-14*mm]))

    story.append(Spacer(1, 3*mm))
    story.append(Paragraph("Q28–Q30. SHORT NOTES — Answer ANY TWO  (3 × 2 = 6 Marks)", h3))
    sn_path = [
        "Q28) Amyloidosis — stains used and classification",
        "Q29) Free radical injury — sources and antioxidant mechanisms",
        "Q30) Granuloma — types of giant cells with examples",
    ]
    for sn in sn_path:
        story.append(Paragraph(sn, qtxt))

    story.append(PageBreak())

    # Section C Haematology
    story.append(colored_box("SECTION C — HAEMATOLOGY  (40 Marks)", LIGHT_RED, RED))
    story.append(Spacer(1, 2*mm))

    story.append(Paragraph("Q31. LONG ESSAY QUESTION — Answer ANY ONE  (10 Marks)", h3))
    story.append(colored_box("(a) A 2-year-old child presents with severe pallor, splenomegaly, frontal bossing. Peripheral smear: target cells, nucleated RBCs, hypochromic microcytic cells.", LIGHT_GREY))
    story.append(Paragraph("(i) Most likely diagnosis? Describe pathogenesis of beta-thalassaemia major. (4)", qtxt))
    story.append(Paragraph("(ii) Describe peripheral blood and bone marrow picture. (3)", qtxt))
    story.append(Paragraph("(iii) Outline investigations and complications. (3)", qtxt))
    story.append(colored_box("OR", LIGHT_RED, RED, pad=3))
    story.append(colored_box("(b) A 15-year-old male with recurrent haemarthrosis. Mother's brother had similar history. Bleeding time normal, PTT prolonged.", LIGHT_GREY))
    story.append(Paragraph("(i) Diagnosis? Explain inheritance and molecular defect. (4)", qtxt))
    story.append(Paragraph("(ii) Describe coagulation cascade and specific defect. (3)", qtxt))
    story.append(Paragraph("(iii) Laboratory diagnosis and treatment principles. (3)", qtxt))
    story.append(Spacer(1, 3*mm))

    story.append(Paragraph("Q32–Q37. SHORT ESSAY QUESTIONS — Answer ANY FIVE  (5 × 5 = 25 Marks)", h3))
    seq_haem = [
        ("Q32", "Classify anaemia. Discuss laboratory diagnosis of iron deficiency anaemia — peripheral smear, iron studies, bone marrow."),
        ("Q33", "Pathogenesis of acute leukaemia. Compare FAB classification of ALL vs AML."),
        ("Q34", "Define DIC. Describe pathogenesis, precipitating conditions, and laboratory diagnosis."),
        ("Q35", "Idiopathic thrombocytopenic purpura (ITP) — pathogenesis, types, laboratory findings, and management."),
        ("Q36", "Peripheral blood and bone marrow changes in megaloblastic anaemia. Include mechanism of hypersegmented neutrophils."),
        ("Q37", "CML — pathogenesis involving Philadelphia chromosome, clinical features, laboratory findings, natural history."),
    ]
    for qn, qt in seq_haem:
        story.append(Table([[
            Paragraph(f"<b>{qn})</b>", S("qn2", fontSize=9.5, fontName="Helvetica-Bold", textColor=RED)),
            Paragraph(qt, qtxt)
        ]], colWidths=[14*mm, PAGE_W-2*MARGIN-14*mm]))

    story.append(Spacer(1, 3*mm))
    story.append(Paragraph("Q38–Q42. SHORT NOTES — Answer ANY THREE  (3 × 3 = 9 Marks)", h3))
    sn_haem = [
        "Q38) Coombs' test — direct and indirect, clinical uses",
        "Q39) Sickle cell disease — pathogenesis of sickling",
        "Q40) Leukaemoid reaction vs Leukaemia",
        "Q41) Reed-Sternberg cells — morphology and significance",
        "Q42) Aplastic anaemia — causes and bone marrow findings",
    ]
    for sn in sn_haem:
        story.append(Paragraph(sn, qtxt))

    story.append(PageBreak())

    # ═══════════════════════════════════════════════════════════════
    # PART 3 — PATHOLOGY REVISION LIST
    # ═══════════════════════════════════════════════════════════════
    story.append(section_header("PART 3 — PATHOLOGY: LAST-MINUTE REVISION PRIORITY", bg=RED))
    story.append(Spacer(1, 3*mm))

    def rev_box(title, items, bg=LIGHT_RED, header_bg=RED):
        content = [
            [Paragraph(f"<b>{title}</b>",
                       S("rb", fontSize=10, fontName="Helvetica-Bold", textColor=WHITE))]
        ]
        for item in items:
            content.append([Paragraph(f"• {item}", body_sm)])
        t = Table(content, colWidths=[PAGE_W - 2*MARGIN])
        t.setStyle(TableStyle([
            ("BACKGROUND", (0,0), (-1,0), header_bg),
            ("BACKGROUND", (0,1), (-1,-1), bg),
            ("BOX", (0,0), (-1,-1), 0.5, MID_GREY),
            ("TOPPADDING", (0,0), (-1,-1), 4),
            ("BOTTOMPADDING", (0,0), (-1,-1), 3),
            ("LEFTPADDING", (0,0), (-1,-1), 8),
        ]))
        return t

    story.append(rev_box("🔴 ABSOLUTE MUST — INFLAMMATION (Hours 1–3)", [
        "Vascular events: 3Cs → Capillary dilation → Congestion → Increased permeability",
        "Cellular events: Margination → Rolling → Adhesion (Selectins/Integrins) → Diapedesis → Chemotaxis → Phagocytosis",
        "Mediators: Histamine (immediate), Serotonin, AA metabolites (PGs via COX, LTs via LOX, TXA2)",
        "C5a = chemotaxis + anaphylatoxin | C3b = opsonisation | C3a/C5a = increased permeability",
        "Giant cells: Langhans (TB), Foreign body, Touton (fat necrosis/xanthoma), Aschoff (rheumatic fever), Warthin-Finkeldey (measles)",
        "1st cell = Neutrophil (6–24h) | 2nd cell = Monocyte/Macrophage (24–48h)"
    ]))
    story.append(Spacer(1, 2*mm))

    story.append(rev_box("🔴 NECROSIS — 6 TYPES (Must know one example each)", [
        "Coagulative = Most common; Ischaemia (except brain); Ghost cells; Firm texture",
        "Liquefactive = Brain infarction; Bacterial abscess (pus = liquefied necrotic material)",
        "Caseous = TB; Cheese-like; Amorphous granular debris; Caseating granuloma",
        "Fat necrosis = Pancreatitis (enzymatic) + Trauma to breast; Calcium soaps (saponification)",
        "Fibrinoid = Vessels in malignant HTN + immune diseases (SLE, PAN); Immune complexes + fibrin",
        "Gangrenous = Dry (limb, coagulative) vs Wet (bowel, liquefactive) vs Gas (C. perfringens)",
        "APOPTOSIS vs NECROSIS: Apoptosis = programmed, single cell, no inflammation, phagocytosed quietly"
    ]))
    story.append(Spacer(1, 2*mm))

    story.append(rev_box("🔴 THROMBOSIS — VIRCHOW'S TRIAD (MCQ gold)", [
        "1. Endothelial injury: Atherosclerosis, HTN, trauma, smoking",
        "2. Stasis/turbulence: AF, post-op immobility, cardiac aneurysm, varicose veins",
        "3. Hypercoagulability: Factor V Leiden, Protein C/S deficiency, OCP, malignancy",
        "Lines of Zahn = alternating red/pale layers (only in ARTERIAL thrombus, ante-mortem)",
        "Fate: Resolution (plasmin) | Organisation | Recanalisation | Embolism | Calcification (phleboliths)",
        "Saddle embolus = lodges at pulmonary artery bifurcation = sudden death"
    ]))
    story.append(Spacer(1, 2*mm))

    # Comparison tables
    story.append(Paragraph("KEY COMPARISON TABLES (High-Scoring Format)", h2))

    def comp_table(title, headers, rows, col_widths, hdr_bg=DARK_BLUE):
        data = [[Paragraph(f"<b>{h}</b>", S("ch", fontSize=8.5, fontName="Helvetica-Bold",
                            textColor=WHITE, leading=12)) for h in headers]]
        for row in rows:
            data.append([Paragraph(str(c), S("cd", fontSize=8, fontName="Helvetica",
                          textColor=GREY, leading=11)) for c in row])
        t = Table(data, colWidths=col_widths)
        ts = [
            ("BACKGROUND", (0,0), (-1,0), hdr_bg),
            ("ROWBACKGROUNDS", (0,1), (-1,-1), [WHITE, LIGHT_GREY]),
            ("GRID", (0,0), (-1,-1), 0.3, colors.HexColor("#CBD5E1")),
            ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
            ("TOPPADDING", (0,0), (-1,-1), 4),
            ("BOTTOMPADDING", (0,0), (-1,-1), 3),
            ("LEFTPADDING", (0,0), (-1,-1), 5),
        ]
        t.setStyle(TableStyle(ts))
        return [Paragraph(f"<b>{title}</b>", h4), t, Spacer(1, 3*mm)]

    story += comp_table(
        "Apoptosis vs Necrosis",
        ["Feature", "Apoptosis", "Necrosis"],
        [
            ["Stimulus",      "Physiological / controlled", "Pathological (ischaemia, toxins)"],
            ["Cell number",   "Single cell",                "Groups of cells"],
            ["Membrane",      "Intact throughout",          "Early disruption"],
            ["Inflammation",  "ABSENT",                     "PRESENT"],
            ["DNA",           "Ladder pattern (180bp)",     "Random degradation"],
            ["Energy",        "ATP-dependent (active)",     "Passive"],
            ["Phagocytosis",  "By adjacent cells/macrophages quietly", "Inflammatory process"],
            ["Examples",      "Embryogenesis, CD8 T-cell killing, hormone withdrawal", "MI, gangrene, abscess"],
        ],
        [44*mm, 70*mm, 50*mm], hdr_bg=GREY
    )

    story += comp_table(
        "IDA vs Thalassaemia Trait",
        ["Feature", "IDA", "Thalassaemia Trait"],
        [
            ["Mentzer Index (MCV/RBC)", ">13", "<13"],
            ["Serum Ferritin",          "↓ (low)",     "Normal or ↑"],
            ["TIBC",                    "↑ (high)",    "Normal"],
            ["Serum iron",              "↓",           "Normal"],
            ["HbA2",                    "Normal",      "↑ (>3.5%)"],
            ["RBC count",               "↓",           "Normal or slightly ↑"],
            ["Response to iron therapy","Good",        "No response"],
        ],
        [48*mm, 58*mm, 58*mm], hdr_bg=TEAL
    )

    story.append(PageBreak())

    # ═══════════════════════════════════════════════════════════════
    # PART 4 — PHARMACOLOGY HIGH-YIELD TOPIC MAP
    # ═══════════════════════════════════════════════════════════════
    story.append(section_header("PART 4 — PHARMACOLOGY PAPER I: HIGH-YIELD TOPIC MAP", bg=PURPLE))
    story.append(Spacer(1, 3*mm))
    story.append(Paragraph("General Pharmacology + ANS + CVS + GIT + Respiratory  |  30-Year PYQ Analysis (1994–2024)", note))
    story.append(Spacer(1, 3*mm))

    pharm_topics = [
        ["Rank", "Topic", "Unit", "Cat", "Freq\n(30yr)", "Format"],
        ["1",  "Adrenergic Drugs (Adrenaline, NA, Dopamine)", "ANS", "🔴", "29/30", "LEQ/SEQ/MCQ"],
        ["2",  "Cholinergic & Anticholinergic Drugs",         "ANS", "🔴", "28/30", "LEQ/SEQ/SN/MCQ"],
        ["3",  "Pharmacokinetics (Bioavailability, t½, Vd)",  "Gen", "🔴", "28/30", "LEQ/SEQ/MCQ"],
        ["4",  "Beta-Blockers (Propranolol, Metoprolol)",     "CVS", "🔴", "27/30", "LEQ/SEQ/SN/MCQ"],
        ["5",  "Antihypertensives (ACEi, CCB, ARB)",         "CVS", "🔴", "26/30", "LEQ/SEQ/MCQ"],
        ["6",  "Anti-Anginal Drugs (Nitrates, Beta-bl, CCB)", "CVS", "🔴", "25/30", "LEQ/SEQ/SN"],
        ["7",  "Antiarrhythmics (Vaughan Williams Class.)",   "CVS", "🔴", "24/30", "LEQ/SEQ/MCQ"],
        ["8",  "Diuretics (Frusemide, Thiazides, Spirono.)",  "CVS", "🔴", "24/30", "LEQ/SEQ/SN/MCQ"],
        ["9",  "Pharmacodynamics (Receptors, DRC, ED50)",     "Gen", "🔴", "23/30", "LEQ/SEQ/MCQ"],
        ["10", "Antiulcer Drugs (PPIs, H2, Sucralfate, H.py)","GIT", "🔴", "22/30", "LEQ/SEQ/SN/MCQ"],
        ["11", "Anticoagulants (Heparin vs Warfarin)",        "CVS", "🟠", "21/30", "LEQ/SEQ/SN/MCQ"],
        ["12", "NM Blocking Agents (Depol vs Non-depol)",     "ANS", "🟠", "20/30", "SEQ/SN/MCQ"],
        ["13", "Organophosphate Poisoning & Management",      "ANS", "🟠", "20/30", "SEQ/SN/MCQ"],
        ["14", "Heart Failure Drugs (Digoxin, ACEi)",         "CVS", "🟠", "19/30", "LEQ/SEQ/SN/MCQ"],
        ["15", "Bioavailability & Drug Metabolism (CYP450)",  "Gen", "🟠", "19/30", "SEQ/SN/MCQ"],
        ["16", "Drug Interactions (PK + PD interactions)",    "Gen", "🟠", "18/30", "SEQ/SN/MCQ"],
        ["17", "Anti-Asthmatic Drugs (Salbutamol, ICS)",      "Resp","🟠", "18/30", "LEQ/SEQ/SN"],
        ["18", "Antiplatelet Drugs (Aspirin, Clopidogrel)",   "CVS", "🟠", "17/30", "SEQ/SN/MCQ"],
        ["19", "ADRs & Drug Toxicity Classification",         "Gen", "🟠", "17/30", "SEQ/SN/MCQ"],
        ["20", "Laxatives & Antidiarrhoeals",                 "GIT", "🟡", "14/30", "SEQ/SN"],
        ["21", "H. pylori Eradication Regimens",              "GIT", "🟡", "13/30", "SEQ/SN/MCQ"],
        ["22", "Plasma Expanders / Fluids",                   "CVS", "🟡", "12/30", "SEQ/SN"],
        ["23", "Routes of Administration",                    "Gen", "🟡", "12/30", "SEQ/SN/MCQ"],
        ["24", "Fixed Dose Combinations & Rational Prescr.",  "Gen", "🟡", "10/30", "SEQ/SN"],
        ["25", "Antiemetics (Metoclopramide, Ondansetron)",   "GIT", "🟡",  "9/30", "SN/MCQ"],
    ]
    col_w2 = [(PAGE_W-2*MARGIN) * x for x in [0.06, 0.34, 0.09, 0.06, 0.09, 0.36]]
    t2 = Table([[Paragraph(str(c), S("th2", fontSize=8, fontName="Helvetica-Bold",
                textColor=WHITE, leading=11)) for c in row]
                for row in pharm_topics], colWidths=col_w2)
    rs2 = [
        ("BACKGROUND", (0,0), (-1,0), PURPLE),
        ("TEXTCOLOR",  (0,0), (-1,0), WHITE),
        ("FONTNAME",   (0,0), (-1,0), "Helvetica-Bold"),
        ("GRID",       (0,0), (-1,-1), 0.3, colors.HexColor("#CBD5E1")),
        ("ALIGN",      (0,0), (-1,-1), "CENTER"),
        ("VALIGN",     (0,0), (-1,-1), "MIDDLE"),
        ("FONTSIZE",   (0,1), (-1,-1), 8),
        ("LEADING",    (0,1), (-1,-1), 11),
        ("TOPPADDING",    (0,0), (-1,-1), 3),
        ("BOTTOMPADDING", (0,0), (-1,-1), 3),
    ]
    for i in range(1, len(pharm_topics)):
        bg = LIGHT_RED if "🔴" in pharm_topics[i][3] else \
             LIGHT_ORANGE if "🟠" in pharm_topics[i][3] else LIGHT_YELLOW
        rs2.append(("BACKGROUND", (0,i), (-1,i), bg))
    t2.setStyle(TableStyle(rs2))
    story.append(t2)
    story.append(PageBreak())

    # ═══════════════════════════════════════════════════════════════
    # PART 5 — PHARMACOLOGY PREDICTED PAPER
    # ═══════════════════════════════════════════════════════════════
    story.append(section_header("PART 5 — PHARMACOLOGY: PREDICTED MODEL QUESTION PAPER", bg=PURPLE))
    story.append(Spacer(1, 2*mm))

    hdr2 = Table([[
        Paragraph("<b>II MBBS DEGREE EXAMINATION — PHARMACOLOGY — PAPER I</b>",
                  S("ph2", fontSize=11, leading=15, textColor=PURPLE,
                    fontName="Helvetica-Bold", alignment=TA_CENTER)),
        Paragraph("Gen Pharmacology + ANS + CVS + GIT + Respiratory  |  Time: 3 Hours  |  Max Marks: 100",
                  S("ps2", fontSize=9, leading=13, textColor=GREY, alignment=TA_CENTER)),
    ]], colWidths=[PAGE_W - 2*MARGIN])
    hdr2.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), LIGHT_PURPLE),
        ("BOX", (0,0), (-1,-1), 1.5, PURPLE),
        ("TOPPADDING", (0,0), (-1,-1), 8),
        ("BOTTOMPADDING", (0,0), (-1,-1), 8),
        ("LEFTPADDING", (0,0), (-1,-1), 10),
    ]))
    story.append(hdr2)
    story.append(Spacer(1, 3*mm))

    story.append(colored_box("SECTION A — MCQs  (20 × 1 = 20 Marks)", LIGHT_PURPLE, PURPLE))
    story.append(Spacer(1, 2*mm))

    mcqs_pharm = [
        ("1", "Bioavailability of a drug given orally refers to:",
         ["A) Amount absorbed from GIT", "B) ★ Amount reaching systemic circulation unchanged",
          "C) Total drug dose given", "D) Drug bound to plasma proteins"]),
        ("2", "Beta-blocker with additional alpha-blocking activity:",
         ["A) Metoprolol", "B) Atenolol", "C) ★ Carvedilol", "D) Timolol"]),
        ("3", "'Adrenaline reversal' is demonstrated after administration of:",
         ["A) Beta-blocker", "B) ★ Alpha-blocker (Dale's vasomotor reversal)",
          "C) Anticholinergic", "D) Antihistamine"]),
        ("4", "Drug of choice for hypertensive emergency in pregnancy:",
         ["A) Enalapril", "B) Sodium nitroprusside",
          "C) ★ Labetalol (IV)", "D) Oral nifedipine"]),
        ("5", "Nitrate tolerance is BEST prevented by:",
         ["A) Increasing dose", "B) ★ Nitrate-free interval of 8–10 hours",
          "C) Adding beta-blocker", "D) Switching to IV"]),
        ("6", "Sucralfate requires acidic pH because:",
         ["A) It neutralises excess acid",
          "B) It acts as a buffer",
          "C) ★ It polymerises at pH <4 to form a viscous protective gel",
          "D) It activates pepsin"]),
        ("7", "Diuretic acting on thick ascending limb of Loop of Henle:",
         ["A) Thiazide", "B) ★ Frusemide", "C) Spironolactone", "D) Acetazolamide"]),
        ("8", "Atropine causes tachycardia by blocking:",
         ["A) Nicotinic receptors", "B) ★ M2 (cardiac muscarinic) receptors",
          "C) Beta-1 receptors", "D) Alpha-1 receptors"]),
        ("9", "Selective beta-1 blocker among the following:",
         ["A) Propranolol", "B) Sotalol", "C) ★ Metoprolol", "D) Timolol"]),
        ("10", "Antidote for heparin overdose:",
         ["A) Vitamin K", "B) ★ Protamine sulphate", "C) FFP", "D) Atropine"]),
        ("11", "PPIs are formulated as enteric-coated tablets because:",
         ["A) ★ They are acid-labile prodrugs destroyed at gastric pH",
          "B) They irritate gastric mucosa directly",
          "C) They taste bitter",
          "D) They need to act locally in stomach"]),
        ("12", "Drug of choice for organophosphate poisoning:",
         ["A) Neostigmine", "B) Physostigmine",
          "C) ★ Atropine + Pralidoxime (2-PAM)", "D) Diazepam only"]),
        ("13", "Zero-order kinetics means:",
         ["A) ★ Constant AMOUNT of drug eliminated per unit time (capacity-limited)",
          "B) Elimination proportional to concentration",
          "C) Half-life is constant", "D) Only renal elimination"]),
        ("14", "Cimetidine causes gynaecomastia by:",
         ["A) Increasing prolactin", "B) Estrogenic activity",
          "C) ★ Anti-androgenic action (blocks androgen receptors)", "D) Thyroid suppression"]),
        ("15", "Most cardioselective calcium channel blocker:",
         ["A) Amlodipine", "B) Nifedipine", "C) ★ Verapamil", "D) Felodipine"]),
        ("16", "Amiodarone toxicity does NOT include:",
         ["A) Thyroid dysfunction", "B) Pulmonary fibrosis",
          "C) Corneal deposits", "D) ★ Renal failure"]),
        ("17", "Drug with t½ of 6 hours reaches steady state in approximately:",
         ["A) 12 hours", "B) 18 hours",
          "C) ★ 30 hours (5 × t½)", "D) 48 hours"]),
        ("18", "Digoxin toxicity is potentiated by:",
         ["A) Hyperkalaemia", "B) Alkalosis",
          "C) ★ Hypokalaemia", "D) Hypernatraemia"]),
        ("19", "Route with MAXIMUM first-pass metabolism:",
         ["A) IV", "B) Sublingual", "C) ★ Oral", "D) Intramuscular"]),
        ("20", "H. pylori triple therapy consists of:",
         ["A) Metronidazole alone", "B) Amoxicillin alone",
          "C) ★ PPI + Amoxicillin + Clarithromycin (OAC regimen)", "D) H2 blocker + two antibiotics"]),
    ]

    for qn, qt, opts in mcqs_pharm:
        story.append(Paragraph(f"<b>Q{qn}.</b> {qt}", qnum))
        for opt in opts:
            is_ans = opt.startswith("★")
            clean = opt.replace("★ ", "")
            sty = correct if is_ans else option
            prefix = "✓ " if is_ans else "   "
            story.append(Paragraph(f"  {prefix}{clean}", sty))
        story.append(Spacer(1, 1.5*mm))

    story.append(PageBreak())

    # Pharm LEQ + SEQ
    story.append(colored_box("SECTION B — PHARMACOLOGY  (80 Marks)", LIGHT_PURPLE, PURPLE))
    story.append(Spacer(1, 2*mm))

    story.append(Paragraph("Q21. LONG ESSAY QUESTION — Answer ANY ONE  (10 Marks)", h3))
    story.append(colored_box("(a) A 60-year-old with peptic ulcer disease is prescribed Omeprazole.", LIGHT_GREY))
    story.append(Paragraph("(i) Why is omeprazole formulated as an enteric-coated tablet? Explain the mechanism of acid-secretion inhibition by PPIs. (5)", qtxt))
    story.append(Paragraph("(ii) Enumerate complications of long-term PPI use — focus on Vit B12 and iron deficiency with mechanism. (3)", qtxt))
    story.append(Paragraph("(iii) Why should sucralfate NOT be given simultaneously? Describe sucralfate's mechanism of cytoprotection. (2)", qtxt))
    story.append(colored_box("OR", LIGHT_PURPLE, PURPLE, pad=3))
    story.append(colored_box("(b) A 65-year-old with HTN, stable angina, and Type 2 DM is considered for beta-blocker therapy.", LIGHT_GREY))
    story.append(Paragraph("(i) Classify beta-blockers. Describe pharmacological actions of propranolol. (4)", qtxt))
    story.append(Paragraph("(ii) Uses of beta-blockers in his combined conditions. (3)", qtxt))
    story.append(Paragraph("(iii) Contraindications relevant to this patient. Which selective beta-blocker would you prefer? (3)", qtxt))
    story.append(Spacer(1, 3*mm))

    story.append(Paragraph("Q22–Q29. SHORT ESSAY QUESTIONS — Answer ANY SEVEN  (5 × 7 = 35 Marks)", h3))
    seq_pharm = [
        ("Q22", "Define bioavailability. Explain first-pass metabolism with examples. Describe methods to bypass it."),
        ("Q23", "Classify adrenergic agonists. Describe pharmacological actions and therapeutic uses of dopamine."),
        ("Q24", "A patient presents with excessive secretions, miosis, bradycardia, and fasciculations after organophosphate exposure. Explain mechanism and outline management."),
        ("Q25", "Classify antihypertensives. Describe mechanism of action, uses, and adverse effects of ACE inhibitors. Include mechanism of dry cough."),
        ("Q26", "Vaughan Williams classification of antiarrhythmics. Describe amiodarone — pharmacology and important adverse effects."),
        ("Q27", "Classify diuretics by site of action. Describe pharmacology of frusemide — mechanism, uses, and adverse effects."),
        ("Q28", "Mechanism of anticoagulant action of heparin. Compare heparin vs warfarin: mechanism, onset, monitoring, reversal, and drug interactions."),
        ("Q29", "Anti-asthmatic drugs. Classify bronchodilators. Mechanism of salbutamol. Role of inhaled corticosteroids."),
    ]
    for qn, qt in seq_pharm:
        story.append(Table([[
            Paragraph(f"<b>{qn})</b>", S("qn3", fontSize=9.5, fontName="Helvetica-Bold", textColor=PURPLE)),
            Paragraph(qt, qtxt)
        ]], colWidths=[14*mm, PAGE_W-2*MARGIN-14*mm]))

    story.append(Spacer(1, 3*mm))
    story.append(Paragraph("Q30–Q35. SHORT NOTES — Answer ANY FIVE  (3 × 5 = 15 Marks)", h3))
    sn_pharm = [
        "Q30) Pralidoxime (2-PAM) — mechanism and limitations (aging of AChE)",
        "Q31) Nitrate tolerance — mechanism (SH group depletion) and prevention (nitrate-free interval)",
        "Q32) Spironolactone — mechanism (aldosterone antagonist) and uses in heart failure/cirrhosis/PCOS",
        "Q33) Misoprostol — pharmacology, uses (NSAID ulcer prophylaxis, PPTB), contraindications (pregnancy)",
        "Q34) Volume of distribution (Vd) — definition, formula, clinical significance, examples",
        "Q35) Atropine — 5 clinical uses with mechanism (premed, bradycardia, OP poisoning, GI spasm, cycloplegia)",
    ]
    for sn in sn_pharm:
        story.append(Paragraph(sn, qtxt))

    story.append(PageBreak())

    # ═══════════════════════════════════════════════════════════════
    # PART 6 — PHARMACOLOGY REVISION
    # ═══════════════════════════════════════════════════════════════
    story.append(section_header("PART 6 — PHARMACOLOGY: LAST-MINUTE REVISION", bg=PURPLE))
    story.append(Spacer(1, 3*mm))

    story.append(rev_box("🔴 SURE-SHOT 15 TOPICS (At least one from each appears every year)", [
        "1. Adrenaline — complete pharmacology (α1, α2, β1, β2 actions; uses; ADRs)",
        "2. Propranolol — complete pharmacology (non-selective beta-blocker)",
        "3. Atropine — pharmacology + poisoning management (physostigmine antidote)",
        "4. Organophosphate poisoning — DUMBBELS/SLUD + Atropine (high-dose) + Pralidoxime",
        "5. Bioavailability + First-pass metabolism (drugs with high FPM: GTN, Propranolol, Lignocaine)",
        "6. ACE inhibitors — mechanism (bradykinin + dry cough via bradykinin/substance P)",
        "7. Digoxin — mechanism (Na/K-ATPase inhibition) + toxicity + Hypokalaemia potentiation",
        "8. Frusemide — site (thick ascending limb), mechanism (NKCC2 inhibitor), ADRs (ototoxicity)",
        "9. Heparin vs Warfarin — 7-point comparison table (mandatory for full 5-mark SEQ)",
        "10. PPIs — why enteric-coated (acid-labile prodrug) + B12/iron deficiency mechanism",
        "11. Sucralfate — polymerisation at pH<4 + why NO antacids (raises pH, blocks activation)",
        "12. Nitrate tolerance — SH group depletion → prevent with 8–10h nitrate-free period",
        "13. H. pylori OAC triple therapy: Omeprazole + Amoxicillin + Clarithromycin (14 days)",
        "14. Beta-blocker classification — cardioselective (MABE: Metoprolol, Atenolol, Bisoprolol, Esmolol)",
        "15. NMBAs — Succinylcholine (depolarising, Phase I→II block) vs Non-depolarising (pancuronium, vecuronium)",
    ], bg=LIGHT_PURPLE, header_bg=PURPLE))
    story.append(Spacer(1, 3*mm))

    # DOC table
    story.append(Paragraph("DRUG OF CHOICE (DOC) — MCQ GOLDMINE", h2))
    doc_data = [
        ["Condition", "DOC", "Reason"],
        ["HTN + Diabetes", "ACE inhibitor (Ramipril)", "Renoprotective, reduces proteinuria"],
        ["HTN + Asthma", "CCB (Amlodipine)", "Beta-blockers contraindicated"],
        ["HTN in Pregnancy", "Methyldopa (1st line)", "Safest; Labetalol/Nifedipine also used"],
        ["Hypertensive Emergency", "IV Labetalol or SNP", "Rapid, titratable"],
        ["Phaeochromocytoma", "Phenoxybenzamine first", "Alpha block before beta block"],
        ["Angina + HTN", "Beta-blocker or CCB", "Reduces HR and O2 demand"],
        ["HF with reduced EF", "ACEi + BB + Spironolactone", "Mortality benefit proven"],
        ["OP Poisoning", "Atropine + Pralidoxime", "Atropine = symptomatic; 2-PAM = causal"],
        ["Nitrate tolerance", "Nitrate-free interval", "8–10 hrs each day (patch-off at night)"],
        ["DVT prevention", "LMWH (Enoxaparin)", "Predictable dose, no monitoring needed"],
        ["Reversal of warfarin (urgent)", "Vit K + FFP/PCC", "FFP for immediate; Vit K for sustained"],
        ["Reversal of heparin", "Protamine sulphate", "Positive charge neutralises heparin"],
        ["Acute severe asthma", "IV Salbutamol + IV Steroids", "Bronchodilation + anti-inflammation"],
        ["H. pylori eradication", "OAC triple therapy", "Omeprazole + Amoxicillin + Clarithromycin"],
    ]
    tw2 = [60*mm, 64*mm, 40*mm]
    td = Table([[Paragraph(str(c), S("dd", fontSize=8, fontName=
                "Helvetica-Bold" if r==0 else "Helvetica",
                textColor=WHITE if r==0 else GREY, leading=11))
                for c in row] for r,row in enumerate(doc_data)], colWidths=tw2)
    td.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,0), PURPLE),
        ("ROWBACKGROUNDS", (0,1), (-1,-1), [WHITE, LIGHT_PURPLE]),
        ("GRID", (0,0), (-1,-1), 0.3, colors.HexColor("#CBD5E1")),
        ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
        ("TOPPADDING", (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 3),
        ("LEFTPADDING", (0,0), (-1,-1), 5),
    ]))
    story.append(td)
    story.append(PageBreak())

    # ═══════════════════════════════════════════════════════════════
    # PART 7 — 10-DAY TIMETABLE
    # ═══════════════════════════════════════════════════════════════
    story.append(section_header("PART 7 — 10-DAY REVISION TIMETABLE (Both Subjects)", bg=TEAL))
    story.append(Spacer(1, 3*mm))

    tt_path = [
        ["Day", "PATHOLOGY Topics", "PHARMACOLOGY Topics", "Priority Focus"],
        ["1",  "Cell Injury → Necrosis → Apoptosis → Free Radicals",
               "General Pharmacokinetics (ADME, Bioavailability, t½, Vd)",
               "LEQ + Formulas"],
        ["2",  "Acute Inflammation (Vascular + Cellular + Mediators)",
               "Pharmacodynamics (Receptors, DRC, ED50, Agonist/Antagonist)",
               "LEQ + MCQ prep"],
        ["3",  "Chronic Inflammation + Granuloma + Wound Healing",
               "ANS: Cholinergic + Anticholinergic + NMBAs + OP Poisoning",
               "LEQ + SEQ"],
        ["4",  "Neoplasia (Carcinogenesis + Hallmarks + Tumour Markers)",
               "ANS: Adrenergic drugs + Sympathomimetics + Adrenaline reversal",
               "LEQ + Comparison tables"],
        ["5",  "Haemodynamics (Thrombosis + Oedema + Shock)",
               "CVS: Beta-blockers + CCBs + Anti-anginals + Nitrate tolerance",
               "SEQ + MCQ DOC lists"],
        ["6",  "Immunopathology (Hypersensitivity I–IV + Amyloidosis)",
               "CVS: Antihypertensives (ACEi, ARBs) + Diuretics",
               "SEQ + SN"],
        ["7",  "Haematology: Anaemias (IDA + Megaloblastic + Haemolytic)",
               "CVS: Antiarrhythmics + Heart failure drugs + Anticoagulants",
               "LEQ + Comparison tables"],
        ["8",  "Haematology: Leukaemias (ALL/AML/CML/CLL) + Lymphoma",
               "GIT: Antiulcer (PPIs + H2 + Sucralfate + Misoprostol + H. pylori)",
               "LEQ + SEQ"],
        ["9",  "Haematology: Bleeding disorders (ITP + DIC + Haemophilia)",
               "Respiratory: Antiasthmatics + Antitussives + Antiemetics",
               "SEQ + SN practice"],
        ["10", "Full revision: All comparison tables + Diagrams + Mock MCQs",
               "Full revision: DOC lists + Drug interactions + Mock MCQs",
               "Exam simulation"],
    ]
    tw3 = [12*mm, 52*mm, 52*mm, 32*mm]
    ttt = Table([[Paragraph(str(c), S("ttr", fontSize=8, fontName=
                 "Helvetica-Bold" if r==0 else "Helvetica",
                 textColor=WHITE if r==0 else GREY, leading=11))
                 for c in row] for r,row in enumerate(tt_path)], colWidths=tw3)
    ttt.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,0), TEAL),
        ("ROWBACKGROUNDS", (0,1), (-1,-1), [WHITE, LIGHT_TEAL]),
        ("GRID", (0,0), (-1,-1), 0.3, colors.HexColor("#CBD5E1")),
        ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
        ("TOPPADDING", (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 4),
        ("LEFTPADDING", (0,0), (-1,-1), 5),
    ]))
    story.append(ttt)
    story.append(Spacer(1, 5*mm))

    # ═══════════════════════════════════════════════════════════════
    # PART 8 — EXAMINER TIPS
    # ═══════════════════════════════════════════════════════════════
    story.append(section_header("PART 8 — EXAMINER'S STRATEGIC TIPS & DIAGRAM CHECKLIST", bg=GREEN))
    story.append(Spacer(1, 3*mm))

    story.append(rev_box("✍️  HOW TO SCORE FULL 10 MARKS IN LEQ — Golden Structure", [
        "1. DEFINITION: 1 mark — Precise, one sentence",
        "2. CLASSIFICATION / TYPES: 1–2 marks — Neat, labelled list",
        "3. PATHOGENESIS / MECHANISM: 3–4 marks — THIS is where most marks come from",
        "4. MORPHOLOGY / BLOOD PICTURE / HISTOLOGY: 2 marks — Gross + microscopy",
        "5. COMPLICATIONS / CLINICAL SIGNIFICANCE: 1 mark — Link to clinical scenario",
        "6. LABELLED DIAGRAM: Always draw if applicable — adds up to 2 bonus marks",
    ], bg=LIGHT_GREEN, header_bg=GREEN))
    story.append(Spacer(1, 3*mm))

    story.append(Paragraph("DIAGRAMS THAT ALWAYS SCORE EXTRA MARKS", h2))
    diag_data = [
        ["Topic", "Diagram to Draw", "Marks Value"],
        ["Acute Inflammation", "Leukocyte rolling-adhesion cascade with molecules labelled", "2 marks"],
        ["Cell Injury",        "Mitochondrial changes in reversible vs irreversible (EM level)", "2 marks"],
        ["Wound Healing",      "Timeline of phases (haemostasis → inflammation → proliferation → remodelling)", "2 marks"],
        ["Thalassaemia",       "Peripheral blood smear (target cells, nucleated RBCs, poikilocytes)", "2 marks"],
        ["Coagulation",        "Intrinsic vs extrinsic coagulation cascade with factor names", "2 marks"],
        ["Thrombosis",         "Virchow's triad triangle diagram", "1 mark"],
        ["Adrenergic drugs",   "Sympathetic nervous system with receptor locations", "2 marks"],
        ["PPI mechanism",      "Parietal cell canaliculus + H/K-ATPase pump + prodrug activation", "2 marks"],
        ["Anti-anginals",      "Mechanism of nitrate (NO → cGMP → smooth muscle relaxation)", "1 mark"],
        ["Heparin vs Warfarin","Coagulation cascade showing sites of action", "2 marks"],
    ]
    tw4 = [50*mm, 80*mm, 34*mm]
    td4 = Table([[Paragraph(str(c), S("dd4", fontSize=8, fontName=
                 "Helvetica-Bold" if r==0 else "Helvetica",
                 textColor=WHITE if r==0 else GREY, leading=11))
                 for c in row] for r,row in enumerate(diag_data)], colWidths=tw4)
    td4.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,0), GREEN),
        ("ROWBACKGROUNDS", (0,1), (-1,-1), [WHITE, LIGHT_GREEN]),
        ("GRID", (0,0), (-1,-1), 0.3, colors.HexColor("#CBD5E1")),
        ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
        ("TOPPADDING", (0,0), (-1,-1), 4),
        ("BOTTOMPADDING", (0,0), (-1,-1), 3),
        ("LEFTPADDING", (0,0), (-1,-1), 5),
    ]))
    story.append(td4)
    story.append(Spacer(1, 5*mm))

    # Final examiner note
    final = Table([[
        Paragraph(
            "<b>SENIOR EXAMINER'S FINAL WORD:</b> Master the TOP 10 topics deeply — not superficially. "
            "Students who score 75%+ know acute inflammation and neoplasia to LEQ level, know their "
            "haematology comparisons cold, and in pharmacology can link mechanism → clinical use → adverse "
            "effects for each major drug class. Draw diagrams. Use headings. Never skip Virchow's triad, "
            "Mentzer index, or Auer rods in Pathology — or Adrenaline reversal, Nitrate tolerance, and "
            "Heparin vs Warfarin in Pharmacology. These appear every single year without fail.",
            S("fin", fontSize=9, leading=14, textColor=DARK_BLUE,
              fontName="Helvetica", alignment=TA_JUSTIFY)
        )
    ]], colWidths=[PAGE_W - 2*MARGIN])
    final.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), LIGHT_BLUE),
        ("BOX", (0,0), (-1,-1), 1.5, MED_BLUE),
        ("TOPPADDING", (0,0), (-1,-1), 10),
        ("BOTTOMPADDING", (0,0), (-1,-1), 10),
        ("LEFTPADDING", (0,0), (-1,-1), 12),
        ("RIGHTPADDING", (0,0), (-1,-1), 12),
    ]))
    story.append(final)

    # ── Page numbers callback ──────────────────────────────────────
    def add_page_num(canvas, doc):
        canvas.saveState()
        canvas.setFont("Helvetica", 8)
        canvas.setFillColor(MID_GREY)
        canvas.drawCentredString(PAGE_W/2, 8*mm,
            f"II MBBS High-Yield Study Guide  •  Page {doc.page}  •  Orris AI Examiner Analysis")
        canvas.restoreState()

    doc.build(story, onFirstPage=add_page_num, onLaterPages=add_page_num)
    print(f"PDF generated: {OUTPUT}")
    print(f"Pages: done")

build_doc()