General Pathology - High-Yield Exam Notes

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, PageBreak, KeepTogether
)
from reportlab.lib.enums import TA_LEFT, TA_CENTER, TA_JUSTIFY
from reportlab.platypus import BaseDocTemplate, Frame, PageTemplate

OUTPUT_PATH = "/home/daytona/workspace/pathology-notes/General_Pathology_Study_Guide.pdf"

# ── Colour palette ──────────────────────────────────────────────────────────
DARK_BLUE   = colors.HexColor("#1a3a5c")
MID_BLUE    = colors.HexColor("#2563a8")
LIGHT_BLUE  = colors.HexColor("#dbeafe")
ACCENT_RED  = colors.HexColor("#b91c1c")
ACCENT_GOLD = colors.HexColor("#b45309")
LIGHT_GOLD  = colors.HexColor("#fef3c7")
LIGHT_GREEN = colors.HexColor("#dcfce7")
LIGHT_RED   = colors.HexColor("#fee2e2")
LIGHT_GREY  = colors.HexColor("#f3f4f6")
MED_GREY    = colors.HexColor("#6b7280")
WHITE       = colors.white
BLACK       = colors.black

# ── Styles ───────────────────────────────────────────────────────────────────
base = getSampleStyleSheet()

def style(name, parent="Normal", **kw):
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COVER_SUB   = style("CoverSub",   fontSize=14, leading=20,
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COVER_BOOK  = style("CoverBook",  fontSize=9,  leading=14,
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PART_TITLE  = style("PartTitle",  fontSize=18, leading=24,
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H2          = style("H2",         fontSize=11, leading=15,
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H3          = style("H3",         fontSize=10, leading=13,
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BODY        = style("Body",       fontSize=9,  leading=13,
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SUB_BULLET  = style("SubBullet",  fontSize=8.5, leading=12,
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TIP_STYLE   = style("Tip",        fontSize=8.5, leading=12,
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FOOTER_S    = style("Footer",     fontSize=7,  leading=9,
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# ── Helper builders ──────────────────────────────────────────────────────────

def part_banner(title):
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        ("RIGHTPADDING",  (0,0), (-1,-1), 12),
        ("ROUNDEDCORNERS", [4]),
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    return t

def section_banner(title):
    """Medium blue banner for section headings."""
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def tip_box(text):
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def bullet(text, indent=0):
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    return Paragraph(f"&#8226; {text}", s)

def body(text):
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def sp(h=4):
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def make_table(headers, rows, col_widths=None, stripe=True):
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        ("VALIGN",        (0,0), (-1,-1), "MIDDLE"),
    ]
    t.setStyle(TableStyle(cmd))
    return t

def highlight_table(data_rows, col_widths=None):
    """Two-column key-value highlight table (gold bg header)."""
    if col_widths is None:
        col_widths = [8*cm, 9*cm]
    hdr_s = ParagraphStyle("HTH", fontSize=8.5, leading=11,
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    cell_s = ParagraphStyle("HTC", fontSize=8, leading=11, textColor=BLACK)
    fmt = []
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        if i == 0:
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    t.setStyle(TableStyle([
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        ("RIGHTPADDING",  (0,0), (-1,-1), 5),
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    return t

# ── Page template with header/footer ─────────────────────────────────────────

def add_page_decorations(canvas, doc):
    canvas.saveState()
    w, h = A4
    # top bar
    canvas.setFillColor(DARK_BLUE)
    canvas.rect(0, h - 18*mm, w, 18*mm, fill=1, stroke=0)
    canvas.setFillColor(WHITE)
    canvas.setFont("Helvetica-Bold", 9)
    canvas.drawString(15*mm, h - 11*mm, "General Pathology — Exam Study Guide")
    canvas.setFont("Helvetica", 8)
    canvas.drawRightString(w - 15*mm, h - 11*mm, "Based on Robbins Pathology")
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    canvas.setFillColor(WHITE)
    canvas.setFont("Helvetica", 7)
    canvas.drawCentredString(w/2, 3.5*mm, f"Page {doc.page}")
    canvas.restoreState()

# ── Cover page ────────────────────────────────────────────────────────────────

def cover_page():
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    # big blue block
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    ct.setStyle(TableStyle([
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        ("LEFTPADDING",   (0,0), (-1,-1), 20),
        ("RIGHTPADDING",  (0,0), (-1,-1), 20),
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    elems.append(Spacer(1, 2*cm))
    elems.append(ct)
    elems.append(sp(10))
    elems.append(Paragraph("EXAM STUDY GUIDE", style("CS2", fontSize=16,
                            textColor=MID_BLUE, alignment=TA_CENTER, fontName="Helvetica-Bold")))
    elems.append(sp(6))
    elems.append(HRFlowable(width="80%", thickness=2, color=MID_BLUE, hAlign="CENTER"))
    elems.append(sp(10))

    topics = [
        ("PART 1", "Cell Injury, Cell Death & Adaptations"),
        ("PART 2", "Inflammation & Repair"),
        ("PART 3", "Neoplasia"),
    ]
    for part, topic in topics:
        row_data = [[
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                                  fontName="Helvetica-Bold", alignment=TA_CENTER)),
            Paragraph(topic, style(f"T_{part}", fontSize=10, textColor=DARK_BLUE,
                                   fontName="Helvetica-Bold")),
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        rt.setStyle(TableStyle([
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        elems.append(rt)
        elems.append(sp(3))

    elems.append(sp(20))
    elems.append(HRFlowable(width="60%", thickness=1, color=MED_GREY, hAlign="CENTER"))
    elems.append(sp(6))
    elems.append(Paragraph(
        "Source: Robbins Basic Pathology &amp; Robbins, Cotran &amp; Kumar Pathologic Basis of Disease",
        style("Src", fontSize=8, textColor=MED_GREY, alignment=TA_CENTER)))
    elems.append(PageBreak())
    return elems

# ── Content ───────────────────────────────────────────────────────────────────

def part1():
    e = []
    e.append(part_banner("PART 1 — CELL INJURY, CELL DEATH & ADAPTATIONS"))
    e.append(sp(6))

    # Key definitions
    e.append(KeepTogether([
        section_banner("KEY DEFINITIONS"),
        sp(4),
        bullet("<b>Etiology</b> — the cause/origin of a disease (the <i>why</i>)"),
        bullet("<b>Pathogenesis</b> — the steps/mechanisms by which disease develops (the <i>how</i>)"),
        bullet("<b>Morphology</b> — structural changes in cells/tissues that characterise a disease"),
        bullet("<b>Homeostasis</b> — the steady state that cells maintain by adapting to their environment"),
    ]))
    e.append(sp(8))

    # Cellular response spectrum
    e.append(section_banner("CELLULAR RESPONSES TO STRESS"))
    e.append(sp(4))
    e.append(make_table(
        ["Stress Level", "Cell Response", "Outcome"],
        [
            ["Mild / reversible", "Adaptation (hypertrophy, hyperplasia, atrophy, metaplasia)", "New steady state"],
            ["Moderate", "Reversible cell injury", "Cell swelling, fatty change"],
            ["Severe / prolonged", "Irreversible injury → Cell Death", "Necrosis or Apoptosis"],
        ],
        col_widths=[4*cm, 8*cm, 5*cm]
    ))
    e.append(sp(8))

    # Causes of cell injury
    e.append(section_banner("CAUSES OF CELL INJURY"))
    e.append(sp(4))
    causes = [
        ("<b>Hypoxia &amp; Ischemia</b>", "Most common cause; ATP depletion is the key event"),
        ("<b>Physical agents</b>", "Trauma, extreme temperature, radiation, electric shock"),
        ("<b>Chemical agents &amp; drugs</b>", "Poisons, pollutants, therapeutic drugs"),
        ("<b>Infectious agents</b>", "Viruses, bacteria, fungi, parasites"),
        ("<b>Immunologic reactions</b>", "Autoimmune disease, hypersensitivity"),
        ("<b>Genetic defects</b>", "Mutations causing protein dysfunction"),
        ("<b>Nutritional imbalances</b>", "Deficiencies or excess"),
    ]
    e.append(make_table(
        ["Cause", "Notes"],
        causes,
        col_widths=[5.5*cm, 11.5*cm]
    ))
    e.append(sp(8))

    # Reversible vs Irreversible
    e.append(section_banner("REVERSIBLE vs IRREVERSIBLE INJURY"))
    e.append(sp(4))
    e.append(make_table(
        ["Feature", "Reversible", "Irreversible"],
        [
            ["Hallmark", "Cell swelling, fatty change", "Membrane damage, lysosomal rupture"],
            ["Mitochondria", "Swollen, amorphous densities", "Flocculent densities"],
            ["Key event", "ATP depletion", "Ca²⁺ influx + membrane destruction"],
            ["Outcome", "Cell recovers", "Necrosis or apoptosis"],
        ],
        col_widths=[4*cm, 6.5*cm, 6.5*cm]
    ))
    e.append(sp(8))

    # Mechanisms of injury
    e.append(section_banner("MECHANISMS OF CELL INJURY — THE BIG 5"))
    e.append(sp(4))
    mechs = [
        ("1. Mitochondrial dysfunction", "ATP depletion → Na⁺/K⁺ pump fails → cell swelling"),
        ("2. Oxidative stress (ROS)", "Damage DNA, lipids, proteins; generated by reperfusion, drugs, radiation"),
        ("3. Membrane damage", "Lysosomal leakage, mitochondrial permeability, plasma membrane damage"),
        ("4. Calcium influx", "Activates destructive enzymes: phospholipases, proteases, endonucleases, ATPases"),
        ("5. DNA damage / ER stress", "Misfolded proteins → unfolded protein response → cell death"),
    ]
    e.append(make_table(
        ["Mechanism", "Consequence"],
        mechs,
        col_widths=[5.5*cm, 11.5*cm]
    ))
    e.append(sp(8))

    # Necrosis vs Apoptosis
    e.append(section_banner("NECROSIS vs APOPTOSIS"))
    e.append(sp(4))
    e.append(make_table(
        ["Feature", "Necrosis", "Apoptosis"],
        [
            ["Cause", "Hypoxia, toxins, severe injury", "Physiologic or pathologic signals"],
            ["Cell size", "Swells (oncosis)", "Shrinks"],
            ["Nucleus", "Karyolysis / karyorrhexis / pyknosis", "Fragmentation (ladder on gel)"],
            ["Membrane", "Disrupted", "Intact (forms blebs)"],
            ["Inflammation", "YES — contents spill out", "NO — phagocytosed cleanly"],
            ["Energy needed", "No (passive)", "Yes (active, caspase-mediated)"],
        ],
        col_widths=[4*cm, 6.5*cm, 6.5*cm]
    ))
    e.append(sp(6))

    e.append(Paragraph("<b>Types of Necrosis:</b>", H2))
    types = [
        ("<b>Coagulative</b>", "Most organs (heart, kidney); ghost cells, structure preserved", "Ischemic infarct"),
        ("<b>Liquefactive</b>", "Brain infarct; bacterial abscesses; enzymes dissolve tissue", "Brain stroke, abscess"),
        ("<b>Caseous</b>", "Soft cheese-like; surrounded by granuloma; AFB positive", "Tuberculosis"),
        ("<b>Fat</b>", "Saponification, chalky deposits (Ca²⁺ + fatty acids)", "Acute pancreatitis, breast"),
        ("<b>Fibrinoid</b>", "Immune complexes in vessel walls", "Malignant HTN, vasculitis"),
        ("<b>Gangrenous</b>", "Dry (coagulative) or wet (liquefactive + infection)", "Diabetic foot, limb ischemia"),
    ]
    e.append(make_table(
        ["Type", "Features", "Example"],
        types,
        col_widths=[3.5*cm, 9*cm, 4.5*cm]
    ))
    e.append(sp(6))

    e.append(Paragraph("<b>Apoptosis Pathways:</b>", H2))
    e.append(bullet("<b>Intrinsic (mitochondrial):</b> DNA damage / growth factor withdrawal → Bcl-2 family regulation → cytochrome c release → caspase-9 → caspase-3 (executioner)"))
    e.append(bullet("<b>Extrinsic (death receptor):</b> FasL or TNF binds receptor → DISC → caspase-8 → caspase-3"))
    e.append(bullet("<b>Bcl-2</b> is anti-apoptotic — overexpressed in <b>follicular lymphoma t(14;18)</b>"))
    e.append(bullet("<b>p53</b> triggers apoptosis in response to DNA damage via intrinsic pathway"))
    e.append(sp(8))

    # Cellular adaptations
    e.append(section_banner("CELLULAR ADAPTATIONS TO STRESS"))
    e.append(sp(4))
    e.append(make_table(
        ["Adaptation", "Definition", "Physiologic Example", "Pathologic Example"],
        [
            ["Hypertrophy", "↑ cell size", "Uterus in pregnancy; skeletal muscle with exercise", "Cardiac hypertrophy in HTN"],
            ["Hyperplasia", "↑ cell number", "Endometrium in menstrual cycle", "Endometrial hyperplasia (excess estrogen)"],
            ["Atrophy", "↓ cell size + number", "Muscle in weightlessness", "Disuse atrophy, denervation atrophy"],
            ["Metaplasia", "One cell type → another", "None (usually pathologic)", "Barrett esophagus; smoker's bronchi (columnar → squamous)"],
        ],
        col_widths=[3*cm, 3.5*cm, 5.5*cm, 5*cm]
    ))
    e.append(sp(4))
    e.append(tip_box("Metaplasia is REVERSIBLE, but predisposes to dysplasia and cancer if the stimulus persists."))
    e.append(sp(8))

    # Intracellular depositions
    e.append(section_banner("INTRACELLULAR ACCUMULATIONS & CALCIFICATION"))
    e.append(sp(4))
    e.append(Paragraph("<b>Common Accumulations:</b>", H2))
    e.append(bullet("<b>Fatty change (steatosis)</b> — liver, heart; in alcoholism, obesity, DM"))
    e.append(bullet("<b>Protein bodies</b> — Mallory bodies (alcoholic liver disease), Russell bodies (plasma cells)"))
    e.append(bullet("<b>Glycogen</b> — DM, glycogen storage diseases"))
    e.append(Paragraph("<b>Pigments:</b>", H3))
    pigments = [
        ["Lipofuscin", "'Wear-and-tear' pigment", "Brown granules in aging/atrophied cells"],
        ["Hemosiderin", "Iron from degraded hemoglobin", "Hemosiderosis (local) vs Hemochromatosis (systemic)"],
        ["Melanin", "Normal skin pigment", "Excess in Addison disease"],
        ["Carbon (anthracite)", "Inhaled carbon particles", "Anthracosis — coal miners' lung"],
    ]
    e.append(make_table(["Pigment", "Origin", "Significance"], pigments,
                        col_widths=[4*cm, 6*cm, 7*cm]))
    e.append(sp(5))

    e.append(Paragraph("<b>Pathologic Calcification:</b>", H2))
    e.append(make_table(
        ["Type", "Serum Ca²⁺", "Site", "Examples"],
        [
            ["Dystrophic", "NORMAL", "Dead / necrotic tissue", "TB foci, atherosclerosis, dead parasites, fat necrosis"],
            ["Metastatic", "HIGH (hypercalcemia)", "Normal tissue", "Hyperparathyroidism, sarcoidosis, hypervitaminosis D"],
        ],
        col_widths=[3.5*cm, 3*cm, 4*cm, 6.5*cm]
    ))
    e.append(PageBreak())
    return e


def part2():
    e = []
    e.append(part_banner("PART 2 — INFLAMMATION & REPAIR"))
    e.append(sp(6))

    e.append(section_banner("OVERVIEW OF INFLAMMATION"))
    e.append(sp(4))
    e.append(body("Inflammation is a protective vascular-connective tissue response that eliminates the cause of injury, removes damaged tissue, and initiates repair. It can be harmful when excessive (e.g., sepsis, autoimmunity, atherosclerosis)."))
    e.append(sp(4))
    e.append(Paragraph("<b>Cardinal Signs (Celsus + Virchow):</b>", H2))
    signs = [
        ["<b>Rubor</b>", "Redness", "Vasodilation → ↑ blood flow"],
        ["<b>Calor</b>", "Heat", "↑ Blood flow to affected area"],
        ["<b>Tumor</b>", "Swelling", "↑ Vascular permeability → oedema"],
        ["<b>Dolor</b>", "Pain", "Bradykinin, PGE2, serotonin"],
        ["<b>Functio laesa</b>", "Loss of function", "Combination of all above"],
    ]
    e.append(make_table(["Sign", "Meaning", "Mechanism"], signs,
                        col_widths=[3*cm, 4*cm, 10*cm]))
    e.append(sp(8))

    e.append(section_banner("RECOGNITION — PATTERN RECOGNITION RECEPTORS (PRRs)"))
    e.append(sp(4))
    e.append(bullet("<b>Toll-like receptors (TLRs)</b> — on cell surface &amp; endosomes; recognise PAMPs and DAMPs"))
    e.append(bullet("<b>NOD-like receptors (NLRs)</b> — cytosolic; form the <b>Inflammasome</b> → activates IL-1β"))
    e.append(bullet("<b>PAMPs</b> = pathogen-associated molecular patterns (e.g., LPS, bacterial DNA)"))
    e.append(bullet("<b>DAMPs</b> = damage-associated molecular patterns (e.g., leaked DNA, ATP, uric acid)"))
    e.append(sp(8))

    e.append(section_banner("ACUTE INFLAMMATION"))
    e.append(sp(4))
    e.append(body("Three major components: (1) vasodilation, (2) ↑ vascular permeability, (3) leukocyte emigration — primarily in <b>postcapillary venules</b>."))
    e.append(sp(4))

    e.append(Paragraph("<b>Leukocyte Recruitment — Step by Step:</b>", H2))
    steps = [
        ["1. Margination", "Stasis → leukocytes move to vessel periphery"],
        ["2. Rolling", "Selectins (E/P-selectin on endothelium; L-selectin on leukocyte)"],
        ["3. Adhesion", "ICAM-1 (endothelium) + Integrins LFA-1/Mac-1 (leukocyte)"],
        ["4. Transmigration", "PECAM-1 (CD31) — diapedesis through vessel wall"],
        ["5. Chemotaxis", "C5a, LTB4, IL-8, bacterial fMLP — directional migration"],
        ["6. Phagocytosis", "Recognition (opsonins: IgG, C3b) → engulfment → killing"],
    ]
    e.append(make_table(["Step", "Key Molecules / Details"], steps,
                        col_widths=[4*cm, 13*cm]))
    e.append(sp(5))

    e.append(Paragraph("<b>Phagocytosis &amp; Killing:</b>", H2))
    e.append(bullet("<b>Opsonins:</b> IgG (Fc receptor) and C3b (CR1/CR3) coat the target"))
    e.append(bullet("<b>Oxidative killing:</b> NADPH oxidase → O₂⁻ → H₂O₂; myeloperoxidase + H₂O₂ + Cl⁻ → HOCl (most potent)"))
    e.append(bullet("<b>Non-oxidative killing:</b> defensins, lysozyme, lactoferrin, BPI"))

    e.append(sp(5))
    e.append(Paragraph("<b>Leukocyte Defects (HIGH YIELD):</b>", H2))
    defects = [
        ["Chronic Granulomatous Disease (CGD)", "Defective NADPH oxidase", "Catalase-positive organisms (S. aureus, Aspergillus, Pseudomonas)"],
        ["Chediak-Higashi Syndrome", "Defective lysosomal fusion (LYST gene)", "Recurrent pyogenic infections; giant granules in neutrophils"],
        ["LAD (Leukocyte Adhesion Deficiency)", "Absent CD18 (β2-integrin)", "Delayed umbilical cord separation; no pus formation"],
        ["MPO deficiency", "Absent myeloperoxidase", "Usually asymptomatic; ↑ Candida infections in DM"],
    ]
    e.append(make_table(["Disorder", "Defect", "Clinical Feature"],
                        defects, col_widths=[5*cm, 5*cm, 7*cm]))
    e.append(sp(8))

    e.append(section_banner("CHEMICAL MEDIATORS OF INFLAMMATION"))
    e.append(sp(4))
    mediators = [
        ["<b>Histamine</b>", "Mast cells, platelets", "Vasodilation, ↑ permeability (early, fast)"],
        ["<b>Serotonin</b>", "Platelets", "↑ Permeability"],
        ["<b>PGE2 / PGI2</b> (COX)", "Arachidonic acid → COX", "Vasodilation, fever, pain sensitisation"],
        ["<b>LTB4</b> (LOX)", "Arachidonic acid → LOX", "Neutrophil chemotaxis"],
        ["<b>LTC4/D4/E4</b> (LOX)", "Mast cells, eosinophils", "Bronchoconstriction, ↑ permeability (slow-reacting SRS-A)"],
        ["<b>TNF &amp; IL-1</b>", "Macrophages", "Fever, acute-phase response, endothelial activation"],
        ["<b>IL-6</b>", "Macrophages, T cells", "Induces acute-phase proteins (CRP, fibrinogen) from liver"],
        ["<b>IL-8 (CXCL8)</b>", "Macrophages, endothelium", "Neutrophil chemotaxis"],
        ["<b>C3a / C5a</b>", "Complement (liver)", "Anaphylatoxins; C5a = chemotaxis + opsonin; MAC = lysis"],
        ["<b>Bradykinin</b>", "Kinin system", "Pain, vasodilation, ↑ permeability"],
        ["<b>NO</b>", "Endothelium, macrophages", "Vasodilation; kills microbes"],
    ]
    e.append(make_table(["Mediator", "Source", "Action"],
                        mediators, col_widths=[4*cm, 5.5*cm, 7.5*cm]))
    e.append(sp(4))
    e.append(tip_box("Drug targets: Aspirin/NSAIDs → block COX → ↓ PGs. Corticosteroids → block phospholipase A2 → ↓ ALL AA metabolites. Montelukast → blocks LT receptors (asthma)."))
    e.append(sp(8))

    e.append(section_banner("MORPHOLOGIC PATTERNS OF ACUTE INFLAMMATION"))
    e.append(sp(4))
    patterns = [
        ["<b>Serous</b>", "Watery, protein-poor fluid leaks into body cavities", "Viral pleuritis, skin blister"],
        ["<b>Fibrinous</b>", "Fibrin exudate; 'bread-and-butter' appearance", "Fibrinous pericarditis, lobar pneumonia"],
        ["<b>Suppurative / Purulent</b>", "Pus = neutrophils + liquefied debris; abscess = walled-off", "Bacterial meningitis, empyema, liver abscess"],
        ["<b>Ulcer</b>", "Epithelial defect exposing underlying tissue", "Peptic ulcer, aphthous stomatitis"],
    ]
    e.append(make_table(["Pattern", "Features", "Examples"],
                        patterns, col_widths=[3.5*cm, 8.5*cm, 5*cm]))
    e.append(sp(8))

    e.append(section_banner("OUTCOMES OF ACUTE INFLAMMATION"))
    e.append(sp(4))
    e.append(bullet("<b>Resolution</b> — complete restoration; most viral infections"))
    e.append(bullet("<b>Abscess formation</b> — walling off of infection with pus"))
    e.append(bullet("<b>Fibrosis / Scarring</b> — if tissue cannot regenerate"))
    e.append(bullet("<b>Progression to chronic inflammation</b> — persistent stimulus"))
    e.append(sp(8))

    e.append(section_banner("CHRONIC INFLAMMATION"))
    e.append(sp(4))
    e.append(body("Duration: weeks to months. Mononuclear cells predominate. Caused by persistent infection, autoimmune disease, or prolonged exposure to toxic agents."))
    e.append(sp(4))

    e.append(Paragraph("<b>Key Cells:</b>", H2))
    cells = [
        ["Macrophages", "Most important; activated by IFN-γ from T cells; produce TNF, IL-12, ROS, lysosomal enzymes"],
        ["Lymphocytes (CD4⁺ T)", "Activate macrophages via IFN-γ; crosstalk amplifies response"],
        ["Plasma cells", "Secrete antibodies; Russell bodies visible"],
        ["Eosinophils", "Parasitic infections; allergic reactions; contain major basic protein"],
        ["Mast cells", "IgE-mediated; release histamine, heparin, cytokines"],
    ]
    e.append(make_table(["Cell", "Role"], cells, col_widths=[4.5*cm, 12.5*cm]))
    e.append(sp(6))

    e.append(Paragraph("<b>Granulomatous Inflammation:</b>", H2))
    e.append(body("Special form of chronic inflammation with <b>epithelioid macrophages</b> (activated, eosinophilic cytoplasm), <b>Langhans giant cells</b> (horseshoe-shaped nuclei), surrounded by CD4⁺ T lymphocytes."))
    e.append(sp(4))

    granulomas = [
        ["<b>Tuberculosis</b>", "Caseating (central cheese-like necrosis)", "AFB positive (Ziehl-Neelsen stain)"],
        ["<b>Sarcoidosis</b>", "'Naked' non-caseating granuloma", "↑ ACE; bilateral hilar adenopathy"],
        ["<b>Leprosy</b>", "Lepromatous (foamy macrophages) or tuberculoid", "AFB + in lepromatous type"],
        ["<b>Crohn disease</b>", "Non-caseating; skip lesions in GI tract", "Transmural inflammation"],
        ["<b>Berylliosis</b>", "Non-caseating; exposure to beryllium", "Mimics sarcoidosis clinically"],
        ["<b>Foreign body</b>", "Giant cells around foreign material", "Sutures, silica, talc"],
        ["<b>Cat-scratch disease</b>", "Stellate granuloma with necrosis", "Bartonella henselae"],
    ]
    e.append(make_table(["Disease", "Type", "Key Feature"],
                        granulomas, col_widths=[4*cm, 7*cm, 6*cm]))
    e.append(tip_box("Naked granuloma = Sarcoidosis (no caseation). Caseating granuloma = TB. Always AFB stain for TB!"))
    e.append(sp(8))

    e.append(section_banner("SYSTEMIC EFFECTS — ACUTE PHASE RESPONSE"))
    e.append(sp(4))
    e.append(bullet("<b>Fever:</b> IL-1, TNF, IL-6 → COX in hypothalamus → ↑ PGE2 → ↑ set point"))
    e.append(bullet("<b>Acute-phase proteins</b> (from liver, induced by IL-6): CRP ↑, fibrinogen ↑, haptoglobin ↑, ferritin ↑; albumin ↓, transferrin ↓"))
    e.append(bullet("<b>Leukocytosis:</b> Bacterial = neutrophilia; Viral = lymphocytosis; Parasites/allergy = eosinophilia; Left shift = ↑ bands (immature neutrophils)"))
    e.append(bullet("<b>Septic shock:</b> Systemic TNF + IL-1 → ↓ BP, DIC, multi-organ failure"))
    e.append(sp(8))

    e.append(section_banner("TISSUE REPAIR"))
    e.append(sp(4))
    e.append(make_table(
        ["Cell Type", "Examples", "Regenerative Capacity"],
        [
            ["<b>Labile</b> (always dividing)", "GI epithelium, skin, bone marrow, oral mucosa", "Excellent — replace themselves continuously"],
            ["<b>Stable</b> (quiescent, re-enter cycle)", "Liver, kidney, fibroblasts, osteoblasts", "Good — regenerate on demand"],
            ["<b>Permanent</b> (cannot divide)", "Neurons, cardiac muscle, skeletal muscle", "Poor — replaced by scar tissue"],
        ],
        col_widths=[4*cm, 7*cm, 6*cm]
    ))
    e.append(sp(5))
    e.append(Paragraph("<b>Steps in Scar Formation:</b>", H2))
    e.append(bullet("Granulation tissue forms: fibroblasts + new capillaries (angiogenesis via VEGF, FGF)"))
    e.append(bullet("Fibroblast activation and collagen deposition — <b>TGF-β is the master regulator</b>"))
    e.append(bullet("Remodeling: MMPs (matrix metalloproteinases) balance collagen synthesis vs. degradation"))
    e.append(sp(5))
    e.append(Paragraph("<b>Factors Impairing Wound Healing:</b>", H2))
    e.append(make_table(
        ["Factor", "Mechanism"],
        [
            ["Infection", "Prolongs inflammation, delays repair"],
            ["Malnutrition (Vit C deficiency)", "Impairs collagen synthesis (prolyl/lysyl hydroxylase needs Vit C)"],
            ["Poor blood supply / ischemia", "Lack of O₂ and nutrients"],
            ["Diabetes mellitus", "↑ Infection, glycosylation of collagen, neuropathy"],
            ["Corticosteroids", "Inhibit fibroblast proliferation, ↓ TGF-β"],
            ["Mechanical stress / movement", "Disrupts scar tissue formation"],
        ],
        col_widths=[6*cm, 11*cm]
    ))
    e.append(PageBreak())
    return e


def part3():
    e = []
    e.append(part_banner("PART 3 — NEOPLASIA"))
    e.append(sp(6))

    e.append(section_banner("DEFINITIONS"))
    e.append(sp(4))
    e.append(bullet("<b>Neoplasia:</b> abnormal, uncontrolled, purposeless cell proliferation that persists after the initiating stimulus is removed"))
    e.append(bullet("<b>Benign tumor:</b> grows locally, does NOT invade or metastasise; well-differentiated"))
    e.append(bullet("<b>Malignant tumor:</b> can invade locally AND metastasise; variable differentiation"))
    e.append(bullet("<b>Dysplasia:</b> disordered growth — pre-malignant; may regress or progress to carcinoma in situ"))
    e.append(bullet("<b>Carcinoma in situ (CIS):</b> full-thickness dysplasia with intact basement membrane"))
    e.append(sp(8))

    e.append(section_banner("NOMENCLATURE"))
    e.append(sp(4))
    e.append(make_table(
        ["Cell Origin", "Benign", "Malignant"],
        [
            ["Squamous epithelium", "Squamous papilloma", "Squamous cell carcinoma"],
            ["Glandular epithelium", "Adenoma", "Adenocarcinoma"],
            ["Fibrous tissue", "Fibroma", "Fibrosarcoma"],
            ["Smooth muscle", "Leiomyoma", "Leiomyosarcoma"],
            ["Skeletal muscle", "Rhabdomyoma", "Rhabdomyosarcoma"],
            ["Cartilage", "Chondroma", "Chondrosarcoma"],
            ["Bone", "Osteoma", "Osteosarcoma"],
            ["Melanocytes", "Melanocytic nevus (mole)", "Melanoma"],
            ["Lymphoid tissue", "—", "Lymphoma"],
            ["Hematopoietic cells", "—", "Leukemia"],
        ],
        col_widths=[5.5*cm, 5.5*cm, 6*cm]
    ))
    e.append(sp(5))
    e.append(Paragraph("<b>Special Terms:</b>", H2))
    e.append(bullet("<b>Hamartoma:</b> disorganised mass of native tissue (e.g., pulmonary hamartoma — cartilage, glands, fat)"))
    e.append(bullet("<b>Choristoma:</b> normal tissue in the wrong location (e.g., gastric mucosa in Meckel's diverticulum)"))
    e.append(bullet("<b>Teratoma:</b> all 3 germ layers; mature (benign, cystic) vs. immature (malignant)"))
    e.append(sp(8))

    e.append(section_banner("BENIGN vs MALIGNANT TUMORS"))
    e.append(sp(4))
    e.append(make_table(
        ["Feature", "Benign", "Malignant"],
        [
            ["Differentiation", "Well-differentiated", "Variable; may be anaplastic"],
            ["Mitoses", "Rare, normal", "Frequent, abnormal (tripolar, multipolar)"],
            ["Nuclear changes", "Normal", "Pleomorphism, ↑ N:C ratio, prominent nucleoli, hyperchromatism"],
            ["Growth rate", "Slow", "Fast"],
            ["Local invasion", "Expansile, encapsulated", "Infiltrative, NOT encapsulated"],
            ["Metastasis", "NO", "YES — hallmark of malignancy"],
            ["Necrosis", "Rare", "Common (outgrows blood supply)"],
        ],
        col_widths=[4*cm, 6.5*cm, 6.5*cm]
    ))
    e.append(sp(4))
    e.append(tip_box("Anaplasia features: Pleomorphism, hyperchromatism, giant tumor cells, ABNORMAL mitoses, prominent nucleoli, loss of polarity."))
    e.append(sp(8))

    e.append(section_banner("HALLMARKS OF CANCER (Hanahan & Weinberg)"))
    e.append(sp(4))
    hallmarks = [
        ["1. Self-sufficiency in growth signals", "Oncogenes mimic growth factor signalling (RAS, MYC, EGFR)"],
        ["2. Insensitivity to growth inhibitory signals", "Loss of tumour suppressors (RB, TP53, APC)"],
        ["3. Evasion of apoptosis", "Overexpression of Bcl-2; loss of p53; survival signals"],
        ["4. Limitless replicative potential", "Telomerase activation — bypasses Hayflick limit"],
        ["5. Sustained angiogenesis", "VEGF, FGF secretion; 'angiogenic switch' at ~1mm³ tumour size"],
        ["6. Invasion and metastasis", "↓ E-cadherin, ↑ MMPs, epithelial-mesenchymal transition (EMT)"],
        ["7. Evasion of immune surveillance", "PD-L1/PD-1 axis, ↓ MHC-I, CTLA-4, TGF-β secretion"],
        ["8. Altered metabolism (Warburg effect)", "Aerobic glycolysis even in O₂; ↑ glucose uptake (PET imaging)"],
        ["9. Tumour-promoting inflammation", "Tumour-associated macrophages supply growth factors"],
        ["10. Genome instability", "↑ mutation rate; microsatellite instability; chromosomal instability"],
    ]
    e.append(make_table(["Hallmark", "Mechanism / Key Points"],
                        hallmarks, col_widths=[6*cm, 11*cm]))
    e.append(sp(8))

    e.append(section_banner("KEY CANCER GENES"))
    e.append(sp(4))
    e.append(Paragraph("<b>Oncogenes (gain-of-function mutations):</b>", H2))
    oncogenes = [
        ["<b>RAS</b>", "Point mutation → GTPase stays 'on'", "Colon, pancreas, lung"],
        ["<b>MYC</b>", "Amplification / translocation t(8;14)", "Burkitt lymphoma"],
        ["<b>HER2/NEU</b>", "Amplification", "Breast cancer (trastuzumab target)"],
        ["<b>BCR-ABL</b>", "t(9;22) Philadelphia chromosome", "CML (imatinib target)"],
        ["<b>RET</b>", "Point mutation (germline)", "MEN2, medullary thyroid CA"],
        ["<b>EGFR</b>", "Mutation / amplification", "Lung adenocarcinoma, CRC"],
        ["<b>BRAF V600E</b>", "Point mutation", "Melanoma, papillary thyroid CA, hairy cell leukemia"],
    ]
    e.append(make_table(["Oncogene", "Mechanism", "Associated Cancer"],
                        oncogenes, col_widths=[3.5*cm, 7*cm, 6.5*cm]))
    e.append(sp(6))

    e.append(Paragraph("<b>Tumour Suppressor Genes (loss-of-function — Knudson Two-Hit):</b>", H2))
    tsgs = [
        ["<b>RB (Rb)</b>", "Cell cycle brake at G1→S checkpoint", "Retinoblastoma, osteosarcoma"],
        ["<b>TP53</b>", "'Guardian of genome' — DNA repair, apoptosis, cell cycle arrest", "Li-Fraumeni; most human cancers (>50%)"],
        ["<b>APC</b>", "WNT/β-catenin signalling suppressor", "FAP, sporadic colon cancer"],
        ["<b>BRCA1/2</b>", "DNA repair (homologous recombination)", "Breast, ovarian cancer"],
        ["<b>CDKN2A (p16)</b>", "CDK4 inhibitor; halts G1 progression", "Melanoma, pancreatic cancer"],
        ["<b>VHL</b>", "Regulates HIF-1α stability", "Clear cell renal cell carcinoma"],
        ["<b>WT1</b>", "Transcription factor in renal development", "Wilms tumor (nephroblastoma)"],
        ["<b>NF1/NF2</b>", "RAS-GAP / Merlin (cytoskeletal)", "Neurofibromatosis type 1/2"],
    ]
    e.append(make_table(["Gene", "Function", "Associated Cancer"],
                        tsgs, col_widths=[3.5*cm, 8*cm, 5.5*cm]))
    e.append(tip_box("Knudson Two-Hit Hypothesis: Both alleles of a TSG must be inactivated. In hereditary cancers, one hit is inherited (germline) and the second is somatic."))
    e.append(sp(8))

    e.append(section_banner("INVASION & METASTASIS"))
    e.append(sp(4))
    e.append(Paragraph("<b>Steps in Metastasis:</b>", H2))
    msteps = ["Local invasion (↓ E-cadherin, ↑ MMPs, EMT)",
              "Intravasation into blood vessels or lymphatics",
              "Survival in circulation (immune evasion, platelet clumping)",
              "Extravasation at distant site",
              "Colonisation (organ-specific — 'seed and soil' hypothesis, Paget 1889)"]
    for i, s in enumerate(msteps, 1):
        e.append(bullet(f"<b>{i}.</b> {s}"))
    e.append(sp(5))

    e.append(make_table(
        ["Route", "Common Tumors", "Typical Sites"],
        [
            ["Hematogenous", "Sarcomas, choriocarcinoma, thyroid, renal", "Liver, lung, bone, brain"],
            ["Lymphatic", "Carcinomas (most common route)", "Regional lymph nodes first"],
            ["Seeding of body cavities", "Colon, ovary, gastric", "Peritoneum; Krukenberg tumor (gastric → both ovaries)"],
            ["Transcoelomic / CSF spread", "Medulloblastoma, ependymoma", "Spinal cord (drop metastases)"],
        ],
        col_widths=[4*cm, 6*cm, 7*cm]
    ))
    e.append(sp(8))

    e.append(section_banner("CARCINOGENIC AGENTS"))
    e.append(sp(4))
    carcinogens = [
        ["<b>Polycyclic hydrocarbons</b> (tobacco smoke)", "Chemical", "Lung, bladder, oropharynx"],
        ["<b>Aflatoxin B1</b> (Aspergillus flavus)", "Chemical / dietary", "Hepatocellular carcinoma"],
        ["<b>Benzene</b>", "Chemical", "AML / leukemia"],
        ["<b>Vinyl chloride</b>", "Chemical", "Angiosarcoma of liver"],
        ["<b>Arsenic</b>", "Chemical", "Skin, lung, bladder"],
        ["<b>Nitrosamines</b> (smoked/pickled food)", "Chemical / dietary", "Gastric, esophageal"],
        ["<b>UV light</b> (pyrimidine dimers → XPC)", "Radiation", "Melanoma, BCC, SCC of skin"],
        ["<b>Ionising radiation</b>", "Radiation", "Leukemia, thyroid CA, breast CA"],
        ["<b>HPV 16/18</b> (E6→p53↓, E7→RB↓)", "Viral", "Cervical, oropharyngeal"],
        ["<b>EBV</b>", "Viral", "Burkitt lymphoma, Hodgkin lymphoma, NPC, PTLD"],
        ["<b>HBV / HCV</b>", "Viral", "Hepatocellular carcinoma"],
        ["<b>HTLV-1</b>", "Viral", "Adult T-cell leukemia/lymphoma"],
        ["<b>HHV-8 (KSHV)</b>", "Viral", "Kaposi sarcoma"],
        ["<b>H. pylori</b>", "Bacterial", "Gastric adenocarcinoma, MALT lymphoma"],
    ]
    e.append(make_table(["Agent", "Category", "Associated Cancer"],
                        carcinogens, col_widths=[5.5*cm, 4*cm, 7.5*cm]))
    e.append(sp(8))

    e.append(section_banner("PARANEOPLASTIC SYNDROMES"))
    e.append(sp(4))
    para = [
        ["Hypercalcemia", "PTHrP secretion", "Squamous cell CA (lung), breast, renal"],
        ["SIADH (↓ Na⁺)", "ADH-like peptide secretion", "Small cell lung cancer (SCLC)"],
        ["Cushing syndrome", "ACTH-like peptide secretion", "SCLC, carcinoid"],
        ["Polycythemia (↑ RBC)", "Ectopic EPO production", "Renal cell CA, hepatocellular CA"],
        ["Migratory thrombophlebitis (Trousseau sign)", "Mucin activates clotting cascade", "Pancreatic CA, GI cancers"],
        ["Eaton-Lambert syndrome", "Anti-VGCC antibodies", "SCLC"],
        ["Acanthosis nigricans", "TGF-α / other growth factors", "Gastric, lung, GI cancers"],
        ["Cerebellar degeneration", "Anti-Yo (anti-Purkinje cell)", "Ovarian, breast cancer"],
    ]
    e.append(make_table(["Syndrome", "Mechanism", "Tumor Type"],
                        para, col_widths=[5.5*cm, 5.5*cm, 6*cm]))
    e.append(sp(8))

    e.append(section_banner("RAPID REVIEW — HIGH-YIELD BUZZWORD TABLE"))
    e.append(sp(4))
    buzz = [
        ["High-Yield Fact", "Answer"],
        ["Most common cause of cell injury", "Hypoxia / Ischemia"],
        ["'Guardian of the genome'", "p53 (TP53)"],
        ["Anti-apoptotic gene in follicular lymphoma", "Bcl-2 — t(14;18)"],
        ["Caseous necrosis + granuloma", "Tuberculosis"],
        ["Non-caseating granuloma", "Sarcoidosis"],
        ["'Bread-and-butter' pericarditis", "Fibrinous inflammation"],
        ["Defective NADPH oxidase", "Chronic Granulomatous Disease (CGD)"],
        ["Philadelphia chromosome t(9;22)", "CML — BCR-ABL (imatinib)"],
        ["t(8;14) MYC translocation", "Burkitt lymphoma"],
        ["Knudson Two-Hit Hypothesis", "Both alleles of TSG must be hit — e.g., RB"],
        ["Seed and soil hypothesis", "Paget — organ tropism in metastasis"],
        ["Hallmark of malignancy", "Metastasis"],
        ["Warburg effect", "Aerobic glycolysis in tumours (PET uses this)"],
        ["HPV E6 protein", "Degrades / inactivates p53"],
        ["HPV E7 protein", "Inactivates RB (pRb)"],
        ["Wear-and-tear pigment", "Lipofuscin"],
        ["Dystrophic vs metastatic calcification", "Dystrophic = normal Ca²⁺; Metastatic = high Ca²⁺"],
        ["Labile vs permanent cells", "Labile regenerate; permanent replaced by scar"],
        ["Master cytokine in scar formation", "TGF-β"],
        ["Angiogenesis growth factor", "VEGF (also FGF)"],
        ["Macrophage activating cytokine", "IFN-γ (from T cells)"],
        ["Acute-phase protein inducer", "IL-6"],
    ]
    e.append(highlight_table(buzz, col_widths=[8*cm, 9*cm]))
    e.append(sp(8))

    e.append(HRFlowable(width="100%", thickness=1.5, color=DARK_BLUE))
    e.append(sp(6))
    e.append(Paragraph(
        "<i>Source: Robbins Basic Pathology (Kumar, Abbas, Aster) &amp; Robbins and Cotran Pathologic Basis of Disease. "
        "All content is for educational/exam preparation purposes.</i>",
        style("Src2", fontSize=7.5, textColor=MED_GREY, alignment=TA_CENTER)
    ))
    return e


# ── Build PDF ─────────────────────────────────────────────────────────────────

def build():
    doc = SimpleDocTemplate(
        OUTPUT_PATH,
        pagesize=A4,
        leftMargin=2*cm,
        rightMargin=2*cm,
        topMargin=3*cm,
        bottomMargin=2*cm,
        title="General Pathology Exam Study Guide",
        author="Orris AI",
        subject="Robbins Pathology — Cell Injury, Inflammation, Neoplasia",
    )

    story = []
    story += cover_page()
    story += part1()
    story += part2()
    story += part3()

    doc.build(story, onFirstPage=add_page_decorations,
              onLaterPages=add_page_decorations)
    print(f"PDF saved to: {OUTPUT_PATH}")


if __name__ == "__main__":
    build()