#!/usr/bin/env python3
"""
MUHS 2nd MBBS Pathology - Comprehensive Revision PDF
Topics: Malaria, Cysticercosis, Leprosy, Viral/Fungal Infections,
        Primary TB, Ghon's Complex
Based on Robbins & Kumar Pathology
"""

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.platypus.flowables import Flowable
from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_JUSTIFY
from reportlab.pdfgen import canvas
from reportlab.graphics.shapes import Drawing, Rect, String, Line, Circle, Polygon
from reportlab.graphics import renderPDF
import os

OUTPUT_PATH = "/home/daytona/workspace/muhs-study-guide/MUHS_Pathology_Revision.pdf"

# ── COLOUR PALETTE ────────────────────────────────────────────────────────────
C_DARK_BLUE   = colors.HexColor("#1a3a5c")
C_MED_BLUE    = colors.HexColor("#2563a8")
C_LIGHT_BLUE  = colors.HexColor("#dbeafe")
C_TEAL        = colors.HexColor("#0f766e")
C_LIGHT_TEAL  = colors.HexColor("#ccfbf1")
C_RED         = colors.HexColor("#b91c1c")
C_LIGHT_RED   = colors.HexColor("#fee2e2")
C_ORANGE      = colors.HexColor("#c2410c")
C_LIGHT_ORANGE= colors.HexColor("#ffedd5")
C_GREEN       = colors.HexColor("#166534")
C_LIGHT_GREEN = colors.HexColor("#dcfce7")
C_PURPLE      = colors.HexColor("#6b21a8")
C_LIGHT_PURPLE= colors.HexColor("#f3e8ff")
C_YELLOW      = colors.HexColor("#854d0e")
C_LIGHT_YELLOW= colors.HexColor("#fef9c3")
C_DARK_GREY   = colors.HexColor("#374151")
C_MID_GREY    = colors.HexColor("#6b7280")
C_LIGHT_GREY  = colors.HexColor("#f3f4f6")
C_WHITE       = colors.white
C_BLACK       = colors.black

# ── STYLES ────────────────────────────────────────────────────────────────────
styles = getSampleStyleSheet()

def make_style(name, parent='Normal', **kwargs):
    return ParagraphStyle(name, parent=styles[parent], **kwargs)

# Cover / section heading
S_COVER_TITLE = make_style('CoverTitle',
    fontSize=28, textColor=C_WHITE, alignment=TA_CENTER,
    fontName='Helvetica-Bold', spaceAfter=8)

S_COVER_SUB = make_style('CoverSub',
    fontSize=14, textColor=colors.HexColor("#bfdbfe"),
    alignment=TA_CENTER, fontName='Helvetica', spaceAfter=6)

S_SECTION = make_style('Section',
    fontSize=16, textColor=C_WHITE, fontName='Helvetica-Bold',
    alignment=TA_LEFT, spaceAfter=6, spaceBefore=4)

S_SUBSECTION = make_style('Subsection',
    fontSize=12, textColor=C_DARK_BLUE, fontName='Helvetica-Bold',
    spaceAfter=4, spaceBefore=8)

S_BODY = make_style('Body',
    fontSize=9.5, textColor=C_DARK_GREY, fontName='Helvetica',
    leading=14, spaceAfter=4, alignment=TA_JUSTIFY)

S_BULLET = make_style('Bullet',
    fontSize=9.5, textColor=C_DARK_GREY, fontName='Helvetica',
    leading=13, spaceAfter=2, leftIndent=14,
    bulletIndent=4)

S_BULLET2 = make_style('Bullet2',
    fontSize=9, textColor=C_DARK_GREY, fontName='Helvetica',
    leading=12, spaceAfter=1, leftIndent=28, bulletIndent=18)

S_MONO = make_style('Mono',
    fontSize=8.5, textColor=C_DARK_GREY, fontName='Courier',
    leading=12, spaceAfter=2, leftIndent=6)

S_MNEMONIC = make_style('Mnemonic',
    fontSize=10.5, textColor=C_TEAL, fontName='Helvetica-Bold',
    leading=14, spaceAfter=3, alignment=TA_CENTER)

S_KEY = make_style('Key',
    fontSize=9, textColor=C_RED, fontName='Helvetica-Bold',
    leading=13, spaceAfter=2)

S_CAPTION = make_style('Caption',
    fontSize=8, textColor=C_MID_GREY, fontName='Helvetica-Oblique',
    alignment=TA_CENTER, spaceAfter=4)

S_TABLE_HEADER = make_style('TblHdr',
    fontSize=9, textColor=C_WHITE, fontName='Helvetica-Bold',
    alignment=TA_CENTER)

S_TABLE_CELL = make_style('TblCell',
    fontSize=8.5, textColor=C_DARK_GREY, fontName='Helvetica',
    leading=12, alignment=TA_LEFT)

S_TABLE_CELL_C = make_style('TblCellC',
    fontSize=8.5, textColor=C_DARK_GREY, fontName='Helvetica',
    leading=12, alignment=TA_CENTER)

S_SMALL = make_style('Small',
    fontSize=8, textColor=C_MID_GREY, fontName='Helvetica',
    leading=11, spaceAfter=2)

# ── HELPER FLOWABLES ─────────────────────────────────────────────────────────

class ColorBox(Flowable):
    """A rounded-rectangle coloured banner."""
    def __init__(self, text, bg_color, text_color=colors.white,
                 width=None, height=28, font_size=13, bold=True):
        Flowable.__init__(self)
        self.text = text
        self.bg_color = bg_color
        self.text_color = text_color
        self.width = width or (A4[0] - 4*cm)
        self.height = height
        self.font_size = font_size
        self.bold = bold

    def wrap(self, availW, availH):
        self.width = min(self.width, availW)
        return self.width, self.height

    def draw(self):
        c = self.canv
        c.setFillColor(self.bg_color)
        c.roundRect(0, 0, self.width, self.height, 6, fill=1, stroke=0)
        c.setFillColor(self.text_color)
        fn = 'Helvetica-Bold' if self.bold else 'Helvetica'
        c.setFont(fn, self.font_size)
        c.drawCentredString(self.width/2, self.height/2 - self.font_size/2 + 2, self.text)


class DiagramBox(Flowable):
    """Pre-drawn ASCII-art style box using ReportLab lines."""
    def __init__(self, lines, bg=C_LIGHT_GREY, border=C_MED_BLUE,
                 width=None, font_size=8):
        Flowable.__init__(self)
        self.lines = lines
        self.bg = bg
        self.border = border
        self._width = width
        self.font_size = font_size
        self.line_height = font_size + 3
        self.padding = 8

    def wrap(self, availW, availH):
        self._width = self._width or availW
        h = len(self.lines) * self.line_height + 2 * self.padding
        return self._width, h

    def draw(self):
        c = self.canv
        h = len(self.lines) * self.line_height + 2 * self.padding
        c.setFillColor(self.bg)
        c.setStrokeColor(self.border)
        c.setLineWidth(1)
        c.roundRect(0, 0, self._width, h, 5, fill=1, stroke=1)
        c.setFont('Courier', self.font_size)
        c.setFillColor(C_DARK_GREY)
        y = h - self.padding - self.font_size
        for line in self.lines:
            c.drawString(self.padding, y, line)
            y -= self.line_height


def section_banner(title, topic_num, color=C_DARK_BLUE):
    """Returns a list of flowables forming a section header."""
    return [
        Spacer(1, 0.3*cm),
        ColorBox(f"TOPIC {topic_num}  |  {title}", bg_color=color, font_size=13),
        Spacer(1, 0.2*cm),
    ]


def subsection(title, color=C_MED_BLUE):
    return [
        Spacer(1, 0.15*cm),
        ColorBox(title, bg_color=color, height=22, font_size=10.5, text_color=C_WHITE),
        Spacer(1, 0.1*cm),
    ]


def mnemonic_box(title, items, bg=C_LIGHT_TEAL, border=C_TEAL):
    """A nicely styled mnemonic box."""
    content = [
        [Paragraph(f"<b>🧠 MNEMONIC: {title}</b>", make_style('Mn2',
            fontSize=10, textColor=C_TEAL, fontName='Helvetica-Bold',
            alignment=TA_CENTER))],
    ]
    for item in items:
        content.append([Paragraph(item, make_style('Mn3',
            fontSize=9.5, textColor=C_TEAL, fontName='Helvetica',
            alignment=TA_CENTER, leading=13))])
    t = Table(content, colWidths=[A4[0] - 4*cm])
    t.setStyle(TableStyle([
        ('BACKGROUND', (0,0), (-1,-1), bg),
        ('BOX', (0,0), (-1,-1), 1.5, border),
        ('ROUNDEDCORNERS', [6]),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 10),
        ('RIGHTPADDING', (0,0), (-1,-1), 10),
    ]))
    return [t, Spacer(1, 0.2*cm)]


def comparison_table(headers, rows, col_widths=None, header_bg=C_DARK_BLUE):
    """Styled comparison table."""
    header_row = [Paragraph(h, S_TABLE_HEADER) for h in headers]
    table_data = [header_row]
    for r in rows:
        table_data.append([Paragraph(str(c), S_TABLE_CELL) for c in r])
    if col_widths is None:
        n = len(headers)
        col_widths = [(A4[0] - 4*cm) / n] * n
    t = Table(table_data, colWidths=col_widths, repeatRows=1)
    style = [
        ('BACKGROUND', (0,0), (-1,0), header_bg),
        ('TEXTCOLOR', (0,0), (-1,0), C_WHITE),
        ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
        ('FONTSIZE', (0,0), (-1,0), 9),
        ('ALIGN', (0,0), (-1,-1), 'LEFT'),
        ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
        ('ROWBACKGROUNDS', (0,1), (-1,-1), [C_WHITE, C_LIGHT_GREY]),
        ('GRID', (0,0), (-1,-1), 0.5, colors.HexColor("#d1d5db")),
        ('TOPPADDING', (0,0), (-1,-1), 5),
        ('BOTTOMPADDING', (0,0), (-1,-1), 5),
        ('LEFTPADDING', (0,0), (-1,-1), 6),
        ('RIGHTPADDING', (0,0), (-1,-1), 6),
    ]
    t.setStyle(TableStyle(style))
    return [t, Spacer(1, 0.25*cm)]


def key_fact(text):
    return Paragraph(f"<b>★ KEY FACT:</b> {text}", S_KEY)


def bp(text, indent=0):
    """Bullet paragraph."""
    prefix = "• "
    style = S_BULLET if indent == 0 else S_BULLET2
    return Paragraph(f"{prefix}{text}", style)


def divider(color=C_MED_BLUE):
    return HRFlowable(width="100%", thickness=1, color=color,
                      spaceAfter=4, spaceBefore=4)


# ── PAGE TEMPLATE ─────────────────────────────────────────────────────────────

def on_first_page(canvas, doc):
    canvas.saveState()
    # Full-page gradient background
    canvas.setFillColor(C_DARK_BLUE)
    canvas.rect(0, 0, A4[0], A4[1], fill=1, stroke=0)
    # Decorative band at top
    canvas.setFillColor(C_MED_BLUE)
    canvas.rect(0, A4[1]-80, A4[0], 80, fill=1, stroke=0)
    # Decorative band at bottom
    canvas.setFillColor(C_TEAL)
    canvas.rect(0, 0, A4[0], 40, fill=1, stroke=0)
    canvas.restoreState()


def on_later_pages(canvas, doc):
    canvas.saveState()
    # Header bar
    canvas.setFillColor(C_DARK_BLUE)
    canvas.rect(0, A4[1]-25, A4[0], 25, fill=1, stroke=0)
    canvas.setFillColor(C_WHITE)
    canvas.setFont('Helvetica-Bold', 8)
    canvas.drawString(1.5*cm, A4[1]-16, "MUHS 2nd MBBS PATHOLOGY — RAPID REVISION")
    canvas.setFont('Helvetica', 8)
    canvas.drawRightString(A4[0]-1.5*cm, A4[1]-16, "Robbins & Kumar Pathology")
    # Footer
    canvas.setFillColor(C_DARK_BLUE)
    canvas.rect(0, 0, A4[0], 18, fill=1, stroke=0)
    canvas.setFillColor(C_WHITE)
    canvas.setFont('Helvetica', 7.5)
    canvas.drawCentredString(A4[0]/2, 5, f"Page {doc.page}")
    canvas.restoreState()


# ── BUILD CONTENT ─────────────────────────────────────────────────────────────

def build_cover():
    elements = []
    # Large vertical spacer to push content to middle of page
    elements.append(Spacer(1, 5.5*cm))
    # Title
    cover_title_style = make_style('CTMain',
        fontSize=30, textColor=C_WHITE, fontName='Helvetica-Bold',
        alignment=TA_CENTER, spaceAfter=10)
    elements.append(Paragraph("MUHS 2nd MBBS PATHOLOGY", cover_title_style))
    elements.append(Paragraph("COMPREHENSIVE RAPID REVISION", make_style('CT2',
        fontSize=20, textColor=colors.HexColor("#93c5fd"),
        fontName='Helvetica-Bold', alignment=TA_CENTER, spaceAfter=16)))
    elements.append(HRFlowable(width="70%", thickness=2,
                               color=C_TEAL, spaceAfter=16, hAlign='CENTER'))
    # Topics
    topic_style = make_style('CTopic',
        fontSize=11.5, textColor=colors.HexColor("#e0f2fe"),
        fontName='Helvetica', alignment=TA_CENTER, spaceAfter=6, leading=18)
    topics = [
        "1. Malaria – Pathogenesis &amp; Morphology",
        "2. Cysticercosis – Etiopathogenesis &amp; Morphology",
        "3. Leprosy – Pathogenesis, Classification &amp; Findings  ★★★",
        "4. Common Viral &amp; Fungal Infections",
        "5. Primary Tuberculosis – Pathogenesis, Sites &amp; Primary Complex  ★",
        "6. Ghon's Complex – Gross, Microscopic &amp; Fate  ★★★",
    ]
    for t in topics:
        elements.append(Paragraph(t, topic_style))
    elements.append(Spacer(1, 1*cm))
    elements.append(HRFlowable(width="70%", thickness=2,
                               color=C_TEAL, spaceAfter=12, hAlign='CENTER'))
    elements.append(Paragraph("Based on Robbins, Cotran &amp; Kumar — Pathologic Basis of Disease (10e)",
        make_style('CRef', fontSize=9, textColor=colors.HexColor("#bfdbfe"),
                   fontName='Helvetica-Oblique', alignment=TA_CENTER)))
    elements.append(PageBreak())
    return elements


# ────────────────────────────────────────────────────────────────────────────
# TOPIC 1 — MALARIA
# ────────────────────────────────────────────────────────────────────────────
def build_malaria():
    E = []
    E += section_banner("MALARIA", 1, C_RED)

    # Overview box
    overview_lines = [
        "Causative organisms: Plasmodium falciparum (most virulent), P. vivax, P. ovale, P. malariae, P. knowlesi",
        "Vector: Female Anopheles mosquito  |  Reservoir: Humans only",
        "200+ million cases/year worldwide  |  600,000+ deaths/year (mostly children < 5 yrs in Africa)",
    ]
    for l in overview_lines:
        E.append(Paragraph(l, S_BODY))
    E.append(Spacer(1, 0.2*cm))

    # Pathogenesis heading
    E += subsection("PATHOGENESIS — Life Cycle", C_MED_BLUE)

    life_cycle = [
        "  MOSQUITO BITE → Sporozoites enter blood",
        "        ↓",
        "  LIVER (Exo-erythrocytic stage) — ASYMPTOMATIC",
        "  Sporozoites bind hepatocytes (thrombospondin + circumsporozoite protein)",
        "  Sporozoites → Merozoites (up to 30,000 per hepatocyte)",
        "  [P. vivax / P. ovale → form HYPNOZOITES → relapse weeks-months later]",
        "        ↓",
        "  Hepatocytes rupture → Merozoites released into blood",
        "        ↓",
        "  RBC INVASION (Erythrocytic stage) — SYMPTOMATIC",
        "  Merozoites bind sialic acid on glycophorin on RBC surface",
        "  Merozoite → Trophozoite → Schizont → new Merozoites",
        "  P. falciparum: PfEMP1 knobs appear on RBC surface",
        "  RBC LYSIS → merozoites released → fever, chills, rigors (TNF surge)",
        "        ↓",
        "  Some trophozoites → GAMETOCYTES (sexual forms)",
        "  Mosquito ingests gametocytes → restarts cycle",
    ]
    E.append(DiagramBox(life_cycle, bg=C_LIGHT_RED, border=C_RED))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("WHY P. FALCIPARUM IS MORE VIRULENT", C_RED)
    virulence = [
        ("1. Infects ALL ages of RBCs", "Causes high-level parasitemia (vs. only young/old RBCs for other spp.)"),
        ("2. PfEMP1 on RBC surface knobs", "Binds ICAM-1, VCAM-1, CD36, E-selectin on endothelium → SEQUESTRATION in capillaries → blocks blood flow → cerebral malaria"),
        ("3. Rosette formation", "Infected RBCs clump together, worsening blockage"),
        ("4. No hypnozoites", "No relapse, but high acute parasitemia"),
        ("5. Antigenic variation", "Switches PfEMP1 variants each generation → escapes antibody response"),
    ]
    E += comparison_table(["Mechanism", "Effect"],
                          virulence,
                          col_widths=[4.5*cm, 10*cm],
                          header_bg=C_RED)

    E += subsection("FEVER PERIODICITY", C_ORANGE)
    fever_data = [
        ("P. vivax / P. ovale", "Every 48 hours", "Benign tertian malaria"),
        ("P. malariae", "Every 72 hours", "Quartan malaria"),
        ("P. falciparum", "Irregular / every 36-48h", "Malignant tertian malaria (most dangerous)"),
        ("P. knowlesi", "Every 24 hours", "Quotidian / potentially severe"),
    ]
    E += comparison_table(["Species", "Periodicity", "Type"],
                          fever_data, header_bg=C_ORANGE)

    E += subsection("MORPHOLOGY — Organ Changes", C_MED_BLUE)
    morphology_data = [
        ("SPLEEN", "Splenomegaly (may exceed 1000g), gray-black hemozoin pigment, red pulp congestion+hyperplasia; chronic → fibrotic, brittle, thick capsule"),
        ("LIVER", "Enlarged, pigmented; Kupffer cells laden with malarial pigment, parasitized RBCs, cellular debris"),
        ("BRAIN\n(P. falciparum)", "Vessels PLUGGED with parasitized RBCs; ring hemorrhages; Dürck granuloma (malarial granuloma); neuronal degeneration; focal ischemic softening"),
        ("KIDNEY", "Enlarged, congested; malarial pigment in glomeruli; hemoglobin casts in tubules (Blackwater fever = massive hemolysis + hemoglobinuria)"),
        ("BONE MARROW / LYMPH NODES", "Pigmented phagocytic cells; hemozoin pigment throughout"),
        ("BLOOD SMEAR\n(Diagnostic)", "Giemsa stain: ring trophozoites, schizonts, gametocytes inside RBCs. Ring forms with double chromatin dot = P. falciparum"),
    ]
    E += comparison_table(["Organ", "Findings"],
                          morphology_data,
                          col_widths=[3.5*cm, 11*cm],
                          header_bg=C_MED_BLUE)

    E += mnemonic_box("Plasmodium species",
        ["'Fever Very Often Makes People Sick'",
         "F = Falciparum  |  V = Vivax  |  O = Ovale  |  M = Malariae  |  P = P. knowlesi  |  S = Sporozoite entry"],
        bg=C_LIGHT_RED, border=C_RED)

    E += mnemonic_box("P. falciparum virulence — 'SCAR'",
        ["S = Sequestration (PfEMP1 binds endothelium)",
         "C = Can infect all age RBCs",
         "A = Antigenic variation (escapes immunity)",
         "R = Rosette formation"],
        bg=C_LIGHT_ORANGE, border=C_ORANGE)

    E.append(key_fact("Diagnostic test = Giemsa-stained peripheral blood smear. Dürck granuloma = pathognomonic of cerebral malaria."))
    E.append(PageBreak())
    return E


# ────────────────────────────────────────────────────────────────────────────
# TOPIC 2 — CYSTICERCOSIS
# ────────────────────────────────────────────────────────────────────────────
def build_cysticercosis():
    E = []
    E += section_banner("CYSTICERCOSIS", 2, C_PURPLE)

    E.append(Paragraph(
        "<b>Definition:</b> Disease caused by <b>larvae (cysticercus)</b> of <i>Taenia solium</i> "
        "(pork tapeworm) when HUMANS act as the <b>INTERMEDIATE HOST</b>.", S_BODY))
    E.append(Spacer(1, 0.15*cm))

    host_data = [
        ("NORMAL life cycle", "Pig = Intermediate host (harbors cysticercus)\nHuman = Definitive host (harbors adult tapeworm in intestine)"),
        ("CYSTICERCOSIS", "HUMAN = Intermediate host (ingests eggs, develops cysticerci in tissues)"),
    ]
    E += comparison_table(["Condition", "Host Role"], host_data,
                          col_widths=[4.5*cm, 10*cm], header_bg=C_PURPLE)

    E += subsection("ETIOPATHOGENESIS", C_PURPLE)
    patho = [
        "  Human ingests T. solium EGGS (contaminated food/water/fecal-oral route)",
        "        ↓",
        "  Eggs hatch in intestine → ONCOSPHERES (hexacanth embryos with 6 hooklets)",
        "        ↓",
        "  Oncospheres penetrate intestinal wall → enter bloodstream",
        "        ↓",
        "  Haematogenous dissemination to TISSUES",
        "        ↓",
        "  Develop into CYSTICERCI (fluid-filled cysts with invaginated scolex)",
        "        ↓",
        "  PREFERRED SITES: Brain, Subcutaneous tissue, Eye, Skeletal muscle, Heart, Liver",
        "        ↓",
        "  ALIVE CYST → minimal inflammation (immune evasion by cyst)",
        "  DYING/DEAD CYST → intense inflammatory response → granuloma → calcification",
    ]
    E.append(DiagramBox(patho, bg=C_LIGHT_PURPLE, border=C_PURPLE))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("CLINICAL FEATURES BY SITE", C_MED_BLUE)
    clinical = [
        ("Neurocysticercosis (NCC)", "Most dangerous; seizures (most common cause of acquired epilepsy in endemic areas), headache, raised ICP, hydrocephalus, focal neurological deficits"),
        ("Ocular cysticercosis", "Floaters, visual disturbances, blindness (subretinal/vitreous cyst)"),
        ("Subcutaneous", "Palpable, non-tender nodules; calcify on X-ray"),
        ("Muscular", "Pseudohypertrophy of muscles; calcified cysts on imaging"),
    ]
    E += comparison_table(["Site", "Manifestations"], clinical,
                          col_widths=[4*cm, 10.5*cm], header_bg=C_MED_BLUE)

    E += subsection("MORPHOLOGY", C_PURPLE)
    E.append(Paragraph("<b>GROSS FEATURES:</b>", S_SUBSECTION))
    gross = [
        "Round/oval translucent fluid-filled cyst, 0.5–2 cm (up to 20 cm in racemose form)",
        "White, glistening wall; SCOLEX visible as white nodule inside",
        "RACEMOSE variant: grapelike cluster, no scolex, found in cisterns/ventricles of brain",
        "Calcified cysts visible on plain X-ray as 'puffed rice' calcifications (in muscles)",
    ]
    for g in gross:
        E.append(bp(g))

    E.append(Spacer(1, 0.15*cm))
    E.append(Paragraph("<b>MICROSCOPIC FEATURES (3 stages):</b>", S_SUBSECTION))
    micro_data = [
        ("VIABLE CYST", "Outer cuticular layer (lamellar, eosinophilic)\nMiddle cellular (reticular) layer\nInner germinal layer\nScolex with suckers and hooklets visible\nMinimal host inflammatory response"),
        ("DEGENERATING/\nDEAD CYST", "Cyst wall hyalinizes and breaks down\nINTENSE INFLAMMATION:\n• Eosinophils, neutrophils, lymphocytes\n• Plasma cells, macrophages\nGranuloma formation with giant cells"),
        ("CALCIFIED CYST\n(Healed)", "Dense calcification of dead scolex and wall\nFibrosis/gliosis surrounding (in brain)\n'Ghost' of cyst remains"),
    ]
    E += comparison_table(["Stage", "Microscopic Features"], micro_data,
                          col_widths=[4*cm, 10.5*cm], header_bg=C_PURPLE)

    E += mnemonic_box("Cysticercosis — 'CHEST'",
        ["C = Cyst (fluid-filled, with scolex)",
         "H = Hooklets on scolex (6 hooklets in oncosphere)",
         "E = Eggs ingested (fecal-oral route)",
         "S = Seizures (most common presentation — NCC)",
         "T = Taenia solium (pork tapeworm)"],
        bg=C_LIGHT_PURPLE, border=C_PURPLE)

    E.append(key_fact("Neurocysticercosis = most common cause of acquired epilepsy in developing countries. Diagnosis: CT/MRI + serology (EITB). Treatment: Albendazole + steroids."))
    E.append(PageBreak())
    return E


# ────────────────────────────────────────────────────────────────────────────
# TOPIC 3 — LEPROSY ★★★
# ────────────────────────────────────────────────────────────────────────────
def build_leprosy():
    E = []
    E += section_banner("LEPROSY (Hansen Disease)  ★★★", 3, C_TEAL)

    E.append(Paragraph(
        "<b>Causative organism:</b> <i>Mycobacterium leprae</i> (and rarely M. lepromatosis). "
        "Slow progressive infection affecting <b>SKIN and PERIPHERAL NERVES</b>. "
        "Cannot be cultured in vitro. Proliferates best at <b>32–34°C</b> (cool tissues). "
        "Transmission via <b>human respiratory secretions</b>.", S_BODY))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("PATHOGENESIS", C_TEAL)
    patho = [
        "  M. leprae enters via respiratory tract",
        "        ↓",
        "  Taken up by DERMAL MACROPHAGES",
        "        ↓",
        "  Disseminates via blood → replicates in COOL TISSUES (skin, extremities, peripheral nerves)",
        "  PGL-1 lipid: invasion of host cells   |   Inhibits mitochondrial energy metabolism",
        "        ↓",
        "       HOST IMMUNE RESPONSE determines disease pattern:",
        "        ↙                                            ↘",
        "   STRONG Th1                                   WEAK Th1",
        "  (IL-2, IFN-γ, Th17)                       (Th2/Reg-T dominant)",
        "        ↓                                            ↓",
        "  TUBERCULOID LEPROSY                       LEPROMATOUS LEPROSY",
        "  (Paucibacillary)                          (Multibacillary)",
        "  Granulomas present                        No granulomas",
        "  Low bacterial load                        High bacterial load",
        "  Nerve destruction dominant                Diffuse skin/nerve invasion",
    ]
    E.append(DiagramBox(patho, bg=C_LIGHT_TEAL, border=C_TEAL))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("CLASSIFICATION", C_TEAL)
    E.append(Paragraph("<b>Ridley-Jopling Classification (Spectrum):</b>", S_SUBSECTION))
    spectrum_lines = [
        "  TUBERCULOID (TT) ←── BT ──── BB ──── BL ───→ LEPROMATOUS (LL)",
        "  |←────────── STRONG IMMUNITY ──────── WEAK IMMUNITY ──────────→|",
        "  |←───────── PAUCIBACILLARY ──────── MULTIBACILLARY ───────────→|",
        "  |←──── FEW SKIN LESIONS ────────── MANY SKIN LESIONS ─────────→|",
    ]
    E.append(DiagramBox(spectrum_lines, bg=C_LIGHT_TEAL, border=C_TEAL))
    E.append(Spacer(1, 0.1*cm))
    E.append(Paragraph("<b>WHO Classification (Clinical Use):</b>", S_SUBSECTION))
    who_data = [
        ("Paucibacillary (PB)", "1–5 skin lesions", "Tuberculoid / Borderline-T", "MDT 6 months"),
        ("Multibacillary (MB)", ">5 skin lesions", "Lepromatous / Borderline-L", "MDT 12 months"),
    ]
    E += comparison_table(["WHO Type", "Skin Lesions", "Ridley-Jopling", "MDT Duration"],
                          who_data, header_bg=C_TEAL)

    E += subsection("IMMUNOLOGY COMPARISON", C_MED_BLUE)
    immune_data = [
        ("T-cell response", "Strong Th1 (IFN-γ, IL-2)", "Weak Th1 / Th2 dominant"),
        ("Bacterial load", "Low (paucibacillary)", "High (multibacillary)"),
        ("Granulomas", "Well-formed, like TB", "Absent — lepra cells instead"),
        ("Antibodies", "Low", "High (but NOT protective — may cause vasculitis)"),
        ("Cell-mediated immunity", "Intact", "Deficient"),
        ("Lepromin test", "POSITIVE", "NEGATIVE"),
        ("Nerve involvement", "Asymmetric, destructive", "Symmetric, less inflamed"),
        ("Skin lesions", "Few, hypopigmented, anesthetic", "Multiple, nodular, leonine"),
    ]
    E += comparison_table(["Feature", "Tuberculoid", "Lepromatous"],
                          immune_data,
                          col_widths=[4.5*cm, 5.5*cm, 4.5*cm],
                          header_bg=C_MED_BLUE)

    E += subsection("GROSS (CLINICAL) FINDINGS", C_TEAL)
    E.append(Paragraph("<b>Tuberculoid Leprosy:</b>", S_KEY))
    tub_clinical = [
        "Flat red lesions → enlarge with indurated, elevated, hyperpigmented margins + depressed pale centres (central healing)",
        "ASYMMETRIC large peripheral nerve involvement (ulnar, radial, peroneal, great auricular)",
        "Skin ANESTHESIA (destroyed nerves)",
        "Muscle atrophy, contractures, chronic ulcers, autoamputation of digits",
        "Facial nerve palsy → eyelid paralysis → keratitis, corneal ulcers",
    ]
    for t in tub_clinical:
        E.append(bp(t))

    E.append(Spacer(1, 0.1*cm))
    E.append(Paragraph("<b>Lepromatous Leprosy:</b>", S_KEY))
    lep_clinical = [
        "SYMMETRIC skin thickening; macular, papular, or NODULAR lesions on face, ears, wrists, elbows, knees",
        "Nodules coalesce → LEONINE FACIES (lion-like face)",
        "Saddle-nose deformity (nasal bone destruction)",
        "Hyposthetic / anesthetic skin lesions",
        "Bacilli-laden nasal discharge",
        "Testes: extensive involvement → destruction of seminiferous tubules → sterility + gynecomastia",
        "Symmetric nerve invasion (ulnar, peroneal) with minimal inflammation",
    ]
    for l in lep_clinical:
        E.append(bp(l))

    E += subsection("MICROSCOPIC FINDINGS", C_TEAL)
    micro_data = [
        ("TUBERCULOID", "Well-formed GRANULOMAS (like TB)\nEpithelioid cells + Langhans giant cells\nDense lymphocytic infiltrate\nGranulomas enclose & DESTROY NERVES\nBacilli ABSENT / very rare (AFB -ve)\nName = PAUCIBACILLARY"),
        ("LEPROMATOUS", "Large aggregates of LIPID-LADEN MACROPHAGES = LEPRA CELLS (Virchow cells)\nLepra cells packed with GLOBI (masses of AFB)\nGlobi look like 'cigar bundles' on AFB stain\nNO granulomas (CMI absent)\nGRENZ ZONE (clear subepidermal zone)\nBacilli abundant — MULTIBACILLARY\nTestes: destruction of seminiferous tubules"),
    ]
    E += comparison_table(["Type", "Microscopic Features"], micro_data,
                          col_widths=[3.5*cm, 11*cm], header_bg=C_TEAL)

    # Lepra cell diagram
    lepra_cell = [
        "          LEPRA CELL DIAGRAM (Lepromatous Leprosy)",
        "    ┌─────────────────────────────────────────────┐",
        "    │          MACROPHAGE (Virchow Cell)           │",
        "    │                                             │",
        "    │   [====AFB====]  [====AFB====]  [==AFB==]   │",
        "    │      GLOBUS 1       GLOBUS 2     GLOBUS 3   │",
        "    │    (masses of acid-fast bacilli in bundles) │",
        "    │                                             │",
        "    │          FOAMY CYTOPLASM (lipid-filled)      │",
        "    │                  [ NUCLEUS ]                │",
        "    └─────────────────────────────────────────────┘",
        "    Stain: Ziehl-Neelsen (AFB) — red bacilli on blue bg",
    ]
    E.append(DiagramBox(lepra_cell, bg=C_LIGHT_TEAL, border=C_TEAL))
    E.append(Spacer(1, 0.15*cm))

    # Langhans giant cell diagram
    lang_cell = [
        "     LANGHANS GIANT CELL DIAGRAM (Tuberculoid / TB)",
        "    ┌──────────────────────────────────────────────┐",
        "    │                                              │",
        "    │         O  O  O  O  O                        │",
        "    │      O                    O                  │",
        "    │                                              │",
        "    │        LARGE PINK CYTOPLASM                  │",
        "    │      (fused epithelioid cells)               │",
        "    │                                              │",
        "    │      O                    O                  │",
        "    │         O  O  O  O  O                        │",
        "    │   Nuclei arranged in HORSESHOE / PERIPHERAL  │",
        "    │             PATTERN (key feature)            │",
        "    └──────────────────────────────────────────────┘",
    ]
    E.append(DiagramBox(lang_cell, bg=C_LIGHT_BLUE, border=C_MED_BLUE))
    E.append(Spacer(1, 0.15*cm))

    E += mnemonic_box("Types of Leprosy — 'TT BB LL (Two Ts, Two Bs, Two Ls)'",
        ["TT = Tuberculoid (one extreme)",
         "BB = Borderline (middle)",
         "LL = Lepromatous (other extreme)",
         "BT = Borderline Tuberculoid  |  BL = Borderline Lepromatous"],
        bg=C_LIGHT_TEAL, border=C_TEAL)

    E += mnemonic_box("LEPRA CELL vs EPITHELIOID CELL — 'Lepra = Lipid-laden, Lepromatous'",
        ["Lepra Cell = Lipid-laden macrophage = Lepromatous = Low immunity = Lots of bacilli",
         "Epithelioid Cell = Elongated macrophage = TB granuloma / Tuberculoid leprosy"],
        bg=C_LIGHT_YELLOW, border=C_YELLOW)

    E.append(key_fact("Leonine facies + saddle nose = Lepromatous leprosy. Anesthetic lesion with thickened peripheral nerve = Tuberculoid leprosy. Most disfiguring = Lepromatous."))
    E.append(PageBreak())
    return E


# ────────────────────────────────────────────────────────────────────────────
# TOPIC 4 — VIRAL & FUNGAL INFECTIONS
# ────────────────────────────────────────────────────────────────────────────
def build_viral_fungal():
    E = []
    E += section_banner("COMMON VIRAL & FUNGAL INFECTIONS", 4, C_ORANGE)

    # VIRAL
    E += subsection("COMMON VIRAL INFECTIONS", C_ORANGE)

    viral_data = [
        ("INFLUENZA", "Type A, B, C\n(RNA virus, 8 segments)\nH and N surface proteins",
         "Antigenic drift (mutations) = epidemics\nAntigenic shift (recombination with animal virus) = PANDEMICS",
         "Diffuse alveolar damage (DAD)\nHyaline membranes\nInterstitial pneumonitis"),
        ("SARS-CoV-2\n(COVID-19)", "Enveloped +ve sense RNA\nSpike protein binds ACE2 on type II alveolar cells + nasopharynx",
         "Viral replication → immune overactivation\n'Cytokine storm'\nCoagulopathy, microthrombi",
         "DAD with hyaline membranes\nMicrothrombi in vessels\nMyocarditis, CNS infiltrates"),
        ("HERPES SIMPLEX\n(HSV-1/2)", "DNA virus (Herpesviridae)\nLatent in ganglia → reactivation",
         "Cell-to-cell spread\nImmune evasion via latency",
         "Cowdry type A intranuclear inclusions\nMultinucleated giant cells with 'ground-glass' nuclei"),
        ("CMV", "Large DNA virus\nDangerous in immunocompromised\n(AIDS, transplant patients)",
         "Reactivation when CMI falls",
         "OWL-EYE intranuclear inclusions (large, purple, surrounded by halo)\nSmaller cytoplasmic inclusions"),
        ("MEASLES\n(Rubeola)", "RNA Paramyxovirus\nDroplet transmission",
         "Enters via respiratory epithelium\nViraemia → dissemination",
         "Warthin-Finkeldey multinucleated giant cells (in lymphoid tissue)\nKoplik spots (buccal mucosa)\nSquamous metaplasia of bronchial epithelium"),
        ("EBV", "DNA Herpesvirus\nB-cell tropism",
         "EBV infects B cells via CD21\nPolyclonal B-cell proliferation",
         "Atypical lymphocytes (Downey cells)\nReactive germinal centres\nAssociated with Burkitt lymphoma, nasopharyngeal carcinoma"),
    ]
    E += comparison_table(
        ["Virus", "Features", "Pathogenesis", "Histology"],
        viral_data,
        col_widths=[2.5*cm, 4*cm, 4.5*cm, 3.5*cm],
        header_bg=C_ORANGE)

    E += subsection("VIRAL INCLUSION BODIES — EASY TABLE", C_RED)
    inclusion_data = [
        ("Cowdry type A (intranuclear)", "HSV, CMV, Yellow Fever", "Large eosinophilic, marginated chromatin"),
        ("Owl-eye inclusions (intranuclear)", "CMV", "Large purple nuclear inclusion + smaller cytoplasmic ones"),
        ("Negri bodies (cytoplasmic)", "Rabies", "Eosinophilic inclusions in neurons (hippocampus, cerebellum)"),
        ("Warthin-Finkeldey giant cells", "Measles", "Multinucleated giant cells in lymphoid tissue"),
        ("Henderson-Patterson bodies", "Molluscum contagiosum", "Large cytoplasmic inclusions"),
        ("Guarnieri bodies (cytoplasmic)", "Smallpox / Vaccinia", "Viral factories in cytoplasm"),
    ]
    E += comparison_table(["Inclusion Body", "Virus", "Description"],
                          inclusion_data,
                          col_widths=[4.5*cm, 3.5*cm, 6.5*cm],
                          header_bg=C_RED)

    # FUNGAL
    E += subsection("COMMON FUNGAL INFECTIONS", C_GREEN)
    fungal_data = [
        ("CANDIDA ALBICANS\n(Candidiasis)", "Pseudohyphae + budding yeast\nPAS / GMS stain",
         "Immunocompromise (neutropenia, AIDS)\nDiabetes, broad-spectrum antibiotics",
         "Superficial: Thrush, vaginitis\nDeep: esophageal, systemic\nNeutrophilic infiltrate with pseudohyphae invading tissue"),
        ("ASPERGILLUS\n(Aspergillosis)", "SEPTATE hyphae\n45° ACUTE ANGLE branching\nGMS / H&E stain",
         "Immunocompromised (neutropenic)\nPre-existing lung cavities\nAtopic patients (ABPA)",
         "3 forms: 1) Aspergilloma (fungal ball in cavity)\n2) ABPA (allergic, eosinophilic)\n3) Invasive: angioinvasion → infarction + hemorrhage"),
        ("CRYPTOCOCCUS\nNEOFORMANS", "Encapsulated yeast\nIndia ink: CLEAR HALO (capsule)\nMucicarmine stain: magenta capsule",
         "Inhalation from pigeon droppings\nOpportunistic in AIDS (CD4 < 200)",
         "Soap-bubble lesions in brain (gelatinous pseudocysts)\nMinimal inflammation in AIDS\nMeningoencephalitis\n'Gumball' appearance on Mucicarmine"),
        ("MUCOR / RHIZOPUS\n(Mucormycosis)", "BROAD non-septate hyphae\n90° RIGHT ANGLE branching\nGMS stain",
         "Diabetics (DKA) — rhinocerebral form\nNeutropenic patients — pulmonary form",
         "Angioinvasion → thrombosis → tissue INFARCTION\nRhinocerebral: orbit, palate, sinuses\nBlack necrotic eschars"),
        ("HISTOPLASMA\nCAPSULATUM", "Small intracellular yeast (2–4 μm)\nInside macrophages\nGMS / PAS stain",
         "Ohio/Mississippi river valleys\nInhalation of bird/bat droppings",
         "Mimics TB: granulomas, caseous necrosis, calcification\nTiny yeast inside macrophages\nDisseminated in AIDS (hepatosplenomegaly)"),
        ("PNEUMOCYSTIS\n(PCP)", "Cysts with 8 intracystic bodies\nGMS stain: dark cysts\nSilver stain",
         "Opportunistic: AIDS (CD4 < 200)\nImmunocompromised (transplant)",
         "Interstitial pneumonia\nFrothy, pink alveolar exudate ('cotton-candy' or 'honeycomb')\nNo granulomas"),
    ]
    E += comparison_table(
        ["Fungus", "Morphology/Stain", "Risk Factors", "Pathology"],
        fungal_data,
        col_widths=[2.8*cm, 3.5*cm, 3.5*cm, 4.7*cm],
        header_bg=C_GREEN)

    E += mnemonic_box("Fungal Hyphae — 'SANE vs BROAD'",
        ["SANE = Septate Acute aNgle = Aspergillus (45° branching)",
         "BROAD = Broad Right-angle Obtuse Angle Dimorphic = Mucor (90° branching, non-septate)"],
        bg=C_LIGHT_GREEN, border=C_GREEN)

    E += mnemonic_box("India Ink Stain — 'Crypto needs a CAP'",
        ["Cryptococcus = India Ink = Clear halo (Clear = Capsule = Crypto)"],
        bg=C_LIGHT_GREEN, border=C_GREEN)

    E.append(key_fact("Invasive Aspergillosis = angioinvasion (like Mucor). Mucor = Right angle, non-septate. Aspergillus = 45° acute angle, septate. CMV = Owl-eye. HSV = Cowdry A."))
    E.append(PageBreak())
    return E


# ────────────────────────────────────────────────────────────────────────────
# TOPIC 5 — PRIMARY TUBERCULOSIS ★
# ────────────────────────────────────────────────────────────────────────────
def build_primary_tb():
    E = []
    E += section_banner("PRIMARY TUBERCULOSIS  ★", 5, C_DARK_BLUE)

    E.append(Paragraph(
        "<b>Definition:</b> Form of TB that develops in a <b>previously unexposed and unsensitized</b> individual. "
        "About <b>5%</b> of newly infected individuals develop significant disease. "
        "Caused by <i>Mycobacterium tuberculosis</i> — acid-fast bacillus (AFB), transmitted by <b>respiratory droplets</b>.", S_BODY))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("PATHOGENESIS", C_DARK_BLUE)
    patho = [
        " INHALATION of M. tuberculosis droplets",
        "       ↓",
        " PHASE 1 — INNATE RESPONSE (first ~3 weeks) — ASYMPTOMATIC",
        " Bacilli reach alveoli → phagocytosed by ALVEOLAR MACROPHAGES",
        " M. tb prevents phagolysosome fusion → survives inside macrophages",
        " Bacilli replicate → macrophages release chemokines → more monocytes recruited",
        " DENDRITIC CELLS carry mycobacterial antigens to HILAR LYMPH NODES",
        "       ↓",
        " PHASE 2 — ADAPTIVE IMMUNITY (~3 weeks) — Th1 RESPONSE",
        " DCs present antigens → Th1 cell differentiation (requires IL-12, IL-18)",
        " Th1 cells produce IFN-γ (CRITICAL mediator)",
        "       ↓",
        " IFN-γ activates macrophages → 3 mechanisms to kill bacteria:",
        "   1. Produces nitric oxide (NO) + reactive oxygen species (ROS)",
        "   2. Mobilizes defensins (cathelicidin)",
        "   3. Stimulates AUTOPHAGY (sequesters & destroys bacilli)",
        "       ↓",
        " Activated macrophages → EPITHELIOID HISTIOCYTES",
        "       ↓",
        " GRANULOMA FORMATION + CASEOUS NECROSIS",
        "       ↓",
        " 95%: Infection CONTAINED → Ghon complex heals → Ranke complex",
        " 5%: Progressive Primary TB (immunocompromised, HIV, malnutrition)",
    ]
    E.append(DiagramBox(patho, bg=C_LIGHT_BLUE, border=C_DARK_BLUE))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("COMMON SITES OF PRIMARY TB", C_DARK_BLUE)
    sites_data = [
        ("1st", "LUNGS (>95%)", "Subpleural; lower part of UPPER LOBE or upper part of LOWER LOBE (close to pleura)"),
        ("2nd", "INTESTINE (ileum)", "From ingestion of M. bovis (infected milk) — rare now"),
        ("3rd", "TONSIL / PHARYNX", "Very rare; from oral entry"),
        ("4th", "SKIN", "Primary inoculation TB (rare)"),
    ]
    E += comparison_table(["Rank", "Site", "Notes"],
                          sites_data,
                          col_widths=[1.5*cm, 4*cm, 9*cm],
                          header_bg=C_DARK_BLUE)

    E += subsection("EVOLUTION OF THE TUBERCLE (GRANULOMA) — 5 STAGES", C_MED_BLUE)
    stages = [
        "STAGE 1 — INITIAL MACROPHAGE ACCUMULATION",
        "  Local accumulation of macrophages (HISTIOCYTES) at site of infection",
        "",
        "STAGE 2 — EPITHELIOID GRANULOMA",
        "  Macrophages transform into EPITHELIOID CELLS",
        "  (elongated, pink cytoplasm, 'footprint-shaped' nuclei — look like epithelium but ARE macrophages)",
        "  Surrounded by LYMPHOCYTES (mainly CD4+ Th1 cells)",
        "",
        "STAGE 3 — LANGHANS GIANT CELL FORMATION",
        "  Epithelioid cells fuse → LANGHANS GIANT CELLS",
        "  KEY FEATURE: Nuclei arranged in HORSESHOE / PERIPHERAL pattern",
        "",
        "STAGE 4 — CASEOUS NECROSIS",
        "  Centre becomes CASEOUS = cheese-like, amorphous, eosinophilic material",
        "  Due to DTH (delayed-type hypersensitivity) reaction",
        "  Caseous necrosis = PATHOGNOMONIC of TB",
        "",
        "STAGE 5 — RESOLUTION OR PROGRESSION",
        "  A) Fibrosis → Calcification (Ranke complex) — HEALING",
        "  B) Liquefaction → Cavity formation — SECONDARY TB",
    ]
    E.append(DiagramBox(stages, bg=C_LIGHT_BLUE, border=C_DARK_BLUE))
    E.append(Spacer(1, 0.2*cm))

    # Tubercle diagram
    tubercle = [
        "        TB GRANULOMA (TUBERCLE) — DIAGRAM",
        "   ┌──────────────────────────────────────────────────┐",
        "   │  ┌────────────────────────────────────────────┐  │",
        "   │  │  ~~~ CASEOUS NECROSIS (CENTRE) ~~~         │  │",
        "   │  │  ~~~  (amorphous, cheese-like,   ~~~       │  │",
        "   │  │  ~~~   eosinophilic material)    ~~~       │  │",
        "   │  └────────────────────────────────────────────┘  │",
        "   │  [Epi][Epi]  LANGHANS GIANT CELL  [Epi][Epi]     │",
        "   │              O  O  O  O  O                        │",
        "   │           O (horseshoe nuclei) O                  │",
        "   │              O  O  O  O  O                        │",
        "   │  [Lym][Lym][Epi][Epi][Epi][Lym][Lym][Lym]       │",
        "   │       Lymphocytes surround epithelioid cells      │",
        "   │  === FIBROUS CAPSULE (outer layer) ===            │",
        "   └──────────────────────────────────────────────────┘",
        "   Epi = Epithelioid cell  |  Lym = Lymphocyte",
    ]
    E.append(DiagramBox(tubercle, bg=C_LIGHT_BLUE, border=C_DARK_BLUE))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("PRIMARY COMPLEX — COMPONENTS  ★", C_RED)
    E.append(Paragraph(
        "The <b>Ghon's Complex (Primary Complex)</b> = THREE components:", S_BODY))

    complex_data = [
        ("1. GHON FOCUS\n(Parenchymal lesion)", "1–1.5 cm gray-white area of consolidation\nSubpleural; lower part of upper lobe / upper part of lower lobe\nCentre → caseous necrosis\nSEE: Parenchymal component"),
        ("2. LYMPHANGITIS\n(Connecting vessel)", "Inflammatory thickening of lymphatic channels\nBetween Ghon focus and hilar lymph nodes\nLinks parenchymal + nodal components"),
        ("3. HILAR LYMPHADENOPATHY\n(Nodal component)", "Caseous enlargement of regional (hilar/mediastinal) lymph nodes\nUsually MORE prominent than parenchymal lesion in children\nNodal caseous necrosis\nSEE: Nodal component"),
    ]
    E += comparison_table(["Component", "Features"],
                          complex_data,
                          col_widths=[4.5*cm, 10*cm],
                          header_bg=C_RED)

    complex_diag = [
        "    PRIMARY COMPLEX DIAGRAM",
        "    ┌────────────────────────────────────────────────┐",
        "    │                                                │",
        "    │  [LUNG PARENCHYMA]                             │",
        "    │                                                │",
        "    │    ●  GHON FOCUS (1-1.5 cm, subpleural)       │",
        "    │    |  (caseous centre, gray-white)             │",
        "    │    |                                           │",
        "    │    | ← LYMPHANGITIS (lymphatic channels)       │",
        "    │    |                                           │",
        "    │    ●  HILAR LYMPH NODES (caseous, enlarged)    │",
        "    │       (often larger than Ghon focus)           │",
        "    │                                                │",
        "    │    Together = GHON'S COMPLEX (Primary Complex) │",
        "    └────────────────────────────────────────────────┘",
    ]
    E.append(DiagramBox(complex_diag, bg=C_LIGHT_BLUE, border=C_DARK_BLUE))

    E += mnemonic_box("Primary Complex = 'GHon FLH' (Focus + Lymphangitis + Hilum)",
        ["G = Ghon Focus (parenchymal lesion in lung)",
         "L = Lymphangitis (connecting lymphatics)",
         "H = Hilar lymphadenopathy (nodal lesion)",
         "All 3 together = Ghon Complex / Primary Complex"],
        bg=C_LIGHT_BLUE, border=C_DARK_BLUE)

    E.append(key_fact("Ghon Focus = parenchymal lesion only. Ghon Complex = Focus + Lymphangitis + Lymphadenitis. Ranke Complex = Calcified Ghon Complex (visible on X-ray)."))
    E.append(PageBreak())
    return E


# ────────────────────────────────────────────────────────────────────────────
# TOPIC 6 — GHON'S COMPLEX ★★★
# ────────────────────────────────────────────────────────────────────────────
def build_ghon_complex():
    E = []
    E += section_banner("GHON'S COMPLEX — Gross, Microscopic & Fate  ★★★", 6, C_GREEN)

    E.append(Paragraph(
        "<b>Ghon's Complex</b> = Ghon Focus (parenchymal lung lesion) + Lymphangitis + "
        "Caseous hilar lymphadenopathy in PRIMARY TUBERCULOSIS. "
        "Named after Anton Ghon (1912).", S_BODY))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("GROSS FEATURES", C_GREEN)
    E.append(Paragraph("<b>A. Ghon Focus (Parenchymal Lesion):</b>", S_SUBSECTION))
    gross_focus = [
        "Location: Subpleural; lower part of UPPER LOBE or upper part of LOWER LOBE",
        "Size: 1–1.5 cm",
        "Colour: Gray-white area of consolidation",
        "Centre: Caseous necrosis — yellow-white, cheese-like, friable material",
        "Surrounding: Zone of grey consolidation (solid pneumonia)",
        "Pleural surface: May show fibrinous exudate / pleural adhesions",
    ]
    for g in gross_focus:
        E.append(bp(g))

    E.append(Spacer(1, 0.1*cm))
    E.append(Paragraph("<b>B. Hilar Lymph Nodes:</b>", S_SUBSECTION))
    gross_nodes = [
        "Enlarged, discrete or matted together at hilum",
        "Cut section: Yellow-white caseous material (more extensive than Ghon focus)",
        "In children: nodal lesion often LARGER than parenchymal lesion",
        "Periadenitis: nodes matted to adjacent structures",
    ]
    for g in gross_nodes:
        E.append(bp(g))

    E.append(Spacer(1, 0.1*cm))
    E.append(Paragraph("<b>C. Lymphatics (Lymphangitis):</b>", S_SUBSECTION))
    E.append(bp("Thickened, visible lymphatic channels between Ghon focus and hilar nodes"))
    E.append(bp("May show 'beaded' appearance due to granulomas along the lymphatic channel"))

    E += subsection("MICROSCOPIC FEATURES", C_GREEN)
    micro_table = [
        ("AT GHON FOCUS", "1. CASEOUS NECROSIS at centre:\n   • Amorphous, granular, eosinophilic material\n   • Ghost cell outlines ('tombstone cells')\n   • Loss of all cellular architecture\n   • No living cells within necrotic core\n\n2. GRANULOMATOUS INFLAMMATION surrounding necrosis:\n   • EPITHELIOID CELLS (activated macrophages)\n     - Elongated, pale pink cytoplasm\n     - 'Footprint-shaped' / oblong nuclei\n   • LANGHANS GIANT CELLS\n     - Peripheral / horseshoe nucleus arrangement\n   • LYMPHOCYTES (mainly CD4+ T cells)\n   • Occasional plasma cells and fibroblasts\n\n3. FIBROUS CAPSULE (outer rim):\n   • Fibroblasts + collagen encapsulating granuloma\n\n4. AFB STAIN (Ziehl-Neelsen):\n   • Red acid-fast bacilli (scanty in primary TB)\n   • More abundant in immunocompromised"),
        ("AT HILAR LYMPH NODES", "• Similar caseating granulomas\n• Effacement of normal nodal architecture\n• Caseous necrosis (may be more extensive)\n• Epithelioid cells + Langhans giant cells\n• Peripheral lymphocyte rim\n• Periadenitis: inflammatory capsular thickening"),
        ("IN IMMUNOCOMPROMISED\n(HIV, CD4 < 200)", "• Granulomas ABSENT\n• Sheets of foamy macrophages with NUMEROUS bacilli\n• No caseous necrosis\n• AFB stain: heavily loaded with acid-fast bacilli\n• = Progressive Primary TB pattern"),
    ]
    E += comparison_table(["Site", "Microscopic Features"],
                          micro_table,
                          col_widths=[3.5*cm, 11*cm],
                          header_bg=C_GREEN)

    # Microscopy diagram
    micro_diag = [
        "    MICROSCOPY OF GHON FOCUS — DIAGRAM",
        "    ┌────────────────────────────────────────────────────┐",
        "    │                                                    │",
        "    │  [FIBROUS CAPSULE] ─────────────────────────────── │",
        "    │                                                    │",
        "    │  Lymphocytes  [L][L][L][L][L][L][L][L]            │",
        "    │                                                    │",
        "    │  Epithelioid cells: [Epi][Epi][Epi][Epi][Epi]     │",
        "    │                                                    │",
        "    │  Langhans Giant Cell:  O O O O O O                 │",
        "    │                       O  LARGE   O  (horseshoe    │",
        "    │                       O  CELL    O   nuclei at    │",
        "    │                       O O O O O O    periphery)   │",
        "    │                                                    │",
        "    │  CASEOUS NECROSIS: ~~~ amorphous ~~~ (centre)      │",
        "    │  ~~~ eosinophilic granular debris ~~~ no cells ~~~ │",
        "    │                                                    │",
        "    └────────────────────────────────────────────────────┘",
    ]
    E.append(DiagramBox(micro_diag, bg=C_LIGHT_GREEN, border=C_GREEN))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("FATE OF GHON'S COMPLEX  ★★★", C_RED)
    fate_diag = [
        "                    GHON'S COMPLEX",
        "                          |",
        "            ┌─────────────┴─────────────┐",
        "         95%                           5%",
        "    Normal immunity               Immunocompromised",
        "         |                             |",
        "         ↓                             ↓",
        "     HEALING                 PROGRESSIVE PRIMARY TB",
        "         |                             |",
        "    ┌────┴────┐               Caseous pneumonia",
        "    ↓         ↓               Miliary spread",
        " FIBROSIS  CALCIFICATION      Tuberculous meningitis",
        "            ↓",
        "       RANKE COMPLEX",
        "   (visible on chest X-ray",
        "    as calcified nodule)",
        "         |",
        "         ↓ (if immunity wanes years later)",
        "    REACTIVATION → SECONDARY TB",
        "    (apical lung cavity)",
    ]
    E.append(DiagramBox(fate_diag, bg=C_LIGHT_GREEN, border=C_GREEN))
    E.append(Spacer(1, 0.2*cm))

    E += subsection("FATE — DETAILED TABLE", C_GREEN)
    fate_data = [
        ("RESOLUTION (95%)", "Immune containment via Th1/IFN-γ", "Fibrosis → Calcification", "Ranke complex on X-ray"),
        ("PROGRESSIVE PRIMARY TB (5%)", "Immunocompromised, HIV, severe malnutrition", "Caseous pneumonia, lobar consolidation", "No granulomas in HIV"),
        ("MILIARY TB", "Haematogenous dissemination via erosion into blood vessel", "Millet-seed foci (1–2 mm) throughout ALL organs (lung, liver, spleen, kidney, brain)", "Classic 'snowstorm' on CXR"),
        ("TB MENINGITIS", "Haematogenous/lymphatic spread to meninges", "Subependymal granuloma ruptures into CSF spaces", "Basal exudate, vasculitis"),
        ("PLEURAL EFFUSION", "Delayed hypersensitivity reaction to TB antigens in pleural space", "Serous lymphocytic effusion", "Exudate, lymphocyte-rich"),
        ("REACTIVATION (Secondary TB)", "Waning immunity (years/decades later)", "Apical lung cavity; cavitation, fibrosis, spread", "AFB-positive sputum"),
    ]
    E += comparison_table(["Fate", "Mechanism", "Pathology", "Notes"],
                          fate_data,
                          col_widths=[3.5*cm, 4.5*cm, 4.5*cm, 2*cm],
                          header_bg=C_GREEN)

    E += subsection("KEY TERMINOLOGY COMPARISON", C_DARK_BLUE)
    terminology = [
        ("Ghon Focus", "Parenchymal lung lesion only (1–1.5 cm caseous nodule)"),
        ("Ghon Complex", "Ghon Focus + Lymphangitis + Hilar lymphadenopathy"),
        ("Ranke Complex", "CALCIFIED Ghon Complex (healed primary TB) — visible on X-ray"),
        ("Primary Complex", "Same as Ghon Complex (broader term)"),
        ("Miliary TB", "Haematogenous dissemination → millet-seed foci throughout body"),
        ("Secondary TB", "Reactivation TB in previously sensitized host — APICAL cavitation"),
    ]
    E += comparison_table(["Term", "Definition"],
                          terminology,
                          col_widths=[3.5*cm, 11*cm],
                          header_bg=C_DARK_BLUE)

    E += mnemonic_box("Fate of Ghon Complex — 'FRAME'",
        ["F = Fibrosis (heals with fibrosis)",
         "R = Ranke complex (calcified form, visible on X-ray)",
         "A = Activation (reactivation → secondary TB if immunity wanes)",
         "M = Miliary spread (haematogenous)",
         "E = Erosion into bronchus (spread to other lung areas) / Effusion"],
        bg=C_LIGHT_GREEN, border=C_GREEN)

    E += mnemonic_box("Granuloma vs Abscess — 'Granuloma = Contained; Abscess = Liquefied'",
        ["Granuloma (TB) = CASEOUS necrosis = dry, cheese-like, NO pus",
         "Abscess (Pyogenic) = LIQUEFACTIVE necrosis = pus, neutrophils",
         "Caseous necrosis = ONLY seen in TB (pathognomonic)"],
        bg=C_LIGHT_YELLOW, border=C_YELLOW)

    E.append(key_fact("MUHS favourite: List 5 fates of Ghon complex. Always include Ranke complex definition. Miliary TB = haematogenous spread with millet-seed lesions everywhere."))

    E.append(Spacer(1, 0.5*cm))
    E.append(divider(C_GREEN))
    E.append(Spacer(1, 0.3*cm))
    E.append(Paragraph("END OF REVISION NOTES", make_style('End',
        fontSize=12, textColor=C_MID_GREY, fontName='Helvetica-Bold',
        alignment=TA_CENTER)))
    E.append(Paragraph("Robbins, Cotran & Kumar — Pathologic Basis of Disease, 10e | Robbins & Kumar Basic Pathology",
        make_style('EndSub', fontSize=8.5, textColor=C_MID_GREY,
                   fontName='Helvetica-Oblique', alignment=TA_CENTER)))
    return E


# ── ASSEMBLE & BUILD ──────────────────────────────────────────────────────────
def build_pdf():
    os.makedirs(os.path.dirname(OUTPUT_PATH), exist_ok=True)
    doc = SimpleDocTemplate(
        OUTPUT_PATH,
        pagesize=A4,
        leftMargin=2*cm,
        rightMargin=2*cm,
        topMargin=2.2*cm,
        bottomMargin=1.8*cm,
        title="MUHS 2nd MBBS Pathology Rapid Revision",
        author="Robbins & Kumar"
    )

    all_elements = []
    all_elements += build_cover()
    all_elements += build_malaria()
    all_elements += build_cysticercosis()
    all_elements += build_leprosy()
    all_elements += build_viral_fungal()
    all_elements += build_primary_tb()
    all_elements += build_ghon_complex()

    doc.build(
        all_elements,
        onFirstPage=on_first_page,
        onLaterPages=on_later_pages
    )
    print(f"PDF successfully generated: {OUTPUT_PATH}")


if __name__ == "__main__":
    build_pdf()

Error: String not found in file: '#!/usr/bin/env python3
"""
MUHS 2nd MBBS Pathology - Comprehensive Revision PDF
Topics: Malaria, Cysticercosis, Leprosy, Viral/Fungal Infections,
        Primary TB, Ghon's Complex
Based on Robbins & Kumar Pathology
"""'