Expand lab knowledge graph markers and videos

Co-authored-by: Codex <chatgpt-codex-connector[bot]@users.noreply.github.com>

kb/knowledge_base.py

@@ -115,6 +115,21 @@ KB: dict[str, MarkerKB] = {
         low="A low reticulocyte count in anemia suggests the marrow is not keeping up with red-cell need.",
         questions=("Is my body replacing red cells appropriately?",),
     ),
+    "Haptoglobin": MarkerKB(
+        high="A high haptoglobin may rise with inflammation because it is an acute-phase protein.",
+        low="A low haptoglobin supports red-cell breakdown when interpreted with LDH, bilirubin, and reticulocytes.",
+        questions=("Does this fit with LDH, bilirubin, and reticulocyte count?",),
+    ),
+    "G6PD": MarkerKB(
+        high="A high G6PD level is usually not clinically important by itself.",
+        low="A low G6PD level can predispose red cells to hemolysis after certain infections, foods, or medications.",
+        questions=("Should I avoid any oxidant medications or foods?",),
+    ),
+    "Erythropoietin": MarkerKB(
+        high="A high erythropoietin may reflect the body's response to anemia or low oxygen levels.",
+        low="A low or inappropriately normal erythropoietin can contribute to anemia in kidney disease.",
+        questions=("Is this appropriate for my hemoglobin level?",),
+    ),
     # --- Metabolic panel ---
     "Glucose": MarkerKB(
         high="An elevated fasting glucose can indicate prediabetes or diabetes, or simply that the sample was not fasting.",
@@ -206,6 +221,11 @@ KB: dict[str, MarkerKB] = {
         low="A low TIBC may appear with inflammation or iron overload.",
         questions=("Does TIBC fit with my ferritin and transferrin saturation?",),
     ),
+    "Transferrin": MarkerKB(
+        high="A high transferrin often appears when the body is trying to transport more iron during iron deficiency.",
+        low="A low transferrin may appear with inflammation, liver disease, malnutrition, or iron overload.",
+        questions=("Does transferrin fit with ferritin, serum iron, and TIBC?",),
+    ),
     "Transferrin Saturation": MarkerKB(
         high="A high saturation may suggest iron overload or excess intake.",
         low="A low saturation is common in iron deficiency.",
@@ -236,6 +256,11 @@ KB: dict[str, MarkerKB] = {
         low="A low homocysteine is generally favorable.",
         questions=("Should we check B12 and folate?",),
     ),
+    "Methylmalonic Acid": MarkerKB(
+        high="A high methylmalonic acid supports functional vitamin B12 deficiency, especially when B12 is borderline.",
+        low="A low methylmalonic acid is usually not a concern.",
+        questions=("Does this clarify whether my B12 level is truly low?",),
+    ),
     "Cystatin C": MarkerKB(
         high="A high cystatin C suggests reduced kidney filtration, similar to creatinine but less muscle-dependent.",
         low="A low cystatin C is usually not a concern.",
@@ -251,6 +276,21 @@ KB: dict[str, MarkerKB] = {
         low="A low beta-2 microglobulin is not typically significant.",
         questions=("Should this be interpreted with kidney function?",),
     ),
+    "C-Peptide": MarkerKB(
+        high="A high C-peptide means the pancreas is making more insulin and may appear with insulin resistance or insulin-producing tumors.",
+        low="A low C-peptide suggests reduced natural insulin production, especially when glucose is high.",
+        questions=("Was glucose measured at the same time?",),
+    ),
+    "Fructosamine": MarkerKB(
+        high="A high fructosamine suggests higher average blood sugar over the prior two to three weeks.",
+        low="A low fructosamine is usually not a concern but can be affected by low blood proteins.",
+        questions=("Is this being used because HbA1c may be unreliable for me?",),
+    ),
+    "Beta-Hydroxybutyrate": MarkerKB(
+        high="A high beta-hydroxybutyrate indicates increased ketone production and can be important in diabetes or prolonged fasting.",
+        low="A low beta-hydroxybutyrate is expected when ketone production is not increased.",
+        questions=("Could this relate to diabetes, fasting, or a low-carbohydrate diet?",),
+    ),
     # --- Liver enzymes ---
     "ALT": MarkerKB(
         high="ALT is fairly liver-specific; elevations can follow fatty liver, alcohol, medications, or viral hepatitis.",
@@ -364,6 +404,16 @@ KB: dict[str, MarkerKB] = {
         low="A negative or low Anti-TPO is expected in most people without autoimmune thyroid disease.",
         questions=("Could this explain my thyroid symptoms or TSH changes?",),
     ),
+    "TSH Receptor Antibodies": MarkerKB(
+        high="A high TSH receptor antibody result supports autoimmune Graves-type thyroid stimulation in the right thyroid pattern.",
+        low="A low result makes TSH-receptor antibody activity less likely.",
+        questions=("Does this fit with my TSH, Free T4, and Free T3?",),
+    ),
+    "Thyroglobulin Antibodies": MarkerKB(
+        high="A high thyroglobulin antibody result may support autoimmune thyroid disease and can interfere with thyroglobulin monitoring.",
+        low="A low result is expected when these antibodies are absent.",
+        questions=("Could this interfere with thyroglobulin interpretation?",),
+    ),
     # --- Vitamins / iron ---
     "Vitamin D": MarkerKB(
         high="A very high vitamin D is uncommon and usually from supplements.",
@@ -380,6 +430,31 @@ KB: dict[str, MarkerKB] = {
         low="A low ferritin is the most specific sign of low iron stores and a common cause of anemia.",
         questions=("Does my ferritin explain my hemoglobin and MCV?", "Should we look for a source of iron loss?"),
     ),
+    "Zinc": MarkerKB(
+        high="A high zinc level is uncommon and may reflect excess supplementation.",
+        low="A low zinc level may relate to poor intake, malabsorption, inflammation, or increased losses.",
+        questions=("Am I taking zinc or other mineral supplements?",),
+    ),
+    "Copper": MarkerKB(
+        high="A high copper level can rise with inflammation, pregnancy, estrogen therapy, or copper disorders.",
+        low="A low copper level may cause anemia or nerve problems and can occur with excess zinc intake.",
+        questions=("Should copper be interpreted with ceruloplasmin and zinc?",),
+    ),
+    "Ceruloplasmin": MarkerKB(
+        high="A high ceruloplasmin may rise with inflammation, pregnancy, or estrogen therapy.",
+        low="A low ceruloplasmin can appear in copper deficiency or Wilson disease workups.",
+        questions=("Does this fit with copper and liver tests?",),
+    ),
+    "Selenium": MarkerKB(
+        high="A high selenium level is usually related to excess supplementation and can be toxic.",
+        low="A low selenium level may reflect poor intake, malabsorption, or severe illness.",
+        questions=("Am I taking selenium-containing supplements?",),
+    ),
+    "Vitamin E": MarkerKB(
+        high="A high vitamin E level is usually supplement-related and may affect bleeding risk at high intakes.",
+        low="A low vitamin E level may occur with fat malabsorption and can affect nerves and red cells.",
+        questions=("Could fat absorption or supplements explain this?",),
+    ),
     "HbA1c": MarkerKB(
         high="A high HbA1c reflects higher average blood sugar over ~3 months and is used to screen for prediabetes and diabetes.",
         low="A low HbA1c is generally not a concern.",
@@ -447,12 +522,42 @@ KB: dict[str, MarkerKB] = {
         low="A negative rheumatoid factor does not rule out arthritis.",
         questions=("Do my joints hurt or swell, especially in the morning?",),
     ),
+    "Anti-CCP Antibodies": MarkerKB(
+        high="A high anti-CCP result is more specific for rheumatoid arthritis than rheumatoid factor in the right symptom pattern.",
+        low="A low anti-CCP result makes anti-CCP-positive rheumatoid arthritis less likely.",
+        questions=("Does this match joint symptoms or imaging?",),
+    ),
+    "Immunoglobulin G": MarkerKB(
+        high="A high IgG may reflect chronic inflammation, infection, autoimmune disease, liver disease, or monoclonal protein.",
+        low="A low IgG may reflect immune deficiency, protein loss, or treatment effects.",
+        questions=("Should this be read with serum protein electrophoresis or vaccine responses?",),
+    ),
+    "Immunoglobulin A": MarkerKB(
+        high="A high IgA may reflect inflammation, liver disease, mucosal immune activation, or monoclonal protein.",
+        low="A low IgA can be selective and may affect interpretation of some celiac tests.",
+        questions=("Does low IgA affect any antibody tests I had?",),
+    ),
+    "Immunoglobulin M": MarkerKB(
+        high="A high IgM may appear with recent immune stimulation or some monoclonal protein disorders.",
+        low="A low IgM may reflect immune deficiency or treatment effects.",
+        questions=("Is this a persistent pattern across immunoglobulins?",),
+    ),
+    "Immunoglobulin E": MarkerKB(
+        high="A high IgE is commonly associated with allergies, eczema, asthma, or parasite exposure.",
+        low="A low IgE is usually not clinically significant.",
+        questions=("Could allergy or asthma explain this?",),
+    ),
     # --- Cardiac ---
     "BNP": MarkerKB(
         high="A high BNP suggests the heart is under strain, as in heart failure or fluid overload.",
         low="A low BNP makes significant heart failure less likely.",
         questions=("Do I have shortness of breath or leg swelling?",),
     ),
+    "NT-proBNP": MarkerKB(
+        high="A high NT-proBNP suggests heart strain or heart failure, but age, kidney function, and rhythm affect interpretation.",
+        low="A low NT-proBNP makes heart failure less likely in the right clinical context.",
+        questions=("How should this be interpreted with my age and kidney function?",),
+    ),
     "Troponin I": MarkerKB(
         high="A high troponin indicates heart-muscle injury and needs urgent clinical evaluation.",
         low="A low troponin is expected when there is no heart injury.",
@@ -468,6 +573,11 @@ KB: dict[str, MarkerKB] = {
         low="A low CK-MB is expected without heart injury.",
         questions=("Was this checked because of chest symptoms?",),
     ),
+    "Myoglobin": MarkerKB(
+        high="A high myoglobin may reflect skeletal or heart muscle injury and is less specific than troponin.",
+        low="A low myoglobin is expected without recent muscle injury.",
+        questions=("Could exercise, trauma, or muscle symptoms explain this?",),
+    ),
     # --- Hormones ---
     "Cortisol": MarkerKB(
         high="A high cortisol may reflect stress, steroids, Cushing syndrome, or lab timing.",
@@ -519,6 +629,26 @@ KB: dict[str, MarkerKB] = {
         low="A low ACTH may appear with steroid use or pituitary causes of low cortisol.",
         questions=("Should ACTH be read with cortisol?",),
     ),
+    "DHEA-S": MarkerKB(
+        high="A high DHEA-S suggests increased adrenal androgen production and may appear in PCOS or adrenal disorders.",
+        low="A low DHEA-S can occur with adrenal insufficiency, aging, or steroid exposure.",
+        questions=("Does this fit with testosterone and symptoms?",),
+    ),
+    "Androstenedione": MarkerKB(
+        high="A high androstenedione may reflect increased adrenal or ovarian androgen production.",
+        low="A low androstenedione is usually interpreted only in endocrine context.",
+        questions=("Should this be paired with DHEA-S and testosterone?",),
+    ),
+    "Anti-Mullerian Hormone": MarkerKB(
+        high="A high AMH may appear with a high ovarian follicle count, including some PCOS patterns.",
+        low="A low AMH may suggest lower ovarian reserve for age, but it does not predict natural fertility by itself.",
+        questions=("How should this be interpreted for my age and fertility goals?",),
+    ),
+    "Beta-hCG": MarkerKB(
+        high="A high beta-hCG most commonly reflects pregnancy, but it is also used in some pregnancy complications and tumor monitoring.",
+        low="A low or negative beta-hCG makes pregnancy less likely at the time tested.",
+        questions=("Should this be repeated to assess the trend?",),
+    ),
     "SHBG": MarkerKB(
         high="A high SHBG binds more testosterone and estrogen, lowering their free fractions.",
         low="A low SHBG is linked to insulin resistance and higher free androgen activity.",
@@ -535,6 +665,31 @@ KB: dict[str, MarkerKB] = {
         low="A low PSA is expected and does not rule out all prostate conditions.",
         questions=("Could recent exercise or infection have raised PSA?", "Is repeat testing planned?"),
     ),
+    "CEA": MarkerKB(
+        high="A high CEA may be followed in some cancers but can also rise with smoking, inflammation, or liver disease.",
+        low="A low CEA is expected and is most useful when compared with prior values during monitoring.",
+        questions=("Is this being used for monitoring rather than screening?",),
+    ),
+    "CA-125": MarkerKB(
+        high="A high CA-125 may be followed in ovarian cancer care but can also rise with benign gynecologic or inflammatory conditions.",
+        low="A low CA-125 is expected and does not rule out disease by itself.",
+        questions=("What trend or imaging is this being compared with?",),
+    ),
+    "CA 19-9": MarkerKB(
+        high="A high CA 19-9 may be followed in pancreaticobiliary cancer care but can also rise with bile duct blockage or inflammation.",
+        low="A low CA 19-9 is expected; some people do not make this marker even with disease.",
+        questions=("Is bilirubin or bile duct blockage affecting this result?",),
+    ),
+    "Alpha-Fetoprotein": MarkerKB(
+        high="A high AFP may be used in liver or germ-cell tumor evaluation and can also rise in pregnancy or liver disease.",
+        low="A low AFP is expected outside pregnancy and monitoring contexts.",
+        questions=("Should this be interpreted with liver imaging or pregnancy status?",),
+    ),
+    "CA 15-3": MarkerKB(
+        high="A high CA 15-3 may be used to monitor some breast cancers but is not specific enough to diagnose cancer alone.",
+        low="A low CA 15-3 is expected and is mainly useful as a trend during monitoring.",
+        questions=("Is this being compared with prior values?",),
+    ),
     "Folate": MarkerKB(
         high="A high folate is usually from supplements or fortified foods.",
         low="A low folate can cause anemia similar to B12 deficiency and affects DNA synthesis.",

kb/marker_videos.json

@@ -2,119 +2,175 @@
   "schema_version": "1.0",
   "description": "Curated educational YouTube links per lab marker. Closest-topic fallbacks are noted in notes.",
   "videos": {
-    "hemoglobin": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "rbc": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "hct": "https://www.youtube.com/watch?v=yF22BfXEO5g",
-    "mcv": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "mch": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "mchc": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "rdw_cv": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "rdw_sd": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "wbc": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "neu_percent": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "lym_percent": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "mon_percent": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "eos_percent": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "bas_percent": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "lym_absolute": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "gra_absolute": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "plt": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "esr": "https://www.youtube.com/watch?v=MMsvv4P2eOM",
-    "mpv": "https://www.youtube.com/watch?v=JVmPu8o2ycc",
-    "neu_absolute": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "mon_absolute": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "eos_absolute": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "bas_absolute": "https://www.youtube.com/watch?v=mzPu7q6GNQA",
-    "reticulocyte_count": "https://www.youtube.com/watch?v=MRzxsX5YG94",
-    "glucose": "https://www.youtube.com/watch?v=-B-RVybvffU",
-    "creatinine": "https://www.youtube.com/watch?v=z0LTY-im8iY",
-    "egfr": "https://www.youtube.com/watch?v=z0LTY-im8iY",
-    "bun": "https://www.youtube.com/watch?v=z0LTY-im8iY",
-    "sodium": "https://www.youtube.com/watch?v=ZQ-sQU9wNxU",
-    "potassium": "https://www.youtube.com/watch?v=ZQ-sQU9wNxU",
-    "chloride": "https://www.youtube.com/watch?v=T_pCeQkpNX8",
-    "calcium": "https://www.youtube.com/watch?v=ZQ-sQU9wNxU",
-    "albumin": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "total_protein": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "globulin": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "bicarbonate": "https://www.youtube.com/watch?v=-Ahjxv5FK0A",
-    "anion_gap": "https://www.youtube.com/watch?v=G2NFzqdRWcU",
-    "magnesium": "https://www.youtube.com/watch?v=ZQ-sQU9wNxU",
-    "phosphate": "https://www.youtube.com/watch?v=ZQ-sQU9wNxU",
-    "uric_acid": "https://www.youtube.com/watch?v=bznoU5bke4U",
-    "serum_iron": "https://www.youtube.com/watch?v=6RbuFyt5Wpo",
-    "tibc": "https://www.youtube.com/watch?v=6RbuFyt5Wpo",
-    "transferrin_saturation": "https://www.youtube.com/watch?v=6RbuFyt5Wpo",
-    "ldh": "https://www.youtube.com/watch?v=XpAO_0-dTAQ",
-    "osmolality": "https://www.youtube.com/watch?v=VofGdSeafTA",
+    "acth": "https://www.youtube.com/watch?v=rk2b3X6CU4w",
+    "albumin": "https://www.youtube.com/watch?v=z1LhGUAUsDg",
+    "alp": "https://www.youtube.com/watch?v=4E9KXGXUXcs",
+    "alpha_fetoprotein": "https://www.youtube.com/watch?v=CKp-TnOWDOg",
+    "alt": "https://www.youtube.com/watch?v=ZDGfAuQHA-w",
     "ammonia": "https://www.youtube.com/watch?v=kHB5e-4q7l8",
-    "lactate": "https://www.youtube.com/watch?v=XuGPoQWzIco",
-    "homocysteine": "https://www.youtube.com/watch?v=CUh5Flt4n1k",
-    "cystatin_c": "https://www.youtube.com/watch?v=fv53QZRk4hs",
-    "prealbumin": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "beta_2_microglobulin": "https://www.youtube.com/watch?v=fv53QZRk4hs",
-    "hba1c": "https://www.youtube.com/watch?v=-B-RVybvffU",
-    "alt": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "ast": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "alp": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "ggt": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "total_bilirubin": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "direct_bilirubin": "https://www.youtube.com/watch?v=JiaMJaA34Jg",
-    "lipase": "https://www.youtube.com/watch?v=XpAO_0-dTAQ",
-    "amylase": "https://www.youtube.com/watch?v=XpAO_0-dTAQ",
-    "total_cholesterol": "https://www.youtube.com/watch?v=nurZ2nNovp8",
-    "ldl_cholesterol": "https://www.youtube.com/watch?v=nurZ2nNovp8",
-    "hdl_cholesterol": "https://www.youtube.com/watch?v=nurZ2nNovp8",
-    "triglycerides": "https://www.youtube.com/watch?v=TrbQ5r31phk",
-    "non_hdl_cholesterol": "https://www.youtube.com/watch?v=nurZ2nNovp8",
-    "apolipoprotein_b": "https://www.youtube.com/watch?v=TrbQ5r31phk",
-    "apolipoprotein_a1": "https://www.youtube.com/watch?v=TrbQ5r31phk",
-    "lipoprotein_a": "https://www.youtube.com/watch?v=TrbQ5r31phk",
-    "tsh": "https://www.youtube.com/watch?v=RuwM6M5ohW4",
-    "free_t4": "https://www.youtube.com/watch?v=RuwM6M5ohW4",
-    "free_t3": "https://www.youtube.com/watch?v=RuwM6M5ohW4",
-    "total_t4": "https://www.youtube.com/watch?v=-naOgnjJlz0",
-    "total_t3": "https://www.youtube.com/watch?v=-naOgnjJlz0",
-    "anti_tpo_antibodies": "https://www.youtube.com/watch?v=ZaxjJ_c0J6o",
-    "vitamin_d": "https://www.youtube.com/watch?v=YEnxruA-bsk",
-    "vitamin_b12": "https://www.youtube.com/watch?v=CUh5Flt4n1k",
-    "ferritin": "https://www.youtube.com/watch?v=6RbuFyt5Wpo",
-    "folate": "https://www.youtube.com/watch?v=mYhb4470rCw",
-    "vitamin_a": "https://www.youtube.com/watch?v=3G_e0tILSmM",
-    "prothrombin_time": "https://www.youtube.com/watch?v=7sGGlvNeXkk",
-    "inr": "https://www.youtube.com/watch?v=7sGGlvNeXkk",
-    "aptt": "https://www.youtube.com/watch?v=7sGGlvNeXkk",
-    "fibrinogen": "https://www.youtube.com/watch?v=SGzp9wqeu84",
-    "d_dimer": "https://www.youtube.com/watch?v=XHbOxEMHeqc",
-    "crp": "https://www.youtube.com/watch?v=MMsvv4P2eOM",
-    "hs_crp": "https://www.youtube.com/watch?v=MMsvv4P2eOM",
-    "procalcitonin": "https://www.youtube.com/watch?v=XuGPoQWzIco",
-    "complement_c3": "https://www.youtube.com/watch?v=I_HoX_uM8EE",
-    "complement_c4": "https://www.youtube.com/watch?v=I_HoX_uM8EE",
-    "rheumatoid_factor": "https://www.youtube.com/watch?v=EB5zxdAQGzU",
-    "bnp": "https://www.youtube.com/watch?v=ypYI_lmLD7g",
-    "troponin_i": "https://www.youtube.com/watch?v=TBG9Jw3yd9I",
-    "creatine_kinase": "https://www.youtube.com/watch?v=TBG9Jw3yd9I",
-    "ck_mb": "https://www.youtube.com/watch?v=TBG9Jw3yd9I",
+    "amylase": "https://www.youtube.com/watch?v=gTbimcKKlKQ",
+    "androstenedione": "https://www.youtube.com/watch?v=BmIKhnE-G04",
+    "anion_gap": "https://www.youtube.com/watch?v=G2NFzqdRWcU",
+    "anti_ccp_antibodies": "https://www.youtube.com/watch?v=EB5zxdAQGzU",
+    "anti_mullerian_hormone": "https://www.youtube.com/watch?v=HiZSaDr2cBY",
+    "anti_tpo_antibodies": "https://www.youtube.com/watch?v=kg9fQ3A9IOA",
+    "apolipoprotein_a1": "https://www.youtube.com/watch?v=ckkpnuqDyLA",
+    "apolipoprotein_b": "https://www.youtube.com/watch?v=V7ywq_s7ATk",
+    "aptt": "https://www.youtube.com/watch?v=uiFicYWMZL0",
+    "ast": "https://www.youtube.com/watch?v=7_-ZtM0TieA",
+    "bas_absolute": "https://www.youtube.com/watch?v=sRIjKEkjWmU",
+    "bas_percent": "https://www.youtube.com/watch?v=VUAVvLkcN0M",
+    "beta_2_microglobulin": "https://www.youtube.com/watch?v=i2-_4wk30po",
+    "beta_hcg": "https://www.youtube.com/watch?v=rM3FVuamrVA",
+    "beta_hydroxybutyrate": "https://www.youtube.com/watch?v=-B-RVybvffU",
+    "bicarbonate": "https://www.youtube.com/watch?v=-Ahjxv5FK0A",
+    "bnp": "https://www.youtube.com/watch?v=QEt2lvWoMxA",
+    "bun": "https://www.youtube.com/watch?v=Q7odN31HK_Y",
+    "c_peptide": "https://www.youtube.com/watch?v=JHFQljIJGzM",
+    "ca_125": "https://www.youtube.com/watch?v=3VmLWc-F3rA",
+    "ca_15_3": "https://www.youtube.com/watch?v=JeV_T32QBv8",
+    "ca_19_9": "https://www.youtube.com/watch?v=gTCxRhgnj-Q",
+    "calcium": "https://www.youtube.com/watch?v=hj-Y4eZ0dkM",
+    "cea": "https://www.youtube.com/watch?v=uJNw9v6UUjE",
+    "ceruloplasmin": "https://www.youtube.com/watch?v=42kduAhoYlw",
+    "chloride": "https://www.youtube.com/watch?v=5Fuav99clbE",
+    "ck_mb": "https://www.youtube.com/watch?v=udVccTOnmrM",
+    "complement_c3": "https://www.youtube.com/watch?v=r_f5cvxwS6w",
+    "complement_c4": "https://www.youtube.com/watch?v=r_f5cvxwS6w",
+    "copper": "https://www.youtube.com/watch?v=42kduAhoYlw",
     "cortisol": "https://www.youtube.com/watch?v=rk2b3X6CU4w",
+    "creatine_kinase": "https://www.youtube.com/watch?v=loBxjfuUVj0",
+    "creatinine": "https://www.youtube.com/watch?v=l2tf-Pxc0wU",
+    "crp": "https://www.youtube.com/watch?v=zTFDB_dk_Gk",
+    "cystatin_c": "https://www.youtube.com/watch?v=upJcuKQ9ppQ",
+    "d_dimer": "https://www.youtube.com/watch?v=uTYlwmDSFvA",
+    "dhea_s": "https://www.youtube.com/watch?v=XWn-DVX_QVE",
+    "direct_bilirubin": "https://www.youtube.com/watch?v=9RixUyMPhO0",
+    "egfr": "https://www.youtube.com/watch?v=fFn0ygOOBuI",
+    "eos_absolute": "https://www.youtube.com/watch?v=7gmKTpODT8o",
+    "eos_percent": "https://www.youtube.com/watch?v=rtnfv_2HSak",
+    "erythropoietin": "https://www.youtube.com/watch?v=wqMQjsf1YD4",
+    "esr": "https://www.youtube.com/watch?v=-ulccBGAvbY",
+    "estradiol": "https://www.youtube.com/watch?v=pOaUnf3MKs8",
+    "ferritin": "https://www.youtube.com/watch?v=aPSfIPtho08",
+    "fibrinogen": "https://www.youtube.com/watch?v=HqmRkEoUe-8",
+    "folate": "https://www.youtube.com/watch?v=dO0aUSqZ_bs",
+    "free_t3": "https://www.youtube.com/watch?v=oz8HFUqwDgw",
+    "free_t4": "https://www.youtube.com/watch?v=IHaH9mlCdVY",
+    "fructosamine": "https://www.youtube.com/watch?v=tXW-qGeTNFk",
+    "fsh": "https://www.youtube.com/watch?v=UL0PFu5fPKA",
+    "g6pd": "https://www.youtube.com/watch?v=iTh-hUU5mxE",
+    "ggt": "https://www.youtube.com/watch?v=c0uISl0fna0",
+    "globulin": "https://www.youtube.com/watch?v=EBf97p7AeZc",
+    "glucose": "https://www.youtube.com/watch?v=V4PJ7n-RDf8",
+    "gra_absolute": "https://www.youtube.com/watch?v=VUAVvLkcN0M",
+    "haptoglobin": "https://www.youtube.com/watch?v=QR_hcSow4OI",
+    "hba1c": "https://www.youtube.com/watch?v=V4PJ7n-RDf8",
+    "hct": "https://www.youtube.com/watch?v=D5PVCKWLgXU",
+    "hdl_cholesterol": "https://www.youtube.com/watch?v=KeoZck3T824",
+    "hemoglobin": "https://www.youtube.com/watch?v=E7c4zr-FHcA",
+    "homocysteine": "https://www.youtube.com/watch?v=XbX9K1OtFFs",
+    "hs_crp": "https://www.youtube.com/watch?v=eRNFtwzyyCo",
+    "igf_1": "https://www.youtube.com/watch?v=_LKdNhF2WhI",
+    "immunoglobulin_a": "https://www.youtube.com/watch?v=pkn3qA7s-NI",
+    "immunoglobulin_e": "https://www.youtube.com/watch?v=z95-fg7bzLA",
+    "immunoglobulin_g": "https://www.youtube.com/watch?v=d_3VZ5vDiHI",
+    "immunoglobulin_m": "https://www.youtube.com/watch?v=0ztF-419fac",
+    "inr": "https://www.youtube.com/watch?v=kCz5Rde9Gp0",
     "insulin": "https://www.youtube.com/watch?v=w4jHtPUNg6E",
-    "testosterone": "https://www.youtube.com/watch?v=mjROZrxBdv4",
-    "estradiol": "https://www.youtube.com/watch?v=pzgUbyD6mCM",
-    "prolactin": "https://www.youtube.com/watch?v=9VsI3UKvLiw",
-    "fsh": "https://www.youtube.com/watch?v=h36poEtEbi4",
-    "lh": "https://www.youtube.com/watch?v=h36poEtEbi4",
-    "progesterone": "https://www.youtube.com/watch?v=pzgUbyD6mCM",
+    "lactate": "https://www.youtube.com/watch?v=XuGPoQWzIco",
+    "ldh": "https://www.youtube.com/watch?v=cr0cnpUEYSM",
+    "ldl_cholesterol": "https://www.youtube.com/watch?v=EfdwqypYAlU",
+    "lh": "https://www.youtube.com/watch?v=JvadRkqsuvQ",
+    "lipase": "https://www.youtube.com/watch?v=gTbimcKKlKQ",
+    "lipoprotein_a": "https://www.youtube.com/watch?v=VSCtsOjQEkk",
+    "lym_absolute": "https://www.youtube.com/watch?v=RBdWjr0BNj8",
+    "lym_percent": "https://www.youtube.com/watch?v=VUAVvLkcN0M",
+    "magnesium": "https://www.youtube.com/watch?v=AE0_1dIgVQc",
+    "mch": "https://www.youtube.com/watch?v=WiuD3wUXHgA",
+    "mchc": "https://www.youtube.com/watch?v=cZXr-91hNr8",
+    "mcv": "https://www.youtube.com/watch?v=OQoV-QpRnLk",
+    "methylmalonic_acid": "https://www.youtube.com/watch?v=ky-Mu5yVyuU",
+    "mon_absolute": "https://www.youtube.com/watch?v=se5Jy1BIJCU",
+    "mon_percent": "https://www.youtube.com/watch?v=VUAVvLkcN0M",
+    "mpv": "https://www.youtube.com/watch?v=gvmOvYazV40",
+    "myoglobin": "https://www.youtube.com/watch?v=udVccTOnmrM",
+    "neu_absolute": "https://www.youtube.com/watch?v=Fju2R0gDTf8",
+    "neu_percent": "https://www.youtube.com/watch?v=VUAVvLkcN0M",
+    "non_hdl_cholesterol": "https://www.youtube.com/watch?v=eoUR7J0J1cA",
+    "nt_probnp": "https://www.youtube.com/watch?v=QEt2lvWoMxA",
+    "osmolality": "https://www.youtube.com/watch?v=VofGdSeafTA",
+    "phosphate": "https://www.youtube.com/watch?v=I0-ltFTa0Sc",
+    "plt": "https://www.youtube.com/watch?v=_1ckWNEwSDA",
+    "potassium": "https://www.youtube.com/watch?v=obJk-dUbQR8",
+    "prealbumin": "https://www.youtube.com/watch?v=UP7Waa6xrCY",
+    "procalcitonin": "https://www.youtube.com/watch?v=XgvB_s-xlaQ",
+    "progesterone": "https://www.youtube.com/watch?v=A1uPKIHS4Cs",
+    "prolactin": "https://www.youtube.com/watch?v=GE85xI4WoAc",
+    "prothrombin_time": "https://www.youtube.com/watch?v=tY28cQSBy3g",
+    "psa": "https://www.youtube.com/watch?v=bTgS0DuhaUU",
     "pth": "https://www.youtube.com/watch?v=y64aXKCkHk4",
-    "acth": "https://www.youtube.com/watch?v=rk2b3X6CU4w",
-    "shbg": "https://www.youtube.com/watch?v=9VsI3UKvLiw",
-    "igf_1": "https://www.youtube.com/watch?v=_LKdNhF2WhI",
-    "psa": "https://www.youtube.com/watch?v=bTgS0DuhaUU"
+    "rbc": "https://www.youtube.com/watch?v=Ho_hsOrdBQQ",
+    "rdw_cv": "https://www.youtube.com/watch?v=fdlLgdgywlU",
+    "rdw_sd": "https://www.youtube.com/watch?v=fdlLgdgywlU",
+    "reticulocyte_count": "https://www.youtube.com/watch?v=vfw2rPn_SuM",
+    "rheumatoid_factor": "https://www.youtube.com/watch?v=EB5zxdAQGzU",
+    "selenium": "https://www.youtube.com/watch?v=BSeV79orP6I",
+    "serum_iron": "https://www.youtube.com/watch?v=KnKTgmAu0Pc",
+    "shbg": "https://www.youtube.com/watch?v=MBhQR-WzqUg",
+    "sodium": "https://www.youtube.com/watch?v=Qzct2Qmjo8c",
+    "testosterone": "https://www.youtube.com/watch?v=MBhQR-WzqUg",
+    "thyroglobulin_antibodies": "https://www.youtube.com/watch?v=q6LzDINcqDM",
+    "tibc": "https://www.youtube.com/watch?v=YczPj71BFPY",
+    "total_bilirubin": "https://www.youtube.com/watch?v=Aew1gWVLYNU",
+    "total_cholesterol": "https://www.youtube.com/watch?v=_SGyJU9BL6o",
+    "total_protein": "https://www.youtube.com/watch?v=V-yepa6wLT4",
+    "total_t3": "https://www.youtube.com/watch?v=SVth4eAKlY8",
+    "total_t4": "https://www.youtube.com/watch?v=0QrcY2IV7No",
+    "transferrin": "https://www.youtube.com/watch?v=j9mR9luWBQY",
+    "transferrin_saturation": "https://www.youtube.com/watch?v=_ziD0NbFjkM",
+    "triglycerides": "https://www.youtube.com/watch?v=rOiLRsWhwsQ",
+    "troponin_i": "https://www.youtube.com/watch?v=udVccTOnmrM",
+    "tsh": "https://www.youtube.com/watch?v=Udaqw1gtKvc",
+    "tsh_receptor_antibodies": "https://www.youtube.com/watch?v=lKIhKsljksk",
+    "uric_acid": "https://www.youtube.com/watch?v=bznoU5bke4U",
+    "vitamin_a": "https://www.youtube.com/watch?v=QcsiBH_j2MA",
+    "vitamin_b12": "https://www.youtube.com/watch?v=CUh5Flt4n1k",
+    "vitamin_d": "https://www.youtube.com/watch?v=YEnxruA-bsk",
+    "vitamin_e": "https://www.youtube.com/watch?v=QcsiBH_j2MA",
+    "wbc": "https://www.youtube.com/watch?v=VUAVvLkcN0M",
+    "zinc": "https://www.youtube.com/watch?v=BSeV79orP6I"
   },
   "notes": {
-    "rdw_sd": "CBC overview discusses RDW percent; RDW-SD is not named separately.",
+    "alpha_fetoprotein": "Tumor-marker overview covers AFP with other markers.",
+    "androstenedione": "PCOS lab overview includes androgen-marker context.",
+    "anti_ccp_antibodies": "Rheumatoid arthritis overview; anti-CCP is correlated through RA evaluation.",
+    "anti_mullerian_hormone": "Fertility hormone-testing overview includes AMH and ovarian-reserve timing.",
+    "ast": "AST/ALT lab-values video covers AST directly alongside ALT.",
+    "beta_hcg": "Reproductive-cycle overview is a broad pregnancy/reproductive hormone context; beta-hCG is not the primary topic.",
+    "beta_hydroxybutyrate": "Diabetes/DKA overview covers ketone production; beta-hydroxybutyrate is not the only focus.",
+    "ca_125": "Tumor-marker overview covers CA-125 with other markers.",
+    "ca_15_3": "Direct CA 15-3 blood-test video; marker is for monitoring context rather than diagnosis.",
+    "cea": "Tumor-marker overview covers CEA with other markers.",
+    "ceruloplasmin": "Trace-mineral/copper overview; ceruloplasmin is linked to copper interpretation.",
+    "copper": "Trace-mineral lab overview covering copper among other minerals.",
+    "free_t3": "Free T3/Free T4 video focuses on free thyroid hormones together.",
+    "fructosamine": "Diabetes overview; fructosamine is a shorter-term glycemic marker and is not the primary topic.",
+    "gra_absolute": "WBC differential overview; granulocyte absolute combines neutrophils, eosinophils, and basophils.",
+    "hct": "Hemoglobin/Hematocrit lab-values video covers hematocrit directly alongside hemoglobin.",
+    "hdl_cholesterol": "HDL/LDL cholesterol video focuses on HDL in direct lipid-marker context.",
+    "immunoglobulin_m": "IgG/IgM antibody-testing video covers IgM directly alongside IgG.",
+    "mcv": "Anemia interpretation video uses MCV directly; also discusses MCH context.",
     "mpv": "FBC/CBC guide covers platelets; MPV is not discussed in detail.",
-    "gra_absolute": "ANC overview; granulocyte absolute combines neutrophils, eosinophils, and basophils.",
-    "prealbumin": "LFT video discusses albumin; prealbumin is not covered directly.",
-    "procalcitonin": "Sepsis lecture focuses on lactate; PCT is not the primary topic."
+    "myoglobin": "Cardiac biomarker overview covers myoglobin with troponin and CK-MB.",
+    "nt_probnp": "Heart-failure overview; NT-proBNP is a heart-strain marker like BNP but not the primary title.",
+    "procalcitonin": "Sepsis lecture focuses on lactate; PCT is not the primary topic.",
+    "selenium": "Trace-mineral lab overview covering selenium among other minerals.",
+    "serum_iron": "Iron blood-test video covers serum iron with related iron-panel markers.",
+    "total_cholesterol": "Total cholesterol lab-values video also covers triglycerides, but total cholesterol is a primary topic.",
+    "total_t4": "T3/T4 lab-values video covers total thyroid hormones together.",
+    "tsh_receptor_antibodies": "Graves/hyperthyroidism overview; TRAb is discussed as thyroid autoimmunity context rather than as a standalone lab lecture.",
+    "vitamin_e": "Fat-soluble vitamin overview covering vitamin E with vitamins A/D/K.",
+    "zinc": "Trace-mineral lab overview covering zinc among other minerals."
   }
 }

scripts/expand_lab_knowledge_graph.py

@@ -30,6 +30,9 @@ MARKER_IDS: dict[str, str] = {
     "Absolute Eosinophil Count": "eos_absolute",
     "Absolute Basophil Count": "bas_absolute",
     "Reticulocyte Count": "reticulocyte_count",
+    "Haptoglobin": "haptoglobin",
+    "G6PD": "g6pd",
+    "Erythropoietin": "erythropoietin",
     "Glucose": "glucose",
     "Creatinine": "creatinine",
     "eGFR": "egfr",
@@ -48,15 +51,20 @@ MARKER_IDS: dict[str, str] = {
     "Uric Acid": "uric_acid",
     "Serum Iron": "serum_iron",
     "TIBC": "tibc",
+    "Transferrin": "transferrin",
     "Transferrin Saturation": "transferrin_saturation",
     "LDH": "ldh",
     "Osmolality": "osmolality",
     "Ammonia": "ammonia",
     "Lactate": "lactate",
     "Homocysteine": "homocysteine",
+    "Methylmalonic Acid": "methylmalonic_acid",
     "Cystatin C": "cystatin_c",
     "Prealbumin": "prealbumin",
     "Beta-2 Microglobulin": "beta_2_microglobulin",
+    "C-Peptide": "c_peptide",
+    "Fructosamine": "fructosamine",
+    "Beta-Hydroxybutyrate": "beta_hydroxybutyrate",
     "HbA1c": "hba1c",
     "ALT": "alt",
     "AST": "ast",
@@ -80,9 +88,16 @@ MARKER_IDS: dict[str, str] = {
     "Total T4": "total_t4",
     "Total T3": "total_t3",
     "Anti-TPO Antibodies": "anti_tpo_antibodies",
+    "TSH Receptor Antibodies": "tsh_receptor_antibodies",
+    "Thyroglobulin Antibodies": "thyroglobulin_antibodies",
     "Vitamin D": "vitamin_d",
     "Vitamin B12": "vitamin_b12",
     "Ferritin": "ferritin",
+    "Zinc": "zinc",
+    "Copper": "copper",
+    "Ceruloplasmin": "ceruloplasmin",
+    "Selenium": "selenium",
+    "Vitamin E": "vitamin_e",
     "Prothrombin Time": "prothrombin_time",
     "INR": "inr",
     "aPTT": "aptt",
@@ -95,10 +110,17 @@ MARKER_IDS: dict[str, str] = {
     "Complement C3": "complement_c3",
     "Complement C4": "complement_c4",
     "Rheumatoid Factor": "rheumatoid_factor",
+    "Anti-CCP Antibodies": "anti_ccp_antibodies",
+    "Immunoglobulin G": "immunoglobulin_g",
+    "Immunoglobulin A": "immunoglobulin_a",
+    "Immunoglobulin M": "immunoglobulin_m",
+    "Immunoglobulin E": "immunoglobulin_e",
     "BNP": "bnp",
+    "NT-proBNP": "nt_probnp",
     "Troponin I": "troponin_i",
     "Creatine Kinase": "creatine_kinase",
     "CK-MB": "ck_mb",
+    "Myoglobin": "myoglobin",
     "Cortisol": "cortisol",
     "Insulin": "insulin",
     "Testosterone": "testosterone",
@@ -109,15 +131,24 @@ MARKER_IDS: dict[str, str] = {
     "Progesterone": "progesterone",
     "Parathyroid Hormone": "pth",
     "ACTH": "acth",
+    "DHEA-S": "dhea_s",
+    "Androstenedione": "androstenedione",
+    "Anti-Mullerian Hormone": "anti_mullerian_hormone",
+    "Beta-hCG": "beta_hcg",
     "SHBG": "shbg",
     "IGF-1": "igf_1",
     "PSA": "psa",
+    "CEA": "cea",
+    "CA-125": "ca_125",
+    "CA 19-9": "ca_19_9",
+    "Alpha-Fetoprotein": "alpha_fetoprotein",
+    "CA 15-3": "ca_15_3",
     "Folate": "folate",
     "Vitamin A": "vitamin_a",
 }
 
 EXTRA_ALIAS_UPDATES: dict[str, list[str]] = {
-    "gra_absolute": ["ANC", "Absolute Neutrophil Count", "Abs Neutrophils", "Neutrophils Absolute"],
+    "gra_absolute": ["Absolute Granulocyte Count", "Granulocytes Absolute", "Abs Granulocytes"],
     "neu_absolute": ["ANC", "Absolute Neutrophil Count", "Abs Neutrophils", "Neutrophils Absolute"],
     "mon_absolute": ["AMC", "Absolute Monocyte Count", "Abs Monocytes", "Monocytes Absolute"],
     "eos_absolute": ["AEC", "Absolute Eosinophil Count", "Abs Eosinophils", "Eosinophils Absolute"],
@@ -335,9 +366,9 @@ def _why_important(name: str, kb_entry: Any) -> str:
         return f"Abnormal {name} values can be clinically meaningful and should be interpreted with symptoms, history, and related tests."
     parts = []
     if kb_entry.high:
-        parts.append(f"A high value may be associated with {kb_entry.high[0].lower()}{kb_entry.high[1:]}")
+        parts.append(kb_entry.high)
     if kb_entry.low:
-        parts.append(f"A low value may be associated with {kb_entry.low[0].lower()}{kb_entry.low[1:]}")
+        parts.append(kb_entry.low)
     return " ".join(parts) if parts else f"{name} helps clinicians evaluate related organ systems and disease patterns."
 
 
@@ -376,6 +407,27 @@ def _merge_aliases(test: dict[str, Any], extra: list[str]) -> None:
     test["aliases"] = aliases
 
 
+def _remove_aliases(test: dict[str, Any], stale: set[str]) -> None:
+    test["aliases"] = [alias for alias in test.get("aliases", []) if alias.casefold() not in stale]
+
+
+def _refresh_generated_fields(test: dict[str, Any], marker: Any, test_id: str, video_url: str, kb_entry: Any) -> None:
+    rebuilt = _build_test(marker, test_id, video_url, kb_entry)
+    for key in (
+        "display_name",
+        "category",
+        "unit",
+        "description",
+        "why_important",
+        "sex_significance",
+        "instructions_to_improve",
+        "statistics_per_group_age",
+        "video_url",
+    ):
+        test[key] = rebuilt[key]
+    _merge_aliases(test, rebuilt["aliases"])
+
+
 def main() -> None:
     import sys
 
@@ -396,7 +448,7 @@ def main() -> None:
         kb_entry = KB.get(marker.name)
         if test_id in existing_by_id:
             test = existing_by_id[test_id]
-            test["video_url"] = video_url
+            _refresh_generated_fields(test, marker, test_id, video_url, kb_entry)
             _merge_aliases(test, list(marker.aliases))
             continue
         existing_by_id[test_id] = _build_test(marker, test_id, video_url, kb_entry)
@@ -406,6 +458,17 @@ def main() -> None:
         if legacy_id in existing_by_id:
             existing_by_id[legacy_id]["video_url"] = videos.get(legacy_id, existing_by_id[legacy_id].get("video_url", ""))
             _merge_aliases(existing_by_id[legacy_id], EXTRA_ALIAS_UPDATES.get(legacy_id, []))
+            if legacy_id == "gra_absolute":
+                _remove_aliases(
+                    existing_by_id[legacy_id],
+                    {
+                        "anc",
+                        "anc when neutrophil-dominant",
+                        "absolute neutrophil count",
+                        "abs neutrophils",
+                        "neutrophils absolute",
+                    },
+                )
 
     for test_id, extra_aliases in EXTRA_ALIAS_UPDATES.items():
         if test_id in existing_by_id:

src/markers.py

@@ -69,6 +69,9 @@ MARKERS: tuple[Marker, ...] = (
     Marker("Absolute Eosinophil Count", "10^3/uL", 0, 0.5, "CBC", "count of allergy and parasite-related white cells", ("AEC", "Eosinophils Absolute", "Abs Eosinophils")),
     Marker("Absolute Basophil Count", "10^3/uL", 0, 0.2, "CBC", "count of histamine-related white cells", ("ABC", "Basophils Absolute", "Abs Basophils")),
     Marker("Reticulocyte Count", "%", 0.5, 2.5, "CBC", "young red cells recently released from bone marrow", ("Retic Count", "Retics")),
+    Marker("Haptoglobin", "mg/dL", 30, 200, "CBC", "protein that binds free hemoglobin after red-cell breakdown", ("HP",)),
+    Marker("G6PD", "U/g Hb", 5.5, 20.5, "CBC", "red-cell enzyme that protects against oxidative stress", ("Glucose-6-Phosphate Dehydrogenase", "G6PDH")),
+    Marker("Erythropoietin", "mIU/mL", 4, 27, "CBC", "kidney hormone that stimulates red-cell production", ("EPO",)),
     # --- Metabolic panel ---
     Marker("Glucose", "mg/dL", 70, 99, "Metabolic", "blood sugar level", ("Fasting Glucose", "GLU", "Blood Sugar", "FBS", "RBS", "Fasting Blood Sugar")),
     Marker("Creatinine", "mg/dL", 0.7, 1.3, "Metabolic", "kidney-function waste product", ("Cr", "Serum Creatinine")),
@@ -88,15 +91,20 @@ MARKERS: tuple[Marker, ...] = (
     Marker("Uric Acid", "mg/dL", 3.5, 7.2, "Metabolic", "breakdown product of purines; linked to gout", ("UA", "Urate")),
     Marker("Serum Iron", "mcg/dL", 60, 170, "Metabolic", "circulating iron available for red-cell production", ("Iron", "Fe", "Iron, Serum")),
     Marker("TIBC", "mcg/dL", 250, 450, "Metabolic", "blood's capacity to bind and transport iron", ("Total Iron Binding Capacity", "Iron Binding Capacity")),
+    Marker("Transferrin", "mg/dL", 200, 360, "Metabolic", "main blood protein that transports iron", ("TRF",)),
     Marker("Transferrin Saturation", "%", 20, 50, "Metabolic", "percent of iron-binding sites occupied", ("TSAT", "Iron Saturation")),
     Marker("LDH", "U/L", 140, 280, "Metabolic", "enzyme released when cells are damaged", ("Lactate Dehydrogenase",)),
     Marker("Osmolality", "mOsm/kg", 275, 295, "Metabolic", "concentration of particles in the blood", ("Serum Osmolality",)),
     Marker("Ammonia", "mcg/dL", 15, 45, "Metabolic", "waste product processed by the liver", ("NH3", "Blood Ammonia")),
     Marker("Lactate", "mmol/L", 0.5, 2.0, "Metabolic", "byproduct of anaerobic metabolism", ("Lactic Acid", "Lactate, Blood")),
     Marker("Homocysteine", "umol/L", 5, 15, "Metabolic", "amino acid linked to B-vitamin status and vascular risk", ("Hcy",)),
+    Marker("Methylmalonic Acid", "nmol/L", None, 378, "Metabolic", "functional marker of vitamin B12 activity", ("MMA",)),
     Marker("Cystatin C", "mg/L", 0.53, 0.95, "Metabolic", "kidney-function marker less affected by muscle mass", ("CysC",)),
     Marker("Prealbumin", "mg/dL", 20, 40, "Metabolic", "short-lived protein reflecting recent nutrition", ("Transthyretin",)),
     Marker("Beta-2 Microglobulin", "mg/L", 0.7, 1.8, "Metabolic", "small protein from cell turnover; kidney and immune marker", ("B2M", "β2-Microglobulin")),
+    Marker("C-Peptide", "ng/mL", 0.5, 2.0, "Metabolic", "pancreatic insulin production marker", ("C Peptide", "Connecting Peptide")),
+    Marker("Fructosamine", "umol/L", 205, 285, "Metabolic", "shorter-term average blood sugar marker", ("Glycated Serum Protein",)),
+    Marker("Beta-Hydroxybutyrate", "mmol/L", 0, 0.4, "Metabolic", "main blood ketone body", ("BHB", "β-Hydroxybutyrate", "3-Hydroxybutyrate")),
     # --- Liver enzymes ---
     Marker("ALT", "U/L", 7, 56, "Liver", "liver enzyme released when liver cells are stressed", ("Alanine Aminotransferase", "SGPT")),
     Marker("AST", "U/L", 10, 40, "Liver", "enzyme from liver and muscle cells", ("Aspartate Aminotransferase", "SGOT")),
@@ -122,10 +130,17 @@ MARKERS: tuple[Marker, ...] = (
     Marker("Total T4", "mcg/dL", 4.5, 12.0, "Thyroid", "total thyroxine including bound and free", ("T4", "Thyroxine")),
     Marker("Total T3", "ng/dL", 80, 200, "Thyroid", "total triiodothyronine including bound and free", ("T3", "Triiodothyronine")),
     Marker("Anti-TPO Antibodies", "IU/mL", None, 35, "Thyroid", "antibodies against thyroid peroxidase", ("TPO Antibodies", "Thyroid Peroxidase Antibodies", "Anti-TPO")),
+    Marker("TSH Receptor Antibodies", "IU/L", None, 1.75, "Thyroid", "antibodies that can stimulate or block the TSH receptor", ("TRAb", "TSH-R Ab")),
+    Marker("Thyroglobulin Antibodies", "IU/mL", None, 4, "Thyroid", "antibodies against thyroglobulin", ("TgAb", "Anti-Thyroglobulin Antibodies")),
     # --- Vitamins / iron ---
     Marker("Vitamin D", "ng/mL", 30, 100, "Vitamin", "vitamin for bone and immune health", ("25-OH Vitamin D", "25-Hydroxyvitamin D", "Vit D")),
     Marker("Vitamin B12", "pg/mL", 200, 900, "Vitamin", "vitamin for nerves and red-cell production", ("B12", "Cobalamin")),
     Marker("Ferritin", "ng/mL", 30, 400, "Vitamin", "stored-iron protein", ("FERR",)),
+    Marker("Zinc", "mcg/dL", 60, 130, "Vitamin", "trace mineral involved in immunity and wound healing", ("Zn",)),
+    Marker("Copper", "mcg/dL", 70, 140, "Vitamin", "trace mineral involved in blood, nerves, and enzymes", ("Cu",)),
+    Marker("Ceruloplasmin", "mg/dL", 20, 35, "Vitamin", "copper-carrying protein made by the liver", ("CP",)),
+    Marker("Selenium", "mcg/L", 70, 150, "Vitamin", "trace mineral used in antioxidant and thyroid-related enzymes", ("Se",)),
+    Marker("Vitamin E", "mg/L", 5.5, 17, "Vitamin", "fat-soluble antioxidant vitamin", ("Alpha-Tocopherol", "Tocopherol")),
     Marker("HbA1c", "%", 4.0, 5.6, "Metabolic", "average blood sugar over ~3 months", ("A1c", "Hemoglobin A1c", "Glycated Hemoglobin")),
     # --- Coagulation ---
     Marker("Prothrombin Time", "seconds", 11, 13.5, "Coagulation", "time for the clotting cascade to form fibrin", ("PT",)),
@@ -141,11 +156,18 @@ MARKERS: tuple[Marker, ...] = (
     Marker("Complement C3", "mg/dL", 90, 180, "Inflammation", "complement protein in immune activation", ("C3",)),
     Marker("Complement C4", "mg/dL", 10, 40, "Inflammation", "complement protein in immune activation", ("C4",)),
     Marker("Rheumatoid Factor", "IU/mL", None, 14, "Inflammation", "antibody sometimes seen in autoimmune arthritis", ("RF",)),
+    Marker("Anti-CCP Antibodies", "U/mL", None, 20, "Inflammation", "autoantibodies associated with rheumatoid arthritis", ("Anti CCP", "CCP Antibodies", "Cyclic Citrullinated Peptide Antibodies")),
+    Marker("Immunoglobulin G", "mg/dL", 700, 1600, "Inflammation", "major circulating antibody class", ("IgG",)),
+    Marker("Immunoglobulin A", "mg/dL", 70, 400, "Inflammation", "antibody class important at mucosal surfaces", ("IgA",)),
+    Marker("Immunoglobulin M", "mg/dL", 40, 230, "Inflammation", "early-response antibody class", ("IgM",)),
+    Marker("Immunoglobulin E", "IU/mL", None, 100, "Inflammation", "antibody class linked to allergy and parasite responses", ("IgE",)),
     # --- Cardiac ---
     Marker("BNP", "pg/mL", None, 100, "Cardiac", "hormone released when the heart is stretched", ("B-Type Natriuretic Peptide", "Brain Natriuretic Peptide")),
+    Marker("NT-proBNP", "pg/mL", None, 125, "Cardiac", "heart-stretch peptide used in heart failure assessment", ("N-terminal pro-BNP", "NT pro BNP")),
     Marker("Troponin I", "ng/mL", None, 0.04, "Cardiac", "heart-muscle protein released with injury", ("TnI", "High-Sensitivity Troponin I")),
     Marker("Creatine Kinase", "U/L", 30, 200, "Cardiac", "enzyme from muscle including heart and skeletal", ("CK", "CPK", "Creatine Phosphokinase")),
     Marker("CK-MB", "ng/mL", None, 5, "Cardiac", "heart-enriched fraction of creatine kinase", ("CKMB", "Creatine Kinase-MB")),
+    Marker("Myoglobin", "ng/mL", 25, 72, "Cardiac", "oxygen-binding muscle protein released with muscle injury", ("Mb",)),
     # --- Hormones ---
     Marker("Cortisol", "mcg/dL", 6, 18, "Hormone", "stress hormone from the adrenal glands", ("AM Cortisol", "Serum Cortisol")),
     Marker("Insulin", "uIU/mL", 2.6, 24.9, "Hormone", "hormone that lowers blood sugar", ("Fasting Insulin",)),
@@ -157,10 +179,19 @@ MARKERS: tuple[Marker, ...] = (
     Marker("Progesterone", "ng/mL", 0.2, 25, "Hormone", "hormone that supports the uterine lining", ("P4",)),
     Marker("Parathyroid Hormone", "pg/mL", 15, 65, "Hormone", "hormone that regulates blood calcium", ("PTH", "Intact PTH")),
     Marker("ACTH", "pg/mL", 7, 63, "Hormone", "pituitary signal that drives cortisol production", ("Adrenocorticotropic Hormone",)),
+    Marker("DHEA-S", "mcg/dL", 35, 430, "Hormone", "adrenal androgen precursor", ("Dehydroepiandrosterone Sulfate", "DHEAS")),
+    Marker("Androstenedione", "ng/dL", 30, 200, "Hormone", "androgen precursor made by adrenal glands and gonads", ("A4",)),
+    Marker("Anti-Mullerian Hormone", "ng/mL", 1, 4, "Hormone", "ovarian reserve-related hormone", ("AMH", "Anti Mullerian Hormone")),
+    Marker("Beta-hCG", "mIU/mL", None, 5, "Hormone", "pregnancy-associated hormone also used in some tumor monitoring", ("β-hCG", "Human Chorionic Gonadotropin", "hCG")),
     Marker("SHBG", "nmol/L", 10, 80, "Hormone", "protein that binds sex hormones in the blood", ("Sex Hormone Binding Globulin",)),
     Marker("IGF-1", "ng/mL", 115, 355, "Hormone", "growth factor reflecting growth-hormone activity", ("Insulin-Like Growth Factor 1", "Somatomedin C")),
     # --- Oncology / screening ---
     Marker("PSA", "ng/mL", None, 4.0, "Oncology", "prostate-specific protein used in screening", ("Prostate Specific Antigen",)),
+    Marker("CEA", "ng/mL", None, 3.0, "Oncology", "tumor marker often followed in colorectal and other cancers", ("Carcinoembryonic Antigen",)),
+    Marker("CA-125", "U/mL", None, 35, "Oncology", "tumor marker often followed in ovarian and related conditions", ("Cancer Antigen 125", "CA 125")),
+    Marker("CA 19-9", "U/mL", None, 37, "Oncology", "tumor marker often followed in pancreaticobiliary conditions", ("CA19-9", "Carbohydrate Antigen 19-9")),
+    Marker("Alpha-Fetoprotein", "ng/mL", None, 10, "Oncology", "tumor marker used in liver and germ-cell tumor follow-up", ("AFP",)),
+    Marker("CA 15-3", "U/mL", None, 30, "Oncology", "tumor marker sometimes followed in breast cancer care", ("CA15-3", "Cancer Antigen 15-3")),
     # --- Vitamins / iron (continued) ---
     Marker("Folate", "ng/mL", 3, 20, "Vitamin", "B vitamin needed for DNA and red-cell production", ("Folic Acid", "Serum Folate")),
     Marker("Vitamin A", "mcg/dL", 30, 65, "Vitamin", "fat-soluble vitamin for vision and immunity", ("Retinol",)),