""" species_reference.py ==================== RodentCGMTel — species/model 특이적 혈당 reference range 라이브러리. 각 모델별로 일반적인 fasted/fed/random 혈당 범위(mg/dL) 및 TIR(time-in-range) 정의용 타겟 범위를 보유한다. 값은 동물실험 IACUC 데이터 사후분석을 위한 참고 기준이며, 연구실/스트레인 배치별로 달라질 수 있으므로 사용자가 UI에서 overlay/override 가능하다. 출처(참고): - Andrikopoulos et al., Am J Physiol Endocrinol Metab 2008 (mouse GTT 권고) - Berglund et al., Diabetes 2008 (C57BL/6 표준) - Leiter, Diabetes 1981 (db/db, ob/ob) - Hummel et al., Science 1966 (db/db) - Hayashi et al., Endocrinology 2002 (KK-Ay) - Ueda et al., Metabolism 1995 (NZO) - Furman, Curr Protoc Pharmacol 2015 (STZ T1DM 모델) - Goto et al., Proc Japan Acad 1975 (GK rat) - Clark et al., Proc Soc Exp Biol Med 1983 (ZDF) - Speakman, Cell Metab 2019 (DIO HFD) DISCLAIMER: 연구·참고용. 임상의사결정용 아님. IACUC 승인 동물실험 데이터 사후 분석용. """ # 단위: mg/dL. CGM telemetry는 ISF 기반이므로 본 라이브러리는 동물용 CGM 보정값(plasma equivalent) 기준이다. # TIR target range: (low, high). hypo cut-off는 mouse 70, rat 60 mg/dL이 통상이며 모델별로 override 한다. SPECIES_REFERENCE = { "C57BL/6J": { "species": "mouse", "strain_type": "control_lean", "fasted_bg": (80, 110), "fed_bg": (140, 180), "random_bg": (110, 180), "tir_target": (80, 180), "hypo_threshold": 70, "severe_hypo": 50, "hyper_threshold": 250, "severe_hyper": 300, "notes": "표준 야생형 대조. dawn phenomenon 약하게 관찰. nocturnal feeder.", "expected_cv_pct": (10, 20), }, "db/db (BKS.Cg-Dock7m+/+ Leprdb)": { "species": "mouse", "strain_type": "T2DM_obese", "fasted_bg": (180, 280), "fed_bg": (350, 550), "random_bg": (300, 500), "tir_target": (80, 250), "hypo_threshold": 70, "severe_hypo": 50, "hyper_threshold": 400, "severe_hyper": 500, "notes": "Leptin receptor null. 6-8주령에 명확한 hyperglycemia. polyuria/polydipsia.", "expected_cv_pct": (15, 30), }, "ob/ob (B6.Cg-Lepob)": { "species": "mouse", "strain_type": "obese_modest_hyper", "fasted_bg": (120, 180), "fed_bg": (200, 320), "random_bg": (180, 280), "tir_target": (80, 250), "hypo_threshold": 70, "severe_hypo": 50, "hyper_threshold": 350, "severe_hyper": 450, "notes": "Leptin null. 비만은 심하나 hyperglycemia는 db/db보다 약함. age-dependent.", "expected_cv_pct": (15, 25), }, "STZ T1DM mouse": { "species": "mouse", "strain_type": "T1DM_chemical", "fasted_bg": (250, 400), "fed_bg": (400, 600), "random_bg": (350, 550), "tir_target": (80, 250), "hypo_threshold": 70, "severe_hypo": 50, "hyper_threshold": 400, "severe_hyper": 500, "notes": "Streptozotocin multi-low-dose 또는 single-high-dose. β-cell ablation. insulin 의존.", "expected_cv_pct": (20, 40), }, "NZO": { "species": "mouse", "strain_type": "polygenic_T2DM", "fasted_bg": (140, 220), "fed_bg": (250, 400), "random_bg": (200, 350), "tir_target": (80, 250), "hypo_threshold": 70, "severe_hypo": 50, "hyper_threshold": 350, "severe_hyper": 450, "notes": "New Zealand Obese. polygenic obesity + IGT, sex-dependent T2DM 발현.", "expected_cv_pct": (15, 25), }, "KK-Ay": { "species": "mouse", "strain_type": "T2DM_obese", "fasted_bg": (150, 240), "fed_bg": (300, 500), "random_bg": (250, 400), "tir_target": (80, 250), "hypo_threshold": 70, "severe_hypo": 50, "hyper_threshold": 400, "severe_hyper": 500, "notes": "Yellow agouti(Ay) allele on KK. 12-16주령 hyperglycemia. obesity + IR.", "expected_cv_pct": (15, 30), }, "Sprague-Dawley (SD)": { "species": "rat", "strain_type": "control_lean", "fasted_bg": (70, 110), "fed_bg": (110, 160), "random_bg": (90, 150), "tir_target": (60, 160), "hypo_threshold": 60, "severe_hypo": 45, "hyper_threshold": 200, "severe_hyper": 250, "notes": "표준 outbred rat 대조. metabolic study baseline.", "expected_cv_pct": (8, 18), }, "Wistar": { "species": "rat", "strain_type": "control_lean", "fasted_bg": (70, 105), "fed_bg": (105, 155), "random_bg": (85, 145), "tir_target": (60, 160), "hypo_threshold": 60, "severe_hypo": 45, "hyper_threshold": 200, "severe_hyper": 250, "notes": "Wistar outbred rat. SD와 유사한 metabolic profile.", "expected_cv_pct": (8, 18), }, "ZDF (Zucker Diabetic Fatty)": { "species": "rat", "strain_type": "T2DM_obese", "fasted_bg": (150, 280), "fed_bg": (300, 500), "random_bg": (250, 450), "tir_target": (60, 250), "hypo_threshold": 60, "severe_hypo": 45, "hyper_threshold": 400, "severe_hyper": 500, "notes": "Leptin receptor mutation rat. males 발현 강함. 8-10주령 hyperglycemia.", "expected_cv_pct": (15, 30), }, "GK (Goto-Kakizaki)": { "species": "rat", "strain_type": "non_obese_T2DM", "fasted_bg": (110, 170), "fed_bg": (170, 280), "random_bg": (150, 250), "tir_target": (60, 220), "hypo_threshold": 60, "severe_hypo": 45, "hyper_threshold": 300, "severe_hyper": 400, "notes": "Non-obese T2DM rat. β-cell mass 감소. spontaneous IGT.", "expected_cv_pct": (12, 22), }, "DIO HFD (C57BL/6J 60% HFD)": { "species": "mouse", "strain_type": "diet_induced_obese", "fasted_bg": (110, 170), "fed_bg": (180, 280), "random_bg": (150, 240), "tir_target": (80, 220), "hypo_threshold": 70, "severe_hypo": 50, "hyper_threshold": 300, "severe_hyper": 400, "notes": "60% kcal HFD ≥12주. obesity + IR + mild hyperglycemia. T2DM 전구.", "expected_cv_pct": (12, 22), }, } # 측정 단위 변환(필요시) def mgdl_to_mmoll(mgdl: float) -> float: """mg/dL → mmol/L (당뇨: 18.0 환산).""" return mgdl / 18.0 def mmoll_to_mgdl(mmoll: float) -> float: return mmoll * 18.0 # 라이트/다크 사이클 표준 (12:12, lights on 07:00) DEFAULT_LIGHT_CYCLE = { "lights_on_hr": 7, "lights_off_hr": 19, } # Challenge 표준 프로토콜 (참고치) CHALLENGE_PROTOCOLS = { "GTT_ip": { "name": "Intraperitoneal Glucose Tolerance Test", "dose_g_per_kg": 2.0, "fasting_hr": 6, "sampling_minutes": [0, 15, 30, 60, 90, 120], "notes": "Andrikopoulos 2008 권고. 마우스 6h fast.", }, "GTT_oral": { "name": "Oral Glucose Tolerance Test", "dose_g_per_kg": 2.0, "fasting_hr": 6, "sampling_minutes": [0, 15, 30, 60, 90, 120], "notes": "GLP-1 inkretin 반영. gavage.", }, "ITT": { "name": "Insulin Tolerance Test", "dose_U_per_kg": 0.75, "fasting_hr": 4, "sampling_minutes": [0, 15, 30, 45, 60, 90], "notes": "insulin sensitivity 추정. severe hypo 모니터.", }, "MTT": { "name": "Mixed Meal Tolerance Test", "dose_kcal_per_kg": 10.0, "fasting_hr": 6, "sampling_minutes": [0, 15, 30, 60, 90, 120, 180], "notes": "physiological postprandial 평가.", }, } def list_models() -> list: """등록된 species/model 키 목록.""" return list(SPECIES_REFERENCE.keys()) def get_reference(model_key: str) -> dict: """모델 키에 해당하는 reference dict 반환. 없으면 KeyError.""" if model_key not in SPECIES_REFERENCE: raise KeyError(f"Unknown model: {model_key}. Available: {list_models()}") return SPECIES_REFERENCE[model_key]