physiology

# Physiology ## What I Do Physiology studies the normal function of living systems at molecular, cellular, and organismal levels. I cover organ systems (cardiovascular, respiratory, nervous, endocrine), homeostasis, metabolism, fluid balance, and integrative physiology. I help understand how organ systems work together to maintain health. ## When to Use Me - Understanding organ system function and regulation - Analyzing homeostatic control mechanisms - Studying metabolism and energy balance - Understanding cardiovascular and respiratory physiology - Studying endocrine and nervous system communication - Analyzing fluid and electrolyte balance - Understanding exercise and environmental physiology ## Core Concepts 1. **Homeostasis**: Negative feedback, set points, allostatic load 2. **Cardiovascular System**: Cardiac output, blood pressure, microcirculation 3. **Respiratory System**: Lung volumes, gas exchange, oxygen transport 4. **Nervous System**: Action potentials, synaptic transmission, reflexes 5. **Endocrine System**: Hormones, feedback loops, target tissue responses 6. **Renal Physiology**: Filtration, reabsorption, secretion, concentration 7. **Gastrointestinal System**: Digestion, absorption, motility, secretion 8. **Metabolism**: Basal metabolic rate, substrate utilization 9. **Thermoregulation**: Heat production, heat loss, hypothalamic control 10. **Muscle Physiology**: Contraction, excitation-contraction coupling ## Code Examples ```python import numpy as np from typing import List, Dict, Tuple class CardiovascularPhysiology: def __init__(self, patient_id: str): self.patient = patient_id def calculate_cardiac_output(self, heart_rate: float, stroke_volume: float) -> float: return heart_rate * stroke_volume def mean_arterial_pressure(self, systolic: float, diastolic: float) -> float: return diastolic + (systolic - diastolic) / 3 def total_peripheral_resistance(self, map_val: float, cardiac_output: float) -> float: return (map_val / cardiac_output) * 80 # mmHg/L/min to dyn·s/cm^5 def ejection_fraction(self, edv: float, esv: float) -> float: return (edv - esv) / edv * 100 def stroke_work(self, map_val: float, stroke_volume: float) -> float: return map_val * stroke_volume * 0.0136 # mmHg·mL to Joules def vo2_max_estimation(self, age: int, sex: str, resting_hr: float) -> float: if sex == 'male': return 15.3 * (resting_hr / 70) ** (-0.4) - age * 0.2 return 15.3 * (resting_hr / 75) ** (-0.4) - age * 0.2 class RespiratoryPhysiology: def __init__(self, subject_id: str): self.subject = subject_id def alveolar_gas_equation(self, patm: float, paco2: float, fio2: float, rq: float) -> float: PAO2 = fio2 * (patm - 47) - (paco2 / rq) + (paco2 * fio2 * (1 - rq) / rq) return PAO2 def alveolar_ventilation(self, vco2: float, paco2: float) -> float: return (vco2 / paco2) * 863 # L/min def calculate_shunt(self, cco2: float, cao2: float, cvo2: float) -> float: return (cco2 - cao2) / (cco2 - cvo2) * 100 def diffusion_capacity(self, vco2: float, paco2: float) -> float: return vco2 / paco2 def lung_compliance(self, volume_change: float, pressure_change: float) -> float: return volume_change / pressure_change class RenalPhysiology: def __init__(self, patient: str): self.patient = patient def glomerular_filtration_rate(self, u creatinine: float, ucr_molar: float, plasma_creatinine: float, pcr_molar: float, age: int, weight: float, sex: str) -> float: if sex == 'male': return (140 - age) * weight / (72 * plasma_creatinine) return (140 - age) * weight * 0.85 / (72 * plasma_creatinine) def effective_circulating_volume(self, map_val: float, cvp: float) -> float: return map_val - cvp def fractional_excretion(self, u_x: float, p_x: float, u_cr: float, p_cr: float) -> float: return (u_x / p_x) / (u_cr / p_cr) * 100 def free_water_clearance(self, osm_plasma: float, u_osm: float, v: float) -> float: return v - (u_osm / osm_plasma) * v def urine_concentration(self, u_osm: float, p_osm: float) -> float: return u_osm / p_osm class MetabolicPhysiology: def __init__(self, individual: str): self.individual = individual def basal_metabolic_rate(self, weight: float, height: float, age: int, sex: str) -> float: if sex == 'male': return 88.362 + 13.397 * weight + 4.799 * height - 5.677 * age return 447.593 + 9.247 * weight + 3.098 * height - 4.330 * age def respiratory_quotient(self, co2_produced: float, o2_consumed: float) -> float: return co2_produced / o2_consumed def substrate_oxidation(self, vo2: float, vco2: float, urinary_nitrogen: float) -> Dict: rq = vco2 / vo2 cho_ox = 4.11 * vco2 - 2.96 * vo2 - 2.54 * urinary_nitrogen fat_ox = 1.68 * vo2 - 1.94 * vco2 - 1.94 * urinary_nitrogen return {'carbohydrate_oxidation': max(0, cho_ox), 'fat_oxidation': max(0, fat_ox), 'respiratory_quotient': rq} def thermic_effect_of_food(self, tef: float, bmr: float) -> float: return tef / bmr * 100 cardio = CardiovascularPhysiology("Patient001") co = cardio.calculate_cardiac_output(70, 70) print(f"Cardiac Output: {co:.1f} L/min") map_press = cardio.mean_arterial_pressure(120, 80) print(f"MAP: {map_press:.1f} mmHg") resp = RespiratoryPhysiology("Subject001") pao2 = resp.alveolar_gas_equation(760, 40, 0.21, 0.8) print(f"Alveolar PO2: {pao2:.1f} mmHg") ``` ## Best Practices 1. Consider whole-organism integration in physiological studies 2. Account for compensatory mechanisms in disease states 3. Use appropriate reference ranges for age, sex, and population 4. Consider circadian rhythms in physiological measurements 5. Validate measurements against gold-standard techniques 6. Account for acclimatization in environmental physiology 7. Use proper units and conversions in calculations 8. Consider inter-individual variability in responses 9. Apply proper ethical standards in human/animal research 10. Document measurement conditions for reproducibility