Individuals with higher body fat percentages often experience more dramatic absolute changes in measurements and weight
--- Practical Example: BPC-157 + TB-500 + GHK-Cu Vials (pre-reconstituted, in fridge): BPC-157: 5mg vial + 2.5mL BAC = 2mg/mL TB-500: 10mg vial + 2mL BAC = 5mg/mL GHK-Cu: 50mg vial + 5mL BAC = 10mg/mL Target doses: BPC-157: 250mcg draw 12.5 units (100u syringe) TB-500: 500mcg draw 10 units GHK-Cu: 1mg draw 10 units Total draw: ~32.5 units = 0.325mL very comfortable for a single subQ injection
At Claudias Concept , we always look beneath the surface and in this case, the science points directly to your iron levels
Disclosure of interest: NO Poster Session I - DIGITAL TRANSFORMATION, AI AND ROBOTICS 07.00 - DIGITAL TRANSFORMATION, AI AND ROBOTICS - 07.01 - TECHNOLOGY INNOVATIONS: ROBOTS, VIRTUAL REALITY, ARTIFICIAL INTELLIGENCE AND MORE P308 - ESOC25-442 CLINICIAN PERSPECTIVES ON MACHINE LEARNING TOOLS FOR OUTCOME PREDICTION AND DECISION-MAKING IN INTRACEREBRAL HAEMORRHAGE Alexandra Hurden 1 , Menglu Ouyang, Leibo Liu 1,2 , Xiaoying Chen 1 , Craig Anderson 1 The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, Australia, 2 Centre for Big Data Research in Health, Faculty of Medicine, University of New South Wales, Sydney, Australia Background and Aims: Machine learning (ML) tools hold promise in outcome prediction and assisting clinicians decision making for patients with acute intracerebral haemorrhage (ICH)
