Nutrition, Diet, Health, Medicine

Continuing on the reference. building … interesting insights emerging.  Lots of fad diets, some kernels of truth, lots of confusion, lots of marketing. lots to sort out. Somewhere along the development,  the connection between inputs and outcomes will become much clearer. Especially if one really isn’t in the huckstering business.

Some sources to consider:

Agatston, A. (2005). The South Beach diet: The delicious, doctor-designed, foolproof plan for fast and healthy weight loss. New York: St. Martin’s Griffin.
Atkins, R. C. (2002). Dr. Atkins’ new diet revolution. New York: M. Evans.
Bijlefeld, M., & Zoumbaris, S. K. (2015). Encyclopedia of diet fads: Understanding science and society (Second edition). Santa Barbara, California: Greenwood, an imprint of ABC-CLIO, LLC.

Bullmore, E. T. (2019). The inflamed mind: A radical new approach to depression (First U.S. edition). New York: Picador.

CRUMPTON, M. J., & DEDMAN, J. R. (1990). Protein terminology tangle. Nature, 345(6272), 212–212. https://doi.org/10.1038/345212a0

Cummings, J. H., & Stephen, A. M. (2007). Carbohydrate terminology and classification. European Journal Of Clinical Nutrition, 61, S5.

DiNicolantonio, J., & Mercola, J. (2018). Super fuel: Ketogenic keys to unlock the secrets of good fats, bad fats, and great health (1st edition). Carlsbad, California: Hay House Inc.

Freeman, J. M., & Freeman, J. M. (Eds.). (2007). The ketogenic diet: A treatment for children and others with epilepsy (4th ed). New York: Demos : Distributed to the trade by Publishers Group West.

Gioffre, D., & Ripa, K. (2018). Get off your acid: 7 steps in 7 days to lose weight, fight inflammation and reclaim your health and energy (First edition). New York, NY: Da Capo.

Goff, S. L., Foody, J. M., Inzucchi, S., Katz, D., Mayne, S. T., & Krumholz, H. M. (2006). BRIEF REPORT: Nutrition and weight loss information in a popular diet book: is it fact, fiction, or something in between? Journal of General Internal Medicine, 21(7), 769–774. https://doi.org/10.1111/j.1525-1497.2006.00501.x

Gudzune, K. A., Doshi, R. S., Mehta, A. K., Chaudhry, Z. W., Jacobs, D. K., Vakil, R. M., … Clark, J. M. (2015). Efficacy of Commercial Weight-Loss Programs: An Updated Systematic Review. Annals of Internal Medicine, 162(7), 501. https://doi.org/10.7326/M14-2238

Ouzounis, C. A., Coulson, R. M. R., Enright, A. J., Kunin, V., & Pereira-Leal, J. B. (2003). Classification schemes for protein structure and function. Nature Reviews Genetics, 4(7), 508–519. https://doi.org/10.1038/nrg1113

Pritikin, N., & MacGrady, P. M. (1979). The Pritikin program for diet and exercise. New York: Grosset & Dunlap.

Rahfeld, P., Sim, L., Moon, H., Constantinescu, I., Morgan-Lang, C., Hallam, S. J., … Withers, S. G. (2019). An enzymatic pathway in the human gut microbiome that converts A to universal O type blood. Nature Microbiology. https://doi.org/10.1038/s41564-019-0469-7

Hagen’s Biological and clinical data integration in healthcare study is great!

Just finished looking at Matt Hagen’s 2014 “Biological and clinical data integration and its applications in healthcare.” PhD  dissertation. This is a great piece of work … You can find it here.

While its around 5 years old, the insights and discussion are excellent.  I like the detailed breakdown of how different ontologies and vocabularies align (and how things fall through the cracks).  I liked the discussion of using Neo4j to analyze relationships and simplify searches and relationship mappings.

Particularly liked the discussion of using  ontologies.  to” facilitate improved prioritization of intensive care admissions and accurate clustering of multimorbidity conditions”.  THIS IS BIG! with enormous potential.

Discussion of his BioSPIDA relational database translator and its contrast with  the separate Entrez Gene, Pubmed, CDD, Refseq, MMDB, and Biosystems NCBI databases.

His Table 7.2: Descriptions of patient clusters is rather illuminating, as his discussion and analysis of ICU Electronic Health Records and findings associated with morbidity outcomes.

For example Cluster 1 contains the following Most Prevalent Conditions: Coronary arteriosclerosis, Hypercholesterolemia, Diabetes, Gastroesophageal reflux disease,  Atrial fibrillation, Hyperlipidemia, Tobacco dependence.  Which led to the following Most Prevalent Procedures:  Catheterization of left heart, Cardiopulmonary bypass operation, Angiocardiography of left heart,.

 

 I  am surprised this work is not cited as much as it should be!.  IMHO, this work definitely should be used as blueprint for additional investigations.