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The larger frame is the depiction frame, and it's where all the alchemy occurs. After setting up your selections, this frame will update when you press the 'Update Map' button. Let's go ahead and set up some imaginary goals for an imaginary client with a 'hot' gut and low overall diversity. We'll tweak Radiance to
· Enhance Akkermansia and Faecalibacterium: These two genera are typically overall 'good guys' in the human microbiome. Akkermansia is a mucin degrader, and because of that occupies a 'keystone' role in the microbiome. Faecalibacterium is a genus thought to be anti-inflammatory via its modulation of IL10.
· Diminish Collinsella and Bilophila: Collinsella is considered an 'inflammatory pathobiont' and is linked to the progression of rheumatoid arthritis. Bilophila likes leftover bile and its overgrowthhas been linked to an increased risk of colon cancer.
To do this we tick the green boxes next to Akkermansia and Faecalibacterium and the orange boxes next to Collinsella and Bilophila; then press the 'Update Map' button. Now, as they used to say, through the magic of television, we see the main screen come to life (Figure 2).
The main Radiance results screen depicts the interaction network involved in the regulation of the four genera we specified and submitted. As with tradition, arrow-tipped edges indicate stimulation/enhancement; and T-bar tipped edges indicate inhibition. Agents that directly impact the selected genera link to its main node. For example, Radiance tells us that Faecalibacterium can be enhanced with arabinoglactan, whilst Collinsella can be inhibited by beta-sitosterol. Useful information in its own right, but we can add more to the mix: network relationships. Because we have data on interacting genera, we can also develop recommendations for agents that enhance genera exerting similar desired secondary effects on our selected microbe targets, a gambit termed The Indirect Approach and summarized by the strategist B.H. Liddell Hart as "The longest way round is often the shortest way home."
For example, Collinsella can be indirectly inhibited by fostering Blautia with type III resistant starch and Bifidobactrium by adding Jerusalem artichoke to the diet. We could possibly enhance Akkermansia by increasing opportunities for Oscillospora, but since this genus tends to inhibit Faecalibacterium we'd probably not want to do that.
The default results frame depicts the relational data as a directly acyclical graph (DAG). You can also view the therapy options as tabular data by ticking 'As List' for the DEPICT option, then pressing the 'Update Map' button one more time. Radiance then updates the screen (see Figure 3).
Looks like this exercise in eubiosis engineering might respond positively to some well-known agents and protocols.
Well, there you have it, my second TL column. I hope it proves helpful. Feel free play with the software. You can't break anything! Email me (firstname.lastname@example.org) with comments, questions, bug reports, and suggestions.
As previously mentioned, next time we'll investigate how to use a common algorithm for spam detection (Naive Bayes), along with NCBI Medical Subject Headings (MeSH) symptom data to develop a probabilistic tool (Candidate, an AI-powered differential diagnosis (DDx) engine).
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Peter D'Adamo is a distinguished professor of clinical medicine at the University of Bridgeport School of Naturopathic Medicine. His New York Times bestselling books have sold over 8 million copies and have been translated into over 75 languages. He is the developer of the acclaimed Opus23 genomic software suite and a variety of other generative apps that can be explored at www.datapunk.net. In his spare time, he brings old VW Beetles back to life at his garage on www.kdf20.com