http://microbiomeprescription.com/Kyber/Bioscreen

A UK reader forwarded their results for analysis. I modified my website to input data from this report (like I did for KyberKompakt) and do analysis using the same database.

The Report

The report is shown below

The Data Entry

To keep life simple, the entry uses the same check marks and arrows as before. So the above report is entered as shown below. There were some minor spelling difference between plural and single versions of names (Bifidobacterium vs Bifidobacteria), but the sequence was maintained for ease of entry.

http://microbiomeprescription.com/Kyber/Verisana

The results can be tuned as before.

The Weight is calculated as:   Sum of bacteria impacted by this.

• Red Wine:
  • Three different “2” items were positively helped… 6
  • One “2” item was negatively helped … 2
  • Bottom Line weight is a 6-2 = 4 (more likely to help — but monitor carefully, we do not know how much it impacts each item.

I did a  KyberKompact analysis a while back, and just put the same same thru my new website to do analysis.

The page is at: http://microbiomeprescription.com/Kyber/Upload/

The process is simple, match the up and down errors for the items on the reports.

Click explore and the current recommendations appear (based on published studies) as shown below.

• You can also take your ubiome results and match up with the selection shown above and use it that way until I get the uBiome version fully tested.
• Clicking on include/parent will increase the recommendations to include the parent (i.e. “family”) or children (“strains”) recommendations
  • As is 142 items appeared, with parents and children the list increased to 162 items.

There are some similar to items (i.e. red wine, resveratrol , red wine polyphenol).

The full list is shown below:

Bottom Line

The number of items above will grow as more and more studies are entered into the database.

This is an education post to facilitate discussing this approach with your medical professionals. It is not medical advice for the treatment of CFS. Always consult with your medical professional before doing any  changes of diet, supplements or activity. Some items cites may interfere with prescription medicines.

A reader sent me over two uBiomes taken 3 months apart and was confused by the results. Fortunately, I could upload her data and do some quick analysis (which will eventually be available as a web page).

Phylum Level Is Improving

The numbers below are the counts. It they are getting closer to normal, it is improving. If further away then a loss.

We see a rare phylum (Euryarchaeota) was one of the two losses, so we really had 4 gains to 1 loss.

Class Changes

The dominant change at the class level are improvement if we take by raw counts. Both Clostridia and Bacteroidia (the two biggest classes have improved). The third largest class Erysipelotrichia has had a loss.

For this overgrowth, we have some suggestions.

NOTE: Walnut is reported at two places. We have contrary results from studies 😦

Order Changes

We see gain and loss here too.

The worst loss was for Rhizobiales, with the following suggestions coming from the website

It is now clear that walnuts should be avoided.

Bottom Line

One concern that I have asked is about undergrowth. Working at the genus level gets very complex here. Working at higher levels like phylum, class and order is simpler.

With this new comparison page proposed, you get better clarity of the numbers and can focus on the highest count targets.

This is an education post to facilitate discussing this approach with your medical professionals. It is not medical advice for the treatment of any condition. Always consult with your medical professional before doing any  changes of diet, supplements or activity. Some items cites may interfere with prescription medicines.