I have moved on to rework the existing code. The processing is done on a dedicated server (32GB of memory, SSD drives for SQL Server. A little over 15,700,000 combinations of taxon needs to be made. Each combination needs to get all data on these taxons that are concurrent in any samples.
I.e. All samples that have Taxon 123 and Taxon 432 being reported.
The computations are done using Parallel and Concurrent libraries. All indices have been tuned for this analysis. The SQL Server and the utility to calculate the associations are on the same server – so no latency or network impact.
I found that the CPU temperatures exceed the maximum recommended for the CPU chip.
2022-03-27 20:12:08 Bacteria2Bacteria - 15,717,260 Items to Inspect
2022-03-29 22:48:34 Bacteria2Bacteria - 15,717,260 Items Inspected
2022-03-29 22:48:47 805,770 Items found
This analysis likely qualifies for the “big data” label. So why is it worth it? The answer is simple, for some bacteria we have no information on what increases or decreases it. If we know which bacteria is associated with the bacteria growth or reduction, then we can synthesize modifiers of these bacteria that we lack information on.
This has not been implemented in suggestions (and will likely be available at the nerd level when it is).
This year I have been focusing on a deep review of the code to improve accuracy and to address a variety of issues. The first item was redoing all of the KEGG Derived data (deriving compounds and enzymes at the species level instead of random strains). See KEGG Data being updated
The second item was cleaning up percentile computations on samples for:
Compound Produced (KEGG)
Compound Consumed (KEGG)
Net Compound (Produced – Consumed) (KEGG)
Medical Conditions (US National Library of Medicine)
Combined with this was also implementing Display Levels across menu. See Display Levels.
Existing Menu Items
New Menu Items
Display Level: Public
Display Level: Beginner
Display Level: Intermediate
Display Level: Advance
In the earlier version, outliers and full data was on two separate pages. These has been combined into a single page with more options.
Are your abnormal?
Calculations are done for you to indicate the level where values may be out of range by random chance. This is illustrated below.
I am hoping to have testing completed by the end of March and will then deploy
After login, change display Level (top left corner) to a higher level, you will see a new menu item appear with several new pages. This post focuses on the probiotic only.
Each page follows the same pattern. Compound listed on left, estimate of number of units produces by cell and alternative names. The Compound or Enzyme is link to the KEGG page providing more (usually very technical) information.
You can search by just typing the name in the search box. Some examples:
Fast identification of Probiotics for specific purpose
This page shows the compound with links to lists of probiotics. On the far right is the ID from the Organic Acts Tests (OATS – where a match could be identified)
An example of the linked to KEGG page is shown below. This page can be a good starting point for a long and steep learning curve.
Compare Probiotics Pages
These pages allows you to select two different probiotics and see what each produces.
This provides information that bridges the gaps in published research. If you know what you are trying to increase or decrease, this should provide guidance for you to discuss with your medical professional.
Tonight I implemented some downloads of data as Comma-Delimited files which may typically just be double clicked and open in Excel. This information is intended for researchers who wish to develop and test their own models from the data available. If you have to ask what these are, you are a non-nerd. See KEGG for support, not me.
Note that the files download have “Trade Secrets” and (C) 2002 in the name indicating that further distribution of this data is not permitted without written consent. By accessing the data you consent to those restrictions and acknowledge the nature of the information received.
As some of you are aware, I have spent the last few months refactoring how I handled data from KEGG: Kyoto Encyclopedia of Genes and Genomes. This weekend, I just finished pushing the data (over 8 millions rows of data) to the web site.
The computation is based on for each cell Sum(Sum(enzymes x compound produced by enzymes) over species), and the same number of cells of each species.
Nota Bene: There is a lot of rewiring from old tables to new tables that is in process. Some site pages may break.
A reader asked for my opinion on this. This is one of those topics where emotions often run hot and reason can be forgotten. I usually avoid these topics — I hate flame wars.
All of these passion topics, tend to have the following critical factors:
If those that advocate also sell the product, there is a clear conflict of interest. I will usually assume that their primary motivation is profit that is clothed in the appearance of wanting to help.
If they do not sell, but often use it, then we have the nasty issue of rose color glasses, selected data picking of their patients. They may have a vested interest in wanting to be right or a pioneer. They usually ignore those that have adverse results (often those people do not return to the people treating — hence they do not see these adverse results or discount them to non-compliance to the treatment plan (blame the patient syndrome).
Last thing is desperation, especially when standard of medical care fails — people are willing to try anything, regardless of the risk and often very low success (which could have happen at random).
These risks applies to most items where feelings run high.
First item, is that there is risk: “Soil-transmitted helminth infections represent a large burden with over a quarter of the world’s population at risk. Low cure rates are observed with standard of care (albendazole)” . Hence, viable (living) helminthiases should be avoid. Killed ones (for their chemicals) would be preferred. If things go bad, you are looking at low cure rate!
Helminth infection is included in my microbiome modifiers with 130+ bacteria impacted, see this page (I also include Round-Up! To include it in your suggestions, pick “Prescription – Other“. Remember NONE of the modifier suggestions should be done without medical review).
Please note also that if the treatment including killing them afterwards, that treatment alone may be responsible for positive effects
“There was evidence of treatment-specific effects among the selected studies, such as findings of treatment-associated taxa, including Sphingobacteriaceae and Flavobacteriaceae (26); increased and decreased Actinobacteria and Bacteroidetes, respectively, after placebo comparison (18); mebendazole treatment-induced changes in the diversity and abundance of Collinsella and Blautia (27);”
The reader referred me to Lindsey Wells, a naturopath, page on Helminth Therapy. The Hygiene Hypothesis of Autoimmunity is cited which I have touched upon in the past 2015, 2018. To me, many advocates of this hypothesis both over simplify and commercialize it. If you wish to take this hypothesis seriously, then there is only one treatments: live on an organic farm, with a lot of different animals — if your boots are not covered in manure, every day — you are not taking the hypothesis seriously!
As I stated at the start, this is among the worst form of study because it is prone to the placebo effect plus discontinuation of patients that are non-responders or who have adverse results. They do mention “1% of paediatric patients experienced severe gastrointestinal pains”. No objective measures (labs, etc) were cited. IMHO, a purely subjective report. Note that the journal that it was published in was Journal of Helminthology (I wonder if there is a bias with those doing peer review?)
“Thus, it should come as no surprise that eradicating helminths can result in expression of diseases influenced by these pathways. There are now many animal models representing a diverse range of diseases for which helminths either prevent and/or reverse ongoing pathology. “
“I hypothesized that a treatment with Trichuris suis soluble products represents a feasible holistic treatment for autism, and the key for the development of novel treatments. Preclinical studies are required to test this hypothesis.”
Bottom line: there are no clinical studies supporting it use for autism, it is all theoretical. Microbiome Prescription does include it in the options of gut modifiers — so you can objectively see if it is a good fit for an autistic child’s microbiome.
A Critical Criteria: If something has been proposed for 5+ years and fail to produce a positive clinical study then assume there have been several studies done with no positive results.
To me, it is not a rational choice — significant risk of known demonstrated adverse issues with no significant demonstrated positive impact. Odds are that going camping for 2 months in the woods will have a greater positive impact, or better still, work on an organic farm tending chickens, pigs and shoveling manure! Getting involved with 4H may be a good thing in many ways!