Why some suggestions may contradict

RECOMMENDED READING Caveats on using the contents of this page. ๐Ÿ‘จโ€โš•๏ธ

If you need help with this information, here is a list of consultants ๐Ÿ‘จโ€โš•๏ธ๐Ÿ‘ฉโ€โš•๏ธ that are available.

Suggestion Parameters

Sample:A Priori (from theoretical deduction)
Bacteria Selection:Outside of Range
Filter: From Special Studies V2: Immune Manifestations: hives_Drugs
Rank Used: All Ranks
Shifts Used:High and Low Levels
Citations Used:

How do we know if the suggestions are reasonable/valid?

๐Ÿฑ Food Menu Planner ๐Ÿฝ๏ธ ๐Ÿ“น How are suggestions determined


The following will shift items that are too high to lower values and values that are too low to higher values.
Items will feed or starve specific bacteria.

With antibiotics, if there is no significant response, there may be antibiotic resistance. Bacteria do share resistance genes between themselves. Consider moving on to a different one, ideally a different family.

The recommended process to obtain a persistent shift of the microbiome is:
 Generate 4 lists from the suggestions with nothing repeated on another list
  Emphasize one list each week
  After 8 weeks (2 cycles), retest the microbiome to obtains the next set of course corrections
This approach allows the microbiome to stablize towards normal.

To Add or Increase Intake

Modifier (Alt Names on Hover) Confidence ๐Ÿ“น
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.713  ๐Ÿ“
chitosan,(sugar) 0.704  ๐Ÿ“
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.681  ๐Ÿ“
Caffeine 0.665
๐Ÿ•ฎ  gentamicin (antibiotic)s 0.65
๐Ÿ•ฎ  acarbose,(prescription) 0.634
๐Ÿ•ฎ  risperidone,(prescription) 0.618
๐Ÿ•ฎ  neomycin (antibiotic)s[CFS] 0.603
Vitamin B9,folic acid 0.601  ๐Ÿ“
๐Ÿ•ฎ  atorvastatin (prescription) 0.593  ๐Ÿ“
๐Ÿ•ฎ  ibuprofen 0.573
๐Ÿ•ฎ  naproxen,(prescription) 0.573
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.573
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.572  ๐Ÿ“
๐Ÿ•ฎ  ofloxacin (antibiotic)s 0.567
๐Ÿ•ฎ  streptomycin (antibiotic)s 0.557
๐Ÿ•ฎ  succinylsulfathiazole (antibiotic) 0.557
๐Ÿ•ฎ  pivmecillinam hydrochloride (antibiotic) 0.557
๐Ÿ•ฎ  pramipexole,(prescription) 0.557
pramoxine hydrochloride,(prescription) 0.557
๐Ÿ•ฎ  pranlukast,(prescription) 0.557
๐Ÿ•ฎ  pranoprofen,(prescription) 0.557
๐Ÿ•ฎ  pravastatin,(prescription) 0.557
๐Ÿ•ฎ  sulindac,(prescription) 0.557
sulmazole non-drug 0.557
๐Ÿ•ฎ  thalidomide,(prescription) 0.557
Theobromine (in food) 0.557
๐Ÿ•ฎ  sulpiride,(prescription) 0.557
sulfabenzamide 0.557
๐Ÿ•ฎ  sulfacetamide sodic hydrate (antibiotic) 0.557
sulfachloropyridazine,(prescription) 0.557
๐Ÿ•ฎ  sulfadiazine (antibiotic) 0.557
๐Ÿ•ฎ  sulfadimethoxine (antibiotic) 0.557
sulfadoxine,(prescription) 0.557
๐Ÿ•ฎ  sulfaguanidine (antibiotic) 0.557
๐Ÿ•ฎ  sulfamerazine (antibiotic) 0.557
sulfameter (antibiotic) 0.557
sulfamethazine sodium salt (antibiotic) 0.557
๐Ÿ•ฎ  sulfamethizole (antibiotic) 0.557
๐Ÿ•ฎ  sulfasalazine,(prescription) 0.557
๐Ÿ•ฎ  sulfathiazole (antibiotic) 0.557
๐Ÿ•ฎ  sulfinpyrazone,(prescription) 0.557
๐Ÿ•ฎ  sulfisoxazole (antibiotic) 0.557
pargyline hydrochloride,(prescription) 0.557
๐Ÿ•ฎ  pentoxifylline,(prescription) 0.557
pentylenetetrazole,(prescription) 0.557
pepstatin a non-drug 0.557
๐Ÿ•ฎ  pergolide mesylate,(prescription) 0.557
๐Ÿ•ฎ  perindopril,(prescription) 0.557
๐Ÿ•ฎ  perphenazine,(prescription) 0.557
phenacetin,(prescription) 0.557
๐Ÿ•ฎ  phenylbutazone,(prescription) 0.557
๐Ÿ•ฎ  phenylpropanolamine hydrochloride,(prescription) 0.557
๐Ÿ•ฎ  phthalylsulfathiazole (antibiotic) 0.557
picotamide monohydrate,(prescription) 0.557
picrotoxinin non-drug 0.557
๐Ÿ•ฎ  piretanide,(prescription) 0.557
๐Ÿ•ฎ  piribedil hydrochloride,(prescription) 0.557
pirlindole mesylate,(prescription) 0.557
piromidic acid (antibiotic) 0.557

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
arabinogalactan (prebiotic) 1
๐Ÿ•ฎ  inulin (prebiotic) 0.983
resistant starch 0.84
red wine 0.771
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.747
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.684
saccharin 0.561
๐Ÿ•ฎ  berberine 0.544
resistant maltodextrin 0.498
๐Ÿ•ฎ  Pulses 0.449
๐Ÿ•ฎ  pectin 0.443
Slippery Elm 0.439
vegetarians 0.427
apple 0.414
refined wheat breads 0.402
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.396
xylan (prebiotic) 0.395
stevia 0.375
plantago asiatica l. 0.36
levan 0.343
non-starch polysaccharides 0.336
wheat bran 0.327
๐Ÿ•ฎ  Burdock Root 0.29
schisandra chinensis(magnolia berry or five-flavor-fruit) 0.282
gallic acid (food additive) 0.282
๐Ÿ•ฎ  cruciferous vegetables (broccoli cabbage) 0.273
pomegranate 0.268
๐Ÿ•ฎ  lactobacillus rhamnosus gg (probiotics) 0.266
l-citrulline 0.266
๐Ÿ•ฎ  glucose (sugar) 0.265
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.262
bacillus licheniformis,(probiotics) 0.262
dietary phytoestrogens (isoflavones) 0.256
l-proline 0.25
Psyllium (Plantago Ovata Husk) 0.246
๐Ÿ•ฎ  ß-glucan 0.245
barley 0.241
dietary fiber 0.235
genistein 0.235
low-fat diets 0.23
barley,oat 0.225
carboxymethyl cellulose (prebiotic) 0.225
animal-based diet 0.225
bile (acid/salts) 0.221
๐Ÿ•ฎ  lactobacillus acidophilus,cellobiose (probiotics) 0.219
bacillus,lactobacillus,streptococcus,saccharomyces probiotic 0.219
germinated barley food-stuff 0.219
๐Ÿ•ฎ  resveratrol (grape seed/polyphenols/red wine) 0.216
๐Ÿ•ฎ  black raspberries 0.212
green-lipped mussel 0.199
๐Ÿ•ฎ  zinc 0.198
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.197
saccharomyces boulardii (probiotics) 0.195
๐Ÿ•ฎ  lactobacillus fermentum (probiotics) 0.189
๐Ÿ•ฎ  iron 0.178
polygonatum kingianum(Orange Flower Solomon's Seal.) 0.173
pea (fiber, protein) 0.172
ku ding cha tea 0.171
hypocaloric hyperproteic diet 0.168
๐Ÿ•ฎ  vitamin d 0.168
NOTE: (Heparin, hyaluronan, or chondroitin sulfate) and Lactobacillus probiotics should not be taken concurrently.

All suggestions are computed solely on their predicted microbiome impact. Safety, side-effects etc must be evaluated by your medical professionals before starting. Some items suggests have significant risk of adverse consequences for some people.

Special thanks to David F Morrison and Geert Van Houcke for doing Quality Assurance. Special thanks to Oliver Luk, B.Sc. (Biology) from BiomeSight for spot checking the coding of data from the US National Library of Medicine

This is an Academic site. It generates theoretical models of what may benefit a specific microbiome results.

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Caveat emptor: Analysis and suggestions are based on modelling (and thus infererence) based on studies. The data sources are usually given for those that wish to consider alternative inferences. theories and models.

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