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: Neurocognitive: Brain Fog_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  gentamicin (antibiotic)s 0.983
๐Ÿ•ฎ  piperacillin-tazobactam (antibiotic)s 0.895
๐Ÿ•ฎ  imipenem (antibiotic)s 0.82
๐Ÿ•ฎ  tobramycin (antibiotic)s 0.793
๐Ÿ•ฎ  ciprofloxacin (antibiotic)s[CFS] 0.725
๐Ÿ•ฎ  thyme (thymol, thyme oil) 0.686
๐Ÿ•ฎ  vancomycin (antibiotic)[CFS] 0.683
๐Ÿ•ฎ  amikacin (antibiotic)s 0.606
๐Ÿ•ฎ  amoxicillin (antibiotic)s[CFS] 0.593
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.567  ๐Ÿ“
๐Ÿ•ฎ  ofloxacin (antibiotic)s 0.565
Caffeine 0.558
vitamin B3,niacin 0.549  ๐Ÿ“
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.535  ๐Ÿ“
๐Ÿ•ฎ  atorvastatin (prescription) 0.527  ๐Ÿ“
๐Ÿ•ฎ  neomycin (antibiotic)s[CFS] 0.518
๐Ÿ•ฎ  benzylpenicillin sodium (antibiotic) 0.51
๐Ÿ•ฎ  meropenem (antibiotic)s 0.509
๐Ÿ•ฎ  norfloxacin (antibiotic)s 0.496
๐Ÿ•ฎ  itraconazole,(prescription) 0.48
๐Ÿ•ฎ  sulfamethoxazole (antibiotic) 0.479
๐Ÿ•ฎ  dopamine (prescription) 0.478
๐Ÿ•ฎ  risperidone,(prescription) 0.471
๐Ÿ•ฎ  acarbose,(prescription) 0.458
๐Ÿ•ฎ  Vitamin B-12 0.452  ๐Ÿ“
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.452
๐Ÿ•ฎ  alverine citrate salt,(prescription) 0.452
๐Ÿ•ฎ  metronidazole (antibiotic)s[CFS] 0.451
๐Ÿ•ฎ  ampicillin (antibiotic)s[CFS] 0.444
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.44  ๐Ÿ“
๐Ÿ•ฎ  spectinomycin dihydrochloride (antibiotic) 0.437
peppermint (spice, oil) 0.433
๐Ÿ•ฎ  cefaclor hydrate (antibiotic) 0.43
alendronate sodium,(prescription) 0.422
๐Ÿ•ฎ  disopyramide,(prescription) 0.422
ethoxyquin non-drug 0.422
calcipotriene,(prescription) 0.422
๐Ÿ•ฎ  nisoldipine,(prescription) 0.422
mephentermine hemisulfate,(prescription) 0.422
parthenolide non-drug 0.422
๐Ÿ•ฎ  fenbufen,(prescription) 0.422
isoxicam,(prescription) 0.422
bephenium hydroxynaphthoate,(prescription) 0.422
๐Ÿ•ฎ  nortriptyline hydrochloride,(prescription) 0.422
๐Ÿ•ฎ  ifenprodil tartrate,(prescription) 0.422
bretylium tosylate,(prescription) 0.422
๐Ÿ•ฎ  sulfamerazine (antibiotic) 0.422
๐Ÿ•ฎ  flunixin meglumine,(prescription) 0.422
oxantel pamoate,(prescription) 0.422
๐Ÿ•ฎ  carbarsone non-drug 0.422
๐Ÿ•ฎ  acetazolamide,(prescription) 0.422
๐Ÿ•ฎ  alclometasone dipropionate,(prescription) 0.422
Arbutin (polyphenol) 0.422  ๐Ÿ“
๐Ÿ•ฎ  benzonatate,(prescription) 0.422
isosorbide mononitrate,(prescription) 0.422
๐Ÿ•ฎ  amcinonide,(prescription) 0.422
๐Ÿ•ฎ  triamterene,(prescription) 0.422
๐Ÿ•ฎ  topiramate,(prescription) 0.422
๐Ÿ•ฎ  chlorpropamide,(prescription) 0.422
deoxycorticosterone,(prescription) 0.422

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
arabinogalactan (prebiotic) 1
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.988
๐Ÿ•ฎ  inulin (prebiotic) 0.932
resistant starch 0.762
red wine 0.733
Slippery Elm 0.714
๐Ÿ•ฎ  berberine 0.708
ketogenic diet 0.613
mediterranean diet 0.588
๐Ÿ•ฎ  Pulses 0.575
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.543
wheat bran 0.515
xylan (prebiotic) 0.514
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.49
๐Ÿ•ฎ  fructo-oligosaccharides (prebiotic) 0.471
proton-pump inhibitors (prescription) 0.445
navy bean 0.438
l-citrulline 0.401
resistant maltodextrin 0.397
non-starch polysaccharides 0.392
saccharin 0.388
๐Ÿ•ฎ  pectin 0.357
๐Ÿ•ฎ  iron 0.341
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.337
๐Ÿ•ฎ  lactulose 0.331
blueberry 0.315
๐Ÿ•ฎ  lactobacillus rhamnosus (probiotics) 0.311
apple 0.309
triphala 0.307
fat 0.307
cranberry bean flour 0.298
schisandra chinensis(magnolia berry or five-flavor-fruit) 0.297
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.283
stevia 0.28
ku ding cha tea 0.273
๐Ÿ•ฎ  Cacao 0.262
soy 0.257
pea (fiber, protein) 0.242
plantago asiatica l. 0.234
chondrus crispus,red sea weed 0.225
๐Ÿ•ฎ  epinephrine 0.225
gynostemma pentaphyllum (Jiaogulan) 0.22
wheat 0.218
๐Ÿ•ฎ  saccharomyces boulardii (probiotics) 0.217
high red meat 0.214
vegetarians 0.213
fasting 0.21
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.21
Alpha-Ketoglutarate 0.203
๐Ÿ•ฎ  bifidobacterium lactis bb12 (probiotics) 0.197
barley,oat 0.196
Conjugated Linoleic Acid 0.195
partially hydrolysed guar gum,fructo-oligosaccharides (prebiotic) 0.193
l-proline 0.192
bacillus subtilis natto (probiotics) 0.19
grape seed extract 0.19
levan 0.183
๐Ÿ•ฎ  lactobacillus rhamnosus gg (probiotics) 0.183
daesiho-tang 0.181
high carbohydrate diet 0.181
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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