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: Abdominal Pain_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  neomycin (antibiotic)s[CFS] 0.402
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.332  ๐Ÿ“
๐Ÿ•ฎ  spectinomycin dihydrochloride (antibiotic) 0.302
๐Ÿ•ฎ  high-fat diets 0.294
๐Ÿ•ฎ  chloramphenicol (antibiotic)s 0.254
๐Ÿ•ฎ  nitrofurantoin (antibiotic) 0.253
๐Ÿ•ฎ  naproxen,(prescription) 0.25
๐Ÿ•ฎ  rifampicin (antibiotic)s 0.237
๐Ÿ•ฎ  ibuprofen 0.233
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.232
๐Ÿ•ฎ  reboxetine mesylate,(prescription) 0.23
๐Ÿ•ฎ  cefaclor hydrate (antibiotic) 0.23
๐Ÿ•ฎ  fenbendazole,(prescription) 0.227
๐Ÿ•ฎ  carbamazepine,(prescription) 0.225
๐Ÿ•ฎ  estradiol valerate,(prescription) 0.217
๐Ÿ•ฎ  guanabenz acetate,(prescription) 0.215
๐Ÿ•ฎ  famciclovir,(prescription) 0.215
๐Ÿ•ฎ  ketoprofen,(prescription) 0.215
pinacidil,(prescription) 0.215
๐Ÿ•ฎ  colchicine,(prescription) 0.215
estradiol-17 beta,(prescription) 0.215
๐Ÿ•ฎ  gliquidone,(prescription) 0.215
๐Ÿ•ฎ  labetalol hydrochloride,(prescription) 0.215
digitoxigenin,(prescription) 0.215
๐Ÿ•ฎ  fenoprofen calcium salt dihydrate,(prescription) 0.215
clofibric acid non-drug 0.215
pronethalol hydrochloride non-drug 0.215
๐Ÿ•ฎ  tribenoside,(prescription) 0.215
๐Ÿ•ฎ  terconazole,(prescription) 0.215
๐Ÿ•ฎ  irsogladine maleate,(prescription) 0.215
lidoflazine,(prescription) 0.215
๐Ÿ•ฎ  venlafaxine,(prescription) 0.215
canrenone,(prescription) 0.215
๐Ÿ•ฎ  fomepizole,(prescription) 0.215
๐Ÿ•ฎ  nizatidine,(prescription) 0.215
๐Ÿ•ฎ  fenofibrate,(prescription) 0.215
๐Ÿ•ฎ  metoprolol-(+;-) (+)-tartrate salt,(prescription) 0.215
๐Ÿ•ฎ  argatroban,(prescription) 0.215
๐Ÿ•ฎ  dimenhydrinate,(prescription) 0.215
๐Ÿ•ฎ  lisinopril,(prescription) 0.215
pentetic acid non-drug 0.215
epitiostanol,(prescription) 0.215
๐Ÿ•ฎ  vorinostat,(prescription) 0.215
๐Ÿ•ฎ  atropine sulfate monohydrate,(prescription) 0.215
๐Ÿ•ฎ  adenosine 5`-monophosphate monohydrate non-drug 0.215
๐Ÿ•ฎ  budesonide,(prescription) 0.215
๐Ÿ•ฎ  flunisolide,(prescription) 0.215
(s)-(-)-atenolol,(prescription) 0.215
imidurea non-drug 0.215
๐Ÿ•ฎ  hydralazine hydrochloride,(prescription) 0.215
๐Ÿ•ฎ  domperidone,(prescription) 0.215
๐Ÿ•ฎ  glipizide,(prescription) 0.215
๐Ÿ•ฎ  benzocaine,(prescription) 0.215
denatonium benzoate non-drug 0.215
nitrocaramiphen hydrochloride non-drug 0.215
๐Ÿ•ฎ  levocabastine hydrochloride,(prescription) 0.215
๐Ÿ•ฎ  repaglinide,(prescription) 0.215
clocortolone pivalate,(prescription) 0.215
๐Ÿ•ฎ  sildenafil,(prescription) 0.215
๐Ÿ•ฎ  oxybutynin chloride,(prescription) 0.215

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  inulin (prebiotic) 1
๐Ÿ•ฎ  fructo-oligosaccharides (prebiotic) 0.884
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.858
soy 0.723
๐Ÿ•ฎ  resveratrol (grape seed/polyphenols/red wine) 0.645
arabinogalactan (prebiotic) 0.639
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.581
resistant starch 0.535
raffinose(sugar beet) 0.532
๐Ÿ•ฎ  lactulose 0.511
bacillus subtilis (probiotics) 0.506
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.504
jerusalem artichoke (prebiotic) 0.447
wheat bran 0.437
๐Ÿ•ฎ  Glucomannan 0.434
๐Ÿ•ฎ  Burdock Root 0.398
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.388
clostridium butyricum (probiotics),Miya,Miyarisan 0.386
almonds/ almond skins 0.373
sesame cake/meal 0.366
apple 0.355
๐Ÿ•ฎ  gum arabic (prebiotic) 0.336
Conjugated Linoleic Acid 0.328
green tea 0.326
๐Ÿ•ฎ  lactobacillus paracasei (probiotics) 0.31
whey 0.305
barley,oat 0.301
ketogenic diet 0.299
fish oil 0.298
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.294
๐Ÿ•ฎ  lactobacillus plantarum,xylooligosaccharides,(prebiotic) (probiotics) 0.287
blueberry 0.269
๐Ÿ•ฎ  zinc 0.264
pomegranate 0.264
mediterranean diet 0.259
red wine 0.258
๐Ÿ•ฎ  noni 0.257
high fiber diet 0.256
wheat 0.254
chondrus crispus,red sea weed 0.254
Lactobacillus Johnsonii (probiotic) 0.254
barley 0.253
proton-pump inhibitors (prescription) 0.252
๐Ÿ•ฎ  pectin 0.249
magnesium 0.247
daesiho-tang 0.247
๐Ÿ•ฎ  bifidobacterium lactis bb12 (probiotics) 0.236
๐Ÿ•ฎ  Cacao 0.231
๐Ÿ•ฎ  rifaximin (antibiotic)s 0.227
navy bean 0.214
fasting 0.204
pediococcus acidilactic (probiotic) 0.203
rosmarinus officinalis,rosemary 0.201
pea (fiber, protein) 0.198
quercetin 0.192
๐Ÿ•ฎ  lactobacillus reuteri (probiotics) 0.19
๐Ÿ•ฎ  enterococcus faecium (probiotic) 0.185
oats 0.185
oregano (origanum vulgare, oil) | 0.181
partially hydrolysed guar gum,fructo-oligosaccharides (prebiotic) 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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Use of data on this site is prohibited except under written license. There is no charge for individual personal use. Use for any commercial applications or research requires a written license.
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.
Inventions/Methodologies on this site are Patent Pending.

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