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: Neurological-Vision: photophobia (Light Sensitivity)_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) 0.691  ๐Ÿ“
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.661
๐Ÿ•ฎ  amoxicillin (antibiotic)s[CFS] 0.636
๐Ÿ•ฎ  neomycin (antibiotic)s[CFS] 0.633
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.626
๐Ÿ•ฎ  risperidone,(prescription) 0.623
๐Ÿ•ฎ  gentamicin (antibiotic)s 0.616
๐Ÿ•ฎ  naproxen,(prescription) 0.609
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.607  ๐Ÿ“
๐Ÿ•ฎ  reboxetine mesylate,(prescription) 0.583
๐Ÿ•ฎ  itraconazole,(prescription) 0.574
๐Ÿ•ฎ  sulfamethoxazole (antibiotic) 0.574
๐Ÿ•ฎ  ibuprofen 0.568
๐Ÿ•ฎ  spectinomycin dihydrochloride (antibiotic) 0.568
๐Ÿ•ฎ  carbamazepine,(prescription) 0.565
๐Ÿ•ฎ  streptomycin (antibiotic)s 0.555
๐Ÿ•ฎ  fenbendazole,(prescription) 0.554
๐Ÿ•ฎ  dopamine (prescription) 0.553
๐Ÿ•ฎ  atorvastatin (prescription) 0.553  ๐Ÿ“
Caffeine 0.55
Vitamin B9,folic acid 0.546  ๐Ÿ“
๐Ÿ•ฎ  furosemide,(prescription) 0.546
๐Ÿ•ฎ  procyclidine hydrochloride,(prescription) 0.546
3-alpha-hydroxy-5-beta-androstan-17-one,(prescription) 0.546
zimelidine dihydrochloride monohydrate,(prescription) 0.546
๐Ÿ•ฎ  darifenacin hydrobromide,(prescription) 0.546
nafronyl oxalate,(prescription) 0.546
๐Ÿ•ฎ  diphenhydramine hydrochloride,(prescription) 0.546
pipenzolate bromide,(prescription) 0.546
๐Ÿ•ฎ  quinidine hydrochloride monohydrate,(prescription) 0.546
๐Ÿ•ฎ  lamotrigine,(prescription) 0.546
๐Ÿ•ฎ  modafinil,(prescription) 0.546
๐Ÿ•ฎ  fosinopril,(prescription) 0.546
๐Ÿ•ฎ  cyclopentolate hydrochloride,(prescription) 0.546
panthenol (d),(prescription) 0.546
metaproterenol sulfate; orciprenaline sulfate,(prescription) 0.546
eserine hemisulfate salt,(prescription) 0.546
remoxipride hydrochloride,(prescription) 0.546
๐Ÿ•ฎ  cyproterone acetate,(prescription) 0.546
๐Ÿ•ฎ  ifosfamide,(prescription) 0.546
quipazine dimaleate salt non-drug 0.546
๐Ÿ•ฎ  busulfan,(prescription) 0.546
๐Ÿ•ฎ  pravastatin,(prescription) 0.546
tranexamic acid,(prescription) 0.546
๐Ÿ•ฎ  thalidomide,(prescription) 0.546
๐Ÿ•ฎ  triamterene,(prescription) 0.546
๐Ÿ•ฎ  benazepril hcl,(prescription) 0.546
๐Ÿ•ฎ  norgestimate,(prescription) 0.546
๐Ÿ•ฎ  Racetams 0.546  ๐Ÿ“
pirenperone non-drug 0.546
bucladesine sodium salt,(prescription) 0.546
picrotoxinin non-drug 0.546
tracazolate hydrochloride non-drug 0.546
๐Ÿ•ฎ  granisetron,(prescription) 0.546
๐Ÿ•ฎ  halcinonide,(prescription) 0.546
๐Ÿ•ฎ  phenoxybenzamine hydrochloride,(prescription) 0.546
๐Ÿ•ฎ  timolol maleate salt,(prescription) 0.546
aminopurine; 6-benzyl non-drug 0.546
oxybenzone non-drug 0.546
๐Ÿ•ฎ  lynestrenol,(prescription) 0.546

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  inulin (prebiotic) 1
arabinogalactan (prebiotic) 0.882
proton-pump inhibitors (prescription) 0.784
๐Ÿ•ฎ  fructo-oligosaccharides (prebiotic) 0.77
Slippery Elm 0.733
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.719
๐Ÿ•ฎ  lactulose 0.698
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.622
๐Ÿ•ฎ  resveratrol (grape seed/polyphenols/red wine) 0.576
raffinose(sugar beet) 0.565
apple 0.538
red wine 0.534
resistant starch 0.533
๐Ÿ•ฎ  berberine 0.499
wheat bran 0.493
๐Ÿ•ฎ  Burdock Root 0.471
๐Ÿ•ฎ  Pulses 0.459
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.442
bacillus subtilis (probiotics) 0.437
mediterranean diet 0.428
๐Ÿ•ฎ  saccharomyces boulardii (probiotics) 0.41
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.405
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.37
fasting 0.339
fat 0.337
pea (fiber, protein) 0.331
๐Ÿ•ฎ  pectin 0.33
almonds/ almond skins 0.324
macrolide ((antibiotic)s) 0.318
soy 0.316
barley,oat 0.311
xylan (prebiotic) 0.308
Conjugated Linoleic Acid 0.29
Lactobacillus Johnsonii (probiotic) 0.288
non-starch polysaccharides 0.287
jerusalem artichoke (prebiotic) 0.285
๐Ÿ•ฎ  zinc 0.279
๐Ÿ•ฎ  gum arabic (prebiotic) 0.273
sesame cake/meal 0.273
vsl#3 (probiotics) 0.272
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.268
๐Ÿ•ฎ  Glucomannan 0.265
high sugar diet 0.263
ketogenic diet 0.259
schisandra chinensis(magnolia berry or five-flavor-fruit) 0.25
magnesium 0.25
blueberry 0.24
l-citrulline 0.232
๐Ÿ•ฎ  lactobacillus fermentum (probiotics) 0.227
resistant maltodextrin 0.224
barley 0.223
๐Ÿ•ฎ  bifidobacterium lactis bb12 (probiotics) 0.22
fish oil 0.218
high red meat 0.216
gallic acid (food additive) 0.211
๐Ÿ•ฎ  rifaximin (antibiotic)s 0.205
gynostemma pentaphyllum (Jiaogulan) 0.204
plantago asiatica l. 0.201
๐Ÿ•ฎ  lactobacillus plantarum,xylooligosaccharides,(prebiotic) (probiotics) 0.2
green-lipped mussel 0.199
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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