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: Chronic Sinusitis_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  acarbose,(prescription) 0.614
๐Ÿ•ฎ  norfloxacin (antibiotic)s 0.555
๐Ÿ•ฎ  metronidazole (antibiotic)s[CFS] 0.536
๐Ÿ•ฎ  sulfamethoxazole (antibiotic) 0.532
๐Ÿ•ฎ  tobramycin (antibiotic)s 0.532
๐Ÿ•ฎ  gentamicin (antibiotic)s 0.529
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.526  ๐Ÿ“
๐Ÿ•ฎ  ofloxacin (antibiotic)s 0.525
๐Ÿ•ฎ  atorvastatin (prescription) 0.51  ๐Ÿ“
๐Ÿ•ฎ  risperidone,(prescription) 0.503
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.498  ๐Ÿ“
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.496  ๐Ÿ“
๐Ÿ•ฎ  azithromycin,(antibiotic)s[CFS] 0.495  ๐Ÿ“
๐Ÿ•ฎ  amoxicillin (antibiotic)s[CFS] 0.494
๐Ÿ•ฎ  cefoxitin (antibiotic)s 0.491
Caffeine 0.469
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.462
prednisone,(prescription) 0.455
๐Ÿ•ฎ  Vitamin B-12 0.446  ๐Ÿ“
๐Ÿ•ฎ  dihydroergotamine tartrate,(prescription) 0.428
๐Ÿ•ฎ  dihydrostreptomycin sulfate (antibiotic) 0.428
๐Ÿ•ฎ  dilazep dihydrochloride,(prescription) 0.428
๐Ÿ•ฎ  diloxanide furoate,(prescription) 0.428
๐Ÿ•ฎ  diltiazem hydrochloride,(prescription) 0.428
dimaprit dihydrochloride non-drug 0.428
n-acetyl-dl-homocysteine thiolactone,(prescription) 0.428
n-acetyl-l-leucine,(prescription) 0.428
๐Ÿ•ฎ  nadide non-drug 0.428
dicyclomine hydrochloride,(prescription) 0.428
๐Ÿ•ฎ  didanosine,(prescription) 0.428
๐Ÿ•ฎ  desloratadine,(prescription) 0.428
๐Ÿ•ฎ  dexamethasone acetate,(prescription) 0.428
dexfenfluramine hydrochloride,(prescription) 0.428
๐Ÿ•ฎ  diethylcarbamazine citrate,(prescription) 0.428
๐Ÿ•ฎ  diflorasone diacetate,(prescription) 0.428
๐Ÿ•ฎ  diflunisal,(prescription) 0.428
digitoxigenin,(prescription) 0.428
digoxigenin non-drug 0.428
๐Ÿ•ฎ  digoxin,(prescription) 0.428
๐Ÿ•ฎ  deflazacort,(prescription) 0.428
dehydrocholic acid non-drug 0.428
dehydroisoandosterone 3-acetate,(prescription) 0.428
demecarium bromide,(prescription) 0.428
denatonium benzoate non-drug 0.428
deoxycorticosterone,(prescription) 0.428
deptropine citrate,(prescription) 0.428
๐Ÿ•ฎ  diazoxide,(prescription) 0.428
dibenzepine hydrochloride,(prescription) 0.428
dibucaine,(prescription) 0.428
dichlorphenamide,(prescription) 0.428
๐Ÿ•ฎ  desipramine hydrochloride,(prescription) 0.428
๐Ÿ•ฎ  diclofenac sodium,(prescription) 0.428
nafronyl oxalate,(prescription) 0.428
๐Ÿ•ฎ  dimenhydrinate,(prescription) 0.428
dimethadione,(prescription) 0.428
dimethisoquin hydrochloride,(prescription) 0.428
๐Ÿ•ฎ  dinoprost trometamol,(prescription) 0.428
diosmin,(polyphenol) 0.428  ๐Ÿ“
dioxybenzone non-drug 0.428
diperodon hydrochloride non-drug 0.428

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  berberine 1
๐Ÿ•ฎ  inulin (prebiotic) 0.967
cranberry bean flour 0.655
Slippery Elm 0.642
red wine 0.63
arabinogalactan (prebiotic) 0.626
fasting 0.526
ketogenic diet 0.504
๐Ÿ•ฎ  metformin (prescription) 0.499
resistant starch 0.479
triphala 0.474
stevia 0.423
๐Ÿ•ฎ  resveratrol (grape seed/polyphenols/red wine) 0.422
๐Ÿ•ฎ  vitamin d 0.418
low-fat diets 0.414
saccharin 0.38
resistant maltodextrin 0.378
๐Ÿ•ฎ  lactobacillus fermentum (probiotics) 0.367
๐Ÿ•ฎ  Pulses 0.349
pomegranate 0.348
๐Ÿ•ฎ  fructo-oligosaccharides (prebiotic) 0.346
๐Ÿ•ฎ  Akkermansia muciniphila (probiotic) 0.335
bacillus licheniformis,(probiotics) 0.334
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.334
barley 0.326
wheat bran 0.326
carboxymethyl cellulose (prebiotic) 0.316
๐Ÿ•ฎ  grapes 0.311
๐Ÿ•ฎ  black raspberries 0.31
๐Ÿ•ฎ  saccharomyces boulardii (probiotics) 0.296
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.288
๐Ÿ•ฎ  Astragalus polysaccharide 0.288
xylan (prebiotic) 0.288
grape seed extract 0.287
gallic acid (food additive) 0.285
๐Ÿ•ฎ  enterococcus faecium (probiotic) 0.275
apple 0.273
l-citrulline 0.268
non-starch polysaccharides 0.267
fibre-rich macrobiotic ma-pi 2 diet 0.264
macrolide ((antibiotic)s) 0.263
high red meat 0.261
schisandra chinensis(magnolia berry or five-flavor-fruit) 0.258
๐Ÿ•ฎ  pectin 0.256
bile (acid/salts) 0.255
bacillus coagulans (probiotics) 0.24
๐Ÿ•ฎ  lactobacillus rhamnosus gg (probiotics) 0.236
animal-based diet 0.23
๐Ÿ•ฎ  lactobacillus rhamnosus (probiotics) 0.224
๐Ÿ•ฎ  bifidobacterium lactis bb12 (probiotics) 0.22
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.211
oligofructose-enriched inulin (prebiotic) 0.21
polydextrose 0.205
๐Ÿ•ฎ  Bofutsushosan 0.201
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.195
sodium butyrate 0.189
levan 0.187
Conjugated Linoleic Acid 0.185
rhubarb 0.183
blueberry 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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