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: Inflammation of skin, eyes or joints_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] 0.488
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.415  ๐Ÿ“
๐Ÿ•ฎ  spectinomycin dihydrochloride (antibiotic) 0.395
๐Ÿ•ฎ  naproxen,(prescription) 0.392
๐Ÿ•ฎ  ibuprofen 0.384
๐Ÿ•ฎ  streptomycin (antibiotic)s 0.345
๐Ÿ•ฎ  carbamazepine,(prescription) 0.332
vitamin B3,niacin 0.331  ๐Ÿ“
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.329
๐Ÿ•ฎ  reboxetine mesylate,(prescription) 0.328
๐Ÿ•ฎ  fenbendazole,(prescription) 0.328
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.323  ๐Ÿ“
๐Ÿ•ฎ  dopamine (prescription) 0.318
๐Ÿ•ฎ  sulfamethoxazole (antibiotic) 0.318
๐Ÿ•ฎ  itraconazole,(prescription) 0.316
๐Ÿ•ฎ  melatonin supplement 0.316  ๐Ÿ“
sulfamethazine sodium salt (antibiotic) 0.312
๐Ÿ•ฎ  homatropine hydrobromide (r;s),(prescription) 0.312
๐Ÿ•ฎ  nicergoline,(prescription) 0.312
2-chloropyrazine non-drug 0.312
๐Ÿ•ฎ  diloxanide furoate,(prescription) 0.312
๐Ÿ•ฎ  mitotane,(prescription) 0.312
gbr 12909 dihydrochloride,(prescription) 0.312
cortisol acetate,(prescription) 0.312
๐Ÿ•ฎ  benperidol,(prescription) 0.312
oxfendazol,(prescription) 0.312
๐Ÿ•ฎ  terbutaline hemisulfate,(prescription) 0.312
๐Ÿ•ฎ  propylthiouracil,(prescription) 0.312
๐Ÿ•ฎ  aceclidine hydrochloride,(prescription) 0.312
๐Ÿ•ฎ  hymecromone,(prescription) 0.312
๐Ÿ•ฎ  primidone,(prescription) 0.312
๐Ÿ•ฎ  azaperone,(prescription) 0.312
๐Ÿ•ฎ  mirtazapine,(prescription) 0.312
mefexamide hydrochloride,(prescription) 0.312
๐Ÿ•ฎ  proglumide,(prescription) 0.312
๐Ÿ•ฎ  levodopa,(prescription) 0.312
๐Ÿ•ฎ  ranolazine,(prescription) 0.312
diphenidol hydrochloride,(prescription) 0.312
tetrahydrozoline hydrochloride,(prescription) 0.312
๐Ÿ•ฎ  ketorolac tromethamine,(prescription) 0.312
clavulanate potassium salt (antibiotic) 0.312
๐Ÿ•ฎ  sulfapyridine (antibiotic) 0.312
dizocilpine maleate,(prescription) 0.312
mianserine hydrochloride,(prescription) 0.312
๐Ÿ•ฎ  sumatriptan succinate,(prescription) 0.312
๐Ÿ•ฎ  naphazoline hydrochloride,(prescription) 0.312
๐Ÿ•ฎ  formestane,(prescription) 0.312
๐Ÿ•ฎ  lofexidine,(prescription) 0.312
methylprednisolone; 6-alpha,(prescription) 0.312
๐Ÿ•ฎ  clopamide,(prescription) 0.312
๐Ÿ•ฎ  chloroquine diphosphate,(prescription)[CFS] 0.312
๐Ÿ•ฎ  valacyclovir hydrochloride,(prescription) 0.312
๐Ÿ•ฎ  piretanide,(prescription) 0.312
norethynodrel,(prescription) 0.312
๐Ÿ•ฎ  gabapentin,(prescription) 0.312
๐Ÿ•ฎ  nadide non-drug 0.312
๐Ÿ•ฎ  ropinirole hcl,(prescription) 0.312
๐Ÿ•ฎ  pergolide mesylate,(prescription) 0.312
๐Ÿ•ฎ  bisoprolol fumarate,(prescription) 0.312
๐Ÿ•ฎ  clebopride maleate,(prescription) 0.312

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  inulin (prebiotic) 1
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.726
๐Ÿ•ฎ  fructo-oligosaccharides (prebiotic) 0.721
arabinogalactan (prebiotic) 0.652
soy 0.609
๐Ÿ•ฎ  resveratrol (grape seed/polyphenols/red wine) 0.593
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.535
๐Ÿ•ฎ  lactulose 0.491
resistant starch 0.473
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.453
bacillus subtilis (probiotics) 0.443
wheat bran 0.424
raffinose(sugar beet) 0.422
proton-pump inhibitors (prescription) 0.402
๐Ÿ•ฎ  Burdock Root 0.382
almonds/ almond skins 0.365
apple 0.36
jerusalem artichoke (prebiotic) 0.359
sesame cake/meal 0.357
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.35
๐Ÿ•ฎ  Glucomannan 0.344
mediterranean diet 0.314
red wine 0.293
๐Ÿ•ฎ  gum arabic (prebiotic) 0.284
clostridium butyricum (probiotics),Miya,Miyarisan 0.274
ketogenic diet 0.262
Conjugated Linoleic Acid 0.258
Lactobacillus Johnsonii (probiotic) 0.257
barley,oat 0.255
whey 0.252
daesiho-tang 0.25
magnesium 0.245
๐Ÿ•ฎ  pectin 0.244
navy bean 0.243
blueberry 0.24
high fiber diet 0.238
๐Ÿ•ฎ  lactobacillus reuteri (probiotics) 0.237
๐Ÿ•ฎ  lactobacillus plantarum,xylooligosaccharides,(prebiotic) (probiotics) 0.235
๐Ÿ•ฎ  Pulses 0.234
pomegranate 0.231
barley 0.23
๐Ÿ•ฎ  rifaximin (antibiotic)s 0.229
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.227
๐Ÿ•ฎ  bifidobacterium lactis bb12 (probiotics) 0.21
green tea 0.207
pea (fiber, protein) 0.206
chondrus crispus,red sea weed 0.203
wheat 0.201
fat 0.193
fish oil 0.192
Slippery Elm 0.19
๐Ÿ•ฎ  noni 0.188
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.188
fasting 0.187
๐Ÿ•ฎ  zinc 0.186
l-proline 0.185
๐Ÿ•ฎ  Cacao 0.18
๐Ÿ•ฎ  lactobacillus paracasei (probiotics) 0.172
pediococcus acidilactic (probiotic) 0.17
plantago asiatica l. 0.165
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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