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: DePaul University Fatigue Questionnaire : Weight change_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  Vitamin B1,thiamine hydrochloride 0.761  ๐Ÿ“
๐Ÿ•ฎ  acarbose,(prescription) 0.753
๐Ÿ•ฎ  risperidone,(prescription) 0.752
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.716  ๐Ÿ“
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.706
๐Ÿ•ฎ  gentamicin (antibiotic)s 0.701
Caffeine 0.695
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.686  ๐Ÿ“
๐Ÿ•ฎ  amoxicillin (antibiotic)s[CFS] 0.664
๐Ÿ•ฎ  carbamazepine,(prescription) 0.661
๐Ÿ•ฎ  itraconazole,(prescription) 0.658
๐Ÿ•ฎ  sulfamethoxazole (antibiotic) 0.657
๐Ÿ•ฎ  neomycin (antibiotic)s[CFS] 0.641
๐Ÿ•ฎ  naproxen,(prescription) 0.631
๐Ÿ•ฎ  spectinomycin dihydrochloride (antibiotic) 0.631
๐Ÿ•ฎ  atorvastatin (prescription) 0.621  ๐Ÿ“
๐Ÿ•ฎ  tiabendazole,(prescription) 0.621
๐Ÿ•ฎ  carbachol,(prescription) 0.621
๐Ÿ•ฎ  sisomicin sulfate (antibiotic) 0.621
๐Ÿ•ฎ  papaverine hydrochloride,(prescription) 0.621
๐Ÿ•ฎ  ciclopirox ethanolamine,(prescription) 0.621
eburnamonine (-),(prescription) 0.621
tomoxetine hydrochloride,(prescription) 0.621
๐Ÿ•ฎ  procainamide hydrochloride,(prescription) 0.621
๐Ÿ•ฎ  alverine citrate salt,(prescription) 0.621
๐Ÿ•ฎ  phentermine hydrochloride,(prescription) 0.621
raclopride non-drug 0.621
๐Ÿ•ฎ  prednisolone,(prescription) 0.621
๐Ÿ•ฎ  benfotiamine,(prescription) 0.621  ๐Ÿ“
flumethasone,(prescription) 0.621
adrenosterone,(prescription) 0.621
iproniazide phosphate,(prescription) 0.621
๐Ÿ•ฎ  meloxicam,(prescription) 0.621
fosfosal,(prescription) 0.621
๐Ÿ•ฎ  nadolol,(prescription) 0.621
๐Ÿ•ฎ  bemegride,(prescription) 0.621
๐Ÿ•ฎ  tiletamine hydrochloride,(prescription) 0.621
๐Ÿ•ฎ  rofecoxib,(prescription) 0.621
๐Ÿ•ฎ  maprotiline hydrochloride,(prescription) 0.621
๐Ÿ•ฎ  flurbiprofen,(prescription) 0.621
๐Ÿ•ฎ  simvastatin,(prescription) 0.621
๐Ÿ•ฎ  estriol,(prescription) 0.621
๐Ÿ•ฎ  phenylbutazone,(prescription) 0.621
clorgyline hydrochloride,(prescription) 0.621
demecarium bromide,(prescription) 0.621
๐Ÿ•ฎ  letrozole,(prescription) 0.621
๐Ÿ•ฎ  molsidomine,(prescription) 0.621
๐Ÿ•ฎ  tyloxapol,(prescription) 0.621
dibucaine,(prescription) 0.621
serotonin hydrochloride non-drug 0.621
๐Ÿ•ฎ  butalbital,(prescription) 0.621
vatalanib,(prescription) 0.621
๐Ÿ•ฎ  etofylline,(prescription) 0.621
edrophonium chloride,(prescription) 0.621
sulfabenzamide 0.621
๐Ÿ•ฎ  nicorandil,(prescription) 0.621
๐Ÿ•ฎ  oxcarbazepine,(prescription) 0.621
๐Ÿ•ฎ  chlorothiazide,(prescription) 0.621
tremorine dihydrochloride non-drug 0.621
๐Ÿ•ฎ  metergoline,(prescription) 0.621

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  inulin (prebiotic) 1
๐Ÿ•ฎ  berberine 0.81
Slippery Elm 0.755
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.641
arabinogalactan (prebiotic) 0.509
red wine 0.439
non-starch polysaccharides 0.386
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.384
๐Ÿ•ฎ  Pulses 0.376
resistant starch 0.374
triphala 0.372
๐Ÿ•ฎ  lactobacillus rhamnosus (probiotics) 0.312
๐Ÿ•ฎ  pectin 0.279
saccharin 0.262
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.261
resistant maltodextrin 0.26
bile (acid/salts) 0.255
๐Ÿ•ฎ  Burdock Root 0.252
stevia 0.242
๐Ÿ•ฎ  fructo-oligosaccharides (prebiotic) 0.234
Alpha-Ketoglutarate 0.232
gallic acid (food additive) 0.227
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.221
๐Ÿ•ฎ  vitamin d 0.212
๐Ÿ•ฎ  minocycline (antibiotic)s[CFS] 0.212
ku ding cha tea 0.211
๐Ÿ•ฎ  Reduce choline (Beef, Chicken Eggs) 0.208
fasting 0.207
levan 0.199
schisandra chinensis(magnolia berry or five-flavor-fruit) 0.181
whole grain diet 0.178
l-citrulline 0.171
chemotherapy (prescription) 0.167
barley 0.166
๐Ÿ•ฎ  saccharomyces boulardii (probiotics) 0.165
pea (fiber, protein) 0.164
๐Ÿ•ฎ  bifidobacterium longum (probiotics) 0.164
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.162
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.161
sodium butyrate 0.161
๐Ÿ•ฎ  lactobacillus rhamnosus gg (probiotics) 0.16
animal-based diet 0.159
plantago asiatica l. 0.159
๐Ÿ•ฎ  cruciferous vegetables (broccoli cabbage) 0.158
cholic acid (bile acid) 0.156
vitamin a 0.155
bacillus licheniformis,(probiotics) 0.151
raw potato starch 0.15
hypocaloric hyperproteic diet 0.147
ketogenic diet 0.144
rare meat 0.143
laminaria digitata,oarweed - seaweed 0.14
fat 0.139
palm kernel meal 0.139
๐Ÿ•ฎ  Fisetin 0.137
gynostemma pentaphyllum (Jiaogulan) 0.134
carboxymethyl cellulose (prebiotic) 0.131
nuts 0.129
high red meat 0.125
lard 0.121
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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