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 : Need to nap during each day_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  gentamicin (antibiotic)s 0.878
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.746
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.662
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.659  ๐Ÿ“
๐Ÿ•ฎ  risperidone,(prescription) 0.614
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.608  ๐Ÿ“
๐Ÿ•ฎ  atorvastatin (prescription) 0.603  ๐Ÿ“
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.574  ๐Ÿ“
๐Ÿ•ฎ  estradiol valerate,(prescription) 0.567
Caffeine 0.565
๐Ÿ•ฎ  Vitamin B-12 0.565  ๐Ÿ“
prednisone,(prescription) 0.549
pregnenolone non-drug 0.544
๐Ÿ•ฎ  propofol,(prescription) 0.544
๐Ÿ•ฎ  quinidine hydrochloride monohydrate,(prescription) 0.544
๐Ÿ•ฎ  promethazine hydrochloride,(prescription) 0.544
pronethalol hydrochloride non-drug 0.544
๐Ÿ•ฎ  propafenone hydrochloride,(prescription) 0.544
propantheline bromide,(prescription) 0.544
proparacaine hydrochloride,(prescription) 0.544
pyrithyldione,(prescription) 0.544
๐Ÿ•ฎ  quetiapine hemifumarate,(prescription) 0.544
quinacrine dihydrochloride dihydrate,(prescription) 0.544
๐Ÿ•ฎ  quinapril hcl,(prescription) 0.544
๐Ÿ•ฎ  propylthiouracil,(prescription) 0.544
๐Ÿ•ฎ  proscillaridin a,(prescription) 0.544
prothionamide (antibiotic) 0.544
๐Ÿ•ฎ  pyrantel tartrate,(prescription) 0.544
๐Ÿ•ฎ  pyrazinamide (antibiotic) 0.544
pyridostigmine iodide,(prescription) 0.544
pyrilamine maleate,(prescription) 0.544
propoxycaine hydrochloride,(prescription) 0.544
๐Ÿ•ฎ  pramipexole,(prescription) 0.544
pramoxine hydrochloride,(prescription) 0.544
๐Ÿ•ฎ  pranlukast,(prescription) 0.544
๐Ÿ•ฎ  pranoprofen,(prescription) 0.544
๐Ÿ•ฎ  pravastatin,(prescription) 0.544
๐Ÿ•ฎ  pridinol methanesulfonate salt,(prescription) 0.544
๐Ÿ•ฎ  prilocaine hydrochloride,(prescription) 0.544
๐Ÿ•ฎ  primaquine diphosphate,(prescription) 0.544
๐Ÿ•ฎ  primidone,(prescription) 0.544
proadifen hydrochloride non-drug 0.544
๐Ÿ•ฎ  probenecid,(prescription) 0.544
๐Ÿ•ฎ  probucol,(prescription) 0.544
๐Ÿ•ฎ  procainamide hydrochloride,(prescription) 0.544
๐Ÿ•ฎ  procaine hydrochloride,(prescription) 0.544
๐Ÿ•ฎ  procarbazine hydrochloride,(prescription) 0.544
๐Ÿ•ฎ  prochlorperazine dimaleate,(prescription) 0.544
๐Ÿ•ฎ  procyclidine hydrochloride,(prescription) 0.544
๐Ÿ•ฎ  racecadotril,(prescription) 0.544
racepinephrine hcl,(prescription) 0.544
๐Ÿ•ฎ  podophyllotoxin,(prescription) 0.544
practolol,(prescription) 0.544
๐Ÿ•ฎ  pralidoxime chloride,(prescription) 0.544
๐Ÿ•ฎ  praziquantel,(prescription) 0.544
๐Ÿ•ฎ  prazosin hydrochloride,(prescription) 0.544
๐Ÿ•ฎ  prednicarbate,(prescription) 0.544
๐Ÿ•ฎ  prednisolone,(prescription) 0.544
๐Ÿ•ฎ  progesterone,(prescription) 0.544
๐Ÿ•ฎ  proglumide,(prescription) 0.544

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  inulin (prebiotic) 1
arabinogalactan (prebiotic) 0.835
walnuts 0.478
saccharomyces boulardii (probiotics) 0.475
resistant starch 0.471
๐Ÿ•ฎ  berberine 0.465
๐Ÿ•ฎ  Pulses 0.417
red wine 0.396
๐Ÿ•ฎ  lactulose 0.354
Slippery Elm 0.346
proton-pump inhibitors (prescription) 0.328
vsl#3 (probiotics) 0.311
fasting 0.293
apple 0.291
wheat 0.291
barley 0.289
barley,oat 0.289
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.286
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.276
๐Ÿ•ฎ  lactobacillus rhamnosus gg (probiotics) 0.26
resistant maltodextrin 0.258
high fiber diet 0.256
๐Ÿ•ฎ  pectin 0.251
soy 0.249
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.242
raffinose(sugar beet) 0.241
l-proline 0.24
non-starch polysaccharides 0.238
๐Ÿ•ฎ  ß-glucan 0.235
macrolide ((antibiotic)s) 0.232
salt (sodium chloride) 0.231
๐Ÿ•ฎ  bifidobacterium longum (probiotics) 0.228
gynostemma pentaphyllum (Jiaogulan) 0.228
wheat bran 0.225
saccharomyces cerevisiae (probiotics) 0.221
ku ding cha tea 0.214
almonds/ almond skins 0.213
bacillus subtilis (probiotics) 0.196
bile (acid/salts) 0.191
green-lipped mussel 0.191
genistein 0.19
sodium butyrate 0.189
๐Ÿ•ฎ  bifidobacterium catenulatum,(probiotics) 0.183
๐Ÿ•ฎ  glycine 0.183
jerusalem artichoke (prebiotic) 0.183
fish oil 0.183
pea (fiber, protein) 0.183
high salt 0.181
levan 0.178
๐Ÿ•ฎ  Cacao 0.163
raw potato starch 0.163
palm kernel meal 0.16
dietary phytoestrogens (isoflavones) 0.16
chondrus crispus,red sea weed 0.157
๐Ÿ•ฎ  bifidobacterium pseudocatenulatum,(probiotics) 0.156
๐Ÿ•ฎ  isepamicin (antibiotic)s 0.154
lividomycin (antibiotic)s 0.154
vitamin a 0.152
disodium fumarate (food additive) 0.151
๐Ÿ•ฎ  tetracycline (antibiotic)s 0.149
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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