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 : Nausea_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 1
๐Ÿ•ฎ  piperacillin-tazobactam (antibiotic)s 0.828
imipenem (antibiotic)s 0.707
๐Ÿ•ฎ  amoxicillin (antibiotic)s[CFS] 0.633
๐Ÿ•ฎ  benzylpenicillin sodium (antibiotic) 0.599
๐Ÿ•ฎ  ciprofloxacin (antibiotic)s[CFS] 0.528
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.504
๐Ÿ•ฎ  vancomycin (antibiotic)[CFS] 0.479
๐Ÿ•ฎ  garlic (allium sativum) 0.468  ๐Ÿ“
๐Ÿ•ฎ  ampicillin (antibiotic)s[CFS] 0.444
cinnamon (oil. spice) 0.442  ๐Ÿ“
๐Ÿ•ฎ  trimethoprim (antibiotic)s 0.423
neem 0.423  ๐Ÿ“
fluoroquinolone (antibiotic)s 0.4
๐Ÿ•ฎ  thyme (thymol, thyme oil) 0.397
syzygium aromaticum (clove) 0.374
๐Ÿ•ฎ  minocycline (antibiotic)s[CFS] 0.368
๐Ÿ•ฎ  Vitamin B-12 0.368  ๐Ÿ“
๐Ÿ•ฎ  tobramycin (antibiotic)s 0.366
foeniculum vulgare,fennel 0.356
๐Ÿ•ฎ  meropenem (antibiotic)s 0.355
๐Ÿ•ฎ  reserpine,(prescription) 0.35
๐Ÿ•ฎ  cefotaxime sodium salt (antibiotic) 0.349
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.347  ๐Ÿ“
๐Ÿ•ฎ  streptomycin (antibiotic)s 0.332
๐Ÿ•ฎ  aztreonam (antibiotic) 0.332
๐Ÿ•ฎ  estradiol valerate,(prescription) 0.327
๐Ÿ•ฎ  alverine citrate salt,(prescription) 0.314
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.313
peppermint (spice, oil) 0.313
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.31  ๐Ÿ“
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.31  ๐Ÿ“
๐Ÿ•ฎ  naproxen,(prescription) 0.308
๐Ÿ•ฎ  ofloxacin (antibiotic)s 0.308
๐Ÿ•ฎ  atorvastatin (prescription) 0.303  ๐Ÿ“
๐Ÿ•ฎ  acarbose,(prescription) 0.302
fluocinolone acetonide,(prescription) 0.298
๐Ÿ•ฎ  fluocinonide,(prescription) 0.298
๐Ÿ•ฎ  fluorometholone,(prescription) 0.298
๐Ÿ•ฎ  flurbiprofen,(prescription) 0.298
fluspirilen,(prescription) 0.298
๐Ÿ•ฎ  flutamide,(prescription) 0.298
๐Ÿ•ฎ  labetalol hydrochloride,(prescription) 0.298
๐Ÿ•ฎ  ciprofibrate,(prescription) 0.298
๐Ÿ•ฎ  clomipramine hydrochloride,(prescription) 0.298
๐Ÿ•ฎ  clozapine,(prescription) 0.298
๐Ÿ•ฎ  flunarizine dihydrochloride,(prescription) 0.298
๐Ÿ•ฎ  flunisolide,(prescription) 0.298
๐Ÿ•ฎ  flunixin meglumine,(prescription) 0.298
folinic acid calcium salt,(prescription) 0.298
๐Ÿ•ฎ  fomepizole,(prescription) 0.298
๐Ÿ•ฎ  formestane,(prescription) 0.298
๐Ÿ•ฎ  formoterol fumarate,(prescription) 0.298
fosfosal,(prescription) 0.298
๐Ÿ•ฎ  iohexol,(prescription) 0.298
๐Ÿ•ฎ  iopamidol,(prescription) 0.298
iopanoic acid,(prescription) 0.298
๐Ÿ•ฎ  iopromide,(prescription) 0.298
๐Ÿ•ฎ  ioversol,(prescription) 0.298
ioxaglic acid,(prescription) 0.298

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
proton-pump inhibitors (prescription) 0.449
๐Ÿ•ฎ  lactulose 0.357
arabinogalactan (prebiotic) 0.357
blueberry 0.269
vsl#3 (probiotics) 0.268
๐Ÿ•ฎ  Reduce choline (Beef, Chicken Eggs) 0.267
macrolide ((antibiotic)s) 0.265
๐Ÿ•ฎ  inulin (prebiotic) 0.249
aspartame (sweetner) 0.242
raffinose(sugar beet) 0.239
ku ding cha tea 0.209
๐Ÿ•ฎ  Pulses 0.197
๐Ÿ•ฎ  berberine 0.187
gynostemma pentaphyllum (Jiaogulan) 0.169
green-lipped mussel 0.169
apple 0.167
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.163
red wine 0.161
lividomycin (antibiotic)s 0.159
๐Ÿ•ฎ  isepamicin (antibiotic)s 0.159
barley,oat 0.158
xylan (prebiotic) 0.138
non-starch polysaccharides 0.138
fasting 0.134
fish oil 0.134
๐Ÿ•ฎ  pectin 0.131
levan 0.127
๐Ÿ•ฎ  high-fat diets 0.125
amaranth 0.119
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.117
๐Ÿ•ฎ  fruit 0.115
resistant starch 0.114
lincosamide (antibiotic)s 0.114
Sijunzi decoction 0.112
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.111
๐Ÿ•ฎ  ß-glucan 0.11
butirosin 0.107
symbioflor 2 e.coli probiotics 0.103
palm kernel meal 0.103
General Biotics Equilibrium 0.101
chondrus crispus,red sea weed 0.101
Slippery Elm 0.097
high fiber diet 0.096
sodium butyrate 0.095
saccharomyces boulardii (probiotics) 0.094
a-glucosidase inhibitors 0.09
mediterranean diet 0.088
๐Ÿ•ฎ  alcoholic beverages 0.088
fat 0.087
saccharomyces cerevisiae (probiotics) 0.082
l-proline 0.079
๐Ÿ•ฎ  zinc 0.078
whole grain diet 0.078
sulfonamide (antibiotic)s 0.077
resistant maltodextrin 0.077
penicillin-moxalactam (antibiotic)s 0.076
๐Ÿ•ฎ  lactobacillus gasseri (probiotics) 0.074
carob 0.073
helminth infection (prescription) 0.071
wheat bran 0.071
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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