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 : Headaches_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  amikacin (antibiotic)s 0.667
foeniculum vulgare,fennel 0.666
๐Ÿ•ฎ  imipenem (antibiotic)s 0.602
๐Ÿ•ฎ  ciprofloxacin (antibiotic)s[CFS] 0.562
๐Ÿ•ฎ  ofloxacin (antibiotic)s 0.542
oregano (origanum vulgare, oil) | 0.528
๐Ÿ•ฎ  amoxicillin (antibiotic)s[CFS] 0.504
๐Ÿ•ฎ  meropenem (antibiotic)s 0.5
๐Ÿ•ฎ  Vitamin B-12 0.496  ๐Ÿ“
๐Ÿ•ฎ  piperacillin-tazobactam (antibiotic)s 0.483
๐Ÿ•ฎ  tobramycin (antibiotic)s 0.466
clostridium butyricum (probiotics),Miya,Miyarisan 0.451  ๐Ÿ“
intesti-bacteriophage 0.432
๐Ÿ•ฎ  hypericin, St. John's Wort 0.426
๐Ÿ•ฎ  cefotaxime sodium salt (antibiotic) 0.42
๐Ÿ•ฎ  garlic (allium sativum) 0.406  ๐Ÿ“
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.401
๐Ÿ•ฎ  benzylpenicillin sodium (antibiotic) 0.399
๐Ÿ•ฎ  reserpine,(prescription) 0.383
๐Ÿ•ฎ  lactobacillus reuteri (probiotics) 0.382  ๐Ÿ“
๐Ÿ•ฎ  trimethoprim (antibiotic)s 0.371
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.368  ๐Ÿ“
nigella sativa seed (black cumin) 0.358  ๐Ÿ“
๐Ÿ•ฎ  aztreonam (antibiotic) 0.354
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.353  ๐Ÿ“
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.348
๐Ÿ•ฎ  acarbose,(prescription) 0.346
๐Ÿ•ฎ  atorvastatin (prescription) 0.342  ๐Ÿ“
๐Ÿ•ฎ  ampicillin (antibiotic)s[CFS] 0.341
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.341  ๐Ÿ“
Caffeine 0.339
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.339  ๐Ÿ“
whey 0.333  ๐Ÿ“
๐Ÿ•ฎ  chloramphenicol (antibiotic)s 0.332
๐Ÿ•ฎ  ceftazidime (antibiotic)s 0.331
๐Ÿ•ฎ  itraconazole,(prescription) 0.33
๐Ÿ•ฎ  alverine citrate salt,(prescription) 0.327
cinnamon (oil. spice) 0.325  ๐Ÿ“
laser trilobum l.,kefe cumin 0.323
moxalactam disodium salt (antibiotic) 0.316
๐Ÿ•ฎ  pioglitazone,(prescription) 0.313
๐Ÿ•ฎ  testosterone propionate,(prescription) 0.313
๐Ÿ•ฎ  tripelennamine hydrochloride,(prescription) 0.313
trioxsalen,(prescription) 0.313
๐Ÿ•ฎ  hydrochlorothiazide,(prescription) 0.313
๐Ÿ•ฎ  ganciclovir,(prescription) 0.313
๐Ÿ•ฎ  captopril,(prescription) 0.313
๐Ÿ•ฎ  allantoin non-drug 0.313
sulmazole non-drug 0.313
mevalonic-d; l acid lactone non-drug 0.313
๐Ÿ•ฎ  pramipexole,(prescription) 0.313
๐Ÿ•ฎ  mizolastine,(prescription) 0.313
๐Ÿ•ฎ  fenoterol hydrobromide,(prescription) 0.313
epiandrosterone,(prescription) 0.313
acetohexamide,(prescription) 0.313
pepstatin a non-drug 0.313
๐Ÿ•ฎ  phthalylsulfathiazole (antibiotic) 0.313
๐Ÿ•ฎ  mephenesin,(prescription) 0.313
๐Ÿ•ฎ  furosemide,(prescription) 0.313

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
Slippery Elm 0.714
aspartame (sweetner) 0.618
๐Ÿ•ฎ  Reduce choline (Beef, Chicken Eggs) 0.394
arabinogalactan (prebiotic) 0.352
red wine 0.306
blueberry 0.284
penicillin-moxalactam (antibiotic)s 0.26
๐Ÿ•ฎ  berberine 0.253
resistant starch 0.243
non-starch polysaccharides 0.242
proton-pump inhibitors (prescription) 0.237
๐Ÿ•ฎ  Pulses 0.235
๐Ÿ•ฎ  inulin (prebiotic) 0.223
fasting 0.208
๐Ÿ•ฎ  saccharomyces boulardii (probiotics) 0.207
macrolide ((antibiotic)s) 0.206
levan 0.189
symbioflor 2 e.coli probiotics 0.184
navy bean 0.169
sulfonamide (antibiotic)s 0.164
l-proline 0.164
walnuts 0.163
ku ding cha tea 0.162
carboxymethyl cellulose (prebiotic) 0.161
xylan (prebiotic) 0.161
saccharin 0.145
mediterranean diet 0.143
wheat bran 0.143
๐Ÿ•ฎ  ß-glucan 0.141
sodium butyrate 0.138
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.129
๐Ÿ•ฎ  tetracycline (antibiotic)s 0.127
๐Ÿ•ฎ  iron 0.124
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.123
๐Ÿ•ฎ  pectin 0.122
red alga Laurencia tristicha 0.117
high fiber diet 0.115
triphala 0.112
Ferric citrate 0.111
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.108
resistant maltodextrin 0.108
a-glucosidase inhibitors 0.106
lividomycin (antibiotic)s 0.102
๐Ÿ•ฎ  isepamicin (antibiotic)s 0.102
green-lipped mussel 0.102
๐Ÿ•ฎ  alcoholic beverages 0.096
l-citrulline 0.095
๐Ÿ•ฎ  netilmicin (antibiotic)s 0.092
acriflavin (prescription) 0.092
๐Ÿ•ฎ  dibekacin (antibiotic)s 0.092
catecholamines (polyphenol) 0.092
colinfant e.coli probiotics 0.092
glycylcycline (antibiotic)s 0.092
l-glutamic acid 0.092
l-serine 0.092
beef 0.092
carob 0.092
cadium 0.092
cephamycin (antibiotic)s 0.092
a-glucosidase inhibitors (prescription) 0.092
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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