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 : Difficulty following things_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 0.757
๐Ÿ•ฎ  imipenem (antibiotic)s 0.749
foeniculum vulgare,fennel 0.699
๐Ÿ•ฎ  Vitamin B-12 0.631  ๐Ÿ“
๐Ÿ•ฎ  ofloxacin (antibiotic)s 0.63
๐Ÿ•ฎ  lactobacillus casei (probiotics) 0.609  ๐Ÿ“
๐Ÿ•ฎ  garlic (allium sativum) 0.601  ๐Ÿ“
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.579  ๐Ÿ“
๐Ÿ•ฎ  ciprofloxacin (antibiotic)s[CFS] 0.554
๐Ÿ•ฎ  piperacillin-tazobactam (antibiotic)s 0.551
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.534
๐Ÿ•ฎ  amoxicillin (antibiotic)s[CFS] 0.528
๐Ÿ•ฎ  tobramycin (antibiotic)s 0.52
๐Ÿ•ฎ  reserpine,(prescription) 0.501
oregano (origanum vulgare, oil) | 0.496
๐Ÿ•ฎ  benzylpenicillin sodium (antibiotic) 0.479
๐Ÿ•ฎ  lactobacillus reuteri (probiotics) 0.465  ๐Ÿ“
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.461  ๐Ÿ“
Caffeine 0.461
๐Ÿ•ฎ  meropenem (antibiotic)s 0.46
๐Ÿ•ฎ  chloramphenicol (antibiotic)s 0.459
intesti-bacteriophage 0.458
๐Ÿ•ฎ  atorvastatin (prescription) 0.453  ๐Ÿ“
๐Ÿ•ฎ  sulfamethoxazole (antibiotic) 0.452
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.448  ๐Ÿ“
๐Ÿ•ฎ  acarbose,(prescription) 0.448
Vitamin C (ascorbic acid) 0.445  ๐Ÿ“
๐Ÿ•ฎ  alverine citrate salt,(prescription) 0.442
clostridium butyricum (probiotics),Miya,Miyarisan 0.438  ๐Ÿ“
๐Ÿ•ฎ  itraconazole,(prescription) 0.436
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.436
๐Ÿ•ฎ  hypericin, St. John's Wort 0.432
๐Ÿ•ฎ  metronidazole (antibiotic)s[CFS] 0.428
๐Ÿ•ฎ  aztreonam (antibiotic) 0.428
๐Ÿ•ฎ  ribavirin,(prescription) 0.428
triflupromazine hydrochloride,(prescription) 0.428
๐Ÿ•ฎ  carvedilol,(prescription) 0.428
๐Ÿ•ฎ  methenamine (antibiotic) 0.428
acefylline,(prescription) 0.428
๐Ÿ•ฎ  rimexolone,(prescription) 0.428
๐Ÿ•ฎ  ciprofibrate,(prescription) 0.428
๐Ÿ•ฎ  ramipril,(prescription) 0.428
๐Ÿ•ฎ  carteolol hydrochloride,(prescription) 0.428
๐Ÿ•ฎ  zalcitabine,(prescription) 0.428
๐Ÿ•ฎ  podophyllotoxin,(prescription) 0.428
dehydrocholic acid non-drug 0.428
๐Ÿ•ฎ  aripiprazole,(prescription) 0.428
guanadrel sulfate,(prescription) 0.428
(+)-isoproterenol (+)-bitartrate salt,(prescription) 0.428
proparacaine hydrochloride,(prescription) 0.428
๐Ÿ•ฎ  chlorprothixene hydrochloride,(prescription) 0.428
๐Ÿ•ฎ  amphotericin b,(prescription) 0.428
olmesartan,(prescription) 0.428
๐Ÿ•ฎ  nalmefene hydrochloride,(prescription) 0.428
๐Ÿ•ฎ  gemfibrozil,(prescription) 0.428
๐Ÿ•ฎ  liranaftate,(prescription) 0.428
fluspirilen,(prescription) 0.428
๐Ÿ•ฎ  nilvadipine,(prescription) 0.428
๐Ÿ•ฎ  clenbuterol hydrochloride,(prescription) 0.428

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
aspartame (sweetner) 0.737
๐Ÿ•ฎ  inulin (prebiotic) 0.644
resistant starch 0.578
arabinogalactan (prebiotic) 0.542
Slippery Elm 0.503
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.485
red wine 0.451
๐Ÿ•ฎ  Reduce choline (Beef, Chicken Eggs) 0.396
blueberry 0.345
non-starch polysaccharides 0.336
macrolide ((antibiotic)s) 0.335
๐Ÿ•ฎ  berberine 0.318
๐Ÿ•ฎ  Pulses 0.312
l-proline 0.287
levan 0.279
resistant maltodextrin 0.277
penicillin-moxalactam (antibiotic)s 0.254
saccharin 0.252
ku ding cha tea 0.251
๐Ÿ•ฎ  pectin 0.246
symbioflor 2 e.coli probiotics 0.243
xylan (prebiotic) 0.241
navy bean 0.24
๐Ÿ•ฎ  lactulose 0.239
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.227
๐Ÿ•ฎ  resveratrol (grape seed/polyphenols/red wine) 0.219
wheat bran 0.201
fasting 0.2
๐Ÿ•ฎ  fructo-oligosaccharides (prebiotic) 0.2
vegetarians 0.191
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.189
jerusalem artichoke (prebiotic) 0.187
๐Ÿ•ฎ  Burdock Root 0.184
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.177
partially hydrolysed guar gum,fructo-oligosaccharides (prebiotic) 0.166
๐Ÿ•ฎ  iron 0.164
barley,oat 0.157
๐Ÿ•ฎ  netilmicin (antibiotic)s 0.156
carob 0.153
mediterranean diet 0.152
green-lipped mussel 0.147
gynostemma pentaphyllum (Jiaogulan) 0.147
๐Ÿ•ฎ  tetracycline (antibiotic)s 0.145
๐Ÿ•ฎ  galactose (milk sugar) 0.139
bile (acid/salts) 0.138
proton-pump inhibitors (prescription) 0.138
a-glucosidase inhibitors 0.137
grape seed extract 0.134
schisandra chinensis(magnolia berry or five-flavor-fruit) 0.134
l-citrulline 0.134
slow digestible carbohydrates 0.131
high fiber diet 0.13
plantago asiatica l. 0.13
Conjugated Linoleic Acid 0.13
almonds/ almond skins 0.128
stevia 0.128
sesame cake/meal 0.127
beef 0.122
catecholamines (polyphenol) 0.122
acriflavin (prescription) 0.122
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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