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: Infection: Lyme_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 0.987
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.839
๐Ÿ•ฎ  piperacillin-tazobactam (antibiotic)s 0.787
๐Ÿ•ฎ  amoxicillin (antibiotic)s[CFS] 0.777
๐Ÿ•ฎ  tobramycin (antibiotic)s 0.722
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.705  ๐Ÿ“
๐Ÿ•ฎ  risperidone,(prescription) 0.689
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.67  ๐Ÿ“
๐Ÿ•ฎ  benzylpenicillin sodium (antibiotic) 0.666
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.665
๐Ÿ•ฎ  atorvastatin (prescription) 0.662  ๐Ÿ“
๐Ÿ•ฎ  imipenem (antibiotic)s 0.658
๐Ÿ•ฎ  vancomycin (antibiotic)[CFS] 0.657
๐Ÿ•ฎ  estradiol valerate,(prescription) 0.646
๐Ÿ•ฎ  itraconazole,(prescription) 0.634
๐Ÿ•ฎ  carbamazepine,(prescription) 0.631
Caffeine 0.628
๐Ÿ•ฎ  sulfamethoxazole (antibiotic) 0.619
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.618  ๐Ÿ“
๐Ÿ•ฎ  iopromide,(prescription) 0.616
dehydroisoandosterone 3-acetate,(prescription) 0.616
๐Ÿ•ฎ  clonidine hydrochloride,(prescription) 0.616
๐Ÿ•ฎ  felbinac,(prescription) 0.616
lithocholic acid non-drug 0.616
nomifensine maleate,(prescription) 0.616
๐Ÿ•ฎ  escitalopram,(prescription) 0.616
๐Ÿ•ฎ  heptaminol hydrochloride,(prescription) 0.616
๐Ÿ•ฎ  adiphenine hydrochloride,(prescription) 0.616
๐Ÿ•ฎ  nicorandil,(prescription) 0.616
๐Ÿ•ฎ  oxcarbazepine,(prescription) 0.616
๐Ÿ•ฎ  chlorothiazide,(prescription) 0.616
tremorine dihydrochloride non-drug 0.616
๐Ÿ•ฎ  metergoline,(prescription) 0.616
pancuronium bromide,(prescription) 0.616
๐Ÿ•ฎ  guanfacine hydrochloride,(prescription) 0.616
etidronic acid; disodium salt,(prescription) 0.616
๐Ÿ•ฎ  etofenamate,(prescription) 0.616
๐Ÿ•ฎ  reserpine,(prescription) 0.616
๐Ÿ•ฎ  losartan,(prescription) 0.616
methapyrilene hydrochloride,(prescription) 0.616
๐Ÿ•ฎ  bupivacaine hydrochloride,(prescription) 0.616
adrenosterone,(prescription) 0.616
๐Ÿ•ฎ  bromperidol,(prescription) 0.616
๐Ÿ•ฎ  penbutolol sulfate,(prescription) 0.616
meprylcaine hydrochloride,(prescription) 0.616
๐Ÿ•ฎ  tranylcypromine hydrochloride,(prescription) 0.616
๐Ÿ•ฎ  citalopram hydrobromide,(prescription) 0.616
๐Ÿ•ฎ  tolnaftate,(prescription) 0.616
๐Ÿ•ฎ  pivmecillinam hydrochloride (antibiotic) 0.616
๐Ÿ•ฎ  quetiapine hemifumarate,(prescription) 0.616
๐Ÿ•ฎ  gestrinone,(prescription) 0.616
amyleine hydrochloride,(prescription) 0.616
isopyrin hydrochloride non-drug 0.616
๐Ÿ•ฎ  crotamiton,(prescription) 0.616
molindone hydrochloride,(prescription) 0.616
๐Ÿ•ฎ  fludrocortisone acetate,(prescription) 0.616
๐Ÿ•ฎ  mebeverine hydrochloride,(prescription) 0.616
๐Ÿ•ฎ  pilocarpine nitrate,(prescription) 0.616
digoxigenin non-drug 0.616
๐Ÿ•ฎ  isoflupredone acetate,(prescription) 0.616

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  inulin (prebiotic) 1
arabinogalactan (prebiotic) 0.799
Slippery Elm 0.763
proton-pump inhibitors (prescription) 0.638
raffinose(sugar beet) 0.598
๐Ÿ•ฎ  lactulose 0.58
๐Ÿ•ฎ  fructo-oligosaccharides (prebiotic) 0.511
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.451
vsl#3 (probiotics) 0.45
๐Ÿ•ฎ  berberine 0.447
๐Ÿ•ฎ  saccharomyces boulardii (probiotics) 0.445
resistant starch 0.415
barley,oat 0.402
barley 0.401
red wine 0.4
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.377
apple 0.37
fish oil 0.368
bacillus subtilis (probiotics) 0.356
jerusalem artichoke (prebiotic) 0.333
chondrus crispus,red sea weed 0.328
๐Ÿ•ฎ  Pulses 0.315
sesame cake/meal 0.311
ku ding cha tea 0.301
macrolide ((antibiotic)s) 0.293
gynostemma pentaphyllum (Jiaogulan) 0.289
๐Ÿ•ฎ  resveratrol (grape seed/polyphenols/red wine) 0.285
high fiber diet 0.277
almonds/ almond skins 0.274
clostridium butyricum (probiotics),Miya,Miyarisan 0.267
green-lipped mussel 0.266
vitamin a 0.259
soy 0.252
๐Ÿ•ฎ  Glucomannan 0.247
lincosamide (antibiotic)s 0.245
wheat 0.242
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.235
pomegranate 0.232
๐Ÿ•ฎ  lactobacillus rhamnosus gg (probiotics) 0.221
๐Ÿ•ฎ  Cacao 0.221
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.216
amaranth 0.216
๐Ÿ•ฎ  lactobacillus gasseri (probiotics) 0.214
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.209
Sijunzi decoction 0.205
wheat bran 0.203
sarcodiotheca gaudichaudii (red sea weed) 0.202
walnuts 0.201
lividomycin (antibiotic)s 0.2
๐Ÿ•ฎ  lincomycin (antibiotic)s 0.2
butirosin 0.2
๐Ÿ•ฎ  isepamicin (antibiotic)s 0.2
magnesium 0.2
๐Ÿ•ฎ  pectin 0.198
๐Ÿ•ฎ  galactose (milk sugar) 0.197
resistant maltodextrin 0.197
palm kernel meal 0.195
bile (acid/salts) 0.194
ketogenic diet 0.193
๐Ÿ•ฎ  bifidobacterium longum (probiotics) 0.191
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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