Why some suggestions may contradict

RECOMMENDED READING Caveats on using the contents of this page. 👨‍⚕️

If you need help with this information, here is a list of consultants 👨‍⚕️👩‍⚕️ that are available.

Suggestion Parameters
Sample:A Priori (from theoretical deduction)
Bacteria Selection:Outside of Range
Filter: From Special Studies V2: Autonomic: Graying or blacking out after standing_Drugs
Rank Used: All Ranks
Shifts Used:High and Low Levels
Citations Used:

How do we know if the suggestions are reasonable/valid?

🍱 Food Menu Planner 🍽️ 📹 How are suggestions determined

Suggestions

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 📹
🕮  gentamicin (antibiotic)s 1
🕮  vancomycin (antibiotic)[CFS] 0.939
🕮  piperacillin-tazobactam (antibiotic)s 0.865
🕮  benzylpenicillin sodium (antibiotic) 0.726
🕮  thyme (thymol, thyme oil) 0.687
🕮  imipenem (antibiotic)s 0.641
🕮  amoxicillin (antibiotic)s[CFS] 0.617
🕮  meropenem (antibiotic)s 0.588
cinnamon (oil. spice) 0.586  📏
🕮  ciprofloxacin (antibiotic)s[CFS] 0.579
🕮  ampicillin (antibiotic)s[CFS] 0.52
syzygium aromaticum (clove) 0.511
🕮  hyoscyamine (l),(prescription) 0.494
neem 0.494  📏
🕮  tobramycin (antibiotic)s 0.462
🕮  minocycline (antibiotic)s[CFS] 0.449
fluoroquinolone (antibiotic)s 0.418
🕮  tetracycline (antibiotic)s 0.401
🕮  glycerol monolaurate (Monolaurin) 0.392
🕮  tigecycline (antibiotic)s 0.365
🕮  garlic (allium sativum) 0.358  📏
trachyspermum ammi, Ajwain 0.353
🕮  trimethoprim (antibiotic)s 0.348
peppermint (spice, oil) 0.348
🕮  risperidone,(prescription) 0.337
foeniculum vulgare,fennel 0.336
🕮  Hesperidin (polyphenol) 0.327  📏
🕮  N-Acetyl Cysteine (NAC), 0.326  📏
🕮  streptomycin (antibiotic)s 0.322
🕮  nitrofurantoin (antibiotic) 0.319
rosmarinus officinalis,rosemary 0.314
🕮  alverine citrate salt,(prescription) 0.303
🕮  naproxen,(prescription) 0.3
lemongrass oil 0.298
saccharin 0.297  📏
salvia officinalis (sage) 0.285
🕮  spectinomycin dihydrochloride (antibiotic) 0.281
🕮  clindamycin (antibiotic)s[CFS] 0.278
🕮  fenbendazole,(prescription) 0.276
🕮  reboxetine mesylate,(prescription) 0.276
galla chinensis (herb) 0.275
aloe vera 0.273
🕮  doxycycline (antibiotic)s[CFS] 0.266
Curcumin 0.262  📏
🕮  itraconazole,(prescription) 0.258
🕮  ketoconazole,(prescription) 0.258
🕮  sulfamethoxazole (antibiotic) 0.258
Caffeine 0.258
🕮  chloramphenicol (antibiotic)s 0.258
🕮  estradiol valerate,(prescription) 0.256
🕮  neomycin (antibiotic)s[CFS] 0.254
🕮  ibuprofen 0.252
clofilium tosylate,(prescription) 0.25
valproic acid,(prescription) 0.25
🕮  ritodrine hydrochloride,(prescription) 0.25
adamantamine fumarate,(prescription) 0.25
🕮  cisapride,(prescription) 0.25
🕮  fluvastatin sodium salt,(prescription) 0.25
ibandronate sodium,(prescription) 0.25
🕮  dihydroergotamine tartrate,(prescription) 0.25

To Remove or Decrease
Modifier Confidence 📹
🕮  inulin (prebiotic) 0.577
🕮  lactulose 0.476
proton-pump inhibitors (prescription) 0.462
🕮  fructo-oligosaccharides (prebiotic) 0.457
🕮  resveratrol (grape seed/polyphenols/red wine) 0.455
arabinogalactan (prebiotic) 0.443
raffinose(sugar beet) 0.391
apple 0.35
bacillus subtilis (probiotics) 0.319
🕮  metformin (prescription) 0.287
fasting 0.282
vsl#3 (probiotics) 0.269
wheat bran 0.261
Lactobacillus Johnsonii (probiotic) 0.239
barley 0.229
ketogenic diet 0.224
macrolide ((antibiotic)s) 0.22
pomegranate 0.213
red wine 0.212
🕮  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.211
fish oil 0.208
Conjugated Linoleic Acid 0.193
pea (fiber, protein) 0.189
barley,oat 0.183
high sugar diet 0.178
jerusalem artichoke (prebiotic) 0.175
🕮  Pulses 0.172
🕮  bifidobacterium lactis bb12 (probiotics) 0.171
Slippery Elm 0.166
🕮  galacto-oligosaccharides (prebiotic) 0.164
blueberry 0.16
almonds/ almond skins 0.159
mediterranean diet 0.158
sesame cake/meal 0.157
🕮  gum arabic (prebiotic) 0.156
🕮  oligosaccharides (prebiotic) 0.152
🕮  saccharomyces boulardii (probiotics) 0.15
palm kernel meal 0.15
🕮  lactobacillus fermentum (probiotics) 0.147
🕮  pectin 0.145
walnuts 0.144
🕮  Astragalus polysaccharide 0.141
🕮  black raspberries 0.139
gynostemma pentaphyllum (Jiaogulan) 0.136
cranberry bean flour 0.136
low-fat diets 0.136
🕮  Ginseng 0.134
🕮  Burdock Root 0.134
daesiho-tang 0.132
xylan (prebiotic) 0.13
amaranth 0.13
🕮  grapes 0.125
high red meat 0.121
lincosamide (antibiotic)s 0.121
sodium butyrate 0.119
fat 0.119
laminaria digitata,oarweed - seaweed 0.119
magnesium 0.115
🕮  noni 0.114
🕮  lactobacillus gasseri (probiotics) 0.11
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.

Copyright 2016-2023 Lassesen Consulting, LLC [2007], DBA, Microbiome Prescription. All rights served.
Permission to data scrap or reverse engineer is explicitly denied to all users. U.S. Code Title 18 PART I CHAPTER 47 § 1030, CETS No.185, CFAA
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.

Microbiome Prescription do not make any representations that data or analyses available on this site is suitable for human diagnostic purposes, for informing treatment decisions, or for any other purposes and accept no responsibility or liability whatsoever for such use.
This site is not Health Insurance Portability and Accountability Act of 1996 (HIPAA) compliant.


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