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: Neurological-Sleep: Chaotic diurnal sleep rhythms (Erratic Sleep)_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

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 ๐Ÿ“น
๐Ÿ•ฎ  gentamicin (antibiotic)s 1
๐Ÿ•ฎ  piperacillin-tazobactam (antibiotic)s 0.796
๐Ÿ•ฎ  amoxicillin (antibiotic)s[CFS] 0.707
๐Ÿ•ฎ  imipenem (antibiotic)s 0.706
๐Ÿ•ฎ  amikacin (antibiotic)s 0.579
๐Ÿ•ฎ  trimethoprim (antibiotic)s 0.573
๐Ÿ•ฎ  acarbose,(prescription) 0.517
๐Ÿ•ฎ  hyoscyamine (l),(prescription) 0.495
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.482  ๐Ÿ“
๐Ÿ•ฎ  benzylpenicillin sodium (antibiotic) 0.473
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.473  ๐Ÿ“
๐Ÿ•ฎ  tobramycin (antibiotic)s 0.466
๐Ÿ•ฎ  aztreonam (antibiotic) 0.454
๐Ÿ•ฎ  ofloxacin (antibiotic)s 0.451
Caffeine 0.449
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.447  ๐Ÿ“
fluoroquinolone (antibiotic)s 0.444
๐Ÿ•ฎ  atorvastatin (prescription) 0.443  ๐Ÿ“
๐Ÿ•ฎ  risperidone,(prescription) 0.438
๐Ÿ•ฎ  loperamide hydrochloride,(prescription) 0.437
๐Ÿ•ฎ  itraconazole,(prescription) 0.433
๐Ÿ•ฎ  carbamazepine,(prescription) 0.428
๐Ÿ•ฎ  ceftazidime (antibiotic)s 0.419
๐Ÿ•ฎ  sulfamethoxazole (antibiotic) 0.417
foeniculum vulgare,fennel 0.416
๐Ÿ•ฎ  Vitamin B-12 0.416  ๐Ÿ“
๐Ÿ•ฎ  ciprofloxacin (antibiotic)s[CFS] 0.415
๐Ÿ•ฎ  streptomycin (antibiotic)s 0.41
๐Ÿ•ฎ  meropenem (antibiotic)s 0.41
lidoflazine,(prescription) 0.409
๐Ÿ•ฎ  venlafaxine,(prescription) 0.409
canrenone,(prescription) 0.409
๐Ÿ•ฎ  fomepizole,(prescription) 0.409
๐Ÿ•ฎ  nizatidine,(prescription) 0.409
๐Ÿ•ฎ  fenofibrate,(prescription) 0.409
๐Ÿ•ฎ  metoprolol-(+;-) (+)-tartrate salt,(prescription) 0.409
๐Ÿ•ฎ  iohexol,(prescription) 0.409
๐Ÿ•ฎ  sulfisoxazole (antibiotic) 0.409
๐Ÿ•ฎ  dexamethasone acetate,(prescription) 0.409
๐Ÿ•ฎ  gliclazide,(prescription) 0.409
methimazole,(prescription) 0.409
๐Ÿ•ฎ  naftopidil dihydrochloride,(prescription) 0.409
๐Ÿ•ฎ  famciclovir,(prescription) 0.409
๐Ÿ•ฎ  ketoprofen,(prescription) 0.409
pinacidil,(prescription) 0.409
๐Ÿ•ฎ  colchicine,(prescription) 0.409
estradiol-17 beta,(prescription) 0.409
indatraline hydrochloride non-drug 0.409
piromidic acid (antibiotic) 0.409
levonordefrin,(prescription) 0.409
๐Ÿ•ฎ  aceclofenac,(prescription) 0.409
๐Ÿ•ฎ  sulindac,(prescription) 0.409
cycloheximide non-drug 0.409
๐Ÿ•ฎ  chlorambucil,(prescription) 0.409
picotamide monohydrate,(prescription) 0.409
androsterone,(prescription) 0.409
๐Ÿ•ฎ  labetalol hydrochloride,(prescription) 0.409
digitoxigenin,(prescription) 0.409
๐Ÿ•ฎ  fenoprofen calcium salt dihydrate,(prescription) 0.409
clofibric acid non-drug 0.409

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  inulin (prebiotic) 0.613
Slippery Elm 0.598
proton-pump inhibitors (prescription) 0.422
arabinogalactan (prebiotic) 0.419
red wine 0.364
resistant starch 0.355
saccharin 0.323
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.312
๐Ÿ•ฎ  tetracycline (antibiotic)s 0.298
๐Ÿ•ฎ  berberine 0.29
non-starch polysaccharides 0.273
๐Ÿ•ฎ  Pulses 0.262
๐Ÿ•ฎ  saccharomyces boulardii (probiotics) 0.255
๐Ÿ•ฎ  pectin 0.236
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.227
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.22
๐Ÿ•ฎ  Prescript Assist (2018 Formula) 0.215
๐Ÿ•ฎ  lactulose 0.211
resistant maltodextrin 0.206
apple 0.201
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.184
xylan (prebiotic) 0.184
๐Ÿ•ฎ  lactobacillus rhamnosus gg (probiotics) 0.18
levan 0.178
fasting 0.178
blueberry 0.173
wheat bran 0.171
fish oil 0.167
schisandra chinensis(magnolia berry or five-flavor-fruit) 0.166
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.166
raffinose(sugar beet) 0.165
bile (acid/salts) 0.157
gynostemma pentaphyllum (Jiaogulan) 0.149
high red meat 0.148
๐Ÿ•ฎ  Nicotine, Nicotine Patch 0.145
l-citrulline 0.143
ku ding cha tea 0.137
๐Ÿ•ฎ  lactobacillus fermentum (probiotics) 0.137
triphala 0.137
๐Ÿ•ฎ  Reduce choline (Beef, Chicken Eggs) 0.136
plantago asiatica l. 0.131
PreforPro 0.13
whole grain diet 0.127
animal-based diet 0.125
barley 0.125
stevia 0.118
macrolide ((antibiotic)s) 0.117
๐Ÿ•ฎ  cruciferous vegetables (broccoli cabbage) 0.116
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.116
hypocaloric hyperproteic diet 0.11
pea (fiber, protein) 0.109
๐Ÿ•ฎ  lactobacillus rhamnosus (probiotics) 0.109
ketogenic diet 0.109
cholic acid (bile acid) 0.108
chemotherapy (prescription) 0.108
refined wheat breads 0.107
vitamin k2 0.106
l-proline 0.106
vsl#3 (probiotics) 0.103
gallic acid (food additive) 0.102
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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