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: emotional overload_No_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.

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
foeniculum vulgare,fennel 1
๐Ÿ•ฎ  thyme (thymol, thyme oil) 0.941
cinnamon (oil. spice) 0.909  ๐Ÿ“
๐Ÿ•ฎ  garlic (allium sativum) 0.87  ๐Ÿ“
๐Ÿ•ฎ  Vitamin B-12 0.802  ๐Ÿ“
oregano (origanum vulgare, oil) | 0.764
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.721  ๐Ÿ“
๐Ÿ•ฎ  hypericin, St. John's Wort 0.685
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.666  ๐Ÿ“
nigella sativa seed (black cumin) 0.642  ๐Ÿ“
๐Ÿ•ฎ  lactobacillus casei (probiotics) 0.619  ๐Ÿ“
neem 0.602  ๐Ÿ“
syzygium aromaticum (clove) 0.579
clostridium butyricum (probiotics),Miya,Miyarisan 0.567  ๐Ÿ“
Caffeine 0.559
vitamin B3,niacin 0.548  ๐Ÿ“
๐Ÿ•ฎ  Vitamin B6,pyridoxine hydrochloride 0.547  ๐Ÿ“
Theobromine (in food) 0.547
Arbutin (polyphenol) 0.547  ๐Ÿ“
diosmin,(polyphenol) 0.547  ๐Ÿ“
retinoic acid,(Vitamin A derivative) 0.547
luteolin (flavonoid) 0.547  ๐Ÿ“
laser trilobum l.,kefe cumin 0.53
Curcumin 0.515  ๐Ÿ“
๐Ÿ•ฎ  vitamin B7, biotin 0.509  ๐Ÿ“
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.508  ๐Ÿ“
peppermint (spice, oil) 0.492
glycyrrhizic acid (licorice) 0.482  ๐Ÿ“
whey 0.454  ๐Ÿ“
Vitamin C (ascorbic acid) 0.452  ๐Ÿ“
๐Ÿ•ฎ  melatonin supplement 0.445  ๐Ÿ“
๐Ÿ•ฎ  jatropha curcas [can be poisonous] 0.436
Guaiacol (polyphenol) 0.431
oplopanax horridus(Devil's Club) 0.408
๐Ÿ•ฎ  vitamin d 0.404  ๐Ÿ“
triphala 0.401  ๐Ÿ“
coriander oil 0.385
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.377  ๐Ÿ“
rosmarinus officinalis,rosemary 0.369
๐Ÿ•ฎ  lactobacillus paracasei (probiotics) 0.363  ๐Ÿ“
tea 0.343
๐Ÿ•ฎ  lactobacillus rhamnosus gg (probiotics) 0.337  ๐Ÿ“
chitosan,(sugar) 0.332  ๐Ÿ“
quercetin 0.326  ๐Ÿ“
salvia officinalis (sage) 0.321
๐Ÿ•ฎ  lactobacillus kefiri (NOT KEFIR) 0.319
sucralose 0.309  ๐Ÿ“
saccharin 0.304  ๐Ÿ“
Sumac(Rhus coriaria) 0.302
galla chinensis (herb) 0.298
laminaria hyperborea( tangle/cuvie - seaweed) 0.297
schinus molle (herb) 0.287
๐Ÿ•ฎ  tulsi 0.279  ๐Ÿ“
mutaflor escherichia coli nissle 1917 (probiotics) 0.277  ๐Ÿ“
lemongrass oil 0.275
barley 0.273  ๐Ÿ“
brown rice 0.27
rosa rugosa 0.267
๐Ÿ•ฎ  selenium 0.26  ๐Ÿ“
green tea 0.255

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  Reduce choline (Beef, Chicken Eggs) 0.567
arabinogalactan (prebiotic) 0.502
๐Ÿ•ฎ  lactulose 0.497
non-starch polysaccharides 0.492
aspartame (sweetner) 0.477
๐Ÿ•ฎ  inulin (prebiotic) 0.472
red wine 0.45
๐Ÿ•ฎ  Burdock Root 0.433
raffinose(sugar beet) 0.428
wheat bran 0.421
ku ding cha tea 0.415
gluten-free diet 0.361
Slippery Elm 0.348
๐Ÿ•ฎ  resveratrol (grape seed/polyphenols/red wine) 0.331
blueberry 0.326
navy bean 0.318
๐Ÿ•ฎ  Pulses 0.313
๐Ÿ•ฎ  high-fat diets 0.302
resistant starch 0.301
๐Ÿ•ฎ  fructo-oligosaccharides (prebiotic) 0.301
high sugar diet 0.291
sesame cake/meal 0.289
๐Ÿ•ฎ  berberine 0.287
apple 0.276
pea (fiber, protein) 0.267
symbioflor 2 e.coli probiotics 0.253
levan 0.25
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.247
mediterranean diet 0.24
fat 0.236
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.236
carob 0.228
๐Ÿ•ฎ  pectin 0.226
xylan (prebiotic) 0.222
fasting 0.216
๐Ÿ•ฎ  zinc 0.215
schisandra chinensis(magnolia berry or five-flavor-fruit) 0.212
Prescript Assist (2018 Formula) 0.212
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.209
๐Ÿ•ฎ  lactobacillus rhamnosus (probiotics) 0.209
almonds/ almond skins 0.208
green-lipped mussel 0.203
๐Ÿ•ฎ  galactose (milk sugar) 0.201
jerusalem artichoke (prebiotic) 0.199
sodium butyrate 0.199
l-citrulline 0.188
๐Ÿ•ฎ  alcoholic beverages 0.186
barley,oat 0.186
Conjugated Linoleic Acid 0.182
l-proline 0.181
Prescript Assist (Original Formula) 0.164
magnesium 0.154
saccharomyces boulardii (probiotics) 0.152
๐Ÿ•ฎ  lactobacillus fermentum (probiotics) 0.142
resistant maltodextrin 0.142
fish oil 0.14
vsl#3 (probiotics) 0.138
plantago asiatica l. 0.133
sugar 0.133
bacillus coagulans (probiotics) 0.131
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 ยงโ€ฏ1030, 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.

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.
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