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: Inability for deep (delta) sleep_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
Vitamin B9,folic acid 0.609  ๐Ÿ“
๐Ÿ•ฎ  Vitamin B1,thiamine hydrochloride 0.586  ๐Ÿ“
Caffeine 0.558
๐Ÿ•ฎ  Hesperidin (polyphenol) 0.558  ๐Ÿ“
Vitamin C (ascorbic acid) 0.511  ๐Ÿ“
๐Ÿ•ฎ  N-Acetyl Cysteine (NAC), 0.501  ๐Ÿ“
luteolin (flavonoid) 0.436  ๐Ÿ“
diosmin,(polyphenol) 0.436  ๐Ÿ“
Arbutin (polyphenol) 0.436  ๐Ÿ“
๐Ÿ•ฎ  Vitamin B6,pyridoxine hydrochloride 0.436  ๐Ÿ“
๐Ÿ•ฎ  vitamin B7, biotin 0.436  ๐Ÿ“
๐Ÿ•ฎ  Vitamin B-12 0.436  ๐Ÿ“
retinoic acid,(Vitamin A derivative) 0.436
Theobromine (in food) 0.436
linseed(flaxseed) 0.417  ๐Ÿ“
๐Ÿ•ฎ  melatonin supplement 0.406  ๐Ÿ“
vitamin B3,niacin 0.388  ๐Ÿ“
sucralose 0.374  ๐Ÿ“
chitosan,(sugar) 0.329  ๐Ÿ“
whole-grain barley 0.276  ๐Ÿ“
๐Ÿ•ฎ  bifidobacterium longum bb536 (probiotics) 0.262
momordia charantia(bitter melon, karela, balsam pear, or bitter gourd) 0.252
๐Ÿ•ฎ  cannabinoids 0.252
๐Ÿ•ฎ  Cacao 0.247  ๐Ÿ“
glycyrrhizic acid (licorice) 0.243  ๐Ÿ“
foeniculum vulgare,fennel 0.238
๐Ÿ•ฎ  lauric acid(fatty acid in coconut oil,in palm kernel oil,) 0.198
vitamin a 0.196  ๐Ÿ“
๐Ÿ•ฎ  lactobacillus kefiri (NOT KEFIR) 0.195
cinnamon (oil. spice) 0.184  ๐Ÿ“
Kimchi 0.178
๐Ÿ•ฎ  garlic (allium sativum) 0.178  ๐Ÿ“
gluten-free diet 0.17
high-protein diet 0.164
high sugar diet 0.163
๐Ÿ•ฎ  thyme (thymol, thyme oil) 0.162
l-glutamine 0.158  ๐Ÿ“
๐Ÿ•ฎ  lactobacillus rhamnosus (probiotics) 0.156  ๐Ÿ“
salvia officinalis (sage) 0.152
Grapefruit seed extract 0.138
high animal protein diet 0.137
Guaiacol (polyphenol) 0.137
๐Ÿ•ฎ  high-fat diets 0.136
galla rhois 0.135
pediococcus acidilactic (probiotic) 0.132
rosmarinus officinalis,rosemary 0.132
chitooligosaccharides (prebiotic) 0.124  ๐Ÿ“
Galangal 0.122
galla chinensis (herb) 0.122
Hibiscus 0.122
Goldenseal 0.122
grape polyphenols 0.122
Citric acid 0.122
Clove 0.122
Coffee 0.122
Cola (w/ aspartame) 0.122
Cilantro 0.122
Cumin 0.122
Echinacea 0.122  ๐Ÿ“
Elderberry 0.122

To Remove or Decrease

Modifier Confidence ๐Ÿ“น
๐Ÿ•ฎ  inulin (prebiotic) 1
resistant starch 0.795
arabinogalactan (prebiotic) 0.676
๐Ÿ•ฎ  berberine 0.657
red wine 0.616
๐Ÿ•ฎ  Human milk oligosaccharides (prebiotic, Holigos, Stachyose) 0.584
non-starch polysaccharides 0.554
๐Ÿ•ฎ  Pulses 0.493
๐Ÿ•ฎ  lactobacillus plantarum (probiotics) 0.49
๐Ÿ•ฎ  vitamin d 0.48
resistant maltodextrin 0.468
saccharin 0.416
walnuts 0.409
pea (fiber, protein) 0.401
saccharomyces boulardii (probiotics) 0.352
apple 0.35
fasting 0.345
gallic acid (food additive) 0.342
stevia 0.326
xylan (prebiotic) 0.317
l-citrulline 0.314
mediterranean diet 0.313
wheat bran 0.308
lupin seeds (anaphylaxis risk, toxic if not prepared properly) 0.299
schisandra chinensis(magnolia berry or five-flavor-fruit) 0.287
๐Ÿ•ฎ  bifidobacterium longum (probiotics) 0.277
๐Ÿ•ฎ  lactobacillus rhamnosus gg (probiotics) 0.275
๐Ÿ•ฎ  pectin 0.265
fibre-rich macrobiotic ma-pi 2 diet 0.261
carboxymethyl cellulose (prebiotic) 0.258
gynostemma pentaphyllum (Jiaogulan) 0.244
levan 0.242
animal-based diet 0.237
soy 0.235
salt (sodium chloride) 0.232
low-fat diets 0.229
๐Ÿ•ฎ  lactobacillus fermentum (probiotics) 0.221
vegetarians 0.22
๐Ÿ•ฎ  lactobacillus acidophilus (probiotics) 0.212
barley 0.207
ketogenic diet 0.202
cranberry bean flour 0.202
plantago asiatica l. 0.2
๐Ÿ•ฎ  Burdock Root 0.193
wheat 0.193
Alpha-Ketoglutarate 0.187
๐Ÿ•ฎ  bifidobacterium bifidum (probiotics) 0.187
๐Ÿ•ฎ  oligosaccharides (prebiotic) 0.184
high salt 0.181
bacillus licheniformis,(probiotics) 0.174
high resistant starch 0.172
raw potato starch 0.172
hypocaloric hyperproteic diet 0.172
high red meat 0.168
sodium butyrate 0.165
๐Ÿ•ฎ  galacto-oligosaccharides (prebiotic) 0.163
methionine-choline-deficient (MCD) diet 0.159
Pork 0.154
๐Ÿ•ฎ  black raspberries 0.154
low protein diet 0.15
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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