I would like to introduce you to a tool for analyzing the gut microbiome that will become a tool for future intestinal examinations.
In the semiconductor process, if there is a problem with the wafer, the process chamber is checked for contamination, the process is stopped, and then restored to a high vacuum state.
If the vacuum does not show a problem, it is connected to the RGA equipment that analyzes the residual gas, and a very small amount of residual gas is detected, amplified, and displayed.
If a very small amount of gas peak different from the usual amount is seen compared to the process gas, this is assumed to be the cause of the problem, and the chamber is opened to find the cause.
The above solution works on two principles.
Amplification, a method of amplifying very small signals, amplifies the entire signal and applies the log function. Then, you can see large and small signals at the same time. It is a method of expressing one/ten/hundred/ten million as 1/2/3/4/5. That is the log that many dropouts complain about in high school. It is all useful.
SPC, not the SPC that makes bread, but ‘statistical process control’. The impurities that I saw at first did not have specs in the first place. However, since they were not there normally and are different from ‘normal’, there is a high probability that they will be the cause of the problem. This quality control technique developed in Japan is simple, but surprisingly useful.
(If Manager Kim, who was always sloppy, suddenly starts putting on makeup and buying clothes, statistically speaking, he has someone he likes. It is not necessarily true, but it means that there is a high probability that it will happen.)
When I first received the NGS data analyzing the intestinal microbiota, I tried to analyze it by creating various graphs using existing bio analysis tools, but I couldn’t figure out what was what.
So at AiBiotics, we tried to apply the method used in semiconductor processing.
Chamber is ‘intestine’ and various gases are ‘microbiome’.
We took the log function of intestinal microorganisms, which number hundreds of millions per gram, and expressed them as a graph, even for bacteria that are detected in very small amounts by attaching to the intestinal wall. And as the data accumulated little by little, we began to see special bacteria that patients had that were different from ‘normal’ ones.
There are no specs, but it is clear that they are ‘different’.
Babies born by cesarean section have a significantly higher level of Citrobacter, patients with enteritis have a higher level of Clostridium, and babies who took antibiotics have a higher level of Enterobacter. People with diabetes
have a higher level of Prevotella Corpori, and babies with atopy have a random abnormal pattern of various strains of Firmicutes and Proteo.
A baby with very low diversity but a high concentration of lactic acid bacteria means that the mother is feeding her expensive lactic acid bacteria even though she is feeding her food that is not very diverse. Even though my son’s favorite food is kimchi stew, if there is no Prevotella and only a lot of Vulgatus, it means that he does not eat kimchi and only eats pork.
An uncle who eats ordinary food but has a lot of Acamanthia is a mountaineering fanatic.
If you input the analysis of the abnormal pattern seen in RGA, various analyses are possible like this. However, since there is no specification, it is not possible to make a diagnosis under medical law.
However, various meaningful analyses are possible.
As we accumulated over 2,000 data points, we began to resemble fortune tellers.
Someday, Spec will be created.
Since the pre-meal blood sugar level is set as Spec and diabetes can be diagnosed based on the number, it is necessary to collect gut microbiome data from many patients to create meaningful data.
RGA, introduced 25 years ago by an ambitious semiconductor engineer, has now become a fundamental tool in semiconductor manufacturing.
We are confident that our tool for analyzing gut microbiota will also become a fundamental tool for gut inspection.
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