scholarly journals A Neural Communication Model between Brain and Internal Organs via Postprandial Plasma Glucose Waveforms Study Based on 95 Liquid Egg Meals and 110 Solid Egg Meals (No. 311)

2020 ◽  
pp. 1-5
Author(s):  
Gerald C Hsu ◽  

In this paper, the author described the progress on his two-year long special research project, from 5/5/2018 through 8/13/2020, to identify a neural communication model between the brain’s cerebral cortex and certain internal organs such as the stomach, liver, and pancreas. He used a continuous glucose monitor (CGM) sensor collected postprandial plasma glucose (PPG) data to investigate the glucose production amount at different timing and waveform differences between 95 liquid egg meals and 110 solid egg meals

2020 ◽  
pp. 1-4
Author(s):  
Gerald C Hsu ◽  

In this paper, the author describes his 2+ years (801 days) research results, from 5/5/2018 through 7/14/2020, using his 171 special meals glucose data. Initially, he researched the detailed postprandial plasma glucose (PPG) data resulting from both food intake and post-meal exercise via 97 solid egg meals (74 pan-fried and 23 hard broiled) and 74 liquid egg meals (egg drop soup). Based on his findings, he adopted a statistical method of “decision making via elimination” to search and verify a hypothetical neural communication model between the brain’s cerebral cortex and internal organs, such as the stomach, intestines, liver, and pancreas


After reviewing the research results for six months, from September 2019 through February 2020, the author identified a probable internal communication model between the nervous system and certain vital internal organs, specifically the stomach and liver regarding postprandial plasma glucose (PPG) production. The author used a continuous glucose monitor device to collect 50,000 glucose data during the past 665 days. He focused on studying the relationships among different food nutritional contents, cooking methods, food material’s physical phases, and different characteristics and variants from his glucose waveform patterns. In this study, he focused on the three major meal groups based on food nutritional ingredients, meal’s preparation, and cooking methods of eggs, squash, and cabbage to create soup-based (liquid) meal and pan-fried (solid) meal. The PPG waveforms from these three meal groups demonstrated that soup-based liquid food produced a much lower glucose value than the pan-fried solid food. Although both liquid and solid meals have similar identical nutritional ingredients, he questions why did this occur? His hypothesis is that his PPG differences are due to specific physical phase of his finished meal either “liquid” or “solid”, which is his ready-to-eat meal’s final physical “phase” that determines his PPG characteristics and waveforms. The author utilized his GH-Method: math-physical medicine (MPM) approach to explore a T2D patient’s glucose production situation from a scientific view of the brain and nervous system’s functionalities. If this specific approach and above interpretation are accurate, we can then “trick” our brain into producing a “lesser” amount of glucose after food intake without altering or sacrificing the needed food nutritional balance. As a result, T2D patients can simply change their cooking method in order to lower both of their peak PPG values and their average PPG levels.


In this paper, the author presents the results of his national segmentation pattern analysis of the sensor PPG data based on both high-carb and low-carb intake amounts. It also verified his earlier findings on the communication model between the brain and internal organs such as the stomach, liver, and pancreas.


After reviewing the research results for six months, from September 2019 through February 2020, the author identified a probable internal communication model between the nervous system and certain vital internal organs, specifically the stomach and liver regarding postprandial plasma glucose (PPG) production. The author used a continuous glucose monitor device to collect 50,000 glucose data during the past 665 days. He focused on studying the relationships among different food nutritional contents, cooking methods, food material’s physical phases, and different characteristics and variants from his glucose waveform patterns. In this study, he focused on the three major meal groups based on food nutritional ingredients, meal’s preparation, and cooking methods of eggs, squash, and cabbage to create soup-based (liquid) meal and pan-fried (solid) meal. The PPG waveforms from these three meal groups demonstrated that soup-based liquid food produced a much lower glucose value than the pan-fried solid food. Although both liquid and solid meals have similar identical nutritional ingredients, he questions why did this occur? His hypothesis is that his PPG differences are due to specific physical phase of his finished meal either “liquid” or “solid”, which is his ready-to-eat meal’s final physical “phase” that determines his PPG characteristics and waveforms. The author utilized his GH-Method: math-physical medicine (MPM) approach to explore a T2D patient’s glucose production situation from a scientific view of the brain and nervous system’s functionalities. If this specific approach and above interpretation are accurate, we can then “trick” our brain into producing a “lesser” amount of glucose after food intake without altering or sacrificing the needed food nutritional balance. As a result, T2D patients can simply change their cooking method in order to lower both of their peak PPG values and their average PPG levels.


2020 ◽  
Vol 3 (3) ◽  

This article address the author’s hypothesis on the neurocommunication model existing between the brain and liver regarding production and glucose secretion in the early morning. This is based on the observation of the difference between glucose at wake up moment in the morning for the fasting plasma glucose (FPG), and glucose at the first bite of breakfast for the glucose at 0-minute or “open glucose” of postprandial plasma glucose (PPG). All of the eight identified glucoses of breakfast PPG are higher than the eight glucoses at time of wake up by a difference of an average of 8 mg/dL. The value difference using Method B of CGM sensor glucoses during the COVID-19 period offers the most accurate picture and credible glucose difference of 8 mg/dL between his FPG at wake-up moment and PPG at the first bite of breakfast. The author believes that the brain senses when a person wakes up due to different kinds of stimuli from many sources, including eye, environment, and even internal organs, which will alert the body to be in “active” mode requiring “energy” through glucose. Even though the person has not eaten anything or is not actively moving, the brain issues a marching order to the liver to produce or release glucose for the body to use in the forthcoming day. This hypothesis can currently explain why his glucose of eating his breakfast is ~8 mg/dL higher than his FPG at wakeup.


2020 ◽  
pp. 1-5
Author(s):  
Gerald C Hsu ◽  

This article address is the author’s hypothesis on the neurocommunication model existing between the brain and liver regarding production and glucose secretion in the early morning. This is based on the observation of the difference between glucose at wake up moment in the morning for the fasting plasma glucose (FPG), and glucose at the first bite of breakfast for the glucose at 0-minute or “open glucose” of postprandial plasma glucose (PPG)


Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 772-P
Author(s):  
MARIKO HIGA ◽  
AYANA HASHIMOTO ◽  
MOE HAYASAKA ◽  
MAI HIJIKATA ◽  
AYAMI UEDA ◽  
...  

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 246-OR
Author(s):  
MARIAM ALATRACH ◽  
CHRISTINA AGYIN ◽  
NITCHAKARN LAICHUTHAI ◽  
JOHN M. ADAMS ◽  
MUHAMMAD ABDUL-GHANI ◽  
...  

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