Medical Research Work Research Articles

Bonding of ceramics to silver-coated titanium-A combined theoretical and experimental study.

It would be very beneficial to have a method for joining of ceramics to titanium reliably. Although several techniques have been developed and tested to prevent extensive interfacial chemical reactions in titanium-ceramic systems, the main problem of the inherent brittleness of interfaces was still unsolved. To overcome this problem also in dental applications, we decided to make use of an interlayer material that needs to meet the following requirements: First, it has to be biocompatible, second, it should not melt below the bonding temperatures, and third, it should not react too strongly with titanium, so that its plasticity will be maintained. Considering possible material options only the metals: gold, platinum, palladium, and silver, fulfill the first and second requirements. To find out-without an extensive experimental testing program-which of the four metals fulfills the third requirement best, the combined thermodynamic and reaction kinetic modeling was employed to evaluate how many and how thick reaction layers are formed between the interlayer metals and titanium. With the help of theoretical modeling, it was shown that silver fulfills the last requirement best. However, before starting to test experimentally the effect of the silver layer on the mechanical integrity of dental ceramic/Ag/Ti joints it was decided to make use of mechanical analysis of the three-point bending test, the result of which indicated that the silver layer increases significantly the bond strength of the joints. This result encouraged us to develop a new technique for plating silver on titanium. Subsequently, we executed numerous three-point bending tests, which demonstrated that silver-plated titanium-ceramic joints are much stronger than conventional titanium-ceramic joints. Hence, it can be concluded that the combined thermodynamic, reaction kinetic, and mechanical modeling method can also be a very valuable tool in medical research and development work.

Options of Funding and Ethical Clearance for Medical Researchers in India

Research forms an integral part of present world development and interest. It is the primary source of speculation and outcome-based decision making. Medical research work proves to be a big challenge in low- and middle-income countries due to the constraint of resources and capacity building. The disparities in the distribution of resources, inadequate policy implementation, and lack of prioritization of research make the research challenging. There has been an increase in medical research in India but it is not adequate when compared to other countries or areas. Medical researchers face multiple issues, mainly funding and ethical approval and are stunted by the unacceptance in high-indexed journals. In this paper, we have compiled the options for funding and ethical options and ways available for researchers in India. This will help and encourage researchers pro-actively by providing some guidance on the issues related to finance and ethics required for conducting scientific research.

WOMEN TEACHING ANATOMY IN R. NORTH MACEDONIA - HISTORICAL BACKGROUND AND CURRENT TRENDS

The establishment of the Faculty of Medicine in 1947 as an educational, medical and research institution enabled rapid development of the health care, health service and health system in the R. North Macedonia. Short overview of the role and participation of women in the process of medical education and scientific research work in the field of anatomy in the country provides insight into the constant rise of women with a continuous upward trend of their participation in the period from the establishment of the Faculty of Medicine until today. Women participation in medicine is of crucial importance for the further development of educational, scientific and highly specialized health care activities in our country.

Viscoelastic or Viscoplastic Glucose Theory (VGT #56): Using the VGT tool to Estimate the Relative Energy Associated with Different Calculated Annual Cancer Risk Percentages Under the Influence of Estimated Average Glucose (eAG) and Body Weight in The Early Morning (BW) Over Two 5-Year Periods, Y2012-Y2016 and Y2017-Y2021, based on GH-Method: Math-Physical Medicine (No. 644)

The author was a professional engineer working in the fields of the space shuttle, naval battleships, nuclear power plants, computer hardware and software, artificial intelligence, and semiconductor chips. After his retirement, he started to self-study and research internal medicine with an emphasis on biomarker relationships exploration and disease prevention. Since 2010, he has utilized the disciplines learned from 7 different universities along with various work experiences to formulate his current medical research work during the past 13 years.

Comparison of Waves and Energies between the 3-Hours Versus 24-Hours of Glucose Fluctuation using 3+ Years of Continuous Glucose Monitoring Sensor Device Collected Data Based on GH-Method: Math-Physical Medicine (No. 457)

Since 2017, the author utilized his collected data of finger pierced glucoses 4x per day, along with the data of 10 metabolism index (MI) categories including 4 medical conditions and 6 lifestyle details over a 9.5-year period, from 2012 to 2021, to estimate his risk probabilities of having diabetic complications. They include macro-vascular and micro-vascular diseases such as cardiovascular disease, stroke, diabetic kidney disease, diabetic retinopathy, foot ulcer, Alzheimer’s disease, and certain cancers. In addition to the mean value of glucoses, namely the average glucose such as HbA1C, the actual glucose excursion or glucose fluctuation (GF) has noticeable influences on these diabetic complications. Starting from 5/5/2018, along with the finger glucoses, he collected 96 data of glucose values per day for 1,120 days using a continuous glucose monitoring (CGM) sensor device for a total of 107,520 glucose data. Thus far, he has accumulated 3+ years of sensor glucose data; therefore, he would like to enhance his medical research work by using them. Especially with 96 glucose data collected per day, he is now able to easily study the phenomenon of glucose excursion, glucose wave vibration, or glucose data oscillation. The medical community has used the term “glycemic variability (GV)” to describe the glucose excursion which involves several defined GV equations with some inconclusive findings. The author believes that the word “variability” could mean many things; therefore, he decided to apply the same basic concept of glucose excursion or GF without using the other defined GV equations in order to deeply understand and precisely describe the basic biophysical phenomenon of “glucose excursion”. The author has been utilizing glucose fluctuation known as “Daily GF or 24-hour GF” over a 24-hour period in his research work each day. The definition of GF is the maximum glucose (usually around 60-minutes after a meal) minus the minimum glucose (usually around 3am to 4am during sleep) within 24-hours or another selected time period. Recently, he noticed the extremely high and extremely low glucoses frequently occurring within a shorter duration of 3 hours. Therefore, he has inserted a new algorithm of computation into his software program to dynamically calculate the difference between the maximum glucose and the minimum glucose within the moving duration of 3 hours, at15-minute increments throughout the day. By the end of a day, the largest number of GF, which is defined as 3-hour GF, is selected and stored on the cloud server

Using Topology Concept of Mathematics and Finite Element Method of Engineering to Develop a Mathematical Model of Metabolism in medicine in order to Control Various Chronic Diseases and their Complications via Overall Health Conditions Improvement Based on GH-Method: Math-Physical Medicine (No. 453)

The author spent 11 years with more than 30,000 hours to self-study and research chronic diseases and lifestyle details in order to control his severe type 2 diabetes (T2D) and various diabetic complications. After self-studying endocrinology and food nutrition for 4 years, from 2010 to 2013, he applied the learned medicine and food knowledge combined with his background of four academic disciplines and practical experiences on mathematics, physics, engineering, and computer science (big data analytics and artificial intelligence) to develop a mathematical model of metabolism during the entire year of 2014. He continued with his development effort of several prediction tools for weight, fasting plasma glucose (FPG), postprandial plasma glucose (PPG), daily glucose, and HbA1C in 2015-2016. Starting from 2017, he started to write papers based on his findings from his research and then published them in various journals. This particular metabolism model includes 10 major categories: 4 medical conditions including weight (M1), glucose (M2), blood pressure (M3), lipids (M4); with 6 lifestyle details including exercise (M5), water intake (M6), sleep (M7), stress (M8), food and meal (M9), and life routines regularity (M10). These 10 categories contain approximately 500 input and output elements. For example, he spent 9 months on developing the stress category with 34 elements. The total number of data collected and processed during the past 10 years have already exceeded 2 million. During 2015 to 2021, for a period of 6.5 years, he applied many theories and techniques from mathematics, physics, and engineering into his medical research work. This included topology, nonlinear algebra, finite element method, linear elastic theory, wave theory, energy theory, quantum mechanics, optical physics, statistics, machine learning, big data analytics, and artificial intelligence (AI). These various theories and techniques have effectively served as his research tools in order to complete many of the medical research tasks. As a result, his collected personal data of both biomarkers and lifestyle details were utilized to illustrate the development process of building a metabolism model of medicine using topology concept of mathematics, finite element method of engineering along with other applicable theories and principles of physics (applied math) and engineering (applied physics). This paper describes the author’s selected approach of building a mathematical model of metabolism. It uses the topology concept, part of finite element engineering modeling technique, applicable theories and principles from physics and engineering, such as optical physics, energy theory, wave theory, linear elasticity, perturbation theory of quantum mechanics, and various computer science and AI tools to investigate and develop a rather complicated metabolism model in a highly quantitative manner. Optimistically and pleasantly, it has actually achieved certain high prediction accuracy in results based on a simple concept but rather general scope of “Metabolism”.

Viscoelastic or viscoplastic glucose theory (vgt #85): a study on the influences of cardiovascular disease risk (cvd risk), estimated daily average glucose (eag), and body weight (bw) from a type 2 diabetes patient’s psychological reactions and lifestyle changes during 9-quarters of the covid-19 pandemic period from y2020q1 to y2022q1 based on gh-method: math-physical medicine, especially the vgt energy tool (no.

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships of a selected medical output (symptom) versus singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their associated data, multiple symptoms, and influential factors are “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. This is what Professor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. During his recent medical research work using the tool of viscoelastic or viscoplastic behavior theory (VGT), he suddenly realized that there is a strong similarity between medicine and economics. The behaviors and patterns of economics variables (inputs and outputs) he observed are comparable to the behaviors and patterns of medical variables he studied and researched (causes and symptoms), in terms of their curve shape & waveforms, fluctuation patterns, moving trends, physical behaviors, etc. For example, he has applied the candlestick chart or K-line diagram from Wall Street as an effective glucose representation tool in medicine. Most importantly, variables in both medicine and economics possessed the common “time-dependent” characteristics. The recent COVID-19 pandemic is a severe and unique experience to worldwide people that is comparable to the Spanish Flu that happened over a century ago. He wondered what type of biomedical impact or inter-relationship from this COVID pandemic had on some of his collected (eAG and BW) or calculated (CVD Risk) biomarkers. Therefore, in this article, he selects a chain of mutually influenced biomarkers of the cardiovascular disease risk % (CVD risk), estimated daily average glucose (eAG), and body weight (BW) along with the COVID-19 infection cases in the USA as the key input variable to conduct a series of inter-connected VGT analysis research work.

Viscoelastic or viscoplastic theory (VGT #83): A study of influences on consumer price index resulted from consumer psychological reactions and consumption behavior change during the COVID-19 pandemic 9-quarters period from Y2020Q1 to Y2022Q1 based on GH-method: math-physical medicine, especially the VGT energy tool (No. 673)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships of a selected medical output (symptom) versus singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their associated data, multiple symptoms, and influential factors are “time-dependent” which means that all of the biomedical variables are changing from time to time because body living cells are dynamically changing. This is what Professor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. From 1980 to 1981, the author attended a college in California for his MBA degree, emphasizing finance and marketing. In addition, he spent many years managing a successful high-tech semiconductor business in Silicon Valley, where it involved many key factors of economics and finance, such as gross domestic product (GDP), inflation rate, consumer price index (CPI), NASDAQ stock performance, price-earnings ratio (P/E ratio), various investment decisions, return on investments (ROI), etc. As a result, money subjects associated with finance and economics are not unfamiliar subjects to him. In addition, during the 9 years from 2002 to 2010, he self-studied psychology and established 4 psychotherapy centers to take care of 200+ abused women and abandoned children. Therefore, he has accumulated a considerable amount of knowledge on psychological behaviors, especially from the field of clinical psychology of abused victims. During his recent medical research work using the tool of viscoelastic or viscoplastic behavior theory, he suddenly realized that there is a strong similarity between medicine and economics. The behaviors and patterns of economic variables (inputs and outputs) he observed are comparable to the behaviors and patterns of medical variables he studied and researched (causes and symptoms), in terms of their curve shape & waveforms, fluctuation patterns, moving trends, physical behaviors, etc. For example, he has applied the candlestick chart or K-line diagram from Wall Street as an effective glucose representation tool in medicine. Most importantly, variables in both medicine and economics possessed the common “time-dependent” characteristics. The recent COVID-19 pandemic is a severe and unique experience to worldwide people that is comparable to the Spanish Flu that happened over a century ago. He wondered what type of economic impact or inter-relationship from this pandemic had on some of the current economic indices. Therefore, in this article, he selects the CPI of US cities as the output variable along with the COVID-19 death and infection cases in the USA as two input variables to conduct his combined study of both economics and medicine.

Viscoelastic or viscoplastic theory (VGT #84): A comparison study of the influences on the gross domestic product (GDP), inflation rate, and consumer price index (CPI) in the USA resulting from consumer psychological reactions and spending behavior changes over 9-quarters during the COVID-19 pandemic period from Y2020Q1 to Y2022Q1 based on GH-method: math-physical medicine, especially the VGT energy tool (No. 674)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships on a selected medical output (symptom) versus either singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their associated data, multiple symptoms, and influential factors are “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. This is what Professor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. From 1980 to 1981, the author attended a college in California for his MBA degree, emphasizing finance and marketing. In addition, he spent many years managing a successful high-tech semiconductor business in Silicon Valley, where it involved many key factors of economics and finance, such as gross domestic product (GDP), inflation rate, consumer price index (CPI), NASDAQ stock performance, price/earnings ratio (P/E ratio), various investment decisions, return on investments (ROI), etc. As a result, he has a strong background in money topics associated with finance and economics. In addition, during the 9 years from 2002 to 2010, he self-studied psychology and established 4 psychotherapy centers to take care of 200+ abused women and abandoned children. Therefore, he has accumulated a considerable amount of knowledge on psychological behaviors, especially in the field of clinical psychology of abused victims. During his recent medical research work using the tool of viscoelastic or viscoplastic behavior theory, he suddenly realized a strong similarity between medicine and economics. The behaviors and patterns of economics variables (inputs and outputs) he observed are comparable to the behaviors and patterns of medical variables he studied and researched (causes and symptoms) in terms of their curve shape & waveforms, fluctuation patterns, moving trends, physical behaviors, etc. For example, he has applied the candlestick chart or K-line diagram from Wall Street as an effective glucose representation tool in medicine. Most importantly, variables in both medicine and economics possessed the common “time-dependent” characteristics.

Viscoelastic or viscoplastic theory (vgt #115): a study of the us unemployment rates and covid-19 infection cases during the pandemic period from y2020q1 to y2022q1 based on gh-method: math-physical medicine, especially the vgt energy tool (no. 705)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written more than 700 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he has written a total of 110 medical research articles and 5 economic research articles using the viscoelasticity and viscoplasticity theories (VGT). These papers aim to explore some hidden biophysical or physical behaviors and provide a quantitative understanding and interpretations of the relationships of a selected medical output (symptom) versus either selected singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their associated data, multiple symptoms, and influential factors are “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. This is what Professor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then.

Viscoelastic or viscoplastic glucose theory (VGT #82): An investigation of economics markers versus COVID pandemic markers during 9 quarters from Y2020Q1 to Y2022Q1 based on GH-method: math-physical medicine, especially the VGT energy tool (No. 672)

Beginning with paper No. 578 dated 1/8/2022, the author wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different datasets of chosen medical subjects. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of inter-relationships between a selected medical symptom, i.e. biomarker, and multiple influential factors, “root causes or risk factors”. These hidden biophysical behaviors and possible inter-relationships existed among lifestyles, medical conditions, chronic diseases, and certain severe complications, such as heart attacks, stroke, cancers, dementia, or longevity. All of the chosen subjects with their datasets, multiple symptoms, and risk factors are “time-dependent” which means that all of the biomedical variables are changing from time to time. This is why he utilizes VGT tools from physics and engineering to conduct his medical research work. From 1979 to 1982, the author attended a university for his MBA degree with an emphasis on finance and marketing. He spent many years managing a successful high-tech business in Silicon Valley, where it focused on many economic key factors, such as GDP, inflation, stock market performance, etc. As a result, money, finance, and economics are not unfamiliar subjects to him. During his recent medical research work using the VGT tool, he suddenly realized that there is a similarity between the medical and economic systems. The economic variables (inputs and outputs) are comparable to medical variables he studied (causes and symptoms), e.g. waveforms, fluctuation, trends, etc. Both medical and economic variables have possessed “time-dependent” characteristics. The recent COVID-19 pandemic is a unique and severe experience in the world other than the Spanish flu that happened over 100 years ago. He wondered what kind of impact or inter-relationship existed during the pandemic outcome along with overall economic activities. Therefore, he selects the US gross domestic product (GDP) numbers as the output variable along with the US inflation rates (inflation) and the US COVID-19 death cases (COVID) as two input variables to conduct his math-physical medicine (MPM) analysis using the VGT tool. In summary, he conducted three related VGT studies in this article. The first is the GDP of economics versus the inflation rate and COVID death. The second is the inflation rate of economics versus pandemic death and infection from medicine. The third is COVID death from medicine versus COVID infection from medicine. Mathematically, these studies have similar methodologies (VGT) but with different outcome observations and interpretations. Initially, he Googled national data on economics and COVID. However, it should be mentioned that the COVID data are rough estimates directly from the published charts from the Center for Disease Control (CDC) and Johns Hopkins University. The COVID data are simplified with rounded numbers to thousands for death and millions for infection because the precise digits do not change the physical characteristics of VGT analysis results. Next, he searched and reviewed a few economics articles related to GDP, inflation, consumer price index (CPI), etc. Over the past 2+ years, due to his medical research interest, he was exposed to the news, many articles, and published research papers and clinical data regarding the COVID pandemic. This study is of particular interest to him since it links national economics with a severe infectious disease. This article is his first attempt to link COVID deaths with some important economic measurements, specifically GDP and inflation rate. The established theory of viscoelasticity and viscoplasticity (from the physics branch of science) should

Viscoelastic or Viscoplastic Glucose Theory (VGT #93): Using a Hybrid Model of Space Domain VGT Energy Method and Frequency Domain Fast Fourier Transform Energy Method from Three VGT Biomedical Research Cases to Identify a More Suitable Selection of Variables Based on GH-Method: MathPhysical Medicine (No. 683)

The author is an engineer who has conducted medical research work over the past 13 years in the fields of endocrinology, metabolic disorder-induced chronic diseases (especially diabetes), and their resulting various medical complications. Thus far, he has written and published nearly 700 research papers in various medical journals using math-physical medicine methodology (MPM). In December 2021, Professor Norman Jones, the author’s adviser at MIT, suggested the utilization of the viscoelastic/plastic method from physics and engineering to conduct his medical research work. Since then, beginning with Paper No. 578 dated 1/8/2022, he has written 90+ medical papers, including 4 economic papers, using the VGT research tools. These papers aim to explore some hidden physical behaviors and provide a deeper understanding and a better quantitative description of the inter-relationships of a selected output (symptom) versus singular input or multiple inputs (root causes, risk factors, or influential factors). In the field of medical research, the hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases including obesity, diabetes, hypertension, hyperlipid- emia, and induced medical complications, such as heart attacks, stroke, kidney failure, cancers, dementia, and even longevity concerns. In the past 13 years of his medical research work, he has noticed that most medical subjects with their associated data, symptoms, and causes are highly “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. Recently, he realized that the VGT theory should not be limited to engineering applications only. Its ability to link certain time-dependent variables and their physical characteristics and associated energy estimation via the hysteresis loop area are equally powerful for applications in medicine as well as many other fields of knowledge, e.g. economics, psychology, and social science. Of course, one of the major challenges of VGT analysis is related to data mining and selection. The author would like to describe the essence of a “hybrid model” that combines the space-domain (SD) viscoelastic /plastic VGT analysis method and the frequency-domain (FD) fast Fourier transform (FFT) analysis method described in 9 steps instead of mathematical equations. This is for readers who do not have an extensive academic background in those subjects of engineering, physics & mathematics - several excerpts from Wikipedia are included in the Method section of this full-text article.

Viscoelastic or Viscoplastic Glucose Theory (VGT #85): A Study on the Influences of Cardiovascular Disease Risk, Estimated Daily Average Glucose, and Body Weight from a Type 2 Diabetes Patient’s Psychological Reactions and Lifestyle Changes During 9-Quarters of the COVID-19 Pandemic Period from Y2020Q1 to Y2022Q1 Based on GH-Method: Math-Physical Medicine, Especially the VGT Energy Tool (No. 675)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships of a selected medical output (symptom) versus either singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their asso- ciated data, multiple symptoms, and influential factors are “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. This is what Profes- sor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. During his recent medical research work using the tool of viscoelastic or viscoplastic behavior theory, he sud- denly realized a strong similarity between medicine and economics. The behaviors and patterns of economics variables (inputs and outputs) he observed are comparable to the behaviors and patterns of medical variables he studied and researched (causes and symptoms) in terms of their curve shape & waveforms, fluctuation patterns, moving trends, physical behaviors, etc. For example, he has applied the candlestick chart or K-line diagram from Wall Street as an effective glucose representation tool in medicine. Most importantly, variables in both medicine and economics possessed the common “time-dependent” characteristics. The recent COVID-19 pandemic is a severe and unique experience to worldwide people that is comparable to the Spanish Flu that happened over a century ago. He wondered what type of biomedical impact or inter-relationship from this COVID pandemic had on some of his collected (eAG and BW) or calculated (CVD Risk) biomarkers. Therefore, in this article, he selects a chain of mutually influenced biomarkers of the cardiovascular disease risk % (CVD risk), estimated daily average glucose (eAG), and body weight (BW) along with the COVID-19 infection cases in the USA as the key input variable to conduct a series of inter-connected VGT analysis research work.

Viscoelastic or Viscoplastic Glucose Theory (VGT #73): A Study on a Chain-Effect of Multiple Causes Versus Single Symptom Starting with Lifestyle Through Diabetes, Cardiovascular Disease, and Cancers to Longevity using a Type 2 Diabetes Patient’s Collected Data of Lifestyle and Biomarkers by Applying the VGT Energy Tool from Physics and Engineering Based on GH-Method: MathPhysical Medicine (No. 663)

The author focuses on investigating the relationships between biomedical causes and symptoms. In the medical field, it is clear that some symptoms can turn into causes for other symptoms as explained by the “m by n” matrix model in the Method Section. To date, he has applied viscoelasticity and viscoplasticity from engineering and physics to his medical research work with 72 written papers. However, most of his VGT studies are (1 x n) matrix, which is a single symptom corresponding to multiple causes. Here, he attempts to develop a “chain-effect” study of four sets of (1 x n) studies, from postprandial plasma glucose (PPG) through estimated average glucose (eAG) and cardiovascular disease (CVD) to the final estimated health age (geriatrics). The first set is PPG vs. carbs & steps, the second set is eAG vs. FPG & PPG, the third set is CVD risk vs. obesity & type 2 diabetes (T2D), and the fourth set is health age (longevity) vs. cancers risk & CVD risk. After conducting four individual VGT analyses, he further investigates a combined VGT study of longevity vs. obesity, CVD, T2D, and cancer (a 1 x 4 model). Since December 2021, the author has written and published ~70 articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on chosen medical subjects. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of inter-relationships between a selected symptom biomarker and a few intermediate steps that include a variety of selected multiple influential factors, “causes”, or “risk factors”. The hidden biophysical behaviors and possible inter-relationships between diseases, complications, or longevity, and selected different sets of multiple risk factors are “time-dependent” which means that all of these variables are changing from time to time. This is why he utilizes VGT from physics and engineering to conduct his medical research work. His research of various biomarkers starts with fasting plasma glucose (FPG). FPG not only reveals many key facts regarding human health, such as pancreatic beta cells, but it also serves as the baseline of PPG. After knowing the PPG baseline level from FPG, the influences from both carbs/sugar intake amount (a “plus” effect) and post-meal walking steps of exercise (a “minus” effect) then enter into the equation to form the ultimate PPG level. After combining FPG and PPG, the HbA1C level can be determined. If hyperglycemic (high glucose level) conditions last for a long period, diabetes will develop. Eventually, diabetes will damage many internal organs of the human body which may result in many complications, such as CVD, stroke, chronic kidney disease (CKD), diabetic retinopathy (DR), neuropathy, foot ulcer, bladder infection, hypothyroidism, even diabetic constipation, and diabetic skin fungal infection.

Viscoelastic or Viscoplastic Glucose Theory (VGT#53) Applying VGT for Selecting an Appropriate Conversion Factor from Finger-Pierced Daily Estimated Average Glucose (eAG) to a Predicted Finger A1C (F.A1C) and using Collected Annual Average Data from Y2012 to Y2022 to Study the Inter-Relationships Among Lab-Tested A1C, Calculated Finger A1C, and Finger-Pierced eAG Based on the GH-Method: Math-Physical Medicine (No. 640)

The author was a professional engineer working in the fields of the space shuttle, naval battleships, nuclear power plant, computer hardware and software, artificial intelligence, and semiconductor chips. After retiring from his work, he initiated self-study and research on internal medicine with an emphasis on biomarker relationship exploration and disease prevention. Since 2010, he has utilized these disciplines learned from 7 different universities along with various work experiences to formulate his current medical research work during the past 13 years. One thing he has learned is that in engineering or medicine, we are frequently seeking answers, illustrations, or explanations for the relationships between the input variable (force applied on a structure or cause of a disease) and output variable (deformation of a structure or symptom of a disease). However, the multiple relationships between input and output could be expressed with many different matrix formats of 1 x 1, 1 x n, m x 1, or m x n (m or n means different multiple variables). In addition to these described mathematical complications, the output resulting from one or more inputs can also become an input of another output, i.e. a symptom of certain causes can become a cause of another different symptom. This phenomenon is a complex scenario with “chain effects”. In fact, engineering and biomedical complications are fundamentally mathematical problems that correlate or conform with many inherent physical laws or principles. Over the past 13 years, in his medical research work, he has encountered more than 100 different sets of biomarkers with almost equal amounts of cause/input variables versus symptom/output variables. For example, food and exercise influence both body weight and glucose lev el, where persistent high glucose can result in diabetes. When diabetes combines with hypertension (high blood pressure) and hyperlipidemia (high blood lipids), it can cause cardiovascular diseases. Furthermore, obesity and diabetes are also linked with various kinds of cancers. These multiple sets of biomedical input versus output have been researched by the author using different tools he has learned from academic fields of mathematics, physics, computer science, and engineering.

Viscoelastic or Viscoplastic Glucose Theory (VGT #89): Using Frequency-Domain Energy Method to Verify the Results from Space-Domain VGT Energy Method for Cardiovascular Disease, Chronic Kidney Disease, and Type 2 Diabetes Resulting from Body Weight Changes over Two Periods, Y12-Y16 Versus Y17-Y22, Based on GH-Method: Math-Physical Medicine (No. 679)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years in the fields of endocrinology, metabolic disorder-induced chronic diseases (especially diabetes), and their resulting various medical complications. Thus far, he has written and published 600+ research papers in various journals using different math-physical medicine methodologies (MPM). Beginning with paper No. 578 dated 1/8/2022, he has written 80+ medical papers and 4 economics papers using viscoelasticity and viscoplasticity theories (VGT) tools from physics and engineering disciplines. These papers aim to explore some hidden physical behaviors and provide a deeper quantitative understanding of the inter-relationships of a selected output (symptom) versus singular input or multiple inputs (root causes, risk factors, or influential factors). In the field of medical research, the hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain medical complications, such as heart at- tacks, stroke, cancers, dementia, and even longevity concerns. He has noticed that most of the medical subjects with their associated data, multiple symptoms, and influential factors are “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. This is what Professor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. Papers No. 671 through No. 674 focused on the COVID infectious disease as input and three key US economic measurements as outputs. From this economics exercise, he realized that the established theory of viscoelasticity and viscoplasticity (from the physics branch of science) should not only be limited to the scope of engineering applications. Its ability to link certain time-dependent variables and their physical characteristics and associated energy estimation via the hysteresis loop area are equally powerful for applications in many other research fields, such as economics and medicine.

Viscoelastic or Viscoplastic Glucose Theory (VGT #67): A Summarized Report of the Relative Risk Probability Percentages of Developing Five Cancer Types Associated with Pancreatic, Liver, Prostate, Kidney, and Ovarian/Uterine Using their Respective Risk Factors to Validate the Suitability of the VGT Tool on Cancer Research Based on GH-Method: Math-Physical Medicine (No. 656)

Recently, the author has conducted individual research work on five specific cancers related to 6 human organs: pancreas, liver, prostate (for male), kidney, and ovarian/uterus (for female). The major focus of his medical research work during the past 13 years has been preventive medicine supported by quantitative analyses using mathematics, physics, and engineering tools.

Viscoelastic or Viscoplastic Theory (VGT #83): A Study of Influences on Consumer Price Index Resulted from Consumer Psychological Reactions and Consumption Behavior Change During the COVID-19 Pandemic 9-Quarters Period from Y2020Q1 to Y2022Q1 Based on GH-Method: Math-Physical Medicine, Especially the VGT Energy Tool (No. 673)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships of a selected medical output (symptom) versus singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their associated data, multiple symptoms, and influential factors are “time-dependent” which means that all of the biomedical variables are changing from time to time because body living cells are dynamically changing. This is what Professor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then.

Viscoelastic or Viscoplastic Theory (VGT #84): A Comparison Study of the Influences on the Gross Domestic Product (GDP), Inflation Rate, and Consumer Price Index (CPI) in the USA Resulting from Consumer Psychological Reactions and Spending Behavior Changes over 9-Quarters During the COVID-19 Pandemic Period from Y2020Q1 to Y2022Q1 Based on GH-Method: MathPhysical Medicine, Especially the VGT Energy Tool (No. 674)

The author is a mathematician and engineer who has conducted medical research work over the past 13 years. Thus far, he has written 670 medical research papers. Beginning with paper No. 578 dated 1/8/2022, he wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different medical problems with their associated data. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of the inter-relationships of a selected medical output (symptom) versus either singular input or multiple inputs (root causes, risk factors, or influential inputs). The hidden biophysical behaviors and possible inter-relationships exist among lifestyle details, medical conditions, chronic diseases, and certain severe medical complications, such as heart attacks, stroke, cancers, dementia, and even longevity concerns. The chosen medical subjects with their asso- ciated data, multiple symptoms, and influential factors are “time-dependent” which means that all biomedical variables change from time to time because body living cells are dynamically changing. This is what Profes- sor Norman Jones, the author’s adviser at MIT, suggested to him in December 2021 and why he utilizes the VGT tools from physics and engineering to conduct his medical research work since then. From 1980 to 1981, the author attended a college in California for his MBA degree, emphasizing finance and marketing. In addition, he spent many years managing a successful high-tech semiconductor business in Silicon Valley, where it involved many key factors of economics and finance, such as gross domestic product (GDP), inflation rate, consumer price index (CPI), NASDAQ stock performance, price/earnings ratio (P/E ratio), various investment decisions, return on investments (ROI), etc. As a result, he has a strong background in money topics associated with finance and economics.

Linear Elastic Glucose Theory (LEGT #40) & Viscoelastic or Viscoplastic Glucose Theory (VGT #76): Comparing the Results from using LEGT Prediction Tool Versus VGT Energy Tool to Study Postprandial Plasma Glucose (Symptom) Versus Fasting Plasma Glucose, Carbohydrates & Sugar Intake Amounts, and Post-Meal Walking Steps (causes) Based on GH-method: Math-Physical Medicine (No. 666)

The author applied linear elasticity theory (LEGT) to conduct various medical research work, resulting in 39 papers starting with paper No. 346 beginning on 10/14/2020. In addition, he utilized viscoelastic and viscoplastic theories (VGT) to conduct 75 sets of studies regarding symptoms (strains ε) versus multiple causes (stresses σ) in the biomedical field with paper No. 578 beginning on 1/8/2022. In this article, he used 5,864 data of postprandial plasma glucose (PPG), fasting plasma glucose (FPG), carbohydrates and sugar intake amounts (carbs), and post-meal walking steps (steps) collected from a continuous glucose monitoring (CGM) sensor device over 4 years from 5/8/2018 to 5/13/2022.