ABSTRACT
@#Following the quantum theory-based physical model of the human body, a new interpretation of the traditional Chinese medicine (TCM) principle of “Cunkou reads viscera” is presented. Then, a Gaussian pulse wave model as a solution to the Schrodinger equation is shown to accurately describe 19 different pulse shapes, and to quantitatively capture the degree of Yin-Yang attributes of 13 pulse shapes. Furthermore, the model suggests using pulse depth and strength as leading-order quantity and pulse shape as first-order quantity, to characterize the hierarchical resonance between the human body and the environment. The future pulse informatics will focus on determining an individual’s unique quantum human equilibrium state, and diagnose its health state according to the pulse deviation from its equilibrium state, to truly achieve the high level of TCM: “knowing the normal state and reaching the change”.
ABSTRACT
@#In the study, a quantum resonant cavity model based on wave-particle duality was proposed for the explanation of the dynamic processes of essence, vigor, and spirit in the human body in traditional Chinese medicine (TCM). It is assumed that there is a macro human order parameter (wave function), and its dynamics are governed by a macro potential field reflecting influences from heaven, earth, and society, and satisfy the generalized Schrodinger equation. This proposed model was applied in the study to interpret basic concepts of human body in TCM, with an aim to unfold the TCM development in the future.
ABSTRACT
Accurate prediction of the translation initiation site (TIS) is an important issue for prokaryotic genome annotation. However, it is still a challenge for the existing methods to predict the TIS in the genomes over a wide variety of GC content. Besides, the existing methods have not yet undergone a comprehensive evaluation, leaving prediction reliability as a largely open problem. A new algorithm MED-StartPlus, a tool that predicts TIS in prokaryotic genomes with a wide variety of GC content was presented. It makes several efforts to model the nucleotide composition bias, the regulatory motifs upstream of the TIS, the sequence patterns around the TIS, and the operon structure. Tests on hundreds of reliable data sets, with TISs confirmed by experiments or having annotated functions, show that the new method achieves a totally high accuracy of TIS prediction. Compared with existing TIS predictors, the method reports a totally higher performance, especially for genomes that are GC-rich or have complex initiation mechanisms. The potential application of the method to improve the TIS annotation deposited in the public database was also proposed.