ABSTRACT
Simulation and prediction of the scale change of fungal community. First, using the experimental data of a variety of fungal decomposition activities, a mathematical model of the decomposition rate and the relationship between the bacterial species was established, thereby revealing the internal mechanism of fungal decomposition activity in a complex environment. Second, based on the linear regression method and the principle of biodiversity, a model of fungal decomposition rate was constructed, and it was concluded that the interaction between mycelial elongation and moisture resistance could increase the fungal decomposition rate. Third, the differential equations are used to quantify the competitive relationship between different bacterial species, divide the boundaries of superior and inferior species, and simulate the long-term and short-term evolution trends of the community under the same initial environment. And an empirical analysis is made by taking the sudden change of the atmosphere affecting the evolution of the colony as an example. Finally, starting from summer, combining soil temperature, humidity, and fungal species data in five different environments such as arid and semiarid, a three-dimensional model and RBF neural network are introduced to predict community evolution. The study concluded that under given conditions, different strains are in short-term competition, and in the long-term, mutually beneficial symbiosis. Biodiversity is important for the biological regulation of nature.
Subject(s)
Biological Evolution , Mycobiome/genetics , Mycobiome/physiology , Neural Networks, Computer , Bacterial Physiological Phenomena , Biodiversity , Computational Biology , Ecosystem , Linear Models , Microbial Interactions , Models, Biological , Seasons , SymbiosisABSTRACT
OBJECTIVE: To investigate the significance of use of modification of diet in renal disease (MDRD) equation in calculating glomerular filtration rate (GFR) so as to estimate the prevalence of "renal insufficiency" in type 2 diabetes patients. METHODS: Serum creatinine (Scr) and 24h-urinary albumin excretion (24 h-UAE) were measured in 1576 hospitalized type 2 diabetes patients. MDRD equation was used to calculate the GFR (GFR(MDRD)). GFR(MDRD) < 60 ml/min per 1.73 m2 was defined as "renal insufficiency". RESULTS: (1) Of the 1576 subjects, 908 (57.6%), 503 (31.9%), and 165 (10.5%) had GFR(MDRD) > or =90, 90-60, and <60 ml/min per 1.73 m2 respectively. The prevalence of "renal insufficiency" was increased with aging (P < 0.01). (2) The prevalence rates of "renal insufficiency" of the normo-, micro-, and macroalbuminuric groups were 4.8%, 14.4%, and 43.4% respectively, with significant differences among them (all P < 0.01). (3) Of the 165 subjects with "renal insufficiency", 21 (12.7%) had neither abnormal Scr nor abnormal albuminuria. CONCLUSION: Able to discover renal insufficiency early, MDRD equation has important clinical significance in evaluating the progression of renal dysfunction in type 2 diabetes patients.