Possible Impact of Global Warming on the Evolution of Hemagglutinins from Influenza A Viruses

Objective To determine if global warming has an impact on the evolution of hemagglutinins from influenza A viruses, because both global warming and influenza pandemics/epidemics threaten the world. Methods 4 706 hemagglutinins from influenza A viruses sampled from 1956 to 2009 were converted to a time‐series to show their evolutionary process and compared with the global, northern hemisphere and southern hemisphere temperatures, to determine if their trends run in similar or opposite directions. Point‐to‐point comparisons between temperature and quantified hemagglutinins were performed for all species and for the major prevailing species. Results The comparisons show that the trends for both hemagglutinin evolution and temperature change run in a similar direction. Conclusion Global warming has a consistent and progressive impact on the hemagglutinin evolution of influenza A viruses.

Prediction of mutation position, mutated amino acid and timing in hemagglutinins from North America H1 influenza A virus

This study was trying to predict the mutations in H1 hemagglutinins of influenza A virus from North America including the predictions of mu-tation position, the predictions of would-be-mutated amino acids and the predictions of time of occurrence of mutations. The results paved a possible way for accurate, precise and reliable prediction of mutation in proteins from influenza A virus.

Determination of inter- and intra-subtype/species varia-tions in polymerase acidic protein from influenza A virus using amino-acid pair predictability

The polymerase acidic protein is an important family of proteins from influenza A virus, which is classified as many different subtypes or spe-cies. Thus, an important question is if these classifications are numerically distinguishable with respect to the polymerase acidic protein. The amino-acid pair predictability was used to transfer 2432 polymerase acidic proteins into 2432 scalar data. The one-way ANOVA found these polymerase acidic proteins distinguish-able in terms of subtypes and species. However, the large residuals in ANOVA suggested a pos-sible large intra-subtype/species variation. Therefore, the inter- and intra-subtype/species variations were studied using the model II ANOVA. The results showed that the in-tra-subtype/species variations accounted most of variation, which was 100% in total for both inter- and intra- subtype/species variations. Our analysis threw lights on the issue of how to de-termine a wide variety of patterns of antigenic variation across space and time, and within and between subtypes as well as hosts.

Descriptively probabilistic relationship between mutated primary structure of von Hippel-Lindau protein and its clinical outcome

In this study, we use the cross-impact analysis to build a descriptively probabilistic relationship between mutant von Hippel-Lindau protein and its clinical outcome after quantifying mutant von Hippel-Lindau proteins with the amino-acid distribution probability, then we use the Bayes-ian equation to determine the probability that the von Hippel-Lindau disease occurs under a mutation, and finally we attempt to distinguish the classifications of clinical outcomes as well as the endocrine and nonendocrine neoplasia induced by mutations of von Hippel-Lindau protein. The results show that a patient has 9/10 chance of being von Hippel-Lindau disease when a new mutation occurs in von Hippel- Lindau protein, the possible distinguishing of classifications of clinical outcomes using mod-eling, and the explanation of the endocrine and nonendocrine neoplasia in modeling view.

Fitting of precipitation in 49 European capitals from 1901 to 1998 using random walk

Mathematical modeling of precipitation is an important step to understand the precipitation patterns, and paves the way to possibly predict the precipitation. In this study, we attempt to use the random walk model to fit the annual precipitation in 49 European capitals from 1901 to 1998. At first, we used the simplest random walk model to fit the precipitation walk, which is the conversion of recorded precipitations into ±1 format, and then we used a more complex random walk model to fit the recorded precipi-tations. The results show that the random walk models can fit both precipitation walk and re-corded precipitation. Thus this study provides a model to describe the precipitation patterns during this period in these cities.