Geographical distribution of Batrachospermaceae genera in Asia and its environmental factors

Batrachospermaceae is an important group of freshwater red algae.Available data of the latitude,longitude,and environmental factors on Batrachospermaceae distribution in Asia were analyzed to understand the geographical distribution of Batrachospermaceae genera in Asia.Statistical analyses,including one-way ANOVA,correlation analysis,stepwise regression analysis,principal component analysis,and linear discriminant analysis were conducted to characterize variation in geographical distribution and growth environment.Results reveal high variation in geographical distribution and growth environment among different Batrachospermaceae genera in Asia.Specifically,correlations between latitude and all environmental factors exclusive of altitude are significant,and longitude is significantly correlated with all environmental factors except for average relative humidity.The geographical distribution and growth environment of different Batrachospermaceae genera significantly differed.Altitude,maximum temperature,average temperature,minimum temperature,average relative humidity,average wind speed,maximum wind speed,and atmospheric pressure all contributed to explaining differences in the geographical distribution of Batrachospermaceae genera.Combining the results of correlation analysis,stepwise regression analysis,and principal component analysis,all environmental factors contributed to the different geographical distribution of Batrachospermum,Paludicola,Sheathia,Sirodotia,and Remainder(the rest),all environmental factors but atmospheric pressure contributed to the different geographical distribution of Kumanoa,and all environmental factors but average wind speed and maximum wind speed contributed to the different geographical distribution of Virescentia.However,the correlation between these significantly related environmental factors and taxa is not necessarily causative,and many other environmental factors,such as temperature,pH,conductivity,shading,current velocity,dissolved oxygen,hardness,substrata types,and nutrients etc.,are likely to have an important impact on the geographical distribution of taxa,which is an important topic for future research.

Authentication based on feature of hand-written signature

The typical features of the coordinate and the curvature as well as the recorded time information were analyzed in the hand-written signatures.In the hand-written signature process 10 biometric features were summarized:the amount of zero speed in direction x and direction y,the amount of zero acceleration in direction x and direction y,the total time of the hand-written signatures,the total distance of the pen traveling in the hand-written process,the frequency for lifting the pen,the time for lifting the pen,the amount of the pressure higher or lower than the threshold values.The formulae of biometric features extraction were summarized.The Gauss function was used to draw the typical information from the above-mentioned biometric features,with which to establish the hidden Markov mode and to train it.The frame of double authentication was proposed by combing the signature with the digital signature.Web service technology was applied in the system to ensure the security of data transmission.The training practice indicates that the hand-written signature verification can satisfy the needs from the office automation systems.

Identification of Significant Genes and Pathways Related to Lung Cancer via Statistical Methods

Cancer genomic research is a relatively new method. It has shown great potential but faces certain challenges. Researchers often have to deal with tens of thousands of genes with a relatively small sample size of patient cases—a dilemma referred to as the “Curse of Dimensionality” [1]—and it makes it hard to learn the data well because of relatively sparse data in high dimensional space. To deal with the dilemma, this study uses p-values of individual genes for pathway enrichment to find statistically significant pathways. The aim of this study is to find significant genes and biological pathways that are related to lung cancer by statistical method and pathway enrichment analysis. Several significant genes, such as WNT2B, VAV2, and significant pathways, such as Metabolism of xenobiotics by cytochrome P450-Homo sapiens (human) and Fatty acid degradation-Homo sapiens (human), are found to be both statistically significant and biological studies supported. Significant genes-including TESK2, C5orf43, and ZSCAN21—and significant pathways such as Pentose and glucoronate interconversions-Homo sapiens (human), are found to be new cancer-related genes and pathways that worth laboratory studies. The idea and method used in this research can be applied to find more significant genes and pathways that worth study experimentally.

Predictive power of statistical significance

A statistically significant research finding should not be defined as a P-value of 0.05 or less, because this definition does not take into account study power. Statistical significance was originally defined by Fisher RA as a P-value of 0.05 or less. According to Fisher, any finding that is likely to occur by random variation no more than 1 in 20 times is considered significant. Neyman J and Pearson ES subsequently argued that Fisher's definition was incomplete. They proposed that statistical significance could only be determined by analyzing the chance of incorrectly considering a study finding was significant(a Type Ⅰ?error) or incorrectly considering a study finding was insignificant(a Type Ⅱ error). Their definition of statistical significance is also incomplete because the error rates are considered separately, not together. A better definition of statistical significance is the positive predictive value of a P-value, which is equal to the power divided by the sum of power and the P-value. This definition is more complete and relevant than Fisher's or Neyman-Peason's definitions, because it takes into account both concepts of statistical significance. Using this definition, a statistically significant finding requires a P-value of 0.05 or less when the power is at least 95%, and a P-value of 0.032 or less when the power is 60%. To achieve statistical significance, P-values must be adjusted downward as the study power decreases.

AB090. MOG1, the genetic modifier at 20q13, delays the age-at-onset of glaucoma by 8 to 10 years

Background:Primary open-angle glaucoma(POAG)is a genetically complex disorder caused primarily by gene-gene interactions.To identify these interactions,we studied the CA family,a large French-Canadian pedigree in which the myocilin K423E mutation(MYOCK423E)causes autosomal dominant glaucoma with diagnoses ranging from juvenile-onset OAG(JOAG)to late adult-onset POAG in the heterozygotes(HTZ).To explain this extreme variability,we hypothesized that a second gene,called a modifier,was interacting with MYOC,the primary disease gene.Our goals were(I)to map the modifier on the human genome and;(II)to characterize the symptoms affected genetically by the modifier.These symptoms are called endophenotypes.Methods:Three hundred seventy-five CA members were studied using four quantitative endophenotypes:age of maximal intra-ocular pressures(IOPmax),IOPs progression,progression of cup to disk ratios and age-at-onset(AAO)defined as age at which ocular hypertension(OHT)was first detected with IOP≥22 mmHg.Genome-wide linkage analysis was performed by genotyping 408 genetic markers in 184 CA members.An unbiased pedigree-based algorithm was designed to identify the individuals who were double-mutants,i.e.,these individuals carried one MYOCK423E mutation(i.e.,they were HTZ,affected or not)and they also carry simultaneously a DNA mutation within the modifier.Results:Out of the 375 CA family members investigated,156 were HTZ for the MYOCK423E mutation.120 HTZ were affected with OAG or OHT with treatment while the remaining 36 HTZ were asymptomatic.AAO ranged from 7 to 63 years old;4 individuals over 50 years old were still asymptomatic.OHT preceded optic nerve damage in>98%of the HTZ carriers,confirming that AAO reflected the true severity of the disorder.The modifier showed strong inherited effects on 2 of the 4 endophenotypes:AAO and IOPmax.We next mapped with very high confidence the modifier locus for AAO at chromosome 20q13.Saturation genotyping with additional markers refined the locus to a 9 to 10 centimorgan interval,or about 10 million DNA nucleotides,between D20S857 and D20S832.The locus was named modifier of glaucoma 1(MOG1).When comparing the AAOs of the double mutants versus the median of the AAOs of the MYOCK423E HTZ who carried a wild-type(normal)MOG1 gene and were 1st cousins or closer with the double mutant under investigation,we observed that MOG1 delayed the ages at onset by an average of 8 to 10 years in the double mutants.Conclusions:The MOG1 locus encodes a DNA element that delays the onset of glaucoma by an average of 8-10 years by hampering the first manifestations of OHT.This research will lead to the development of new therapeutic targets for glaucoma.These treatments should prevent optic nerve damage by maintaining IOPs within the normal range.

Characterization of the Origin of Pollutants in Groundwater from Biostatistical Tests:The Case of Catchment Ehania,South-Eastern Cote d’Ivoire

The threat of agro-industrial exploitations on the quality of groundwater resources has become a major concern for the world’s population, mainly in agricultural areas. To solve this problem, several methods such as vulnerability to pollutants and statistics methods, have been adopted to protect these groundwaters. In this study, statistical tests were used to determine the likely source of pollutants in the groundwater resources. First, we made a comparative analysis and then analyzed pollutants parameters using Kohonen self-organizing map (SOM) which allows basic on the similarity to help out any correlation between the physic-chemical parameters. To validate these results, a land use map was developed to identify the sources of pollutants in production functions of different activities taking place on the catchment area. The results indicate very high levels of certain pollutants such as NO3-, Cl- and SO42- with generally higher than World Health Organization (WHO) standards values. These high levels observed could be attributed to the generally free nature of aquifers alteration and sedimentary formations in areas of high agro-industrial production. The analysis of the data from SOM method reveals a strong correlation between pollutants (NO3-, SO42-,Cl- ) and conductivity showing the likely origin of these surface pollutants,an origin that is linked to the existence of larges agro-industrials exploitations. These results are reinforced by those of the overlay map of the sampling sites on the land use map, which shows a strong coincidence between high values of pollutants and production areas of the pollutants that are agro-industrial exploitations. These areas of coincidence are observed in the north where found banana’s industrials plantations that are less visible and mostly in the southwest part where is one of the largest oil palm plantations in the world (36,000 hectares).

Predicting Arabidopsis Freezing Tolerance and Heterosis in Freezing Tolerance from Metabolite Composition

Heterosis, or hybrid vigor, is one of the most important tools in plant breeding and has previously been dem- onstrated for plant freezing tolerance. Freezing tolerance is an important trait because it can limit the geographical dis- tribution of plants and their agricultural yield. Plants from temperate climates increase in freezing tolerance during exposure to low, non-freezing temperatures in a process termed ＇cold acclimation＇. Metabolite profiling has indicated a major reprogramming of plant metabolism in the cold, but it has remained unclear in previous studies which of these changes are related to freezing tolerance. In the present study, we have used metabolic profiling to discover combinations of metabolites that predict freezing tolerance and its heterosis in Arabidopsis thaliana. We identified compatible solutes and, in particular, the pathway leading to raffinose as crucial statistical predictors for freezing tolerance and its heterosis, while some TCA cycle intermediates contribute only to predicting the heterotic phenotype. This indicates coordinate links between heterosis and metabolic pathways, suggesting that a limited number of regulatory genes may determine the extent of heterosis in this complex trait. In addition, several unidentified metabolites strongly contributed to the prediction of both freezing tolerance and its heterosis and we present an exemplary analysis of one of these, identifying it as a hexose conjugate.

Hypothesis testing and statistical analysis of microbiome

After the initiation of Human Microbiome Project in 2008,various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies.In this review and perspective,we discuss the research and statistical hypotheses in gut microbiome studies,focusing on mechanistic concepts that underlie the complex relationships among host,microbiome,and environment.We review the current available statistic tools and highlight recent progress of newly developed statistical methods and models.Given the current challenges and limitations in biostatistic approaches and tools,we discuss the future direction in developing statistical methods and models for the microbiome studies.

Identification of Lignin and Polysaccharide Modifications in Populus Wood by Chemometric Analysis of 2D NMR Spectra from Dissolved Cell Walls

2D ^13C-^1H HSQC NMR spectroscopy of acetylated cell walls in solution gives a detailed fingerprint that can be used to assess the chemical composition of the complete wall without extensive degradation. We demonstrate how multivariate analysis of such spectra can be used to visualize cell wall changes between sample types as high-resolution 2D NMR loading spectra. Changes in composition and structure for both lignin and polysaccharides can subsequently be interpreted on a molecular level. The multivariate approach alleviates problems associated with peak picking of overlapping peaks, and it allows the deduction of the relative importance of each peak for sample discrimination. As a first proof of concept, we compare Populus tension wood to normal wood. All well established differences in cellulose, hemicellulose, and lignin compositions between these wood types were readily detected, confirming the reliability of the multivariate approach, In a second example, wood from transgenic Populus modified in their degree of pectin methylesterification was compared to that of wild-type trees. We show that differences in both lignin and polysaccharide composition that are difficult to detect with traditional spectral analysis and that could not be a priori predicted were revealed by the multivariate approach. 2D NMR of dissolved cell wall samples combined with multivariate analysis constitutes a novel approach in cell wall analysis and provides a new tool that will benefit cell wall research.