Shrink–swell index prediction through deep learning

Growing application of artificial intelligence in geotechnical engineering has been observed; however, its ability to predict the properties and nonlinear behaviour of reactive soil is currently not well considered. Although previous studies provided linear correlations between shrink–swell index and Atterberg limits, obtained model accuracy values were found unsatisfactory results. Artificial intelligence, specifically deep learning, has the potential to give improved accuracy. This research employed deep learning to predict more accurate values of shrink–swell indices, which explored two scenarios; Scenario 1 used the features liquid limit, plastic limit, plasticity index, and linear shrinkage, whilst Scenario 2 added the input feature, fines percentage passing through a 0.075-mm sieve (%fines). Findings indicated that the implementation of deep learning neural networks resulted in increased model measurement accuracy in Scenarios 1 and 2. The values of accuracy measured in this study were suggestively higher and have wider variance than most previous studies. Global sensitivity analyses were also conducted to investigate the influence of each input feature. These sensitivity analyses resulted in a range of predicted values within the variance of data in Scenario 2, with the %fines having the highest contribution to the variance of the shrink–swell index and a relevant interaction between linear shrinkage and %fines. The proposed model Scenario 2 was around 10–65% more accurate than the preceding models considered in this study, which can then be used to expeditiously estimate more accurate values of shrink–swell indices

Spatio-temporal Models of Lymphangiogenesis in Wound Healing

Several studies suggest that one possible cause of impaired wound healing is failed or insufficient lymphangiogenesis, that is the formation of new lymphatic capillaries. Although many mathematical models have been developed to describe the formation of blood capillaries (angiogenesis), very few have been proposed for the regeneration of the lymphatic network. Lymphangiogenesis is a markedly different process from angiogenesis, occurring at different times and in response to different chemical stimuli. Two main hypotheses have been proposed: 1) lymphatic capillaries sprout from existing interrupted ones at the edge of the wound in analogy to the blood angiogenesis case; 2) lymphatic endothelial cells first pool in the wound region following the lymph flow and then, once sufficiently populated, start to form a network. Here we present two PDE models describing lymphangiogenesis according to these two different hypotheses. Further, we include the effect of advection due to interstitial flow and lymph flow coming from open capillaries. The variables represent different cell densities and growth factor concentrations, and where possible the parameters are estimated from biological data. The models are then solved numerically and the results are compared with the available biological literature.Comment: 29 pages, 9 Figures, 6 Tables (39 figure files in total

Two Distinct Triatoma dimidiata (Latreille, 1811) Taxa Are Found in Sympatry in Guatemala and Mexico

Approximately 10 million people are infected with Trypanosoma cruzi, the causative agent of Chagas disease, which remains the most serious parasitic disease in the Americas. Most people are infected via triatomine vectors. Transmission has been largely halted in South America in areas with predominantly domestic vectors. However, one of the main Chagas vectors in Mesoamerica, Triatoma dimidiata, poses special challenges to control due to its diversity across its large geographic range (from Mexico into northern South America), and peridomestic and sylvatic populations that repopulate houses following pesticide treatment. Recent evidence suggests T. dimidiata may be a complex of species, perhaps including cryptic species; taxonomic ambiguity which confounds control. The nuclear sequence of the internal transcribed spacer 2 (ITS2) of the ribosomal DNA and the mitochondrial cytochrome b (mt cyt b) gene were used to analyze the taxonomy of T. dimidiata from southern Mexico throughout Central America. ITS2 sequence divides T. dimidiata into four taxa. The first three are found mostly localized to specific geographic regions with some overlap: (1) southern Mexico and Guatemala (Group 2); (2) Guatemala, Honduras, El Salvador, Nicaragua, and Costa Rica (Group 1A); (3) and Panama (Group 1B). We extend ITS2 Group 1A south into Costa Rica, Group 2 into southern Guatemala and show the first information on isolates in Belize, identifying Groups 2 and 3 in that country. The fourth group (Group 3), a potential cryptic species, is dispersed across parts of Mexico, Guatemala, and Belize. We show it exists in sympatry with other groups in Peten, Guatemala, and Yucatan, Mexico. Mitochondrial cyt b data supports this putative cryptic species in sympatry with others. However, unlike the clear distinction of the remaining groups by ITS2, the remaining groups are not separated by mt cyt b. This work contributes to an understanding of the taxonomy and population subdivision of T. dimidiata, essential for designing effective control strategies

Multiple Data Analyses and Statistical Approaches for Analyzing Data from Metagenomic Studies and Clinical Trials

Metagenomics, also known as environmental genomics, is the study of the genomic content of a sample of organisms (microbes) obtained from a common habitat. Metagenomics and other “omics” disciplines have captured the attention of researchers for several decades. The effect of microbes in our body is a relevant concern for health studies. There are plenty of studies using metagenomics which examine microorganisms that inhabit niches in the human body, sometimes causing disease, and are often correlated with multiple treatment conditions. No matter from which environment it comes, the analyses are often aimed at determining either the presence or absence of specific species of interest in a given metagenome or comparing the biological diversity and the functional activity of a wider range of microorganisms within their communities. The importance increases for comparison within different environments such as multiple patients with different conditions, multiple drugs, and multiple time points of same treatment or same patient. Thus, no matter how many hypotheses we have, we need a good understanding of genomics, bioinformatics, and statistics to work together to analyze and interpret these datasets in a meaningful way. This chapter provides an overview of different data analyses and statistical approaches (with example scenarios) to analyze metagenomics samples from different medical projects or clinical trials

Improving Cry8Ka toxin activity towards the cotton boll weevil (Anthonomus grandis)

<p>Abstract</p> <p>Background</p> <p>The cotton boll weevil (<it>Anthonomus grandis</it>) is a serious insect-pest in the Americas, particularly in Brazil. The use of chemical or biological insect control is not effective against the cotton boll weevil because of its endophytic life style. Therefore, the use of biotechnological tools to produce insect-resistant transgenic plants represents an important strategy to reduce the damage to cotton plants caused by the boll weevil. The present study focuses on the identification of novel molecules that show improved toxicity against the cotton boll weevil. <it>In vitro </it>directed molecular evolution through DNA shuffling and phage display screening was applied to enhance the insecticidal activity of variants of the Cry8Ka1 protein of <it>Bacillus thuringiensis</it>.</p> <p>Results</p> <p>Bioassays carried out with <it>A. grandis </it>larvae revealed that the LC₅₀of the screened mutant Cry8Ka5 toxin was 3.15-fold higher than the wild-type Cry8Ka1 toxin. Homology modelling of Cry8Ka1 and the Cry8Ka5 mutant suggested that both proteins retained the typical three-domain Cry family structure. The mutated residues were located mostly in loops and appeared unlikely to interfere with molecular stability.</p> <p>Conclusions</p> <p>The improved toxicity of the Cry8Ka5 mutant obtained in this study will allow the generation of a transgenic cotton event with improved potential to control <it>A. grandis</it>.</p

Coevolution between a Family of Parasite Virulence Effectors and a Class of LINE-1 Retrotransposons

Parasites are able to evolve rapidly and overcome host defense mechanisms, but the molecular basis of this adaptation is poorly understood. Powdery mildew fungi (Erysiphales, Ascomycota) are obligate biotrophic parasites infecting nearly 10,000 plant genera. They obtain their nutrients from host plants through specialized feeding structures known as haustoria. We previously identified the AVRk1 powdery mildew-specific gene family encoding effectors that contribute to the successful establishment of haustoria. Here, we report the extensive proliferation of the AVRk1 gene family throughout the genome of B. graminis, with sequences diverging in formae speciales adapted to infect different hosts. Also, importantly, we have discovered that the effectors have coevolved with a particular family of LINE-1 retrotransposons, named TE1a. The coevolution of these two entities indicates a mutual benefit to the association, which could ultimately contribute to parasite adaptation and success. We propose that the association would benefit 1) the powdery mildew fungus, by providing a mechanism for amplifying and diversifying effectors and 2) the associated retrotransposons, by providing a basis for their maintenance through selection in the fungal genome

The ITS1-5.8S-ITS2 Sequence Region in the Musaceae: Structure, Diversity and Use in Molecular Phylogeny

Genes coding for 45S ribosomal RNA are organized in tandem arrays of up to several thousand copies and contain 18S, 5.8S and 26S rRNA units separated by internal transcribed spacers ITS1 and ITS2. While the rRNA units are evolutionary conserved, ITS show high level of interspecific divergence and have been used frequently in genetic diversity and phylogenetic studies. In this work we report on the structure and diversity of the ITS region in 87 representatives of the family Musaceae. We provide the first detailed information on ITS sequence diversity in the genus Musa and describe the presence of more than one type of ITS sequence within individual species. Both Sanger sequencing of amplified ITS regions and whole genome 454 sequencing lead to similar phylogenetic inferences. We show that it is necessary to identify putative pseudogenic ITS sequences, which may have negative effect on phylogenetic reconstruction at lower taxonomic levels. Phylogenetic reconstruction based on ITS sequence showed that the genus Musa is divided into two distinct clades – Callimusa and Australimusa and Eumusa and Rhodochlamys. Most of the intraspecific banana hybrids analyzed contain conserved parental ITS sequences, indicating incomplete concerted evolution of rDNA loci. Independent evolution of parental rDNA in hybrids enables determination of genomic constitution of hybrids using ITS. The observation of only one type of ITS sequence in some of the presumed interspecific hybrid clones warrants further study to confirm their hybrid origin and to unravel processes leading to evolution of their genomes