Soil biochemistry and microbial activity in vineyards under conventional and organic management at Northeast Brazil.

The São Francisco Submedium Valley is located at the Brazilian semiarid region and is an important center for irrigated fruit growing. This region is responsible for 97% of the national exportation of table grapes, including seedless grapes. Based on the fact that orgThe São Francisco Submedium Valley is located at the Brazilian semiarid region and is an important center for irrigated fruit growing. This region is responsible for 97% of the national exportation of table grapes, including seedless grapes. Based on the fact that organic fertilization can improve soil quality, we compared the effects of conventional and organic soil management on microbial activity and mycorrhization of seedless grape crops. We measured glomerospores number, most probable number (MPN) of propagules, richness of arbuscular mycorrhizal fungi (AMF) species, AMF root colonization, EE-BRSP production, carbon microbial biomass (C-MB), microbial respiration, fluorescein diacetate hydrolytic activity (FDA) and metabolic coefficient (qCO2). The organic management led to an increase in all variables with the exception of EE-BRSP and qCO2. Mycorrhizal colonization increased from 4.7% in conventional crops to 15.9% in organic crops. Spore number ranged from 4.1 to 12.4 per 50 g-1 soil in both management systems. The most probable number of AMF propagules increased from 79 cm-3 soil in the conventional system to 110 cm-3 soil in the organic system. Microbial carbon, CO2 emission, and FDA activity were increased by 100 to 200% in the organic crop. Thirteen species of AMF were identified, the majority in the organic cultivation system. Acaulospora excavata, Entrophospora infrequens, Glomus sp.3 and Scutellospora sp. were found only in the organically managed crop. S. gregaria was found only in the conventional crop. Organically managed vineyards increased mycorrhization and general soil microbial activity

Highly Disordered Proteins in Prostate Cancer

Prostate cancer is one of the major threats to the man’s health. There are several mechanisms of the prostate cancer development characterized by the involvement of various androgen-related and androgen-unrelated factors in prostate cancer pathogenesis and in the metastatic carcinogenesis of prostate. In all these processes, proteins play various important roles, and the KEGG database has information on 88 human proteins experimentally shown to be involved in prostate cancer. It is known that many proteins associated with different human maladies are intrinsically disordered (i.e., they do not have stable secondary and/or tertiary structure in their unbound states). The goal of this review is to consider several highly disordered proteins known to be associated with the prostate cancer pathogenesis in order to better understand the roles of disordered proteins in this disease. We also hope that consideration of the pathology-related proteins from the perspective of intrinsic disorder can potentially lead to future experimental studies of these proteins to find novel pathways associated with prostate cancer

Highly Disordered Proteins in Prostate Cancer

Prostate cancer is one of the major threats to the man’s health. There are several mechanisms of the prostate cancer development characterized by the involvement of various androgen-related and androgen-unrelated factors in prostate cancer pathogenesis and in the metastatic carcinogenesis of prostate. In all these processes, proteins play various important roles, and the KEGG database has information on 88 human proteins experimentally shown to be involved in prostate cancer. It is known that many proteins associated with different human maladies are intrinsically disordered (i.e., they do not have stable secondary and/or tertiary structure in their unbound states). The goal of this review is to consider several highly disordered proteins known to be associated with the prostate cancer pathogenesis in order to better understand the roles of disordered proteins in this disease. We also hope that consideration of the pathology-related proteins from the perspective of intrinsic disorder can potentially lead to future experimental studies of these proteins to find novel pathways associated with prostate cancer

Unfoldomics of prostate cancer: on the abundance and roles of intrinsically disordered proteins in prostate cancer

Prostatic diseases such as prostate cancer and benign prostatic hyperplasia are highly prevalent among men. The number of studies focused on the abundance and roles of intrinsically disordered proteins in prostate cancer is rather limited. The goal of this study is to analyze the prevalence and degree of disorder in proteins that were previously associated with the prostate cancer pathogenesis and to compare these proteins to the entire human proteome. The analysis of these datasets provides means for drawing conclusions on the roles of disordered proteins in this common male disease. We also hope that the results of our analysis can potentially lead to future experimental studies of these proteins to find novel pathways associated with this disease

Hybrid Automata Library: A flexible platform for hybrid modeling with real-time visualization.

The Hybrid Automata Library (HAL) is a Java Library developed for use in mathematical oncology modeling. It is made of simple, efficient, generic components that can be used to model complex spatial systems. HAL's components can broadly be classified into: on- and off-lattice agent containers, finite difference diffusion fields, a GUI building system, and additional tools and utilities for computation and data collection. These components are designed to operate independently and are standardized to make them easy to interface with one another. As a demonstration of how modeling can be simplified using our approach, we have included a complete example of a hybrid model (a spatial model with interacting agent-based and PDE components). HAL is a useful asset for researchers who wish to build performant 1D, 2D and 3D hybrid models in Java, while not starting entirely from scratch. It is available on GitHub at https://github.com/MathOnco/HAL under the MIT License. HAL requires the Java JDK version 1.8 or later to compile and run the source code

Preprint: Evolutionary dynamics of neoantigens in growing tumours

Cancer evolution is driven by the acquisition of somatic mutations that provide cells with a beneficial phenotype in a changing microenvironment. However, mutations that give rise to neoantigens, novel cancer–specific peptides that elicit an immune response, are likely to be disadvantageous. Here we show how the clonal structure and immunogenotype of growing tumours is shaped by negative selection in response to neoantigenic mutations. We construct a mathematical model of neoantigen evolution in a growing tumour, and verify the model using genomic sequencing data. The model predicts that, in the absence of active immune escape mechanisms, tumours either evolve clonal neoantigens (antigen– ‘hot’), or have no clonally– expanded neoantigens at all (antigen– ‘cold’), whereas antigen– ‘warm’ tumours (with high frequency subclonal neoantigens) form only following the evolution of immune evasion. Counterintuitively, strong negative selection for neoantigens during tumour formation leads to an increased number of antigen– warm or – hot tumours, as a consequence of selective pressure for immune escape. Further, we show that the clone size distribution under negative selection is effectively– neutral, and moreover, that stronger negative selection paradoxically leads to more neutral– like dynamics. Analysis of antigen clone sizes and immune escape in colorectal cancer exome sequencing data confirms these results. Overall, we provide and verify a mathematical framework to understand the evolutionary dynamics and clonality of neoantigens in human cancers that may inform patient– specific immunotherapy decision– making

Preprint: Niche engineering drives early passage through an immune bottleneck in progression to colorectal cancer

Colorectal cancer develops from its precursor lesion, the adenoma. The immune system is hypothesized to be key in modulating progression, but tumor-immune eco-evolutionary dynamics remain uncharacterized. Here, we demonstrate a key role for immune evasion in the progression of human benign disease to colorectal cancer. We constructed a mathematical model of tumor-immune eco-evolutionary dynamics that predicted ecological succession, from an “immune-hot” adenoma immune ecology rich in T cells to an “immune-cold” carcinoma ecology, deficient in T cells and rich in immunosuppressive cells. Using a cross-sectional cohort of adenomas and carcinomas, we validated this prediction by direct measurement of the tumor-immune ecology using whole-slide 10-marker immunohistochemistry (IHC), and analysis of neoantigen clonal architecture multi-region exome sequencing data. Changes in immune ecology relax selection against antigens with high recognition potentials. This study indicates that immune surveillance represents a key evolutionary bottleneck in the evolution of colon cancer