Effects of different prey and rearing densities on growth and survival of octopus maya hatchlings

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Effect of Defoliation Frequency on Forage Yield from Intensive Silvopastoral Systems Compared to a Monoculture Grassland

Livestock production in the tropical regions of the world faces serious constraints as a result of climate change. Monoculture based pastures require the use of large amounts of nitrogen fertilizers to sustain production throughout the year. In general terms, tropical grasses are of low quality and when consumed by ruminant species, contribute to the emission of greenhouse gases (methane, carbon dioxide and nitrous oxide) (Herrero et al. 2009; Place et al. 2009). The establishment of intensive silvopastoral systems (iSPS) with associated shrubs legumes and grasses can increase the yield and quality of forage as well as fixation and transfer of atmospheric nitrogen (N) (Murgueitio et al. 2011). Therefore, the costs of nitrogen fertilizers and the emissions of greenhouse gases under practical conditions can be reduced. The intensive silvopastoral system is a kind of agroforestal practice that it is environmentally friendly and at the same time improves productivity of livestock systems. However, several aspects of its management have not been fully evaluated. This is the case of the response to defoliation, which is an important management factor associated to the overall biomass productivity (Solorio 2005)

Cumulative signal transmission in nonlinear reaction-diffusion networks

Quantifying signal transmission in biochemical systems is key to uncover the mechanisms that cells use to control their responses to environmental stimuli. In this work we use the time-integral of chemical species as a measure of a network’s ability to cumulatively transmit signals encoded in spatiotemporal concentrations. We identify a class of nonlinear reaction-diffusion networks in which the time-integrals of some species can be computed analytically. The derived time-integrals do not require knowledge of the solution of the reaction-diffusion equation, and we provide a simple graphical test to check if a given network belongs to the proposed class. The formulae for the time-integrals reveal how the kinetic parameters shape signal transmission in a network under spatiotemporal stimuli. We use these to show that a canonical complex-formation mechanism behaves as a spatial low-pass filter, the bandwidth of which is inversely proportional to the diffusion length of the ligand

Case report: A familial B-acute lymphoblastic leukemia associated with a new germline pathogenic variant in PAX5. The first report in Mexico

B-cell acute lymphoblastic leukemia (B-ALL) is one of the most common childhood cancers worldwide. Although most cases are sporadic, some familial forms, inherited as autosomal dominant traits with incomplete penetrance, have been described over the last few years. Germline pathogenic variants in transcription factors such as PAX5, IKZF1, and ETV6 have been identified as causal in familial forms. The proband was a 7-year-old Mexican girl diagnosed with high-risk B-ALL at five years and 11 months of age. Family history showed that the proband’s mother had high-risk B-ALL at 16 months of age. She received chemotherapy and was discharged at nine years of age without any evidence of recurrence of leukemia. The proband’s father was outside the family nucleus, but no history of leukemia or cancer was present up to the last contact with the mother. We performed exome sequencing on the proband and the proband’s mother and identified the PAX5 variant NM_016734.3:c.963del: p.(Ala322LeufsTer11), located in the transactivation domain of the PAX5 protein. The variant was classified as probably pathogenic according to the ACMG criteria. To the best of our knowledge, this is the first Mexican family with an inherited increased risk of childhood B-ALL caused by a novel germline pathogenic variant of PAX5. Identifying individuals with a hereditary predisposition to cancer is essential for modern oncological practice. Individuals at high risk of leukemia would benefit from hematopoietic stem cell transplantation, but family members carrying the pathogenic variant should be excluded as hematopoietic stem cell donors

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin

Analysis of protein-coding genetic variation in 60,706 humans

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of truncating variants with 72% having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes