Sexual Selection and the Evolution of Brain Size in Primates

Reproductive competition among males has long been considered a powerful force in the evolution of primates. The evolution of brain size and complexity in the Order Primates has been widely regarded as the hallmark of primate evolutionary history. Despite their importance to our understanding of primate evolution, the relationship between sexual selection and the evolutionary development of brain size is not well studied. The present research examines the evolutionary relationship between brain size and two components of primate sexual selection, sperm competition and male competition for mates. Results indicate that there is not a significant relationship between relative brain size and sperm competition as measured by relative testis size in primates, suggesting sperm competition has not played an important role in the evolution of brain size in the primate order. There is, however, a significant negative evolutionary relationship between relative brain size and the level of male competition for mates. The present study shows that the largest relative brain sizes among primate species are associated with monogamous mating systems, suggesting primate monogamy may require greater social acuity and abilities of deception

Deep diversification of an AAV capsid protein by machine learning.

Modern experimental technologies can assay large numbers of biological sequences, but engineered protein libraries rarely exceed the sequence diversity of natural protein families. Machine learning (ML) models trained directly on experimental data without biophysical modeling provide one route to accessing the full potential diversity of engineered proteins. Here we apply deep learning to design highly diverse adeno-associated virus 2 (AAV2) capsid protein variants that remain viable for packaging of a DNA payload. Focusing on a 28-amino acid segment, we generated 201,426 variants of the AAV2 wild-type (WT) sequence yielding 110,689 viable engineered capsids, 57,348 of which surpass the average diversity of natural AAV serotype sequences, with 12-29 mutations across this region. Even when trained on limited data, deep neural network models accurately predict capsid viability across diverse variants. This approach unlocks vast areas of functional but previously unreachable sequence space, with many potential applications for the generation of improved viral vectors and protein therapeutics

Two new rapid SNP-typing methods for classifying Mycobacterium tuberculosis complex into the main phylogenetic lineages

There is increasing evidence that strain variation in Mycobacterium tuberculosis complex (MTBC) might influence the outcome of tuberculosis infection and disease. To assess genotype-phenotype associations, phylogenetically robust molecular markers and appropriate genotyping tools are required. Most current genotyping methods for MTBC are based on mobile or repetitive DNA elements. Because these elements are prone to convergent evolution, the corresponding genotyping techniques are suboptimal for phylogenetic studies and strain classification. By contrast, single nucleotide polymorphisms (SNP) are ideal markers for classifying MTBC into phylogenetic lineages, as they exhibit very low degrees of homoplasy. In this study, we developed two complementary SNP-based genotyping methods to classify strains into the six main human-associated lineages of MTBC, the 'Beijing' sublineage, and the clade comprising Mycobacterium bovis and Mycobacterium caprae. Phylogenetically informative SNPs were obtained from 22 MTBC whole-genome sequences. The first assay, referred to as MOL-PCR, is a ligation-dependent PCR with signal detection by fluorescent microspheres and a Luminex flow cytometer, which simultaneously interrogates eight SNPs. The second assay is based on six individual TaqMan real-time PCR assays for singleplex SNP-typing. We compared MOL-PCR and TaqMan results in two panels of clinical MTBC isolates. Both methods agreed fully when assigning 36 well-characterized strains into the main phylogenetic lineages. The sensitivity in allele-calling was 98.6% and 98.8% for MOL-PCR and TaqMan, respectively. Typing of an additional panel of 78 unknown clinical isolates revealed 99.2% and 100% sensitivity in allele-calling, respectively, and 100% agreement in lineage assignment between both methods. While MOL-PCR and TaqMan are both highly sensitive and specific, MOL-PCR is ideal for classification of isolates with no previous information, whereas TaqMan is faster for confirmation. Furthermore, both methods are rapid, flexible and comparably inexpensive

Bioavailability in soils

The consumption of locally-produced vegetables by humans may be an important exposure pathway for soil contaminants in many urban settings and for agricultural land use. Hence, prediction of metal and metalloid uptake by vegetables from contaminated soils is an important part of the Human Health Risk Assessment procedure. The behaviour of metals (cadmium, chromium, cobalt, copper, mercury, molybdenum, nickel, lead and zinc) and metalloids (arsenic, boron and selenium) in contaminated soils depends to a large extent on the intrinsic charge, valence and speciation of the contaminant ion, and soil properties such as pH, redox status and contents of clay and/or organic matter. However, chemistry and behaviour of the contaminant in soil alone cannot predict soil-to-plant transfer. Root uptake, root selectivity, ion interactions, rhizosphere processes, leaf uptake from the atmosphere, and plant partitioning are important processes that ultimately govern the accumulation ofmetals and metalloids in edible vegetable tissues. Mechanistic models to accurately describe all these processes have not yet been developed, let alone validated under field conditions. Hence, to estimate risks by vegetable consumption, empirical models have been used to correlate concentrations of metals and metalloids in contaminated soils, soil physico-chemical characteristics, and concentrations of elements in vegetable tissues. These models should only be used within the bounds of their calibration, and often need to be re-calibrated or validated using local soil and environmental conditions on a regional or site-specific basis.Mike J. McLaughlin, Erik Smolders, Fien Degryse, and Rene Rietr

Multiple Determinants of Whole and Regional Brain Volume among Terrestrial Carnivorans

Mammalian brain volumes vary considerably, even after controlling for body size. Although several hypotheses have been proposed to explain this variation, most research in mammals on the evolution of encephalization has focused on primates, leaving the generality of these explanations uncertain. Furthermore, much research still addresses only one hypothesis at a time, despite the demonstrated importance of considering multiple factors simultaneously. We used phylogenetic comparative methods to investigate simultaneously the importance of several factors previously hypothesized to be important in neural evolution among mammalian carnivores, including social complexity, forelimb use, home range size, diet, life history, phylogeny, and recent evolutionary changes in body size. We also tested hypotheses suggesting roles for these variables in determining the relative volume of four brain regions measured using computed tomography. Our data suggest that, in contrast to brain size in primates, carnivoran brain size may lag behind body size over evolutionary time. Moreover, carnivore species that primarily consume vertebrates have the largest brains. Although we found no support for a role of social complexity in overall encephalization, relative cerebrum volume correlated positively with sociality. Finally, our results support negative relationships among different brain regions after accounting for overall endocranial volume, suggesting that increased size of one brain regions is often accompanied by reduced size in other regions rather than overall brain expansion

Lessons Learned Developing a Diagnostic Tool for HIV-Associated Dementia Feasible to Implement in Resource-Limited Settings: Pilot Testing in Kenya

Objective: To conduct a preliminary evaluation of the utility and reliability of a diagnostic tool for HIV-associated dementia (HAD) for use by primary health care workers (HCW) which would be feasible to implement in resource-limited settings. Background: In resource-limited settings, HAD is an indication for anti-retroviral therapy regardless of CD4 T-cell count. Anti-retroviral therapy, the treatment for HAD, is now increasingly available in resource-limited settings. Nonetheless, HAD remains under-diagnosed likely because of limited clinical expertise and availability of diagnostic tests. Thus, a simple diagnostic tool which is practical to implement in resource-limited settings is an urgent need. Methods: A convenience sample of 30 HIV-infected outpatients was enrolled in Western Kenya. We assessed the sensitivity and specificity of a diagnostic tool for HAD as administered by a primary HCW. This was compared to an expert clinical assessment which included examination by a physician, neuropsychological testing, and in selected cases, brain imaging. Agreement between HCW and an expert examiner on certain tool components was measured using Kappa statistic. Results: The sample was 57 % male, mean age was 38.6 years, mean CD4 T-cell count was 323 cells/mL, and 54 % had less than a secondary school education. Six (20%) of the subjects were diagnosed with HAD by expert clinical assessment. The diagnostic tool was 63 % sensitive and 67 % specific for HAD. Agreement between HCW and expert examiners was poor for many individual items of the diagnostic tool (K =.03–.65). This diagnostic tool had moderate sensitivity and specificity fo

Key stages in mammary gland development: The cues that regulate ductal branching morphogenesis

Part of how the mammary gland fulfills its function of producing and delivering adequate amounts of milk is by forming an extensive tree-like network of branched ducts from a rudimentary epithelial bud. This process, termed branching morphogenesis, begins in fetal development, pauses after birth, resumes in response to estrogens at puberty, and is refined in response to cyclic ovarian stimulation once the margins of the mammary fat pad are met. Thus it is driven by systemic hormonal stimuli that elicit local paracrine interactions between the developing epithelial ducts and their adjacent embryonic mesenchyme or postnatal stroma. This local cellular cross-talk, in turn, orchestrates the tissue remodeling that ultimately produces a mature ductal tree. Although the precise mechanisms are still unclear, our understanding of branching in the mammary gland and elsewhere is rapidly improving. Moreover, many of these mechanisms are hijacked, bypassed, or corrupted during the development and progression of cancer. Thus a clearer understanding of the underlying endocrine and paracrine pathways that regulate mammary branching may shed light on how they contribute to cancer and how their ill effects might be overcome or entirely avoided

Relationship between Exercise Capacity and Brain Size in Mammals

A great deal of experimental research supports strong associations between exercise, cognition, neurogenesis and neuroprotection in mammals. Much of this work has focused on neurogenesis in individual subjects in a limited number of species. However, no study to date has examined the relationship between exercise and neurobiology across a wide range of mammalian taxa. It is possible that exercise and neurobiology are related across evolutionary time. To test this hypothesis, this study examines the association between exercise and brain size across a wide range of mammals.Controlling for associations with body size, we examined the correlation between brain size and a proxy for exercise frequency and capacity, maximum metabolic rate (MMR; ml O(2) min(-1)). We collected brain sizes and MMRs from the literature and calculated residuals from the least-squares regression line describing the relationship between body mass and each variable of interest. We then analyzed the correlation between residual brain size and residual MMR both before and after controlling for phylogeny using phylogenetic independent contrasts. We found a significant positive correlation between maximum metabolic rate and brain size across a wide range of taxa.These results suggest a novel hypothesis that links brain size to the evolution of locomotor behaviors in a wide variety of mammalian species. In the end, we suggest that some portion of brain size in nonhuman mammals may have evolved in conjunction with increases in exercise capacity rather than solely in response to selection related to cognitive abilities