Evidence of a Role for the Lateral Hypothalamic Area Juxtadorsomedial Region (LHAjd) in Defensive Behaviors Associated with Social Defeat

Our understanding of the extrinsic connections of the lateral hypothalamic area (LHA) has deepened in recent years. In particular, a series of studies using neural pathway-tracing methods to investigate the macroconnections of histologically differentiated LHA regions, have revealed that the neural connections of these regions are substantially distinct, and have robust connections with neural circuits controlling survival behaviors. To begin testing functional associations suggested by the distinct LHA region neural connections, the present study has investigated the role of the LHA juxtadorsomedial region (LHAjd) in the control of social defeat (a socially-relevant defensive behavior). Male rats received bilateral cytotoxic lesions targeted to the LHAjd. A resident-intruder paradigm was then employed to investigate the effect of these lesions on defensive behavioral responses. Behavioral data were collected during three phases of testing: 1) pre-encounter habituation to testing context, 2) encounter with a dominant conspecific in the testing context, and 3) post-encounter context. Statistical analysis of behavioral measures revealed a significant decrease in risk assessment behaviors during post-encounter context testing in lesioned intruders compared to sham-lesioned and intact rats. However, changes in defensive behavioral measures during the habituation, or during resident-intruder encounters, did not reach significance. We discuss these data in relation to LHAjd (and neighboring LHA region) neural connections, and in relation to current advances in understanding of the neural control of defensive behaviors. A refined model for the neural circuits that are central to the control of socially-relevant defensive behaviors is outlined. We also consider possible broader implications of these data for disorders of behavioral control

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

BACKGROUND: Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. RESULTS: Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. CONCLUSION: This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases

Aerosol influences on low-level clouds in the West African monsoon

Low-level clouds (LLC) cover a wide area of southern West Africa (SWA) during the summer monsoon months, and have an important cooling effect on the regional climate. Previous studies of these clouds have focused on modelling and remote sensing via satellite. We present the first comprehensive set of regional, in situ measurements of cloud microphysics, taken during June – July 2016, as part of the DACCIWA (Dynamics-Aerosol-Chemistry-Clouds Interactions in West Africa) campaign, assessing spatial and temporal variation in the properties of these clouds. LLC developed overnight and mean cloud cover peaked a few hundred kilometres inland around 10:00 local solar time (LST), before clouds began to dissipate and convection intensified in the afternoon. Additional sea breeze clouds developed near the coast in the late morning, reaching a maximum extent around 12:00 LST. Regional variation in LLC cover was largely determined by the modulation of the cool maritime inflow by the local orography, with peaks on the upwind side of hills and minima on the leeward sides. In the broad-scale cloud field, no lasting impacts related to anthropogenic aerosol were observed downwind of major population centres. The boundary layer cloud drop number concentration (CDNC) was locally variable inland, ranging from 200 to 840 cm−3 (10th and 90th percentiles at standard temperature and pressure), but showed no systematic regional variations. Enhancements were seen in pollution plumes from the coastal cities, but were not statistically significant across the region. The majority of accumulation mode aerosols, and therefore cloud condensation nuclei, were from ubiquitous biomass burning smoke transported from the southern hemisphere. Consequently, all clouds measured (inland and offshore) had significantly higher CDNC and lower effective radius than clouds over the remote south Atlantic from literature. A parcel model sensitivity analysis showed that doubling or halving local emissions only changed the calculated CDNC by 13–22 %, as the high background meant local emissions were a small fraction of total aerosol. As the population of SWA grows, local emissions are expected to rise. Biomass burning smoke transported from the southern hemisphere is likely to dampen any effect of these increased local emissions on cloud-aerosol interactions. An integrative analysis between local pollution and Central African biomass burning emissions must be considered when predicting anthropogenic impacts on the regional cloud field during the West African monsoon

The Response of Vocal Fold Fibroblasts and Mesenchymal Stromal Cells to Vibration

Illumination of cellular changes caused by mechanical forces present within the laryngeal microenvironment may well guide strategies for tissue engineering the vocal fold lamina propria. The purpose of this study was to compare the response of human vocal fold fibroblasts (hVFF) and bone marrow mesenchymal stem cells (BM-MSC) to vibratory stimulus. In order to study these effects, a bioreactor capable of vibrating two cell seeded substrates was developed. The cell seeded substrates contact each other as a result of the sinusoidal frequency, producing a motion similar to the movement of true vocal folds. Utilizing this bioreactor, hVFF and BM-MSC were subjected to 200 Hz vibration and 20% strain for 8 hours. Immunohistochemistry (Ki-67 and TUNEL) was performed to examine cell proliferation and apoptosis respectively, while semi-quantitative RT-PCR was used to assess extracellular matrix related gene expression. HVFF significantly proliferated (p = 0.011) when subjected to 200 Hz vibration and 20% strain, while BM-MSC did not (p = 1.0). A statistically significant increase in apoptosis of BM-MSC (p = 0.0402) was observed under the experimental conditions; however high cell viability (96%) was maintained. HVFF did not have significantly altered apoptosis (p = 0.7849) when subjected to vibration and strain. Semi-quantitative RT-PCR results show no significant differences in expression levels of collagen I (BM-MSC p = 0.1951, hVFF p = v0.3629), fibronectin (BM-MSC p = 0.1951, hVFF p = 0.2513), and TGF-β1 (BM-MSC p = 0.2534, hVFF p = 0.6029) between vibratory and static conditions in either cell type. Finally, smooth muscle actin mRNA was not present in either vibrated or static samples, indicating that no myofibroblast differentiation occurred for either cell type. Together, these results demonstrate that BM-MSC may be a suitable alternative to hVFF for vocal fold tissue engineering. Further investigation into a larger number of gene markers, protein levels, increased number of donors and vibratory conditions are warranted

Inflation and Dark Energy from spectroscopy at z > 2

The expansion of the Universe is understood to have accelerated during two epochs: in its very first moments during a period of Inflation and much more recently, at z < 1, when Dark Energy is hypothesized to drive cosmic acceleration. The undiscovered mechanisms behind these two epochs represent some of the most important open problems in fundamental physics. The large cosmological volume at 2 < z < 5, together with the ability to efficiently target high-$z$ galaxies with known techniques, enables large gains in the study of Inflation and Dark Energy. A future spectroscopic survey can test the Gaussianity of the initial conditions up to a factor of ~50 better than our current bounds, crossing the crucial theoretical threshold of $\sigma(f_{NL}^{\rm local})$ of order unity that separates single field and multi-field models. Simultaneously, it can measure the fraction of Dark Energy at the percent level up to $z = 5$, thus serving as an unprecedented test of the standard model and opening up a tremendous discovery space

Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples

Background: Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting. Methodology: We developed and implemented an optimized mutation profiling platform (“OncoMap”) to interrogate ∼400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact. Conclusions: Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of “actionable” cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents

\u3ci\u3eFundulus\u3c/i\u3e as the premier teleost model in environmental biology: Opportunities for new insights using genomics

A strong foundation of basic and applied research documents that the estuarine fish Fundulus heteroclitus and related species are unique laboratory and field models for understanding how individuals and populations interact with their environment. In this paper we summarize an extensive body of work examining the adaptive responses of Fundulus species to environmental conditions, and describe how this research has contributed importantly to our understanding of physiology, gene regulation, toxicology, and ecological and evolutionary genetics of teleosts and other vertebrates. These explorations have reached a critical juncture at which advancement is hindered by the lack of genomic resources for these species. We suggest that a more complete genomics toolbox for F. heteroclitus and related species will permit researchers to exploit the power of this model organism to rapidly advance our understanding of fundamental biological and pathological mechanisms among vertebrates, as well as ecological strategies and evolutionary processes common to all living organisms

Impact of Simian Immunodeficiency Virus Infection on Chimpanzee Population Dynamics

Like human immunodeficiency virus type 1 (HIV-1), simian immunodeficiency virus of chimpanzees (SIVcpz) can cause CD4+ T cell loss and premature death. Here, we used molecular surveillance tools and mathematical modeling to estimate the impact of SIVcpz infection on chimpanzee population dynamics. Habituated (Mitumba and Kasekela) and non-habituated (Kalande) chimpanzees were studied in Gombe National Park, Tanzania. Ape population sizes were determined from demographic records (Mitumba and Kasekela) or individual sightings and genotyping (Kalande), while SIVcpz prevalence rates were monitored using non-invasive methods. Between 2002–2009, the Mitumba and Kasekela communities experienced mean annual growth rates of 1.9% and 2.4%, respectively, while Kalande chimpanzees suffered a significant decline, with a mean growth rate of −6.5% to −7.4%, depending on population estimates. A rapid decline in Kalande was first noted in the 1990s and originally attributed to poaching and reduced food sources. However, between 2002–2009, we found a mean SIVcpz prevalence in Kalande of 46.1%, which was almost four times higher than the prevalence in Mitumba (12.7%) and Kasekela (12.1%). To explore whether SIVcpz contributed to the Kalande decline, we used empirically determined SIVcpz transmission probabilities as well as chimpanzee mortality, mating and migration data to model the effect of viral pathogenicity on chimpanzee population growth. Deterministic calculations indicated that a prevalence of greater than 3.4% would result in negative growth and eventual population extinction, even using conservative mortality estimates. However, stochastic models revealed that in representative populations, SIVcpz, and not its host species, frequently went extinct. High SIVcpz transmission probability and excess mortality reduced population persistence, while intercommunity migration often rescued infected communities, even when immigrating females had a chance of being SIVcpz infected. Together, these results suggest that the decline of the Kalande community was caused, at least in part, by high levels of SIVcpz infection. However, population extinction is not an inevitable consequence of SIVcpz infection, but depends on additional variables, such as migration, that promote survival. These findings are consistent with the uneven distribution of SIVcpz throughout central Africa and explain how chimpanzees in Gombe and elsewhere can be at equipoise with this pathogen

Association of genetic variants in complement factor H and factor H-related genes with systemic lupus erythematosus susceptibility

Systemic lupus erythematosus (SLE), a complex polygenic autoimmune disease, is associated with increased complement activation. Variants of genes encoding complement regulator factor H (CFH) and five CFH-related proteins (CFHR1-CFHR5) within the chromosome 1q32 locus linked to SLE, have been associated with multiple human diseases and may contribute to dysregulated complement activation predisposing to SLE. We assessed 60 SNPs covering the CFH-CFHRs region for association with SLE in 15,864 case-control subjects derived from four ethnic groups. Significant allelic associations with SLE were detected in European Americans (EA) and African Americans (AA), which could be attributed to an intronic CFH SNP (rs6677604, in intron 11, Pmeta = 6.6×10-8, OR = 1.18) and an intergenic SNP between CFHR1 and CFHR4 (rs16840639, Pmeta = 2.9×10-7, OR = 1.17) rather than to previously identified disease-associated CFH exonic SNPs, including I62V, Y402H, A474A, and D936E. In addition, allelic association of rs6677604 with SLE was subsequently confirmed in Asians (AS). Haplotype analysis revealed that the underlying causal variant, tagged by rs6677604 and rs16840639, was localized to a ~146 kb block extending from intron 9 of CFH to downstream of CFHR1. Within this block, the deletion of CFHR3 and CFHR1 (CFHR3-1Δ), a likely causal variant measured using multiplex ligation-dependent probe amplification, was tagged by rs6677604 in EA and AS and rs16840639 in AA, respectively. Deduced from genotypic associations of tag SNPs in EA, AA, and AS, homozygous deletion of CFHR3-1Δ (Pmeta = 3.2×10-7, OR = 1.47) conferred a higher risk of SLE than heterozygous deletion (Pmeta = 3.5×10-4, OR = 1.14). These results suggested that the CFHR3-1Δ deletion within the SLE-associated block, but not the previously described exonic SNPs of CFH, might contribute to the development of SLE in EA, AA, and AS, providing new insights into the role of complement regulators in the pathogenesis of SLE