Zika virus infection in the developing mouse produces dramatically different neuropathology dependent on viral strain

Zika virus (ZIKV) infection during pregnancy has been causally linked to a constellation of neurodevelopmental deformities in the fetus resulting in a disease termed congenital Zika syndrome (CZS). Here we detail how ZIKV infection produces extensive neuropathology in the developing mouse brain and spinal cord of both sexes. Surprisingly, neuropathology differs depending on viral strain with a French Polynesian isolate producing primarily excitotoxicity and a Brazilian isolate being almost exclusively apoptotic but occurring over a prolonged period that is more likely to produce severe hypoplasia. We also show exposure can produce a characteristic pattern of infection that mirrors neuropathology and ultimately results in gross morphological deformities strikingly similar to CZS. This research provides a valuable mouse model mirroring the clinical course of disease that can be used to test potential therapies to improve treatment and gain a better understanding of the disabilities associated with CZS

Optimal model complexity for terrestrial carbon cycle prediction

The terrestrial carbon cycle plays a critical role in modulating the interactions of climate with the Earth system, but different models often make vastly different predictions of its behavior. Efforts to reduce model uncertainty have commonly focused on model structure, namely by introducing additional processes and increasing structural complexity. However, the extent to which increased structural complexity can directly improve predictive skill is unclear. While adding processes may improve realism, the resulting models are often encumbered by a greater number of poorly determined or over-generalized parameters. To guide efficient model development, here we map the theoretical relationship between model complexity and predictive skill. To do so, we developed 16 structurally distinct carbon cycle models spanning an axis of complexity and incorporated them into a model–data fusion system. We calibrated each model at six globally distributed eddy covariance sites with long observation time series and under 42 data scenarios that resulted in different degrees of parameter uncertainty. For each combination of site, data scenario, and model, we then predicted net ecosystem exchange (NEE) and leaf area index (LAI) for validation against independent local site data. Though the maximum model complexity we evaluated is lower than most traditional terrestrial biosphere models, the complexity range we explored provides universal insight into the inter-relationship between structural uncertainty, parametric uncertainty, and model forecast skill. Specifically, increased complexity only improves forecast skill if parameters are adequately informed (e.g., when NEE observations are used for calibration). Otherwise, increased complexity can degrade skill and an intermediate-complexity model is optimal. This finding remains consistent regardless of whether NEE or LAI is predicted. Our COMPLexity EXperiment (COMPLEX) highlights the importance of robust observation-based parameterization for land surface modeling and suggests that data characterizing net carbon fluxes will be key to improving decadal predictions of high-dimensional terrestrial biosphere models.</p

Treatment resistance NMDA receptor pathway polygenic score is associated with brain glutamate in schizophrenia

Dysfunction of glutamate neurotransmission has been implicated in the pathophysiology of schizophrenia and may be particularly relevant in severe, treatment-resistant symptoms. The underlying mechanism may involve hypofunction of the NMDA receptor. We investigated whether schizophrenia-related pathway polygenic scores, composed of genetic variants within NMDA receptor encoding genes, are associated with cortical glutamate in schizophrenia. Anterior cingulate cortex (ACC) glutamate was measured in 70 participants across 4 research sites using Proton Magnetic Resonance Spectroscopy (1H-MRS). Two NMDA receptor gene sets were sourced from the Molecular Signatories Database and NMDA receptor pathway polygenic scores were constructed using PRSet. The NMDA receptor pathway polygenic scores were weighted by single nucleotide polymorphism (SNP) associations with treatment-resistant schizophrenia, and associations with ACC glutamate were tested. We then tested whether NMDA receptor pathway polygenic scores with SNPs weighted by associations with non-treatment-resistant schizophrenia were associated with ACC glutamate. A higher NMDA receptor complex pathway polygenic score was significantly associated with lower ACC glutamate (β = −0.25, 95 % CI = −0.49, −0.02, competitive p = 0.03). When SNPs were weighted by associations with non-treatment-resistant schizophrenia, there was no association between the NMDA receptor complex pathway polygenic score and ACC glutamate (β = 0.05, 95 % CI = −0.18, 0.27, competitive p = 0.79). These results provide initial evidence of an association between common genetic variation implicated in NMDA receptor function and ACC glutamate levels in schizophrenia. This association was specific to when the NMDA receptor complex pathway polygenic score was weighted by SNP associations with treatment-resistant schizophrenia

Cancer-selective, single agent chemoradiosensitising gold nanoparticles

Two nanometre gold nanoparticles (AuNPs), bearing sugar moieties and/or thiol-polyethylene glycol-amine (PEG-amine), were synthesised and evaluated for their in vitro toxicity and ability to radiosensitise cells with 220 kV and 6 MV X-rays, using four cell lines representing normal and cancerous skin and breast tissues. Acute 3 h exposure of cells to AuNPs, bearing PEG-amine only or a 50:50 ratio of alpha-galactose derivative and PEG-amine resulted in selective uptake and toxicity towards cancer cells at unprecedentedly low nanomolar concentrations. Chemotoxicity was prevented by co-administration of N-acetyl cysteine antioxidant, or partially prevented by the caspase inhibitor Z-VAD-FMK. In addition to their intrinsic cancer-selective chemotoxicity, these AuNPs acted as radiosensitisers in combination with 220 kV or 6 MV X-rays. The ability of AuNPs bearing simple ligands to act as cancer-selective chemoradiosensitisers at low concentrations is a novel discovery that holds great promise in developing low-cost cancer nanotherapeutics

Phylogeography Unplugged: Comparative Surveys in the Genomic Era

In March 2012, the authors met at the National Evolutionary Synthesis Center (NESCent) in Durham, North Carolina, USA, to discuss approaches and cooperative ventures in Indo-Pacific phylogeography. The group emerged with a series of findings: (1) Marine population structure is complex, but single locus mtDNA studies continue to provide powerful first assessment of phylogeographic patterns. (2) These patterns gain greater significance/power when resolved in a diversity of taxa. New analytical tools are emerging to address these analyses with multi-taxon approaches. (3) Genome-wide analyses are warranted if selection is indicated by surveys of standard markers. Such indicators can include discordance between genetic loci, or between genetic loci and morphology. Phylogeographic information provides a valuable context for studies of selection and adaptation. (4) Phylogeographic inferences are greatly enhanced by an understanding of the biology and ecology of study organisms. (5) Thorough, range-wide sampling of taxa is the foundation for robust phylogeographic inference. (6) Congruent geographic and taxonomic sampling by the Indo-Pacific community of scientists would facilitate better comparative analyses. The group concluded that at this stage of technology and software development, judicious rather than wholesale application of genomics appears to be the most robust course for marine phylogeographic studies. Therefore, our group intends to affirm the value of traditional ( unplugged ) approaches, such as those based on mtDNA sequencing and microsatellites, along with essential field studies, in an era with increasing emphasis on genomic approaches