Spatiotemporal modeling of first and second wave outbreak dynamics of COVID-19 in Germany

The COVID-19 pandemic has kept the world in suspense for the past year. In most federal countries such as Germany, locally varying conditions demand for state- or county-level decisions to adapt to the disease dynamics. However, this requires a deep understanding of the mesoscale outbreak dynamics between microscale agent models and macroscale global models. Here, we use a reparameterized SIQRD network model that accounts for local political decisions to predict the spatiotemporal evolution of the pandemic in Germany at county resolution. Our optimized model reproduces state-wise cumulative infections and deaths as reported by the Robert Koch Institute and predicts the development for individual counties at convincing accuracy during both waves in spring and fall of 2020. We demonstrate the dominating effect of local infection seeds and identify effective measures to attenuate the rapid spread. Our model has great potential to support decision makers on a state and community politics level to individually strategize their best way forward during the months to come.

     

Activation of the replicative DNA helicase: breaking up is hard to do

The precise duplication of the eukaryotic genome is accomplished by carefully coordinating the loading and activation of the replicative DNA helicase so that each replication origin is unwound and assembles functional bi-directional replisomes just once in each cell cycle. The essential Minichromosome Maintenance 2-7 (Mcm2-7) proteins, comprising the core of the replicative DNA helicase, are first loaded at replication origins in an inactive form. The helicase is then activated by recruitment of the Cdc45 and GINS proteins into a holo-helicase known as CMG (Cdc45, Mcm2-7, GINS). These steps are regulated by multiple mechanisms to ensure that Mcm2-7 loading can only occur during G1 phase, whilst activation of Mcm2-7 cannot occur during G1 phase. Here we review recent progress in understanding these critical reactions focusing on the mechanism of helicase loading and activation.     

Complex Regional Pain Syndrome Type I Affects Brain Structure in Prefrontal and Motor Cortex

The complex regional pain syndrome (CRPS) is a rare but debilitating pain disorder that mostly occurs after injuries to the upper limb. A number of studies indicated altered brain function in CRPS, whereas possible influences on brain structure remain poorly investigated.We acquired structural magnetic resonance imaging data from CRPS type I patients and applied voxel-by-voxel statistics to compare white and gray matter brain segments of CRPS patients with matched controls. Patients and controls were statistically compared in two different ways: First, we applied a 2-sample ttest to compare whole brain white and gray matter structure between patients and controls. Second, we aimed to assess structural alterations specifically of the primary somatosensory (S1) and motor cortex (M1) contralateral to the CRPS affected side. To this end, MRI scans of patients with left-sided CRPS (and matched controls) were horizontally flipped before preprocessing and region-of-interest-based group comparison. The unpaired ttest of the “non-flipped” data revealed that CRPS patients presented increased gray matter density in the dorsomedial prefrontal cortex. The same test applied to the “flipped” data showed further increases in gray matter density, not in the S1, but in the M1 contralateral to the CRPS-affected limb which were inversely related to decreased white matter density of the internal capsule within the ipsilateral brain hemisphere. The gray-white matter interaction between motor cortex and internal capsule suggests compensatory mechanisms within the central motor system possibly due to motor dysfunction. Altered gray matter structure in dorsomedial prefrontal cortex may occur in response to emotional processes such as pain-related suffering or elevated analgesic top-down control.     

Large carbon release legacy from bark beetle outbreaks across Western United States

Warmer conditions over the past two decades have contributed to rapid expansion of bark beetle outbreaks killing millions of trees over a large fraction of western United States (US) forests. These outbreaks reduce plant productivity by killing trees and transfer carbon from live to dead pools where carbon is slowly emitted to the atmosphere via heterotrophic respiration which subsequently feeds back to climate change. Recent studies have begun to examine the local impacts of bark beetle outbreaks in individual stands, but the full regional carbon consequences remain undocumented for the western US. In this study, we quantify the regional carbon impacts of the bark beetle outbreaks taking place in western US forests. The work relies on a combination of postdisturbance forest regrowth trajectories derived from forest inventory data and a process‐based carbon cycle model tracking decomposition, as well as aerial detection survey (ADS) data documenting the regional extent and severity of recent outbreaks. We find that biomass killed by bark beetle attacks across beetle‐affected areas in western US forests from 2000 to 2009 ranges from 5 to 15 Tg C yr^?1 and caused a reduction of net ecosystem productivity (NEP) of about 6.1–9.3 Tg C y^?1 by 2009. Uncertainties result largely from a lack of detailed surveys of the extent and severity of outbreaks, calling out a need for improved characterization across western US forests. The carbon flux legacy of 2000–2009 outbreaks will continue decades into the future (e.g., 2040–2060) as committed emissions from heterotrophic respiration of beetle‐killed biomass are balanced by forest regrowth and accumulation.     

Parameters Influencing Baseline HIV-1 Genotypic Tropism Testing Related to Clinical Outcome in Patients on Maraviroc

ObjectivesWe analysed the impact of different parameters on genotypic tropism testing related to clinical outcome prediction in 108 patients on maraviroc (MVC) treatment.Methods87 RNA and 60 DNA samples were used. The viral tropism was predicted using the geno2pheno_[coreceptor] and T-CUP tools with FPR cut-offs ranging from 1%-20%. Additionally, 27 RNA and 28 DNA samples were analysed in triplicate, 43 samples with the ESTA assay and 45 with next-generation sequencing. The influence of the genotypic susceptibility score (GSS) and 16 MVC-resistance mutations on clinical outcome was also studied.ResultsConcordance between single-amplification testing compared to ESTA and to NGS was in the order of 80%. Concordance with NGS was higher at lower FPR cut-offs. Detection of baseline R5 viruses in RNA and DNA samples by all methods significantly correlated with treatment success, even with FPR cut-offs of 3.75%-7.5%. Triple amplification did not improve the prediction value but reduced the number of patients eligible for MVC. No influence of the GSS or MVC-resistance mutations but adherence to treatment, on the clinical outcome was detected.ConclusionsProviral DNA is valid to select candidates for MVC treatment. FPR cut-offs of 5%-7.5% and single amplification from RNA or DNA would assure a safe administration of MVC without excluding many patients who could benefit from this drug. In addition, the new prediction system T-CUP produced reliable results.     

A single nucleotide polymorphism on chromosome 10 is highly predictive for the polled phenotype in Australian Merino sheep

The aim of this study was to fine map the genomic location of the Horns locus in the Australian Merino sheep population and to identify markers that can be used to predict the horn phenotype. A linkage disequilibrium analysis of horn data from Australian Merino sheep mapped the Horns locus to a small region on chromosome 10. A single nucleotide polymorphism in the region was found to be highly predictive for the polled phenotype in an experimental population of Merino sheep. This was owing to a dominance effect of one of the alleles when inherited maternally. It was suggested that a genetic test would provide a good predictor of the polled phenotype. Finally, an evaluation of industry data showed that the SNP is at very different frequencies in Poll Merino sheep that have been bred for polledness (based on phenotype alone) compared with the Merino sheep breed.