Rib fracture after stereotactic radiotherapy on follow-up thin-section computed tomography in 177 primary lung cancer patients

<p>Abstract</p> <p>Background</p> <p>Chest wall injury after stereotactic radiotherapy (SRT) for primary lung cancer has recently been reported. However, its detailed imaging findings are not clarified. So this study aimed to fully characterize the findings on computed tomography (CT), appearance time and frequency of chest wall injury after stereotactic radiotherapy (SRT) for primary lung cancer</p> <p>Materials and methods</p> <p>A total of 177 patients who had undergone SRT were prospectively evaluated for periodical follow-up thin-section CT with special attention to chest wall injury. The time at which CT findings of chest wall injury appeared was assessed. Related clinical symptoms were also evaluated.</p> <p>Results</p> <p>Rib fracture was identified on follow-up CT in 41 patients (23.2%). Rib fractures appeared at a mean of 21.2 months after the completion of SRT (range, 4 -58 months). Chest wall edema, thinning of the cortex and osteosclerosis were findings frequently associated with, and tending to precede rib fractures. No patients with rib fracture showed tumors > 16 mm from the adjacent chest wall. Chest wall pain was seen in 18 of 177 patients (10.2%), of whom 14 patients developed rib fracture. No patients complained of Grade 3 or more symptoms.</p> <p>Conclusion</p> <p>Rib fracture is frequently seen after SRT for lung cancer on CT, and is often associated with chest wall edema, thinning of the cortex and osteosclerosis. However, related chest wall pain is less frequent and is generally mild if present.</p

Dosimetric evaluation of Acuros XB Advanced Dose Calculation algorithm in heterogeneous media

<p>Abstract</p> <p>Background</p> <p>A study was realised to evaluate and determine relative figures of merit of a new algorithm for photon dose calculation when applied to inhomogeneous media.</p> <p>Methods</p> <p>The new Acuros XB algorithm implemented in the Varian Eclipse treatment planning system was compared against a Monte Carlo method (VMC++), and the Analytical Anisotropic Algorithm (AAA). The study was carried out in virtual phantoms characterized by simple geometrical structures. An insert of different material and density was included in a phantom built of skeletal-muscle and HU = 0 (setting "A"): Normal Lung (lung, 0.198 g/cm³); Light Lung (lung, 0.035 g/cm³); Bone (bone, 1.798 g/cm³); another phantom (setting "B") was built of adipose material and including thin layers of bone (1.85 g/cm³), adipose (0.92 g/cm³), cartilage (1.4745 g/cm³), air (0.0012 g/cm³). Investigations were performed for 6 and 15 MV photon beams, and for a large (13 × 13 cm²) and a small (2.8 × 13 cm²) field.</p> <p>Results</p> <p>Results are provided in terms of depth dose curves, transverse profiles and Gamma analysis (3 mm/3% and 2 mm/2% distance to agreement/dose difference criteria) in planes parallel to the beam central axis; Monte Carlo simulations were assumed as reference. Acuros XB gave an average gamma agreement, with a 3 mm/3% criteria, of 100%, 86% and 100% for Normal Lung, Light Lung and Bone settings, respectively, and dose to medium calculations. The same figures were 86%, 11% and 100% for AAA, where only dose rescaled to water calculations are possible.</p> <p>Conclusions</p> <p>In conclusion, Acuros XB algorithm provides a valid and accurate alternative to Monte Carlo calculations for heterogeneity management.</p

Effect of logging wounds on diameter growth of beech (Fagus orientalis Lipsky) trees following selection cutting in Caspian forests of Iran

Background Logging damage to residual trees during selection cutting may lead to serious economic losses in terms of both timber quality and diameter growth reduction. In this study, we investigated the effect of logging operations on residual tree damage and the consequence of injuries on diameter growth in an uneven-aged mixed forest dominated by beech (Fagus orientalis Lipsky)

Evolutionary potential and adaptation of Banksia attenuata (Proteaceae) to climate and fire regime in southwestern Australia, a global biodiversity hotspot

Substantial climate changes are evident across Australia, with declining rainfall and rising temperature in conjunction with frequent fires. Considerable species loss and range contractions have been predicted; however, our understanding of how genetic variation may promote adaptation in response to climate change remains uncertain. Here we characterized candidate genes associated with rainfall gradients, temperatures, and fire intervals through environmental association analysis. We found that overall population adaptive genetic variation was significantly affected by shortened fire intervals, whereas declining rainfall and rising temperature did not have a detectable influence. Candidate SNPs associated with rainfall and high temperature were diverse, whereas SNPs associated with specific fire intervals were mainly fixed in one allele. Gene annotation further revealed four genes with functions in stress tolerance, the regulation of stomatal opening and closure, energy use, and morphogenesis with adaptation to climate and fire intervals. B. attenuata may tolerate further changes in rainfall and temperature through evolutionary adaptations based on their adaptive genetic variation. However, the capacity to survive future climate change may be compromised by changes in the fire regime

Genomic signatures of local adaptation reveal source-sink dynamics in a high gene flow fish species

Understanding source-sink dynamics is important for conservation management, particularly when climatic events alter species' distributions. Following a 2011 'marine heatwave' in Western Australia, we observed high recruitment of the endemic fisheries target species Choerodon rubescens, towards the cooler (southern) end of its distribution. Here, we use a genome wide set of 14 559 single-nucleotide polymorphisms (SNPs) to identify the likely source population for this recruitment event. Most loci (76%) showed low genetic divergence across the species' range, indicating high levels of gene flow and confirming previous findings using neutral microsatellite markers. However, a small proportion of loci showed strong patterns of differentiation and exhibited patterns of population structure consistent with local adaptation. Clustering analyses based on these outlier loci indicated that recruits at the southern end of C. rubescens' range originated 400 km to the north, at the centre of the species' range, where average temperatures are up to 3 °C warmer. Survival of these recruits may be low because they carry alleles adapted to an environment different to the one they now reside in, but their survival is key to establishing locally adapted populations at and beyond the range edge as water temperatures increase with climate change

Tree diversity and species identity effects on soil fungi, protists and animals are context dependent

Plant species richness and the presence of certain influential species (sampling effect) drive the stability and functionality of ecosystems as well as primary production and biomass of consumers. However, little is known about these floristic effects on richness and community composition of soil biota in forest habitats owing to methodological constraints. We developed a DNA metabarcoding approach to identify the major eukaryote groups directly from soil with roughly species-level resolution. Using this method, we examined the effects of tree diversity and individual tree species on soil microbial biomass and taxonomic richness of soil biota in two experimental study systems in Finland and Estonia and accounted for edaphic variables and spatial autocorrelation. Our analyses revealed that the effects of tree diversity and individual species on soil biota are largely context dependent. Multiple regression and structural equation modelling suggested that biomass, soil pH, nutrients and tree species directly affect richness of different taxonomic groups. The community composition of most soil organisms was strongly correlated due to similar response to environmental predictors rather than causal relationships. On a local scale, soil resources and tree species have stronger effect on diversity of soil biota than tree species richness per se

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care