Pleosporales

One hundred and five generic types of Pleosporales are described and illustrated. A brief introduction and detailed history with short notes on morphology, molecular phylogeny as well as a general conclusion of each genus are provided. For those genera where the type or a representative specimen is unavailable, a brief note is given. Altogether 174 genera of Pleosporales are treated. Phaeotrichaceae as well as Kriegeriella, Zeuctomorpha and Muroia are excluded from Pleosporales. Based on the multigene phylogenetic analysis, the suborder Massarineae is emended to accommodate five families, viz. Lentitheciaceae, Massarinaceae, Montagnulaceae, Morosphaeriaceae and Trematosphaeriaceae

Structural and Functional Changes of the Human Macula during Acute Exposure to High Altitude

Background: This study aimed to quantify structural and functional changes at the macula during acute exposure to high altitude and to assess their structure/function relationship. This work is related to the Tuebingen High Altitude Ophthalmology (THAO) study. Methodology/Principal Findings: Spectral domain optical coherence tomography and microperimetry were used to quantify changes of central retinal structure and function in 14 healthy subjects during acute exposure to high altitude (4559 m). High-resolution volume scans and fundus-controlled microperimetry of the posterior pole were performed in addition to best-corrected visual acuity (BCVA) measurements and assessment of acute mountain sickness. Analysis of measurements at altitude vs. baseline revealed increased total retinal thickness (TRT) in all four outer ETDRS grid subfields during acute altitude exposure (TRTouter = 2.8061.00 mm; mean change695%CI). This change was inverted towards the inner four subfields (TRT inner = 21.8960.97 mm) with significant reduction of TRT in the fovea (TRT foveal = 26.6260.90 mm) at altitude. BCVA revealed no significant difference compared to baseline (0.0660.08 logMAR). Microperimetry showed stable mean sensitivity in all but the foveal subfield (MSfoveal = 21.1260.68 dB). At baseline recordings before and.2 weeks after high altitude exposure, all subjects showed equal levels with no sign of persisting structural or functional sequels. Conclusions/Significance: During acute exposure to high altitude central retinal thickness is subject to minor, ye

Mild hypothermia reduces cardiac post-ischemic reactive hyperemia

BACKGROUND: In experimentally induced myocardial infarction, mild hypothermia (33–35°C) is beneficial if applied prior to ischemia or reperfusion. Hypothermia, when applied after reperfusion seems to confer little or no benefit. The mechanism by which hypothermia exerts its cell-protective effect during cardiac ischemia remains unclear. It has been hypothesized that hypothermia reduces the reperfusion damage; the additional damage incurred upon the myocardium during reperfusion. Reperfusion results in a massive increase in blood flow, reactive hyperemia, which may contribute to reperfusion damage. We postulated that hypothermia could attenuate the post-ischemic reactive hyperemia. METHODS: Sixteen 25–30 kg pigs, in a closed chest model, were anesthetized and temperature was established in all pigs at 37°C using an intravascular cooling catheter. The 16 pigs were then randomized to hypothermia (34°C) or control (37°C). The left main coronary artery was then catheterized with a PCI guiding catheter. A Doppler flow wire was placed in the mid part of the LAD and a PCI balloon was then positioned proximal to the Doppler wire but distal to the first diagonal branch. The LAD was then occluded for ten minutes in all pigs. Coronary blood flow was measured before, during and after ischemia/reperfusion. RESULTS: The peak flow seen during post-ischemic reactive hyperemia (during the first minutes of reperfusion) was significantly reduced by 43 % (p < 0.01) in hypothermic pigs compared to controls. CONCLUSION: Mild hypothermia significantly reduces post-ischemic hyperemia in a closed chest pig model. The reduction of reactive hyperemia during reperfusion may have an impact on cardiac reperfusion injury

Mitochondrial Cox1 Sequence Data Reliably Uncover Patterns of Insect Diversity But Suffer from High Lineage-Idiosyncratic Error Rates

The demand for scientific biodiversity data is increasing, but taxonomic expertise is often limited or not available. DNA sequencing is a potential remedy to overcome this taxonomic impediment. Mitochondrial DNA is most commonly used, e.g., for species identification ("DNA barcoding"). Here, we present the first study in arthropods based on a near-complete species sampling of a family-level taxon from the entire Australian region. We aimed to assess how reliably mtDNA data can capture species diversity when many sister species pairs are included. Then, we contrasted phylogenetic subsampling with the hitherto more commonly applied geographical subsampling, where sister species are not necessarily captured. We sequenced 800 bp cox1 for 1,439 individuals including 260 Australian species (78% species coverage). We used clustering with thresholds of 1 to 10% and general mixed Yule Coalescent (GMYC) analysis for the estimation of species richness. The performance metrics used were taxonomic accuracy and agreement between the morphological and molecular species richness estimation. Clustering (at the 3% level) and GMYC reliably estimated species diversity for single or multiple geographic regions, with an error for larger clades of lower than 10%, thus outperforming parataxonomy. However, the rates of error were higher for some individual genera, with values of up to 45% when very recent species formed nonmonophyletic clusters. Taxonomic accuracy was always lower, with error rates above 20% and a larger variation at the genus level (0 to 70%). Sørensen similarity indices calculated for morphospecies, 3% clusters and GMYC entities for different pairs of localities was consistent among methods and showed expected decrease over distance. Cox1 sequence data are a powerful tool for large-scale species richness estimation, with a great potential for use in ecology and β-diversity studies and for setting conservation priorities. However, error rates can be high in individual lineages

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Mining the human phenome using allelic scores that index biological intermediates

J. Kaprio ja M-L. Lokki työryhmien jäseniä.It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.Peer reviewe

CKLF1 Aggravates Focal Cerebral Ischemia Injury at Early Stage Partly by Modulating Microglia/Macrophage Toward M1 Polarization Through CCR4

CKLF1 is a chemokine with increased expression in ischemic brain, and targeting CKLF1 has shown therapeutic effects in cerebral ischemia model. Microglia/macrophage polarization is a mechanism involved in poststroke injury expansion. Considering the quick and obvious response of CKLF1 and expeditious evolution of stroke lesions, we focused on the effects of CKLF1 on microglial/macrophage polarization at early stage of ischemic stroke (IS). The present study is to investigate the CKLF1-mediated expression of microglia/macrophage phenotypes in vitro and in vivo, discussing the involved pathway. Primary microglia culture was used in vitro, and mice transient middle cerebral artery occlusion (MCAO) model was adopted to mimic IS. CKLF1 was added to the primary microglia for 24h, and we found that CKLF1 modulated primary microglia skew toward M1 phenotype. In mice transient IS model, CKLF1 was stereotactically microinjected to the lateral ventricle of ischemic hemisphere. CKLF1 aggravated ischemic injury, accompanied by promoting microglia/macrophage toward M1 phenotypic polarization. Increased expression of pro-inflammatory cytokines and decreased expression of anti-inflammatory cytokines were observed in mice subjected to cerebral ischemia and administrated with CKLF1. CKLF1(-/-) mice were used to confirm the effects of CKLF1. CKLF1(-/-) mice showed lighter cerebral damage and decreased M1 phenotype of microglia/macrophage compared with the WT control subjected to cerebral ischemia. Moreover, NF-B activation enhancement was detected in CKLF1 treatment group. Our results demonstrated that CKLF1 is an important mediator that skewing microglia/macrophage toward M1 phenotype at early stage of cerebral ischemic injury, which further deteriorates followed inflammatory response, contributing to early expansion of cerebral ischemia injury. Targeting CKLF1 may be a novel way for IS therapy