Decreased Serum Levels of S-100B Protein Reflect Successful Treatment Effects in a Rabbit Model of Acute Ischemic Stroke

Serum levels of S-100B were investigated as a marker for infarct volume and response to treatment following acute ischemic stroke in rabbits. Following subselective angiography, rabbits (n=31) were embolized by injection of a 3-day-old blood clot (0.6x4.0-mm) into the internal carotid artery. Treatment began 1-hr post-embolization, groups included: Control (n=8, embolization only), tissue plasminogen activator (tPA, n=12, 0.9mg/kg), and perflutren lipid microbubbles with transcranial ultrasound (MB+US, n=11, MB at 0.16mg/kg, US at 1-MHz pulsed-wave, 0.8 W/cm2 for 1-hr). Serum S-100B levels were significantly increased (P<0.01) 24-hours following embolization in control (3.1-fold over baseline) and tPA (2.9-fold) groups, while treatment with MB+US resulted in an attenuated, non-significant (P=0.221) increase (1.6-fold). Twenty-four hour infarct volumes averaged 4.76%±1.16% for controls, 2.25%±0.95% for rabbits treated with tPA (P=0.32 vs. control), and 0.79%±0.99% for rabbits treated with MB+US (P=0.04 vs. control). Twenty-four hour concentrations of S-100B were positively correlated with infarct volume (r=0.59, P=0.0004)

A novel conjugal donor strain for improved DNA transfer into Clostridium spp.

© 2019 The Authors Importance: The ability to transfer genetic material into a target organism is crucial for the development of a wide range of targeted genetic manipulation techniques. Overcoming the organisms’ native restriction systems which target foreign incoming DNA is one strategy that can increase the efficiency of genetic transfer. The novel E. coli donor strain described here employs this strategy, increasing the frequencies of conjugation into a range of clostridial strains, and therefore opening up the potential to implement novel gene manipulation techniques. Furthermore this novel donor strain has potential applications across a wide range of genetically recalcitrant organisms, and should be beneficial wherever the frequently occurring Type IV restriction systems are possessed by the target in question

Dependence as a Unifying Construct in Defining Alzheimer's Disease Severity

This article reviews measures of Alzheimer's disease (AD) progression in relation to patient dependence and offers a unifying conceptual framework for dependence in AD. Clinicians typically characterize AD by symptomatic impairments in three domains: cognition, function, and behavior. From a patient's perspective, changes in these domains, individually and in concert, ultimately lead to increased dependence and loss of autonomy. Examples of dependence in AD range from a need for reminders (early AD) to requiring safety supervision and assistance with basic functions (late AD). Published literature has focused on the clinical domains as somewhat separate constructs and has given limited attention to the concept of patient dependence as a descriptor of AD progression. This article presents the concept of dependence on others for care needs as a potential method for translating the effect of changes in cognition, function, and behavior into a more holistic, transparent description of AD progression

Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus.

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. SIGNIFICANCE: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene.See related commentary by Choi and Brown, p. 439

Community-based knowledge transfer and exchange: Helping community-based organizations link research to action

<p>Abstract</p> <p>Background</p> <p>Community-based organizations (CBOs) are important stakeholders in health systems and are increasingly called upon to use research evidence to inform their advocacy, program planning, and service delivery efforts. CBOs increasingly turn to community-based research (CBR) given its participatory focus and emphasis on linking research to action. In order to further facilitate the use of research evidence by CBOs, we have developed a strategy for community-based knowledge transfer and exchange (KTE) that helps CBOs more effectively link research evidence to action. We developed the strategy by: outlining the primary characteristics of CBOs and why they are important stakeholders in health systems; describing the concepts and methods for CBR and for KTE; comparing the efforts of CBR to link research evidence to action to those discussed in the KTE literature; and using the comparison to develop a framework for community-based KTE that builds on both the strengths of CBR and existing KTE frameworks.</p> <p>Discussion</p> <p>We find that CBR is particularly effective at fostering a climate for using research evidence and producing research evidence relevant to CBOs through community participation. However, CBOs are not always as engaged in activities to link research evidence to action on a larger scale or to evaluate these efforts. Therefore, our strategy for community-based KTE focuses on: an expanded model of 'linkage and exchange' (<it>i.e</it>., producers and users of researchers engaging in a process of asking and answering questions together); a greater emphasis on both producing and disseminating systematic reviews that address topics of interest to CBOs; developing a large-scale evidence service consisting of both 'push' efforts and efforts to facilitate 'pull' that highlight actionable messages from community relevant systematic reviews in a user-friendly way; and rigorous evaluations of efforts for linking research evidence to action.</p> <p>Summary</p> <p>Through this type of strategy, use of research evidence for CBO advocacy, program planning, and service delivery efforts can be better facilitated and continually refined through ongoing evaluations of its impact.</p

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100

High aboveground carbon stock of African tropical montane forests

Tropical forests store 40-50 per cent of terrestrial vegetation carbon(1). However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests(2). Owing to climatic and soil changes with increasing elevation(3), AGC stocks are lower in tropical montane forests compared with lowland forests(2). Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1-164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network(4) and about 70 per cent and 32 per cent higher than averages from plot networks in montane(2,5,6) and lowland(7) forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa(8). We find that the low stem density and high abundance of large trees of African lowland forests(4) is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse(9,10) and carbon-rich ecosystems. The aboveground carbon stock of a montane African forest network is comparable to that of a lowland African forest network and two-thirds higher than default values for these montane forests.Peer reviewe