Secondary Liability, ISP Immunity, and Incumbent Entrenchment

More than fifteen years have passed since the two major U.S. statutes concerning the secondary liability of Internet service providers were adopted--the Communications Decency Act and the Digital Millennium Copyright Act. The statutes have been criticized; however, very little of the criticism has come from Internet service providers, who have enjoyed the benefits of generous safe harbors and immunity from suit guaranteed by these statutes. This Article raises the question of whether these statutes contribute to incumbent entrenchment--solidifying the position of the existing Internet service providers to the detriment of potential new entrants. The current laws and industry self-regulation may hamper the entry of new service providers into the market and thereby retard the technological progress that best serves society

Rapid fragmentation during seeded lysozyme aggregation revealed at the single molecule level

Protein aggregation is associated with neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. The poorly understood pathogenic mechanism of amyloid diseases makes early stage diagnostics or therapeutic intervention a challenge. Seeded polymerization that reduces the duration of the lag phase and accelerates fibril growth is a widespread model to study amyloid formation. Seeding effects are hypothesized to be important in the "infectivity" of amyloids and are linked to the development of systemic amyloidosis in vivo. The exact mechanism of seeding is unclear yet critical to illuminating the propagation of amyloids. Here we report on the lateral and axial fragmentation of seed fibrils in the presence of lysozyme monomers at short time scales, followed by the generation of oligomers and growth of fibrils

Monitoring Drought Impact on Annual Forage Production in Semi-Arid Grasslands: A Case Study of Nebraska Sandhills

Land management practices and disturbances (e.g. overgrazing, fire) have substantial effects on grassland forage production. When using satellite remote sensing to monitor climate impacts, such as drought stress on annual forage production, minimizing land management practices and disturbance effects sends a clear climate signal to the productivity data. This study investigates the effect of this climate signal by: (1) providing spatial estimates of expected biomass under specific climate conditions, (2) determining which drought indices explain the majority of interannual variability in this biomass, and (3) developing a predictive model that estimates the annual biomass early in the growing season. To address objective 1, this study uses an established methodology to determine Expected Ecosystem Performance (EEP) in the Nebraska Sandhills, US, representing annual forage levels after accounting for non-climatic influences. Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Dierence Vegetation Index (NDVI) data were used to approximate actual ecosystem performance. Seventeen years (2000–2016) of annual EEP was calculated using piecewise regression tree models of site potential and climate data. Expected biomass (EB), EEP converted to biomass in kg*ha-1*yr-1, was then used to examine the predictive capacity of several drought indices and the onset date of the growing season. Subsets of these indices were used to monitor and predict annual expected grassland biomass. Independent field-based biomass production data available from two Sandhills locations were used for validation of the EEP model. The EB was related to field-based biomass production (R2 = 0.66 and 0.57) and regional rangeland productivity statistics of the Soil Survey Geographic Database (SSURGO) dataset. The Evaporative Stress Index (ESI), the 3- and 6-month Standardized Precipitation Index (SPI), and the U.S. Drought Monitor (USDM), which represented moisture conditions during May, June and July, explained the majority of the interannual biomass variability in this grassland system (three-month ESI explained roughly 72% of the interannual biomass variability). A new model was developed to use drought indices from early in the growing season to predict the total EB for the whole growing season. This unique approach considers only climate-related drought signal on productivity. The capability to estimate annual EB by the end of May will potentially enable land managers to make informed decisions about stocking rates, hay purchase needs, and other management issues early in the season, minimizing their potential drought losses

6-benzothiazolyl ureas, thioureas and guanidines are potent inhibitors of ABAD/17β-HSD10 and potential drugs for Alzheimer's disease treatment : design, synthesis and in vitro evaluation

Background : The mitochondrial enzyme amyloid beta-binding alcohol dehydrogenase (ABAD) also known as 17β-hydroxysteroid dehydrogenase type 10 (17β-HSD10) has been connected with the pathogenesis of Alzheimer’s disease (AD). ABAD/ 17β-HSD10 is a binding site for the amyloid-beta peptide (Aβ) inside the mitochondrial matrix where it exacerbates Aβ toxicity. Interaction between these two proteins triggers a series of events leading to mitochondrial dysfunction as seen in AD. Methods : As ABAD’s enzymatic activity is required for mediating Aβ toxicity, its inhibition presents a promising strategy for AD treatment. In this study, a series of new benzothiazolylurea analogues have been prepared and evaluated in vitro for their potency to inhibit ABAD/ 17β-HSD10 enzymatic activity. The most potent compounds have also been tested for their cytotoxic properties and their ability to permeate through blood-brain barrier has been predicted. To explain the structure-activity relationship QSAR and pharmacophore studies have been performed. Results and Conclusions : Compound 12 was identified being the most promising hit compound with good inhibitory activity (IC50 = 3.06 ± 0.40µM) and acceptable cytotoxicity profile comparable to the parent compound of frentizole. The satisfactory physical-chemical properties suggesting its capability to permeate through BBB make compound 12 a novel lead structure for further development and biological assessment.PostprintPeer reviewe

Climate Change Predicted to Shift Wolverine Distributions, Connectivity, and Dispersal Corridors

Boreal species sensitive to the timing and duration of snow cover are particularly vulnerable to global climate change. Recent work has shown a link between wolverine (Gulo gulo) habitat and persistent spring snow cover through 15 May, the approximate end of the wolverine’s reproductive denning period. We modeled the distribution of snow cover within the Columbia, Upper Missouri, and Upper Colorado River Basins using a downscaled ensemble climate model. The ensemble model was based on the arithmetic mean of 10 global climate models (GCMs) that best fit historical climate trends and patterns within these three basins. Snow cover was estimated from resulting downscaled temperature and precipitation patterns using a hydrologic model. We bracketed our ensemble model predictions by analyzing warm (miroc 3.2) and cool (pcm1) downscaled GCMs. Because Moderate-Resolution Imaging Spectroradiometer (MODIS)-based snow cover relationships were analyzed at much finer grain than downscaled GCM output, we conducted a second analysis based on MODIS-based snow cover that persisted through 29 May, simulating the onset of spring two weeks earlier in the year. Based on the downscaled ensemble model, 67% of predicted spring snow cover will persist within the study area through 2030–2059, and 37% through 2070–2099. Estimated snow cover for the ensemble model during the period 2070– 2099 was similar to persistent MODIS snow cover through 29 May. Losses in snow cover were greatest at the southern periphery of the study area (Oregon, Utah, and New Mexico, USA) and least in British Columbia, Canada. Contiguous areas of spring snow cover become smaller and more isolated over time, but large (.1000 km2) contiguous areas of wolverine habitat are predicted to persist within the study area throughout the 21st century for all projections. Areas that retain snow cover throughout the 21st century are British Columbia, north-central Washington, northwestern Montana, and the Greater Yellowstone Area. By the late 21st century, dispersal modeling indicates that habitat isolation at or above levels associated with genetic isolation of wolverine populations becomes widespread. Overall, we expect wolverine habitat to persist throughout the species range at least for the first half of the 21st century, but populations will likely become smaller and more isolated

Homeobox gene expression in acute myeloid leukemia is linked to typical underlying molecular aberrations

__Background:__ Although distinct patterns of homeobox (HOX) gene expression have been described in defined cytogenetic and molecular subsets of patients with acute myeloid leukemia (AML), it is unknown whether these patterns are the direct result of transcriptional alterations or rather represent the differentiation stage of the leukemic cell. __Method:__ To address this question, we used qPCR to analyze mRNA expression of HOXA and HOXB genes in bone marrow (BM) samples of 46 patients with AML and sorted subpopulations of healthy BM cells. These various stages of myeloid differentiation represent matched counterparts of morphological subgroups of AML. To further study the transcriptional alterations of HOX genes in hematopoiesis, we also analyzed gene expression of epigenetic modifiers in the subpopluations of healthy BM and leukemic cells. __Results:__ Unsupervised hierarchical clustering divided the AMLs into five clusters characterized by the presence of prevalent molecular genetic aberrations. Notably, the impact of genotype on HOX gene expression was significantly more pronounced than that of the differentiation stage of the blasts. This driving role of molecular aberrations was best exemplified by the repressive effect of the PML-RARa fusion gene on HOX gene expression, regardless of the presence of the FLT3/ITD mutation. Furthermore, HOX gene expression was positively correlated with mRNA levels of histone demethylases (JMJD3 and UTX) and negatively correlated with gene expression of DNA methyltranferases. No such relationships were observed in subpopulations of healthy BM cells. __Conclusion:__ Our results demonstrate that specific molecular genetic aberrations, rather than differentiation per se, underlie the observed differences in HOX gene expression in AML. Moreover, the observed correlations between epigenetic modifiers and HOX ex pression that are specific to malignant hematopoiesis, suggest their potential causal relationships

Deriving a mutation index of carcinogenicity using protein structure and protein interfaces

With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/

Which health professionals are most at risk for cardiovascular disease? Or do not be a manager

Objectives: Health care workers constitute a high-risk occupational category owing to the character of their work that includes high-risk environment, shift work and mental as well as physical stress. In occupational medicine, caring for their health condition should be a priority and include measures aimed at preventing cardiovascular diseases. The study aimed at determining the prevalence of cardiovascular disease (CVD) risk factors in employees of a large hospital and assessing their effect on the incidence of cardiovascular events. Materials and Methods: The group comprised 3124 employees with a mean age of 36.1 years (SD = 11.4), out of whom 562 were males (mean age of 37.1 years, range: 18-72; SD = 12.26) and 2562 were females (mean age of 35.9 years, range: 18-68; SD = 11.24). At their initial examination, the employees filled in a questionnaire on basic CVD risk factors (according to valid recommendations). This was supplemented with objective data to determine the risk of CVD using valid charts. From this group, a subset of persons at a high or intermediate risk was selected, comprising 247 individuals with a mean age of 54.1 years (SD = 5.73). After 5-9 years (mean 7.24±1.38 years), they either underwent another examination or their health status was ascertained by phone or in a computer database. The end point was the incidence of cardiovascular events (sudden death, acute myocardial infarction, unstable angina pectoris, percutaneous coronary intervention, cardiac failure, stroke or transient ischemic attack). Results: The end point was noted in a total of 15 males (6.07%) and 6 females (2.42%), being statistically significantly present in managers (males p < 0.00007, females p < 0.00001), male physicians/surgeons (p < 0.025), tertiary-educated males (p < 0.0095), female smokers (p < 0.015), male ex-smokers (p < 0.007), overweight or obese males (p < 0.02) and those with the waist-to-hip ratio above 1.0 (p < 0.005). Conclusions: Cardiovascular events are most likely to occur in obese male physicians/surgeons holding managerial positions and in female managers

Genomic distance entrained clustering and regression modelling highlights interacting genomic regions contributing to proliferation in breast cancer

<p>Abstract</p> <p>Background</p> <p>Genomic copy number changes and regional alterations in epigenetic states have been linked to grade in breast cancer. However, the relative contribution of specific alterations to the pathology of different breast cancer subtypes remains unclear. The heterogeneity and interplay of genomic and epigenetic variations means that large datasets and statistical data mining methods are required to uncover recurrent patterns that are likely to be important in cancer progression.</p> <p>Results</p> <p>We employed ridge regression to model the relationship between regional changes in gene expression and proliferation. Regional features were extracted from tumour gene expression data using a novel clustering method, called genomic distance entrained agglomerative (GDEC) clustering. Using gene expression data in this way provides a simple means of integrating the phenotypic effects of both copy number aberrations and alterations in chromatin state. We show that regional metagenes derived from GDEC clustering are representative of recurrent regions of epigenetic regulation or copy number aberrations in breast cancer. Furthermore, detected patterns of genomic alterations are conserved across independent oestrogen receptor positive breast cancer datasets. Sequential competitive metagene selection was used to reveal the relative importance of genomic regions in predicting proliferation rate. The predictive model suggested additive interactions between the most informative regions such as 8p22-12 and 8q13-22.</p> <p>Conclusions</p> <p>Data-mining of large-scale microarray gene expression datasets can reveal regional clusters of co-ordinate gene expression, independent of cause. By correlating these clusters with tumour proliferation we have identified a number of genomic regions that act together to promote proliferation in ER+ breast cancer. Identification of such regions should enable prioritisation of genomic regions for combinatorial functional studies to pinpoint the key genes and interactions contributing to tumourigenicity.</p