Deriving phytoplankton size classes from satellite data: Validation along a trophic gradient in the eastern Atlantic Ocean

In recent years, the global distribution of phytoplankton functional types (PFT) and phytoplankton size classes (PSC) has been determined by remote sensing. Many of these methods rely on interpretation of phytoplankton size or type from pigment data, but independent validation has been difficult due to lack of appropriate in situ data on cell size. This work uses in situ data (photosynthetic pigments concentration and cell abundances) from the north-east Atlantic, along a trophic gradient, sampled from 2005 to 2010, as well as Atlantic Meridional Transect (AMT) data for the same region, to test a previously developed conceptual model, which calculates the fractional contributions of pico-, nano- and micro-plankton to total phytoplankton chlorophyll biomass (Brewin et al., 2010). The application of the model proved to be successful, as shown by low mean absolute error between data and model fit. However, regional values obtained for the model parameters had some effect on the relative distribution of size classes as a function of chlorophyll-a, compared with the results according to the original model. The regional parameterisation yielded a dominance of micro-plankton contribution for chlorophyll-a concentrations greater than 0.5 mg m− 3, rather than from 1.3 mg m− 3 in the original model. Intracellular chlorophyll-a (Chla) per cell, for each size class, was computed from the cell enumeration results (microscope counts and flow cytometry) and the chlorophyll-a concentration for that size class given by the model. The median intracellular chlorophyll-a values computed were 0.004, 0.224 and 26.78 pg Chla cell− 1 for pico-, nano-, and micro-plankton respectively. This is generally consistent with the literature, thereby providing an indirect validation of the method based on pigments to assign size classes. Using a satellite-derived composite image of chlorophyll-a for the study area, a map of cell abundance was generated based on the computed intracellular chlorophyll-a for each size-class, thus extending the remote-sensing method for mapping size classes of phytoplankton from chlorophyll-a concentration to mapping cell numbers in each class. The map reveals the ubiquitous presence of pico-plankton, and shows that all size classes are more abundant in more productive areas

Abnormal cognition, sleep, EEG and brain metabolism in a novel knock-in Alzheimer mouse, PLB1

Peer reviewedPublisher PD

Translocation t(2;7)(p12;q21-22) with dysregulation of the CDK6 gene mapping to 7q21-22 in a non-Hodgkin’s lymphoma with leukemia

Background and Objectives. A female patient presented with splenomegaly and lymphocytosis with atypical lymphoid cell morphology, We identified t(2;7)(p12;q21) prompting studies of the translocation breakpoint and its consequences on protein expression to confirm or otherwise the recently reported involvement of CDK6 and IG kappa genes in the t(2;7) leading to over-expression of CDK6 protein. Design and Methods. A variety of clinical and laboratory techniques including cell marker, cytogenetic and histologic studies were applied in order to establish the diagnosis. Fluorescence in situ hybridization (FISH) and Southern blotting were used for mapping the translocation breakpoint and Western blotting for assessing protein expression. Results. Immunophenotyping showed the presence of a B-cell population with strong expression of FMC7, CD22, CD79b, CD5 and K restricted surface immunoglobulins. Based on morphology and immunophenotypic markers the diagnosis of B-cell nonHodgkin’s lymphoma was made. Karyotyping revealed a clone with t(2;7)(p12;q21-22). Evidence for clonal evolution with additional abnormalities including a deletion of the TP53 was present, We established by FISH and Southern blotting that the breakpoint on 7q21-22 fell in a region 66kb telomeric to the previously reported breakpoint for the t(2;7) and was the same as that observed in a t(7;21). CDK6 protein was over-expressed. The patient received alkylating agents and splenectomy and is alive but the lymphocytosis persists with evidence of disease progression. Interpretations and Conclusions. We have demonstrated that CDK6 expression is dysregulated even when the breakpoint on 7q21-22 is located 66kb upstream from the coding region. Interestingly, the precise assignment of the lymphoma type in our case was not possible even when the splenic histology was analyzed. (C)2002, Ferrata Storti Foundation

CRISPR-Cas9 screens in human cells and primary neurons identify modifiers of C9ORF72 dipeptide-repeat-protein toxicity.

Hexanucleotide-repeat expansions in the C9ORF72 gene are the most common cause of amyotrophic lateral sclerosis and frontotemporal dementia (c9ALS/FTD). The nucleotide-repeat expansions are translated into dipeptide-repeat (DPR) proteins, which are aggregation prone and may contribute to neurodegeneration. We used the CRISPR-Cas9 system to perform genome-wide gene-knockout screens for suppressors and enhancers of C9ORF72 DPR toxicity in human cells. We validated hits by performing secondary CRISPR-Cas9 screens in primary mouse neurons. We uncovered potent modifiers of DPR toxicity whose gene products function in nucleocytoplasmic transport, the endoplasmic reticulum (ER), proteasome, RNA-processing pathways, and chromatin modification. One modifier, TMX2, modulated the ER-stress signature elicited by C9ORF72 DPRs in neurons and improved survival of human induced motor neurons from patients with C9ORF72 ALS. Together, our results demonstrate the promise of CRISPR-Cas9 screens in defining mechanisms of neurodegenerative diseases

Minimal in vivo efficacy of iminosugars in a lethal Ebola virus guinea pig model

The antiviral properties of iminosugars have been reported previously in vitro and in small animal models against Ebola virus (EBOV); however, their effects have not been tested in larger animal models such as guinea pigs. We tested the iminosugars N-butyl-deoxynojirimycin (NB-DNJ) and N-(9-methoxynonyl)-1deoxynojirimycin (MON-DNJ) for safety in uninfected animals, and for antiviral efficacy in animals infected with a lethal dose of guinea pig adapted EBOV. 1850 mg/kg/day NB-DNJ and 120 mg/kg/day MON-DNJ administered intravenously, three times daily, caused no adverse effects and were well tolerated. A pilot study treating infected animals three times within an 8 hour period was promising with 1 of 4 infected NB-DNJ treated animals surviving and the remaining three showing improved clinical signs. MON-DNJ showed no protective effects when EBOV-infected guinea pigs were treated. On histopathological examination, animals treated with NB-DNJ had reduced lesion severity in liver and spleen. However, a second study, in which NB-DNJ was administered at equally-spaced 8 hour intervals, could not confirm drug-associated benefits. Neither was any antiviral effect of iminosugars detected in an EBOV glycoprotein pseudotyped virus assay. Overall, this study provides evidence that NB-DNJ and MON-DNJ do not protect guinea pigs from a lethal EBOV-infection at the dose levels and regimens tested. However, the one surviving animal and signs of improvements in three animals of the NB-DNJ treated cohort could indicate that NB-DNJ at these levels may have a marginal beneficial effect. Future work could be focused on the development of more potent iminosugars

The development and cognitive testing of the positive outcomes HIV PROM: a brief novel patient-reported outcome measure for adults living with HIV

Background People living with HIV experience burdensome multidimensional symptoms and concerns requiring person-centred care. Routine use of patient reported outcome measures can improve outcomes. There is no brief patient reported outcome measure (PROM) that currently reflects the breadth of concerns for people living with HIV. This study aimed to develop and cognitively test a brief novel patient reported outcome measure for use within routine adult HIV care– the “Positive Outcomes” HIV PROM. Methods Development followed the COSMIN taxonomy and guidance for relevance and comprehensiveness, and Rothrock guidance on development of valid patient reported outcome measures. The Positive Outcomes HIV PROM was developed by a steering group (people living with HIV, HIV professionals and health services researchers) using findings from a previously reported qualitative study of priority outcomes for people living with HIV. The prototype measure was cognitively tested with a purposive sample of people living with HIV. Results The Positive Outcomes HIV PROM consists of 23 questions (22 structured, and one open question) informed by the priorities of key stakeholders (n = 28 people living with HIV, n = 21 HIV professionals and n = 8 HIV commissioners) to ensure face and content validity, and refined through cognitive testing (n = 6 people living with HIV). Cognitive testing demonstrated high levels of acceptability and accessibility. Conclusions The Positive Outcomes HIV PROM is the first brief patient reported outcome measure reflecting the diverse needs of people living with HIV designed specifically for use in the clinical setting to support patient assessment and care, and drive service quality improvement. It is derived from primary data on the priority outcomes for people living with HIV and is comprehensive and acceptable. Further psychometric testing is required to ensure reliability and responsiveness

Duration of unemployment and depression: a cross-sectional survey in Lithuania

BACKGROUND: In spite of a growing economy, unemployment is still a severe socio-economic problem in Lithuania. Nonetheless, no studies have been performed about the associations between unemployment and mental health in Lithuania. The aim of this study was to evaluate the associations between unemployment duration and depression in Lithuania. METHODS: The data was collected in a cross-sectional study in 2005. There were 429 filled-in questionnaires received (53.6% response rate) from unemployed persons registered with the Kaunas Labour Market Office. The severity of depression symptoms was evaluated using the Beck Depression Inventory (BDI). Logistic regression was used to estimate the risk factors for occurrence of depression. Sex, age, place of residence, marital status, education, income and practiced religion were the independent variables. Long-term unemployment was defined as lasting a duration of 12 months or more. RESULTS: The findings showed that long-term unemployed persons had more episodes of a depressive mood in the past 12 months in comparison with the group of the short-term unemployed. In addition, the BDI score mean was higher among the long-term unemployed compared with the short-term unemployed (10.1 ± 8.8 and 14.2 ± 9.5 respectively, p < 0.001). It was estimated that the duration of unemployment and BDI score had a positive correlation (r = 0.1968, p < 0.001). Among the short-term unemployed, the risk of depression increased significantly when the person was female, had an older age and had experienced more episodes of unemployment. Among the long-term unemployed, an older age was the risk factor for development of depression. However, higher education and income were the factors that significantly decreased the risk of developing depression for-short term as well as for long-term unemployed. CONCLUSION: The results indicated that depression is a severe problem in the unemployed population. Depression is more elevated among the long-term unemployed. This leads to arguing for common efforts in providing needed social support and health care to reduce the effects of unemployment on mental health

Predictive models for anti-tubercular molecules using machine learning on high-throughput biological screening datasets

<p>Abstract</p> <p>Background</p> <p>Tuberculosis is a contagious disease caused by <it>Mycobacterium tuberculosis </it>(Mtb), affecting more than two billion people around the globe and is one of the major causes of morbidity and mortality in the developing world. Recent reports suggest that Mtb has been developing resistance to the widely used anti-tubercular drugs resulting in the emergence and spread of multi drug-resistant (MDR) and extensively drug-resistant (XDR) strains throughout the world. In view of this global epidemic, there is an urgent need to facilitate fast and efficient lead identification methodologies. Target based screening of large compound libraries has been widely used as a fast and efficient approach for lead identification, but is restricted by the knowledge about the target structure. Whole organism screens on the other hand are target-agnostic and have been now widely employed as an alternative for lead identification but they are limited by the time and cost involved in running the screens for large compound libraries. This could be possibly be circumvented by using computational approaches to prioritize molecules for screening programmes.</p> <p>Results</p> <p>We utilized physicochemical properties of compounds to train four supervised classifiers (Naïve Bayes, Random Forest, J48 and SMO) on three publicly available bioassay screens of Mtb inhibitors and validated the robustness of the predictive models using various statistical measures.</p> <p>Conclusions</p> <p>This study is a comprehensive analysis of high-throughput bioassay data for anti-tubercular activity and the application of machine learning approaches to create target-agnostic predictive models for anti-tubercular agents.</p