Prevalence and Correlates of Common Mental Disorders among Mothers of Young Children in Kilimanjaro Region of Tanzania.

Although poor maternal mental health is a major public health problem, with detrimental effects on the individual, her children and society, information on its correlates in low-income countries is sparse. This study investigates the prevalence of common mental disorders (CMD) among at-risk mothers, and explores its associations with sociodemographic factors. This population-based survey of mothers of children aged 0-36 months used the 14-item Shona Symptom Questionnaire (SSQ). Mothers whose response was "yes" to 8 or more items on the scale were defined as "at risk of CMD." Of the 1,922 mothers (15-48 years), 28.8% were at risk of CMD. Risk of CMD was associated with verbal abuse, physical abuse, a partner who did not help with the care of the child, being in a polygamous relationship, a partner with low levels of education, and a partner who smoked cigarettes. Cohabiting appeared to be protective. Taken together, our results indicate the significance of the quality of relations with one's partner in shaping maternal mental health. The high proportion of mothers who are at risk of CMD emphasizes the importance of developing evidence-based mental health programmes as part of the care package aimed at improving maternal well-being in Tanzania and other similar settings

Review: optical fiber sensors for civil engineering applications

Optical fiber sensor (OFS) technologies have developed rapidly over the last few decades, and various types of OFS have found practical applications in the field of civil engineering. In this paper, which is resulting from the work of the RILEM technical committee “Optical fiber sensors for civil engineering applications”, different kinds of sensing techniques, including change of light intensity, interferometry, fiber Bragg grating, adsorption measurement and distributed sensing, are briefly reviewed to introduce the basic sensing principles. Then, the applications of OFS in highway structures, building structures, geotechnical structures, pipelines as well as cables monitoring are described, with focus on sensor design, installation technique and sensor performance. It is believed that the State-of-the-Art review is helpful to engineers considering the use of OFS in their projects, and can facilitate the wider application of OFS technologies in construction industry

Stable lepton mass matrices

Abstract: We study natural lepton mass matrices, obtained assuming the stability of physical flavour observables with respect to the variations of individual matrix elements. We identify all four possible stable neutrino textures from algebraic conditions on their entries. Two of them turn out to be uniquely associated to specific neutrino mass patterns. We then concentrate on the semi-degenerate pattern, corresponding to an overall neutrino mass scale within the reach of future experiments. In this context we show that i) the neutrino and charged lepton mixings and mass matrices are largely constrained by the requirement of stability, ii) naturalness considerations give a mild preference for the Majorana phase most relevant for neutrinoless double-\u3b2 decay, \u3b1 3c \u3c0/2, and iii) SU(5) unification allows to extend the implications of stability to the down quark sector. The above considerations would benefit from an experimental determination of the PMNS ratio 1aU32/U31 1a, i.e. of the Dirac phase \u3b4. \ua9 2016, The Author(s)

CLUSS: Clustering of protein sequences based on a new similarity measure

<p>Abstract</p> <p>Background</p> <p>The rapid burgeoning of available protein data makes the use of clustering within families of proteins increasingly important. The challenge is to identify subfamilies of evolutionarily related sequences. This identification reveals phylogenetic relationships, which provide prior knowledge to help researchers understand biological phenomena. A good evolutionary model is essential to achieve a clustering that reflects the biological reality, and an accurate estimate of protein sequence similarity is crucial to the building of such a model. Most existing algorithms estimate this similarity using techniques that are not necessarily biologically plausible, especially for hard-to-align sequences such as proteins with different domain structures, which cause many difficulties for the alignment-dependent algorithms. In this paper, we propose a novel similarity measure based on matching amino acid subsequences. This measure, named SMS for Substitution Matching Similarity, is especially designed for application to non-aligned protein sequences. It allows us to develop a new alignment-free algorithm, named CLUSS, for clustering protein families. To the best of our knowledge, this is the first alignment-free algorithm for clustering protein sequences. Unlike other clustering algorithms, CLUSS is effective on both alignable and non-alignable protein families. In the rest of the paper, we use the term "<it>phylogenetic</it>" in the sense of "<it>relatedness of biological functions</it>".</p> <p>Results</p> <p>To show the effectiveness of CLUSS, we performed an extensive clustering on COG database. To demonstrate its ability to deal with hard-to-align sequences, we tested it on the GH2 family. In addition, we carried out experimental comparisons of CLUSS with a variety of mainstream algorithms. These comparisons were made on hard-to-align and easy-to-align protein sequences. The results of these experiments show the superiority of CLUSS in yielding clusters of proteins with similar functional activity.</p> <p>Conclusion</p> <p>We have developed an effective method and tool for clustering protein sequences to meet the needs of biologists in terms of phylogenetic analysis and prediction of biological functions. Compared to existing clustering methods, CLUSS more accurately highlights the functional characteristics of the clustered families. It provides biologists with a new and plausible instrument for the analysis of protein sequences, especially those that cause problems for the alignment-dependent algorithms.</p

Ezrin interacts with the SARS coronavirus spike protein and restrains infection at the entry stage

© 2012 Millet et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: Entry of Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) and its envelope fusion with host cell membrane are controlled by a series of complex molecular mechanisms, largely dependent on the viral envelope glycoprotein Spike (S). There are still many unknowns on the implication of cellular factors that regulate the entry process. Methodology/Principal Findings: We performed a yeast two-hybrid screen using as bait the carboxy-terminal endodomain of S, which faces the cytosol during and after opening of the fusion pore at early stages of the virus life cycle. Here we show that the ezrin membrane-actin linker interacts with S endodomain through the F1 lobe of its FERM domain and that both the eight carboxy-terminal amino-acids and a membrane-proximal cysteine cluster of S endodomain are important for this interaction in vitro. Interestingly, we found that ezrin is present at the site of entry of S-pseudotyped lentiviral particles in Vero E6 cells. Targeting ezrin function by small interfering RNA increased S-mediated entry of pseudotyped particles in epithelial cells. Furthermore, deletion of the eight carboxy-terminal amino acids of S enhanced S-pseudotyped particles infection. Expression of the ezrin dominant negative FERM domain enhanced cell susceptibility to infection by SARS-CoV and S pseudotyped particles and potentiated S-dependent membrane fusion. Conclusions/Significance: Ezrin interacts with SARS-CoV S endodomain and limits virus entry and fusion. Our data present a novel mechanism involving a cellular factor in the regulation of S-dependent early events of infection.This work was supported by the Research Grant Council of Hong Kong (RGC#760208)and the RESPARI project of the International Network of Pasteur Institutes

The educational impact of assessment: a comparison of DOPS and MCQs

Aim: To evaluate the impact of two different assessment formats on the approaches to learning of final year veterinary students. The relationship between approach to learning and examination performance was also investigated. Method: An 18-item version of the Study Process Questionnaire (SPQ) was sent to 87 final year students. Each student responded to the questionnaire with regards to DOPS (Direct Observation of Procedural Skills) and a Multiple Choice Examination (MCQ). Semi-structured interviews were conducted with 16 of the respondents to gain a deeper insight into the students’ perception of assessment. Results: Students’ adopted a deeper approach to learning for DOPS and a more surface approach with MCQs. There was a positive correlation between an achieving approach to learning and examination performance. Analysis of the qualitative data revealed that deep, surface and achieving approaches were reported by the students and seven major influences on their approaches to learning were identified: motivation, purpose, consequence, acceptability, feedback, time pressure and the individual difference of the students. Conclusions: The format of DOPS has a positive influence on approaches to learning. There is a conflict for students between preparing for final examinations and preparing for clinical practice

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

Background: The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems' level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log(2)- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results: The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions: BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation