Are we underestimating microplastic abundance in the marine environment? A comparison of microplastic capture with nets of different mesh-size

Microplastic debris is ubiquitous and yet sampling, classifying and enumerating this prolific pollutant in marine waters has proven challenging. Typically, waterborne microplastic sampling is undertaken using nets with a 333 μm mesh, which cannot account for smaller debris. In this study, we provide an estimate of the extent to which microplastic concentrations are underestimated with traditional sampling. Our efforts focus on coastal waters, where microplastics are predicted to have the greatest influence on marine life, on both sides of the North Atlantic Ocean. Microplastic debris was collected via surface trawls using 100, 333 and 500 μm nets. Our findings show that sampling using nets with a 100 μm mesh resulted in the collection of 2.5-fold and 10-fold greater microplastic concentrations compared with using 333 and 500 μm meshes respectively (P < 0.01). Based on the relationship between microplastic concentrations identified and extrapolation of our data using a power law, we estimate that microplastic concentrations could exceed 3700 microplastics m−3 if a net with a 1 μm mesh size is used. We further identified that use of finer nets resulted in the collection of significantly thinner and shorter microplastic fibres (P < 0.05). These results elucidate that estimates of marine microplastic concentrations could currently be underestimated

A Systematic Review and Meta-Analysis of Symptoms of Anxiety, Depression, and Insomnia in Spain in the COVID-19 Crisis.

BACKGROUND: General population, frontline healthcare workers (HCWs), and adult students in Spain are at risk of anxiety, depression, and insomnia symptoms during the COVID-19 crisis. A meta-analysis of the individual studies on these symptoms would provide systematic evidence to aid policymakers and researchers in focusing on prevalence, risk, and best interventions. OBJECTIVE: This paper aims to be the first meta-analysis and systematic review to calculate the prevalence of anxiety, depression, and insomnia symptoms in Spain's adult population (general population, frontline healthcare workers (HCWs), and adult students) during the Covid-19 epidemic. METHOD: Random-effect meta-analysis was used to estimate the prevalence of anxiety, depression, and insomnia. RESULTS: The meta-analysis includes 28 studies with 38 individual samples in Spain. The pooled prevalence of anxiety symptoms in 22 studies comprising a sample population of 82,024 was 20% (95% CI: 15-25%), that of depression symptoms in 22 articles with a total sample comprising 82,890 individuals was 22% (95% CI: 18-28%), and that of insomnia symptoms in three articles with a sample population of 745 was 57% (95% CI: 48-66%. CONCLUSIONS: The accumulative evidence reveals that adults in Spain suffered higher prevalence rates of mental symptoms during the COVID-19 crisis, with a significantly higher rate relative to other countries such as China. Our synthesis also reveals a relative lack of studies on frontline and general HCWs in Spain

Mental Health during the COVID-19 Crisis in Africa: A Systematic Review and Meta-Analysis.

We aim to provide a systematic review and meta-analysis of the prevalence rates of mental health symptoms among major African populations during the COVID-19 pandemic. We include articles from PubMed, Embase, Web of Science, PsycINFO, and medRxiv between 1 February 2020 and 6 February 2021, and pooled data using random-effects meta-analyses. We identify 28 studies and 32 independent samples from 12 African countries with a total of 15,071 participants. The pooled prevalence of anxiety was 37% in 27 studies, of depression was 45% in 24 studies, and of insomnia was 28% in 9 studies. The pooled prevalence rates of anxiety, depression, and insomnia in North Africa (44%, 55%, and 31%, respectively) are higher than those in Sub-Saharan Africa (31%, 30%, and 24%, respectively). We find (a) a scarcity of studies in several African countries with a high number of COVID-19 cases; (b) high heterogeneity among the studies; (c) the extent and pattern of prevalence of mental health symptoms in Africa is high and differs from elsewhere-more African adults suffer from depression rather than anxiety and insomnia during COVID 19 compared to adult populations in other countries/regions. Hence, our findings carry crucial implications and impact future research to enable evidence-based medicine in Africa

Mental disorder symptoms during the COVID-19 pandemic in Latin America - a systematic review and meta-analysis.

AIMS: There is a lack of evidence related to the prevalence of mental health symptoms as well as their heterogeneities during the coronavirus disease 2019 (COVID-19) pandemic in Latin America, a large area spanning the equator. The current study aims to provide meta-analytical evidence on mental health symptoms during COVID-19 among frontline healthcare workers, general healthcare workers, the general population and university students in Latin America. METHODS: Bibliographical databases, such as PubMed, Embase, Web of Science, PsycINFO and medRxiv, were systematically searched to identify pertinent studies up to August 13, 2021. Two coders performed the screening using predefined eligibility criteria. Studies were assigned quality scores using the Mixed Methods Appraisal Tool. The double data extraction method was used to minimise data entry errors. RESULTS: A total of 62 studies with 196 950 participants in Latin America were identified. The pooled prevalence of anxiety, depression, distress and insomnia was 35%, 35%, 32% and 35%, respectively. There was a higher prevalence of mental health symptoms in South America compared to Central America (36% v. 28%, p < 0.001), in countries speaking Portuguese (40%) v. Spanish (30%). The pooled prevalence of mental health symptoms in the general population, general healthcare workers, frontline healthcare workers and students in Latin America was 37%, 34%, 33% and 45%, respectively. CONCLUSIONS: The high yet heterogenous level of prevalence of mental health symptoms emphasises the need for appropriate identification of psychological interventions in Latin America

Mineral maturity and crystallinity index are distinct characteristics of bone mineral

The purpose of this study was to test the hypothesis that mineral maturity and crystallinity index are two different characteristics of bone mineral. To this end, Fourier transform infrared microspectroscopy (FTIRM) was used. To test our hypothesis, synthetic apatites and human bone samples were used for the validation of the two parameters using FTIRM. Iliac crest samples from seven human controls and two with skeletal fluorosis were analyzed at the bone structural unit (BSU) level by FTIRM on sections 2–4 lm thick. Mineral maturity and crystallinity index were highly correlated in synthetic apatites but poorly correlated in normal human bone. In skeletal fluorosis, crystallinity index was increased and maturity decreased, supporting the fact of separate measurement of these two parameters. Moreover, results obtained in fluorosis suggested that mineral characteristics can be modified independently of bone remodeling. In conclusion, mineral maturity and crystallinity index are two different parameters measured separately by FTIRM and offering new perspectives to assess bone mineral traits in osteoporosis

Rediscovering vitamin D

Over the past 2 years there has been a radical change in standard clinical practice with respect to vitamin D. As a result of a growing body of knowledgeable physicians are assessing the vitamin D nutritional status of their patients and prescribing aggressive repletion regimens of a vitamin D supplement. The present paper summarizes some basic information about this essential nutrient and reviews some of the more recent data implicating vitamin D deficiency in disease etiology with an emphasis on cardiovascular disease and cancer. Finally a rational approach to the dosing of vitamin D in different patient populations is provided

Theory of Star Formation

We review current understanding of star formation, outlining an overall theoretical framework and the observations that motivate it. A conception of star formation has emerged in which turbulence plays a dual role, both creating overdensities to initiate gravitational contraction or collapse, and countering the effects of gravity in these overdense regions. The key dynamical processes involved in star formation -- turbulence, magnetic fields, and self-gravity -- are highly nonlinear and multidimensional. Physical arguments are used to identify and explain the features and scalings involved in star formation, and results from numerical simulations are used to quantify these effects. We divide star formation into large-scale and small-scale regimes and review each in turn. Large scales range from galaxies to giant molecular clouds (GMCs) and their substructures. Important problems include how GMCs form and evolve, what determines the star formation rate (SFR), and what determines the initial mass function (IMF). Small scales range from dense cores to the protostellar systems they beget. We discuss formation of both low- and high-mass stars, including ongoing accretion. The development of winds and outflows is increasingly well understood, as are the mechanisms governing angular momentum transport in disks. Although outstanding questions remain, the framework is now in place to build a comprehensive theory of star formation that will be tested by the next generation of telescopes.Comment: 120 pages, to appear in ARAA. No changes from v1 text; permission statement adde

Background risk of breast cancer and the association between physical activity and mammographic density

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ccTSA: A Coverage-Centric Threaded Sequence Assembler

De novo sequencing, a process to find the whole genome or the regions of a species without references, requires much higher computational power compared to mapped sequencing with references. The advent and continuous evolution of next-generation sequencing technologies further stress the demands of high-throughput processing of myriads of short DNA fragments. Recently announced sequence assemblers, such as Velvet, SOAPdenovo, and ABySS, all exploit parallelism to meet these computational demands since contemporary computer systems primarily rely on scaling the number of computing cores to improve performance. However, most of them are not tailored to exploit the full potential of these systems, leading to suboptimal performance. In this paper, we present ccTSA, a parallel sequence assembler that utilizes coverage to prune k-mers, find preferred edges, and resolve conflicts in preferred edges between k-mers. We minimize computation dependencies between threads to effectively parallelize k-mer processing. We also judiciously allocate and reuse memory space in order to lower memory usage and further improve sequencing speed. The results of ccTSA are compelling such that it runs several times faster than other assemblers while providing comparable quality values such as N50