scispace - formally typeset
Search or ask a question

Showing papers in "PLOS ONE in 2018"


Journal ArticleDOI
Mary F. Feitosa1, Aldi T. Kraja1, Daniel I. Chasman2, Yun J. Sung1  +296 moreInstitutions (86)
18 Jun 2018-PLOS ONE
TL;DR: In insights into the role of alcohol consumption in the genetic architecture of hypertension, a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions is conducted.
Abstract: Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

1,218 citations


Journal ArticleDOI
16 May 2018-PLOS ONE
TL;DR: The RAVDESS is a validated multimodal database of emotional speech and song consisting of 24 professional actors, vocalizing lexically-matched statements in a neutral North American accent, which shows high levels of emotional validity and test-retest intrarater reliability.
Abstract: The RAVDESS is a validated multimodal database of emotional speech and song. The database is gender balanced consisting of 24 professional actors, vocalizing lexically-matched statements in a neutral North American accent. Speech includes calm, happy, sad, angry, fearful, surprise, and disgust expressions, and song contains calm, happy, sad, angry, and fearful emotions. Each expression is produced at two levels of emotional intensity, with an additional neutral expression. All conditions are available in face-and-voice, face-only, and voice-only formats. The set of 7356 recordings were each rated 10 times on emotional validity, intensity, and genuineness. Ratings were provided by 247 individuals who were characteristic of untrained research participants from North America. A further set of 72 participants provided test-retest data. High levels of emotional validity and test-retest intrarater reliability were reported. Corrected accuracy and composite "goodness" measures are presented to assist researchers in the selection of stimuli. All recordings are made freely available under a Creative Commons license and can be downloaded at https://doi.org/10.5281/zenodo.1188976.

1,036 citations


Journal ArticleDOI
18 Oct 2018-PLOS ONE
TL;DR: The core of miRWalk is the miRNA target site prediction with the random-forest-based approach software TarPmiR searching the complete transcript sequence including the 5’-UTR, CDS and 3’ -UTR.
Abstract: miRWalk is an open-source platform providing an intuitive interface that generates predicted and validated miRNA-binding sites of known genes of human, mouse, rat, dog and cow. The core of miRWalk is the miRNA target site prediction with the random-forest-based approach software TarPmiR searching the complete transcript sequence including the 5’-UTR, CDS and 3’-UTR. Moreover, it integrates results other databases with predicted and validated miRNA-target interactions. The focus is set on a modular design and extensibility as well as a fast update cycle. The database is available using Python, MySQL and HTML/Javascript Database URL: http://mirwalk.umm.uni-heidelberg.de.

902 citations


Journal ArticleDOI
27 Mar 2018-PLOS ONE
TL;DR: It is found that the post-sample accuracy of popular ML methods are dominated across both accuracy measures used and for all forecasting horizons examined, and that their computational requirements are considerably greater than those of statistical methods.
Abstract: Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions.

800 citations


Journal ArticleDOI
25 Jan 2018-PLOS ONE
TL;DR: In this paper, the authors investigated the neuro-regenerative potential of Sema3A on adult peripheral nervous system neurons such as those that innervate the cornea and found that upon cornea injury, there is a fast increase in Semaphorin3A expression.
Abstract: The peripheral sensory nerves that innervate the cornea can be easily damaged by trauma, surgery, infection or diabetes. Several growth factors and axon guidance molecules, such as Semaphorin3A (Sema3A) are upregulated upon cornea injury. Nerves can regenerate after injury but do not recover their original density and patterning. Sema3A is a well known axon guidance and growth cone repellent protein during development, however its role in adult cornea nerve regeneration remains undetermined. Here we investigated the neuro-regenerative potential of Sema3A on adult peripheral nervous system neurons such as those that innervate the cornea. First, we examined the gene expression profile of the Semaphorin class 3 family members and found that all are expressed in the cornea. However, upon cornea injury there is a fast increase in Sema3A expression. We then corroborated that Sema3A totally abolished the growth promoting effect of nerve growth factor (NGF) on embryonic neurons and observed signs of growth cone collapse and axonal retraction after 30 min of Sema3A addition. However, in adult isolated trigeminal ganglia or dorsal root ganglia neurons, Sema3A did not inhibited the NGF-induced neuronal growth. Furthermore, adult neurons treated with Sema3A alone produced similar neuronal growth to cells treated with NGF and the length of the neurites and branching was comparable between both treatments. These effects were replicated in vivo, where thy1-YFP neurofluorescent mice subjected to cornea epithelium debridement and receiving intrastromal pellet implantation containing Sema3A showed increased corneal nerve regeneration than those receiving pellets with vehicle. In adult PNS neurons, Sema3A is a potent inducer of neuronal growth in vitro and cornea nerve regeneration in vivo. Our data indicates a functional switch for the role of Sema3A in PNS neurons where the well-described repulsive role during development changes to a growth promoting effect during adulthood. The high expression of Sema3A in the normal and injured adult corneas could be related to its role as a growth factor.

674 citations


Journal ArticleDOI
07 Dec 2018-PLOS ONE
TL;DR: The 5C scale provides a novel tool to monitor psychological antecedents of vaccination and facilitates diagnosis, intervention design and evaluation and its short version is suitable for field settings and regular global monitoring of relevant antecedent vaccination.
Abstract: Background Monitoring the reasons why a considerable number of people do not receive recommended vaccinations allows identification of important trends over time, and designing and evaluating strategies to address vaccine hesitancy and increase vaccine uptake. Existing validated measures assessing vaccine hesitancy focus primarily on confidence in vaccines and the system that delivers them. However, empirical and theoretical work has stated that complacency (not perceiving diseases as high risk), constraints (structural and psychological barriers), calculation (engagement in extensive information searching), and aspects pertaining to collective responsibility (willingness to protect others) also play a role in explaining vaccination behavior. The objective was therefore to develop a validated measure of these 5C psychological antecedents of vaccination. Methods and findings Three cross-sectional studies were conducted. Study 1 uses factor analysis to develop an initial scale and assesses the sub-scales' convergent, discriminant, and concurrent validity (N = 1,445, two German convenience-samples). In Study 2, a sample representative regarding age and gender for the German population (N = 1,003) completed the measure for vaccination in general and for specific vaccinations to assess the potential need for a vaccine-specific wording of items. Study 3 compared the novel scale's performance with six existing measures of vaccine hesitancy (N = 350, US convenience-sample). As an outcome, a long (15-item) and short (5-item) 5C scale were developed as reliable and valid indicators of confidence, complacency, constraints, calculation, and collective responsibility. The 5C sub-scales correlated with relevant psychological concepts, such as attitude (confidence), perceived personal health status and invulnerability (complacency), self-control (constraints), preference for deliberation (calculation), and communal orientation (collective responsibility), among others. The new scale provided similar results when formulated in a general vs. vaccine-specific way (Study 2). In a comparison of seven measures the 5C scale was constantly among the scales that explained the highest amounts of variance in analyses predicting single vaccinations (between 20% and 40%; Study 3). The present studies are limited to the concurrent validity of the scales. Conclusions The 5C scale provides a novel tool to monitor psychological antecedents of vaccination and facilitates diagnosis, intervention design and evaluation. Its short version is suitable for field settings and regular global monitoring of relevant antecedents of vaccination.

623 citations


Journal ArticleDOI
11 Apr 2018-PLOS ONE
TL;DR: Based on consumer guidelines, the results indicate the average person ingests over 5,800 particles of synthetic debris from these three sources annually, with the largest contribution coming from tap water (88%).
Abstract: Plastic pollution has been well documented in natural environments, including the open waters and sediments within lakes and rivers, the open ocean and even the air, but less attention has been paid to synthetic polymers in human consumables. Since multiple toxicity studies indicate risks to human health when plastic particles are ingested, more needs to be known about the presence and abundance of anthropogenic particles in human foods and beverages. This study investigates the presence of anthropogenic particles in 159 samples of globally sourced tap water, 12 brands of Laurentian Great Lakes beer, and 12 brands of commercial sea salt. Of the tap water samples analyzed, 81% were found to contain anthropogenic particles. The majority of these particles were fibers (98.3%) between 0.1-5 mm in length. The range was 0 to 61 particles/L, with an overall mean of 5.45 particles/L. Anthropogenic debris was found in each brand of beer and salt. Of the extracted particles, over 99% were fibers. After adjusting for particles found in lab blanks for both salt and beer, the average number of particles found in beer was 4.05 particles/L with a range of 0 to 14.3 particles/L and the average number of particles found in each brand of salt was 212 particles/kg with a range of 46.7 to 806 particles/kg. Based on consumer guidelines, our results indicate the average person ingests over 5,800 particles of synthetic debris from these three sources annually, with the largest contribution coming from tap water (88%).

596 citations


Journal ArticleDOI
30 Aug 2018-PLOS ONE
TL;DR: While the review identified increased presentations by the elderly with complex and chronic conditions as an emerging and widespread driver of crowding, more research is required to isolate the precise local factors leading to ED crowding.
Abstract: Background Emergency department crowding is a major global healthcare issue. There is much debate as to the causes of the phenomenon, leading to difficulties in developing successful, targeted solutions. Aim The aim of this systematic review was to critically analyse and summarise the findings of peer-reviewed research studies investigating the causes and consequences of, and solutions to, emergency department crowding. Method The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A structured search of four databases (Medline, CINAHL, EMBASE and Web of Science) was undertaken to identify peer-reviewed research publications aimed at investigating the causes or consequences of, or solutions to, emergency department crowding, published between January 2000 and June 2018. Two reviewers used validated critical appraisal tools to independently assess the quality of the studies. The study protocol was registered with the International prospective register of systematic reviews (PROSPERO 2017: CRD42017073439). Results From 4,131 identified studies and 162 full text reviews, 102 studies met the inclusion criteria. The majority were retrospective cohort studies, with the greatest proportion (51%) trialling or modelling potential solutions to emergency department crowding. Fourteen studies examined causes and 40 investigated consequences. Two studies looked at both causes and consequences, and two investigated causes and solutions. Conclusions The negative consequences of ED crowding are well established, including poorer patient outcomes and the inability of staff to adhere to guideline-recommended treatment. This review identified a mismatch between causes and solutions. The majority of identified causes related to the number and type of people attending ED and timely discharge from ED, while reported solutions focused on efficient patient flow within the ED. Solutions aimed at the introduction of whole-of-system initiatives to meet timed patient disposition targets, as well as extended hours of primary care, demonstrated promising outcomes. While the review identified increased presentations by the elderly with complex and chronic conditions as an emerging and widespread driver of crowding, more research is required to isolate the precise local factors leading to ED crowding, with system-wide solutions tailored to address identified causes.

568 citations


Journal ArticleDOI
26 Dec 2018-PLOS ONE
TL;DR: It is demonstrated that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis, and the high information content of nuclear RNA for characterization of cellular diversity in brain tissues is illustrated.
Abstract: Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.

368 citations


Journal ArticleDOI
20 Mar 2018-PLOS ONE
TL;DR: A healthy lifestyle pattern could lead to decreased risk for T2DM, and future randomized clinical trials should focus on identifying efficient strategies to modify harmful daily habits and predisposing dietary patterns.
Abstract: Background Type 2 diabetes mellitus (T2DM) is a global epidemic associated with increased health expenditure, and low quality of life. Many non-genetic risk factors have been suggested, but their overall epidemiological credibility has not been assessed. Methods We searched PubMed to capture all meta-analyses and Mendelian randomization studies for risk factors of T2DM. For each association, we estimated the summary effect size, its 95% confidence and prediction interval, and the I2 metric. We examined the presence of small-study effects and excess significance bias. We assessed the epidemiological credibility through a set of predefined criteria. Results We captured 86 eligible papers (142 associations) covering a wide range of biomarkers, medical conditions, and dietary, lifestyle, environmental and psychosocial factors. Adiposity, low hip circumference, serum biomarkers (increased level of alanine aminotransferase, gamma-glutamyl transferase, uric acid and C-reactive protein, and decreased level of adiponectin and vitamin D), an unhealthy dietary pattern (increased consumption of processed meat and sugar-sweetened beverages, decreased intake of whole grains, coffee and heme iron, and low adherence to a healthy dietary pattern), low level of education and conscientiousness, decreased physical activity, high sedentary time and duration of television watching, low alcohol drinking, smoking, air pollution, and some medical conditions (high systolic blood pressure, late menarche age, gestational diabetes, metabolic syndrome, preterm birth) presented robust evidence for increased risk of T2DM. Conclusions A healthy lifestyle pattern could lead to decreased risk for T2DM. Future randomized clinical trials should focus on identifying efficient strategies to modify harmful daily habits and predisposing dietary patterns.

360 citations


Journal ArticleDOI
11 Jan 2018-PLOS ONE
TL;DR: High incidence and prevalence levels for patellofemoral pain are demonstrated and within the context of this, and poor long term prognosis and high disability levels, PFP should be an urgent research priority.
Abstract: Background: Patellofemoral pain is considered one of the most common forms of knee pain, affecting adults, adolescents, and physically active populations. Inconsistencies in reported incidence and prevalence exist and in relation to the allocation of healthcare and research funding, there is a clear need to accurately understand the epidemiology of patellofemoral pain. Methods: An electronic database search was conducted, as well as grey literature databases, from inception to June 2017. Two authors independently selected studies, extracted data and appraised methodological quality. If heterogeneous, data were analysed descriptively. Where studies were homogeneous, data were pooled through a meta-analysis. Results: 23 studies were included. Annual prevalence for patellofemoral pain in the general population was reported as 22.7%, and adolescents as 28.9%. Incidence rates in military recruits ranged from 9.7 – 571.4/1,000 person-years, amateur runners in the general population at 1080.5/1,000 person-years and adolescents amateur athletes 5.1% - 14.9% over 1 season. One study reported point prevalence within military populations as 13.5%. The pooled estimate for point prevalence in adolescents was 7.2% (95% Confidence Interval: 6.3% - 8.3%), and in female only adolescent athletes was 22.7% (95% Confidence Interval 17.4% - 28.0%). Conclusion: This review demonstrates high incidence and prevalence levels for patellofemoral pain. Within the context of this, and poor long term prognosis and high disability levels, PFP should be an urgent research priority.

Journal ArticleDOI
01 Aug 2018-PLOS ONE
TL;DR: It is shown that the most commonly used plastics produce two greenhouse gases, methane and ethylene, when exposed to ambient solar radiation, and plastics represent a heretofore unrecognized source of climate-relevant trace gases that are expected to increase as more plastic is produced and accumulated in the environment.
Abstract: Mass production of plastics started nearly 70 years ago and the production rate is expected to double over the next two decades. While serving many applications because of their durability, stability and low cost, plastics have deleterious effects on the environment. Plastic is known to release a variety of chemicals during degradation, which has a negative impact on biota. Here, we show that the most commonly used plastics produce two greenhouse gases, methane and ethylene, when exposed to ambient solar radiation. Polyethylene, which is the most produced and discarded synthetic polymer globally, is the most prolific emitter of both gases. We demonstrate that the production of trace gases from virgin low-density polyethylene increase with time, with rates at the end of a 212-day incubation of 5.8 nmol g-1 d-1 of methane, 14.5 nmol g-1 d-1 of ethylene, 3.9 nmol g-1 d-1 of ethane and 9.7 nmol g-1 d-1 of propylene. Environmentally aged plastics incubated in water for at least 152 days also produced hydrocarbon gases. In addition, low-density polyethylene emits these gases when incubated in air at rates ~2 times and ~76 times higher than when incubated in water for methane and ethylene, respectively. Our results show that plastics represent a heretofore unrecognized source of climate-relevant trace gases that are expected to increase as more plastic is produced and accumulated in the environment.

Journal ArticleDOI
04 Jan 2018-PLOS ONE
TL;DR: Loneliness shows a harmful effect for all-cause mortality and this effect is slightly stronger in men than in women, which was independent from the quality evaluation of each article and the effect of depression.
Abstract: Introduction Loneliness has social and health implications. The aim of this article is to evaluate the association of loneliness with all-cause mortality. Methods Pubmed, PsycINFO, CINAHL and Scopus databases were searched through June 2016 for published articles that measured loneliness and mortality. The main characteristics and the effect size values of each article were extracted. Moreover, an evaluation of the quality of the articles included was also carried out. A meta-analysis was performed firstly with all the included articles and secondly separating by gender, using a random effects model. Results A total of 35 articles involving 77220 participants were included in the systematic review. Loneliness is a risk factor for all-cause mortality [pooled HR = 1.22, 95% CI = (1.10, 1.35), p < 0.001] for both genders together, and for women [pooled HR = 1.26, 95% CI = (1.07, 1.48); p = 0.005] and men [pooled HR = 1.44; 95% CI = (1.19, 1.76); p < 0.001] separately. Conclusions Loneliness shows a harmful effect for all-cause mortality and this effect is slightly stronger in men than in women. Moreover, the impact of loneliness was independent from the quality evaluation of each article and the effect of depression.

Journal ArticleDOI
29 Mar 2018-PLOS ONE
TL;DR: Specific school food environment policies can improve targeted dietary behaviors; effects on adiposity and metabolic risk require further investigation.
Abstract: Background School food environment policies may be a critical tool to promote healthy diets in children, yet their effectiveness remains unclear. Objective To systematically review and quantify the impact of school food environment policies on dietary habits, adiposity, and metabolic risk in children. Methods We systematically searched online databases for randomized or quasi-experimental interventions assessing effects of school food environment policies on children’s dietary habits, adiposity, or metabolic risk factors. Data were extracted independently and in duplicate, and pooled using inverse-variance random-effects meta-analysis. Habitual (within+outside school) dietary intakes were the primary outcome. Heterogeneity was explored using meta-regression and subgroup analysis. Funnel plots, Begg’s and Egger’s test evaluated potential publication bias. Results From 6,636 abstracts, 91 interventions (55 in US/Canada, 36 in Europe/New Zealand) were included, on direct provision of healthful foods/beverages (N = 39 studies), competitive food/beverage standards (N = 29), and school meal standards (N = 39) (some interventions assessed multiple policies). Direct provision policies, which largely targeted fruits and vegetables, increased consumption of fruits by 0.27 servings/d (n = 15 estimates (95%CI: 0.17, 0.36)) and combined fruits and vegetables by 0.28 servings/d (n = 16 (0.17, 0.40)); with a slight impact on vegetables (n = 11; 0.04 (0.01, 0.08)), and no effects on total calories (n = 6; -56 kcal/d (-174, 62)). In interventions targeting water, habitual intake was unchanged (n = 3; 0.33 glasses/d (-0.27, 0.93)). Competitive food/beverage standards reduced sugar-sweetened beverage intake by 0.18 servings/d (n = 3 (-0.31, -0.05)); and unhealthy snacks by 0.17 servings/d (n = 2 (-0.22, -0.13)), without effects on total calories (n = 5; -79 kcal/d (-179, 21)). School meal standards (mainly lunch) increased fruit intake (n = 2; 0.76 servings/d (0.37, 1.16)) and reduced total fat (-1.49%energy; n = 6 (-2.42, -0.57)), saturated fat (n = 4; -0.93%energy (-1.15, -0.70)) and sodium (n = 4; -170 mg/d (-242, -98)); but not total calories (n = 8; -38 kcal/d (-137, 62)). In 17 studies evaluating adiposity, significant decreases were generally not identified; few studies assessed metabolic factors (blood lipids/glucose/pressure), with mixed findings. Significant sources of heterogeneity or publication bias were not identified. Conclusions Specific school food environment policies can improve targeted dietary behaviors; effects on adiposity and metabolic risk require further investigation. These findings inform ongoing policy discussions and debates on best practices to improve childhood dietary habits and health.

Journal ArticleDOI
17 Oct 2018-PLOS ONE
TL;DR: Results show that participants who performed any type of perspective-taking task reported feeling more empathetic and connected to the homeless than the participants who only received information, and the theoretical and practical implications of these findings are discussed.
Abstract: Virtual Reality (VR) has been increasingly referred to as the “ultimate empathy machine” since it allows users to experience any situation from any point of view. However, empirical evidence supporting the claim that VR is a more effective method of eliciting empathy than traditional perspective-taking is limited. Two experiments were conducted in order to compare the short and long-term effects of a traditional perspective-taking task and a VR perspective-taking task (Study 1), and to explore the role of technological immersion when it comes to different types of mediated perspective-taking tasks (Study 2). Results of Study 1 show that over the course of eight weeks participants in both conditions reported feeling empathetic and connected to the homeless at similar rates, however, participants who became homeless in VR had more positive, longer-lasting attitudes toward the homeless and signed a petition supporting the homeless at a significantly higher rate than participants who performed a traditional perspective-taking task. Study 2 compared three different types of perspective-taking tasks with different levels of immersion (traditional vs. desktop computer vs. VR) and a control condition (where participants received fact-driven information about the homeless). Results show that participants who performed any type of perspective-taking task reported feeling more empathetic and connected to the homeless than the participants who only received information. Replicating the results from Study 1, there was no difference in self-report measures for any of the perspective-taking conditions, however, a significantly higher number of participants in the VR condition signed a petition supporting affordable housing for the homeless compared to the traditional and less immersive conditions. We discuss the theoretical and practical implications of these findings.

Journal ArticleDOI
12 Apr 2018-PLOS ONE
TL;DR: This systematic review provides a comprehensive comparison of methodologies used in studies of the prevalence of psychosis, which can provide insightful information for future epidemiological studies in adopting the most relevant methodological approach.
Abstract: Objectives The purpose of this study is to provide an updated systematic review to identify studies describing the prevalence of psychosis in order to explore methodological factors that could account for the variation in prevalence estimates. Methods Studies with original data related to the prevalence of psychosis (published between 1990 and 2015) were identified via searching electronic databases and reviewing manual citations. Prevalence estimates were sorted according to prevalence type (point, 12-months and lifetime). The independent association between key methodological variables and the mean effect of prevalence was examined (prevalence type, case-finding setting, method of confirming diagnosis, international classification of diseases, diagnosis category, and study quality) by meta-analytical techniques and random-effects meta-regression. Results Seventy-three primary studies were included, providing a total of 101 estimates of prevalence rates of psychosis. Across these studies, the pooled median point and 12-month prevalence for persons was 3.89 and 4.03 per 1000 respectively; and the median lifetime prevalence was 7.49 per 1000. The result of the random-effects meta-regression analysis revealed a significant effect for the prevalence type, with higher rates of lifetime prevalence than 12-month prevalence (p<0.001). Studies conducted in the general population presented higher prevalence rates than those carried out in populations attended in health/social services (p = 0.006). Compared to the diagnosis of schizophrenia only, prevalence rates were higher in the probable psychotic disorder (p = 0.022) and non-affective psychosis (p = 0.009). Finally, a higher study quality is associated with a lower estimated prevalence of psychotic disorders (p<0.001). Conclusions This systematic review provides a comprehensive comparison of methodologies used in studies of the prevalence of psychosis, which can provide insightful information for future epidemiological studies in adopting the most relevant methodological approach.

Journal ArticleDOI
13 Jul 2018-PLOS ONE
TL;DR: This study predicts the spatial patterns of land use in 2025 and 2036 based on the dynamic changes in land use patterns using remote sensing and geographic information system and can provide suggestions and a basis for urban development planning in Jiangle County.
Abstract: Land use and land cover change research has been applied to landslides, erosion, land planning and global change. Based on the CA-Markov model, this study predicts the spatial patterns of land use in 2025 and 2036 based on the dynamic changes in land use patterns using remote sensing and geographic information system. CA-Markov integrates the advantages of cellular automata and Markov chain analysis to predict future land use trends based on studies of land use changes in the past. Based on Landsat 5 TM images from 1992 and 2003 and Landsat 8 OLI images from 2014, this study obtained a land use classification map for each year. Then, the genetic transition probability from 1992 to 2003 was obtained by IDRISI software. Based on the CA-Markov model, a predicted land use map for 2014 was obtained, and it was validated by the actual land use results of 2014 with a Kappa index of 0.8128. Finally, the land use patterns of 2025 and 2036 in Jiangle County were determined. This study can provide suggestions and a basis for urban development planning in Jiangle County.

Journal ArticleDOI
17 Apr 2018-PLOS ONE
TL;DR: Maternity care should be designed to fulfil or exceed womens’ personal and socio-cultural beliefs and expectations, and most healthy childbearing women want a positive birth experience.
Abstract: Introduction Design and provision of good quality maternity care should incorporate what matters to childbearing women. This qualitative systematic review was undertaken to inform WHO intrapartum guidelines. Methods Using a pre-determined search strategy, we searched Medline, CINAHL, PsycINFO, AMED, EMBASE, LILACS, AJOL, and reference lists of eligible studies published 1996-August 2016 (updated to January 2018), reporting qualitative data on womens’ childbirth beliefs, expectations, and values. Studies including specific interventions or health conditions were excluded. PRISMA guidelines were followed. Data collection and analysis Authors’ findings were extracted, logged on a study-specific data form, and synthesised using meta-ethnographic techniques. Confidence in the quality, coherence, relevance and adequacy of data underpinning the resulting themes was assessed using GRADE-CERQual. A line of argument synthesis was developed. Results 35 studies (19 countries) were included in the primary search, and 2 in the update. Confidence in most results was moderate to high. What mattered to most women was a positive experience that fulfilled or exceeded their prior personal and socio-cultural beliefs and expectations. This included giving birth to a healthy baby in a clinically and psychologically safe environment with practical and emotional support from birth companions, and competent, reassuring, kind clinical staff. Most wanted a physiological labour and birth, while acknowledging that birth can be unpredictable and frightening, and that they may need to ‘go with the flow’. If intervention was needed or wanted, women wanted to retain a sense of personal achievement and control through active decision-making. These values and expectations were mediated through womens’ embodied (physical and psychosocial) experience of pregnancy and birth; local familial and sociocultural norms; and encounters with local maternity services and staff. Conclusions Most healthy childbearing women want a positive birth experience. Safety and psychosocial wellbeing are equally valued. Maternity care should be designed to fulfil or exceed womens’ personal and socio-cultural beliefs and expectations.

Journal ArticleDOI
22 Aug 2018-PLOS ONE
TL;DR: This study performed the first quantitative, medium-N analysis of snowball sampling to identify pathways to sample diversity, analysing 211 reach-outs conducted via snowball sampling, resulting in 81 interviews; these interviews were administered for a research project on anti-dam movements in Southeast Asia.
Abstract: Snowball sampling is a commonly employed sampling method in qualitative research; however, the diversity of samples generated via this method has repeatedly been questioned. Scholars have posited several anecdotally based recommendations for enhancing the diversity of snowball samples. In this study, we performed the first quantitative, medium-N analysis of snowball sampling to identify pathways to sample diversity, analysing 211 reach-outs conducted via snowball sampling, resulting in 81 interviews; these interviews were administered between April and August 2015 for a research project on anti-dam movements in Southeast Asia. Based upon this analysis, we were able to refine and enhance the previous recommendations (e.g., showcasing novel evidence on the value of multiple seeds or face-to-face interviews). This paper may thus be of particular interest to scholars employing or intending to employ snowball sampling.

Journal ArticleDOI
30 Oct 2018-PLOS ONE
TL;DR: This work proposes an attention-based hybrid CNN and RNN (CNN-RNN) architecture to better capture temporal properties of electromyogram signal for gesture recognition problem and presents a new sEMG image representation method based on a traditional feature vector which enables deep learning architectures to extract implicit correlations between different channels for sparse multi-channel electromyograms.
Abstract: The surface electromyography (sEMG)-based gesture recognition with deep learning approach plays an increasingly important role in human-computer interaction. Existing deep learning architectures are mainly based on Convolutional Neural Network (CNN) architecture which captures spatial information of electromyogram signal. Motivated by the sequential nature of electromyogram signal, we propose an attention-based hybrid CNN and RNN (CNN-RNN) architecture to better capture temporal properties of electromyogram signal for gesture recognition problem. Moreover, we present a new sEMG image representation method based on a traditional feature vector which enables deep learning architectures to extract implicit correlations between different channels for sparse multi-channel electromyogram signal. Extensive experiments on five sEMG benchmark databases show that the proposed method outperforms all reported state-of-the-art methods on both sparse multi-channel and high-density sEMG databases. To compare with the existing works, we set the window length to 200ms for NinaProDB1 and NinaProDB2, and 150ms for BioPatRec sub-database, CapgMyo sub-database, and csl-hdemg databases. The recognition accuracies of the aforementioned benchmark databases are 87.0%, 82.2%, 94.1%, 99.7% and 94.5%, which are 9.2%, 3.5%, 1.2%, 0.2% and 5.2% higher than the state-of-the-art performance, respectively.

Journal ArticleDOI
02 Jan 2018-PLOS ONE
TL;DR: A large negative correlation between the 5-Year-Impact-Factor of a journal and the female representation at prestigious authorships was revealed and a very slow harmonization of authorships odds between the two genders was forecast.
Abstract: Background The present study aims to elucidate the state of gender equality in high-quality research by analyzing the representation of female authorships in the last decade (from 2008 to 2016). Methods Based on the Gendermetrics platform, 293,557 research articles from 54 journals listed in the Nature Index were considered covering the categories Life Science, Multidisciplinary, Earth & Environmental and Chemistry. The core method was the combined analysis of the proportion of female authorships and the female-to-male odds ratio for first, co- and last authorships. The distribution of prestigious authorships was measured by the Prestige Index. Results 29.8% of all authorships and 33.1% of the first, 31.8% of the co- and 18.1% of the last authorships were held by women. The corresponding female-to-male odds ratio is 1.19 (CI: 1.18-1.20) for first, 1.35 (CI: 1.34-1.36) for co- and 0.47 (CI: 0.46-0.48) for last authorships. Women are underrepresented at prestigious authorships compared to men (Prestige Index = -0.42). The underrepresentation accentuates in highly competitive articles attracting the highest citation rates, namely, articles with many authors and articles that were published in highest-impact journals. More specifically, a large negative correlation between the 5-Year-Impact-Factor of a journal and the female representation at prestigious authorships was revealed (r(52) = -.63, P

Journal ArticleDOI
12 Nov 2018-PLOS ONE
TL;DR: The prevalence of burnout syndrome was significantly higher among surgical/urgency residencies than in clinical specialties, and among medical residents in general surgery, internal medicine, plastic surgery and pediatrics.
Abstract: Background Burnout is a psychological syndrome that is very common among medical residents. It consists of emotional exhaustion (EE), depersonalization (DP) and reduced personal accomplishment (PA). Objective To estimate burnout among different medical residency specialties. Methods A systematic review with meta-analysis was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A search of bibliographic databases and grey literature was conducted, from inception to March 2018. The following databases were accessed: Embase, PubMed, Web of Science, Google Scholar and Scopus, and 3,575 studies were found. Methodological quality was evaluated by Agency for Healthcare Research and Quality Methodology Checklist for Cross-Sectional/Prevalence Study. In the final analysis, 26 papers were included. Their references were checked for additional studies, but none were included. Results 4,664 medical residents were included. High DP, EE and low PA proportions were compared. Specialties were distributed into three groups of different levels of burnout prevalence: general surgery, anesthesiology, obstetrics/gynecology and orthopedics (40.8%); internal medicine, plastic surgery and pediatrics (30.0%); and otolaryngology and neurology (15.4%). Overall burnout prevalence found for all specialties was 35.7%. Conclusion The prevalence of burnout syndrome was significantly higher among surgical/urgency residencies than in clinical specialties. Prospero registration CRD42018090270.

Journal ArticleDOI
08 Oct 2018-PLOS ONE
TL;DR: This paper describes the collection and fine-grained annotation of a cyberbullying corpus for English and Dutch and performs a series of binary classification experiments to determine the feasibility of automatic cyberbullies detection.
Abstract: While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online. Recent studies report that cyberbullying constitutes a growing problem among youngsters. Successful prevention depends on the adequate detection of potentially harmful messages and the information overload on the Web requires intelligent systems to identify potential risks automatically. The focus of this paper is on automatic cyberbullying detection in social media text by modelling posts written by bullies, victims, and bystanders of online bullying. We describe the collection and fine-grained annotation of a cyberbullying corpus for English and Dutch and perform a series of binary classification experiments to determine the feasibility of automatic cyberbullying detection. We make use of linear support vector machines exploiting a rich feature set and investigate which information sources contribute the most for the task. Experiments on a hold-out test set reveal promising results for the detection of cyberbullying-related posts. After optimisation of the hyperparameters, the classifier yields an F1 score of 64% and 61% for English and Dutch respectively, and considerably outperforms baseline systems.

Journal ArticleDOI
20 Sep 2018-PLOS ONE
TL;DR: A network simulation model used to study a possible relationship between echo chambers and the viral spread of misinformation finds an “echo chamber effect”: the presence of an opinion and network polarized cluster of nodes in a network contributes to the diffusion of complex contagions.
Abstract: The viral spread of digital misinformation has become so severe that the World Economic Forum considers it among the main threats to human society This spread have been suggested to be related to the similarly problematized phenomenon of “echo chambers”, but the causal nature of this relationship has proven difficult to disentangle due to the connected nature of social media, whose causality is characterized by complexity, non-linearity and emergence This paper uses a network simulation model to study a possible relationship between echo chambers and the viral spread of misinformation It finds an “echo chamber effect”: the presence of an opinion and network polarized cluster of nodes in a network contributes to the diffusion of complex contagions, and there is a synergetic effect between opinion and network polarization on the virality of misinformation The echo chambers effect likely comes from that they form the initial bandwagon for diffusion These findings have implication for the study of the media logic of new social media

Journal ArticleDOI
11 Jun 2018-PLOS ONE
TL;DR: Data shows that methods other than differential centrifugation can be applied to quickly and efficiently isolate exosomes from reduced biofluid volumes and the possibility to use small volumes is fundamental in the context of translational and clinical research, thus the results here presented contribute significantly in this respect.
Abstract: The potential of exosomes as biomarker resources for diagnostics, prognostics and even for therapeutics is an area of intense research. Despite the various approaches available, there is no consensus with respect to the best methodology for isolating exosomes and to provide substantial yields with reliable quality. Differential centrifugation is the most commonly used method but it is time-consuming and requires large sample volumes, thus alternative methods are urgently needed. In this study two precipitation-based methods and one column-based approach were compared for exosome isolation from distinct biofluids (serum, plasma and cerebrospinal fluid). Exosome characterization included morphological analyses, determination of particle concentration, stability and exosome preparations’ purity, using different complementary approaches such as Nanoparticle Tracking Analysis, Electrophoretic Light Scattering, Transmission Electron Microscopy, EXOCET colorimetric assay, protein quantification methods and western blotting. The three commercial kits tested successfully isolated exosomes from the biofluids under study, although ExoS showed the best performance in terms of exosome yield and purity. Data shows that methods other than differential centrifugation can be applied to quickly and efficiently isolate exosomes from reduced biofluid volumes. The possibility to use small volumes is fundamental in the context of translational and clinical research, thus the results here presented contribute significantly in this respect.

Journal ArticleDOI
31 May 2018-PLOS ONE
TL;DR: This review supports the effectiveness of MHFA training in improving mental health literacy and appropriate support for those with mental health problems up to 6 months after training.
Abstract: Objective To provide an up-to-date assessment of the effectiveness of the Mental Health First Aid (MHFA) training program on improving mental health knowledge, stigma and helping behaviour. Design Systematic review and meta-analysis. Methods A systematic search of electronic databases was conducted in October 2017 to identify randomised controlled trials or controlled trials of the MHFA program. Eligible trials were in adults, used any comparison condition, and assessed one or more of the following outcomes: mental health first aid knowledge; recognition of mental disorders; treatment knowledge; stigma and social distance; confidence in or intentions to provide mental health first aid; provision of mental health first aid; mental health of trainees or recipients of mental health first aid. Risk of bias was assessed and effect sizes (Cohen's d) were pooled using a random effects model. Separate meta-analyses examined effects at post-training, up to 6 months post-training, and greater than 6 months post-training. Results A total of 18 trials (5936 participants) were included. Overall, effects were generally small-to-moderate post-training and up to 6 months later, with effects up to 12-months later unclear. MHFA training led to improved mental health first aid knowledge (ds 0.31-0.72), recognition of mental disorders (ds 0.22-0.52) and beliefs about effective treatments (ds 0.19-0.45). There were also small reductions in stigma (ds 0.08-0.14). Improvements were also observed in confidence in helping a person with a mental health problem (ds 0.21-0.58) and intentions to provide first aid (ds 0.26-0.75). There were small improvements in the amount of help provided to a person with a mental health problem at follow-up (d = 0.23) but changes in the quality of behaviours offered were unclear. Conclusion This review supports the effectiveness of MHFA training in improving mental health literacy and appropriate support for those with mental health problems up to 6 months after training. Trial registration PROSPERO (CRD42017060596).

Journal ArticleDOI
09 Aug 2018-PLOS ONE
TL;DR: In high income countries, caloric supply and urbanization were positively associated with the number of overweight and obese pregnant women, and the percentage of employment in agriculture was inversely associated withThe number of obese pregnantWomen, but only in upper middle income countries and lowermiddle income countries.
Abstract: Objective To estimate the global and country-level burden of overweight and obesity among pregnant women from 2005 to 2014. Methods Publicly accessible country-level data were collected from the World Health Organization, the World Bank and the Food and Agricultural Organization. We estimated the number of overweight and obese pregnant women among 184 countries and determined the time-related trend from 2005 to 2014. Based on panel data model, we determined the effects of food energy supply, urbanization, gross national income and female employment on the number of overweight and obese pregnant women. Results We estimated that 38.9 million overweight and obese pregnant women and 14.6 million obese pregnant women existed globally in 2014. In upper middle income countries and lower middle income countries, there were sharp increases in the number of overweight and obese pregnant women. In 2014, the percentage of female with overweight and obesity in India was 21.7%, and India had the largest number of overweight and obese pregnant women (4.3 million), which accounted for 11.1% in the world. In the United States of America, a third of women were obese, and the number of obese pregnant women was 1.1 million. In high income countries, caloric supply and urbanization were positively associated with the number of overweight and obese pregnant women. The percentage of employment in agriculture was inversely associated with the number of overweight and obese pregnant women, but only in upper middle income countries and lower middle income countries. Conclusion The number of overweight and obese pregnant women has increased in high income and middle income countries. Environmental changes could lead to increased caloric supply and decreased energy expenditure among women. National and local governments should work together to create a healthy food environment.

Journal ArticleDOI
20 Jun 2018-PLOS ONE
TL;DR: The concept of saturation in salience is advanced and probing to increase the amount of information collected per respondent to increase sample efficiency is focused on.
Abstract: Sample size determination for open-ended questions or qualitative interviews relies primarily on custom and finding the point where little new information is obtained (thematic saturation). Here, we propose and test a refined definition of saturation as obtaining the most salient items in a set of qualitative interviews (where items can be material things or concepts, depending on the topic of study) rather than attempting to obtain all the items. Salient items have higher prevalence and are more culturally important. To do this, we explore saturation, salience, sample size, and domain size in 28 sets of interviews in which respondents were asked to list all the things they could think of in one of 18 topical domains. The domains-like kinds of fruits (highly bounded) and things that mothers do (unbounded)-varied greatly in size. The datasets comprise 20-99 interviews each (1,147 total interviews). When saturation was defined as the point where less than one new item per person would be expected, the median sample size for reaching saturation was 75 (range = 15-194). Thematic saturation was, as expected, related to domain size. It was also related to the amount of information contributed by each respondent but, unexpectedly, was reached more quickly when respondents contributed less information. In contrast, a greater amount of information per person increased the retrieval of salient items. Even small samples (n = 10) produced 95% of the most salient ideas with exhaustive listing, but only 53% of those items were captured with limited responses per person (three). For most domains, item salience appeared to be a more useful concept for thinking about sample size adequacy than finding the point of thematic saturation. Thus, we advance the concept of saturation in salience and emphasize probing to increase the amount of information collected per respondent to increase sample efficiency.

Journal ArticleDOI
24 May 2018-PLOS ONE
TL;DR: A novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture is developed, showing that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone.
Abstract: The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in regions associated with extreme events, where data is sparse.

Journal ArticleDOI
25 Jan 2018-PLOS ONE
TL;DR: This work uses a nationally representative internet survey in the U.S. to investigate socio-political characteristics to assess attitudes about vaccination and demonstrates that ideology has a direct effect on vaccine attitudes.
Abstract: In light of the increasing refusal of some parents to vaccinate children, public health strategies have focused on increasing knowledge and awareness based on a “knowledge-deficit” approach. However, decisions about vaccination are based on more than mere knowledge of risks, costs, and benefits. Individual decision making about vaccinating involves many other factors including those related to emotion, culture, religion, and socio-political context. In this paper, we use a nationally representative internet survey in the U.S. to investigate socio-political characteristics to assess attitudes about vaccination. In particular, we consider how political ideology and trust affect opinions about vaccinations for flu, pertussis, and measles. Our findings demonstrate that ideology has a direct effect on vaccine attitudes. In particular, conservative respondents are less likely to express pro-vaccination beliefs than other individuals. Furthermore, ideology also has an indirect effect on immunization propensity. The ideology variable predicts an indicator capturing trust in government medical experts, which in turn helps to explain individual-level variation with regards to attitudes about vaccine choice.