Expanded Somatic Mutation Spectrum of MED12 Gene in Uterine Leiomyomas of Saudi Arabian Women

MED12, a subunit of mediator complex genes is known to harbor genetic mutations, (mostly in exon 2), causal to the genesis of uterine leiomyomas among Caucasian, African American, and Asian women. However, the precise relationship between genetic mutations vs. protein or disease phenotype is not well-explained. Therefore, we sought to replicate the MED12 mutation frequency in leiomyomas of Saudi Arabian women, who represents ethnically and culturally distinct population. We performed molecular screening of MED12 gene (in 308 chromosomes belonging to 154 uterine biopsies), analyzed the genotype-disease phenotype correlations and determined the biophysical characteristics of mutated protein through diverse computational approaches. We discovered that >44% (34/77) leiomyomas of Arab women carry a spectrum of MED12 mutations (30 missense, 1 splice site, and 3 indels). In addition to known codon 44, we observed novel somatic mutations in codons 36, 38, and 55. Most genetically mutated tumors (27/30; 90%) demonstrated only one type of genetic change, highlighting that even single allele change in MED12 can have profound impact in transforming the normal uterine myometrium to leiomyomas. An interesting inverse correlation between tumor size and LH is observed when tumor is positive to MED12 mutation (p < 0.05). Our computational investigations suggest that amino acid substitution mutations in exon-2 region of MED12 might contribute to potential alterations in phenotype as well as the stability of MED12 protein. Our study, being the first one from Arab world, confirms the previous findings that somatic MED12 mutations are critical to development and progression of uterine leiomyomas irrespective of the ethnic background. We recommend that mutation screening, particularly codon 44 of MED12 can assist in molecular diagnostics of uterine leiomyomas in majority of the patients

Computer-based technology and student engagement: a critical review of the literature

Computer-based technology has infiltrated many aspects of life and industry, yet there is little understanding of how it can be used to promote student engagement, a concept receiving strong attention in higher education due to its association with a number of positive academic outcomes. The purpose of this article is to present a critical review of the literature from the past 5 years related to how web-conferencing software, blogs, wikis, social networking sites (Facebook and Twitter), and digital games influence student engagement. We prefaced the findings with a substantive overview of student engagement definitions and indicators, which revealed three types of engagement (behavioral, emotional, and cognitive) that informed how we classified articles. Our findings suggest that digital games provide the most far-reaching influence across different types of student engagement, followed by web-conferencing and Facebook. Findings regarding wikis, blogs, and Twitter are less conclusive and significantly limited in number of studies conducted within the past 5 years. Overall, the findings provide preliminary support that computer-based technology influences student engagement, however, additional research is needed to confirm and build on these findings. We conclude the article by providing a list of recommendations for practice, with the intent of increasing understanding of how computer-based technology may be purposefully implemented to achieve the greatest gains in student engagement. © 2017, The Author(s)

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

THE INFINITE GAUSSIAN MODELS: AN APPLICATION TO SPEAKER IDENTIFICATION

When modeling speech with traditional Gaussian Mixture Models (GMM) a major problem is that one need to fix a priori the number of GMMs. Using the infinite version of GMMs allows to overcome this problem. This is based on considering a Dirichlet process with a Bayesian inference via Gibbs sampling rather than the traditional EM inference. The paper investigates the usefulness of the infinite Gaussian modeling using the state of the art SVM classifiers. We consider the particular case of the speaker identification under limited data condition that is very short speech sequences. Basically, recognition rates of 100% are achieved after only 5 iterations using training and test samples less than 1 second. Experiments are carried out over NIST SRE 2000 corpus

Online Temperature Control System

In this paper, a remote temperature control system has been proposed. The physical system is controlled in real time through the Internet network. For educational purpose, the students use only a web browser to tune and test a PID controller via shared user interface. The PID parameters are calculated using the basic experimental Ziegler—Nichols tuning rules. After hardware and software experiment description, the remote online experiment is tested and the results are given

Migrations et diasporas méditerranéennes (Xe-XVIe siècles)

La Méditerranée a été de tout temps zone de brassage. La période médiévale a vu s'y déployer bien des migrations, proches par leurs caractères des grands déplacements humains de l'époque contemporaine : flux et reflux des marchands italiens allant s'installer dans les comptoirs d'outre-mer, migrations forcées des Arméniens créant un nouveau foyer en Cilicie, ou des juifs espagnols cherchant refuge dans l'empire ottoman après le décret d'expulsion de 1492, migrations économiques d'Albanais, de Coumans, de Syriens, de Bulgares, ou de gens de guerre pour qui ne comptent que l'aventure et l'appât du gain. Les motivations sont multiples, de même que les itinéraires empruntés. Migrations et diasporas, à l'origine de la création de colonies et de comptoirs, révèlent un système de valeurs et montrent comment les groupements humains assurent la continuité et le renouvellement de leurs propres structures, tout en s'adaptant aux changements imposés par la conjoncture. Le monde méditerranéen fut et demeure le lieu de profonds bouleversements humains que seule une différence d'échelle sépare aujourd'hui de ceux d'hier. Saisir ceux-ci dans leur complexité aide à mieux comprendre le monde contemporain

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling. Proteomics can be used to refine cancer classification. Here, the authors characterise chronic lymphocytic leukaemia patients by proteogenomics, and identified a subtype of patients with poor prognosis associated with aberrant B cell receptor signalling