89 research outputs found

    Energetics and stability of nanostructured amorphous carbon

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    Monte Carlo simulations, supplemented by ab initio calculations, shed light into the energetics and thermodynamic stability of nanostructured amorphous carbon. The interaction of the embedded nanocrystals with the host amorphous matrix is shown to determine in a large degree the stability and the relative energy differences among carbon phases. Diamonds are stable structures in matrices with sp^3 fraction over 60%. Schwarzites are stable in low-coordinated networks. Other sp^2-bonded structures are metastable.Comment: 11 pages, 7 figure

    ApHMM: Accelerating Profile Hidden Markov Models for Fast and Energy-Efficient Genome Analysis

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    Profile hidden Markov models (pHMMs) are widely employed in various bioinformatics applications to identify similarities between biological sequences, such as DNA or protein sequences. In pHMMs, sequences are represented as graph structures. These probabilities are subsequently used to compute the similarity score between a sequence and a pHMM graph. The Baum-Welch algorithm, a prevalent and highly accurate method, utilizes these probabilities to optimize and compute similarity scores. However, the Baum-Welch algorithm is computationally intensive, and existing solutions offer either software-only or hardware-only approaches with fixed pHMM designs. We identify an urgent need for a flexible, high-performance, and energy-efficient HW/SW co-design to address the major inefficiencies in the Baum-Welch algorithm for pHMMs. We introduce ApHMM, the first flexible acceleration framework designed to significantly reduce both computational and energy overheads associated with the Baum-Welch algorithm for pHMMs. ApHMM tackles the major inefficiencies in the Baum-Welch algorithm by 1) designing flexible hardware to accommodate various pHMM designs, 2) exploiting predictable data dependency patterns through on-chip memory with memoization techniques, 3) rapidly filtering out negligible computations using a hardware-based filter, and 4) minimizing redundant computations. ApHMM achieves substantial speedups of 15.55x - 260.03x, 1.83x - 5.34x, and 27.97x when compared to CPU, GPU, and FPGA implementations of the Baum-Welch algorithm, respectively. ApHMM outperforms state-of-the-art CPU implementations in three key bioinformatics applications: 1) error correction, 2) protein family search, and 3) multiple sequence alignment, by 1.29x - 59.94x, 1.03x - 1.75x, and 1.03x - 1.95x, respectively, while improving their energy efficiency by 64.24x - 115.46x, 1.75x, 1.96x.Comment: Accepted to ACM TAC

    Child wasting and concurrent stunting in low- and middle-income countries

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    Sustainable Development Goal 2.2—to end malnutrition by 2030—includes the elimination of child wasting, defined as a weight-for-length z-score that is more than two standard deviations below the median of the World Health Organization standards for child growth 1. Prevailing methods to measure wasting rely on cross-sectional surveys that cannot measure onset, recovery and persistence—key features that inform preventive interventions and estimates of disease burden. Here we analyse 21 longitudinal cohorts and show that wasting is a highly dynamic process of onset and recovery, with incidence peaking between birth and 3 months. Many more children experience an episode of wasting at some point during their first 24 months than prevalent cases at a single point in time suggest. For example, at the age of 24 months, 5.6% of children were wasted, but by the same age (24 months), 29.2% of children had experienced at least one wasting episode and 10.0% had experienced two or more episodes. Children who were wasted before the age of 6 months had a faster recovery and shorter episodes than did children who were wasted at older ages; however, early wasting increased the risk of later growth faltering, including concurrent wasting and stunting (low length-for-age z-score), and thus increased the risk of mortality. In diverse populations with high seasonal rainfall, the population average weight-for-length z-score varied substantially (more than 0.5 z in some cohorts), with the lowest mean z-scores occurring during the rainiest months; this indicates that seasonally targeted interventions could be considered. Our results show the importance of establishing interventions to prevent wasting from birth to the age of 6 months, probably through improved maternal nutrition, to complement current programmes that focus on children aged 6–59 months

    Early-childhood linear growth faltering in low- and middle-income countries

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    Globally, 149 million children under 5 years of age are estimated to be stunted (length more than 2 standard deviations below international growth standards) 1,2. Stunting, a form of linear growth faltering, increases the risk of illness, impaired cognitive development and mortality. Global stunting estimates rely on cross-sectional surveys, which cannot provide direct information about the timing of onset or persistence of growth faltering—a key consideration for defining critical windows to deliver preventive interventions. Here we completed a pooled analysis of longitudinal studies in low- and middle-income countries (n = 32 cohorts, 52,640 children, ages 0–24 months), allowing us to identify the typical age of onset of linear growth faltering and to investigate recurrent faltering in early life. The highest incidence of stunting onset occurred from birth to the age of 3 months, with substantially higher stunting at birth in South Asia. From 0 to 15 months, stunting reversal was rare; children who reversed their stunting status frequently relapsed, and relapse rates were substantially higher among children born stunted. Early onset and low reversal rates suggest that improving children’s linear growth will require life course interventions for women of childbearing age and a greater emphasis on interventions for children under 6 months of age

    Causes and consequences of child growth faltering in low-resource settings

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    Growth faltering in children (low length for age or low weight for length) during the first 1,000 days of life (from conception to 2 years of age) influences short-term and long-term health and survival 1,2. Interventions such as nutritional supplementation during pregnancy and the postnatal period could help prevent growth faltering, but programmatic action has been insufficient to eliminate the high burden of stunting and wasting in low- and middle-income countries. Identification of age windows and population subgroups on which to focus will benefit future preventive efforts. Here we use a population intervention effects analysis of 33 longitudinal cohorts (83,671 children, 662,763 measurements) and 30 separate exposures to show that improving maternal anthropometry and child condition at birth accounted for population increases in length-for-age z-scores of up to 0.40 and weight-for-length z-scores of up to 0.15 by 24 months of age. Boys had consistently higher risk of all forms of growth faltering than girls. Early postnatal growth faltering predisposed children to subsequent and persistent growth faltering. Children with multiple growth deficits exhibited higher mortality rates from birth to 2 years of age than children without growth deficits (hazard ratios 1.9 to 8.7). The importance of prenatal causes and severe consequences for children who experienced early growth faltering support a focus on pre-conception and pregnancy as a key opportunity for new preventive interventions

    Relationship between obesity, ethnicity and risk of late stillbirth: a case control study

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    <p>Abstract</p> <p>Background</p> <p>In high income countries there has been little improvement in stillbirth rates over the past two decades. Previous studies have indicated an ethnic disparity in the rate of stillbirths. This study aimed to determine whether maternal ethnicity is independently associated with late stillbirth in New Zealand.</p> <p>Methods</p> <p>Cases were women with a singleton, late stillbirth (≥28 weeks' gestation) without congenital abnormality, born between July 2006 and June 2009 in Auckland, New Zealand. Two controls with ongoing pregnancies were randomly selected at the same gestation at which the stillbirth occurred. Women were interviewed in the first few weeks following stillbirth, or at the equivalent gestation for controls. Detailed demographic data were recorded. The study was powered to detect an odds ratio of 2, with a power of 80% at the 5% level of significance, given a prevalence of the risk factor of 20%. A multivariable regression model was developed which adjusted for known risk factors for stillbirth, as well as significant risk factors identified in the current study, and adjusted odds ratios and 95% confidence intervals were calculated.</p> <p>Results</p> <p>155/215 (72%) cases and 310/429 (72%) controls consented. Pacific ethnicity, overweight and obesity, grandmultiparity, not being married, not being in paid work, social deprivation, exposure to tobacco smoke and use of recreational drugs were associated with an increased risk of late stillbirth in univariable analysis. Maternal overweight and obesity, nulliparity, grandmultiparity, not being married and not being in paid work were independently associated with late stillbirth in multivariable analysis, whereas Pacific ethnicity was no longer significant (adjusted Odds Ratio 0.99; 0.51-1.91).</p> <p>Conclusions</p> <p>Pacific ethnicity was not found to be an independent risk factor for late stillbirth in this New Zealand study. The disparity in stillbirth rates between Pacific and European women can be attributed to confounding factors such as maternal obesity and high parity.</p

    Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

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    The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants, respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity
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