RESUMO
BACKGROUND: It is unclear whether cognitive skill deficits during childhood carry risk for suicide attempt or mortality later in adulthood at the population level. We conducted a systematic review and meta-analysis of population-based studies examining the association between childhood cognitive skills and adult suicidal behavior, namely attempt and mortality. METHOD: We systematically searched databases for articles then extracted study characteristics and estimates on the association between childhood cognitive skills (i.e., IQ or school performance at age ≤ 18 years) and later suicide attempt and mortality. Random-effect meta-analysis was used to quantify this association across all studies with available data. RESULTS: Twenty-three studies met the inclusion criteria and suggest an association between lower childhood cognitive skills and increased risk of suicidal behavior. Meta-analysis of the adjusted estimates from 11 studies (N = 2,830,191) found the association to be small but statistically significant. Heterogeneity was significant but moderate, and results were unlikely to be influenced by publication bias. In subgroup analyses, associations were significant only for males. No difference in effect size was found between suicide attempt and suicide mortality. LIMITATIONS: Cognitive skills were measured with different cognitive subtests. Heterogeneity in the age of cognitive skills assessment. Meta-regression and subgroup analyses were based on a relatively low number of studies. CONCLUSIONS: Individuals with lower cognitive skills in childhood have a greater risk of suicidal behavior in adulthood, especially males. Although the association was small, interventions improving cognitive skills may yield large effects on suicide prevention at the population level if the association is causal.
Assuntos
Ideação Suicida , Tentativa de Suicídio , Masculino , Criança , Humanos , Adulto , Adolescente , Tentativa de Suicídio/psicologia , Prevenção do Suicídio , Comportamento Infantil , CogniçãoRESUMO
Resumen La alineación de ADN es un proceso clave para la reconstrucción de genomas, a partir de los millones de lecturas cortas producidas por las máquinas de secuenciación paralela masiva. Tal proceso suele realizarse mediante algoritmos con elevada complejidad espacial y temporal, requiriendo varias horas para entregar los resultados, así como decenas de GB de RAM. Esto ha motivado la búsqueda de nuevos algoritmos y/o estrategias que permitan disminuir los tiempos de ejecución, mientras se utilizan recursos mínimos de memoria. En este artículo se presenta ABPSE, un nuevo alineador de ADN que combina el algoritmo de Ferragina y Manzini (o índices de FM) y el algoritmo de Myers, mediante la estrategia siembra y extiende. En la siembra, los índices de FM permiten calcular de manera rápida regiones con alta probabilidad de alineación; mientras que en la extensión, el algoritmo de Myers refina la alineación utilizando operaciones basadas en vectores de bits, calculando simultáneamente varias celdas de la matriz de programación dinámica. Los resultados muestran un 96.1% de lecturas alineadas correctamente, un factor de aceleración de 2.45x en relación a BWA-SW y un uso de memoria de apenas 7.6 GB, cuando se alinea el genoma humano completo.
Abstract DNA alignment is a key process in the assembly of genomes from the millions of short reads that are produced by massive parallel sequencing machines. Such a process is usually done by means of high spatial and temporal complexity algorithms, which takes hours to deliver the results as well as tens of GB of RAM. This has prompted the search for new algorithms and/or strategies that allow shorter runtimes, while using minimal memory footprint. In this article, we present ABPSE, a new DNA aligner that combines the Ferragina and Manzini algorithm (or FM indexes) and the Myers algorithm, by means of the seed and extend strategy. In the seeding, the FM indices allow a rapid calculation of the regions with high probability of alignment. In the extension, the Myers algorithm refines the alignment using operations based on bit vectors. It simultaneously calculates several cells of the dynamic programming matrix. The results show 96.1% of correctly aligned reads, an acceleration factor of 2.45x in relation to BWA-SW and a memory footprint of only 7.6 GB when aligning the entire human genome.
RESUMO
En los últimos años ha ocurrido un avance impresionante en las máquinas de secuenciación paralela masiva, también llamadas de secuenciación de siguiente generación (NGS), por ejemplo, máquinas recientes como Illumina Hiseq son capaces de generar millones de lecturas en una sola corrida. No obstante, estas tecnologías están limitadas a secuenciar solo fragmentos pequeños de material genético (entre 35 y 1100 nucleótidos), por lo que para secuenciar un genoma completo es necesario dividir la cadena, secuenciar y posteriormente ensamblar las lecturas cortas obtenidas. En este trabajo se revisan y comparan las tecnologías de secuenciación recientes, se estudia el proceso de ensamble de genomas completos y se establece formalmente el problema de la alineación. También se incluye un resumen de los principales programas de alineación y sus algoritmos que lo soportan. Finalmente, después de concluir que las tecnologías de secuenciación han superado en velocidad por un factor mayor a 10x a los programas de alineación, se revisa la aceleración Hardware como alternativa para acelerar tales programas. Este trabajo al ser una revisión integral pretende contribuir al desarrollo de investigación en el área de bioinformática en el país.
In recent years, impressive progress has occurred in the machines of massively parallel sequencing, also called of next-generation sequencing (NGS), for example, recent machines like Illumina HiSeq are capable of generating millions of reads in a single run. However, these technologies are limited to sequence only small fragments of genetic material (35 to 1100 nucleotides), so that for complete-genome sequencing, it is necessary to divide the chain, to sequence the fragments, and, subsequently, to assemble the obtained short readings. In this paper, the recent NGS sequencing technologies are reviewed and compared, analyzing the problem of sequence assembly, and formally establishing the problem of alignment. Also, it is examined the main alignment programs and the algorithms that support them. Finally, after concluding that sequencing technologies have speed that exceeds 10 times to the speed of the alignment programs, the hardware acceleration is reviewed as an alternative to accelerate these programs. This work, which is a comprehensive analysis and review, aims to contribute to the development of the research in the area of bioinformatics in the country.
