High prevalence of syphilis among demobilized child soldiers in Eastern Congo: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Syphilis, a known major public health issue for soldiers during periods of conflict, is exacerbated in the Democratic Republic of Congo due to widespread sexual violence. However, there has been no previous study to determine the extent of this problem. Therefore, we determined the prevalence of syphilis among young demobilized soldiers.</p> <p>Methods</p> <p>Screening of syphilis using the rapid plasma reagin test and the <it>Treponema pallidum </it>hemagglutination assay was conducted in three transit sites of soldier reintegration in 2005. The Fisher Exact probability test was used to compare results.</p> <p>Results</p> <p>The prevalence of syphilis was found to be 3.4%, with almost equal distribution in respect to sex, location.</p> <p>Conclusion</p> <p>Syphilis continues to be highly prevalent in demobilized child soldiers in Eastern Congo. Syphilis screening tests are recommended.</p

Social Cost Guarantees in Smart Route Guidance

We model and study the problem of assigning traffic in an urban road network infrastructure. In our model, each driver submits their intended destination and is assigned a route to follow that minimizes the social cost (i.e., travel distance of all the drivers). We assume drivers are strategic and try to manipulate the system (i.e., misreport their intended destination and/or deviate from the assigned route) if they can reduce their travel distance by doing so. Such strategic behavior is highly undesirable as it can lead to an overall suboptimal traffic assignment and cause congestion. To alleviate this problem, we develop moneyless mechanisms that are resilient to manipulation by the agents and offer provable approximation guarantees on the social cost obtained by the solution. We then empirically test the mechanisms studied in the paper, showing that they can be effectively used in practice in order to compute manipulation resistant traffic allocations

Reconstructing cancer genomes from paired-end sequencing data

<p>Abstract</p> <p>Background</p> <p>A cancer genome is derived from the germline genome through a series of somatic mutations. Somatic structural variants - including duplications, deletions, inversions, translocations, and other rearrangements - result in a cancer genome that is a scrambling of intervals, or "blocks" of the germline genome sequence. We present an efficient algorithm for reconstructing the block organization of a cancer genome from paired-end DNA sequencing data.</p> <p>Results</p> <p>By aligning paired reads from a cancer genome - and a matched germline genome, if available - to the human reference genome, we derive: (i) a partition of the reference genome into intervals; (ii) adjacencies between these intervals in the cancer genome; (iii) an estimated copy number for each interval. We formulate the Copy Number and Adjacency Genome Reconstruction Problem of determining the cancer genome as a sequence of the derived intervals that is consistent with the measured adjacencies and copy numbers. We design an efficient algorithm, called Paired-end Reconstruction of Genome Organization (PREGO), to solve this problem by reducing it to an optimization problem on an interval-adjacency graph constructed from the data. The solution to the optimization problem results in an Eulerian graph, containing an alternating Eulerian tour that corresponds to a cancer genome that is consistent with the sequencing data. We apply our algorithm to five ovarian cancer genomes that were sequenced as part of The Cancer Genome Atlas. We identify numerous rearrangements, or structural variants, in these genomes, analyze reciprocal vs. non-reciprocal rearrangements, and identify rearrangements consistent with known mechanisms of duplication such as tandem duplications and breakage/fusion/bridge (B/F/B) cycles.</p> <p>Conclusions</p> <p>We demonstrate that PREGO efficiently identifies complex and biologically relevant rearrangements in cancer genome sequencing data. An implementation of the PREGO algorithm is available at <url>http://compbio.cs.brown.edu/software/</url>.</p

Computational Cancer Biology: An Evolutionary Perspective

ISSN:1553-734XISSN:1553-735

Repercussões da terapia cognitivo comportamental na Depressão de pacientes submetidos a cirurgia bariátrica: Repercussions of behavioral cognitive therapy on Depression in patients undergoing bariatric surgery

A obesidade é um problema de saúde pública, que possui a cirurgia bariátrica como possibilidade de tratamento muito realizado, nos dias hodiernos. Entretanto, alguns distúrbios psiquiátricos têm sido associados à obesidade e ao pré-operatório dos pacientes bariátricos, mas não há diretrizes que abordem a forma com a qual a avaliação psicológica desses pacientes deve ser feita.&nbsp; Metodologia: Foi realizada uma revisão de literatura integrativa. Os artigos foram pesquisados por meio da plataforma Pubmed e os descritores utilizados foram “Obesity”, “Bariatric Surgery” e “Depression”, os quais foram pesquisados em Descritores em Ciências da Saúde (DeCS). Os critérios de inclusão foram ensaios clínicos controlados, ensaios clínicos controlados e randomizados e estudos observacionais, em inglês, entre 2017 a 2022. Resultados: Foram encontrados 32 artigos, dos quais 23 foram excluídos de acordo com os critérios de exclusão, 9 artigos foram selecionados. Discussão: A taxa de depressão pré-operatória em pacientes bariátricos é significativa e está relacionada a um risco de ganho de peso no pós-cirúrgico. Além disso, a melhora na qualidade de vida foi maior naqueles pacientes tratados para os distúrbios psiquiátricos. Com isso, é fundamental realizar uma boa avaliação psicológica desses pacientes no pré-operatório, o que pode ser feito por meio de uma escala de avaliação comportamental, para diagnóstico e tratamento. Uma alternativa, que se mostrou eficaz para os problemas relatados, foi a terapia cognitiva comportamental. Conclusão: O paciente bariátrico deve ser avaliado e abordado nos múltiplos domínios relacionados à saúde mental para melhores resultados antes e após a cirurgia

CSI-OMIM - Clinical Synopsis Search in OMIM

<p>Abstract</p> <p>Background</p> <p>The OMIM database is a tool used daily by geneticists. Syndrome pages include a Clinical Synopsis section containing a list of known phenotypes comprising a clinical syndrome. The phenotypes are in free text and different phrases are often used to describe the same phenotype, the differences originating in spelling variations or typing errors, varying sentence structures and terminological variants.</p> <p>These variations hinder searching for syndromes or using the large amount of phenotypic information for research purposes. In addition, negation forms also create false positives when searching the textual description of phenotypes and induce noise in text mining applications.</p> <p>Description</p> <p>Our method allows efficient and complete search of OMIM phenotypes as well as improved data-mining of the OMIM phenome. Applying natural language processing, each phrase is tagged with additional semantic information using UMLS and MESH. Using a grammar based method, annotated phrases are clustered into groups denoting similar phenotypes. These groups of synonymous expressions enable precise search, as query terms can be matched with the many variations that appear in OMIM, while avoiding over-matching expressions that include the query term in a negative context. On the basis of these clusters, we computed pair-wise similarity among syndromes in OMIM. Using this new similarity measure, we identified 79,770 new connections between syndromes, an average of 16 new connections per syndrome. Our project is Web-based and available at <url>http://fohs.bgu.ac.il/s2g/csiomim</url></p> <p>Conclusions</p> <p>The resulting enhanced search functionality provides clinicians with an efficient tool for diagnosis. This search application is also used for finding similar syndromes for the candidate gene prioritization tool S2G.</p> <p>The enhanced OMIM database we produced can be further used for bioinformatics purposes such as linking phenotypes and genes based on syndrome similarities and the known genes in Morbidmap.</p