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1.
BMC Bioinformatics ; 21(Suppl 14): 368, 2020 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-32998690

RESUMO

BACKGROUND: Lung cancer is the leading cause of the largest number of deaths worldwide and lung adenocarcinoma is the most common form of lung cancer. In order to understand the molecular basis of lung adenocarcinoma, integrative analysis have been performed by using genomics, transcriptomics, epigenomics, proteomics and clinical data. Besides, molecular prognostic signatures have been generated for lung adenocarcinoma by using gene expression levels in tumor samples. However, we need signatures including different types of molecular data, even cohort or patient-based biomarkers which are the candidates of molecular targeting. RESULTS: We built an R pipeline to carry out an integrated meta-analysis of the genomic alterations including single-nucleotide variations and the copy number variations, transcriptomics variations through RNA-seq and clinical data of patients with lung adenocarcinoma in The Cancer Genome Atlas project. We integrated significant genes including single-nucleotide variations or the copy number variations, differentially expressed genes and those in active subnetworks to construct a prognosis signature. Cox proportional hazards model with Lasso penalty and LOOCV was used to identify best gene signature among different gene categories. We determined a 12-gene signature (BCHE, CCNA1, CYP24A1, DEPTOR, MASP2, MGLL, MYO1A, PODXL2, RAPGEF3, SGK2, TNNI2, ZBTB16) for prognostic risk prediction based on overall survival time of the patients with lung adenocarcinoma. The patients in both training and test data were clustered into high-risk and low-risk groups by using risk scores of the patients calculated based on selected gene signature. The overall survival probability of these risk groups was highly significantly different for both training and test datasets. CONCLUSIONS: This 12-gene signature could predict the prognostic risk of the patients with lung adenocarcinoma in TCGA and they are potential predictors for the survival-based risk clustering of the patients with lung adenocarcinoma. These genes can be used to cluster patients based on molecular nature and the best candidates of drugs for the patient clusters can be proposed. These genes also have a high potential for targeted cancer therapy of patients with lung adenocarcinoma.


Assuntos
Adenocarcinoma de Pulmão/patologia , Genômica/métodos , Neoplasias Pulmonares/patologia , Transcriptoma , Adenocarcinoma de Pulmão/genética , Adenocarcinoma de Pulmão/mortalidade , Área Sob a Curva , Análise por Conglomerados , Variações do Número de Cópias de DNA , Bases de Dados Genéticas , Regulação Neoplásica da Expressão Gênica , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/mortalidade , Estadiamento de Neoplasias , Prognóstico , Modelos de Riscos Proporcionais , Mapas de Interação de Proteínas/genética , Curva ROC , Fatores de Risco , Taxa de Sobrevida
2.
BMC Bioinformatics ; 21(Suppl 14): 367, 2020 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-32998698

RESUMO

BACKGROUND: Essential genes are those genes that are critical for the survival of an organism. The prediction of essential genes in bacteria can provide targets for the design of novel antibiotic compounds or antimicrobial strategies. RESULTS: We propose a deep neural network for predicting essential genes in microbes. Our architecture called DEEPLYESSENTIAL makes minimal assumptions about the input data (i.e., it only uses gene primary sequence and the corresponding protein sequence) to carry out the prediction thus maximizing its practical application compared to existing predictors that require structural or topological features which might not be readily available. We also expose and study a hidden performance bias that effected previous classifiers. Extensive results show that DEEPLYESSENTIAL outperform existing classifiers that either employ down-sampling to balance the training set or use clustering to exclude multiple copies of orthologous genes. CONCLUSION: Deep neural network architectures can efficiently predict whether a microbial gene is essential (or not) using only its sequence information.


Assuntos
Bactérias/genética , Genes Essenciais , Redes Neurais de Computação , Área Sob a Curva , Análise por Conglomerados , Códon , Bactérias Gram-Negativas/genética , Bactérias Gram-Positivas/genética , Curva ROC
3.
BMC Bioinformatics ; 21(Suppl 14): 364, 2020 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-32998700

RESUMO

BACKGROUND: Machine learning has been utilized to predict cancer drug response from multi-omics data generated from sensitivities of cancer cell lines to different therapeutic compounds. Here, we build machine learning models using gene expression data from patients' primary tumor tissues to predict whether a patient will respond positively or negatively to two chemotherapeutics: 5-Fluorouracil and Gemcitabine. RESULTS: We focused on 5-Fluorouracil and Gemcitabine because based on our exclusion criteria, they provide the largest numbers of patients within TCGA. Normalized gene expression data were clustered and used as the input features for the study. We used matching clinical trial data to ascertain the response of these patients via multiple classification methods. Multiple clustering and classification methods were compared for prediction accuracy of drug response. Clara and random forest were found to be the best clustering and classification methods, respectively. The results show our models predict with up to 86% accuracy; despite the study's limitation of sample size. We also found the genes most informative for predicting drug response were enriched in well-known cancer signaling pathways and highlighted their potential significance in chemotherapy prognosis. CONCLUSIONS: Primary tumor gene expression is a good predictor of cancer drug response. Investment in larger datasets containing both patient gene expression and drug response is needed to support future work of machine learning models. Ultimately, such predictive models may aid oncologists with making critical treatment decisions.


Assuntos
Antineoplásicos/farmacologia , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Aprendizado de Máquina , Antineoplásicos/uso terapêutico , Área Sob a Curva , Análise por Conglomerados , Bases de Dados Genéticas , Desoxicitidina/análogos & derivados , Desoxicitidina/farmacologia , Desoxicitidina/uso terapêutico , Fluoruracila/uso terapêutico , Humanos , Neoplasias/tratamento farmacológico , Curva ROC
4.
BMC Public Health ; 20(1): 1525, 2020 Oct 08.
Artigo em Inglês | MEDLINE | ID: mdl-33032575

RESUMO

BACKGROUND: This study was intended to investigate the epidemiological characteristics of COVID-19 clusters and the severity distribution of clinical symptoms of involved cases in Sichuan Province, so as to provide information support for the development and adjustment of strategies for the prevention and control of local clusters. METHODS: The epidemiological characteristics of 67 local clusters of COVID-19 cases in Sichuan Province reported as of March 17, 2020 were described and analyzed. Information about all COVID-19 clusters and involved cases was acquired from the China Information System for Disease Control and Prevention and analyzed with the epidemiological investigation results taken into account. RESULTS: The clusters were temporally and regionally concentrated. Clusters caused by imported cases from other provinces accounted for 73.13%; familial clusters accounted for 68.66%; the average attack rate was 8.54%, and the average secondary attack rate was 6.11%; the median incubation period was 8.5 d; a total of 28 cases met the criteria for incubation period determination, and in the 28 cases, the incubation period was > 14 d in 21.43% (6/28). a total of 226 confirmed cases were reported in the 67 clusters. Ten cases were exposed before the confirmed cases they contacted with developed clinical symptoms, and the possibility of exposure to other infection sources was ruled out; two clusters were caused by asymptomatic carriers; confirmed cases mainly presented with fever, respiratory and systemic symptoms; a gradual decline in the severity of clinical symptoms was noted with the increase of the case generation. CONCLUSIONS: Population movement and gathering restrictions and strict close contact management measures will significantly contribute to the identification and control of cases. Transmission during the incubation period and asymptomatic infections have been noted. Studies on the pathogenicity and transmissibility in these populations and on COVID-19 antibody levels and protective effects in healthy people and cases are required.


Assuntos
Infecções por Coronavirus/epidemiologia , Pneumonia Viral/epidemiologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , China/epidemiologia , Análise por Conglomerados , Feminino , Humanos , Lactente , Masculino , Pessoa de Meia-Idade , Pandemias , Adulto Jovem
5.
Rev Soc Bras Med Trop ; 53: e20200494, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32876320

RESUMO

Diagnosing cases of coronavirus disease (COVID-19) with only non-respiratory symptoms has been challenging. We reported the diagnosis of a child who tested positive for COVID-19 with abdominal pain/diarrhea and tracked his family cluster. One member of the family tested positive for COVID-19 on real-time reverse-transcription polymerase chain reaction assay and three other family members had anti-SARS-CoV-2 antibodies.


Assuntos
Infecções por Coronavirus/diagnóstico , Coronavirus/isolamento & purificação , Diarreia/diagnóstico , Pandemias , Pneumonia Viral/diagnóstico , Dor Abdominal/etiologia , Betacoronavirus , Pré-Escolar , Técnicas de Laboratório Clínico , Análise por Conglomerados , Busca de Comunicante , Diarreia/etiologia , Febre/etiologia , Humanos , Masculino , Faringite/etiologia
6.
Zhonghua Liu Xing Bing Xue Za Zhi ; 41(8): 1319-1323, 2020 Aug 10.
Artigo em Chinês | MEDLINE | ID: mdl-32867443

RESUMO

Objective: To understand the characteristics of spatiotemporal clustering on hepatitis A in Gansu province and to provide evidence for hepatitis A prevention and control. Methods: Data related to hepatitis A were retrieved from National Notifiable Disease Report System, ArcGIS 10.3 and SaTScan 9.1 in Gansu province from 2004 to 2018. Results: The annual average report incidence rate of hepatitis A was 10.91/100 000, showing a descending trend with no periodic or seasonal features. After the implementation of national expanded immunization program, high annual incidence rates had been seen in Linxia Hui autonomous prefecture and Gannan Tibetan autonomous prefecture. From 2004 to 2012, the lowest RR value appeared in the 0-9 age group (P=0.000) while the highest RR value was in the over 60 age group during 2013-2018 except for the age 0-9 group in 2015. The annual average incidence rate was increasing from south to north and west to east, across the territory. Results from the temporal scanning program revealed that the incidence of hepatitis A was temporally aggregated from 2004 to 2018. For spatio-temporal scanning of 2004-2008, data showed one most likely cluster area (radius: 91.95 km, Time frame: 2004-2005), apparel mainly in Linxia and Longnan cities. Results from the spatio-temporal scanning program of 2009-2018 also showed that the most likely cluster areas (radius: 183.26 km, Time frame: 2009-2012) were in Gannan, Linxia, Dingxi and Longnan areas. Conclusions: The reported incidence rates of hepatitis A were declining, without significant periodic or seasonal pattern in Gansu province from 2004 to 2018. In the 0-9 years-old group, the incidence rate showed the lowest, while the highest was in the 60 year-olds group. Spatio-temporal clustering of hepatitis A was observed in Gansu province from 2004 to 2018. Strategies on prevention and control of the disease should be targeted in the southwest regions of the province.


Assuntos
Hepatite A/epidemiologia , Criança , Pré-Escolar , China/epidemiologia , Cidades/epidemiologia , Análise por Conglomerados , Humanos , Incidência , Lactente , Recém-Nascido , Pessoa de Meia-Idade , Análise Espaço-Temporal
7.
Environ Monit Assess ; 192(10): 638, 2020 Sep 14.
Artigo em Inglês | MEDLINE | ID: mdl-32924079

RESUMO

Surface water is one of the primary sources for drinking, irrigation, and industrial activities in Ergene River, Turkey. However, its quality has deteriorated due to the point and non-point pollution sources. Therefore, an appropriate assessment of surface water quality is very important. Water quality classification is calculated separately for each quality parameter in Turkey. An overall assessment of surface water quality is essential for water management. In this study, self-organizing maps (SOMs) and fuzzy C-means clustering (FCM) methods have been used for assessing surface water quality in the Ergene River. Seven water quality parameters have been considered as important indicators to evaluate water quality status in 7 observation points located in the river, covering the period from 1985 to 2013.


Assuntos
Rios , Qualidade da Água , Análise por Conglomerados , Monitoramento Ambiental , Turquia
8.
BMJ Open ; 10(9): e039886, 2020 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-32873684

RESUMO

OBJECTIVES: To illustrate the intersections of, and intercounty variation in, individual, household and community factors that influence the impact of COVID-19 on US counties and their ability to respond. DESIGN: We identified key individual, household and community characteristics influencing COVID-19 risks of infection and survival, guided by international experiences and consideration of epidemiological parameters of importance. Using publicly available data, we developed an open-access online tool that allows county-specific querying and mapping of risk factors. As an illustrative example, we assess the pairwise intersections of age (individual level), poverty (household level) and prevalence of group homes (community-level) in US counties. We also examine how these factors intersect with the proportion of the population that is people of colour (ie, not non-Hispanic white), a metric that reflects histories of US race relations. We defined 'high' risk counties as those above the 75th percentile. This threshold can be changed using the online tool. SETTING: US counties. PARTICIPANTS: Analyses are based on publicly available county-level data from the Area Health Resources Files, American Community Survey, Centers for Disease Control and Prevention Atlas file, National Center for Health Statistic and RWJF Community Health Rankings. RESULTS: Our findings demonstrate significant intercounty variation in the distribution of individual, household and community characteristics that affect risks of infection, severe disease or mortality from COVID-19. About 9% of counties, affecting 10 million residents, are in higher risk categories for both age and group quarters. About 14% of counties, affecting 31 million residents, have both high levels of poverty and a high proportion of people of colour. CONCLUSION: Federal and state governments will benefit from recognising high intrastate, intercounty variation in population risks and response capacity. Equitable responses to the pandemic require strategies to protect those in counties at highest risk of adverse COVID-19 outcomes and their social and economic impacts.


Assuntos
Fatores Etários , Infecções por Coronavirus , Grupos Étnicos/estatística & dados numéricos , Características da Família , Pandemias , Pneumonia Viral , Pobreza/estatística & dados numéricos , Saúde Pública , Análise de Sobrevida , Adulto , Idoso , Betacoronavirus , Análise por Conglomerados , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/epidemiologia , Estudos Transversais , Feminino , Humanos , Masculino , Pneumonia Viral/diagnóstico , Pneumonia Viral/epidemiologia , Prevalência , Saúde Pública/métodos , Saúde Pública/estatística & dados numéricos , Medição de Risco/métodos , Medição de Risco/estatística & dados numéricos , Fatores de Risco , Índice de Gravidade de Doença , Estados Unidos
9.
Zhongguo Zhong Yao Za Zhi ; 45(15): 3659-3665, 2020 Aug.
Artigo em Chinês | MEDLINE | ID: mdl-32893555

RESUMO

As a traditional Chinese medicinal material, Chrysosplenium is urgently needed for genetic resource investigation and protection research due to the decrease of its wild resources in recent years. After investigating the wild resources, we conducted genetic polymorphism and clustering studies of 24 species(a total of 36 samples) of Chrysosplenium using SRAP technique. The results showed that a total of 374 polymorphic bands were obtained using 18 pairs of SRAP primers to amplify these samples, on average of 20.7 bands for each primer pair. We used the biological software to analyze the population's genetic parameter and got the N_a value as 2.000 0, N_(e )value as 1.408 4, the average Nei's index as 0.263 5, and the average Shannon information index as 0.419 1. UPGMA cluster analysis showed that all the samples can be divided into three major groups at the genetic similarity coefficient of 0.70: there are 18 species(24 samples) gathered for the Ⅰ groups, 3 species or variation(7 samples) for Ⅱ groups, and 3 species(5 samples) for Ⅲ groups. The differences of these Chrysosplenium species at the molecular level are consistent with that of their geographical and ecological distribution. At the same time, we used SRAP technology to construct 36 DNA digital fingerprints of Chrysosplenium and obtained the unique molecular identification band type of each material. These results will provide effective methods and reliable basis for the identification, protection and genetic diversity analysis of the germplasm resources of Chrysosplenium, and lay a foundation for the further development and utilization of them.


Assuntos
Impressões Digitais de DNA , Variação Genética , Análise por Conglomerados , Marcadores Genéticos , Filogenia , Polimorfismo Genético
10.
Artigo em Inglês | MEDLINE | ID: mdl-32907528

RESUMO

Cumulatively to 30 August there have been 25,686 case notifications and 577 deaths. The number of new cases reported nationally this fortnight was 1,751, a 61% decrease from the previous fortnight (4,501). On average this represented 125 cases diagnosed each day over the reporting period, a decrease from 322 cases per day over the previous reporting period. 94% (1,640) of all cases were reported in Victoria, with a smaller number of cases reported from New South Wales (86), Queensland (19), Western Australia (5) and South Australia (1). In Victoria, the majority of cases (1,528; 93%) were locally acquired, with a further 112 (7%) under investigation at the time of analysis, but likely also to be locally acquired. Of the remaining 111 cases reported, 22 (20%) were overseas acquired; 82 (74%) were locally acquired, predominantly in NSW, and 7 (6%) were reported as under investigation. The continued decrease in new cases observed this fortnight in Victoria is likely associated with the enhanced public health measures that are currently in place in Victoria. Locally acquired cases which were predominantly associated with several interconnected clusters continued to be reported in NSW. In Qld a cluster of cases associated with a youth detention centre was identified. A total of 26 deaths were reported from cases diagnosed in this reporting period, all from Victoria and aged 75 years or older. Testing rates remain high across all jurisdictions, with an overall positivity rate for the reporting period of 0.27%. Victoria reported a positivity rate of 0.90% for this reporting period; in all other jurisdictions the positivity rate was 0.03% or lower.


Assuntos
Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/epidemiologia , Pneumonia Viral/diagnóstico , Pneumonia Viral/epidemiologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Austrália/epidemiologia , Betacoronavirus/genética , Criança , Pré-Escolar , Análise por Conglomerados , Infecções por Coronavirus/mortalidade , Saúde Global , Humanos , Lactente , Pessoa de Meia-Idade , Grupo com Ancestrais Oceânicos , Pandemias , Pneumonia Viral/mortalidade , Administração em Saúde Pública , Adulto Jovem
11.
BMC Bioinformatics ; 21(1): 399, 2020 Sep 09.
Artigo em Inglês | MEDLINE | ID: mdl-32907544

RESUMO

BACKGROUND: Cryo-electron tomography is an important and powerful technique to explore the structure, abundance, and location of ultrastructure in a near-native state. It contains detailed information of all macromolecular complexes in a sample cell. However, due to the compact and crowded status, the missing edge effect, and low signal to noise ratio (SNR), it is extremely challenging to recover such information with existing image processing methods. Cryo-electron tomogram simulation is an effective solution to test and optimize the performance of the above image processing methods. The simulated images could be regarded as the labeled data which covers a wide range of macromolecular complexes and ultrastructure. To approximate the crowded cellular environment, it is very important to pack these heterogeneous structures as tightly as possible. Besides, simulating non-deformable and deformable components under a unified framework also need to be achieved. RESULT: In this paper, we proposed a unified framework for simulating crowded cryo-electron tomogram images including non-deformable macromolecular complexes and deformable ultrastructures. A macromolecule was approximated using multiple balls with fixed relative positions to reduce the vacuum volume. A ultrastructure, such as membrane and filament, was approximated using multiple balls with flexible relative positions so that this structure could deform under force field. In the experiment, 400 macromolecules of 20 representative types were packed into simulated cytoplasm by our framework, and numerical verification proved that our method has a smaller volume and higher compression ratio than the baseline single-ball model. We also packed filaments, membranes and macromolecules together, to obtain a simulated cryo-electron tomogram image with deformable structures. The simulated results are closer to the real Cryo-ET, making the analysis more difficult. The DOG particle picking method and the image segmentation method are tested on our simulation data, and the experimental results show that these methods still have much room for improvement. CONCLUSION: The proposed multi-ball model can achieve more crowded packaging results and contains richer elements with different properties to obtain more realistic cryo-electron tomogram simulation. This enables users to simulate cryo-electron tomogram images with non-deformable macromolecular complexes and deformable ultrastructures under a unified framework. To illustrate the advantages of our framework in improving the compression ratio, we calculated the volume of simulated macromolecular under our multi-ball method and traditional single-ball method. We also performed the packing experiment of filaments and membranes to demonstrate the simulation ability of deformable structures. Our method can be used to do a benchmark by generating large labeled cryo-ET dataset and evaluating existing image processing methods. Since the content of the simulated cryo-ET is more complex and crowded compared with previous ones, it will pose a greater challenge to existing image processing methods.


Assuntos
Citoplasma/ultraestrutura , Tomografia com Microscopia Eletrônica/métodos , Simulação de Dinâmica Molecular , Algoritmos , Análise por Conglomerados , Microscopia Crioeletrônica , Citoplasma/metabolismo , Processamento de Imagem Assistida por Computador , Substâncias Macromoleculares/química , Substâncias Macromoleculares/metabolismo , Razão Sinal-Ruído
12.
PLoS One ; 15(8): e0236186, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32866164

RESUMO

AIM: To establish a gene co-expression network for identifying principal modules and hub genes that are associated with drought resistance mechanisms, analyzing their mechanisms, and exploring candidate genes. METHODS AND FINDINGS: 42 data sets including PRJNA380841 and PRJNA369686 were used to construct the co-expression network through weighted gene co-expression network analysis (WGCNA). A total of 1,896,897,901 (284.30 Gb) clean reads and 35,021 differentially expressed genes (DEGs) were obtained from 42 samples. Functional enrichment analysis indicated that photosynthesis, DNA replication, glycolysis/gluconeogenesis, starch and sucrose metabolism, arginine and proline metabolism, and cell cycle were significantly influenced by drought stress. Furthermore, the DEGs with similar expression patterns, detected by K-means clustering, were grouped into 29 clusters. Genes involved in the modules, such as dark turquoise, yellow, and brown, were found to be appreciably linked with drought resistance. Twelve central, greatly correlated genes in stage-specific modules were subsequently confirmed and validated at the transcription levels, including TraesCS7D01G417600.1 (PP2C), TraesCS5B01G565300.1 (ERF), TraesCS4A01G068200.1 (HSP), TraesCS2D01G033200.1 (HSP90), TraesCS6B01G425300.1 (RBD), TraesCS7A01G499200.1 (P450), TraesCS4A01G118400.1 (MYB), TraesCS2B01G415500.1 (STK), TraesCS1A01G129300.1 (MYB), TraesCS2D01G326900.1 (ALDH), TraesCS3D01G227400.1 (WRKY), and TraesCS3B01G144800.1 (GT). CONCLUSIONS: Analyzing the response of wheat to drought stress during different growth stages, we have detected three modules and 12 hub genes that are associated with drought resistance mechanisms, and five of those genes are newly identified for drought resistance. The references provided by these modules will promote the understanding of the drought-resistance mechanism. In addition, the candidate genes can be used as a basis of transgenic or molecular marker-assisted selection for improving the drought resistance and increasing the yields of wheat.


Assuntos
Aclimatação/genética , Regulação da Expressão Gênica de Plantas , Redes Reguladoras de Genes , Estresse Fisiológico/genética , Triticum/genética , China , Análise por Conglomerados , Conjuntos de Dados como Assunto , Secas , Perfilação da Expressão Gênica , Genes de Plantas , Melhoramento Vegetal/métodos , RNA-Seq , Seleção Genética
13.
PLoS Comput Biol ; 16(9): e1008182, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32931516

RESUMO

Recent advances in experimental biology allow creation of datasets where several genome-wide data types (called omics) are measured per sample. Integrative analysis of multi-omic datasets in general, and clustering of samples in such datasets specifically, can improve our understanding of biological processes and discover different disease subtypes. In this work we present MONET (Multi Omic clustering by Non-Exhaustive Types), which presents a unique approach to multi-omic clustering. MONET discovers modules of similar samples, such that each module is allowed to have a clustering structure for only a subset of the omics. This approach differs from most existent multi-omic clustering algorithms, which assume a common structure across all omics, and from several recent algorithms that model distinct cluster structures. We tested MONET extensively on simulated data, on an image dataset, and on ten multi-omic cancer datasets from TCGA. Our analysis shows that MONET compares favorably with other multi-omic clustering methods. We demonstrate MONET's biological and clinical relevance by analyzing its results for Ovarian Serous Cystadenocarcinoma. We also show that MONET is robust to missing data, can cluster genes in multi-omic dataset, and reveal modules of cell types in single-cell multi-omic data. Our work shows that MONET is a valuable tool that can provide complementary results to those provided by existent algorithms for multi-omic analysis.


Assuntos
Algoritmos , Genômica/métodos , Análise por Conglomerados , Bases de Dados Genéticas , Humanos , Neoplasias/genética , Neoplasias/metabolismo , Análise de Célula Única
14.
PLoS One ; 15(9): e0238214, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32946442

RESUMO

Brazil detected community transmission of COVID-19 on March 13, 2020. In this study we identified which areas in the country were the most vulnerable for COVID-19, both in terms of the risk of arrival of cases, the risk of sustained transmission and their social vulnerability. Probabilistic models were used to calculate the probability of COVID-19 spread from São Paulo and Rio de Janeiro, the initial hotspots, using mobility data from the pre-epidemic period, while multivariate cluster analysis of socio-economic indices was done to identify areas with similar social vulnerability. The results consist of a series of maps of effective distance, outbreak probability, hospital capacity and social vulnerability. They show areas in the North and Northeast with high risk of COVID-19 outbreak that are also highly socially vulnerable. Later, these areas would be found the most severely affected. The maps produced were sent to health authorities to aid in their efforts to prioritize actions such as resource allocation to mitigate the effects of the pandemic. In the discussion, we address how predictions compared to the observed dynamics of the disease.


Assuntos
Betacoronavirus , Infecções por Coronavirus/transmissão , Modelos Teóricos , Morbidade/tendências , Pneumonia Viral/transmissão , Brasil/epidemiologia , Análise por Conglomerados , Infecções por Coronavirus/epidemiologia , Surtos de Doenças/estatística & dados numéricos , Previsões/métodos , Humanos , Pandemias , Pneumonia Viral/epidemiologia , Fatores Socioeconômicos
15.
Science ; 369(6509): 1305-1306, 2020 09 11.
Artigo em Inglês | MEDLINE | ID: mdl-32913091
16.
Nat Commun ; 11(1): 4669, 2020 09 16.
Artigo em Inglês | MEDLINE | ID: mdl-32938940

RESUMO

The prefrontal cortex and striatum form a recurrent network whose spiking activity encodes multiple types of learning-relevant information. This spike-encoded information is evident in average firing rates, but finer temporal coding might allow multiplexing and enhanced readout across the connected network. We tested this hypothesis in the fronto-striatal network of nonhuman primates during reversal learning of feature values. We found that populations of neurons encoding choice outcomes, outcome prediction errors, and outcome history in their firing rates also carry significant information in their phase-of-firing at a 10-25 Hz band-limited beta frequency at which they synchronize across lateral prefrontal cortex, anterior cingulate cortex and anterior striatum when outcomes were processed. The phase-of-firing code exceeds information that can be obtained from firing rates alone and is evident for inter-areal connections between anterior cingulate cortex, lateral prefrontal cortex and anterior striatum. For the majority of connections, the phase-of-firing information gain is maximal at phases of the beta cycle that were offset from the preferred spiking phase of neurons. Taken together, these findings document enhanced information of three important learning variables at specific phases of firing in the beta cycle at an inter-areally shared beta oscillation frequency during goal-directed behavior.


Assuntos
Corpo Estriado/fisiologia , Giro do Cíngulo/fisiologia , Aprendizagem/fisiologia , Neurônios/fisiologia , Córtex Pré-Frontal/fisiologia , Animais , Análise por Conglomerados , Corpo Estriado/citologia , Sincronização de Fases em Eletroencefalografia , Eletrofisiologia/métodos , Eletrofisiologia/estatística & dados numéricos , Giro do Cíngulo/citologia , Macaca mulatta , Masculino , Rede Nervosa , Córtex Pré-Frontal/citologia , Recompensa
17.
Nat Commun ; 11(1): 4556, 2020 09 11.
Artigo em Inglês | MEDLINE | ID: mdl-32917883

RESUMO

Previous genetic studies have identified local population structure within the Netherlands; however their resolution is limited by use of unlinked markers and absence of external reference data. Here we apply advanced haplotype sharing methods (ChromoPainter/fineSTRUCTURE) to study fine-grained population genetic structure and demographic change across the Netherlands using genome-wide single nucleotide polymorphism data (1,626 individuals) with associated geography (1,422 individuals). We identify 40 haplotypic clusters exhibiting strong north/south variation and fine-scale differentiation within provinces. Clustering is tied to country-wide ancestry gradients from neighbouring lands and to locally restricted gene flow across major Dutch rivers. North-south structure is temporally stable, with west-east differentiation more transient, potentially influenced by migrations during the middle ages. Despite superexponential population growth, regional demographic estimates reveal population crashes contemporaneous with the Black Death. Within Dutch and international data, GWAS incorporating fine-grained haplotypic covariates are less confounded than standard methods.


Assuntos
Grupos Étnicos/genética , Genética Populacional , Estudo de Associação Genômica Ampla , Estudos de Casos e Controles , Análise por Conglomerados , Emigração e Imigração , Grupo com Ancestrais do Continente Europeu/genética , Fluxo Gênico , Variação Genética/genética , Genoma , Geografia , Haplótipos , Humanos , Pessoa de Meia-Idade , Modelos Genéticos , Países Baixos , Polimorfismo de Nucleotídeo Único
18.
Virol J ; 17(1): 138, 2020 09 14.
Artigo em Inglês | MEDLINE | ID: mdl-32928234

RESUMO

The outbreak of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed significant threats to international health. The genetic traits as well as evolutionary processes in this novel coronavirus are not fully characterized, and their roles in viral pathogenesis are yet largely unknown. To get a better picture of the codon architecture of this newly emerging coronavirus, in this study we perform bioinformatic analysis, based on publicly available nucleotide sequences of SARS-CoV-2 along with those of other members of human coronaviruses as well as non-human coronaviruses in different hosts, to take a snapshot of the genome-wide codon usage pattern of SARS-CoV-2 and uncover that all over-represented codons end with A/U and this newly emerging coronavirus has a relatively low codon usage bias, which is shaped by both mutation pressure and natural selection. Additionally, there is slight variation in the codon usage pattern among the SARS-CoV-2 isolates from different geo-locations. Furthermore, the overall codon usage pattern of SARS-CoV-2 is generally similar to that of its phylogenetic relatives among non-human betacoronaviruses such as RaTG13. Taken together, we comprehensively analyze the characteristics of codon usage pattern in SARS-CoV-2 via bioinformatic approaches. The information from this research may not only be helpful to get new insights into the evolution of SARS-CoV-2, but also have potential value for developing coronavirus vaccines.


Assuntos
Betacoronavirus/genética , Uso do Códon , Infecções por Coronavirus/virologia , Genoma Viral , Pneumonia Viral/virologia , Animais , Sequência de Bases , Análise por Conglomerados , Códon , Biologia Computacional , Evolução Molecular , Humanos , Mutação , Pandemias , Filogenia , Seleção Genética , Proteínas Virais/genética , Sequenciamento Completo do Genoma
19.
BMJ ; 370: m3208, 2020 09 16.
Artigo em Inglês | MEDLINE | ID: mdl-32938633

RESUMO

OBJECTIVE: To investigate whether opportunistic screening in primary care increases the detection of atrial fibrillation compared with usual care. DESIGN: Cluster randomised controlled trial. SETTING: 47 intention-to-screen and 49 usual care primary care practices in the Netherlands, not blinded for allocation; the study was carried out from September 2015 to August 2018. PARTICIPANTS: In each practice, a fixed sample of 200 eligible patients, aged 65 or older, with no known history of atrial fibrillation in the electronic medical record system, were randomly selected. In the intention-to-screen group, 9218 patients eligible for screening were included, 55.0% women, mean age 75.2 years. In the usual care group, 9526 patients were eligible for screening, 54.3% women, mean age 75.0 years. INTERVENTIONS: Opportunistic screening (that is, screening in patients visiting their general practice) consisted of three index tests: pulse palpation, electronic blood pressure measurement with an atrial fibrillation algorithm, and electrocardiography (ECG) with a handheld single lead electrocardiographic device. The reference standard was 12 lead ECG, performed in patients with at least one positive index test and in a sample of patients (10%) with three negative tests. If 12 lead ECG showed no atrial fibrillation, patients were invited for more screening by continuous monitoring with a Holter electrocardiograph for two weeks. MAIN OUTCOME MEASURES: Difference in the detection rate of newly diagnosed atrial fibrillation over one year in intention-to-screen versus usual care practices. RESULTS: Follow-up was complete for 8874 patients in the intention-to-screen practices and for 9102 patients in the usual care practices. 144 (1.62%) new diagnoses of atrial fibrillation in the intention-to-screen group versus 139 (1.53%) in the usual care group were found (adjusted odds ratio 1.06 (95% confidence interval 0.84 to 1.35)). Of 9218 eligible patients in the intention-to-screen group, 4106 (44.5%) participated in the screening protocol. In these patients, 12 lead ECG detected newly diagnosed atrial fibrillation in 26 patients (0.63%). In the 266 patients who continued with Holter monitoring, four more diagnoses of atrial fibrillation were found. CONCLUSIONS: Opportunistic screening for atrial fibrillation in primary care patients, aged 65 and over, did not increase the detection rate of atrial fibrillation, which implies that opportunistic screening for atrial fibrillation is not useful in this setting. TRIAL REGISTRATION: Netherlands Trial Register No NL4776 (old NTR4914).


Assuntos
Fibrilação Atrial/diagnóstico , Seleção de Pacientes , Atenção Primária à Saúde , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Análise por Conglomerados , Eletrocardiografia , Feminino , Humanos , Análise de Intenção de Tratamento , Masculino , Programas de Rastreamento , Fatores de Risco
20.
PLoS Comput Biol ; 16(9): e1008173, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32946435

RESUMO

Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate nine different single-cell combinatorial indexed Hi-C (sci-Hi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 19,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sci-Hi-C data in the form of "chromatin topics." We further show enrichment of particular compartment structures associated with locus pairs in these topics.


Assuntos
Cromatina , Biologia Computacional/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Análise de Célula Única/métodos , Linhagem Celular , Cromatina/química , Cromatina/genética , Análise por Conglomerados , Biblioteca Gênica , Humanos , Processamento de Linguagem Natural
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