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1.
J Med Internet Res ; 24(7): e39590, 2022 Jul 05.
Artigo em Inglês | MEDLINE | ID: mdl-35788102

RESUMO

BACKGROUND: In 2020, more than 250 eHealth solutions were added to app stores each day, or 90,000 in the year; however, the vast majority of these solutions have not undergone clinical validation, their quality is unknown, and the user does not know if they are effective and safe. We sought to develop a simple prescreening scoring method that would assess the quality and clinical relevance of each app. We designed this tool with 3 health care stakeholder groups in mind: eHealth solution designers seeking to evaluate a potential competitor or their own tool, investors considering a fundraising candidate, and a hospital clinician or IT department wishing to evaluate a current or potential eHealth solution. OBJECTIVE: We built and tested a novel prescreening scoring tool (the Medical Digital Solution scoring tool). The tool, which consists of 26 questions that enable the quick assessment and comparison of the clinical relevance and quality of eHealth apps, was tested on 68 eHealth solutions. METHODS: The Medical Digital Solution scoring tool is based on the 2021 evaluation criteria of the French National Health Authority, the 2022 European Society of Medical Oncology recommendations, and other provided scores. We built the scoring tool with patient association and eHealth experts and submitted it to eHealth app creators, who evaluated their apps via the web-based form in January 2022. After completing the evaluation criteria, their apps obtained an overall score and 4 categories of subscores. These criteria evaluated the type of solution and domain, the solution's targeted population size, the level of clinical assessment, and information about the provider. RESULTS: In total, 68 eHealth solutions were evaluated with the scoring tool. Oncology apps (22%, 20/90) and general health solutions (23%, 21/90) were the most represented. Of the 68 apps, 32 (47%) were involved in remote monitoring by health professionals. Regarding clinical outcomes, 5% (9/169) of the apps assessed overall survival. Randomized studies had been conducted for 21% (23/110) of the apps to assess their benefit. Of the 68 providers, 38 (56%) declared the objective of obtaining reimbursement, and 7 (18%) out of the 38 solutions seeking reimbursement were assessed as having a high probability of reimbursement. The median global score was 11.2 (range 4.7-17.4) out of 20 and the distribution of the scores followed a normal distribution pattern (Shapiro-Wilk test: P=.33). CONCLUSIONS: This multidomain prescreening scoring tool is simple, fast, and can be deployed on a large scale to initiate an assessment of the clinical relevance and quality of a clinical eHealth app. This simple tool can help a decision-maker determine which aspects of the app require further analysis and improvement.


Assuntos
Indicadores de Qualidade em Assistência à Saúde , Software , Telemedicina , Humanos , Garantia da Qualidade dos Cuidados de Saúde/métodos , Garantia da Qualidade dos Cuidados de Saúde/normas , Indicadores de Qualidade em Assistência à Saúde/normas , Qualidade da Assistência à Saúde/normas , Software/normas , Telemedicina/normas
2.
Herzschrittmacherther Elektrophysiol ; 33(2): 247-254, 2022 Jun.
Artigo em Alemão | MEDLINE | ID: mdl-35604450

RESUMO

Programming of implantable cardiac devices, especially dual-chamber pacemakers, can be challenging in daily clinical practice. Precise knowledge of programmable parameters is important; furthermore, one should also be familiar with the specific algorithms of each manufacturer. During programming, the patient's individual requirements should be taken into account, but out-of-the-box programming should be avoided. Another important goal of programming should be to stimulate as much as needed but as little as possible to provide the patient good exercise capacity while not being aware of the pacing. Manufacturers' algorithms can help reach these aims but need to be understood and-in case of inappropriate behavior-to be deactivated.


Assuntos
Estimulação Cardíaca Artificial/normas , Eletrodos Implantados/normas , Marca-Passo Artificial , Software/normas , Algoritmos , Estimulação Cardíaca Artificial/métodos , Estimulação Cardíaca Artificial/tendências , Eletrodos Implantados/tendências , Humanos , Marca-Passo Artificial/normas , Software/tendências
3.
Nature ; 602(7895): 172-173, 2022 02.
Artigo em Inglês | MEDLINE | ID: mdl-35102330
4.
Prostate ; 82(2): 227-234, 2022 02.
Artigo em Inglês | MEDLINE | ID: mdl-34734428

RESUMO

BACKGROUND: Magnetic resonance imaging (MRI)-targeted prostate biopsy is a routinely used diagnostic tool for prostate cancer (PCa) detection. However, a clear superiority of the optimal approach for software-based MRI processing during biopsy procedures is still unanswered. To investigate the impact of robotic approach and software-based image processing (rigid vs. elastic) during MRI/transrectal ultrasound (TRUS) fusion prostate biopsy (FBx) on overall and clinically significant (cs) PCa detection. METHODS: The study relied on the instructional retrospective biopsy data collected data between September 2013 and August 2017. Overall, 241 men with at least one suspicious lesion (PI-RADS ≥ 3) on multiparametric MRI underwent FBx. The study protocol contains a systematic 12-core sextant biopsy plus 2 cores per targeted lesion. One experienced urologist performed 1048 targeted biopsy cores; 467 (45%) cores were obtained using rigid processing, while the remaining 581 (55%) cores relied on elastic image processing. CsPCa was defined as International Society of Urological Pathology (ISUP) grade ≥ 2. The effect of rigid versus elastic FBx on overall and csPCa detection rates was determined. Propensity score weighting and multivariable regression models were used to account for potential biases inherent to the retrospective study design. RESULTS: In multivariable regression analyses, age, prostate-specific antigen (PSA), and PIRADS ≥ 3 lesion were related to higher odds of finding csPCa. Elastic software-based image processing was independently associated with a higher overall PCa (odds ratio [OR] = 3.6 [2.2-6.1], p < 0.001) and csPCa (OR = 4.8 [2.6-8.8], p < 0.001) detection, respectively. CONCLUSIONS: Contrary to existing literature, our results suggest that the robotic-driven software registration with elastic fusion might have a substantial effect on PCa detection.


Assuntos
Detecção Precoce de Câncer , Imageamento por Ressonância Magnética/métodos , Próstata/patologia , Neoplasias da Próstata , Software , Ultrassonografia de Intervenção/métodos , Pesquisa Comparativa da Efetividade , Detecção Precoce de Câncer/métodos , Detecção Precoce de Câncer/normas , Detecção Precoce de Câncer/estatística & dados numéricos , Módulo de Elasticidade , Humanos , Biópsia Guiada por Imagem/métodos , Masculino , Pessoa de Meia-Idade , Pontuação de Propensão , Antígeno Prostático Específico/análise , Neoplasias da Próstata/sangue , Neoplasias da Próstata/diagnóstico , Neoplasias da Próstata/patologia , Software/classificação , Software/normas
6.
Multimedia | Recursos Multimídia | ID: multimedia-9536

RESUMO

Como parte de la respuesta de los gobiernos nacionales y sub-nacionales a la pandemia de COVID-19, se han utilizado las tecnologías digitales para apoyar la misma, generando una avalancha de soluciones y servicios digitales por parte de la industria del Software. Sin embargo, muchos países se han apoyado en el Software Libre y Código Abierto, sobre todo en soluciones con ya una historia sólida en respuesta a temas de salud pública. En este conversatorio virtual, conoceremos las distintas perspectivas de las soluciones líderes.


Assuntos
Telemedicina , Estratégias de eSaúde , Sistemas de Informação em Saúde , Software/normas , Acesso à Informação , Informática Médica , COVID-19/epidemiologia , Monitoramento Epidemiológico
7.
Sci Rep ; 11(1): 23905, 2021 12 13.
Artigo em Inglês | MEDLINE | ID: mdl-34903773

RESUMO

To develop a fully automatic model capable of reliably quantifying epicardial adipose tissue (EAT) volumes and attenuation in large scale population studies to investigate their relation to markers of cardiometabolic risk. Non-contrast cardiac CT images from the SCAPIS study were used to train and test a convolutional neural network based model to quantify EAT by: segmenting the pericardium, suppressing noise-induced artifacts in the heart chambers, and, if image sets were incomplete, imputing missing EAT volumes. The model achieved a mean Dice coefficient of 0.90 when tested against expert manual segmentations on 25 image sets. Tested on 1400 image sets, the model successfully segmented 99.4% of the cases. Automatic imputation of missing EAT volumes had an error of less than 3.1% with up to 20% of the slices in image sets missing. The most important predictors of EAT volumes were weight and waist, while EAT attenuation was predicted mainly by EAT volume. A model with excellent performance, capable of fully automatic handling of the most common challenges in large scale EAT quantification has been developed. In studies of the importance of EAT in disease development, the strong co-variation with anthropometric measures needs to be carefully considered.


Assuntos
Tecido Adiposo/diagnóstico por imagem , Interpretação de Imagem Assistida por Computador/métodos , Aprendizado de Máquina , Pericárdio/diagnóstico por imagem , Feminino , Humanos , Interpretação de Imagem Assistida por Computador/normas , Masculino , Programas de Rastreamento/métodos , Pessoa de Meia-Idade , Software/normas
8.
Sci Rep ; 11(1): 23912, 2021 12 13.
Artigo em Inglês | MEDLINE | ID: mdl-34903781

RESUMO

Histological stratification in metastatic non-small cell lung cancer (NSCLC) is essential to properly guide therapy. Morphological evaluation remains the basis for subtyping and is completed by additional immunohistochemistry labelling to confirm the diagnosis, which delays molecular analysis and utilises precious sample. Therefore, we tested the capacity of convolutional neural networks (CNNs) to classify NSCLC based on pathologic HES diagnostic biopsies. The model was estimated with a learning cohort of 132 NSCLC patients and validated on an external validation cohort of 65 NSCLC patients. Based on image patches, a CNN using InceptionV3 architecture was trained and optimized to classify NSCLC between squamous and non-squamous subtypes. Accuracies of 0.99, 0.87, 0.85, 0.85 was reached in the training, validation and test sets and in the external validation cohort. At the patient level, the CNN model showed a capacity to predict the tumour histology with accuracy of 0.73 and 0.78 in the learning and external validation cohorts respectively. Selecting tumour area using virtual tissue micro-array improved prediction, with accuracy of 0.82 in the external validation cohort. This study underlines the capacity of CNN to predict NSCLC subtype with good accuracy and to be applied to small pathologic samples without annotation.


Assuntos
Carcinoma Pulmonar de Células não Pequenas/patologia , Carcinoma de Células Escamosas/patologia , Interpretação de Imagem Assistida por Computador/métodos , Aprendizado de Máquina/normas , Carcinoma Pulmonar de Células não Pequenas/classificação , Carcinoma de Células Escamosas/classificação , Humanos , Interpretação de Imagem Assistida por Computador/normas , Imuno-Histoquímica/métodos , Sensibilidade e Especificidade , Software/normas
9.
Sci Rep ; 11(1): 23895, 2021 12 13.
Artigo em Inglês | MEDLINE | ID: mdl-34903808

RESUMO

There have been few independent evaluations of computer-aided detection (CAD) software for tuberculosis (TB) screening, despite the rapidly expanding array of available CAD solutions. We developed a test library of chest X-ray (CXR) images which was blindly re-read by two TB clinicians with different levels of experience and then processed by 12 CAD software solutions. Using Xpert MTB/RIF results as the reference standard, we compared the performance characteristics of each CAD software against both an Expert and Intermediate Reader, using cut-off thresholds which were selected to match the sensitivity of each human reader. Six CAD systems performed on par with the Expert Reader (Qure.ai, DeepTek, Delft Imaging, JF Healthcare, OXIPIT, and Lunit) and one additional software (Infervision) performed on par with the Intermediate Reader only. Qure.ai, Delft Imaging and Lunit were the only software to perform significantly better than the Intermediate Reader. The majority of these CAD software showed significantly lower performance among participants with a past history of TB. The radiography equipment used to capture the CXR image was also shown to affect performance for some CAD software. TB program implementers now have a wide selection of quality CAD software solutions to utilize in their CXR screening initiatives.


Assuntos
Aprendizado de Máquina/normas , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Tuberculose Pulmonar/diagnóstico por imagem , Adolescente , Adulto , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Interpretação de Imagem Radiográfica Assistida por Computador/normas , Radiografia Torácica/métodos , Software/normas , Tuberculose Pulmonar/diagnóstico
10.
Mol Cells ; 44(11): 843-850, 2021 Nov 30.
Artigo em Inglês | MEDLINE | ID: mdl-34819397

RESUMO

The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http://qomics.sookmyung.ac.kr.


Assuntos
Pesquisa Biomédica/métodos , Biologia Computacional/métodos , Genômica/métodos , Neoplasias/genética , Software/normas , Humanos
11.
Nat Commun ; 12(1): 6947, 2021 11 29.
Artigo em Inglês | MEDLINE | ID: mdl-34845212

RESUMO

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework, and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.


Assuntos
Substâncias Macromoleculares/química , Simulação de Acoplamento Molecular , Proteínas/química , Software/normas , Benchmarking , Sítios de Ligação , Humanos , Ligantes , Substâncias Macromoleculares/metabolismo , Ligação Proteica , Proteínas/metabolismo , Reprodutibilidade dos Testes
12.
Genes (Basel) ; 12(11)2021 11 18.
Artigo em Inglês | MEDLINE | ID: mdl-34828418

RESUMO

Biological omics data such as transcriptomes and methylomes have the inherent "large p small n" paradigm, i.e., the number of features is much larger than that of the samples. A feature selection (FS) algorithm selects a subset of the transcriptomic or methylomic biomarkers in order to build a better prediction model. The hidden patterns in the FS solution space make it challenging to achieve a feature subset with satisfying prediction performances. Swarm intelligence (SI) algorithms mimic the target searching behaviors of various animals and have demonstrated promising capabilities in selecting features with good machine learning performances. Our study revealed that different SI-based feature selection algorithms contributed complementary searching capabilities in the FS solution space, and their collaboration generated a better feature subset than the individual SI feature selection algorithms. Nine SI-based feature selection algorithms were integrated to vote for the selected features, which were further refined by the dynamic recursive feature elimination framework. In most cases, the proposed Zoo algorithm outperformed the existing feature selection algorithms on transcriptomics and methylomics datasets.


Assuntos
Epigenoma , Genômica/métodos , Software/normas , Transcriptoma , Biomarcadores/metabolismo , Genômica/normas , Humanos , Aprendizado de Máquina
13.
Nutrients ; 13(11)2021 Oct 26.
Artigo em Inglês | MEDLINE | ID: mdl-34836046

RESUMO

My E-Diary for Activities and Lifestyle (MEDAL), a web-based application, was developed to assess the diets of children. This study examined the validity of school recess meals reported by children on MEDAL, using meal photography as the reference. Recess meals were photographed by trained researchers, and food items and portion sizes of recess meals reported on MEDAL were compared to recess meal photos. Validity was assessed by percentages of match, omission and intrusion for food items and percentages of the match, underestimation and overestimation for portion sizes. The Mann-Whitney test and the Wilcoxon matched-pairs signed-rank test examined if sex, school and day of recording influenced the validity of food item reporting. We found that participants (n = 33, aged 10-11 years) recalled 60.2% of food items consumed at recess accurately (matches); omissions (24.6%) were more common than intrusions (15.2%). Omissions tended to be side dishes, and intrusions tended to be high-calorie items. Sex, school and day of recording did not influence validity. For food portion sizes, 58.3% of items were accurately reported. Overestimations (33.3%) were more common than underestimations (8.3%). In conclusion, these children were able to report food items consumed during school recess meals using MEDAL, albeit with limitations on the degree of accuracy.


Assuntos
Registros de Dieta , Inquéritos sobre Dietas/normas , Serviços de Alimentação/estatística & dados numéricos , Serviços de Saúde Escolar/estatística & dados numéricos , Software/normas , Criança , Dieta/psicologia , Inquéritos sobre Dietas/métodos , Ingestão de Alimentos/psicologia , Feminino , Humanos , Intervenção Baseada em Internet , Masculino , Refeições/psicologia , Fotografação , Tamanho da Porção/psicologia , Reprodutibilidade dos Testes , Estatísticas não Paramétricas
14.
Mol Genet Metab ; 134(3): 274-280, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34663554

RESUMO

Gaucher disease (GD) is a rare lysosomal storage disorder that is divided into three subtypes based on presentation of neurological manifestations. Distinguishing between the types has important implications for treatment and counseling. Yet, patients with neuronopathic forms of GD, types 2 and 3, often present at young ages and can have overlapping phenotypes. It has been shown that new technologies employing artificial intelligence and facial recognition software can assist with dysmorphology assessments. Though classically not associated nor previously described with a dysmorphic facial phenotype, this study investigated whether a facial recognition platform could distinguish between photos of patients with GD2 and GD3 and discriminate between them and photos of healthy controls. Each cohort included over 100 photos. A cross validation scheme including a series of binary comparisons between groups was used. Outputs included a composite photo of each cohort and either a receiver operating characteristic curve or a confusion matrix. Binary comparisons showed that the software could correctly group photos at least 89% of the time. Multiclass comparison between GD2, GD3, and healthy controls demonstrated a mean accuracy of 76.6%, compared to a 37.7% chance for random comparison. Both GD2 and GD3 have now been added to the facial recognition platform as established syndromes that can be identified by the algorithm. These results suggest that facial recognition and artificial intelligence, though no substitute for other diagnostic methods, may aid in the recognition of neuronopathic GD. The algorithm, in concert with other clinical features, also appears to distinguish between young patients with GD2 and GD3, suggesting that this tool can help facilitate earlier implementation of appropriate management.


Assuntos
Inteligência Artificial/normas , Reconhecimento Facial , Doença de Gaucher/fisiopatologia , Fenótipo , Software/normas , Adolescente , Adulto , Criança , Pré-Escolar , Estudos de Coortes , Feminino , Doença de Gaucher/classificação , Doença de Gaucher/diagnóstico , Humanos , Lactente , Recém-Nascido , Masculino , Anormalidades Musculoesqueléticas , Curva ROC , Adulto Jovem
15.
BMC Genom Data ; 22(1): 43, 2021 10 21.
Artigo em Inglês | MEDLINE | ID: mdl-34674637

RESUMO

BACKGROUND: Mitochondrial haplogroup assignment is an important tool for forensics and evolutionary genetics. African populations are known to display a high diversity of mitochondrial haplogroups. In this research we explored mitochondrial haplogroup assignment in African populations using commonly used genome-wide SNP arrays. RESULTS: We show that, from eight commonly used SNP arrays, two SNP arrays outperform the other arrays when it comes to the correct assignment of African mitochondrial haplogroups. One array enables the recognition of 81% of the African mitochondrial haplogroups from our compiled dataset of full mitochondrial sequences. Other SNP arrays were able to assign 4-62% of the African mitochondrial haplogroups present in our dataset. We also assessed the performance of available software for assigning mitochondrial haplogroups from SNP array data. CONCLUSIONS: These results provide the first cross-checked quantification of mitochondrial haplogroup assignment performance from SNP array data. Mitochondrial haplogroup frequencies inferred from most common SNP arrays used for human population analysis should be considered with caution.


Assuntos
/genética , DNA Mitocondrial/genética , Haplótipos/genética , Mitocôndrias/genética , Análise de Sequência com Séries de Oligonucleotídeos/normas , Polimorfismo de Nucleotídeo Único/genética , Conjuntos de Dados como Assunto , Humanos , Software/normas
16.
Genes (Basel) ; 12(10)2021 09 28.
Artigo em Inglês | MEDLINE | ID: mdl-34680927

RESUMO

Predicting gene expression from genotyped data is valuable for studying inaccessible tissues such as the brain. Herein we present eGenScore, a polygenic/poly-variation method, and compare it with PrediXcan, a method based on regularized linear regression using elastic nets. While both methods have the same purpose of predicting gene expression based on genotype, they carry important methodological differences. We compared the performance of expression quantitative trait loci (eQTL) models to predict gene expression in the frontal cortex, comparing across these frameworks (eGenScore vs. PrediXcan) and training datasets (BrainEAC, which is brain-specific, vs. GTEx, which has data across multiple tissues). In addition to internal five-fold cross-validation, we externally validated the gene expression models using the CommonMind Consortium database. Our results showed that (1) PrediXcan outperforms eGenScore regardless of the training database used; and (2) when using PrediXcan, the performance of the eQTL models in frontal cortex is higher when trained with GTEx than with BrainEAC.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Genótipo , Modelos Genéticos , Software/normas , Transcriptoma , Encéfalo/metabolismo , Bases de Dados Genéticas , Humanos , Herança Multifatorial , Locos de Características Quantitativas
17.
Genes (Basel) ; 12(10)2021 09 30.
Artigo em Inglês | MEDLINE | ID: mdl-34680954

RESUMO

Probabilistic genotyping has become widespread. EuroForMix and DNAStatistX are both based upon maximum likelihood estimation using a γ model, whereas STRmix™ is a Bayesian approach that specifies prior distributions on the unknown model parameters. A general overview is provided of the historical development of probabilistic genotyping. Some general principles of interpretation are described, including: the application to investigative vs. evaluative reporting; detection of contamination events; inter and intra laboratory studies; numbers of contributors; proposition setting and validation of software and its performance. This is followed by details of the evolution, utility, practice and adoption of the software discussed.


Assuntos
Técnicas de Genotipagem/métodos , Software/normas , Probabilidade
18.
BMC Microbiol ; 21(1): 228, 2021 08 18.
Artigo em Inglês | MEDLINE | ID: mdl-34407769

RESUMO

BACKGROUND: Targeted metagenomics and IS-Pro method are two of the many methods that have been used to study the microbiome. The two methods target different regions of the 16 S rRNA gene. The aim of this study was to compare targeted metagenomics and IS-Pro methods for the ability to discern the microbial composition of the lung microbiome of COPD patients. METHODS: Spontaneously expectorated sputum specimens were collected from COPD patients. Bacterial DNA was extracted and used for targeted metagenomics and IS-Pro method. The analysis was performed using QIIME2 (targeted metagenomics) and IS-Pro software (IS-Pro method). Additionally, a laboratory cost per isolate and time analysis was performed for each method. RESULTS: Statistically significant differences were observed in alpha diversity when targeted metagenomics and IS-Pro methods' data were compared using the Shannon diversity measure (p-value = 0.0006) but not with the Simpson diversity measure (p-value = 0.84). Distinct clusters with no overlap between the two technologies were observed for beta diversity. Targeted metagenomics had a lower relative abundance of phyla, such as the Proteobacteria, and higher relative abundance of phyla, such as Firmicutes when compared to the IS-Pro method. Haemophilus, Prevotella and Streptococcus were most prevalent genera across both methods. Targeted metagenomics classified 23 % (144/631) of OTUs to a species level, whereas IS-Pro method classified 86 % (55/64) of OTUs to a species level. However, unclassified OTUs accounted for a higher relative abundance when using the IS-Pro method (35 %) compared to targeted metagenomics (5 %). The two methods performed comparably in terms of cost and time; however, the IS-Pro method was more user-friendly. CONCLUSIONS: It is essential to understand the value of different methods for characterisation of the microbiome. Targeted metagenomics and IS-Pro methods showed differences in ability in identifying and characterising OTUs, diversity and microbial composition of the lung microbiome. The IS-Pro method might miss relevant species and could inflate the abundance of Proteobacteria. However, the IS-Pro kit identified most of the important lung pathogens, such as Burkholderia and Pseudomonas and may work in a more diagnostics-orientated setting. Both methods were comparable in terms of cost and time; however, the IS-Pro method was easier to use.


Assuntos
Pulmão/microbiologia , Metagenômica/métodos , Metagenômica/normas , Microbiota/genética , Software/normas , Idoso , Idoso de 80 Anos ou mais , DNA Bacteriano/genética , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , RNA Ribossômico 16S/genética , Escarro/microbiologia
19.
Acta Crystallogr F Struct Biol Commun ; 77(Pt 7): 226-229, 2021 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-34196613

RESUMO

In macromolecular crystallography, paired refinement is generally accepted to be the optimal approach for the determination of the high-resolution cutoff. The software tool PAIREF provides automation of the protocol and associated analysis. Support for phenix.refine as a refinement engine has recently been implemented in the program. This feature is presented here using previously published data for thermolysin. The results demonstrate the importance of the complete cross-validation procedure to obtain a thorough and unbiased insight into the quality of high-resolution data.


Assuntos
Cristalografia por Raios X/métodos , Bases de Dados de Proteínas , Software , Cristalografia por Raios X/normas , Bases de Dados de Proteínas/normas , Software/normas
20.
Retrovirology ; 18(1): 16, 2021 06 27.
Artigo em Inglês | MEDLINE | ID: mdl-34176496

RESUMO

The characterisation of the HIV-1 reservoir, which consists of replication-competent integrated proviruses that persist on antiretroviral therapy (ART), is made difficult by the rarity of intact proviruses relative to those that are defective. While the only conclusive test for the replication-competence of HIV-1 proviruses is carried out in cell culture, genetic characterization of genomes by near full-length (NFL) PCR and sequencing can be used to determine whether particular proviruses have insertions, deletions, or substitutions that render them defective. Proviruses that are not excluded by having such defects can be classified as genetically intact and, possibly, replication competent. Identifying and quantifying proviruses that are potentially replication-competent is important for the development of strategies towards a functional cure. However, to date, there are no programs that can be incorporated into deep-sequencing pipelines for the automated characterization and annotation of HIV genomes. Existing programs that perform this work require manual intervention, cannot be widely installed, and do not have easily adjustable settings. Here, we present HIVIntact, a python-based software tool that characterises genomic defects in NFL HIV-1 sequences, allowing putative intact genomes to be identified in-silico. Unlike other applications that assess the genetic intactness of HIV genomes, this tool can be incorporated into existing sequence-analysis pipelines and applied to large next-generation sequencing datasets.


Assuntos
DNA Viral/genética , Genoma Viral , HIV-1/genética , Software/normas , Humanos , Provírus/genética , Integração Viral , Latência Viral
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