Currently, the outbreak of COVID-19 is rapidly spreading especially in Wuhan city, and threatens 14 million people in central China. In the present study we applied the Moran index, a strong ...statistical tool, to the spatial panel to show that COVID-19 infection is spatially dependent and mainly spread from Hubei Province in Central China to neighbouring areas. Logistic model was employed according to the trend of available data, which shows the difference between Hubei Province and outside of it. We also calculated the reproduction number R0 for the range of 2.23, 2.51 via SEIR model. The measures to reduce or prevent the virus spread should be implemented, and we expect our data-driven modeling analysis providing some insights to identify and prepare for the future virus control.
Abstract Background This study retrospectively evaluated the capability of computed-tomography (CT) based radiomic features to predict EGFR mutation status in surgically-resected peripheral lung ...adenocarcinomas in an Asian cohort of patients. Materials and Methods 298 patients with surgically resected peripheral lung adenocarcinomas were investigated in this institutional review board-approved retrospective study with waived consent. 219 quantitative 3D features were extracted from segmented volumes of each tumor, and 59 of these which were considered as independent features were included in the analysis. Clinical and pathological information were obtained from the institutional database. Results Mutant EGFR was significantly associated with female gender ( p =0.0005); never smoker status ( p <0.0001), lepidic predominant adenocarcinomas ( p =0.017), and low or intermediate pathologic grade ( p =0.0002). Statistically significant differences were found in 11 radiomic features between EGFR mutant and wild type groups on univariate analysis. Mutant EGFR status could be predicted by a set of five radiomic features that fall in three broad groups: CT attenuation energy, tumor main direction and texture defined by wavelets and Laws (AUC 0.647). Multiple logistic regression model showed that adding radiomic features to a clinical model resulted in a significant improvement of predicting power, as the AUC increased from 0.667 to 0.709 ( p <0.0001). Conclusions CT based radiomic features of peripheral lung adenocarcinomas can capture useful information regarding tumor phenotype, and the model we built can be useful to predict the presence of EGFR mutations in peripheral lung adenocarcinoma in Asian patients when mutational profiling is not available or possible.
Thousands of novel transcripts have been identified using deep transcriptome sequencing. This discovery of large and 'hidden' transcriptome rejuvenates the demand for methods that can rapidly ...distinguish between coding and noncoding RNA. Here, we present a novel alignment-free method, Coding Potential Assessment Tool (CPAT), which rapidly recognizes coding and noncoding transcripts from a large pool of candidates. To this end, CPAT uses a logistic regression model built with four sequence features: open reading frame size, open reading frame coverage, Fickett TESTCODE statistic and hexamer usage bias. CPAT software outperformed (sensitivity: 0.96, specificity: 0.97) other state-of-the-art alignment-based software such as Coding-Potential Calculator (sensitivity: 0.99, specificity: 0.74) and Phylo Codon Substitution Frequencies (sensitivity: 0.90, specificity: 0.63). In addition to high accuracy, CPAT is approximately four orders of magnitude faster than Coding-Potential Calculator and Phylo Codon Substitution Frequencies, enabling its users to process thousands of transcripts within seconds. The software accepts input sequences in either FASTA- or BED-formatted data files. We also developed a web interface for CPAT that allows users to submit sequences and receive the prediction results almost instantly.
This article provides an overview of recent developments in mediation analysis, that is, analyses used to assess the relative magnitude of different pathways and mechanisms by which an exposure may ...affect an outcome. Traditional approaches to mediation in the biomedical and social sciences are described. Attention is given to the confounding assumptions required for a causal interpretation of direct and indirect effect estimates. Methods from the causal inference literature to conduct mediation in the presence of exposure-mediator interactions, binary outcomes, binary mediators, and case-control study designs are presented. Sensitivity analysis techniques for unmeasured confounding and measurement error are introduced. Discussion is given to extensions to time-to-event outcomes and multiple mediators. Further flexible modeling strategies arising from the precise counterfactual definitions of direct and indirect effects are also described. The focus throughout is on methodology that is easily implementable in practice across a broad range of potential applications.
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