Utilization of rapid antigen tests for screening SARS-CoV-2 prior to dental treatment.

Potential aerosols containing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral particles can be generated during dental treatment. Hence, patient triage is essential to prevent the spread of SARS-CoV-2 in dental clinical settings. The present study described the use of rapid antigen tests for SARS-CoV-2 screening prior to dental treatment in an academic dental clinical setting in Thailand during the pandemic.

Incorporating biological networks into high-dimensional Bayesian survival analysis using an ICM/M algorithm.

The Cox proportional hazards model has been widely used in cancer genomic research that aims to identify genes from high-dimensional gene expression space associated with the survival time of patients. With the increase in expertly curated biological pathways, it is challenging to incorporate such complex networks in fitting a high-dimensional Cox model. This paper considers a Bayesian framework that employs the Ising prior to capturing relations among genes represented by graphs.

Integrating Biological Knowledge Into Case-Control Analysis Through Iterated Conditional Modes/Medians Algorithm.

Logistic regression is an effective tool in case-control analysis. With the advanced high throughput technology, a quest to seek a fast and efficient method in fitting high-dimensional logistic regression has gained much interest. An empirical Bayes model for logistic regression is considered in this article.

A fast and efficient approach for genomic selection with high-density markers.

Recent advances in high-throughput genotyping have motivated genomic selection using high-density markers. However, an increasingly large number of markers brings up both statistical and computational issues and makes it difficult to estimate the breeding values. We propose to apply the penalized orthogonal-components regression (POCRE) method to estimate breeding values.

Genome-wide association analysis of GAW17 data using an empirical Bayes variable selection.

Next-generation sequencing technologies enable us to explore rare functional variants. However, most current statistical techniques are too underpowered to capture signals of rare variants in genome-wide association studies. We propose a supervised coalescing of single-nucleotide polymorphisms to obtain gene-based markers that can stably reveal possible genetic effects related to rare alleles.

Genome-wide case-control study in GAW17 using coalesced rare variants.

Genome-wide association studies have successfully identified numerous loci at which common variants influence disease risks or quantitative traits of interest. Despite these successes, the variants identified by these studies have generally explained only a small fraction of the variations in the phenotype. One explanation may be that many rare variants that are not included in the common genotyping platforms may contribute substantially to the genetic variations of the diseases.

Delineating diseases by IMS-MS profiling of serum N-linked glycans.

Altered branching and aberrant expression of N-linked glycans is known to be associated with disease states such as cancer. However, the complexity of determining such variations hinders the development of specific glycomic approaches for assessing disease states. Here, we examine a combination of ion mobility spectrometry (IMS) and mass spectrometry (MS) measurements, with principal component analysis (PCA) for characterizing serum N-linked glycans from 81 individuals: 28 with cirrhosis of the liver, 25 with liver cancer, and 28 apparently healthy.

Simultaneous genome-wide association studies of anti-cyclic citrullinated peptide in rheumatoid arthritis using penalized orthogonal-components regression.

Genome-wide associations between single-nucleotide polymorphisms and clinical traits were simultaneously conducted using penalized orthogonal-components regression. This method was developed to identify the genetic variants controlling phenotypes from a massive number of candidate variants. By investigating the association between all single-nucleotide polymorphisms to the phenotype of antibodies against cyclic citrullinated peptide using the rheumatoid arthritis data provided by Genetic Analysis Workshop 16, we identified genetic regions which may contribute to the pathogenesis of rheumatoid arthritis.

Case-control genome-wide association study of rheumatoid arthritis from Genetic Analysis Workshop 16 using penalized orthogonal-components regression-linear discriminant analysis.

Currently, genome-wide association studies (GWAS) are conducted by collecting a massive number of SNPs (i.e., large p) for a relatively small number of individuals (i.

Quantitative serum glycomics of esophageal adenocarcinoma and other esophageal disease onsets.

Aberrant glycosylation has been implicated in various types of cancers and changes in glycosylation may be associated with signaling pathways during malignant transformation. Glycomic profiling of blood serum, in which cancer cell proteins or their fragments with altered glycosylation patterns are shed, could reveal the altered glycosylation. We performed glycomic profiling of serum from patients with no known disease (N = 18), patients with high grade dysplasia (HGD, N = 11) and Barrett's esophagus (N = 5), and patients with esophageal adenocarcinoma (EAC, N = 50) in an attempt to delineate distinct differences in glycosylation between these groups.