Predicting locus-specific DNA methylation levels in cancer and paracancer tissues.

To predict base-resolution DNA methylation in cancerous and paracancerous tissues. We collected six cancer DNA methylation datasets from The Cancer Genome Atlas and five cancer datasets from Gene Expression Omnibus and established machine learning models using paired cancerous and paracancerous tissues. Tenfold cross-validation and independent validation were performed to demonstrate the effectiveness of the proposed method.

The transcriptional risk scores for kidney renal clear cell carcinoma using XGBoost and multiple omics data.

Most kidney cancers are kidney renal clear cell carcinoma (KIRC) that is a main cause of cancer-related deaths. Polygenic risk score (PRS) is a weighted linear combination of phenotypic related alleles on the genome that can be used to assess KIRC risk. However, standalone SNP data as input to the PRS model may not provide satisfactory result.

Parameter estimation of the COVID-19 transmission model using an improved quantum-behaved particle swarm optimization algorithm.

The outbreak of coronavirus disease (COVID-19) and its accompanying pandemic have created an unprecedented challenge worldwide. Parametric modeling and analyses of the COVID-19 play a critical role in providing vital information about the character and relevant guidance for controlling the pandemic. However, the epidemiological utility of the results obtained from the COVID-19 transmission model largely depends on accurately identifying parameters.

Diagnosis and Treatment of Cervical Spondylotic Radiculopathy Using Selective Nerve Root Block (SNRB): Where are We Now?

Cervical spondylotic radiculopathy (CSR) is one of the most common degenerative diseases of the spine that is commonly treated with surgery. The primary goal of surgery is to relieve symptoms through decompression or relieving pressure on compressed cervical nerves. Nevertheless, cutaneous pain distribution is not always predictable, making accurate diagnosis challenging and increasing the likelihood of inadequate surgical outcomes.