Value of the combination of intraepithelial tumor-infiltrating lymphocyte density and the heterogeneity of density as a prognostic marker in stage III colorectal cancers.

Tumor-infiltrating lymphocyte (TIL) density is both a prognostic and a predictive factor in colorectal cancer (CRC). Whether the heterogeneity of TIL density across the tumor plays an important role in the clinical outcome of CRC is not well known. Adjuvant chemotherapy-treated patients with stage III CRC were analyzed for survival according to TIL density and density heterogeneity, which were determined on CD8-immunostained slides using a machine learning method and by calculating the Simpson evenness index, respectively.

Limitations of a proper SFTSV mouse model using human C-type lectin receptors.

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a tick-borne virus with a human mortality rate of up to 30%, posing a significant threat to public health. However, the lack of suitable research models has impeded the development of effective human vaccines. In this study, we engineered transgenic mice (3xTg) using a novel construct that simultaneously expresses three C-type Lectin receptors, identified as critical SFTSV entry receptors.

Identification and characterization of 17 novel polynucleotide microsatellite markers in Ocypode stimpsoni (Decapoda: Ocypodidae).

Objective: The ghost crab Ocypode stimpsoni (Decapoda) is designated as a protected marine species in Korea due to its declining population. In this study, we successfully identified 17 microsatellite markers for O. stimpsoni through next-generation sequencing.

Emission characteristics analysis on microplastics by inorganic sludge discharged from recycling processes of agricultural waste vinyl in Korea.

Globally, various policies are being implemented to phase out plastic, and South Korea has set targets to reduce waste and increase recycling rates by 2030. Concerns about managing microplastic pollution are growing. Most advanced research has primarily focused on aquatic ecosystems.

Accurate predictions of SARS-CoV-2 infectivity from comprehensive analysis.

An unprecedented amount of SARS-CoV-2 data has been accumulated compared with previous infectious diseases, enabling insights into its evolutionary process and more thorough analyses. This study investigates SARS-CoV-2 features as it evolved to evaluate its infectivity. We examined viral sequences and identified the polarity of amino acids in the receptor binding motif (RBM) region.