Design, development and characterization of a chimeric protein with disulfide reductase and protease domain showing keratinase activity.

Keratin is one of the major components of solid waste, and the degradation products have extensive applications in various commercial industries. Due to the complexity of the structure of keratin, especially the disulfide bonds between keratin polypeptides, keratinolytic activity is efficient with a mixture of proteins with proteases, peptidases, and oxidoreductase activity. The present work aimed to create an engineered chimeric protein with a disulfide reductase domain and a protease domain connected with a flexible linker.

Cleavage of cell junction proteins as a host invasion strategy in leptospirosis.

Infection and invasion are the prerequisites for developing the disease symptoms in a host. While the probable mechanism of host invasion and pathogenesis is known in many pathogens, very little information is available on Leptospira invasion/pathogenesis. For causing systemic infection Leptospira must transmigrate across epithelial barriers, which is the most critical and challenging step.

Characteristics and predictors associated with cancer-related fatigue among solid and liquid tumors.

Purpose: Cancer-related fatigue (CRF) is a devastating complication with limited recognized clinical risk factors. We examined characteristics among solid and liquid cancers utilizing Machine learning (ML) approaches for predicting CRF.

Methods: We utilized 2017 National Inpatient Sample database and employed generalized linear models to assess the association between CRF and the outcome of burden of illness among hospitalized solid and non-solid tumors patients.

Application of big data analyses to compare the impact of oral and gastrointestinal mucositis on risks and outcomes of febrile neutropenia and septicemia among patients hospitalized for the treatment of leukemia or multiple myeloma.

Purpose: Oral ulcerative mucositis (UM) and gastrointestinal mucositis (GIM) have been associated with increased likelihood of systemic infection (bacteremia and sepsis) in patients being treated for hematological malignancies. To better define and contrast differences between UM and GIM, we utilized the United States 2017 National Inpatient Sample and analyzed patients hospitalized for the treatment of multiple myeloma (MM) or leukemia.

Methods: We utilized generalized linear models to assess the association between adverse events-UM and GIM-among hospitalized MM or leukemia patients and the outcome of febrile neutropenia (FN), septicemia, burden of illness, and mortality.