Evaluation of End-of-Life Quality Care Between American Indian and White North Carolina Decedents Diagnosed With Lung Cancer, 2003-2020.

Purpose: Lung cancer mortality rates for American Indians (AIs) are the highest among US race groups. End-of-life (EOL) care presents opportunities to limit aggressive and potentially unnecessary treatment. We evaluated differences in EOL quality of care between AI and White (WH) decedents with lung cancer.

Characterizing Cancer Burden in the American Indian Population in North Carolina.

Background: The American Indian (AI) population in North Carolina has limited access to the Indian Health Service. Consequently, cancer burden and disparities may differ from national estimates. We describe the AI cancer population and examine AI-White disparities in cancer incidence and mortality.

Patient- And Provider-Level Predictors of Survival Among Patients With Metastatic Renal Cell Carcinoma Initiating Oral Anticancer Agents.

Purpose: In an era of rapid expansion of FDA approvals for oral anticancer agents (OAAs), it is important to understand the factors associated with survival among real-world populations, which include groups not well-represented in pivotal clinical trials of OAAs, such as the elderly, racial minorities, and medically complex patients. Our objective was to evaluate patient- and provider-level characteristics' associations with mortality among a multi-payer cohort of metastatic renal cell carcinoma (mRCC) patients who initiated OAAs.

Methods: This retrospective cohort study was conducted using data from the North Carolina state cancer registry linked to multi-payer claims data for the years 2004 to 2015.

Provider- and patient-level predictors of oral anticancer agent initiation and adherence in patients with metastatic renal cell carcinoma.

Background: Improving oral anticancer agent (OAA) initiation and adherence is the important quality-of-care issues, particularly since one fourth of anticancer agents being developed will be administered orally. Our objective was to identify provider- and patient-level characteristics associated with OAA initiation and adherence among individuals with metastatic renal cell carcinoma (mRCC).

Methods: We used state cancer registry data linked to multi-payer claims data to identify patients with mRCC diagnosed in 2004-2015.

SGC-AAK1-1: A Chemical Probe Targeting AAK1 and BMP2K.

Inhibitors based on a 3-acylaminoindazole scaffold were synthesized to yield potent dual AAK1/BMP2K inhibitors. Optimization furnished a small molecule chemical probe (SGC-AAK1-1, ) that is potent and selective for AAK1/BMP2K over other NAK family members, demonstrates narrow activity in a kinome-wide screen, and is functionally active in cells. This inhibitor represents one of the best available small molecule tools to study the functions of AAK1 and BMP2K.

Intrinsically disordered proteins and structured proteins with intrinsically disordered regions have different functional roles in the cell.

Many studies about classification and the functional annotation of intrinsically disordered proteins (IDPs) are based on either the occurrence of long disordered regions or the fraction of disordered residues in the sequence. Taking into account both criteria we separate the human proteome, taken as a case study, into three variants of proteins: i) ordered proteins (ORDPs), ii) structured proteins with intrinsically disordered regions (IDPRs), and iii) intrinsically disordered proteins (IDPs). The focus of this work is on the different functional roles of IDPs and IDPRs, which up until now have been generally considered as a whole.

Identification of a Robust Methylation Classifier for Cutaneous Melanoma Diagnosis.

Early diagnosis improves melanoma survival, yet the histopathological diagnosis of cutaneous primary melanoma can be challenging, even for expert dermatopathologists. Analysis of epigenetic alterations, such as DNA methylation, that occur in melanoma can aid in its early diagnosis. Using a genome-wide methylation screening, we assessed CpG methylation in a diverse set of 89 primary invasive melanomas, 73 nevi, and 41 melanocytic proliferations of uncertain malignant potential, classified based on interobserver review by dermatopathologists.

SMAC: Spatial multi-category angle-based classifier for high-dimensional neuroimaging data.

With the development of advanced imaging techniques, scientists are interested in identifying imaging biomarkers that are related to different subtypes or transitional stages of various cancers, neuropsychiatric diseases, and neurodegenerative diseases, among many others. In this paper, we propose a novel spatial multi-category angle-based classifier (SMAC) for the efficient identification of such imaging biomarkers. The proposed SMAC not only utilizes the spatial structure of high-dimensional imaging data but also handles both binary and multi-category classification problems.