TBM Hunter: Identify and Score Canonical, Extended, and Unconventional Tankyrase-Binding Motifs in Any Protein.

Tankyrases, a versatile protein group within the poly(ADP-ribose) polymerase family, are essential for post-translational poly(ADP-ribosyl)ation, influencing various cellular functions and contributing to diseases, particularly cancer. Consequently, tankyrases have become important targets for anti-cancer drug development. Emerging approaches in drug discovery aim to disrupt interactions between tankyrases and their binding partners, which hinge on tankyrase-binding motifs (TBMs) within partner proteins and ankyrin repeat cluster domains within tankyrases. Our study addresses the challenge of identifying and ranking TBMs. We have conducted a comprehensive review of the existing literature, classifying TBMs into three distinct groups, each with its own scoring system. To facilitate this process, we introduce TBM Hunter-an accessible, web-based tool. This user-friendly platform provides a cost-free and efficient means to screen and assess potential TBMs within any given protein. TBM Hunter can handle individual proteins or lists of proteins simultaneously. Notably, our results demonstrate that TBM Hunter not only identifies known TBMs but also uncovers novel ones. In summary, our study offers an all-encompassing perspective on TBMs and presents an easy-to-use, precise, and free tool for identifying and evaluating potential TBMs in any protein, thereby enhancing research and drug development efforts focused on tankyrases.

Association Between In-Home Treatment and Engagement in Psychosocial Services Among Medicaid-Enrolled Youth.

OBJECTIVE: Prior studies have identified low rates of engagement in mental health (MH) services in clinic settings among children enrolled in Medicaid. Yet, little is known about whether the delivery of in-home MH treatment (in which the clinician travels to the child's home) improves engagement for this population. This study examines the association between the delivery of in-home psychosocial treatment and engagement in services among Medicaid-enrolled youth. METHOD: We used 2010 to 2014 Georgia Medicaid claims data to identify 53,508 children and adolescents (aged 5-17 years) with a MH diagnosis that initiated new psychosocial treatment. We estimated regression models controlling for covariates to examine the relationship of the receipt of any in-home psychosocial treatment in the home setting with 3 outcome measures of engagement: receipt of at least 4 psychosocial visits during the first 12 weeks; total number of psychosocial visits during the first 12 weeks; and total duration of service use. RESULTS: Those who received any in-home psychosocial treatment (compared to those who did not) had 4.3 times the odds (odds ratio = 4.3, 95% CI = 4.0, 4.7) of receiving at least 4 visits during the first 12 weeks, had 4.5 (95% CI = 4.3, 4.7) more predicted visits during the first 12 weeks, and had a longer treatment episode duration (mean rate ratio = 1.54, 95% CI = 1.48,1.59). CONCLUSION: Although many Medicaid-enrolled youth do not receive a sufficient number of MH services to achieve positive outcomes, our findings suggest that providing in-home psychosocial treatment can improve service engagement and potentially help address this challenge.

Human against Machine? Machine Learning Identifies MicroRNA Ratios as Biomarkers for Melanoma.

Identification of quantitative molecular biomarkers to distinguish melanoma from nevi is highly desirable. Expressions of microRNAs (miRNAs) are promising candidates but lack consensus in many studies. Torres et al. (2020) utilized a machine learning pipeline to identify miRNA ratios as strong biomarkers. Results indicate that machine learning, although powerful, requires human input to identify high quality biomarker signatures.