Revisiting the druggable genome using predicted structures and data mining.

Identification of novel drug targets is a key component of modern drug discovery. While antimalarial targets are often identified through the mechanism of action studies on phenotypically derived inhibitors, this method tends to be time- and resource-consuming. The discoverable target space is also constrained by existing compound libraries and phenotypic assay conditions.

Historical data provide new insights into inheritance of traits important for diploid potato breeding.

Using a diploid potato diversity panel of 246 breeding lines, a genotyping-by-sequencing and a GWAS approach, we mapped QTL for ten traits important to potato breeders, including two previously unmapped traits: boiled tuber taste and pollen fertility. Potato breeding at the diploid level has a long history and has gained new impetus recently, when F1 hybrid breeding was made possible with the discovery of a dominant gene for self-compatibility. Our study deploys a unique diploid diversity panel with a broadened cultivated potato gene pool obtained as a result of introgressing valuable traits from wild potato relatives into the Solanum tuberosum background.

Neuroscience-informed psychoeducation for addiction: a conceptual and feasibility study.

Over the past few decades, our understanding of substance use disorders (SUD) has been reshaped by evidence from neuroscience, which suggests that SUD are characterized by specific neuromarkers that transcend traditional diagnostic boundaries and act as pre-diagnostic markers that could be targeted through preventive attempts. Connectivity-based neuromarkers or brain networks have emerged as a promising framework, providing new insights into the neurocognitive mechanisms of SUD. Utilizing this data-driven framework assists prevention and intervention developers in offering a non-judgmental insight for adolescents regarding the potential vulnerability of neurocognitive systems to continued substance use.

Multimodal machine learning to predict surgical site infection with healthcare workload impact assessment.

Remote monitoring is essential for healthcare digital transformation, however, this poses greater burdens on healthcare providers to review and respond as the data collected expands. This study developed a multimodal neural network to automate assessments of patient-generated data from remote postoperative wound monitoring. Two interventional studies including adult gastrointestinal surgery patients collected wound images and patient-reported outcome measures (PROMs) for 30-days postoperatively.

Assessing STI and HIV risks among autistic individuals: Implications for healthcare access and intervention.

Background: Sexually transmitted infections (STIs) are prevalent in the general population. Autistic individuals, both with and without intellectual disability (ID), are potentially at increased risk due to gaps in sexual health education, increased vulnerability to sexual abuse, victimization, and disparities in access to primary and reproductive health care.

Objective: This study aims to identify the prevalence of STIs and HIV among a national sample of Medicaid-enrolled autistic individuals and their peers, identifying opportunities for intervention.