Low Vapor Pressure Solvents for Single-Molecule Junction Measurements.

Nonpolar solvents commonly used in scanning tunneling microscope-based break junction measurements exhibit hazards and relatively low boiling points (bp) that limit the scope of solution experiments at elevated temperatures. Here we show that low toxicity, ultrahigh bp solvents such as bis(2-ethylhexyl) adipate (bp = 417 °C) and squalane (457 °C) can be used to probe molecular junctions at ≥100 °C. With these, we extend solvent- and temperature-dependent conductance trends for junction components such as 4,4'-bipyridine and thiomethyl-terminated oligophenylenes and reveal the gold snapback distance is larger at 100 °C due to increased surface atom mobility. We further show the rate of surface transmetalation and homocoupling reactions using phenylboronic acids increases at 100 °C, while junctions comprising anticipated boroxine condensation products form only at room temperature in an anhydrous glovebox atmosphere. Overall, this work demonstrates the utility of low vapor pressure solvents for the comprehensive characterization of junction properties and chemical reactivity at the single-molecule limit.

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma.

Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on multiparametric MRI (mpMRI) for diagnosis, treatment planning, and longitudinal treatment monitoring; yet automated, objective, and quantitative tools for non-invasive assessment of meningiomas on mpMRI are lacking. The BraTS meningioma 2023 challenge will provide a community standard and benchmark for state-of-the-art automated intracranial meningioma segmentation models based on the largest expert annotated multilabel meningioma mpMRI dataset to date. Challenge competitors will develop automated segmentation models to predict three distinct meningioma sub-regions on MRI including enhancing tumor, non-enhancing tumor core, and surrounding nonenhancing T2/FLAIR hyperintensity. Models will be evaluated on separate validation and held-out test datasets using standardized metrics utilized across the BraTS 2023 series of challenges including the Dice similarity coefficient and Hausdorff distance. The models developed during the course of this challenge will aid in incorporation of automated meningioma MRI segmentation into clinical practice, which will ultimately improve care of patients with meningioma.

Satellite monitoring of terrestrial plastic waste.

Plastic waste is a significant environmental pollutant that is difficult to monitor. We created a system of neural networks to analyze spectral, spatial, and temporal components of Sentinel-2 satellite data to identify terrestrial aggregations of waste. The system works at wide geographic scale, finding waste sites in twelve countries across Southeast Asia. We evaluated performance in Indonesia and detected 374 waste aggregations, more than double the number of sites found in public databases. The same system deployed in Southeast Asia identifies 996 subsequently confirmed waste sites. For each detected site, we algorithmically monitor waste site footprints through time and cross-reference other datasets to generate physical and social metadata. 19% of detected waste sites are located within 200 m of a waterway. Numerous sites sit directly on riverbanks, with high risk of ocean leakage.