Segmentation aware probabilistic phenotyping of single-cell spatial protein expression data.

Spatial protein expression technologies can map cellular content and organization by simultaneously quantifying the expression of >40 proteins at subcellular resolution within intact tissue sections and cell lines. However, necessary image segmentation to single cells is challenging and error prone, easily confounding the interpretation of cellular phenotypes and cell clusters. To address these limitations, we present STARLING, a probabilistic machine learning model designed to quantify cell populations from spatial protein expression data while accounting for segmentation errors.

Entropy engineering activation of UiO-66 for boosting catalytic transfer hydrogenation.

High-entropy metal-organic frameworks (HE-MOFs) hold promise as versatile materials, yet current rare examples are confined to low-valence elements in the fourth period, constraining their design and optimization for diverse applications. Here, a novel high-entropy, defect-rich and small-sized (32 nm) UiO-66 (ZrHfCeSnTi HE-UiO-66) has been synthesized for the first time, leveraging increased configurational entropy to achieve high tolerance to doping with diverse metal ions. The lattice distortion of HE-UiO-66 induces high exposure of metal nodes to create coordination unsaturated metal sites with a concentration of 322.

Basic Science and Pathogenesis.

Background: Hallmark pathologies of Alzheimer's Disease (AD) include the accumulation of both extracellular amyloid and intracellular tau proteins. While a significant body of knowledge exists surrounding the role of the protein aggregates in the context of AD, research supporting these as targets for therapeutic development have yielded inconsistent findings. One significant barrier is the inability to restore cognitive function despite the successful clearance of these proteins.

Adjuvant Dose-Dense Chemotherapy in Hormone Receptor-Positive Breast Cancer.

Purpose: In light of evolving evidence that some patients with node-positive estrogen receptor-positive (ER+) disease may receive less benefit from chemotherapy, this study reports 12-year outcomes of the C9741 trial overall, and by the sensitivity to endocrine therapy (SET2,3) test index, a biomarker measuring endocrine transcriptional activity, to identify patients most likely to benefit from dose-dense chemotherapy.

Methods: In all, 1,973 patients were randomly assigned to dose-dense versus conventional chemotherapy. Hazard ratios (HRs) for prognosis and for predictive interaction with chemotherapy schedule were estimated from Cox models of long-term disease-free survival (DFS) and overall survival (OS).