Bento: a toolkit for subcellular analysis of spatial transcriptomics data.

The spatial organization of molecules in a cell is essential for their functions. While current methods focus on discerning tissue architecture, cell-cell interactions, and spatial expression patterns, they are limited to the multicellular scale. We present Bento, a Python toolkit that takes advantage of single-molecule information to enable spatial analysis at the subcellular scale.

Computational cell-cell interaction technologies drive mechanistic and biomarker discovery in the tumor microenvironment.

Complex networks of cell-cell interactions (CCIs) within the tumor microenvironment (TME) play a crucial role in cancer persistence. These communication axes represent prime targets for therapeutic intervention, but our incomplete understanding of the cellular heterogeneity and interacting partners within the TME remains a stubborn barrier to complete drug responses. This review outlines recent advances in the study of CCIs that leverage single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) technologies that can clarify TME dynamics.

De novo design of potent and resilient hACE2 decoys to neutralize SARS-CoV-2.

We developed a de novo protein design strategy to swiftly engineer decoys for neutralizing pathogens that exploit extracellular host proteins to infect the cell. Our pipeline allowed the design, validation, and optimization of de novo human angiotensin-converting enzyme 2 (hACE2) decoys to neutralize severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The best monovalent decoy, CTC-445.

design of ACE2 protein decoys to neutralize SARS-CoV-2.

There is an urgent need for the ability to rapidly develop effective countermeasures for emerging biological threats, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes the ongoing coronavirus disease 2019 (COVID-19) pandemic. We have developed a generalized computational design strategy to rapidly engineer proteins that precisely recapitulate the protein surface targeted by biological agents, like viruses, to gain entry into cells. The designed proteins act as decoys that block cellular entry and aim to be resilient to viral mutational escape.

Development and content validity of the Lupus Foundation of America rapid evaluation of activity in lupus (LFA-REAL™): a patient-reported outcome measure for lupus disease activity.

Background/purpose: The LFA REAL™ is a measurement system for evaluating lupus disease activity from both clinician and patient perspectives. Patients' viewpoints are captured using a patient-reported outcome (PRO) questionnaire. A series of visual analog scales are designed to rate disease severity and progress over the past 4 weeks.

Preliminary test of the LFA rapid evaluation of activity in lupus (LFA-REAL): an efficient outcome measure correlates with validated instruments.

Objective: Current disease activity measures for systemic lupus erythematosus (SLE) are difficult to score or interpret and problematic for use in clinical practice. Lupus Foundation of America (LFA)-Rapid Evaluation of Activity in Lupus (REAL) is a pilot application composed of anchored visual analogue scores (0-100 mm each) for each organ affected by lupus. This study evaluated the use of LFA-REAL in capturing SLE disease activity.