Correction to: Atomistic Simulations Modify Interpretation of Spin-Label Oximetry Data. Part 1: Intensified Water-Lipid Interfacial Resistances.

[This corrects the article PMC10249954.].

A general deep learning model for bird detection in high-resolution airborne imagery.

Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural networks can learn to detect individual objects in imagery. However, developing supervised models for ecological monitoring is challenging because it requires large amounts of human-labeled training data, requires advanced technical expertise and computational infrastructure, and is prone to overfitting.

Atomistic simulations modify interpretation of spin-label oximetry data. Part 1: intensified water-lipid interfacial resistances.

The role of membrane cholesterol in cellular function and dysfunction has been the subject of much inquiry. A few studies have suggested that cholesterol may slow oxygen diffusive transport, altering membrane physical properties and reducing oxygen permeability. The primary experimental technique used in recent years to study membrane oxygen transport is saturation-recovery electron paramagnetic resonance (EPR) oximetry, using spin-label probes targeted to specific regions of a lipid bilayer.

Updated Evaluation of Cholesterol's Influence on Membrane Oxygen Permeability.

There is a surprising gap in knowledge regarding the mechanism of oxygen (O) diffusional delivery at the level of tissues and cells. Yet, the effectiveness of tumor radiotherapy, the success of tissue engineering, and healthy metabolism all require ample intracellular oxygen. Tissue-level diffusion takes place in a complex and crowded macromolecular environment.