Color-neutral and reversible tissue transparency enables longitudinal deep-tissue imaging in live mice.

Unlabelled: Light scattering in biological tissue presents a significant challenge for deep imaging. Our previous work demonstrated the ability to achieve optical transparency in live mice using intensely absorbing dye molecules, which created transparency in the red spectrum while blocking shorter-wavelength photons. In this paper, we extend this capability to achieve optical transparency across the entire visible spectrum by employing molecules with strong absorption in the ultraviolet spectrum and sharp absorption edges that rapidly decline upon entering the visible spectrum.

Probabilistic Correspondence Analysis in Pediatric Health by Using Variational Mixture Models.

Analyzing brain structures in medical imaging poses challenging problems due to heterogeneity in pediatric diseases. Besides, measuring brain changes quantitatively is crucial to evaluating clinical outcomes related to anatomical factors. From an artificial intelligence perspective, establishing correspondences between nonrigid shapes often requires computing similarity-based measures that, in most cases, are unavailable.

Unsupervised Anomaly Detection by Learning Elastic Transformations Within an Autoencoder Approach.

Machine learning has approached magnetic resonance image (MRI) analysis using multiple techniques, including deep supervised learning methodologies, where lesions such as tumors or features associated with defined pathologies have been identified satisfactorily. However, many of these models require a certain amount of labeled data which access is usually restricted, due to the protection of health information. Furthermore, those methodologies are focused only on the pathologies considered in the training process, causing the model to ignore other kinds of brain lesions.

Biogeographic Ancestry Analysis of Microtia Patients in Colombia using Nonlinear Probabilistic Clustering.

Population composition is crucial in exploring genetic associations and investigating conditions and diseases. Single nucleotide polymorphisms (SNPs) are the subject of extensive studies, as they represent the most prevalent genetic variability in the human population. This work proposes a hierarchical framework for nonlinear probabilistic clustering of individuals with mixed ancestry population components.

Effects of Step Length and Stride Variation During Forward Lunges on Lower-Extremity Muscle Activity.

Background: The forward lunge is a closed-chain weight-bearing multi-joint exercise simulating the activities of daily living, such as walking or stair climbing, which mainly activates hip, knee, and ankle musculature and is also used by athletes and other individuals to train lower-extremity musculature.

Objectives: The purpose of this study is to compare lower-extremity muscle recruitment patterns between stride and step length variations in forward lunges.

Methods: Twenty participants had a mean (±SD) age, mass, and height of 26 ± 6 y, 79 ± 8 kg, and 176 ± 7 cm, respectively, for males, and 27 ± 4 y, 62 ± 6 kg, and 161 ± 7 cm, respectively, for females.