Optimal trade-off control in machine learning-based library design, with application to adeno-associated virus (AAV) for gene therapy.

Adeno-associated viruses (AAVs) hold tremendous promise as delivery vectors for gene therapies. AAVs have been successfully engineered-for instance, for more efficient and/or cell-specific delivery to numerous tissues-by creating large, diverse starting libraries and selecting for desired properties. However, these starting libraries often contain a high proportion of variants unable to assemble or package their genomes, a prerequisite for any gene delivery goal.

On the sparsity of fitness functions and implications for learning.

Fitness functions map biological sequences to a scalar property of interest. Accurate estimation of these functions yields biological insight and sets the foundation for model-based sequence design. However, the fitness datasets available to learn these functions are typically small relative to the large combinatorial space of sequences; characterizing how much data are needed for accurate estimation remains an open problem.

Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions.

Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions has remained small for the vastness of the sequence space combined with the ruggedness of many fitness functions. While deep neural networks (DNNs) can capture high-order epistatic interactions among the mutational sites, they tend to overfit to the small number of labeled sequences available for training. Here, we developed Epistatic Net (EN), a method for spectral regularization of DNNs that exploits evidence that epistatic interactions in many fitness functions are sparse.

Ready Exerciser One: Effects of music and virtual reality on cycle ergometer exercise.

Objectives: Physical inactivity remains a major global health concern, and researchers have been encouraged to explore the role of technology in the promotion of physical activity. Technologies that deliver audio-visual stimuli are frequently applied in the exercise domain. However, there is a paucity of research that examines the efficacy of modern virtual reality (VR) technology in this context.

Effects of music, video, and 360-degree video on cycle ergometer exercise at the ventilatory threshold.

Despite the seemingly ubiquitous presence of audiovisual stimuli in modern exercise facilities, there is a dearth of research examining the effects of audiovisual stimuli in combination during exercise. Accordingly, we examined the influence of a range of audiovisual stimuli on the improvement of affective, perceptual, and enjoyment responses to cycle ergometer exercise at the ventilatory threshold (VT), an intensity that is associated with the most affect-related interindividual variability. A within-subject design was employed, and participants (N = 18) completed a 25-minute protocol that consisted of 2 minutes of seated rest, 5 minutes of warm-up, 10 minutes of exercise at VT, 5 minutes of cooldown, and 3 minutes of seated rest.

Improvements to the APBS biomolecular solvation software suite.

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that have provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses the three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001.

PB-AM: An open-source, fully analytical linear poisson-boltzmann solver.

We present the open source distributed software package Poisson-Boltzmann Analytical Method (PB-AM), a fully analytical solution to the linearized PB equation, for molecules represented as non-overlapping spherical cavities. The PB-AM software package includes the generation of outputs files appropriate for visualization using visual molecular dynamics, a Brownian dynamics scheme that uses periodic boundary conditions to simulate dynamics, the ability to specify docking criteria, and offers two different kinetics schemes to evaluate biomolecular association rate constants. Given that PB-AM defines mutual polarization completely and accurately, it can be refactored as a many-body expansion to explore 2- and 3-body polarization.

Finding Our Way in the Dark Proteome.

The traditional structure-function paradigm has provided significant insights for well-folded proteins in which structures can be easily and rapidly revealed by X-ray crystallography beamlines. However, approximately one-third of the human proteome is comprised of intrinsically disordered proteins and regions (IDPs/IDRs) that do not adopt a dominant well-folded structure, and therefore remain "unseen" by traditional structural biology methods. This Perspective considers the challenges raised by the "Dark Proteome", in which determining the diverse conformational substates of IDPs in their free states, in encounter complexes of bound states, and in complexes retaining significant disorder requires an unprecedented level of integration of multiple and complementary solution-based experiments that are analyzed with state-of-the art molecular simulation, Bayesian probabilistic models, and high-throughput computation.

Experimental Inferential Structure Determination of Ensembles for Intrinsically Disordered Proteins.

We develop a Bayesian approach to determine the most probable structural ensemble model from candidate structures for intrinsically disordered proteins (IDPs) that takes full advantage of NMR chemical shifts and J-coupling data, their known errors and variances, and the quality of the theoretical back-calculation from structure to experimental observables. Our approach differs from previous formulations in the optimization of experimental and back-calculation nuisance parameters that are treated as random variables with known distributions, as opposed to structural or ensemble weight optimization or use of a reference ensemble. The resulting experimental inferential structure determination (EISD) method is size extensive with O(N) scaling, with N = number of structures, that allows for the rapid ranking of large ensemble data comprising tens of thousands of conformations.

Family of Oxygen-Oxygen Radial Distribution Functions for Water.

In a typical X-ray diffraction experiment, the elastically scattered intensity, I(Q), is the experimental observable. I(Q) contains contributions from both intramolecular as well as intermolecular correlations embodied in the scattering factors, HOO(Q) and HOH(Q), with negligible contributions from HHH(Q). Thus, to accurately define the oxygen-oxygen radial distribution function, gOO(r), a model of the electron density is required to accurately weigh the HOO(Q) component relative to the intramolecular and oxygen-hydrogen correlations from the total intensity observable.

Mapping brain activity during loss of situation awareness: an EEG investigation of a basis for top-down influence on perception.

Objective: The objective was to map brain activity during early intervals in loss of situation awareness (SA) to examine any co-activity in visual and high-order regions, reflecting grounds for top-down influences on Level I SA.

Background: Behavioral and neuroscience evidence indicates that high-order brain areas can engage before perception is complete. Inappropriate top-down messages may distort perception during loss of SA.

Role of hydrophilicity and length of diblock arms for determining star polymer physical properties.

We present a molecular simulation study of star polymers consisting of 16 diblock copolymer arms bound to a small adamantane core by varying both arm length and the outer hydrophilic block when attached to the same hydrophobic block of poly-δ-valerolactone. Here we consider two biocompatible star polymers in which the hydrophilic block is composed of polyethylene glycol (PEG) or polymethyloxazoline (POXA) in addition to a polycarbonate-based polymer with a pendant hydrophilic group (PC1). We find that the different hydrophilic blocks of the star polymers show qualitatively different trends in their interactions with aqueous solvent, orientational time correlation functions, and orientational correlation between pairs of monomers of their polymeric arms in solution, in which we find that the PEG polymers are more thermosensitive compared with the POXA and PC1 star polymers over the physiological temperature range we have investigated.

Abstract numeric relations and the visual structure of algebra.

Formal algebras are among the most powerful and general mechanisms for expressing quantitative relational statements; yet, even university engineering students, who are relatively proficient with algebraic manipulation, struggle with and often fail to correctly deploy basic aspects of algebraic notation (Clement, 1982). In the cognitive tradition, it has often been assumed that skilled users of these formalisms treat situations in terms of semantic properties encoded in an abstract syntax that governs the use of notation without particular regard to the details of the physical structure of the equation itself (Anderson, 2005; Hegarty, Mayer, & Monk, 1995). We explore how the notational structure of verbal descriptions or algebraic equations (e.

Searching for information on Francis Cyril Mason (1907-99).

I am researching my family tree and would appreciate some help. I am looking to find more information about my uncle, Francis Cyril Mason, who was a nurse.