Updates to the Integrated Protein–Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark Version 2

We present an updated and integrated version of our widely used protein–protein docking and binding affinity benchmarks. The benchmarks consist of non-redundant, high-quality structures of protein–protein complexes along with the unbound structures of their components. Fifty-five new complexes were added to the docking benchmark, 35 of which have experimentally measured binding affinities. These updated docking and affinity benchmarks now contain 230 and 179 entries, respectively. In particular, the number of antibody–antigen complexes has increased significantly, by 67% and 74% in the docking and affinity benchmarks, respectively. We tested previously developed docking and affinity prediction algorithms on the new cases. Considering only the top 10 docking predictions per benchmark case, a prediction accuracy of 38% is achieved on all 55 cases and up to 50% for the 32 rigid-body cases only. Predicted affinity scores are found to correlate with experimental binding energies up to r = 0.52 overall and r = 0.72 for the rigid complexes.Peer ReviewedPostprint (author's final draft

Scientific Utopia III: crowdsourcing science

Most scientific research is conducted by small teams of investigators who together formulate hypotheses, collect data, conduct analyses, and report novel findings. These teams operate independently as vertically integrated silos. Here we argue that scientific research that is horizontally distributed can provide substantial complementary value, aiming to maximize available resources, promote inclusiveness and transparency, and increase rigor and reliability. This alternative approach enables researchers to tackle ambitious projects that would not be possible under the standard model. Crowdsourced scientific initiatives vary in the degree of communication between project members from largely independent work curated by a coordination team to crowd collaboration on shared activities. The potential benefits and challenges of large-scale collaboration span the entire research process: ideation, study design, data collection, data analysis, reporting, and peer review. Complementing traditional small science with crowdsourced approaches can accelerate the progress of science and improve the quality of scientific research

Morphological Variation Among Herring Gulls (Larus Argentatus) And Great Black-Backed Gulls (Larus Marinus) In Eastern North America

Herring Gull (Larus argentatus) and Great Black-backed Gull (L. marinus) morphometric data from various eastern North American locations was collected to examine the sources of variation in body size within and among geographic regions. For Herring Gulls, significant differences in all commonly taken measurements at local and regional scales were found. However, most of the variation in measurements was due to sex differences and the natural variance seen within local populations. Herring Gulls breeding in the Arctic did not show any evidence of being morphologically different from other groups. A discriminant function derived from a Newfoundland, Canada, breeding population of Herring Gulls successfully assigned the sex of birds in Atlantic Canada and Nunavut, Canada, further emphasizing that most of the variation seen is between sexes and not among local or even regional populations. It also indicates that the evitable variation introduced by inter-individual differences in measurements was insufficient to compromise the utility of the discriminant function. The correct classification rate was lower for Great Lakes breeding Herring Gulls, indicating that these birds have different morphologies than those of populations in easterly regions. In contrast, few differences and no clear geographic patterns were found in measurements for Great Black-backed Gulls. These results were consistent with recent genetic information, suggesting an older west to east radiation of Herring Gulls across North America and a lack of isolation among Great Black-Backed Gull populations

Spreadsheets for Analyzing and Optimizing Space Missions

XCALIBR (XML Capability Analysis LIBRary) is a set of Extensible Markup Language (XML) database and spreadsheet- based analysis software tools designed to assist in technology-return-on-investment analysis and optimization of technology portfolios pertaining to outer-space missions. XCALIBR is also being examined for use in planning, tracking, and documentation of projects. An XCALIBR database contains information on mission requirements and technological capabilities, which are related by use of an XML taxonomy. XCALIBR incorporates a standardized interface for exporting data and analysis templates to an Excel spreadsheet. Unique features of XCALIBR include the following: It is inherently hierarchical by virtue of its XML basis. The XML taxonomy codifies a comprehensive data structure and data dictionary that includes performance metrics for spacecraft, sensors, and spacecraft systems other than sensors. The taxonomy contains >700 nodes representing all levels, from system through subsystem to individual parts. All entries are searchable and machine readable. There is an intuitive Web-based user interface. The software automatically matches technologies to mission requirements. The software automatically generates, and makes the required entries in, an Excel return-on-investment analysis software tool. The results of an analysis are presented in both tabular and graphical displays

Standards for heart valve surgery in a ‘heart valve centre of excellence’

Surgical centres of excellence should include multidisciplinary teams with specialist expertise in imaging, clinical assessment and surgery for patients with heart valve disease. There should be structured training programmes for the staff involved in the periprocedural care of the patient and these should be overseen by national or international professional societies. Good results are usually associated with high individual and centre volumes, but this relationship is complex. Results of surgery should be published by centre and should include rates of residual regurgitation for mitral repairs and reoperation rates matched to the preoperative pathology and risk

Towards local electromechanical probing of cellular and biomolecular systems in a liquid environment

Electromechanical coupling is ubiquitous in biological systems with examples ranging from simple piezoelectricity in calcified and connective tissues to voltage-gated ion channels, energy storage in mitochondria, and electromechanical activity in cardiac myocytes and outer hair cell stereocilia. Piezoresponse force microscopy (PFM) has originally emerged as a technique to study electromechanical phenomena in ferroelectric materials, and in recent years, has been employed to study a broad range of non-ferroelectric polar materials, including piezoelectric biomaterials. At the same time, the technique has been extended from ambient to liquid imaging on model ferroelectric systems. Here, we present results on local electromechanical probing of several model cellular and biomolecular systems, including insulin and lysozyme amyloid fibrils, breast adenocarcinoma cells, and bacteriorhodopsin in a liquid environment. The specific features of SPM operation in liquid are delineated and bottlenecks on the route towards nanometer-resolution electromechanical imaging of biological systems are identified.Comment: 37 pages (including refs), 8 figure

Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence

Despite the progress in deep learning networks, efficient learning at the edge (enabling adaptable, low-complexity machine learning solutions) remains a critical need for defense and commercial applications. We envision a pipeline to utilize large neuroimaging datasets, including maps of the brain which capture neuron and synapse connectivity, to improve machine learning approaches. We have pursued different approaches within this pipeline structure. First, as a demonstration of data-driven discovery, the team has developed a technique for discovery of repeated subcircuits, or motifs. These were incorporated into a neural architecture search approach to evolve network architectures. Second, we have conducted analysis of the heading direction circuit in the fruit fly, which performs fusion of visual and angular velocity features, to explore augmenting existing computational models with new insight. Our team discovered a novel pattern of connectivity, implemented a new model, and demonstrated sensor fusion on a robotic platform. Third, the team analyzed circuitry for memory formation in the fruit fly connectome, enabling the design of a novel generative replay approach. Finally, the team has begun analysis of connectivity in mammalian cortex to explore potential improvements to transformer networks. These constraints increased network robustness on the most challenging examples in the CIFAR-10-C computer vision robustness benchmark task, while reducing learnable attention parameters by over an order of magnitude. Taken together, these results demonstrate multiple potential approaches to utilize insight from neural systems for developing robust and efficient machine learning techniques.Comment: 11 pages, 4 figure

Catching Element Formation In The Act

Gamma-ray astronomy explores the most energetic photons in nature to address some of the most pressing puzzles in contemporary astrophysics. It encompasses a wide range of objects and phenomena: stars, supernovae, novae, neutron stars, stellar-mass black holes, nucleosynthesis, the interstellar medium, cosmic rays and relativistic-particle acceleration, and the evolution of galaxies. MeV gamma-rays provide a unique probe of nuclear processes in astronomy, directly measuring radioactive decay, nuclear de-excitation, and positron annihilation. The substantial information carried by gamma-ray photons allows us to see deeper into these objects, the bulk of the power is often emitted at gamma-ray energies, and radioactivity provides a natural physical clock that adds unique information. New science will be driven by time-domain population studies at gamma-ray energies. This science is enabled by next-generation gamma-ray instruments with one to two orders of magnitude better sensitivity, larger sky coverage, and faster cadence than all previous gamma-ray instruments. This transformative capability permits: (a) the accurate identification of the gamma-ray emitting objects and correlations with observations taken at other wavelengths and with other messengers; (b) construction of new gamma-ray maps of the Milky Way and other nearby galaxies where extended regions are distinguished from point sources; and (c) considerable serendipitous science of scarce events -- nearby neutron star mergers, for example. Advances in technology push the performance of new gamma-ray instruments to address a wide set of astrophysical questions.Comment: 14 pages including 3 figure