De novo protein design by citizen scientists.

Online citizen science projects such as GalaxyZoo1, Eyewire2 and Phylo3 have proven very successful for data collection, annotation and processing, but for the most part have harnessed human pattern-recognition skills rather than human creativity. An exception is the game EteRNA4, in which game players learn to build new RNA structures by exploring the discrete two-dimensional space of Watson-Crick base pairing possibilities. Building new proteins, however, is a more challenging task to present in a game, as both the representation and evaluation of a protein structure are intrinsically three-dimensional. We posed the challenge of de novo protein design in the online protein-folding game Foldit5. Players were presented with a fully extended peptide chain and challenged to craft a folded protein structure and an amino acid sequence encoding that structure. After many iterations of player design, analysis of the top-scoring solutions and subsequent game improvement, Foldit players can now-starting from an extended polypeptide chain-generate a diversity of protein structures and sequences that encode them in silico. One hundred forty-six Foldit player designs with sequences unrelated to naturally occurring proteins were encoded in synthetic genes; 56 were found to be expressed and soluble in Escherichia coli, and to adopt stable monomeric folded structures in solution. The diversity of these structures is unprecedented in de novo protein design, representing 20 different folds-including a new fold not observed in natural proteins. High-resolution structures were determined for four of the designs, and are nearly identical to the player models. This work makes explicit the considerable implicit knowledge that contributes to success in de novo protein design, and shows that citizen scientists can discover creative new solutions to outstanding scientific challenges such as the protein design problem.

Macromolecular modeling and design in Rosetta: recent methods and frameworks.

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at http://www.rosettacommons.org.

Building de novo cryo-electron microscopy structures collaboratively with citizen scientists.

With the rapid improvement of cryo-electron microscopy (cryo-EM) resolution, new computational tools are needed to assist and improve upon atomic model building and refinement options. This communication demonstrates that microscopists can now collaborate with the players of the computer game Foldit to generate high-quality de novo structural models. This development could greatly speed the generation of excellent cryo-EM structures when used in addition to current methods.

Foldit Standalone: a video game-derived protein structure manipulation interface using Rosetta.

SUMMARY: Foldit Standalone is an interactive graphical interface to the Rosetta molecular modeling package. In contrast to most command-line or batch interactions with Rosetta, Foldit Standalone is designed to allow easy, real-time, direct manipulation of protein structures, while also giving access to the extensive power of Rosetta computations. Derived from the user interface of the scientific discovery game Foldit (itself based on Rosetta), Foldit Standalone has added more advanced features and removed the competitive game elements. Foldit Standalone was built from the ground up with a custom rendering and event engine, configurable visualizations and interactions driven by Rosetta. Foldit Standalone contains, among other features: electron density and contact map visualizations, multiple sequence alignment tools for template-based modeling, rigid body transformation controls, RosettaScripts support and an embedded Lua interpreter. AVAILABILITY AND IMPLEMENTATION: Foldit Standalone is available for download at https://fold.it/standalone , under the Rosetta license, which is free for academic and non-profit users. It is implemented in cross-platform C ++ and binary executables are available for Windows, macOS and Linux. CONTACT: scooper@ccs.neu.edu.

Predicting protein structures with a multiplayer online game.

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

WeFold: a coopetition for protein structure prediction.

The protein structure prediction problem continues to elude scientists. Despite the introduction of many methods, only modest gains were made over the last decade for certain classes of prediction targets. To address this challenge, a social-media based worldwide collaborative effort, named WeFold, was undertaken by 13 labs. During the collaboration, the laboratories were simultaneously competing with each other. Here, we present the first attempt at "coopetition" in scientific research applied to the protein structure prediction and refinement problems. The coopetition was possible by allowing the participating labs to contribute different components of their protein structure prediction pipelines and create new hybrid pipelines that they tested during CASP10. This manuscript describes both successes and areas needing improvement as identified throughout the first WeFold experiment and discusses the efforts that are underway to advance this initiative. A footprint of all contributions and structures are publicly accessible at http://www.wefold.org.

Are quadrilateral surface buttress plates comparable to traditional forms of transverse acetabular fracture fixation?

BACKGROUND: Several construct options exist for transverse acetabular fracture fixation. Accepted techniques use a combination of column plates and lag screws. Quadrilateral surface buttress plates have been introduced as potential fixation options, but as a result of their novelty, biomechanical data regarding their stabilizing effects are nonexistent. Therefore, we aimed to determine if this fixation method confers similar stability to traditional forms of fixation. QUESTIONS/PURPOSES: We biomechanically compared two acetabular fixation plates with quadrilateral surface buttressing with traditional forms of fixation using lag screws and column plates. METHODS: Thirty-five synthetic hemipelves with a transverse transtectal acetabular fracture were allocated to one of five groups: anterior column plate+posterior column lag screw, posterior column plate+anterior column lag screw, anterior and posterior column lag screws only, infrapectineal plate+anterior column plate, and suprapectineal plate alone. Specimens were loaded for 1500 cycles up to 2.5x body weight and stiffness was calculated. Thereafter, constructs were destructively loaded and failure loads were recorded. RESULTS: After 1500 cycles, final stiffness was not different with the numbers available between the infrapectineal (568±43 N/mm) and suprapectineal groups (602±87 N/mm, p=0.988). Both quadrilateral plates were significantly stiffer than the posterior column buttress plate with supplemental lag screw fixation group (311±99 N/mm, p<0.006). No difference in stiffness was identified with the numbers available between the quadrilateral surface plating groups and the lag screw group (423±219 N/mm, p>0.223). The infrapectineal group failed at the highest loads (5.4±0.6 kN) and this was significant relative to the suprapectineal (4.4±0.3 kN; p=0.023), lag screw (2.9±0.8 kN; p<0.001), and anterior buttress plate with posterior column lag screw (4.0±0.6 kN; p=0.001) groups. CONCLUSIONS: Quadrilateral surface buttress plates spanning the posterior and anterior columns are biomechanically comparable and, in some cases, superior to traditional forms of fixation in this synthetic hemipelvis model. CLINICAL RELEVANCE: Quadrilateral surface buttress plates may present a viable alternative for the treatment of transtectal transverse acetabular fractures. Clinical studies are required to fully define the use of this new form of fixation for such fractures when accessed through the anterior intrapelvic approach.

Algorithm discovery by protein folding game players.

Foldit is a multiplayer online game in which players collaborate and compete to create accurate protein structure models. For specific hard problems, Foldit player solutions can in some cases outperform state-of-the-art computational methods. However, very little is known about how collaborative gameplay produces these results and whether Foldit player strategies can be formalized and structured so that they can be used by computers. To determine whether high performing player strategies could be collectively codified, we augmented the Foldit gameplay mechanics with tools for players to encode their folding strategies as "recipes" and to share their recipes with other players, who are able to further modify and redistribute them. Here we describe the rapid social evolution of player-developed folding algorithms that took place in the year following the introduction of these tools. Players developed over 5,400 different recipes, both by creating new algorithms and by modifying and recombining successful recipes developed by other players. The most successful recipes rapidly spread through the Foldit player population, and two of the recipes became particularly dominant. Examination of the algorithms encoded in these two recipes revealed a striking similarity to an unpublished algorithm developed by scientists over the same period. Benchmark calculations show that the new algorithm independently discovered by scientists and by Foldit players outperforms previously published methods. Thus, online scientific game frameworks have the potential not only to solve hard scientific problems, but also to discover and formalize effective new strategies and algorithms.

Practical recommendations from a multi-perspective needs and challenges assessment of citizen science games.

Citizen science games are an increasingly popular form of citizen science, in which volunteer participants engage in scientific research while playing a game. Their success depends on a diverse set of stakeholders working together-scientists, volunteers, and game developers. Yet the potential needs of these stakeholder groups and their possible tensions are poorly understood. To identify these needs and possible tensions, we conducted a qualitative data analysis of two years of ethnographic research and 57 interviews with stakeholders from 10 citizen science games, following a combination of grounded theory and reflexive thematic analysis. We identify individual stakeholder needs as well as important barriers to citizen science game success. These include the ambiguous allocation of developer roles, limited resources and funding dependencies, the need for a citizen science game community, and science-game tensions. We derive recommendations for addressing these barriers.

High-resolution structure of a retroviral protease folded as a monomer.

Mason-Pfizer monkey virus (M-PMV), a D-type retrovirus assembling in the cytoplasm, causes simian acquired immunodeficiency syndrome (SAIDS) in rhesus monkeys. Its pepsin-like aspartic protease (retropepsin) is an integral part of the expressed retroviral polyproteins. As in all retroviral life cycles, release and dimerization of the protease (PR) is strictly required for polyprotein processing and virion maturation. Biophysical and NMR studies have indicated that in the absence of substrates or inhibitors M-PMV PR should fold into a stable monomer, but the crystal structure of this protein could not be solved by molecular replacement despite countless attempts. Ultimately, a solution was obtained in mr-rosetta using a model constructed by players of the online protein-folding game Foldit. The structure indeed shows a monomeric protein, with the N- and C-termini completely disordered. On the other hand, the flap loop, which normally gates access to the active site of homodimeric retropepsins, is clearly traceable in the electron density. The flap has an unusual curled shape and a different orientation from both the open and closed states known from dimeric retropepsins. The overall fold of the protein follows the retropepsin canon, but the C(α) deviations are large and the active-site 'DTG' loop (here NTG) deviates up to 2.7 Å from the standard conformation. This structure of a monomeric retropepsin determined at high resolution (1.6 Å) provides important extra information for the design of dimerization inhibitors that might be developed as drugs for the treatment of retroviral infections, including AIDS.

Signaligner Pro: A Tool to Explore and Annotate Multi-day Raw Accelerometer Data.

Human activity recognition using wearable accelerometers can enable in-situ detection of physical activities to support novel human-computer interfaces. Many of the machine-learning-based activity recognition algorithms require multi-person, multi-day, carefully annotated training data with precisely marked start and end times of the activities of interest. To date, there is a dearth of usable tools that enable researchers to conveniently visualize and annotate multiple days of high-sampling-rate raw accelerometer data. Thus, we developed Signaligner Pro, an interactive tool to enable researchers to conveniently explore and annotate multi-day high-sampling rate raw accelerometer data. The tool visualizes high-sampling-rate raw data and time-stamped annotations generated by existing activity recognition algorithms and human annotators; the annotations can then be directly modified by the researchers to create their own, improved, annotated datasets. In this paper, we describe the tool's features and implementation that facilitate convenient exploration and annotation of multi-day data and demonstrate its use in generating activity annotations.

Is humeral segmental defect replacement device a stronger construct than locked IM nailing?

Intramedullary (IM) nailing is currently the most common method for treating patients with impending pathologic humeral fractures; however, this treatment is associated with known complications primarily owing to violation of the rotator cuff during insertion. A better option is needed. To determine if a humeral segmental replacement prosthesis would provide a stronger construct compared with an IM nail in this setting, we compared the mechanical properties of these two devices in a cadaver model simulating an impending pathologic fracture. In each of nine matched pairs of fresh human humeri one was randomly selected to undergo a 50% lateral middiaphyseal defect simulating an impending pathologic fracture and subsequent fixation with an IM nail and bone cement. The contralateral humerus underwent fixation using a humeral segmental defect prosthesis. We determined T-scores using DEXA. Each specimen subsequently was tested in torsion to failure. Peak torque and peak rotation at failure were greater for the prosthesis specimens whereas torsional stiffness was greater for the IM nail specimens. We found a linear relationship between peak torque and T-score for each device with the slopes of the lines suggesting the construct with the prosthesis can withstand greater forces than the IM nail and the differences between devices were greater in weaker bones.

Preinjury Narcotic Use Does Not Affect Treatment for Compartment Syndrome.

OBJECTIVES: To determine the association of preinjury opioid use on incidence of fasciotomy after lower extremity trauma. DESIGN: Retrospective case-control study. SETTING: Level 1 trauma center. PATIENTS/PARTICIPANTS: We identified 245 consecutive patients treated with fasciotomy for compartment syndrome of the lower extremity from 2011 to 2016. Of these, 115 were excluded for isolated vascular injury without fracture, age younger than 18 years, out-of-state residence, nontraumatic etiology, and/or incomplete opioid records. Three hundred ninety age- and sex-matched patients with tibial fractures not requiring fasciotomy were selected for comparison. INTERVENTION: Review of demographics, injury characteristics, and opioid prescriptions. MAIN OUTCOME MEASUREMENTS: Rate of preinjury narcotic use. RESULTS: There was no significant difference in chronic opioid use between patients requiring fasciotomy and those who did not (odds ratio = 0.80, 95% confidence interval: 0.43-1.50, P = 0.49). There was no significant difference in average morphine milligram equivalents (MME)/day (66.6 vs. 77.4, P = 0.68). There was no significant difference in active opioid use (odds ratio = 0.76, 95% confidence interval: 0.45-1.29, P = 0.30). There was no significant difference in average MME/day (69.3 vs. 75.6, P = 0.80) for active narcotic users. CONCLUSION: There were no differences in the rate or average MME/day of preinjury opioid use between patients with a tibia fracture treated with or without fasciotomy for compartment syndrome. These results indicate that pre-existing opioid use does not interfere with the accurate diagnosis of compartment syndrome in trauma patients. The diagnosis and treatment of compartment syndrome is not affected by preinjury narcotic use and potential associations with opiate-induced hyperalgesia. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Inferring and Comparing Game Difficulty Curves using Player-vs-Level Match Data.

Prior work has focused on formalizing difficulty curves by using function composition to give precise definitions to curves and their transformations. However, the proposed framework was demonstrated using a single game, and the curves and transformations were defined with respect to the game's ratings-based dynamic difficulty system. In this work, we infer difficulty curves from gameplay data using a method that is based on the aforementioned difficulty system but that can also be generalized to other games for which information on player-vs-level win/loss outcomes is available. Moreover, since this method uses the same difficulty mechanism as past work, it lets us similarly leverage function composition to compare difficulty curves across games, having either a fixed or dynamic level ordering, using a clearly defined vocabulary. We use four different games to demonstrate our method, which relies on an adjustment to traditional playback of ratings-based match data, which we also present in this work.

Large-Scale Analysis of Visualization Options in a Citizen Science Game.

Visualization is a valuable tool in problem solving, especially for citizen science games. In this study, we analyze data from 36,351 unique players of the citizen science game Foldit over a period of 5 years to understand how their choice of visualization options are affected by expertise and problem type. We identified clusters of visualization options, and found differences in how experts and novices view puzzles and that experts differentially change their views based on puzzle type. These results can inform new design approaches to help both novice and expert players visualize novel problems, develop expertise, and problem solve.

Expertise and Engagement: Re-Designing Citizen Science Games With Players' Minds in Mind.

Many studies have already shown that games can be a useful tool to make boring or difficult tasks more engaging. However, with serious game design being a relatively nascent field, such experiences can still be hard to learn and not very motivating. In this paper, we explore the use of learning and motivation frameworks to improve player experience in the well-known citizen science game Foldit. Using Cognitive Load Theory (CLT) and Self Determination Theory (SDT), we developed six interface and mechanical changes to the tutorial levels in Foldit designed to increase engagement and retention. We tested these features with new players of Foldit and collected both behavioral data, using game metrics, and prior experience data, using self-report measures. This study offers three major contributions: (1) we document the process of operationalizing CLT and SDT as new game features, a unique methodology not used in game design previously; (2) the user interface, specifically the level selection screen, significantly impacts how players progress through the game; and (3) a player's expertise, whether from prior domain knowledge or prior gaming experience, increases their engagement. We discuss both implications of these findings as well as how these implementations can generalize to other designs.

Designing Videogames to Crowdsource Accelerometer Data Annotation for Activity Recognition Research.

Human activity recognition using wearable accelerometers can enable in-situ detection of physical activities to support novel human-computer interfaces and interventions. However, developing valid algorithms that use accelerometer data to detect everyday activities often requires large amounts of training datasets, precisely labeled with the start and end times of the activities of interest. Acquiring annotated data is challenging and time-consuming. Applied games, such as human computation games (HCGs) have been used to annotate images, sounds, and videos to support advances in machine learning using the collective effort of "non-expert game players." However, their potential to annotate accelerometer data has not been formally explored. In this paper, we present two proof-of-concept, web-based HCGs aimed at enabling game players to annotate accelerometer data. Using results from pilot studies with Amazon Mechanical Turk players, we discuss key challenges, opportunities, and, more generally, the potential of using applied videogames for annotating raw accelerometer data to support activity recognition research.

Creating custom Foldit puzzles for teaching biochemistry.

The computer game Foldit is currently widely used as a biology and biochemistry teaching aid. Herein, we introduce a new feature of Foldit called "custom contests" that allows educators to create puzzles that fit their curriculum. The effectiveness of the custom contests is demonstrated by the use of five distinct custom contests in an upper-level biochemistry class. The new custom contest feature can be implemented in classes ranging from middle school to graduate school to enable educators to best complement their current curriculum. © 2019 International Union of Biochemistry and Molecular Biology, 47(2): 133-139, 2019.

A Monte Carlo Approach to Skill-Based Automated Playtesting.

In order to create well-crafted learning progressions, designers guide players as they present game skills and give ample time for the player to master those skills. However, analyzing the quality of learning progressions is challenging, especially during the design phase, as content is ever-changing. This research presents the application of Stratabots-automated player simulations based on models of players with varying sets of skills-to the human computation game Foldit. Stratabot performance analysis coupled with player data reveals a relatively smooth learning progression within tutorial levels, yet still shows evidence for improvement. Leveraging existing general gameplaying algorithms such as Monte Carlo Evaluation can reduce the development time of this approach to automated playtesting without losing predicitive power of the player model.

Repurposing Citizen Science Games as Software Tools for Professional Scientists.

Scientific software is often developed with professional scientists in mind, resulting in complex tools with a steep learning curve. Citizen science games, however, are designed for citizen scientists- members of the general public. These games maintain scientific accuracy while placing design goals such as usability and enjoyment at the forefront. In this paper, we identify an emerging use of game-based technology, in the repurposing of citizen science games to be software tools for professional scientists in their work. We discuss our experience in two such repurposings: Foldit, a protein folding and design game, and Eyewire, a web-based 3D neuron reconstruction game. Based on this experience, we provide evidence that the software artifacts produced for citizen science can be useful for professional scientists, and provide an overview of key design principles we found to be useful in the process of repurposing.