Video description: As in the workshop of the seasons, Autumn takes place near the scale model of the Earth, and using his tools, he must move his season on the planet!
A new software improves data-independent acquisition proteomics by providing a computational workflow that permits highly sensitive and accurate data analysis. Proteins are essential for our cells to function, yet many questions about their synthesis, abundance, functions, and defects still remain unanswered. High-throughput techniques can help improve our understanding of these molecules. For analysis by liquid chromatography followed by mass spectrometry (MS), proteins are broken down into smaller peptides, in a process referred to as “shotgun proteomics.” The mass-to-charge ratio of these peptides is subsequently determined with a mass spectrometer, resulting in MS spectra. From these spectra, information about the identity of the analyzed proteins can be reconstructed. However, the enormous amount and complexity of data make data analysis and interpretation challenging.
Two main methods are used in shotgun proteomics: Data-dependent acquisition (DDA) and data-independent acquisition (DIA). In DDA, the most abundant peptides of a sample are preselected for fragmentation and measurement. This allows to reconstruct the sequences of these few preselected peptides, making analysis simpler and faster. However, this method induces a bias towards highly abundant peptides. DIA, in contrast, is more robust and sensitive. All peptides from a certain mass range are fragmented and measured at once, without preselection by abundance.
Jürgen Cox and his team have now developed a software that provides a complete computational workflow for DIA data. It allows, for the first time, to apply algorithms to DDA and DIA data in the same way. Consequently, studies based on either DDA or DIA will now become more easily comparable. MaxDIA analyzes proteomics data with and without spectral libraries. Using machine learning, the software predicts peptide fragmentation and spectral intensities. Hence, it creates precise MS spectral libraries in silico. In this way, MaxDIA includes a library-free discovery mode with reliable control of false positive protein identifications.
Source (Max-Planck-Gesellschaft. “MaxDIA: Taking proteomics to the next level.” ScienceDaily. ScienceDaily, 12 July 2021.)
Paper: Sinitcyn, P., Hamzeiy, H., Salinas Soto, F., Itzhak, D., McCarthy, F., Wichmann, C., Steger, M., Ohmayer, U., Distler, U., Kaspar-Schoenefeld, S. and Prianichnikov, N., 2021. MaxDIA enables library-based and library-free data-independent acquisition proteomics. Nature Biotechnology, pp.1-11.
Researchers have developed a new approach in which robotic exosuit assistance can be calibrated to an individual and adapt to a variety of real-world walking tasks in a matter of seconds. The bioinspired system uses ultrasound measurements of muscle dynamics to develop a personalized and activity-specific assistance profile for users of the exosuit.
People rarely walk at a constant speed and a single incline. We change speed when rushing to the next appointment, catching a crosswalk signal, or going for a casual stroll in the park. Slopes change all the time too, whether we’re going for a hike or up a ramp into a building. In addition to environmental variably, how we walk is influenced by sex, height, age, and muscle strength, and sometimes by neural or muscular disorders such as stroke or Parkinson’s Disease.
Researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a new approach in which robotic exosuit assistance can be calibrated to an individual and adapt to a variety of real-world walking tasks in a matter of seconds. The bioinspired system uses ultrasound measurements of muscle dynamics to develop a personalized and activity-specific assistance profile for users of the exosuit.
The new system only needs a few seconds of walking, even one stride may be sufficient, to capture the muscle’s profile. For each of the ultrasound-generated profiles, the researchers measure how much metabolic energy the person uses during walking with and without the exosuit. The researchers found that the muscle-based assistance provided by the exosuit significantly reduced the metabolic energy of walking across a range of walking speeds and inclines. The exosuit also applied lower assistance force to achieve the same or improved metabolic energy benefit than previous published studies.
Source (Harvard John A. Paulson School of Engineering and Applied Sciences. “A personalized exosuit for real-world walking: Ultrasound measurements of muscle dynamics provide customized, activity-specific assistance.” ScienceDaily. ScienceDaily, 10 November 2021.)
Original paper: R. W. Nuckols, S. Lee, K. Swaminathan, D. Orzel, R. D. Howe, C. J. Walsh. Individualization of exosuit assistance based on measured muscle dynamics during versatile walking. Science Robotics, 2021; 6 (60) DOI: 10.1126/scirobotics.abj1362
The wait is over! The first 3 episodes of Arcane are available on Netflix, and the premiere was viewed by 1.5 million people on Twitch. The series follows two sisters trying to cope in different ways with what life throws at them, but it also beautifully captures the complex lives of people from Zaun and Piltover.
The opening ceremony of the Worlds 2021 Championship also paid tribute to these iconic characters.
Previously, we touched on the topics of intrinsic and extrinsic camera parameters, as well as camera calibration to remove lens distortion. In the following video, a more comprehensive explanation is presented to link these together, with the added touch of being able to implement in Python these concepts.
Video description: In this Computer Vision and OpenCV Tutorial, We’ll talk about Camera Calibration and Geometry. We will first talk about the basics of camera geometry and how it can be used for calibrating cameras. We will see different types of distortion on cameras and images. At the end of the video, I’ll show you in a Python script how to apply what we have learned and calibrate a camera from a practical computer vision setup.