When hyping technology is a crime

The rise and fall of Elizabeth Holmes, former chief executive officer (CEO) of the high-flying, privately held, American medical diagnostics company Theranos, has riveted the public for years. A bestseller, a documentary, and a seemingly endless stream of news stories have chronicled the drama, which came to a climax last week when a jury decided that Holmes committed fraud. Although a verdict has been rendered, it’s worth examining how the culture of science innovation contributed to the problem. For too long, fledging companies promoting technological and scientific advances have relied too much on style and not enough on substance.

Protein Sequencing, One Molecule at a Time

Despite tremendous gains over the past decade, methods for characterizing proteins have generally lagged behind those for nucleic acids, which are characterized by extremely high sensitivity, dynamic range, and throughput. However, the ability to directly characterize proteins at nucleic acid levels would address critical biological challenges such as more sensitive medical diagnostics, deeper protein quantification, large-scale measurement, and discovery of alternate protein isoforms and modifications and would open new paths to single-cell proteomics. In response to this need, there has been a push to radically improve protein sequencing technologies by taking inspiration from high-throughput nucleic acid sequencing, with a particular focus on developing practical methods for single-molecule protein sequencing (SMPS). SMPS technologies fall generally into three categories: sequencing by degradation (e.g., mass spectrometry or fluorosequencing), sequencing by transit (e.g., nanopores or quantum tunneling), and sequencing by affinity (as in DNA hybridization–based approaches). We describe these diverse approaches, which range from those that are already experimentally well-supported to the merely speculative, in this nascent field striving to reformulate proteomics. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Development of a Robust, Simple, and Affordable Human Gait Analysis System Using Bottom-Up Pose Estimation With a Smartphone Camera

Gait analysis is used in many fields such as Medical Diagnostics, Osteopathic medicine, Comparative and Sports-related biomechanics, etc. The most commonly used system for capturing gait is the advanced video camera-based passive marker system such as VICON. However, such systems are expensive, and reflective markers on subjects can be intrusive and time-consuming. Moreover, the setup of markers for certain rehabilitation patients, such as people with stroke or spinal cord injuries, could be difficult. Recently, some markerless systems were introduced to overcome the challenges of marker-based systems. However, current markerless systems have low accuracy and pose other challenges in gait analysis with people in long clothing, hiding the gait kinematics. The present work attempts to make an affordable, easy-to-use, accurate gait analysis system while addressing all the mentioned issues. The system in this study uses images from a video taken with a smartphone camera (800 × 600 pixels at an average rate of 30 frames per second). The system uses OpenPose, a 2D real-time multi-person keypoint detection technique. The system learns to associate body parts with individuals in the image using Convolutional Neural Networks (CNNs). This bottom-up system achieves high accuracy and real-time performance, regardless of the number of people in the image. The proposed system is called the “OpenPose based Markerless Gait Analysis System” (OMGait). Ankle, knee, and hip flexion/extension angle values were measured using OMGait in 16 healthy volunteers under different lighting and clothing conditions. The measured kinematic values were compared with a standard video camera based normative dataset and data from a markerless MS Kinect system. The mean absolute error value of the joint angles from the proposed system was less than 90 for different lighting conditions and less than 110 for different clothing conditions compared to the normative dataset. The proposed system is adequate in measuring the kinematic values of the ankle, knee, and hip. It also performs better than the markerless systems like MS Kinect that fail to measure the kinematics of ankle, knee, and hip joints under dark and bright light conditions and in subjects with long robe clothing.

Biomedical Applications of Nanoparticles

In recent years, there has been significant growth and burgeoning interest in utilizing nanoparticles for various biomedical applications, including medical diagnostics, targeted drug delivery, tissue engineering, regenerative medicine, and biomedical textiles. In particular, nanoparticles functionalized with biological molecules have unique properties and are very effective in medical diagnostics. Besides that, nanoparticles have a wide range of therapeutic applications, including the development of nanodrug delivery systems, the design of novel drugs, as well as their contribution to the design of therapeutic materials. This chapter provides an overview of recent advancements in the biomedical applications of nanoparticles. Finally, this chapter discusses the challenges of the toxicological evaluation of engineered nanoparticles and the importance of conducting detailed studies on the synthesis of future nanomaterials to develop cutting-edge technologies for addressing a wide range of biomedical issues.

Conventional and Non-Conventional ANNs in Medical Diagnostics

Computer technology advancements in recent days have offered professionals in different fields the ability to gather data, process information, store, and retrieve at a faster rate and make effective decisions. The large collection of data among all various applications including medical diagnosis has paved the need to employ advanced artificial neural networks (ANN). This chapter provides a detailed working view of ANN, covering its various architectures and design techniques in brief. A detailed analysis and summary of medical diagnostics applications using various ANN techniques will be leveraged. Imbalanced data is the major problem with medical data. This chapter briefs on the various methods to handle imbalanced data. Finally, future directions and potential current challenges are suggested for additional applications in neural networks.

Ultrawideband Antennas: Growth and Evolution

Narrowband antennas fail to radiate short pulses of nano- or picosecond length over the broader band of frequencies. Therefore, Ultrawideband (UWB) technology has gained momentum over the past couple of years as it utilizes a wide range of frequencies, typically between 3.1–10.6 GHz. UWB antennas have been utilized for various applications such as ground-penetrating radars, disaster management through detection of unexploded mines, medical diagnostics, and commercial applications ranging from USB dongles to detection of cracks in highways and bridges. In the first section of the manuscript, UWB technology is detailed with its importance for future wireless communications systems. In the next section various types of UWB antennas and their design methodology are reviewed, and their important characteristics are highlighted. In section four the concept of a UWB notch antenna is presented. Here various methods to obtain the notch, such as slots, parasitic resonators, metamaterials, and filters are discussed in detail. In addition, various types of important notch antenna design with their technical specifications, advantages, and disadvantages are presented. Finally, the need of reconfigurable UWB notch antennas is discussed in the next section. Here various insight to the design of frequency reconfigurable notch antennas is discussed and presented. Overall, this article aims to showcase the beginnings of UWB technology, the reason for the emergence of notching in specific frequency bands, and ultimately the need for reconfiguring UWB antennas along with their usage.

Performance Evaluation of Convolutional Neural Network Using Synthetic Medical Data Augmentation Generated by GAN

Data augmentation is widely used in image processing and pattern recognition problems in order to increase the richness in diversity of available data. It is commonly used to improve the classification accuracy of images when the available datasets are limited. Deep learning approaches have demonstrated an immense breakthrough in medical diagnostics over the last decade. A significant amount of datasets are needed for the effective training of deep neural networks. The appropriate use of data augmentation techniques prevents the model from over-fitting and thus increases the generalization capability of the network while testing afterward on unseen data. However, it remains a huge challenge to obtain such a large dataset from rare diseases in the medical field. This study presents the synthetic data augmentation technique using Generative Adversarial Networks to evaluate the generalization capability of neural networks using existing data more effectively. In this research, the convolutional neural network (CNN) model is used to classify the X-ray images of the human chest in both normal and pneumonia conditions; then, the synthetic images of the X-ray from the available dataset are generated by using the deep convolutional generative adversarial network (DCGAN) model. Finally, the CNN model is trained again with the original dataset and augmented data generated using the DCGAN model. The classification performance of the CNN model is improved by 3.2% when the augmented data were used along with the originally available dataset.

Terahertz radiation in ophthalmology (review)

Terahertz (THz) radiation is one of the new, intensively studied interdisciplinary fi elds of scientifi c knowledge, including medicine, in the fi rst decades of the 21st century. At the beginning of this article (review), in a brief form, the basic statements on THz radiation, the main parameters and properties are presented; the modern THz biophtonics technologies used in biology and medicine are considered – THz refl ectometry, THz spectroscopy methods. Then a number of directions and examples of possible use of THz technologies in biology and medicine, including pharmaceuticals, are given. The main part of the review presents the progress of experimental research and the prospects for the clinical application of medical technologies of THz spectroscopy, THz imaging, in ophthalmology in the study of the morphological and functional state of the ocular surface structures, diagnosis, medical testing, and treatment of ophthalmopathology of the ocular surface. The article concludes with a review of experimental studies on the safety of using THz waves for medical diagnostics and treatment of ophthalmopathology. In the fi nal part, the main problems and prospects of introducing medical THz technologies into the clinical practice of an ophthalmologist are considered.