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International Journal of Molecular... Jul 2023Graphene is the first two-dimensional material that becomes the center material in various research areas of material science, chemistry, condensed matter, and... (Review)
Review
Graphene is the first two-dimensional material that becomes the center material in various research areas of material science, chemistry, condensed matter, and engineering due to its advantageous properties, including larger specific area, lower density, outstanding electrical conductivity, and ease of processability. These properties attracted the attention of material researchers that resulted in a large number of publications on EMI shielding in a short time and play a central role in addressing the problems and challenges faced in this modern era of electronics by electromagnetic interference. After the popularity of graphene, the community of material researchers investigated other two-dimensional materials like MXenes, hexagonal boron nitride, black phosphorous, transition metal dichalcogenides, and layered double hydroxides, to additionally enhance the EMI shielding response of materials. The present article conscientiously reviews the current progress in EMI shielding materials in reference to two-dimensional materials and addresses the future challenges and research directions to achieve the goals.
Topics: Graphite; Electric Conductivity; Electronics; Phosphorus
PubMed: 37569645
DOI: 10.3390/ijms241512267 -
PloS One 2023Mechanical signals play a vital role in cell biology and is a vast area of research. Thus, there is motivation to understand cell deformation and mechanobiological...
Mechanical signals play a vital role in cell biology and is a vast area of research. Thus, there is motivation to understand cell deformation and mechanobiological responses. However, the ability to controllably deform cells in the ultrasonic regime and test their response is a noted challenge throughout the literature. Quantifying and eliciting an appropriate stimulus has proven to be difficult, resulting in methods that are either too aggressive or oversimplified. Furthermore, the ability to gain a real-time insight into cell deformation and link this with the biological response is yet to be achieved. One application of this understanding is in ultrasonic surgical cutting, which is a promising alternative to traditional methods, but with little understanding of its effect on cells. Here we present the image based ultrasonic cell shaking test, a novel method that enables controllable loading of cells and quantification of their response to ultrasonic vibrations. Practically, this involves seeding cells on a substrate that resonates at ultrasonic frequencies and transfers the deformation to the cells. This is then incorporated into microscopic imaging techniques to obtain high-speed images of ultrasonic cell deformation that can be analysed using digital image correlation techniques. Cells can then be extracted after excitation to undergo analysis to understand the biological response to the deformation. This method could aid in understanding the effects of ultrasonic stimulation on cells and how activated mechanobiological pathways result in physical and biochemical responses.
Topics: Ultrasonics; Ultrasonic Waves; Aggression; Biophysics; Motivation
PubMed: 37713387
DOI: 10.1371/journal.pone.0285906 -
PloS One 2023Self-supervised learning, which is strikingly referred to as the dark matter of intelligence, is gaining more attention in biomedical applications of deep learning. In...
Self-supervised learning, which is strikingly referred to as the dark matter of intelligence, is gaining more attention in biomedical applications of deep learning. In this work, we introduce a novel self-supervision objective for the analysis of cells in biomedical microscopy images. We propose training deep learning models to pseudo-colorize masked cells. We use a physics-informed pseudo-spectral colormap that is well suited for colorizing cell topology. Our experiments reveal that approximating semantic segmentation by pseudo-colorization is beneficial for subsequent fine-tuning on cell detection. Inspired by the recent success of masked image modeling, we additionally mask out cell parts and train to reconstruct these parts to further enrich the learned representations. We compare our pre-training method with self-supervised frameworks including contrastive learning (SimCLR), masked autoencoders (MAEs), and edge-based self-supervision. We build upon our previous work and train hybrid models for cell detection, which contain both convolutional and vision transformer modules. Our pre-training method can outperform SimCLR, MAE-like masked image modeling, and edge-based self-supervision when pre-training on a diverse set of six fluorescence microscopy datasets. Code is available at: https://github.com/roydenwa/pseudo-colorize-masked-cells.
Topics: Humans; Electric Power Supplies; Intelligence; Microscopy, Fluorescence; Physics; Self-Management
PubMed: 37616272
DOI: 10.1371/journal.pone.0290561 -
International Journal of Molecular... Dec 2023Over the last ten years, the discovery of topological materials has opened up new areas in condensed matter physics. These materials are noted for their distinctive... (Review)
Review
Over the last ten years, the discovery of topological materials has opened up new areas in condensed matter physics. These materials are noted for their distinctive electronic properties, unlike conventional insulators and metals. This discovery has not only spurred new research areas but also offered innovative approaches to electronic device design. A key aspect of these materials is now that transforming them into nanostructures enhances the presence of surface or edge states, which are the key components for their unique electronic properties. In this review, we focus on recent synthesis methods, including vapor-liquid-solid (VLS) growth, chemical vapor deposition (CVD), and chemical conversion techniques. Moreover, the scaling down of topological nanomaterials has revealed new electronic and magnetic properties due to quantum confinement. This review covers their synthesis methods and the outcomes of topological nanomaterials and applications, including quantum computing, spintronics, and interconnects. Finally, we address the materials and synthesis challenges that need to be resolved prior to the practical application of topological nanomaterials in advanced electronic devices.
Topics: Computing Methodologies; Quantum Theory; Electronics; Gases; Nanostructures
PubMed: 38203574
DOI: 10.3390/ijms25010400 -
PLoS Computational Biology Oct 2023Tissue Forge is an open-source interactive environment for particle-based physics, chemistry and biology modeling and simulation. Tissue Forge allows users to create,...
Tissue Forge is an open-source interactive environment for particle-based physics, chemistry and biology modeling and simulation. Tissue Forge allows users to create, simulate and explore models and virtual experiments based on soft condensed matter physics at multiple scales, from the molecular to the multicellular, using a simple, consistent interface. While Tissue Forge is designed to simplify solving problems in complex subcellular, cellular and tissue biophysics, it supports applications ranging from classic molecular dynamics to agent-based multicellular systems with dynamic populations. Tissue Forge users can build and interact with models and simulations in real-time and change simulation details during execution, or execute simulations off-screen and/or remotely in high-performance computing environments. Tissue Forge provides a growing library of built-in model components along with support for user-specified models during the development and application of custom, agent-based models. Tissue Forge includes an extensive Python API for model and simulation specification via Python scripts, an IPython console and a Jupyter Notebook, as well as C and C++ APIs for integrated applications with other software tools. Tissue Forge supports installations on 64-bit Windows, Linux and MacOS systems and is available for local installation via conda.
Topics: Computer Simulation; Software; Physics; Biophysics
PubMed: 37871133
DOI: 10.1371/journal.pcbi.1010768 -
History and Philosophy of the Life... May 2024This essay focuses on Mario Ageno (1915-1992), initially director of the physics laboratory of the Italian National Institute of Health and later professor of biophysics...
This essay focuses on Mario Ageno (1915-1992), initially director of the physics laboratory of the Italian National Institute of Health and later professor of biophysics at Sapienza University of Rome. A physicist by training, Ageno became interested in explaining the special characteristics of living organisms origin of life by means of quantum mechanics after reading a book by Schrödinger, who argued that quantum mechanics was consistent with life but that new physical principles must be found. Ageno turned Schrödinger's view into a long-term research project. He aimed to translate Schrödinger's ideas into an experimental programme by building a physical model for at least a very simple living organism. The model should explain the transition from the non-living to the living. His research, however, did not lead to the expected results, and in the 1980s and the 1990s he focused on its epistemological aspect, thinking over the tension between the lawlike structure of physics and the historical nature of biology. His reflections led him to focus on the nature of the theory of evolution and its broader scientific meaning.
Topics: History, 20th Century; Biophysics; Italy; Quantum Theory; Physics; Biological Evolution
PubMed: 38787483
DOI: 10.1007/s40656-024-00617-7 -
Clinical and Translational Science Aug 2023Recently, digital health technologies (DHTs) and digital biomarkers have gained a lot of traction in clinical investigations, motivating sponsors, investigators, and... (Review)
Review
Recently, digital health technologies (DHTs) and digital biomarkers have gained a lot of traction in clinical investigations, motivating sponsors, investigators, and regulators to discuss and implement integrated approaches for deploying DHTs. These new tools present new and unique challenges for optimal technology integration in clinical trial processes, including operational, ethical, and regulatory issues. In this paper, we gathered different perspectives to discuss challenges and perspectives from three different stakeholders: industry, US regulators, and a public-private partnership consortium. The complexities of DHT implementation, which include regulatory definitions, defining the scope of validation experiments, and the need for partnerships between BioPharma and the technology sectors, are highlighted. Most of these challenges are related to translation of DHT-derived measures into endpoints that are meaningful to clinicians and patients, participant safety, training, and retention and privacy of data. The example of the Wearable Assessments in the Clinic and Home in PD (WATCH-PD) study is discussed as an example that demonstrated the advantages of pre-competitive collaborations, which include early regulatory feedback, data sharing, and multistakeholder alignment. Future advances in DHTs are expected to spur device-agnostic measured development and incorporate patient reported outcomes in drug development. More efforts are needed to define validation experiments for a defined context of use, incentivize data sharing and development of data standards. Multistakeholder collaborations via precompetitive consortia will help facilitate broad acceptance of DHT-enabled measures in drug development.
Topics: Humans; Digital Technology; Drug Development; Information Dissemination
PubMed: 37157935
DOI: 10.1111/cts.13533 -
ACS Sensors Mar 2024Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of... (Review)
Review
Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection and sequential injection analysis, microfluidics, robotics, and other prototypes addressing specific real-world problems. Finally, we discuss the role of computer technology in sensing systems. Automated flow injection and sequential injection techniques offer precise and efficient sample handling and dependable outcomes. They enable continuous analysis of numerous samples, boosting throughput, and saving time and resources. They enhance safety by minimizing contact with hazardous chemicals. Microfluidic systems are enhanced by automation to enable precise control of parameters and increase of analysis speed. Robotic sampling and sample preparation platforms excel in precise execution of intricate, repetitive tasks such as sample handling, dilution, and transfer. These platforms enhance efficiency by multitasking, use minimal sample volumes, and they seamlessly integrate with analytical instruments. Other sensor prototypes utilize mechanical devices and computer technology to address real-world issues, offering efficient, accurate, and economical real-time solutions for analyte identification and quantification in remote areas. Computer technology is crucial in modern sensing systems, enabling data acquisition, signal processing, real-time analysis, and data storage. Machine learning and artificial intelligence enhance predictions from the sensor data, supporting the Internet of Things with efficient data management.
Topics: Humans; Artificial Intelligence; Reproducibility of Results; Automation; Robotics; Microfluidics
PubMed: 38363106
DOI: 10.1021/acssensors.3c01887 -
Advanced Materials (Deerfield Beach,... Sep 2023Flexible and stretchable bioelectronics provides a biocompatible interface between electronics and biological systems and has received tremendous attention for in situ... (Review)
Review
Flexible and stretchable bioelectronics provides a biocompatible interface between electronics and biological systems and has received tremendous attention for in situ monitoring of various biological systems. Considerable progress in organic electronics has made organic semiconductors, as well as other organic electronic materials, ideal candidates for developing wearable, implantable, and biocompatible electronic circuits due to their potential mechanical compliance and biocompatibility. Organic electrochemical transistors (OECTs), as an emerging class of organic electronic building blocks, exhibit significant advantages in biological sensing due to the ionic nature at the basis of the switching behavior, low driving voltage (<1 V), and high transconductance (in millisiemens range). During the past few years, significant progress in constructing flexible/stretchable OECTs (FSOECTs) for both biochemical and bioelectrical sensors has been reported. In this regard, to summarize major research accomplishments in this emerging field, this review first discusses structure and critical features of FSOECTs, including working principles, materials, and architectural engineering. Next, a wide spectrum of relevant physiological sensing applications, where FSOECTs are the key components, are summarized. Last, major challenges and opportunities for further advancing FSOECT physiological sensors are discussed.
Topics: Wearable Electronic Devices; Electronics; Semiconductors; Prostheses and Implants; Engineering; Transistors, Electronic
PubMed: 36808773
DOI: 10.1002/adma.202209906 -
Scientific Reports Jul 2023In the last decade, Ultrafast ultrasound localisation microscopy has taken non-invasive deep vascular imaging down to the microscopic level. By imaging diluted...
In the last decade, Ultrafast ultrasound localisation microscopy has taken non-invasive deep vascular imaging down to the microscopic level. By imaging diluted suspensions of circulating microbubbles in the blood stream at kHz frame rate and localizing the center of their individual point spread function with a sub-resolution precision, it enabled to break the unvanquished trade-off between depth of imaging and resolution by microscopically mapping the microbubbles flux and velocities deep into tissue. However, ULM also suffers limitations. Many small vessels are not visible in the ULM images due to the noise level in areas dimly explored by the microbubbles. Moreover, as the vast majority of studies are performed using 2D imaging, quantification is limited to in-plane velocity or flux measurements which hinders the accurate velocity determination and quantification. Here we show that the backscattering amplitude of each individual microbubble can also be exploited to produce backscattering images of the vascularization with a higher sensitivity compared to conventional ULM images. By providing valuable information about the relative distance of the microbubble to the 2D imaging plane in the out-of-plane direction, backscattering ULM images introduces a physically relevant 3D rendering perception in the vascular maps. It also retrieves the missing information about the out-of-plane motion of microbubbles and provides a way to improve 3D flow and velocity quantification using 2D ULM. These results pave the way to improved visualization and quantification for 2D and 3D ULM.
Topics: Microscopy; Microbubbles; Phantoms, Imaging; Biological Phenomena; Ultrasonography; Contrast Media
PubMed: 37455266
DOI: 10.1038/s41598-023-38531-w