Smart facemask for wireless CO2 monitoring

The use of facemasks by the general population is recommended worldwide to prevent the spread of SARS-CoV-2. Despite the evidence in favour of facemasks to reduce community transmission, there is also agreement on the potential adverse effects of their prolonged usage, mainly caused by CO2 rebreathing. Herein we report the development of a sensing platform for gaseous CO2 real-time determination inside FFP2 facemasks. The system consists of an opto-chemical sensor combined with a flexible, battery-less, near-field-enabled tag with resolution and limit of detection of 103 and 140 ppm respectively, and sensor lifetime of 8 h, which is comparable with recommended FFP2 facemask usage times. We include a custom smartphone application for wireless powering, data processing, alert management, results displaying and sharing. Through performance tests during daily activity and exercise monitoring, we demonstrate its utility for non-invasive, wearable health assessment and its potential applicability for preclinical research and diagnostics.

Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization

Ultra-Wide Bandwidth (UWB) and mm-wave radio systems can resolve specular multipath components (SMCs) from estimated channel impulse response measurements. A geometric model can describe the delays, angles-of-arrival, and angles-of-departure of these SMCs, allowing for a prediction of these channel features. For the modeling of the amplitudes of the SMCs, a data-driven approach has been proposed recently, using Gaussian Process Regression (GPR) to map and predict the SMC amplitudes. In this paper, the applicability of the proposed multipath-resolved, GPR-based channel model is analyzed by studying features of the propagation channel from a set of channel measurements. The features analyzed include the energy capture of the modeled SMCs, the number of resolvable SMCs, and the ranging information that could be extracted from the SMCs. The second contribution of the paper concerns the potential applicability of the channel model for a multipath-resolved, single-anchor positioning system. The predicted channel knowledge is used to evaluate the measurement likelihood function at candidate positions throughout the environment. It is shown that the environmental awareness created by the multipath-resolved, GPR-based channel model yields higher robustness against position estimation outliers.

Impact of Graphene Derivatives as Artificial Extracellular Matrices on Mesenchymal Stem Cells

Thanks to stem cells’ capability to differentiate into multiple cell types, damaged human tissues and organs can be rapidly well-repaired. Therefore, their applicability in the emerging field of regenerative medicine can be further expanded, serving as a promising multifunctional tool for tissue engineering, treatments for various diseases, and other biomedical applications as well. However, the differentiation and survival of the stem cells into specific lineages is crucial to be exclusively controlled. In this frame, growth factors and chemical agents are utilized to stimulate and adjust proliferation and differentiation of the stem cells, although challenges related with degradation, side effects, and high cost should be overcome. Owing to their unique physicochemical and biological properties, graphene-based nanomaterials have been widely used as scaffolds to manipulate stem cell growth and differentiation potential. Herein, we provide the most recent research progress in mesenchymal stem cells (MSCs) growth, differentiation and function utilizing graphene derivatives as extracellular scaffolds. The interaction of graphene derivatives in human and rat MSCs has been also evaluated. Graphene-based nanomaterials are biocompatible, exhibiting a great potential applicability in stem-cell-mediated regenerative medicine as they may promote the behaviour control of the stem cells. Finally, the challenges, prospects and future trends in the field are discussed.

A Comparison of Various Correction and Blending Techniques for Creating an Improved Satellite-Gauge Rainfall Dataset over Australia

Satellites offer a way of estimating rainfall away from rain gauges which can be utilised to overcome the limitations imposed by gauge density on traditional rain gauge analyses. In this study, Australian station data along with the Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mapping of Precipitation (GSMaP) and the Bureau of Meteorology’s (BOM) Australian Gridded Climate Dataset (AGCD) rainfall analysis are combined to develop an improved satellite-gauge rainfall analysis over Australia that uses the strengths of the respective data sources. We investigated a variety of correction and blending methods with the aim of identifying the optimal blended dataset. The correction methods investigated were linear corrections to totals and anomalies, in addition to quantile-to-quantile matching. The blending methods tested used weights based on the error variance to MSWEP (Multi-Source Weighted Ensemble Product), distance to the closest gauge, and the error from a triple collocation analysis to ERA5 and Soil Moisture to Rain. A trade-off between away-from- and at-station performances was found, meaning there was a complementary nature between specific correction and blending methods. The most high-performance dataset was one corrected linearly to totals and subsequently blended to AGCD using an inverse error variance technique. This dataset demonstrated improved accuracy over its previous version, largely rectifying erroneous patches of excessive rainfall. Its modular use of individual datasets leads to potential applicability in other regions of the world.

Virus-Like Particles: Revolutionary Platforms for Developing Vaccines Against Emerging Infectious Diseases

Virus-like particles (VLPs) are nanostructures that possess diverse applications in therapeutics, immunization, and diagnostics. With the recent advancements in biomedical engineering technologies, commercially available VLP-based vaccines are being extensively used to combat infectious diseases, whereas many more are in different stages of development in clinical studies. Because of their desired characteristics in terms of efficacy, safety, and diversity, VLP-based approaches might become more recurrent in the years to come. However, some production and fabrication challenges must be addressed before VLP-based approaches can be widely used in therapeutics. This review offers insight into the recent VLP-based vaccines development, with an emphasis on their characteristics, expression systems, and potential applicability as ideal candidates to combat emerging virulent pathogens. Finally, the potential of VLP-based vaccine as viable and efficient immunizing agents to induce immunity against virulent infectious agents, including, SARS-CoV-2 and protein nanoparticle-based vaccines has been elaborated. Thus, VLP vaccines may serve as an effective alternative to conventional vaccine strategies in combating emerging infectious diseases.

DNA Origami-Templated Bimetallic Nanostar Assemblies for Ultra-Sensitive Detection of Dopamine

The abundance of hotspots tuned via precise arrangement of coupled plasmonic nanostructures highly boost the surface-enhanced Raman scattering (SERS) signal enhancements, expanding their potential applicability to a diverse range of applications. Herein, nanoscale assembly of Ag coated Au nanostars in dimer and trimer configurations with tunable nanogap was achieved using programmable DNA origami technique. The resulting assemblies were then utilized for SERS-based ultra-sensitive detection of an important neurotransmitter, dopamine. The trimer assemblies were able to detect dopamine with picomolar sensitivity, and the assembled dimer structures achieved SERS sensitivity as low as 1 fM with a limit of detection of 0.225 fM. Overall, such coupled nanoarchitectures with superior plasmon tunability are promising to explore new avenues in biomedical diagnostic applications.

Characterization, Classification, and Authentication of Polygonatum sibiricum Samples by Volatile Profiles and Flavor Properties

The importance of monitoring key aroma compounds as food characteristics to solve sample classification and authentication is increasing. The rhizome of Polygonatum sibiricum (PR, Huangjing in Chinese) has great potential to serve as an ingredient of functional foods owing to its tonic effect and flavor properties. In this study, we aimed to characterize and classify PR samples obtained from different processing levels through their volatile profiles and flavor properties by using electronic nose, electronic tongue, and headspace gas chromatography-mass spectrometry. Nine flavor indicators (four odor indicators and five taste indicators) had a strong influence on the classification ability, and a total of 54 volatile compounds were identified in all samples. The traditional Chinese processing method significantly decreased the contents of aldehydes and alkanes, while more ketones, nitrogen heterocycles, alcohols, terpenoids, sulfides, and furans/pyrans were generated in the processing cycle. The results confirmed the potential applicability of volatile profiles and flavor properties for classification of PR samples, and this study provided new insights for determining the processing level in food and pharmaceutical industries based on samples with specific flavor characteristics.

Rice Hull-Derived Carbon for Supercapacitors: Towards Sustainable Silicon-Carbon Supercapacitors

A simple and effective mixing carbonization-activation process was developed to prepare rice hull-derived porous Si–carbon materials. The morphologies and pore structures of the materials were controlled effectively without any loading or additions at various carbonization temperatures. The structures of the samples changed from large pores and thick walls after 800 ∘C carbonization to small pores and thin walls after 1000 ∘C carbonization. An additional alkali activation–carbonization process led to coral reef-like structures surrounded by squama in the sample that underwent 900 ∘C carbonization (Act-RH-900). This optimal material (Act-RH-900) had a large specific surface area (768 m2 g−1), relatively stable specific capacitance (150.8 F g−1), high energy density (31.9 Wh kg−1), and high-power density (309.2 w kg−1) at a current density of 0.5 A g−1 in 1 M KOH electrolyte, as well as a good rate performance and high stability (capacitance retention > 87.88% after 5000 cycles). The results indicated that Act-RH-900 is a promising candidate for capacitive applications. This work overcomes the restrictions imposed by the complex internal structure of biomass, implements a simple reaction environment, and broadens the potential applicability of biomass waste in the field of supercapacitors.

Expanding the Diversity at the C-4 Position of Pyrido[2,3-d]pyrimidin-7(8H)-ones to Achieve Biological Activity against ZAP-70

Pyrido[2,3-d]pyrimidin-7(8H)-ones have attracted widespread interest due to their similarity with nitrogenous bases found in DNA and RNA and their potential applicability as tyrosine kinase inhibitors. Such structures, presenting up to five diversity centers, have allowed the synthesis of a wide range of differently substituted compounds; however, the diversity at the C4 position has mostly been limited to a few substituents. In this paper, a general synthetic methodology for the synthesis of 4-substituted-2-(phenylamino)-5,6-dihydropyrido[2,3-d]pyrimidin-7(8H)-ones is described. By using cross-coupling reactions, such as Ullmann, Buchwald–Hartwig, Suzuki–Miyaura, or Sonogashira reactions, catalyzed by Cu or Pd, we were able to describe new potential biologically active compounds. The resulting pyrido[2,3-d]pyrimidin-7(8H)-ones include N-alkyl, N-aryl, O-aryl, S-aryl, aryl, and arylethynyl substituents at C4, which have never been explored in connection with the biological activity of such heterocycles as tyrosine kinase inhibitors, in particular as ZAP-70 inhibitors.