Non-targeted metallomics through synchrotron radiation X-ray fluorescence with machine learning for cancer screening using blood samples.

Cancer is the leading cause of death in many countries. The development of new methods for early screening of cancers is highly desired. Targeted metallomics has been successfully applied in the screening of cancers through quantification of elements in the matrix, which is time consuming and requires combined techniques for the quantification due to the large elemental difference in the matrix. This work proposed a non-targeted metallomics (NTM) approach through synchrotron radiation based X-ray fluorescence (SRXRF) and machine learning algorithms (MLAs) for the screening of cancers. One hundred serum samples were collected from cancer patients who were confirmed by pathological examination with 100 matched serum samples from healthy volunteers. The serum samples were studied with SRXRF and the spectra from both groups were directly clarified through MLAs, which did not require the quantification of elements. The NTM approach through SRXRF and MLAs is fast (5s for data collection for one sample) and accurate (over 96% accuracy) for cancer screening. Besides, this approach can also identify the most affected elements in cancer samples like Ca, Zn and Ti as we found, which may shed lights on the drug development for cancer treatment. This NTM approach can also be applied through commercially available XRF instruments or ICP-TOF-MS with MLAs. It has the potential for the screening and prediction of other diseases like COVID-19 and neurodegenerative diseases in a high throughput and least invasive way.

Microplastic Extraction from the Sediment Using Potassium Formate Water Solution (H2O/KCOOH)

Microplastics (MPs) are considered an important stratigraphic indicator, or ‘technofossils’, of the Anthropocene. Research on MP abundance in the environment has gained much attention but the lack of a standardized procedure has hindered the comparability of the results. The development of an effective and efficient method of MP extraction from the matrix is crucial for the proper identification and quantifying analysis of MPs in environmental samples. The procedures of density separation used currently have various limitations: high cost of reagents, limited solution density range, hazardous reagents, or a combination of the above. In this research, a procedure based on density separation with the use of potassium formate water solution (H2O/KCOOH) in controlled conditions was performed. Experimental sediment mixtures, spiked with polyethylene (PE), polystyrene (PS), polyurethane (PUR) and polyethylene terephthalate (PET) particles were prepared and an extraction procedure was tested in the context of a weight-based quantitative analysis of MPs. This article discusses the effectiveness and safety of the method. It additionally provides new information on the interactions between MP particles and the mineral matter of the sediment. Results were acquired with the use of instrumental methods, namely thermogravimetry (TG), Fourier Transform Infrared (FTIR) spectroscopy, Field Emission Scanning Electron microscopy and Energy Dispersive spectrometry (SEM/EDS), as well as X-ray fluorescence (XRF) analysis.

Characterization of Materials Used as Face Coverings for Respiratory Protection.

Use of masks is a primary tool to prevent the spread of the novel COVID-19 virus resulting from unintentional close contact with infected individuals. However, detailed characterization of the chemical properties and physical structure of common mask materials is lacking in the current literature. In this study, a series of commercial masks and potential mask materials, including 3M Particulate Respirator 8210 N95, a material provided by Oak Ridge National Laboratory Carbon Fiber Technology Facility (ORNL/CFTF), and a Filti Face Mask Material, were characterized by a suite of techniques, including scanning electron microscopy, X-ray diffraction, Raman spectroscopy, and X-ray photoelectron spectroscopy. Wetting properties of the mask materials were quantified by measurements of contact angle with a saliva substitute. Mask pass-through experiments were performed using a dispersed metal oxide nanoparticle suspension to model the SARS-CoV-2 virus, with quantification via spatially resolved X-ray fluorescence mapping. Notably, all mask materials tested provided a strong barrier against respiratory droplet breakthrough. The comparisons and characterizations provided in this study provide useful information when evaluating mask materials for respiratory protection.

More than the Eye Can See: Shedding New Light on SARS-CoV-2 Lateral Flow Device-Based Immunoassays.

Containing the global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been an unprecedented challenge due to high horizontal transmissivity and asymptomatic carriage rates. Lateral flow device (LFD) immunoassays were introduced in late 2020 to detect SARS-CoV-2 infection in asymptomatic or presymptomatic individuals rapidly. While LFD technologies have been used for over 60 years, their widespread use as a public health tool during a pandemic is unprecedented. By the end of 2020, data from studies into the efficacy of the LFDs emerged and showed these point-of-care devices to have very high specificity (ability to identify true negatives) but inadequate sensitivity with high false-negative rates. The low sensitivity (<50%) shown in several studies is a critical public health concern, as asymptomatic or presymptomatic carriers may wrongly be assumed to be noninfectious, posing a significant risk of further spread in the community. Here, we show that the direct visual readout of SARS-CoV-2 LFDs is an inadequate approach to discriminate a potentially infective viral concentration in a biosample. We quantified significant immobilized antigen-antibody-labeled conjugate complexes within the LFDs visually scored as negative using high-sensitivity synchrotron X-ray fluorescence imaging. Correlating quantitative X-ray fluorescence measurements and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) determined numbers of viral copies, we identified that negatively scored samples could contain up to 100 PFU (equivalent here to ∼10 000 RNA copies/test). The study demonstrates where the shortcomings arise in many of the current direct-readout SARS-CoV-2 LFDs, namely, being a deficiency in the readout as opposed to the potential level of detection of the test, which is orders of magnitude higher. The present findings are of importance both to public health monitoring during the Coronavirus Disease 2019 (COVID-19) pandemic and to the rapid refinement of these tools for immediate and future applications.