Reduced levels of pulmonary surfactant in COVID-19 ARDS.

To provide novel data on surfactant levels in adult COVID-19 patients, we collected bronchoalveolar lavage fluid less than 72 h after intubation and used Fourier Transform Infrared Spectroscopy to measure levels of dipalmitoylphosphatidylcholine (DPPC). A total of eleven COVID-19 patients with moderate-to-severe ARDS (CARDS) and 15 healthy controls were included. CARDS patients had lower DPPC levels than healthy controls. Moreover, a principal component analysis was able to separate patient groups into distinguishable subgroups. Our findings indicate markedly impaired pulmonary surfactant levels in COVID-19 patients, justifying further studies and clinical trials of exogenous surfactant.

Studying the Key Intermediate of RNA Autohydrolysis by Cryogenic Gas-Phase Infrared Spectroscopy.

Over the course of the COVID-19 pandemic, mRNA-based vaccines have gained tremendous importance. The development and analysis of modified RNA molecules benefit from advanced mass spectrometry and require sufficient understanding of fragmentation processes. Analogous to the degradation of RNA in solution by autohydrolysis, backbone cleavage of RNA strands was equally observed in the gas phase; however, the fragmentation mechanism remained elusive. In this work, autohydrolysis-like intermediates were generated from isolated RNA dinucleotides in the gas phase and investigated using cryogenic infrared spectroscopy in helium nanodroplets. Data from both experiment and density functional theory provide evidence for the formation of a five-membered cyclic phosphate intermediate and rule out linear or six-membered structures. Furthermore, the experiments show that another prominent condensed-phase reaction of RNA nucleotides can be induced in the gas phase: the tautomerization of cytosine. Both observed reactions are therefore highly universal and intrinsic properties of the investigated molecules.

Towards the direct detection of viral materials at the surface of protective face masks via infrared spectroscopy.

The ongoing COVID-19 pandemic represents a considerable risk for the general public and especially for health care workers. To avoid an overloading of the health care system and to control transmission chains, the development of rapid and cost-effective techniques allowing for the reliable diagnosis of individuals with acute respiratory infections are crucial. Uniquely, the present study focuses on the development of a direct face mask sampling approach, as worn (i.e., used) disposable face masks contain exogenous environmental constituents, as well as endogenously exhaled breath aerosols. Optical techniques-and specifically infrared (IR) molecular spectroscopic techniques-are promising tools for direct virus detection at the surface of such masks. In the present study, a rapid and non-destructive approach for monitoring exposure scenarios via medical face masks using attenuated total reflection infrared spectroscopy is presented. Complementarily, IR external reflection spectroscopy was evaluated in comparison for rapid mask analysis. The utility of a face mask-based sampling approach was demonstrated by differentiating water, proteins, and virus-like particles sampled onto the mask. Data analysis using multivariate statistical algorithms enabled unambiguously classifying spectral signatures of individual components and biospecies. This approach has the potential to be extended towards the rapid detection of SARS-CoV-2-as shown herein for the example of virus-like particles which are morphologically equivalent to authentic virus-without any additional sample preparation or elaborate testing equipment at laboratory facilities. Therefore, this strategy may be implemented as a routine large-scale monitoring routine, e.g., at health care institutions, nursing homes, etc. ensuring the health and safety of medical personnel.

AI-based spectroscopic monitoring of real-time interactions between SARS-CoV-2 and human ACE2.

The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), invades a human cell via human angiotensin-converting enzyme 2 (hACE2) as the entry, causing the severe coronavirus disease (COVID-19). The interactions between hACE2 and the spike glycoprotein (S protein) of SARS-CoV-2 hold the key to understanding the molecular mechanism to develop treatment and vaccines, yet the dynamic nature of these interactions in fluctuating surroundings is very challenging to probe by those structure determination techniques requiring the structures of samples to be fixed. Here we demonstrate, by a proof-of-concept simulation of infrared (IR) spectra of S protein and hACE2, that time-resolved spectroscopy may monitor the real-time structural information of the protein-protein complexes of interest, with the help of machine learning. Our machine learning protocol is able to identify fine changes in IR spectra associated with variation of the secondary structures of S protein of the coronavirus. Further, it is three to four orders of magnitude faster than conventional quantum chemistry calculations. We expect our machine learning protocol would accelerate the development of real-time spectroscopy study of protein dynamics.

Infrared Based Saliva Screening Test for COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in an unprecedented need for diagnostic testing that is critical in controlling the spread of COVID-19. We propose a portable infrared spectrometer with purpose-built transflection accessory for rapid point-of-care detection of COVID-19 markers in saliva. Initially, purified virion particles were characterized with Raman spectroscopy, synchrotron infrared (IR) and AFM-IR. A data set comprising 171 transflection infrared spectra from 29 subjects testing positive for SARS-CoV-2 by RT-qPCR and 28 testing negative, was modeled using Monte Carlo Double Cross Validation with 50 randomized test and model sets. The testing sensitivity was 93 % (27/29) with a specificity of 82 % (23/28) that included positive samples on the limit of detection for RT-qPCR. Herein, we demonstrate a proof-of-concept high throughput infrared COVID-19 test that is rapid, inexpensive, portable and utilizes sample self-collection thus minimizing the risk to healthcare workers and ideally suited to mass screening.

Implementing an integrated multi-technology platform for drug checking: Social, scientific, and technological considerations.

The illicit drug overdose crisis in North America continues to devastate communities with fentanyl detected in the majority of illicit drug overdose deaths. The COVID-19 pandemic has heightened concerns of even greater unpredictability in the drug supplies and unprecedented rates of overdoses. Portable drug-checking technologies are increasingly being integrated within overdose prevention strategies. These emerging responses are raising new questions about which technologies to pursue and what service models can respond to the current risks and contexts. In what has been referred to as the epicenter of the overdose crisis in Canada, a multi-technology platform for drug checking is being piloted in community settings using a suite of chemical analytical methods to provide real-time harm reduction. These include infrared absorption, Raman scattering, gas chromatography with mass spectrometry, and antibody-based test strips. In this Perspective, we illustrate some advantages and challenges of using multiple techniques for the analysis of the same sample, and provide an example of a data analysis and visualization platform that can unify the presentation of the results and enable deeper analysis of the results. We also highlight the implementation of a various service models that co-exist in a research setting, with particular emphasis on the way that drug checking technicians and harm reduction workers interact with service users. Finally, we provide a description of the challenges associated with data interpretation and the communication of results to a diverse audience.

A comprehensive review on plasmonic-based biosensors used in viral diagnostics.

The proliferation and transmission of viruses has become a threat to worldwide biosecurity, as exemplified by the current COVID-19 pandemic. Early diagnosis of viral infection and disease control have always been critical. Virus detection can be achieved based on various plasmonic phenomena, including propagating surface plasmon resonance (SPR), localized SPR, surface-enhanced Raman scattering, surface-enhanced fluorescence and surface-enhanced infrared absorption spectroscopy. The present review covers all available information on plasmonic-based virus detection, and collected data on these sensors based on several parameters. These data will assist the audience in advancing research and development of a new generation of versatile virus biosensors.

DFT calculations towards the geometry optimization, electronic structure, infrared spectroscopy and UV-vis analyses of Favipiravir adsorption on the first-row transition metals doped fullerenes; a new strategy for COVID-19 therapy.

With the global epidemic of the COVID-19 virus, extensive and rapid research on drug therapy is underway around the world. In this regard, one of the most widely studied drugs is Favipiravir. Our aim in this paper is to conduct comprehensive research based on the Density Functional Theory (DFT) on the potential of metallofullerenes as suitable drug carriers. The surface interaction of Favipiravir with organometallic compound resulted by doping of the five transition metals of the first row of the periodic table (Ti, Cr, Cr, Fe, Ni, and Zn) was examined in depth to select the most suitable metallofullerenes. First, the adsorption geometries of Favipiravir drug onto each metallofullerene were deeply investigated. It was found that Cr-, Fe-, and Ni-doped fullerenes provide the excellent adsorbent property with adsorption energies of -148.2, -149.6, and -146.6 kJ/mol, respectively. The Infrared spectroscopy (IR) study was conducted to survey the stretching vibration of bonds involving in the systems, specialty the CO in the drug, CM in the metallofullerene, and MO in the metallofullerene-drug complex. Finally, the UV-vis analysis showed that the absorption spectra for the studied systems may be attributed to the transition from π-π* and/or n-π*.