Rapid and Low-Cost Detection of Human Corona Virus Using MEMS ATR-FTIR Spectroscopy

The conventional methods used for the diagnostics of viral infection are either expensive and time-consuming or not accurate enough and dependent on consumable reagents. In the presence of pandemics, a fast and reagent-free solution is needed for mass screening. Recently, the diagnosis of viral infections using infrared spectroscopy has been reported as a fast and low-cost method. In this work a fast and low-cost solution for corona viral detection using infrared spectroscopy based on a compact micro-electro-mechanical systems (MEMS) device and artificial intelligence (AI) suitable for mass deployment is presented. Among the different variants of the corona virus that can infect people, 229E is used in this study due to its low pathogeny. The MEMS ATR-FTIR device employs a 6 reflections ZnSe crystal interface working in the spectral range of 2200-7000 cm-1. The virus was propagated and maintained in a medium for long enough time then cell supernatant was collected and centrifuged. The supernatant was then transferred and titrated using plaque titration assay. Positive virus samples were prepared with a concentration of 105 PFU/mL. Positive and negative control samples were applied on the crystal surface, dried using a heating lamp and the spectrum was captured. Principal component analysis and logistic regression were used as simple AI techniques. A sensitivity of about 90 % and a specificity of about 80 % were obtained demonstrating the potential detection of the virus based on the MEMS FTIR device. © 2023 SPIE.

Raman and fourier transform infrared spectroscopy techniques for detection of coronavirus (COVID-19): a mini review.

Coronavirus pandemic has been a huge jeopardy to human health in various systems since it outbroke, early detection and prevention of further escalation has become a priority. The current popular approach is to collect samples using the nasopharyngeal swab method and then test for RNA using the real-time polymerase chain reaction, which suffers from false-positive results and a longer diagnostic time scale. Alternatively, various optical techniques, namely, optical sensing, spectroscopy, and imaging shows a great promise in virus detection. In this mini review, we briefly summarize the development progress of vibrational spectroscopy techniques and its applications in the detection of SARS-CoV family. Vibrational spectroscopy techniques such as Raman spectroscopy and infrared spectroscopy received increasing appreciation in bio-analysis for their speediness, accuracy and cost-effectiveness in detection of SARS-CoV. Further, an account of emerging photonics technologies of SARS-CoV-2 detection and future possibilities is also explained. The progress in the field of vibrational spectroscopy techniques for virus detection unambiguously show a great promise in the development of rapid photonics-based devices for COVID-19 detection.

Secondary Structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 Spike Proteins Revealed by Infrared Vibrational Spectroscopy.

All coronaviruses are characterized by spike glycoproteins whose S1 subunits contain the receptor binding domain (RBD). The RBD anchors the virus to the host cellular membrane to regulate the virus transmissibility and infectious process. Although the protein/receptor interaction mainly depends on the spike's conformation, particularly on its S1 unit, their secondary structures are poorly known. In this paper, the S1 conformation was investigated for MERS-CoV, SARS-CoV, and SARS-CoV-2 at serological pH by measuring their Amide I infrared absorption bands. The SARS-CoV-2 S1 secondary structure revealed a strong difference compared to those of MERS-CoV and SARS-CoV, with a significant presence of extended ß-sheets. Furthermore, the conformation of the SARS-CoV-2 S1 showed a significant change by moving from serological pH to mild acidic and alkaline pH conditions. Both results suggest the capability of infrared spectroscopy to follow the secondary structure adaptation of the SARS-CoV-2 S1 to different environments.

Abundance, spatial distribution, and chemical characterization of face masks on the beaches of SE Kanyakumari, India.

Personal Protective Equipment (PPE) is a new world of waste during the COVID-19 pandemic. In this baseline study, the occurrence of PPE faces masks were assessed on the eleven beaches of Kanyakumari, India concerning the abundance, spatial distribution, and chemical characterization (ATR-FTIR spectroscopy). A total of 1593 items/m2 of PPE face masks and their mean density of 0.16 PPE/m2, ranging from 0.02 to 0.54 PPE/m2 were determined in the study area. Kanyakumari beach (n = 430 items/m2) has the highest concentration of masks (26.99 %), with a mean density of 0.54 m2 due to recreational, sewage disposal, and tourism activities. This is perhaps the most important study describing the scientific data that focuses on the significant effects of communal activities and accessibility on COVID-19 PPE face mask pollution. It also highlights the need for sufficient management facilities to optimize PPE disposal.

Scoliosis Management through Apps and Software Tools.

Background: Scoliosis is curvature of the spine, often found in adolescents, which can impact on quality of life. Generally, scoliosis is diagnosed by measuring the Cobb angle, which represents the gold standard for scoliosis grade quantification. Commonly, scoliosis evaluation is conducted in person by medical professionals using traditional methods (i.e., involving a scoliometer and/or X-ray radiographs). In recent years, as has happened in various medicine disciplines, it is possible also in orthopedics to observe the spread of Information and Communications Technology (ICT) solutions (i.e., software-based approaches). As an example, smartphone applications (apps) and web-based applications may help the doctors in screening and monitoring scoliosis, thereby reducing the number of in-person visits. Objectives: This paper aims to provide an overview of the main features of the most popular scoliosis ICT tools, i.e., apps and web-based applications for scoliosis diagnosis, screening, and monitoring. Several apps are assessed and compared with the aim of providing a valid starting point for doctors and patients in their choice of software-based tools. Benefits for the patients may be: reducing the number of visits to the doctor, self-monitoring of scoliosis. Benefits for the doctors may be: monitoring the scoliosis progression over time, managing several patients in a remote way, mining the data of several patients for evaluating different therapeutic or exercise prescriptions. Materials and Methods: We first propose a methodology for the evaluation of scoliosis apps in which five macro-categories are considered: (i) technological aspects (e.g., available sensors, how angles are measured); (ii) the type of measurements (e.g., Cobb angle, angle of trunk rotation, axial vertebral rotation); (iii) availability (e.g., app store and eventual fee to pay); (iv) the functions offered to the user (e.g., posture monitoring, exercise prescription); (v) overall evaluation (e.g., pros and cons, usability). Then, six apps and one web-based application are described and evaluated using this methodology. Results: The results for assessment of scoliosis apps are shown in a tabular format for ease of understanding and intuitive comparison, which can help the doctors, specialists, and families in their choice of scoliosis apps. Conclusions: The use of ICT solutions for spinal curvature assessment and monitoring brings several advantages to both patients and orthopedics specialists. Six scoliosis apps and one web-based application are evaluated, and a guideline for their selection is provided.

Preparation and FTIR-ATR combined with chemometrics analysis of self-emulsifying loaded sungkai extract from Peronema canecens

The use of immunomodulators is one strategy in maintaining the immune system during the Covid-19 pandemic. Sungkai leaf extract from Peronema canecens keeps the immune system in good shape. Therefore, in this study, we formulated a self-emulsifying loaded sungkai leaves extract (SE-SLE) with oleic acid and virgin coconut oil (VCO) oil phases, span 80 and tween 80 as surfactants and co-surfactants in the form of PEG-400 and PG. Chemometric analysis was conducted by observing the typical pattern in each FTIR-ATR spectra. The pattern is divided into several groups based on the wavenumber and analyzed using principal component analysis (PCA) to identify the compounds contained therein. Grouping based on chemical properties via IR spectra on SE-SLE resulted in two large groups. The results obtained are beneficial as initial information in developing and optimizing the self-nano emulsifying drug delivery system formula.Copyright © RJPT All right reserved.

ATR-FTIR spectrum analysis of plasma samples for rapid identification of recovered COVID-19 individuals.

The development of fast, cheap and reliable methods to determine seroconversion against infectious agents is of great practical importance. In the context of the COVID-19 pandemic, an important issue is to study the rate of formation of the immune layer in the population of different regions, as well as the study of the formation of post-vaccination immunity in individuals after vaccination. Currently, the main method for this kind of research is enzyme immunoassay (ELISA, enzyme-linked immunosorbent assay). This technique is sufficiently sensitive and specific, but it requires significant time and material costs. We investigated the applicability of attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy associated with machine learning in blood plasma to detect seroconversion against SARS-CoV-2. The study included samples of 60 patients. Clear spectral differences in plasma samples from recovered COVID-19 patients and conditionally healthy donors were identified using multivariate and statistical analysis. The results showed that ATR-FTIR spectroscopy, combined with principal components analysis (PCA) and linear discriminant analysis (LDA) or artificial neural network (ANN), made it possible to efficiently identify specimens from recovered COVID-19 patients. We built classification models based on PCA associated with LDA and ANN. Our analysis led to 87% accuracy for PCA-LDA model and 91% accuracy for ANN, respectively. Based on this proof-of-concept study, we believe this method could offer a simple, label-free, cost-effective tool for detecting seroconversion against SARS-CoV-2. This approach could be used as an alternative to ELISA.

Study of the Long-Term Aging of Polypropylene-Made Disposable Surgical Masks and Filtering Facepiece Respirators.

The main purpose of this work is to contribute to understanding the mechanism of oxidation of the polymeric components of common disposable masks used during the COVID-19 pandemic to offer the chemical basis to understand their long-term behavior under typical environmental conditions. Artificial aging of representative mask layers under isothermal conditions (110 °C) or accelerated photoaging showed that all the PP-made components underwent a fast oxidation process, following the typical hydrocarbon oxidation mechanism. In particular, yellowing and the melting temperature drop are early indicators of their diffusion-limited oxidation. Morphology changes also induced a loss of mechanical properties, observable as embrittlement of the fabric fibers. Results were validated through preliminary outdoor aging of masks, which allows us to predict they will suffer fast and extensive oxidation only in the case of contemporary exposure to sunlight and relatively high environmental temperature, leading to their extensive breakdown in the form of microfiber fragments, i.e., microplastics.

SARS-CoV-2 structures detection in artificial saliva using ATR-FTIR associated with Linear Discriminant Analysis

Here, we used ATR-FTIR platform supported by artificial intelligence algorithms to identify unique infrared vibrational modes of a pseudotyped human immunodeficiency virus type-1 (HIV-1) coupled to Spike (S) protein of SARS-CoV-2 (HIV/NanoLuc-SARS-CoV-2 pseudotype virus). © Optica Publishing Group 2022 The Authors.

SARS-CoV-2 structures detection in artificial saliva using ATR-FTIR associated with Linear Discriminant Analysis

Here, we used ATR-FTIR platform supported by artificial intelligence algorithms to identify unique infrared vibrational modes of a pseudotyped human immunodeficiency virus type-1 (HIV-1) coupled to Spike (S) protein of SARS-CoV-2 (HIV/NanoLuc-SARS-CoV-2 pseudotype virus). © Optica Publishing Group 2022 The Authors.

Elevated Risk of Recurrent Ablation in Black Compared to White Patients With Atrial Fibrillation: Another Paradox of Atrial Fibrillation in Blacks

Introduction: Lower prevalence of atrial fibrillation (AF) despite a higher prevalence of risk factors in blacks compared to whites (AF paradox) has been reported. However, less information is available about recurrent ablation events in blacks compared to whites. Method(s): Demographic characteristics and one-year recurrent ablation events were analyzed in AF patients admitted to a community hospital from 2018 to 2021. Result(s): Recurrent AF ablation occurred in 3.7% (16/435) of the study population and was significantly higher in black compared to white patients [9/86 (10.5%) vs. 7/349 (2.0%), respectively, p=0.0001]. Black race and history of atrial flutter were predictors of recurrent AF ablation (p<0.05) within one year of initial ablation. Black patients were younger (p=0.03) with a significantly higher prevalence of hypertension, diabetes, cardiomyopathy/heart failure, thyroid disease, renal disease, sleep apnea, COVID-19, pacemaker/AICD placement, and history of Ventricular tachycardia (Table). Concomitant medications were similar between races besides higher use of antihypertensive medications in black patients (Table). Conclusion(s): In our community hospital setup, black patients with AF had a higher prevalence of comorbidities and significantly higher incidence of one-year recurrent ablation events despite similar therapy compared to white patients. These observations should be explored in a larger prospective study to understand the differential association of comorbidities in black AF patients and associated higher risk for recurrent events.

The MEK1/2 Inhibitor ATR-002 (Zapnometinib) Synergistically Potentiates the Antiviral Effect of Direct-Acting Anti-SARS-CoV-2 Drugs.

The coronavirus disease 2019 (COVID-19) represents a global public health burden. In addition to vaccination, safe and efficient antiviral treatment strategies to restrict the viral spread within the patient are urgently needed. An alternative approach to a single-drug therapy is the combinatory use of virus- and host-targeted antivirals, leading to a synergistic boost of the drugs' impact. In this study, we investigated the property of the MEK1/2 inhibitor ATR-002's (zapnometinib) ability to potentiate the effect of direct-acting antivirals (DAA) against SARS-CoV-2 on viral replication. Treatment combinations of ATR-002 with nucleoside inhibitors Molnupiravir and Remdesivir or 3C-like protease inhibitors Nirmatrelvir and Ritonavir, the ingredients of the drug Paxlovid, were examined in Calu-3 cells to evaluate the advantage of their combinatory use against a SARS-CoV-2 infection. Synergistic effects could be observed for all tested combinations of ATR-002 with DAAs, as calculated by four different reference models in a concentration range that was very well-tolerated by the cells. Our results show that ATR-002 has the potential to act synergistically in combination with direct-acting antivirals, allowing for a reduction in the effective concentrations of the individual drugs and reducing side effects.

A new strategy based on PCA for inter-batches quality consistency evaluation.

Due to cultivation position, climate, harvest times, storage conditions and processing method, the evaluation of intra- and inter- batches quality consistency of botanical drugs has always been a thorny problem since it concerns safety and efficacy. The combination of fingerprint based on instrumental analysis and chemometrics is a common evaluation method in recent years. The differences between groups can be judged intuitively and superficially through principal component analysis (PCA) multi-dimensional score plots, but there is a lack of scientific and quantitative index to quantify the differences between groups. How to quantify the difference between groups is basically a blank area of research. Based on traditional F-statistic, we proposed a new F*-statistic to quantify the difference between groups in PCA score plots from the perspective of statistics. As the results revealed, the calculated F*-statistic was 2.58, smaller than the critical value 3.17 (α = 0.05), which indicated that there was no significant difference between groups. Our study add another dimension for PCA application, which offers a new strategy to quantify differences between groups by a new perspective, namely, a combination of fingerprint, chemometrics and statistics to evaluate inter-batches quality consistency quantitatively and objectively. Therefore, this manuscript could provide new ideas and technical references for the quality consistency evaluation of natural drugs, thus better guarantee their clinical efficacy and safety, and better promote industrial development.

Cholesterol Significantly Affects the Interactions between Pirfenidone and DPPC Liposomes: Spectroscopic Studies

In this work, we studied the effect of as on the interaction of membrane DPPC with the key antifibrotic drug pirfenidone. Liposomal forms of pirfenidone were obtained using passive loading. The addition of cholesterol reduces the loading efficiency of pirfenidone by 10%. The main binding site of pirfenidone in DPPC liposomes is the carbonyl group: the interaction with PF significantly increases the proportion of low-hydrated carbonyl groups as revealed by ATR-FTIR spectroscopy. The phosphate group acts as an additional binding site;however, due to shielding by the choline group, this interaction is weak. The hydrophobic part of the bilayer is not involved in PF binding at room temperature. Cholesterol changes the way of interaction between carbonyl groups and pirfenidone probably because of the formation of two subpopulations of DPPC and causes a dramatic redistribution of carbonyl groups onto the degrees of hydration. The proportion of moderately hydrated carbonyl groups increases, apparently due to the deepening of pirfenidone into the circumpolar region of the bilayer. For the first time, a change in the microenvironment of pirfenidone upon binding to liposomes was shown: aromatic moiety interacts with the bilayer.

The MEK1/2-inhibitor ATR-002 efficiently blocks SARS-CoV-2 propagation and alleviates pro-inflammatory cytokine/chemokine responses.

Coronavirus disease 2019 (COVID-19), the illness caused by a novel coronavirus now called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to more than 260 million confirmed infections and 5 million deaths to date. While vaccination is a powerful tool to control pandemic spread, medication to relieve COVID-19-associated symptoms and alleviate disease progression especially in high-risk patients is still lacking. In this study, we explore the suitability of the rapid accelerated fibrosarcoma/mitogen-activated protein kinase/extracellular signal-regulated kinase (Raf/MEK/ERK) pathway as a druggable target in the treatment of SARS-CoV-2 infections. We find that SARS-CoV-2 transiently activates Raf/MEK/ERK signaling in the very early infection phase and that ERK1/2 knockdown limits virus replication in cell culture models. We demonstrate that ATR-002, a specific inhibitor of the upstream MEK1/2 kinases which is currently evaluated in clinical trials as an anti-influenza drug, displays strong anti-SARS-CoV-2 activity in cell lines as well as in primary air-liquid-interphase epithelial cell (ALI) cultures, with a safe and selective treatment window. We also observe that ATR-002 treatment impairs the SARS-CoV-2-induced expression of pro-inflammatory cytokines, and thus might prevent COVID-19-associated hyperinflammation, a key player in COVID-19 progression. Thus, our data suggest that the Raf/MEK/ERK signaling cascade may represent a target for therapeutic intervention strategies against SARS-CoV-2 infections and that ATR-002 is a promising candidate for further drug evaluation.

Study of ergocalciferol and cholecalciferol (Vitamin D): Modeled optical properties and optical detection using absorption and Raman spectroscopy.

The task of assembling and calculating spectrally significant lines of Vitamin D2 and D3 is related to a wider goal of establishing if it is possible to develop non-invasive optical sensors for these substances present at concentrations on the order of tens of nmol/L. Such a non-invasive in vivo sensor would be helpful for medical considerations, among others, related to multiple sclerosis prevention, reduced risk of mortality in D3-treated acute in-patients admitted with COVID 19, systemic infection, acute respiratory tract infections, including epidemic influenza, community-acquired pneumonia at concentrations <50nmol/L(<20ng/mL), dental health (90-100nmol/L) of 25(OH) D, general health and others. Currently, to determine the concentration of these substances, it is necessary to draw a sample from a vein in ambulatory settings and analyse the sample with the gold standard of mass spectroscopy or immunoassay. In this article Vitamin D optical properties are studied by density functional theory calculations, compared to reported data, and the new calculated and measured D2 and D3 optical absorption lines are presented, as well as the calculations compared with spectral measurements of optical transmission, FTIR ATR and Raman spectra.

CoronaVac (Sinovac) COVID-19 vaccine-induced molecular changes in healthy human serum by infrared spectroscopy coupled with chemometrics.

From the beginning of the COVID-19 coronavirus pandemic in December of 2019, the disease has infected millions of people worldwide and caused hundreds of thousands of deaths. Since then, several vaccines have been developed. One of those vaccines is inactivated CoronaVac-Sinovac COVID-19 vaccine. In this proof of concept study, we first aimed to determine CoronaVac-induced biomolecular changes in healthy human serum using infrared spectroscopy. Our second aim was to see whether the vaccinated group can be separated or not from the non-vaccinated group by applying chemometric techniques to spectral data. The results revealed that the vaccine administration induced significant changes in some functional groups belonging to lipids, proteins and nucleic acids. In addition, the non-vaccinated and vaccinated groups were successfully separated from each other by principal component analysis (PCA) and linear discriminant analysis (LDA). This proof-of-concept study will encourage future studies on CoronaVac as well as other vaccines and will lead to make a comparison between different vaccines to establish a better understanding of the vaccination outcomes on serum biomolecules.

Antiviral drug screen identifies DNA-damage response inhibitor as potent blocker of SARS-CoV-2 replication.

SARS-CoV-2 has currently precipitated the COVID-19 global health crisis. We developed a medium-throughput drug-screening system and identified a small-molecule library of 34 of 430 protein kinase inhibitors that were capable of inhibiting the SARS-CoV-2 cytopathic effect in human epithelial cells. These drug inhibitors are in various stages of clinical trials. We detected key proteins involved in cellular signaling pathways mTOR-PI3K-AKT, ABL-BCR/MAPK, and DNA-damage response that are critical for SARS-CoV-2 infection. A drug-protein interaction-based secondary screen confirmed compounds, such as the ATR kinase inhibitor berzosertib and torin2 with anti-SARS-CoV-2 activity. Berzosertib exhibited potent antiviral activity against SARS-CoV-2 in multiple cell types and blocked replication at the post-entry step. Berzosertib inhibited replication of SARS-CoV-1 and the Middle East respiratory syndrome coronavirus (MERS-CoV) as well. Our study highlights key promising kinase inhibitors to constrain coronavirus replication as a host-directed therapy in the treatment of COVID-19 and beyond as well as provides an important mechanism of host-pathogen interactions.

Investigations into the Effects of pH on Quantitative Measurements of Lactate in Biological Media Using ATR-FTIR Spectroscopy.

Quantification of lactate/lactic acid in critical care environments is essential as lactate serves as an important biochemical marker for the adequacy of the haemodynamic circulation in shock and of cell respiration at the onset of sepsis/septic shock. Hence, in this study, ATR-FTIR was explored as a potential tool for lactate measurement, as the current techniques depend on sample preparation and fails to provide rapid response. Moreover, the effects of pH on PBS samples (7.4, 7, 6.5 and 6) and change in solution conditions (PBS to whole blood) on spectral features were also investigated. A total 189 spectra from five sets of lactate containing media were obtained. Results suggests that lactate could be measured with more than 90% accuracy in the wavenumber range of 1500-600 cm-1. The findings of this study further suggest that there exist no effects of change in pH or media, when estimating lactate concentration changes in this range of the Mid-IR spectral region.

Computational biophysical characterization of the SARS-CoV-2 spike protein binding with the ACE2 receptor and implications for infectivity.

SARS-CoV-2 is a novel highly virulent pathogen which gains entry to human cells by binding with the cell surface receptor - angiotensin converting enzyme (ACE2). We computationally contrasted the binding interactions between human ACE2 and coronavirus spike protein receptor binding domain (RBD) of the 2002 epidemic-causing SARS-CoV-1, SARS-CoV-2, and bat coronavirus RaTG13 using the Rosetta energy function. We find that the RBD of the spike protein of SARS-CoV-2 is highly optimized to achieve very strong binding with human ACE2 (hACE2) which is consistent with its enhanced infectivity. SARS-CoV-2 forms the most stable complex with hACE2 compared to SARS-CoV-1 (23% less stable) or RaTG13 (11% less stable). Notably, we calculate that the SARS-CoV-2 RBD lowers the binding strength of angiotensin 2 receptor type I (ATR1) which is the native binding partner of ACE2 by 44.2%. Strong binding is mediated through strong electrostatic attachments with every fourth residue on the N-terminus alpha-helix (starting from Ser19 to Asn53) as the turn of the helix makes these residues solvent accessible. By contrasting the spike protein SARS-CoV-2 Rosetta binding energy with ACE2 of different livestock and pet species we find strongest binding with bat ACE2 followed by human, feline, equine, canine and finally chicken. This is consistent with the hypothesis that bats are the viral origin and reservoir species. These results offer a computational explanation for the increased infection susceptibility by SARS-CoV-2 and allude to therapeutic modalities by identifying and rank-ordering the ACE2 residues involved in binding with the virus.