Objective: To evaluate the hypothesis that light could reduce the lethality of COVID-19. Methods: Most models for projections of the spread and lethality of COVID-19 take into account the ambient temperature, neglecting light. Recent advances in understanding the mechanism of action of COVID-19 have shown that it causes a systemic infection that significantly affects the hematopoietic system and hemostasis, factors extremely dependent of light, mainly in the region of visible and infrared radiation. Results: In the COVID-19 patients hemoglobin is decreasing and protoporphyrin is increasing, generating an extremely harmful accumulation of iron ions in the bloodstream, which are able to induce an intense inflammatory process in the body with a consequent increase in C-reactive protein and albumin. Observing the unsaturation characteristics of the cyclic porphyrin ring allows it to absorb and emit radiation mainly in the visible region. This characteristic can represent an important differential to change this process in the event of an imbalance in this system, through the photobiomodulation to increase the production of adenosine triphosphate (ATP) using red and nearinfrared radiation (R-NIR) and vitamin D using ultraviolet B (UVB) radiation. These two compounds have the primary role of activating the defense mechanisms of the immune system, enabling greater resistance of the individual against the attack by the virus. According to the theory of electron excitation in photosensitive molecules, similar to hemoglobin heme, after the photon absorption there would be an increase in the stability of the iron ion bond with the center of the pyrrole ring, preventing the losses of heme function oxygen transport (HbO 2). The light is also absorbed by cytochrome c oxidase in the R-NIR region, with a consequent increase in electron transport, regulating enzyme activity and resulting in a significant increase of oxygen rate consumption by mitochondria, increasing ATP production. Conclusions: The most favorable range of optical radiation to operate in this system is between R-NIR region, in which cytochrome c oxidase and porphyrin present absorption peaks centered at 640 nm and HbO 2 with absorption peak centered at 900 nm. Based on the mechanisms described earlier, our hypothesis is that light could reduce the lethality of COVID-19.

The severe COVID‐19 pandemic requires the development of novel, rapid, accurate, and label‐free techniques that facilitate the detection and discrimination of SARS‐CoV‐2 infected subjects. Raman spectroscopy has been used to diagnose COVID‐19 in serum samples of suspected patients without clinical symptoms of COVID‐19 but presented positive immunoglobulins M and G (IgM and IgG) assays versus Control (negative IgM and IgG). A dispersive Raman spectrometer (830 nm, 350 mW) was employed, and triplicate spectra were obtained. A total of 278 spectra were used from 94 serum samples (54 Control and 40 COVID‐19). The main spectral differences between the positive IgM and IgG versus Control, evaluated by principal component analysis (PCA), were features assigned to proteins including albumin (lower in the group COVID‐19 and in the group IgM/IgG and IgG positive) and features assigned to lipids, phospholipids, and carotenoids (higher the group COVID‐19 and in the group IgM/IgG positive). Features referred to nucleic acids, tryptophan, and immunoglobulins were also seen (higher the group COVID‐19). A discriminant model based on partial least squares regression (PLS‐DA) found sensitivity of 84.0%, specificity of 95.0%, and accuracy of 90.3% for discriminating positive Ig groups versus Control. When considering individual Ig group versus Control, it was found sensitivity of 77.3%, specificity of 97.5%, and accuracy of 88.8%. The higher classification error was found for the IgM group (no success classification). Raman spectroscopy may become a technique of choice for rapid serological evaluation aiming COVID‐19 diagnosis, mainly detecting the presence of IgM/IgG and IgG after COVID‐19 infection.

This study proposed the diagnosis of COVID-19 by means of Raman spectroscopy. Samples of blood serum from 10 patients positive and 10 patients negative for COVID-19 by RT-PCR RNA and ELISA tests were analyzed. Raman spectra were obtained with a dispersive Raman spectrometer (830 nm, 350 mW) in triplicate, being submitted to exploratory analysis with principal component analysis (PCA) to identify the spectral differences and discriminant analysis with PCA (PCA-DA) and partial least squares (PLS-DA) for classification of the blood serum spectra into Control and COVID-19. The spectra of both groups positive and negative for COVID-19 showed peaks referred to the basal constitution of the serum (mainly albumin). The difference spectra showed decrease in the peaks referred to proteins and amino acids for the group positive. PCA variables showed more detailed spectral differences related to the biochemical alterations due to the COVID-19 such as increase in lipids, nitrogen compounds (urea and amines/amides) and nucleic acids, and decrease of proteins and amino acids (tryptophan) in the COVID-19 group. The discriminant analysis applied to the principal component loadings (PC2, PC4, PC5, and PC6) could classify spectra with 87% sensitivity and 100% specificity compared to 95% sensitivity and 100% specificity indicated in the RT-PCR kit leaflet, demonstrating the possibilities of a rapid, label-free, and costless technique for diagnosing COVID-19 infection.

This preliminary study proposed the diagnosis of COVID-19 by means of Raman spectroscopy. Samples of blood serum from 10 patients positive and 10 patients negative for COVID-19 by RT-PCR RNA and ELISA tests were analyzed. Raman spectra were obtained with a dispersive Raman spectrometer (830 nm, 350 mW) in triplicate, being submitted to exploratory analysis with principal component analysis (PCA) to identify the spectral differences and discriminant analysis with PCA (PCA-DA) and partial least squares (PLS-DA) for classification of the blood serum spectra into Control and COVID-19. The spectra of both groups positive and negative for COVID-19 showed peaks referred to the basal constitution of the serum (mainly albumin). The difference spectra showed decrease in the peaks referred to proteins and amino acids for the group positive. PCA variables showed more detailed spectral differences related to the biochemical alterations due to the COVID-19 such as increase in lipids, nitrogen compounds (urea and amines/amides) and nucleic acids, and decrease of proteins and amino acids (tryptophan) in the COVID-19 group. The discriminant analysis applied to the principal component loadings (PC 2, PC 4, PC 5 and PC 6) could classify spectra with 87% sensitivity and 100% specificity compared to 95% sensitivity and 100% specificity indicated in the RT-PCR kit leaflet, demonstrating the possibilities of a rapid, label-free and costless technique for diagnosing COVID-19 infection.

The purpose of this study was to perform a comparative biochemical analysis between conventional spectrophotometry and Raman spectroscopy, techniques used for diagnoses, on the urine of healthy (CT) and diabetic and hypertensive patients (DM&HBP). Urine from 40 subjects (20 in the CT group and 20 in the DM&HBP group) was examined in a dispersive Raman spectrometer (an 830 nm excitation and a 350 mW power). The mean Raman spectra between both groups showed a significant difference in peaks of glucose; exploratory analysis by principal component analysis (PCA) identified spectral differences between the groups, with higher peaks of glucose and proteins in the DM&HBP group. A partial least squares (PLS) regression model estimated by the Raman data indicated the concentrations of urea, creatinine, glucose, phosphate, and total protein; creatinine and glucose were the biomarkers that presented the best correlation coefficient (r) between the two techniques analyzed (r = 0.68 and r = 0.98, respectively), both with eight latent variables (LVs) and a root mean square error of cross-validation (RMSecv) of 3.6 and 5.1 mmol/L (41 and 92 mg/dL), respectively. Discriminant analysis (PLS-DA) using the entire Raman spectra was able to differentiate the samples of the groups in the study, with a higher accuracy (81.5%) compared to the linear discriminant analysis (LDA) models using the concentration values of the spectrometric analysis (60.0%) and the concentrations predicted by the PLS regression (69.8%). Results indicated that spectral models based on PLS applied to Raman spectra may be used to distinguish subjects with diabetes and blood hypertension from healthy ones in urinalysis aimed at population screening.

Visceral leishmaniasis (VL) is a zoonosis and chronic disease caused by the protozoan Leishmania spp. which is of great concern to public health. Currently, the drugs used to treat the disease are costly and present undesirable side effects. The use of ozone to treat chronic diseases in both humans and dogs has shown satisfactory results. The aim of this study was to evaluate the ozone therapy in dogs with VL (n=6), administered by intra-abdominal application (IAA), to evaluate hematological and serum biochemical parameters. The protocol involves one gas dose per week for four consecutive weeks. The immunomodulatory action of ozone was determined in the laboratory analyses, confirmed by the increase trend in the white series and maintenance of the renal and hepatic function. Ozone therapy was found to be well tolerated and no adverse effects were observed. Further studies are required to elucidate the mechanisms of action on the infected host.

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