Comparison of rainwater quality before and during the MCO using chemometric analyses.

This study aimed to classify the spatiotemporal analysis of rainwater quality before and during the Movement Control Order (MCO) implementation due to the COVID-19 pandemic. Chemometric analysis was carried out on rainwater samples collected from 24-gauge stations throughout Malaysia to determine the samples' chemical content, pH, and conductivity. Other than that, hierarchical agglomerative cluster analysis (HACA) and discriminant analysis (DA) were used to classify the quality of rainwater at each location into four clusters, namely good, satisfactory, moderate, and bad clusters. Note that DA was carried out on the predefined clusters. The reduction in acidity levels occurred in 11 stations (46% of overall stations) after the MCO was implemented. Chemical content and ion abundance followed a downward trend, indicating that Cl- and Na+ were the most dominant among the anions and cations. Apart from that, NH4+, Ca2+, NO3-, and SO42- concentrations were evident in areas with significant anthropogenic activity, as there was a difference in the total chemical content in rainwater when compared before and during the MCO. Based on the dataset before the MCO, 75% of gauge stations were in the good cluster, 8.3% in the satisfactory cluster, 12.5% in the moderate cluster, and 4.2% in the bad cluster. Meanwhile, the dataset during the MCO shows that 72.7% of gauge stations were in the good cluster, 9.1% in the satisfactory cluster, 9.1% in the moderate, and 4.5% in the bad cluster. From this study, the chemometric analysis of the year 2020 rainwater chemical composite dataset strongly indicates that reduction of human activities during MCO affected the quality of rainwater.

ATR-FTIR spectroscopy and chemometrics as a quick and simple alternative for discrimination of SARS-CoV-2 infected food of animal origin.

Alternative routes such as virus transmission or cross-contamination by food have been suggested, due to reported cases of SARS-CoV-2 in frozen chicken wings and fish or seafood. Delay in routine testing due to the dependence on the PCR technique as the standard method leads to greater virus dissemination. Therefore, alternative detection methods such as FTIR spectroscopy emerge as an option. Here, we demonstrate a fast (3 min), simple and reagent-free methodology using attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy for discrimination of food (chicken, beef and fish) contaminated with the SARS-CoV-2 virus. From the IR spectra of the samples, the "bio-fingerprint" (800 - 1900 cm-1) was selected to investigate the distinctions caused by the virus contamination. Exploratory analysis of the spectra, using Principal Component of Analysis (PCA), indicated the differentiation in the data due to the presence of single bands, marked as contamination from nucleic acids including viral RNA. Furthermore, the partial least squares discriminant analysis (PLS-DA) classification model allowed for discrimination of each matrix in its pure form and its contaminated counterpart with sensitivity, specificity and accuracy of 100 %. Therefore, this study indicates that the use of ATR-FTIR can offer a fast and low cost and not require chemical reagents and with minimal sample preparation to detect the SARS-CoV-2 virus in food matrices, ensuring food safety and non-dissemination by consumers.

A green spectrophotometric method for the simultaneous determination of nasal binary mixture used in respiratory diseases: Applying isosbestic point and chemometric approaches as a resolving tool, greenness evaluation.

Nasal drug combination is a very useful therapy for elevating the symptoms of various respiratory diseases as seasonal allergic rhinitis and infectious respiratory illness as pandemic COVID-19. One of best combination is Fluticasone propionate (FLU) and Azelastine (AZE). In this study, different UV spectrophotometric and chemometric methods have been applied for quantitative analysis of FLU and AZE without previous separation in their pure form, laboratory prepared mixture and pharmaceutical dosage form. Absorbance subtraction (AS) and Amplitude modulation (AM) spectrophotometric methods have been applied for the simultaneous determination of the cited drugs. Besides, three well-known chemometric techniques; namely, classical least squares (CLS), partial least square (PLS), and principal component regression (PCR) have been applied for the simultaneous analysis of both drugs by using spectrophotometric data. To be friendly to the environment, the greenness of the proposed methods was taken into consideration and evaluation of the analytical methods' greenness was done using two green analytical chemistry metrics known as, Analytical Greenness Calculator and an eco-scale scoring method. They indicated that the methods were environmentally friendly in relation to numerous approaches like instrument, reagents, and safety of waste. Analyzing laboratory prepared mixtures including different quantities of FLU and AZE, as well as their marketed dose form, was used to assess the selectivity of the applied methods. The validity of the developed methods was investigated by applying the standard addition technique. The resulting data were statistically compared to those obtained by the official or reported HPLC methods for FLU and AZE, which revealed no significant difference in accuracy and precision at p = 0.05.

Chemical profiling and unraveling of anti-COVID-19 biomarkers of red sage (Lantana camara L.) cultivars using UPLC-MS/MS coupled to chemometric analysis, in vitro study and molecular docking.

ETHNOPHARMACOLOGICAL RELEVANCE: Red sage (Lantana camara L.) (Verbenaceae) is a widely spread plant that was traditionally used in Brazil, India, Kenya, Thailand, Mexico, Nigeria, Australia and Southeast Asia for treating several ailments including rheumatism and leprosy. Despite its historical role in relieving respiratory diseases, limited studies progressed to the plant's probable inhibition to respiratory viruses especially after the striking spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. AIM OF THE STUDY: This study aimed to investigate the inhibitory activity of different L. camara cultivars to SARS-CoV-2, that was not previously inspected, and clarify their mechanisms of action in the metabolomics viewpoint, and to determine the biomarkers that are related to such activity using UPLC-MS/MS coupled to in vitro-studies and chemometric analysis. MATERIALS AND METHODS: Chemical profiling of different cultivars was accomplished via UPLC-MS/MS. Principle component analysis (PCA) and orthogonal projection to latent structures (OPLS) models were built using SIMCA® (multivariate data analysis software). Cytotoxicity and COVID-19 inhibitory activity testing were done followed by TaqMan Real-time RT-PCR (Reverse transcription polymerase chain reaction) assay that aimed to study extracts' effects on RNA-dependent RNA polymerase (RdRp) and E-genes expression levels. Detected biomarkers from OPLS analysis were docked into potential targets pockets to investigate their possible interaction patterns using Schrodinger® suite. RESULTS: UPLC-MS/MS analysis of different cultivars yielded 47 metabolites, most of them are triterpenoids and flavonoids. PCA plots revealed that inter-cultivar factor has no pronounced effect on the chemical profiles of extracts except for L. camara, cultivar Drap d'or flowers and leaves extracts as well as for L. camara cv Chelsea gem leaves extract. Among the tested extracts, flowers and leaves extracts of L. camara cv Chelsea gem, flowers extracts of L. camara cv Spreading sunset and L. camara cv Drap d'or showed the highest selectivity indices scoring 12.3, 10.1, 8.6 and 7.8, respectively, indicating their relative high safety and efficacy. Leaves and flowers extracts of L. camara cv Chelsea gem, flowers extracts of L. camara cv Spreading sunset and L. camara cv Drap d'or were the most promising inhibitors to viral plaques exhibiting IC50 values of 3.18, 3.67, 4.18 and 5.01 µg/mL, respectively. This was incremented by OPLS analysis that related their promising COVID-19 inhibitory activities to the presence of twelve biomarkers. Inhibiting the expression of RdRp gene is the major mechanism behind the antiviral activity of most extracts at almost all concentration levels. Molecular docking of the active biomarkers against RdRp revealed that isoverbascoside, luteolin-7,4'-O-diglucoside, camarolic acid and lantoic acid exhibited higher docking scores of -11.378, -10.64, -6.72 and -6.07 kcal/mol, respectively, when compared to remdesivir (-5.75 kcal/mol), thus these four compounds can serve as promising anti-COVID-19 candidates. CONCLUSION: Flowers and leaves extracts of four L. camara cultivars were recognized as rich sources of phytoconstituents possessing anti-COVID-19 activity. Combination of UPLC-MS/MS and chemometrics is a promising approach to detect chemical composition differences among the cultivars and correlate them to COVID-19 inhibitory activities allowing to pinpoint possible biomarkers. Further in-vitro and in-vivo studies are required to verify their activity.