Mechanism and Kinetics of The Degradation of Nitazoxanide and Hydroxychloroquine Drugs by Hydroxyl Radicals: Theoretical Approach to Ecotoxicity

The efforts of contrasting the effects caused by the Covid-19 (coronavirus disease 2019) pandemic increased the disposal of active pharmaceutical ingredients. This paper reports the mechanisms and kinetics of the degradation in aqueous environments induced by 'OH of two drugs, among those most widely probed at the outbreak of coronavirus, nitazoxanide and hydroxychloroquine. The investigation exploits quantum chemistry techniques and a reaction rate theory combined with diffusion-controlled processes and quantum mechanical tunneling. The reaction rate constants are obtained in an environmentally relevant temperature range. The results show that (i) the deacetylation of nitazoxanide with formation of tizoxanide is kinetically the most favorable channel, in agreement with experimental work;(ii) for hydroxychloroquine, the present theoretical calculations show that the most favorable channel is the addition of 'OH at the aromatic ring. The half-life time degradation products are for both cases in the range between 12 to 138 days. Both drugs presented toxicities between harmful and toxic as obtained by computational toxicology calculations: The toxicity is also calculated for the degradation products: (i) in the nitazoxanide degradation process, tizoxanide was characterized as more toxic, while (ii) in the case of hydroxychloroquine, the major degradation product showed a decrease in the toxicity.

Fully automated measurement system for temperature-dependent X-ray total scattering at beamline BL04B2 at SPring-8.

Data-driven approaches in materials science demand the collection of large amounts of data on the target materials at synchrotron beamlines. To accurately gather suitable experimental data, it is essential to establish fully automated measurement systems to reduce the workload of the beamline staff. Moreover, the recent COVID-19 pandemic has further emphasized the necessity of automated and/or remote measurements at synchrotron beamlines. Here, the installation of a new sample changer combined with a high-temperature furnace and a fully automated alignment system on beamline BL04B2 at SPring-8 is reported. The system allows X-ray total scattering measurements of up to 21 samples at different temperatures (from room temperature to 1200°C) to be conducted without any human assistance.

A weather temperature methodology on the Italian electricity demand

This paper presents a proposal methodology to study the temperature dependence of the Italian electricity demand. Indeed, weather temperature has a significant influence on the electricity consumption. From a Transmission System Operator (TSO) perspective, an accurate estimation of this effect is crucial to interpret and predict demand fluctuations. Several dispatching applications consider these phenomena, as for example adequacy analysis, demand forecasting tools, and real-time operational procedures. Based on the geographical features of Italy, it was possible to identify various sensitivity behaviors at regional scale. The purpose of this study is to develop a temperature sensitivity model to be applied on electricity demand profile with different time granularity (e.g., daily, hourly). A clustering analysis on the historical input data is performed. Furthermore, a thorough investigation to identify the optimal best-fitting method for this application is described. In order to test the methodology, some relevant business cases are simulated considering also extreme scenarios. Results on COVID-19 scenario is also described. Finally, an outlook on the planned future developments of the method is provided. © 2021 AEIT.

Long-Term In-Use NOx Emissions from London Buses with Retrofitted NOx Aftertreatment.

Buses constitute a significant source of air pollutant emissions in cities. In this study, we present real-world NOx emissions from 97 diesel-hybrid buses measured using on-board diagnostic systems over 44 months and 6.35 million km in London. Each bus had previously been retrofitted with a selective catalytic reduction (SCR) aftertreatment system to reduce emissions of nitrogen oxides (NOx). On average, parallel hybrid (PH) and series hybrid (SH) buses emitted 3.80 g of NOx/km [standard deviation (SD) of 1.02] and 2.37 g of NOx/km (SD of 0.51), respectively. The SCR systems reduced engine-out emissions by 79.8% (SD of 5.0) and 87.2% (SD of 2.9) for the PHs and SHs, respectively. Lower ambient temperatures (0-10 °C) increased NOx emissions of the PHs by 24.2% but decreased NOx emissions of the SHs by 27.9% compared to values found at more moderate temperatures (10-20 °C). To improve emissions inventories, we provide new distance-based NOx emissions factors for different ranges of ambient temperature. During the COVID-19 pandemic, the emissions benefits of reduced congestion were largely offset by more frequent route layovers leading to lower SCR temperatures and effectiveness. This study shows that continuous in-service measurements enable quantification of real-world vehicle emissions over a wide range of operations that complements conventional testing approaches.

Temperature dependence of the SARS-CoV-2 affinity to human ACE2 determines COVID-19 progression and clinical outcome.

The SARS-CoV-2 virus and its homolog SARS-CoV penetrate human cells by binding of viral spike protein and human angiotensin converting enzyme II (ACE2). SARS-CoV causes high fever in almost all patients, while SARS-CoV-2 does not. Moreover, analysis of the clinical data revealed that the higher body temperature is a protective factor in COVID-19 patients, making us to hypothesize a temperature-dependent binding affinity of SARS-CoV-2 to human ACE2 receptor. In this study, our molecular dynamics simulation and protein surface plasmon resonance cohesively proved the SARS-CoV-2-ACE2 binding was less affinitive and stable under 40 °C (~18 nM) than the optimum temperature 37 °C (6.2 nM), while SARS-CoV-ACE2 binding was not (6.4 nM vs. 8.5 nM), which evidenced the temperature-dependent affinity and explained that higher temperature is related to better clinical outcome. The decreased infection at higher temperature was also validated by pseudovirus entry assay using Vero and Caco-2 cells. We also demonstrated the structural basis of the distinct temperature-dependence of the two coronaviruses. Furthermore, the meta-analysis revealed a milder inflammatory response happened in the early stage of COVID-19, which explained the low fever tendency of COVID-19 and indicated the co-evolution of the viral protein structure and the inflammatory response. The temperature dependence of the binding affinity also indicated that higher body temperature at early stages might be beneficial to the COVID-19 patients.