Jing Guan Fang (JGF) is an anti-COVID-19 Chinese Medicine decoction comprised of five medicinal herbs to possess anti-inflammatory and antiviral properties for treatment. This study aims to electrochemically decipher the anti-coronavirus activity of JGF and show that microbial fuel cells may serve as a platform for screening efficacious herbal medicines and providing scientific bases for the mechanism of action (MOA) of TCMs.

Traditional herbal medicines usually contain electron shuttle (ES)-like structures compounds which are potential candidates for antiviral compounds selection. is applied as a biomaterial to decipher its potential applications in bioenergy extraction in microbial fuel cells (MFCs) and anti-COVID-19 via molecular docking evaluation.

The COVID-19 pandemic has leveraged facial masks to be one of the most effective measures to prevent the spread of the virus, which thereby has exponentially increased the usage of facial masks that lead to medical waste mismanagements which pose a serious threat to life. Thermal degradation or pyrolysis is an effective treatment method for the used facial mask wastes and this study aims to investigate the thermal degradation of the same.

Nowadays, wearing a 3-layered face mask (3LFM) to protect against coronavirus illness (COVID-19) has become commonplace, resulting in massive, hazardous solid waste. Since most of them are infected with viruses, a secure way of disposal is necessary to prevent further virus spread. Pyrolysis treatment has recently developed as an effective method for disposing of such hazardous waste and consequently converting them into energy products. In this regard, the goal of the present study is to physicochemically characterize the 3LFM followed by pyrolysis in a TGA to evaluate the pyrolysis performance, kinetic, and thermodynamic parameters and in a semi-batch reactor to characterize the volatile product. Furthermore, an artificial neural network (ANN) was used to forecast thermal deterioration data. The results demonstrated a strong correlation between real and anticipated values. The study proved the relevance of the ANN model and the applicability of pyrolysis for disposing of 3LFM while simultaneously producing energy products.

This first-attempt study explored indigenous herbs from agricultural waste with bioenergy and biorefinery-stimulating potentials for possible anti-COVID-19 drug development. As prior novel study revealed, medicinal herbs abundant in -dihydroxyl substituents and flavonoid-bearing chemicals were likely not only electron shuttle (ES)-steered, but also virus transmission-resisted.

Traditional Chinese medicine (TCM) has been used as an "immune booster" for disease prevention and clinical treatment since ancient China. However, many studies were focused on the organic herbal extract rather than aqueous herbal extract (AHE; decoction). Due to the COVID-19 pandemics, this study tended to decipher phytochemical contents in the decoction of herbs and derived bioactivities (e.g., anti-oxidant and anti-inflammatory properties). As prior works revealed, the efficacy of Parkinson's medicines and antiviral flavonoid herbs was strongly governed by their bioenergy-stimulating proficiency.

Coronavirus disease 2019 (COVID-19) has caused a substantial increase in mortality and economic and social disruption. The absence of US Food and Drug Administration-approved drugs for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) highlights the need for new therapeutic drugs to combat COVID-19.

The SARS-CoV-2 virus, promoter of COVID-19, already infected millions of people around the world, resulting in thousands of fatal victims. Facing this unprecedented crisis in human history, several research groups, industrial companies and governments have been spending efforts to develop vaccines and medications. People from distinct knowledge fields are doing their part in order to overcome this crisis. Chemical Engineers are also contributing in the development of actions to control the SARS-CoV-2 virus. However, many chemical engineers still do not know how to use the knowledge acquired from Chemical Engineering school to collaborate in the fight against the COVID-19. In this context, the present paper aims to discuss several knowledge fields within the Chemical Engineering and correlated areas successfully applied to create innovative and effective solutions in the fight against the COVID-19.

In this research, the effect of Dexamethasone drug (DM) on mild steel corrosion  in  2 M HCl was analyzed using weight loss, potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) and MD-simulation. In addition, Fourier transform infrared spectra (FTIR), scanning electron microscopy (SEM), Energy dispersive x-ray spectroscopy (EDX), and atomic force microscopy (AFM) were employed to inspect the mild steel surface in the blank and inhibited medium. For the optimization tool, adaptive neuro-fuzzy inference system (ANFIS) model was developed to predict the inhibition efficiency. The experimental data was categorized into two different sections for training and testing the ANFIS model. The developed model aimed to evaluate the fitness between the experimental and predicted values. From the results generated, optimum value (IE%) of DM was recorded as 80%, 81% and 83% at concentration of 0.4 g/L for weight loss, EIS and PDP respectively. Potentiodynamic polarization results reveal that Dexamethasone functions as a mixed-type inhibitor, whereas studies of EIS show that the inhibition mechanism is by the transfer of charges. Mild steel surface examination confirmed the presence of a protective adsorbed film on the mild steel surface. Thermodynamic parameters obtained imply that Dexamethasone is adsorbed on the steel surface by a physiochemical process and obeys Langmuir adsorption isotherm. Also the MD-simulation results evidenced that DM forms a metallic surface adsorbed film on the steel surface. From the ANFIS model, the sensitivity analysis shows that time and inhibitor concentration were the most important input variable while other input variables could not be neglected. ANFIS model coefficient of determination ( 0.993) was found between the observed and predicted values. ANFIS model gave optimum prediction (80%) with high degree accuracy and robustness. The outcomes of this investigation provide more information, simulation, and prediction about inhibition of metal corrosion.

This first-attempt study deciphered combined characteristics of species evolution and bioelectricity generation of microbial community in microbial fuel cells (MFCs) supplemented with green tea (GT) extracts for biomass energy extraction. Prior studies indicated that polyphenols-rich extracts as effective redox mediators (RMs) could exhibit significant electrochemical activities to enhance power generation in MFCs. However, the supplementation of GT extract obtained at room temperature with significant redox capabilities into MFCs unexpectedly exhibited obvious inhibitory effect towards power generation. This systematic study indicated that the presence of antimicrobial components (especially catechins) in GT extract might significantly alter the distribution of microbial community, in particular a decrease of microbial diversity and evenness. For practical applications to different microbial systems, pre-screening criteria of selecting biocompatible RMs should not only consider their promising redox capabilities (abiotic), but also possible inhibitory potency (biotic) to receptor microbes. Although tea extract was well-characterized as GRAS energy drink, some contents (e.g., catechins) may still express inhibition towards organisms and further assessment upon biotoxicity may be inevitably required for practice.

Inhibitors of aminopeptidase N (APN) have been thought as potential drugs for the treatment of tumor angiogenesis, invasion and metastasis and a considerable number of APN inhibitors have been reported recently. To clarify the essential structure-activity relationship for the APN inhibitors as well as identify new potent leads against APN, pharmacophore models were established using structure- and common feature-based approaches and validated with a database of active and inactive compounds. These validated pharmacophores were then used in database screening for novel virtual leads. The hit compounds were further subjected to molecular docking studies to refine the retrieved hits. Finally, six structurally diverse compounds that showed strong interactions with the key amino acids and the zinc ion were selected for biological evaluation, where two hits showed more than 70% inhibition against APN at 60 μM concentration. The evaluation results show the potential of our screening approach in identifying APN inhibitors.

The effect of relative size of two co-axially hybridized gene targets on the hybridization efficiency was studied for two DNA probe configurations and various probe concentrations. Each of two sets of microarrayed probes contained a pair of DNA probes and a pair of their complementary samples labeled with two distinct fluorescent dyes. The sequence of each probe is especially designed so that two targets are simultaneously complementary to two adjacent sections of the probe. The molecular steric effect on the hybridization efficiency is investigated by comparing the dye signals between configurations of one-target and two-target hybridization scenarios. The results show that a low probe concentration gives better hybridization efficiency and the first-hybridization conducted by a shorter-size DNA target improves the hybridization efficiency of the second target coupling onto the same probe.

Cysteine has been considered as a "hydrophilic" amino acid because of its p and its ability to form (weak) hydrogen bonds. However, cysteines are found mostly in hydrophobic environments, either in S-S (disulphide) form or in free cysteine form. When free cysteines are found on the surface of proteins, they are often involved in catalytic residues, as in cysteine proteases, P-loop phosphatases, Additionally, a unique property of cysteines is that their side-chain volume is different from all other amino acids. This study is focused on the discrimination between structural versus active free cysteines based on a local environment analysis which does not appear to have been attempted previously. We have demonstrated the corresponding structural positions associated with free cysteines in their three-dimensional localization environment. We examined protein samples including nine, sequenced, coronavirus proteases and cysteine-rich non-membrane proteins. Our present study shows that the sequential environments of free cysteines of coronavirus proteases are rather hydrophobic and that the free cysteines of non-membrane proteases have a higher amount of contacts to hydrophobic residues and lower amount of contacts to polar or charged residues.