Potential Health Survey of Traditional Spices & Herbs in Prevention and Treatment of COVID-19: A Review

The coronavirus (COVID-19) is a global public health pandemic disease emerged from the novel strain of the coronavirus 2 (SARS-CoV-2) that caused severe acute respiratory syndrome. It is the most significant respiratory illness that has affected the world since World War II. Currently, there is no globally approved drug for the treatment of pandemic COVID-19 except for some recently approved vaccines. Instead, various non-specific treatment options are being utilized by different countries. While some of these are effective, there is a lack of well-documented studies on the impact of traditional medicines on the management of SARS-CoV-2 in vitro and in silico. For thousands of years, traditional healers have been using various herbs and spices products and dietary plants to treat various diseases. This review aims to provide information on the use of traditional spices & herbs in COVID-19 protection and treatment and present the main characteristics of these products and their potential antiviral actions. Various databases were searched for articles related to the use of various herbs for the treatment of viral infections. Many of these studies show that various plant compounds can be utilized for the treatment of viral infections. This study aims to summarize the common used of herbal products and dietary supplements with potent bioactive compounds in treatment or prevent of COVID-19.

Fast one-pot microwave-assisted green synthesis of highly fluorescent plant-inspired S,N-self-doped carbon quantum dots as a sensitive probe for the antiviral drug nitazoxanide and hemoglobin

In this study, we report a one-pot, green, cost-efficient, and fast synthesis of plant-based sulfur and nitrogen self-co-doped carbon quantum dots (S,N-CQDs). By 4-min microwave treatment of onion and cabbage juices as renewable, cheap, and green carbon sources and self-passivation agents, blue emissive S,N-CQDs have been synthesized (λex/λem of 340/418 nm) with a fluorescence quantum yield of 15.2%. A full characterization of the natural biomass-derived quantum dots proved the self-doping with nitrogen and sulfur. The S,N-CQDs showed high efficiency as a fluorescence probe for sensitive determination of nitazoxanide (NTZ), that recently found wide applicability as a repurposed drug for COVID-19, over the concentration range of 0.25–50.0 μM with LOD of 0.07 μM. The nanoprobe has been successfully applied for NTZ determination in pharmaceutical samples with excellent % recovery of 98.14 ± 0.42. Furthermore, the S,N-CQDs proved excellent performance as a sensitive fluorescence nanoprobe for determination of hemoglobin (Hb) over the concentration range of 36.3–907.5 nM with a minimum detectability of 10.30 nM. The probe has been applied for the determination of Hb in blood samples showing excellent agreement with the results documented by a medical laboratory. The greenness of the developed probe has been positively investigated by different greenness metrics and software. The green character of the proposed analytical methods originates from the synthesis of S,N-CQDs from sustainable, widely available, and cheap plants via low energy/low cost microwave-assisted technique. Omission of organic solvents and harsh chemicals beside dependence on mix-and-read analytical approach corroborate the method greenness. The obtained results demonstrated the substantial potential of the synthesized green, safe, cheap, and sustainable S,N-CQDs for pharmaceutical and biological applications. © 2022 Elsevier B.V.

CO2-mediated thermal treatment of disposable plastic food containers

In accordance with global economic prosperity, the frequencies of food delivery and takeout orders have been increasing. The pandemic life, specifically arising from COVID-19, rapidly expanded the food delivery service. Thus, the massive generation of disposable plastic food containers has become significant environmental problems. Establishing a sustainable disposal platform for plastic packaging waste (PPW) of food delivery containers has intrigued particular interest. To comprise this grand challenge, a reliable thermal disposable platform has been suggested in this study. From the pyrolysis process, a heterogeneous plastic mixture of PPW was converted into syngas and value-added hydrocarbons (HCs). PPW collected from five different restaurants consisted of polypropylene (36.9 wt%), polyethylene (10.5 wt%), polyethylene terephthalate (18.1 wt%), polystyrene (13.5 wt%), polyvinyl chloride (4.2 wt%), and other composites (16.8 wt%). Due to these compositional complexities, pyrolysis of PPW led to formations of a variety of benzene derivatives and aliphatic HCs. Adapting multi-stage pyrolysis, the different chemicals were converted into industrial chemicals (benzene, toluene, styrene, etc.). To selectively convert HCs into syngas (H2 and CO), catalytic pyrolysis was adapted using supported Ni catalyst (5 wt% Ni/SiO2). Over Ni catalyst, H2 was produced as a main product due to C[sbnd]H bond scission of HCs. When CO2 was used as a co-reactant, HCs were further transformed to H2 and CO through the chemical reactions of CO2 with gas phase HCs. CO2-assisted catalytic pyrolysis also retarded catalyst deactivation inhibiting coke deposition on Ni catalyst. © 2022 Elsevier B.V.

Rhamnetin is a better inhibitor of SARS-CoV-2 2'-O-methyltransferase than Dolutegravir: a computational prediction

Background: The 2'-O-methyltransferase is responsible for the capping of SARS-CoV-2 mRNA and consequently the evasion of the host's immune system. This study aims at identifying prospective natural inhibitors of the active site of SARS-CoV-2 2'O-methyltransferase (2'-OMT) through an in silico approach. Materials and Method: The target was docked against a library of natural compounds obtained from edible African plants using PyRx - virtual screening software. The antiviral agent, Dolutegravir which has a binding affinity score of -8.5 kcal mol-1 with the SARS-CoV-2 2'-OMT was used as a standard. Compounds were screened for bioavailability through the SWISSADME web server using their molecular descriptors. Screenings for pharmacokinetic properties and bioactivity were performed with PKCSM and Molinspiration web servers respectively. The PLIP and Fpocket webservers were used for the binding site analyses. The Galaxy webserver was used for simulating the time-resolved motions of the apo and holo forms of the target while the MDWeb web server was used for the analyses of the trajectory data.

Efficiency Droop and Degradation in AlGaN-Based UVB Light-Emitting Diodes

In this study, we found that the current droop (J-droop) in AlGaN-based UVB light-emitting diodes was more obvious at higher temperatures, despite both the main and parasitic peaks undergoing monotonic decreases in their intensity upon an increase in the temperature. The slower temperature droop (T-droop) did not occur when the forward current was increased to temperatures greater than 298 K. After an aging time of 6000 h, the emission wavelengths did not undergo any obvious changes, while the intensity of the parasitic peak barely changed. Thus, the degradation in the light output power during long-term operation was not obviously correlated to the existence of the parasitic peak.

Urban Particulate Matter Hazard Mapping and Monitoring Site Selection in Nablus, Palestine

Few air pollution studies have been applied in the State of Palestine and all showed an increase in particulate matter concentrations above WHO guidelines. However, there is no clear methodology for selecting monitoring locations. In this study, a methodology based on GIS and locally calibrated low-cost sensors was tested. A GIS-based weighted overlay summation process for the potential sources of air pollution (factories, quarries, and traffic), taking into account the influence of altitude and climate, was used to obtain an air pollution hazard map for Nablus, Palestine. To test the methodology, eight locally calibrated PM sensors (AirUs) were deployed to measure PM2.5 concentrations for 55 days from 7 January to 2 March 2022. The results of the hazard map showed that 82% of Nablus is exposed to a high and medium risk of PM pollution. Sensors’ readings showed a good match between the hazard intensity and PM concentrations. It also shows an elevated PM2.5 concentrations above WHO guidelines in all areas. In summary, the overall average for PM2.5 in the Nablus was 48 µg/m3. This may indicate the effectiveness of mapping methodology and the use of low-cost, locally calibrated sensors in characterizing air quality status to identify the potential remediation options.

CeO2-Based Heterogeneous Catalysts in Dry Reforming Methane and Steam Reforming Methane: A Short Review

Transitioning to lower carbon energy and environment sustainability requires a reduction in greenhouse gases such as carbon dioxide (CO2) and methane (CH4) that contribute to global warming. One of the most actively studied rare earth metal catalysts is cerium oxide (CeO2) which produces remarkable improvements in catalysts in dry reforming methane. This paper reviews the management of CO2 emissions and the recent advent and trends in bimetallic catalyst development utilizing CeO2 in dry reforming methane (DRM) and steam reforming methane (SRM) from 2015 to 2021 as a way to reduce greenhouse gas emissions. This paper focus on the identification of key trends in catalyst preparation using CeO2 and the effectiveness of the catalysts formulated.

Indo-China Trade Relationship in Last Quarter Century: An Empirical Analysis

Purpose: The study tries to find pattern in the bilateral trade and impact of macro happenings like GFC, Chinese meltdown, Galwan conflict, COVID-19 on it over the period of 1995 to 2020. Design/Methodology/Approach: The study has two dimensions. The first one analyses the monthly export and import figures between India and China product wise (based on HS Code at two-digit level) from Jan2016 to Jan 2021 whereas second one focus on annual data of Indo-China Export and Import along with their annual GDP for 26 years starting from 19941995 to 2019-2020. Bilateral trades are analysed by using four tools namelyBilateral Trade Dependence Index (BTDI);Trade Intensity Index (TIT);Herfindahl Hirschmann Market Concentration Index (HHI);and Index of Export market penetration (IEMP). The study has also used Time series analysis to find the relationship between total bilateral trade and GDP of respective countries using Johansen Cointegration Test, Granger Causality Test, and VAR model. Findings: The annual growth rate of import and export for India with China suggest the short-term impact of macro happenings. Research Limitations: The study has several limitations with respect to availability of very recent data, availability of cost components of trade items in respective countries etc. Managerial Implications: Policy makers for India are suggested to work towards import substitution via various programs like Make-in-India with priority of domestic productions of HS Code 85, 84, 29 which are increasing the trade deficit continuously. Originality/Value: This study is an original effort to highlight the dynamic bilateral trade relationships between India and China in last twenty-five years.

The perils of machine learning in designing new chemicals and materials

[...]the need is obvious when you consider that less than 1% of the chemicals registered for commercial use in the United States have undergone toxicity characterization, whether they are used for medicinal purposes or for fracking. [...]there are many scientific, ethical, and economic advantages to replacing the animals currently used in toxicity tests with non-animal test systems, and great speed and cost advantages in using computer systems. [...]material and chemical usage has increased to 60 billion tonnes per year during the twentieth century2, underscoring the advantages of a rapid machine-learning approach for toxicity characterization. [...]the number of materials and chemicals that can be designed digitally far exceeds the number that have been well characterized.

Application of Machine Learning to Predict the Performance of an EMIPG Reactor Using Data from Numerical Simulations

Microwave-driven plasma gasification technology has the potential to produce clean energy from municipal and industrial solid wastes. It can generate temperatures above 2000 K (as high as 30,000 K) in a reactor, leading to complete combustion and reduction of toxic byproducts. Characterizing complex processes inside such a system is however challenging. In previous studies, simulations using computational fluid dynamics (CFD) produced reproducible results, but the simulations are tedious and involve assumptions. In this study, we propose machine-learning models that can be used in tandem with CFD, to accelerate high-fidelity fluid simulation, improve turbulence modeling, and enhance reduced-order models. A two-dimensional microwave-driven plasma gasification reactor was developed in ANSYS (Ansys, Canonsburg, PA, USA) Fluent (a CFD tool), to create 644 (geometry and temperature) datasets for training six machine-learning (ML) models. When fed with just geometry datasets, these ML models were able to predict the proportion of the reactor area with temperature above 2000 K. This temperature level is considered a benchmark to prevent formation of undesirable byproducts. The ML model that achieved highest prediction accuracy was the feed forward neural network;the mean absolute error was 0.011. This novel machine-learning model can enable future optimization of experimental microwave plasma gasification systems for application in waste-to-energy.

Trade integration, product diversification and the gravity equation: evidence from the Chinese merchandise imports

PurposeThe purpose of this paper is to identify trade integration and structure effects on bilateral trade between China and its partners, focusing on Chinese merchandise imports during the period 1995–2018.Design/methodology/approachThe methodological approach applied here uses the augmented gravity model to investigate the factors lying behind import intensity, by use of the ordinary least squares (OLS) and Poisson pseudo maximum likelihood (PPML) estimators.FindingsThe findings provide evidence of complementarity between the Chinese demand and the world commodity markets. Free trade agreements between China and third countries seem to gradually lose significance, as the Chinese economy consolidates in world trade. Higher product diversification in export structures of China’s trading partners can become advantageous for facilitating market penetration. Diversification of energy resources, the steady, high demand for infrastructure equipment and more sophisticated consumer products constantly determine the structure of Chinese merchandise imports originating mainly and increasingly from countries with direct access to the Pacific Ocean.Originality/valueThe analytical breakdown of Chinese imports, presented in this paper, adds value to the existing literature with regard to trade structure analysis for China, paving the way for similar research for other developing countries as well.

Addressing The Post Covid-19 Economic Consequences Of Lockdown In India

On account of the national closedown, the economy has suffered a severe slump. The reduced purchase of goods and services has lead to slow down of domestic manufacturing and agricultural sectors, leading to severe unemployment in urban industrial areas and contraction of the rural economy. This lockdown has influenced economy and business circumstance in India as it has occurred in other nations. The ongoing lockdown due to COVID-19 outbreak affects the Indian economy in many ways, including sharp declines in domestic demand, lower tourism and business travel, trade and production linkages, supply disruptions, and health effects. There are certain sectors that have been affected due to the outbreak of corona virus. This research paper, anticipates indicative measures that may be taken to revive the economy as well as affected sectors to some extent. First, this paper provides an overview of effect of this lockdown on Indian economy. With no manufacturing activity, it is likely that growth of gross domestic product (GDP) will be slowed down. This will be followed listing of the sectors affected due to COVID-19, which carries the risk of global supply chain disruptions. This includes five import items that are heavily dependent on China - electrical machinery, mechanical appliances, organic chemicals, plastics and surgical instruments - that make up about 28% of India's import basket could be the mostly affected ones due to this potential shutdown. Next, the paper will present some of the indicative measures to revive the economy and rejuvenate the affected sectors. Protection of workers at the workplace must be given utmost priority followed by adapting to new work arrangements such as work-from-home (WFH). This will be followed by measures to stimulate the economy and labour demand by making and implementing active fiscal policy. Making expenditure on purchasing domestic goods and services will be the best way to push the economy. As a matter of fact, it is now may be required to evaluate on what can be produced here (in India) and give a deliberate thought to it towards implanting the same. Further, India will be at advantage by having domestically based and well established 'pharma industry'. This sector may act as 'catalyst sector' towards economic growth of the country.

Targeting impaired nutrient sensing with repurposed therapeutics to prevent or treat age-related cognitive decline and dementia: A systematic review.

BACKGROUND: Dementia is a debilitating syndrome that significantly impacts individuals over the age of 65 years. There are currently no disease-modifying treatments for dementia. Impairment of nutrient sensing pathways has been implicated in the pathogenesis of dementia, and may offer a novel treatment approach for dementia. AIMS: This systematic review collates all available evidence for Food and Drug Administration (FDA)-approved therapeutics that modify nutrient sensing in the context of preventing cognitive decline or improving cognition in ageing, mild cognitive impairment (MCI), and dementia populations. METHODS: PubMed, Embase and Web of Science databases were searched using key search terms focusing on available therapeutics such as 'metformin', 'GLP1', 'insulin' and the dementias including 'Alzheimer's disease' and 'Parkinson's disease'. Articles were screened using Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia). The risk of bias was assessed using the Cochrane Risk of Bias tool v 2.0 for human studies and SYRCLE's risk of bias tool for animal studies. RESULTS: Out of 2619 articles, 114 were included describing 31 different 'modulation of nutrient sensing pathway' therapeutics, 13 of which specifically were utilized in human interventional trials for normal ageing or dementia. Growth hormone secretagogues improved cognitive outcomes in human mild cognitive impairment, and potentially normal ageing populations. In animals, all investigated therapeutic classes exhibited some cognitive benefits in dementia models. While the risk of bias was relatively low in human studies, this risk in animal studies was largely unclear. CONCLUSIONS: Modulation of nutrient sensing pathway therapeutics, particularly growth hormone secretagogues, have the potential to improve cognitive outcomes. Overall, there is a clear lack of translation from animal models to human populations.