The current COVID-19 pandemic is one of the most devastating events in recent history. The virus causes relatively minor damage to young, healthy populations, imposing life-threatening danger to the elderly and people with diseases of chronic inflammation. Therefore, if we could reduce the risk for vulnerable populations, it would make the COVID-19 pandemic more similar to other typical outbreaks. Children don’t suffer from COVID-19 as much as their grandparents and have a much higher melatonin level. Bats are nocturnal animals possessing high levels of melatonin, which may contribute to their high anti-viral resistance. Viruses induce an explosion of inflammatory cytokines and reactive oxygen species, and melatonin is the best natural antioxidant that is lost with age. The programmed cell death coronaviruses cause, which can result in significant lung damage, is also inhibited by melatonin. Coronavirus causes inflammation in the lungs which requires inflammasome activity. Melatonin blocks these inflammasomes. General immunity is impaired by anxiety and sleep deprivation. Melatonin improves sleep habits, reduces anxiety and stimulates immunity. Fibrosis may be the most dangerous complication after COVID-19. Melatonin is known to prevent fibrosis. Mechanical ventilation may be necessary but yet imposes risks due to oxidative stress, which can be reduced by melatonin. Thus, by using the safe over-the-counter drug melatonin, we may be immediately able to prevent the development of severe disease symptoms in coronavirus patients, reduce the severity of their symptoms, and/or reduce the immuno-pathology of coronavirus infection on patients’ health after the active phase of the infection is over.

The global pandemic caused by the new SARS-COV-2 coronavirus makes it necessary to search for drugs for its control. Within of this research it has been known that the ivermectin drug, a FDA-approved drugs which is formulated as an 80:20 mixture of ivermectin B1a and B1b and used commonly for parasitic infections, has an inhibitory effect on viruses, includes SARS-COV-2 at in vitro level. In the particular case of SARS-COV-2 its mechanism of action remains elusive and controversial. Interestingly, the energy of interaction of ivermectin with any of the proteins the SARS-CoV-2 and the possible structural alterations at the protein level that this drug can cause have not been reported. In this sense, we carried out a bioinformatics study with docking strategies and molecular dynamics to predict the binding and disturbance induced by ivermectin in proteins associated with SARS-CoV-2. We use DockThor and Molegro docking scores. The DockThor server and myPresto software were used to build complexes and dynamics studies, respectively. The results obtained suggested that ivermectin is capable of docking with the 3CL protease and the HR2 domain, and may promote structural changes in these proteins by inducing unfolding/folding. Specifically, ivermectin brings protease to a significantly more deployed conformational state and the HR2 domain to a more compact state compared to the native state. Finally, it is shown that B1a and B1b macrocyclic lactones have a behavior different from to each target protein. These results suggest a possible inhibitory effect against SARS-CoV-2 due to a synergistic role of this drug to spontaneously bind to two important proteins involve in the proliferation of this virus. However, more studies are required on this possible mechanism of action.

An outbreak of a pandemic COVID-19 disease caused by a novel coronavirus SARS-CoV-2 has posed a serious threat to human health and the economy of the whole world. Bangladesh is one of the most densely populated countries in the world, which has also come under the attack of this viral disease. This perspective report aimed to describe the responses of Bangladesh to tackle the COVID-19, particularly on how Bangladesh is dealing with this novel viral disease with limited resources. The first case of a COVID-19 patient was detected in Bangladesh on March 8, 2020. Since then, a total of 2,144 peoples are officially reported as COVID-19 infected with 84 deaths. To combat the COVID-19, the government has taken various steps to tackle the epidemic outbreak of it such as diagnosis of the suspected cases, quarantine of doubted people and isolation of infected patients, local or regional lockdown, grant general leave from all offices for staying home of people, increase public awareness and enforce social distancing and so on. In addition, to address the socio-economic situations, the government announced several financial stimulus packages of about USD 11.17 billion. However, very limited diagnostic facilities, health workers, resources such as hospital beds, personal protective equipment, intensive care unit, and ventilators in the hospitals along with limited public unawareness are the major challenges for Bangladesh to tackle the situation effectively. This report described the responses of Bangladesh to tackle the COVID-19 and discusses prevailing challenges to mitigate this highly contagious disease with limited resources.

Sports video analysis is an interesting and emerging field in the domain of computer vision. It has become a very popular subject among scholars all over the world in the last decade due to the need of automated classification of events such as offsides, in/out situations, goals and so on. The most important problem in sports video analysis is detection and tracking of ball and players. Extraction of court lines is also another important problem since it is necessary in the classification of aforementioned events. In this study, considering some of the previous work on the subject, we develop a method for tracking the ball and players in tennis videos where the camera position and orientation is supposed fixed.

A novel coronavirus (SARS-CoV-2) that is initially found to trigger human severe respiratory illness in Wuhan City of China in 2019, has killed 2,718 people in China by February 26, 2020, and which has been recognized as a public health emergency of international concern as well. And the virus has spread to more than 38 countries around the world. However, the drug has not yet been officially licensed or approved to treat SARS-Cov-2 infection. NSP12-NSP7-NSP8 complex of SARS-CoV-2, essential for viral replication and transcription, is generally regarded as a potential target to fight against the virus. According to the NSP12-NSP7-NSP8 complex (PDB ID: 6NUR) structure of SARS, two homologous models were established for virtual screening in the present study, namely NSP12-NSP7 interface model and NSP12-NSP8 interface model. Seven compounds (Saquinavir, Tipranavir, Lonafarnib, Tegobuvir, Olysio, Filibuvir, and Cepharanthine) were selected for binding free energy calculations based on virtual screening and docking scores. All seven compounds can combine well with NSP12-NSP7-NSP8 in the homologous model, providing drug candidates for the treatment and prevention of SARS-CoV-2.

The paper demonstrates the analysis of Corona Virus Disease based on a probabilistic model. It involves a technique for classification and prediction by recognizing typical and diagnostically most important CT images features relating to Corona Virus. The main contributions of the research include predicting the probability of recurrences in no recurrence (first time detection) cases at applying our proposed approach for feature extraction. The combination of the conventional statistical and machine learning tools is applied for feature extraction from CT images through four images filters in combination with proposed composite hybrid feature extraction (CHFS). The selected features were classified by the stack hybrid classification system(SHC). Experimental study with real data demonstrates the feasibility and potential of the proposed approach for the said cause.

Interfaces between layers in 3D-printed elements produced by extrusion-based material deposition were investigated on both macro- and micro-scales. On the macro-scale, compression and bend tests were performed on two 3D-printable cement-based compositions (3PCs), namely C1 and C2. The influences of binder composition and time interval between layers on layer-interface strength were critically analyzed. In the context of additive manufacturing, the optimized composition C2, containing pozzolanic additives, exhibited mechanical performance superior to that of the mixture with Portland cement as the sole binder. In particular, Mixture C2 showed a less pronounced decrease in interface tensile strength. Even for time intervals between depositions of two layers as long as 1 day the loss in corresponding flexural strength was below 25%, as compared with C2 specimens tested in the perpendicular direction. In contrast, the decrease in flexural strength measured for C1 specimens amounted to over 90% for the same set of parameters. Higher porosity at the interfaces of the printed concrete layers was identified as the cause for the lower interface strengths of C1. Microscopic observations supported the findings of the macroscopic investigations. While a pronounced recovery (“self-healing”) of the porous, discontinuous interlayers was observed with increasing age for Mixture C2, in case of C1 the filling products grown in the porous interlayer were found to be non-strengthening.

We applied a generalized SEIR epidemiological model to the recent SARS-CoV-2 outbreak in the world, with a focus on Italy and its Lombardia, Piemonte, and Veneto regions. We focus on the application of a stochastic approach in fitting the model numerous parameters using a Particle Swarm Optimization (PSO) solver, to improve the reliability of predictions in the medium term (30 days). We analyze the official data and the predicted evolution of the epidemic in the Italian regions, and we compare the results with data and predictions of Spain and South Korea. We link the model equations to the changes in people’s mobility, with reference to Google’s COVID-19 Community Mobility Reports. We discuss the effectiveness of policies taken by different regions and countries and how they have an impact on past and future infection scenarios.

SARS-CoV-2 or COVID-19, a new seventh human corona virus, has out-broken in Wuhan, China since 31^st December 2019, and quickly escalated to take the form of pandemic which killed many human beings throughout almost all countries across continents. The rapidity of its transmission from human to human is far greater than all previous human corona viruses which came into existence like SARS-CoV, MERS-CoV, etc. The nucleotide sequence of SARS-CoV-2 (isolates Wuhan-Hu-1) is 29,875 bp in ss-RNA. Symptoms of SARS-CoV-2 infected pneumonia include from asymptomatic to high fever and/or respiratory illnesses. Coronavirus virion (spherical/round /elliptical in shape) consists of three parts- outer membrane or envelope, nucleocapsid and genome (RNA). SARS-CoV-2 was shown to use receptor, angiotensin converting enzyme 2 (ACE2) for attachment to the cells through its surface spike (S) protein (S1), and the virion enters into the host cell through two routes- direct membrane fusion and endocytotic pathway. The RNA of SARS-CoV acts directly as mRNA and here minus(-) 1 programmed ribosomal frameshift (-1PRF) is being operated by slippery sequence and pseudoknot, so it translates 16 nonstructural proteins including RNA dependent RNA replicase. Then genomic RNA replicated continuously on – strand RNA template and subgenomic RNA transcribed discontinuously on –RNA template to sgmRNA. Subgenomic RNAs/sgmRNAs synthesize all structural proteins. This article takes into consideration the details of established theories of viral structure, viral attachment, mode of entry into human cells, different models of replication and transcription of virus genome proposed by eminent scientists over the years, and makes an in depth examination highlighting meaningful points or important target cites of viral propagation or synthesis, which are conserved, for prompt development of potent drugs or vaccine to counter COVID-19 for which human race is anxiously and eagerly waiting.

The IoT Internet of Things being a promising technology of the future. It is expected to connect billions of devices. The increased communication number is expected to generate data mountain and the data security can be a threat. The devices in the architecture are fundamentally smaller in size and low powered. In general, classical encryption algorithms are computationally expensive and this due to their complexity and needs numerous rounds for encrypting, basically wasting the constrained energy of the gadgets. Less complex algorithm, though, may compromise the desired integrity. In this paper we apply a lightweight encryption algorithm named as Secure IoT (SIT) to a quantized speech image for Secure IoT. It is a 64-bit block cipher and requires 64-bit key to encrypt the data. This quantized speech image is constructed by first quantizing a speech signal and then splitting the quantized signal into frames. Then each of these frames is transposed for obtaining the different columns of this quantized speech image. Simulations result shows the algorithm provides substantial security in just five encryption rounds.

This paper presents tea leaves moisture monitoring system based on RF reflectometry techniques. The system was divided into two parts which are the sensor and reflectometer parts. The large coaxial probe was used as a sensor of the system. The reflectometer part plays a role as signal generator and also data acquisition. The reflectometer-sensor system was operated with a graphical user interface at 1.529 GHz at room temperature. The system was able to measure the moisture content of tea leaves ranging 0% m.c to 50% m.c on a wet basis. In this study, up to five kinds of tea leaves bulk were tested. The mean of absolute errors in the moisture measurement for tea leaves was ±2.

The SARS-CoV-2 was confirmed to cause the regional outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China. The 3C-like protease (3CL^pro), an essential enzyme for viral replication, is a valid target to compacts SARS-CoV and MERS-CoV. In this research, an integrated library consisting of 1000 compounds from Asinex Focused Covalent (AFCL) library and 16 FDA-approved protease inhibitors were screened against SARS-CoV-2 3CL^pro. Top compounds with significant docking scores and making stable interactions with catalytic dyad residues were obtained. The screening results in identification of compound 621 from AFCL library as well as Paritaprevir and Simeprevir from FDA-approved protease inhibitors as potential inhibitors of SARS-CoV-2 3CL^pro. The mechanism and dynamic stability of binding between the identified compounds and SARS-CoV-2 3CL^pro were characterized using 50 nanoseconds (ns) molecular dynamic (MD) simulation approach. The identified compounds are potential inhibitors worthy of further development as SARS-CoV-2 3CLpro inhibitors/drugs. Importantly, the identified FDA-approved therapeutics could be ready for clinical trials to treat infected patients and help to curb the COVID-19.

To date, viral RNA detection is almost the only way to confirm SARS-CoV-2infectionin practice.However, variousreasons can cause low sensitivity for RNA detection, and thisposes aserious challenge to disease control. We tested the performance of detecting total antibody(Ab) and IgM levels in serum by the methods of chemiluminescence, enzyme-linked immunosorbent assay (ELISA), and colloidal golddetection. The datashowed that the sensitivity and specificity for detecting total Ab and IgM levels were high by all three methods, and the sensitivity was higher for detecting total Ab than for detecting IgM. Evidence from studieshas shown thatviral RNA testingcombinedwith serological testing could increase the diagnostic sensitivity while maintaining a high specificity. Specific serology testsfor SARS-CoV-2 havegreat value for clinical practice and public health.

The software industry has adopted component-based software development (CBSD) to rapidly build and deploy large and complex software systems with significant savings at minimal engineering effort, cost, and time. However, CBSD encounters issues on security trust, mainly with respect to dependability attributes. A system is considered dependable when it can produce the outputs for which it was designed with no adverse effect on its intended environment. Dependability consists of several attributes that imply availability, confidentiality, integrity, reliability, safety, and maintainability. Dependability attributes must be embedded in a CBSD model to develop dependable component software. Motivated by the importance of these attributes, this paper pursues two objectives: to design a model for developing a dependable system that mitigates the vulnerabilities of software components, and to evaluate the proposed model. The model proposed in this study is labelled as developing dependable component-based software (2DCBS). To develop this model, the CBSD architectural phases and processes must be framed and the six dependability attributes embedded according to the best practice method. The expert opinion approach was applied to evaluate 2DCBS framing. In addition, the 2DCBS model was applied to the development of an information communication technology (ICT) portal through an empirical study method. Vulnerability assessment tools (VATs) were employed to verify the dependability attributes of the developed ICT portal. Results show that the 2DCBS model can be adopted to develop web application systems and to mitigate the vulnerabilities of the developed systems. This study contributes to CBSD and facilitates the specification and evaluation of dependability attributes throughout model development. Furthermore, the reliability of the dependable model can increase confidence in the use of CBSD for industries.

A comprehensive kinetic model of the Fischer-Tropsch synthesis (FTS) is developed in a fixed bed reactor under operating conditions (temperature, 230–235°C, pressure, 20–25 bar, gas hourly space velocity, 4000–5000 cm³(STP)/h/g_catalyst ,H₂/CO feed molar ratio, 2.1) over a Co based catalyst. Reaction rate equations based on Eley-Rideal (ER) type model for initiation step and Langmuir-Hinshelwood-Hougen-Watson (LHHW) type model for propagation and termination steps of the FTS reactions have been considered and the readsorption of olefins were taken into account. The model that was reported in the literature was modified in order to explain many significant deviations from the ASF distribution. Optimum parameters have been obtained by Genetic Algorithms (GA). The calculated activation energies to produce n-paraffins and 1-olefins were in the range of 82.24 to 90.68 kJ/mol and 100.66 to 105.24 kJ/mol, respectively. The hydrocarbon distribution in FTS reactions was satisfactorily predicted particularly for paraffins.

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become the chief concern of the international community in almost no time. As of May 9th, 2021, more than 150 million cases and 3.2 million deaths have been recorded. Considering the early struggle in treating COVID-19 patients, the researchers and clinicians have decided to try the previously available drugs according to their mechanisms of action. Hence, many antivirals, antibiotics, antiparasitics, and antipyretics have been proposed. Pregnant women, fetuses, and infants are known high-risk populations that are threatened during disease outbreaks. Therefore, this article reviews the safety of potential drugs for COVID-19 patients during pregnancy and breastfeeding.

Dayaoshan, as an important metal ore producing area in China, is faced with the dilemma of resource depletion due to long-term exploitation. In this paper, remote sensing method is used to circle the favorable metallogenic areas and find new ore points for Gulong. Firstly, vegetation interference bas been removed by using mixed pixel decomposition method with hyperplane and genetic algorithm (GA) optimization; then, altered mineral distribution information has been extracted based on principal component analysis (PCA) and support vector machine (SVM) method; Thirdly, the favorable areas of gold mining in Gulong has been delineated by using ant colony algorithm (ACA) optimization SVM model to remove false altered minerals; Lastly, field survey verified that the extracted alteration mineralization information is correct and effective. The results show that the mineral alteration extraction method proposed in this paper has certain guiding significance for metallogenic prediction by remote sensing.

New coronavirus (SARS-CoV-2) treatments and vaccines are under development to combat the COVID-19 disease. Several approaches are being used by scientists for investigation including 1) various small molecule approaches targeting RNA polymerase, 3C-like protease, and RNA endonuclease and 2) exploration of antibodies obtained from convalescent plasma from patients who have recovered from COVID-19. The coronavirus genome is highly prone to mutations that lead to genetic drift and escape from immune recognition; thus, it is imperative that sub-strains with different mutations are also accounted for during vaccine development. As the disease has grown to become a pandemic, new B-cell and T-cell epitopes predicted from SARS coronavirus have been reported. Using the epitope information along with variants of the virus, we have found several variants which might cause drifts. Among such variants, 23403A>G variant (p.D614G) in spike protein B-cell epitope is observed frequently in European countries such as the Netherlands, Switzerland and France.

One notable features of the SARS-CoV-2 genome is that the spike protein of SARS-CoV-2 has a functional polybasic (furin) cleavage site (RRAR) at the S1–S2 boundary through the insertion of 12 nucleotides encoding PRRA. To date, the furin cleavage site (FCS) remains an experimentally uncharted territory both structurally and functionally. For instance, whether or not FCS is actually cleaved, before or after viral cell entry or exit, still remains to be experimentally investigated. With currently available structural data, this article presents a computational structural characterization of the FCS inserted into SARS-CoV-2 spike glycoprotein, and puts forward a set of structural hypothesis against the hypothesis of SARS-CoV-2 from purposeful manipulation: (1), the inserted FCS does not alter, neither stabilize nor de-stabilize, the overall structure of SARS-CoV-2 spike glycoprotein; (2), the net structural consequence of FCS is the insertion of a furin cleavage site into SARS-CoV-2 spike glycoprotein, whose S1 and S2 subunits will still be bonded together even if the FCS is actually cleaved by furin protease.

In 2019, Chinese government implemented the first round of National Centralized Drug Procurement (NCDP) pilot (so-called "4+7" policy) in mainland China, achieved a prominent price reduction of 52% on average for 25 bidding winning products. Under cross-price elasticity theory, the price behavior of pharmaceutical enterprises for policy-related drugs might change. This study used drug purchasing data from the Centralized Drug Procurement Survey in Shenzhen 2019, and applied single-group Interruption Time Series (ITS) design to examine the impact of "4+7" policy on the drug price index (DPI) of policy-related drugs. The ITS analysis showed that the DPI of winning (-0.183 per month, p<0.0001) and non-winning (-0.034 per month, p=0.046) products significantly decreased after the implementation of "4+7" policy. No significant difference was found for the immediate change of DPI for alternative drugs (p=0.537), while a significant decrease in change trend was detected in the post-"4+7" policy period (-0.003 per month, p=0.014). The DPI of the overall policy-related drugs significantly decreased (-0.261 per month, p<0.0001) after "4+7" policy. These findings indicate that the price behavior of pharmaceutical enterprises changed under NCDP policy, while the price linkage effect is still limited. It is necessary to further expand the scope of centralized purchased drugs and strengthen the monitoring of related drugs regarding price change and consumption structure.

The world is facing a major health crisis, the global pandemic of COVID-19 caused by the SARS-CoV-2 coronavirus, for which no approved antiviral agents or vaccines are currently available. Here we describe a collection of codon-optimized coding sequences for SARS-CoV-2 cloned into Gateway-compatible entry vectors, which enable rapid transfer into a variety of expression and tagging vectors. The collection is freely available via Addgene. We hope that widespread availability of this SARS-CoV-2 resource will enable many subsequent molecular studies to better understand the viral life cycle and how to block it.

The abundant mechanical vibration energy in bridge road environment can be converted into electric energy by using the piezoelectric energy harvest technology, which could be an efficient way to provide energy required by the wireless sensor network in the bridge condition monitoring system. An autonomous energy harvesting system has been designed based on cantilever beams for sensing and acquiring the bridge vibration energy. After the analysis of the dynamic properties of the piezoelectric cantilever beam in the energy conversion, three kinds of interface circuits were compared through simulation and experimental results. It was shown that the VD interface circuit has less power loss. Furthermore, the proposed closed loop control method based on the VD circuit was simple, adaptive, and self-powered, which is suitable for the road energy harvesting application. Finally, the energy harvesting system based on VD circuit was realized with harvested power of around 0.8mW.

This study investigated the neuroprotective effects of methyl 3,4-dihydroxybenzoate (MDHB) against t-butylhydroperoxide(TBHP) induced oxidative damage in SH-SY5Y (human neuroblastoma cells) and the underlying mechanisms. SH-SY5Y were cultured in DMEM+10% FBS for 24 hours and pretreated with different concentrations of MDHB or N-acetyl-L-cysteine (NAC) for 4 hours prior to the addition of 40 μM TBHP for 24 hours. Cell viability was analyzed using the methyl thiazolyl tetrazolium (MTT) and lactate dehydrogenase (LDH) assays. An annexin V-FITC assay was used to detect cell apoptosis rate. The 2',7'-dichlorofluorescin diacetate (DCFH-DA) assay was used to determine intracellular ROS levels. The activities of antioxidative enzymes (GSH-Px and SOD) were measured using commercially available kits. The oxidative DNA damage marker 8-OHdG was detected using ELISA. Western blotting was used to determine the expression of Bcl-2, Bax, caspase 3, p-Akt and Akt proteins in treated SH-SY5Y cells. Our results showed that MDHB is an effective neuroprotective compound that can mitigate oxidative stress and inhibit apoptosis in SH-SY5Y cells

People often say that beer tastes better from a bottle than from a can. However, one can ask whether this perceived difference is reliable across consumers; And, if so, whether it is purely a psychological phenomenon (associated with the influence of packaging on taste perception), or whether instead it reflects some more mundane physico-chemical interaction between the packaging material (or packing procedure/process) and the contents. We conducted two experiments in order to address these important questions. In the main experiment, 151 participants at the 2016 Edinburgh Science Festival were served a beer in a plastic cup. The beer was either poured from a bottle or can (i.e., a between-participants experimental design was used) and the participants were encouraged to pick up the packaging in order to inspect the label before tasting the beer. The participants rated the perceived taste, quality, and freshness of the beer, as well as their likelihood of purchase, and their estimate of the price. All of the beer came from the same batch (from Barney’s Brewery in Edinburgh). Nevertheless, those who evaluated the bottled beer rated it as tasting better than those who rated the beer that had been served from a can. Having demonstrated such a perceptual difference in terms of taste, we then went on to investigate whether people would prefer one packaging format over the other when the beer from bottle and can was served to a new group of participants blind (i.e., when the participants did not know the packaging material). The participants in this control study (N = 29) were asked which beer they preferred or else could state that the two samples tasted the same. No sign of preference was obtained under such conditions. Explanations for the psychological impact of the packaging format, in terms of differences in packaging weight (between tin and glass), and/or prior associations of quality with specific packaging materials/formats (what some have chosen to call ‘image molds’) are discussed.

There is a relatively high risk of virus transmission in dental procedures and oropharyngeal examinations. We investigated the effects of mouthwashes on covid-19 viral load reduction during dental practices and oro-pharyngeal assessments. We performed a systematic search in PubMed, EMBASE, Scopus, Web of Science, Cochrane library for relevant studies up to February 2021. Papers evaluating patients with covid-19 infection (patients) who rinse mouthwashes (intervention) compared to patients who don’t rinse them (comparison) for reducing covid-19 viral load or reducing cross-infection of covid-19 (outcome) in the randomized and non-randomized clinical trial and quasi-experimental studies (study) were included due to PICOS question. Three independent authors conducted literature screening and data extraction. We extracted the most relevant data and we evaluated the risk of bias from the included studies. Out of 344 potentially eligible articles, six studies were included in this systematic review. Regarding viral load and negative cycle threshold (ct) values, 1% PVP_I and Listerine mouthwash were effective. 0.12% CHX mouthwash was effective 0-2 hours post rinsing, but it was not effective after 2 hours. A mixture solution of 0.2% Chlorhexidine gluconate and 6% Hydrogen peroxide was effective on day 5 of intervention. Gargling 1% hydrogen peroxide, 0.075% Cetylpiridinum Chloride (CPC), 0.5%PVP-I and 0.2% CHX mouthwashes was not effective on SARS-COV-2. It cannot be guaranteed that rinsing a specific kind of mouthwash prevents cross-infection of covid-19; however, the viral load of SARS-COV-2 in saliva will be decreased after rinsing mouthwashes containing 1%PVP-I and Listerine.

The Coronavirus Disease 2019 (COVID-19) is a new viral infection caused by the severe acute respiratory coronavirus 2 (SARS-CoV-2). Genomic analyses have revealed that SARS-CoV-2 is related to Pangolin and Bat coronaviruses. In this report, a structural comparison between the Sars-CoV-2 Envelope and Membrane proteins from different human isolates with homologous proteins from closely related viruses is described. The analyses here reported show the high structural similarity of Envelope and Membrane proteins to the counterparts from Pangolin and Bat coronavirus isolates. However, the comparisons have also highlighted structural differences specific of Sars-CoV-2 proteins which may be correlated to the cross-species transmission and/or to the properties of the virus. Structural modelling has been applied to map the variant sites onto the predicted three-dimensional structure of the Envelope and Membrane proteins.

The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. On the one hand, blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. On the other hand, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature. First, we introduce a new conceptual architecture which integrates blockchain and AI specific for COVID-19 fighting. Particularly, we highlight the key solutions that blockchain and AI can provide to combat the COVID-19 outbreak. Then, we survey the latest research efforts on the use of blockchain and AI for COVID-19 fighting in a wide range of applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.

Smoking is a risk factor for respiratory infections and there is reasonable concern that it may affect COVID-19 susceptibility and severity. Recent studies have focused on the interaction between smoking (and nicotine) and ACE2 expression, suggesting that ACE2 up-regulation could contribute to enhanced viral cell entry. However, case series have shown that there is an unexpectedly low prevalence of smoking among hospitalized COVID-19 cases. Since early April, we were the first to hypothesize that dysfunction of the nicotinic cholinergic system (NCS) may be implicated in the pathophysiology of severe COVID-19. We recently reported that many of the clinical manifestations of severe COVID-19 could be explained by dysregulation of the NCS. In this study, we present an amino acid sequence in the receptor binding domain of the SARS-CoV-2 Spike glycoprotein which is homologous to a sequence of a snake venom toxin. We present the 3D structural location of this “toxin-like” sequence on the Spike Glycoprotein. These findings suggest that SARS-CoV-2 could potentially interact with acetylcholine receptors causing dysregulation of the NCS and the cholinergic anti-inflammatory pathway.

The novel coronavirus (SARS-CoV-2) is a human pathogen recently emerged in China, causing a global pandemic of severe respiratory illness (COVID19). SARS-CoV-2 makes entry into human cells through its spike (S) protein that binds to cell surface receptors. Widespread of SARS-CoV-2 has been attributed to high affinity of S protein to its receptor. A homology model of the receptor binding domain of SARS-CoV-2 S protein (RBD) was built. RBD- receptor docking and published molecular dynamics data were used to map the key RBD-receptor interaction hotspot (RBDhp) on the RBD. Primary virtual screening was carried out against RBDhp using more than 3300 compounds approved by U.S Food and Drug Administration (FDA) and other authorities for human use. Compounds that bind to hpRBD with a binding energy ≤ - 6.5 kcal/mol were subjected to secondary screening using a recently published cryo EM (2.9 Å) structure of RBD. A cardiac glycoside (dgitoxin), two anthracyclines (zorubicin and aclarubicin), a tetracycline derivative (rolitetracycline), a cephalosporin (cefoperazone) and a food dye (E-155) were predicted to be most potent inhibitors of RBD – receptor interaction. An anti-asthmatic drug (zafirlukast) and several other drugs (itrazol, fazadinium, troglitazone, gliquidone, Idarubicin, Oxacillin) were found to be high affinity binders that may have a potential to inhibit RBD – receptor interaction.

The endoplasmic reticulum (ER) comprises a network of tubules and vesicles that constitutes the largest organelle of the eukaryotic cell. Being the location where most proteins are synthesized and folded, it is crucial for the upkeep of cellular homeostasis. In addition, it is the largest ionic calcium reservoir in cells, tightly regulating the levels of this second messenger according to cellular necessities. Disturbed ER homeostasis triggers the activation of an intricate and conserved molecular machinery, termed the unfolded protein response (UPR). Given the impact of this signaling network upon an extensive list of cellular processes, ER stress is involved in the onset and progression of multiple diseases, including cancer and neurodegenerative disorders. There is, for this reason, an increasing number of publications focused on characterizing and/or modulating ER stress, which have resulted in a wide array of techniques employed to study ER-related molecular events. This review aims to sum up the tools available design a study of this nature.

This paper is purposed to delineate the current situation around Bangladesh as well as impacts of Coronavirus Disease-2019 (COVID-19) around the country and how the people over here are encountering this threatening pandemic. COVID-19 is an international epidemic that has got rapid wide-spread throughout different countries of the world to date. After its first outbreak in China different continents started to make sense and get aware against COVID-19 though, due to its special strategy of transmission several countries have been quite deteriorated preventing it. All the countries are moving at their best forward to find out any solution so that whole world could get rid of this horrifying situation as soon as possible. The authors here have reported an overview of how the outbreak of COVID-19 had put its commence in Bangladesh and to date how people over here have been tracing the way to tackle this havoc. Also, the changes that have brought around due to the crisis have offered us some fertile lessons that are enunciated here by the authors. To conclude, special considerations are anticipated to be highlighted pertaining COVID-19 outbreak in Bangladesh.

There is an urgent need to advance safe and affordable COVID-19 vaccines for low- and middle-income countries of Asia, Africa and Latin America. Such vaccines rely on proven technologies such as recombinant protein-based vaccines to facilitate its transfer for emerging market vaccine manufacturers. Our group is developing a two-pronged approach to advance recombinant protein-based vaccines to prevent COVID-19 caused by SARS CoV2 and other coronavirus infections. One vaccine is based on a yeast-derived (Pichia pastoris) recombinant protein comprised of the receptor binding domain (RBD) of the SARS-CoV formulated on alum and referred to as the CoV RBD219-N1 Vaccine. Potentially this vaccine could be used as a heterologous vaccine against COVID-19. A second vaccine specific for COVID-19 is also being advanced using the corresponding RBD of SARS-CoV-2. The first antigen has already undergone cGMP manufacture and is therefore “shovel ready” for advancing into clinical trials, following vialing and required GLP toxicology testing. Evidence for its potential efficacy to cross-protect against SARS-CoV-2 includes cross-neutralization and binding studies using polyclonal and monoclonal antibodies. Evidence in support of its safety profile include our internal assessments in a mouse challenge model using a lethal mouse adapted SARS strain, which show that SARS-CoV RBD 291N1 (when adsorbed to Alhydrogel®) does not elicit eosinophilic lung pathology. Together these findings suggest that recombinant protein-based vaccines based on the RBD warrant further development to prevent SARS, COVID-19 or other coronaviruses of pandemic potential.

Since the outbreak of the COVID-19 (Coronavirus Disease 19) pandemic, researchers have been trying to investigate several active compounds found in plants that have the potential to inhibit the proliferation of SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2). The present study aimed to evaluate bioactive compounds found in plants by using a molecular docking approach to inhibit the Main Protease (M^pro) and Spike (S) glycoprotein of SARS-CoV-2. The evaluation was performed on the docking scores calculated using AutoDock Vina as a docking engine. A rule of five (RO5) was calculated to determine whether a compound meets the criteria as an active drug orally in humans. The determination of the docking score was done by selecting the best conformation of the protein-ligand complex that had the highest affinity (most negative Gibbs' free energy of binding / ΔG). As a comparison, nelfinavir (an antiretroviral drug), chloroquine and hydroxychloroquine sulfate (anti-malarial drugs recommended by the FDA as emergency drugs) were used. The results showed that hesperidin, nabiximols, pectolinarin, epigallocatechin gallate, and rhoifolin had better poses than nelfinavir, chloroquine, and hydroxychloroquine sulfate as spike glycoprotein inhibitors. Hesperidin, rhoifolin, pectolinarin, and nabiximols had about the same pose as nelfinavir, but were better than chloroquine and hydroxychloroquine sulfate as M^pro inhibitors. These plant compounds have the potential to be developed as specific therapeutic agents against COVID-19. Several natural compounds of plants evaluated in this study showed better binding free energy compared to nelfinavir, chloroquine, and hydroxychloroquine sulfate which so far are recommended in the treatment of COVID-19. As judged by the RO5 and previous study by others, the compounds kaempferol, herbacetin, eugenol, and 6-shogaol have good oral bioavailability, so they are also seen as promising candidates for the development lead compounds to treat infections caused by SARS-CoV-2.

Decisions affecting the COVID-19 pandemic, by the individual and those with highest authority, are being made on the basis of unreliable data. Data about cases and deaths are collected daily but represent only a sample of reality. Statistics convert sample data into more reliable estimates. However, statistics have no magical powers; reliability requires dependable data. It is futile to rail against this darkness; COVID-19 is not a scientific experiment. However, we must do better both with data collection and data analysis. In this review, I focus on one element of the data, the asymptomatic case of COVID-19. Without reliable information about this number, decision makers are significantly blinded. By its nature, the asymptomatic case is hidden but contaminating to understanding COVID-19. The true case rate and death rate per case are unknowable without knowing the fraction of cases that are asymptomatic. The best estimate of asymptomatic cases is in the CDC document: COVID-19 Pandemic Planning Scenarios. For four different scenarios the estimates range from 10% to 70%, with the best estimate of 40% for asymptomatic cases. However, even the definition of the asymptomatic case is problematic. In simplest terms, two elements are required: an infection and no symptoms. How is “no symptoms” to be usefully defined? It appears to be analogous to pontificating about black swans from studying only white swans. It implies infection, but how is infection defined? Is it presence of the virus, replication of the virus, or presence of antibodies? Is asymptomatic disease an oxymoron? Without extensive, purposeful screening for specifically defined, essential symptoms and appropriate virus and antibody testing over time, the class of asymptomatic cases remains unknown. Current estimates range from <20% to ˃80%. If low, it can be ignored; if high, it dramatically and proportionately lowers the case rate and the death rate per case. Consequentially, the asymptomatic rate dramatically affects our societal and political responses. In this focused review, we assess the limitations of the published estimates, bring attention to the importance of obtaining accurate data, and exhort that high priority be given in the scientific community to understanding the issue, asymptomatic COVID-19 cases.

Deep Learning is a recent and important addition to the computational toolbox available for image reconstruction in fluorescence microscopy. We review state-of-the-art applications such as image restoration, super-resolution, and light-field imaging, and discuss how the latest Deep Learning research can be applied to other image reconstruction tasks such as structured illumination, spectral deconvolution, and sample stabilisation. Despite its successes, Deep Learning also poses significant challenges, has often misunderstood capabilities, and overlooked limits. We will address key questions, such as: What are the challenges in obtaining training data? Can we discover structures not present in the training data? And, what is the danger of inferring unsubstantiated image details?

Introduction: An epidemic of Coronavirus Disease 2019 (COVID-19) begun in December 2019 in China, causing a Public Health Emergency of International Concern. Among raised questions, clinical, laboratory, and imaging features have been partially characterized in some observational studies. No systematic reviews have been published on this matter. Methods: We performed a systematic literature review with meta-analysis, using three databases to assess clinical, laboratory, imaging features, and outcomes of COVID-19 confirmed cases. Observational studies, and also case reports, were included and analyzed separately. We performed a random-effects model meta-analysis to calculate the pooled prevalence and 95% confidence interval (95%CI). Results: 660 articles were retrieved (1/1/2020-2/23/2020). After screening by abstract/title, 27 articles were selected for full-text assessment. Of them, 19 were finally included for qualitative and quantitative analyses. Additionally, 39 case report articles were included and analyzed separately. For 656 patients, fever (88.7%, 95%CI 84.5-92.9%), cough (57.6%, 40.8-74.4%) and dyspnea (45.6%, 10.9-80.4%) were the most prevalent manifestations. Among the patients, 20.3% (95%CI 10.0-30.6%) required intensive care unit (ICU), with 32.8% presenting acute respiratory distress syndrome (ARDS) (95%CI 13.7-51.8), 6.2% (95%CI 3.1-9.3) with shock and 13.9% (95%CI 6.2-21.5%) of hospitalized patients with fatal outcomes (case fatality rate, CFR).Conclusion: COVID-19 brings a huge burden to healthcare facilities, especially in patients with comorbidities. ICU was required for approximately 20% of polymorbid, COVID-19 infected patients and this group was associated with a CFR of over 13%. As this virus spreads globally, countries need to urgently prepare human resources, infrastructure, and facilities to treat severe COVID-19.

In the face of the newly emergent COVID-19 pandemic, researchers around the world are racing to identify efficacious drugs capable of preventing or treating its infection. They are doing that by testing already available and approved antimicrobials for their rapid repurposing against COVID-19. Using the data emerging on the comparable efficacy of various compounds having different mechanisms of action and indications, I suggest in this report, their potential mechanistic convergence. Specifically, I highlight the lysosome as a key possible therapeutic target for COVID-19, proposing one of the lysosomal storage disorders, Niemann-Pick type C disease (NPC), as a prototypical condition with inherent resistance or an “unfavorable” host cell environment for viral propagation. The included reasoning evolves from previously generated data in NPC, along with the emerging data on COVID-19. The aim of this report is to suggest that pharmacological induction of a “transient” NPC-like lysosomal dysfunction, could hold answers for targeting the ongoing COVID-19 pandemic.

Rare earths are classified as most important and critical material for US economy and defense by Congress and a mandate has been set to increase their in-house production, domestic resource utilization and decrease reliance on foreign resources and reserves. They are widely available in earth crust as ore (bastnaesite (La, Ce)FCO₃, monazite, (Ce, La, Y, Th)PO₄, and xenotime, YPO₄), but their so-called economic reserves are sparsely located geographically. They may be produced by various means such as beneficiation (physical, chemical, mechanical, or electrical), reduction (direct or indirect), electrolysis (of aqueous or molten / fused single or mixed salt systems) at high temperature or hydrometallurgy. Out of these, direct reduction also known as metallothermic reduction (La and Ca reduction) is mostly utilized. Its variant, high temperature electrowinning of fused salts is also practiced widely. These processes are material and application specific. In this study, author will employ thermodynamics (Ellingham diagrams, free energy of formation, reduction potential, Nernst equation, Pourbaix (E_h-pH) diagrams, E-pO^-2 diagrams), kinetics and energetic of a chemical reaction (chemical metallurgy) to reduce rare earth oxide / salt to rare earth metals (REO/RES – REM). It is shown that materials and energy requirement vary greatly depending on type of mineral ore, production facility, and beneficiation / mineral processing method selected. Aim is to reduce dependence on coal deposits. It is anticipated this route will be able to produce rare earths with > 35% yield and > 98% purity which be described in subsequent studies and patents.

In the present work, the state of the art of the most common additive manufacturing (AM) technologies used for the manufacturing of complex shape structures of graphene-based ceramic nanocomposites, ceramic and graphene-based parts is explained. A brief overview of the AM processes for ceramic, which are grouped by the type of feedstock used in each technology, is presented. The main technical factors that affect the quality of the final product were reviewed. The AM processes used for 3D printing of graphene-based materials are described in more detail; moreover, some studies in a wide range of applications related to these AM techniques are cited. Furthermore, different feedstock formulations and their corresponding rheological behaviour were explained. Additionally, the most important works about the fabrication of composites using graphene-based ceramic pastes by Direct Ink Writing (DIW) are disclosed in detail and illustrated with representative examples. Various examples of the most relevant approaches for the manufacturing of graphene-based ceramic nanocomposites by DIW are provided.

SARS-CoV-2 (CoV-2) is a coronavirus which is causing the actual COVID-19 pandemic. The disease caused by 2019 new coronavirus (2019-nCoV) was named coronavirus disease-19 (COVID-19) by the World Health Organization in February 2020. Primary non-specific reported symptoms of 2019-nCoV infection at the prodromal phase are malaise, fever, and dry cough. The most commonly reported signs and symptoms are fever (98%), cough (76%), dyspnea (55%), and myalgia or fatigue (44%). Nonetheless, recent reports suggest an association between COVID-19 and altered olfactory and taste functions, although smell seems to be more affected than taste. These associations of smell and taste dysfunctions and CoV-2 are consistent with case reports describing a patient with SARS with long term anosmia after recovery from respiratory distress, with the observation that olfactory function is commonly altered after infection with endemic coronaviruses, and with data demonstrating that intentional experimental infection of humans with CoV-299 raises the thresholds at which odors can be detected. Post-viral anosmia and is one of the leading causes of loss of sense of smell in adults, accounting for up to 40% cases of anosmia. Viruses that give rise to the common cold are well known to cause post-infectious loss, and over 200 different viruses are known to cause upper respiratory tract infections. I reviewed the possible mechanisms of smell and taste loss in COVID-19. I concluded that since the existence of such a relationship is likely, it is highly recommended that those patients who experience complications such as smell and/or taste loss, even as unique symptoms, should be considered as potential SARS-CoV-2 virus carriers.

Cycling reliability is crucial for Si-based materials due to severe volume change during cycles that results in the fast capacity fading. Though the binder only occupies a very low amount of the total mass of anodes, it is proved to perform a key parameter to improve the cycle performance of Si-based anodes. Because they are eco-friendly and cost saving, water-based binders styrene-butadiene rubber (SBR) and carboxymethyl cellulose (CMC) are regarded as the better binder to substitute Poly (vinylidene difluoride) (PVDF) as the binder for Si-based anode. In this study, the anodes are fabricated by simply mixing the active materials (naso Si, graphite and conductive additive) together and using the mixture of SBR and CMC as a binder. The results showed that the retention capacities of the anodes are more than 440 mAh/g after 400 cycles. It indicates that it is an easy and simple way to make high performance anodes.

The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the world health organization declared it pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. In this urgency situation, development of SARS-CoV-2 based vaccines is immediately required. Immunoinformatic and molecular modelling are generally used time-efficient methods to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines is proved to be a promising immunization strategy against viruses and pathogens, which induce more comprehensive protective immunity. The current study demonstrated a comprehensive in-silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in-silico cloning in a known pET28a vector system also estimated the possibility of MVC expression in E. Coli. Despite this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can present to be a better prophylactic solution against COVID-19.

Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids.

Olive trees have been of economic and cultural value since pre-Roman times, and continue to dominate landscapes and agriculture in many mediterranean regions. Recent mass losses of olive trees in Southern Italy due to an exotic plant pathogen highlight the need for methods that to monitor the olive trees in a landscape or region operationally. Here, we develop a method for counting olive trees from aerial photographs and test it in areas with a high diversity of olive tree ages, sizes, and shapes. This heterogeneity complicates tree counting as centennial trees often have crowns that are split into multiple segments, resembling multiple crowns, while nearby crowns often form a semi-closed canopy comprising multiple trees. Comparisons with reference counts in two 20 ha sites and over three different years indicate the automated counts tend to be reasonably accurate (median error 13%, n = 6), but heavily influenced by a few olive orchards with particularly high planting densities and a relatively closed canopy in which distinguishing individual trees is challenging. Overall, the algorithm estimated tree densities well (counting 82 to 109 trees/ha versus 87 to 104 trees/ha in the reference counts), indicating the method is suitable to track the number of olive trees over large areas.

SARS-CoV-2, the novel coronavirus behind COVID-19 pandemic is acquiring new mutations in its genome. Although some mutations provide benefits to the virus against human immune response, a number of them may result in their reduced pathogenicity and virulence. By analyzing more than 3000 high-coverage, complete genome sequences deposited in the GISAID database, here I report a unique 28881-28883:GGG>AAC trinucleotide-bloc mutation in the SARS-CoV-2 genome that results in two sub-strains, described here as SARS-CoV-2g (28881-28883:GGG genotype) and SARS-CoV-2a (28881-28883:AAC genotype). Computational analysis and literature review suggest that this bloc mutation would bring 203-204:RG(arginine-glycine)>KR(lysine-arginine) amino acid changes in the nucleocapsid (N) protein affecting the SR (serine-arginine)-rich motif of the protein, a critical region for the transcription of viral RNA and replication of the virus. Thus, 28881-28883:GGG>AAC bloc-mutation is expected to modulate the pathogenicity of the SARS-CoV-2. Remarkably, SARS-CoV-2g and SARS-CoV-2a strains can be linked with the heterogeneity of COVID-19 cases across different regions within and between countries by analyzing existing data. Sequence analysis suggests that severely affected cities, such as Milan, Lombardy, New York, Paris have the predominant presence of SARS-CoV-2g strains, whereas less affected places like Abruzzo, Lyon, Valencia have a relatively higher presence of SARS-CoV-2a, an indication that the latter strain may contribute to the reduced cases of COVID-19. A similar relationship is observed when Netherlands, Portugal are compared with Spain, France and Germany. These analyses suggest that the SARS-CoV-2 has already evolved into a less infective SARS-CoV-2a affecting COVID-19 cases in different regions. The time a country or region needs to acquire SARS-CoV-2a strains may be indicative to the time it would need to overcome the peak of the COVID-19 cases. To confirm these assumptions, prompt retrospective and prospective epidemiological studies should be conducted in different countries to understand the course of pathogenicity of the SARS-CoV-2a and SARS-CoV-2g. Potential drugs can be designed targeting 28881-28883 region of the N protein to modulate virus pathogenicity.

The XChem facility at Diamond Light Source offers fragment screening by X-ray crystallography as a general access user program. The main advantage of X-ray crystallography as a primary fragment screen is that it yields directly the location and pose of the fragment hits, whether within pockets of interest or merely on surface sites: this is the key information for structure-based design and for enabling synthesis of follow-up molecules. Extensive streamlining of the screening experiment at XChem has engendered a very active user programme that is generating large amounts of data: in 2017, 36 academic and industry groups generated 35,000 datasets of uniquely soaked crystals. It has also generated a large number of learnings concerning the main remaining bottleneck, namely obtaining a suitable crystal system that will support a successful fragment screen. Here we discuss the practicalities of generating screen-ready crystals that have useful electron density maps, and how to ensure they will be successfully reproduced and usable at a facility outside the home lab.

A novel coronavirus (SARS-CoV-2), causing an emerging coronavirus disease (COVID-19), first detected in Wuhan City, Hubei Province, China has resulted in an outbreak in China which has taken a catastrophic turn with high toll rates in China and subsequently spreading across the globe. The rapid spread of this virus to more than 175 countries while affecting nearly 500,000 persons and causing more than 22,000 human deaths, it has resulted in a pandemic situation in the world. The SARS-CoV-2 virus belongs to the genus Betacoronavirus, like MERS-CoV and SARS-CoV, all of which originated in bats. It is highly contagious, causing symptoms like fever, dyspnea, asthenia and pneumonia, thrombocytopenia and the severely infected patients succumb to the disease. Coronaviruses (CoVs) among all known RNA viruses have the largest genomes ranging from 26 to 32 kb in length. Extensive research has been conducted to understand the molecular basis of the SARS-CoV-2 infection and evolution, develop effective therapeutics, antiviral drugs and vaccines, and to design rapid and confirmatory viral diagnostics as well as adopt appropriate prevention and control strategies. Till date, no clinically proclaimed, proven therapeutic antibodies or specific drugs and therapeutics, and vaccines have turned up. Several molecular diagnostic tests such as Real Time-PCR, isothermal loop-mediated amplification of coronavirus (i-LACO), full genome analysis by next-generation sequencing (NGS), multiplex nucleic acid amplification, and microarray-based assays are in use currently for the laboratory confirmation of this CoV infection. In this review article, we describe the basic molecular organization and phylogenetic analysis of the coronaviruses, including the SARS-CoV-2, and recent advances in diagnosis and vaccine development in brief and focusing mainly on developing potential therapeutic options that can be explored to manage this pandemic virus infection, which would help in valid countering of COVID-19.

Coronavirus Disease 2019 (COVID-19), caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome - Coronavirus-2) of the family Coronaviridae, appeared in Wuhan, Hubei province, China being its epicenter in December 2019. This disease was declared as posing Public Health International Emergency by World Health Organization on January 30, 2020, attained the status of a very high-risk category on February 29, and now having a pandemic status (March 11, 2020). COVID-19 has presently spread to more than 195 countries/territories while killing nearly 19,600 humans out of cumulative confirmed cases accounting to more than 430,000 within a short period of just a few weeks. The majority of deaths have been reported in Italy and China. Researchers worldwide are pacing with high efforts to counter the spread of this virus and to design effective vaccines and therapeutics/drugs. Few of the studies have shown the potential of animal-human interface and zoonotic links in the origin of SARS-CoV-2. Exploring the possible zoonosis and revealing the factors responsible for its initial transmission from animals to humans will pave ways to design and implement effective preventive and control strategies to counter COVID-19. The present review presents an overview of COVID-19 and the causative virus SARS-CoV-2, with particular emphasis on the role of animals and their jumping the cross-species barriers, experiences learned from SARS- and MERS-CoVs, zoonotic links, and spillover events, transmission to humans and rapid spread., highlighting in very brief the preventive and control measures along with a few of the recent research developments to counter this pandemic virus/disease.

Covid-19 is a new coronavirus disease first described in December 2019. This respiratory illness is severe and potentially fatal. Severe cases make up to 15%, lethality ranges between 1.5 and more than 10 %. What is urgently needed is an efficient pharmacological treatment for the treatment of severe cases. During the infection of alveolar epithelial cells of the lung, the ACE2 receptor has a central function. The antimalarial drugs chloroquine phosphate (CQ) and hydroxychloroquine (HCQ) impair in vitro the terminal glycosylation of ACE2 without significant change of cell-surface ACE2 and, therefore, might be potent inhibitors of SARS-CoV-2 infections. Starting inhibition at 0.1 µM, CQ completely prevented in vitro infections at 10 µM, suggesting a prophylactic effect and preventing the virus spread 5 hours after infection. In a first clinical trial, CQ was effective in inhibiting exacerbation of pneumonia, improving lung imaging findings, promotion of virus-negative conversion, and shortening the disease. In addition, HCQ, which is three times more potent than CQ in SARS-CoV-2 infected cells (EC50 0.72 µM), was significantly associated with viral load reduction/disappearance in COVID-19 patients compared to controls. Theoretically, CQ and HCQ could thus be effectively used in the treatment of SARS-CoV pneumonia. From a pharmacological standpoint, however, the major problems of oral treatment with these drugs are possible severe side effects and toxicity. Concretely, this relates to (a) the inconsistent individual bioavailability of these drugs at the alveolar target cells, depending on intestinal resorption, hepatic first-pass metabolism and accumulation in liver, spleen and lung, and (b) the need for a relatively high concentration of 1-5 µM at the alveolar surface. Therefore, we propose in a first dose estimation the use of HCQ as an aerosol in a dosage of 2-4 mg per inhalation in order to reach sufficient therapeutic levels at the alveolar epithelial cells. By using a low-dose non-systemic aerosol, adverse drug reactions will markedly be reduced compared with oral application. This increase in tolerability enables a broader use for prevention and after contact with an infected person, which would be an advantage especially for the high-risk, often multi-morbid and elderly patients. Empirical data on self-medication with a one-week aerosol application by two of the authors is presented. Inhalation was well tolerated without relevant side effects.

Abstract Background: Diabetes mellitus is dramatically increasing in the wide world. The managing of diabetes care emphasized the self-management education and support into patients’ care and family care. Objective: to review and synthesizes the effectiveness of DSME strategies involving family as a key person to provide social support for diabetes mellitus self-management of glycemic uncontrolled patients Method: Three databases through PubMed, CINAHL, and Scopus were reviewed to assess the relevant articles. The following search terms: “type 2 diabetes,” “self-management,” “family support,” and “glycemic uncontrolled.” We summarized details of family support on self-management among glycemic uncontrolled patients for 14 existing studies. Results: A total of 22 intervention studies were identified. Those studies have a heterogeneous of the education strategies, support perceived, follow-ups strategies and outcomes among type 2 DM. Family integration on diabetes self-management education (DSME) has a positive impact on several outcomes including, self-care behaviors, psychological outcomes, self-efficacy and clinical outcomes Conclusions: This systematic review found robust data related to the integration of family support on diabetes self-management among glycemic uncontrolled patients. Consequently, the improvement in outcomes was identified. Implications: The findings suggest model of family engagement is better and needed for sustaining the diabetes care in the long-term care

The purpose of current study was to investigate the expression characteristic of circular RNAs (circRNAs) in peripheral blood of type 2 diabetes mellitus (T2DM) patients and their potentials as diagnostic biomarkers for pre-diabetes and T2DM. In present study, the circRNAs in the peripheral blood from 6 healthy individuals and 6 T2DM patients were collected for microarray analysis. The results indicated that there were 489 differentially expressed circRNAs, of which 78 were upregulated and 411 were downregulated in the T2DM group. Then we selected 5 circRNAs as the candidate biomarkers under a stricter screening criteria and further verified them in another cohort (control group, n=20; pre-diabetes group, n =20; T2DM group; n=20). 3 of the 5 circRNAs presented upregulated expression in the experimental groups, including 2 circRNAs of the T2DM group that had higher expression than the pre-diabetes group. Hsa_circ_0054633 was identified to have the largest area value under the carve (AUC). In another independent cohort (control group, n=60; pre-diabetes group, n=63; T2DM group, n=64), the diagnostic capacity of hsa_circ_0054633 was tested. The results showed that the AUC for the diagnosis of pre-diabetes was 0.751(95% confidence interval=[0. 666-0.835], P＜0.001) while it was 0.793 ([0.716-0.871], P＜0.001) for the diagnosis of T2DM. After including the risk factors of T2DM, the AUC increased to 0.841 ([0.773-0.910], P <0.001) and 0.834 ([0.762-0.905], P <0.001), respectively. Hsa_circ_0054633 presented a certain diagnostic capability for pre-diabetes and T2DM.

The microstructural evolution, thermodynamics and kinetics of Mo-21%Tm₂O₃ (mass fraction, %) powder mixtures during ball milling were investigated using X-ray diffraction and transmission electron microscopy. Ball milling induced Tm₂O₃ to be decomposed and then dissolved into Mo crystal. The supersaturated nanocrystalline solid solution of Mo (Tm, O) was obtained after 96 h of ball milling. The elements of Mo, Tm and O were distributed uniformly in the ball-milled particles. Based on the semi-experimental theory of Miedema, a thermodynamic model was developed to calculate the driving force of phase evolution. There was no chemical driving force to form a crystal solid solution of Tm atoms in Mo crystal or an amorphous phase because the Gibbs free energy for both processes was higher than zero. For Mo-21%Tm₂O₃, it was mechanical work, not negative heat of mixing, that provided the driving force to form supersaturated nanocrystalline Mo (Tm, O) solid solution.

Aims/Hypothesis): Type 1 diabetes is an immune-mediated disease with destruction of the pancreatic β-cells, a process that is conditioned by multiple genes and other factors. HLA counts as the major susceptibility gene. Significant variations in HLA genetic susceptibility to type 1 diabetes between Caucasians, African and Asian and other ethnic groups may have led to the variation in incidence of type 1 diabetes globally. Type 1 diabetes is characterized upon HLA identification. In this chapter we discuss global variations in genetic susceptibility of HLA with regard to type 1 diabetes globally with a particular attention to Arab population. Methods): Haplotype configuration of HLA class I A, B, C and Class II –DR/DQ/DP were studied in Caucasians, African and Asian and in Arab population to see if that is responsible for the exponential rise in the rate of type 1 diabetes. Results): Although Arabs have one of the highest global incidence and prevalence rates of type 1 diabetes, unfortunately, there is a dearth amount of information regarding HLA genetic susceptibility to type 1 diabetes in the Arab world. HLA haplotype configurations contribute to its risk value. However, out of an insufficient present study there are examples of misjudgment of HLA risk according to HLA alleles rather than haplotypes. Conclusion): To date HLA outlooks for the characterization of type 1 diabetes. There is an ethnicity difference in HLA characteristics which is responsible for variation in type 1 diabetes. Although Arab population have contributed heavily in the rise of burden of type 1 diabetes, however, there is significantly a dearth amount of studies on HLA in Arab population. Obviously, any future prediction, prevention or cure of the disease will be based on the HLA genetics. There is a dire need for a systematic screening of HLA for Arab population with type 1 diabetes, identification of Arab HLA-risk values and identify those who are prone to get the disease.

Gwosch et al. (2020) and Balzarotti et al. (2017) purport MINFLUX as the next revolutionary fluorescence microscopy technique claiming a spatial resolution in the range of 1-3 nm in fixed and living cells. Though the claim of molecular resolution is attractive, I am concerned whether true 1 nm resolution has been attained. Here, I compare the performance with other super-resolution methods focussing particularly on spatial resolution claims, atypical image rendering, visualisation enhancement, subjective filtering of localizations, detection vs labelling efficiency and the possible limitations when imaging biological samples containing densely labelled structures. I hope the analysis and evaluation parameters presented here are not only useful for future research directions but also microscope users, developers and core facility managers when deciding on an investment for the next 'state-of-the-art' instrument.

We analyzed the SARS-CoV-2 spike (S) protein amino acid sequence extracted from 11,542 viral genomic sequences submitted to the Global Initiative on Sharing All Influenza Data (GISAID) database through April 27, 2020. Consistent with prior reports, we found a major S protein mutation, D614 to G614, that was represented in 56% of all the analyzed sequences. All other mutations combined were less than 10%. After parsing the data geographically, we found most of the Chinese patient samples showed D614 (97%). By contrast, most patient samples in many European countries showed G614 (51 to 88%). In the United States, the genotypic distribution in California and Washington was similar to Asian countries, while the distribution in other US states was comparable to Europe. We observed a dramatic increase in the frequency of G614 over time in multiple regions, surpassing D614 when both were present, suggesting G614 S protein virus outcompetes D614 S protein virus. To gain insight into the consequences of the D614G mutation, homology modeling using a multi-template threading mechanism with ab initio structural refinement was performed for a region of the S protein (S591 to N710) spanning the D614G mutation and the S1 furin cleavage site. Molecular models of this region containing D614 or G614 revealed a major difference in secondary structure at the furin domain (RRARS, R682 to S686). The D614 model predicted a random coil structure in the furin domain whereas the G614 model predicted an alpha helix. Critical residues in the cleavage domain of G614 model were found to better align with the PDB structure of a furin inhibitor. Thus, homology modeling studies suggest a potential mechanism whereby the D614G mutation may confer a competitive advantage at the furin binding domain that may contribute to the rise of the D614G SARS-CoV-2 mutant.

Diseases in articular cartilages have affected millions of people globally. Although the biochemical and cellular composition of articular cartilages is relatively simple, there is the limitation in self-repair ability of cartilage. Therefore, developing the strategies for cartilage repair is very important. Here, we reported a new manufacturing process of water-based polyurethane based photosensitive materials with hyaluronic acid and applied the materials for 3D printed customized cartilage scaffolds. The scaffold has high cytocompatibility and is one that closely mimics the mechanical properties of articular cartilages. It is suitable for culturing human Wharton's jelly mesenchymal stem cells (hWJMSCs) and the cells showed an excellent chondrogenic differentiation capacity. We consider that the 3D printing hybrid scaffolds may have potential in customized tissue engineering and facilitate the development of cartilage tissue engineering.

Utility of vaccine campaigns to control coronavirus disease 2019 (COVID-19) is not merely dependent on vaccine efficacy and safety. Vaccine acceptance among the general public and the healthcare workers, appears to have a decisive role for successful control of the pandemic. The aim of this review was to provide an up-to-date assessment of COVID-19 vaccination acceptance rates worldwide. A systematic search of the peer-reviewed English survey literature indexed in PubMed was done on December 25, 2020. Results from 30 studies, met the inclusion criteria and formed the basis for final COVID-19 vaccine acceptance estimates. Results of an additional recent survey from Jordan and Kuwait was considered in this review as well. Survey studies on COVID-19 vaccine acceptance rates were found from 33 different countries. Among adults representing the general public, the highest COVID-19 vaccine acceptance rates were found in Ecuador (97.0%), Malaysia (94.3%), Indonesia (93.3%) and China (91.3%). On the other hand, the lowest COVID-19 vaccine acceptance rates were found in Kuwait (23.6%), Jordan (28.4%), Italy (53.7), Russia (54.9%), Poland (56.3%), US (56.9%), and France (58.9%). Only eight surveys among healthcare workers (doctors, nurses) were found, with vaccine acceptance rates ranging from 27.7% in the Democratic Republic of the Congo to 78.1% in Israel. In a majority of survey studies among the general public (62%), the acceptance of COVID-19 vaccination showed a level of ≥ 70%. Low rates of COVID-19 vaccine acceptance were reported in the Middle East, Russia, Africa and several European countries. This could represent a major problem in the global efforts that aim to control the current COVID-19 pandemic. More studies are recommended to address the scope of COVID-19 vaccine hesitancy. Such studies are particularly needed in the Middle East Africa, Eastern Europe, Central Asia, Middle and Latin America.

The actions of many drugs involve enzyme inhibition. This is exemplified by the inhibitors of monoamine oxidases (MAO) and the cholinsterases (ChE) that have been used for several pharmacological purposes. This review describes key principles and approaches for the reliable determination of enzyme activities and inhibition as well as some of the methods that are in current use for such studies with these two enzymes. Their applicability and potential pitfalls arising from their inappropriate use are discussed. Since inhibitor potency is frequently assessed in terms of the quantity necessary to give 50% inhibition (the IC50 value), the relationships between this and the mode of inhibition is also considered, in terms of the misleading information that it may provide. Incorporation of more than one functionality into the same molecule to give a multi-target-directed ligands (MTDLs) requires careful assessment to ensure that the specific target effects are not significantly altered and that the kinetic behaviour remains as favourable with the MTDL as it does with the individual components. Such factors will be considered in terms of recently developed MTDLs that combine MAO and ChE inhibitory functions.

The spillover of a virus from an animal reservoir to humans requires both molecular and ecological risk factors to align. While extensive research both before and after the emergence of SARS-CoV-2 in 2019 implicates horseshoe bats as the significant animal reservoir for the new human coronavirus, it remains unclear why it emerged at this time. One massive disruption to animal-human contacts in 2019 is linked to the on-going African swine fever virus (ASFV) pandemic. Pork is the major meat source in the Chinese diet. We hypothesize that the dramatic shortage of pork following large-scale culling and restrictions of pig movement (resulting in marked price increases) led to alternative sources of meat and unusual animal and meat movements nationwide, e.g., involving wildlife, and thus greatly increased opportunities for human-sarbecovirus contacts. Pork prices were particularly high in southern provinces (Guangdong, Guangxi, Fujian, Jiangxi, Hunan, and Hubei), where wildlife is farmed and more frequently consumed. Major wildlife farming provinces are spread from Northern to Southern China, which overlaps with horseshoe bat host ranges, potential hosts of the proximal SARS-CoV-2 ancestor, and wildlife sourcing provinces of Wuhan Huanan market and possibly other markets. Trading of SARS-CoV-2 susceptible wildlife in these markets, such as minks, raccoon dogs, foxes and palm civets in Wuhan markets, could have increased the risk of SARS-CoV-2 from an intermediary host. Moreover, large quantities of animals raised for fur could have entered the human food chain undetected and significantly increased risks of animal-human contact. Performing retrospective testing of stored susceptible animals and their meat sold before December 2019 may be helpful in the next stage of tracing the animal origin of SARS-CoV-2 as spillover events are more likely to have taken place in 2019 when China was experiencing the worst effects of the ASFV pandemic.

Spread of severe acute respiratory syndrome coronavirus (SARS-CoV-2) made a historic transition between December 2019 to March 2020. In the present scenario SARS-CoV-2 as becomes a major burden on public health and economic stability of societies around the globe. From the substantial evidences gained from the pandemic of SARS-CoV-2 and MERS-CoV (Middle East respiratory syndrome coronavirus), scientists and clinicians strongly believes that these pathogenic viruses share common homology of some biologically active enzymes which includes RNA-dependent RNA polymerase (RdRP), 3-chymotrypsin-like protease (3CL^pro), papain-like protease (PL^pro) etc. RdRP relatively grabs higher level of clinical importance in comparison with other enzyme target. Indian system of traditional medicine pioneering the therapy towards infectious disease since several centuries. In view of this potential therapeutic leads from some of the Indian medicines along with standard drug favipiravir subjected to docking investigation targeting SARS-CoV-2- RNA dependent RNA polymerase (RdRp). Residual proximity analysis reveals 18 out of 28 compounds reveals potential binding affinity of about 100% with the target amino acid residue (618 ASP, 760 ASP,761 ASP), 7 out of 28 reveals 75% binding efficacy and 3 out of 28 reveals 25% binding efficacy with that of the target residue. Hence further clinical validation may be warranted with proper in-vitro and in-vivo studies prior to the clinical recommendation in treating COVID-19 patient’s.

The coronavirus disease 2019 (COVID-19) is now a global pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Unlike other known coronaviruses, such as the Middle East respiratory syndrome coronavirus (MERS-CoV), SARS-CoV-2 reveals new clinical, immunological, and pathologic features. The lymphocyte depletion, macrophage and neutrophil hyperactivation, cytokine dysregulation, thrombophilia, delayed antiviral response, and immune exhaustion are key immunological findings linked to the clinical progression of this disease. Understanding and identifying the underlying immunological basis of COVID-19 is crucial to designing effective therapies. Here, we provide an overview of immunopathogenesis driven by SARS-CoV-2 after its interactions with the immune system.

Exact solutions to conformable time fractional (3+1)- dimensional equations are derived by using the modified form of the Kudryashov method. The compatible wave transformation reduces the equations to an ODE with integer orders. The predicted solution of the finite series of a rational exponential function is substituted into this ODE. The resultant polynomial equation is solved by using algebraic operations. The method works for the Jimbo-Miwa, the Zakharov-Kuznetsov and the modified Zakharov-Kuznetsov equations in conformable time fractional forms. All the solutions are expressed in explicit forms.

Over the last decade, the field of Human Attribute Recognition (HAR) has dramatically changed, mainly due to the improvements brought by deep learning solutions. This survey reviews the progress obtained in HAR, considering the transition from the traditional hand-crafted to deep-learning approaches. The most relevant works on the field are analyzed concerning the advances proposed to address the HAR's typical challenges. Furthermore, we outline the applications and typical evaluation metrics used in the HAR context. Finally, we provide a comprehensive review of the publicly available datasets for the development and evaluation of novel HAR approaches.

The global use of alcohol based hand sanitizers (ABHS) as a means of controlling the transmission of infectious disease increased dramatically in 2020 as governments and public health agencies across the world advocated hand hygiene as a preventative measure during the COVID-19 pandemic. Although the performance of these products is most commonly defined as a function of their alcohol concentration, they are multifaceted products in which an interplay of several factors is important in determining efficacy. The hand sanitizer tetrahedron, is a novel concept that considers both ABHS formulation factors and product performance factors from a multi-dimensional perspective. The four faces of the tetrahedron represent input/formulation factors: 1) the type and amount of alcohol, 2) inactive ingredients, 3) the type of formulation/delivery system and 4) manufacturing practices. The four corners of the tetrahedron represent output/product performance factors: 1) efficacy, 2) sensory characteristics, 3) usage, usability and compliance and 4) product safety/adverse effects. All factors are of importance to ensuring the effectiveness and utility of these products.

Carcinoembriogenic antigen (CEA) is a routine marker for follow-up of colo-rectal cancers. We aimed to determine whether a CEA increase within the normal range can be linked to a recurrence risk. We included 78 consecutive patients with colo-rectal cancer, who underwent curative surgical treatment with or without chemo- or radiotherapy. As reference, we used the smallest value of the CEA during follow-up. A total of 34/78 patients (43.6%) had fluctuations of CEA of at least 1.1 ng/ml, with or without increases above 5 ng/ml. In 27/34 patients (79.4%) increases of CEA were explained either by recurrence (15/34 patients, 44.1%), adjuvant chemotherapy (7/34 patients, 20.6%) or benign pathology (5/34 patients, 14.7%). In 5 of 22 recurrences (23%) a CEA increase of at least 1.1 ng/ml, but below 5 ng/ml preceded the clinical relapse by a median of 8 months (range 3-22 months). The 4-year disease-free survival was 89% in patients with postoperative CEA <2.5 ng/ml, and 55% in patients with CEA >2.5 ng/ml. CEA increase by at least 1.1 ng/ml within the normal range, after curative treatment of colorectal cancer can be either an early sign of relapse or can be usually explained by other pathological processes.

Summary CoV-GLUE is an online web application for the interpretation and analysis of SARS-CoV-2 virus genome sequences, with a focus on amino acid sequence variation. It is based on the GLUE data-centric bioinformatics environment and provides a browsable database of amino acid replacements and coding region indels that have been observed in sequences from the pandemic. Users may also analyse their own SARS-CoV-2 sequences by submitting them to the web application to receive an interactive report containing visualisations of phylogenetic classification and highlighting genomic variation of potentially high impact, for example linked to primer mismatches.Availability and implementation Available at http://cov-glue.cvr.gla.ac.uk. Implemented using GLUE, an open source framework for the development of virus sequence data resources. Contact josh.singer@glasgow.ac.uk

Identifying the total number of fruits on trees has long been of interest in agricultural crop estimation work. Yield prediction of fruits in practical environment is one of the hard and significant tasks to obtain better results in crop management system to achieve more productivity with regard to moderate cost. Utilized color vision in machine vision system to identify citrus fruits, and estimated yield information of the citrus grove in-real time. Fruit recognition algorithms based on color features to estimate the number of fruit. In the current research work, some low complexity and efficient image analysis approach was proposed to count yield fruits image in the natural scene. Semi automatic segmentation and yield calculation of fruit based on shape analysis is presented. Color and shape analysis was utilized to segment the images of different fruits like apple, pomegranate obtained under different lighting conditions. First the input sectional tree image was converted from RGB colour space into the colour space transform (i.e., YUV, YIQ, or YCbCr). The resultant image was then applied to the algorithm for fruit segmentation. After it is applied Morphological Operations which is enhanced image then execute Blob counting method which identify the object and count the number of it. Accuracy of this algorithm used in this thesis is 82.21% for images that have been scanned.

Prediction of stock groups values has always been attractive and challenging for shareholders. This paper concentrates on the future prediction of stock market groups. Four groups named diversified financials, petroleum, non-metallic minerals and basic metals from Tehran stock exchange are chosen for experimental evaluations. Data are collected for the groups based on ten years of historical records. The values predictions are created for 1, 2, 5, 10, 15, 20 and 30 days in advance. The machine learning algorithms utilized for prediction of future values of stock market groups. We employed Decision Tree, Bagging, Random Forest, Adaptive Boosting (Adaboost), Gradient Boosting and eXtreme Gradient Boosting (XGBoost), and Artificial neural network (ANN), Recurrent Neural Network (RNN) and Long short-term memory (LSTM). Ten technical indicators are selected as the inputs into each of the prediction models. Finally, the result of predictions is presented for each technique based on three metrics. Among all algorithms used in this paper, LSTM shows more accurate results with the highest model fitting ability. Also, for tree_based models, there is often an intense competition between Adaboost, Gradient Boosting and XGBoost.

Global food security for the increasing world population not only requires increased sustainable production of food but a significant reduction in pre- and post-harvest waste. The timing of when a fruit is harvested is critical for reducing waste along the supply chain and increasing fruit quality for consumers. The early in field assessment of fruit ripeness and prediction of the harvest date and yield by non-destructive technologies have the potential to revolutionize farming practices and enable the consumer to eat the tastiest and freshest fruit possible. A variety of non-destructive techniques have been applied to estimate the ripeness or maturity but not all of them are applicable for in situ (field or glasshouse) assessment. This review focuses on the non-destructive methods which are promising, or have already been, applied to the pre-harvest in field measurement including colorimetry, visible imaging, spectroscopy and spectroscopic imaging. Machine learning and regression models used in assessing ripeness are also discussed.

In research applications across several areas, noise removal is indispensable for accuracy of final results. Noise is caused due to physical principals, such as background electronic noise, quantum effect, and wave rebound effect to name a few. Noise removal can help improve results in medical, astronomy, defense, and numerous other fields. Addressing this limitation would result in potentially low cost, automatic, and reliable systems. In this paper, a generalized new approach i.e. Multi-Frame Noise Removal (MFNR) is proposed for noise removal. Given any type of data, the probability density function (PDF) of the noise can be determined. Herein, we extracted the noise PDF parameters using KDE (Kernel Density Estimation). Because the data is corrupted by “deterministic” noise, hence can be cleaned. This could be used as a general purpose noise removal tool. The data point with same position in multiple frames helps us determine the noise PDF characteristics and hence making it possible to remove noise. The conventional wisdom which states that noise removal and detail preservation are contrary to each other is not true for MFNR. Experimental results validate our proposed method which showed practically complete noise reduction based on number of frames used, as compared to existing benchmark methods.

As the first initiative of its kind in Algeria, here is presented a solar-powered mobile “Ultraviolet Germicidal Irradiation” disinfection unit (UVGI) based on a special germicidal ultraviolet-C (UVC) radiator. The system was designed to disinfect several objects such as: medical tools, reusable masks, face-shields, gloves, phones, laptops, keys, money and many other portable devices that need to be disinfected/sterilized. It offers the advantage of complete autonomy through the built-in photovoltaic (PV) system that includes a solar panel, a gel battery, a charge controller and a power inverter. The system provides an extra 220V-50Hz outlet with 375VA maximum power to be used when energy is needed. The system is easily scalable to generate higher ultraviolet dosages by adding more UVC lamps. The chemical-free germicidal UVC sanitizing method employed by this device effectively disactivates a very wide range of microorganisms (microbes, bacteria and fungi and viruses including the actual SARS-CoV-2 that causes COVID-19 respiratory disease) and it has several advantages in comparison to chemical-based sanitizing methods. The total cost to make this open source device is below 1000 € and is easily customizable and scalable. This device is an open source, secure and fast equipment for objects and surface disinfection. The device will be fully automated by adding PIR sensors or remote control after further funding will be received.

The processing of cloud free geo-referenced imagery is one of the preliminary processing step of any land application. This letter describe the methodology developed to obtain a seamless cloud free composite of Africa for 2016 using Sentinel-2A data at 10 meters resolution freely available from the European Space Agency. The method is based on an hybrid method resulting from the merging of the two most robust time series methods namely the "darkest pixel" and the "maximum NDVI" previously developed with AVHRR time series.

The current emergency due to the worldwide spread of the COVID-19 caused by the new SARS-CoV-2 is a great concern for global public health. Already in the past, the outbreak of severe acute respiratory syndrome (SARS) in 2003 and Middle Eastern respiratory syndrome (MERS) in 2012 demonstrates the potential of coronaviruses to cross-species borders and further underlines the importance of identifying new-targeted drugs. An ideal antiviral agent should target essential proteins involved in the lifecycle of SARS-CoV. Currently, some HIV protease inhibitors (i.e., Lopinavir) are proposed for the treatment of COVID-19, although their effectiveness was not yet assessed. The main protease (Mpro) provides a highly validated pharmacological target for the discovery and design of inhibitors. We identified potent Mpro inhibitors employing computational techniques that entail the screening of a Marine Natural Product (MNP) library. MNP library was screened by hyphenated pharmacophore model, and molecular docking approaches. Molecular dynamics and re-docking further confirmed the results obtained by structure-based techniques and allowed to highlight some crucial aspects. Seventeen potential SARS-CoV-2 Mpro inhibitors have been identified among the natural substances of marine origin. As these compounds were extensively validated by a consensus approach and by molecular dynamics, the likelihood that at least one of these compounds could be bioactive is excellent.

The latest methods based on deep learning have achieved amazing results regarding the complex work of inpainting large missing areas in an image. This type of method generally attempts to generate one single "optimal" inpainting result, ignoring many other plausible results. However, considering the uncertainty of the inpainting task, one sole result can hardly be regarded as a desired regeneration of the missing area. In view of this weakness, which is related to the design of the previous algorithms, we propose a novel deep generative model equipped with a brand new style extractor which can extract the style noise (a latent vector) from the ground truth image. Once obtained, the extracted style noise and the ground truth image are both input into the generator. We also craft a consistency loss that guides the generated image to approximate the ground truth. Meanwhile, the same extractor captures the style noise from the generated image, which is forced to approach the input noise according to the consistency loss. After iterations, our generator is able to learn the styles corresponding to multiple sets of noise. The proposed model can generate a (sufficiently large) number of inpainting results consistent with the context semantics of the image. Moreover, we check the effectiveness of our model on three databases, i.e., CelebA, Agricultural Disease, and MauFlex. Compared to state-of-the-art inpainting methods, this model is able to offer desirable inpainting results with both a better quality and higher diversity. The code and model will be made available on https://github.com/vivitsai/SEGAN.

Mycophenolate mofetil was reported to have broad in vitro activity against different viruses and had been tried in combination with IFN-β in treating MERS infection. We tested the pharmacological activity of mycophenolate mofetil using SARS-CoV-2 infected Vero cells. The half-maximal effective concentration (EC₅₀) of mycophenolate mofetil against SARS-CoV-2 was 0.47 μM while that of remdesivir was 0.77 μM. Molecular docking results of mycophenolate mofetil to potential target proteins of COVID-19 suggested that mycophenolate mofetil might inhibit SARS-CoV-2 mainly by interacting with DHODH and IMPDH2. Furthermore, mycophenolate mofetil as an immunosuppressant may be a good therapeutic option for the management of hyperinflammation in patients with severe COVID-19. Based on its high potency against SARS-CoV-2 in Vero E6 cells, its good pharmacokinetics and clinical safety profile, mycophenolate mofetil deserves further exploration as potential treatment for COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is characterized by a high mortality of elderly men with age-related comorbidities. In most of these patients, uncontrolled local and systemic hyperinflammation induces severe and often lethal outcomes. The aging process is characterized by the gradual development of a chronic subclinical systemic inflammation (inflamm-aging) and by acquired immune system impairment (immune senescence). Here, we advance the hypothesis that some key features of aging contribute to the disproportionate SARS-CoV-2 mortality suffered by elderly men. At least four well-recognized aging-related characteristics that are strongly expressed in older men go some way towards explaining why these patients account for the vast majority of fatalities: i. the presence of subclinical systemic inflammation without overt disease, ii. a blunted acquired immune system and type I interferon response due to the chronic inflammation; iii. the downregulation of ACE2 (SARS-CoV-2 receptor), which triggers inflammation, particularly in patients with age-related comorbid diseases such as type II diabetes; and iv. accelerated biological aging, as measured by epigenetic and senescence markers (e.g. telomere shortening) associated to the chronic inflammatory state. Though typical of the aged, especially of elderly men, it is conceivable that these features are also shared by some subsets of the younger population. The high mortality rate of SARS-CoV-2 infection suggests that clarification of the mechanisms of inflamm-aging and immune senescence can help combat not only age-related disorders but also SARS-CoV-2 infection.

With the COVID-19 pandemic now ongoing for close to a year, people all over the world are still waiting for a vaccine to become available. The initial focus of accelerated global research and development efforts to bring a vaccine to market as soon as possible was on novel platform technologies that promised speed but had limited history in the clinic. In contrast, recombinant protein vaccines, with numerous examples in the clinic for many years, missed out on the early wave of investments from government and industry. Emerging data are now surfacing suggesting that recombinant protein vaccines indeed might offer an advantage or complement to the nucleic acid or viral vector vaccines that will likely reach the clinic faster. Here, we summarize the current public information on the nature and on the development status of recombinant subunit antigens and adjuvants targeting SARS-CoV-2 infections.

The COVID-19 pandemic caused by SARS-CoV-2 has been showing a speedy growth in the number of infected patients with a remarkable mortality rate, thus it has become a worldwide public health concern. From March 8, 2020, the disease was confirmed to start spreading in Bangladesh. Since then, people got infected so exponentially that the country positions at the list of top infected countries in the world. Therefore, the objective of this comprehensive review was representing overall scenario of COVID-19 in different sectors of Bangladesh, particularly prioritizing the health sector. Up to 14 September 2020, 339,332 confirmed cases and 4,759 deaths were reported. An alarming fact is that while the global mutation rate of coronavirus is 7.23 % in average, the rate is 12.6 % in Bangladesh. Although the government ruled preventive strategies such as nationwide lockdown, social distancing, contact monitoring, quarantine and isolation, it was difficult to implement those due to lack of public awareness, inappropriate attitudes and so on. Moreover, the overburdened healthcare system had a weak response at initial stage because of insufficient healthcare facilities. Consequently, this pandemic affected severely almost all the important sectors of the country, specifically the economy, agriculture and health sectors. Hence, focusing on healthcare system as well as maintaining social distance and other essential precautions can limit the spread of infection and help to alleviate the severity of the pandemic.

Acute lung injury (ALI) is characterized by inflammation of the lung tissue and oxidative injury caused by excessive accumulation of reactive oxygen species. Studies have suggested that anti-inflammatory or antioxidant agents could be used for the treatment of ALI with a good outcome. Therefore, our study aimed to test whether the mycelium extract of Sanghuangporus sanghuang (SS-1), believed to exhibit antioxidant and anti-inflammatory properties, could be used against the excessive inflammatory response associated with LPS-induced ALI in mice and to investigate its possible mechanism of action. The experimental results showed that the administration of SS-1 could inhibit LPS-induced inflammation. SS-1 could reduce the number of inflammatory cells, inhibit MPO activity, regulate the TLR4/PI3K/Akt/mTOR pathway and the signal transduction of NF-κB and MAPK pathways in the lung tissue, and inhibit HNGB1 activity in BALF. In addition, SS-1 could affect the synthesis of antioxidant enzymes HO-1 and Trx-1 in the lung tissue and regulate signal transduction in the KAP1/Nrf2/Keap1 pathway. Histological results showed that administration of SS-1 prior to induction could inhibit the large-scale LPS-induced neutrophil infiltration of the lung tissue. Therefore, based on all experimental results, we propose that SS-1 exhibits a protective effect against LPS-induced (ALI) in mice. The mycelium of S. sanghuang can potentially be used for the treatment or prevention of inflammation-related diseases

COVID-19 (coronavirus disease 2019) is a public health emergency of international concern caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). As of this time, there is no known effective pharmaceutical, phytopharmaceutical or traditional medicine for cure or prevention of COVID-19, although it is urgently needed. In this review, based on the current understanding of the disease molecular mechanisms of novel Coronavirus SARS-CoV-2 and its closest relative SARS-CoV and other human Coronaviruses, I have identified some naturally occurring plant based substances and Ayurvedic medicinal herbs that could feasibly be tested as a matter of urgency for prevention as well as therapeutic option for COVID-19 in India and other parts of the world. I conclude that dried rhizome of Curcuma longa L. i.e. turmeric, and its active ingredient curcumin may be effective in preventing as well as cure the COVID-19 pandemic due to its proven antiviral activities, this however need to be tested by appropriate clinical trials as research priority.

In this study, we investigated the effects of Akebia quinata ethanol extract (AE), Akebia quinata sikhye (AS), and Akebia quinata water extract (AW) on alcohol-induced liver injury in rats. The hepatoprotective, anti-inflammatory, anti-apoptotic, and antioxidant effects of AE, AS, and AW were examined. Experimental animals were randomly divided into five groups: normal, ethanol, AE (10 mL/kg), AS (10 mL/kg), and AW (10 mL/kg). Each group was administered the respective treatment orally once per day for 21 days. CYP2E1 mRNA expression was significantly lower in the AE, AS, and AW groups than that in the ethanol group. Pro-inflammatory cytokines including cyclooxygenase-2, IL-6, and TNF-α increased significantly in the ethanol group but these increases were ameliorated with AE, AS, and AW treatment. Moreover, the expression of the apoptosis-associated proteins Bax, p53, procaspase-3, and PARP decreased after treatment with AE, AS, and AW. The expression of antioxidant enzymes including BCL-2, SOD, and GST slightly decreased in the ethanol group, but AE, AS, and AW treatment augmented their activities. AQ extracts and AS attenuated ethanol-induced increases in the levels of phosphorylated p-AKT, p-ERK, and p-JNK. These results demonstrate that AQ is a competence indicator for inhibiting alcoholic liver injury.

One of the tools for optimal crop production is regular monitoring and assessment of crops. During the growing season of fruit trees, the bloom period has increased photosynthetic rates that correlate with the fruiting process. This paper presents the development of an image processing algorithm to detect peach blossoms on trees. Images of an experimental peach orchard were acquired from the Parma Research and Extension Center of the University of Idaho using an off-the-shelf unmanned aerial system (UAS), equipped with a multispectral camera (Near-infrared, Green, Blue). The orchard has different stone fruit varieties and different plant training system. Individual tree images (high-resolution) and arrays of trees images (low-resolution) were acquired to evaluate the detection capability. The image processing algorithm was based on different vegetation indices. Initial results showed that the image processing algorithm could detect peach blossoms and demonstrate good potential as a monitoring tool for orchard management.

Caveolin-1 (Cav-1) is 22 kDa caveolae protein, acts as a scaffold within caveolar membranes. It interacts with alpha subunits of G-protein and thereby regulates their activity. Earlier studies reported elevated or up-regulated levels of caveolin-1 in the serum of prostate cancer patients. Secreted Cav-1 promotes angiogenesis, cell proliferation and anti-apoptotic activities in prostate cancer patients. Cav-1 upregulation is mainly related to prostate cancer metastasis. Keeping above facts in view, the present study was designed to explore Cav-1 as a target for prostate cancer therapy using computational approach. Molecular docking, structural base molecular modelling and molecular dynamics simulations were performed to investigate Cav-1 inhibitors. A predictive model was generated and validated to establish a stable structure. ZINC database of biogenic compounds was used for induced fit docking (IFD) and high throughput virtual screening. The H-bond interactions of the compounds with active site residues of Cav-1 were estimated by IFD and 100 ns long molecular dynamic simulations. The reported compounds showed significant binding and thus can be considered as potent therapeutic inhibitors of Cav-1. This study provides a valuable insight into biochemical interactions of Cav-1 for therapeutic applications and warrants for experimental validation of the predicted ‘active(s)’.

Aiming at the problems that are poor generalization performance, low retrieval accuracy and large time consumption of existing content-based image retrieval system, the hierarchical image retrieval method based on multi feature fusion is proposed in this paper. The retrieval accuracy rates on Corel5K, UKbeach and Holidays are 68.23(Top 1), 3.73(N-S) and 88.20(mAp), respectively. The experimental results show that the method proposed in this paper can effectively improve the deficiency of single feature retrieval and save time significantly in the premise of a small amount of loss of accuracy.

SARS-CoV-2 is a novel betacoronavirus and the aetiological agent of the current COVID-19 outbreak that originated in Hubei Province, China. While polymerase chain reaction is the front-line tool for SARS-CoV-2 surveillance, application of amplification-free and culture-free methods for isolation of SARS-CoV-2 RNA, partnered with next-generation sequencing, would provide a useful tool for both surveillance and research of SARS-CoV-2. We here release into the public domain a set of bait capture hybridization probe sequences for enrichment of SARS-CoV-2 RNA from complex biological samples. These probe sequences have been designed using rigorous bioinformatics methods to provide sensitivity, accuracy, and minimal off-target hybridization. Probe design was based on existing, validated approaches for detecting antimicrobial resistance genes in complex samples and it is our hope that this SARS-CoV-2 bait capture platform, once validated by those with samples in hand, will be of aid in combating the current outbreak.

The human angiotensin-converting enzyme 2 (ACE2) has a crucial role on blood pressure control; however, ACE2 is also the primary SARS-CoV-2 (S domain) virus receptor. Inhibiting or even reducing the expression of the native ACE2 might diminish the viral entry into the cells, but may cause a failure of ACE2 biological activity, primarily in patients with comorbidities, including diabetes mellitus or hypertension. Since the ACE2 catalytic site and the SARS-Cov-2 receptor are distinct, we designed a Crispr-Cas9 model system, predicting the respective sequences for a guide RNA (gRNA) and a single-stranded oligo dideoxy nucleotide (ssODN), to introduce point mutations into the exon 1 of the human ACE2 gene, which encodes the alpha-helix, implicated on the binding of the SARS-CoV-2 envelope S protein. Protein modeling predicted that the specific substitutions of residues Phe28, Lys31, and Tyr41 for Ala at the ACE2 alpha-helix do not significantly alter ACE2 native conformation. The analysis of the impact of these mutations on ACE2 receptor function predicted a weakening of the binding of the SARS-CoV-2 protein S. An experimental genome editing of cells based on these Crispr-Cas9 elements might reduce the SARS-CoV-2 ability to enter the epithelial cell, preserving the biological activity of ACE2 enzyme.

There are limited proven therapies for the treatment of COVID-19. Vitamin C’s antioxidant, anti-inflammatory and immunomodulating effects, make it a potential therapeutic candidate, both for the prevention and amelioration of COVID-19 infection, and as an adjunctive therapy in the critical care of COVID-19, supporting anti-inflammatory treatment. This literature review focuses on vitamin C deficiency in respiratory infections including COVID-19; the mechanism of action in infectious disease and adrenal function supporting the anti-inflammatory actions of glucocorticosteroids: its role in preventing and treating colds and pneumonia and its role in treating sepsis and COVID-19. The evidence to date indicates that oral vitamin C (2-8g/d) may reduce incidence and duration of respiratory infections and intravenous vitamin C (2-24g/d) has been shown to reduce mortality, Intensive Care Unit and hospital stays, time on mechanical ventilation in severe respiratory infections. Further trials are urgently warranted. Given the favourable safety profile and low cost of vitamin C, and frequency of vitamin C deficiency in respiratory infections it may be worthwhile testing patients’ vitamin C status and treating accordingly with intravenous use within ICUs and orally with doses between 2 and 8g/day in hospitalised and infected persons.

This study aims to test a model linking destination image, perceived value, tourist satisfaction, and tourist loyalty. Based on a sample of 300 tourists travelling by car from the World Natural Heritage Site of Tianchi, China, a new model of destination image was explored and data were analysed using partial least squares structural equation modelling (PLS-SEM). The results show that perceived value and satisfaction are direct antecedents of destination loyalty. Above all, perceived value and tourist satisfaction mediate the relationship between destination image and loyalty. Finally, this study discusses the theoretical and management implications of the findings in order to boost the tourism industry in the context of car trips.

This paper has two major parts. In the first part histogram equalization for the image enhancement was implemented without using the built-in function in MATLAB. Here, at first, a color image of a rat was chosen and the image was transformed into a grayscale image. After this conversion, histogram equalization was implemented on the grayscale image. Later on, in the same image for each RGB channel, histogram equalization was implemented to observe the effect of histogram equalization on each channel. In the end, the histogram equalization was implemented to this specific color image of a rat. In the second part, for the grayscale image in part 1, the desired histogram of another colored image of a rat was introduced and histogram specification was implemented on the original colored image.

Coronavirus, also known as COVID-19, has been declared a pandemic by the World Health Organization (WHO). At the time of conducting this study, it had recorded over 1.6 million cases while more than 105,000 have died due to it, with these figures rising on a daily basis across the globe. The burden of this highly contagious respiratory disease is that it presents itself in both symptomatic and asymptomatic patterns in those already infected, thereby leading to an exponential rise in the number of contractions of the disease and fatalities. It is therefore crucial to expedite the process of early detection and diagnosis of the disease across the world. The case-based reasoning (CBR) model is an effective paradigm that allows for the utilization of cases’ specific knowledge previously experienced, concrete problem situations or specific patient cases for solving new cases. This study therefore aims to leverage the very rich database of cases of COVID-19 to solve new cases. The approach adopted in this study employs the use of an improved CBR model for state-of-the-art reasoning task in classification of suspected cases of Covid19. The CBR model leverages on a novel feature selection and semantic-based mathematical model proposed in this study for case similarity computation. An initial population of the archive was achieved with 68 cases obtained from the Italian Society of Medical and Interventional Radiology (SIRM) repository. Results obtained revealed that the proposed approach in this study successfully classified suspected cases into their categories at an accuracy of 97.10%. The study found that the proposed model can support physicians to easily diagnose suspected cases of Covid19 base on their medical records without subjecting the specimen to laboratory test. As a result, there will be a global minimization of contagion rate occasioned by slow testing and as well reduce false positive rates of diagnosed cases as observed in some parts of the globe.

Corona Virus Infectious Disease-2019 (COVID-19) outbreak originated recently at Wuhan, China in December 2019. It has already spread rapidly to more than 200 countries and has been declared a pandemic by WHO. It is caused by a beta-coronavirus named as SARS-CoV-2. There is no definitive cure, either drug or vaccine, to treat or prevent this viral disease. Recently, the crystal structure of the main protease M^pro has been determined. M^pro is responsible for the proteolytic maturation of the polyprotein essential for the viral replication and transcription, which makes it an important drug target. The discovery of new drug molecules may take years before getting to the clinics. So, considering urgency we performed molecular docking studies using FDA approved drugs to identify molecules that could potentially bind to the substrate-binding site and inhibit SARS-CoV-2 main protease (M^pro). We used the Glide module in Schrodinger software suite to perform molecular docking studies followed by MM-GBSA based energy calculations to score the hit molecules. Molecular docking and manual analysis suggest that several drugs may bind and potentially inhibit M^pro. We also performed molecular simulations studies for selected compounds to evaluate protein-drug interactions. Interestingly, we observed only one antiviral compound, Adefovir, in the top50 list of compounds. Considering bioavailability, lesser toxicity, route of administration some of the top-ranked drugs including lumefantrine (antimalarial), dipyridamole (coronary vasodilator), dihydroergotamine (used for treating migraine), hexoprenaline (anti- asthmatic), riboflavin (vitamin B2) and pantethine (vitamin B5) may be taken forward for further in vitro and in vivo experiments to investigate their therapeutic potential.

The endocannabinoid system has been found to be pervasive in mammalian species. It has also been described in invertebrate species primitive as the Hydra. Insects apparently are devoid of this otherwise ubiquitous system that provides homeostatic balance to the nervous and immune systems, as well as many other organ systems. The endocannabinoid system (ECS) has been defined to consist of three parts: 1. Endogenous ligands, 2. G-protein coupled receptors (GPCRs), and 3. Enzymes to degrade and recycle the ligands. Two endogenous molecules have been identified as ligands in the ECS to date. These are the endocannabinoids: Anandamide (arachidonoyl ethanolamide) and 2-AG (2-arachidonoyl glycerol). Two G-coupled protein receptors have been described as part of this system, with other putative GPC being considered. Coincidentally, the phytochemicals produced in large quantities by the Cannabis sativa L plant, and in lesser amounts by other plants, can interact with this system as ligands. These plant-based cannabinoids are termed, phytocannabinoids. The precise determination of the distribution of cannabinoid receptors in animal species is an ongoing project, with the canine cannabinoid receptor distribution currently receiving the most interest in non-human animals.

In our study we investigated the additive manufacturing (AM) of ceramic-based Functionally Graded Materials (FGM) by the direct AM technology Thermoplastic 3D-Printing (T3DP). Zirconia components with a varying microstructure were additively manufactured by using thermoplastic suspensions with different contents of pore forming agents (PFA) and were co-sintered defect-free. Different materials were investigated concerning their suitability as PFA for the T3DP process. Different zirconia-based suspensions were prepared and used for AM of single- and multi-material test components. All samples were sintered defect-free and in the end we could realize a brick wall-like component consisting of dense (<1% porosity) and porous (approx. 5% porosity) zirconia areas to combine different properties in one component. The T3DP opens the door to AM of further ceramic-based 4D-components like multi-color or multi-material, especially multi-functional components.

Li₂TiO₃ nanopowders were synthesized by hydrothermal process using anatase TiO₂ and LiOH H₂O as raw materials. Li₂TiO₃ crystallizes in the layered monoclinic structure (space group C2/c) with average crystallite size of 34 nm. Morphology, elemental composition and local structure of products were carried out using HRTEM, FESEM, EDS, Raman and FTIR spectroscopy. Transport properties investigated by d.c. (4-probe measurements) and a.c. (complex impedance spectroscopy) show the activation energy of 0.71 and 0.65 eV, respectively. The ionic transport properties of Li⁺ ions in nanocrystalline Li₂TiO₃ characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) validate the good electrochemical properties of this anode material for lithium-ion batteries.

β-Lactams are pharmacologically important compounds because of their various biological uses, including antibiotic and so on. β-Lactams were synthesized from benzylidene-inden derivatives and acetoxyacetyl chloride. The inhibitory effect of these compounds was also examined for human carbonic anhydrase I and II (hCA I, and II) and acetylcholinesterase (AChE). The results reveal that β-lactams are inhibitors of hCA I, II and AChE. The K_i values of β-lactams (2a-k) were 0.44-6.29 nM against hCA I, 0.93-8.34 nM against hCA II, and 0.25-1.13 nM against AChE. Our findings indicate that β-lactams (2a-k) inhibit both CA isoenzymes and AChE at low nanomolar concentrations.

1) Background: The Aicardi-Goutières syndrome (AGS) is a rare congenital disease which courses with severe psychomotor delay in neurodevelopment. We studied a 3-years and 4-months old child with very important growth and weight affectation, microcephaly and loss of his developmental skills from 16-months of age, in which previous metabolic and genetic studies discarded any abnormality. Therefore diagnosis was cerebral palsy of unknown etiology. He presented spastic paraparesia, poor fine motricity, cognitive impairment and absence of oral communication. One year after discharge, a de novo mutation was detected in a single nucleotide in the gene IFIH1: c.2317G>C, being then diagnosed of AGS. 2) Methods: Blood analysis showed very low IGF-1 and slightly elevated liver transaminases. Treatment consisted in GH (0.04 mg/kg/day), melatonin (20 mg/day, and after 3-months 50 mg/day), and daily intense neurorehabilitation (5 days/week). Tests for evaluating childhood developmental milestones (GMFM-88, BDIST and the WeeFim test) were carried out every 3-months. 3) Results: The equivalent age at admission (10-months) increased to 24-months at discharge. There were clear improvements in spasticity, fine motor function, swallowing, cognition and autonomy as well as in communication, growth and weight. 4) Conclusion: Most likely melatonin blocked or decreased the interferon signature, allowing GH and neurorehabiltation to act on neurodevelopment.

SARS CoV-2 or COVID-19 pandemic global-outbreak created the most unstable situation of human health-economy. Last two decades different parts of the word experienced smaller or bigger outbreak related to human-coronaviruses. The spike-glycoproteins of the COVID-19 (similar to SARS-CoV) attach to the angiotensin-converting-enzyme (ACE-2) and transit over a stabilized open-state for the viral-internalization to the host-cells and propagate with great efficacy. Higher rate of mutability makes this virus unpredictable/less-sensitive to the protein/nucleic-acid based-drugs. In this emergent situation, drug-induced destabilization of spike-binding to RBD could be a good strategy. In the current study we demonstrated by Bioinformatics (CASTp: Computed-Atlas-of-Surface-Topography, PyMol: molecular-visualization) and Molecular docking (PatchDock) experiments that tea flavonoids catechin-products mainly EGCG or other like theaflavin gallate demonstrated higher Atomic Contact Energy (ACE), surface area and more amino-acid interactions than hydroxychloroquine (HCQ) during binding in the central channel of the spike-protein. Moreover, out of three distinct binding-sites (I, II and III) of spike core when HCQ binds only with site III (farthest from the vCoV-RBD of ACE2 contact), EGCG and TG bind all three sites. As because site I and II is in closer contact with open state location and viral-host contact area so these drugs might have significant effects. Taking into account the toxicity/side-effects by CQ/HCQ, present drugs may be important. Our laboratory is working on tea flavonoids and other phytochemicals in the protection from toxicity, DNA/mitochondrial damage, inflammation etc. The present data might be helpful for further analysis of flavonoids in this emergent pandemic situation.

Neurofibromatosis type1 (NF1) is an autosomal dominant disorder caused by mutations in the NF1gene. Although congenital pseudarthrosis of the tibia (CPT) has frequently been associated with NF1, the underlying molecular mechanism of CPT in these NF1 patients is yet ill-understood. The aim of the present study was to detect NF1 mutations from genomic DNA and to harbor variants associated with CPT in NF1 patients. Whole-exome sequencing was first carried out with samples from two patients with CPT in one NF1 family, and a novel mutation c.2324A>G (p.E775G) in NF1 gene was identified. Additionally, a missense variant c.455C>T (p.P152L) in BCOR gene completely co-segregated with the CPT phenotype within this family. Subsequently, NF1 and NF2 genes in four other unrelated patients with both NF1 and CPT were screened using targeted sequencing. Four mutations in NF1 gene, including two known mutations (c.2288T>C/p.L763P, c.574 C>T/p.R192*) and two novel mutations (c.768delT/p.F256Lfs*25, c.2229_2230delTG/ p.V744Qfs*23) were detected. Further study confirmed that CPT was present in NF1 families, and NF1 mutations were closely associated with these complex phenotypes. Moreover, the data from the current study indicated that male gender might be a susceptibility factor for CPT in NF1. Therefore, we speculated that BCOR variants might be related to CPT phenotype among male NF1 patients.

In this short review paper we have assembled the main characteristics of partial oxidation reactions (oxidative dehydrogenation and selective oxidation to olefins or oxygenates, as aldehydes and carboxylic acids and nitriles), as well as total oxidation, particularly for depollution, environmental issues and wastewater treatments. Both gas-solid and liquid-solid media have been considered with recent and representative examples within these fields. We have also discussed about their potential and prospective industrial applications. Particular attention has been brought to new raw materials stemming from biomass and to liquid-solid catalysts cases. This review paper also summarizes the progresses made in the use of unconventional activation methods for performing oxidation reactions, highlighting the synergy of these technologies with heterogeneous catalysis. Focus has been centered on usual catalysts activation methods but also on less usual ones, such as the use of ultrasounds, microwaves, grinding (mechanochemistry) and photo-activated processes, as well as their combined use.

Recent discovery of triangular boron Nanotubes makes it a competitor of carbon in many respects. Closed forms of M-polynomial of nanotubes produce closed forms of many degree-based topological indices which are numerical parameters of the structure and, in combination, determine properties of the concerned nanotubes. In this report, we give M-polynomials of triangular boron nanotubes and recover many important topological degree-based indices of these nanotubes. We also plot surfaces associated to these nanotubes.