A Review on Cucumis sativus L. and its Anti-Ulcer Activity

The term "medicinal plant" refers to a plant that has active components with therapeutic properties and is used to treat disease or illness in various medical systems or conventionally. Every continent uses medicinal plants extensively and successfully. Herbal medicine is an extremely well-known and well-documented technique in Asia. Cucumis sativus L. is a well-known medicinal herb having variety of pharmacological activity. In traditional Unani medicine system this plant is use to cure variety of disease, ulcer is one of them. In this article we have discussed about its anti-ulcer potentiality

Bibliometric of Feature Selection Using Optimization Techniques in Healthcare using Scopus and Web of Science Databases

Feature selection technique is an important step in the prediction and classification process, primarily in data mining related aspects or related to medical field. Feature selection is immersive with the errand of choosing a subset of applicable features that could be utilized in developing a prototype. Medical datasets are huge in size; hence some effective optimization techniques are required to produce accurate results. Optimization algorithms are a critical function in medical data mining particularly in identifying diseases since it offers excellent effectiveness in minimum computational expense and time. The classification algorithms also produce superior outcomes when an objective function is built using the feature selection algorithm. The solitary motive of the research paper analysis is to comprehend the reach and utility of optimization algorithms such as the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO) and the Ant Colony Optimization (ACO) in the field of Health care. The aim is to bring efficiency and maximum optimization in the health care sector using the vast information that is already available related to these fields. With the help of data sets that are available in the health care analysis, our focus is to extract the most important features using optimization techniques and work on different algorithms so as to get the most optimized result. Precision largely depends on usefulness of features that are taken into consideration along with finding useful patterns in those features to characterize the main problem. The Performance of the optimized algorithm finds the overall optimum with less function evaluation. The principle target of this examination is to optimize feature selection technique to bring an optimized and efficient model to cater to various health issues. In this research paper, to do bibliometric analysis Scopus and Web of Science databases are used. This bibliometric analysis considers important keywords, datasets, significance of the considered research papers. It also gives details about types, sources of publications, yearly publication trends, significant countries from Scopus and Web of Science. Also, it captures details about co-appearing keywords, authors, source titles through networked diagrams. In a way, this research paper can be useful to researchers who want to contribute in the area of feature selection and optimization in healthcare. From this research paper it is observed that there is a lot scope for research for the considered research area. This kind of research will also be helpful for analyzing pandemic scenarios like COVID-19

Fabrication of PVA-Silver nanoparticle composite film for elimination of microbial contaminant from effluent

The effluent contains many harmful microbes which should be eliminated before it is discharged into a water body. Silver nanoparticles (AgNPs) being high-quality significance and have a great impact on this research field as it inhibits microbial proliferation and infection. Therefore, it may use for Bioremediation purposes, our laboratory is fascinated by the production of polymer matrix entrapment silver nanoparticles for in situ bio-remediation purposes. The AgNPs was prepared from sawdust by decoction method. The yellowish solution turns into dark brown colour indicating the formation of AgNPs. A sharp SPR (Surface Plasmon Resonance) band formation in UV-vis spectroscopy scan establishes the formation and stability of silver nanoparticles in an aqueous solution. SEM microphotograph indicated roughly spheroidal structure with (63±3) nm average diameters of newly synthesized AgNp. Polyvinyl alcohol (PVA) is eco-friendly and non-toxic to the environment was chosen for the preparation of polymeric matrix. The non-toxic concentration (1 μg/mL) of AgNp was dispersed into PVA solution followed by cross-linked with maleic acid. PVA- maleic acid is cross-linked by the formation of an ester bond, whereas silver nanoparticles physically entrap into the cross-linked matrix. The silver nanoparticles were released from the matrix nearly after 10 min of swelling of the composite film. In a microbial assay using E. coli agar medium, PVA-AgNp composite film shows the significant killing of microorganisms. Microbial elimination is measured indirectly by pH measurement and dissolved oxygen concentration measurement of the effluent in situ against RO- water, taken as control. The dissolved oxygen concentration from RO water and effluent water was measured on Day “0” followed by treatment and incubation at the BOD chamber. The treatment with PVA-AgNp composite film reduced the BOD Level and increase dissolved oxygen level simultaneously increasing the quality of water

Bibliometric of Feature Selection Using Optimization Techniques in Healthcare using Scopus and Web of Science Databases

Feature selection technique is an important step in the prediction and classification process, primarily in data mining related aspects or related to medical field. Feature selection is immersive with the errand of choosing a subset of applicable features that could be utilized in developing a prototype. Medical datasets are huge in size; hence some effective optimization techniques are required to produce accurate results. Optimization algorithms are a critical function in medical data mining particularly in identifying diseases since it offers excellent effectiveness in minimum computational expense and time. The classification algorithms also produce superior outcomes when an objective function is built using the feature selection algorithm. The solitary motive of the research paper analysis is to comprehend the reach and utility of optimization algorithms such as the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO) and the Ant Colony Optimization (ACO) in the field of Health care. The aim is to bring efficiency and maximum optimization in the health care sector using the vast information that is already available related to these fields. With the help of data sets that are available in the health care analysis, our focus is to extract the most important features using optimization techniques and work on different algorithms so as to get the most optimized result. Precision largely depends on usefulness of features that are taken into consideration along with finding useful patterns in those features to characterize the main problem. The Performance of the optimized algorithm finds the overall optimum with less function evaluation. The principle target of this examination is to optimize feature selection technique to bring an optimized and efficient model to cater to various health issues. In this research paper, to do bibliometric analysis Scopus and Web of Science databases are used. This bibliometric analysis considers important keywords, datasets, significance of the considered research papers. It also gives details about types, sources of publications, yearly publication trends, significant countries from Scopus and Web of Science. Also, it captures details about co-appearing keywords, authors, source titles through networked diagrams. In a way, this research paper can be useful to researchers who want to contribute in the area of feature selection and optimization in healthcare. From this research paper it is observed that there is a lot scope for research for the considered research area. This kind of research will also be helpful for analyzing pandemic scenarios like COVID-19

Solvation change and ion release during aminoacylation by aminoacyl-tRNA synthetases

Discrimination between cognate and non-cognate tRNAs by aminoacyl-tRNA synthetases occurs at several steps of the aminoacylation pathway. We have measured changes of solvation and counter-ion distribution at various steps of the aminoacylation pathway of glutamyl- and glutaminyl-tRNA synthetases. The decrease in the association constant with increasing KCl concentration is relatively small for cognate tRNA binding when compared to known DNA–protein interactions. The electro-neutral nature of the tRNA binding domain may be largely responsible for this low ion release stoichiometry, suggesting that a relatively large electrostatic component of the DNA–protein interaction free energy may have evolved for other purposes, such as, target search. Little change in solvation upon tRNA binding is seen. Non-cognate tRNA binding actually increases with increasing KCl concentration indicating that charge repulsion may be a significant component of binding free energy. Thus, electrostatic interactions may have been used to discriminate between cognate and non-cognate tRNAs in the binding step. The catalytic constant of glutaminyl-tRNA synthetase increases with increasing osmotic pressure indicating a water release of 8.4 ± 1.4 mol/mol in the transition state, whereas little change is seen in the case of glutamyl-tRNA synthetase. We propose that the significant amount of water release in the transition state, in the case of glutaminyl-tRNA synthetase, is due to additional contact of the protein with the tRNA in the transition state

Integrating Organic Lewis Acid and Redox Catalysis: The Phenalenyl Cation in Dual Role

In recent years, merging different types of catalysis in a single pot has drawn considerable attention and these catalytic processes have mainly relied upon metals. However, development of a completely metal free approach integrating organic redox and organic Lewis acidic property into a single system has been missing in the current literature. This study establishes that a redox active phenalenyl cation can activate one of the substrates by single electron transfer process while the same can activate the other substrate by a donor–acceptor type interaction using its Lewis acidity. This approach has successfully achieved light and metal-free catalytic C–H functionalization of unactivated arenes at ambient temperature (39 entries, including core moiety of a top-selling molecule boscalid), an economically attractive alternative to the rare metal-based multicatalysts process. A tandem approach involving trapping of reaction intermediates, spectroscopy along with density functional theory calculations unravels the dual role of phenalenyl cation

Reduced-Phenalenyl-Based Molecule as a Super Electron Donor for Radical-Mediated C–N Coupling Catalysis at Room Temperature

We demonstrate that an in situ generated di-reduced phenalenyl (PLY) species accumulates sufficiently high energy and acts as a super electron donor to generate aryl radicals from aryl halides to accomplish Buchwald–Hartwig-type C–N cross-coupling reactions at room temperature. This catalytic protocol does not require any external stimuli such as heat, light, or cathodic current. This protocol shows a wide variety of substrate scope covering different genres of aryl and heteroaryl halides with various aromatic as well as aliphatic amines and late-stage functionalization of the well-known natural products. The control experiments, along with extensive density functional theory (DFT) calculations, unveil that the aryl radical is generated by a single electron transfer from the di-reduced PLY to the aryl halide substrate. The aryl radical acts as an electrophile and binds with amine, leading to the chemically driven radical-mediated C–N cross-coupling under transition-metal-free conditions

Piceatannol induces regulatory T cells and modulates the inflammatory response and adipogenesis

The beneficial effects of the polyphenolic compound piceatannol (PC) has been reported for metabolic diseases, antiproliferative, antioxidant, and anti-cancer properties. Despite its beneficial effects on inflammatory diseases, little is known about how PC regulates inflammatory responses and adipogenesis. Therefore, this study was designed to determine the effects of PC on the inflammatory response and adipogenesis. The effect of PC on splenocytes, 3T3-L1 adipocytes, and RAW264.7 macrophages was analyzed by flow cytometry, qRT-PCR, morphometry, and western blot analysis. PC induced apoptosis in activated T cells in a dose-dependent manner using stimulated splenocytes and reduced the activation of T cells, altered T cell frequency, and interestingly induced the frequency of regulatory T (Treg) cells as compared to controls. PC suppressed the expression of TNF-α, iNOS, IL-6R, and NF-κB activation in RAW264.7 macrophages after lipopolysaccharides (LPS)-induction as compared to the control. Interestingly, PC altered the cell morphology of 3T3-L1 adipocytes with a concomitant decrease in cell volume, lipid deposition, and TNF-α expression, but upregulation of leptin and IL-1β. Our findings suggested that PC induced apoptosis in activated T cells, decreased immune cell activation and inflammatory response, and hindered adipogenesis. This new set of data provides promising hope as a new therapeutic to treat both inflammatory disease and obesity

Triple-photoinduced electron transfer (tri-PET) catalysis for activation of super strong bonds

Single electron redox processes allow the formation of highly reactive radicals – valuable intermediates that enable unique transformations in organic chemistry (1,2). An established concept to create radical intermediates is photoexcitation of a catalyst to a higher energy intermediate, subsequently leading to a photoinduced electron transfer (PET) with a reaction partner (3–7). The known concept of consecutive photoinduced electron transfer (con PET) leads to catalytically active species even higher in energy by the uptake of two photons (8). This process has already been used widely for catalytic reductions; however, limitations towards strong bonds and electron rich substrates remain (9,10). Generally speaking, increased photon uptake leads to a more potent reductant. Here, we introduce triple-photoinduced electron transfer catalysis, termed tri-PET, enabled by the three-photon uptake of a dye molecule leading to an excited dianionic super-reductant which is more potent than Li metal (11) – one of the strongest chemical reductants known. Irradiation of the metal-free catalyst by violet light enables the cleavage of strong carbon-fluoride bonds and reduction of other halides even in very electron-rich substrates. The resulting radicals are quenched by hydrogen atoms or engaged in carbon-carbon and carbon-phosphorus bond formations, highlighting the utility of tri-PET for organic chemistry. Thorough spectroscopic, chemical and computational investigations are presented to understand this novel mode of photoredox catalysis. The existence of the dianion which takes up a third photon when irradiated was proven by X-ray diffraction analysis