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Objectives: Several studies demonstrated the antioxidant and anti-inflammatory role of melatonin and celecoxib. This study is designed to explore the underlying mechanism of hepatoprotective effects of melatonin and celecoxib against ethanol-induced hepatotoxicity by morphological, and biochemical approaches.Materials and methods: Adult male rats were divided into five groups: saline, ethanol, melatonin, and celecoxib were administered for 11 consecutive days after ethanol injection. Biochemical analyses were performed for the determination of glutathione (GSH), glutathione S-transferase (GST), and inducible nitric oxide (iNOS). Immunohistochemistry was performed to determine the level of different inflammatory markers.Results: Histopathological results showed that ethanol-induced marked hepatic injury leads to cloudy swelling, hydropic degeneration, apoptosis, and focal necrosis in all hepatic zones. Biochemical analysis revealed significant increases in serum transaminases and alkaline phosphatase in the ethanol group. Oxidative stress associated with attenuated antioxidant enzymes was also spotted in the ethanol group, as ethanol down-regulated GSH, GST, and upregulated NO. Additionally, ethanol increased the activation and the expression of tumor necrotic factor (TNF-α), p-NFKB, and COX2. Finally, hepatic cellular apoptosis was clearly obvious in ethanol intoxicated animals using activated JNK staining.Conclusion: These results provided pieces of evidence that the hepatoprotective effect of melatonin and celecoxib is possibly mediated through the modulation of JNK and TNF-α signaling pathways with subsequent suppression of inflammatory and apoptotic processes.

In the present study, simultaneous effects of metallic nanoparticles and magnetohydrodynamic due to stagnation point flow of nanofluid along a wave circular cylinder is presented. The effect of induced magnetic field is incorporated to deal the boundary and thermal boundary layer domain. Mathematical modelling for momentum and energy equation is constructed that is based upon three different kinds of nanoparticles namely: copper (Cu), Titanium di oxide (TiO2), and alumina (Al2O3) within the working fluid water. Each mixture is analysed at the individual level and made comparison amongst all the mixture to examine the resistance and thermal conductivity of nanofluid within the boundary layer region. The solutions are exposed via boundary value problem using shooting method along with the Runge-Kutta-Fehlberg method. The characteristics of emerging parameters for the fluid flow and heat transfer are discussed through graphs and tables. The effects of ϕ (nanoparticle volume fraction) on heat transfer and shear stress at the wall are analysed in detail. It is finally concluded that by increasing the ratio of nanoparticles there is a significant increase in the temperature but slight decrease in the velocity profile.

Recently, it has been observed that ecological and environmental condition of Pakistan is going worse due to greenhouse gases emissions. Therefore, an immediate response is necessary to mitigate the high impact of these gases. We employed modern time series econometric models to examine the association between green revolution and carbon dioxide emission in Pakistan spanning the time period of 1972-2014. These modern econometrics techniques encompassing of Johansen cointegration, ARDL bounds testing approach and its diagnostics statistics. Evidence of the Johansen model shows significant long-run cointegration between the green revolution and carbon dioxide emission in Pakistan. Results of the ARDL model show that a 1% increase in area irrigated, agricultural tractors and fertilizer used will increase carbon dioxide emissions by 0.35, 0.33 and 0.32%, respectively. Moreover, an inverted U-shaped relation was found between crops production and carbon dioxide emission both in the short and long-run. This relationship indicates that environmental Kuznets curve hypothesis validation prevailed in the presence of green revolution. The ARDL model credibility, stability and reliability were found correct based on the diagnostic statistics. The findings of variance decomposition analysis revealed that the green revolution in Pakistan significantly causes carbon dioxide emissions.

Lithium ion batteries are considered to be smart power sources for applications in a broad range of portable electronics and fast-growing electric vehicles. However, the existing electrode system suffers from a limited lifespan triggered by lithium alloying agglomeration, which affects the full-scale reversible insertion of Li+ into the anode material. The discovery of novel alternative strategies that could improve the lifespan and rate performance of active electrode materials is of immense importance. Herein, we fabricated two semiconductor metalloids, selenium and tellurium, into a 1D architecture (Se/Te nanorods) and subsequently wrapped in reduced graphene oxide (rGO) nanosheets. The designed Se/Te nanorods at GO material is named Se/Te@rGO composite and investigated as the anode material for Li+ ion batteries. The Se/Te@rGO electrode showed an exceptional reversible storage capacity of 1456 mA h g−1 as compared to SeNr (400 mA h g−1) and Se/TeNr (800 mA h g−1) at 0.1 A g−1 after 100 cycles. Furthermore, when cycled at 5 A g−1, the Se/Te@rGO electrode showed an initial specific capacity of 804 mA h g−1 and retained a high specific capacity of 704 mA h g−1 after 3000 cycles (99.5% C.E), indicating the superior performance of the newly fabricated hybrid material. The improved electrochemical storage performance of the Se/Te@rGO electrode material could be ascribed to the 1D Se/Te nanorod architecture, which can provide a short diffusion path for Li-ions and buffer the strain produced during charge–discharge cycles. The incorporated 2D rGO template further enhanced the mechanical strength of the active Se/Te material and suppressed its dissolution and volume expansion during lithiation/delithiation processes. Our contribution highlights substantial progress in the development of high storage materials for applications in long-life Li-ion batteries.

Objective(s): This study was designed to investigate various gastrointestinal effects of Manilkara zapota (Sapodilla), exploring its anti-diarrheal, anti-secretary, anti-spasmodic, anti-ulcer and anti-motility potential.Materials and Methods: Antidiarrheal and anti-secretary activities were investigated using castor oil induced diarrhea and castor oil induced fluid accumulation. Isolated rabbit jejunum tissues (antispasmodic) were employed for in vitro experiments. Antiulcer, antimotility and molecular docking were performed using ethanol-HCl induced ulcer assay, charcoal meal transit time and Auto Doc Vina.Results: Mz.Cr exhibited protection against castor oil-induced diarrhea (PConclusion: In present study, M. zapota is reported to exhibits anti-diarrheal, anti-secretory, anti-spasmodic, anti-motility, anti-ulcer effects and computational binding affinities against gastrointestinal targets.

S-allyl-L-cysteine (SAC) is an organosulfur compound derived from aged garlic extract (AGE). Studies have reported that AGE possesses bioprotective capacity, including antidiabetic, antimicrobial, antioxidant, and antitumor effects. The present study examined the protective effects of SAC against carbon tetrachloride (CCl4) induced hepatotoxicity in rats. Ten male Wistar rats aged 11 - 12 weeks were randomly divided into two groups (five rats/group) as control and SAC groups. All rats had ad libitum access to water, and the SAC group received water containing SAC intragastrically (200 mg/kg) once daily for five consecutive weeks. In the fifth experimental week, 50% CCl4 in olive oil (1 mL/kg) was administered intraperitoneally three times a week to induce liver injury in both groups. Rats were sacrificed at 24 hours after the last CCl4 injection, and liver tissues were excised for histopathological, immunohistochemical and antioxidant analyses. The rats in the SAC group did not show abnormal behavior, such as decreased water intake or food consumption, during the experimental period. Body weights in all groups did not change significantly over the experimental period. Histopathological analysis showed that the percentage of hepatic steatosis was lower in the SAC group at 12.75% ± 3.74% compared to 24.64% ± 5.29% in the control group (p p 4-induced liver damage by decreasing hepatic steatosis and reducing CYP2E1 expression in rats.

The deployment of new airborne small cells in conjunction with an existing network equipped with a multiple-input multiple-output (MIMO) system can be a promising solution to meet the high throughput and coverage needs of future networks. In this study, we present the potential benefits of deploying a large number of antenna elements in downlink vertical heterogeneous cellular networks (VHCNets). The network model consists of a terrestrial base station (TBS) with an array of massive antenna elements and an aerial base station (ABS) with a single antenna to provide connectivity for ground user equipment (GUEs). The locations of the TBS and ABS are modeled as two-dimensional and three-dimensional Poisson point processes, respectively. An appropriate air-to-ground channel model encompasses both line-of-sight (LOS) and non-line-of-sight (NLOS) communication between GUEs and ABS. Using the concepts of stochastic geometry, the performance of the VHCNet was analyzed in terms of coverage probability, area spectral efficiency, and average ergodic rate. The approximated expressions for these performance metrics were validated using Monte Carlo simulations, and a close match was observed between the analytical and simulated results. Based on the simulation results, subsequent use of a massive number of antennas at TBSs in conjunction with ABSs in the VHCNet can improve the overall performance of the network.

Background: The current study investigates the effects of natural chemicals like berbamine (BBR), bergepten (BRG), and carveol (CAR) on paclitaxel (PTX) associated neuro-inflammatory pain. Methods: The induction was carried out by administering 2 mg/kg PTX for a week with a day gap. On 7th, 14th and 21st days, behavioral testing was executed, and tissue was removed for molecular analysis. Results: Treatment attenuates thermal hyperalgesia, improved latency of falling, normalized the changes in body weight and increased threshold for pain sensation. The drugs increased the protective GSH and GST levels in the sciatic nerve and spinal cord, while lowering iNOS and LPO. H and E and IHC examinations confirmed that the medication reversed the abnormal alterations. Conclusion: The aforementioned natural substances inhibit COX-2, TNF-α and NF-κB over-expression, as evidenced by enzyme-linked immunosorbent assay (Elisa) and western blot, and hence provide neuroprotection in chronic constriction damage.

Respiratory diseases due to particulate matter are a serious health issue. We sought to investigate the efficacy of isopanepoxydone (ISO) isolated from theISO was isolated from a culture broth ofISO effectively inhibited CFA-induced NO production with no cytotoxicity on MH-S cells and pro-inflammatory mediators and cytokines were also inhibited (except tumor necrosis factor α and interleukin-6). ISO enhanced the protein expression of nuclear factor erythroid 2-related factor 2, while suppressing proteins in the inflammasome pathway, but did not suppress the expression of nuclear factor-kappa B. ISO also reduced detectable ROS other than preventing the activation of ASC.Pathways of action of ISO in MH-S cells that prevent oxidative damage and suppress the expression of proteins in the inflammasome pathway were investigated. ISO may be developed as a treatment for respiratory inflammation.

We demonstrate that artificial intelligence (AI) can learn four-dimensional (4D) atomistic systems in the spacetime continuum. Given the initial conditions – nuclear positions and velocities at time zero – the proposed 4D-atomistic AI (4D-A2I) models can predict nuclear positions at any time in the future or past for the simplest systems as we show for H2. For larger polyatomic molecules, AI is capable of learning distant but finite future as we demonstrate for an ethanol molecule. 4D-A2I models provide direct access to a multitude of properties at a given time such as geometries, velocities, forces, and energies which can be used in simulating physicochemical transformations and spectra. Our approach can be used as a cost-efficient alternative to traditional molecular dynamics. We show an example of a 4D-A2I model describing the dynamical behavior of ethanol at the coupled-cluster level with the speed of one nanosecond simulation time per one hour wall-clock time on a single GPU card – a previously unachievable feat with traditional Born–Oppenheimer molecular dynamics. 4D-A2I model is also demonstrated to provide direct access to atomistic time-resolved details of physicochemical transformations.

Iris recognition become one of the most accurate and reliable steadfast human biometric recognition system of the decad. This paper presents an accurate framework for iris recognition system using hybrid algorithm in preprocess and feature extraction section. The proposed model for iris recognition with significant feature extraction was divided into three main levels. First level is having pre-processing steps which are necessary for the desired tasks. Our model deploys on three types of datasets such as UBIRIS, CASIA, and MMU and gets optimal results for performing activity. At last, perform matching process with decision based classifier for iris recognition with acceptance or rejection rates. Experimental based results provide for analysis according to the false receipt rate and false refusal amount. In the third level, the error rate will be checked along with some statistical measures for final optimal results. Constructed on the outcome the planned method provided the most efficient effect as compared to the rest of the approach.

Gastric ulcer is one of the most common chronic gastrointestinal diseases characterized by a significant defect in the mucosal barrier. The current study has been conducted to evaluate the brucine anti-ulcer effect. Brucine has binding energy values ranging from −2.99 to −8.11 kcal/mol against chosen targets, according to in silico research. Brucine exhibits an inhibitory effect against Helicobacter pylori. In vivo findings revealed that brucine (3 mg/kg) showed effective results in healing ethanol-induced ulcer lesions of the gastric region in rats. Brucine showed an inhibitory effect against H+/K+-ATPase. Levels of glutathione, glutathione-s-transferase, and catalase were enhanced in the gastric rat tissue with the use of brucine, while a significant decrease in lipid peroxide levels was seen. Histopathological evaluation showed improvement in cellular architecture and a decrease in inflammatory indicators like cyclooxygenase, tumor necrosis factor, and nuclear factor kappa B expression, validated through immunohistochemistry, enzyme-linked immunosorbent assay, and Western blot techniques. In the reverse transcription–polymerase chain reaction, brucine decreased H+/K+-ATPase mRNA levels. This study reveals that brucine possesses stable binding affinities against selected targets. Brucine exhibits an anti-ulcer effect, mediated via anti-H. pylori, H+/K+-ATPase inhibition, and antioxidant and anti-inflammatory pathways.

International audience; This chapter will briefly introduce how machine learning can assist excited-state dynamics. We start with an overview of two traditional excited-state dynamics, a two-state system-bath approach in full quantum dynamics and the trajectory surface hopping approach in mixed quantum-classical dynamics. Then, we introduce a combination of machine learning with each of these two approaches. Finally, we present case studies in a tutorial format, enabling readers to perform simple dynamics simulations on model systems and realistic molecules.

Human telencephalon is an evolutionarily advanced brain structure associated with many uniquely human behaviors and disorders. However, cell lineages and molecular pathways implicated in human telencephalic development remain largely unknown. We produce human telencephalic organoids from stem cell-derived single neural rosettes and investigate telencephalic development under normal and pathological conditions. We show that single neural rosette-derived organoids contain pallial and subpallial neural progenitors, excitatory and inhibitory neurons, as well as macroglial and periendothelial cells, and exhibit predictable organization and cytoarchitecture. We comprehensively characterize the properties of neurons in SNR-derived organoids and identify transcriptional programs associated with the specification of excitatory and inhibitory neural lineages from a common pool of NPs early in telencephalic development. We also demonstrate that neurons in organoids with a hemizygous deletion of an autism- and intellectual disability-associated geneSHANK3exhibit intrinsic and excitatory synaptic deficits and impaired expression of several clustered protocadherins. Collectively, this study validates SNR-derived organoids as a reliable model for studying human telencephalic cortico-striatal development and identifies intrinsic, synaptic, and clustered protocadherin expression deficits in human telencephalic tissue withSHANK3hemizygosity.

This study empirically examined the impact of information and communication technology (ICT) on transaction costs in the sales stage from three dimensions of information costs, negotiation costs, and enforcing costs. The micro-sampling survey data was collected from 1338 vegetable growers in Hebei and Shandong provinces of China. We applied propensity score matching to examine the facts that adopting ICT can significantly decrease farmers’ information costs through improving information accuracy and reducing searching difficulty, and reducing negotiation costs by lowering the negotiation time. However, using ICT has no significant impact on default risk and transportation difficulty thus enforcing costs of farmers have a slight difference. Therefore, a coordinated set of policies including cultivating farmers’ ability to obtain information, advancing the construction of vegetable distribution channels and improving the market supervision mechanism are put forward.

Nonadiabatic quantum dynamics are important for understanding light-harvesting processes, but their propagation with traditional methods can be rather expensive. Here we present a one-shot trajectory learning approach that allows to directly make ultra-fast prediction of the entire trajectory of the reduced density matrix for a new set of such simulation parameters as temperature and reorganization energy. The whole 10ps long propagation takes 70 milliseconds as we demonstrate on the comparatively large quantum system, the Fenna–Matthews–Olsen (FMO) complex. Our approach also significantly reduces time and memory requirements for training.

Additional file 1: Figure S1. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and omeprazole with hydrogen potassium atipase pump (H+/K+-ATPase) evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S2. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and phenoxy benzamine with muscarinic receptor (M1) respectively, evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S3. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4- nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and ranitidine with histamine receptor (H2) respectively, evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S4. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4- nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and aspirin with cyclooxiginase-1 (COX1) respectively, evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S5. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and meclofenamate with cyclooxiginase-2 (COX2) respectively, evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S6. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and dinopristone with prostaglandin-E2 (PGE2) respectively, evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S7. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4- nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and curcumin with nuclear factor kappa B (NFĸB) respectively, evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S8. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and aspirin with tumor necrosis factor alpha (TNF- α) respectively, evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S1A. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and Omeprazole with hydrogen potassium ATPase (H+/K+-ATPase) evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S2A. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and Phenoxy-benzamine with Muscarinic receptor (M1) evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S3A. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and Ranitidine with histaminergic receptor (H2), evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S4A. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and Aspirin with cyclooxygenase-1 (COX1), evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S5A. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and Meclofinamate with cyclooxygenase-2 (COX2) evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S6A. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl) amino)-4-oxobut-2-enoate (DTN) and Dinopristone with prostaglandin-E2 (PGE2), evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S7A. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl)amino)-4-oxobut-2-enoate (DTN) and Curcumin with Nuclear Factor kappa-B (NFκB) evaluated through Biovia Discovery Studio Visualizer (DSV) 2016. Figure S8A. (A) and (B) represents 2D-interactions of 2E,2′E) dibutylstannanediyl bis(4-(4-nitrophenyl) amino)-4-oxobut-2-enoate (DTN) and aspirin with Tumor necrosis factor alpha (TNF-α) evaluated through Biovia Discovery Studio Visualizer (DSV) 2016.

In this paper, we discuss the Anthroponotic Cutaneous Leishmania transmission. In addition, we develop a mathematical model for the Anthroponotic Cutaneous Leishmania transmission and consider its qualitative behavior. We derive the threshold number $R_{0}$ R 0 of the model using the next generation method. In the disease-free case, we carry out the local and global stability under the condition $R_{0} R 0 < 1 . Moreover, we derive the global stability at the disease-free equilibrium point by utilizing the Castillo-Chavez method. On the other hand, at the endemic equilibrium point, we show the local and global stability to be held under specific conditions and $R_{0}>1$ R 0 > 1 . We also establish the global stability at the endemic equilibrium point with the help of a geometrical approach, which is a generalization of Lyapunov theory, by using a second additive compound matrix. Finally, we take into account the sensitivity analysis of the threshold number with other parameters. We also discuss several graphs of important parameters.

Open-chain imaginary-time path-integral sampling approach known with the acronym OPSCF (J. Chem. Phys. 148, 102340 (2018)) is an approach to the calculation of approximate symmetrized quantum time correlation functions. In OPSCF approach, the real time t is treated as a parameter, and therefore for each real time t, a separate simulation on the imaginary time axis is needed to be run, which makes the OPSCF approach quite expensive and as a result, the approach loses the advantage of being a standard path-integral sampling approach. In this study, I propose that the use of OPSCF approach in combination with machine learning can reduce the computational cost by 75% to 90% (depending on the problem at hand). Combining OPSCF approach with ML is very straight forward which gives an upper hand to OPSCF approach over the trajectory-based methods such as the centroid molecular dynamics (CMD) and the ring-polymer molecular dynamics (RPMD).

Exploring excitation energy transfer (EET) in light-harvesting complexes (LHCs) is essential for understanding the natural processes and design of highly-efficient photovoltaic devices. LHCs are open systems, where quantum effects may play a crucial role for almost perfect utilization of solar energy. Simulation of energy transfer with inclusion of quantum effects can be done within the framework of dissipative quantum dynamics (QD), which are computationally expensive. Thus, artificial intelligence (AI) offers itself as a tool for reducing the computational cost. Here we suggest AI-QD approach using AI to directly predict QD as a function of time and other parameters such as temperature, reorganization energy, etc., completely circumventing the need of recursive step-wise dynamics propagation in contrast to the traditional QD and alternative, recursive AI-based QD approaches. Our trajectory-learning AI-QD approach is able to predict the correct asymptotic behavior of QD at infinite time. We demonstrate AI-QD on seven-sites Fenna-Matthews-Olson (FMO) complex.

Keeping in view the aim of better alternatives of 4-Hydroxy-3-(3-oxo-1-phenylbutyl)-2H-chromen-2-one (warfarin), eleven analogs of warfarin have been synthesized with the goal to increase enantioselectivity of (S) enantiomer by using appropriate catalyst and minimize tautomerism by replacing methyl group of the side chain with aryl group. There are many reports of the serious complications with warfarin use, which are associated with the tautomeric forms of warfarin. The key step was highly enantioselective Michael addition of variously substituted chalcone and 4-hydroxycoumarin by using cinchona based 9-amino-9-deoxyepiquinine as chiral catalyst. Synthesized compounds were characterized by IR, 1HNMR,13CNMR, EIMS and CD studies. Enantiomeric excess (%ee) was determined by chiral HPLC which was upto 98%. Synthesized analogues were screened for anticoagulant, antibacterial and antifungal activities. In-vitro anticoagulant activity was evaluated by plasma recalcification time (PRT) method and out of eleven, ten synthesized compounds showed improved IC50 values as compaired to IC50 values of standard drug warfarin. Compound 4 showed 68.25% inhibation against staphylococcus aureus and compound 7 showed 68% inhibation against bacillus subtillis, gram positive strains of bacteria, compound 6 shows 70% inhibation against fungal strain candida albicans. Furthermore, molecular docking studies were carried out with Vitamin K1 epoxide reductase VKOR1 receptor 3kp9, a potential target of warfarin for anticoagulant activity.

The Gain assisted medium is being investigated to modify the rotary photon drag with the phase and angular momentum of the photon. Significant gain doublets and normal/anomalous dispersion with high subliminal/superluminal are controlled and modified by the angular quantum number and phase of angular momentum of the probe beam. Parameters of pump and control and angular momentum of probe fields enhanced photon drag from micro radian to milli radian. A $$\pm\,5$$ micro radian drag is tune to $$\pm\, 100$$ milli radian with these parameters. The rotary photon drag show large fluctuation with phase and quantum number of angular momentum of probe beam. The rotary photon drag is greatly improved as compared to the previously studied cases. The work is useful for advancing the technologies of position control, phase matching conditions and special modes of imaging coding.

Routinely used anti-inflammatory drugs are associated with off-target effects such as cyclooxygenase (COX)-1 inhibition and gastric ulcers. The aim of this study is to examine the anti-inflammatory potential and gastroprotective effects of synthetic amino acid derivatives of 2-mercaptobenzimidazole (MBAA1, MBAA2, MBAA3, MBAA4 and MBAA5). The results showed that compound MBAA5 possess a potential anti-inflammatory action by inhibition of 15-LOX and COX-2. MBAA5 also attenuated the pro-inflammatory cytokines and mediators (TNF-α, IL-1β and COX-2) in rat hind paw in carrageenan-induced inflammatory model of rat. 2-mercaptobenzimidazole derivative, MBAA5 also inhibited gastric H+/K+ ATPase and demonstrated a better selectivity index for COX-2 (SI 27.17) in comparison to celecoxib (SI 41.43). Molecular docking studies predicted the binding interactions of the synthesized compounds with retrieved target proteins of H

Today, the world is confronted with the issue of environmental pollution as a result of our dependence on fossil fuels for our energy needs. Developed and developing countries are therefore adopting different strategies to curb environmental problems. This work is thus designed to probe the effect of renewable energy (RE), information and communication technologies (ICT), government stability, and GDP on ecological footprints (EF) in G11 nations. We utilized the annual data from 1990–2020 and applied robust methodologies to present the findings. The CS-ARDL method shows that renewable energy, ICT, and government stability are essential factors in lowering environmental pollution in G11 countries. Therefore, in light of the findings, this work suggests an increase in the use of RE sources such as solar, wind, and hydropower in the total energy mix of the various countries. RE usage improves air quality and saves the natural environment from further destruction. The countries also need to enhance their communication technologies in the economic sector. Moreover, policymakers must also introduce the required policies that would promote the use of RE in various countries. This will make people adopt clean energy sources at the domestic and commercial levels.

The type of environments to which a quantum system is exposed has a significant impact on the quantum system’s entanglement and coherence protection. In this regard, we investigate the time evolution of tripartite entanglement and coherence in GHZ-like state when subject to independent classical environments. In particular, we focus on local environments with the same and mixed disorders, resulting in various Gaussian noisy conditions, namely pure power-law noise, pure fractional Gaussian noise, power-law noise maximized, and fractional Gaussian noise maximized configurations. We show that the environments with mixed disorders are more detrimental than those having single kind of disorder for entanglement and coherence preservation using time-dependent quantum negativity, entanglement witnesses, purity, and decoherence metrics. Besides, there is no ultimate solution for avoiding the negative consequences of fractional Gaussian noise-assisted classical environments in both pure and mixed noise conditions. Not only the noise, but also the number of qubits driven by a certain noise, has been discovered to strongly influence the amount, nature of the decay, and preservation intervals. We also show that the GHZ-like states can be modelled in classical channels driven by pure power-law noise for extended quantum correlations, coherence, and quantum information preservation. In addition, we compare the entanglement measurement efficiency between entanglement witness and negativity measures.

The lack of morphological differentiation among chiropteran species and cryptic speciation impedes species identification. So, DNA-based approaches boost species identification and are increasing biological diversity. Rhyneptesicus nasutus (Sind Serotine Bat) is a rarely distributed and poorly studied species in Pakistan. This study explores the range extension of Sind bat within the territorial limits of Pakistan from Sind and Baluchistan to Federally Administered Areas (FATA) of Pakistan. No molecular record exists for the species in Pakistan. In the present study, we for the first time present the data to confirm the species identification by genetic marker (cytochrome b) along with morphometric analysis of Rhyneptesicus nasutus from Pakistan. The neighbor-joining tree based on Kimura-2 parameters was created to infer the phylogenetic analyses. We sequenced the cytochrome b gene segment and conducted a phylogenetic analysis with previously published data from other countries. Sequences from Pakistan made a clade with Iranian Rhyneptesicus nasutus species suggesting a common ancestry. Various morphometric parameters (mean values) were measured like Head and Body length (44.3mm), Tail length (43.4mm), Hindfoot length (8.3mm), Forearm length (35.7mm), and Ear length 36mm while 5th Metacarpal Length, 4th Metacarpal Length, and 3rd Metacarpal Lengths were 33.2mm, 34.7mm, 35.3mm. Approaches based on DNA barcoding reveals high diversity of bat species in the study area. The data will enable researchers to build an improved evolutionary landscape of the Serotine bats from this region and subsequently reconstruct a detailed evolutionary history of the genus. Further research is required to test other molecular markers to support the findings of the current study in Pakistan.

We investigated whether isoleucilactucin, an active constituent of Ixeridium dentatum, reduces inflammation caused by coal fly ash (CFA) in alveolar macrophages (MH-S). The anti-inflammatory effects of isoleucilactucin were assessed by measuring the concentration of nitric oxide (NO) and the expression of pro-inflammatory mediators in MH-S cells exposed to CFA-induced inflammation. We found that isoleucilactucin reduced CFA-induced NO generation dose-dependently in MH-S cells. Moreover, isoleucilactucin suppressed CFA-activated proinflammatory mediators, including cyclooxygenase-2 (COX2) and inducible NO synthase (iNOS), and the proinflammatory cytokines such as interleukin-(IL)-1β, IL-6, and tumor necrosis factor (TNF-α). The inhibiting properties of isoleucilactucin on the nuclear translocation of phosphorylated nuclear factor-kappa B (p-NF-κB) were observed. The effects of isoleucilactucin on the NF-κB and mitogen-activated protein kinase (MAPK) pathways were also measured in CFA-stimulated MH-S cells. These results indicate that isoleucilactucin suppressed CFA-stimulated inflammation in MH-S cells by inhibiting the NF-κB and MAPK pathways, which suggest it might exert anti-inflammatory properties in the lung.

We investigate the preservation of quantum coherence and entanglement carried by the three non-interacting qubits during their evolution in the presence of an external fluctuating field characterized by a classical Gaussian noise. Initially, the three non-interacting qubits are considered in two different maximally entangled states, namely Greenberger–Horne–Zeilinger ( $$\mathcal {X}_{G}$$ ) and Werner $$(\mathcal {X}_{W})$$ state. Besides this, we study the time evolution of the two states in three different schemes, namely: common, mixed, and independent system–environment couplings. By deploying different measures, we show that the system–environment coupling and the Gaussian noise greatly affected the quantum correlation and coherence. We also found that the non-local correlation and coherence remain more dominant and robust in common system–environment coupling for the $$\mathcal {X_G}$$ state under the Gaussian noise. Hence, this kind of feature of the $$\mathcal {X}_{G}$$ state is a vital resource for the transmission of quantum information with reduced loss.

Natural killer T (NKT) cells, a small population of T cells, are capable of influencing a wide range of the immune cells, including T cells, B cells, dendritic cells and macrophages. In the present review, the antiviral role of the NKT cells and the strategies of viruses to evade the functioning of NKT cell have been illustrated. The nanoparticle-based formulations have superior immunoadjuvant potential by facilitating the efficient antigen processing and presentation that favorably elicits the antigen-specific immune response. Finally, the immunoadjuvant potential of the NKT cell ligand was explored in the development of antiviral vaccines. The use of an NKT cell-activating nanoparticle-based vaccine delivery system was supported in order to avoid the NKT cell anergy. The results from the animal and preclinical studies demonstrated that nanoparticle-incorporated NKT cell ligands may have potential implications as an immunoadjuvant in the formulation of an effective antiviral vaccine that is capable of eliciting the antigen-specific activation of the cell-mediated and humoral immune responses.

Bronchial asthma (BA) is a heterogeneous allergic respiratory disease with diverse inflammatory symptoms, pathology, and responses to treatment. Thyme is a natural product which is consisted of multiple phenolic compounds of therapeutic significance for treatment of cough and bronchitis. This study evaluated the efficacy of thyme oil against ovalbumin (OVA)-induced BA in an experimental rabbit model. Forty male rabbits were divided into four equal groups [control group (G1), OVA (G2), thyme oil (G3), and OVA plus thyme oil (G4)]. Animals were treated for 30 days, and clinical, histopathological (HP), histochemical (HC), immunohistochemical (IHC), morphometric, biochemical and flow cytometry methods were performed, followed by statistical analysis. All used methods revealed normal structure of the lung tissues in rabbits of G1 and G3. In contrast, the clinical examination of G2 rabbits revealed an obvious increase in the respiratory rate, sneezing and wheezing, whereas the HP, HC and IHC techniques exhibited substantial inflammatory changes in the peribronchio-vascular lung tissues with thinning, degeneration, apoptosis (using the TUNEL assay), necrosis, and shedding of the airway epithelium. Furthermore, the morphometric results confirmed significant increases in the numbers of inflammatory cells, goblet cells, eosinophils and apoptotic cells from (12, 0, 2, 2 cells) to (34,10, 16, 18 cells) respectively, as well as the area percentage of collagen fiber deposition and immunoexpression of eotaxin-1/10 high power fields. Additionally, the biochemical results revealed significant increases in the serum levels of TSLP, IL-4, IL-5, IL-9, IL-13, IgE and eotaxin-1 cytokines from (140, 40, 15, 38, 120, 100, 48) pg./ml to (360, 270, 130, 85, 365, 398, 110) pg./ml respectively, while analysis of ROS by flow cytometry revealed remarkable oxidative stress effects in G2 rabbits. On the other hand, treatment of rabbits with thyme oil in G4 substantially alleviated all OVA-induced alterations. Overall, our findings indicate for the first time that thyme oil can ameliorate OVA-induced BA via its immunomodulatory, anti-inflammatory, antiapoptotic, and antioxidant effects on the lung tissues of rabbits.

The present investigation imparts the mixed convection non-linear Falkner-Skan flow and heat flux analysis of ZnO-SAE50 nanolubricant over a stationary/moving Riga-plate in presence of thermal radiation. Additionally, velocity and thermal slip boundary conditions are considered. In the current study, a micro-convection model (Patel model) is considered. The present model has great influence in significant enrichment of heat transport capability of the nanoliquids. The similar transformed nonlinear coupled governing expressions are examined numerically by the Runge-Kutta-Fehlberg integration scheme. The important outcome of the present study is that the augmented pressure gradient impedes the motion of nano-lubricant while reverse trend is attained due to the amplification of modified Hartmann number and velocity slip at the boundary. Further, the growth of thermal slip peters out the heat transfer rate from the Riga plate.

We discuss the time evolution of entanglement, purity, and coherence of two non-interacting maximally entangled qubits in two different classical environmental configurations: bipartite and independent system–environment configuration. Gaussian noises, such as fractional Gaussian $$(\mathcal {F_G})$$ and power-law ( $$\mathcal {P_L})$$ noise, are considered characterizing these environments. In particular, we are interested in exploring the dephasing effects in two qubits caused by the Gaussian noises in pure and mixed situations using entanglement witness, concurrence, purity, and decoherence measures. We notice both the noises in pure and in mixed forms are highly dephasing, and the bipartite quantum correlation, purity, and coherence eventually disappear after a finite interaction time. We notice that the current quantum phenomena decay faster under $$\mathcal {F_G}$$ noise than under $$\mathcal {P_L}$$ noise. Also, in independent system–environment configuration, the bipartite state is found to have slightly longer quantum correlation, purity, and coherence preservation than common environments, suggesting it more favourable for such quantum operations. For increasing values of the memory parameter of the $$\mathcal {F_G}$$ noise, the entanglement, purity, and coherence become initially robust, defying the dephasing character of parameters of nearly all the noises. The wide spectrum of the pure $$\mathcal {P_L}$$ noise can be readily exploited to design long preservation effects, especially by fixing the noise parameters to utmost low values. Also, the decay outlook induced by both noises is a monotonous function of time, with no entanglement sudden death and births observed.

Infrastructure service model provides different kinds of virtual computing resources such as networking, storage service, and hardware as per user demands. Host load prediction is an important element in cloud computing for improvement in the resource allocation systems. Hosting initialization issues still exist in cloud computing due to this problem hardware resource allocation takes serval minutes of delay in the response process. To solve this issue prediction techniques are used for proper prediction in the cloud data center to dynamically scale the cloud in order for maintaining a high quality of services. Therefore in this paper, we propose a hybrid convolutional neural network long with short-term memory model for host prediction. In the proposed hybrid model, vector auto regression method is firstly used to input the data for analysis which filters the linear interdependencies among the multivariate data. Then the enduring data are computed and entered into the convolutional neural network layer that extracts complex features for each central processing unit and virtual machine usage components after that long short-term memory is used which is suitable for modeling temporal information of irregular trends in time series components. In all process, the main contribution is that we used scaled polynomial constant unit activation function which is most suitable for this kind of model. Due to the higher inconsistency in data center, accurate prediction is important in cloud systems. For this reason in this paper two real-world load traces were used to evaluate the performance. One is the load trace in the Google data center, while the other is in the traditional distributed system. The experiment results show that our proposed method achieves state-of-the-art performance with higher accuracy in both datasets as compared with ARIMA-LSTM, VAR-GRU, VAR-MLP, and CNN models.

Objective: To assess the prevalence of temporomandibular ailments and their severity in dental undergraduate students. Study Design: Cross sectional study Place and Duration of Study: Department of Orthodontics, Bacha Khan Medical & Dental College, Mardan from1st October 2020 to 31st March 2021. Methodology: Five hundred and fifty dentistry students were enrolled. After ethical approval each student and written permission for participating in this study was taken. A Fonseca questionnaire was used for assessing the temporomandibular ailments. Responses in form of yes, no and sometimes were scored as 10, 0 and 5 points. A score between 0-15 was considered as nil for temporomandibular disorders while 20-40 as mild, 45-65 as moderate and 70-100 as severe. Results: Three hundred and forty-seven students were nil for temporomandibular, 112 were mild, 58 were moderate while 33 were severe. Conclusion: A 37% had temporomandibular disorders in dentistry students with severity common in 6 percent. Keywords: Temporomandibular ailment, Prevalence, Severity

The development of a durable and efficient composite material that could perform a long-life antibacterial activity and radical scavenging ability is highly needed. In this paper, selenium nanostructures of different morphologies were synthesized by a wet chemical method under mild experimental setup. Silver nanoparticles were doped on the surface of these nanostructures and successfully characterized by X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray, and high-resolution transmission electron microscopy. The potential applications of the designed composite were investigated in multiple disciplines including antibacterial, antioxidant, and photocatalytic activities. The selenium silver (Se–Ag) nanocomposite was employed as an antibacterial agent against a Gram-positive bacterium and a Gram-negative bacterium, and our findings disclosed that the designed composite is an excellent material in inhibiting the challenged bacterial strains. The Se–Ag composite has shown excellent activity with 30-mm inhibition zone at 2 mg/ml concentration, and maintains significant antibacterial efficacy for 72 h, indicating its sustainable performance for a long-life period. Furthermore, Se–Ag nanocomposite also exhibited a significant radical scavenging property against 2,2-diphenyl-1-picrylhydrazyl free radical and an enhanced photocatalytic activity (90–95%) with complete dye decolorization in 70 min. The superior antibacterial activity (zone of inhibition 30 mm), photocatalytic (95%) and antioxidant performance (78%) of the nanocomposite are due to the combined antibacterial (17 mm), photocatalytic (~ 30%) and antioxidant potentials (15%) of the Ag and Se (16 mm, 40%, 25%), respectively.

Selenium (Se), a member of the sulfur family, is considered as a potential alternative cathode material due to its high electronic conductivity and comparable volumetric capacity density to sulfur. Herein, we report on a simple one-step procedure to prepare trigonal selenium nanorods (t-Se) on graphene oxide (GO) without using any surfactant. The developed method does not utilize any harmful chemicals or harsh experimental conditions, and is, therefore, friendly from the environmental and economic point of views. We discovered that well-dispersed Se nanorods can be prepared at 20 mM Se under heating at 85 °C for 3 h. The successful growth of t-Se rods on GO sheets was confirmed by X-ray diffraction (crystalline structure), transmission electron microscopy (morphology), Raman spectroscopy (crystalline form and defects), and XPS technique (elemental composition). The Se nanorod-loaded GO composite (GO–Se) displayed a promising specific capacity of 405.5 mAh g−1 at a high current density (10 A g−1) and high cycling stability with a negligible capacity decay over 1000 cycles. Importantly, the GO–Se electrode delivered a high reversible capacity of 471.5 mAh g−1 at 0.5 A g−1. The improved electrical performance of the GO–Se composite could be attributed to the electrical conductivity and unique architecture of reduced graphene, which effectively enhances the utilization of active Se rods and significantly augment the electronic conductivity of the GO–Se electrode. The present study demonstrates that a hybrid system of 1D t-Se impregnated GO composite could be a promising cathode material for long-life batteries and other storage devices.