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The purpose of this paper is to present modelling and mathematical studies of neuronal NO‐synthase and discuss the case for nitric oxide (NO) versus nitroso‐arginine (NA) theory.

Introduces recent studies, NO studied models and the experimental model before considering the diffusion‐reaction model. Enzymatic kinetics and an analysis of systems and the NA diffusion equations in mice cortex are given. Numerical results are featured.

Based on these studies, both a bio‐mathematical and physiological conclusions are given. The way to protect the brain was to inhibit the NO‐synthase of the neurons during a stroke.

The paper is of value, particularly as stroke is the second leading cause of mortality worldwide and the most common cause of dementia in western countries. In Europe, each year, over 1,200,000 people experience a stroke.

This study aims to investigate the potential of pumpkin seed oil (PSO) and zinc to attenuate oxidative stress and neuroinflammation caused by chronic mild stress (CMS) in the cerebral cortex of male rats.

The rats were submitted to stress for six weeks and then the behavior of the rats was tested by forced swimming test (FST) and novel cage test. The treated groups were given venlafaxine (20 mg/kg), pumpkin seed oil (40 mg/kg) and zinc (4 mg/kg). The cortex homogenate was used for the detection of the oxidative stress parameters, the concentration of neurotransmitters, tumor necrosis factor-α (TNF-α) and interleukin 1β (IL-1β), Na+/K+-ATPase activity, and the expression of histamine N-methyltransferase (Hnmt) and tyrosine hydroxylase (Th).

CMS causes a significant increase in immobility time in the FST and a significant decrease in the number of rearing in the novel cage test. CMS group showed a significant increase in alanine aminotransferase (ALT) activity, levels of cortisol, TNF-α, IL-1β, nitric oxide and malondialdehyde. CMS caused a significant decrease in the concentrations of serotonin, GABA, norepinephrine, and the activities of glutathione peroxidase, catalase, superoxide dismutase and Na⁺/K⁺-ATPase. CMS caused a marked reduction in the expression of Hnmt and Th in the cortex. PSO and zinc attenuated the Na⁺/K⁺-ATPase activity, oxidative parameters and neuroinflammation induced by the CMS, and this was reflected by the elevation of the concentration of neurotransmitters and reduction of cortisol and ALT, in addition to the behavior normalization. PSO and zinc attenuated the CMS by improving the antioxidant milieu and anti-inflammatory status of the cerebral cortex.

There are no studies on the effect of pumpkin seed oil on depression

Polyphenols possess anti-allergic activities. Catechin is one of the polyphenols that are abundantly present in the Acacia catechu. In this study, the authors investigated the effect of catechin isolated from A. catechu in an experimental mouse model of ovalbumin (OVA)-induced allergic asthma.

Catechin was isolated from A. catechu, and phytochemical analysis was carried out by ultraviolet visible and thin-layer chromatography (TLC), high pressure thin-layer chromatography was used for the determination of an amount of catechin present. In a first set of an experiment, the authors have carried out dose-dependent evaluation of catechin on histamine synthesis in normal rats. In another study, allergic asthma was induced in BALB/c mice by intraperitoneal injection of 50 mg OVA dissolved in 4 mg aluminum hydroxide dissolved in 0.2 ml saline on Days 0 and 14. Catechin was given orally at the dose of 100 mg/kg, once a day from Day 1 to Day 35 and after which various respiratory parameters such as tidal volume, respiratory rate and airflow rate, biochemical parameters such as histamine release from mast cells, bronchoalveolar (BAL) lavage fluid analysis and histopathology of lungs were carried out.

Catechin showed significant (p < 0.05) improvement in respiratory parameters such as tidal volume, respiratory rate and airflow rate, as well as biochemical and hematological parameters such as blood histamine, serum bicarbonate and nitric oxide levels as compared to the disease control group. The treatment also showed inhibitory effects on histamine synthesis in rat peritoneal as well as BAL mast cells. Also, a significant (p < 0.05) improvement in lung histopathology was observed with catechin.

From the present study, the authors can conclude that catechin exhibited potent anti-allergic activity by inhibition of histamine synthesis by inhibition of histidine decarboxylase enzyme. The study suggests that catechin has therapeutic potential for the treatment of allergic inflammatory disease in humans.

Diabetes is one of the most prevailed chronic diseases in the world. Pro-inflammatory cytokines play a key role in the type 2 diabetes mellitus. Pomegranate seed oil (PSO) has potential anti-inflammatory properties. The purpose of this study is to evaluate the antidiabetic effects of the use of PSO on the expression of peroxisome proliferator-activated receptor-gamma (PPAR-γ), pro-inflammatory biomarkers and lipid profile levels in obese type 2 diabetic patients.

In total, 52 patients were randomly assigned to the PSO (n = 26) and placebo (n = 26) groups. Subjects received daily PSO 3 g placebo (paraffin) in 1 g soft-gel capsules (along with breakfast, lunch and dinner meals) for eight weeks.

Serum levels of fasting blood sugar (FBS) decreased from 161.46 ± 34.44 to 143.50 ± 24.2 mg/dL (p = 0.008), IL-6 decreased from 5.17 ± 2.25 to 4.52 ± 1.90 (p = 0.049) and tumor necrosis factor alpha (TNF-α) significantly decreased from 9.17 ± 4.13 to 7.74 ± 2.44 pmol/mL in PSO group (p = 0.030). However, changes in the expression of PPAR-γ gene, serum levels of hs-CRP and lipid profile levels were not significant.

Lack of PSO concentration measurements and the short duration of the study were the key limitations. Future randomized clinical trials with a longer period of follow-up are needed to assess the potential anti-diabetic effects of PSO.

Administration of PSO in obese type 2 diabetic patients reduced the levels of FBS, interleukin 6 and TNF-α; nevertheless, changes in the insulin, lipid profiles and hs-CRP were not significant.

The aim of this paper is to better understand the impact of petroleum production facilities on ambient air quality of host airshed.

Field measurements were taken daily for four consecutive months around petroleum production facilities in the Niger Delta area, of Nigeria, one of the world's important petroleum producing areas. Statistical analysis tool and air quality analytical tool known as the air quality index (AQI) were applied on the field data obtained.

The mean measured daily concentrations of both carbon monoxide (CO) and nitrogen dioxide (NO₂) between distances 50 and 500 m of petroleum flow stations were of the range 140 – 3400 μg/m3 and 23 – 1250 μg/m3 respectively. The AQI from measured CO concentrations in the study area ranged between 1 and 44, an indication of good AQI category with no known health effects but a need for cautionary statement. Similarly, over 97 percent of the measured concentrations of NO₂ were below 0.60 ppm which implies that the AQI of the host environment of the flow stations were below 200 with respect to NO₂ thus indicating a good category of air with no health alarm. However, at the 60 m distance around a flow station, the AQI was 210 thus the quality of available air at this point could be described as very unhealthy. Generally the concentrations of CO were higher than NO₂ in all the distances from the flow stations and were corroborated with their significant T‐test values. The T‐test results of the relationship between the concentrations of the air pollutants per time of the day, showed that their T‐test values were not significant, indicating that concentrations of these air pollutants were independent of the sampling time. A strong and positive correlation existed between the two air pollutants signifying common sources.

The paper highlights that at 60 m distance around petroleum production facilities, people with respiratory or heart disease, the elderly and children should be prevented from gaining access in the morning without taking necessary precautionary measures against the inhalation of air pollutants.

The primary aim of this paper is to develop a reference model for measuring corporate sustainability that can be used by organizations to integrate sustainability measures into their current performance measurement system, helping them to embed sustainability into daily activities and to forge a sustainability culture. A secondary intent is to present a critical analysis of some well‐known sustainability measurement initiatives, showing their strengths and shortcomings.

The approach employed to develop the reference model described in this paper is a qualitative analysis of the complementarity, shortcomings and strengths of eight well‐known sustainability measurement initiatives alongside an extant corporate sustainability literature review.

The research carried out has found that there is not a single initiative analyzed that tackles all sustainability issues and in fact there is no consensus around what should be measured and how. The main divergences are related to the following aspects: different criteria are applied by the initiatives to classify issues between dimensions; same impacts are evaluated at different levels of a cause‐effect relationship continuum by the same initiative; disagreement about the groups of stakeholders a company should engage and assessing the company impacts that should be taken into account (direct only or those of its whole value chain). Moreover, the way in which most initiatives measure sustainability performance is not the most adequate to embed it into the performance measurement systems, since they evaluate sustainability via presence of management practice and employ absolute values indicators rather than result‐oriented measures and ratio indicators that are more adequate for internal decision making. In this context, a sustainability measurement model was developed that is more comprehensive, objective and value‐oriented, constituting an attempt to shed light on these problems.

The major limitation is the fact that the proposed model does not provide any guidance to select the sustainability key issues for an organization to be integrated into its current performance measurement system. It mainly provides a very comprehensive set of sustainability issues and measures that could be used.

This paper sheds light on some sustainability measurement current challenges – lack of consensus of what should be measured and how – and sustainability embedment into daily activities. Academics will find it useful in their research efforts since it presents a broad review of sustainability concepts as well as an analysis of strengths and shortcomings of all and each sustainability initiative focused. Practitioners will also find it useful as a tool to better understand the sustainability concept, to start measuring sustainability performance, to integrate it in, as well as to evaluate, their current performance measurement systems.

Considers the role of a range of materials being used in advanced sensor technology, including diamond, fullerenes, silicon carbide, superconductors, rare earths and III‐V compounds. Sensors based on these materials are described and their applications discussed.

Artificial neural networks (ANN) are appearing as alternatives to traditional statistical modeling techniques in many scientific disciplines. However, the inherent drawbacks of neural networks such as topology specification, undue training expense, local minima and training unpredictability will overlay their merits in engineering applications, especially. In this paper, adaptive radial basis function (ARBF) network and improved support vector machine (SVM) are presented in atmospheric sciences. The principle component analysis (PCA) technique is employed to the ARBF network as well, namely, ARBF/PCA network for the convenience of expression and comparison, so as to fasten the learning process. Comparing with traditional neural network models, the proposed models can automatically determine the size of network and parameters, fasten the learning process and achieve good generalization performances in prediction of pollutant level. The simulation results based on a real‐world data set demonstrate the effectiveness and robustness of the proposed methods.

The purpose of this paper is to investigate the ability of transition metals (TMs) of iron-, nickel- and zinc-doped graphene nanosheet for adsorption of toxic gas of nitric oxide (NO). The results of this paper have provided a favorable understanding of the interaction between TM-doped graphene nanosheet and NO molecule.

A high performance of TM-doped graphene nanosheet as a gas sensor is demonstrated by modeling the material’s transport characteristics by means of the Langmuir adsorption and three-layered ONIOM/ density functional theory method. The Langmuir adsorption model has been done with a three-layered ONIOM using CAM-B3LYP functional and LANL2DZ and 6–311G (d, p) basis sets by Gaussian 16 revision C.01 program towards the formation of of NO→TM(Mn, Co, Cu)-doped on the Gr nanosheet.

The changes of charge density for Langmuir adsorption of NO on Mn-, Co- and Cu-doped graphene nanosheet orderly have been achieved as: ΔQ_Co-doped = +0.309 >> ΔQ_Mn-doped = −0.074 > ΔQ_Cu-doped = −0.051. Therefore, the number of changes of charge density have concluded a more remarkable charge transfer for Mn-doped graphene nanosheet. However, based on nuclear magnetic resonance spectroscopy, the sharp peaks around Cu doped on the surface of graphene nanosheet and C19 close to junction of N2 and Co17 have been observed. In addition, Cu-doped graphene sheet has a large effect on bond orbitals of C8–Cu 17, C15–Cu 17 and C16–Cu17 in the adsorption of NO on the Cu-doped/Gr which has shown the maximum occupancy. The amounts of ΔGads,NO→Mn−Co through IR computations based on polarizability have exhibited that ΔGads,NO→Mn−Co has indicated the most energy gap because of charge density transfer from the nitrogen atom in NO to Mn-doped graphene nanosheet, though ΔG(NO→Cu−C)0> ΔG(NO→Co−C)0>ΔG(NO→Mn−C)0.

This research aims to explore the adsorption of hazardous pollutant gas of “NO” by using carbon nanostructure doped by “TM” of iron, nickel and zinc to evaluate the effectiveness of adsorption parameters of various TM-doped graphene nanosheets.