Kinetics of 1,3-dipolar cycloaddition reaction between C,N-diphenylnitrone and dimethyl fumarate in various solvents and aqueous solutions

Gholami, Mohammad Reza; Yangjeh, Aziz Habibi

doi:10.1002/(sici)1097-4601(2000)32:7<431::aid-kin5>3.0.co;2-j

Cited by 38 publications

(17 citation statements)

References 16 publications

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“…2b). For comparison, in the case of the one-step cycloaddition of (Z)-C,N-diphenylnitrone with dimethyl fumarate, the activation enthalpy is 54.4 kJ mol -1 [28]. In turn, activation entropies have large, negative values (-144.11 ± 3.6 and -147.11 ± 4.4 J mol -1 K -1 for reactions 1 ?…”

Section: Resultsmentioning

confidence: 99%

Kinetic aspects of [3+2] cycloaddition reactions between (E)-3,3,3-trichloro-1-nitroprop-1-ene and ketonitrones

Jasiński

Mróz

2015

Reac Kinet Mech Cat

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Section: Resultsmentioning

confidence: 99%

Kinetic aspects of [3+2] cycloaddition reactions between (E)-3,3,3-trichloro-1-nitroprop-1-ene and ketonitrones

Jasiński

Mróz

2015

Reac Kinet Mech Cat

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“…[41] Here, we conducted tests on POCA:PPF fibrous dressings in order to demonstrate their anti-inflammatory activity. Three different groups of mice were investigated: animals not exposed to UVB light (no UVB), exposed to UVB but not treated with dressings (UVB), and exposed to UVB and treated with POCA:PPF dressings (UVB-POCA:PPF).…”

Section: Citokynes and Mpo Analysismentioning

confidence: 99%

Fumarate-loaded electrospun nanofibers with anti-inflammatory activity for fast recovery of mild skin burns

et al. 2016

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In the biomedical sector the availability of engineered scaffolds and dressings that control and reduce inflammatory states is highly desired, particularly for the management of burn wounds. In this work, we demonstrate for the first time, to the best of our knowledge, that electrospun fibrous dressings of poly(octyl cyanoacrylate) (POCA) combined with polypropylene fumarate (PPF) possess anti-inflammatory activity and promote the fast and effective healing of mild skin burns in an animal model. The fibers produced had an average diameter of (0.8 ± 0.1) µm and they were able to provide a conformal coverage of the injured tissue. The application of the fibrous mats on the burned tissue effectively reduced around 80% of the levels of pro-inflammatory cytokines in the first 48 h in comparison with un-treated animals, and enhanced skin epithelialization. From histological analysis, the skin thickness of the animals treated with POCA : PPF dressings appeared similar to that of one of the naïve animals: (13.7 ± 1.4) µm and (14.3 ± 2.5) µm for naïve and treated animals, respectively. The density of dermal cells was comparable as well: (1100 ± 112) cells mm−2 and (1358 ± 255) cells mm−2 for naïve and treated mice, respectively. The results demonstrate the suitability of the electrospun dressings in accelerating and effectively promoting the burn healing process.

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“…has well established. [1][2][3][4][5][6][7][8] The use of solvatochromic indicators is a suitable method for studing solute-solvent interactions, since the transition energy of the indicators depends on the solvation's sphere composition and properties. 1 The solvatochromic parameter for measuring empirically the polarity of solvents, E T (30), is calculated from the maxima of absorbance of the betaine dye as a solution in the solvent under investigation at 25 o C and at a pressure of 0.1 MPa expressed in wavenumber.…”

Section: Introductionmentioning

confidence: 99%

“…Such QSPR/ QSAR correlation equations are usually multi-parametric. [2][3][4][5][6][7] To obtain a significant correlation, it is crucial that appropriate descriptors be employed. 9 Famini et al used theoretical linear solvation energy relationship (TLSER) methodology to correlate E T N of 30 solvents with molecular descriptors.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network Prediction of Normalized Polarity Parameter for Various Solvents with Diverse Chemical Structures

2007

Bulletin of the Korean Chemical Society

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Artificial neural networks (ANNs) are successfully developed for the modeling and prediction of normalized polarity parameter (E T N ) of 216 various solvents with diverse chemical structures using a quantitative-structure property relationship. ANN with architecture 5-9-1 is generated using five molecular descriptors appearing in the multi-parameter linear regression (MLR) model. The most positive charge of a hydrogen atom (q + ), total charge in molecule (q t ), molecular volume of solvent (V m ), dipole moment (µ) and polarizability term (π I ) are input descriptors and its output is E T N . It is found that properly selected and trained neural network with 192 solvents could fairly represent the dependence of normalized polarity parameter on molecular descriptors. For evaluation of the predictive power of the generated ANN, an optimized network is applied for prediction of the E T N values of 24 solvents in the prediction set, which are not used in the optimization procedure. Correlation coefficient (R) and root mean square error (RMSE) of 0.903 and 0.0887 for prediction set by MLR model should be compared with the values of 0.985 and 0.0375 by ANN model. These improvements are due to the fact that the E T N of solvents shows non-linear correlations with the molecular descriptors.

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Kinetics of 1,3-dipolar cycloaddition reaction between C,N-diphenylnitrone and dimethyl fumarate in various solvents and aqueous solutions

Cited by 38 publications

References 16 publications

Kinetic aspects of [3+2] cycloaddition reactions between (E)-3,3,3-trichloro-1-nitroprop-1-ene and ketonitrones

Kinetic aspects of [3+2] cycloaddition reactions between (E)-3,3,3-trichloro-1-nitroprop-1-ene and ketonitrones

Fumarate-loaded electrospun nanofibers with anti-inflammatory activity for fast recovery of mild skin burns

Artificial Neural Network Prediction of Normalized Polarity Parameter for Various Solvents with Diverse Chemical Structures

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