Synthesis, in vitro antibacterial and carbonic anhydrase II inhibitory activities of N-acylsulfonamides using silica sulfuric acid as an efficient catalyst under both solvent-free and heterogeneous conditions

Silica sulfuric acid catalyzes efficiently the reaction of sulfonamides with both carboxylic acid anhydrides and chlorides under solvent-free and heterogeneous conditions. All the reactions were done at room temperature and the N-acylsulfonamides were obtained with high yields and purity via an easy work-up procedure. This method is attractive and is in a close agreement with green chemistry. These compounds were also investigated for antibacterial activity, including Gram-positive cocci and Gram-negative bacilli, and carbonic anhydrase II inhibitory activity.     

Complete Genome Sequence and Genome Analysis of Eggplant mottled dwarf virus‐Iranian Isolate

The full‐length nucleotide sequence of the Iranian isolate of Eggplant mottled dwarf virus (EMDV), a phytorhabdovirus, was determined using the random polymerase chain reaction method (rPCR) followed by PCR with specific primers to fill in the gaps. The negative‐sense RNA genome of the Iranian isolate of EMDV contains 13154 nucleotides and seven open‐reading frames (ORFs) in the order 3′‐leader‐N‐X‐P‐Y‐M‐G‐L‐trailer‐5′. These ORFs encode the nucleocapsid, X protein (of unknown function), phosphoprotein, Y protein (putative movement protein), matrix protein, glycoprotein and RNA‐dependent RNA polymerase, respectively. EMDV has a 199 nt 3′ leader RNA and a 151 nt 5′ trailer, and the ORFs are separated by conserved intergenic sequences. Phylogenetic analyses indicate that EMDV is most closely related to Potato yellow dwarf virus, which has a distinctly different geographical distribution.     

Performance evaluation of a machine vision system for insect pests identification of field crops using artificial neural networks

Feature extraction is a crucial part of advanced image recognition systems. In this research, an autonomous detection device was designed and developed for insect pest detection to improve the ability of intelligent systems in order to annihilate harmful insect pests in agricultural crop fields. Device included a dark chamber, a CCD digital camera, a LDR lightening module and a personal computer. The proposed programme for precise insect pest detection was based on an image processing algorithm and artificial neural networks (ANNs). After image acquisition, the insect pests’ images were extracted from original images with Canny filtration. Afterwards, four morphological and three textural features from the obtained images were measured and normalised. Performance of ANN model was tested successfully for Beet armyworm (Spodoptera exigua) recognition in images using back-propagation supervised learning method and inspection data. Results showed that proposed system was able to identify S. exigua in the images from other species. Such this machine vision system can be used in autonomous field robots to achieve a modern farmer’s assistant.     

An artificial neural network approach to identify fungal diseases of cucumber (Cucumis sativus L.) plants using digital image processing

Nowadays, artificial intelligence solutions such as digital image processing and artificial neural networks (ANN) have become important applicable techniques in phytomonitoring and plant health detection systems. In this research, an autonomous device was designed and developed for detecting two types of fungi (Pseudoperonospora cubensis, Sphaerotheca fuliginea) that infect the cucumber (Cucumis sativus L.) plant leaves. This device was able to recognise the fungal diseases of plants by detecting their symptoms on plant leaves (downy mildew and powdery mildew). For leaves of cucumber inoculated with different spores of the fungi, it was possible to estimate the amount of hour post inoculation (HPI) by extracting leaves’ image parameters. Device included a dark chamber, a CCD digital camera, a thermal camera, a light dependent resistor lightening module and a personal computer. The proposed programme for precise disease detection was based on an image processing algorithm and ANN. Three textural features and two thermal parameters from the obtained images were measured and normalised. Performance of ANN model was tested successfully for disease recognition and detecting HPI in images using back-propagation supervised learning method and inspection data. Such this machine vision system can be used in robotic intelligent systems to achieve a modern farmer’s assistant in agricultural crop fields.     

Molecular Analysis of ORF6, ORF7 and ORF8 of Beet yellows virus Iranian Isolate

Beet yellows virus (BYV), a member of the Closteroviridae family, is one of the most important sugar beet yellowing viruses. The nine ORFs of BYV genome encode different proteins required for BYV life cycle. We sequenced a part of the genome of BYV Iranian isolate consisting of ORF6, ORF7 and ORF8. The primer pair BYVA/Z was used for amplification of this region in RT‐PCR. The amplicon (1615 bp) was cloned and sequenced. Comparisons showed the amplified segment is corresponding to ORF6, ORF7 and ORF8 of BYV genome encoding coat protein, p20 and p21 proteins, respectively. The ORF7 of BYV Iranian isolate overlaps with ORF6 and ORF8 in four and 26 nucleotides at 5′ and 3′ ends, respectively. The ORF7 of Iranian isolate of BYV was sequenced completely. However, approximately 24 nt. from the beginning of ORF6 and 23 nt. from end of ORF8, including the stop codon, were not determined. ORF6, ORF7 and ORF8 showed the highest similarity at nucleotide (98.3, 99.4 and 99.2%) and amino acid (97.4, 98.9 and 100%) sequence levels, with BYV Ukrainian isolate. Phylogenetic analysis of the deduced amino acid sequences of ORF6, ORF7 and ORF8 revealed closer relationship of Iranian isolate of BYV with BYV Ukrainian isolate than other BYV isolates available at GenBank.     

Human Serum Protein Adsorption onto Synthesis Nano-Hydroxyapatite

Adsorption of human serum proteins (Albumin and total protein) onto high purity synthesis nano-hydroxyapatite (HA), Ca₁₀(PO₄)₆(OH)₂, has been studied in a wide temperature range by UV–visible spectrophotometer. Adsorption isotherm is basically important to describe how solutes interact with adsorbent, and is critical in optimizing the use of adsorbent. In the present study, the experimental results were fitted to the Langmuir, Freundlich, Temkin and Dubinin-Radushkevich (DR) models to obtain the characteristic parameters of each model and square of the correlation coefficients (R²). According to the results, the DR isotherm model had the best agreement with the experimental data. The effect of temperature on adsorption of human serum proteins (HSP) onto the synthesized nano-HA was studied. The experimental results indicated that temperature increase generally causes an increase in the adsorption of HSP onto the nano-HA. This is basically due to the effect of temperature on the HSP activity and its diffusion rate on HA surfaces.     

Convenient Synthesis of Novel Chalcone and Pyrazoline Sulfonamide Derivatives as Potential Antibacterial Agents

Russian Journal of Bioorganic Chemistry - Novel chalcone sulfonamide derivatives were synthesized starting from benzophenones and aldehydes in 3 steps. Also,...