The aim of this study is to explore the capability of subcritical methanol to reduce the acidity of naphthenic acids and to determine reaction kinetics for large-scale reactor design.The experiments were carried out in a 25 mL autoclave reactor (China) at temperatures of 70-120oC, Methanol Partial Pressures (MPPs) of 0.1-1.5 MPa, and reaction times of 0-60 min. The total acid number content of the samples was analyzed using ASTM D 974 techniques. Experimental results reveal that total acid number reduction of naphthenic acids increased with increasing reaction temperature, MPP, and reaction time. Approximately 74.20% total acid number was reducedat a temperature of 120oC, a MPP of 1 MPa, and a reaction time of 60 min. Experimental data revealed that total acid number removal reaction kinetics followed second-order kinetics with an activation energy of 11.27 kcal/mol. Therefore, subcritical methanol is able to reduce the total acid number of naphthenic acids without the addition of any catalyst.

In recent years, modeling uncertainties through natural language has attracted growing attention, with Z-numbers, introduced by Zadeh in 2011, being a key concept. A Z-number consists of two fuzzy components: the first represents the possibility of an event&rsquo, s occurrence, while the second expresses the probability of that occurrence. A major challenge in applying Z-numbers lies in properly structuring these two components, inappropriate strategies can lead to inaccurate results, especially in group decision-making contexts with large data volumes. To address this, the paper proposes an optimal clustering approach for structuring the components of Z-numbers more systematically and purposefully. This method enhances the accuracy of Z-number modeling by reducing errors in component formation. The effectiveness of the proposed approach is validated through a comparison with conventional fuzzy methods, demonstrating improved performance in handling uncertainty.

Introduction: One of the causes of error and perturbation in isodose curves in conventional radiotherapy treatment planning is the existence of tissues having either very high density (bone, prosthesis) or very low density (lung, air cavities). Nowadays, the use of CT images to solve this problem is growing, and so is the need for calibration curves that convert the CT-number of the tissue to electron density for dose calculation. The conventional method to obtain this curve is purely measurement-based, in which a phantom containing various materials of known electron densities is imaged. Alternatively, a more fundamental method of stoichiometry has been used in this work.Material and Methods: For the stoichiometric method, initially a cylindrical polyethylene phantom was built. The phantom consists of inserts of high-purity aluminum, PVC, polyethylene, water and cork to model hard bone, skeleton, fat, muscle and lung tissues, respectively. CT imaging was then performed at 120 kVp using a spiral CT scanner (GE model NXI). A system of simultaneous equations was solved to get the appropriate CT-number to electron-density conversion for each tissue type using the CT-numbers from the phantom images, the physical and radiological data of the materials. A conversion curve showing the variation of CT-number with relative electron density was also plotted. The result of the stoichiometric conversion was then compared to that from other methods.Results: The system of simultaneous equations yielded the factors, the experimental and the computed CT-numbers were compared. The highest uncertainty was estimated to be approximately 5.6% for a relatively high-density material such as aluminum and 4% for polyethylene. The curves representing the electron density based on CT-number start diverging at CT-number equal to zero and above.Discussion and Conclusion: Comparing the results obtained from the experimental and computational methods suggest an acceptable level of accuracy for the computational (stoichiometric) conversion. The uncertainty in the electron density obtained is greater for materials of higher electron density.

Introduction: Copy number variation (CNV) consist of deletion, insertion, and duplications. It is an important source of genetic variation in organisms and thus influences on the gene expression and phenotypic variation. Copy number variation (CNV) is one of the structural variant with an intermediate size class larger than 50bp which involves unbalanced rearrangements that increase or decrease the amount of DNA (Pirooznia et al 2015, Alkan et al 2011). The size of CNVs is larger than 50bp, while smaller segments are known as insertions or deletions (indels). Thereupon these structural variations comprise more polymorphic than SNPs because of enormity, detection of them and their effect on phenotype has caught the attention of many researchers recently. It has been reported that CNVs changes in gene dosage and regulation as well as in transcript structure, and thus contribute to phenotypic variability (Pirooznia et al 2015, Alkan et al 2011). The pea-comb phenotype is caused by a CNV mapping to intron 1 of the SRY (sex determining region Y)-box 5 (SOX5) gene (Wright et al. 2009). Late feathering in chickens is due to incomplete duplication in PRLR and SPEF2 genes (Elfrink et al. 2008). In swine, dominant white colour has been related with a duplication of a 450-kb fragment of the KIT gene (Giuffra et al. 1999) and a splice mutation causing the skipping of exon 17 (Giuffra et al. 1999). In sheep, doubling in the ASIP gene results in the regulation of pigment in body coat (Norris et al. 2008). Doubling the 4.6 k base pair into the six introns of the STX17 gene results in a gray body color in the horse with age. Deletion of the intergenic region with a length of 11.7 kbp in the goat genome leads to the removal of horns (Clop et al. 2012). Chicken is the most intensively farmed animal on earth and is a major food source with billions of birds used in meat and egg production each year. A big share of chicken CNVs involves protein coding or regulatory sequences. A comprehensive study of chicken CNV can provide valuable information on genetic diversity and assist future analyses of associations between CNV and economically important traits in chickens. Unique chicken genome with macro and micro chromosomes and its biology make it an ideal organism for studies in development and evolution, as well as applications in agriculture and medicine (Burt 2005). In the last several years, There has been an increasing interest in the study of CNVs in the chicken. This study focuses on comparison of CNV between the broilers and layers chicken to find evidence of domestication on the genome using whole genome sequencing.Material and methods: we used n=90 female birds of two commercial broiler (n=40) and layer (n=50) chicken. The broilers (BRs) were represented by 20 DNA samples of each of two lines (BRA and BRB) established independently and previously collected as part of the AVIANDIV project. In the layer group (LRs), data from 25 birds each from purebred white (WL) and brown (BL) egg laying populations, sequenced in the frame of the SYNBREED project (http://www.synbreed.tum.de/index.php?id=2 ,(were included. The paired-end reads with a read length of 101bp were mapped against the current reference genome assembly Galgal6 using the Burrows-Wheeler aligner (bwa, 0.6.2-r126 Version, with default parameters. Duplicate reads were masked during post-processing using the Picard tool set (version 2.9.2, http://picard.sourceforge.net). Finally, Genome Analysis Toolkit-3.3.0 was used to realign reads for correcting errors caused by InDels. Using GATK software package and Depth Of Coverage function (McKenna et al 2010), the depth of readings was calculated for each sample. Then filter out reads with mapping quality below 20. Because comparing the genomes of individuals in different groups was time consuming and computationally difficult for all parts of the genome, the genomes of each individual were divided into 1000 bp non-overlapping windows and the average reading depth per window was calculated. Then the results were normalized against the BL sample that showed highest average depth. In short, we created a correction factor per population and applied it on the depth of coverage value for each window. For all the contrasts, we performed an analysis of variance (ANOVA) as described (Carneiro et al 2014). For the Broilers-Layers contrast we scanned 935247 windows. 70372 windows showed significant by FDR with P < 0.001, with ANOVA using the Benjamini-Hochberg FDR method for multiple corrections (Benjamini and Hochberg 1995).Results and discussion: Mapping sequencing data to galGal6 assembly showed an average 98.61% mapping rate and 11.51 depth. Manhattan plot was plotted for regions of the genome that differed significantly between the two groups (FDR = 0.001). The points above the hypothetical line were identified and examined in a 25 Kbp confidence interval to identify possible genes. 39 regions were identified that half of them dose not contain any genes. Although Long noncoding RNAs are under lower selective pressure than protein-coding genes (Batista and Chang 2013), The other 11 regions contained 16 genes related to long non-coding RNAs. Long noncoding RNAs (lncRNAs) play a critical role in organizing the 3-dimensional genome architecture and regulating gene activity in cis or in trans through multiple mechanisms (Zhang et al 2019, Batista and Chang 2013). 6 othere regions also contained 12 coding genes. Most of the identified genes were somehow linked to the immune system disease or cancer. Genes such as DEDs and TNFAIP8 are involved in programmed cell death (apoptosis) and two genes NPAL3 and RCAN, which are involved in the immune system, had a copy number variation in the studied samples. In addition RCAN is involved in Down syndrome. The PFDN gene, located on chromosome 25, is also involved in Alzheimer's and Parkinson's disease.

Rosemary plant extract as a natural anti-oxidant is 4 times stronger than synthetic anti-oxidant like BHT and BHA. For this reason, it has been under attention not only for its anti-oxidant properties rather for its anti-inflammatory, anti-tumor, anti-bacterial, and anti-virus properties in different studies. This research investigates the effects of temperature, time, pH, and substance concentration in the labeling of irradiated rosmarinic acid by radioisotope gallium-67 as a high-resolution imaging agent for SPECT imaging. In this study, gamma irradiated rosmarinic acid nanoparticles at 20 kGy and 30 kGy levels in two concentrations of 0.5 and 1% were radiolabeled by gallium-67 radioisotope produced in Karaj cyclotron, and their efficiency and radiochemical purity were compared. Labeling conditions (including pH, temperature, time, and compound concentration) were investigated. Quality control was performed by thin-layer chromatography (RTLC). Resulting from the experiments, 30 kGy level and 1% concentration at 45 °C for 30 minutes at pH = 5.5-6 proved to be the best time for labeling rosemary nanoparticles, and the highest radiochemical purity achieved was 95%; radio conjugate also showed good stability after 12 hours.

Introduction: Ursolic acid (UA) is a triterpenoid compound which widely found in the apple’ s peel. It has wide health-promoting properties; as previous studies properly indicated to its abilities. In this scenario our attention has been paid to the application of UA as an anti-diabetic compound. Based on our recent studies in relating to SIRT1 protein/gene and UA, the aim of this research was to evaluate UA effects on the SIRT1 expression in diabetic rat’ s pancreas. Methods: In this study we used 20 male diabetic wistar rats. To develop diabetic rats, they received 30mg/kg of streptozotocin for 2 days sequentially. Then, they classified to 2 groups, the ones received UA + corn oil twice daily for two weeks and others (the control group) just received corn oil. Results: Our findings obviously showed that UA enhanced SIRT1 (4± 0. 2 folds) proteins levels in pancreas (P<0. 001), in comparison with control rats. In addition, the findings showed that UA significantly decreased fasting blood glucose from 416. 17± 12 mg/dl to 149. 75± 11 mg/dl. Moreover, we found that UA increased β-cell numbers and islet Langerhans diameters (~2 folds). Conclusion: Our results provide valuable information not only into the mechanisms underlying β-cells protection but also into the regulation of SIRT1 as a main target to attenuate β-cells damage. Therefore, UA is a promising pharmacological therapeutic target for β-cell regeneration through enhancing of SIRT1 over-expression.

Nitrite salts of sodium have been used traditionally in meat products as preservatives, antioxidant and color fixative agents. Nitrite is highly carcinogenic agent. The aim of this work was to study acid lactic bacteria inoculation effects on nitrite and load of bacterial reduction in sausages products. Three lactic acid bacteria strains (L. fermentum PTCC 1638, L. plantarum PTCC 1058, Leu. mesenteroides subsp mesenteroides PTCC 1563) were selected for considering of their nitrite reduction ability primarily. Two strains of them (L. fermentum, L. plantarum) and their mixture were evaluated as starter cultures in the production of sausage. Their density standardized with 0.05 Mac-Farland dilution in 600nm wave length by spectrophotometric method. Mentioned strains and their mixture with finally number of (108cfu/g farsh) inoculated to sausage containing 120 mg/g nitrite. During “Fermentation period” nitrite residual mean value: pH, acidity, total number of  lactic acid bacteria, total number of mesophilic aerobic bacteria and total number of Enterobacteriacea were significantly different  in compared to no inoculation treatments(control) (P<o.o5). Residual nitrite in fermented sausage by L. fermentum, L. plantarum and their mixture, was reduced to 65.8%, 75.4% and 68.3% respectively, while it was 60% in no inoculation treatment. Result revealed, there is no difference between total aerobic bacteria men values in fermented sausages, by L. fermentum and mixture starter cultures (P>0.05).