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Background: Quinolone resistant Salmonella serotypes have been reported in recent years and have become increasingly widespread worldwide. Objectives: We evaluated the molecular mechanism of quinolone resistance in non-typhoidal Salmonella strains isolated from clinical samples in Tehran, Iran. Methods: The present study included the Salmonella isolates originated from hospitalized individuals and outpatients in Tehran, Iran. Serotyping of nalidixic acid-resistant Salmonella isolates was done by slide agglutination method. Then, the quinolone resistance-determining region (QRDR) of topoisomerase gene gyrA and the plasmid-mediated quinolone resistance (PMQR) determinants were detected using the polymerase chain reaction (PCR) method. Restriction fragment length polymorphism (RFLP) analysis was also employed to determine the possible mutation in the gyrA gene of those strains. Mutant strains were detected by enzymatic digestion, and their PCR products were sequenced immediately. Results: Amongst 141 isolates, 60% showed nalidixic acid resistance, whereas none of them were ciprofloxacin-resistant. The commonly prevalent serotypes were S. Enteritidis and S. Infantis. Of 85 nalidixic acid-resistant strains, 17 (20%) isolates harbored the qnrS gene. However, PCR analysis of the quinolone-resistant strains did not detect qnrA and qnrB genes. PCR-RFLP and sequencing analysis of the QRDRs of the gyrA gene indicated that 16 (18.8%) isolates had mutant patterns, and the most common point mutation was serine to phenylalanine at position 83. Conclusions: Our results demonstrated that point mutations in gyrA and the existence of plasmid-mediated gene qnrS were important mechanisms of quinolone resistance in non-typhoidal Salmonella strains isolated from human origin. Other alternative mechanisms of resistance, such as alterations in the expression of efflux pumps, should be studied to provide greater insight into the molecular mechanism of quinolone-resistant non-typhoidal Salmonella isolates.

This paper considers the vehicle control process in emergency lane change (ELC). The control method is divided into two parts: before crossing the obstacle and after crossing it. The first part is done by a feed-forward controller inspired by the driver’s behavior pattern in the ELC maneuver. This controller is compensated by a neural network system and two proportional-integral (PI) and proportional-derivative (PD) controllers, which correct the output of the feed-forward controller to follow the path more accurately. The second part consists of two PD controllers responsible for controlling and steering the vehicle in the main path after crossing the obstacle. The main novelty of the proposed method is that the computational burden is low because of using a feed-forward controller, which is the main source of the calculation’s burden. So as a result, the controller system can cover the ELC maneuver in under 2 seconds in various lateral displacements to bypass the obstacle and prevent collisions. The co-simulations are performed in CarSim software and MATLAB/Simulink, which shows that the control system can appropriately steer the vehicle and follow the desired at different speeds, in the presence of road friction and parameter uncertainty.

Aptamers can be regarded as efficient substitutes for monoclonal antibodies in many diagnostic and therapeutic applications. Due to the tedious and prohibitive nature of SELEX (systematic evolution of ligands by exponential enrichment), the in silico methods have been developed to improve the enrichment processes rate. However, the majority of these methods did not show any effort in designing novel aptamers. Moreover, some target proteins may have not any binding RNA candidates in nature and a reductive mechanism is needed to generate novel aptamer pools among enormous possible combinations of nucleotide acids to be examined in vitro. We have applied a genetic algorithm (GA) with an embedded binding predictor fitness function to in silico design of RNA aptamers. As a case study of this research, all steps were accomplished to generate an aptamer pool against aminopeptidase N (CD13) biomarker. First, the model was developed based on sequential and structural features of known RNA-protein complexes. Then, utilizing RNA sequences involved in complexes with positive prediction results, as the first-generation, novel aptamers were designed and top-ranked sequences were selected. A 76-mer aptamer was identified with the highest fitness value with a 3 to 6 time higher score than parent oligonucleotides. The reliability of obtained sequences was confirmed utilizing docking and molecular dynamic simulation. The proposed method provides an important simplified contribution to the oligonucleotide-aptamer design process. Also, it can be an underlying ground to design novel aptamers against a wide range of biomarkers.

In the present study, a series of all-atom molecular dynamics simulations were applied to shed light on the molecular mechanism of the activity of CM11, a short cecropin–melittin hybrid peptide obtained through a sequence combination approach, against gram-positive (GP) and gram-negative (GN) bacterial membrane models. In addition, the peptide adsorption mechanism on the surface of the membrane models, the thermodynamic and structural contribution of each residue in the antibacterial activity of the peptide against both GP and GN bacterial membranes were investigated. Our findings showed that the peptide was strongly bound to the GP membrane type in comparison with the GN membrane and was stabilized quickly. These strong bonds are caused by the interactions between basic residues and POPG molecules, which have higher concentrations in GP than GN membranes. Calculation of binding free energies revealed that both electrostatic and van der Waals energy components were desired for the peptide binding and insertion in the membrane. Electrostatic interactions were the main driving force in the adsorption and surface localization of the peptide. Determining the contribution of each residue to the binding free energy indicated that W1, K2, K5, K6 and K9 residues played an important role in the activity of the peptide. These results can be used as a roadmap to provide in-depth insights into the design of appropriate peptides in the fight against multidrug-resistant bacteria.

There are numerous experimentally validated simulations for mono-dispersed systems in the literature based on discrete element method (DEM). In practice, however, most of granular systems consist of polydispersed assemblies of particles. Few studies have considered the effect of polydispersity, and yet fewer have experimentally validated the results. In this study, application of a new experimental method for granular flow analysis is presented, capable of validating the results of an in-house developed GPU-based DEM solver in both monodispersed and polydispersed assemblies. Silo discharge is chosen as the case study in which discharge time, flow pattern and more importantly, the outlet composition variation with time (for polydispersed configurations) have been experimentally evaluated and validated with numerical results. The outlet composition, which is the ratio of fine to coarse particles in the outlet stream, is an essential measure of segregation in polydispersed silos, and its numerical prediction can be correct only if the interactions between fine and coarse particles within the silo are modelled precisely. Measuring this parameter is not possible using conventional experimental methods established in silo discharge studies such as high speed photographing or high-frequency weight measurement of the bed. A new apparatus has been developed which can measure this parameter. The device is a compartmented wheel rotating with a motor which gathers the outlet stream of the silo into different compartments. Due to practical limitations, design and function of the apparatus are not ideal. Forward mixing, distribution of particles with the same resident time in different compartments, is the most critical problem. Non-idealities must be compensated by means of post-processing codes so that comparable results are obtained from experiment and simulation.

Gene selection methods are critical in cancer classification, which depends on the expression of a small number of biomarker genes, which have been a significant issue of enormous recent studies. Microarray technology allows generating tumors gene expression datasets. Cancer classification based on these datasets commonly has a kind of small sample size against the number of genes involved and includes multiclass categories. In this paper, grey wolf algorithm was used for extracting notable features in the pre-processing stage, and deep neural network (DNN) was used as deep learning for improving the accuracy degree of cancer detection from three datasets, i.e., STAD (Stomach adenocarcinoma), LUAD (lung adenocarcinoma) and BRCA (breast invasive carcinoma). The proposed method achieved the highest accuracy for these three datasets. The proposed method was able to achieve accuracy close to 100. Furthermore, the proposed method was compared with linear support vector machine classification, RBF, the nearest neighbor, linear regression, one vs. all, Naive Bayes, and decision tree algorithms. The proposed method had 0.57 improvement on the LUAD dataset, 1.11 optimization on the STAD dataset, and 0.78 development on the BRCA dataset.

Combustion of heavy fuels is one of the main sources of greenhouse gases, particulate emissions, ashes, NOx and SOx. Gasification is an advanced and environmentally friendly process that generates combustible and clean gas products such as hydrogen. Some entrained flow gasifiers operate with Heavy Fuel Oil (HFO) feedstock. In this application, HFO atomization is very important in determining the performance and efficiency of the gasifiers. The atomization characteristics of HFO (Mazut) discharging from a pressure-swirl atomizer (PSA) are studied for different pressures difference (Δp) and temperatures in the atmospheric ambient. The investigated parameters include atomizer mass flow rate ( m ), discharge coefficient (CD), spray cone angle (θ), breakup length (Lb), the unstable wavelength of undulations on the liquid sheet (λs), global and local SMD (sauter mean diameter) and size distribution of droplets. The characteristics of Mazut sheet breakup are deduced from the shadowgraph technique. The experiments on Mazut film breakup were compared with the predictions obtained from the liquid film breakup model. Validity of the theory for predicting maximum unstable wavelength was investigated for HFO (as a highly viscous liquid). A modification on the formulation of maximum unstable wavelength was presented for HFO. SMD decreases by getting far from the atomizer. The measurement for SMD and θ were compared with the available correlations. The comparisons of the available correlations with the measurements of SMD and θ show a good agreement for Ballester and Varde correlations, respectively. The results show that the experimental sizing data could be presented by Rosin-Rammler distributions very well at different pressure difference and temperatures.

BACKGROUND: Considerable evidence supports that SLE could be related to apoptotic cells and EBV infection. OBJECTIVE: The aim of this study was to identify the transcriptional signature of EBV infection in SLE patients for survey of the molecular apoptosis signaling pathways. METHODS: The PBMCs gene expression profiles of healthy control and SLE patients were obtained from GEO. Functional annotation and signaling pathway enrichment were carried out using DAVID, KEGG. To validate bioinformatics analysis the changes in genes expression of some of obtained genes, Real time PCR was performed on PBMCs from 28 SLE patients and 18 controls. RESULTS: We found that mean viral load was 6013 ± 390.1 copy/μg DNA from PBMCs in all patients. QRT-PCR results showed that the expression of the DUSP1 and LAMP3 genes which had most changes in the logFC among 4 candidate genes, increased significantly in comparison with control. The consistent expression of LMP2 as viral latency gene involve in apoptosis signaling pathways was detected in SLE patients with EBV viral load and some controls. CONCLUSIONS: The study indicated that some cellular genes may have an important role in pathogenesis of SLE through apoptosis signaling pathways. Beside, EBV infection as an environmental risk factor for SLE may affect the dysfunction of apoptosis.

In the last century, the emergence of in silico tools has improved the quality of healthcare studies by providing high quality predictions. In the case of COVID-19, these tools have been advantageous for bioinformatics analysis of SARS-CoV-2 structures, studying potential drugs and introducing drug targets, investigating the efficacy of potential natural product components at suppressing COVID-19 infection, designing peptide-mimetic and optimizing their structure to provide a better clinical outcome, and repurposing of the previously known therapeutics. These methods have also helped medical biotechnologists to design various vaccines; such as multi-epitope vaccines using reverse vaccinology and immunoinformatics methods, among which some of them have showed promising results through in vitro, in vivo and clinical trial studies. Moreover, emergence of artificial intelligence and machine learning algorithms have helped to classify the previously known data and use them to provide precise predictions and make plan for future of the pandemic condition. At this contemporary review, by collecting related information from the collected literature on valuable data sources; such as PubMed, Scopus, and Web of Science, we tried to provide a brief outlook regarding the importance of in silico tools in managing different aspects of COVID-19 pandemic infection and how these methods have been helpful to biomedical researchers.

SARS-CoV-2 is a corona virus that has been the cause for one of the deadliest pandemics of history, started since 2019. Suppressing the activity of the critical enzymes in the SARS-CoV-2 could potentially inhibit a vital step in viral life cycle. Papain-like protease (PLpro) could be regarded as a critical enzyme in viral replication of SARS-CoV-2. In this research, it was aimed to suppress the activity of PLpro enzyme by using potential plant-derived protease inhibitor peptides. For this purpose, 11 plant derived peptides that could potentially inhibit protease activity were selected from literature. The structures of the PLpro and the peptide ligands were acquired from PDB (protein data bank) and after structural optimization, were docked by using HADDOCK 2.4 program. Analyzing the results indicated that VcTI from Veronica hederifolia provides effective molecular interactions at both liable Zn site and classic active site of PLpro, making it a potential inhibitory ligand for this enzyme that could be used for halting the replication of SARS-CoV-2. Molecular dynamic assay confirmed that the selected receptor and ligand complex was stable. Future in vitro and in vivo investigations are required to verify the efficiency of this compound as a potential therapeutic against SARS-CoV-2 infection. Supplementary Information The online version contains supplementary material available at 10.1007/s10989-021-10331-8.

Background Tympanometry is used as part of a battery of tests for screening of middle ear function and may help diagnose middle ear disorders, but remains available only on expensive test equipment. Methods We report a low-cost smartphone-based tympanometer system that consists of a lightweight and portable attachment to vary air pressure in the ear and measure middle ear function. The smartphone displays a tympanogram and reports peak acoustic admittance in realtime. Our programmable and open-source system operates at 226 Hz and was tested on 50 pediatric patient ears in an audiology clinic in parallel with a commercial tympanometer. Results Our study shows an average agreement of 86 ± 2% between the 100 tympanograms produced by the smartphone and commercial device when five pediatric audiologists classified them into five classes based on the Liden and Jerger classification. Conclusion Given the accessibility and prevalence of budget smartphones in developing countries, our open-source tool may help provide timely and affordable screening of middle ear disorders.

Prenatal screening of different anomalies including chromosomal aneuploidies have become a part of routine pregnancy care in most countries around the world. These tests can help pregnant mothers to have informed decisions. In this study we gathered relevant scientific and governmental/official data about uptake rate of these screenings in different developed countries and Iran. We have tried to use the latest articles and reports, and also consider to the global trend of screening and abortion policies in developed countries. Also, some pitfalls when comparing prenatal screening of different countries will be explained. These data can help to have a better insight about Iran’s prenatal screening status when compared with developed countries to improve public health policies.

Background Different factors have been introduced which influence the pathogenesis of chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC). COPD as an independent factor is involved in the development of lung cancer. Moreover, there are certain resemblances between NSCLC and COPD, such as growth factors, activation of intracellular pathways, as well as epigenetic factors. One of the best approaches to understand the possible shared pathogenesis routes between COPD and NSCLC is to study the biological pathways that are activated. MicroRNAs (miRNAs) are critical biomolecules that implicate the regulation of several biological and cellular processes. As such, the main goal of this study was to use a systems biology approach to discover common dysregulated miRNAs between COPD and NSCLC, one that targets most genes within common enriched pathways. Results To reconstruct the miRNA-pathways for each disease, we used the microarray miRNA expression data. Then, we employed “miRNA set enrichment analysis” (MiRSEA) to identify the most significant joint miRNAs between COPD and NSCLC based on the enrichment scores. Overall, our study revealed the involvement of the targets of miRNAs (such as has-miR-15b, hsa-miR-106a, has-miR-17, has-miR-103, and has-miR-107) in the most important common biological pathways. Conclusions According to the promising results of the pathway analysis, the identified miRNAs can be utilized as the new potential signatures for therapy through understanding the molecular mechanisms of both diseases.

The exaggerated host response to Sars-CoV-2 plays an important role in COVID-19 pathology but provides a therapeutic opportunity until definitive virus targeted therapies and vaccines become available. Given a central role of endothelial dysfunction and systemic inflammation, repurposing ACE inhibitors (ACEIs), angiotensin receptor blockers (ARBs), statins, and aspirin has been of interest. In this retrospective, single-center study, we evaluated the primary outcomes of mortality and ICU admission in 587 hospitalized patients with documented COVID-19 with or without ACEIs, ARBs, statins, and aspirin. Atorvastatin was associated with reduced mortality, which persisted after adjusting for age, lockdown status, and other medications (OR: 0.18. 95% CI: 0.06-0.49, P = 0.001). ACEIs were also associated with reduced mortality in the crude model (OR: 0.20, CI: 0.06-0.66, P = 0.008), as ACEIs and ARBs were combined as a single group (OR: 0.35, CI: 0.16-0.75, P = 0.007), although ARBs alone did not reach statistical significance. There was no association between any medications and risk of ICU admission. Aspirin only achieved a significant association of reduced mortality in a subgroup of patients with diabetes in the crude model (OR: 0.17, CI: 0.04-0.80, P = 0.02). The reduced mortality observed with atorvastatin is consistent with other literature, and consideration should be given to atorvastatin as a COVID-19 treatment. While there was suggested benefit of ACEIs and ARBs in the present study, other studies are varied and further studies are warranted to recommend employing these medications as a treatment strategy. Nevertheless, this study combined with others continues to give credibility that ACEIs and ARBs are safe to continue in the setting of COVID-19.

Spatial modelling of land use change is a technique for understanding changes in terms of the location and amount. In this study, logistic regression and Geomod approaches were used for modelling forest change in Gorgan area in Northern Iran in the time period of 1988-2007. To do this, at first, remotely sensed imagery data of the years 1988, 1998 and 2007 were used to produce land use maps. Land use maps accuracy assessments were achieved using Error matrix method and then the maps were used to implement change detection process in two time periods of 1988-1998 and 1998-2007. Results indicated a reduction in forest areas during the mentioned time period. Next, the independent variables were extracted in order to land use change modeling. The Results of the models implementation showed the ability of both models for forest change modeling in this region. Also, the models were used to predict the future condition of forest area in the years 2016 and 2025. The results revealed that the forest area would be associated with a reduction in the future. Comparison of the results of the models using kappa indices showed the successful implementation of both models for forest change modelling in this region. The results of this research reveal the need for appropriate applications of the proper plans to control land use change in order to preserve the environment and ecological balance of the area. Therefore, careful planning can reduce the land use change and its impacts in the future in this region.

In the present study, the release of zinc (Zn) from polylactic acid/zinc oxid nanoparticles (PLA/ZnO NPs) nanocomposites to three aqueous food simulants (10% ethanol, 20% ethanol and 95% ethanol) was evaluated (during 15 days at 4, 25, and 40 °C) by atomic absorption spectrometry (AAS). The results indicated that temperature and the simulant type affected the migration of Zn and at a constant temperature; the maximum Zn release was observed in the 95% ethanol simulant. Pseudo-Fickian behavior was observed during the diffusion of Zn and diffusion coefficients (D values) of 0.002–6.08 10−11 cm2 s−1 were obtained in different migration conditions. The obtained partition coefficients (K) were between 21.66 and 0.057 μg g−1. The Zn release data were fitted with the Weibull model, and the b and n model parameters had values ranging from 0.008 to 0.07 and 0.24 to 0.49, respectively. The results of the present study indicated that Zn had little migration from PLA films into food simulants (especially in water at 4–40 °C) which was attributed to the high activation energy (Ea) values for Zn diffusion from PLA/ZnO NPs nanocomposites.

The purpose of this study was to investigate the relationship between financial distress and transactions with affiliated individuals. In this research financial information of 152 companies accepted in Tehran Stock Exchange during the period of 1391 to 1396 has been investigated. The purpose of this study is applied. In terms of collecting and analyzing data, this research is a descriptive correlation method. From the point of view of information gathering, post-event research is used to analyze the data using descriptive, inferential statistics and multi-variable regression analysis. . This research has been investigated with two hypotheses by ERW software. In this regard, in the initial implementation of the first model, using the printing statistics and Yasmin, the appropriate regression model model (computational or stationary data with random effects) has been determined and using statistics such as ; The novelty of this and Chou's reliability of variables are investigated. Then, in the second run, the classic regression assumptions model, including the normal distribution of variables, the independence of the distribution of errors, the normal distribution of errors, the heterogeneity of variances and the linear relationship between independent and control variables, have been investigated. Finally, the results of the research show that financial distress through transactions with affiliated persons but the size of the auditor is not relevant to transactions with affiliated persons.

Long non‐coding RNAs (lncRNAs) are a subclass of non‐protein coding transcripts that are involved in several regulatory processes and are considered as potential biomarkers for almost all cancer types. This study aims to investigate the prognostic value of lncRNAs for lung adenocarcinoma (LUAD), the most prevalent subtype of lung cancer. To this end, the processed data of The Cancer Genome Atlas LUAD were retrieved from GEPIA and circlncRNAnet databases, matched with each other and integrated with the analysis results of a non‐small cell lung cancer plasma RNA‐Seq study. Then, the data were filtered in order to separate the differentially expressed lncRNAs that have a prognostic value for LUAD. Finally, the selected lncRNAs were functionally annotated using a bioinformatic and systems biology approach. Accordingly, we identified 19 lncRNAs as the novel LUAD prognostic lncRNAs. Also, based on our results, all 19 lncRNAs might be involved in lung cancer‐related biological processes. Overall, we suggested several novel biomarkers and drug targets which could help early diagnosis, prognosis and treatment of LUAD patients.

Objectives To evaluate efficacy of addition of duloxetine to usual analgesic regimens in management of burn pain. Methods In a 3-week open label randomized controlled trial, burn patients were assigned to the intervention (duloxetine 60 mg/day + usual analgesic regimens) or control group (usual analgesic regimens: morphine ± acetaminophen ± gabapentin). Intensity and quality of background pain and severity of procedural pain were evaluated using neuropathic pain scale (NPS) and visual analog scale (VAS), respectively. The primary outcome measure was “intensity” item of the NPS (evaluating intensity of the background pain). Results Forty six patients (age: 35.5 ± 6.3 years, TBSA: 36.7 ± 15%) (23 per group) completed the study. At baseline, scores of the “intensity” item were 9.13 ± 1.42 and 9.13 ± 1.86 (P = 1) in the intervention and control group, respectively. Comparison of difference in mean changes from baseline to the end of the study showed that addition of duloxetine only significantly reduced the scores of the “intensity” {1.74 (95% CI: 0.61 to 2.86); P = 0.003}, and “hot” {1.39 (95% CI: 0.166 to 2.614) P = 0.02} items and score of the VAS {2.13 (95% CI: 1.476 to 2.784) P Conclusion Addition of duloxetine may increase efficacy of the other analgesics in reduction of the burn pain.

The available SMD (Sauter mean diameter) correlations on pressure-swirl injectors predict droplet sizing very different from each other, especially for heavy fuels. Also there was a lack in the literature for comparing available correlations. So an experimental study was conducted on a heavy fuel oil (HFO) spray, Mazut 380. A pressure swirl injector was designed and fabricated. The experiments for Mazut at 40 °C and 80 °C were compared with the results for water, including spray half cone angle, breakup length and mean droplet diameter, at different injection pressures. Lower spray angle, higher breakup length and larger droplets were observed for lower injection pressures and higher liquid viscosity. SMD was about 75 μm for water and about 87 μm for Mazut at 80 °C. The results for droplet mean diameter were also compared with correlations from previous studies on pressure swirl atomizers. The SMD results show that for water spray, LISA method was in good agreement, also Babu and Ballester correlations were successful when high viscosity fluid was injected.

High energy storage capacity of tin oxide (SnO2) makes it a promising anode material for high capacity lithium (Li)-ion batteries. Previous experiments reported by Nie et al. (2013) and Huang et al. (2010) have shown that SnO2 lithiation occurs in two stages. First, Li diffuses rapidly through distinct narrow stripes along the electrode axis. This is followed by a second stage where the diffusion/amorphization of the nanowire occurs. In order to understand and possibly predict this complex chemo-mechanical phenomenon, a finite element (FE) model is developed in this work. The model captures the formation of the striped diffusion regime and the corresponding expansion of the nanowire during the lithiation of SnO2. The effect of the stress on the Li diffusion is modeled at the macroscopic level by implementing a stress-dependent expression for the diffusion coefficient. The modeling results clearly show the formation of the striped diffusion regime due to the induced stresses, at low concentrations of Li. This results in a small strain of 0.017 within the nanowire followed by a bulk diffusion and expansion at higher Li concentrations. Thus, the model allows for the spatiotemporally resolved analysis of Li diffusion/intercalation and helps predicting its influence on the mechanical performance of the electrode under the realistic operational conditions.

In the current study, the active packaging films based on poly lactic acid (PLA) containing 1.5% w/w zinc oxide (ZnO) nanoparticles and varying concentrations (0.5, 1, 1.5% w/w) of Zataria multiflora Boiss. essential oil (ZEO) and Menthe piperita L. essential oil (MEO) were produced. The efficacies of the resulted active films on shelf life extension of Otolithes ruber fish during 16 days of refrigerated storage (4 ± 1 °C) were evaluated. The antibacterial activity of the films was tested against five common food-borne pathogens (Escherichia coli, Salmonella enterica, Pseudomonas aeruginosa, Bacillus cereus and Staphylococcus aureus) by disc diffusion method. The fillet samples were analyzed periodically for microbiological (aerobic count, Enterobacteriaceae count, Pseudomonas spp., Lactic acid bacteria (LAB) count and H2S-producing bacteria) and chemical (TBARS and TVB-N). PLA/ZnO/ZEO and PLA/ZnO/MEO films showed enhanced antibacterial (691 and 513.33 mm2, repectively, against S. aureus) and antioxidant (69.14 and 49.08%, repectively) activity than control. Based on the microbial count, the active films significantly increased the shelf life of fillets from 8 to 16 days. The lowest TBARS (0.8 mg MA/kg muscle) and TVB-N (21.23 mg/100 g muccle) values were obtained in fillets wrapped with PLA/ZnO containing 1.5% ZEO. Carvacrol and menthone were found to be the main compounds of ZEO and MEO following GC analysis, respectively. Atomic absorption spectrophotometer showed transfer only a minuscule amount of Zn2+ ions to the meat. Overally, the PLA/ZnO films containing the essential oils could be deemed as a potential alternative to the current common technologies for extending the shelf-life of meat products like ‘Otolithes ruber fillets.

In this study, the efficacy of household sanitizers application on reduction of Escherichia coli O157:H7, ascorbic acid, total phenolics, DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging and overall acceptability of inoculated fresh basil leaves (Ocimum basilicum), at temperature of 40 °C was investigated. Sanitizers containing lactic acid (LA), acetic acid (AA) and citric acid (CA) were used at concentration of 2%, individually or in combination with H2O2 (1% or 2%), and NaCl (7%). Control a and b were unwashed and washed leaves with distilled, deionized and sterilized water, respectively. All sanitizing treatments, in comparison to the control a, reduced the numbers of E. coli O157:H7 (0.24 ± 0.12–3.37 ± 0.48 log CFU/g) at day 1 (1 h after sanitizing). The lowest number of E. coli O157:H7 population (2.35 ± 0.26 log CFU/g) was observed by applying the LA + H2O2 (%2) treatment at first day of chilled storage. The highest amount of ascorbic acid (27.77 ± 0.06 mg/100 g), total phenolic (112.2 ± 0.5 mg gallic acid equivalents/100 g) and DPPH radical scavenging activity (95.2 ± 0.5%) was observed in control a at first day (P

The vibration analysis and control of containers with heavy loaded fluid is undertaken in this paper. The problem of fluid–structure vibration is viewed and analyzed from several viewpoints including both analytical methods and numerical techniques. In order to effectively control the fluid–structure vibration, one of the side walls is made flexible where two piezoelectric patches are utilized to sense the distributed displacements resulting from fluid-structure movements, while the other one is used to actively control the vibration. For this, a boundary control technique is used to actively control the multi-modal vibration of fluid–structure. The simulation results for the analytical models are further validated using a comprehensive finite element method. Before applying the proposed controller, the results show that the fluid vibration is different in different heights and distances. However, the simulation results indicate that the piezoelectrically-excited beam is able to suppress the vibrations of all the positions very effectively and quickly. These results prove the feasibility of utilizing piezoelectrically-excited beams in vibration control of fluid–structure.

For chemically active particles suspended in a liquid solution and moving by self-phoresis, the dynamics near chemically inert, planar walls is studied theoretically by employing various choices for the activity function, i.e., the spatial distribution of the sites where various chemical reactions take place. We focus on the case of solutions composed of electrically neutral species. This analysis extends previous studies of the case that the chemical activity can be modeled effectively as the release of a "product" molecular species from parts of the surface of the particle by accounting for annihilation of the product molecules by chemical reactions, either on the rest of the surface of the particle or in the volume of the surrounding solution. We show that, for the models considered here, the emergence of "sliding" and "hovering" wall-bound states is a generic, robust feature. However, the details of these states, such as the range of parameters within which they occur, depend on the specific model for the activity function. Additionally, in certain cases there is a reversal of the direction of the motion compared to the one observed if the particle is far away from the wall. We have also studied the changes of the dynamics induced by a direct interaction between the particle and the wall by including a short-ranged repulsive component to the interaction in addition to the steric one (a procedure often employed in numerical simulations of active colloids). Upon increasing the strength of this additional component, while keeping its range fixed, significant qualitative changes occur in the phase portraits of the dynamics near the wall: for sufficiently strong short-ranged repulsion, the sliding steady states of the dynamics are transformed into hovering states. Furthermore, our studies provide evidence for an additional "oscillatory" wall-bound steady state of motion for chemically active particles due to a strong, short-ranged, and direct repulsion. This kind of particle translates along the wall at a distance from it which oscillates between a minimum and a maximum.

The shelf life of quail carcass was examined after imposing separate and combined treatments of spraying with lactic acid (LA, 1% v/v), dipping in chitosan (CH, 1% w/v) and placing the carcass in modified atmosphere package (MAP, 65% CO2 + 30% N2 + 5% O2) at 4 ± 1 °C for 20 days. The control group was packed under similar atmospheric condition but without any antimicrobial agents. Microbiological populations, physicochemical properties and sensory attributes (color, odor and overall appearance) were monitored at 4-day intervals. All antibacterial treatments effectively lowered microbial numbers, compared to the control during chilled storage. The total viable count, as an indicator of meat spoilage, on day 8 of the storage in treated samples was 0.5–3.4 log CFU/g which was lower than the control. The weakest and strongest effects were caused by LA and LA + CH + MAP treatments, respectively. Similar impact intensity occurred in other microbial tests during refrigerated storage. Binary combination treatments of MAP and chitosan showed synergistic effects on controlling microbial growth, and had no significant difference with LA + CH + MAP. Evaluations on days 4 and 8 showed that all treatments significantly controlled microbial growth, pH value, peroxide value and reactive substances of thiobarbituric acid in comparison with the control (P 7) during the entire chilled storage. It is noteworthy that organoleptic evaluations correlated well with physicochemical and microbiological data. Based on microbiological data and the overall appearance results of the carcasses, the shelf lives of the control, LA, CH, MAP, LA + MAP, LA + CH, CH + MAP and LA + CH + MAP samples were 6, 7, 11, 12, 12, 15, 20 and 20 days, respectively, under chilled conditions.

This study investigated the effects of different particle sizes of sterilized wheat bran (100–200, 200–300 and 300–400 μm), their replacement levels at 5, 10, and 15% (based on flour w/w) and also their fermentation by Saccharomyces cerevisiae PTCC 5052 on the qualities of Tafton bread. Measurements indicated how these parameters affected pH, TTA, phytic acid, protein, ash, fat, soluble and insoluble dietary fiber contents in sterilized wheat bran samples. The volume of dough samples and the sensory properties of Tafton bread samples were examined. The lowest amount of phytic acid (2.0 ± 0.12%) was observed in fermented sterilized wheat bran (FSWB) which had particle sizes of 100–200 μm (p

Many experimental and computational studies have identified key protein coding genes in initiation and progression of esophageal squamous cell carcinoma (ESCC). However, the number of researches that tried to reveal the role of long non-coding RNAs (lncRNAs) in ESCC has been limited. LncRNAs are one of the important regulators of cancers which are transcribed dominantly in the genome and in various conditions. The main goal of this study was to use a systems biology approach to predict novel lncRNAs as well as protein coding genes associated with ESCC and assess their prognostic values. By using microarray expression data for mRNAs and lncRNAs from a large number of ESCC patients, we utilized “Weighted Gene Co-expression Network Analysis” (WGCNA) method to make a big coding-non-coding gene co-expression network, and discovered important functional modules. Gene set enrichment and pathway analysis revealed major biological processes and pathways involved in these modules. After selecting some protein coding genes involved in biological processes and pathways related to cancer, we used “LncTar”, a computational tool to predict potential interactions between these genes and lncRNAs. By combining interaction results with Pearson correlations, we introduced some novel lncRNAs with putative key regulatory roles in the network. Survival analysis with Kaplan-Meier estimator and Log-rank test statistic confirmed that most of the introduced genes are associated with poor prognosis in ESCC. Overall, our study reveals novel protein coding genes and lncRNAs associated with ESCC, along with their predicted interactions. Based on the promising results of survival analysis, these genes can be used as good estimators of patients' survival, or even can be analyzed further as new potential signatures or targets for the therapy of ESCC disease.

The aim of this study was to investigate the effect of internal factors of the company on the Tobin's Q ration and the value of companies admitted in Tehran Securities Exchange Stock Exchange with the approach of structural equation modeling. In this study the effect of corporate governance, capital structure and profit sharing policy as internal variables on corporate value was investigated. This research is practical in terms of goal. Statistical population of the present study is the companies accepted in the Tehran Stock Exchange between 2012 to 2016. Among them, 161 companies were selected as sample through systematic elimination. After finding to fit the acceptable model of ‏ measurement and structure of the research, the results showed that internal variables have a positive effect on the Tobin's Q ratio. Among the internal variables, the return-sharing policy has the most impact on the Tobin's Q ratio. The Tobin's Q ratio can mediate the relationship between local variables and the corporate value., {"references":["Balatbat, M., Taylor, S. L, and Walter, T. S. (2004). Corporate governance, insider ownership, and operating performance of Australian initial public offerings. Accounting and Finance Journal, 44 : 299-328.","Fama, E. F. and Jensen, M. C. (1983). Separation of Ownership and Control. Journal of Law and Economics, 16: 301-325.","Gonzalez, V. M. (2013). Leverage and corporate performance: International evidence, International Review of Economics and Finance, Vol. 25, pp. 169- 184.","Javadi, N. and Fattahi (2017), Investigating the effect of managers reward on capital structure and financial performance of companies accepted in Tehran Stock Exchange. Strategic Management Magazine. Fourth year number four. PP 69-94.","Mirzaie, H.; Khataie, M.; and Ghanbari, Y. (2013). \"Investigating the Relationship between Business Riskand Financial Risk with the Performance of Pharmaceutical Companies Listed on the Tehran Stock Exchange\", Journal of Health Accounting, Vol. 2, No. 2, pp. 77-91."]}

The exaggerated host response to Sars-CoV-2 plays an important role in COVID-19 pathology but provides a therapeutic opportunity until definitive virus targeted therapies and vaccines become available. Given a central role of endothelial dysfunction and systemic inflammation, repurposing ACE inhibitors (ACEIs), angiotensin receptor blockers (ARBs), statins, and aspirin has been of interest. In this retrospective, single-center study, we evaluated the primary outcomes of mortality and ICU admission in 587 hospitalized patients with documented COVID-19 with or without ACEIs, ARBs, statins, and aspirin. Atorvastatin was associated with reduced mortality, which persisted after adjusting for age, lockdown status, and other medications (OR: 0.18. 95% CI: 0.06-0.49, P = 0.001). ACEIs were also associated with reduced mortality in the crude model (OR: 0.20, CI: 0.06-0.66, P = 0.008), as ACEIs and ARBs were combined as a single group (OR: 0.35, CI: 0.16-0.75, P = 0.007), although ARBs alone did not reach statistical significance. There was no association between any medications and risk of ICU admission. Aspirin only achieved a significant association of reduced mortality in a subgroup of patients with diabetes in the crude model (OR: 0.17, CI: 0.04-0.80, P = 0.02). The reduced mortality observed with atorvastatin is consistent with other literature, and consideration should be given to atorvastatin as a COVID-19 treatment. While there was suggested benefit of ACEIs and ARBs in the present study, other studies are varied and further studies are warranted to recommend employing these medications as a treatment strategy. Nevertheless, this study combined with others continues to give credibility that ACEIs and ARBs are safe to continue in the setting of COVID-19.

Background: While social media have an immense effect on children and adolescent interactions, they also have serious and potential effects on physical and mental health. Cyberbullying, as a form of bullying using electronic means, is an example of this trend. Objectives: The purpose of this study was to determine the prevalence of cyber-related behaviors and some of their related factors among high school students in Tehran. Methods: This was a cross-sectional analytical study examining cyber behaviors in students in grades 7, 8, and 9. Since our study was conducted in line with an international study, we used the questionnaire of that research to collect data. Some of the characteristics of the adolescents and behavioral problems associated with them were examined, and students' experiences of cyberbullying and cybervictimization were asked in this study. A multi-stage cluster sampling was performed. The statistical population consisted of students from five districts of north, south, west, east, and center regions of Tehran, in which 1,456 questionnaires were completed. Results: The prevalence rate of cyberbullying was 22.3% while that of cybervictimization was 18%. It was also demonstrated that both trends were more significant in boys than in girls. Other parameters such as substance use, body thought scale, school environment difficulties, peer, conduct, and emotional problems had significant correlations with cybervictimization (P = 0.03 for peer problems to P < 0.001 for emotional problems) and cyberbullying (P < 0.04 for peer problems to P < 0.001 for school environment). A significant relationship was also found between prosocial problems and cyberbullying (P = 0.01). Conclusions: Cyberbullying and cybervictimization are more prevalent in boys than in girls. This phenomenon is related to many physical and mental health problems. This evidence can be used to inform decision-makers in the social arena to provide strategies for preventive programs and future interventions.

Background: The Coronavirus disease 2019 (COVID-19) outbreak quickly has spread and became a pandemic. However, no approved therapeutics or effective treatment is available for the treatment of these patients. The present study was done to retrospectively assess the treatment strategies (e.g., pharmaceutical care services) for COVID-19 patients in selected hospitals and highlight the importance of such services in the management of a pandemic. Materials and Methods: Data from a series of COVID-19 patients (978 patients; 658 males [66.9%] and 324 females [33.1%]) admitted to the selected hospitals in Tehran from 20 February to 19 March 2020 were retrieved retrospectively from the Health Information System (HIS) of the hospitals. The statistical tests were used for analyzing the effect and correlation of the variables (drugs) with the average length of stay (ALOS) in the hospital. Results: Diverse medication classes and old drugs with or without strong evidence of therapeutic effects against the novel coronavirus, some previously tried as a treatment for SARS-CoV and MERS-CoV, were mostly used for the treatment of patients in the hospitals. Many medications (broad-spectrum antibiotics and antivirals) or combination therapies are used without evidence of their therapeutic effects during pandemics. Conclusion: Therefore, guidelines should be provided for the off-label use of these drugs by policymakers and stakeholders during a pandemic emergency due to high demands. Also, monitoring of the HIS data can play an important role in improving public health response to emerging diseases.

Background: Retraction is a mechanism for correcting the literature and a warning for readers in relation to publications that contain serious flaws or erroneous data. As a result of growth and development of Iranian publications in the last two decades, that brings unethical behavior of researchers led to retraction of their publications. We aimed to investigate Iranian retracted publications indexed in PubMed database. Methods: All Iranian retracted publications published in PubMed up to Dec 2017 have been retrieved. Bibliographic information of retracted publications, retraction notice, time lag between article publication date and the date of retraction notice, reasons of retraction, Issuer of retraction and acknowledge information of retracted publication were recorded. Additionally, citation data of retracted publications before 2013 were analyzed. Results: Overall, 164 Iranian retracted publications were identified. Meantime lag was 20.8 months. "Islamic Azad University" and "Tehran University of Medical Sciences (TUMS)" were two affiliations that have received highest number of retracted publications. The most issuer of retraction publications was editor-in-chief and the most mentioned reasons for retractions were authorship issues, plagiarism, and redundant publication. Thirtythree (20.12%) publications have received funds from various agencies. Citation study of retracted publications indicates that these publications have received 789 citations (Citation per publication=11.6). Conclusion: Although Iranian retracted publications represent small portion of all Iranian publications, but the number of retracted publications has increased. More than half of retracted publications have had authorship issues and plagiarism that requires more attention to research ethics authorities.

Coronavirus disease-19 (COVID-19) is an acute resolved disease, with estimated 3.4% case fatality rate. Due to insufficient data and short onset time of the disease, researchers have to change the strategy against its associated virus, SARS-CoV-2. One of these strategies is the use of computational methods in the field of drug and vaccine design, which can greatly reduce the time and cost of the therapeutic or immunogenic development projects. In this study, we employed various immunoinformatics tools to design a multi-epitope vaccine polypeptide with the highest potential for activating the human immune system against SARS-CoV-2. The initial epitope set was extracted from the whole set of viral structural proteins. Their potential non-toxic and non-allergenic T- cell and B-cell binding and cytokine inducing epitopes were then identified through a priori immunoinformatic prediction. Selected epitopes were bonded to each other with appropriate links. A suitable adjuvant was added to the N-terminus of the vaccine polypeptide sequence to increase its immunogenicity. Molecular modelling of the 3D structure of the vaccine polypeptide, docking, molecular dynamics simulations and free energy calculations confirmed that the designed vaccine had high affinity for Toll-like receptor 3 binding, and that the vaccine-receptor complex was highly stable. Therefore, the designed polypeptide is promising for antigenicity and inducing an effective and safe immune response against SARS-CoV-2 inside the human body.

Metabolic syndrome and its indexes is one of the critical health problems during pregnancy. This study aimed to examine the effects of a care intervention program on pregnancy outcome in pregnant women with Metabolic Syndrome during 2017-2018.This randomized clinical trial study was conducted in 120 singleton pregnant women with metabolic syndrome. The participants were selected using purposive sampling method from pregnant women referred to two health centers of Babol. They were randomly divided in two control and intervention groups (60 samples in each group). Intervention group received one motivational interview session for 120 min, two consultation sessions with expert for nutritional recommendations based on Nutrition Guidelines of Ministry of Health for Pregnant Women. They were also theoretically and practically provided by three training sessions for physical activity and pregnancy exercises combining pelvic floor muscles, bodybuilding, muscle strengthening, stretching, and relaxation and walking activities. To follow up on the intervention, the researcher made a phone call with the participants in intervention group every 10 days to two weeks. Pregnancy outcomes were assessed using SPSS software.The obtained results showed that there was a significant difference between the two groups in maternal complications including gestational diabetes, hospitalization due to gestational diabetes, nutritional diet for gestational diabetes, pregnancy weight gain and 2-hour post-prandial blood glucose test (The results of the study indicated that intervention program improved the maternal pregnancy outcome such as gestational diabetes and weight gain during the pregnancy in the intervention group. This program had no adverse effects for the mother who is consistent with pregnancy health objectives.

Aptamers can be regarded as efficient substitutes for monoclonal antibodies in many diagnostic and therapeutic applications. Due to the tedious and prohibitive nature of SELEX (systematic evolution of ligands by exponential enrichment), the in silico methods have been developed to improve the enrichment processes rate. However, the majority of these methods did not show any effort in designing novel aptamers. Moreover, some target proteins may have not any binding RNA candidates in nature and a reductive mechanism is needed to generate novel aptamer pools among enormous possible combinations of nucleotide acids to be examined in vitro. We have applied a genetic algorithm (GA) with an embedded binding predictor fitness function to in silico design of RNA aptamers. As a case study of this research, all steps were accomplished to generate an aptamer pool against aminopeptidase N (CD13) biomarker. First, the model was developed based on sequential and structural features of known RNA-protein complexes. Then, utilizing RNA sequences involved in complexes with positive prediction results, as the first-generation, novel aptamers were designed and top-ranked sequences were selected. A 76-mer aptamer was identified with the highest fitness value with a 3 to 6 time higher score than parent oligonucleotides. The reliability of obtained sequences was confirmed utilizing docking and molecular dynamic simulation. The proposed method provides an important simplified contribution to the oligonucleotide-aptamer design process. Also, it can be an underlying ground to design novel aptamers against a wide range of biomarkers.

Predicting scene depth from RGB images is a challenging task. Since the cameras are the most available, least restrictive and cheapest source of information for autonomous vehicles; in this work, a monocular image has been used as the only source of data to estimate the depth of the car within the frontal view. In addition to the detection of cars in the frontal image; a convolutional neural network (CNN) has been trained to detect and localize the lights corresponding to each car. This approach is less sensitive to errors due to the disposition of bounding boxes. An enhancement on the COCO dataset has also been provided by adding the car lights labels. Simulation results show that the proposed approach outperforms those who only use the height and width of bounding boxes to estimate the depth.

Vision serves as an essential sensory input for insects but consumes substantial energy resources. The cost to support sensitive photoreceptors has led many insects to develop high visual acuity in only small retinal regions and evolve to move their visual systems independent of their bodies through head motion. By understanding the trade-offs made by insect vision systems in nature, we can design better vision systems for insect-scale robotics in a way that balances energy, computation, and mass. Here, we report a fully wireless, power-autonomous, mechanically steerable vision system that imitates head motion in a form factor small enough to mount on the back of a live beetle or a similarly sized terrestrial robot. Our electronics and actuator weigh 248 milligrams and can steer the camera over 60° based on commands from a smartphone. The camera streams "first person" 160 pixels-by-120 pixels monochrome video at 1 to 5 frames per second (fps) to a Bluetooth radio from up to 120 meters away. We mounted this vision system on two species of freely walking live beetles, demonstrating that triggering image capture using an onboard accelerometer achieves operational times of up to 6 hours with a 10-milliamp hour battery. We also built a small, terrestrial robot (1.6 centimeters by 2 centimeters) that can move at up to 3.5 centimeters per second, support vision, and operate for 63 to 260 minutes. Our results demonstrate that steerable vision can enable object tracking and wide-angle views for 26 to 84 times lower energy than moving the whole robot.