Prevalence of qnr, intI, and intII genes in extendedspectrum beta-lactamase (ESBL)-producing Escherichia coli isolated from clinical samples in Iran

Purpose: To investigate the prevalence of qnr, intI, and intII genes in extended spectrum betalactamase (ESBL)-producing Escherichia coli isolated from clinical samples in Kerman, Iran.Methods: A total of 127 E. coli were collected from clinical samples in Kerman hospitals. The antibiotic susceptibility test was performed using disc diffusion method, while the presence of ESBL-producing E. coli was determined by phenotypic confirmatory test. Furthermore, the presence of qnrA, qnrB, qnrS, intI, intII, and β-lactamase-encoding genes was detected by polymerase chain reaction (PCR). Finally, the data were analyzed and associations between different genes and antibiotic resistance were evaluated.Results: The highest and lowest rates of resistance were observed against ampicillin (72.4 %) and imipenem (2.3 %), respectively. Also, 41.7 % of the isolates produced ESBL-enzymes. The qnrS and genes were detected in 6.3 and 0.78 %, respectively, of the isolates, while qnrA gene was not detected in the current study. The results revealed that 64.5 and 10.2 % of isolates carried intI and intII genes, respectively. Data analysis showed a significant association between ESBL production and class I integrin gene in E. coli isolates.Conclusions: Due to the variation in the resistance patterns of E. coli against antibiotics in different geographical regions, antimicrobial treatments should be based on local experience. Also, the coexistence of ESBL and intI gene in the majority of E. coli isolates suggests that care should be taken in choosing antibiotic therapy.Keywords: Extended-spectrum β-lactamase, E. coli, Integrin, Imipenem, Bacterial genes, Antibiotic resistanc

Ideal nasal preferences: A quantitative investigation with 3D imaging in the Iranian population

Background Though in facial plastic surgery, the ideal nasal characteristics are defined by average European-American facial features known as neoclassical cannons, many ethnicities do not perceive these characteristics as suitable. Methods To investigate the preferences for nasofrontal angle, nasolabial angle, dorsal height, alar width, and nasal tip projection, manipulated pictures of one male and one female model were shown to 203 volunteer patients from a tertiary university hospital’s facial plastic clinic. Results The most aesthetically preferred nasofrontal angles were 137.64 ± 4.20 for males and 133.55 ± 4.53 for females. Acute nasofrontal angles were more desirable in participants aged 25 to 44. The most preferred nasolabial angles were 107.56 ± 5.20 and 98.92 ± 4.88 respectively. Volunteers aged 19 to 24 preferred more acute male nasolabial angles. A straight dorsum was the most desirable in both genders (0.03 ± 0.78 mm and 0.26 ± 0.75 mm, respectively). The ideal male and female alar widths were -0.51 ± 2.26 mm and -1.09 ± 2.18 mm, respectively. More 45- to 64-year-old volunteers preferred alar widths equal to intercanthal distance. The ideal female and male tip projections were 0.57 ± 0.01 and 0.56 ± 0.01, respectively. Conclusions Results indicate that the general Iranian patients prefer thinner female noses with wider nasofrontal angles for both genders. However, the ideal nasolabial angles, dorsal heights, and tip projections were consistent with the neoclassical cannons. Besides ethnic differences, the trend of nasal beauty is also affected by gender, age, and prior history of aesthetic surgery

BAT algorithm-based ANN to predict the compressive strength of concrete - A comparative study

The number of effective factors and their nonlinear behaviour\u2014mainly the nonlinear effect of the factors on concrete properties\u2014has led researchers to employ complex models such as artificial neural networks (ANNs). The compressive strength is certainly a prominent characteristic for design and analysis of concrete structures. In this paper, 1030 concrete samples from literature are considered to model accurately and efficiently the compressive strength. To this aim, a Feed-Forward (FF) neural network is employed to model the compressive strength based on eight different factors. More in detail, the parameters of the ANN are learned using the bat algorithm (BAT). The resulting optimized model is thus validated by comparative analyses towards ANNs optimized with a genetic algorithm (GA) and Teaching-Learning-Based-Optimization (TLBO), as well as a multi-linear regression model, and four compressive strength models proposed in literature. The results indicate that the BAT-optimized ANN is more accurate in estimating the compressive strength of concrete

BAT Algorithm-Based ANN to Predict the Compressive Strength of Concrete—A Comparative Study

The number of effective factors and their nonlinear behaviour—mainly the nonlinear effect of the factors on concrete properties—has led researchers to employ complex models such as artificial neural networks (ANNs). The compressive strength is certainly a prominent characteristic for design and analysis of concrete structures. In this paper, 1030 concrete samples from literature are considered to model accurately and efficiently the compressive strength. To this aim, a Feed-Forward (FF) neural network is employed to model the compressive strength based on eight different factors. More in detail, the parameters of the ANN are learned using the bat algorithm (BAT). The resulting optimized model is thus validated by comparative analyses towards ANNs optimized with a genetic algorithm (GA) and Teaching-Learning-Based-Optimization (TLBO), as well as a multi-linear regression model, and four compressive strength models proposed in literature. The results indicate that the BAT-optimized ANN is more accurate in estimating the compressive strength of concrete

Bedside Teaching and Its Alternatives in the COVID-19 Pandemic

Background: Bedside teaching is a concentrated form of small-group teaching that takes place in the presence of the patient. Improvement in communication skills in a sympathetic manner with the patient and the ability to provide a purposeful history description and earning skills in clinical examinations is a goal that can only be achieved at the patient’s bedside. Bedside teaching has declined in recent years despite all its benefits; however, there are strong recommendations to continue this teaching modality for its valued benefits. In this context, we aimed to deal with the importance of bedside teaching and the challenges ahead in the covid epidemic as well as its alternatives for teaching medical students.  Evidence acquisition: This study was conducted through a literature search on articles in English with the relevant keywords (((((((“students, medical”[Mesh]) AND (“COVID-19”[Mesh])) AND (“education”[Mesh])) AND (“patient-centered care”[Mesh])) AND (“patient care team”[Mesh])) OR (“teaching rounds”[Mesh])) OR (“education, distance”[Mesh])) AND (“Physical examination”[Mesh]) using PubMed, Scopus, Web of Sciences, Cochrane, and Embase databases from 2001 to 2022. Results: In our search, 22 related articles were found, 3 of which were clinical trials) and 4 were review articles. This study summarized the following important issues related to bedside teaching: 1- We discussed the definition, importance, benefits, and difficulties of bedside teaching on the way to education; 2- We deliberated the causes of reluctance to carry out education at the bedside and the ways to deal with the reduction of its implementation; 3-we also noticed alternative methods for medical education in periods of special contact restrictions with patients such as the COVID-19 epidemic in this review. Conclusions: Bedside teaching has a fundamental role in medical education. In particular circumstances, such as covid 19 epidemy, in which the bedside teaching courses were suspended, it is necessary to allocate other educational arrangements and design a distance learning curriculum, including virtual teaching, uploading videos to view clinical procedures on social media platforms, interview with a virtual patient, and simulation