Antibiotic resistance and genetic diversity among Pseudomonas aeruginosa isolated from urinary tract infections in Iran

Aims: To determine the antibiotic resistance and genetic diversity of Pseudomonas aeruginosa isolates. Methods: The antibiotic resistance, genetic diversity and the conjugate transformation among Pseudomonas aeruginosa collected from patients with urinary tract infection in Tehran, Iran, was investigated. Results: Antibiotic resistance against cefepime was seen in 51.74% of the isolates, followed by amikacin (47.76%). blaOXA-10 and blaVIM were the most prevalent extended-spectrum β-lactamase and metallo-β-lactamases genes, respectively. Five clusters (C1-C5) were obtained by pulse field gel electrophoresis and multilocus sequence typing revealed two strain types, ST235 and ST664. Conjugation detected blaOXA-48 and blaNDM genes were transferred to Escherichia coli K12. Conclusion: The resistance of P. aeruginosa to antibiotics is increasing, which highlights the need to determine the resistance patterns to design better treatment strategies.

Analysis of Energy Harvesting Enhancement in Piezoelectric Unimorph Cantilevers

Environmental energy harvesting is a major operation in research and industries. Currently, researchers have started analyzing small-scale energy scavengers for the supply of energy in low-power electrical appliances. One area of interest is the use of piezoelectric materials, especially in the presence of mechanical vibrations. This study analyzed a unimorph cantilever beam in different modes by evaluating the effects of various parameters, such as geometry, piezoelectric material, lengths of layers, and the proof mass to the energy harvesting process. The finite element method was employed for analysis. The proposed model was designed and simulated in COMSOL Multiphysics, and the output parameters, i.e., natural frequencies and the output voltage, were then evaluated. The results suggested a considerable effect of geometrical and physical parameters on the energy harvesters and could lead to designing devices with a higher functional efficiency.

A fully automated deep learning-based network for detecting COVID-19 from a new and large lung CT scan dataset

This paper aims to propose a high-speed and accurate fully-automated method to detect COVID-19 from the patient's chest CT scan images. We introduce a new dataset that contains 48,260 CT scan images from 282 normal persons and 15,589 images from 95 patients with COVID-19 infections. At the first stage, this system runs our proposed image processing algorithm that analyzes the view of the lung to discard those CT images that inside the lung is not properly visible in them. This action helps to reduce the processing time and false detections. At the next stage, we introduce a novel architecture for improving the classification accuracy of convolutional networks on images containing small important objects. Our architecture applies a new feature pyramid network designed for classification problems to the ResNet50V2 model so the model becomes able to investigate different resolutions of the image and do not lose the data of small objects. As the infections of COVID-19 exist in various scales, especially many of them are tiny, using our method helps to increase the classification performance remarkably. After running these two phases, the system determines the condition of the patient using a selected threshold. We are the first to evaluate our system in two different ways on Xception, ResNet50V2, and our model. In the single image classification stage, our model achieved 98.49% accuracy on more than 7996 test images. At the patient condition identification phase, the system correctly identified almost 234 of 245 patients with high speed. Our dataset is accessible at https://github.com/mr7495/COVID-CTset.

A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2

In this paper, we have trained several deep convolutional networks with introduced training techniques for classifying X-ray images into three classes: normal, pneumonia, and COVID-19, based on two open-source datasets. Our data contains 180 X-ray images that belong to persons infected with COVID-19, and we attempted to apply methods to achieve the best possible results. In this research, we introduce some training techniques that help the network learn better when we have an unbalanced dataset (fewer cases of COVID-19 along with more cases from other classes). We also propose a neural network that is a concatenation of the Xception and ResNet50V2 networks. This network achieved the best accuracy by utilizing multiple features extracted by two robust networks. For evaluating our network, we have tested it on 11302 images to report the actual accuracy achievable in real circumstances. The average accuracy of the proposed network for detecting COVID-19 cases is 99.50%, and the overall average accuracy for all classes is 91.4%.

First Study of Antimicrobial Activity of Ceftazidime-Avibactam and Ceftolozane-Tazobactam Against Pseudomonas aeruginosa Isolated from Patients with Urinary Tract Infection in Tehran, Iran

Purpose

Pseudomonas aeruginosa causes complicated and/or nosocomial UTI. These infections are usually associated with severe and multi-drug resistant P. aeruginosa isolates. As there is no study about the activity of novel antibiotics ceftazidime-avibactam (CZA) and ceftolozane-tazobactam (C/T) against P. aeruginosa isolates in Iran, we aimed to evaluate for the first time the efficacy of these agents against P. aeruginosa isolated from patients with UTI in Iran. Then, the genetic diversity of the resistant isolates was assayed.

Methods

In this study, a total of 200 P. aeruginosa isolates were collected from patients with UTI in Tehran, Iran. Disk diffusion and Minimum Inhibitory Concentration (MIC) methods were applied to determine the resistance of the isolates to CZA, C/T, and the other antibiotics. Extended-spectrum β-lactamases (ESBLs) and Metallo Beta Lactamase (MBL) production were assayed by Combination disk diffusion test (CDDT). Polymerase chain reaction (PCR) was carried out to detect the resistance genes, including beta-lactamases and carbapenemases genes. Finally, genomic analysis of the isolates was performed using the Pulse field gel electrophoresis (PFGE).

Results

Among the isolates, 16 (8%) were resistant to CZA and C/T that MIC confirmed it. The resistant isolates showed high resistance to the other classes of antibiotics. Among the resistant isolates, 31.2% and 75% were ESBL and MBL producers, respectively. The prevalence of bla_OXA10, bla_VIM, bla_OXA48, bla_OXA2, and bla_CTX-M was 100%, 50%, 31.2%, 25%, and 12.5%. Furthermore, two isolates (12.5%) harbored bla_PER and bla_NDM genes. The resistant isolates were grouped into 14 distinct pulsotypes and two shared pulsotypes were found.

Conclusion

Ceftazidime-avibactam and ceftolozane-tazobactam showed high activity against the P. aeruginosa isolated from patients with UTI in Iran. The low rate of resistance to the antibiotics is also alarming and should be considered to avoid further spreading of the antibiotic resistance among the P. aeruginosa and the other bacteria.

FoxP3 gene polymorphism is associated with breast cancer in Iranian patients

AIM

Breast cancer (BC) is one of the leading causes of cancer death among women. Recent studies have characterized FoxP3 as a marker of regulatory T cells and an X-linked tumor suppressor gene, which is involved in the pathogenesis of BC. Therefore, we investigated the potential influence of three single-nucleotide polymorphisms (SNPs) of FoxP3 gene on the development of BC in Iranian women.

MATERIALS AND METHODS

The association between FoxP3 rs2232365, rs3761548 and rs4824747 polymorphisms and BC risk was assessed in 124 BC patients and 198 healthy controls using sequence-specific primers.

RESULTS

We identified significant difference of rs3761548 in both allele and genotype frequencies between cases and control groups. Our results showed that individuals carrying FoxP3 rs3761548 AA genotype had about 4.3-fold increased risk of BC compared with CC carriers. No significant association was found between rs3761548C>A polymorphism and clinical outcome parameters (age of onset, tumor size, lymph nodes metastasis, tumor stage, progesterone receptor status, estrogen receptor status, Ki-67 status, HER-2 status and duration of disease).

CONCLUSION

This study has provided the first genetic data on the FoxP3 gene polymorphism in south of Iran and proposes the rs3761548 polymorphism of FoxP3 gene as a risk factor, but not a prognostic marker in the development of BC in Iranian population.

Dimensions of Safety Climate among Iranian Nurses

BACKGROUND

Workplace safety has been a concern of workers and managers for decades. Measuring safety climate is crucial in improving safety performance. It is also a method of benchmarking safety perception.

OBJECTIVE

To develop and validate a psychometrics scale for measuring nurses' safety climate.

METHODS

Literature review, subject matter experts and nurse's judgment were used in items developing. Content validity and reliability for new tool were tested by content validity index (CVI) and test-retest analysis, respectively. Exploratory factor analysis (EFA) with varimax rotation was used to improve the interpretation of latent factors.

RESULTS

A 40-item scale in 6 factors was developed, which could explain 55% of the observed variance. The 6 factors included employees' involvement in safety and management support, compliance with safety rules, safety training and accessibility to personal protective equipment, hindrance to safe work, safety communication and job pressure, and individual risk perception.

CONCLUSION

The proposed scale can be used in identifying the needed areas to implement interventions in safety climate of nurses.

Molecular detection of metallo-β-lactamase genes, bla IMP-1, bla VIM-2 and bla SPM-1 in imipenem resistant Pseudomonas aeruginosa isolated from clinical specimens in teaching hospitals of Ahvaz, Iran

BACKGROUND AND OBJECTIVES

Carbapenem resistant Pseudomonas aeruginosa is a serious cause of nosocomial infections. The main purpose of the study is to determine the prevalence rate of imipenem resistant Pseudomonas aeruginosa carrying metallo-ß-lactamase (MBL) genes.

MATERIAL AND METHODS

236 Pseudomonas aeruginosa isolates were collected from teaching hospitals of Ahvaz University of Medical Sciences during a period of 9 months in 2012. These strains were identified using conventional microbiological tests. The susceptibility of isolates to antibiotics were assessed using disk diffusion test. The IMP-EDTA combination disk phenotypic test was performed for detection of MBL producing strains. Finally, polymerase chain reaction (PCR) was performed to detect MBL genes, bla IMP-1, bla VIM-2 and bla SPM-1 in imipenem resistant strains.

RESULTS

Out of 236 examined isolates, 122 isolates (51.4%) were resistant to imipenem. The IMP-EDTA combination test showed that among 122 imipenem resistant strains, 110 strains (90%) were phenotipically MBL producers. Additionally, the results of PCR method showed that 2 strains (1.6%) and 67strains (55%) of imipenem resistant Pseudomonas aeruginosa isolates contained bla VIM-2 and bla IMP-1 genes respectively. No SPM-1gene was found in the examined samples.

CONCLUSION

Resistance of P. aeruginosa isolates to imipenem due to MBL enzymes is increasing in Ahavaz. Because of clinical significance of this kind of resistance, rapid detection of MBL producing strains and followed by appropriate treatment is necessary to prevent the spreading of these organisms.

Functional, biochemical, and histopathologic consequences of high-dose interleukin-2 administration in rats

A variety of side effects have been reported with the use of interleukin-2 alone or in combination with lymphokine-activated killer cells in patients with disseminated neoplasms. The present study was undertaken to determine the effects of high-dose interleukin-2 administration in normal rats. Sprague-Dawley rats were treated with intravenous recombinant interleukin-2 (900,000 IU/kg/day) for 9 consecutive days. Animals were placed in individual metabolic cages, and arterial blood pressure, food intake, body weight, and urine output were monitored. On day 10, animals were killed by exsanguination, various tissues were harvested, and a variety of hematologic and chemical assays were performed. The results were compared with those of placebo-injected normal control and pair-fed groups. The interleukin-2-treated group exhibited anorexia, weight loss, hypotension, anemia, leukocytosis, lymphocytosis, eosinophilia, hypercalcemia, azotemia, and a marked urinary concentration defect. Histologic examination of various tissues revealed widespread infiltration with mono-nuclear cells and eosinophils in most organs, especially in the lungs and liver of interleukin-2-treated animals. Other abnormalities included severe panlobular hepatitis, hepatocellular necrosis, and thymic involution. Renal involvement was mild and consisted of focal interstitial infiltration by mononuclear cells. According to these observations, administration of high-dose interleukin-2 in normal rats results in a score of significant functional, biochemical, and histologic abnormalities.