Molecular characterization of methicillin resistant Staphylococcus aureus isolated from hospitals environments and patients in Northern Palestine

BACKGROUND: Staphylococcus aureus (S. aureus) is considered one of the most common pathogen to humans. Infections caused by this mocroorganism can be acquired through both hospital and community settings. This study was carried out to investigate molecular characterization of MRSA strains isolated from the patients and their environment in two hospitals (Rafidia hospital and Thabet hospital) inNorthern Palestine, and to determine the clonal identity between these strains and their possible contribution to nosocomial infections. METHODS: Two hundred sixty five swabbed samples were collected from these hospitals, S. aureus was isolated,  antibiotic resistant genes were Panton–Valentin leukocidin (PVL) gene were detected and SCCmec and spA were typed by PCR and/or sequencing. RESULTS: The prevalence of MRSA among S. aureus isolates was 29% and 8.2% in Rafidia hospital and Thabet hospital, respectively. All strains resistant to oxacilllin disk were carried mecA gene. Majority of strains (84.6%) carried SCCmec type II (n = 11), type IVa and non-typeable were also detected. In addition, PVL was detected in 2 (14.3%) clinical strains. ERIC PCR patterns revealed that 2 strains recovered from patient bed and nasal swab isolated from Thabet Hospital were nontypeable, spA typing showed that they belonged to type t386 and have identical DNA sequences. Other 2 clinical isolates were spa typed, one belonged to clone t044, while the other is new clone not exist in database. CONCLUSIONS: Results may give evidence that environmental contamination possibly contributing to nosocomial infections

Susceptibility of Candida albicans isolates to Terbinafine and Ketoconazole

 The prevalence of drug resistance has become an important issue in various yeast infections, which have a significant effects on both human animal health. In this study, an attempt has been made to determine susceptibility pattern of two antifungal agents Terbinafine and Ketoconazole against 45 oral and non oral Candida albicans isolates using broth microdilution method. Under in vitro conditions, results showed that (42/45) 93% of the C. albicans isolates had MIC values indicating susceptibility to Ketoconazole (?0.125 ?g/ml) and MICs ranged from ?0.03125-8.0 ?g/ml. According to Terbinafine, (40/45) 88.9% of isolates had MICs less than 4 ?g/ml and MICs ranged from 0.25-8.0 ?g/ml. This is the first report of in vitro antifungal susceptibility data to be published from Palestine against clinical isolates of Candida albicans. Availability of sensitive and highly accurate antifungal susceptibility testing methods, can permit analysis of data in vitro and with outcome in vivo, important to assist physician for making appropriate drug choices and patient management decision. These data indicated that Terbinafine and Ketoconazole are still active against C. albicans and may therefore have clinical applications against some of these organisms. Key words: C. albicans, Antifungal agents, Terbinafine, Ketoconazole, MIC

Multi-Method Diagnosis of CT Images for Rapid Detection of Intracranial Hemorrhages Based on Deep and Hybrid Learning

Intracranial hemorrhaging is considered a type of disease that affects the brain and is very dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT images are one of the most important methods of diagnosing intracranial hemorrhages. CT images contain huge amounts of information, requiring a lot of experience and taking a long time for proper analysis and diagnosis. Thus, artificial intelligence techniques provide an automatic mechanism for evaluating CT images to make a diagnosis with high accuracy and help radiologists make their diagnostic decisions. In this study, CT images for rapid detection of intracranial hemorrhages are diagnosed by three proposed systems with various methodologies and materials, where each system contains more than one network. The first system is proposed by three pretrained deep learning models, which are GoogLeNet, ResNet-50 and AlexNet. The second proposed system using a hybrid technology consists of two parts: the first part is the GoogLeNet, ResNet-50 and AlexNet models for extracting feature maps, while the second part is the SVM algorithm for classifying feature maps. The third proposed system uses artificial neural networks (ANNs) based on the features of the GoogLeNet, ResNet-50 and AlexNet models, whose dimensions are reduced by a principal component analysis (PCA) algorithm, and then the low-dimensional features are combined with the features of the GLCM and LBP algorithms. All the proposed systems achieved promising results in the diagnosis of CT images for the rapid detection of intracranial hemorrhages. The ANN network based on fusion of the deep feature of AlexNet with the features of GLCM and LBP reached an accuracy of 99.3%, precision of 99.36%, sensitivity of 99.5%, specificity of 99.57% and AUC of 99.84

Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning

Intracranial hemorrhaging is considered a type of disease that affects the brain and is very dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT images are one of the most important methods of diagnosing intracranial hemorrhages. CT images contain huge amounts of information, requiring a lot of experience and taking a long time for proper analysis and diagnosis. Thus, artificial intelligence techniques provide an automatic mechanism for evaluating CT images to make a diagnosis with high accuracy and help radiologists make their diagnostic decisions. In this study, CT images for rapid detection of intracranial hemorrhages are diagnosed by three proposed systems with various methodologies and materials, where each system contains more than one network. The first system is proposed by three pretrained deep learning models, which are GoogLeNet, ResNet-50 and AlexNet. The second proposed system using a hybrid technology consists of two parts: the first part is the GoogLeNet, ResNet-50 and AlexNet models for extracting feature maps, while the second part is the SVM algorithm for classifying feature maps. The third proposed system uses artificial neural networks (ANNs) based on the features of the GoogLeNet, ResNet-50 and AlexNet models, whose dimensions are reduced by a principal component analysis (PCA) algorithm, and then the low-dimensional features are combined with the features of the GLCM and LBP algorithms. All the proposed systems achieved promising results in the diagnosis of CT images for the rapid detection of intracranial hemorrhages. The ANN network based on fusion of the deep feature of AlexNet with the features of GLCM and LBP reached an accuracy of 99.3%, precision of 99.36%, sensitivity of 99.5%, specificity of 99.57% and AUC of 99.84%

Determination of Antibiotic Resistance Profile and Virulence Genes in Escherichia coli Isolates from Palestinian Patients

Introduction: Escherichia coli (E. coli) is considered one of the most frequent intestinal and extraintestinal pathogen.&#x0D; Methods:  A total of 49 isolates of E. coli were collected from different clinical samples, from different hospitals in Northern West Bank-Palestine, during January-March 2019.&#x0D; Aims: To detect the distribution of Type III secretion system (T3SS) genes, class 1, 2 and 3 integrons, virulence factors (fyuA, papGIII, iutA and sfa⁄foc) using multiplex PCR and antibiotic resistance using disc diffusion method.&#x0D; Results: In this study, E. coli isolates showed high resistance rate against different types of antibiotics and 71.4% of the isolates were multidrug resistant (MDR). Only class 1 integron was detected in these isolates with prevalence 57%, and 65.7% of MDR isolates carried integron genes. The prevalence of T3SS genes was 0.0%. In addition, results of this study showed that the prevalence of virulence genes papGIII, sfa⁄foc, fyuA and iutA was 4.1%, 40%, 64%, and 79.6%, respectively.&#x0D; Conclusions: The isolates of E. coli showed high resistance rate against different types of antibiotics. The co-occurrence of class 1 integrons and antimicrobial resistance genes in these isolates is an additional threat for spread of the antimicrobial resistance traits which may further complicate future strategies for treatment the infections caused by this pathogen. In addition, E. coli isolated from Palestinian patients showed one or more virulence factors that could increase their pathogenic potential.</jats:p

Molecular characterization and phylogenetic analysis of Middle East 2009 H1N1 pdm isolates

AbstractObjectiveTo study hemagglutinin genetic evolution of some Middle East (ME) 2009 H1N1 pdm isolates and compared them with prototype vaccine strain [A/California/07/2009 (H1N1)], which is used as a vaccine strain in the Northern Hemisphere 2010-2011.MethodsNucleotide and/or amino acid sequences of HA gene of fifty-four ME 2009 H1N1 pdm isolates were retrieved from GenBank Database by using Basic BLAST engine. Phylogenetic trees were established for both nucleotide and amino acid sequences using the muscle algorithm of the computer program CLC free workbench 5.6.1 JRE software. Amino acids alignment was also done to compare sequences HA1 domains of HA genes of ME 2009 H1N1 pdm isolates (n=39) with amino acid sequence of prototype vaccine strain A/California/07/2009 (H1N1).ResultsPhylogenetic analysis of amino acids and nucleotides of the HA gene of the ME 2009 H1N1 pdm isolates confirmed their evolutionary position in cluster with prototype vaccine strain (A/California/07/2009 (H1N1)) which is used as vaccine strain in the Northern Hemisphere 2010-2011. Antigenically, the ME 2009 H1N1 pdm isolates were homogeneous and closely related to prototype vaccine. Only a few amino acid substitutions in the HA among the ME 2009 H1N1 pdm isolates were analyzed.ConclusionsThe current influenza vaccine is expected to provide a good protection against ME 2009 H1N1 pdm because it contains strains with H1 HA [A/California/07/2009 (H1N1)]-like strain

In silico Molecular Characterization and Phylogenetic Analyses of SARS-CoV-2 in Mediterranean Basin

Background: The novel human coronavirus disease COVID-19 has become the fifth reported pandemic since the global spread of 1918 flu and counted as the first documented coronavirus worldwide spread in the history. The COVID-19 was initially considered as a respiratory disease, but SARS-CoV-2 can lead to cause other serious complications.&#x0D; Purpose: This study aimed to conduct phylogenetic analyses of the whole genome of SARS-CoV-2 strains isolated from infected humans in Mediterranean basin countries, Orf1ab gene, S gene, M gene, N gene and Orf3a gene sequences. In addition, the products of Orf1ab, S, M and N genes were also phylogenetically analyzed. Changes that occurred on the S-gene product of these SARS-CoV-2 strains were also detected.&#x0D; Materials and Methods: The whole genome of SARS-CoV-2 isolates, the genes and the gene products (Accessed July 20, 2020) were recovered in Mediterranean basin countries were retrieved from GenBank Database previously available in National Center for Biotechnology Information (NCBI) using BLAST (Basic Local Alignment Search Tool) system. Analyses of these sequences were carried out using computer program MEGA6 software.&#x0D; Results: The Phylogenetic analyses showed that Bat coronavirus RaTG13 isolate is more closely related to SARS-CoV-2 isolates than Pangolin coronaviruse isolates. The S gene product of this virus mediates entry into the host cell and has S1/S2 cleavage site containing multibasic amino acid sequence (PRRAR) which is not detected in other closely related coronaviruses. Many coronavirus strains that deposited in GenBank, showed that they have PRR sequence in Orf1ab gene product. Conclusion: we conclude that part of multibasic S1/S2 motif acquired by recombination or insertion. Theoretically, any coronavirus strain acquired this sequence becomes highly pathogenic to humans. The dominant mutation (79.3%) at S gene product level was 614D→G. The impact of mutations detected in S gene product on virus transmission, diagnosis, pathogenicity and strategies of antiviral therapy, should be rapidly assessed in further studies.</jats:p

ANTIBIOTIC RESISTANCE AGAINST STAPHYLOCOCCAL ISOLATES RECOVERED FROM SUBCLINICAL MASTITIS IN THE NORTH OF PALESTINE

The antimicrobial resistance to 10 antibiotics was determined in 132 staphylococcal isolates. These representing Staphylococcus aureus (n=66) and Staphylococcus epidermidis (n=66). All isolates were from milk samples obtained from subclinical mastitis from Awassi ewes, local goats and Fresian cows. Results indicated that among all the antimicrobial agents tested the highest resistance of staphylococcal isolates was to ampicillin. The frequency of resistance to ampicillin was 75.8 and 66.7% against S. aureus and S. epidermidis isolates, respectively. Resistance to amikacin, cefepime, vancomycin, tobramycin or chloramphenicol was rare. None of staphylococcal isolates was susceptible to all tested antibiotics. Resistance to at least 3 drugs was found in (35) 53% and (28) 42.4 % of S. aureus and S. epidermidis isolates, respectively