Detection of virulence factors and antimicrobial resistance patterns in shiga toxin-producing Escherichia coli isolates from sheep

Abstract: In order to detect virulence factors in Shiga toxin-producing Escherichia coli (STEC) isolates and investigate the antimicrobial resistance profile, rectal swabs were collected from healthy sheep of the races Santa Inês and Dorper. Of the 115 E. coli isolates obtained, 78.3% (90/115) were characterized as STEC, of which 52.2% (47/90) carried stx1 gene, 33.3% (30/90) stx2 and 14.5% (13/90) both genes. In search of virulence factors, 47.7% and 32.2% of the isolates carried the genes saa and cnf1. According to the analysis of the antimicrobial resistance profile, 83.3% (75/90) were resistant to at least one of the antibiotics tested. In phylogenetic classification grouped 24.4% (22/90) in group D (pathogenic), 32.2% (29/90) in group B1 (commensal) and 43.3% (39/90) in group A (commensal). The presence of several virulence factors as well as the high number of multiresistant isolates found in this study support the statement that sheep are potential carriers of pathogens threatening public health.

From Molecular Blocks To Bioanalytical Assays: Combining Lanthanide Luminescence and Bioaffinity Binders for Protein Detection

Measuring protein biomarkers from sample matrix, such as plasma, is one of the basic tasks in clinical diagnostics. Bioanalytical assays used for the measuring should be able to measure proteins with high sensitivity and specificity. Furthermore, multiplexing capability would also be advantageous. To ensure the utility of the diagnostic test in point-of-care setting, additional requirements such as short turn-around times, ease-ofuse and low costs need to be met. On the other hand, enhancement of assay sensitivity could enable exploiting novel biomarkers, which are present in very low concentrations and which the current immunoassays are unable to measure. Furthermore, highly sensitive assays could enable the use of minimally invasive sampling. In the development of high-sensitivity assays the label technology and affinity binders are in pivotal role. Additionally, innovative assay designs contribute to the obtained sensitivity and other characteristics of the assay as well as its applicability. The aim of this thesis was to study the impact of assay components on the performance of both homogeneous and heterogeneous assays. Applicability of two different lanthanide-based label technologies, upconverting nanoparticles and switchable lanthanide luminescence, to protein detection was explored. Moreover, the potential of recombinant antibodies and aptamers as alternative affinity binders were evaluated. Additionally, alternative conjugation chemistries for production of the labeled binders were studied. Different assay concepts were also evaluated with respect to their applicability to point-of-care testing, which requires simple yet sensitive methods. The applicability of upconverting nanoparticles to the simultaneous quantitative measurement of multiple analytes using imaging-based detection was demonstrated. Additionally, the required instrumentation was relatively simple and inexpensive compared to other luminescent lanthanide-based labels requiring time-resolved measurement. The developed homogeneous assays exploiting switchable lanthanide luminescence were rapid and simple to perform and thus applicable even to point-ofcare testing. The sensitivities of the homogeneous assays were in the picomolar range, which are still inadequate for some analytes, such as cardiac troponins, requiring ultralow limits of detection. For most analytes, however, the obtained limits of detection were sufficient. The use of recombinant antibody fragments and aptamers as binders allowed site-specific and controlled covalent conjugation to construct labeled binders reproducibly either by using chemical modification or recombinant technology. Luminescent lanthanide labels were shown to be widely applicable for protein detection in various assay setups and to contribute assay sensitivity.

Use of magnitude-squared coherence to identify the maximum driving response band of the somatosensory evoked potential

The present study proposes to apply magnitude-squared coherence (MSC) to the somatosensory evoked potential for identifying the maximum driving response band. EEG signals, leads [Fpz'-Cz'] and [C3'-C4'], were collected from two groups of normal volunteers, stimulated at the rate of 4.91 (G1: 26 volunteers) and 5.13 Hz (G2: 18 volunteers). About 1400 stimuli were applied to the right tibial nerve at the motor threshold level. After applying the anti-aliasing filter, the signals were digitized and then further low-pass filtered (200 Hz, 6th order Butterworth and zero-phase). Based on the rejection of the null hypothesis of response absence (MSC(f) > 0.0060 with 500 epochs and the level of significance set at a = 0.05), the beta and gamma bands, 15-66 Hz, were identified as the maximum driving response band. Taking both leads together ("logical-OR detector", with a false-alarm rate of a = 0.05, and hence a = 0.0253 for each derivation), the detection exceeded 70% for all multiples of the stimulation frequency within this range. Similar performance was achieved for MSC of both leads but at 15, 25, 35, and 40 Hz. Moreover, the response was detected in [C3'-C4'] at 35.9 Hz and in [Fpz'-Cz'] at 46.2 Hz for all members of G2. Using the "logical-OR detector" procedure, the response was detected at the 7th multiple of the stimulation frequency for the series as a whole (considering both groups). Based on these findings, the MSC technique may be used for monitoring purposes.

Topographic distribution of the tibial somatosensory evoked potential using coherence

The objective of the present study was to determine the adequate cortical regions based on the signal-to-noise ratio (SNR) for somatosensory evoked potential (SEP) recording. This investigation was carried out using magnitude-squared coherence (MSC), a frequency domain objective response detection technique. Electroencephalographic signals were collected (International 10-20 System) from 38 volunteers, without history of neurological pathology, during somatosensory stimulation. Stimuli were applied to the right posterior tibial nerve at the rate of 5 Hz and intensity slightly above the motor threshold. Response detection was based on rejecting the null hypothesis of response absence (significance level α= 0.05 and M = 500 epochs). The best detection rates (maximum percentage of volunteers for whom the response was detected for the frequencies between 4.8 and 72 Hz) were obtained for the parietal and central leads mid-sagittal and ipsilateral to the stimulated leg: C4 (87%), P4 (82%), Cz (89%), and Pz (89%). The P37-N45 time-components of the SEP can also be observed in these leads. The other leads, including the central and parietal contralateral and the frontal and fronto-polar leads, presented low detection capacity. If only contralateral leads were considered, the centro-parietal region (C3 and P3) was among the best regions for response detection, presenting a correspondent well-defined N37; however, this was not observed in some volunteers. The results of the present study showed that the central and parietal regions, especially sagittal and ipsilateral to the stimuli, presented the best SNR in the gamma range. Furthermore, these findings suggest that the MSC can be a useful tool for monitoring purposes.

Human papillomavirus detection and p16 methylation pattern in a case of esophageal papilloma

Esophageal cancer is a prevalent cancer worldwide. Some studies have reported the possible etiology of human papillomavirus (HPV) in benign and malignant papillomas of the esophagus but the conclusions are controversial. In the present study, we investigated an esophageal papilloma from a 30-year-old male patient presenting aphasia. HPV DNA was detected by generic PCR using MY09/11 primers, and restriction fragment length polymorphism revealed the presence of HPV54, usually associated with benign genital lesions. Hypermethylation of the pINK4A gene was also investigated due to its relation to malignant transformation, but no modification was detected in the host gene. Except for an incipient reflux, no risk factors such as cigarette smoking, alcohol abuse or an infected sexual partner were recorded. Since esophageal lesions may have a malignant potential, HPV detection and typing are useful tools for patient follow-up.

Development of two potential diagnostic monoclonal antibodies against human cytomegalovirus glycoprotein B

Human cytomegalovirus glycoprotein B (gB) represents a target for diagnosis and treatment in view of the role it plays in virus entry and spread. Nevertheless, to our knowledge, rare detection of a gB antigen has been reported in transplant patients and limited information is available about diagnostic gB monoclonal antibodies (mAbs). Our aim was to develop gB mAbs with diagnostic potential. Hydrophilic gB peptides (ST: amino acids 27-40, SH: amino acids 81-94) of favorable immunogenicity were synthesized and used to immunize BALB/c mice. Two mAbs, named ZJU-FH6 and ZJU-FE6, were generated by the hybridoma technique and limited serial dilution and then characterized by indirect ELISA, Western blotting, immunoprecipitation, and immunohistochemical staining. The mAbs displayed high titers of specific binding affinities for the ST and SH synthetic peptides at an mAb dilution of 1:60,000 and 1:240,000, respectively. Western blotting and immunoprecipitation indicated that these mAbs recognized both denatured and native gB of the Towne and AD169 strains. The mAbs, when used as the primary antibody, showed positive staining in cells infected with both Towne and AD169 strains. The mAbs were then tested on patients submitted to allogeneic hematopoietic stem cell transplantation. The gB antigen positivity rates of the patients tested using ZJU-FH6 and ZJU-FE6 were 62.0 and 63.0%, respectively. The gB antigen showed a significant correlation with the level of pp65 antigen in peripheral blood leukocytes. In conclusion, two potential diagnostic gB mAbs were developed and were shown to be capable of recognizing gB in peripheral blood leukocytes in a reliable manner.

Role of a GenoType MTBDRplus line probe assay in early detection of multidrug-resistant tuberculosis at a Brazilian reference center

Resistance to Mycobacterium tuberculosis is a reality worldwide, and its diagnosis continues to be difficult and time consuming. To face this challenge, the World Health Organization has recommended the use of rapid molecular tests. We evaluated the routine use (once a week) of a line probe assay (Genotype MTBDRplus) for early diagnosis of resistance and for assessment of the main related risk factors over 2 years. A total of 170 samples were tested: 15 (8.8%) were resistant, and multidrug resistance was detected in 10 (5.9%). The sensitivity profile took 3 weeks (2 weeks for culture and 1 week for rapid testing). Previous treatment for tuberculosis and the persistence of positive acid-fast smears after 4 months of supervised treatment were the major risk factors observed. The use of molecular tests enabled early diagnosis of drug-resistant bacilli and led to appropriate treatment of the disease. This information has the potential to interrupt the transmission chain of resistant M. tuberculosis.

Detection of enterotoxins produced by B. cereus through PCR analysis of ground and roasted coffee samples in Rio de Janeiro, Brazil

Coffee is one of the most appreciated drinks in the world. Coffee ground is obtained from the fruit of a small plant that belongs to the genus Coffea. Coffea arabica and Coffea canephora robusta are the two most commercially important species. They are more commonly known as arabica and robusta, respectively. Two-thirds of Coffea arabica plants are grown in South and Central America, and Eastern Africa - the place of origin for this coffee species. Contamination by microorganisms has been a major matter affecting coffee quality in Brazil, mainly due to the harvesting method adopted. Brazilian harvests are based on fruits collected from the ground mixed with those that fall on collection cloths. As the Bacillus cereus bacterium frequently uses the soil as its environmental reservoir, it is easily capable of becoming a contaminant. This study aimed to evaluate the contamination and potential of B. cereus enterotoxin genes encoding the HBL and NHE complexes, which were observed in strains of ground and roasted coffee samples sold in Rio de Janeiro. The PCR (Polymerase Chain Reaction) results revealed high potential of enterotoxin production in the samples. The method described by Speck (1984) was used for the isolation of contaminants. The investigation of the potential production of enterotoxins through isolates of the microorganism was performed using the B. cereus enterotoxin Reverse Passive Latex Agglutination test-kit (BCET-RPLA, Oxoid), according to the manufacturer's instructions. The potential of enterotoxin production was investigated using polymerase chain reaction (PCR) methods for hblA, hblD and hblC genes (encoding hemolysin HBL) and for nheA, nheB and nheC genes (encoding non-hemolytic enterotoxin - NHE). Of all the 17 strains, 100% were positive for at least 1 enterotoxin gene; 52.9% (9/17) were positive for the 3 genes encoding the HBL complex; 35.3% (6/17) were positive for the three NHE encoding genes; and 29.4% (5/17) were positive for all enterotoxic genes.

Assessment of toxic potential of Cerrado fruit seeds using Artemia salina bioassay

Artemia salina bioassay was used to assess toxicity of seeds and kernels of Brazilian fruits from cerrado (central high plains region) and other inner regions of the country. Water extracts of the kernels were filtered and added to Artemia cultures containing ten individuals per mL. Dose - response curves were constructed, and LD50 values were calculated. Pure potassium cyanide standard was used to draw a calibration curve for comparison to detect the presence of cyanide in the samples tested. Extracts of the seeds of araticum, mangaba, cagaita, jatobá, and tucumã were found toxic to Artemia salina, and some of the dose - response curves were very similar in shape to those obtained with pure potassium cyanide standards, while the samples of baru, cajá-manga, siriguela, trauma, and veludo showed no toxicity at all. The Guignard test, specific for cyanide detection, showed negative results in all toxic samples, suggesting the presence of other toxic compounds rather than cyanide. The comparison of araticum dose - response curve with those of other annonaceous fruits suggests the presence acetogenins as the main toxic compounds in the seeds. These results could be useful to prevent poisoning by industrial derivatives of the fruits studied.

Detection of exopolysaccharide production and biofilm-related genes in Staphylococcus spp. isolated from a poultry processing plant

Staphylococcus spp. can survive in biofilms for long periods of time, and they can be transferred from one point to another and cause environmental contamination in food processing. The aim of this study was to detect Staphylococcus strains isolated from a poultry processing plant by the presence of adhesion genes and the phenotypic production of exopolysaccharide. In the present study, the production of exopolysaccharide and the presence of adhesion genes in 65 strains of Staphylococcus spp. were evaluated. All strains of Staphylococcus spp. produced exopolysaccharide, as confirmed by formation of black and opaque colonies in Congo Red Agar. The variation of sucrose content was critical for the production of exopolysaccharide in Congo Red Agar since at low sucrose concentrations all strains presented a characteristic result, i.e., there was no exopolysaccharide production. The atl gene was found in all strains, and the icaA and icaD genes were found in 97% of them. The data obtained suggest that Staphylococcus spp. isolated from the poultry processing plant evaluated has a potential for biofilm formation. An efficient control of this microorganism in food processing environment is necessary as they may represent a potential risk to consumers.

BotCloud Detection System

Leveraging cloud services, companies and organizations can significantly improve their efficiency, as well as building novel business opportunities. Cloud computing offers various advantages to companies while having some risks for them too. Advantages offered by service providers are mostly about efficiency and reliability while risks of cloud computing are mostly about security problems. Problems with security of the cloud still demand significant attention in order to tackle the potential problems. Security problems in the cloud as security problems in any area of computing, can not be fully tackled. However creating novel and new solutions can be used by service providers to mitigate the potential threats to a large extent. Looking at the security problem from a very high perspective, there are two focus directions. Security problems that threaten service user’s security and privacy are at one side. On the other hand, security problems that threaten service provider’s security and privacy are on the other side. Both kinds of threats should mostly be detected and mitigated by service providers. Looking a bit closer to the problem, mitigating security problems that target providers can protect both service provider and the user. However, the focus of research community mostly is to provide solutions to protect cloud users. A significant research effort has been put in protecting cloud tenants against external attacks. However, attacks that are originated from elastic, on-demand and legitimate cloud resources should still be considered seriously. The cloud-based botnet or botcloud is one of the prevalent cases of cloud resource misuses. Unfortunately, some of the cloud’s essential characteristics enable criminals to form reliable and low cost botclouds in a short time. In this paper, we present a system that helps to detect distributed infected Virtual Machines (VMs) acting as elements of botclouds. Based on a set of botnet related system level symptoms, our system groups VMs. Grouping VMs helps to separate infected VMs from others and narrows down the target group under inspection. Our system takes advantages of Virtual Machine Introspection (VMI) and data mining techniques.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Detection of Epilepsy with a Commercial EEG Headband

Epilepsy is a chronic brain disorder, characterized by reoccurring seizures. Automatic sei-zure detector, incorporated into a mobile closed-loop system, can improve the quality of life for the people with epilepsy. Commercial EEG headbands, such as Emotiv Epoc, have a potential to be used as the data acquisition devices for such a system. In order to estimate that potential, epileptic EEG signals from the commercial devices were emulated in this work based on the EEG data from a clinical dataset. The emulated characteristics include the referencing scheme, the set of electrodes used, the sampling rate, the sample resolution and the noise level. Performance of the existing algorithm for detection of epileptic seizures, developed in the context of clinical data, has been evaluated on the emulated commercial data. The results show, that after the transformation of the data towards the characteristics of Emotiv Epoc, the detection capabilities of the algorithm are mostly preserved. The ranges of acceptable changes in the signal parameters are also estimated.

Buried Treasure: The Economics of Leak Detection and Water Loss Prevention in Ontario

On average approximately 13% of the water that is withdrawn by Canadian municipal water suppliers is lost before it reaches final users. This is an important topic for several reasons: water losses cost money, losses force water agencies to draw more water from lakes and streams thereby putting more stress on aquatic ecosystems, leaks reduce system reliability, leaks may contribute to future pipe failures, and leaks may allow contaminants to enter water systems thereby reducing water quality and threatening the health of water users. Some benefits of leak detection fall outside water agencies’ accounting purview (e.g. reduced health risks to households connected to public water supply systems) and, as a result, may not be considered adequately in water agency decision-making. Because of the regulatory environment in which Canadian water agencies operate, some of these benefits-especially those external to the agency or those that may accrue to the agency in future time periods- may not be fully counted when agencies decide on leak detection efforts. Our analysis suggests potential reforms to promote increased efforts for leak detection: adoption of a Canada-wide goal of universal water metering; development of full-cost accounting and, pricing for water supplies; and co-operation amongst the provinces to promulgate standards for leak detection efforts and provide incentives to promote improved efficiency and rational investment decision-making.

STUDYING ABERRANT METHYLATION AND miRNA PROFILING FOR THE DETECTION OF LUNG CANCER BIOMARKERS

Lung cancer is a major chronic disease responsible for the highest mortality rate, among other types of cancer, and represents 29% of all deaths in Canada. The clinical diagnosis of lung carcinoma still requires a standard diagnostic approach, as there are no symptoms in its early stage. Therefore, it is usually diagnosed at a later stage, when the survival rate is low. With the recent advancement in molecular biology and biotechnology, a molecular biomarker approach for the diagnosis of early lung cancer seems to be a potential option. In this study, we aimed to investigate and standardize a promising Lung ,Cancer Biomarker by studying the aberrant methylation of two tumour suppressor genes, namely RASSFIA and RAR-B, and the miRNA profiling of four . commonly deregulated miRNA (miR-199a-3p, miR-182, miR-lOO and miR-221). Four lung cancer cell lines were used (two SCLC and two NSCLC), with comparisons being made with normal lung cell lines. Our results, we found that none of these genes were methylated. We then evaluated TP53, and found the promoter of this gene to be methylated in the cancer cell lines, as compared to the normal cell lines, indicating gene inactivation. We carried out miRNA profiling of the cancer cell lines and reported that 80 miRNAs are deregulated in lung cancer cell lines as compared to the normal cell lines. Our study was the first of its kind to indicate that hsa-mir-4301, hsa-mir-4707-5p and hsa-mir-4497 (newly discovered miRNAs) are deregulated in lung cancer cell lines. We also investigated miR-199a-3p, mir-lOO and miR-182, and found that miR-199a -3p and mir-l00 were down-regulated in cancer lines, whereas miR-182 was up-regulated in the cancer cell lines. In the final part of the study we observed that mir-221 could be a putative biomarker to distinguish between the two types of lung cancer because it was down-regulated in SCLC, and up-regulated in the NSCLC cell lines. In conclusion, we found four miRNA molecular biomarkers that possibly could be used in the early diagnosis of the lung cancer. More studies are still required with larger numbers of samples to effectively establish these as molecular biomarkers for the diagnosis of lung cancer