Gene expression profiling in periodontitis

The chronic inflammatory disease periodontitis is characterized by destruction of periodontal tissue, i.e. the tissues that surround and support the teeth. This complex disease is multifactorial, involving oral pathogens, an unfavorable host inflammatory response, environmental and genetic factors, as well as an altered gene expression contributing to disease pathology. Despite extensive research of excellent quality, the genes involved in periodontitis remain uncharacterized and the mechanisms responsible for the destruction of periodontal tissue are poorly understood. Here, in attempt to gain further insight into and identify biomarkers for this disease, we have characterized global gene expression in periodontitis-affected gingival tissue and gingival fibroblasts. Initially, we employed microarrays to examine gene expression in gingival fibroblasts, the predominant cell type in gingival connective tissue, after evoking an inflammatory response in these cells with tumor necrosis factor-α (TNF-α). This inflammatory mediator up-regulated the expression of a wide range of genes and, furthermore, activated several signaling pathways involved in immune and inflammatory responses, in particular the toll-like receptor (TLR) signaling pathway. We subsequently confirmed for the first time that TNF-α-enhances the expression of TLR2 in gingival fibroblasts at both the mRNA and protein levels. In addition, we found that the c-Jun N-terminal kinase (JNK) and nuclear factor-kappa B (NFkB) signal transduction pathways, as well as prostaglandin 15d-PGJ2, which has been proposed to be anti-inflammatory, are involved in this up-regulation. Next, we examined the transcriptome, employing RNA-sequencing, in periodontitis-affected and healthy gingival tissue from patients with periodontitis. We demonstrated, as expected, that the degree of inflammation in periodontitis-affected gingival tissue is more pronounced than in corresponding healthy tissue from the same individual. Cluster analysis revealed that the clustering depended on the degree of inflammation, rather than the individual from whom the tissue was taken, indicating the existence of a characteristic gene expression profile for periodontitis. In addition, we identified two novel genes, interferon regulatory factor 4 (IRF4) and Chemokine (C-C motif) ligand 18 (CCL18) that were up-regulated in association with periodontitis. In our third study, we utilized the RNA-sequencing approach to characterize gene expression in a large number of gingival biopsies both from patients with periodontitis and healthy control subjects. Among the several genes that were significantly up- or down-regulated in periodontitis, the two most differentially expressed were mucin 4 (MUC4) and matrix metalloproteinase 7 (MMP7). This investigation provides a comprehensive map of the gene expression associated with periodontitis and, suggests that MUC4 and MMP7 might be potentially valuable biomarkers and clinical therapeutic targets for periodontitis. In conclusion, the information we present here provides new insights into the molecular mechanisms underlying the etiology and progression of this chronic inflammatory disease

Human MAIT cells endowed with HBV specificity are cytotoxic and migrate towards HBV-HCC while retaining antimicrobial functions

Background & Aims: Virus-specific T cell dysfunction is a common feature of HBV-related hepatocellular carcinoma (HBV-HCC). Conventional T (ConT) cells can be redirected towards viral antigens in HBV-HCC when they express an HBV-specific receptor; however, their efficacy can be impaired by liver-specific physical and metabolic features. Mucosal-associated invariant T (MAIT) cells are the most abundant innate-like T cells in the liver and can elicit potent intrahepatic effector functions. Here, we engineered ConT and MAIT cells to kill HBV expressing hepatoma cells and compared their functional properties. Methods: Donor-matched ConT and MAIT cells were engineered to express an HBV-specific T cell receptor (TCR). Cytotoxicity and hepatocyte homing potential were investigated using flow cytometry, real-time killing assays, and confocal microscopy in 2D and 3D HBV-HCC cell models. Major histocompatibility complex (MHC) class I-related molecule (MR1)-dependent and MR1-independent activation was evaluated in an Escherichia coli THP-1 cell model and by IL-12/IL-18 stimulation, respectively. Results: HBV TCR-MAIT cells demonstrated polyfunctional properties (CD107a, interferon [IFN] γ, tumour necrosis factor [TNF], and IL-17A) with strong HBV target sensitivity and liver-homing chemokine receptor expression when compared with HBV TCR-ConT cells. TCR-mediated lysis of hepatoma cells was comparable between the cell types and augmented in the presence of inflammation. Coculturing with HBV+ target cells in a 3D microdevice mimicking aspects of the liver microenvironment demonstrated that TCR-MAIT cells migrate readily towards hepatoma targets. Expression of an ectopic TCR did not affect the ability of the MAIT cells to be activated via MR1-presented bacterial antigens or IL-12/IL-18 stimulation. Conclusions: HBV TCR-MAIT cells demonstrate anti-HBV functions without losing their endogenous antimicrobial mechanisms or hepatotropic features. Our results support future exploitations of MAIT cells for liver-directed immunotherapies. Lay summary: Chronic HBV infection is a leading cause of liver cancer. T cell receptor (TCR)-engineered T cells are patients’ immune cells that have been modified to recognise virus-infected and/or cancer cells. Herein, we evaluated whether mucosal-associated invariant T cells, a large population of unconventional T cells in the liver, could recognise and kill HBV infected hepatocytes when engineered with an HBV-specific TCR. We show that their effector functions may exceed those of conventional T cells currently used in the clinic, including antimicrobial properties and chemokine receptor profiles better suited for targeting liver tumours

Comparative Analysis of Gingival Tissue Antigen Presentation Pathways in Ageing and Periodontitis

AIM: Gingival tissues of periodontitis lesions contribute to local elevations in mediators, including both specific T cell and antibody immune responses to oral bacterial antigens. Thus, antigen processing and presentation activities must exist in these tissues to link antigen-presenting cells with adaptive immunity. We hypothesized that alterations in the transcriptome of antigen processing and presentation genes occur in ageing gingival tissues and that periodontitis enhances these differences reflecting tissues less capable of immune resistance to oral pathogens. MATERIALS AND METHODS: Rhesus monkeys (n = 34) from 3 to 23 years of age were examined. A buccal gingival sample from healthy or periodontitis sites was obtained, total RNA isolated, and microarray analysis was used to describe the transcriptome. RESULTS: The results demonstrated increased transcription of genes related to the MHC class II and negative regulation of NK cells with ageing in healthy gingival tissues. In contrast, both adult and ageing periodontitis tissues showed decreased transcription of genes for MHC class II antigens, coincident with up-regulation of MHC class I-associated genes. CONCLUSION: These transcriptional changes suggest a response of healthy ageing tissues through the class II pathway (i.e. endocytosed antigens) and altered responses in periodontitis that could reflect host-associated self-antigens or targeting cytosolic intracellular microbial pathogens

Techniques for Detecting Intrusions

Detecting intrusions is usually the first step in containing a security breach. In this dissertation, we focus on how we can understand and profile IoT malware behavior in order to find intrusions. Specifically, we want to develop a holistic view of how the malware behaves once installed in an IoT device, which will encompass: (a) how does the malware communicate with its Command and Control server, (b) how does the malware communication and infrastructure change over time, and (c) how does a network-affected data flows through the device (which is known as taint analysis). In the first chapter of this thesis, we propose a novel solution for finding IP and port addresses of live Command and Control (CnC) servers of IoT botnets. Furthermore, we present a solution for detecting intrusions using only network level patterns given a malware binary. Our novelty lies in activating the malware binary and extracting patterns that can precisely indicate intrusions without the need of deep packet inspection. In the second chapter, we conduct an extensive study of the behaviors of both bots and CnC servers over time. In more detail, we probe IP networks that show signs of CnC hosting and search for CnC servers among neighbor hosts on a daily basis. This approach allows us to find CnC servers in an active manner; we find CnC servers even before their corresponding malware samples are collected by honeypots. In addition, the collected data provides insight on the network infrastructure of IoT botnets. Finally, we shed light on the non-CnC traffic of the IoT malware that mainly tries to spread the malware.In the third chapter, we focus on taint analysis where the goal is to understand the flow of data within a system. In the Intrusion Detection context, the input data is the network traffic e.g. a command from the CnC. We discuss how dynamic taint analysis can be selectively applied for whole system analysis in intrusion detection systems, and show how this approach can speed up the system.Overall, this thesis provides a fundamental step in understanding IoT malware behavior, which can lead to better defenses in terms of detecting and containing the associated damage

Diffusion Tensor Imaging for Glioma Grading: Analysis of Fiber Density Index

Introduction: The most common primary tumors of brain are gliomas and tumor grading is essential for designing proper treatment strategies. The gold standard choice to determine grade of glial tumor is biopsy which is an invasive method. The purpose of this study was to investigatethe role of fiber density index (FDi) by means of diffusion tensor imaging (DTI) (as a noninvasive method) in glial tumor grading. Methods: A group of 20 patients with histologically confirmed diagnosis of gliomas wereevaluated in this study. We used a 1.5 Tesla MR system (AVANTO; Siemens, Germany) with a standard head coil for scanning. Multidirectional diffusion weighted imaging (measured in 12 noncollinear directions), and T1 weighted nonenhanced were performed for all patients. We defined two regions of interest (ROIs); 1) White matter fibers near the tumor and 2) Similar fibers in the contralateral hemisphere. Results: FDi of the low-grade gliomas was higher than those of high-grade gliomas, which was significant (P=0.017). FDi ratio (ratio of fiber density in vicinity of the tumor to homologous fiber tracts in the contralateral hemisphere) is higher in low-grade than high-grade tumors, (P=0.05). In addition, we performed ROC (receiver operating characteristic) curve and the area under curve (AUC) was 0.813(P=0.013). Conclusion: Our findings prove significant difference in FDi near by low-grade and high-grade gliomas. Therefore, FDi values and ratios are helpful in glial tumor grading.&nbsp

Diffusion Tensor Imaging for Glioma Grading: Analysis of Fiber Density Index

Introduction: The most common primary tumors of brain are gliomas and tumor grading is essential for designing proper treatment strategies. The gold standard choice to determine grade of glial tumor is biopsy which is an invasive method. The purpose of this study was to investigatethe role of fiber density index (FDi) by means of diffusion tensor imaging (DTI) (as a noninvasive method) in glial tumor grading. Methods: A group of 20 patients with histologically confirmed diagnosis of gliomas wereevaluated in this study. We used a 1.5 Tesla MR system (AVANTO; Siemens, Germany) with a standard head coil for scanning. Multidirectional diffusion weighted imaging (measured in 12 noncollinear directions), and T1 weighted nonenhanced were performed for all patients. We defined two regions of interest (ROIs); 1) White matter fibers near the tumor and 2) Similar fibers in the contralateral hemisphere. Results: FDi of the low-grade gliomas was higher than those of high-grade gliomas, which was significant (P=0.017). FDi ratio (ratio of fiber density in vicinity of the tumor to homologous fiber tracts in the contralateral hemisphere) is higher in low-grade than high-grade tumors, (P=0.05). In addition, we performed ROC (receiver operating characteristic) curve and the area under curve (AUC) was 0.813(P=0.013). Conclusion: Our findings prove significant difference in FDi near by low-grade and high-grade gliomas. Therefore, FDi values and ratios are helpful in glial tumor grading.&nbsp

Transcriptional profiling of human gingival fibroblasts in response to multi-species in vitro subgingival biofilms

Periodontitis is an infectious inflammatory disease that destroys the tooth-supporting tissues. It is initiated by complex subgingival biofilms, triggering an inflammatory response by the juxtaposed gingival tissue. The range of transcriptional events initiated in the gingiva following biofilm challenge is not fully elucidated. By employing gene microarray technology, this study aimed to characterize the overall transcriptional changes (more than two-fold regulation) of cultured human gingival fibroblasts in response to a 10-species in vitro subgingival biofilm model (BF), over a challenge period of 6 h. The relative involvement of the three 'red complex' species in these transcriptional events was evaluated by omitting these species from the biofilm composition (BF-RC). When compared with the unchallenged control, challenge with BF and BF-RC differentially regulated 386 and 428 genes, respectively, with an overlap of 52-75%. Interestingly, the expression of only three genes was significantly different between the BF and BF-RC challenged groups. There was also a strong overlap of the affected signalling pathways and gene ontology processes. These signalling pathways involved primarily the immune response, and included toll-like receptors, interleukin-1, interleukin-17 and heat-shock proteins 60 and 70. In conclusion, subgingival biofilms elicited a large number of transcriptional changes in gingival fibroblasts, while the presence of the 'red complex' in the biofilm did not yield any substantial differences. These findings show a uniform 'non-specific' transcriptional response of host cells to subgingival biofilms, and denote that redundancies may exist in the virulence properties of individual bacterial species within a polymicrobial biofilm community

Diversity: A poor man's solution to drone takeover

Drones are the new targets for hackers. On one hand, their widespread use and security weakness have made them very attractive for the attackers. On the other hand, there are a few security solutions for drones. Out of these few, some are just proposals, and fewer are in the early stage of development. We first assess the requirements of a security solution for drones and then analyse the effect of traditional cryptographic solutions on the drone's traffic volume and energy consumption. With recourse to Moving Target Defence, we propose a novel instruction diversity solution for drone security that is portable, and has zero overhead