Transcriptional Profiling of Mycobacterium Tuberculosis During Infection: Lessons Learned

Infection with Mycobacterium tuberculosis, the causative agent of tuberculosis, is considered one of the biggest infectious disease killers worldwide. A significant amount of attention has been directed toward revealing genes involved in the virulence and pathogenesis of this air-born pathogen. With the advances in technologies for transcriptional profiling, several groups, including ours, took advantage of DNA microarrays to identify transcriptional units differentially regulated by M. tuberculosis within a host. The main idea behind this approach is that pathogens tend to regulate their gene expression levels depending on the host microenvironment, and preferentially express those needed for survival. Identifying this class of genes will improve our understanding of pathogenesis. In our case, we identified an in vivo expressed genomic island that was preferentially active in murine lungs during early infection, as well as groups of genes active during chronic tuberculosis. Other studies have identified additional gene groups that are active during macrophage infection and even in human lungs. Despite all of these findings, one of the lingering questions remaining was whether in vivo expressed transcripts are relevant to the virulence, pathogenesis, and persistence of the organism. The work of our group and others addressed this question by examining the contribution of in vivo expressed genes using a strategy based on gene deletions followed by animal infections. Overall, the analysis of most of the in vivo expressed genes supported a role of these genes in M. tuberculosis pathogenesis. Further, these data suggest that in vivo transcriptional profiling is a valid approach to identify genes required for bacterial pathogenesis

Immunohistochemical Assessment of TNFAIP3/A20 Expression Correlates With Early Tumorigenesis in Breast Cancer

BACKGROUND/AIM: Limited data exist on the expression pattern of TNFAIP3/A20, as assayed by immunohistochemistry (IHC), in breast cancer tissues. This study aimed to assess A20 expression pattern in breast cancer. Materials and Methods: The expression of A20 was analysed using IHC in 50 breast cancer cases retrieved from the Sharjah Breast Cancer Center at the University Hospital Sharjah, United Arab Emirates. Omics survival data were also used to analyse its association with survival in endocrine-treated subgroups. Results: A20 expression in breast cancer tissues was 'tumor-specific', and as compared to normal tissue areas, its expression was associated with both intensity and extent in early grade 1 (p<0.0001) in all molecular subtypes. In addition, using omics survival data from a cohort of 3,520 breast cancer patients, we showed that A20 overexpression associated with lower overall survival rate in the endocrine treated subgroups [hazard ratio (HR)=2.14, 95%CI=1.61-2.82, p<0.0001]. Conclusion: A20 can serve as a biomarker for early diagnosis of breast cancers

Performance Enhancement of TBAI Capped CdSe-Quantum Dot Sensitized Solar Cells by an Interlayer Gold Nanoparticles

The photovoltaic performance (PV) of quantum dot sensitized solar cells (QDSSCs) has been studied by the addition of gold nanoparticles (Au NPs) at three configuration interlayer positions in the photoanodes. The resulting photoanodes are (i) Fluorine doped tin oxide (FTO) /Au NPs/TiO2/CdSe QDs,(ii) FTO/TiO2/Au NPs/CdSe QDs and (iii) FTO/TiO2/CdSe QDs/Au NPs. The TOPO and HDA capping of CdSe QDs has been modified to be TBAI in order to decrease the CdSe-TiO2 molecular separation. The average size of Au NPs is ~ 15nm as measured by HRTEM. Our results show that the configuration with Au NPs deposited directly on FTO exhibit a noticeable improvement of the power conversion efficiency (PCE) from 0.62% to 1.1%, while the other two configurations show a slight improvement in their performance. The effect of Au NPs in the three photonode configurations on the photovoltaic performance are discussed

Development of exchange lists for M editerranean and H ealthy E ating D iets: implementation in an intervention trial

Background There has been little research published on the adaptation of diabetic exchange list diet approaches for the design of intervention diets in health research despite their clinical utility. The exchange list approach can provide clear and precise guidance on multiple dietary changes simultaneously. The present study aimed to develop exchange list diets for M editerranean and H ealthy E ating, and to evaluate adherence, dietary intakes and markers of health risks with each counselling approach in 120 subjects at increased risk for developing colon cancer. Methods A randomised clinical trial was implemented in the USA involving telephone counselling. The M editerranean diet had 10 dietary goals targeting increases in mono‐unsaturated fats, n ‐3 fats, whole grains and the amount and variety of fruits and vegetables. The Healthy Eating diet had five dietary goals that were based on the US H ealthy P eople 2010 recommendations. Results Dietary compliance was similar in both diet arms, with 82–88% of goals being met at 6 months, although subjects took more time to achieve the M editerranean goals than the H ealthy E ating goals. The relatively modest fruit and vegetable goals in the Healthy Eating arm were exceeded, resulting in fruit and vegetable intakes of approximately eight servings per day in each arm after 6 months. A significant ( P  < 0.05) weight loss and a decrease in serum C ‐reactive protein concentrations were observed in the overweight/obese subgroup of subjects in the M editerranean arm in the absence of weight loss goals. Conclusions Counselling for the M editerranean diet may be useful for both improving diet quality and for achieving a modest weight loss in overweight or obese individuals.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108685/1/jhn12158.pd

The Photovoltaic Performance of CdS/Cu2S (QD) Co-Sensitized Solar Cell

The performance of CdS/Cu2S co-sensitized quantum dot solar cell (QDSSCs) is studied. CdS quantum dots (QDs) were adsorbed onto TiO2 using Successive Ionic Layer Adsorption and Reaction (SILAR) method for different cycles (2, 4, 6, 8 and 10). The Cu2S QDs were deposited onto TiO2/CdS10 cycle photoanodes using the same method. The FTO counter electrodes were coated with platinum, while the electrolyte containing polysulfide redox species was sandwiched between the two electrodes. The current density- voltage (J-V) characteristic curves of the assembled QDSSCs were measured at different cycles and AM 1.5 simulated sunlight. The value of current density (Jsc) and conversion efficiency (η) of TiO2/CdS/Cu2S are 252% larger than the TiO2/CdS values. The maximum values of Jsc and η are 3.56 mA/cm2 and 1.21% respectively corresponding to CdS10/Cu2S for 6 cycles of Cu2S

Contribution of proton and electron precipitation to the observed electron concentration in October–November 2003 and September 2005

Understanding the altitude distribution of particle precipitation forcing is vital for the assessment of its atmospheric and climate impacts. However, the proportion of electron and proton forcing around the mesopause region during solar proton events is not always clear due to uncertainties in satellite-based flux observations. Here we use electron concentration observations of the European Incoherent Scatter Scientific Association (EISCAT) incoherent scatter radars located at Tromsø (69.58° N, 19.23° E) to investigate the contribution of proton and electron precipitation to the changes taking place during two solar proton events. The EISCAT measurements are compared to the results from the Sodankylä Ion and Neutral Chemistry Model (SIC). The proton ionization rates are calculated by two different methods – a simple energy deposition calculation and the Atmospheric Ionization Model Osnabrück (AIMOS v1.2), the latter providing also the electron ionization rates. Our results show that in general the combination of AIMOS and SIC is able to reproduce the observed electron concentration within ± 50% when both electron and proton forcing is included. Electron contribution is dominant above 90 km, and can contribute significantly also in the upper mesosphere especially during low or moderate proton forcing. In the case of strong proton forcing, the AIMOS electron ionization rates seem to suffer from proton contamination of satellite-based flux data. This leads to overestimation of modelled electron concentrations by up to 90% between 75–90 km and up to 100–150% at 70–75 km. Above 90 km, the model bias varies significantly between the events. Although we cannot completely rule out EISCAT data issues, the difference is most likely a result of the spatio-temporal fine structure of electron precipitation during individual events that cannot be fully captured by sparse in situ flux (point) measurements, nor by the statistical AIMOS model which is based upon these observations

Genome-Wide Analysis of the Emerging Infection with Mycobacterium avium Subspecies paratuberculosis in the Arabian Camels (Camelus dromedarius)

Mycobacterium avium subspecies paratuberculosis (M. ap) is the causative agent of paratuberculosis or Johne's disease (JD) in herbivores with potential involvement in cases of Crohn's disease in humans. JD is spread worldwide and is economically important for both beef and dairy industries. Generally, pathogenic ovine strains (M. ap-S) are mainly found in sheep while bovine strains (M. ap-C) infect other ruminants (e.g. cattle, goat, deer), as well as sheep. In an effort to characterize this emerging infection in dromedary/Arabian camels, we successfully cultured M. ap from several samples collected from infected camels suffering from chronic, intermittent diarrhea suggestive of JD. Gene-based typing of isolates indicated that all isolates belong to sheep lineage of strains of M. ap (M. ap-S), suggesting a putative transmission from infected sheep herds. Screening sheep and goat herds associated with camels identified the circulation of this type in sheep but not goats. The current genome-wide analysis recognizes these camel isolates as a sub-lineage of the sheep strain with a significant number of single nucleotide polymorphisms (SNPs) between sheep and camel isolates (∼1000 SNPs). Such polymorphism could represent geographical differences among isolates or host adaptation of M. ap during camel infection. To our knowledge, this is the first attempt to examine the genomic basis of this emerging infection in camels with implications on the evolution of this important pathogen. The sequenced genomes of M. ap isolates from camels will further assist our efforts to understand JD pathogenesis and the dynamic of disease transmission across animal species

A site assessment tool for inpatient controlled human infection models for enteric disease pathogens

The use of the controlled human infection model to facilitate product development and to advance understanding of host-pathogen interactions is of increasing interest. While administering a virulent (or infective) organism to a susceptible host necessitates an ongoing evaluation of safety and ethical considerations, a central theme in conducting these studies in a safe and ethical manner that yields actionable data is their conduct in facilities well-suited to address their unique attributes. To that end, we have developed a framework for evaluating potential sites in which to conduct inpatient enteric controlled human infection model to ensure consistency and increase the likelihood of success.publishedVersio

Towards a novel biologically-inspired cloud elasticity framework

With the widespread use of the Internet, the popularity of web applications has significantly increased. Such applications are subject to unpredictable workload conditions that vary from time to time. For example, an e-commerce website may face higher workloads than normal during festivals or promotional schemes. Such applications are critical and performance related issues, or service disruption can result in financial losses. Cloud computing with its attractive feature of dynamic resource provisioning (elasticity) is a perfect match to host such applications. The rapid growth in the usage of cloud computing model, as well as the rise in complexity of the web applications poses new challenges regarding the effective monitoring and management of the underlying cloud computational resources. This thesis investigates the state-of-the-art elastic methods including the models and techniques for the dynamic management and provisioning of cloud resources from a service provider perspective. An elastic controller is responsible to determine the optimal number of cloud resources, required at a particular time to achieve the desired performance demands. Researchers and practitioners have proposed many elastic controllers using versatile techniques ranging from simple if-then-else based rules to sophisticated optimisation, control theory and machine learning based methods. However, despite an extensive range of existing elasticity research, the aim of implementing an efficient scaling technique that satisfies the actual demands is still a challenge to achieve. There exist many issues that have not received much attention from a holistic point of view. Some of these issues include: 1) the lack of adaptability and static scaling behaviour whilst considering completely fixed approaches; 2) the burden of additional computational overhead, the inability to cope with the sudden changes in the workload behaviour and the preference of adaptability over reliability at runtime whilst considering the fully dynamic approaches; and 3) the lack of considering uncertainty aspects while designing auto-scaling solutions. This thesis seeks solutions to address these issues altogether using an integrated approach. Moreover, this thesis aims at the provision of qualitative elasticity rules. This thesis proposes a novel biologically-inspired switched feedback control methodology to address the horizontal elasticity problem. The switched methodology utilises multiple controllers simultaneously, whereas the selection of a suitable controller is realised using an intelligent switching mechanism. Each controller itself depicts a different elasticity policy that can be designed using the principles of fixed gain feedback controller approach. The switching mechanism is implemented using a fuzzy system that determines a suitable controller/- policy at runtime based on the current behaviour of the system. Furthermore, to improve the possibility of bumpless transitions and to avoid the oscillatory behaviour, which is a problem commonly associated with switching based control methodologies, this thesis proposes an alternative soft switching approach. This soft switching approach incorporates a biologically-inspired Basal Ganglia based computational model of action selection. In addition, this thesis formulates the problem of designing the membership functions of the switching mechanism as a multi-objective optimisation problem. The key purpose behind this formulation is to obtain the near optimal (or to fine tune) parameter settings for the membership functions of the fuzzy control system in the absence of domain experts’ knowledge. This problem is addressed by using two different techniques including the commonly used Genetic Algorithm and an alternative less known economic approach called the Taguchi method. Lastly, we identify seven different kinds of real workload patterns, each of which reflects a different set of applications. Six real and one synthetic HTTP traces, one for each pattern, are further identified and utilised to evaluate the performance of the proposed methods against the state-of-the-art approaches