Lipid Metabolism

Perilipin 2, also known as Adipose differentiation-relation protein or PLIN2, is a lipid droplet-binding protein present in almost every tissue. The absence of PLIN2 upregulates hepatic very low-density lipoprotein secretion, relieves hepatosteatosis, and improves whole body insulin resistance in mice. Despite of the importance in mediating lipid metabolism, the regulation of PLIN2 itself remains largely unknown. Previous reports have shown that X-box binding protein 1 (XBP1) is an important regulator of lipogenesis. XBP1 is a transcription factor that recognizes and binds to a consensus sequence, 5’-TGACGTGG-3’. Interestingly, when we looked through the promoter region of mouse Plin2 gene, we found that the consensus sequence is present in the Plin2 promoter. Therefore, we hypothesize that XBP1 might directly bind to Plin2 promoter and regulate the Plin2 expression. To test our hypothesis, we will perform the luciferase assay to examine whether the Plin2 promoter activity is regulated by XBP1. We first designed forward and reverse PCR primers, which include BglII and BamHI restriction enzyme sites respectively, to amplify the Plin2 promoter region (from -1100 to +40). We performed PCR and cloned the Plin2 promoter to a TA vector. The TA vector was then sequenced to exclude any point mutations. After sequencing, we sub cloned the Plin2 promoter into a vector containing a luciferase reporter. In the future, we will transfect 293T, a human embryonic kidney cell line, with the Plin2 promoter-luciferase vector we generated. We will compare the Plin2 promoter activity by measuring the luminescence in the presence or absence of XBP1

Positive Organizational Leadership: Some Recent Findings in Positive Organizational Scholarship

The study of positivity is multifaceted, with roots across psychology, philosophy, and more recently organizational behavior (Csikszentmihalyi, 1997; 2014). This review article highlights the framework from which the study of positivity originates, and then explores positive behaviors in the workplace that have correlated to increases in fulfillment, productivity, engagement, and leadership capacity (Cameron & Dutton, 2003). This essay reveals core components of positive organizational scholarship (POS), notably the interaction of positivity within job demands and job resources, positive employee engagement, and positive deviance, and uncovers some recent findings of these POS components in empirical research and application within human resource management

Multimodal Imaging And Asymmetry Of Disease Progression In Rhodopsin-Associated Autosomal Dominant Retinitis Pigmentosa

Retinitis pigmentosa (RP) is a group of genetically and clinically heterogeneous inherited retinal degenerative diseases with no known cure to date. The recent gene therapy treatment for Leber’s congenital amaurosis and RP caused by mutations in RPE65 have resulted in dramatic improvements in vision, leading to excitement for other potential gene therapies on the horizon. Upcoming clinical trials will be targeting patients with specific mutations, and measurements of disease progression will be needed for each genetic subtype of RP in order to determine whether treatments are successful. In this retrospective cohort study, we examined 27 RP patients with confirmed autosomal dominant mutations in the rhodopsin gene by monitoring rates of progression as measured structurally with ellipsoid zone (EZ) line width on spectral domain optical coherence tomography (SD-OCT), horizontal and vertical hyperautofluorescent ring diameters on short wavelength fundus autofluorescence (SW-FAF), and as measured functionally with 30 Hz flicker amplitudes on electroretinography (ERG). Each structural parameter was measured twice by the author four weeks apart. The mean rates of progression were -158.5 μm per year (-8.4%) for EZ line widths, -122.7 μm per year (-3.5%) for horizontal diameters, and -108.3 μm per year ( 3.9%) for vertical diameters. High test-retest reliability was observed for the parameters (EZ line intraclass coefficient [ICC] = 0.9989, horizontal diameter ICC = 0.9889, vertical diameter ICC = 0.9771). The three parameters were also correlated with each other (r = 0.9325 for EZ line and horizontal diameter; r = 0.9081 for EZ line and vertical diameter; r = 0.9630 for horizontal and vertical diameters). No significant changes in ERG amplitude were seen. The subjects were classified by rhodopsin mutation class (I, IIa, IIb, III) and morphology of the hyperautofluorescent ring (typical vs. atypical). No significant differences in rates of structural progression were observed by rhodopsin mutation class or by ring morphology. Finally, higher rates of asymmetry of progression between the left and right eyes were detected for EZ line width (23% of subjects), horizontal diameter (17%), and vertical diameter (25%), as compared to studies on other forms of RP

The Assistive Multi-Armed Bandit

Learning preferences implicit in the choices humans make is a well studied problem in both economics and computer science. However, most work makes the assumption that humans are acting (noisily) optimally with respect to their preferences. Such approaches can fail when people are themselves learning about what they want. In this work, we introduce the assistive multi-armed bandit, where a robot assists a human playing a bandit task to maximize cumulative reward. In this problem, the human does not know the reward function but can learn it through the rewards received from arm pulls; the robot only observes which arms the human pulls but not the reward associated with each pull. We offer sufficient and necessary conditions for successfully assisting the human in this framework. Surprisingly, better human performance in isolation does not necessarily lead to better performance when assisted by the robot: a human policy can do better by effectively communicating its observed rewards to the robot. We conduct proof-of-concept experiments that support these results. We see this work as contributing towards a theory behind algorithms for human-robot interaction.Comment: Accepted to HRI 201

Modeling virtualized application performance from hypervisor counters

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 61-64).Managing a virtualized datacenter has grown more challenging, as each virtual machine's service level agreement (SLA) must be satisfied, when the service levels are generally inaccessible to the hypervisor. To aid in VM consolidation and service level assurance, we develop a modeling technique that generates accurate models of service level. Using only hypervisor counters as inputs, we train models to predict application response times and predict SLA violations. To collect training data, we conduct a simulation phase which stresses the application across many workloads levels, and collects each response time. Simultaneously, hypervisor performance counters are collected. Afterwards, the data is synchronized and used as training data in ensemble-based genetic programming for symbolic regression. This modeling technique is quite efficient at dealing with high-dimensional datasets, and it also generates interpretable models. After training models for web servers and virtual desktops, we test generalization across different content. In our experiments, we found that our technique could distill small subsets of important hypervisor counters from over 700 counters. This was tested for both Apache web servers and Windows-based virtual desktop infrastructures. For the web servers, we accurately modeled the breakdown points and also the service levels. Our models could predict service levels with 90.5% accuracy on a test set. On a untrained scenario with completely different contending content, our models predict service levels with 70% accuracy, but predict SLA violation with 92.7% accuracy. For the virtual desktops, on test scenarios similar to training scenarios, model accuracy was 97.6%. Our main contribution is demonstrating that a completely data-driven approach to application performance modeling can be successful. In contrast to many other works, our models do not use workload level or response times as inputs to the models, but nevertheless predicts service level accurately. Our approach also lets the models determine which inputs are important to a particular model's performance, rather than hand choosing a few inputs to train on.by Lawrence L. Chan.M.Eng

Establishment of the advanced printing technology centre at Hong Kong institute of vocational education (Kwun tong)

This paper describes an industry and academic partnership initiative at Hong Kong Institute of Vocational Education (Kwun Tong). The project includes the establishment of the Advanced Printing Technology Centre at the Institute using a US$1.1 million funding from the Government. The Centre has set up a state-of-the-art digital printing production environment with equipment connected together using high-speed computer network. Generous support has been obtained from equipment manufacturers, which have installed about US$2.3 million worth of advanced equipment at the Centre. This initiative has created a 3-way winning situation for the students, the industry, and the equipment manufacturers. The students can acquire hands-on experience in using the advanced printing equipment, the printing industry can send its personnel to the Centre to receive training, and finally the manufacturers can use the Centre to showcase their latest products. This kind of establishment creates a partnership model that benefits all parties concerned and the model can be extended to other industries as well

Modeling Equilibrium of microRNA Expression

MicroRNAs are a class of non-coding RNAs and the dysregulated expression of these short RNA molecules was frequently observed in cancer cells. The steady state level of microRNA concentration may differentiate the biological function of the cells between normal and impaired. To understand the steady state or equilibrium of microRNAs, their interactions with transcription factors and target genes need to be explored and visualized through prediction and network analysis algorithms. This article discusses the application of mathematical model for simulating the dynamics of network feedback loop so as to decipher the mechanism of microRNA regulation

DRG-targeted helper-dependent adenoviruses mediate selective gene delivery for therapeutic rescue of sensory neuronopathies in mice

Dorsal root ganglion (DRG) neuron dysfunction occurs in a variety of sensory neuronopathies for which there are currently no satisfactory treatments. Here we describe the development of a strategy to target therapeutic genes to DRG neurons for the treatment of these disorders. We genetically modified an adenovirus (Ad) to generate a helper virus (HV) that was detargeted for native adenoviral tropism and contained DRG homing peptides in the adenoviral capsid fiber protein; we used this HV to generate DRG-targeted helper-dependent Ad (HDAd). In mice, intrathecal injection of this HDAd produced a 100-fold higher transduction of DRG neurons and a markedly attenuated inflammatory response compared with unmodified HDAd. We also injected HDAd encoding the β subunit of β-hexosaminidase (Hexb) into Hexb-deficient mice, a model of the neuronopathy Sandhoff disease. Delivery of the DRG-targeted HDAd reinstated neuron-specific Hexb production, reversed gangliosidosis, and ameliorated peripheral sensory dysfunction. The development of DRG neuron–targeted HDAd with proven efficacy in a preclinical model may have implications for the treatment of sensory neuronopathies of diverse etiologies

The 105-kDa Basement Membrane Autoantigen p105 Is N-Terminally Homologous to a Tumor-Associated Antigen

Certain constitutive skin basement membrane components, such as bullous pemphigoid antigens and epidermolysis bullosa acquisita antigen, were discovered because they were targeted by an autoimmune reaction. We aimed to purify and characterize a 105-kDa skin basement membrane protein termed p105 recognized by autoantibodies (anti-p105) from patients with a unique immune-mediated subepidermal blistering skin disease. A simian virus 40-transformed human fibroblast cell line that synthesizes and secretes p105 was utilized as the protein source. p105 was partially purified by salt-gradient fractionation of serum-free conditioned medium through a Mono Q anion-exchange column and by examining each fraction with protein staining and immunoblotting against anti-p105. p105 was isolated from polyacrylamide gel electrophoresis gels, blotted onto polyvinylidene difluoride membrane, and subjected to protein microsequencing. The 20 microsequenced N-terminal amino acids exhibited no homology to known basement membrane proteins but exhibited a 70% homology to a 90-kDa tumor-associated antigen. Antibodies raised against a peptide generated from these amino acid sequences reacted to a 105-kDa western-blotted keratinocyte and fibroblast protein and a basement membrane component. p105 resisted digestion by glycosidases chondroitinase ABC, neuraminidase, and N-glycosidase F but was cleaved by protease V8 to antigenic fragments of 22kDa and 14kDa. The synthesis of p105 was inhibited by cycloheximide. We conclude that p105 is a unique basement membrane component produced by both keratinocytes and fibroblasts