A "synaptoplasmic cistern" mediates rapid inhibition of cochlear hair cells

Cochlear hair cells are inhibited by cholinergic efferent neurons. The acetylcholine (ACh) receptor of the hair cell is a ligand-gated cation channel through which calcium enters to activate potassium channels and hyperpolarize the cell. It has been proposed that calcium-induced calcium release (CICR) from a near-membrane postsynaptic store supplements this process. Here, we demonstrate expression of type I ryanodine receptors in outer hair cells in the apical turn of the rat cochlea. Consistent with this finding, ryanodine and other store-active compounds alter the amplitude of transient currents produced by synaptic release of ACh, as well as the response of the hair cell to exogenous ACh. Like the sarcoplasmic reticulum of muscle, the "synaptoplasmic" cistern of the hair cell efficiently couples synaptic input to CICR.Fil: Lioudyno, Maria. Johns Hopkins University School of Medicine; Estados UnidosFil: Hiel, Hakim. Johns Hopkins University School of Medicine; Estados UnidosFil: Kong, Jee-Hyun. Johns Hopkins University School of Medicine; Estados UnidosFil: Katz, Eleonora. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Waldman, Erik. Johns Hopkins University School of Medicine; Estados UnidosFil: Parameshwaran Iyer, Suchitra. Johns Hopkins University School of Medicine; Estados UnidosFil: Glowatzki, Elisabeth. Johns Hopkins University School of Medicine; Estados UnidosFil: Fuchs, Paul A.. Johns Hopkins University School of Medicine; Estados Unido

Structural mechanisms of DREAM complex assembly and regulation

The DREAM complex represses cell cycle genes during quiescence through scaffolding MuvB proteins with E2F4/5 and the Rb tumor suppressor paralog p107 or p130. Upon cell cycle entry, MuvB dissociates from p107/p130 and recruits B-Myb and FoxM1 for up-regulating mitotic gene expression. To understand the biochemical mechanisms underpinning DREAM function and regulation, we investigated the structural basis for DREAM assembly. We identified a sequence in the MuvB component LIN52 that binds directly to the pocket domains of p107 and p130 when phosphorylated on the DYRK1A kinase site S28. A crystal structure of the LIN52–p107 complex reveals that LIN52 uses a suboptimal LxSxExL sequence together with the phosphate at nearby S28 to bind the LxCxE cleft of the pocket domain with high affinity. The structure explains the specificity for p107/p130 over Rb in the DREAM complex and how the complex is disrupted by viral oncoproteins. Based on insights from the structure, we addressed how DREAM is disassembled upon cell cycle entry. We found that p130 and B-Myb can both bind the core MuvB complex simultaneously but that cyclin-dependent kinase phosphorylation of p130 weakens its association. Together, our data inform a novel target interface for studying MuvB and p130 function and the design of inhibitors that prevent tumor escape in quiescence

Stress Analysis in Bipolar Transistors

Stress effects in semiconductor devices have gained significant attention in semiconductor industry nowadays. Stress effect in semiconductor devices is used as a beneficial effect in sensor applications and strain engineering and efforts are taken to increase these effects. Strain engineering is widely used for MOSFETs. Performance of SiGe based heterostructure bipolar transistors (HBTs) is improved by bandgap and strain engineering. However this approach is not fully developed for Si bipolar junction transistors (BJTs). While stress effects are useful in some areas there are some unwanted stress effects as well. The unintentional stresses developed during fabrication, processing and packaging are harmful in semiconductor devices and efforts are taken to mitigate these stress effects. In this research work, stress-induced changes were investigated in the perspective of improvement for strain engineering in Si BJTs as well as mitigation of stress effects in precision analog circuits. npn and pnp BJTs on (100) and (111) planes were studied using experimental and modeling approaches. Modeling approach was mainly used for this study in order to overcome the practical difficulties associated with fabrication of devices with different orientation and sizes and controlled application of stress in various orientations for measurements. Measurements were taken for in-plane normal stress and the validity of the model was verified. A new one-dimensional numerical model was developed in Matlab in order to make the stress analysis easier and more in-depth with short running time. Simulation results of the 1-D model and Sentaurus TCAD tool were compared and both results showed very good agreement. While commercial TCAD tools usually takes tens of minutes for 2-D or hours for 3-D simulations for this type of stress analysis, the newly developed 1-D model gives comparable results in seconds and without any loss of information generated. This model can be used for fast stress analysis/prediction in vertical or lateral npn/pnp BJTs in any plane and will help in developing optimal design for strain engineering in BJTs or stress mitigation in analog circuits. The stress induced changes in vertical and lateral bipolar transistors on (100) plane were quantitatively analyzed for different stress orientations. Our analysis revealed that for a vertical npn transistor substantial enhancement in collector current (IC), dc current gain, cutoff frequency (fT), and maximum oscillation frequency (fmax) can be achieved using an uniaxial in-plane compressive or an out-of-plane tensile stress. In a vertical pnp considerable improvement in IC can be achieved with an in-plane or an out-of-plane compressive stress while the changes in dc current gain, fT and fmax are minimal. Lateral pnp BJTs showed much higher improvement for in-plane longitudinal compressive stress. In addition, lateral npn BJTs showed higher improvement for out-of-plane compressive stress. These results revealed a promising opportunity for strain engineering in both vertical and lateral Si BJTs. This study also revealed that the transport limited BJTs are less sensitive to stress than injection limited BJTs. In addition, vertical pnp on (100) silicon is less sensitive to stress than the vertical npn on (100) plane or vertical npn or pnp on (111) plane. On (111) silicon vertical npn BJTs are less sensitive than the vertical pnp BJTs. Finally, stress effects in precision analog circuits have been explored with the help of Spice simulations incorporating the 1-D theoretical model. Some methods for stress mitigation in precision analog circuits are also suggested including usage of less sensitive BJTs whenever possible, keeping the matching BJTs in close proximity to avoid stress gradients, avoiding high stress regions in chips, usage of enclosed lateral devices for stress compensation

Structural and biochemical characterization of marburgvirus VP35 and its role in immune evasion

Filoviruses are among the most deadly pathogens that cause acute disease in humans. Ebolavirus (EBOV) and marburgvirus (MARV) are the two members of this family, which have been documented to cause infrequent but severe outbreaks of hemorrhagic fever in humans. The severe pathogenesis and high lethality associated with filoviral infections, is in part, due to the suppression of host innate immune responses by virus-encoded proteins. Hence, structural and biochemical studies of filoviral proteins, to uncover the immune evasion mechanisms employed by filoviral proteins are an intense area of investigation. Previous studies on EBOV, have shown that one of the viral proteins called VP35 plays a key role in virus replication by functioning as a cofactor in the viral replication complex, and immune suppression by antagonizing the type I interferon (IFN) pathway. The C-terminal region of EBOV VP35 was implicated in dsRNA binding and IFN antagonism, although the mechanisms for immune evasion remained poorly defined. Recent work from our lab has resulted in crystal structures of Zaire ebolavirus (ZEBOV) and Reston ebolavirus (REBOV) VP35 C-terminal domain, and ZEBOV VP35 C-terminal domain bound to dsRNA. These studies gave new insights into the role of conserved basic residues in the C-terminal domain in both viral replication and immune evasion functions of VP35. These studies also established that mutation of residues mediating dsRNA binding also resulted in diminished IFN-inhibition using in vivo assays. In addition, the dsRNA bound structure suggested a potential mechanism by which EBOV VP35 hides viral dsRNA from detection by host RIG-I like receptors (RLRs). Studies addressing immune evasion mechanisms by filoviruses have predominantly been done on ZEBOV, and functions of MARV proteins are largely uncharacterized and are inferred through homology to EBOV. Moreover recent reports on MARV proteins have shown that there are important differences in cell entry, host tropism, replication complex formation, and immune evasion mechanisms between the two viruses. The goal of my thesis work was to develop a comparative understanding of EBOV and MARV VP35, by characterizing MARV VP35 mediated immune evasion mechanisms using structural, biochemical, and cell biological studies. During the course of this study, we solved the crystal structure of MARV VP35 interferon inhibitory domain (IID) bound to dsRNA. This structure revealed several similarities with ZEBOV VP35 IID, but importantly there are several striking differences. Similar to ZEBOV, mutation of residues involved in dsRNA contacts in the MARV VP35 IID-dsRNA structure results in diminished dsRNA binding and IFN inhibition in vivo. While both MARV and ZEBOV VP35 IID bind to dsRNA in a sequence independent manner, MARV VP35 IID binds long(er) dsRNA compared to ZEBOV. We did not observe any interactions of MARV VP35 IID with the dsRNA blunt-ends, as in the case ZEBOV VP35. We biochemically validated these structural differences by in vitro dsRNA binding assays and show that MARV VP35 IID binds preferentially to longer dsRNA. Moreover MARV VP35 IID is insensitive to the presence of 5\u27 or 3\u27 overhangs in dsRNA, whereas ZEBOV VP35 IID binds preferentially to blunt-end dsRNA compared to overhang containing dsRNA. In this study, for the first time, using in vitro ATPase assays, we show that while both MARV and ZEBOV VP35 IID can inhibit RIG-I activation by overhang containing dsRNA, only ZEBOV VP35 IID can inhibit RIG-I activation by short blunt-end dsRNA. In addition we show that both MARV and ZEBOV VP35 IID can inhibit MDA5 activation by poly I:C, a long dsRNA mimic, mediated ATPase activation. The results from this study supports a model based on both structural and biochemical data, in which MARV and ZEBOV VP35 IID inhibit host immune responses by sequestration of overlapping (double-strandedness) and distinct (blunt-ends) RNA PAMPs from being detected by host RIG-I like receptors. This work provides new insight into the structure and function of MARV VP35 IID, and advances our understanding of the structural basis for dsRNA binding by MARV VP35 IID and its role in IFN antagonism and immune evasion

Conflict of Laws in the Enforcement of Foreign Awards and Foreign Judgments: the Public Policy Defense and Practice in U.S. Courts

Public policy is one of the defenses that a court or a party may invoke in order to resist enforcement of an unjust foreign award or judgment. The purpose of this study is to analyze the status of the public policy as a defense to enforcement in the U.S and to examine its success rate. The thesis will contain suggestions to make public policy a more meaningful defense with respect to the enforcement of foreign judgments and its role in bringing about uniformity in the field of foreign judgments will be analyzed

Deep Architectures for Visual Recognition and Description

In recent times, digital media contents are inherently of multimedia type, consisting of the form text, audio, image and video. Several of the outstanding computer Vision (CV) problems are being successfully solved with the help of modern Machine Learning (ML) techniques. Plenty of research work has already been carried out in the field of Automatic Image Annotation (AIA), Image Captioning and Video Tagging. Video Captioning, i.e., automatic description generation from digital video, however, is a different and complex problem altogether. This study compares various existing video captioning approaches available today and attempts their classification and analysis based on different parameters, viz., type of captioning methods (generation/retrieval), type of learning models employed, the desired output description length generated, etc. This dissertation also attempts to critically analyze the existing benchmark datasets used in various video captioning models and the evaluation metrics for assessing the final quality of the resultant video descriptions generated. A detailed study of important existing models, highlighting their comparative advantages as well as disadvantages are also included. In this study a novel approach for video captioning on the Microsoft Video Description (MSVD) dataset and Microsoft Video-to-Text (MSR-VTT) dataset is proposed using supervised learning techniques to train a deep combinational framework, for achieving better quality video captioning via predicting semantic tags. We develop simple shallow CNN (2D and 3D) as feature extractors, Deep Neural Networks (DNNs and Bidirectional LSTMs (BiLSTMs) as tag prediction models and Recurrent Neural Networks (RNNs) (LSTM) model as the language model. The aim of the work was to provide an alternative narrative to generating captions from videos via semantic tag predictions and deploy simpler shallower deep model architectures with lower memory requirements as solution so that it is not very memory extensive and the developed models prove to be stable and viable options when the scale of the data is increased. This study also successfully employed deep architectures like the Convolutional Neural Network (CNN) for speeding up automation process of hand gesture recognition and classification of the sign languages of the Indian classical dance form, ‘Bharatnatyam’. This hand gesture classification is primarily aimed at 1) building a novel dataset of 2D single hand gestures belonging to 27 classes that were collected from (i) Google search engine (Google images), (ii) YouTube videos (dynamic and with background considered) and (iii) professional artists under staged environment constraints (plain backgrounds). 2) exploring the effectiveness of CNNs for identifying and classifying the single hand gestures by optimizing the hyperparameters, and 3) evaluating the impacts of transfer learning and double transfer learning, which is a novel concept explored for achieving higher classification accuracy

Application of a Machine Learning Algorithm in a Multi Stage Production System

This paper examines a permutation flow-shop scheduling problem, which is a complex combinatorial problem encountered in many practical applications. The objective of the research is to reduce the maximum completion time, i.e., the makespan of all jobs. In order to increase productivity and to meet the demand, manufacturers are continuously under pressure to attain the shortest possible completion time. Estimation of accurate cycle time can tremendously help production planning and scheduling in manufacturing industries. Since production planning is characterised by NP-hardness and a wide range, traditional optimization methods and heuristic rules are unable to find satisfactory solutions. Q-learning, a type of reinforcement learning algorithm, is used in this paper to find a solution that is close to being optimal. Q-learning is a branch of machine learning referring to the way an intelligent agent should act in order to maximize the concept of cumulative reward in a given environment. To validate the performance of the algorithm, Taillard’s benchmark problems were solved and compared with the upper bound value. The results showed that the performance of the algorithm is better and has low computational time. Based on the performance of the proposed algorithm, two case studies were done and the solutions are compared with the performance of a metaheuristic algorithm. The result shows that the proposed algorithm can effectively and efficiently solve the problem stated above and that it is an interesting solution to resolving complex scheduling problems