Fully Distributed Adaptive Controllers for Cooperative Output Regulation of Heterogeneous Linear Multi-agent Systems with Directed Graphs

This paper considers the cooperative output regulation problem for linear multi-agent systems with a directed communication graph, heterogeneous linear subsystems, and an exosystem whose output is available to only a subset of subsystems. Both the cases with nominal and uncertain linear subsystems are studied. For the case with nominal linear subsystems, a distributed adaptive observer-based controller is designed, where the distributed adaptive observer is implemented for the subsystems to estimate the exogenous signal. For the case with uncertain linear subsystems, the proposed distributed observer and the internal model principle are combined to solve the robust cooperative output regulation problem. Compared with the existing works, one main contribution of this paper is that the proposed control schemes can be designed and implemented by each subsystem in a fully distributed fashion for general directed graphs. For the special case with undirected graphs, a distributed output feedback control law is further presented.Comment: 8 pages, 2 figures. submitted for publicatio

Deep generative modeling for single-cell transcriptomics.

Single-cell transcriptome measurements can reveal unexplored biological diversity, but they suffer from technical noise and bias that must be modeled to account for the resulting uncertainty in downstream analyses. Here we introduce single-cell variational inference (scVI), a ready-to-use scalable framework for the probabilistic representation and analysis of gene expression in single cells ( https://github.com/YosefLab/scVI ). scVI uses stochastic optimization and deep neural networks to aggregate information across similar cells and genes and to approximate the distributions that underlie observed expression values, while accounting for batch effects and limited sensitivity. We used scVI for a range of fundamental analysis tasks including batch correction, visualization, clustering, and differential expression, and achieved high accuracy for each task

Semantic inference using chemogenomics data for drug discovery

<p>Abstract</p> <p>Background</p> <p>Semantic Web Technology (SWT) makes it possible to integrate and search the large volume of life science datasets in the public domain, as demonstrated by well-known linked data projects such as LODD, Bio2RDF, and Chem2Bio2RDF. Integration of these sets creates large networks of information. We have previously described a tool called WENDI for aggregating information pertaining to new chemical compounds, effectively creating evidence paths relating the compounds to genes, diseases and so on. In this paper we examine the utility of automatically inferring new compound-disease associations (and thus new links in the network) based on semantically marked-up versions of these evidence paths, rule-sets and inference engines.</p> <p>Results</p> <p>Through the implementation of a semantic inference algorithm, rule set, Semantic Web methods (RDF, OWL and SPARQL) and new interfaces, we have created a new tool called Chemogenomic Explorer that uses networks of ontologically annotated RDF statements along with deductive reasoning tools to infer new associations between the query structure and genes and diseases from WENDI results. The tool then permits interactive clustering and filtering of these evidence paths.</p> <p>Conclusions</p> <p>We present a new aggregate approach to inferring links between chemical compounds and diseases using semantic inference. This approach allows multiple evidence paths between compounds and diseases to be identified using a rule-set and semantically annotated data, and for these evidence paths to be clustered to show overall evidence linking the compound to a disease. We believe this is a powerful approach, because it allows compound-disease relationships to be ranked by the amount of evidence supporting them.</p

Nemitin, a Novel Map8/Map1s Interacting Protein with Wd40 Repeats

In neurons, a highly regulated microtubule cytoskeleton is essential for many cellular functions. These include axonal transport, regional specialization and synaptic function. Given the critical roles of microtubule-associated proteins (MAPs) in maintaining and regulating microtubule stability and dynamics, we sought to understand how this regulation is achieved. Here, we identify a novel LisH/WD40 repeat protein, tentatively named nemitin (neuronal enriched MAP interacting protein), as a potential regulator of MAP8-associated microtubule function. Based on expression at both the mRNA and protein levels, nemitin is enriched in the nervous system. Its protein expression is detected as early as embryonic day 11 and continues through adulthood. Interestingly, when expressed in non-neuronal cells, nemitin displays a diffuse pattern with puncta, although at the ultrastructural level it localizes along the microtubule network in vivo in sciatic nerves. These results suggest that the association of nemitin to microtubules may require an intermediary protein. Indeed, co-expression of nemitin with microtubule-associated protein 8 (MAP8) results in nemitin losing its diffuse pattern, instead decorating microtubules uniformly along with MAP8. Together, these results imply that nemitin may play an important role in regulating the neuronal cytoskeleton through an interaction with MAP8

Development of a chemically defined medium and discovery of new mitogenic growth factors for mouse hepatocytes: Mitogenic effects of FGF1/2 and PDGF

Chemically defined serum-free media for rat hepatocytes have been useful in identifying EGFR ligands and HGF/MET signaling as direct mitogenic factors for rat hepatocytes. The absence of such media for mouse hepatocytes has prevented screening for discovery of such mitogens for mouse hepatocytes. We present results obtained by designing such a chemically defined medium for mouse hepatocytes and demonstrate that in addition to EGFR ligands and HGF, the growth factors FGF1 and FGF2 are also important mitogenic factors for mouse hepatocytes. Smaller mitogenic response was also noticed for PDGF AB. Mouse hepatocytes are more likely to enter into spontaneous proliferation in primary culture due to activation of cell cycle pathways resulting from collagenase perfusion. These results demonstrate unanticipated fundamental differences in growth biology of hepatocytes between the two rodent species. Copyright: © 2014 Reekie et al

Production of Virus-Derived Ping-Pong-Dependent piRNA-like Small RNAs in the Mosquito Soma

The natural maintenance cycles of many mosquito-borne pathogens require establishment of persistent non-lethal infections in the invertebrate host. The mechanism by which this occurs is not well understood, but we have previously shown that an antiviral response directed by small interfering RNAs (siRNAs) is important in modulating the pathogenesis of alphavirus infections in the mosquito. However, we report here that infection of mosquitoes with an alphavirus also triggers the production of another class of virus-derived small RNAs that exhibit many similarities to ping-pong-dependent piwi-interacting RNAs (piRNAs). However, unlike ping-pong-dependent piRNAs that have been described previously from repetitive elements or piRNA clusters, our work suggests production in the soma. We also present evidence that suggests virus-derived piRNA-like small RNAs are capable of modulating the pathogenesis of alphavirus infections in dicer-2 null mutant mosquito cell lines defective in viral siRNA production. Overall, our results suggest that a non-canonical piRNA pathway is present in the soma of vector mosquitoes and may be acting redundantly to the siRNA pathway to target alphavirus replication

Downregulation of FIP200 Induces Apoptosis of Glioblastoma Cells and Microvascular Endothelial Cells by Enhancing Pyk2 Activity

The expression of focal adhesion kinase family interacting protein of 200-kDa (FIP200) in normal brain is limited to some neurons and glial cells. On immunohistochemical analysis of biopsies of glioblastoma tumors, we detected FIP200 in the tumor cells, tumor-associated endothelial cells, and occasional glial cells. Human glioblastoma tumor cell lines and immortalized human astrocytes cultured in complete media also expressed FIP200 as did primary human brain microvessel endothelial cells (MvEC), which proliferate in culture and resemble reactive endothelial cells. Downregulation of endogenous expression of FIP200 using small interfering RNA resulted in induction of apoptosis in the human glioblastoma tumor cells, immortalized human astrocytes, and primary human brain MvEC. It has been shown by other investigators using cells from other tissues that FIP200 can interact directly with, and inhibit, proline-rich tyrosine kinase 2 (Pyk2) and focal adhesion kinase (FAK). In the human glioblastoma tumor cells, immortalized human astrocytes, and primary human brain MvEC, we found that downregulation of FIP200 increased the activity of Pyk2 without increasing its expression, but did not affect the activity or expression of FAK. Coimmunoprecipitation and colocalization studies indicated that the endogenous FIP200 was largely associated with Pyk2, rather than FAK, in the glioblastoma tumor cells and brain MvEC. Moreover, the pro-apoptotic effect of FIP200 downregulation was inhibited significantly by a TAT-Pyk2-fusion protein containing the Pyk2 autophosphorylation site in these cells. In summary, downregulation of endogenous FIP200 protein in glioblastoma tumor cells, astrocytes, and brain MvECs promotes apoptosis, most likely due to the removal of a direct interaction of FIP200 with Pyk2 that inhibits Pyk2 activation, suggesting that FIP200 expression may be required for the survival of all three cell types found in glioblastoma tumors

Robotic Table Tennis: A Case Study into a High Speed Learning System

We present a deep-dive into a real-world robotic learning system that, in previous work, was shown to be capable of hundreds of table tennis rallies with a human and has the ability to precisely return the ball to desired targets. This system puts together a highly optimized perception subsystem, a high-speed low-latency robot controller, a simulation paradigm that can prevent damage in the real world and also train policies for zero-shot transfer, and automated real world environment resets that enable autonomous training and evaluation on physical robots. We complement a complete system description, including numerous design decisions that are typically not widely disseminated, with a collection of studies that clarify the importance of mitigating various sources of latency, accounting for training and deployment distribution shifts, robustness of the perception system, sensitivity to policy hyper-parameters, and choice of action space. A video demonstrating the components of the system and details of experimental results can be found at https://youtu.be/uFcnWjB42I0.Comment: Published and presented at Robotics: Science and Systems (RSS2023

Neuronal circuitry for pain processing in the dorsal horn

Neurons in the spinal dorsal horn process sensory information, which is then transmitted to several brain regions, including those responsible for pain perception. The dorsal horn provides numerous potential targets for the development of novel analgesics and is thought to undergo changes that contribute to the exaggerated pain felt after nerve injury and inflammation. Despite its obvious importance, we still know little about the neuronal circuits that process sensory information, mainly because of the heterogeneity of the various neuronal components that make up these circuits. Recent studies have begun to shed light on the neuronal organization and circuitry of this complex region