Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

Search for Charged Higgs Bosons in e+e- Collisions at \sqrt{s} = 189 GeV

A search for pair-produced charged Higgs bosons is performed with the L3 detector at LEP using data collected at a centre-of-mass energy of 188.6 GeV, corresponding to an integrated luminosity of 176.4 pb^-1. Higgs decays into a charm and a strange quark or into a tau lepton and its associated neutrino are considered. The observed events are consistent with the expectations from Standard Model background processes. A lower limit of 65.5 GeV on the charged Higgs mass is derived at 95 % confidence level, independent of the decay branching ratio Br(H^{+/-} -> tau nu)

Prevalence of Cataract Surgery and Visual Outcomes in Indian Immigrants in Singapore: The Singapore Indian Eye Study

10.1371/journal.pone.0075584PLoS ONE810-POLN

Interaction of Pattern Recognition Receptors with Mycobacterium Tuberculosis.

Tuberculosis (TB) is considered a major worldwide health problem with 10 million new cases diagnosed each year. Our understanding of TB immunology has become greater and more refined since the identification of Mycobacterium tuberculosis (MTB) as an etiologic agent and the recognition of new signaling pathways modulating infection. Understanding the mechanisms through which the cells of the immune system recognize MTB can be an important step in designing novel therapeutic approaches, as well as improving the limited success of current vaccination strategies. A great challenge in chronic disease is to understand the complexities, mechanisms, and consequences of host interactions with pathogens. Innate immune responses along with the involvement of distinct inflammatory mediators and cells play an important role in the host defense against the MTB. Several classes of pattern recognition receptors (PRRs) are involved in the recognition of MTB including Toll-Like Receptors (TLRs), C-type lectin receptors (CLRs) and Nod-like receptors (NLRs) linked to inflammasome activation. Among the TLR family, TLR1, TLR2, TLR4, and TLR9 and their down-stream signaling proteins play critical roles in the initiation of the immune response in the pathogenesis of TB. The inflammasome pathway is associated with the coordinated release of cytokines such as IL-1β and IL-18 which also play a role in the pathogenesis of TB. Understanding the cross-talk between these signaling pathways will impact on the design of novel therapeutic strategies and in the development of vaccines and immunotherapy regimes. Abnormalities in PRR signaling pathways regulated by TB will affect disease pathogenesis and need to be elucidated. In this review we provide an update on PRR signaling during M. tuberculosis infection and indicate how greater knowledge of these pathways may lead to new therapeutic opportunities

Measurement of Triple-Gauge-Boson Couplings of the W Boson at LEP

We report on measurements of the triple-gauge-boson couplings of the W boson in $\mathrm{e^+e^-}$ collisions with the L3 detector at LEP. W-pair, single-W and single-photon events are analysed in a data sample corresponding to a total luminosity of 76.7~pb$^{-1}$ collected at centre-of-mass energies between 161~GeV and 183~GeV. CP-conserving as well as both C- and P-conserving triple-gauge-boson couplings are determined. The results, in good agreement with the Standard-Model expectations, confirm the existence of the self coupling among the electroweak gauge bosons and constrain its structure

Hsa-miRNA-765 as a key mediator for inhibiting growth, migration and invasion in fulvestrant-treated prostate cancer

Fulvestrant (ICI-182,780) has recently been shown to effectively suppress prostate cancer cell growth in vitro and in vivo. But it is unclear whether microRNAs play a role in regulating oncogene expression in fulvestrant-treated prostate cancer. Here, this study reports hsa-miR-765 as the first fulvestrant-driven, ERβ-regulated miRNA exhibiting significant tumor suppressor activities like fulvestrant, against prostate cancer cell growth via blockage of cell-cycle progression at the G2/M transition, and cell migration and invasion possibly via reduction of filopodia/intense stress-fiber formation. Fulvestrant was shown to upregulate hsa-miR-765 expression through recruitment of ERβ to the 5′-regulatory-region of hsa-miR-765. HMGA1, an oncogenic protein in prostate cancer, was identified as a downstream target of hsa-miR-765 and fulvestrant in cell-based experiments and a clinical study. Both the antiestrogen and the hsa-miR-765 mimic suppressed HMGA1 protein expression. In a neo-adjuvant study, levels of hsa-miR-765 were increased and HMGA1 expression was almost completely lost in prostate cancer specimens from patients treated with a single dose (250 mg) of fulvestrant 28 days before prostatectomy. These findings reveal a novel fulvestrant signaling cascade involving ERβ-mediated transcriptional upregulation of hsa-miR-765 that suppresses HMGA1 protein expression as part of the mechanism underlying the tumor suppressor action of fulvestrant in prostate cancer. © 2014 Leung et al

The disruption of proteostasis in neurodegenerative diseases

Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio

Essential Domains of Anaplasma phagocytophilum Invasins Utilized to Infect Mammalian Host Cells

Anaplasma phagocytophilum causes granulocytic anaplasmosis, an emerging disease of humans and domestic animals. The obligate intracellular bacterium uses its invasins OmpA, Asp14, and AipA to infect myeloid and non-phagocytic cells. Identifying the domains of these proteins that mediate binding and entry, and determining the molecular basis of their interactions with host cell receptors would significantly advance understanding of A. phagocytophilum infection. Here, we identified the OmpA binding domain as residues 59 to 74. Polyclonal antibody generated against a peptide spanning OmpA residues 59 to 74 inhibited A. phagocytophilum infection of host cells and binding to its receptor, sialyl Lewis x (sLex-capped P-selectin glycoprotein ligand 1. Molecular docking analyses predicted that OmpA residues G61 and K64 interact with the two sLex sugars that are important for infection, α2,3-sialic acid and α1,3-fucose. Amino acid substitution analyses demonstrated that K64 was necessary, and G61 was contributory, for recombinant OmpA to bind to host cells and competitively inhibit A. phagocytophilum infection. Adherence of OmpA to RF/6A endothelial cells, which express little to no sLex but express the structurally similar glycan, 6-sulfo-sLex, required α2,3-sialic acid and α1,3-fucose and was antagonized by 6-sulfo-sLex antibody. Binding and uptake of OmpA-coated latex beads by myeloid cells was sensitive to sialidase, fucosidase, and sLex antibody. The Asp14 binding domain was also defined, as antibody specific for residues 113 to 124 inhibited infection. Because OmpA, Asp14, and AipA each contribute to the infection process, it was rationalized that the most effective blocking approach would target all three. An antibody cocktail targeting the OmpA, Asp14, and AipA binding domains neutralized A. phagocytophilumbinding and infection of host cells. This study dissects OmpA-receptor interactions and demonstrates the effectiveness of binding domain-specific antibodies for blocking A. phagocytophilum infection

Transforming ophthalmic education into virtual learning during COVID-19 pandemic : a global perspective

Objective: The coronavirus disease 2019 (COVID-19) pandemic has imposed measures of social distancing and barriers in delivery of "in person" education. Institutions, involved in training the next generation of ophthalmologists, are using alternative teaching methods to maintain the standard of education. Methods: We conducted a worldwide survey among physicians, who are actively involved in Ophthalmology-related education, between 3 and 14 April 2020. The expert survey, developed on the basis of literature search and focus group discussions, comprised 23 questions addressing the use of e-learning in Ophthalmology during the COVID-19 pandemic. Results: A total of 321 participants from both academic and non-academic institutions worldwide, with variable practice experience and expertise, completed the survey. Before the pandemic, the majority of participants used traditional training modalities, including lectures, grand rounds and journal clubs, and 48% did not use any e-learning. There was a statistically significant increase in the use of all e-learning alternatives during the pandemic (p < 0.001), associated mainly with the availability of e-learning facilities (p < 0.001) and the academic character of institutions (p < 0.001). Zoom\uae was recognized as the mostly used platform for virtual teaching. Although theoretical teaching may take place, the surgical training of residents/fellows was dramatically reduced. The latter was significantly associated with participants' perspectives about teaching practices (p < 0.001). Conclusion: COVID-19 pandemic imposed great challenges in the educational field of Ophthalmology. The experience related to virtual training in Ophthalmology, gained during the pandemic, may change the traditional teaching practices in the world and provide new educational opportunities

Improving the Alignment Quality of Consistency Based Aligners with an Evaluation Function Using Synonymous Protein Words

Most sequence alignment tools can successfully align protein sequences with higher levels of sequence identity. The accuracy of corresponding structure alignment, however, decreases rapidly when considering distantly related sequences (<20% identity). In this range of identity, alignments optimized so as to maximize sequence similarity are often inaccurate from a structural point of view. Over the last two decades, most multiple protein aligners have been optimized for their capacity to reproduce structure-based alignments while using sequence information. Methods currently available differ essentially in the similarity measurement between aligned residues using substitution matrices, Fourier transform, sophisticated profile-profile functions, or consistency-based approaches, more recently