Impaired heterologous immunity in aged ferrets during sequential influenza A H1N1 infection

The major burden of influenza morbidity resides within the elderly population. The challenge managing influenza-associated illness in the elderly is the decline of immune function, where mechanisms leading to immunological senescence have not been elucidated. To better represent the immune environment, we investigated clinical morbidity and immune function during sequential homologous and heterologous H1N1 influenza infection in an aged ferret model. Our findings demonstrated experimentally that aged ferrets had significant morbidity during monosubtypic heterologous 2° challenge with significant weight loss and respiratory symptoms. Furthermore, increased clinical morbidity was associated with slower and shorter hemagglutinin antibody generation and attenuated type 1 T-cell gene responses in peripheral blood. These results revealed dampened immune activation during sequential influenza infection in aged ferrets. With the presence of an aged model, dissecting clinical morbidity, viral dynamics and immune response during influenza infection will aid the development of future prophylactics such as age specific influenza vaccines

Generating Images Instead of Retrieving Them : Relevance Feedback on Generative Adversarial Networks

Finding images matching a user’s intention has been largely basedon matching a representation of the user’s information needs withan existing collection of images. For example, using an exampleimage or a written query to express the information need and re-trieving images that share similarities with the query or exampleimage. However, such an approach is limited to retrieving onlyimages that already exist in the underlying collection. Here, wepresent a methodology for generating images matching the userintention instead of retrieving them. The methodology utilizes arelevance feedback loop between a user and generative adversarialneural networks (GANs). GANs can generate novel photorealisticimages which are initially not present in the underlying collection,but generated in response to user feedback. We report experiments(N=29) where participants generate images using four differentdomains and various search goals with textual and image targets.The results show that the generated images match the tasks andoutperform images selected as baselines from a fixed image col-lection. Our results demonstrate that generating new informationcan be more useful for users than retrieving it from a collection ofexisting information.Peer reviewe

Symmetry-breaking in the endofullerene H2O@C60 revealed in the quantum dynamics of ortho and para-water: a neutron scattering investigation

Inelastic neutron scattering (INS) has been employed to investigate the quantum dynamics of water molecules permanently entrapped inside the cages of C60 fullerene molecules. This study of the supramolecular complex, H2O@C60, provides the unique opportunity to study isolated water molecules in a highly symmetric environment. Free from strong interactions, the water molecule has a high degree of rotational freedom enabling its nuclear spin isomers, ortho-H2O and para-H2O to be separately identified and studied. The INS technique mediates transitions between the ortho and para spin isomers and using three INS spectrometers, the rotational levels of H2O have been investigated, correlating well with the known levels in gaseous water. The slow process of nuclear spin conversion between ortho-H2O and para-H2O is revealed in the time dependence of the INS peak intensities over periods of many hours. Of particular interest to this study is the observed splitting of the ground state of ortho-H2O, raising the three-fold degeneracy into two states with degeneracy 2 and 1 respectively. This is attributed to a symmetry-breaking interaction of the water environment

Small-scale proxies for large-scale Transformer training instabilities

Teams that have trained large Transformer-based models have reported training instabilities at large scale that did not appear when training with the same hyperparameters at smaller scales. Although the causes of such instabilities are of scientific interest, the amount of resources required to reproduce them has made investigation difficult. In this work, we seek ways to reproduce and study training stability and instability at smaller scales. First, we focus on two sources of training instability described in previous work: the growth of logits in attention layers (Dehghani et al., 2023) and divergence of the output logits from the log probabilities (Chowdhery et al., 2022). By measuring the relationship between learning rate and loss across scales, we show that these instabilities also appear in small models when training at high learning rates, and that mitigations previously employed at large scales are equally effective in this regime. This prompts us to investigate the extent to which other known optimizer and model interventions influence the sensitivity of the final loss to changes in the learning rate. To this end, we study methods such as warm-up, weight decay, and the $\mu$Param (Yang et al., 2022), and combine techniques to train small models that achieve similar losses across orders of magnitude of learning rate variation. Finally, to conclude our exploration we study two cases where instabilities can be predicted before they emerge by examining the scaling behavior of model activation and gradient norms

Ig Superfamily Ligand and Receptor Pairs Expressed in Synaptic Partners in Drosophila

Information processing relies on precise patterns of synapses between neurons. The cellular recognition mechanisms regulating this specificity are poorly understood. In the medulla of the Drosophila visual system, different neurons form synaptic connections in different layers. Here, we sought to identify candidate cell recognition molecules underlying this specificity. Using RNA sequencing (RNA-seq), we show that neurons with different synaptic specificities express unique combinations of mRNAs encoding hundreds of cell surface and secreted proteins. Using RNA-seq and protein tagging, we demonstrate that 21 paralogs of the Dpr family, a subclass of immunoglobulin (Ig)-domain containing proteins, are expressed in unique combinations in homologous neurons with different layer-specific synaptic connections. Dpr interacting proteins (DIPs), comprising nine paralogs of another subclass of Ig-containing proteins, are expressed in a complementary layer-specific fashion in a subset of synaptic partners. We propose that pairs of Dpr/DIP paralogs contribute to layer-specific patterns of synaptic connectivity

Joint Goal and Strategy Inference across Heterogeneous Demonstrators via Reward Network Distillation

Reinforcement learning (RL) has achieved tremendous success as a general framework for learning how to make decisions. However, this success relies on the interactive hand-tuning of a reward function by RL experts. On the other hand, inverse reinforcement learning (IRL) seeks to learn a reward function from readily-obtained human demonstrations. Yet, IRL suffers from two major limitations: 1) reward ambiguity - there are an infinite number of possible reward functions that could explain an expert's demonstration and 2) heterogeneity - human experts adopt varying strategies and preferences, which makes learning from multiple demonstrators difficult due to the common assumption that demonstrators seeks to maximize the same reward. In this work, we propose a method to jointly infer a task goal and humans' strategic preferences via network distillation. This approach enables us to distill a robust task reward (addressing reward ambiguity) and to model each strategy's objective (handling heterogeneity). We demonstrate our algorithm can better recover task reward and strategy rewards and imitate the strategies in two simulated tasks and a real-world table tennis task.Comment: In Proceedings of the 2020 ACM/IEEE In-ternational Conference on Human-Robot Interaction (HRI '20), March 23 to 26, 2020, Cambridge, United Kingdom.ACM, New York, NY, USA, 10 page

The Hubble Space Telescope Wide Field Camera 3 Early Release Science data: Panchromatic Faint Object Counts for 0.2-2 microns wavelength

We describe the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) Early Release Science (ERS) observations in the Great Observatories Origins Deep Survey (GOODS) South field. The new WFC3 ERS data provide calibrated, drizzled mosaics in the UV filters F225W, F275W, and F336W, as well as in the near-IR filters F098M (Ys), F125W (J), and F160W (H) with 1-2 HST orbits per filter. Together with the existing HST Advanced Camera for Surveys (ACS) GOODS-South mosaics in the BViz filters, these panchromatic 10-band ERS data cover 40-50 square arcmin at 0.2-1.7 {\mu}m in wavelength at 0.07-0.15" FWHM resolution and 0.090" Multidrizzled pixels to depths of AB\simeq 26.0-27.0 mag (5-{\sigma}) for point sources, and AB\simeq 25.5-26.5 mag for compact galaxies. In this paper, we describe: a) the scientific rationale, and the data taking plus reduction procedures of the panchromatic 10-band ERS mosaics; b) the procedure of generating object catalogs across the 10 different ERS filters, and the specific star-galaxy separation techniques used; and c) the reliability and completeness of the object catalogs from the WFC3 ERS mosaics. The excellent 0.07-0.15" FWHM resolution of HST/WFC3 and ACS makes star- galaxy separation straightforward over a factor of 10 in wavelength to AB\simeq 25-26 mag from the UV to the near-IR, respectively.Comment: 51 pages, 71 figures Accepted to ApJS 2011.01.2

Plasma membrane dynamics and tetrameric organisation of ABCG2 transporters in mammalian cells revealed by single particle imaging techniques

ABCG2 is one of three human ATP binding cassette (ABC) transporters involved in the export from cells of a chemically and structurally diverse range of compounds. This multidrug efflux capability, together with a broad tissue distribution in the body, means that ABCG2 exerts a range of effects on normal physiology such as kidney urate transport, as well as contributing towards the pharmacokinetic profiles of many exogenous drugs. The primary sequence of ABCG2 contains only half the number of domains required for a functioning ABC transporter and so it must oligomerise in order to function, yet its oligomeric state in intact cell membranes remains uncharacterized. We have analysed ABCG2 in living cell membranes using a combination of fluorescence correlation spectroscopy, photon counting histogram analysis, and stepwise photobleaching to demonstrate a predominantly tetrameric structure for ABCG2 in the presence or absence of transport substrates. These results provide the essential basis for exploring pharmacological manipulation of oligomeric state as a strategy to modulate ABCG2 activity in future selective therapeutics

Acute Respiratory Distress Syndrome Induced by a Swine 2009 H1N1 Variant in Mice

Background: Acute respiratory distress syndrome (ARDS) induced by pandemic 2009 H1N1 influenza virus has been widely reported and was considered the main cause of death in critically ill patients with 2009 H1N1 infection. However, no animal model has been developed for ARDS caused by infection with 2009 H1N1 virus. Here, we present a mouse model of ARDS induced by 2009 H1N1 virus. Methodology Principal Findings: Mice were inoculated with A/swine/Shandong/731/2009 (SD/09), which was a 2009 H1N1 influenza variant with a G222D mutation in the hemagglutinin. Clinical symptoms were recorded every day. Lung injury was assessed by lung water content and histopathological observation. Arterial blood gas, leukocyte count in the bronchial alveolar lavage fluid and blood, virus titers, and cytokine levels in the lung were measured at various times post-inoculation. Mice infected with SD/09 virus showed typical ARDS symptoms characterized by 60 % lethality on days 8–10 postinoculation, highly edematous lungs, inflammatory cellular infiltration, alveolar and interstitial edema, lung hemorrhage, progressive and severe hypoxemia, and elevated levels of proinflammatory cytokines and chemokines. Conclusions/Significance: These results suggested that we successfully established an ARDS mouse model induced by a virulent 2009 H1N1 variant without previous adaptation, which may be of benefit for evaluating the pathogenesis or therapy of human ARDS caused by 2009 H1N1 virus