Real-time association mining in large social networks.

There is a growing realisation that to combat the waning effectiveness of traditional marketing, social media platform owners need to find new ways to monetise their data. Social media data contains rich information describing how real world entities relate to each other. Understanding the allegiances, communities and structure of key entities is of vital importance for decision support in a swathe of industries that have hitherto relied on expensive, small scale survey data. In this paper, we present a real-time method to query and visualise regions of networks that are closely related to a set of input vertices. The input vertices can define an industry, political party, sport etc. The key idea is that in large digital social networks measuring similarity via direct connections between nodes is not robust, but that robust similarities between nodes can be attained through the similarity of their neighbourhood graphs. We are able to achieve real-time performance by compressing the neighbourhood graphs using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines to milliseconds on standard laptops. Our method allows analysts to interactively explore strongly associated regions of large networks in real time. Our work has been deployed in software that is actively used by analysts to understand social network structure

Performance deficits of NK1 receptor knockout mice in the 5 choice serial reaction time task: effects of d Amphetamine, stress and time of day.

Background The neurochemical status and hyperactivity of mice lacking functional substance P-preferring NK1 receptors (NK1R-/-) resemble abnormalities in Attention Deficit Hyperactivity Disorder (ADHD). Here we tested whether NK1R-/- mice express other core features of ADHD (impulsivity and inattentiveness) and, if so, whether they are diminished by d-amphetamine, as in ADHD. Prompted by evidence that circadian rhythms are disrupted in ADHD, we also compared the performance of mice that were trained and tested in the morning or afternoon. Methods and Results The 5-Choice Serial Reaction-Time Task (5-CSRTT) was used to evaluate the cognitive performance of NK1R-/- mice and their wildtypes. After training, animals were tested using a long (LITI) and a variable (VITI) inter-trial interval: these tests were carried out with, and without, d-amphetamine pretreatment (0.3 or 1 mg/kg i.p.). NK1R-/- mice expressed greater omissions (inattentiveness), perseveration and premature responses (impulsivity) in the 5-CSRTT. In NK1R-/- mice, perseveration in the LITI was increased by injection-stress but reduced by d-amphetamine. Omissions by NK1R-/- mice in the VITI were unaffected by d-amphetamine, but premature responses were exacerbated by this psychostimulant. Omissions in the VITI were higher, overall, in the morning than the afternoon but, in the LITI, premature responses of NK1R-/- mice were higher in the afternoon than the morning. Conclusion In addition to locomotor hyperactivity, NK1R-/- mice express inattentiveness, perseveration and impulsivity in the 5-CSRTT, thereby matching core criteria for a model of ADHD. Because d-amphetamine reduced perseveration in NK1R-/- mice, this action does not require functional NK1R. However, the lack of any improvement of omissions and premature responses in NK1R-/- mice given d-amphetamine suggests that beneficial effects of this psychostimulant in other rodent models, and ADHD patients, need functional NK1R. Finally, our results reveal experimental variables (stimulus parameters, stress and time of day) that could influence translational studies

Synovial Tissue Sampling in Rheumatological Practice—Past Developments and Future Perspectives

Synovial biopsies are performed in routine clinical care in order to refine diagnosis as well as within a research setting. Progress in the development of minimally invasive synovial sampling methods in the last century has accelerated and facilitated novel insights into disease pathogenesis. This review discusses the development of synovial biopsy techniques as well as examining the three currently most commonly used approaches: arthroscopic, blind needle biopsy and ultrasound guided approaches. It also highlights major research advances driven through synovial research and considers future developments

Lactate Regulates Metabolic and Proinflammatory Circuits in Control of T Cell Migration and Effector Functions

Licensed by the Creative Commons Attribution Licens

Real-time community detection in full social networks on a laptop

For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As global social networks (e.g., Facebook and Twitter) are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities) of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to continue to provide free services that are valued by billions of people globally

Automated operant assessments of Huntington's Disease mouse models

Huntington’s disease (HD) presents clinically with a triad of motor, cognitive, and psychiatric symptoms. Cognitive symptoms often occur early within the disease progression, prior to the onset of motor symptoms, and they are significantly burdensome to people who are affected by HD. In order to determine the suitability of mouse models of HD in recapitulating the human condition, these models must be behaviorally tested and characterized. Operant behavioral testing offers an automated and objective method of behaviorally profiling motor, cognitive, and psychiatric dysfunction in HD mice. Furthermore, operant testing can also be employed to determine any behavioral changes observed after any associated interventions or experimental therapeutics. We here present an overview of the most commonly used operant behavioral tests to dissociate motor, cognitive, and psychiatric aspects of mouse models of HD

The De-Ubiquitinylating Enzyme, USP2, Is Associated with the Circadian Clockwork and Regulates Its Sensitivity to Light

We have identified a novel component of the circadian clock that regulates its sensitivity to light at the evening light to dark transition. USP2 (Ubiquitin Specific Protease 2), which de-ubiquitinylates and stabilizes target proteins, is rhythmically expressed in multiple tissues including the SCN. We have developed a knockout model of USP2 and found that exposure to low irradiance light at ZT12 increases phase delays of USP2−/− mice compared to wildtype. We additionally show that USP2b is in a complex with several clock components and regulates the stability and turnover of BMAL1, which in turn alters the expression of several CLOCK/BMAL1 controlled genes. Rhythmic expression of USP2 in the SCN and other tissues offers a new level of control of the clock machinery through de-ubiqutinylation and suggests a role for USP2 during circadian adaptation to environmental day length changes

Epstein-Barr virus persistence and infection of autoreactive plasma cells in synovial lymphoid structures in rheumatoid arthritis.

OBJECTIVES: Rheumatoid arthritis (RA) is associated with an increased Epstein-Barr virus (EBV) blood DNA load, a robust immune response to EBV and cross-reactive circulating antibodies to viral and self-antigens. However, the role of EBV in RA pathogenesis remains elusive. Here, we investigated the relationship between synovial EBV infection, ectopic lymphoid structures (ELS) and immunity to citrullinated self and EBV proteins. METHODS: Latent and lytic EBV infection was investigated in 43 RA synovial tissues characterised for presence/absence of ELS and in 11 control osteoarthritis synovia using RT-PCR, in situ hybridisation and immunohistochemistry. Synovial production of anti-citrullinated protein (ACPA) and anti-citrullinated EBV peptide (VCP1/VCP2) antibodies was investigated in situ and in vivo in the severe combined immunodeficiency (SCID)/RA chimeric model. RESULTS: EBV dysregulation was observed exclusively in ELS+ RA but not osteoarthritis (OA) synovia, as revealed by presence of EBV latent (LMP2A, EBV-encoded small RNA (EBER)) transcripts, EBER+ cells and immunoreactivity for EBV latent (LMP1, LMP2A) and lytic (BFRF1) antigens in ELS-associated B cells and plasma cells, respectively. Importantly, a large proportion of ACPA-producing plasma cells surrounding synovial germinal centres were infected with EBV. Furthermore, ELS-containing RA synovia transplanted into SCID mice supported production of ACPA and anti-VCP1/VCP2 antibodies. Analysis of CD4+ and CD8+ T-cell localisation and granzyme B expression suggests that EBV persistence in ELS-containing synovia may be favoured by exclusion of CD8+ T cells from B-cell follicles and impaired CD8-mediated cytotoxicity. CONCLUSIONS: We demonstrated active EBV infection within ELS in the RA synovium in association with local differentiation of ACPA-reactive B cells

Continuous flow analysis methods for sodium, magnesium and calcium detection in the Skytrain ice core

AbstractDissolved and particulate sodium, magnesium and calcium are analyzed in ice cores to determine past changes in sea ice extent, terrestrial dust variability and atmospheric aerosol transport efficiency. They are also used to date ice cores if annual layers are visible. Multiple methods have been developed to analyze these important compounds in ice cores. Continuous flow analysis (CFA) is implemented with instruments that sample the meltstream continuously. In this study, CFA with ICP-MS (inductively coupled-plasma mass spectrometry) and fast ion chromatography (FIC) methods are compared for analysis of sodium and magnesium. ICP-MS, FIC and fluorescence methods are compared for analysis of calcium. Respective analysis of a 10 m section of the Antarctic WACSWAIN Skytrain Ice Rise ice core shows that all of the methods result in similar levels of the compounds. The ICP-MS method is the most suitable for analysis of the Skytrain ice core due to its superior precision (relative standard deviation: 1.6% for Na, 1.3% for Mg and 1.2% for Ca) and sampling frequency compared to the FIC method. The fluorescence detection method may be preferred for calcium analysis due to its higher depth resolution (1.4 cm) relative to the ICP-MS and FIC methods (~4 cm).European Research Counci

Can Synovial Pathobiology Integrate with Current Clinical and Imaging Prediction Models to Achieve Personalized Health Care in Rheumatoid Arthritis?

Although great progress has been made in the past decade toward understanding the pathogenesis of rheumatoid arthritis (RA), clinicians remain some distance from a goal of personalized health care. The capacity to diagnose RA early, predict prognosis, and moreover predict response to biologic therapies has been a research focus for many years. How currently available clinical prediction models can facilitate such goals is reviewed in this article. In addition, the role of current imaging techniques in this regard is also discussed. Finally, the authors review the current literature regarding synovial biomarkers and consider whether integration of synovial pathobiology into clinical prediction algorithms may enhance their predictive value