Eosinophilic Otitis Media: CT and MRI Findings and Literature Review

Eosinophilic otitis media (EOM) is a relatively rare, intractable, middle ear disease with extremely viscous mucoid effusion containing eosinophils. EOM is associated with adult bronchial asthma and nasal allergies. Conventional treatments for otitis media with effusion (OME) or for chronic otitis media (COM), like tympanoplasty or mastoidectomy, when performed for the treatment of EOM, can induce severe complications such as deafness. Therefore, it should be differentiated from the usual type of OME or COM. To our knowledge, the clinical and imaging findings of EOM of temporal bone are not well-known to radiologists. We report here the CT and MRI findings of two EOM cases and review the clinical and histopathologic findings of this recently described disease entity

Emotional persistence in online chatting communities

How do users behave in online chatrooms, where they instantaneously read and write posts? We analyzed about 2.5 million posts covering various topics in Internet relay channels, and found that user activity patterns follow known power-law and stretched exponential distributions, indicating that online chat activity is not different from other forms of communication. Analysing the emotional expressions (positive, negative, neutral) of users, we revealed a remarkable persistence both for individual users and channels. I.e. despite their anonymity, users tend to follow social norms in repeated interactions in online chats, which results in a specific emotional "tone" of the channels. We provide an agent-based model of emotional interaction, which recovers qualitatively both the activity patterns in chatrooms and the emotional persistence of users and channels. While our assumptions about agent's emotional expressions are rooted in psychology, the model allows to test different hypothesis regarding their emotional impact in online communication.Comment: 34 pages, 4 main and 12 supplementary figure

Hyaluronan Binding Motifs of USP17 and SDS3 Exhibit Anti-Tumor Activity

BACKGROUND: We previously reported that the USP17 deubiquitinating enzyme having hyaluronan binding motifs (HABMs) interacts with human SDS3 (suppressor of defective silencing 3) and specifically deubiquitinates Lys-63 branched polyubiquitination of SDS3 resulting in negative regulation of histone deacetylase (HDAC) activity in cancer cells. Furthermore, USP17 and SDS3 mutually interact with each other to block cell proliferation in HeLa cells but the mechanism for this inhibition in cell proliferation is not known. We wished to investigate whether the HABMs of USP17 were responsible for tumor suppression activity. METHODOLOGY/PRINCIPAL FINDINGS: Similarly to USP17, we have identified that SDS3 also has three consecutive HABMs and shows direct binding with hyaluronan (HA) using cetylpyridinium chloride (CPC) assay. Additionally, HA oligosaccharides (6-18 sugar units) competitively block binding of endogenous HA polymer to HA binding proteins. Thus, administration of HA oligosaccharides antagonizes the interaction between HA and USP17 or SDS3. Interestingly, HABMs deleted USP17 showed lesser interaction with SDS3 but retain its deubiquitinating activity towards SDS3. The deletion of HABMs of USP17 could not alter its functional regulation on SDS3-associated HDAC activity. Furthermore, to explore whether HABMs in USP17 and SDS3 are responsible for the inhibition of cell proliferation, we investigated the effect of USP17 and SDS3-lacking HABMs on cell proliferation by soft agar, apoptosis, cell migration and cell proliferation assays. CONCLUSIONS: Our results have demonstrated that these HABMs in USP17 and its substrate SDS3 are mainly involved in the inhibition of anchorage-independent tumor growth

Languages cool as they expand: Allometric scaling and the decreasing need for new words

We analyze the occurrence frequencies of over 15 million words recorded in millions of books published during the past two centuries in seven different languages. For all languages and chronological subsets of the data we confirm that two scaling regimes characterize the word frequency distributions, with only the more common words obeying the classic Zipf law. Using corpora of unprecedented size, we test the allometric scaling relation between the corpus size and the vocabulary size of growing languages to demonstrate a decreasing marginal need for new words, a feature that is likely related to the underlying correlations between words. We calculate the annual growth fluctuations of word use which has a decreasing trend as the corpus size increases, indicating a slowdown in linguistic evolution following language expansion. This ‘‘cooling pattern’’ forms the basis of a third statistical regularity, which unlike the Zipf and the Heaps law, is dynamical in nature

Clinical significance of carcinoembryonic antigen in peritoneal fluid detected during operation in stage I–III colorectal cancer patients

Background/AimsEarly diagnosis of peritoneal metastases in patients with colorectal cancer (CRC) can influence patient prognosis. The aim of this study was to identify the clinical significance of carcinoembryonic antigen (CEA) in peritoneal fluid detected during operation in stage I–III CRC patients.MethodsBetween April 2009 and April 2015, we reviewed medical records from a total of 60 stage I–III CRC patients who had peritoneal fluid collected during operation. Patients who had positive cytology in the assessment of peritoneal fluid were excluded. We evaluated the values of CEA in peritoneal fluid (pCEA) to predict the long-term outcomes of these patients using Kaplan-Meier curves and Cox regression models.ResultsThe median follow-up duration was 37 months (interquartile range, 21–50 months). On receiver operating characteristic analysis, pCEA had the largest area under the curve (0.793; 95% confidence interval, 0.635–0.950; P=0.001) with an optimal cutoff value of 26.84 (sensitivity, 80.0%; specificity, 76.6%) for predicting recurrence. The recurrence rate was 8.1% in patients with low pCEA (<26.84 ng/mL, n=37), and 52.2% in patients with high pCEA (≥26.84 ng/mL, n=23). In multivariate Cox regression analysis, high pCEA (≥26.84 ng/mL) was a risk factor for poor cancer-free survival (CFS) in stage I–III patients.ConclusionsIn this study, we determined that high pCEA (≥26.84 ng/mL) detected during operation was helpful for the prediction of poor CFS in patients with stage I–III CRC

Discovering study-specific gene regulatory networks

This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets

Flavor Physics in an SO(10) Grand Unified Model

In supersymmetric grand-unified models, the lepton mixing matrix can possibly affect flavor-changing transitions in the quark sector. We present a detailed analysis of a model proposed by Chang, Masiero and Murayama, in which the near-maximal atmospheric neutrino mixing angle governs large new b -> s transitions. Relating the supersymmetric low-energy parameters to seven new parameters of this SO(10) GUT model, we perform a correlated study of several flavor-changing neutral current (FCNC) processes. We find the current bound on B(tau -> mu gamma) more constraining than B(B -> X_s gamma). The LEP limit on the lightest Higgs boson mass implies an important lower bound on tan beta, which in turn limits the size of the new FCNC transitions. Remarkably, the combined analysis does not rule out large effects in B_s-B_s-bar mixing and we can easily accomodate the large CP phase in the B_s-B_s-bar system which has recently been inferred from a global analysis of CDF and DO data. The model predicts a particle spectrum which is different from the popular Constrained Minimal Supersymmetric Standard Model (CMSSM). B(tau -> mu gamma) enforces heavy masses, typically above 1 TeV, for the sfermions of the degenerate first two generations. However, the ratio of the third-generation and first-generation sfermion masses is smaller than in the CMSSM and a (dominantly right-handed) stop with mass below 500 GeV is possible.Comment: 44 pages, 5 figures. Footnote and references added, minor changes, Fig. 2 corrected; journal versio