Sensory Processing Disorders are Associated with Duration of Current Episode and Severity of Side Effects

Objective: Longer duration of untreated illness, longer duration of current episode, and the severity of medication side effects may negatively impact on the perceived disability and psychosocial impairment of patients with major affective and anxiety disorders. Studies also suggested the involvement of sensory perception in emotional and psychopathological processes. The present study aimed to examine the relationship between Sensory Processing Disorders (SPD), duration of untreated illness and current illness episode, and the severity of side effects related to psychoactive medications. Methods: The sample included 178 participants with an age ranging from 17 to 85 years (mean=53.84±15.55). Participants were diagnosed with unipolar Major Depressive Disorder (MDD) (50%), Bipolar Disorder (BD) (33.7%), and Anxiety disorders (16.3%). They completed a socio-demographic questionnaire, the Udvalg for Kliniske Undersøgelser (UKU), and Adolescent/Adult Sensory Profile (AASP) questionnaire. Results: Longer duration of current episode correlated with greater registration of sensory input and lower avoidance from sensory input among unipolar patients; with lower registration of sensory input, and higher tendency for sensory sensitivity/avoidance among bipolar participants; with lower sensory sensitivity/avoidance among anxiety participants, respectively. Also, mean UKU total scores correlated with lower sensory sensitivity among bipolar individuals. Conclusion: SPD expressed in either hypo/hyper sensitivity may serve to clinically characterize subjects with major affective and anxiety disorders

Bridging topological and functional information in protein interaction networks by short loops profiling

Protein-protein interaction networks (PPINs) have been employed to identify potential novel interconnections between proteins as well as crucial cellular functions. In this study we identify fundamental principles of PPIN topologies by analysing network motifs of short loops, which are small cyclic interactions of between 3 and 6 proteins. We compared 30 PPINs with corresponding randomised null models and examined the occurrence of common biological functions in loops extracted from a cross-validated high-confidence dataset of 622 human protein complexes. We demonstrate that loops are an intrinsic feature of PPINs and that specific cell functions are predominantly performed by loops of different lengths. Topologically, we find that loops are strongly related to the accuracy of PPINs and define a core of interactions with high resilience. The identification of this core and the analysis of loop composition are promising tools to assess PPIN quality and to uncover possible biases from experimental detection methods. More than 96% of loops share at least one biological function, with enrichment of cellular functions related to mRNA metabolic processing and the cell cycle. Our analyses suggest that these motifs can be used in the design of targeted experiments for functional phenotype detection.This research was supported by the Biotechnology and Biological Sciences Research Council (BB/H018409/1 to AP, ACCC and FF, and BB/J016284/1 to NSBT) and by the Leukaemia & Lymphoma Research (to NSBT and FF). SSC is funded by a Leukaemia & Lymphoma Research Gordon Piller PhD Studentship

Allergic Rhinitis and its Associated Co-Morbidities at Bugando Medical Centre in Northwestern Tanzania; A Prospective Review of 190 Cases.

Allergic rhinitis is one of the commonest atopic diseases which contribute to significant morbidity world wide while its epidemiology in Tanzania remains sparse. There was paucity of information regarding allergic rhinitis in our setting; therefore it was important to conduct this study to describe our experience on allergic rhinitis, associated co-morbidities and treatment outcome in patients attending Bugando Medical Centre. This was descriptive cross-sectional study involving all patients with a clinical diagnosis of allergic rhinitis at Bugando Medical Centre over a three-month period between June 2011 and August 2011. Data was collected using a pre-tested coded questionnaire and analyzed using SPSS statistical computer software version 17.0. A total of 190 patients were studied giving the prevalence of allergic rhinitis 14.7%. The median age of the patients was 8.5 years. The male to female ratio was 1:1. Adenoid hypertrophy, tonsillitis, hypertrophy of inferior turbinate, nasal polyps, otitis media and sinusitis were the most common co-morbidities affecting 92.6% of cases and were the major reason for attending hospital services. Sleep disturbance was common in children with adenoids hypertrophy (χ2 = 28.691, P = 0.000). Allergic conjunctivitis was found in 51.9%. The most common identified triggers were dust, strong perfume odors and cold weather (P < 0.05). Strong perfume odors affect female than males (χ2 = 4.583, P = 0.032). In this study family history of allergic rhinitis was not a significant risk factor (P =0.423). The majority of patients (68.8%) were treated surgically for allergic rhinitis co morbidities. Post operative complication and mortality rates were 2.9% and 1.6% respectively. The overall median duration of hospital stay of in-patients was 3 days (2 - 28 days). Most patients (98.4%) had satisfactory results at discharge. The study shows that allergic rhinitis is common in our settings representing 14.7% of all otorhinolaryngology and commonly affecting children and adolescent. Sufferers seek medical services due to co-morbidities of which combination of surgical and medical treatment was needed. High index of suspicions in diagnosing allergic rhinitis and early treatment is recommended

Fulminant hepatic failure in murine hepatitis virus strain 3 infection: tissue-specific expression of a novel fgl2 prothrombinase.

Activation of the immune coagulation system has been implicated in the pathogenesis of fulminant liver failure caused by murine hepatitis virus strain 3 (MHV-3). The recent discovery of the fgl2 gene, which encodes for MHV-3-induced prothrombinase (fgl2 prothrombinase), allows for fundamental studies to determine the molecular basis for fulminant liver failure. Transcription of the fgl2 gene and translation of the protein it encodes were examined in the liver and other organs of susceptible mice following MHV-3 infection. No constitutive expression of the fgl2 gene or the fgl2 prothrombinase was detected. Within 12 to 24 h of MHV-3 infection, however, fgl2 gene transcripts were detected in large amounts in the liver, spleen, and lungs, all of which are rich in reticuloendothelial cells, but were only focally present in small amounts in the kidney and brain. There was sequential detection of fgl2 prothrombinase in the liver, where it was localized specifically to the endothelium of intrahepatic veins and hepatic sinusoids; this was allowed by fibrin deposition, which resulted in confluent hepatocellular necrosis. These results provide further evidence for the role of the selective expression of this novel fgl2 prothrombinase in the pathogenesis of MHV-3-induced fulminant liver failure

The Index-Based Subgraph Matching Algorithm (ISMA): Fast Subgraph Enumeration in Large Networks Using Optimized Search Trees

Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma

Prior knowledge based mining functional modules from Yeast PPI networks with gene ontology

<p>Abstract</p> <p>Background</p> <p>In the literature, there are fruitful algorithmic approaches for identification functional modules in protein-protein interactions (PPI) networks. Because of accumulation of large-scale interaction data on multiple organisms and non-recording interaction data in the existing PPI database, it is still emergent to design novel computational techniques that can be able to correctly and scalably analyze interaction data sets. Indeed there are a number of large scale biological data sets providing indirect evidence for protein-protein interaction relationships.</p> <p>Results</p> <p>The main aim of this paper is to present a prior knowledge based mining strategy to identify functional modules from PPI networks with the aid of Gene Ontology. Higher similarity value in Gene Ontology means that two gene products are more functionally related to each other, so it is better to group such gene products into one functional module. We study (i) to encode the functional pairs into the existing PPI networks; and (ii) to use these functional pairs as pairwise constraints to supervise the existing functional module identification algorithms. Topology-based modularity metric and complex annotation in MIPs will be used to evaluate the identified functional modules by these two approaches.</p> <p>Conclusions</p> <p>The experimental results on Yeast PPI networks and GO have shown that the prior knowledge based learning methods perform better than the existing algorithms.</p

Sequential Logic Model Deciphers Dynamic Transcriptional Control of Gene Expressions

Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here.Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM) is developed to decipher control mechanisms of dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. is a promising step for further application of the proposed method

Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks

<p>Abstract</p> <p>Background</p> <p>Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions.</p> <p>Results</p> <p>Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways). Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods.</p> <p>Conclusions</p> <p>Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.</p