A new method for determination of varicella-zoster virus immunoglobulin G avidity in serum and cerebrospinal fluid

BACKGROUND: Avidity determination of antigen-specific immunoglobulin G (IgG) antibodies is an established serological method to differentiate acute from past infections. In order to compare the avidity of varicella-zoster virus (VZV) IgG in pairs of serum and cerebrospinal fluid (CSF) samples, we developed a new technique of avidity testing, the results of which are not influenced by the concentration of specific IgG. METHODS: The modifications introduced for the new VZV IgG avidity method included the use of urea hydrogen peroxide as denaturing reagent, the adaptation of the assay parameters in order to increase the sensitivity for the detection of low-level VZV IgG in CSF, and the use of a new calculation method for avidity results. The calculation method is based on the observation that the relationship between the absorbance values of the enzyme immunoassays with and without denaturing washing step is linear. From this relationship, a virtual absorbance ratio can be calculated. To evaluate the new method, a panel of serum samples from patients with acute and past VZV infection was tested as well as pairs of serum and CSF. RESULTS: For the serum panel, avidity determination with the modified assay gave results comparable to standard avidity methods. Based on the coefficient of variation, the new calculation method was superior to established methods of avidity calculation. CONCLUSIONS: The new avidity method permits a meaningful comparison of VZV IgG avidity in serum and CSF and should be of general applicability for easy determination of avidity results, which are not affected by the concentration of specific IgG

Bayesian statistical modelling of human protein interaction network incorporating protein disorder information

<p>Abstract</p> <p>Background</p> <p>We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive approaches. The model is capable to capture generic and structural properties of a network as emergent from local interdependencies and uses a limited number of parameters. Here, we consider one global parameter capturing the density of edges in the network, and local parameters representing each node's contribution to the formation of edges in the network. The modelling suggests a novel definition of important nodes in the network, namely <it>social</it>, as revealed based on the local <it>sociality </it>parameters of the model. Moreover, the sociality parameters help to reveal organizational principles of the network. An inherent advantage of our approach is the possibility of hypotheses testing: <it>a priori </it>knowledge about biological properties of the nodes can be incorporated into the statistical model to investigate its influence on the structure of the network.</p> <p>Results</p> <p>We applied the statistical modelling to the human protein interaction network obtained with Y2H experiments. Bayesian approach for the estimation of the parameters was employed. We deduced <it>social </it>proteins, essential for the formation of the network, while incorporating into the model information on protein disorder. <it>Intrinsically disordered </it>are proteins which lack a well-defined three-dimensional structure under physiological conditions. We predicted the fold group (ordered or disordered) of proteins in the network from their primary sequences. The network analysis indicated that protein disorder has a positive effect on the connectivity of proteins in the network, but do not fully explains the interactivity.</p> <p>Conclusions</p> <p>The approach opens a perspective to study effects of biological properties of individual entities on the structure of biological networks.</p

YKL-40 tissue expression and plasma levels in patients with ovarian cancer

<p>Abstract</p> <p>Background</p> <p>YKL-40 (chitinase-3-like-1) is a member of "mammalian chitinase-like proteins". The protein is expressed in many types of cancer cells and the highest plasma YKL-40 levels have been found in patients with metastatic disease, short recurrence/progression-free intervals, and short overall survival. The aim of the study was to determine the expression of YKL-40 in tumor tissue and plasma in patients with borderline ovarian tumor or epithelial ovarian cancer (OC), and investigate prognostic value of this marker.</p> <p>Methods</p> <p>YKL-40 protein expression was determined by immunohistochemistry in tissue arrays from 181 borderline tumors and 473 OC. Plasma YKL-40 was determined by ELISA in preoperative samples from 19 patients with borderline tumor and 76 OC patients.</p> <p>Results</p> <p>YKL-40 protein expression was found in cancer cells, tumor associated macrophages, neutrophils and mast cells. The tumor cell expression was higher in OC than in borderline tumors (p = 0.001), and associated with FIGO stage (p < 0.0001) and histological subtype (p = 0.0009). Positive YKL-40 expression (≥ 5% staining) was not associated with reduced survival. Plasma YKL-40 was also higher in patients with OC than in patients with borderline tumors (p < 0.0001), and it was positively correlated to serum CA-125 (p < 0.0001) and FIGO stage (p = 0.0001). Univariate Cox analysis of plasma YKL-40 showed association with overall survival (p < 0.0001). Multivariate Cox analysis, including plasma YKL-40, serum CA125, FIGO stage, age and radicality after primary surgery as variables, showed that elevated plasma YKL-40 was associated with a shorter survival (HR = 2.13, 95% CI: 1.40–3.25, p = 0.0004).</p> <p>Conclusion</p> <p>YKL-40 in OC tissue and plasma are related to stage and histology, but only plasma YKL-40 is a prognostic biomarker in patients with OC.</p

Predicting range shifts of African apes under global change scenarios

Aim: Modelling African great ape distribution has until now focused on current or past conditions, while future scenarios remain scarcely explored. Using an ensemble forecasting approach, we predicted changes in taxon-specific distribution under future scenarios of climate, land use and human populations for (1) areas outside protected areas (PAs) only (assuming complete management effectiveness of PAs), (2) the entire study region and (3) interspecies range overlap. Location: Tropical Africa. Methods: We compiled occurrence data (n = 5,203) on African apes from the IUCN A.P.E.S. database and extracted relevant climate-, habitat- and human-related predictors representing current and future (2050) conditions to predict taxon-specific range change under a best- and a worst-case scenario, using ensemble forecasting. Results The predictive performance of the models varied across taxa. Synergistic interactions between predictors are shaping African ape distribution, particularly human-related variables. On average across taxa, a range decline of 50% is expected outside PAs under the best scenario if no dispersal occurs (61% in worst scenario). Otherwise, an 85% range reduction is predicted to occur across study regions (94% worst). However, range gains are predicted outside PAs if dispersal occurs (52% best, 21% worst), with a slight increase in gains expected across study regions (66% best, 24% worst). Moreover, more than half of range losses and gains are predicted to occur outside PAs where interspecific ranges overlap. Main Conclusions: Massive range decline is expected by 2050, but range gain is uncertain as African apes will not be able to occupy these new areas immediately due to their limited dispersal capacity, migration lag and ecological constraints. Given that most future range changes are predicted outside PAs, Africa's current PA network is likely to be insufficient for preserving suitable habitats and maintaining connected ape populations. Thus, conservation planners urgently need to integrate land use planning and climate change mitigation measures at all decision-making levels both in range countries and abroad

The pancreas in human type 1 diabetes

Type 1 diabetes (T1D) is considered a disorder whose pathogenesis is autoimmune in origin, a notion drawn in large part from studies of human pancreata performed as far back as the 1960s. While studies of the genetics, epidemiology, and peripheral immunity in T1D have been subject to widespread analysis over the ensuing decades, efforts to understand the disorder through analysis of human pancreata have been far more limited. We have reviewed the published literature pertaining to the pathology of the human pancreas throughout all stages in the natural history of T1D. This effort uncovered a series of findings that challenge many dogmas ascribed to T1D and revealed data suggesting the marked heterogeneity in terms of its pathology. An improved understanding and appreciation for pancreatic pathology in T1D could lead to improved disease classification, an understanding of why the disorder occurs, and better therapies for disease prevention and management

Activity and Habitat Use of Chimpanzees (Pan troglodytes verus) in the Anthropogenic Landscape of Bossou, Guinea, West Africa

Many primate populations inhabit anthropogenic landscapes. Understanding their long-term ability to persist in such environments and associated real and perceived risks for both primates and people is essential for effective conservation planning. Primates in forest–agricultural mosaics often consume cultivars to supplement their diet, leading to potentially negative encounters with farmers. When crossing roads, primates also face the risk of encounters with people and collision with vehicles. Chimpanzees (Pan troglodytes verus) in Bossou, Guinea, West Africa, face such risks regularly. In this study, we aimed to examine their activity budget across habitat types and the influence of anthropogenic risks associated with cultivated fields, roads, and paths on their foraging behavior in noncultivated habitat. We conducted 6-h morning or afternoon follows daily from April 2012 to March 2013. Chimpanzees preferentially used forest habitat types for traveling and resting and highly disturbed habitat types for socializing. Wild fruit and crop availability influenced seasonal habitat use for foraging. Overall, chimpanzees preferred mature forest for all activities. They showed a significant preference for foraging at >200 m from cultivated fields compared to 0–100 m and 101–200 m, with no effect of habitat type or season, suggesting an influence of associated risk. Nevertheless, the chimpanzees did not actively avoid foraging close to roads and paths. Our study reveals chimpanzee reliance on different habitat types and the influence of human-induced pressures on their activities. Such information is critical for the establishment of effective land use management strategies in anthropogenic landscapes

Using graph theory to analyze biological networks

Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system

Search for gravitational waves from Scorpius X-1 in the second Advanced LIGO observing run with an improved hidden Markov model

We present results from a semicoherent search for continuous gravitational waves from the low-mass x-ray binary Scorpius X-1, using a hidden Markov model (HMM) to track spin wandering. This search improves on previous HMM-based searches of LIGO data by using an improved frequency domain matched filter, the J-statistic, and by analyzing data from Advanced LIGO's second observing run. In the frequency range searched, from 60 to 650 Hz, we find no evidence of gravitational radiation. At 194.6 Hz, the most sensitive search frequency, we report an upper limit on gravitational wave strain (at 95% confidence) of h095%=3.47×10-25 when marginalizing over source inclination angle. This is the most sensitive search for Scorpius X-1, to date, that is specifically designed to be robust in the presence of spin wandering. © 2019 American Physical Society

Search for gravitational waves from Scorpius X-1 in the second Advanced LIGO observing run with an improved hidden Markov model

We present results from a semicoherent search for continuous gravitational waves from the low-mass x-ray binary Scorpius X-1, using a hidden Markov model (HMM) to track spin wandering. This search improves on previous HMM-based searches of LIGO data by using an improved frequency domain matched filter, the J-statistic, and by analyzing data from Advanced LIGO’s second observing run. In the frequency range searched, from 60 to 650 Hz, we find no evidence of gravitational radiation. At 194.6 Hz, the most sensitive search frequency, we report an upper limit on gravitational wave strain (at 95% confidence) of h95%0=3.47×10−25 when marginalizing over source inclination angle. This is the most sensitive search for Scorpius X-1, to date, that is specifically designed to be robust in the presence of spin wandering