Family connections versus optimised treatment-as-usual for family members of individuals with borderline personality disorder: non-randomised controlled study

Background: Borderline personality disorder (BPD) is challenging for family members who are often required to fulfil multiple roles such as those of advocate, caregiver, coach and guardian. To date, two uncontrolled studies by the treatment developers suggest that Family Connections (FC) is an effective programme to support, educate and teach skills to family members of individuals with BPD. However, such studies have been limited by lack of comparison to other treatment approaches. This study aimed to compare the effectiveness of FC with an optimised treatment-as-usual (OTAU) programme for family members of individuals with BPD. A secondary aim was to introduce a long term follow-up to investigate if positive gains from the intervention would be maintained following programme completion. Methods: This study was a non-randomised controlled study, with assessment of outcomes at baseline (pre-intervention) and end of programme (post-intervention) for both FC and OTAU groups, and at follow-up (3 months post-intervention; 12 or 19 months post-intervention) for the FC group. Eighty family members participated in the FC (n = 51) and the OTAU (n = 29) programmes. Outcome measures included burden, grief, depression and mastery. Linear mixed-effects models were used to assess baseline differences in the outcome measures by gender, age group and type of relationship to the individual with BPD. Linear mixed-effects models were also used to estimate the treatment effect (FC versus OTAU) utilising all available data from baseline and end of programme. Results: The FC group showed changes indicating significant improvement with respect to all four outcome measures (p < 0.001). The OTAU group showed changes in the same direction as the intervention group but none of the changes were statistically significant. The intervention effect was statistically significant for total burden (including both subscales; p = .02 for subjective burden and p = .048 for objective burden) and grief (p = 0.013). Improvements were maintained at follow-up for FC participants. Conclusions: The findings of the current study indicate that FC results in statistically significant improvements on key measures while OTAU does not yield comparable changes. Lack of significant change on all measures for OTAU suggests that a three session psycho-education programme is of limited benefit. Further research is warranted on programme components and long-term supports for family members

Standardising RNA profiling based biomarker application in cancer - the need for robust control of technical variables

Histopathology-based staging of colorectal cancer (CRC) has utility in assessing the prognosis of patient subtypes, but as yet cannot accurately predict individual patient’s treatment response. Transcriptomics approaches, using array based or next generation sequencing (NGS) platforms, of formalin fixed paraffin embedded tissue can be harnessed to develop multi-gene biomarkers for predicting both prognosis and treatment response, leading to stratification of treatment. While transcriptomics can shape future biomarker development, currently &lt; 1% of published biomarkers become clinically validated tests, often due to poor study design or lack of independent validation. In this review of a large number of CRC transcriptional studies, we identify recurrent sources of technical variability that encompass collection, preservation and storage of malignant tissue, nucleic acid extraction, methods to quantitate RNA transcripts and data analysis pipelines. We propose a series of defined steps for removal of these confounding issues, to ultimately aid in the development of more robust clinical biomarkers

A Computational Approach for Designing Tiger Corridors in India

Wildlife corridors are components of landscapes, which facilitate the movement of organisms and processes between intact habitat areas, and thus provide connectivity between the habitats within the landscapes. Corridors are thus regions within a given landscape that connect fragmented habitat patches within the landscape. The major concern of designing corridors as a conservation strategy is primarily to counter, and to the extent possible, mitigate the effects of habitat fragmentation and loss on the biodiversity of the landscape, as well as support continuance of land use for essential local and global economic activities in the region of reference. In this paper, we use game theory, graph theory, membership functions and chain code algorithm to model and design a set of wildlife corridors with tiger (Panthera tigris tigris) as the focal species. We identify the parameters which would affect the tiger population in a landscape complex and using the presence of these identified parameters construct a graph using the habitat patches supporting tiger presence in the landscape complex as vertices and the possible paths between them as edges. The passage of tigers through the possible paths have been modelled as an Assurance game, with tigers as an individual player. The game is played recursively as the tiger passes through each grid considered for the model. The iteration causes the tiger to choose the most suitable path signifying the emergence of adaptability. As a formal explanation of the game, we model this interaction of tiger with the parameters as deterministic finite automata, whose transition function is obtained by the game payoff.Comment: 12 pages, 5 figures, 6 tables, NGCT conference 201

The interplay of microscopic and mesoscopic structure in complex networks

Not all nodes in a network are created equal. Differences and similarities exist at both individual node and group levels. Disentangling single node from group properties is crucial for network modeling and structural inference. Based on unbiased generative probabilistic exponential random graph models and employing distributive message passing techniques, we present an efficient algorithm that allows one to separate the contributions of individual nodes and groups of nodes to the network structure. This leads to improved detection accuracy of latent class structure in real world data sets compared to models that focus on group structure alone. Furthermore, the inclusion of hitherto neglected group specific effects in models used to assess the statistical significance of small subgraph (motif) distributions in networks may be sufficient to explain most of the observed statistics. We show the predictive power of such generative models in forecasting putative gene-disease associations in the Online Mendelian Inheritance in Man (OMIM) database. The approach is suitable for both directed and undirected uni-partite as well as for bipartite networks

Proteomic Identification of IPSE/alpha-1 as a Major Hepatotoxin Secreted by Schistosoma mansoni Eggs

The flatworm disease, schistosomiasis, is a major public health problem in sub-Saharan Africa, South America and East Asia. A hallmark of infection with Schistosoma mansoni is the immune response to parasite eggs trapped in the liver and other organs. This response involves an infiltration of cells that surround the parasite egg forming a “granuloma.” In mice deprived of T-cells, this granulomatous response is lacking, and toxic products released by eggs quickly cause liver damage and death. Thus the granulomata protect the host from toxic egg products. Only one hepatotoxic molecule, omega-1, has been described to date. We set out to identify other S. mansoni egg hepatotoxins using liver cells grown in culture. We first showed that live eggs, their secretions, and pure omega-1 are toxic. Using a physical separation technique to prepare fractions from whole egg secretions, we identified the presence of IPSE/alpha-1, a protein that is known to strongly influence the immune system. We showed that IPSE/alpha-1 is also hepatotoxic, and that toxicity of both omega-1 and IPSE/alpha-1 can be prevented by first mixing the proteins with specific neutralizing antibodies. Both proteins constitute the majority of hepatotoxicity released by eggs

Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

Stromal-derived intratumoural heterogeneity (ITH) has been shown to undermine molecular stratification of patients into appropriate prognostic/predictive subgroups. Here, using several clinically relevant colorectal cancer (CRC) gene expression signatures, we assessed the susceptibility of these signatures to the confounding effects of ITH using gene expression microarray data obtained from multiple tumour regions of a cohort of 24 patients, including central tumour, the tumour invasive front and lymph node metastasis. Sample clustering alongside correlative assessment revealed variation in the ability of each signature to cluster samples according to patient-of-origin rather than region-of-origin within the multi-region dataset. Signatures focused on cancer-cell intrinsic gene expression were found to produce more clinically useful, patient-centred classifiers, as exemplified by the CRC intrinsic signature (CRIS), which robustly clustered samples by patient-of-origin rather than region-of-origin. These findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of stromal-derived ITH

In-depth clinical and biological exploration of DNA Damage Immune Response (DDIR) as a biomarker for oxaliplatin use in colorectal cancer

PURPOSE: The DNA Damage Immune Response (DDIR) assay was developed in breast cancer (BC) based on biology associated with deficiencies in homologous recombination and Fanconi Anemia (HR/FA) pathways. A positive DDIR call identifies patients likely to respond to platinum-based chemotherapies in breast and oesophageal cancers. In colorectal cancer (CRC) there is currently no biomarker to predict response to oxaliplatin. We tested the ability of the DDIR assay to predict response to oxaliplatin-based chemotherapy in CRC and characterised the biology in DDIR-positive CRC. METHODS: Samples and clinical data were assessed according to DDIR status from patients who received either 5FU or FOLFOX within the FOCUS trial (n=361, stage 4), or neo-adjuvant FOLFOX in the FOxTROT trial (n=97, stage 2/3). Whole transcriptome, mutation and immunohistochemistry data of these samples were used to interrogate the biology of DDIR in CRC. RESULTS: Contrary to our hypothesis, DDIR negative patients displayed a trend towards improved outcome for oxaliplatin-based chemotherapy compared to DDIR positive patients. DDIR positivity was associated with Microsatellite Instability (MSI) and Colorectal Molecular Subtype 1 (CMS1). Refinement of the DDIR signature, based on overlapping interferon-related chemokine signalling associated with DDIR positivity across CRC and BC cohorts, further confirmed that the DDIR assay did not have predictive value for oxaliplatin-based chemotherapy in CRC. CONCLUSIONS: DDIR positivity does not predict improved response following oxaliplatin treatment in CRC. However, data presented here suggests the potential of the DDIR assay in identifying immune-rich tumours that may benefit from immune checkpoint blockade, beyond current use of MSI status

Deciphering the connectivity structure of biological networks using MixNet

<p>Abstract</p> <p>Background</p> <p>As biological networks often show complex topological features, mathematical methods are required to extract meaningful information. Clustering methods are useful in this setting, as they allow the summary of the network's topology into a small number of relevant classes. Different strategies are possible for clustering, and in this article we focus on a model-based strategy that aims at clustering nodes based on their connectivity profiles.</p> <p>Results</p> <p>We present MixNet, the first publicly available computer software that analyzes biological networks using mixture models. We apply this method to various networks such as the <it>E. coli </it>transcriptional regulatory network, the macaque cortex network, a foodweb network and the <it>Buchnera aphidicola </it>metabolic network. This method is also compared with other approaches such as module identification or hierarchical clustering.</p> <p>Conclusion</p> <p>We show how MixNet can be used to extract meaningful biological information, and to give a summary of the networks topology that highlights important biological features. This approach is powerful as MixNet is adaptive to the network under study, and finds structural information without any a priori on the structure that is investigated. This makes MixNet a very powerful tool to summarize and decipher the connectivity structure of biological networks.</p

Growth inhibition of oral mutans streptococci and candida by commercial probiotic lactobacilli - an in vitro study

<p>Abstract</p> <p>Background</p> <p>Probiotic bacteria are suggested to play a role in the maintenance of oral health. Such health promoting bacteria are added to different commercial probiotic products. The aim of the study was to investigate the ability of a selection of lactobacilli strains, used in commercially available probiotic products, to inhibit growth of oral mutans streptococci and <it>C. albicans in vitro</it>.</p> <p>Methods</p> <p>Eight probiotic lactobacilli strains were tested for growth inhibition on three reference strains and two clinical isolates of mutans streptococci as well as two reference strains and three clinical isolates of <it>Candida albicans </it>with an agar overlay method.</p> <p>Results</p> <p>At concentrations ranging from 10⁹to 10⁵CFU/ml, all lactobacilli strains inhibited the growth of the mutans streptococci completely with the exception of <it>L. acidophilus </it>La5 that executed only a slight inhibition of some strains at concentrations corresponding to 10⁷and 10⁵CFU/ml. At the lowest cell concentration (10³CFU/ml), only <it>L. plantarum </it>299v and <it>L. plantarum </it>931 displayed a total growth inhibition while a slight inhibition was seen for all five mutans streptococci strains by <it>L. rhamnosus </it>LB21, <it>L. paracasei </it>F19, <it>L. reuteri </it>PTA 5289 and <it>L. reuteri </it>ATCC 55730. All the tested lactobacilli strains reduced candida growth but the effect was generally weaker than for mutans streptococci. The two <it>L. plantarum </it>strains and <it>L. reuteri </it>ATCC 55730 displayed the strongest inhibition on <it>Candida albicans</it>. No significant differences were observed between the reference strains and the clinical isolates.</p> <p>Conclusion</p> <p>The selected probiotic strains showed a significant but somewhat varying ability to inhibit growth of oral mutans streptococci and <it>Candida albicans in vitro</it>.</p

Temporal resolution of protein–protein interactions in the live-cell plasma membrane

We have recently devised a method to quantify interactions between a membrane protein (“bait”) and a fluorophore-labeled protein (“prey”) directly in the live-cell plasma membrane (Schwarzenbacher et al. Nature Methods 5:1053–1060 2008). The idea is to seed cells on surfaces containing micro-patterned antibodies against the exoplasmic domain of the bait, and monitor the co-patterning of the fluorescent prey via fluorescence microscopy. Here, we characterized the time course of bait and prey micropattern formation upon seeding the cells onto the micro-biochip. Patterns were formed immediately after contact of the cells with the surface. Cells were able to migrate over the chip surface without affecting the micropattern contrast, which remained constant over hours. On single cells, bait contrast may be subject to fluctuations, indicating that the bait can be released from and recaptured on the micropatterns. We conclude that interaction studies can be performed at any time-point ranging from 5 min to several hours post seeding. Monitoring interactions with time opens up the possibility for new assays, which are briefly sketched in the discussion section