Emergence of skew distributions in controlled growth processes

Starting from a master equation, we derive the evolution equation for the size distribution of elements in an evolving system, where each element can grow, divide into two, and produce new elements. We then probe general solutions of the evolution quation, to obtain such skew distributions as power-law, log-normal, and Weibull distributions, depending on the growth or division and production. Specifically, repeated production of elements of uniform size leads to power-law distributions, whereas production of elements with the size distributed according to the current distribution as well as no production of new elements results in log-normal distributions. Finally, division into two, or binary fission, bears Weibull distributions. Numerical simulations are also carried out, confirming the validity of the obtained solutions.Comment: 9 pages, 3 figure

Matching-adjusted indirect treatment comparison of [¹⁷⁷Lu]Lu-DOTA-TATE, everolimus and sunitinib in advanced, unresectable gastroenteropancreatic neuroendocrine tumours:Relative effectiveness of [¹⁷⁷Lu]Lu-DOTA-TATE in gastroenteropancreatic neuroendocrine tumours

Head-to-head comparisons of the efficacy of treatments for gastroenteropancreatic neuroendocrine tumours (GEP-NETs) have not yet been reported. This study used a series of matching-adjusted indirect comparisons to indirectly compare the effectiveness of [177Lu]Lu-DOTA-TATE to everolimus, sunitinib and best supportive care (BSC) for extending progression-free survival and overall survival in patients with advanced, unresectable gastrointestinal (GI)-NETs and P-NETs. The results of the main analysis suggest that after accounting for differences in key prognostic variables, the hazard of progression was 62% (hazard ratio [HR], 0.38; confidence interval [CI]95 0.25–0.58) and 65% (HR 0.35 CI95 0.21–0.59) lower in patients with GI-NETs treated with [177Lu]Lu-DOTA-TATE than in those treated with everolimus and BSC, respectively. Similarly, the hazard of progression was 64% (HR 0.36 CI95 0.18–0.70), 54% (HR 0.46 CI95 0.30–0.71) and 79–87% (HR 0.21 CI95 0.13–0.32; HR 0.13 CI95 0.08–0.22) lower in patients with P-NET treated with [177Lu]Lu-DOTA-TATE than in those treated with sunitinib, everolimus and BSC, respectively. The hazard of death was 58% (HR 0.42 CI95 0.25–0.72), 47% (HR 0.53 CI95 0.33–0.87) and 44–64% (HR 0.56 CI95 0.36–0.90; HR 0.34 CI95 0.20–0.57) lower in P-patients with NET treated with [177Lu]Lu-DOTA-TATE than in those treated with sunitinib, everolimus and BSC, respectively. While our results must be interpreted with caution given the non-randomised nature of the comparisons and the potential for residual confounding, the magnitude of the effect sizes we observe and their consistency across comparators suggest that [177Lu]Lu-DOTA-TATE may be a more effective treatment option than everolimus, sunitinib and BSC in advanced, unresectable GEP-NETs

Arginine–glycine–aspartic acid functional branched semi-interpenetrating hydrogels

For the first time a series of functional hydrogels based on semi-interpenetrating networks with both branched and crosslinked polymer components have been prepared and we show the successful use of these materials as substrates for cell culture. The materials consist of highly branched poly(N-isopropyl acrylamide)s with peptide functionalised end groups in a continuous phase of crosslinked poly(vinyl pyrrolidone). Functionalisation of the end groups of the branched polymer component with the GRGDS peptide produces a hydrogel that supports cell adhesion and proliferation. The materials provide a new synthetic functional biomaterial that has many of the features of extracellular matrix, and as such can be used to support tissue regeneration and cell culture. This class of high water content hydrogel material has important advantages over other functional hydrogels in its synthesis and does not require postprocessing modifications nor are functional-monomers, which change the polymerisation process, required. Thus, the systems are amenable to large scale and bespoke manufacturing using conventional moulding or additive manufacturing techniques. Processing using additive manufacturing is exemplified by producing tubes using microstereolithography

Injectable biomaterial induces regeneration of the intervertebral disc in a caprine loaded disc culture model †

Back pain is the leading cause of disability with half of cases attributed to intervertebral disc (IVD) degeneration, yet currently no therapies target this cause. We previously reported an ex vivo caprine loaded disc culture system (LDCS) that accurately represents the cellular phenotype and biomechanical environment of human IVD degeneration. Here, the efficacy of an injectable hydrogel system (LAPONITE® crosslinked pNIPAM-co-DMAc, (NPgel)) to halt or reverse the catabolic processes of IVD degeneration was investigated within the LDCS. Following enzymatic induction of degeneration using 1 mg mL−1 collagenase and 2 U mL−1 chondroitinase ABC within the LDCS for 7 days, IVDs were injected with NPgel alone or with encapsulated human bone marrow progenitor cells (BMPCs). Un-injected caprine discs served as degenerate controls. IVDs were cultured for a further 21 days within the LDCS. Tissues were then processed for histology and immunohistochemistry. No extrusion of NPgel was observed during culture. A significant decrease in histological grade of degeneration was seen in both IVDs injected with NPgel alone and NPgel seeded with BMPCs, compared to un-injected controls. Fissures within degenerate tissue were filled by NPgel and there was evidence of native cell migration into injected NPgel. The expression of healthy NP matrix markers (collagen type II and aggrecan) was increased, whereas the expression of catabolic proteins (MMP3, ADAMTS4, IL-1β and IL-8) was decreased in NPgel (±BMPCs) injected discs, compared to degenerate controls. This demonstrates that NPgel promotes new matrix production at the same time as halting the degenerative cascade within a physiologically relevant testing platform. This highlights the potential of NPgel as a future therapy for IVD degeneration

Ventilatory Chaos Is Impaired in Carotid Atherosclerosis

Ventilatory chaos is strongly linked to the activity of central pattern generators, alone or influenced by respiratory or cardiovascular afferents. We hypothesized that carotid atherosclerosis should alter ventilatory chaos through baroreflex and autonomic nervous system dysfunctions. Chaotic dynamics of inspiratory flow was prospectively evaluated in 75 subjects undergoing carotid ultrasonography: 27 with severe carotid stenosis (>70%), 23 with moderate stenosis (<70%), and 25 controls. Chaos was characterized by the noise titration method, the correlation dimension and the largest Lyapunov exponent. Baroreflex sensitivity was estimated in the frequency domain. In the control group, 92% of the time series exhibit nonlinear deterministic chaos with positive noise limit, whereas only 68% had a positive noise limit value in the stenoses groups. Ventilatory chaos was impaired in the groups with carotid stenoses, with significant parallel decrease in the noise limit value, correlation dimension and largest Lyapunov exponent, as compared to controls. In multiple regression models, the percentage of carotid stenosis was the best in predicting the correlation dimension (p<0.001, adjusted R2: 0.35) and largest Lyapunov exponent (p<0.001, adjusted R2: 0.6). Baroreflex sensitivity also predicted the correlation dimension values (p = 0.05), and the LLE (p = 0.08). Plaque removal after carotid surgery reversed the loss of ventilatory complexity. To conclude, ventilatory chaos is impaired in carotid atherosclerosis. These findings depend on the severity of the stenosis, its localization, plaque surface and morphology features, and is independently associated with baroreflex sensitivity reduction. These findings should help to understand the determinants of ventilatory complexity and breathing control in pathological conditions

Comparative Study of Complete and Partial Omentectomy in Radical Subtotal Gastrectomy for Early Gastric Cancer

∙ The authors have no financial conflicts of interest. © Copyright: Yonsei University College of Medicine 2011 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial Licens

Statistical and visual differentiation of subcellular imaging

<p>Abstract</p> <p>Background</p> <p>Automated microscopy technologies have led to a rapid growth in imaging data on a scale comparable to that of the genomic revolution. High throughput screens are now being performed to determine the localisation of all of proteins in a proteome. Closer to the bench, large image sets of proteins in treated and untreated cells are being captured on a daily basis to determine function and interactions. Hence there is a need for new methodologies and protocols to test for difference in subcellular imaging both to remove bias and enable throughput. Here we introduce a novel method of statistical testing, and supporting software, to give a rigorous test for difference in imaging. We also outline the key questions and steps in establishing an analysis pipeline.</p> <p>Results</p> <p>The methodology is tested on a high throughput set of images of 10 subcellular localisations, and it is shown that the localisations may be distinguished to a statistically significant degree with as few as 12 images of each. Further, subtle changes in a protein's distribution between nocodazole treated and control experiments are shown to be detectable. The effect of outlier images is also examined and it is shown that while the significance of the test may be reduced by outliers this may be compensated for by utilising more images. Finally, the test is compared to previous work and shown to be more sensitive in detecting difference. The methodology has been implemented within the iCluster system for visualising and clustering bio-image sets.</p> <p>Conclusion</p> <p>The aim here is to establish a methodology and protocol for testing for difference in subcellular imaging, and to provide tools to do so. While iCluster is applicable to moderate (<1000) size image sets, the statistical test is simple to implement and will readily be adapted to high throughput pipelines to provide more sensitive discrimination of difference.</p

A highly efficient multi-core algorithm for clustering extremely large datasets

<p>Abstract</p> <p>Background</p> <p>In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer.</p> <p>Results</p> <p>We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization.</p> <p>Conclusions</p> <p>Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer.</p

Mining protein loops using a structural alphabet and statistical exceptionality

<p>Abstract</p> <p>Background</p> <p>Protein loops encompass 50% of protein residues in available three-dimensional structures. These regions are often involved in protein functions, e.g. binding site, catalytic pocket... However, the description of protein loops with conventional tools is an uneasy task. Regular secondary structures, helices and strands, have been widely studied whereas loops, because they are highly variable in terms of sequence and structure, are difficult to analyze. Due to data sparsity, long loops have rarely been systematically studied.</p> <p>Results</p> <p>We developed a simple and accurate method that allows the description and analysis of the structures of short and long loops using structural motifs without restriction on loop length. This method is based on the structural alphabet HMM-SA. HMM-SA allows the simplification of a three-dimensional protein structure into a one-dimensional string of states, where each state is a four-residue prototype fragment, called structural letter. The difficult task of the structural grouping of huge data sets is thus easily accomplished by handling structural letter strings as in conventional protein sequence analysis. We systematically extracted all seven-residue fragments in a bank of 93000 protein loops and grouped them according to the structural-letter sequence, named structural word. This approach permits a systematic analysis of loops of all sizes since we consider the structural motifs of seven residues rather than complete loops. We focused the analysis on highly recurrent words of loops (observed more than 30 times). Our study reveals that 73% of loop-lengths are covered by only 3310 highly recurrent structural words out of 28274 observed words). These structural words have low structural variability (mean RMSd of 0.85 Å). As expected, half of these motifs display a flanking-region preference but interestingly, two thirds are shared by short (less than 12 residues) and long loops. Moreover, half of recurrent motifs exhibit a significant level of amino-acid conservation with at least four significant positions and 87% of long loops contain at least one such word. We complement our analysis with the detection of statistically over-represented patterns of structural letters as in conventional DNA sequence analysis. About 30% (930) of structural words are over-represented, and cover about 40% of loop lengths. Interestingly, these words exhibit lower structural variability and higher sequential specificity, suggesting structural or functional constraints.</p> <p>Conclusions</p> <p>We developed a method to systematically decompose and study protein loops using recurrent structural motifs. This method is based on the structural alphabet HMM-SA and not on structural alignment and geometrical parameters. We extracted meaningful structural motifs that are found in both short and long loops. To our knowledge, it is the first time that pattern mining helps to increase the signal-to-noise ratio in protein loops. This finding helps to better describe protein loops and might permit to decrease the complexity of long-loop analysis. Detailed results are available at <url>http://www.mti.univ-paris-diderot.fr/publication/supplementary/2009/ACCLoop/</url>.</p