Mechanisms influencing the spread of a native marine alga

Like invasive macrophytes, some native macrophytes are spreading rapidly with consequences for community structure. There is evidence that the native alga Caulerpa filiformis is spreading along intertidal rocky shores in New South Wales, Australia, seemingly at the expense of native Sargassum spp. We experimentally investigated the role physical disturbance plays in the spread of C. filiformis and its possible consequences for Sargassum spp. Cleared patches within beds of C. filiformis (Caulerpa habitat) or Sargassum spp. (Sargassum habitat) at multiple sites showed that C. filiformis had significantly higher recruitment (via propagules) into its own habitat. The recruitment of Sargassum spp. to Caulerpa habitat was rare, possibly due in part to sediment accretion within Caulerpa habitat. Diversity of newly recruited epibiotic assemblages within Caulerpa habitat was significantly less than in Sargassum habitat. In addition, more C. filiformis than Sargassum spp. recruited to Sargassum habitat at some sites. On common boundaries between these two macroalgae, the vegetative growth of adjacent C. filiformis into cleared patches was significantly higher than for adjacent Sargassum spp. In both experiments, results were largely independent of the size of disturbance (clearing). Lastly, we used PAM fluorometry to show that the photosynthetic condition of Sargassum spp. fronds adjacent to C. filiformis was generally suppressed relative to those distant from C. filiformis. Thus, physical disturbance, combined with invasive traits (e.g. high levels of recruitment and vegetative growth) most likely facilitate the spread of C. filiformis, with the ramifications being lower epibiotic diversity and possibly reduced photosynthetic condition of co-occurring native macrophytes. © 2014 Zhang et al

Investigating the Origins of Cancer in the Intestinal Crypt with a Gene Network Agent Based Hybrid Model

Colorectal cancer (CRC) is the second most common tumour in the world (Bray, 2018). It has been proposed that morbidity and mortality could be mitigated by screening methods that identify key genetic mutations in the DNA of a patient’s biosample (Traverso, 2002). However, for this to work, a theoretical understanding of the most likely mutations that initiate malignant transformation, and how they affect subsequent microevolution, is needed. Specifically, we hypothesise that there is a CRC-proliferative mutation that is more likely to be initially fixated in the crypt. To investigate this, we developed an agent-based model of cells in the colon crypt that shows emergent biological homeostasis at the tissue level from the cellular and molecular interactions. We equipped each of the cells with a molecular gene network which, in their wildtype state, regulates homeostasis in the crypt and recapitulates known behaviour. We identified and modelled key genes implicated in CRC which, when mutated, alter the rate of death and division of cells. We used this model to study the biological first principles of the fixation of mutations, offering key spatial and temporal understanding of this process. We discuss the impact and clinical relevance of proliferative genetic mutations in isolation, pointing to the KRAS gene as a likely mutation to be initially fixed in the crypt

On Quantifying Local Geometric Structures of Fiber Tracts

International audienceIn diffusion MRI, fiber tracts, represented by densely distributed 3D curves, can be estimated from diffusion weighted images using tractography. The spatial geometric structure of white matter fiber tracts is known to be complex in human brain, but it carries intrinsic information of human brain. In this paper, inspired by studies of liquid crystals, we propose tract-based director field analysis (tDFA) with total six rotationally invariant scalar indices to quantify local geometric structures of fiber tracts. The contributions of tDFA include: 1) We propose orientational order (OO) and orientational dispersion (OD) indices to quantify the degree of alignment and dispersion of fiber tracts; 2) We define the local orthogonal frame for a set of unoriented curves, which is proved to be a generalization of the Frenet frame defined for a single oriented curve; 3) With the local orthogonal frame, we propose splay, bend, and twist indices to quantify three types of orientational distortion of local fiber tracts, and a total distortion index to describe distortions of all three types. The proposed tDFA for fiber tracts is a generalization of the voxel-based DFA (vDFA) which was recently proposed for a spherical function field (i.e., an ODF field). To our knowledge, this is the first work to quantify orientational distortion (splay, bend, twist, and total distortion) of fiber tracts. Experiments show that the proposed scalar indices are useful descriptors of local geometric structures to visualize and analyze fiber tracts

Draf III frontal sinus surgery for the treatment of Pott's puffy tumour in adults: our case series and a review of frontal sinus anatomy risk factors

Purpose: We present our case series of four adult patients with Pott’s puffy tumour (PPT), successfully treated with Draf III over a mean period of 11 months. A critical review of the literature is also provided. Methods: A retrospective review of patients undergoing Draf III for PPT from January 2018 to January 2019 was performed. Results: Four consecutive male patients ranging from 26 to 62 years, with a mean age of 49.5 ± 16.3 years, undergoing Draf III for Pott’s puffy tumour were included. Two patients had a Kuhn type IV frontal cell narrowing the frontonasal pathway and presented without previous sinus surgery, whereas the other two had previous sinus surgery. The success rate of the operation was 100% with an average length of follow-up of 11 months (range 5–18). Conclusion: In our experience, the Draf III procedure is a highly effective treatment of PPT. In particular, we have demonstrated it to be very effective in accessing highly positioned Kuhn type IV cells

Missing Slice Imputation in Population CMR Imaging via Conditional Generative Adversarial Nets

Accurate ventricular volume measurements depend on complete heart coverage in cardiac magnetic resonance (CMR) from where most immediate indicators of normal/abnormal cardiac function are available non-invasively. However, incomplete coverage, especially missing basal or apical slices in CMR sequences is insufficiently addressed in population imaging and current clinical research studies yet has important impact on volume calculation accuracy. In this work, we propose a new deep architecture, coined Missing Slice Imputation Generative Adversarial Network (MSIGAN), to learn key features of cardiac short-axis (SAX) slices across different positions, and use them as conditional variables to effectively infer missing slices in the query volumes. In MSIGAN, the slices are first mapped to latent vectors with position features through a regression net. The latent vector corresponding to the desired position is then projected onto the slice manifold conditional on slice intensity through a generator net. The latent vector along with the slice features (i.e., intensity) and desired position control the generation vs. regression. Two adversarial networks are imposed on the regressor and generator, encouraging more realistic slices. Experimental results show that our method outperforms the previous state-of-the-art in missing slice imputation for cardiac MRI

lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers

We assume data sampled from a mixture of d-dimensional linear subspaces with spherically symmetric distributions within each subspace and an additional outlier component with spherically symmetric distribution within the ambient space (for simplicity we may assume that all distributions are uniform on their corresponding unit spheres). We also assume mixture weights for the different components. We say that one of the underlying subspaces of the model is most significant if its mixture weight is higher than the sum of the mixture weights of all other subspaces. We study the recovery of the most significant subspace by minimizing the lp-averaged distances of data points from d-dimensional subspaces, where p>0. Unlike other lp minimization problems, this minimization is non-convex for all p>0 and thus requires different methods for its analysis. We show that if 0<p<=1, then for any fraction of outliers the most significant subspace can be recovered by lp minimization with overwhelming probability (which depends on the generating distribution and its parameters). We show that when adding small noise around the underlying subspaces the most significant subspace can be nearly recovered by lp minimization for any 0<p<=1 with an error proportional to the noise level. On the other hand, if p>1 and there is more than one underlying subspace, then with overwhelming probability the most significant subspace cannot be recovered or nearly recovered. This last result does not require spherically symmetric outliers.Comment: This is a revised version of the part of 1002.1994 that deals with single subspace recovery. V3: Improved estimates (in particular for Lemma 3.1 and for estimates relying on it), asymptotic dependence of probabilities and constants on D and d and further clarifications; for simplicity it assumes uniform distributions on spheres. V4: minor revision for the published versio

The battle of the SNPs

This month’s Genome Watch highlights new perspectives on polygenic adaptation and its consequences for fitness in microbial populations

RepSeq-A database of amino acid repeats present in lower eukaryotic pathogens

BACKGROUND Amino acid repeat-containing proteins have a broad range of functions and their identification is of relevance to many experimental biologists. In human-infective protozoan parasites (such as the Kinetoplastid and Plasmodium species), they are implicated in immune evasion and have been shown to influence virulence and pathogenicity. RepSeq http://repseq.gugbe.com is a new database of amino acid repeat-containing proteins found in lower eukaryotic pathogens. The RepSeq database is accessed via a web-based application which also provides links to related online tools and databases for further analyses. RESULTS The RepSeq algorithm typically identifies more than 98% of repeat-containing proteins and is capable of identifying both perfect and mismatch repeats. The proportion of proteins that contain repeat elements varies greatly between different families and even species (3 - 35% of the total protein content). The most common motif type is the Sequence Repeat Region (SRR) - a repeated motif containing multiple different amino acid types. Proteins containing Single Amino Acid Repeats (SAARs) and Di-Peptide Repeats (DPRs) typically account for 0.5 - 1.0% of the total protein number. Notable exceptions are P. falciparum and D. discoideum, in which 33.67% and 34.28% respectively of the predicted proteomes consist of repeat-containing proteins. These numbers are due to large insertions of low complexity single and multi-codon repeat regions. CONCLUSION The RepSeq database provides a repository for repeat-containing proteins found in parasitic protozoa. The database allows for both individual and cross-species proteome analyses and also allows users to upload sequences of interest for analysis by the RepSeq algorithm. Identification of repeat-containing proteins provides researchers with a defined subset of proteins which can be analysed by expression profiling and functional characterisation, thereby facilitating study of pathogenicity and virulence factors in the parasitic protozoa. While primarily designed for kinetoplastid work, the RepSeq algorithm and database retain full functionality when used to analyse other species

Proteomic profile of KSR1-regulated signalling in response to genotoxic agents in breast cancer

Kinase suppressor of Ras 1 (KSR1) has been implicated in tumorigenesis in multiple cancers, including skin, pancreatic and lung carcinomas. However, our recent study revealed a role of KSR1 as a tumour suppressor in breast cancer, the expression of which is potentially correlated with chemotherapy response. Here, we aimed to further elucidate the KSR1-regulated signalling in response to genotoxic agents in breast cancer. Stable isotope labelling by amino acids in cell culture (SILAC) coupled to high-resolution mass spectrometry (MS) was implemented to globally characterise cellular protein levels induced by KSR1 in the presence of doxorubicin or etoposide. The acquired proteomic signature was compared and GO-STRING analysis was subsequently performed to illustrate the activated functional signalling networks. Furthermore, the clinical associations of KSR1 with identified targets and their relevance in chemotherapy response were examined in breast cancer patients. We reveal a comprehensive repertoire of thousands of proteins identified in each dataset and compare the unique proteomic profiles as well as functional connections modulated by KSR1 after doxorubicin (Doxo-KSR1) or etoposide (Etop-KSR1) stimulus. From the up-regulated top hits, several proteins, including STAT1, ISG15 and TAP1 are also found to be positively associated with KSR1 expression in patient samples. Moreover, high KSR1 expression, as well as high abundance of these proteins, is correlated with better survival in breast cancer patients who underwent chemotherapy. In aggregate, our data exemplify a broad functional network conferred by KSR1 with genotoxic agents and highlight its implication in predicting chemotherapy response in breast cancer