ParaKMeans: Implementation of a parallelized K-means algorithm suitable for general laboratory use

<p>Abstract</p> <p>Background</p> <p>During the last decade, the use of microarrays to assess the transcriptome of many biological systems has generated an enormous amount of data. A common technique used to organize and analyze microarray data is to perform cluster analysis. While many clustering algorithms have been developed, they all suffer a significant decrease in computational performance as the size of the dataset being analyzed becomes very large. For example, clustering 10000 genes from an experiment containing 200 microarrays can be quite time consuming and challenging on a desktop PC. One solution to the scalability problem of clustering algorithms is to distribute or parallelize the algorithm across multiple computers.</p> <p>Results</p> <p>The software described in this paper is a high performance multithreaded application that implements a parallelized version of the K-means Clustering algorithm. Most parallel processing applications are not accessible to the general public and require specialized software libraries (e.g. MPI) and specialized hardware configurations. The parallel nature of the application comes from the use of a web service to perform the distance calculations and cluster assignments. Here we show our parallel implementation provides significant performance gains over a wide range of datasets using as little as seven nodes. The software was written in C# and was designed in a modular fashion to provide both deployment flexibility as well as flexibility in the user interface.</p> <p>Conclusion</p> <p>ParaKMeans was designed to provide the general scientific community with an easy and manageable client-server application that can be installed on a wide variety of Windows operating systems.</p

ParaSAM: a parallelized version of the significance analysis of microarrays algorithm

Motivation: Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements

Congruences modulo prime powers of Hecke eigenvalues in level 11

We continue the study of strong, weak, and $dc$-weak eigenforms introduced by Chen, Kiming, and Wiese. We completely determine all systems of Hecke eigenvalues of level $1$ modulo $128$, showing there are finitely many. This extends results of Hatada and can be considered as evidence for the more general conjecture formulated by the author together with Kiming and Wiese on finiteness of systems of Hecke eigenvalues modulo prime powers at any fixed level. We also discuss the finiteness of systems of Hecke eigenvalues of level $1$ modulo $9$, reducing the question to the finiteness of a single eigenvalue. Furthermore, we answer the question of comparing weak and $dc$-weak eigenforms and provide the first known examples of non-weak $dc$-weak eigenforms.Comment: 28 pages; Minor revisio

Weekly and daily tooth brushing by care staff reduces gingivitis and calculus in racing greyhounds

SIMPLE SUMMARY: Dental disease affects many dogs worldwide and is believed to be particularly problematic for racing greyhounds. It costs the industry and rehoming charities financially and likely causes unnecessary suffering to a large number of dogs. The risk factors for dental disease in this population are debated, and the best methods to overcome it are relatively unresearched. We carried out a trial in which 160 racing greyhounds were divided into three groups. The staff looking after them either brushed their teeth daily, weekly or never, for a period of two months. An experimenter measured the dog’s level of calculus (hardened dental plaque) and gingivitis (gum inflammation) at the start, and again after two months. We found that both weekly and daily brushing resulted in significant reductions in calculus, but for gingivitis only daily brushing resulted in a significant reduction. The effects, however, were not noticeable on the front incisor teeth. Since the staff implementing the routine reported a minimal time commitment and positive experiences, we suggest that daily brushing is recommended for racing greyhounds, and that emphasis is placed on brushing all teeth groups. Similar trials need to be conducted with retired greyhounds since these have been shown to present particularly high levels of periodontal disease. ABSTRACT: Periodontal disease is one of the most common conditions affecting dogs worldwide and is reported to be particularly prevalent in racing greyhounds. A range of potential risk factors have been hypothesised. Previous research has suggested that regular tooth brushing can reduce both calculus and gingivitis, but the frequency required is unclear. Here, we report a controlled blinded in situ trial, in which kennel staff brushed 160 racing greyhounds’ teeth (living at six kennel establishments), either weekly, daily or never over a two-month period. All of the visible teeth were scored for calculus and gingivitis, using previously validated scales. We calculated average scores for each of the three teeth groups and overall whole mouth scores, averaging the teeth groups. Changes were compared to the baseline. After two months, the total calculus scores (controlling for baseline) were significantly different in the three treatment groups, (F((2,129)) = 10.76, p < 0.001) with both weekly and daily brushing resulting in significant reductions. Gingivitis was also significantly different between groups (F((2,128)) = 4.57, p = 0.012), but in this case, only daily brushing resulted in a significant reduction. Although the dogs in different kennels varied significantly in their levels of both calculus (F((5,129)) = 8.64, p < 0.001) and gingivitis (F((5,128)) = 3.51 p = 0.005), the intervention was similarly effective in all of the establishments. The teeth groups varied, and the incisors were not significantly affected by the treatment. Since the trainers implementing the routine, reported a minimal time commitment and positive experiences, we suggest that daily brushing is recommended for racing greyhounds, and that any instructions or demonstrations should include attention to all teeth groups including the incisors. Similar trials need to be conducted with retired greyhounds since these have been shown to present particularly high levels of periodontal disease

Thymus-derived regulatory T cells control tolerance to commensal microbiota

Peripheral mechanisms preventing autoimmunity and maintaining tolerance to commensal microbiota involve CD4+Foxp3+ regulatory T cells1,2 generated in the thymus (tTregs) or extrathymically by induction of naive CD4+Foxp3− T cells (iTregs). Prior studies suggested that the T cell receptor (TCR) repertoires of tTregs and iTregs are biased towards self and non-self antigens, respectively 3–6 but their relative contribution in controlling immunopathology, e.g. colitis and other untoward inflammatory responses triggered by different types of antigens, remains unresolved 7. The intestine, and especially the colon, is a particularly suitable organ to study this question, given the variety of self-, microbiota- and food-derived antigens to which Tregs and other T cell populations are exposed. Intestinal environments can enhance conversion to a regulatory lineage 8,9 and favor tolerogenic presentation of antigens to naive CD4+ T cells 10,11, suggesting that intestinal homeostasis depends on microbiota-specific iTregs 12–15. Here, to identify the origin and antigen-specificity of intestinal Tregs, we performed single cell as well as high-throughput (HT) sequencing of the TCR repertoires of CD4+Foxp3+ and CD4+Foxp3− T cells and analyzed their reactivity against specific commensal species. We show that tTregs constitute the majority of Tregs in all lymphoid and intestinal organs, including colon, where their repertoire is heavily influenced by the composition of the microbiota. Our results suggest that tTregs, and not iTregs, dominantly mediate tolerance to antigens produced by intestinal commensals

A modified hyperplane clustering algorithm allows for efficient and accurate clustering of extremely large datasets

Motivation: As the number of publically available microarray experiments increases, the ability to analyze extremely large datasets across multiple experiments becomes critical. There is a requirement to develop algorithms which are fast and can cluster extremely large datasets without affecting the cluster quality. Clustering is an unsupervised exploratory technique applied to microarray data to find similar data structures or expression patterns. Because of the high input/output costs involved and large distance matrices calculated, most of the algomerative clustering algorithms fail on large datasets (30 000 + genes/200 + arrays). In this article, we propose a new two-stage algorithm which partitions the high-dimensional space associated with microarray data using hyperplanes. The first stage is based on the Balanced Iterative Reducing and Clustering using Hierarchies algorithm with the second stage being a conventional k-means clustering technique. This algorithm has been implemented in a software tool (HPCluster) designed to cluster gene expression data. We compared the clustering results using the two-stage hyperplane algorithm with the conventional k-means algorithm from other available programs. Because, the first stage traverses the data in a single scan, the performance and speed increases substantially. The data reduction accomplished in the first stage of the algorithm reduces the memory requirements allowing us to cluster 44 460 genes without failure and significantly decreases the time to complete when compared with popular k-means programs. The software was written in C# (.NET 1.1)

Efficacy of Chlorine-based, Enzymatic and Combined Chlorine-enzyme Treatments on Biofilm Removal

Glyphosate resistance evolution in weeds is a growing problem in world agriculture. Here, we have investigated the mechanism(s) of glyphosate resistance in a Lolium rigidum population (DAG1) from South Africa. Nucleotide sequencing revealed the existence of at least three EPSPS homologues in the L. rigidum genome and identified a novel proline 106 to leucine substitution (P106L) in 52% DAG1 individuals. This mutation conferred a 1.7-fold resistance increase to glyphosate at the whole plant level. Additionally, a 3.1-fold resistance increase, not linked to metabolism or translocation, was estimated between wild-type P106-DAG1 and P106-STDS sensitive plants. Point accepted mutation analysis suggested that other amino acid substitutions at EPSPS position 106 are likely to be found in nature besides the P106/S/A/T/L point mutations reported to date. This study highlights the importance of minor mechanisms acting additively to confer significant levels of resistance to commercial field rates of glyphosate in weed populations subjected to high selection pressure

Metabolic Pathway of Topramezone in Multiple-Resistant Waterhemp (Amaranthus tuberculatus) Differs From Naturally Tolerant Maize

Waterhemp [Amaranthus tuberculatus (Moq.) Sauer] is a problematic dicot weed in maize, soybean, and cotton production in the United States. Waterhemp has evolved resistance to several commercial herbicides that inhibit the 4-hydroxyphenylpyruvate-dioxygenase (HPPD) enzyme in sensitive dicots, and research to date has shown that HPPD-inhibitor resistance is conferred by rapid oxidative metabolism of the parent compound in resistant populations. Mesotrione and tembotrione (both triketones) have been used exclusively to study HPPD-inhibitor resistance mechanisms in waterhemp and a related species, A. palmeri (S. Wats.), but the commercial HPPD inhibitor topramezone (a pyrazolone) has not been investigated from a mechanistic standpoint despite numerous reports of cross-resistance in the field and greenhouse. The first objective of our research was to determine if two multiple herbicide-resistant (MHR) waterhemp populations (named NEB and SIR) metabolize topramezone more rapidly than two HPPD inhibitor-sensitive waterhemp populations (named SEN and ACR). Our second objective was to determine if initial topramezone metabolite(s) detected in MHR waterhemp are qualitatively different than those formed in maize. An excised leaf assay and whole-plant study investigated initial rates of topramezone metabolism (&lt;24 h) and identified topramezone metabolites at 48 hours after treatment (HAT), respectively, in the four waterhemp populations and maize. Results indicated both MHR waterhemp populations metabolized more topramezone than the sensitive (SEN) population at 6 HAT, while only the SIR population metabolized more topramezone than SEN at 24 HAT. Maize metabolized more topramezone than any waterhemp population at each time point examined. LC-MS analysis of topramezone metabolites at 48 HAT showed maize primarily formed desmethyl and benzoic acid metabolites, as expected based on published reports, whereas SIR formed two putative hydroxylated metabolites. Subsequent LC-MS/MS analyses identified both hydroxytopramezone metabolites in SIR as different hydroxylation products of the isoxazole ring, which were also present in maize 48 HAT but at very low levels. These results indicate that SIR initially metabolizes and detoxifies topramezone in a different manner than tolerant maize

A 96-well DNase I footprinting screen for drug–DNA interactions

The established protocol for DNase I footprinting has been modified to allow multiple parallel reactions to be rapidly performed in 96-well microtitre plates. By scrutinizing every aspect of the traditional method and making appropriate modifications it has been possible to considerably reduce the time, risk of sample loss and complexity of footprinting, whilst dramatically increasing the yield of data (30-fold). A semi-automated analysis system has also been developed to present footprinting data as an estimate of the binding affinity of each tested compound to any base pair in the assessed DNA sequence, giving an intuitive ‘one compound–one line’ scheme. Here, we demonstrate the screening capabilities of the 96-well assay and the subsequent data analysis using a series of six pyrrolobenzodiazepine-polypyrrole compounds and human Topoisomerase II alpha promoter DNA. The dramatic increase in throughput, quantified data and decreased handling time allow, for the first time, DNase I footprinting to be used as a screening tool to assess DNA-binding agents