Nematocidal effects of a coriander essential oil and five pure principles on the infective larvae of major ovine gastrointestinal nematodes in vitro

The anthelmintic effects of extracted coriander oil and five pure essential oil constituents (geraniol, geranyl acetate, eugenol, methyl iso-eugenol, and linalool) were tested, using larval motility assay, on the third-stage larvae (L3s) of Haemonchus contortus, Trichostrongylus axei, Teladorsagia circumcincta, Trichostrongylus colubriformis, Trichostrongylus vitrinus and Cooperia oncophora. Coriander oil and linalool, a major component of tested coriander oil, showed a strong inhibitory efficacy against all species, except C. oncophora with a half maximal inhibitory concentration (IC50) that ranged from 0.56 to 1.41% for the coriander oil and 0.51 to 1.76% for linalool. The coriander oil and linalool combinations conferred a synergistic anthelmintic effect (combination index [CI] <1) on larval motility comparable to positive control (20 mg/mL levamisole) within 24 h (p < 0.05), reduced IC50 values to 0.11–0.49% and induced a considerable structural damage to L3s. Results of the combined treatment were validated by quantitative fluorometric microplate-based assays using Sytox green, propidium iodide and C12-resazurin, which successfully discriminated live/dead larvae. Only Sytox green staining achieved IC50 values comparable to that of the larval motility assay. The cytotoxicity of the combined coriander oil and linalool on Madin–Darby Canine Kidney cells was evaluated using sulforhodamine-B (SRB) assay and showed no significant cytotoxic effect at concentrations < 1%. These results indicate that testing essential oils and their main components may help to find new potential anthelmintic compounds, while at the same time reducing the reliance on synthetic anthelmintics

qDTY1.1, a major QTL for rice grain yield under reproductive-stage drought stress with a consistent effect in multiple elite genetic backgrounds

<p>Abstract</p> <p>Background</p> <p>Drought is one of the most important abiotic stresses causing drastic reductions in yield in rainfed rice environments. The suitability of grain yield (GY) under drought as a selection criterion has been reported in the past few years. Most of the quantitative trait loci (QTLs) for GY under drought in rice reported so far has been in the background of low-yielding susceptible varieties. Such QTLs have not shown a similar effect in multiple high- yielding drought-susceptible varieties, thus limiting their use in marker-assisted selection. Genetic control of GY under reproductive-stage drought stress (RS) in elite genetic backgrounds was studied in three F_3:4mapping populations derived from crosses of N22, a drought-tolerant <it>aus </it>cultivar, with Swarna, IR64, and MTU1010, three high-yielding popular mega-varieties, with the aim to identify QTLs for GY under RS that show a consistent effect in multiple elite genetic backgrounds. Three populations were phenotyped under RS in the dry seasons (DS) of 2009 and 2010 at IRRI. For genotyping, whole-genome scans for N22/MTU1010 and bulked segregant analysis for N22/Swarna and N22/IR64 were employed using SSR markers.</p> <p>Results</p> <p>A major QTL for GY under RS, <it>qDTY_1.1</it>, was identified on rice chromosome 1 flanked by RM11943 and RM431 in all three populations. In combined analysis over two years, <it>qDTY</it>_{<it>1.1 </it>}showed an additive effect of 29.3%, 24.3%, and 16.1% of mean yield in N22/Swarna, N22/IR64, and N22/MTU1010, respectively, under RS. <it>qDTY</it>_{<it>1.1 </it>}also showed a positive effect on GY in non-stress (NS) situations in N22/Swarna, N22/IR64 over both years, and N22/MTU1010 in DS2009.</p> <p>Conclusions</p> <p>This is the first reported QTL in rice with a major and consistent effect in multiple elite genetic backgrounds under both RS and NS situations. Consistency of the QTL effect across different genetic backgrounds makes it a suitable candidate for use in marker-assisted breeding.</p

Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data

International audienceBACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM) of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52%) corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra-species variability

Strengthening of short splices in RC beams using Post-Tensioned Metal Straps

This paper investigates the effectiveness of a novel and cost-effective strengthening technique using Post-Tensioned Metal Straps (PTMS) at enhancing the bond behaviour of short lap spliced steel bars in reinforced concrete (RC) beams. Twelve RC beams with a short lap splice length of 10d b (d b = bar diameter) at the midspan zone were tested in flexure to examine the bond splitting failure. The effect of confinement (no confinement, internal steel stirrups or external PTMS), bar diameter and concrete cover were examined. The results show that, whilst unconfined control beams failed prematurely due to cover splitting, the use of PTMS confinement enhanced the bond strength of the spliced bars by up to 58 % and resulted in a less brittle behaviour. Based on the test results, a new analytical model is proposed to predict the additional bond strength provided by PTMS confinement. The model should prove useful in the strengthening design of substandard lap spliced RC elements

Assessment of personal care and medical robots from older adults' perspective

Demographic reports indicate that population of older adults is growing significantly over the world and in particular in developed nations. Consequently, there are a noticeable number of demands for certain services such as health-care systems and assistive medical robots and devices. In today's world, different types of robots play substantial roles specifically in medical sector to facilitate human life, especially older adults. Assistive medical robots and devices are created in various designs to fulfill specific needs of older adults. Though medical robots are utilized widely by senior citizens, it is dramatic to find out into what extent assistive robots satisfy their needs and expectations. This paper reviews various assessments of assistive medical robots from older adults' perspectives with the purpose of identifying senior citizen's needs, expectations, and preferences. On the other hand, these kinds of assessments inform robot designers, developers, and programmers to come up with robots fulfilling elderly's needs while improving their life quality

Clinical significance of altered nm23-H1, EGFR, RB and p53 expression in bilharzial bladder cancer

<p>Abstract</p> <p>Background</p> <p>Clinical characterization of bladder carcinomas is still inadequate using the standard clinico-pathological prognostic markers. We assessed the correlation between <it>nm23-H1</it>, <it>Rb, EGFR </it>and <it>p53 </it>in relation to the clinical outcome of patients with muscle invasive bilharzial bladder cancer (MI-BBC).</p> <p>Methods</p> <p><it>nm23-H1</it>, <it>Rb, EGFR and p53 </it>expression was assessed in 59 MI-BBC patients using immunohistochemistry and reverse transcription (RT-PCR) and was correlated to the standard clinico-pathological prognostic factors, patient's outcome and the overall survival (OS) rate.</p> <p>Results</p> <p>Overexpression of <it>EGFR </it>and <it>p53 </it>proteins was detected in 66.1% and 35.6%; respectively. Loss of <it>nm23-H1</it>and <it>Rb </it>proteins was detected in 42.4% and 57.6%; respectively. Increased <it>EGFR and </it>loss of <it>nm23-H1 </it>RNA were detected in 61.5% and 36.5%; respectively. There was a statistically significant correlation between <it>p53 </it>and <it>EGFR </it>overexpression (<it>p </it>< 0.0001), <it>nm23 </it>loss (protein and RNA), lymph node status (<it>p </it>< 0.0001); between the incidence of local recurrence and <it>EGFR </it>RNA overexpression (p= 0.003) as well as between the incidence of metastasis and altered <it>Rb </it>expression (<it>p </it>= 0.026), <it>p53 </it>overexpression (<it>p </it>< 0.0001) and mutation (<it>p </it>= 0.04). Advanced disease stage correlated significantly with increased <it>EGFR </it>(protein and RNA) (<it>p </it>= 0.003 & 0.01), reduced <it>nm23-H1 </it>RNA (<it>p </it>= 0.02), altered <it>Rb </it>(<it>p </it>= 0.023), and <it>p53 </it>overexpression (<it>p </it>= 0.004). OS rates correlated significantly, in univariate analysis, with <it>p53 </it>overexpression (<it>p </it>= 0.011), increased <it>EGFR </it>(protein and RNA, <it>p </it>= 0.034&0.031), <it>nm23-H1 RNA </it>loss (<it>p </it>= 0.021) and aberrations of ≥ 2 genes. However, multivariate analysis showed that only high <it>EGFR </it>overexpression, metastatic recurrence, high tumor grade and the combination of ≥ 2 affected markers were independent prognostic factors.</p> <p>Conclusion</p> <p><it>nm23-H1, EGFR </it>and <it>p53 </it>could be used as prognostic biomarkers in MI-BBC patients. In addition to the standard pathological prognostic factors, a combination of these markers (≥ 2) has synergistic effects in stratifying patients into variable risk groups. The higher is the number of altered biomarkers, the higher will be the risk of disease progression and death.</p

Effect of missing data on multitask prediction methods

There has been a growing interest in multitask prediction in chemoinformatics, helped by the increasing use of deep neural networks in this field. This technique is applied to multitarget data sets, where compounds have been tested against different targets, with the aim of developing models to predict a profile of biological activities for a given compound. However, multitarget data sets tend to be sparse; i.e., not all compound-target combinations have experimental values. There has been little research on the effect of missing data on the performance of multitask methods. We have used two complete data sets to simulate sparseness by removing data from the training set. Different models to remove the data were compared. These sparse sets were used to train two different multitask methods, deep neural networks and Macau, which is a Bayesian probabilistic matrix factorization technique. Results from both methods were remarkably similar and showed that the performance decrease because of missing data is at first small before accelerating after large amounts of data are removed. This work provides a first approximation to assess how much data is required to produce good performance in multitask prediction exercises

Tumor-Infiltrating T Cells Correlate with NY-ESO-1-Specific Autoantibodies in Ovarian Cancer

BACKGROUND: Tumor-infiltrating CD8+ T cells are correlated with prolonged progression-free and overall survival in epithelial ovarian cancer (EOC). A significant fraction of EOC patients mount autoantibody responses to various tumor antigens, however the relationship between autoantibodies and tumor-infiltrating T cells has not been investigated in EOC or any other human cancer. We hypothesized that autoantibody and T cell responses may be correlated in EOC and directed toward the same antigens. METHODOLOGY AND PRINCIPAL FINDINGS: We obtained matched serum and tumor tissue from 35 patients with high-grade serous ovarian cancer. Serum samples were assessed by ELISA for autoantibodies to the common tumor antigen NY-ESO-1. Tumor tissue was examined by immunohistochemistry for expression of NY-ESO-1, various T cell markers (CD3, CD4, CD8, CD25, FoxP3, TIA-1 and Granzyme B) and other immunological markers (CD20, MHC class I and MHC class II). Lymphocytic infiltrates varied widely among tumors and included cells positive for CD3, CD8, TIA-1, CD25, FoxP3 and CD4. Twenty-six percent (9/35) of patients demonstrated serum IgG autoantibodies to NY-ESO-1, which were positively correlated with expression of NY-ESO-1 antigen by tumor cells (r = 0.57, p = 0.0004). Autoantibodies to NY-ESO-1 were associated with increased tumor-infiltrating CD8+, CD4+ and FoxP3+ cells. In an individual HLA-A2+ patient with autoantibodies to NY-ESO-1, CD8+ T cells isolated from solid tumor and ascites were reactive to NY-ESO-1 by IFN-gamma ELISPOT and MHC class I pentamer staining. CONCLUSION AND SIGNIFICANCE: We demonstrate that tumor-specific autoantibodies and tumor-infiltrating T cells are correlated in human cancer and can be directed against the same target antigen. This implies that autoantibodies may collaborate with tumor-infiltrating T cells to influence clinical outcomes in EOC. Furthermore, serological screening methods may prove useful for identifying clinically relevant T cell antigens for immunotherapy