Does the Embedding Chemistry Interact with Tissue?

Resins and resin compounds interact with tissue in two ways, physico-chemically and by chemical reaction. The physico-chemical influences affect both the structure and biological activity of the tissue causing proteins to change shape or phase equilibria to be disrupted by a change in solvent or by the growth of polymer networks within existing biological polymeric structures. Chemical reactivity between tissue and resin components also reduces biological activity by changing either the structure of polymeric matter already present, e.g., crosslinking proteins, grafting hydrophobic resins onto hydrophilic protein backbones, or by modifying the hydrophobicity of specific sites, e.g., acylation of amino groups by hydrophobic anhydrides. The consequences of all these interactions can only be a fall in activity of the tissue leading to longer reaction times and the need for amplification of specific group reaction. Low crosslink densities, moderate temperatures, and partial rather than total removal of water are possible ways of reducing the effects of resin tissue interaction

Serum microRNA array analysis identifies miR-140-3p, miR-33b-3p and miR-671-3p as potential osteoarthritis biomarkers involved in metabolic processes.

Background: MicroRNAs (miRNAs) in circulation have emerged as promising biomarkers. In this study, we aimed to identify a circulating miRNA signature for osteoarthritis (OA) patients and in combination with bioinformatics analysis to evaluate the utility of selected differentially expressed miRNAs in the serum as potential OA biomarkers. Methods: Serum samples were collected from 12 primary OA patients, and 12 healthy individuals were screened using the Agilent Human miRNA Microarray platform interrogating 2549 miRNAs. Receiver Operating Characteristic (ROC) curves were constructed to evaluate the diagnostic performance of the deregulated miRNAs. Expression levels of selected miRNAs were validated by quantitative real-time PCR (qRT-PCR) in all serum and in articular cartilage samples from OA patients (n = 12) and healthy individuals (n = 7). Bioinformatics analysis was used to investigate the involved pathways and target genes for the above miRNAs. Results: We identified 279 differentially expressed miRNAs in the serum of OA patients compared to controls. Two hundred and five miRNAs (73.5%) were upregulated and 74 (26.5%) downregulated. ROC analysis revealed that 77 miRNAs had area under the curve (AUC) > 0.8 and p < 0.05. Bioinformatics analysis in the 77 miRNAs revealed that their target genes were involved in multiple signaling pathways associated with OA, among which FoxO, mTOR, Wnt, pI3K/akt, TGF-β signaling pathways, ECM-receptor interaction, and fatty acid biosynthesis. qRT-PCR validation in seven selected out of the 77 miRNAs revealed 3 significantly downregulated miRNAs (hsa-miR-33b-3p, hsa-miR-671-3p, and hsa-miR-140-3p) in the serum of OA patients, which were in silico predicted to be enriched in pathways involved in metabolic processes. Target-gene analysis of hsa-miR-140-3p, hsa-miR-33b-3p, and hsa-miR-671-3p revealed that InsR and IGFR1 were common targets of all three miRNAs, highlighting their involvement in regulation of metabolic processes that contribute to OA pathology. Hsa-miR-140-3p and hsa-miR-671-3p expression levels were consistently downregulated in articular cartilage of OA patients compared to healthy individuals. Conclusions: A serum miRNA signature was established for the first time using high density resolution miR-arrays in OA patients. We identified a three-miRNA signature, hsa-miR-140-3p, hsa-miR-671-3p, and hsa-miR-33b-3p, in the serum of OA patients, predicted to regulate metabolic processes, which could serve as a potential biomarker for the evaluation of OA risk and progression.Peer reviewedFinal Published versio

Hsp90 orchestrates transcriptional regulation by Hsf1 and cell wall remodelling by MAPK signalling during thermal adaptation in a pathogenic yeast

Acknowledgments We thank Rebecca Shapiro for creating CaLC1819, CaLC1855 and CaLC1875, Gillian Milne for help with EM, Aaron Mitchell for generously providing the transposon insertion mutant library, Jesus Pla for generously providing the hog1 hst7 mutant, and Cathy Collins for technical assistance.Peer reviewedPublisher PD

Growth and nutrient absorption of Cape Gooseberry (Physalis Peruviana L.) in soilless culture

"This is an Author's Accepted Manuscript of an article published in [include the complete citation information for the final version of the article as published in the Journal of Plant Nutrition 2015 March, available online at: http://www.tandfonline.com/10.1080/01904167.2014.934474."Cape gooseberry (Physalis peruviana L.) is a solanaceous plant. The growth and time-course of nutrient accumulation of the plant and its partitioning between roots, stems, leaves, and fruits were examined. The study was conducted analyzing two nutrient solutions in soilless culture under greenhouse conditions during two consecutive seasons. The macronutrient contents were analyzed. On average, the yield was 8.9 t.ha(-1). Growth of the plant until 90 d after transplanting obeys an exponential function of time and the relative growth rate for this period was determined. Nitrogen (N) was the element that showed the highest concentration, corresponding to leaves (4.67%), followed by potassium (K) in stems (4.46%). The highest accumulations of N, phosphorous (P), calcium (Ca), and magnesium (Mg) were found in leaves and of K in the stems. Potassium showed the highest nutrient accumulation (29 g.plant(-1)) and the highest specific uptake rate.Torres Rubio, JF.; Pascual Seva, N.; San Bautista Primo, A.; Pascual España, B.; López Galarza, SV.; Alagarda Pardo, J.; Maroto Borrego, JV. (2015). Growth and nutrient absorption of Cape Gooseberry (Physalis Peruviana L.) in soilless culture. Journal of Plant Nutrition. 38(4):485-496. doi:10.1080/01904167.2014.934474S485496384Bellaloui, N., & Brown, P. H. (1998). Plant and Soil, 198(2), 153-158. doi:10.1023/a:1004343031242Bennett, J. P., Oshima, R. J., & Lippert, L. F. (1979). Effects of ozone on injury and dry matter partitioning in pepper plants. Environmental and Experimental Botany, 19(1), 33-39. doi:10.1016/0098-8472(79)90022-4CAUSTON, D. R. (1991). Plant Growth Analysis: The Variability of Relative Growth Rate Within a Sample. Annals of Botany, 67(2), 137-144. doi:10.1093/oxfordjournals.aob.a088112Convenio MAG-IICA (Ministerio de Agricultura y Ganadería. Institución Interamericana de Cooperación para la Agricultura). 2001. The cape gooseberry (Physalis peruvianaL.Physalis edulis). Subprograma de Cooperación Técnica, Ecuador. Available at: http://www.sica.gov.ec/agronegocios/Biblioteca/Convenio%20MAG%20IICA/productos/uvilla_mag.pdf (Accessed July 2007, in Spanish).El-Tohamy, W. A., El-Abagy, H. M., Abou-Hussein, S. D., & Gruda, N. (2009). Response of Cape gooseberry (Physalis peruviana L.) to nitrogen application under sandy soil conditions. Gesunde Pflanzen, 61(3-4), 123-127. doi:10.1007/s10343-009-0211-0Fresquet, J., Pascual, B., López-Galarza, S., Bautista, S., Baixauli, C., Gisbert, J. M., & Maroto, J. V. (2001). Nutrient uptake of pepino plants in soilless cultivation. The Journal of Horticultural Science and Biotechnology, 76(3), 338-343. doi:10.1080/14620316.2001.11511373Heuvelink, E., Bakker, M. J., Elings, A., Kaarsemaker, R. C., & Marcelis, L. F. M. (2005). EFFECT OF LEAF AREA ON TOMATO YIELD. Acta Horticulturae, (691), 43-50. doi:10.17660/actahortic.2005.691.2Leskovar, D. I., & Cantliffe, D. J. (1993). Comparison of Plant Establishment Method, Transplant, or Direct Seeding on Growth and Yield of Bell Pepper. Journal of the American Society for Horticultural Science, 118(1), 17-22. doi:10.21273/jashs.118.1.17Marcelis, L. F. M. (1993). Fruit growth and biomass allocation to the fruits in cucumber. 1. Effect of fruit load and temperature. Scientia Horticulturae, 54(2), 107-121. doi:10.1016/0304-4238(93)90059-yPuente, L. A., Pinto-Muñoz, C. A., Castro, E. S., & Cortés, M. (2011). Physalis peruviana Linnaeus, the multiple properties of a highly functional fruit: A review. Food Research International, 44(7), 1733-1740. doi:10.1016/j.foodres.2010.09.034Radford, P. J. (1967). Growth Analysis Formulae - Their Use and Abuse1. Crop Science, 7(3), 171. doi:10.2135/cropsci1967.0011183x000700030001xRamadan, M. F., & Moersel, J. T. (2007). Impact of enzymatic treatment on chemical composition, physicochemical properties and radical scavenging activity of goldenberry (Physalis peruviana L.) juice. Journal of the Science of Food and Agriculture, 87(3), 452-460. doi:10.1002/jsfa.2728Ramadan, M. F., & Moersel, J.-T. (2009). Oil extractability from enzymatically treated goldenberry (Physalis peruvianaL.) pomace: range of operational variables. International Journal of Food Science & Technology, 44(3), 435-444. doi:10.1111/j.1365-2621.2006.01511.xSalazar, M. R., Jones, J. W., Chaves, B., & Cooman, A. (2008). A model for the potential production and dry matter distribution of Cape gooseberry (Physalis peruviana L.). Scientia Horticulturae, 115(2), 142-148. doi:10.1016/j.scienta.2007.08.015Scholberg, J., McNeal, B. L., Jones, J. W., Boote, K. J., Stanley, C. D., & Obreza, T. A. (2000). Growth and Canopy Characteristics of Field-Grown Tomato. Agronomy Journal, 92(1), 152. doi:10.2134/agronj2000.921152xTrinchero, G. D., Sozzi, G. O., Cerri, A. M., Vilella, F., & Fraschina, A. A. (1999). Ripening-related changes in ethylene production, respiration rate and cell-wall enzyme activity in goldenberry (Physalis peruviana L.), a solanaceous species. Postharvest Biology and Technology, 16(2), 139-145. doi:10.1016/s0925-5214(99)00011-3Turner, A. (1994). Dry Matter Assimilation and Partitioning in Pepper Cultivars Differing in Susceptibility to Stress-induced Bud and Flower Abscission. Annals of Botany, 73(6), 617-622. doi:10.1006/anbo.1994.1077WILLIAMS, R. F. (1946). The Physiology of Plant Growth with Special Reference to the Concept of Net Assimilation Rate. Annals of Botany, 10(1), 41-72. doi:10.1093/oxfordjournals.aob.a083119Zapata, J.L., A. Saldarriaga, M. Londoño, and C. Díaz. 2002. Cape gooseberry Management in Colombia. Antioquia, Colombia: Rionegro, Programa Nacional de Transferencia de Tecnología Agropecuaria - Corpoica Regional Cuatro (in Spanish).Zerihun, A. (2000). Compensatory Roles of Nitrogen Uptake and Photosynthetic N-use Efficiency in Determining Plant Growth Response to Elevated CO2: Evaluation Using a Functional Balance Model. Annals of Botany, 86(4), 723-730. doi:10.1006/anbo.2000.123

Experimental Demonstration of the Fitness Consequences of an Introduced Parasite of Darwin's Finches

Introduced parasites are a particular threat to small populations of hosts living on islands because extinction can occur before hosts have a chance to evolve effective defenses. An experimental approach in which parasite abundance is manipulated in the field can be the most informative means of assessing a parasite's impact on the host. The parasitic fly Philornis downsi, recently introduced to the Galápagos Islands, feeds on nestling Darwin's finches and other land birds. Several correlational studies, and one experimental study of mixed species over several years, reported that the flies reduce host fitness. Here we report the results of a larger scale experimental study of a single species at a single site over a single breeding season.We manipulated the abundance of flies in the nests of medium ground finches (Geospiza fortis) and quantified the impact of the parasites on nestling growth and fledging success. We used nylon nest liners to reduce the number of parasites in 24 nests, leaving another 24 nests as controls. A significant reduction in mean parasite abundance led to a significant increase in the number of nests that successfully fledged young. Nestlings in parasite-reduced nests also tended to be larger prior to fledging.Our results confirm that P. downsi has significant negative effects on the fitness of medium ground finches, and they may pose a serious threat to other species of Darwin's finches. These data can help in the design of management plans for controlling P. downsi in Darwin's finch breeding populations

Correlation of cell growth and heterologous protein production by Saccharomyces cerevisiae

With the increasing demand for biopharmaceutical proteins and industrial enzymes, it is necessary to optimize the production by microbial fermentation or cell cultures. Yeasts are well established for the production of a wide range of recombinant proteins, but there are also some limitations; e.g., metabolic and cellular stresses have a strong impact on recombinant protein production. In this work, we investigated the effect of the specific growth rate on the production of two different recombinant proteins. Our results show that human insulin precursor is produced in a growth-associated manner, whereas alpha-amylase tends to have a higher yield on substrate at low specific growth rates. Based on transcriptional analysis, we found that the difference in the production of the two proteins as function of the specific growth rate is mainly due to differences in endoplasmic reticulum processing, protein turnover, cell cycle, and global stress response. We also found that there is a shift at a specific growth rate of 0.1 h(-1) that influences protein production. Thus, for lower specific growth rates, the alpha-amylase and insulin precursor-producing strains present similar cell responses and phenotypes, whereas for higher specific growth rates, the two strains respond differently to changes in the specific growth rate

A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB

BACKGROUND: Sharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support. RESULTS: We propose a simple tab-delimited, spreadsheet-based format, MAGE-TAB, which will become a part of the MAGE microarray data standard and can be used for annotating and communicating microarray data in a MIAME compliant fashion. CONCLUSION: MAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML

A Non-Death Role of the Yeast Metacaspase: Yca1p Alters Cell Cycle Dynamics

Caspase proteases are a conserved protein family predominantly known for engaging and executing apoptotic cell death. Nevertheless, in higher eukaryotes, caspases also influence a variety of cell behaviors including differentiation, proliferation and growth control. S. cerevisiae expresses a primordial caspase, yca1, and exhibits apoptosis-like death under certain stresses; however, the benefit of a dedicated death program to single cell organisms is controversial. In the absence of a clear rationale to justify the evolutionary retention of a death only pathway, we hypothesize that yca1 also influences non-apoptotic events. We report that genetic ablation and/or catalytic inactivation of Yca1p leads to a longer G1/S transition accompanied by slower growth in fermentation conditions. Downregulation of Yca1p proteolytic activity also results in failure to arrest during nocodazole treatment, indicating that Yca1p participates in the G2/M mitotic checkpoint. 20s proteasome activity and ROS staining of the Δyca1 strain is indistinguishable from its isogenic control suggesting that putative regulation of the oxidative stress response by Yca1p does not instigate the cell cycle phenotype. Our results demonstrate multiple non-death roles for yca1 in the cell cycle

The Euchromatic and Heterochromatic Landscapes Are Shaped by Antagonizing Effects of Transcription on H2A.Z Deposition

A role for variant histone H2A.Z in gene expression is now well established but little is known about the mechanisms by which it operates. Using a combination of ChIP–chip, knockdown and expression profiling experiments, we show that upon gene induction, human H2A.Z associates with gene promoters and helps in recruiting the transcriptional machinery. Surprisingly, we also found that H2A.Z is randomly incorporated in the genome at low levels and that active transcription antagonizes this incorporation in transcribed regions. After cessation of transcription, random H2A.Z quickly reappears on genes, demonstrating that this incorporation utilizes an active mechanism. Within facultative heterochromatin, we observe a hyper accumulation of the variant histone, which might be due to the lack of transcription in these regions. These results show how chromatin structure and transcription can antagonize each other, therefore shaping chromatin and controlling gene expression

Mining for genotype-phenotype relations in Saccharomyces using partial least squares

<p>Abstract</p> <p>Background</p> <p>Multivariate approaches are important due to their versatility and applications in many fields as it provides decisive advantages over univariate analysis in many ways. Genome wide association studies are rapidly emerging, but approaches in hand pay less attention to multivariate relation between genotype and phenotype. We introduce a methodology based on a BLAST approach for extracting information from genomic sequences and Soft- Thresholding Partial Least Squares (ST-PLS) for mapping genotype-phenotype relations.</p> <p>Results</p> <p>Applying this methodology to an extensive data set for the model yeast <it>Saccharomyces cerevisiae</it>, we found that the relationship between genotype-phenotype involves surprisingly few genes in the sense that an overwhelmingly large fraction of the phenotypic variation can be explained by variation in less than 1% of the full gene reference set containing 5791 genes. These phenotype influencing genes were evolving 20% faster than non-influential genes and were unevenly distributed over cellular functions, with strong enrichments in functions such as cellular respiration and transposition. These genes were also enriched with known paralogs, stop codon variations and copy number variations, suggesting that such molecular adjustments have had a disproportionate influence on <it>Saccharomyces </it>yeasts recent adaptation to environmental changes in its ecological niche.</p> <p>Conclusions</p> <p>BLAST and PLS based multivariate approach derived results that adhere to the known yeast phylogeny and gene ontology and thus verify that the methodology extracts a set of fast evolving genes that capture the phylogeny of the yeast strains. The approach is worth pursuing, and future investigations should be made to improve the computations of genotype signals as well as variable selection procedure within the PLS framework.</p