DIVERSITY OF FUNGI IN THE ALLIUM URSINUM L COVERED SOIL FOREST

In the soil,ecosystem there are differences in the diversity and spatial distribution of the fungal community. Forest soil samples were harvested in the spring season from the area of influence of plants of Allium ursinum L., in the western part of the country.The study of fungal diversity was carried out on the "soil grain method" on the sifted and ungrounded soil samples. The composition of fungal species is diverse, but there are also repetions (rehearsals) where the number of species is limited. The species present in both forest soil samples is Circinellaspp, followed by Penicillium spp and Aspergillus spp, the latter being isolated only from the sifted soil sample.The low-frequency species are: Torulaherbarum (species isolated from both soil samples), Chaetomium spirale (highlighted only in sampled (sifted) soil), Fusarium spp, Helminthosporiumspp and Mortierellamonospora, the last species isolated from the unsifted soil sample.Â

MAID : An effect size based model for microarray data integration across laboratories and platforms

<p>Abstract</p> <p>Background</p> <p>Gene expression profiling has the potential to unravel molecular mechanisms behind gene regulation and identify gene targets for therapeutic interventions. As microarray technology matures, the number of microarray studies has increased, resulting in many different datasets available for any given disease. The increase in sensitivity and reliability of measurements of gene expression changes can be improved through a systematic integration of different microarray datasets that address the same or similar biological questions.</p> <p>Results</p> <p>Traditional effect size models can not be used to integrate array data that directly compare treatment to control samples expressed as log ratios of gene expressions. Here we extend the traditional effect size model to integrate as many array datasets as possible. The extended effect size model (MAID) can integrate any array datatype generated with either single or two channel arrays using either direct or indirect designs across different laboratories and platforms. The model uses two standardized indices, the standard effect size score for experiments with two groups of data, and a new standardized index that measures the difference in gene expression between treatment and control groups for one sample data with replicate arrays. The statistical significance of treatment effect across studies for each gene is determined by appropriate permutation methods depending on the type of data integrated. We apply our method to three different expression datasets from two different laboratories generated using three different array platforms and two different experimental designs. Our results indicate that the proposed integration model produces an increase in statistical power for identifying differentially expressed genes when integrating data across experiments and when compared to other integration models. We also show that genes found to be significant using our data integration method are of direct biological relevance to the three experiments integrated.</p> <p>Conclusion</p> <p>High-throughput genomics data provide a rich and complex source of information that could play a key role in deciphering intricate molecular networks behind disease. Here we propose an extension of the traditional effect size model to allow the integration of as many array experiments as possible with the aim of increasing the statistical power for identifying differentially expressed genes.</p

Colour reconnections in Herwig++

We describe the implementation details of the colour reconnection model in the event generator Herwig++. We study the impact on final-state observables in detail and confirm the model idea from colour preconfinement on the basis of studies within the cluster hadronization model. Moreover, we show that the description of minimum bias and underlying event data at the LHC is improved with this model and present results of a tune to available data.Comment: 19 pages, 21 figures, 2 tables. Matches with published versio

Uticaj intenziteta parazitske infekcije sa Strongyloides papillosus i terapije albendazolom na biohemijske parametre u krvi ovaca

The aim of this report was to study the biochemical parameters in sheep blood under conditions of various intensities of parasitic infection with Strongyloides papillosus, as well as after therapy with albendazole (ABZ). Investigations were performed on sheep of the Würtemberg race (n = 30) in which were detected mild, moderate and high intensities of parasitic infection with S. papillosus. The control group (n = 10) was composed of sheep negative to parasitic infections. The degree and type of changes were monitored by determining the concentrations of glucose, total proteins, albumin, A/G ratio, AST, urea, total bilirubin, calcium, phosphorus, total LDH activity and isoenzymatic LDH1-5 distributions. On the basis of the obtained results, we determined, through isoenzymatic LDH distribution, that during parasitic infection with S. papillosus, there is ongoing damage to the liver, heart muscle and lung, while after therapy with ABZ, the liver suffers the most damage. The concentration of glucose, total proteins and albumin fell linearly with the rise in the intensity of parasitic infection (p LT 0.05), while after therapy with ABZ, the fall of these parameters was at a statistically significantly higher level (p LT 0.01). The activity of AST, concentration of urea and total bilirubin also rose linearly with the intensity of parasitic infection (p LT 0.05). After therapy with ABZ, the activity of AST and the concentration of total bilirubin were at a statistically significantly higher level (p LT 0.001), while the concentration of urea retained the same levels as in the case of parasitic infection. Values of calcium concentrations (p>0.05) and phosphorus (p LT 0.05) also fall linearly with the rise of the intesity of the parasitic infection. The trend in the concentration fall of these macroelements, continues also after treatment with albendazole (p LT 0.001). Having in mind our previous studies in the field of oxidative stress and phenomena lying behind these changes, we strongly recommend that in antiparasitic treatment protocols, beside antihelminthics, compounds with antioxidative properties should also be used.Cilj ovog rada je bio da se ispitaju biohemijski parametri u krvi ovaca u uslovima različitog intenziteta parazitske infekcije sa Strongyloides papillosus, kao i nakon terapije sa albendazolom (ABZ). Istraživanje je izvedeno na ovcama Wurtemberg rase (n = 30) kod kojih je utvrđen blagi, srednji i visoki intenzitet parazitske infekcije sa S. papillosus. Kontrolnu grupu (n = 10) činile su ovce negativne na prisustvo parazitske infekcije. Stepen i vrsta promene praćeni su određivanjem koncentracije glukoze, ukupnih proteina, albumina, A/G ratio, AST, urea, ukupnog bilirubina, kalcijuma, fosfora, ukupne aktivnosti LDH i izoenzimske distribucije LDH1-5. Na osnovu dobijenih rezultata utvrdili smo, preko izoenzimske distribucije LDH, da u toku parazitske infekcije sa S. papillosus dolazi do oštećenja jetre, srčanog mišića i pluća, dok nakon terapije sa ABZ jetra je organ koji je najviše oštećen. Koncentracija glukoze, ukupnih proteina i albumina linearno je opadala sa rastom intenziteta parazitske infekcije (p LT 0.05), a nakon terapije sa ABZ pad koncentracije ovih parametara bio je na statistički značajnom većem nivou (p LT 0.01). Aktivnost AST, koncentracija uree i ukupnog bilirubina takođe su linearno rasle sa intenzitetom parazitske infekcije (p LT 0.05). Nakon terapije sa ABZ aktivnost AST i koncentracija ukupnog bilirubina bile su na statistički značajno većem nivou (p LT 0.001), dok je koncentracija uree zadržala iste nivoe kao u slučaju parazitske infekcije. Vrednosti koncentracija kalcijuma (p > 0.05) i fosfora (p LT 0.05) takođe linearno opadaju sa rastom intenziteta parazitske infekcije. Trend pada koncentracije ovih makroelemenata, nastavlja se i nakon terapije sa albendazolom (p LT 0.001). Imajući u vidu naša prethodna istraživanja na polju oksidativnog stresa, fenomena koji se nalazi u osnovi ovih promena, strogo preporučujemo da se u antiparazitske protokole, pored antihelmintika koriste i preparati sa antioksidativnim osobinama

Modelling Smart Grid Technologies in Optimisation Problems for Electricity Grids

Copyright © 2023 by the authors. The decarbonisation of the electricity grid is expected to create new electricity flows. As a result, it may require that network planners make a significant amount of investments in the electricity grids over the coming decades so as to allow the accommodation of these new flows in a way that both the thermal and voltage network constraints are respected. These investments may include a portfolio of infrastructure assets consisting of traditional technologies and smart grid technologies. One associated key challenge is the presence of uncertainty around the location, the timing, and the amount of new demand or generation connections. This uncertainty unavoidably introduces risk into the investment decision-making process as it may lead to inefficient investments and inevitably give rise to excessive investment costs. Smart grid technologies have properties that enable them to be regarded as investment options, which can allow network planners to hedge against the aforementioned uncertainty. This paper focuses on key smart technologies by providing a critical literature review and presenting the latest mathematical modelling that describes their operation.This research received no external funding

Local charge compensation from colour preconfinement as a key to the dynamics of hadronization

If, as is commonly accepted, the colour-singlet, `preconfined', perturbative clusters are the primary units of hadronization, then the electric charge is necessarily compensated locally at the scale of the typical cluster mass. As a result, the minijet electric charge is suppressed at scales that are greater than the cluster mass. We hence argue, and demonstrate by means of Monte Carlo simulations using HERWIG, that the scale at which charge compensation is violated is close to the mass of the clusters involved in hadronization, and its measurement would provide a clue to resolving the nature of the dynamics. We repeat the calculation using PYTHIA and find that the numbers produced by the two generators are similar. The cluster mass distribution is sensitive to soft emission that is considered unresolved in the parton shower phase. We discuss how the description of the splitting of large clusters in terms of unresolved emission modifies the algorithm of HERWIG, and relate the findings to the yet unknown underlying nonperturbative mechanism. In particular, we propose a form of $\alpha_S$ that follows from a power-enhanced beta function, and discuss how this $\alpha_S$ that governs unresolved emission may be related to power corrections. Our findings are in agreement with experimental data.Comment: 37 pages, 20 figure

A statistical framework for integrating two microarray data sets in differential expression analysis

<p>Abstract</p> <p>Background</p> <p>Different microarray data sets can be collected for studying the same or similar diseases. We expect to achieve a more efficient analysis of differential expression if an efficient statistical method can be developed for integrating different microarray data sets. Although many statistical methods have been proposed for data integration, the genome-wide concordance of different data sets has not been well considered in the analysis.</p> <p>Results</p> <p>Before considering data integration, it is necessary to evaluate the genome-wide concordance so that misleading results can be avoided. Based on the test results, different subsequent actions are suggested. The evaluation of genome-wide concordance and the data integration can be achieved based on the normal distribution based mixture models.</p> <p>Conclusion</p> <p>The results from our simulation study suggest that misleading results can be generated if the genome-wide concordance issue is not appropriately considered. Our method provides a rigorous parametric solution. The results also show that our method is robust to certain model misspecification and is practically useful for the integrative analysis of differential expression.</p

Environmental influence of chemical contaminants on farm animals and rodents (review research)

The presence of chemical environmental pollutants (heavy metals) and their influence on health status of farm animals has been study in long period. We monitored the influence of chemical pollutants on rodents leaving on farms. Heavy metals has special danger for leaving systems, which react with organic molecules to change their structures and function. Heavy metals enter the body through respiratory system, digestive system and skin. The results of our many years of research indicate that there is danger of contamination of animal feed with heavy metals and their position in their body of animals, as well as a negative effect on the reproductive capacity of domestic animals. Heavy metal toxicity general leads to the formation of free radicals, inhibiting the activity of antioxidant defense enzymes as well as glutathione oxidation and the formation malonyl dialdehyde (MDA) as a marker of oxidative stress. Their toxicity stems from the tendency to form covalent bonds with sulfhydryl groups of biomacromolecules or displace certain cofactors, there by inhibiting the activity of certain enzymes. Our recommendation for industrial type farms is to reduce the risk of heavy metals. To introduce multilevel monitoring of the quality of raw materials and final products, as well as to apply adequate protectors against the toxic effect of these agents

Increasing consistency of disease biomarker prediction across datasets

Microarray studies with human subjects often have limited sample sizes which hampers the ability to detect reliable biomarkers associated with disease and motivates the need to aggregate data across studies. However, human gene expression measurements may be influenced by many non-random factors such as genetics, sample preparations, and tissue heterogeneity. These factors can contribute to a lack of agreement among related studies, limiting the utility of their aggregation. We show that it is feasible to carry out an automatic correction of individual datasets to reduce the effect of such 'latent variables' (without prior knowledge of the variables) in such a way that datasets addressing the same condition show better agreement once each is corrected. We build our approach on the method of surrogate variable analysis but we demonstrate that the original algorithm is unsuitable for the analysis of human tissue samples that are mixtures of different cell types. We propose a modification to SVA that is crucial to obtaining the improvement in agreement that we observe. We develop our method on a compendium of multiple sclerosis data and verify it on an independent compendium of Parkinson's disease datasets. In both cases, we show that our method is able to improve agreement across varying study designs, platforms, and tissues. This approach has the potential for wide applicability to any field where lack of inter-study agreement has been a concern. © 2014 Chikina, Sealfon