6 resultados para diversity indices

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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In order to study the colonization and development of moss mites (Oribatida) communities in a Scots pine forest of a reclaimed limestone mine dump in Northern Poland, 3 plots from the dump were chosen. The selected plots differed in age, 5 years old, 35 and 50 years old. From a total of 30 samples 499 mites (Acari) were extracted in Tullgren funnel from which 262 were Oribatida. Abundance (N) was analyzed in all mites and after determining the species of both, juvenile and adult stages of oribatids, the following indices were analyzed: Abundance (N), Dominance (D), Species diversity (S), Species richness (s) and Shannon’s diversity index (H). Regarding to the results obtained; oribatid mites were dominant with the highest abundance in all assemblages (Plot 1: 139 Oribatida /299 Acari. Plot 2: 40/55 and Plot 3: 83/145). Tectocepheus velatus showed a very high dominance (45,99%) in plot 1; the highest value for Shannon’s diversity index belonged to plot 3. On the other hand, juvenile’s percentage was significantly higher than adult’s percentage, especially at plot 2 (95,02%). These results made us to conclude that the high abundance of oribatids in the youngest forest is due to T. velatus’s high abundance and that plot 3 is the best habitat for mites. Finally, the high occurrence of juvenile stages requires keeping on studying the area.

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Este trabajo se encuentra bajo la licencia Creative Commons Attribution 3.0.

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The evaluation and comparison of internal cluster validity indices is a critical problem in the clustering area. The methodology used in most of the evaluations assumes that the clustering algorithms work correctly. We propose an alternative methodology that does not make this often false assumption. We compared 7 internal cluster validity indices with both methodologies and concluded that the results obtained with the proposed methodology are more representative of the actual capabilities of the compared indices.

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In a multi-target complex network, the links (L-ij) represent the interactions between the drug (d(i)) and the target (t(j)), characterized by different experimental measures (K-i, K-m, IC50, etc.) obtained in pharmacological assays under diverse boundary conditions (c(j)). In this work, we handle Shannon entropy measures for developing a model encompassing a multi-target network of neuroprotective/neurotoxic compounds reported in the CHEMBL database. The model predicts correctly >8300 experimental outcomes with Accuracy, Specificity, and Sensitivity above 80%-90% on training and external validation series. Indeed, the model can calculate different outcomes for >30 experimental measures in >400 different experimental protocolsin relation with >150 molecular and cellular targets on 11 different organisms (including human). Hereafter, we reported by the first time the synthesis, characterization, and experimental assays of a new series of chiral 1,2-rasagiline carbamate derivatives not reported in previous works. The experimental tests included: (1) assay in absence of neurotoxic agents; (2) in the presence of glutamate; and (3) in the presence of H2O2. Lastly, we used the new Assessing Links with Moving Averages (ALMA)-entropy model to predict possible outcomes for the new compounds in a high number of pharmacological tests not carried out experimentally.

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Lipoproteins are responsible for cholesterol traffic in humans. Low density lipoprotein (LDL) delivers cholesterol from liver to peripheral tissues. A misleading delivery can lead to the formation of atherosclerotic plaques. LDL has a single protein, apoB-100, that binds to a specific receptor. It is known that the failure associated with a deficient protein-receptor binding leads to plaque formation. ApoB-100 is a large single lipid-associated polypeptide difficulting the study of its structure. IR spectroscopy is a technique suitable to follow the different conformational changes produced in apoB-100 because it is not affected by the size of the protein or the turbidity of the sample. We have analyzed LDL spectra of different individuals and shown that, even if there are not big structural changes, a different pattern in the intensity of the band located around 1617 cm 21 related with strands embedded in the lipid monolayer, can be associated with a different conformational rearrangement that could affect to a protein interacting region with the receptor.