552 resultados para BIOLOGISTS
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The cell:cell bond between an immune cell and an antigen presenting cell is a necessary event in the activation of the adaptive immune response. At the juncture between the cells, cell surface molecules on the opposing cells form non-covalent bonds and a distinct patterning is observed that is termed the immunological synapse. An important binding molecule in the synapse is the T-cell receptor (TCR), that is responsible for antigen recognition through its binding with a major-histocompatibility complex with bound peptide (pMHC). This bond leads to intracellular signalling events that culminate in the activation of the T-cell, and ultimately leads to the expression of the immune eector function. The temporal analysis of the TCR bonds during the formation of the immunological synapse presents a problem to biologists, due to the spatio-temporal scales (nanometers and picoseconds) that compare with experimental uncertainty limits. In this study, a linear stochastic model, derived from a nonlinear model of the synapse, is used to analyse the temporal dynamics of the bond attachments for the TCR. Mathematical analysis and numerical methods are employed to analyse the qualitative dynamics of the nonequilibrium membrane dynamics, with the specic aim of calculating the average persistence time for the TCR:pMHC bond. A single-threshold method, that has been previously used to successfully calculate the TCR:pMHC contact path sizes in the synapse, is applied to produce results for the average contact times of the TCR:pMHC bonds. This method is extended through the development of a two-threshold method, that produces results suggesting the average time persistence for the TCR:pMHC bond is in the order of 2-4 seconds, values that agree with experimental evidence for TCR signalling. The study reveals two distinct scaling regimes in the time persistent survival probability density prole of these bonds, one dominated by thermal uctuations and the other associated with the TCR signalling. Analysis of the thermal fluctuation regime reveals a minimal contribution to the average time persistence calculation, that has an important biological implication when comparing the probabilistic models to experimental evidence. In cases where only a few statistics can be gathered from experimental conditions, the results are unlikely to match the probabilistic predictions. The results also identify a rescaling relationship between the thermal noise and the bond length, suggesting a recalibration of the experimental conditions, to adhere to this scaling relationship, will enable biologists to identify the start of the signalling regime for previously unobserved receptor:ligand bonds. Also, the regime associated with TCR signalling exhibits a universal decay rate for the persistence probability, that is independent of the bond length.
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Case-based Reasoning's (CBR) origins were stimulated by a desire to understand how people remember information and are in turn reminded of information, and that subsequently it was recognized that people commonly solve problems by remembering how they solved similar problems in the past. Thus CBR became an appropriate way to find out the most suitable solution method for a new problem based on the old methods for the same or even similar problems. The research highlights how to use CBR to aid biologists in finding the best method to cryo preserve algae. The study found CBR could be used successfully to find the similarity percentage between the new algae and old cases in the case base. The prediction result showed approximately 93.75% accuracy, which proves the CBR system can offer appropriate recommendations for most situations. © 2011 IEEE.
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Why the leaves of many woody species accumulate anthocyanins prior to being shed has long puzzled biologists because it is unclear what effects anthocyanins may have on leaf function. Here, we provide evidence for red-osier dogwood (Cornus stolonifera) that anthocyanins form a pigment layer in the palisade mesophyll layer that decreases light capture by chloroplasts. Measurements of leaf absorbance demonstrated that red-senescing leaves absorbed more light of blue-green to orange wavelengths (495–644 nm) compared with yellow-senescing leaves. Using chlorophyll a fluorescence measurements, we observed that maximum photosystem II (PSII) photon yield of red-senescing leaves recovered from a high-light stress treatment, whereas yellow-senescing leaves failed to recover after 6 h of dark adaptation, which suggests photo-oxidative damage. Because no differences were observed in light response curves of effective PSII photon yield for red- and yellow-senescing leaves, differences between red- and yellow-senescing cannot be explained by differences in the capacities for photochemical and non-photochemical light energy dissipation. A role of anthocyanins as screening pigments was explored further by measuring the responses PSII photon yield to blue light, which is preferentially absorbed by anthocyanins, versus red light, which is poorly absorbed. We found that dark-adapted PSII photon yield of red-senescing leaves recovered rapidly following illumination with blue light. However, red light induced a similar, prolonged decrease in PSII photon yield in both red- and yellow-senescing leaves. We suggest that optical masking of chlorophyll by anthocyanins reduces risk of photo-oxidative damage to leaf cells as they senesce, which otherwise may lower the efficiency of nutrient retrieval from senescing autumn leaves.
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The primary aim of this dissertation is to develop data mining tools for knowledge discovery in biomedical data when multiple (homogeneous or heterogeneous) sources of data are available. The central hypothesis is that, when information from multiple sources of data are used appropriately and effectively, knowledge discovery can be better achieved than what is possible from only a single source. ^ Recent advances in high-throughput technology have enabled biomedical researchers to generate large volumes of diverse types of data on a genome-wide scale. These data include DNA sequences, gene expression measurements, and much more; they provide the motivation for building analysis tools to elucidate the modular organization of the cell. The challenges include efficiently and accurately extracting information from the multiple data sources; representing the information effectively, developing analytical tools, and interpreting the results in the context of the domain. ^ The first part considers the application of feature-level integration to design classifiers that discriminate between soil types. The machine learning tools, SVM and KNN, were used to successfully distinguish between several soil samples. ^ The second part considers clustering using multiple heterogeneous data sources. The resulting Multi-Source Clustering (MSC) algorithm was shown to have a better performance than clustering methods that use only a single data source or a simple feature-level integration of heterogeneous data sources. ^ The third part proposes a new approach to effectively incorporate incomplete data into clustering analysis. Adapted from K-means algorithm, the Generalized Constrained Clustering (GCC) algorithm makes use of incomplete data in the form of constraints to perform exploratory analysis. Novel approaches for extracting constraints were proposed. For sufficiently large constraint sets, the GCC algorithm outperformed the MSC algorithm. ^ The last part considers the problem of providing a theme-specific environment for mining multi-source biomedical data. The database called PlasmoTFBM, focusing on gene regulation of Plasmodium falciparum, contains diverse information and has a simple interface to allow biologists to explore the data. It provided a framework for comparing different analytical tools for predicting regulatory elements and for designing useful data mining tools. ^ The conclusion is that the experiments reported in this dissertation strongly support the central hypothesis.^
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Background: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. Results: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. Conclusions: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations.
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Background Post transcriptional gene silencing (PTGS) is a mechanism harnessed by plant biologists to knock down gene expression. siRNAs contribute to PTGS that are synthesized from mRNAs or viral RNAs and function to guide cellular endoribonucleases to target mRNAs for degradation. Plant biologists have employed electroporation to deliver artificial siRNAs to plant protoplasts to study gene expression mechanisms at the single cell level. One drawback of electroporation is the extensive loss of viable protoplasts that occurs as a result of the transfection technology. Results We employed fluorescent conjugated polymer nanoparticles (CPNs) to deliver siRNAs and knockdown a target gene in plant protoplasts. CPNs are non toxic to protoplasts, having little impact on viability over a 72 h period. Microscopy and flow cytometry reveal that CPNs can penetrate protoplasts within 2 h of delivery. Cellular uptake of CPNs/siRNA complexes were easily monitored using epifluorescence microscopy. We also demonstrate that CPNs can deliver siRNAs targeting specific genes in the cellulose biosynthesis pathway (NtCesA-1a and NtCesA-1b). Conclusions While prior work showed that NtCesA-1 is a factor involved in cell wall synthesis in whole plants, we demonstrate that the same gene plays an essential role in cell wall regeneration in isolated protoplasts. Cell wall biosynthesis is central to cell elongation, plant growth and development. The experiments presented here shows that NtCesA is also a factor in cell viability. We show that CPNs are valuable vehicles for delivering siRNAs to plant protoplasts to study vital cellular pathways at the single cell level.
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Background The infraorder Anomura has long captivated the attention of evolutionary biologists due to its impressive morphological diversity and ecological adaptations. To date, 2500 extant species have been described but phylogenetic relationships at high taxonomic levels remain unresolved. Here, we reconstruct the evolutionary history—phylogeny, divergence times, character evolution and diversification—of this speciose clade. For this purpose, we sequenced two mitochondrial (16S and 12S) and three nuclear (H3, 18S and 28S) markers for 19 of the 20 extant families, using traditional Sanger and next-generation 454 sequencing methods. Molecular data were combined with 156 morphological characters in order to estimate the largest anomuran phylogeny to date. The anomuran fossil record allowed us to incorporate 31 fossils for divergence time analyses. Results Our best phylogenetic hypothesis (morphological + molecular data) supports most anomuran superfamilies and families as monophyletic. However, three families and eleven genera are recovered as para- and polyphyletic. Divergence time analysis dates the origin of Anomura to the Late Permian ~259 (224–296) MYA with many of the present day families radiating during the Jurassic and Early Cretaceous. Ancestral state reconstruction suggests that carcinization occurred independently 3 times within the group. The invasion of freshwater and terrestrial environments both occurred between the Late Cretaceous and Tertiary. Diversification analyses found the speciation rate to be low across Anomura, and we identify 2 major changes in the tempo of diversification; the most significant at the base of a clade that includes the squat-lobster family Chirostylidae. Conclusions Our findings are compared against current classifications and previous hypotheses of anomuran relationships. Many families and genera appear to be poly- or paraphyletic suggesting a need for further taxonomic revisions at these levels. A divergence time analysis provides key insights into the origins of major lineages and events and the timing of morphological (body form) and ecological (habitat) transitions. Living anomuran biodiversity is the product of 2 major changes in the tempo of diversification; our initial insights suggest that the acquisition of a crab-like form did not act as a key innovation.
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Following the launch of the "Marion Dufresne 1", first supply ship of the Terres Australes and Antarctiques Françaises and part time oceanographic vessel in the Indian Ocean, a new marine geology program was developped at the Laboratoire de Géologie, MNHN. The first oceanographic cruise of the "Marion Dufresne 1" started in 1973 in the Southwestern Indian Ocean (OSIRIS I cruise). Forty piston-cores recovered nearly 200 m of sediments consisting in the first of the 450 cores of the Indian Ocean collection now deposited at the Museum. L. Leclaire being Director from 1980 to 1991, a multidisciplinary team (including sedimentologists and micropaleontologists) was involved in many oceanographic cruises in the Indian Ocean. Marine sedimentology was developped during annual cruises programs in collaboration with geophysicists, geochemists, and biologists. In 1995, the "Marion Dufresne 2" replaced the initial "Marion Dufresne 1".
Resumo:
Oxygen equilibrium curves have been widely used to understand oxygen transport in numerous organisms. A major challenge has been to monitor oxygen binding characteristics and concomitant pH changes as they occur in vivo, in limited sample volumes. Here we report a technique allowing highly resolved and simultaneous monitoring of pH and blood pigment saturation in minute blood volumes. We equipped a gas diffusion chamber with a broad range fibre optic spectrophotometer and a micro-pH optode and recorded changes of pigment oxygenation along PO2 and pH gradients to test the setup. Oxygen binding parameters derived from measurements in only 15 µl of haemolymph from the cephalopod Octopus vulgaris showed low instrumental error (0.93%) and good agreement with published data. Broad range spectra, each resolving 2048 data points, provided detailed insight into the complex absorbance characteristics of diverse blood types. After consideration of photobleaching and intrinsic fluorescence, pH optodes yielded accurate recordings and resolved a sigmoidal shift of 0.03 pH units in response to changing PO2 from 0-21 kPa. Highly resolved continuous recordings along pH gradients conformed to stepwise measurements at low rates of pH changes. In this study we showed that a diffusion chamber upgraded with a broad range spectrophotometer and an optical pH sensor accurately characterizes oxygen binding with minimal sample consumption and manipulation. We conclude that the modified diffusion chamber is highly suitable for experimental biologists who demand high flexibility, detailed insight into oxygen binding as well as experimental and biological accuracy combined in a single set up.
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Funding: This work was supported by the Swiss National Science Foundation [grants PPOA-102913 and 3100AO_120517 to AR and 31003A_124988 to PB). © 2015. Published by The Company of Biologists Ltd.
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© 2016. Published by The Company of Biologists Ltd.
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Bacteria living on and in leaves and roots influence many aspects of plant health, so the extent of a plant's genetic control over its microbiota is of great interest to crop breeders and evolutionary biologists. Laboratory-based studies, because they poorly simulate true environmental heterogeneity, may misestimate or totally miss the influence of certain host genes on the microbiome. Here we report a large-scale field experiment to disentangle the effects of genotype, environment, age and year of harvest on bacterial communities associated with leaves and roots of Boechera stricta (Brassicaceae), a perennial wild mustard. Host genetic control of the microbiome is evident in leaves but not roots, and varies substantially among sites. Microbiome composition also shifts as plants age. Furthermore, a large proportion of leaf bacterial groups are shared with roots, suggesting inoculation from soil. Our results demonstrate how genotype-by-environment interactions contribute to the complexity of microbiome assembly in natural environments.
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Scientists planning to use underwater stereoscopic image technologies are often faced with numerous problems during the methodological implementations: commercial equipment is too expensive; the setup or calibration is too complex; or the imaging processing (i.e. measuring objects in the stereo-images) is too complicated to be performed without a time-consuming phase of training and evaluation. The present paper addresses some of these problems and describes a workflow for stereoscopic measurements for marine biologists. It also provides instructions on how to assemble an underwater stereo-photographic system with two digital consumer cameras and gives step-by-step guidelines for setting up the hardware. The second part details a software procedure to correct stereo-image pairs for lens distortions, which is especially important when using cameras with non-calibrated optical units. The final part presents a guide to the process of measuring the lengths (or distances) of objects in stereoscopic image pairs. To reveal the applicability and the restrictions of the described systems and to test the effects of different types of camera (a compact camera and an SLR type), experiments were performed to determine the precision and accuracy of two generic stereo-imaging units: a diver-operated system based on two Olympus Mju 1030SW compact cameras and a cable-connected observatory system based on two Canon 1100D SLR cameras. In the simplest setup without any correction for lens distortion, the low-budget Olympus Mju 1030SW system achieved mean accuracy errors (percentage deviation of a measurement from the object's real size) between 10.2 and -7.6% (overall mean value: -0.6%), depending on the size, orientation and distance of the measured object from the camera. With the single lens reflex (SLR) system, very similar values between 10.1% and -3.4% (overall mean value: -1.2%) were observed. Correction of the lens distortion significantly improved the mean accuracy errors of either system. Even more, system precision (spread of the accuracy) improved significantly in both systems. Neither the use of a wide-angle converter nor multiple reassembly of the system had a significant negative effect on the results. The study shows that underwater stereophotography, independent of the system, has a high potential for robust and non-destructive in situ sampling and can be used without prior specialist training.
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The domestication of plants and animals marks one of the most significant transitions in human, and indeed global, history. Traditionally, study of the domestication process was the exclusive domain of archaeologists and agricultural scientists; today it is an increasingly multidisciplinary enterprise that has come to involve the skills of evolutionary biologists and geneticists. Although the application of new information sources and methodologies has dramatically transformed our ability to study and understand domestication, it has also generated increasingly large and complex datasets, the interpretation of which is not straightforward. In particular, challenges of equifinality, evolutionary variance, and emergence of unexpected or counter-intuitive patterns all face researchers attempting to infer past processes directly from patterns in data. We argue that explicit modeling approaches, drawing upon emerging methodologies in statistics and population genetics, provide a powerful means of addressing these limitations. Modeling also offers an approach to analyzing datasets that avoids conclusions steered by implicit biases, and makes possible the formal integration of different data types. Here we outline some of the modeling approaches most relevant to current problems in domestication research, and demonstrate the ways in which simulation modeling is beginning to reshape our understanding of the domestication process.
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Seals must manage their energy reserves carefully while they fast on land to ensure that they go to sea with sufficient fuel to sustain them until they find food. Glucocorticoids (GCs) have been implicated in the control of fuel metabolism and termination of fasting in pinnipeds. Here we tested the hypothesis that dexamethasone, an artificial GC, increases fat and protein catabolism, and induces departure from the breeding colony in wild, fasting grey seal pups. A single intramuscular dose of dexamethasone completely suppressed cortisol production for 24–72 h, demonstrating activation of GC receptors. In experiment 1, we compared the effects of a single dose of dexamethasone or saline administered 10 days after weaning on fasting mass and body composition changes, cortisol, blood urea nitrogen (BUN) and glucose levels, and timing of departure from the colony. In experiment 2, we investigated the effects of dexamethasone on short-term (5 days) changes in mass loss, body composition and BUN levels. In experiment 1, dexamethasone induced a short-lived increase in mass loss, but there was no difference in timing of departure between dexamethasone- and saline-treated pups (N=10). In experiment 2, dexamethasone increased protein and water loss and prevented a decrease in BUN levels (N=11). Our data suggest changes in cortisol contribute to regulation of protein catabolism in fasting seal pups, irrespective of the sex of the animal, but do not terminate fasting. By affecting the rate of protein depletion, lasting changes in cortisol levels could influence the amount of time seal pups have to find food, and thus may have important consequences for their survival.