1000 resultados para Ovariole Number


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A honeybee queen normally mates with 10-20 drones, and reproductive conflicts may arise among a colony's different worker patrilines, especially after a colony has lost its single queen and the workers commence egg laying. In this study, we employed microsatellite markers to study aspects of worker reproductive competition in two queenless Africanized honeybee colonies. First, we determined whether there was a bias among worker patrilines in their maternity of drones and, second, we asked whether this bias could be attributed to differences in the degree of ovary activation of workers. Third, we relate these behavioral and physiological factors to ontogenetic differences between workers with respect to ovariole number. Workers from each of three (colony A) and one (colony B) patrilineal genotypes represented less than 6% of the worker population, yet each produced at least 13% of the drones in a colony, and collectively they produced 73% of the drones. Workers representing these genotypes also had more developed follicles and a greater number of ovarioles per ovary. Across all workers, ovariole development and number were closely correlated. This suggests a strong effect of worker genotype on the development of the ovary already in the postembryonic stages and sets a precedent to adult fertility, so that

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The aim of the present study is to characterize the way worker and queen ovaries differentiate in, Apis mellifera, a species with trophic determination of female castes. A morphological study carried out with light and transmission electron microscopy showed that the differences in ovary development between the two castes begin as soon as the differential nursing of larvae is initiated. The decrease in ovariole number in worker ovaries is due to a process of cell death occurring in germinative cells and autophagic regression of somatic cells in the ovarioles that commence in the third instar larvae and proceed until the fifth instar where the process is more intense. Germinative cell death leads to ovariole disintegration and incorporation of the remaining somatic cells of the latter into the stromatic cells in such a way that the total volume of the ovary is little affected during larval development, although the ovariole number decreases. By the end of the larval stage, loss of cells is observed among the stromatic cells of the ovary. As a result, the ovary starts to decrease in volume and takes on the adult form.

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A influência do hormônio juvenil sobre o desenvolvimento do ovário de larvas de operárias de Apis mellifera foi analisada levando em conta a determinação trófica das castas, segundo a qual a alimentação larval é controlada pelas operárias de maneira a promover uma diferenciação de castas controlada pela produção e disponibilidade desse hormônio. A hipótese testada é que a ação do hormônio juvenil seja capaz de proteger ou prevenir a degeneração nos ovários das larvas de operárias. Foi feita aplicação tópica de 1 ml de hormônio dissolvido em hexano na concentração de 1 mg/ml do segundo até o quinto dia de vida larval, e a morfologia dos ovários avaliada nos dias subseqüentes à aplicação até ao sexto dia de vida larval. Como controles foram utilizadas larvas nas quais se aplicou 1 ml de hexano e larvas que não receberam nenhum tratamento. Constatou-se que o efeito do hormônio juvenil varia conforme a idade larval em que é aplicado e que este efeito foi maior quando a aplicação foi feita no terceiro dia de vida larval.

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Pós-graduação em Ciências Biológicas (Biologia Celular e Molecular) - IBRC

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Species coexist using the same nutritional resource by partitioning it either in space or time, but few studies explore how species-specific nutritional requirements allow partitioning. Zaprionus indianus and Drosophila simulans co-exist in figs by invading the fruit at different stages; Z. indianus colonizes ripe figs, whereas D. simulans oviposits in decaying fruit. Larvae feed on yeast growing on the fruit, which serves as their primary protein source. Because yeast populations increase as fruit decays, we find that ripe fruit has lower protein content than rotting fruit. Therefore, we hypothesized that Z. indianus and D. simulans larvae differ in their dietary requirements for protein. We used nutritional geometry to assess the effects of protein and carbohydrate concentration in the larval diet on life history characters in both species. Survival, development time, and ovariole number respond differently to the composition of the larval diet, with Z. indianus generally performing better across a wider range of protein concentrations. Correspondingly, we found that Z. indianus females preferred to lay eggs on low protein foods, while D. simulans females chose higher protein foods for oviposition when competing with Z. indianus. We propose the different nutritional requirements and oviposition preference of these two species allows them to temporally partition their habitat.

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Organisms from slime moulds to humans carefully regulate their macronutrient intake to optimize a wide range of life history characters including survival, stress resistance, and reproductive success. However, life history characters often differ in their response to nutrition, forcing organisms to make foraging decisions while balancing the trade-offs between these effects. To date, we have a limited understanding of how the nutritional environment shapes the relationship between life history characters and foraging decisions. To gain insight into the problem, we used a geometric framework for nutrition to assess how the protein and carbohydrate content of the larval diet affected key life history traits in the fruit fly, Drosophila melanogaster. In no-choice assays, survival from egg to pupae, female and male body size, and ovariole number - a proxy for female fecundity - were maximized at the highest protein to carbohydrate (P:C) ratio (1.5:1). In contrast, development time was minimized at intermediate P:C ratios, around 1:2. Next, we subjected larvae to two-choice tests to determine how they regulated their protein and carbohydrate intake in relation to these life history traits. Our results show that larvae targeted their consumption to P:C ratios that minimized development time. Finally, we examined whether adult females also chose to lay their eggs in the P:C ratios that minimized developmental time. Using a three-choice assay, we found that adult females preferentially laid their eggs in food P:C ratios that were suboptimal for all larval life history traits. Our results demonstrate that D. melanogaster larvae make foraging decisions that trade-off developmental time with body size, ovariole number, and survival. In addition, adult females make oviposition decisions that do not appear to benefit the larvae. We propose that these decisions may reflect the living nature of the larval nutritional environment in rotting fruit. These studies illustrate the interaction between the nutritional environment, life history traits, and foraging choices in D. melanogaster, and lend insight into the ecology of their foraging decisions.

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Animals from flies to humans adjust their development in response to environmental conditions through a series of developmental checkpoints, which alter the sensitivity of organs to environmental perturbation. Despite their importance, we know little about the molecular mechanisms through which this change in sensitivity occurs. Here we identify two phases of sensitivity to larval nutrition that contribute to plasticity in ovariole number, an important determinant of fecundity, in Drosophila melanogaster. These two phases of sensitivity are separated by the developmental checkpoint called "critical weight"; poor nutrition has greater effects on ovariole number in larvae before critical weight than after. We find that this switch in sensitivity results from distinct developmental processes. In precritical weight larvae, poor nutrition delays the onset of terminal filament cell differentiation, the starting point for ovariole development, and strongly suppresses the rate of terminal filament addition and the rate of increase in ovary volume. Conversely, in postcritical weight larvae, poor nutrition affects only the rate of increase in ovary volume. Our results further indicate that two hormonal pathways, the insulin/insulin-like growth factor and the ecdysone-signaling pathways, modulate the timing and rates of all three developmental processes. The change in sensitivity in the ovary results from changes in the relative contribution of each pathway to the rates of terminal filament addition and increase in ovary volume before and after critical weight. Our work deepens our understanding of how hormones act to modify the sensitivity of organs to environmental conditions, thereby affecting their plasticity.

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Queensland fruit fly, Bactrocera (Dacus) tryoni (QFF) is arguably the most costly horticultural insect pest in Australia. Despite this, no model is available to describe its population dynamics and aid in its management. This paper describes a cohort-based model of the population dynamics of the Queensland fruit fly. The model is primarily driven by weather variables, and so can be used at any location where appropriate meteorological data are available. In the model, the life cycle is divided into a number of discreet stages to allow physiological processes to be defined as accurately as possible. Eggs develop and hatch into larvae, which develop into pupae, which emerge as either teneral females or males. Both females and males can enter reproductive and over-wintering life stages, and there is a trapped male life stage to allow model predictions to be compared with trap catch data. All development rates are temperature-dependent. Daily mortality rates are temperature-dependent, but may also be influenced by moisture, density of larvae in fruit, fruit suitability, and age. Eggs, larvae and pupae all have constant establishment mortalities, causing a defined proportion of individuals to die upon entering that life stage. Transfer from one immature stage to the next is based on physiological age. In the adult life stages, transfer between stages may require additional and/or alternative functions. Maximum fecundity is 1400 eggs per female per day, and maximum daily oviposition rate is 80 eggs/female per day. The actual number of eggs laid by a female on any given day is restricted by temperature, density of larva in fruit, suitability of fruit for oviposition, and female activity. Activity of reproductive females and males, which affects reproduction and trapping, decreases with rainfall. Trapping of reproductive males is determined by activity, temperature and the proportion of males in the active population. Limitations of the model are discussed. Despite these, the model provides a useful agreement with trap catch data, and allows key areas for future research to be identified. These critical gaps in the current state of knowledge exist despite over 50 years of research on this key pest. By explicitly attempting to model the population dynamics of this pest we have clearly identified the research areas that must be addressed before progress can be made in developing the model into an operational tool for the management of Queensland fruit fly. (C) 2003 Published by Elsevier B.V.

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Caste determination in Trigona spinipes Fabricius (Hymenoptera, Apidae, Meliponini) is trophogenic. Larvae that eat about 360 mu l of food become queens, while those who consume 36 mu l develop into workers. We studied the effect of larval nutrition on the number and length of ovarioles and on ovarian development in fifth instar larvae, white eyed, pink eyed and black-eyed pupae as well as newly emerged adults. All larvae have four ovarioles per ovary, while in queen pupae this number ranged from 8 to 15. Cyst formation, the cell death and other characteristics of ovary morphogenesis were the same regardless of the quantity of food consumed. These results are discussed in relation to caste differentiation in other bees.

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A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.

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Knowledge of particle emission characteristics associated with forest fires and in general, biomass burning, is becoming increasingly important due to the impact of these emissions on human health. Of particular importance is developing a better understanding of the size distribution of particles generated from forest combustion under different environmental conditions, as well as provision of emission factors for different particle size ranges. This study was aimed at quantifying particle emission factors from four types of wood found in South East Queensland forests: Spotted Gum (Corymbia citriodora), Red Gum (Eucalypt tereticornis), Blood Gum (Eucalypt intermedia), and Iron bark (Eucalypt decorticans); under controlled laboratory conditions. The experimental set up included a modified commercial stove connected to a dilution system designed for the conditions of the study. Measurements of particle number size distribution and concentration resulting from the burning of woods with a relatively homogenous moisture content (in the range of 15 to 26 %) and for different rates of burning were performed using a TSI Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 600 nm and a TSI Dust Trak for PM2.5. The results of the study in terms of the relationship between particle number size distribution and different condition of burning for different species show that particle number emission factors and PM2.5 mass emission factors depend on the type of wood and the burning rate; fast burning or slow burning. The average particle number emission factors for fast burning conditions are in the range of 3.3 x 1015 to 5.7 x 1015 particles/kg, and for PM2.5 are in the range of 139 to 217 mg/kg.

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The measurement of submicrometre (< 1.0 m) and ultrafine particles (diameter < 0.1 m) number concentration have attracted attention since the last decade because the potential health impacts associated with exposure to these particles can be more significant than those due to exposure to larger particles. At present, ultrafine particles are not regularly monitored and they are yet to be incorporated into air quality monitoring programs. As a result, very few studies have analysed their long-term and spatial variations in ultrafine particle concentration, and none have been in Australia. To address this gap in scientific knowledge, the aim of this research was to investigate the long-term trends and seasonal variations in particle number concentrations in Brisbane, Australia. Data collected over a five-year period were analysed using weighted regression models. Monthly mean concentrations in the morning (6:00-10:00) and the afternoon (16:00-19:00) were plotted against time in months, using the monthly variance as the weights. During the five-year period, submicrometre and ultrafine particle concentrations increased in the morning by 105.7% and 81.5% respectively whereas in the afternoon there was no significant trend. The morning concentrations were associated with fresh traffic emissions and the afternoon concentrations with the background. The statistical tests applied to the seasonal models, on the other hand, indicated that there was no seasonal component. The spatial variation in size distribution in a large urban area was investigated using particle number size distribution data collected at nine different locations during different campaigns. The size distributions were represented by the modal structures and cumulative size distributions. Particle number peaked at around 30 nm, except at an isolated site dominated by diesel trucks, where the particle number peaked at around 60 nm. It was found that ultrafine particles contributed to 82%-90% of the total particle number. At the sites dominated by petrol vehicles, nanoparticles (< 50 nm) contributed 60%-70% of the total particle number, and at the site dominated by diesel trucks they contributed 50%. Although the sampling campaigns took place during different seasons and were of varying duration these variations did not have an effect on the particle size distributions. The results suggested that the distributions were rather affected by differences in traffic composition and distance to the road. To investigate the occurrence of nucleation events, that is, secondary particle formation from gaseous precursors, particle size distribution data collected over a 13 month period during 5 different campaigns were analysed. The study area was a complex urban environment influenced by anthropogenic and natural sources. The study introduced a new application of time series differencing for the identification of nucleation events. To evaluate the conditions favourable to nucleation, the meteorological conditions and gaseous concentrations prior to and during nucleation events were recorded. Gaseous concentrations did not exhibit a clear pattern of change in concentration. It was also found that nucleation was associated with sea breeze and long-range transport. The implications of this finding are that whilst vehicles are the most important source of ultrafine particles, sea breeze and aged gaseous emissions play a more important role in secondary particle formation in the study area.