231 research outputs found
The "ram effect": new insights into neural modulation of the gonadotropic axis by male odors and socio-sexual interactions
Reproduction in mammals is controlled by the hypothalamo-pituitary-gonadal (HPG) axis under the influence of external and internal factors such as photoperiod, stress, nutrition, and social interactions. Sheep are seasonal breeders and stop mating when day length is increasing (anestrus). However, interactions with a sexually active ram during this period can override the steroid negative feedback responsible for the anoestrus state, stimulate LH secretion and eventually reinstate cyclicity. This is known as the ram effect and research into the mechanisms underlying it is shedding new light on HPG axis regulation. The first step in the ram effect is increased LH pulsatile secretion in anestrus ewes exposed to a sexually active male or only to its fleece, the latter finding indicating a pheromone-like effect. Estradiol secretion increases in all ewes and this eventually induces a LH surge and ovulation, just as during the breeding season. An exception is a minority of ewes that exhibit a precocious LH surge (within 4h) with no prior increase in estradiol. The main olfactory system and the cortical nucleus of the amygdala are critical brain structures in mediating the ram effect since it is blocked by their inactivation. Sexual experience is also important since activation (increased c-fos expression) in these and other regions is greatly reduced in sexually naïve ewes. In adult ewes kisspeptin neurons in both arcuate and preoptic regions and some preoptic GnRH neurons are activated 2h after exposure to a ram. Exposure to rams also activates noradrenergic neurons in the locus coeruleus and A1 nucleus and increased noradrenalin release occurs in the posterior preoptic area. Pharmacological modulation of this system modifies LH secretion in response to the male or his odor. Together these results show that the ram effect can be a fruitful model to promote both a better understanding of the neural and hormonal regulation of the HPG axis in general and also the spe
The "Ram Effect": A "Non-Classical" Mechanism for Inducing LH Surges in Sheep
During spring sheep do not normally ovulate but exposure to a ram can induce ovulation. In some ewes an LH surge is induced immediately after exposure to a ram thus raising questions about the control of this precocious LH surge. Our first aim was to determine the plasma concentrations of oestradiol (E2) E2 in anoestrous ewes before and after the "ram effect" in ewes that had a "precocious" LH surge (starting within 6 hours), a "normal" surge (between 6 and 28h) and "late» surge (not detected by 56h). In another experiment we tested if a small increase in circulating E2 could induce an LH surge in anoestrus ewes. The concentration of E2 significantly was not different at the time of ram introduction among ewes with the three types of LH surge. "Precocious" LH surges were not preceded by a large increase in E2 unlike "normal" surges and small elevations of circulating E2 alone were unable to induce LH surges. These results show that the "precocious" LH surge was not the result of E2 positive feedback. Our second aim was to test if noradrenaline (NA) is involved in the LH response to the "ram effect". Using double labelling for Fos and tyrosine hydroxylase (TH) we showed that exposure of anoestrous ewes to a ram induced a higher density of cells positive for both in the A1 nucleus and the Locus Coeruleus complex compared to unstimulated controls. Finally, the administration by retrodialysis into the preoptic area, of NA increased the proportion of ewes with an LH response to ram odor whereas treatment with the α1 antagonist Prazosin decreased the LH pulse frequency and amplitude induced by a sexually active ram. Collectively these results suggest that in anoestrous ewes NA is involved in ram-induced LH secretion as observed in other induced ovulators
Caractérisation phénotypique des vaches laitières portant l'haplotype " fertil+/+ " ou " fertil-/- " pour un QTL de fertilité femelle situé sur le chromosome 3
Au cours de ces dernières années, la fertilité des vaches laitières hautes productrices a fortement diminué, notamment en race Prim'Holstein. Cette baisse de fertilité est en partie liée à une intense sélection de la productivité laitière. Des études réalisées par des généticiens ont mis en évidence plusieurs QTLs (Quantitative Trait Locus) de fertilité femelle chez la vache laitière. Nous avons choisi d'étudier des vaches laitières homozygotes à l'haplotype favorable "fertil+/+" ou défavorable "fertil-/-" pour un QTL de fertilité femelle situé sur le chromosome 3 (QTL-Fert-F-BTA3), ce QTL étant impliqué dans les échecs précoces de la gestation. Plusieurs paramètres ont été étudiés sur quarante cinq génisses puis sur quarante et une vaches en première lactation. Nous avons observé que les primipares "fertil-/-" ont perdu plus de poids que les primipares "fertil+/+" dans les sept premières semaines après vêlage. Dans cette même période, la production laitière ainsi que l'ingéré alimentaire des primipares "fertil-/-" ont été inférieurs à ceux des primipares "fertil+/+". Grâce aux profils de progestérone plasmatique, nous avons constaté que les animaux "fertil+/+" ont repris leur activité ovarienne plus vite que les animaux "fertil-/-" après le vêlage. Nous avons enfin constaté un meilleur taux de réussite à la première insémination artificielle pour les animaux "fertil+/+" que pour les animaux "fertil-/-". La perte de poids après vêlage plus importante chez les animaux "fertil-/-" pourrait expliquer un allongement de l'inactivité ovarienne post-partum et une fertilité plus faible chez ces animaux par rapport aux animaux "fertil+/+"
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Chemical fertility of forest ecosystems. Part 2: Towards redefining the concept by untangling the role of the different components of biogeochemical cycling
Many forest ecosystems are developed on acidic and nutrient-poor soils and it is not yet clearly understood how forests sustain their growth with low nutrient resources. In forestry, the soil chemical fertility is commonly defined, following concepts inherited from agronomy, as the pool of plant-available nutrients in the soil at a given time compared to the nutritional requirement of the tree species. In this two-part study, Part 1 (Hansson et al., 2020) showed, through the compiled dataset of 49 forest ecosystems in France, Brazil and Republic of Congo, the limits of this definition of soil chemical fertility in forest ecosystem contexts. In this study (Part 2), we investigated the nutrient pools and fluxes between the different ecosystem compartments at 11 of the 49 sites in order to better characterize the role of the biogeochemical cycling of nutrients in the chemical fertility of forest ecosystems, and in particular the roles of the biological and geochemical components of biogeochemical cycling.
The analysis of our dataset shows different types of biogeochemical functioning. When the geochemical component (inputs through mineral weathering and/or atmospheric inputs, capillary rise) is predominant, sufficient nutrients are provided to the plant-soil system to ensure tree nutrition and growth. Conversely, when the geochemical component of the cycle brings too few nutrients to the plant-soil system, the biological component (litterfall, plant internal cycling) becomes predominant in tree nutrition and growth. In the latter case, forest production may be high even when pools of nutrients in the soil reservoir are low because small but active nutrient fluxes may continuously replenish the soil reservoir or may directly ensure tree nutrition by bypassing the soil reservoir.
This study highlights the necessity to include biogeochemical cycling and recycling fluxes in the definition and diagnosis methods of soil chemical fertility in forest ecosystems. We show that the chemical fertility is not only supported by the soil in forest ecosystem but by the sum of all the ecosystem’s compartments and fluxes between these pools
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Chemical fertility of forest ecosystems. Part 1: Common soil chemical analyses were poor predictors of stand productivity across a wide range of acidic forest soils
Forest soil fertility can be defined as a combination of physical, chemical and biological factors characterising the biomass production capacity of the soil. However, numerous ecological variables affect tree growth and the aim of the present study was to investigate the specific influence of soil chemical properties on tree productivity at 49 acidic forest sites. A standardized tree productivity index based on tree height expressed as dominant height of the studied stand divided by maximum tree height observed at the same age for the same species in the same climatic region was firstly computed at each site. This index is assumed to limit the influence of species, ages and climate. A soil database was also compiled with data on soil properties from 47 temperate (France) and two tropical (Congo, Brazil) sites. Data included seven tree species, varying in age from 1 to 175 years. Commonly used indicators such as C:N ratio, soil pH, as well as available and total pools of soil nutrients were compared to the standardized tree productivity index, to find the most reliable indicator(s). Nutrient pools at fixed mineral soil depths (down to 100 cm) were used, as well as (for 11 stands) the depth comprising 95% of fine roots. Our results show that none of the common soil chemical parameters tested in this paper could individually explain stand productivity. Combinations of different parameters were also tested using PCA and they could better explain the variability of the data set but without being able to separate the sites according to their standardized tree productivity index. Moreover, random Forests performed on our dataset were unable to properly predict the standardized tree productivity index. Our results reinforce the idea that the influence of the soil chemical fertility on stand productivity is complex and the soil chemical parameters alone (individually or combined) are poor predictors of tree productivity as assessed by the H0:Hmax index. In this paper we focused on static soil chemical indicator and more dynamic indictors, such as nutrient fluxes involved in the biogeochemical cycles, could better explain stand productivity. A companion paper (Legout et al., 2020) focuses on the connection between productivity and different components of the biogeochemical cycle, using data from 11 of the stands presented in this paper
Is implicit motor learning preserved after stroke? A systematic review with meta-analysis
© 2016 Kal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Many stroke patients experience difficulty with performing dual-tasks. A promising intervention to target this issue is implicit motor learning, as it should enhance patients' automaticity of movement. Yet, although it is often thought that implicit motor learning is preserved poststroke, evidence for this claim has not been systematically analysed yet. Therefore, we systematically reviewed whether implicit motor learning is preserved post-stroke, and whether patients benefit more from implicit than from explicit motor learning. We comprehensively searched conventional (MEDLINE, Cochrane, Embase, PEDro, PsycINFO) and grey literature databases (BIOSIS, Web of Science, OpenGrey, British Library, trial registries) for relevant reports. Two independent reviewers screened reports, extracted data, and performed a risk of bias assessment. Overall, we included 20 out of the 2177 identified reports that allow for a succinct evaluation of implicit motor learning. Of these, only 1 study investigated learning on a relatively complex, whole-body (balance board) task. All 19 other studies concerned variants of the serial-reaction time paradigm, with most of these focusing on learning with the unaffected hand (N = 13) rather than the affected hand or both hands (both: N = 4). Four of the 20 studies compared explicit and implicit motor learning post-stroke. Meta-analyses suggest that patients with stroke can learn implicitly with their unaffected side (mean difference (MD) = 69 ms, 95% CI[45.1, 92.9], p < .00001), but not with their affected side (standardized MD = -.11, 95% CI[-.45, .25], p = .56). Finally, implicit motor learning seemed equally effective as explicit motor learning post-stroke (SMD = -.54, 95% CI[-1.37, .29], p = .20). However, overall, the high risk of bias, small samples, and limited clinical relevance of most studies make it impossible to draw reliable conclusions regarding the effect of implicit motor learning strategies post-stroke. High quality studies with larger samples are warranted to test implicit motor learning in clinically relevant contexts
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