Olfaction scaffolds the developing human from neonate to adolescent and beyond

The impact of the olfactory sense is regularly apparent across development. The foetus is bathed in amniotic fluid that conveys the mother’s chemical ecology. Transnatal olfactory continuity between the odours of amniotic fluid and milk assists in the transition to nursing. At the same time, odours emanating from the mammary areas provoke appetitive responses in newborns. Odours experienced from the mother’s diet during breastfeeding, and from practices such as pre-mastication, may assist in the dietary transition at weaning. In parallel, infants are attracted to and recognise their mother’s odours; later, children are able to recognise other kin and peers based on their odours. Familiar odours, such as those of the mother, regulate the child’s emotions, and scaffold perception and learning through non-olfactory senses. During adolescence, individuals become more sensitive to some bodily odours, while the timing of adolescence itself has been speculated to draw from the chemical ecology of the family unit. Odours learnt early in life and within the family niche continue to influence preferences as mate choice becomes relevant. Olfaction thus appears significant in turning on, sustaining and, in cases when mother odour is altered, disturbing adaptive reciprocity between offspring and caregiver during the multiple transitions of development between birth and adolescence

Transforming growth factor beta-1 decreases the yield of the second meiotic division of rat pachytene spermatocytes in vitro

BACKGROUND: TGF beta and its receptors are present in both germ cells and somatic cells of the male gonad. However, knock-out strategies for studying spermatogenesis regulation by TGF beta have been disappointing since TGF beta-or TGF beta receptor-null mice do not survive longer than a few weeks. METHODS: In the present study, we addressed the role of TGF beta-1 on the completion of meiosis by rat pachytene spermatocytes (PS) cocultured with Sertoli cells. Identification and counting of meiotic cells were performed by cytology and cytometry. RESULTS: Under our culture conditions, some PS differentiated into round spermatids (RS). When TGF beta-1 was added to the culture medium, neither the number of PS or of secondary spermatocytes nor the half-life of RS was modified by the factor. By contrast, the number of RS and the amount of TP1 mRNA were lower in TGF beta-1-treated cultures than in control cultures. Very few metaphase I cells were ever observed both in control and TGF beta-1-treated wells. Higher numbers of metaphase II were present and their number was enhanced by TGF beta-1 treatment. A TGF beta-like bioactivity was detected in control culture media, the concentration of which increased with the time of culture. CONCLUSION: These results indicate that TGF beta-1 did not change greatly, if any, the yield of the first meiotic division but likely enhanced a bottleneck at the level of metaphase II. Taken together, our results suggest strongly that TGF beta participates in an auto/paracrine pathway of regulation of the meiotic differentiation of rat spermatocytes

Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue

Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SARerr model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SARerr model, which led to a trend SARerr model. Overall, BT spread from north-eastern to south-western France. The average trend SARerr-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SARerr-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. Models such as the trend SARerr models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases

Bacterial Bioluminescent Biosensor Characterisation for On-line Monitoring of Heavy Metals Pollutions in Waste Water Treatment Plant Effluents

International audienc

Presentation, evaluation and sensitivity of a discharge algorithm for remotely sensed river measurements : Test cases on Sacramento and Garonne Rivers

We present an improvement to a previously presented algorithm that used a Bayesian Markov Chain Monte Carlo method for estimating river discharge from remotely sensed observations of river height, width, and slope. We also present an error budget for discharge calculations from the algorithm. The algorithm may be utilized by the upcoming Surface Water and Ocean Topography (SWOT) mission. We present a detailed evaluation of the method using synthetic SWOT-like observations (i.e., SWOT and AirSWOT, an airborne version of SWOT). The algorithm is evaluated using simulated AirSWOT observations over the Sacramento and Garonne Rivers that have differing hydraulic characteristics. The algorithm is also explored using SWOT observations over the Sacramento River. SWOT and AirSWOT height, width, and slope observations are simulated by corrupting the ‘‘true’’ hydraulic modeling results with instrument error. Algorithm discharge root mean square error (RMSE) was 9% for the Sacramento River and 15% for the Garonne River for the AirSWOT case using expected observation error. The discharge uncertainty calculated from Manning’s equation was 16.2% and 17.1%, respectively. For the SWOT scenario, the RMSE and uncertainty of the discharge estimate for the Sacramento River were 15% and 16.2%, respectively. A method based on the Kalman filter to correct errors of discharge estimates was shown to improve algorithm performance. From the error budget, the primary source of uncertainty was the a priori uncertainty of bathymetry and roughness parameters. Sensitivity to measurement errors was found to be a function of river characteristics. For example, Steeper Garonne River is less sensitive to slope errors than the flatter Sacramento River