Milling plant and soil material in plastic tubes over-estimates carbon and under-estimates nitrogen concentrations

Peer reviewedPostprin

Neuroimaging young children and associations with neurocognitive development in a South African birth cohort study.

Magnetic resonance imaging (MRI) is an indispensable tool for investigating brain development in young children and the neurobiological mechanisms underlying developmental risk and resilience. Sub-Saharan Africa has the highest proportion of children at risk of developmental delay worldwide, yet in this region there is very limited neuroimaging research focusing on the neurobiology of such impairment. Furthermore, paediatric MRI imaging is challenging in any setting due to motion sensitivity. Although sedation and anesthesia are routinely used in clinical practice to minimise movement in young children, this may not be ethical in the context of research. Our study aimed to investigate the feasibility of paediatric multimodal MRI at age 2-3 years without sedation, and to explore the relationship between cortical structure and neurocognitive development at this understudied age in a sub-Saharan African setting. A total of 239 children from the Drakenstein Child Health Study, a large observational South African birth cohort, were recruited for neuroimaging at 2-3 years of age. Scans were conducted during natural sleep utilising locally developed techniques. T1-MEMPRAGE and T2-weighted structural imaging, resting state functional MRI, diffusion tensor imaging and magnetic resonance spectroscopy sequences were included. Child neurodevelopment was assessed using the Bayley-III Scales of Infant and Toddler Development. Following 23 pilot scans, 216 children underwent scanning and T1-weighted images were obtained from 167/216 (77%) of children (median age 34.8 months). Furthermore, we found cortical surface area and thickness within frontal regions were associated with cognitive development, and in temporal and frontal regions with language development (beta coefficient ?0.20). Overall, we demonstrate the feasibility of carrying out a neuroimaging study of young children during natural sleep in sub-Saharan Africa. Our findings indicate that dynamic morphological changes in heteromodal association regions are associated with cognitive and language development at this young age. These proof-of-concept analyses suggest similar links between the brain and cognition as prior literature from high income countries, enhancing understanding of the interplay between cortical structure and function during brain maturation

Tracking long-distance migration to assess marine pollution impact

Animal tracking provides new means to assess far-reaching environmental impacts. In the aftermath of the Deepwater Horizon explosion in the Gulf of Mexico, a long-distance migrant, the northern gannet (Morus bassanus) suffered the highest oiling among beach-wrecked birds recovered. Analysis of bird-borne tracking data indicated that 25 per cent of their North American population from multiple colonies in eastern Canada migrated to the pollution zone. Findings contrasted sharply with available mark-recapture (band recovery) data. The timing of movement into and out of the Gulf indicates that immature birds would have absorbed most oil-induced mortality. Consequently, one of two outcomes is likely: either a lagged (likely difficult to assess) population decrease, or an undetectable population response buffered by age-related life-history adaptations. Tracking research is especially useful when little information on animal distributions in pollution zones is available, as is the case in the Gulf of Mexico. Ongoing research highlights current risks and conservation concerns

SPFC: a tool to improve water management and hay production in the Crau region

Correspondance: [email protected] ; UMR SYSTEM équipe CONSYSTThis article deals with the development and application of SPFC, a model used to improve water and grassland production (HC) in this region of France. This model is composed of two sub-models: an irrigation model and a crop model. As the fields are border irrigated, these two sub-models are coupled. The crop model simulates dry matter, Leaf Area Index (LAI) and soil water reserve (SWR) variations. LAI and SWR are both used for border model updating: SWR for the deficit of saturation required by the infiltration equation and LAI for the roughness coefficient n. After calibration and validation, SPFC is then used to identify realistic management strategies for the irrigation and production system at the plot level. By scheduling irrigation when SWR is 50% depleted, would result in a low Dry Matter DM production loss (around 10%), reduced labour (8 irrigation events instead of 11) and in significant water saving compared with farmers' practices, on the basis of an average climatic scenario. Furthermore, this improvement of irrigation efficiency is not incompatible with groundwater recharge used for the potable water supply of the region

Global Analysis of Circulating Immune Cells by Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry

Background: MALDI-TOF mass spectrometry is currently used in microbiological diagnosis to characterize bacterial populations. Our aim was to determine whether this technique could be applied to intact eukaryotic cells, and in particular, to cells involved in the immune response. Methodology/Principal Findings: A comparison of frozen monocytes, T lymphocytes and polymorphonuclear leukocytes revealed specific peak profiles. We also found that twenty cell types had specific profiles, permitting the establishment of a cell database. The circulating immune cells, namely monocytes, T lymphocytes and polymorphonuclear cells, were distinct from tissue immune cells such as monocyte-derived macrophages and dendritic cells. In addition, MALDI-TOF mass spectrometry was valuable to easily identify the signatures of monocytes and T lymphocytes in peripheral mononuclear cells. Conclusions/Significance: This method was rapid and easy to perform, and unlike flow cytometry, it did not require any additional components such as specific antibodies. The MALDI-TOF mass spectrometry approach could be extended t

A Bayesian Outlier Criterion to Detect SNPs under Selection in Large Data Sets

Background: The recent advent of high-throughput SNP genotyping technologies has opened new avenues of research for population genetics. In particular, a growing interest in the identification of footprints of selection, based on genome scans for adaptive differentiation, has emerged.[br/] Methodology/Principal Findings: The purpose of this study is to develop an efficient model-based approach to perform Bayesian exploratory analyses for adaptive differentiation in very large SNP data sets. The basic idea is to start with a very simple model for neutral loci that is easy to implement under a Bayesian framework and to identify selected loci as outliers via Posterior Predictive P-values (PPP-values). Applications of this strategy are considered using two different statistical models. The first one was initially interpreted in the context of populations evolving respectively under pure genetic drift from a common ancestral population while the second one relies on populations under migration-drift equilibrium. Robustness and power of the two resulting Bayesian model-based approaches to detect SNP under selection are further evaluated through extensive simulations. An application to a cattle data set is also provided.[br/] Conclusions/Significance: The procedure described turns out to be much faster than former Bayesian approaches and also reasonably efficient especially to detect loci under positive selection

Role of voiding and storage symptoms for the quality of life before and after treatment in men with voiding dysfunction

Previous studies on associations between voiding dysfunction and quality of life (QoL) have largely been limited to baseline data. Therefore, we have explored associations between Q (max) and voiding and storage sub-scores of the International Prostate Symptom Score (IPSS) before and after treatment with QoL. Analysis of a single-center database of 2,316 men with voiding dysfunction attributed to benign prostatic hyperplasia undergoing various medical and surgical treatment forms. Q (max) exhibited little correlation with QoL before or after treatment. IPSS inversely correlated with QoL at baseline and after treatment, and IPSS improvements correlated with those of QoL. The associations applied to both the voiding and storage sub-score of the IPSS, with the latter consistently exhibiting somewhat tighter associations. Our post-treatment data support the idea of a cause-effect relationship between voiding symptoms and QoL irrespective of treatment form. While both voiding and storage symptoms contribute to this relationship, storage symptoms play a somewhat greater rol

A Network Integration Approach to Predict Conserved Regulators Related to Pathogenicity of Influenza and SARS-CoV Respiratory Viruses

Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel "crowd-based" approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse 'omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models