Cross-contamination of oilseeds by insecticide residues during storage

Pesticide residues are found in oilseeds (rapeseed and sunflower) and crude oils: they are mainly organophosphate insecticides (pirimiophos-methyl, malathion when authorized) used in empty storage facilities and for direct application to stored cereal grain. Even if some secondary pests are found in stored oilseeds, French regulations do not allow use of these insecticides on stored oilseeds. These residues arise from cross-contamination from storage bins and grain handling equipment of grain stores, and not from illegal use. This uptake of insecticide residues from their storage environment by oilseeds may lead to residue contents that exceed regulatory limits. A three-year investigation in grain storage companies allowed us to follow the course of sunflower batches and rapeseed batches during storage seasons 2006-2007, 2007-2008 and 2008-2009, from reception at the storage facility to outloading. Each of these batches was sampled at outloading, and was analyzed for insecticide residues. Traceability of oilseeds established by grain-store managers allowed us to identify cross-contamination sources. The insecticides that were most commonly detected were pirimiophos-methyl, malathion, and dichlorvos (in sunflower 2006-2007), plus chlorpyriphos-methyl and deltamethrin. Pirimiophos-methyl was the most commonly detected active substance, and caused the most cases of non-accordance with regulatory levels in rapeseed. Cross-contamination could have occurred when cereal grains were treated upon receipt, when rapeseed was also delivered, especially when treatments were done systematically to the cereal grains. For sunflower, the main cross-contamination hazard resulted from treatment of cereals at the period of receipt or at their outloading, just before sunflower seeds batches were outloaded. Another situation led to cross-contamination, but generally at a lower extent: oilseeds stored in bins that contained previously treated cereals, or loaded in empty bins with handling equipment treated before the receipt of oilseeds.Keywords: Oilseed storage, Cross-contamination, Insecticide residues, Rapeseed, Sunflowe

A self-consistent treatment of non-equilibrium spin torques in magnetic multilayers

It is known that the transfer of spin angular momenta between current carriers and local moments occurs near the interface of magnetic layers when their moments are non-collinear. However, to determine the magnitude of the transfer, one should calculate the spin transport properties far beyond the interface regions. Based on the spin diffusion equation, we present a self-consistent approach to evaluate the spin torque for a number of layered structures. One of the salient features is that the longitudinal and transverse components of spin accumulations are inter-twined from one layer to the next, and thus, the spin torque could be significantly amplified with respect to treatments which concentrate solely on the transport at the interface due to the presence of the much longer longitudinal spin diffusion length. We conclude that bare spin currents do not properly estimate the spin angular momentum transferred between to the magnetic background; the spin transfer that occurs at interfaces should be self-consistently determined by embedding it in our globally diffuse transport calculations.Comment: 21 pages, 6 figure

Anatomical connectivity patterns predict face selectivity in the fusiform gyrus

A fundamental assumption in neuroscience is that brain structure determines function. Accordingly, functionally distinct regions of cortex should be structurally distinct in their connections to other areas. We tested this hypothesis in relation to face selectivity in the fusiform gyrus. By using only structural connectivity, as measured through diffusion-weighted imaging, we were able to predict functional activation to faces in the fusiform gyrus. These predictions outperformed two control models and a standard group-average benchmark. The structure–function relationship discovered from the initial participants was highly robust in predicting activation in a second group of participants, despite differences in acquisition parameters and stimuli. This approach can thus reliably estimate activation in participants who cannot perform functional imaging tasks and is an alternative to group-activation maps. Additionally, we identified cortical regions whose connectivity was highly influential in predicting face selectivity within the fusiform, suggesting a possible mechanistic architecture underlying face processing in humans.United States. Public Health Service (DA023427)National Institute of Mental Health (U.S.) (F32 MH084488)National Eye Institute (T32 EY013935)Poitras FoundationSimons FoundationEllison Medical Foundatio

Deterministic diffusion fiber tracking improved by quantitative anisotropy

Diffusion MRI tractography has emerged as a useful and popular tool for mapping connections between brain regions. In this study, we examined the performance of quantitative anisotropy (QA) in facilitating deterministic fiber tracking. Two phantom studies were conducted. The first phantom study examined the susceptibility of fractional anisotropy (FA), generalized factional anisotropy (GFA), and QA to various partial volume effects. The second phantom study examined the spatial resolution of the FA-aided, GFA-aided, and QA-aided tractographies. An in vivo study was conducted to track the arcuate fasciculus, and two neurosurgeons blind to the acquisition and analysis settings were invited to identify false tracks. The performance of QA in assisting fiber tracking was compared with FA, GFA, and anatomical information from T 1-weighted images. Our first phantom study showed that QA is less sensitive to the partial volume effects of crossing fibers and free water, suggesting that it is a robust index. The second phantom study showed that the QA-aided tractography has better resolution than the FA-aided and GFA-aided tractography. Our in vivo study further showed that the QA-aided tractography outperforms the FA-aided, GFA-aided, and anatomy-aided tractographies. In the shell scheme (HARDI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 30.7%, 32.6%, and 24.45% of the false tracks, respectively, while the QA-aided tractography has 16.2%. In the grid scheme (DSI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 12.3%, 9.0%, and 10.93% of the false tracks, respectively, while the QA-aided tractography has 4.43%. The QA-aided deterministic fiber tracking may assist fiber tracking studies and facilitate the advancement of human connectomics. © 2013 Yeh et al

Connectivity-based parcellation of the human frontal polar cortex

The frontal pole corresponds to Brodmann area (BA) 10, the largest single architectonic area in the human frontal lobe. Generally, BA10 is thought to contain two or three subregions that subserve broad functions such as multitasking, social cognition, attention, and episodic memory. However, there is a substantial debate about the functional and structural heterogeneity of this large frontal region. Previous connectivity-based parcellation studies have identified two or three subregions in the human frontal pole. Here, we used diffusion tensor imaging to assess structural connectivity of BA10 in 35 healthy subjects and delineated subregions based on this connectivity. This allowed us to determine the correspondence of structurally based subregions with the scheme previously defined functionally. Three subregions could be defined in each subject. However, these three subregions were not spatially consistent between subjects. Therefore, we accepted a solution with two subregions that encompassed the lateral and medial frontal pole. We then examined resting-state functional connectivity of the two subregions and found significant differences between their connectivities. The medial cluster was connected to nodes of the default-mode network, which is implicated in internally focused, self-related thought, and social cognition. The lateral cluster was connected to nodes of the executive control network, associated with directed attention and working memory. These findings support the concept that there are two major anatomical subregions of the frontal pole related to differences in functional connectivity

Measuring macroscopic brain connections in vivo

Decades of detailed anatomical tracer studies in non-human animals point to a rich and complex organization of long-range white matter connections in the brain. State-of-the art in vivo imaging techniques are striving to achieve a similar level of detail in humans, but multiple technical factors can limit their sensitivity and fidelity. In this review, we mostly focus on magnetic resonance imaging of the brain. We highlight some of the key challenges in analyzing and interpreting in vivo connectomics data, particularly in relation to what is known from classical neuroanatomy in laboratory animals. We further illustrate that, despite the challenges, in vivo imaging methods can be very powerful and provide information on connections that is not available by any other means

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments