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The aim of this study was to evaluate the validity of an orthotic deformation test on insole arches and the impact of researcher expertise on the test’s reproducibility. Three researchers with different levels of experience evaluated orthotic deformation by applying a vertical force with their thumb on the dorsal surface of 48 polypropylene orthoses. An electromechanical test machine was used to evaluate the stiffness of the orthoses, and the results were compared with those of the orthotic deformation tests. Fleiss’ kappa and weighted kappa and Mann–Whitney U tests were used to evaluate the interobserver reliability and the validity, respectively. There was no consensus among the three researchers (Kappa = 0.080; p-value = 0.334), although the two researchers with higher levels of experience exhibited moderate consensus (Kappa = 0.52; p-value < 0.001). Orthoses characterised by a positive test suffered from more pronounced deformation when a constant vertical force was applied by the electromechanical test machine (5.62 [4.64–7.38] vs. 4.56 [3.59–5.28] mm; p-value = 0.003). The orthotic deformation test is valid for interpreting the degree of deformation of polypropylene custom orthoses when it is compared with an axial force from a compression-device test. However, considering the high dispersion of the results, it suggests that clinical experience is required to properly interpret the tests.

IntroductionType C hepatic encephalopathy (HE) is a decompensating event of chronic liver disease leading to severe motor and cognitive impairment. The progression of type C HE is associated with changes in brain metabolite concentrations measured by 1H magnetic resonance spectroscopy (MRS), most noticeably a strong increase in glutamine to detoxify brain ammonia. In addition, alterations of brain cellular architecture have been measured ex vivo by histology in a rat model of type C HE. The aim of this study was to assess the potential of diffusion-weighted MRS (dMRS) for probing these cellular shape alterations in vivo by monitoring the diffusion properties of the major brain metabolites.MethodsThe bile duct-ligated (BDL) rat model of type C HE was used. Five animals were scanned before surgery and 6- to 7-week post-BDL surgery, with each animal being used as its own control. 1H-MRS was performed in the hippocampus (SPECIAL, TE = 2.8 ms) and dMRS in a voxel encompassing the entire brain (DW-STEAM, TE = 15 ms, diffusion time = 120 ms, maximum b-value = 25 ms/μm2) on a 9.4 T scanner. The in vivo MRS acquisitions were further validated with histological measures (immunohistochemistry, Golgi-Cox, electron microscopy).ResultsThe characteristic 1H-MRS pattern of type C HE, i.e., a gradual increase of brain glutamine and a decrease of the main organic osmolytes, was observed in the hippocampus of BDL rats. Overall increased metabolite diffusivities (apparent diffusion coefficient and intra-stick diffusivity—Callaghan’s model, significant for glutamine, myo-inositol, and taurine) and decreased kurtosis coefficients were observed in BDL rats compared to control, highlighting the presence of osmotic stress and possibly of astrocytic and neuronal alterations. These results were consistent with the microstructure depicted by histology and represented by a decline in dendritic spines density in neurons, a shortening and decreased number of astrocytic processes, and extracellular edema.DiscussiondMRS enables non-invasive and longitudinal monitoring of the diffusion behavior of brain metabolites, reflecting in the present study the globally altered brain microstructure in BDL rats, as confirmed ex vivo by histology. These findings give new insights into metabolic and microstructural abnormalities associated with high brain glutamine and its consequences in type C HE.

Aerification and topdressing are important cultural management practices that help prevent organic matter accumulation and soil compaction in golf greens. However, these practices result in surface disruption and decreased putting quality during recovery. A 2-year study was conducted on a ‘TifEagle’ hybrid bermudagrass (Cynodon dactylon × C. transvaalensis) putting green to determine the effect of different aerification methods and topdressing materials on soil properties and turfgrass recovery. Plots were aerified four times per year (May to Aug.) using 1/2-inch hollow tines, 1/4-inch hollow needle tines, hollow tines 2X + hollow needle tines 2X, or sand injection, and topdressed with either 90:10 (sand:peat) or green-dyed sand. Visual quality, normalized difference vegetation index, percent green cover, dark green color index (DGCI), surface firmness and volumetric water content were measured before initial aerification and at 7 and 21 days after aerification. Saturated hydraulic conductivity (Ksat) and organic matter (OM) content were measured monthly. Aerification with hollow tines and hollow tines 2X + hollow needle tines 2X resulted in lower firmness and OM and higher Ksat compared with hollow needle tines and sand injection. Sand injection showed the highest percent green cover and similar OM content compared with hollow tines and hollow tines 2X + hollow needle tines 2X. Green-dyed sand showed a higher percent green cover and DGCI compared with 90:10 sand:peat. Using hollow tines only or alternating them with hollow needle tines is the best option to decrease OM content while increasing Ksat in hybrid bermudagrass greens; however, their use could result in slower turfgrass recovery compared with other aerification methods.

Abstract Our study explores the potential of conventional and advanced diffusion MRI techniques including diffusion tensor imaging (DTI), and single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD) to investigate complex microstructural changes following severe traumatic brain injury in rats at a chronic phase. Rat brains after sham-operation or lateral fluid percussion (LFP) injury were scanned ex vivo in a 9.4 T scanner. Our region-of-interest-based approach of tensor-, and SS3T-CSD derived fixel-, 3-tissue signal fraction maps were sensitive to changes in both white matter (WM) and grey matter (GM) areas. Tensor-based measures, such as fractional anisotropy (FA) and radial diffusivity (RD), detected more changes in WM and GM areas as compared to fixel-based measures including apparent fiber density (AFD), peak FOD amplitude and primary fiber bundle density, while 3-tissue signal fraction maps revealed distinct changes in WM, GM, and phosphate-buffered saline (PBS) fractions highlighting the complex tissue microstructural alterations post-trauma. Track-weighted imaging demonstrated changes in track morphology including reduced curvature and average pathlength distal from the primary lesion in severe TBI rats. In histological analysis, changes in the diffusion MRI measures could be associated to decreased myelin density, loss of myelinated axons, and increased cellularity, revealing progressive microstructural alterations in these brain areas five months after injury. Overall, this study highlights the use of combined conventional and advanced diffusion MRI measures to obtain more precise insights into the complex tissue microstructural alterations in chronic phase of severe brain injury.

IntroductionDeep brain stimulation (DBS) is a rapidly developing therapeutic intervention with constantly expanding neurological and psychiatric indications. A major challenge for the approach is the precise targeting and limitation of the effect on the desired neural pathways. We have introduced a new approach, orientation selective stimulation (OSS) that allows free rotation of the induced electric field on a plane when using a probe with three parallel electrodes forming an equilateral triangle at the tip. Here, we expand the technique by introducing a tetrahedral stimulation probe that enables adjustment of the primary electric field direction freely at any angle in a 3D space around the stimulating probe. OSS in 3D will enable better targeting of the electric field according to the local brain anatomy. We tested its utility in a rat model of DBS for treatment-resistant depression. The stimulation directed to the subgenual anterior cingulate cortex (sgACC) has yielded dramatic improvement in individual patients suffering from therapy resistant depression, but no consistent benefit in larger series. This failure has been ascribed to the challenging anatomy of sgACC with several crossing neural tracts and individual differences in the local anatomy.MethodsWe stimulated infralimbic cortex (IL), the rat analog of sgACC, and recorded local electrical responses in amygdala (AMG) that is monosynaptically connected to IL and plays a central role in emotional states. We further traced AMG–IL connections using a viral vector and tractography using diffusion magnetic resonance imaging (MRI). Finally, we mimicked the clinical situation by delivering sustained 130 Hz stimulation at IL at the most effective field orientation and followed changes in resting-state functional connectivity with IL using functional MRI. To help interpretation of responses in functional connectivity, we stimulated only the left IL, which we did not expect to evoke measurable changes in the rat behavior.ResultsThe AMG evoked responses depended systematically on the IL stimulation field orientation and yielded the maximum response in near vertical field orientation in accordance with tractography. Sustained 130 Hz stimulation at a field orientation yielding the strongest AMG evoked responses increased functional connectivity between IL and AMG on the stimulation side.ConclusionThese findings suggest that OSS in 3D provides a new approach to optimize the DBS for every individual patient with a single stimulation probe implantation.

Abstract A system of lymphatic vessels has been recently characterized in the meninges, with a postulated role in ‘cleaning’ the brain via cerebral fluid drainage. As meninges are the origin site of migraine pain, we hypothesized that malfunctioning of the lymphatic system should affect the local trigeminal nociception. To test this hypothesis, we studied nociceptive and inflammatory mechanisms in the hemiskull preparations (containing the meninges) of K14-VEGFR3-Ig (K14) mice lacking the meningeal lymphatic system. We recorded the spiking activity of meningeal afferents and estimated the local mast cells population, calcitonin gene-related peptide (CGRP) and cytokine levels as well as the dural trigeminal innervation in freshly-isolated hemiskull preparations from K14-VEGFR3-Ig (K14) or wild type C57BL/6 mice (WT). Spiking activity data have been confirmed in an acquired model of meningeal lymphatic dysfunction (AAV-mVEGFR3(1–4)Ig induced lymphatic ablation). We found that levels of the pro-inflammatory cytokine IL12-p70 and CGRP, implicated in migraine, were reduced in the meninges of K14 mice, while the levels of the mast cell activator MCP-1 were increased. The other migraine-related pro-inflammatory cytokines (basal and stimulated), did not differ between the two genotypes. The patterns of trigeminal innervation in meninges remained unchanged and we did not observe alterations in basal or ATP-induced nociceptive firing in the meningeal afferents associated with meningeal lymphatic dysfunction. In summary, the lack of meningeal lymphatic system is associated with a new balance between pro- and anti-migraine mediators but does not directly trigger meningeal nociceptive state.

Abstract The recently introduced orientation selective deep brain stimulation (OS-DBS) technique freely controls the direction of the electric field’s spatial gradient by using multiple contacts with independent current sources within a multielectrode array. The goal of OS-DBS is to align the electrical field along the axonal track of interest passing through the stimulation site. Here we utilized OS-DBS with a planar 3-channel electrode for stimulating the rat entorhinal cortex (EC) and medial septal nucleus (MSN), two promising areas for DBS treatment of Alzheimer’s disease. The brain responses to OS-DBS were monitored by whole brain functional magnetic resonance imaging (fMRI) at 9.4 T with Multi-Band Sweep Imaging with Fourier Transformation (MB-SWIFT). Varying the in-plane OS-DBS stimulation angle in the EC resulted in activity modulation of multiple downstream brain areas involved in memory and cognition. Contrary to that, no angle dependence of brain activations was observed when stimulating the MSN, consistent with predictions based on the electrode configuration and on the main axonal directions of the targets derived from diffusion MRI tractography and histology. We conclude that tuning the OS-DBS stimulation angle modulates the activation of brain areas relevant to Alzheimer’s disease, thus holding great promise in the DBS treatment of the disease.

Ensuring international benefit-sharing from sequence data without jeopardising open sharing is a major obstacle for the Convention on Biological Diversity and other UN negotiations. Here, the authors propose a solution to address the concerns of both developing countries and life scientists.

Non-invasive magnetic resonance imaging (MRI) methods have proved useful in the diagnosis and prognosis of neurodegenerative diseases. However, the interpretation of imaging outcomes in terms of tissue pathology is still challenging. This study goes beyond the current interpretation of in vivo diffusion tensor imaging (DTI) by constructing multivariate models of quantitative tissue microstructure in status epilepticus (SE)-induced brain damage. We performed in vivo DTI and histology in rats at 79 days after SE and control animals. The analyses focused on the corpus callosum, hippocampal subfield CA3b, and layers V and VI of the parietal cortex. Comparison between control and SE rats indicated that a combination of microstructural tissue changes occurring after SE, such as cellularity, organization of myelinated axons, and/or morphology of astrocytes, affect DTI parameters. Subsequently, we constructed a multivariate regression model for explaining and predicting histological parameters based on DTI. The model revealed that DTI predicted well the organization of myelinated axons (cross-validated R = 0.876) and astrocyte processes (cross-validated R = 0.909) and possessed a predictive value for cell density (CD) (cross-validated R = 0.489). However, the morphology of astrocytes (cross-validated R > 0.05) was not well predicted. The inclusion of parameters from CA3b was necessary for modeling histopathology. Moreover, the multivariate DTI model explained better histological parameters than any univariate model. In conclusion, we demonstrate that combining several analytical and statistical tools can help interpret imaging outcomes to microstructural tissue changes, opening new avenues to improve the non-invasive diagnosis and prognosis of brain tissue damage.

With DeepACSON, Abdollahzadeh et al. combines existing deep learning-based methods for semantic segmentation and a novel shape decomposition technique for the instance segmentation. The pipeline is used to segment low-resolution 3D-EM datasets allowing quantification of white matter morphology in large fields-of-view.

We develop a cylindrical shape decomposition (CSD) algorithm to decompose an object, a union of several tubular structures, into its semantic components. We decompose the object using its curve skeleton and restricted translational sweeps. For that, CSD partitions the curve skeleton into maximal-length sub-skeletons over an orientation cost, each sub-skeleton corresponds to a semantic component. To find the intersection of the tubular components, CSD translationally sweeps the object in decomposition intervals to identify critical points at which the shape of the object changes substantially. CSD cuts the object at critical points and assigns the same label to parts along the same sub-skeleton, thereby constructing a semantic component. The proposed method further reconstructs the acquired semantic components at the intersection of object parts using generalized cylinders. We apply CSD for segmenting axons in large 3D electron microscopy images and decomposing vascular networks and synthetic objects. We show that our proposal is robust to severe surface noise and outperforms state-of-the-art decomposition techniques in its applications.

Diverse approaches such as oscillating gradients, tensor-valued encoding, and diffusion-relaxation correlation have been used to study microstructure and heterogeneity in healthy and pathological biological tissues. Recently, acquisition schemes with free gradient waveforms exploring both the frequency-dependent and tensorial aspects of the encoding spectrum b(ω) have enabled estimation of nonparametric distributions of frequency-dependent diffusion tensors. These “D(ω)-distributions” allow investigation of restricted diffusion for each distinct component resolved in the diffusion tensor trace, anisotropy, and orientation dimensions. Likewise, multidimensional methods combining longitudinal and transverse relaxation rates, R1 and R2, with (ω-independent) D-distributions capitalize on the component resolution offered by the diffusion dimensions to investigate subtle differences in relaxation properties of sub-voxel water populations in the living human brain, for instance nerve fiber bundles with different orientations. By measurements on an ex vivo rat brain, we here demonstrate a “massively multidimensional” diffusion-relaxation correlation protocol joining all the approaches mentioned above. Images acquired as a function of the magnitude, normalized anisotropy, orientation, and frequency content of b(ω), as well as the repetition time and echo time, yield nonparametric D(ω)-R1-R2-distributions via a Monte Carlo data inversion algorithm. The obtained per-voxel distributions are converted to parameter maps commonly associated with conventional lower-dimensional methods as well as unique statistical descriptors reporting on the correlations between restriction, anisotropy, and relaxation.

Our study investigates the potential of diffusion MRI (dMRI), including diffusion tensor imaging (DTI), fixel-based analysis (FBA) and neurite orientation dispersion and density imaging (NODDI), to detect microstructural tissue abnormalities in rats after mild traumatic brain injury (mTBI). The brains of sham-operated and mTBI rats 35 days after lateral fluid percussion injury were imaged ex vivo in a 11.7-T scanner. Voxel-based analyses of DTI-, fixel- and NODDI-based metrics detected extensive tissue changes in directly affected brain areas close to the primary injury, and more importantly, also in distal areas connected to primary injury and indirectly affected by the secondary injury mechanisms. Histology revealed ongoing axonal abnormalities and inflammation, 35 days after the injury, in the brain areas highlighted in the group analyses. Fractional anisotropy (FA), fiber density (FD) and fiber density and fiber bundle cross-section (FDC) showed similar pattern of significant areas throughout the brain; however, FA showed more significant voxels in gray matter areas, while FD and FDC in white matter areas, and orientation dispersion index (ODI) in areas most damage based on histology. Region-of-interest (ROI)-based analyses on dMRI maps and histology in selected brain regions revealed that the changes in MRI parameters could be attributed to both alterations in myelinated fiber bundles and increased cellularity. This study demonstrates that the combination of dMRI methods can provide a more complete insight into the microstructural alterations in white and gray matter after mTBI, which may aid diagnosis and prognosis following a mild brain injury.

It is necessary to develop reliable biomarkers for epileptogenesis and cognitive impairment after traumatic brain injury when searching for novel antiepileptogenic and cognition-enhancing treatments. We hypothesized that a multiparametric magnetic resonance imaging (MRI) analysis along the septotemporal hippocampal axis could predict the development of post-traumatic epilepsy and cognitive impairment. We performed quantitative T2 and T2* MRIs at 2, 7 and 21 days, and diffusion tensor imaging at 7 and 21 days after lateral fluid-percussion injury in male rats. Morris water maze tests conducted between 35–39 days post-injury were used to diagnose cognitive impairment. One-month-long continuous video-electroencephalography monitoring during the 6th post-injury month was used to diagnose epilepsy. Single-parameter and regularized multiple linear regression models were able to differentiate between sham-operated and brain-injured rats. In the ipsilateral hippocampus, differentiation between the groups was achieved at most septotemporal locations (cross-validated area under the receiver operating characteristic curve (AUC) 1.0, 95% confidence interval 1.0–1.0). In the contralateral hippocampus, the highest differentiation was evident in the septal pole (AUC 0.92, 95% confidence interval 0.82–0.97). Logistic regression analysis of parameters imaged at 3.4 mm from the contralateral hippocampus’s temporal end differentiated between the cognitively impaired rats and normal rats (AUC 0.72, 95% confidence interval 0.55–0.84). Neither single nor multiparametric approaches could identify the rats that would develop post-traumatic epilepsy. Multiparametric MRI analysis of the hippocampus can be used to identify cognitive impairment after an experimental traumatic brain injury. This information can be used to select subjects for preclinical trials of cognition-improving interventions.

Introduction To assess the cost-effectiveness of a multidisciplinary and comprehensive innovative diabetes care program (CAIPaDi) versus usual treatment in public health institutions.Research design and methods Using a cost-effectiveness analysis, we compared the CAIPaDi program versus usual treatment given in Mexican public health institutions. The analysis was based on the IQVIA Core Diabetes Model, a validated simulation model used to estimate long-term clinical outcomes. Data were prospectively obtained from the CAIPaDi program and from public databases and published papers. Health outcomes were expressed in terms of life-years gained and quality-adjusted life years (QALYs). Health and economic outcomes were estimated from a public perspective and discounted at 5% per year over a 20-year horizon. Costs are reported in US dollars (US$) of 2019. A probabilistic sensitivity analysis was performed using life-years gained and QALYs.Results The CAIPaDi costs on average US$559 (95% CI: −$879 to −$239) less than the usual treatment (95% CI: −$879 to −$239) and produced a difference in mean life-years gained (0.48, 95% CI: 0.45 to 0.52) and mean QALYs (1.43, 95% CI: 1.40 to 1.46). The cost-effectiveness ratio resulted in a saving per life-year gained of −US$1155 (95% CI: −$1962 to −$460). Mean differences in QALYs resulted in a saving per QALY of −US$735 (95% CI: −$1193 to −$305). Probabilistic sensitivity analysis proved the results are robust on both life-years gained and QALYs.Conclusions CAIPaDi has a better cost-effectiveness ratio than the usual therapy in Mexican public health institutions.

La intencionalidad del embarazo se ha tratado de explicar desde diversos marcos teóricos, pero no siempre se considera el contexto cultural; por ello persisten complicaciones conceptuales y metodológicas. A lo largo de este estudio se pretendió identificar las representaciones sociales que las adolescentes de León (Guanajuato, México) tienen del embarazo no deseado y no planeado, estudio basado en el enfoque teórico de las representaciones sociales, con el uso de técnicas asociativas derivadas de la antropología cognitiva, específicamente listados libres y comparación de pares. Participaron 72 mujeres de 15 a 19 años. Las representaciones sociales del embarazo no planeado se centraron en aspectos económicos y emocionales negativos; el embarazo no deseado se asoció con aspectos emocionales negativos (sentimientos de enojo y culpa por la situación), además de que se consideró el aborto como solución.

Skull-stripping and region segmentation are fundamental steps in preclinical magnetic resonance imaging (MRI) studies, and these common procedures are usually performed manually. We present Multi-task U-Net (MU-Net), a convolutional neural network designed to accomplish both tasks simultaneously. MU-Net achieved higher segmentation accuracy than state-of-the-art multi-atlas segmentation methods with an inference time of 0.35 s and no pre-processing requirements.We trained and validated MU-Net on 128 T2-weighted mouse MRI volumes as well as on the publicly available MRM NeAT dataset of 10 MRI volumes. We tested MU-Net with an unusually large dataset combining several independent studies consisting of 1782 mouse brain MRI volumes of both healthy and Huntington animals, and measured average Dice scores of 0.906 (striati), 0.937 (cortex), and 0.978 (brain mask). Further, we explored the effectiveness of our network in the presence of different architectural features, including skip connections and recently proposed framing connections, and the effects of the age range of the training set animals.These high evaluation scores demonstrate that MU-Net is a powerful tool for segmentation and skull-stripping, decreasing inter and intra-rater variability of manual segmentation. The MU-Net code and the trained model are publicly available at https://github.com/Hierakonpolis/MU-Net.

Remyelination is a naturally occurring response to demyelination and has a central role in the pathophysiology of multiple sclerosis and traumatic brain injury. Recently we demonstrated that a novel MRI technique entitled Relaxation Along a Fictitious Field (RAFF) in the rotating frame of rank n (RAFFn) achieved exceptional sensitivity in detecting the demyelination processes induced by lysophosphatidylcholine (LPC) in rat brain. In the present work, our aim was to test whether RAFF4, along with magnetization transfer (MT) and diffusion tensor imaging (DTI), would be capable of detecting the changes in the myelin content and microstructure caused by modifications of myelin sheets around axons or by gliosis during the remyelination phase after LPC-induced demyelination in the corpus callosum of rats. We collected MRI data with RAFF4, MT and DTI at 3 days after injection (demyelination stage) and at 38 days after injection (remyelination stage) of LPC (n = 12) or vehicle (n = 9). Cell density and myelin content were assessed by histology. All MRI metrics detected differences between LPC-injected and control groups of animals in the demyelination stage, on day 3. In the remyelination phase (day 38), RAFF4, MT parameters, fractional anisotropy, and axial diffusivity detected signs of a partial recovery consistent with the remyelination evident in histology. Radial diffusivity had undergone a further increase from day 3 to 38 and mean diffusivity revealed a complete recovery correlating with the histological assessment of cell density attributed to gliosis. The combination of RAFF4, MT and DTI has the potential to differentiate between normal, demyelinated and remyelinated axons and gliosis and thus it may be able to provide a more detailed assessment of white matter pathologies in several neurological diseases.

Validation and interpretation of diffusion magnetic resonance imaging (dMRI) requires detailed understanding of the actual microstructure restricting the diffusion of water molecules. In this study, we used serial block-face scanning electron microscopy (SBEM), a three-dimensional electron microscopy (3D-EM) technique, to image seven white and grey matter volumes in the rat brain. SBEM shows excellent contrast of cellular membranes, which are the major components restricting the diffusion of water in tissue. Additionally, we performed 3D structure tensor (3D-ST) analysis on the SBEM volumes and parameterised the resulting orientation distributions using Watson and angular central Gaussian (ACG) probability distributions as well as spherical harmonic (SH) decomposition. We analysed how these parameterisations described the underlying orientation distributions and compared their orientation and dispersion with corresponding parameters from two dMRI methods, neurite orientation dispersion and density imaging (NODDI) and constrained spherical deconvolution (CSD). Watson and ACG parameterisations and SH decomposition captured well the 3D-ST orientation distributions, but ACG and SH better represented the distributions due to its ability to model asymmetric dispersion. The dMRI parameters corresponded well with the 3D-ST parameters in the white matter volumes, but the correspondence was less evident in the more complex grey matter. SBEM imaging and 3D-ST analysis also revealed that the orientation distributions were often not axially symmetric, a property neatly captured by the ACG distribution. Overall, the ability of SBEM to image diffusion barriers in intricate detail, combined with 3D-ST analysis and parameterisation, provides a step forward toward interpreting and validating the dMRI signals in complex brain tissue microstructure.

We present a fully convolutional neural network (ConvNet), named RatLesNetv2, for segmenting lesions in rodent magnetic resonance (MR) brain images. RatLesNetv2 architecture resembles an autoencoder and it incorporates residual blocks that facilitate its optimization. RatLesNetv2 is trained end to end on three-dimensional images and it requires no preprocessing. We evaluated RatLesNetv2 on an exceptionally large dataset composed of 916 T2-weighted rat brain MRI scans of 671 rats at nine different lesion stages that were used to study focal cerebral ischemia for drug development. In addition, we compared its performance with three other ConvNets specifically designed for medical image segmentation. RatLesNetv2 obtained similar to higher Dice coefficient values than the other ConvNets and it produced much more realistic and compact segmentations with notably fewer holes and lower Hausdorff distance. The Dice scores of RatLesNetv2 segmentations also exceeded inter-rater agreement of manual segmentations. In conclusion, RatLesNetv2 could be used for automated lesion segmentation, reducing human workload and improving reproducibility. RatLesNetv2 is publicly available at https://github.com/jmlipman/RatLesNetv2.

El manejo de nutrientes es la implementación de prácticas que permitan obtener un rendimiento óptimo de cultivo y al mismo tiempo minimizar el impacto ambiental. El objetivo de esta publicación es proporcionar principios y prácticas para el manejo de nutrientes en la producción de hortalizas. Este completo artículo contiene recomendaciones de fertilidad para los principales cultivos de Florida, instrucciones para el cálculo de fertilizantes, una guía para detectar deficiencias de nutrientes y más. This is a minor revision adding Tatiana Sanchez as author.

Deep brain stimulation (DBS) has become an important tool in the management of a wide spectrum of diseases in neurology and psychiatry. Target selection is a vital aspect of DBS so that only the desired areas are stimulated. Segmented leads and current steering have been shown to be promising additions to DBS technology enabling better control of the stimulating electric field. Recently introduced orientation selective DBS (OS-DBS) is a related development permitting sensitization of the stimulus to axonal pathways with different orientations by freely controlling the primary direction of the electric field using multiple contacts. Here, we used OS-DBS to stimulate the subthalamic nucleus (STN) in healthy rats while simultaneously monitoring the induced brain activity with fMRI. Maximal activation of the sensorimotor and basal ganglia-thalamocortical networks was observed when the electric field was aligned mediolaterally in the STN pointing in the lateral direction, while no cortical activation was observed with the electric field pointing medially to the opposite direction. Such findings are consistent with mediolateral main direction of the STN fibers, as seen with high resolution diffusion imaging and histology. The asymmetry of the OS-DBS dipolar field distribution using three contacts along with the potential stimulation of the internal capsule, are also discussed. We conclude that OS-DBS offers an additional degree of flexibility for optimization of DBS of the STN which may enable a better treatment response.

Introduction Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings.Research design and methods We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999–2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup.Results SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89).Conclusions Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications.

Non-invasive imaging methods have become essential tools for understanding the central nervous system (CNS) in health and disease. In particular, magnetic resonance imaging (MRI) techniques provide information about the anatomy, microstructure, and function of the brain and spinal cord in vivo non-invasively. However, MRI is limited by its spatial resolution and signal specificity. In order to mitigate these shortcomings, it is crucial to validate MRI with an array of ancillary ex vivo imaging techniques. These techniques include histological methods, such as light and electron microscopy (EM), which can provide specific information on the tissue structure in healthy and diseased brain and spinal cord, at cellular and subcellular level. However, these conventional histological techniques are intrinsically two-dimensional (2D) and, as a result of sectioning, lack volumetric information of the tissue. This limitation can be overcome with genuine three-dimensional (3D) imaging approaches of the tissue. 3D highly resolved information of the CNS achievable by means of other imaging techniques can complement and improve the interpretation of MRI measurements. In this article, we provide an overview of different 3D imaging techniques that can be used to validate MRI. As an example, we introduce an approach of how to combine diffusion MRI and synchrotron X-ray phase contrast tomography (SXRPCT) data. Our approach paves the way for a new multiscale assessment of the CNS allowing to validate and to improve our understanding of in vivo imaging (such as MRI).

Previous studies that focused on treating major depressive disorder with conventional deep brain stimulation (DBS) paradigms produced inconsistent results. In this proof-of-concept preclinical study in rats (n = 8), we used novel paradigms of orientation selective DBS for stimulating the complex circuitry crossing the infralimbic cortex, an area considered analogous to human subgenual cingulate cortex. Using functional MRI at 9.4 T, we monitored whole brain responses to varying the electrical field orientation of DBS within the infralimbic cortex. Substantial alterations of functional MRI responses in the amygdala, a major node connected to the infralimbic cortex implicated in the pathophysiology of depression, were observed. As expected, the activation cluster near the electrode was insensitive to the changes of the stimulation orientation. Hence, our findings substantiate the ability of orientation selective stimulation (OSS) to recruit neuronal pathways of distinct orientations relative to the position of the electrode, even in complex circuits such as those involved in major depressive disorder. We conclude that OSS is a promising approach for stimulating brain areas that inherently require individualisation of the treatment approach.

Disease modification of epilepsy refers to the alleviation of epileptogenesis or comorbidities after genetic or acquired epileptogenic brain insults. There are currently 30 proof-of-concept experimental pharmacologic studies that have demonstrated some beneficial disease-modifying effects. None of these studies, however, has yet passed from the laboratory to the clinic. The International League Against Epilepsy and American Epilepsy Society working groups on antiepileptogenic (AEG) therapies recently released recommendations for conducting preclinical AEG studies, taking into account many of the critiques raised by previous study designs. One of the issues relates to the lack of analysis of AEG efficacy in both sexes. A review of the literature reveals that most of the preclinical studies have been performed using male rodents, whereas clinical study cohorts include both males and females. Therefore, it is important to determine whether sex differences should be taken into account to a greater extent than they have been historically at different phases of experimental studies. Here we address the following questions based on analysis of available experimental AEG studies: (a) whether sex differences should be considered when searching for novel AEG targets, (b) how sex differences can affect the preclinical AEG study designs and analysis of outcome measures, and (c) what factors should be considered when examining the effect of sex on outcome of clinical AEG trials or the clinical use of AEGs.

In this work a new MRI modality entitled Relaxation Along a Fictitious Field in the rotating frame of rank 4 (RAFF4) was evaluated in its ability to detect lower myelin content in lysophosphatidyl choline (LPC)-induced demyelinating lesions. The lesions were induced in two areas of the rat brain with either uniform or complex fiber orientations, i.e., in the corpus callosum (cc) and dorsal tegmental tract (dtg), respectively. RAFF4 showed excellent ability to detect demyelinated lesions and good correlation with myelin content in both brain areas. In comparison, diffusion tensor imaging metrices, fractional anisotropy, mean diffusivity and axonal and radial diffusivity, and magnetization transfer (MT) metrices, longitudinal relaxation during off-resonance irradiation and MT ratio, either failed to detect demyelination in dtg or showed lower correlation with myelin density quantified from gold chloride stained histological sections. Good specifity of RAFF4 to myelin was confirmed by its low correlation with cell density assesed from Nissl stained sections as well as its lack of sensitivity to pH changes in the physiological range as tested in heat denaturated bovine serum albumin phantoms. The excellent ability of RAFF4 to detect myelin content and its insensitivity to fiber orientation distribution, gliosis and pH, together with low specific absorption rate, demonstrates the promise of rotating frame of rank n (RAFFn) as a valuable MRI technique for non-invasive imaging of demyelinating lesions.

Multi-modal MRI techniques have identified biomarkers that could help to predict whether someone will develop epilepsy.

Introducción: los factores psicosociales han mostrado influenciar el estado clínico de pacientes con insuficiencia cardiaca (IC) crónica, particularmente en aquellos pacientes dependientes con alteración del estado mental o déficit del soporte social, en Colombia pocos estudios han sido conducidos para describir la influencia de factores psicosociales y otros factores clínicos relacionados con la enfermedad; por lo cual se realizó la siguiente pregunta de investigación: ¿Cuál es el diagnóstico psicosocial de una cohorte de pacientes del Programa de falla cardiaca y su correlación entre sí y con los parámetros clínicos medidos por Clase funcional, NT-ProBNP y fracción de eyección del ventrículo izquierdo (FEVI%)? Materiales y Métodos: para determinar la influencia de factores psicosociales y clínicos de pacientes con IC, se analizaron las características clínicas, funcionales, biológicas y psicosociales de 68 pacientes con IC crónica de launidad de insuficiencia cardiaca de la Clínica Colombiaa evaluación psicológica y social se realizó en forma prospectiva por enfermeras y psicólogas con entrenamiento en insuficiencia cardiaca, utilizando escalas validadas (escala de depresión geriátrica GDS, minimental, índice de Barthel, test de Minnesota de calidad de vida en pacientes con falla cardiaca y escala europea de autocuidado en insuficiencia cardiaca). Análisis Estadístico: se sistematizó la información en el paquete SPSS versión 15.0. Se describen las variables cualitativas con frecuencias simples y porcentajes y las numéricas con medidas de tendencia central (promedio y mediana) y de dispersión (rango y desviación estándar). Las relaciones de las variables de evaluación psicosocial con género y clase funcional se analizaron con la prueba ji cuadrado de Pearson, con una prueba de verosimilitud exacta menor de 5. La relación entre si de las pruebas psicosociales se analizó con ji cuadrado de Pearson. Las diferencias en edad, fracción de eyección del ventrículo izquierdo (FEVI) y BNP con la prueba no paramétrica para grupos independientes exacta de Mann Whitney Resultados: la cohorte conformada por 68 pacientes tuvo una edad promedio 68,7 ± 13,4 años, 60,3% hombres, 44% en clase funcional de la NYHA III-IV, disminución de la FEVI (menor 40%) en 59% y etiología isquémica en 45,6% de los pacientes. La evaluación del estado afectivo fue anormal en 11,9% de los pacientes, mostró una correlación directa con los niveles de BNP (p=0.024) y una tendencia a correlación con el test de APGAR para disfunción familiar (p=0,61). Se observó una peor calidad de vida en los pacientes con mayor Clase Funcional de la NYHA (p=0.001) y FEVI

The adverse effects of alcohol consumption during pregnancy are known, but the molecular events that lead to the phenotypic characteristics are unclear. To unravel the molecular mechanisms, we have used a mouse model of gestational ethanol exposure, which is based on maternal ad libitum ingestion of 10% (v/v) ethanol for the first 8 days of gestation (GD 0.5-8.5). Early neurulation takes place by the end of this period, which is equivalent to the developmental stage early in the fourth week post-fertilization in human. During this exposure period, dynamic epigenetic reprogramming takes place and the embryo is vulnerable to the effects of environmental factors. Thus, we hypothesize that early ethanol exposure disrupts the epigenetic reprogramming of the embryo, which leads to alterations in gene regulation and life-long changes in brain structure and function. Genome-wide analysis of gene expression in the mouse hippocampus revealed altered expression of 23 genes and three miRNAs in ethanol-exposed, adolescent offspring at postnatal day (P) 28. We confirmed this result by using two other tissues, where three candidate genes are known to express actively. Interestingly, we found a similar trend of upregulated gene expression in bone marrow and main olfactory epithelium. In addition, we observed altered DNA methylation in the CpG islands upstream of the candidate genes in the hippocampus. Our MRI study revealed asymmetry of brain structures in ethanol-exposed adult offspring (P60): we detected ethanol-induced enlargement of the left hippocampus and decreased volume of the left olfactory bulb. Our study indicates that ethanol exposure in early gestation can cause changes in DNA methylation, gene expression, and brain structure of offspring. Furthermore, the results support our hypothesis of early epigenetic origin of alcohol-induced disorders: changes in gene regulation may have already taken place in embryonic stem cells and therefore can be seen in different tissue types later in life.

HS-1102, a 20-page fact sheet by Alejandra Sierra, Eric Simonne, and Danielle Treadwell, explains 5 key principles and 3 key practices for nutrient management in vegetable production for Spanish-speaking audiences. Includes references, and several tables. Published by the UF Department of Horticultural Sciences, July 2007. HS1102/HS356: Principios y prácticas para el manejo de nutrientes en la produccion de hortalizas (ufl.edu)

Introduction: Psychological inflexibility is the systematic use of ineffective behavioral regulation strategies that in the long-term worsen psychological distress and quality of life. Evidence suggests that psychological inflexibility is a trans-diagnostic process essential to mental-health that predicts "emotional and affective disorders". This study proposes two trans-diagnostic models of risk based on experiential avoidance, cognitive fusion, repetitive negative thinking, and values obstruction and generalized pliance as part of a "psychological inflexibility" super-ordinated factor using available instruments which already have psychometric properties and factor structure analyses, along with evidence of validity and reliability in Colombia. Said super-ordinated factor is expected to be associated to the outcome variables in the current sample and have some relationship with other latent superordinated factors deemed "sociodemographic variables", "sexuality", "mental health history" and "suicide risk". Method: There was a cross-sectional correlational design and a non-randomized convenience sampling. The sample was 541 young adults from Cundinamarca aging from 18 to 39 (M=28.86; SD=5.66), most of them cisgender (98%; n=530), assigned female at birth (81.9%; n=443) and identified as women (81.5%; n=441). They responded to an online survey inquiring sexuality, sociodemographic and mental health history aspects and including emotional symptomatology, experiential avoidance, cognitive fusion, repetitive negative thinking, values obstruction and generalized pliance assessment. Structural Equation Modelling was used to adjust the aforementioned models. Results: Both models had a good fit. Psychological inflexibility (β= .70) and suicide risk (β= .33) had a moderate relationship (r= .66) and were associated with emotional symptomatology. Emotional symptomatology (β= 1.56) and psychological inflexibility (β=-.77) had a strong relationship (r= .95) and were associated with suicide risk. Discussion: There is preliminary evidence for the role of psychological inflexibility and sexuality related variables as potential risk factors associated with emotional symptomatology and suicide risk, supporting some of the assumptions from the ACT model. [ABSTRACT FROM AUTHOR]