A Killing Disease Epidemic Among Displaced Sudanese Population Identified as Visceral Leishmaniasis.

A fatal disease epidemic affected the Bentiu area in southern Sudan and led to a mass migration of the Nuer tribe searching for treatment. The initially available information revealed a high mortality rate due to a possible occurrence of tuberculosis, malaria, enteric fever or visceral leishmaniasis (VL). Serological screening of 53 of the most severely affected patients in an enzyme-linked immunosorbent assay (ELISA) or an improved direct agglutination test (DAT) revealed positivity for VL. In 39 of those patients, diagnosis was confirmed by identification of Leishmania donovani amastigotes in lymph node or bone-marrow aspirates. In a total of 2714 patients observed, 1195 (44.0%) had clinical symptoms suggesting VL: DAT positive titers (1:3200-greater than or equal to 1:12800) were obtained in 654 (24.1%), of whom 325 were confirmed parasitologically. Forty-two VL cases died before or during treatment, giving a mortality rate of 6.4%. Among the intercurrent infections diagnosed in the VL population (654), respiratory involvements (31.7%) and malaria (10.7%) were most prevalent. With the exception of four (0.6%), all other VL patients (509) responded readily to sodium stibogluconate. The factors initiating the outbreak are discussed. Malnutrition and nomadic movements to potential VL endemic areas appeared to be the most important. HIV infection as a possible predisposition seemed remote considering the clinical and epidemiological similarity to VL occurring in East Africa, adequate humoral response in DAT, and immediate positive response to specific anti-Leishmania chemotherapy

The K luminosity-metallicity relation for dwarf galaxies and the tidal dwarf galaxies in the tails of HCG 31

We determine a K-band luminosity-metallicity (K-Z) relation for dwarf irregular galaxies, over a large range of magnitudes, -20.5 < M_K < -13.5, using a combination of K photometry from either the 2-micron all sky survey (2MASS) or the recent study of Vadivescu er al. (2005), and metallicities derived mainly with the T_e method, from several different studies. We then use this newly-derived relation, together with published K_s photometry and our new spectra of objects in the field of HCG 31 to discuss the nature of the possible tidal dwarf galaxies of this group. We catalogue a new member of HCG 31, namely "R", situated ~40 kpc north of the group center, composed by a ring of H alpha knots which coincides with a peak in HI. This object is a deviant point in the K-Z relation (it has too high metallicity for its luminosity) and its projected distance to the parent galaxy and large gas reservoir makes it one of the most promising tidal dwarf galaxy candidates of HCG 31, together with object F. The subsystems A1, E, F, H and R all have metallicities similar to that of the galaxies A+C and B, result that is expected in a scenario where those were formed from material expelled from the central galaxies of HCG 31. While objects A1, E and H will most probably fall back onto their progenitors, F and R may survive as tidal dwarf galaxies. We find that two galaxies of HCG 31, G and Q, have A+em spectral signatures, and are probably evolving toward a post-starburst phase.Comment: 32 pages, 4 figures - Submitted to AJ - A version of this paper with full resolution figures can be found at http://www.astro.iag.usp.br/~eduardo/HCG31-KZrelation.pd

Automated characterization of noise distributions in diffusion MRI data

Knowledge of the noise distribution in diffusion MRI is the centerpiece to quantify uncertainties arising from the acquisition process. Accurate estimation beyond textbook distributions often requires information about the acquisition process, which is usually not available. We introduce two new automated methods using the moments and maximum likelihood equations of the Gamma distribution to estimate all unknown parameters using only the magnitude data. A rejection step is used to make the framework automatic and robust to artifacts. Simulations were created for two diffusion weightings with parallel imaging. Furthermore, MRI data of a water phantom with different combinations of parallel imaging were acquired. Finally, experiments on freely available datasets are used to assess reproducibility when limited information about the acquisition protocol is available. Additionally, we demonstrated the applicability of the proposed methods for a bias correction and denoising task on an in vivo dataset. A generalized version of the bias correction framework for non integer degrees of freedom is also introduced. The proposed framework is compared with three other algorithms with datasets from three vendors, employing different reconstruction methods. Simulations showed that assuming a Rician distribution can lead to misestimation of the noise distribution in parallel imaging. Results showed that signal leakage in multiband can also lead to a misestimation of the noise distribution. Repeated acquisitions of in vivo datasets show that the estimated parameters are stable and have lower variability than compared methods. Results show that the proposed methods reduce the appearance of noise at high b-value. The proposed algorithms herein can estimate both parameters of the noise distribution automatically, are robust to signal leakage artifacts and perform best when used on acquired noise maps.Comment: v3: Peer reviewed version v2: Manuscript as submitted to Medical image analysis v1: Manuscript as submitted to Magnetic resonance in medicin

Embryologically Based Classification Specifies Gender Differences in the Prevalence of Orofacial Cleft Subphenotypes

Background: A recently published validated classification system divides all orofacial cleft (OFC) subphenotypes into groups based on underlying developmental mechanisms, that is, fusion and differentiation, and their timing, that is, early and late periods, in embryogenesis of the primary and secondary palates. Aims: The aim of our study was to define gender differences in prevalence for all subphenotypes in newborns with OFC in the Netherlands. Methods: This was a retrospective cross-sectional study on children with OFC born from 2006 to 2016. Clefts were classified in early (E-), late (L-), and early/late (EL-) embryonic periods, in primary (P-), secondary (S-), and primary/secondary (PS-) palates, and further divided into fusion (F-), differentiation (D-), and fusion/differentiation (FD-) defects, respectively. Results: A total of 2089 OFC children were analyzed (1311 males and 778 females). Orofacial cleft subphenotypes in females occurred significantly more frequent in the L-period compared to males (66% vs 55%, P = .000), whereas clefts in males occurred significantly more in the EL-periods (40% vs 27%, P = .000). Females had significantly more S-palatal clefts (42% vs 23%, P = .000), while males had significantly more PS-palatal clefts (44% vs 30%, P = .000). Furthermore, the clefts in females were significantly more frequent the result of an F-defect (60% vs 52%, P = .000). Conclusions: Orofacial cleft in females mainly occur in the L-period are mostly S-palatal clefts, and are usually the result of an F-defect. Orofacial cleft in males more commonly occur in the EL-periods, are therefore more often combined PS-palatal clefts, and are more frequent D- and FD-defects

Falls prevention at GP practices:A description of daily practice

BACKGROUND: General practitioners (GPs) can be considered the designated professionals to identify high fall risk and to guide older people to fall preventive care. Currently it is not exactly known how GPs treat this risk. This study aims to investigate GPs’ daily practice regarding fall preventive care for frail older patients. METHODS: Sixty-five GPs from 32 Dutch practices participated in this study for a period of 12 months. When a GP entered specific International Classification of Primary Care-codes related to frailty and/or high fall risk in their Electronic Health Records, a pop-up appeared asking “Is this patient frail?”. If the GP confirmed this, the GP completed a short questionnaire about patient’s fall history and fear of falling (FOF), and the fall preventive care provided. RESULTS: The GPs completed questionnaires regarding 1394 frail older patients aged ≥75. Of 20% of these patients, the GPs did not know whether they had experienced a fall or not. The GPs did not know whether a FOF existed in even more patients (29%). Of the patients with a fall history and/or a FOF (N = 726), 37% (N = 271) received fall preventive care. Two main reasons for not offering fall preventive care to these patients were: I) the patient finds treatment too intensive or too much of a hassle (37%), and II) the GP identified a high fall risk but the patient did not acknowledge this (14%). When patients were treated for high fall risk, the GP and the physiotherapist were the most frequently involved health care providers. The involved health care providers most often treated mobility limitations, cardiovascular risk factors, and FOF. CONCLUSIONS: The results from this study show that GPs were frequently not aware of their frail patient’s fall history and/or FOF and that the majority of the frail older patients with a fall history and/or FOF did not receive fall preventive care. Developing systematic screening strategies for the primary care setting enhancing the identification of high fall risk and the provision of fall preventive care may improve patients’ quality of life and reduce health care costs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12875-021-01540-7

Transferring principles of solid-state and Laplace NMR to the field of in vivo brain MRI

Magnetic resonance imaging (MRI) is the primary method for non-invasive investigations of the human brain in health, disease, and development, but yields data that are difficult to interpret whenever the millimeter scale voxels contain multiple microscopic tissue environments with different chemical and structural properties. We propose a novel MRI framework to quantify the microscopic heterogeneity of the living human brain as spatially resolved five-dimensional relaxation-diffusion distributions by augmenting a conventional diffusion-weighted imaging sequence with signal encoding principles from multidimensional solid-state nuclear magnetic resonance (NMR) spectroscopy, relaxation-diffusion correlation methods from Laplace NMR of porous media, and Monte Carlo data inversion. The high dimensionality of the distribution space allows resolution of multiple microscopic environments within each heterogeneous voxel as well as their individual characterization with novel statistical measures that combine the chemical sensitivity of the relaxation rates with the link between microstructure and the anisotropic diffusivity of tissue water. The proposed framework is demonstrated on a healthy volunteer using both exhaustive and clinically viable acquisition protocols

The effect of gradient nonlinearities on fiber orientation estimates from spherical deconvolution of diffusion MRI data

Gradient nonlinearities in magnetic resonance imaging (MRI) cause spatially varying mismatches between the imposed and the effective gradients and can cause significant biases in rotationally invariant diffusion MRI measures derived from, for example, diffusion tensor imaging. The estimation of the orientational organization of fibrous tissue, which is nowadays frequently performed with spherical deconvolution techniques ideally using higher diffusion weightings, can likewise be biased by gradient nonlinearities. We explore the sensitivity of two established spherical deconvolution approaches to gradient nonlinearities, namely constrained spherical deconvolution (CSD) and damped Richardson‐Lucy (dRL). Additionally, we propose an extension of dRL to take into account gradient imperfections, without the need of data interpolation. Simulations show that using the effective b‐matrix can improve dRL fiber orientation estimation and reduces angular deviations, while CSD can be more robust to gradient nonlinearity depending on the implementation. Angular errors depend on a complex interplay of many factors, including the direction and magnitude of gradient deviations, underlying microstructure, SNR, anisotropy of the effective response function, and diffusion weighting. Notably, angular deviations can also be observed at lower b‐values in contrast to the perhaps common assumption that only high b‐value data are affected. In in vivo Human Connectome Project data and acquisitions from an ultrastrong gradient (300 mT/m) scanner, angular differences are observed between applying and not applying the effective gradients in dRL estimation. As even small angular differences can lead to error propagation during tractography and as such impact connectivity analyses, incorporating gradient deviations into the estimation of fiber orientations should make such analyses more reliable

Computing and visualising intra-voxel orientation-specific relaxation-diffusion features in the human brain

Diffusion MRI techniques are used widely to study the characteristics of the human brain connectome in vivo. However, to resolve and characterise white matter (WM) fibres in heterogeneous MRI voxels remains a challenging problem typically approached with signal models that rely on prior information and constraints. We have recently introduced a 5D relaxation–diffusion correlation framework wherein multidimensional diffusion encoding strategies are used to acquire data at multiple echo‐times to increase the amount of information encoded into the signal and ease the constraints needed for signal inversion. Nonparametric Monte Carlo inversion of the resulting datasets yields 5D relaxation–diffusion distributions where contributions from different sub‐voxel tissue environments are separated with minimal assumptions on their microscopic properties. Here, we build on the 5D correlation approach to derive fibre‐specific metrics that can be mapped throughout the imaged brain volume. Distribution components ascribed to fibrous tissues are resolved, and subsequently mapped to a dense mesh of overlapping orientation bins to define a smooth orientation distribution function (ODF). Moreover, relaxation and diffusion measures are correlated to each independent ODF coordinate, thereby allowing the estimation of orientation‐specific relaxation rates and diffusivities. The proposed method is tested on a healthy volunteer, where the estimated ODFs were observed to capture major WM tracts, resolve fibre crossings, and, more importantly, inform on the relaxation and diffusion features along with distinct fibre bundles. If combined with fibre‐tracking algorithms, the methodology presented in this work has potential for increasing the depth of characterisation of microstructural properties along individual WM pathways