Endoscopic Diagnosis of Jejuno-Gastric Intussusception

Jejunogastric intussusception is a rare complication of gastric surgery that is potentially life threatening if it is not diagnosed early. This condition is a surgical emergency and is most commonly seen after gastro-jejunostomy. The authors report a case of an elderly female patient who presented with  hematemesis and abdominal pain. Endoscopic evaluation revealed prolapsed small bowel into the stomach which was subsequently reduced intra-operatively. She had an uneventful post operative stay. This entity is fatal without surgical intervention. Diagnostic modalities like CT scan and  endoscopy are key in the management of this entity.Keywords: Retrograde jejunogastric intususception, Gastric surgery, Gastro-jejunostom

Geospatial modeling of child mortality across 27 countries in Sub-Saharan Africa

Preventable mortality of children has been targeted as one of the UN’s Sustainable Development Goals for the 2015-30 period. Global decreases in child mortality (4q1) have been seen, although sub-Saharan Africa remains an area of concern, with child mortality rates remaining high relative to global averages or even increasing in some cases. Furthermore, the spatial distribution of child mortality in sub-Saharan Africa is highly heterogeneous. Thus, research that identifies primary risk factors and protective measures in the geographic context of sub-Saharan Africa is needed. In this study, household survey data collected by The Demographic and Health Surveys (DHS) Program aggregated at DHS sub-national area scale are used to evaluate the spatial distribution of child mortality (age 1 to 4) across 27 sub-Saharan Africa countries in relation to a number of demographic and health indicators collected in the DHS surveys. In addition, this report controls for spatial variation in potential environmental drivers of child mortality by modeling it against a suite of geospatial datasets. These datasets vary across the study area in an autoregressive spatial model that accounts for the spatial autocorrelation present in the data. This study shows that socio-demographic factors such as birth interval, stunting, access to health facilities and literacy, along with geospatial factors such as prevalence of Plasmodium falciparum malaria, variety of ethnic groups, mean temperature, and intensity of lights at night can explain up to 60% of the variance in child mortality across 255 DHS sub-national areas in the 27 countries. Additionally, three regions - Western, Central, and Eastern Africa - have markedly different mortality rates. By identifying the relative importance of policy-relevant socio-demographic and environmental factors, this study highlights priorities for research and programs targeting child mortality over the next decade. <br/

Transition State Analysis of the Reaction Catalyzed by the Phosphotriesterase from Sphingiobium sp. TCM1

Organophosphorus flame retardants are stable toxic compounds used in nearly all durable plastic products and are considered major emerging pollutants. The phosphotriesterase from Sphingobium sp. TCM1 (Sb-PTE) is one of the few enzymes known to be able to hydrolyze organophosphorus flame retardants such as triphenyl phosphate and tris(2-chloroethyl) phosphate. The effectiveness of Sb-PTE for the hydrolysis of these organophosphates appears to arise from its ability to hydrolyze unactivated alkyl and phenolic esters from the central phosphorus core. How Sb-PTE is able to catalyze the hydrolysis of the unactivated substituents is not known. To interrogate the catalytic hydrolysis mechanism of Sb-PTE, the pH dependence of the reaction and the effects of changing the solvent viscosity were determined. These experiments were complemented by measurement of the primary and secondary 18-oxygen isotope effects on substrate hydrolysis and a determination of the effects of changing the pKa of the leaving group on the magnitude of the rate constants for hydrolysis. Collectively, the results indicated that a single group must be ionized for nucleophilic attack and that a separate general acid is not involved in protonation of the leaving group. The Brønsted analysis and the heavy atom kinetic isotope effects are consistent with an early associative transition state with subsequent proton transfers not being rate limiting. A novel binding mode of the substrate to the binuclear metal center and a catalytic mechanism are proposed to explain the unusual ability of Sb-PTE to hydrolyze unactivated esters from a wide range of organophosphate substrates

Multivariate risks and depth-trimmed regions

We describe a general framework for measuring risks, where the risk measure takes values in an abstract cone. It is shown that this approach naturally includes the classical risk measures and set-valued risk measures and yields a natural definition of vector-valued risk measures. Several main constructions of risk measures are described in this abstract axiomatic framework. It is shown that the concept of depth-trimmed (or central) regions from the multivariate statistics is closely related to the definition of risk measures. In particular, the halfspace trimming corresponds to the Value-at-Risk, while the zonoid trimming yields the expected shortfall. In the abstract framework, it is shown how to establish a both-ways correspondence between risk measures and depth-trimmed regions. It is also demonstrated how the lattice structure of the space of risk values influences this relationship.Comment: 26 pages. Substantially revised version with a number of new results adde

Explainability of deep neural networks for MRI analysis of brain tumors

Purpose Artificial intelligence (AI), in particular deep neural networks, has achieved remarkable results for medical image analysis in several applications. Yet the lack of explainability of deep neural models is considered the principal restriction before applying these methods in clinical practice. Methods In this study, we propose a NeuroXAI framework for explainable AI of deep learning networks to increase the trust of medical experts. NeuroXAI implements seven state-of-the-art explanation methods providing visualization maps to help make deep learning models transparent. Results NeuroXAI has been applied to two applications of the most widely investigated problems in brain imaging analysis, i.e., image classification and segmentation using magnetic resonance (MR) modality. Visual attention maps of multiple XAI methods have been generated and compared for both applications. Another experiment demonstrated that NeuroXAI can provide information flow visualization on internal layers of a segmentation CNN. Conclusion Due to its open architecture, ease of implementation, and scalability to new XAI methods, NeuroXAI could be utilized to assist radiologists and medical professionals in the detection and diagnosis of brain tumors in the clinical routine of cancer patients. The code of NeuroXAI is publicly accessible at https://github.com/razeineldin/NeuroXAI

iRegNet: Non-rigid Registration of MRI to Interventional US for Brain-Shift Compensation using Convolutional Neural Networks

Accurate and safe neurosurgical intervention can be affected by intra-operative tissue deformation, known as brain-shift. In this study, we propose an automatic, fast, and accurate deformable method, called iRegNet, for registering pre-operative magnetic resonance images to intra-operative ultrasound volumes to compensate for brain-shift. iRegNet is a robust end-to-end deep learning approach for the non-linear registration of MRI-iUS images in the context of image-guided neurosurgery. Pre-operative MRI (as moving image) and iUS (as fixed image) are first appended to our convolutional neural network, after which a non-rigid transformation field is estimated. The MRI image is then transformed using the output displacement field to the iUS coordinate system. Extensive experiments have been conducted on two multi-location databases, which are the BITE and the RESECT. Quantitatively, iRegNet reduced the mean landmark errors from pre-registration value of (4.18 ± 1.84 and 5.35 ± 4.19 mm) to the lowest value of (1.47 ± 0.61 and 0.84 ± 0.16 mm) for the BITE and RESECT datasets, respectively. Additional qualitative validation of this study was conducted by two expert neurosurgeons through overlaying MRI-iUS pairs before and after the deformable registration. Experimental findings show that our proposed iRegNet is fast and achieves state-of-the-art accuracies outperforming state-of-the-art approaches. Furthermore, the proposed iRegNet can deliver competitive results, even in the case of non-trained images as proof of its generality and can therefore be valuable in intra-operative neurosurgical guidance

The pro-neurotrophin receptor sortilin is a major neuronal apolipoprotein E receptor for catabolism of amyloid-β peptide in the brain

Apolipoprotein E (APOE) is the major risk factor for sporadic Alzheimer's disease. Among other functions, APOE is proposed to sequester neurotoxic amyloid-{beta} (A{beta}) peptides in the brain, delivering them to cellular catabolism via neuronal APOE receptors. Still, the receptors involved in this process remain controversial. Here, we identified the pro-neurotrophin receptor sortilin as major endocytic pathway for clearance of APOE/A{beata} complexes in neurons. Sortilin binds APOE with high affinity. Lack of receptor expression in mice results in accumulation of APOE and of A{beta} in the brain and in aggravated plaque burden. Also, primary neurons lacking sortilin exhibit significantly impaired uptake of APOE/A{beta} complexes despite proper expression of other APOE receptors. Despite higher than normal brain APOE levels, sortilin-deficient animals display anomalies in brain lipid metabolism (e.g., accumulation of sulfatides) seen in APOE-deficient mice, indicating functional deficiency in cellular APOE uptake pathways. Together, our findings identified sortilin as an essential neuronal pathway for APOE-containing lipoproteins in vivo and suggest an intriguing link between A{beta} catabolism and pro-neurotrophin signaling converging on this receptor

Block of death-receptor apoptosis protects mouse cytomegalovirus from macrophages and is a determinant of virulence in immunodeficient hosts.

The inhibition of death-receptor apoptosis is a conserved viral function. The murine cytomegalovirus (MCMV) gene M36 is a sequence and functional homologue of the human cytomegalovirus gene UL36, and it encodes an inhibitor of apoptosis that binds to caspase-8, blocks downstream signaling and thus contributes to viral fitness in macrophages and in vivo. Here we show a direct link between the inability of mutants lacking the M36 gene (ΔM36) to inhibit apoptosis, poor viral growth in macrophage cell cultures and viral in vivo fitness and virulence. ΔM36 grew poorly in RAG1 knockout mice and in RAG/IL-2-receptor common gamma chain double knockout mice (RAGγC(-/-)), but the depletion of macrophages in either mouse strain rescued the growth of ΔM36 to almost wild-type levels. This was consistent with the observation that activated macrophages were sufficient to impair ΔM36 growth in vitro. Namely, spiking fibroblast cell cultures with activated macrophages had a suppressive effect on ΔM36 growth, which could be reverted by z-VAD-fmk, a chemical apoptosis inhibitor. TNFα from activated macrophages synergized with IFNγ in target cells to inhibit ΔM36 growth. Hence, our data show that poor ΔM36 growth in macrophages does not reflect a defect in tropism, but rather a defect in the suppression of antiviral mediators secreted by macrophages. To the best of our knowledge, this shows for the first time an immune evasion mechanism that protects MCMV selectively from the antiviral activity of macrophages, and thus critically contributes to viral pathogenicity in the immunocompromised host devoid of the adaptive immune system