Genetic landscape of autism spectrum disorder in Vietnamese children

Autism spectrum disorder (ASD) is a complex disorder with an unclear aetiology and an estimated global prevalence of 1%. However, studies of ASD in the Vietnamese population are limited. Here, we first conducted whole exome sequencing (WES) of 100 children with ASD and their unaffected parents. Our stringent analysis pipeline was able to detect 18 unique variants (8 de novo and 10 ×-linked, all validated), including 12 newly discovered variants. Interestingly, a notable number of X-linked variants were detected (56%), and all of them were found in affected males but not in affected females. We uncovered 17 genes from our ASD cohort in which CHD8, DYRK1A, GRIN2B, SCN2A, OFD1 and MDB5 have been previously identified as ASD risk genes, suggesting the universal aetiology of ASD for these genes. In addition, we identified six genes that have not been previously reported in any autism database: CHM, ENPP1, IGF1, LAS1L, SYP and TBX22. Gene ontology and phenotype-genotype analysis suggested that variants in IGF1, SYP and LAS1L could plausibly confer risk for ASD. Taken together, this study adds to the genetic heterogeneity of ASD and is the first report elucidating the genetic landscape of ASD in Vietnamese children

An Efficient Event-driven Neuromorphic Architecture for Deep Spiking Neural Networks

© 2019 IEEE. Deep Neural Networks (DNNs) have been successfully applied to various real-world machine learning applications. However, performing large DNN inference tasks in real-time remains a challenge due to its substantial computational costs. Recently, Spiking Neural Networks (SNNs) have emerged as an alternative way of processing DNN'fs task. Due to its eventbased, data-driven computation, SNN reduces both inference latency and complexity. With efficient conversion methods from traditional DNN, SNN exhibits similar accuracy, while leveraging many state-of-the-art network models and training methods. In this work, an efficient neuromorphic hardware architecture for image recognition task is presented. To preserve accuracy, the analog-to-spiking conversion algorithm is adopted. The system aims to minimize hardware area cost and power consumption, enabling neuromorphic hardware processing in edge devices. Simulation results have shown that, with the MNIST digit recognition task, the system has achieved × 20 reduction in terms of core area cost compared to the state-of-the-art works, with an accuracy of 94.4%, core area of 15 μ m2 at a maximum frequency of 250 MHz

Eco-friendly facile synthesis of Co3O4-Pt nanorods for ethylene detection towards fruit quality monitoring

Ethylene, a biomarker widely employed for evaluating fruit ripening during storage, exists at extremely low concentrations. Therefore a gas sensor with high sensitivity and a sub-ppm detection limit is needed. In this work, porous Co3O4 nanorods were synthesized through a hydrothermal method involving Co(NO3)2, Na2C2O4, H2O and ethylene glycol (EG), followed by annealing at 400 degrees C in air. The surface of the porous Co3O4 nanorods was functionalized with Pt nanoparticles to enhance the ethylene sensing performance. The effect of Co3O4 surface functionalisation with Pt nanoparticles was investigated by adding different amounts of nanoparticles. The sensor's outstanding performance at the optimum working temperature of 250 degrees C is attributed to the synergy between the high catalytic activity of Pt nanoparticles and the extensive surface area of the porous Co3O4 nanorods. Compared to pure Co3O4, the 0.031 wt% Pt sensor showed better ethylene sensing performance with a response 3.4 times that of pristine Co3O4. The device also demonstrated high selectivity, repeatability, long-term stability and a detection limit of 0.13 ppm for ethylene, which is adequate for fruit quality monitoring. The gas sensing mechanism of porous Co3O4 nanorods and the influence of Pt decoration on sensor performance are discussed

Coma in fatal adult human malaria is not caused by cerebral oedema

<p>Abstract</p> <p>Background</p> <p>The role of brain oedema in the pathophysiology of cerebral malaria is controversial. Coma associated with severe <it>Plasmodium falciparum </it>malaria is multifactorial, but associated with histological evidence of parasitized erythrocyte sequestration and resultant microvascular congestion in cerebral vessels. To determine whether these changes cause breakdown of the blood-brain barrier and resultant perivascular or parenchymal cerebral oedema, histology, immunohistochemistry and image analysis were used to define the prevalence of histological patterns of oedema and the expression of specific molecular pathways involved in water balance in the brain in adults with fatal falciparum malaria.</p> <p>Methods</p> <p>The brains of 20 adult Vietnamese patients who died of severe malaria were examined for evidence of disrupted vascular integrity. Immunohistochemistry and image analysis was performed on brainstem sections for activation of the vascular endothelial growth factor (VEGF) receptor 2 and expression of the aquaporin 4 (AQP4) water channel protein. Fibrinogen immunostaining was assessed as evidence of blood-brain barrier leakage and perivascular oedema formation. Correlations were performed with clinical, biochemical and neuropathological parameters of severe malaria infection.</p> <p>Results</p> <p>The presence of oedema, plasma protein leakage and evidence of VEGF signalling were heterogeneous in fatal falciparum malaria and did not correlate with pre-mortem coma. Differences in vascular integrity were observed between brain regions with the greatest prevalence of disruption in the brainstem, compared to the cortex or midbrain. There was a statistically non-significant trend towards higher AQP4 staining in the brainstem of cases that presented with coma (<it>P </it>= .02).</p> <p>Conclusions</p> <p>Histological evidence of cerebral oedema or immunohistochemical evidence of localised loss of vascular integrity did not correlate with the occurrence of pre-mortem coma in adults with fatal falciparum malaria. Enhanced expression of AQP4 water channels in the brainstem may, therefore, reflect a mix of both neuropathological or attempted neuroprotective responses to oedema formation.</p

Evaluation of the MODS Culture Technique for the Diagnosis of Tuberculous Meningitis

Tuberculous meningitis (TBM) is a devastating condition. The rapid instigation of appropraite chemotherapy is vital to reduce morbidity and mortality. However rapid diagnosis remains elusive; smear microscopy has extremely low sensitivity on cerebrospinal fluid (CSF) in most laboratories and PCR requires expertise with advanced infrastructure and has sensitivity of only around 60% under optimal conditions. Neither technique allows for the microbiological isolation of M. tuberculosis and subsequent drug susceptibility testing. We evaluated the recently developed microscopic observation drug susceptibility (MODS) assay format for speed and accuracy in diagnosing TBM.Two hundred and thirty consecutive CSF samples collected from 156 patients clinically suspected of TBM on presentation at a tertiary referal hospital in Vietnam were enrolled into the study over a five month period and tested by Ziehl-Neelsen (ZN) smear, MODS, Mycobacterial growth Indicator tube (MGIT) and Lowenstein-Jensen (LJ) culture. Sixty-one samples were from patients already on TB therapy for >1day and 19 samples were excluded due to untraceable patient records. One hundred and fifty samples from 137 newly presenting patients remained. Forty-two percent (n = 57/137) of patients were deemed to have TBM by clinical diagnostic and microbiological criteria (excluding MODS). Sensitivity by patient against clinical gold standard for ZN smear, MODS MGIT and LJ were 52.6%, 64.9%, 70.2% and 70.2%, respectively. Specificity of all microbiological techniques was 100%. Positive and negative predictive values for MODS were 100% and 78.7%, respectively for HIV infected patients and 100% and 82.1% for HIV negative patients. The median time to positive was 6 days (interquartile range 5-7), significantly faster than MGIT at 15.5 days (interquartile range 12-24), and LJ at 24 days (interquartile range 18-35 days) (P<0.01).We have shown MODS to be a sensitive, rapid technique for the diagnosis of TBM with high sensitivity, ease of performance and low cost (0.53 USD/sample)

Diagnostic Accuracy of NS1 ELISA and Lateral Flow Rapid Tests for Dengue Sensitivity, Specificity and Relationship to Viraemia and Antibody Responses

Dengue is a viral infection of humans that is transmitted by mosquitoes. Dengue is a very important public health problem in many developing countries. Recently, new tests to help diagnose patients with dengue have been developed. Evaluating these tests to see how well they perform in different countries and in different health care settings is an important process that helps to guide health care policy on whether these assays are likely to be useful in making a diagnosis, and if so, when best to use them. Our hospital-based results, using two different types of NS1 tests for diagnosing dengue, indicates that these tests are most sensitive when used during the first 3 days of illness and are most likely to be positive if the patient has primary dengue. Our results also show that a positive NS1 test result is a reflection of the amount of virus in the blood, so that patients with high amounts of virus in the blood are more likely to be NS1 positive. Collectively, the results indicate these NS1 tests deserve inclusion in the diagnostic approach to dengue

Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases

Distinct Temporal and Anatomical Distributions of Amyloid-β and Tau Abnormalities following Controlled Cortical Impact in Transgenic Mice

Traumatic brain injury (TBI) is a major environmental risk factor for Alzheimer's disease. Intracellular accumulations of amyloid-β and tau proteins have been observed within hours following severe TBI in humans. Similar abnormalities have been recapitulated in young 3xTg-AD mice subjected to the controlled cortical impact model (CCI) of TBI and sacrificed at 24 h and 7 days post injury. This study investigated the temporal and anatomical distributions of amyloid-β and tau abnormalities from 1 h to 24 h post injury in the same model. Intra-axonal amyloid-β accumulation in the fimbria was detected as early as 1 hour and increased monotonically over 24 hours following injury. Tau immunoreactivity in the fimbria and amygdala had a biphasic time course with peaks at 1 hour and 24 hours, while tau immunoreactivity in the contralateral CA1 rose in a delayed fashion starting at 12 hours after injury. Furthermore, rapid intra-axonal amyloid-β accumulation was similarly observed post controlled cortical injury in APP/PS1 mice, another transgenic Alzheimer's disease mouse model. Acute increases in total and phospho-tau immunoreactivity were also evident in single transgenic TauP301L mice subjected to controlled cortical injury. These data provide further evidence for the causal effects of moderately severe contusional TBI on acceleration of acute Alzheimer-related abnormalities and the independent relationship between amyloid-β and tau in this setting