Correlation of serum aspartate aminotransferase level to platelet count ratio index with non-alcoholic fatty liver disease activity score

In case of non-alcoholic fatty liver disease, the ratio of serum aspartate  aminotransferase (AST) level to platelet count index has been proposed as a non-invasive and readily available tool for the assessment of non-alcoholic steatohepatitis. The study was conducted on 50  non-alcoholic fatty liver disease patient (25  non-alcoholic steatohepatitis and 25 simple steatosis). The mean (± SD) serum AST level in the non-alcoholic steatohepatitis group  was 55.2 ± 30.1 IU/L whereas in simple steatosis group it was 33.6 ± 20.0 IU/L. The mean platelet count in the non-alcoholic steatohepatitis group was 303.1 ± 68.7 x 109 /L whereas in the simple steatosis group it was 327.8 ± 66.8 x 109/L. The mean AST platelet ratio index (APRI) score in non-alcoholic steatohepatitis group was 0.5 ± 0.3 and in the simple steatosis group it was 0.3 ± 0.2. In conclusion, the APRI  was  significantly higher in the non-alcoholic steatohepatitis group than the simple steatosis group

Properties of exchange coupled all-garnet magneto-optic thin film multilayer structures

The effects of exchange coupling on magnetic switching properties of all-garnet multilayer thin film structures are investigated. All-garnet structures are fabricated by sandwiching a magneto-soft material of composition type Bi1.8Lu1.2Fe3.6Al1.4O12 or Bi3Fe5O12:Dy2O3 in between two magneto-hard garnet material layers of composition type Bi2Dy1Fe4Ga1O12 or Bi2Dy1Fe4Ga1O12:Bi12O3. The fabricated RF magnetron sputtered exchange-coupled all-garnet multilayers demonstrate a very attractive combination of magnetic properties, and are of interest for emerging applications in optical sensors and isolators, ultrafast nanophotonics and magneto-plasmonics. An unconventional type of magnetic hysteresis behavior not observed previously in magnetic garnet thin films is reported and discussed

Digital Applications Using Real-Time Vehicle Exhaust Information

Vehicle emission is a major source of air pollution that causes a significant number of deaths globally. It has a profound impact on energy and the environment as well. The existing vehicle emission monitoring system is unable to help mitigating the pollution properly and therefore, requires precise real-time pollution measurement. The purpose of this paper is to discuss novel applications using the real-time measurement of pollutants from a vehicle tailpipe where exhaust gases enter the environment. Today, it is possible to measure such emission due to the emergence of affordable digital technologies such as the Internet of Things (IoT), wireless connectivity, cloud platform, and artificial intelligence. This paper discusses how digital technologies can be used for real-time monitoring of NOx gas as a measure of vehicle emission and predictive analytics applications. A description of data collection and pre-processing methodologies, actual collected data, and an approach to identify patterns between inputs such as vehicle speed and altitude and output such as NOx emission are included. Applying a simple neural network has produced promising results and is a first step towards developing predictive applications

Detection, Quantification and Classification of Ripened Tomatoes: A Comparative Analysis of Image Processing and Machine Learning

In this paper, specifically for detection of ripe/unripe tomatoes with/without defects in the crop field, two distinct methods are described and compared. One is a machine learning approach, known as ‘Cascaded Object Detector’ and the other is a composition of traditional customized methods, individually known as ‘Colour Transformation’, ‘Colour Segmentation’ and ‘Circular Hough Transformation’. The (Viola Jones) Cascaded Object Detector generates ‘histogram of oriented gradient’ (HOG) features to detect tomatoes. For ripeness checking, the RGB mean is calculated with a set of rules. However, for traditional methods, color thresholding is applied to detect tomatoes either from a natural or solid background and RGB colour is adjusted to identify ripened tomatoes. In this work, Colour Segmentation is applied in the detection of tomatoes with defects, which has not previously been applied under machine learning techniques. The function modules of this algorithm are fed formatted images, captured by a camera mounted on a mobile robot. This robot was designed, built and operated in a tomato field to identify and quantify both green and ripened tomatoes as well as to detect damaged/blemished ones. This algorithm is shown to be optimally feasible for any micro-controller based miniature electronic devices in terms of its run time complexity of O(n3) for traditional method in best and average cases. Comparisons show that the accuracy of the machine learning method is 95%, better than that of the Colour Segmentation Method using MATLAB. This result is potentially significant for farmers in crop fields to identify the condition of tomatoes quickly

Tunable optical nanocavity of iron-garnet with a buried metal layer

We report on the fabrication and characterization of a novel magnetophotonic structure designed as iron garnet based magneto-optical nanoresonator cavity constrained by two noble metal mirrors. Since the iron garnet layer requires annealing at high temperatures, the fabrication process can be rather challenging. Special approaches for the protection of metal layers against oxidation and morphological changes along with a special plasma-assisted polishing of the iron garnet layer surface were used to achieve a 10-fold enhancement of the Faraday rotation angle (up to 10.8°=μm) within a special resonance peak of 12 nm (FWHM) linewidth at a wavelength of 772 nm, in the case of a resonator with two silver mirrors. These structures are promising for tunable nanophotonics applications, in particular, they can be used as magneto-optical (MO) metal-insulator-metal waveguides and modulators

High prevalence of urinary schistosomiasis in two communities in South Darfur: implication for interventions

<p>Abstract</p> <p>Background</p> <p>There are few data on the prevalence of schistosomiasis in Darfur. We conducted this study in response to reports of 15 laboratory confirmed cases of schistosomiasis and visible haematuria among children from two communities in South Darfur. The aim of the study was to estimate the prevalence of schistosomiasis in the area and to decide on modalities of intervention.</p> <p>Methods</p> <p>A cross-sectional survey involving 811 children and adults from schools and health facilities was conducted in two communities of South Darfur in March 2010. Urine samples were collected and examined for ova of <it>Schistosoma haematobium </it>using a sedimentation technique. A semi-structured format was used to collect socio-demographic characteristics of the participants.</p> <p>Results</p> <p>Eight hundred eleven (811) urine samples were collected, 415 from Alsafia and 396 from Abuselala. Of the collected samples in 56.0% (95% Confidence Interval (CI); 52.6-59.4) <it>Schistosoma </it>eggs were found. The prevalence was high in both Abuselala 73.3% (95% CI; 68.9-77.6) and Alsafia 39.5% (95% CI; 34.8-44.2). More males (61.7%, 95%CI; 56.5-64.9) were infected than females (52.1%, 95%CI; 48.2-56.0). Children in the age group 10-14 has the highest (73.0%, 95%CI; 68.7-77.2) infection rate. School age children (6-15 years) are more likely to be infected than those >15 years (Adjusted Odds Ratio (AOR) = 2.70, 95% CI; 1.80-4.06). Individuals in Abuselala are more likely to be infected than those who live in Alsafia (AOR = 4.3, 95% CI; 3.2-5.9).</p> <p>Conclusion</p> <p>The findings of this study indicate that <it>S. hematobium </it>is endemic in Alsafia and Abuselala South Darfur in Sudan with a high prevalence of infection among older children. This signifies the importance of urgent intervention through Mass Drug Administration (MDA) to halt the infection cycle and tailored health messages to targeted groups. Based on the findings MDA was conducted in the villages.</p

Biopsy-based calibration of T2* magnetic resonance for estimation of liver iron concentration and comparison with R2 Ferriscan.

BACKGROUND: There is a need to standardise non-invasive measurements of liver iron concentrations (LIC) so clear inferences can be drawn about body iron levels that are associated with hepatic and extra-hepatic complications of iron overload. Since the first demonstration of an inverse relationship between biopsy LIC and liver magnetic resonance (MR) using a proof-of-concept T2* sequence, MR technology has advanced dramatically with a shorter minimum echo-time, closer inter-echo spacing and constant repetition time. These important advances allow more accurate calculation of liver T2* especially in patients with high LIC. METHODS: Here, we used an optimised liver T2* sequence calibrated against 50 liver biopsy samples on 25 patients with transfusional haemosiderosis using ordinary least squares linear regression, and assessed the method reproducibility in 96 scans over an LIC range up to 42 mg/g dry weight (dw) using Bland-Altman plots. Using mixed model linear regression we compared the new T2*-LIC with R2-LIC (Ferriscan) on 92 scans in 54 patients with transfusional haemosiderosis and examined method agreement using Bland-Altman approach. RESULTS: Strong linear correlation between ln(T2*) and ln(LIC) led to the calibration equation LIC = 31.94(T2*)-1.014. This yielded LIC values approximately 2.2 times higher than the proof-of-concept T2* method. Comparing this new T2*-LIC with the R2-LIC (Ferriscan) technique in 92 scans, we observed a close relationship between the two methods for values up to 10 mg/g dw, however the method agreement was poor. CONCLUSIONS: New calibration of T2* against liver biopsy estimates LIC in a reproducible way, correcting the proof-of-concept calibration by 2.2 times. Due to poor agreement, both methods should be used separately to diagnose or rule out liver iron overload in patients with increased ferritin

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation