Global sourcing of low-inorganic arsenic rice grain

Arsenic in rice grain is dominated by two species: the carcinogen inorganic arsenic (the sum of arsenate and arsenite) and dimethylarsinic acid (DMA). Rice is the dominant source of inorganic arsenic into the human diet. As such, there is a need to identify sources of low-inorganic arsenic rice globally. Here we surveyed polished (white) rice across representative regions of rice production globally for arsenic speciation. In total 1180 samples were analysed from 29 distinct sampling zones, across 6 continents. For inorganic arsenic the global x ~ x~ was 66 μg/kg, and for DMA this figure was 21 μg/kg. DMA was more variable, ranging from < 2 to 690 μg/kg, while inorganic arsenic ranged from < 2 to 399 μg/kg. It was found that inorganic arsenic dominated when grain sum of species was < 100 μg/kg, with DMA dominating at higher concentrations. There was considerable regional variance in grain arsenic speciation, particularly in DMA where temperate production regions had higher concentrations. Inorganic arsenic concentrations were relatively consistent across temperate, subtropical and northern hemisphere tropical regions. It was only in southern hemisphere tropical regions, in the eastern hemisphere that low-grain inorganic arsenic is found, namely East Africa (x ~ x~  < 10 μg/kg) and the Southern Indonesian islands (x ~ x~  < 20 μg/kg). Southern hemisphere South American rice was universally high in inorganic arsenic, the reason for which needs further exploration

Rice grain cadmium concentrations in the global supply-chain

One of cadmium’s major exposure routes to humans is through rice consumption. The concentrations of cadmium in the global polished (white), market rice supply-chain were assessed in 2270 samples, purchased from retailers across 32 countries, encompassing 6 continents. It was found on a global basis that East Africa had the lowest cadmium with a median for both Malawi and Tanzania at 4.9 μg/kg, an order of magnitude lower than the highest country, China with a median at 69.3 μg/kg. The Americas were typically low in cadmium, but the Indian sub-continent was universally elevated. In particular certain regions of Bangladesh had high cadmium, that when combined with the high daily consumption rate of rice of that country, leads to high cadmium exposures. Concentrations of cadmium were compared to the European Standard for polished rice of 200 μg/kg and 5% of the global supply-chain exceeded this threshold. For the stricter standard of 40 μg/kg for processed infant foods, for which rice can comprise up to 100% by composition (such as rice porridges, puffed rice cereal and cakes), 25% of rice would not be suitable for making pure rice baby foods. Given that rice is also elevated in inorganic arsenic, the only region of the world where both inorganic arsenic and cadmium were low in grain was East Africa

The effectiveness of computerized clinical guidelines in the process of care: a systematic review

<p>Abstract</p> <p>Background</p> <p>Clinical practice guidelines have been developed aiming to improve the quality of care. The implementation of the computerized clinical guidelines (CCG) has been supported by the development of computerized clinical decision support systems.</p> <p>This systematic review assesses the impact of CCG on the process of care compared with non-computerized clinical guidelines.</p> <p>Methods</p> <p>Specific features of CCG were studied through an extensive search of scientific literature, querying electronic databases: Pubmed/Medline, Embase and Cochrane Controlled Trials Register. A multivariable logistic regression was carried out to evaluate the association of CCG's features with positive effect on the process of care.</p> <p>Results</p> <p>Forty-five articles were selected. The logistic model showed that Automatic provision of recommendation in electronic version as part of clinician workflow (Odds Ratio [OR]= 17.5; 95% confidence interval [CI]: 1.6-193.7) and Publication Year (OR = 6.7; 95%CI: 1.3-34.3) were statistically significant predictors.</p> <p>Conclusions</p> <p>From the research that has been carried out, we can conclude that after implementation of CCG significant improvements in process of care are shown. Our findings also suggest clinicians, managers and other health care decision makers which features of CCG might improve the structure of computerized system.</p

A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss

Skin cancers are the most cancers diagnosed worldwide, with an estimated &gt; 1.5 million new cases in 2020. Use of computer-aided diagnosis (CAD) systems for early detection and classification of skin lesions helps reduce skin cancer mortality rates. Inspired by the success of the transformer network in natural language processing (NLP) and the deep convolutional neural network (DCNN) in computer vision, we propose an end-to-end CNN transformer hybrid model with a focal loss (FL) function to classify skin lesion images. First, the CNN extracts low-level, local feature maps from the dermoscopic images. In the second stage, the vision transformer (ViT) globally models these features, then extracts abstract and high-level semantic information, and finally sends this to the multi-layer perceptron (MLP) head for classification. Based on an evaluation of three different loss functions, the FL-based algorithm is aimed to improve the extreme class imbalance that exists in the International Skin Imaging Collaboration (ISIC) 2018 dataset. The experimental analysis demonstrates that impressive results of skin lesion classification are achieved by employing the hybrid model and FL strategy, which shows significantly high performance and outperforms the existing work

Sorption of Arsenite on Cu-Al, Mg-Al, Mg-Fe, and Zn-Al Layered Double Hydroxides in the Presence of Inorganic Anions Commonly Found in Aquatic Environments

Use of layered double hydroxides (LDHs) in the environmental field is gaining popularity due to their potential to sorb toxic anions, attributed to their large surface area, high anion exchange capacity, and good thermal stability. In this study, four different LDHs (i.e., Cu-Al-, Mg-Al-, Mg-Fe-, and Zn-Al-LDH) were synthesized to select one or more efficient sorbents, capable of removing arsenite [As(III)] from contaminated waters. In particular, we studied the following: (1) X-ray diffraction patterns and specific surface area of the synthesized LDHs; (2) sorption isotherms of As(III) at pH 7.0; and (3) sorption of As(III) on LDHs, in the presence of inorganic anions [carbonate (CO3), chloride (Cl), fluoride (F), phosphate (PO4), sulfate (SO4)] commonly present in aquatic environments. The poorly crystalline LDHs (i.e., Cu-Al-LDH and Mg-Fe-LDH) sorbed greater amounts of As(III) than the well-crystalline LDHs (i.e, Mg-Al-LDH and Zn-Al-LDH). The efficiency of the competing anions at inhibiting As(III) sorption by the LDHs was Cl ≤ F < SO4 << CO3 << PO4, regardless of initial ligand/As(III) molar ratios (R) or LDH. Although Cu-Al-LDH sorbed lower amounts of As(III) than the Mg-Fe-LDH, it showed, surprisingly, a higher affinity for As(III). This surprising behavior puts this LDH in the forefront as a potential sorbent for the treatment of arsenic-contaminated waters

Influence of compost on the mobility of arsenic in soil and its uptake by bean plants (Phaseolus vulgaris L.) irrigated with arsenite-contaminated water.

The influence of compost on the growth of bean plants irrigated with As-contaminated waters and its influence on the mobility of As in the soils and the uptake of As (as NaAsIIIO2) by plant components was studied at various compost application rates (3·104 and 6·104kgha-1) and at three As concentrations (1, 2 and 3mgkg-1). The biomass and As and P concentrations of the roots, shoots and beans were determined at harvest time, as well as the chlorophyll content of the leaves and nonspecific and specifically bound As in the soil.The bean plants exposed to As showed typical phytotoxicity symptoms; no plants however died over the study. The biomass of the bean plants increased with the increasing amounts of compost added to the soil, attributed to the phytonutritive capacity of compost. Biomass decreased with increasing As concentrations, however, the reduction in the biomass was significantly lower with the addition of compost, indicating that the As phytotoxicity was alleviated by the compost. For the same As concentration, the As content of the roots, shoots and beans decreased with increasing compost added compared to the Control. This is due to partial immobilization of the As by the organic functional groups on the compost, either directly or through cation bridging. Most of the As adsorbed by the bean plants accumulated in the roots, while a scant allocation of As occurred in the beans. Hence, the addition of compost to soils could be used as an effective means to limit As accumulation in crops from As-contaminated waters

Wireless Sensor Network Calibration for PM10 Measurement

The proposal of an Advanced Metering Infrastructure based on short-range communication is suggested for the continuous monitoring of Particulate Matter. A prototype of Automatic Measurement System (AMS), including a low-cost off-the-shelf PM sensor, has been developed as a remote node to be adopted in the radio Local Area Network. The results of the system calibration and comparison with the data quality requirements of the PM measurement according to European regulations, as well as the simulation of a typical Smart City scenario in terms of communication performance, confirm the feasibility of the proposed distributed AMS for an effective adoption within an urban area