Iodine from brown algae in human nutrition,with an emphasis on bioaccessibility,bioavailability, chemistry,and effects of processing: A systematic review

Brown algae are becoming increasingly popular as a food source and dietary supplement in Europe and other Western countries. As they are highly rich in iodine, they represent a potential new dietary iodine source. Iodine deficiency has been re-emerging in Europe, and it is important to ensure adequate intake through one's diet. However, macroalgae, and especially brown algae, may contain very high amounts of iodine, and both iodine deficiency and excessive iodine may increase the risk of negative health effects. The iodine content of algae or foods containing algae is currently not regulated in the European Union. The aim of this paper is to review the literature to determine the chemical species of iodine in brown algae, the loss of iodine during processing, and the bioavailability and bioaccessibility of iodine. A systematic search of the literature was performed in April 2021, via the databases Web of Science and PubMed. The review includes studies of iodine in brown macroalgae in relation to bioavailability, bioaccessibility, processing and speciation. A meta-analysis was conducted in relation to the following topics: (i) the correlation between total iodine and iodide (I^–) content in brown algae; (ii) the correlation between the loss of iodine during processing and the I^– content; and (iii) the correlation between bioavailability and the I^– content. The bioavailability of iodine from brown algae was generally high, with in vivo bioavailability ranging from 31% to 90%. The in vitro bioavailability of iodine (2%–28%) was systematically lower than in vivo bioavailability (31%–90%), indicating an inadequate in vitro methodology. Processing may reduce the iodine content of brown algae, and a higher I^– content was positively correlated with increased iodine loss during processing. Although processing strategies may reduce the iodine content of brown algae significantly, the iodine content may still be high after processing. These findings may be used in food safety evaluations of brown algae as well as in the development of macroalgae-containing foods with iodine contents suitable for human consumption. Further research on processing techniques to reduce the iodine content in brown macroalgae are warranted.     

Removal of As(V) Ions from Solution by Akaganeite bgr-FeO(OH) Nanocrystals

The original method is developed for producing the new inorganic sorption material of akaganeite bgr-FeO(OH). The material in question is characterized relative to arsenic contained in aqua. The possibility is established for removing arsenate ions from water by contemporary physicochemical methods.     

Study on Adsorption Behavior of Rare Earth Complexes on Nanometer-Size Titanium Dioxide with ICP-AES

Inrecentyears ,rareearthelements (REEs)havebeenwidelyusedinfunctionalmaterials ,cata lystsandotherproductsinindustry ,diagnosisreagentsofmagneticresonanceimaging (MRI)inmedicineandsomefertilizersinagricultureespeciallyinChina .However,asaresultoftheirusage ,moreandmoreREEsaregettingintotheenvironment,andalsointohumanbodyviafoodchain[1,2 ] .Itisnotclearwhetherrareearthelementsareessentialforman ,soitisveryurgenttostudythebiologicaleffectofrareearthelementsinhumanhealthandenvironment .Inthes…     

氯化铵在含砷金银铅锌矿选别中的应用

某多金属铅锌矿含砷较高．采用常规铅、锌优先浮选方法，铅、锌精矿中砷含量超标。为了解决铅、锌精矿中砷超标的问题，在铅、锌粗、精选作业中加入氯化铵，成功地降低了铅、锌精矿中砷的含量，使铅、锌精矿质量合格．将这一结果应用于生产，取得了良好的效果。     

Predictive modeling of mercury speciation in combustion flue gases using GMDH-based abductive networks

Modeling mercury speciation is an important requirement for estimating harmful emissions from coal-fired power plants and developing strategies to reduce them. First-principle models based on chemical, kinetic, and thermodynamic aspects exist, but these are complex and difficult to develop. The use of modern data-based machine learning techniques has been recently introduced, including neural networks. Here we propose an alternative approach using abductive networks based on the group method of data handling (GMDH) algorithm, with the advantages of simplified and more automated model synthesis, automatic selection of significant inputs, and more transparent input–output model relationships. Models were developed for predicting three types of mercury speciation (elemental, oxidized, and particulate) using a small dataset containing six inputs parameters on the composition of the coal used and boiler operating conditions. Prediction performance compares favourably with neural network models developed using the same dataset, with correlation coefficients as high as 0.97 for training data. Network committees (ensembles) are proposed as a means of improving prediction accuracy, and suggestions are made for future work to further improve performance.     

Fabrication of Arsenic Sulfide Optical Fiber with Low Hydrogen Impurities

Arsenic sulfide glass optical fibers typically possess extrinsic absorption bands in the infrared wavelength region associated with residual hydrogen and oxygen related impurities, despite using purified precursors. We report a purification process based on the addition of tellurium tetrachloride (TeCl₄) to the glass. During melting, the chlorine from TeCl₄ reacts with the hydrogen impurities to produce volatile products (e.g., HCl) that can be removed by subsequent dynamic distillation. The processing conditions have been modified accordingly to produce optical fibers with significantly reduced loss due to hydrogen sulfide impurity content (1.5 dB/m).     

Speciation of the semivolatile hydrocarbon engine emissions from sunflower biodiesel

Biodiesel fuel is a very attractive alternative to conventional fuel and its effects in the engine performance and regulated emissions have been widely studied. However, the impact on unregulated individual compounds or chemical characteristics of exhaust emissions is not fully characterized. In this paper, the semivolatile fractions of the exhaust emissions of biodiesel blends and conventional fuel have been speciated. The results show great differences between the compounds emitted, especially regarding oxygenated and aromatic species. Likewise, there is a clear relationship between speciated hydrocarbons and other important emissions such as total hydrocarbons (HC), particulate matter (PM), volatile organic fraction (VOF) and mean particle diameter (Dm) of PM.     

镇沅金精矿选择性固砷焙烧—氰化浸出新工艺研究

对云南镇沅金矿的难当金精矿进行了选择性固砷焙烧－氰化浸出的试验研究，取得了满意结果。砷固定率大于９２％，硫挥发率为７８％－８４％，金浸出率可达９１％－９３％。选择性固砷焙烧－氰化浸出新工艺可有效消除砷害，综合利用有价成分硫，特别适宜于含砷高硫，同时含碳等杂质的细粒浸染型难浸金矿石的处理，在我国有较大的发展前景。     

不同浊度下的泥沙对水体镉、铅、砷去除的影响分析

针对流域突发性重金属污染,不同浊度下的泥沙对重金属有一定的去除效果。以浊度为指示指标,通过试验研究了常温(25 ℃)和低温(5 ℃)条件下浊度50～650 NTU(Nephelometric Turbidity Unit)范围内泥沙对重金属镉、铅、砷吸附去除的影响。试验结果表明:泥沙对重金属镉、铅、砷的去除效果为铅＞镉＞砷,其中铅的去除率达到99%。浊度与能处理达标的最高重金属浓度呈线性关系,常温下浊度与能处理达标的最高镉、铅、砷浓度关系曲线的相关系数分别为0.996、0.998、0.999,低温下其相关系数分别为0.999、0.996、0.998。常温较低温更利于泥沙对重金属镉、铅、砷的去除,能去除更高浓度的重金属,达到生活饮用水卫生标准。     

河套盆地晚更新世以来黄河改道对高砷地下水分布的控制机制

针对河套盆地开展了历时多年的水文地质环境地质调查,利用采集的298组浅层地下水样品以及收集并甄选的382个水文地质钻孔记录分析发现:河套盆地内95%的高砷地下水(As质量浓度10μg/L)集中在黄河决口、改道形成的古河道影响带及黄河决口扇裙带。其中,盆地南部首次发现了较为集中的高砷地下水,其分布范围与黄河北岸的晚更新世以来黄河决口、改道形成的4个大型决口扇,在空间上有着良好的对应关系。黄河古河道带及决口扇裙带表现为较强的还原环境及蒸发浓缩作用以及较弱的地表水补给强度。受pH值、含铁氧化物的还原性溶解等因素影响,决口扇裙带浅层地下水中砷的含量略低于平原中部黄河古河道带。结果表明:黄河古河道带及决口扇裙带特定的沉积环境控制着地下水的水文地球化学过程,进而对高砷地下水的分布具有决定性的作用。