Bio-accumulation and health risk assessment of heavy metals in different edible fish species from Hurghada City,Red Sea,Egypt

BackgroundHeavy metal contamination has become a serious issue in this century especially detected in fish organs. Due to the presence of radioactive compounds in agricultural and sewage effluent, which destroys aquatic ecosystems, threatening human livelihoods. Health hazards associated with low and high consumption consumers assessed in five commercial fish species collected from Hurghada City, Egypt, during winter and summer, 2020. Atomic absorption spectrophotometer technique used for determination heavy meals in different organs and expressed as μg/g wet weight.ResultsHeavy metal concentrations in muscle ranged between:(0.054–0.109), (0.260–1.043), (0.264–0.897), (5.895–11.898), (0.381–0.970), (13.582–29.133) and (0.332–0.589) µg/g for Cd, Pb, Mn, Zn, Cu, Fe and Ni respectively, which were lower than those of gills and liver. These concentrations were within WHO, FAO/WHO, and EU standards. Consumption of edible species was lower than the (TDIs) established by the (JECFA) and Egyptian Standards. Even though THQ and TTHQ values were < 1 while, in children with highly consumer were> 1.ConclusionThis study concluded that intake of Red Sea fish is safe for human health. It is critical for consumers to be aware of the consequences of excessive fish consumption, particularly children with highly consumer, which represent possible health risks.     

Adsorptive removal of lead from aqueous solutions by amine–functionalized magMCM-41 as a low–cost nanocomposite prepared from rice husk: Modeling and optimization by response surface methodology

Amorphous silica that was extracted from rice husk was used to synthesize the magMCM-41 mesoporous silica. This was then functionalized by the APTMS group in order to produce NH₂-magMCM-41 as a novel and low–cost adsorbent. The XRD, VSM, N₂ adsorption–desorption, FT–IR, TGA, SEM and TEM analyses were utilized to characterize the produced materials. In order to optimize the adsorption of the Pb(II) ions, the RSM (response surface methodology) was applied by using the synthesized adsorbent in aqueous solutions. A rotatable CCD (central composite design) was adopted to carry out the experiments and RSM was used to analyze them. Three independent factors namely, initial solution pH (3–7), adsorbent dosage (0.1–2 g L^?1), and initial Pb(II) concentration (15–150 mg L^?1) were used to investigate the removal procedure. According to the obtained results, the initial solution pH of 5.22, adsorbent dosage of 0.1 g L^?1, and initial Pb(II) concentration of 150 mg L^?1 were considered as the optimum conditions with 64.32% removal of Pb(II) and an adsorption capacity of 540.64 mg g^?1. The maximum removal efficiency of Pb(II) ions was found to be 96.76%. The Sips isotherm model represents a better correlation with equilibrium data. It was reported by the kinetic study that data taken from the experiments fitted better to the pseudo–second–order model compared to the pseudo–first–order and intraparticle diffusion models. Finally, according to the thermodynamic study, the removal process strongly depends on temperature, which indicates an exothermic behavior and spontaneous nature of the adsorption.     

Electrochemical detection and quantification of Reactive Red 195 dyes on graphene modified glassy carbon electrode

Reactive Red 195 was detected from industrial waste samples electrochemically on graphene modified glassy carbon electrode (GCE), using both bare and surface changed GCE at different pH media from 1.0 to 13.0. The optimum pH was determined to be 4.0. RR 195 exhibited good linear responds at pH 4.0 on both electrode surfaces. Other parameters, such as accumulation potential, accumulation time, initial scan potential, pulse height, pulse width, and potential scan increment and scan rate are optimized and calibration plot was also derived on different concentrations of the dye. The stripping voltammetric behavior of dye exhibits very low limit of detection on graphene coated electrode (30?ppb). The adsorption of compound on GCE and graphene coated GCE are confirmed using atomic force microscopy studies.     

Infective Endocarditis Due to Treponema pallidum: A Case Diagnosed Using Polymerase Chain Reaction Analysis of Aortic Valve

Syphilis is a sexually transmitted disease caused by Treponema pallidum. Syphilitic aortitis might coexist in a dysfunctional aortic valve, but the etiology remains unclear, because microbiological diagnosis is difficult. A 62-year-old man with low-grade fever was diagnosed with aortitis and infective endocarditis, due to Treponema pallidum infection, using polymerase chain reaction analysis. This case suggests that syphilis might cause infective endocarditis.     

空间统计学在食品污染物分布研究中的应用

目的 以2017年某省食品安全监测大米中砷含量数据为例，探讨空间统计学方法在食品污染物分析中的应用价值。方法 采用空间点模式估计、核密度分析，全局以及局部自相关性分析等空间统计学方法，在县级空间尺度下，对某省大米中砷含量进行探索性空间数据分析。结果 空间点模式分布图显示，该省大米砷污染的空间分布比较分散，核密度分析结果显示污染热点区域主要在该省中东部地区。全局自相关Moran''s I指数值为0.11，有统计学意义，大米样品中砷污染呈现出低度空间聚集性。有1个"高-高"聚集区，2个典型的"低-低"聚集区。结论 空间统计学运用于食物污染物分布研究上，可以很好地可视化展示、识别污染分布规律、热点地区和聚集区，为基于问题的监测工作的开展提供技术支持。     

红树莓生物活性成分的药理作用研究进展

红树莓是蔷薇科悬钩子属类植物，其含有多种营养成分及多种生物活性物质，对人体健康有益，因此被称为黄金水果。长期食用红树莓可以降低罹患多种慢性疾病的风险并起到治疗作用。红树莓及其活性成分能够抑制氧化应激、减轻炎症反应、调节内皮功能，从而起到减缓或者治疗心、脑血管系统疾病的作用。红树莓能通过抑制α-淀粉酶和α-葡萄糖苷酶的活性，减少餐后葡萄糖的吸收。红树莓含有大量的膳食纤维和酚类活性物质，能够调节脂类代谢。抗炎作用机制主要是减少低密度脂蛋白（Low-density lipoprotein，LDL）及脂质的氧化、DNA损伤、活性氧（Reactive Oxygen Species, ROS）、及一氧化氮（Nitric Oxide,NO）的产生、增加抗氧化物酶活性。抗肿瘤机制主要包括清除ROS以防止DNA氧化损伤、抑制DNA加合物的形成、加强DNA修复能力，以及调节细胞增殖、凋亡等信号通路。本文对红树莓在心、脑血管疾病，糖尿病，肥胖，炎症，肿瘤等疾病中的药理作用进行综述。     

Diagnostic and prognostic value of red blood cell distribution width in sepsis: A narrative review

Previous studies showed that red blood cell distribution width (RDW) can be used as a prognostic and diagnostic index in various non-hematological diseases, including severe infections and sepsis. Here, we provide a narrative review to summarize the findings of available studies investigating the relationship between RDW and sepsis. Current evidence suggests that increased RDW on admission, both in adults and neonates, may be associated with unfavorable outcomes on the short- and long-term. In patients with suspected sepsis, RDW has modest value for predicting positive blood culture. Accordingly, its diagnostic value for sepsis seems limited, whilts dynamic changes of RDW are associated with outcome of sepsis. Taken together, these results suggest that RDW could be used as a prognostic index in septic patients.     

Patient Management Assisted by a Neural Network Reduces Mortality in an Intermediate Care Unit

IntroductionMortality risk prediction for Intermediate Respiratory Care Unit's (IRCU) patients can facilitate optimal treatment in high-risk patients. While Intensive Care Units (ICUs) have a long term experience in using algorithms for this purpose, due to the special features of the IRCUs, the same strategics are not applicable. The aim of this study is to develop an IRCU specific mortality predictor tool using machine learning methods.MethodsVital signs of patients were recorded from 1966 patients admitted from 2007 to 2017 in the Jiménez Díaz Foundation University Hospital's IRCU. A neural network was used to select the variables that better predict mortality status. Multivariate logistic regression provided us cut-off points that best discriminated the mortality status for each of the parameters. A new guideline for risk assessment was applied and mortality was recorded during one year.ResultsOur algorithm shows that thrombocytopenia, metabolic acidosis, anemia, tachypnea, age, sodium levels, hypoxemia, leukocytopenia and hyperkalemia are the most relevant parameters associated with mortality. First year with this decision scene showed a decrease in failure rate of a 50%.ConclusionsWe have generated a neural network model capable of identifying and classifying mortality predictors in the IRCU of a general hospital. Combined with multivariate regression analysis, it has provided us with an useful tool for the real-time monitoring of patients to detect specific mortality risks. The overall algorithm can be scaled to any type of unit offering personalized results and will increase accuracy over time when more patients are included to the cohorts.