Functionalised microwave sensors for real-time monitoring of copper and zinc concentration in mining-impacted water

Microwave spectroscopy has been identified as a novel and inexpensive method for the monitoring of water pollutants. Integrating microwave sensors with developed coatings is a novel strategy to make the sensing system more specific for a target contaminant. This study describes the determination of copper and zinc concentration in water in both lab-prepared and acquired mine-water samples from two abandoned mining areas in Wales, UK. Uncoated sensors immersed in samples spiked with 1.25 mg/L concentrations of copper and zinc, using the standard addition method, were able to quantify the concentration at 0.44 GHz with a strong linear correlation (R2=0.99) for the reflection coefficient magnitude (|S11|). Functionalised microwave sensors with l-cysteine, chitosan and bismuth-zinc-cobalt oxide based coatings have shown improvement in the sensing performance. Specifically, the linear correlation at 0.91-1.00 GHz between |S11| and a polluted sample spiked with Cu showed a higher R2 (=0.98), sensitivity (1.65ΔdB/mg/L) and quality factor (135) compared with uncoated sensors (R2=0.88, sensitivity of 0.82 ΔdB/mg/L and Q-factor 30.7). A Lorentzian-peak fitting function was applied for performing advanced multiple peak analysis and identifying the changes in the resonant frequency peaks which are related to the change in metal ion content. This novel sensor platform offers the possibility of in situ monitoring of toxic metal concentrations in mining-impacted water and multiple peak features, such as area, full-width half maximum, centre, and height of the peaks have the possibility to offer higher specificity for similar toxic metals, as between copper and zinc ions

Screen-Printed f-EM Sensors based on two chelating-polymers and a metal oxide for the continuous detection of Cu ions in surface water

Pollutants affect water worldwide and consequently present a risk to both the environment and to human health. Cu is an essential element for many organisms, but becomes toxic at relatively high concentrations. Current laboratory-based methods are not able to monitor water quality continuously, as they require laborious sampling and offline monitoring. A potential method that is capable to addressing this problem, guaranteeing the continuous monitoring of water resources, is the integration of microwave spectroscopy with functionalised electromagnetic (f-EM) sensors. The feasibility of using this combined method for achieving a more specific response toward low concentrations of Cu has been demonstrated

Detection of Zn in water using novel functionalised planar microwave sensors

Metal pollution in aquatic environments has attracted global attention. Current methods are not able to monitor water quality in-situ at low-cost. This paper reports on a novel approach for detecting changes in the concentration of zinc in water using electrical and a microwave sensor method, adopting two planar sensors: one was functionalised with a screen-printed β-Bi2O3 based coating, while the other was uncoated. Results show that both electrical and the microwave sensor responses were dependent on the presence and concentration of Zn in water with R2 = 0.93-0.99. The functionalised sensor with a 60 μm thick β-Bi2O3 based film offers improved performance compared with both uncoated and functionalised sensors with 40 μm thick coating for detecting the changes of Zn concentrations in water for low levels (100 and 500 μg/L). This novel sensing system could be a cost-effective alternative to the current offline methods

New Sensing System Based on Electromagnetic Waves and Functionalised EM Sensors for Continuous Monitoring of Zn in Freshwater

Toxic metals are a signi cant cause for concern, considering freshwater the major route of their transport even far from point and di use sources. ¬ is paper presents a novel combined method using electrical measurements and microwave spectroscopy based on functionalised electromagnetic (f-EM) sensors. ¬ ick lms based on -Bi2O3 were screen-printed on planar sensors for monitoring continuously Zn concentrations in water. Results demonstrate the capability of this novel sensing system to measure in real-time Zn concentrations, especially in the range 0-1 mg/L and consequently the possibility to detect an unexpected pollution event, which can generate an increase of Zn in water

Biomarker-predicted sugars intake compared with self-reported measures in US Hispanics/Latinos: results from the HCHS/SOL SOLNAS study

Abstract Objective Measurement error in self-reported total sugars intake may obscure associations between sugars consumption and health outcomes, and the sum of 24 h urinary sucrose and fructose may serve as a predictive biomarker of total sugars intake. Design The Study of Latinos: Nutrition & Physical Activity Assessment Study (SOLNAS) was an ancillary study to the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) cohort. Doubly labelled water and 24 h urinary sucrose and fructose were used as biomarkers of energy and sugars intake, respectively. Participants’ diets were assessed by up to three 24 h recalls (88 % had two or more recalls). Procedures were repeated approximately 6 months after the initial visit among a subset of ninety-six participants. Setting Four centres (Bronx, NY; Chicago, IL; Miami, FL; San Diego, CA) across the USA. Subjects Men and women ( n 477) aged 18–74 years. Results The geometric mean of total sugars was 167·5 (95 % CI 154·4, 181·7) g/d for the biomarker-predicted and 90·6 (95 % CI 87·6, 93·6) g/d for the self-reported total sugars intake. Self-reported total sugars intake was not correlated with biomarker-predicted sugars intake ( r =−0·06, P =0·20, n 450). Among the reliability sample ( n 90), the reproducibility coefficient was 0·59 for biomarker-predicted and 0·20 for self-reported total sugars intake. Conclusions Possible explanations for the lack of association between biomarker-predicted and self-reported sugars intake include measurement error in self-reported diet, high intra-individual variability in sugars intake, and/or urinary sucrose and fructose may not be a suitable proxy for total sugars intake in this study population

General Practitioners involvement in enteral tube feeding at home: a qualitative study

<p>Abstract</p> <p>Background</p> <p>Complex medical treatment is moving from hospital to primary care and General Practitioners (GPs) are increasingly asked to undertake new roles. There are now an estimated 19,500 patients being fed in the UK in the community on enteral tube feeding using a variety of different feeding tubes (Percutaneous endoscopic gastrostomy (PEG), Jejunostomy, or nasogastric (NG). The majority of patients are over the age of 65 years when they had artificial feeding initiated and mainly because of dysphagia. The aim of this study was to explore GPs knowledge, attitudes and skills relating to enteral feeding in the community.</p> <p>Methods</p> <p>Semi-structured one-to-one interviews with a convenience sample of GPs in Northern Ireland.</p> <p>Results</p> <p>Twenty-three GPs in three health boards in Northern Ireland participated in the study. Most found dealing with enteral feeding to be a predominantly negative experience. They had little involvement in patient selection for the procedure and poor or no discharge information. GPs felt inadequately trained, there was poor communication between primary and secondary care and little support. There was anger and frustration among GPs about lack of resources (funding and training), and the perception that primary care was used as a dumping ground.</p> <p>Conclusion</p> <p>Moving complex medical treatment from secondary to primary care has major implications for GPs who should be included in the patient selection process, have adequate discharge information about their patients, be adequately resourced and have appropriate support and training.</p

Genetic analysis of the GLUT10 glucose transporter (SLC2A10) polymorphisms in Caucasian American type 2 diabetes

BACKGROUND: GLUT10 (gene symbol SLC2A10) is a facilitative glucose transporter within the type 2 diabetes (T2DM)-linked region on chromosome 20q12-13.1. Therefore, we evaluated GLUT10 as a positional candidate gene for T2DM in Caucasian Americans. METHODS: Twenty SNPs including 4 coding, 10 intronic and 6 5' and 3' to the coding sequence were genotyped across a 100 kb region containing the SLC2A10 gene in DNAs from 300 T2DM cases and 310 controls using the Sequenom MassArray Genotyping System. Allelic association was evaluated, and linkage disequilibrium (LD) and haplotype structure of SLC2A10 were also determined to assess whether any specific haplotypes were associated with T2DM. RESULTS: Of these variants, fifteen had heterozygosities greater than 0.80 and were analyzed further for association with T2DM. No evidence of significant association was observed for any variant with T2DM (all P ≥ 0.05), including Ala206Thr (rs2235491) which was previously reported to be associated with fasting insulin. Linkage disequilibrium analysis suggests that the SLC2A10 gene is contained in a single haplotype block of 14 kb. Haplotype association analysis with T2DM did not reveal any significant differences between haplotype frequencies in T2DM cases and controls. CONCLUSION: From our findings, we can conclude that sequence variants in or near GLUT10 are unlikely to contribute significantly to T2DM in Caucasian Americans

Horizontal DNA transfer mechanisms of bacteria as weapons of intragenomic conflict

Horizontal DNA transfer (HDT) is a pervasive mechanism of diversification in many microbial species, but its primary evolutionary role remains controversial. Much recent research has emphasised the adaptive benefit of acquiring novel DNA, but here we argue instead that intragenomic conflict provides a coherent framework for understanding the evolutionary origins of HDT. To test this hypothesis, we developed a mathematical model of a clonally descended bacterial population undergoing HDT through transmission of mobile genetic elements (MGEs) and genetic transformation. Including the known bias of transformation toward the acquisition of shorter alleles into the model suggested it could be an effective means of counteracting the spread of MGEs. Both constitutive and transient competence for transformation were found to provide an effective defence against parasitic MGEs; transient competence could also be effective at permitting the selective spread of MGEs conferring a benefit on their host bacterium. The coordination of transient competence with cell-cell killing, observed in multiple species, was found to result in synergistic blocking of MGE transmission through releasing genomic DNA for homologous recombination while simultaneously reducing horizontal MGE spread by lowering the local cell density. To evaluate the feasibility of the functions suggested by the modelling analysis, we analysed genomic data from longitudinal sampling of individuals carrying Streptococcus pneumoniae. This revealed the frequent within-host coexistence of clonally descended cells that differed in their MGE infection status, a necessary condition for the proposed mechanism to operate. Additionally, we found multiple examples of MGEs inhibiting transformation through integrative disruption of genes encoding the competence machinery across many species, providing evidence of an ongoing "arms race." Reduced rates of transformation have also been observed in cells infected by MGEs that reduce the concentration of extracellular DNA through secretion of DNases. Simulations predicted that either mechanism of limiting transformation would benefit individual MGEs, but also that this tactic's effectiveness was limited by competition with other MGEs coinfecting the same cell. A further observed behaviour we hypothesised to reduce elimination by transformation was MGE activation when cells become competent. Our model predicted that this response was effective at counteracting transformation independently of competing MGEs. Therefore, this framework is able to explain both common properties of MGEs, and the seemingly paradoxical bacterial behaviours of transformation and cell-cell killing within clonally related populations, as the consequences of intragenomic conflict between self-replicating chromosomes and parasitic MGEs. The antagonistic nature of the different mechanisms of HDT over short timescales means their contribution to bacterial evolution is likely to be substantially greater than previously appreciated

Validity of Resting Energy Expenditure Predictive Equations before and after an Energy-Restricted Diet Intervention in Obese Women

Background We investigated the validity of REE predictive equations before and after 12-week energy-restricted diet intervention in Spanish obese (30 kg/m2>BMI<40 kg/m2) women. Methods We measured REE (indirect calorimetry), body weight, height, and fat mass (FM) and fat free mass (FFM, dual X-ray absorptiometry) in 86 obese Caucasian premenopausal women aged 36.7±7.2 y, before and after (n = 78 women) the intervention. We investigated the accuracy of ten REE predictive equations using weight, height, age, FFM and FM. Results At baseline, the most accurate equation was the Mifflin et al. (Am J Clin Nutr 1990; 51: 241–247) when using weight (bias:−0.2%, P = 0.982), 74% of accurate predictions. This level of accuracy was not reached after the diet intervention (24% accurate prediction). After the intervention, the lowest bias was found with the Owen et al. (Am J Clin Nutr 1986; 44: 1–19) equation when using weight (bias:−1.7%, P = 0.044), 81% accurate prediction, yet it provided 53% accurate predictions at baseline. Conclusions There is a wide variation in the accuracy of REE predictive equations before and after weight loss in non-morbid obese women. The results acquire especial relevance in the context of the challenging weight regain phenomenon for the overweight/obese population.The present study was supported by the University of the Basque Country (UPV 05/80), Social Foundation of the Caja Vital- Kutxa and by the Department of Health of the Government of the Basque Country (2008/111062), and by the Spanish Ministry of Science and Innovation (RYC-2010-05957)

Rapid automatic segmentation of abnormal tissue in late gadolinium enhancement cardiovascular magnetic resonance images for improved management of long-standing persistent atrial fibrillation

Background: Atrial fibrillation (AF) is the most common heart rhythm disorder. In order for late Gd enhancement cardiovascular magnetic resonance (LGE CMR) to ameliorate the AF management, the ready availability of the accurate enhancement segmentation is required. However, the computer-aided segmentation of enhancement in LGE CMR of AF is still an open question. Additionally, the number of centres that have reported successful application of LGE CMR to guide clinical AF strategies remains low, while the debate on LGE CMR’s diagnostic ability for AF still holds. The aim of this study is to propose a method that reliably distinguishes enhanced (abnormal) from non-enhanced (healthy) tissue within the left atrial wall of (pre-ablation and 3 months post-ablation) LGE CMR data-sets from long-standing persistent AF patients studied at our centre. Methods: Enhancement segmentation was achieved by employing thresholds benchmarked against the statistics of the whole left atrial blood-pool (LABP). The test-set cross-validation mechanism was applied to determine the input feature representation and algorithm that best predict enhancement threshold levels. Results: Global normalized intensity threshold levels T PRE = 1 1/4 and T POST = 1 5/8 were found to segment enhancement in data-sets acquired pre-ablation and at 3 months post-ablation, respectively. The segmentation results were corroborated by using visual inspection of LGE CMR brightness levels and one endocardial bipolar voltage map. The measured extent of pre-ablation fibrosis fell within the normal range for the specific arrhythmia phenotype. 3D volume renderings of segmented post-ablation enhancement emulated the expected ablation lesion patterns. By comparing our technique with other related approaches that proposed different threshold levels (although they also relied on reference regions from within the LABP) for segmenting enhancement in LGE CMR data-sets of AF patients, we illustrated that the cut-off levels employed by other centres may not be usable for clinical studies performed in our centre. Conclusions: The proposed technique has great potential for successful employment in the AF management within our centre. It provides a highly desirable validation of the LGE CMR technique for AF studies. Inter-centre differences in the CMR acquisition protocol and image analysis strategy inevitably impede the selection of a universally optimal algorithm for segmentation of enhancement in AF studies