Glycemic Control: Risk Factors, Quality of Life, Workforce Participation, and Mortality Among US Adults with Type 2 Diabetes

Despite research showing the benefits of glycemic control, it remains suboptimal among adults with diabetes in the United States. Possible reasons include unaddressed risk factors as well as lack of awareness of its immediate and long term consequences. The objectives of this study were to, using cross-sectional data, 1) ascertain the association between suboptimal (Hemoglobin A1c (HbA1c) ≥7%), borderline (HbA1c 7-8.9%), and poor (HbA1c ≥9%) glycemic control and potentially new risk factors (e.g. work characteristics), and 2) assess whether aspects of poor health and well-being such as poor health related quality of life (HRQOL), unemployment, and missed-work are associated with glycemic control; and 3) using prospective data, assess the relationship between mortality risk and glycemic control in US adults with type 2 diabetes. Data from the 1988-1994 and 1999-2004 National Health and Nutrition Examination Surveys were used. HbA1c values were used to create dichotomous glycemic control indicators. Binary logistic regression models were used to assess relationships between risk factors, employment status and glycemic control. Multinomial logistic regression analyses were conducted to assess relationships between glycemic control and HRQOL variables. Zero-inflated Poisson regression models were used to assess relationships between missed work days and glycemic control. Cox-proportional hazard models were used to assess effects of glycemic control on mortality risk. Using STATA software, analyses were weighted to account for complex survey design and non-response. Multivariable models adjusted for socio-demographics, body mass index, among other variables. Results revealed that being a farm worker and working over 40 hours/week were risk factors for suboptimal glycemic control. Having greater days of poor mental was associated with suboptimal, borderline, and poor glycemic control. Having greater days of inactivity was associated with poor glycemic control while having greater days of poor physical health was associated with borderline glycemic control. There were no statistically significant relationships between glycemic control, self-reported general health, employment, and missed work. Finally, having an HbA1c value less than 6.5% was protective against mortality. The findings suggest that work-related factors are important in a person’s ability to reach optimal diabetes management levels. Poor glycemic control appears to have significant detrimental effects on HRQOL.

Trading Democracy for Security? The Effects of the International Drug War on the Quality of Democracy in the Dominican Republic, 1996 -2008

The purpose of the research is to study the relationship between international drug interdiction policies and domestic politics in fragile democracies, and to demonstrate how international drug control policies and the use of force fit the rhetoric of war, are legitimized by the principles of a just war, but may also cause collateral damage and negative unintended consequences. The method used is a case study of the Dominican Republic. The research has found that international drug control regimes, primarily led by the U.S. and narrowly focused on interdiction, have influenced an increasingly militarized approach to domestic law enforcement in the Dominican Republic. The collateral damage caused by militarized enforcement comes in the form of negative perceptions of citizen security, loss of respect for the rule of law and due process, and low levels of civil society development. The drug war has exposed the need for significant reform of the institutions charged with carrying out enforcement, the police force and the judicial system in particular. The dissertation concludes that the extent of drug trafficking in the Dominican Republic is beyond the scope of domestic reform efforts alone, but that the programs implemented do show some potential for future success. The dissertation also concludes that the framework of warfare is not the most appropriate for the international problems of drug traffic and abuse. A broader, multipronged approach should be considered by world policy makers in order to address all conditions that allow drugs to flourish without infringing upon democratic and civil rights in the process.

The relationship between dietary magnesium intake, stroke and its major risk factors, blood pressure and cholesterol, in the EPIC-Norfolk cohort

Copyright © 2015. Published by Elsevier Ireland Ltd.

The relationship between dietary magnesium intake, stroke and its major risk factors, blood pressure and cholesterol, in the EPIC-Norfolk cohort

Copyright © 2015. Published by Elsevier Ireland Ltd.

The relationship between dietary magnesium intake, stroke and its major risk factors, blood pressure and cholesterol, in the EPIC-Norfolk cohort

Copyright © 2015. Published by Elsevier Ireland Ltd.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

The Relationship Between Support Systems and Disease Burden for Families Coping with Sickle Cell Disease in South Africa and Cameroon

Background: Sickle cell disease (SCD) is a debilitating genetic blood disorder that seriously impacts the quality of life of affected individuals and their families. With 85% of cases occurring in sub-Saharan Africa, it is essential to identify the barriers and facilitators of optimal outcomes for people with SCD in this setting. This study focuses on understanding the relationship between support systems and disease outcomes for SCD patients and their families in Cameroon and South Africa.

Methods: This mixed-methods study utilizes surveys and semi-structured interviews to assess the experiences of 29 SCD patients and 28 caregivers of people with SCD across three cities in two African countries: Cape Town, South Africa; Yaoundé, Cameroon; and Limbe, Cameroon.

Results: Patients in Cameroon had less treatment options, a higher frequency of pain crises, and a higher incidence of malaria than patients in South Africa. Social support networks in Cameroon consisted of both family and friends and provided emotional, financial, and physical assistance during pain crises and hospital admissions. In South Africa, patients relied on a strong medical support system and social support primarily from close family members; they were also diagnosed later in life than those in Cameroon.

Conclusions: The strength of medical support systems influences the reliance of SCD patients and their caregivers on social support systems. In Cameroon the health care system does not adequately address all factors of SCD treatment and social networks of family and friends are used to complement the care received. In South Africa, strong medical and social support systems positively affect SCD disease burden for patients and their caregivers. SCD awareness campaigns are necessary to reduce the incidence of SCD and create stronger social support networks through increased community understanding and decreased stigma.

Irish and Jordanian general student nurses’ attitudes towards people with mental illness (PWMI) and their relationship to cultural and religious beliefs

Background Attitudes held and cultural and religious beliefs of general nursing students towards individuals with mental health problems are key factors that contribute to the quality of care provided. Negative attitudes towards mental illness and to individuals with mental health problems are held by the general public as well as health professionals. Negative attitudes towards people with mental illness have been reported to be associated with low quality of care, poor access to health care services and feelings of exclusion. Furthermore, culture has been reported to play a significant role in shaping people’s attitudes, values, beliefs, and behaviours, but has been poorly investigated. Research has also found that religious beliefs and practices are associated with better recovery for individuals with mental illness and enhanced coping strategies and provide more meaning and purpose to thinking and actions. The literature indicated that both Ireland and Jordan lack baseline data of general nurses’ and general nursing students’ attitudes towards mental illness and associated cultural and religious beliefs. Aims: To measure general nursing students’ attitudes towards individuals with mental illness and their relationships to socio-demographic variables and cultural and religious beliefs. Method: A quantitative descriptive study was conducted (n=470). 185 students in Jordan and 285 students in Ireland participated, with a response rate of 86% and 73%, respectively. Data were collected using the Community Attitudes towards the Mentally Ill instrument and a Cultural and Religious Beliefs Scale to People with Mental Illness constructed by the author. Results: Irish students reported more positive attitudes yet did not have strong cultural and religious beliefs compared to students from Jordan. Country of origin, considering a career in mental health nursing, knowing somebody with mental illness and cultural and religious beliefs were the most significant variables associated with students’ attitudes towards people with mental illness. In addition, students living in urban areas reported more positive attitudes to people with mental illness compared to those living in rural areas.

The influence of socio-demographic, psychological and knowledge-related variables alongside perceived cooking and food skills abilities in the prediction of diet quality in adults: a nationally representative cross-sectional study

Background: Interventions to increase cooking skills (CS) and food skills (FS) as a route to improving overall diet are popular within public health. This study tested a comprehensive model of diet quality by assessing the influence of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. The correspondence of two measures of diet quality further validated the Eating Choices Index (ECI) for use in quantitative research.
Methods: A cross-sectional survey was conducted in a quota-controlled nationally representative sample of 1049 adults aged 20–60 years drawn from the Island of Ireland. Surveys were administered in participants’ homes via computer-assisted personal interviewing (CAPI) assessing a range of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. Regression models were used to model factors influencing diet quality. Correspondence between 2 measures of diet quality was assessed using chi-square and Pearson correlations.
Results: ECI score was significantly negatively correlated with DINE Fat intake (r = -0.24, p < 0.001), and ECI score was significantly positively correlated with DINE Fibre intake (r = 0.38, p < 0.001), demonstrating a high agreement. Findings indicated that males, younger respondents and those with no/few educational qualifications scored significantly lower on both CS and FS abilities. The relative influence of socio-demographic, knowledge, psychological variables and CS and FS abilities on dietary outcomes varied, with regression models explaining 10–20 % of diet quality variance. CS ability exerted the strongest relationship with saturated fat intake (β = -0.296, p < 0.001) and was a significant predictor of fibre intake (β = -0.113, p < 0.05), although not for healthy food choices (ECI) (β = 0.04, p > 0.05).
Conclusion: Greater CS and FS abilities may not lead directly to healthier dietary choices given the myriad of other factors implicated; however, CS appear to have differential influences on aspects of the diet, most notably in relation to lowering saturated fat intake. Findings suggest that CS and FS should not be singular targets of interventions designed to improve diet; but targeting specific sub-groups of the population e.g. males, younger adults, those with limited education might be more fruitful. A greater understanding of the interaction of factors influencing cooking and food practices within the home is needed.

Obesity, diet quality and absenteeism in a working population

The relationship between workplace absenteeism and adverse lifestyle factors (smoking, physical inactivity and poor dietary patterns) remains ambiguous. Reliance on self-reported absenteeism and obesity measures may contribute to this uncertainty. Using objective absenteeism and health status measures, the present study aimed to investigate what health status outcomes and lifestyle factors influence workplace absenteeism. Cross-sectional data were obtained from a complex workplace dietary intervention trial, the Food Choice at Work Study. Four multinational manufacturing workplaces in Cork, Republic of Ireland. Participants included 540 randomly selected employees from the four workplaces. Annual count absenteeism data were collected. Physical assessments included objective health status measures (BMI, midway waist circumference and blood pressure). FFQ measured diet quality from which DASH (Dietary Approaches to Stop Hypertension) scores were constructed. A zero-inflated negative binomial (zinb) regression model examined associations between health status outcomes, lifestyle characteristics and absenteeism. The mean number of absences was 2·5 (sd 4·5) d. After controlling for sociodemographic and lifestyle characteristics, the zinb model indicated that absenteeism was positively associated with central obesity, increasing expected absence rate by 72 %. Consuming a high-quality diet and engaging in moderate levels of physical activity were negatively associated with absenteeism and reduced expected frequency by 50 % and 36 %, respectively. Being in a managerial/supervisory position also reduced expected frequency by 50 %. To reduce absenteeism, workplace health promotion policies should incorporate recommendations designed to prevent and manage excess weight, improve diet quality and increase physical activity levels of employees.

Are physical measures good indicators of image quality at low dose levels? A pilot study

Purpose: To evaluate if physical measures of noise predict image quality at high and low noise levels. Method: Twenty-four images were acquired on a DR system using a Pehamed DIGRAD phantom at three kVp settings (60, 70 and 81) across a range of mAs values. The image acquisition setup consisted of 14 cm of PMMA slabs with the phantom placed in the middle at 120 cm SID. Signal-to-noise ratio (SNR) and Contrast-tonoise ratio (CNR) were calculated for each of the images using ImageJ software and 14 observers performed image scoring. Images were scored according to the observer`s evaluation of objects visualized within the phantom. Results: The R2 values of the non-linear relationship between objective visibility score and CNR (60kVp R2 = 0.902; 70Kvp R2 = 0.913; 80kVp R2 = 0.757) demonstrate a better fit for all 3 kVp settings than the linear R2 values. As CNR increases for all kVp settings the Object Visibility also increases. The largest increase for SNR at low exposure values (up to 2 mGy) is observed at 60kVp, when compared with 70 or 81kVp.CNR response to exposure is similar. Pearson r was calculated to assess the correlation between Score, OV, SNR and CNR. None of the correlations reached a level of statistical significance (p>0.01). Conclusion: For object visibility and SNR, tube potential variations may play a role in object visibility. Higher energy X-ray beam settings give lower SNR but higher object visibility. Object visibility and CNR at all three tube potentials are similar, resulting in a strong positive relationship between CNR and object visibility score. At low doses the impact of radiographic noise does not have a strong influence on object visibility scores because in noisy images objects could still be identified.

Variation in composition of macro-benthic invertebrates as an indication of water quality status in three bays in Lake Victoria

Knowledge of how biota can be used to monitor ecosystem health and assess impacts by human alterations such as land use and management measures taken at different spatial scales is critical for improving the ecological quality of aquatic ecosystems. This knowledge in Uganda is very limited or unavailable yet it is needed to better understand the relationship between environmental factors at different spatial scales, assemblage structure and taxon richness of aquatic ecosystems. In this study, benthic invertebrate community patterns were sampled between June 2001 and April 2002 and analysed in relation to water quality and catchment land use patterns from three shallow near-shore bays characterized by three major land uses patterns: urban (Murchison Bay); semi-urban (Fielding Bay); rural (Hannington Bay). Variations in density and guild composition of benthic macro-invertebrates communities were evaluated using GIS techniques along an urban-rural gradient of land use and differences in community composition were related to dissolved oxygen and conductivity variation. Based on numerical abundance and tolerance values, Hilsenhoff's Biotic Index ofthe invertebrates was determined in order to evaluate the relative importance of water quality in the three bays. Murchison Bay supported a relatively taxa-poor invertebrate assemblage mainly comprising stenotopic and eurytopic populations of pollution-tolerant groups such as worms and Chironomus sp. with an overall depression in species diversity. On the contrary, the communities in Fielding and Hannington bays were quite similar and supported distinct and diverse assemblages including pollution-intolerant forms such as Ephemeroptera (mayflies), Odonata (dragonflies). The Hilsenhoff Biotic Index in Murchison Bay was 6.53. (indicating poor water quality) compared to 6.34 for Fielding Bay and 5.78 for Hannington Bay (both indicating fair water quality). The characterization of maximum taxa richness balanced among taxa groups with good representation of intolerant individuals in Hannington Bay relative to Fielding and Murchison bays concludes that the bay is the cleanest in terms of water quality. Contrary, the dominance of few taxa with many tolerant iqdividuals present in Murchison Bay indicates that the bay is degraded in terms of water quality. These result are ofimportance when planning conservation and management measures, implementing large-scale biomonitoring programs, and predicting how human alterations (e.g nutrient loading) affect water ecosystems. Therefore, analysis of water quality in relation to macro-invertebrate community composition patterns as bio-indicators can lead to further understanding of their responses to environmental manipulations and perturbations.

Selection for muscle fat content and triploidy affect flesh quality in pan-size rainbow trout, Oncorhynchus mykiss

A lean muscle line (L) and a fat muscle line (F) of rainbow trout were established (Quillet et al., 2005) by a two-way selection for muscle lipid content performed on pan-size rainbow trout using a non-destructive measurement of muscle lipid content (Distell Fish Fat Meter®). The aim of the present study was to evaluate the consequences of this selective breeding on flesh quality of pan size (290 g) diploid and triploid trout after three generations of selection. Instrumental evaluations of fillet color and pH measurement were performed at slaughter. Flesh color, pH, dry matter content and mechanical resistance were measured at 48 h and 96 h postmortem on raw and cooked flesh, respectively. A sensorial profile analysis was performed on cooked fillets. Fillets from the selected fatty muscle line (F) had a higher dry matter content and were more colorful for both raw and cooked fillets. Mechanical evaluation indicated a tendency of raw flesh from F fish to be less firm, but this was not confirmed after cooking, neither instrumentally or by sensory analysis. The sensory analysis revealed higher fat loss, higher intensity of flavor of cooked potato, higher exudation, higher moisture content and a more fatty film left on the tongue for flesh from F fish. Triploid fish had mechanically softer raw and cooked fillets, but the difference was not perceived by the sensorial panel. The sensorial evaluation also revealed a lower global intensity of odor, more exudation and a higher moisture content in the fillets from triploid fish. These differences in quality parameters among groups of fish were associated with larger white muscle fibers in F fish and in triploid fish. The data provide additional information about the relationship between muscle fat content, muscle cellularity and flesh quality.

Biofloc contribution to antioxidant defence status, lipid nutrition and reproductive performance of broodstock of the shrimp Litopenaeus stylirostris: Consequences for the quality of eggs and larvae

The aim of this study was to determine biofloc contributions to the antioxidant status and lipid nutrition of broodstock of Litopenaeus stylirostris in relationship with their reproductive performance and the health of larvae produced. Shrimp broodstock reared with Biofloc technology (BFT) compared to Clear water (CW) exhibited a higher health status with (i) a better final survival rate during the reproduction period (52.6% in CW against 79.8% in BFT); (ii) higher glutathione level (GSH) and total antioxidant status (TAS), reduced oxidized/reduced glutathione ratio and a higher spawning rate and frequency as well as higher gonado-somatic index and number of spawned eggs. Finally, larvae from broodstock from BFT exhibited higher survival rates at the Zoe 2 (+ 37%) and Post Larvae 1 (+ 51%) stages when compared with those from females from CW treatment. The improved reproductive performance of the broodstock and higher larvae survival rate resulting from BFT treatment may be linked to the dietary supplement obtained by the shrimp from natural productivity during BFT rearing. Indeed, our study confirms that biofloc particulates represent a potential source of dietary glutathione and a significant source of lipids, particularly essential phospholipids and n-3 highly unsaturated fatty acids (HUFA) for shrimps. Thus, broodstock from BFT treatment accumulated phospholipids, n-3 HUFA and arachidonic acid, which are necessary for vitellogenesis, embryogenesis and pre-feeding larval development. The predominant essential fatty acids, arachidonic acid (ARA), eicopentaeonic acid (EPA) and docosahexaenoic acid (DHA), had levels in the eggs that were, respectively, 2.5, 2.8 and 3 fold higher for BFT compared to the CW treatment. Statement of Relevance Today, the influence of biofloc technology on shrimp broodstock is not enough described and no information was available on the larvae quality. Moreover, two key pieces of new information emerge from the present study. Firstly, biofloc is a source of further dietary lipids that can act as energetic substrates, but also as a source of phospholipids and essential fatty acids necessary to sustain reproduction, embryonic and larval development. Second, improving the reproduction of the broodstock also leads to an improvement in the quality of the larvae. We think that our research is new and important to increase knowledge on biofloc topic. We believe the paper will contribute to the development of more efficient and therefore more sustainable systems.

Sex differences in quality of life in stroke survivors. Data from the Tinzaparin in Acute Ischaemic Stroke Trial (TAIST)

Introduction: Female sex is predictive of poor functional outcome in stroke, even after correction for prognostic factors. Poor quality of life (QoL) is observed in stroke survivors, with lower scores seen in the most disabled patients. We used data from the TAIST trial to assess the relationship between sex and QoL after ischaemic stroke. Methods: TAIST was a randomised controlled trial assessing the safety and efficacy of tinzaparin versus aspirin in 1,484 patients with acute ischaemic stroke. QoL was measured at 180 days post randomisation using the short-form 36 health survey which assesses QoL across eight domains. The relationship between sex and each domain was assessed using ordinal regression, both unadjusted and adjusted for key prognostics factors. Results: Of the 1,484 patients randomised into TAIST, 216 had died at 180 days post randomisation. 1,268 survivors were included in this analysis, 694 males (55%), 574 females (45%). Females tended to score lower than males across all QoL domains (apart from general health); statistically significant lower scores were seen for physical functioning (odds ratio (OR) 0.58, 95% confidence interval (CI) 0.47-0.72), vitality (OR 0.79, 95% CI 0.64-0.98) and mental health (OR 0.75, 95% CI 0.61-0.93). The results for physical functioning and mental health remained significant after adjustment for prognostic variables (OR 0.73, 95% CI 0.58-0.92; OR 0.76, 95% CI 0.60-0.95 respectively). Conclusions: QoL, in particular physical function and mental health domains, is lower in female patients after stroke. This difference persists even after correction for known prognostic factors such as age and stroke severity.