Assessment of the occurrence and potential risks of antibiotics and their metabolites in South Florida waters using liquid chromatography tandem mass spectrometry

An automated on-line SPE-LC-MS/MS method was developed for the quantitation of multiple classes of antibiotics in environmental waters. High sensitivity in the low ng/L range was accomplished by using large volume injections with 10-mL of sample. Positive confirmation of analytes was achieved using two selected reaction monitoring (SRM) transitions per antibiotic and quantitation was performed using an internal standard approach. Samples were extracted using online solid phase extraction, then using column switching technique; extracted samples were immediately passed through liquid chromatography and analyzed by tandem mass spectrometry. The total run time per each sample was 20 min. The statistically calculated method detection limits for various environmental samples were between 1.2 and 63 ng/L. Furthermore, the method was validated in terms of precision, accuracy and linearity. ^ The developed analytical methodology was used to measure the occurrence of antibiotics in reclaimed waters (n=56), surface waters (n=53), ground waters (n=8) and drinking waters (n=54) collected from different parts of South Florida. In reclaimed waters, the most frequently detected antibiotics were nalidixic acid, erythromycin, clarithromycin, azithromycin trimethoprim, sulfamethoxazole and ofloxacin (19.3-604.9 ng/L). Detection of antibiotics in reclaimed waters indicates that they can't be completely removed by conventional wastewater treatment process. Furthermore, the average mass loads of antibiotics released into the local environment through reclaimed water were estimated as 0.248 Kg/day. Among the surface waters samples, Miami River (reaching up to 580 ng/L) and Black Creek canal (up to 124 ng/L) showed highest concentrations of antibiotics. No traces of antibiotics were found in ground waters. On the other hand, erythromycin (monitored as anhydro erythromycin) was detected in 82% of the drinking water samples (n.d-66 ng/L). The developed approach is suitable for both research and monitoring applications.^ Major metabolites of antibiotics in reclaimed wates were identified and quantified using high resolution benchtop Q-Exactive orbitrap mass spectrometer. A phase I metabolite of erythromycin was tentatively identified in full scan based on accurate mass measurement. Using extracted ion chromatogram (XIC), high resolution data-dependent MS/MS spectra and metabolic profiling software the metabolite was identified as desmethyl anhydro erythromycin with molecular formula C36H63NO12 and m/z 702.4423. The molar concentration of the metabolite to erythromycin was in the order of 13 %. To my knowledge, this is the first known report on this metabolite in reclaimed water. Another compound acetyl-sulfamethoxazole, a phase II metabolite of sulfamethoxazole was also identified in reclaimed water and mole fraction of the metabolite represent 36 %, of the cumulative sulfamethoxazole concentration. The results were illustrating the importance to include metabolites also in the routine analysis to obtain a mass balance for better understanding of the occurrence, fate and distribution of antibiotics in the environment. ^ Finally, all the antibiotics detected in reclaimed and surface waters were investigated to assess the potential risk to the aquatic organisms. The surface water antibiotic concentrations that represented the real time exposure conditions revealed that the macrolide antibiotics, erythromycin, clarithromycin and tylosin along with quinolone antibiotic, ciprofloxacin were suspected to induce high toxicity to aquatic biota. Preliminary results showing that, among the antibiotic groups tested, macrolides posed the highest ecological threat, and therefore, they may need to be further evaluated with, long-term exposure studies considering bioaccumulation factors and more number of species selected. Overall, the occurrence of antibiotics in aquatic environment is posing an ecological health concern.^

Biocompatibility assessment of biosorbable polymer coated nitinol alloys

Owing to an increased risk of aging population and a higher incidence of coronary artery disease (CAD), there is a need for more reliable and safer treatments. Numerous varieties of durable polymer-coated drug eluting stents (DES) are available in the market in order to mitigate in-stent restenosis. However, there are certain issues regarding their usage such as delayed arterial healing, thrombosis, inflammation, toxic corrosion by-products, mechanical stability and degradation. As a result, significant amount of research has to be devoted to the improvement of biodegradable polymer-coated implant materials in an effort to enhance their bioactive response. ^ In this investigation, magneto-electropolished (MEP) and a novel biodegradable polymer coated ternary Nitinol alloys, NiTiTa and NiTiCr were prepared to study their bio and hemocompatibility properties. The initial interaction of a biomaterial with its surroundings is dependent on its surface characteristics such as, composition, corrosion resistance, work of adhesion and morphology. In-vitro corrosion tests such as potentiodynamic polarization and electrochemical impedance spectroscopic (EIS) studies were conducted to determine the coating stability and longevity. In-vitro hemocompatibility studies and HUVEC cell growth was performed to determine their thrombogenic and biocompatibility properties. Critical delamination load of the polymer coated Nitinol alloys was determined using Nano-scratch analysis. Sulforhodamine B (SRB) assays were performed to elucidate the effect of metal ions leached from Nitinol alloys on the viability of HUVEC cells. Scanning Electron Microscopy (SEM), X-ray Photoelectron Spectroscopy (XPS), contact angle meter and X-ray diffraction (XRD) were used to characterize the surface of the alloys. ^ MEP treated and polymer coated (PC) Nitinol alloys displayed a corrosion resistant polymer coating as compared to uncoated alloys. MEP and PC has resulted in reduced Ni and Cr ion leaching from NiTi5Cr and subsequently low cytotoxicity. Thrombogenicity tests revealed significantly less platelet adhesion and confluent endothelial cell growth on polymer coated and uncoated ternary MEP Nitinol alloys. Finally, this research addresses the bio and hemocompatibility of MEP + PC ternary Nitinol alloys that could be used to manufacture blood contacting devices such as stents and vascular implants which can lead to lower U.S. healthcare spending.^

Prioritizing tropical habitats for long-distance migratory songbirds: an assessment of habitat quality at a stopover site in Colombia

Long-distance migratory birds are declining globally and migration has been identified as the primary source of mortality in this group. Despite this, our lack of knowledge of habitat use and quality at stopovers, i.e., sites where the energy for migration is accumulated, remains a barrier to designing appropriate conservation measures, especially in tropical regions. There is therefore an urgent need to assess stopover habitat quality and concurrently identify efficient and cost-effective methods for doing so. Given that fuel deposition rates directly influence stopover duration, departure fuel load, and subsequent speed of migration, they are expected to provide a direct measure of habitat quality and have the advantage of being measurable through body-mass changes. Here, we examined seven potential indicators of quality, including body-mass change, for two ecologically distinct Neotropical migratory landbirds on stopover in shade-coffee plantations and tropical humid premontane forest during spring migration in Colombia: (1) rate of body-mass change; (2) foraging rate; (3) recapture rate; (4) density; (5) flock size; (6) age and sex ratios; and (7) body-mass distribution. We found higher rates of mass change in premontane forest than in shade-coffee in Tennessee Warbler Oreothlypis peregrina, a difference that was mirrored in higher densities and body masses in forest. In Gray-cheeked Thrush Catharus minimus, a lack of recaptures in shade-coffee and higher densities in forest, also suggested that forest provided superior fueling conditions. For a reliable assessment of habitat quality, we therefore recommend using a suite of indicators, taking into account each species’ ecology and methodological considerations. Our results also imply that birds stopping over in lower quality habitats may spend a longer time migrating and require more stopovers, potentially leading to important carryover effects on reproductive fitness. Evaluating habitat quality is therefore imperative prior to defining the conservation value of newly identified stopover regions.

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.

Automated Assessment of Image Quality and Dose Attributes in Clinical CT Images

Computed tomography (CT) is a valuable technology to the healthcare enterprise as evidenced by the more than 70 million CT exams performed every year. As a result, CT has become the largest contributor to population doses amongst all medical imaging modalities that utilize man-made ionizing radiation. Acknowledging the fact that ionizing radiation poses a health risk, there exists the need to strike a balance between diagnostic benefit and radiation dose. Thus, to ensure that CT scanners are optimally used in the clinic, an understanding and characterization of image quality and radiation dose are essential.

The state-of-the-art in both image quality characterization and radiation dose estimation in CT are dependent on phantom based measurements reflective of systems and protocols. For image quality characterization, measurements are performed on inserts imbedded in static phantoms and the results are ascribed to clinical CT images. However, the key objective for image quality assessment should be its quantification in clinical images; that is the only characterization of image quality that clinically matters as it is most directly related to the actual quality of clinical images. Moreover, for dose estimation, phantom based dose metrics, such as CT dose index (CTDI) and size specific dose estimates (SSDE), are measured by the scanner and referenced as an indicator for radiation exposure. However, CTDI and SSDE are surrogates for dose, rather than dose per-se.

Currently there are several software packages that track the CTDI and SSDE associated with individual CT examinations. This is primarily the result of two causes. The first is due to bureaucracies and governments pressuring clinics and hospitals to monitor the radiation exposure to individuals in our society. The second is due to the personal concerns of patients who are curious about the health risks associated with the ionizing radiation exposure they receive as a result of their diagnostic procedures.

An idea that resonates with clinical imaging physicists is that patients come to the clinic to acquire quality images so they can receive a proper diagnosis, not to be exposed to ionizing radiation. Thus, while it is important to monitor the dose to patients undergoing CT examinations, it is equally, if not more important to monitor the image quality of the clinical images generated by the CT scanners throughout the hospital.

The purposes of the work presented in this thesis are threefold: (1) to develop and validate a fully automated technique to measure spatial resolution in clinical CT images, (2) to develop and validate a fully automated technique to measure image contrast in clinical CT images, and (3) to develop a fully automated technique to estimate radiation dose (not surrogates for dose) from a variety of clinical CT protocols.

Neurosurgical Needs and Assets Assessment of Public Hospitals in Uganda: An Eevaluation of Mulago Hospital to Inform Neurosurgical Program Planning at Mbarara

Background: Since 2007, there has been an ongoing collaboration between Duke University and Mulago National Referral Hospital (NRH) in Kampala, Uganda to increase surgical capacity. This program is prepared to expand to other sites within Uganda to improve neurosurgery outside of Kampala as well. This study assessed the existing progress at Mulago NRH and the neurosurgical needs and assets at two potential sites for expansion. Methods: Three public hospitals were visited to assess needs and assets: Mulago NRH, Mbarara Regional Referral Hospital (RRH), and Gulu RRH. At each site, a surgical capacity tool was administered and healthcare workers were interviewed about perceived needs and assets. A total of 39 interviews were conducted between the three sites. Thematic analysis of the interviews was conducted to identify the reported needs and assets at each hospital. Results: Some improvements are needed to the Duke-Mulago Collaboration model prior to expansion; minor changes to the neurosurgery residency program as well as the method for supply donation and training provided during neurosurgery camps need to examined. Neurosurgery can be implemented at Mbarara RRH currently but the hospital needs a biomedical equipment technician on staff immediately. Gulu RRH is not well positioned for Neurosurgery until there is a CT Scanner somewhere in the Northern Region of Uganda or at the hospital. Conclusions: Neurosurgery is already present in Uganda on a small scale and needs rapid expansion to meet patient needs. This progression is possible with prudent allocation of resources on strategic equipment purchases, human resources including clinical staff and biomedical staff, and changes to the supply chain management system.

Biocompatibility Assessment of Biosorbable Polymer Coated Nitinol Alloys

Owing to an increased risk of aging population and a higher incidence of coronary artery disease (CAD), there is a need for more reliable and safer treatments. Numerous varieties of durable polymer-coated drug eluting stents (DES) are available in the market in order to mitigate in-stent restenosis. However, there are certain issues regarding their usage such as delayed arterial healing, thrombosis, inflammation, toxic corrosion by-products, mechanical stability and degradation. As a result, significant amount of research has to be devoted to the improvement of biodegradable polymer-coated implant materials in an effort to enhance their bioactive response. In this investigation, magneto-electropolished (MEP) and a novel biodegradable polymer coated ternary Nitinol alloys, NiTiTa and NiTiCr were prepared to study their bio and hemocompatibility properties. The initial interaction of a biomaterial with its surroundings is dependent on its surface characteristics such as, composition, corrosion resistance, work of adhesion and morphology. In-vitro corrosion tests such as potentiodynamic polarization and electrochemical impedance spectroscopic (EIS) studies were conducted to determine the coating stability and longevity. In-vitro hemocompatibility studies and HUVEC cell growth was performed to determine their thrombogenic and biocompatibility properties. Critical delamination load of the polymer coated Nitinol alloys was determined using Nano-scratch analysis. Sulforhodamine B (SRB) assays were performed to elucidate the effect of metal ions leached from Nitinol alloys on the viability of HUVEC cells. Scanning Electron Microscopy (SEM), X-ray Photoelectron Spectroscopy (XPS), contact angle meter and X-ray diffraction (XRD) were used to characterize the surface of the alloys. MEP treated and polymer coated (PC) Nitinol alloys displayed a corrosion resistant polymer coating as compared to uncoated alloys. MEP and PC has resulted in reduced Ni and Cr ion leaching from NiTi5Cr and subsequently low cytotoxicity. Thrombogenicity tests revealed significantly less platelet adhesion and confluent endothelial cell growth on polymer coated and uncoated ternary MEP Nitinol alloys. Finally, this research addresses the bio and hemocompatibility of MEP + PC ternary Nitinol alloys that could be used to manufacture blood contacting devices such as stents and vascular implants which can lead to lower U.S. healthcare spending.

Assessment of the cortisol awakening response: Real-time analysis and curvilinear effects of sample timing inaccuracy

The cortisol awakening response (CAR) is typically measured in the domestic setting. Moderate sample timing inaccuracy has been shown to result in erroneous CAR estimates and such inaccuracy has been shown partially to explain inconsistency in the CAR literature. The need for more reliable measurement of the CAR has recently been highlighted in expert consensus guidelines where it was pointed out that less than 6% of published studies provided electronic-monitoring of saliva sampling time in the post-awakening period. Analyses of a merged data-set of published studies from our laboratory are presented. To qualify for selection, both time of awakening and collection of the first sample must have been verified by electronic-monitoring and sampling commenced within 15 min of awakening. Participants (n = 128) were young (median age of 20 years) and healthy. Cortisol values were determined in the 45 min post-awakening period on 215 sampling days. On 127 days, delay between verified awakening and collection of the first sample was less than 3 min (‘no delay’ group); on 45 days there was a delay of 4–6 min (‘short delay’ group); on 43 days the delay was 7–15 min (‘moderate delay’ group). Cortisol values for verified sampling times accurately mapped on to the typical post-awakening cortisol growth curve, regardless of whether sampling deviated from desired protocol timings. This provides support for incorporating rather than excluding delayed data (up to 15 min) in CAR analyses. For this population the fitted cortisol growth curve equation predicted a mean cortisol awakening level of 6 nmols/l (±1 for 95% CI) and a mean CAR rise of 6 nmols/l (±2 for 95% CI). We also modelled the relationship between real delay and CAR magnitude, when the CAR is calculated erroneously by incorrectly assuming adherence to protocol time. Findings supported a curvilinear hypothesis in relation to effects of sample delay on the CAR. Short delays of 4–6 min between awakening and commencement of saliva sampling resulted an overestimated CAR. Moderate delays of 7–15 min were associated with an underestimated CAR. Findings emphasize the need to employ electronic-monitoring of sampling accuracy when measuring the CAR in the domestic setting.

Viewbrics: Formative Assessment of Complex Skills with Video-Enhanced Rubrics (VER) in Dutch Secondary Education

To learn complex skills, like collaboration, learners need to acquire a concrete and consistent mental model of what it means to master this skill. If learners know their current mastery level and know their targeted mastery level, they can better determine their subsequent learning activities. Rubrics support learners in judging their skill performance as they provide textual descriptions of skills’ mastery levels with performance indicators for all constituent subskills. However, text-based rubrics have a limited capacity to support the formation of mental models with contextualized, time-related and observable behavioral aspects of a complex skill. This paper outlines the design of a study that intends to investigate the effect of rubrics with video modelling examples compared to text-based rubrics on skills acquisition and feedback provisioning. The hypothesis is that video-enhanced rubrics, compared to text based rubrics, will improve mental model formation of a complex skill and improve the feedback quality a learner receives (from e.g. teachers, peers) while practicing a skill, hence positively effecting final mastery of a skill.

External quality assessment of BRAF molecular analysis in melanoma

The availability of BRAF inhibitors has given metastatic melanoma patients an effective new treatment choice and molecular testing to determine the presence or absence of a BRAF codon 600 mutation is pivotal in the clinical management of these patients. This molecular test must be performed accurately and appropriately to ensure that the patient receives the most suitable treatment in a timely manner. Laboratories have introduced such testing; however, some experience low sample throughput making it critical that an external quality assurance programme is available to help promote a high standard of testing, reporting and provide an educational aspect for BRAF molecular testing. Laboratories took part in three rounds of external quality assessment (EQA) during a 12-month period giving participants a measure of the accuracy of genotyping, clinical interpretation of the result and experience in testing a range of different samples. Formalin fixed paraffin embedded tissue sections from malignant melanoma patients were distributed to participants for BRAF molecular testing. The standard of testing was generally high but distribution of a mutation other than the most common, p.(Val600Glu), highlighted concerns with detection or reporting of the presence of rarer mutations. The main issues raised in the interpretation of the results were the importance of clear unambiguous interpretation of the result tailored to the patient and the understanding that the treatment is different from that given to other stratified medicine programmes. The variability in reporting and wide range of methodologies used indicate a continuing need for EQA in this field.

Assessment of turbulence model predictions for a centrifugal compressor simulation

Steady-state computational fluid dynamics (CFD) simulations are an essential tool in the design process of centrifugal compressors. Whilst global parameters, such as pressure ratio and efficiency, can be predicted with reasonable accuracy, the accurate prediction of detailed compressor flow fields is a much more significant challenge. Much of the inaccuracy is associated with the incorrect selection of turbulence model. The need for a quick turnaround in simulations during the design optimisation process, also demands that the turbulence model selected be robust and numerically stable with short simulation times.
In order to assess the accuracy of a number of turbulence model predictions, the current study used an exemplar open CFD test case, the centrifugal compressor ‘Radiver’, to compare the results of three eddy viscosity models and two Reynolds stress type models. The turbulence models investigated in this study were (i) Spalart-Allmaras (SA) model, (ii) the Shear Stress Transport (SST) model, (iii) a modification to the SST model denoted the SST-curvature correction (SST-CC), (iv) Reynolds stress model of Speziale, Sarkar and Gatski (RSM-SSG), and (v) the turbulence frequency formulated Reynolds stress model (RSM-ω). Each was found to be in good agreement with the experiments (below 2% discrepancy), with respect to total-to-total parameters at three different operating conditions. However, for the off-design conditions, local flow field differences were observed between the models, with the SA model showing particularly poor prediction of local flow structures. The SST-CC showed better prediction of curved rotating flows in the impeller. The RSM-ω was better for the wake and separated flow in the diffuser. The SST model showed reasonably stable, robust and time efficient capability to predict global and local flow features.

Colorimetric Assessment of BCR-ABL1 Transcripts in Clinical Samples Via Gold Nanoprobes

Gold nanoparticles functionalized with thiolated oligonucleotides (Au-nanoprobes) have been used in a range of applications for the detection of bioanalytes of interest, from ions to proteins and DNA targets. These detection strategies are based on the unique optical properties of gold nanoparticles, in particular, the intense color that is subject to modulation by modification of the medium dieletric. Au-nanoprobes have been applied for the detection and characterization of specific DNA sequences of interest, namely pathogens and disease biomarkers. Nevertheless, despite its relevance, only a few reports exist on the detection of RNA targets. Among these strategies, the colorimetric detection of DNA has been proven to work for several different targets in controlled samples but demonstration in real clinical bioanalysis has been elusive. Here, we used a colorimetric method based on Au-nanoprobes for the direct detection of the e14a2 BCR-ABL fusion transcript in myeloid leukemia patient samples without the need for retro-transcription. Au-nanoprobes directly assessed total RNA from 38 clinical samples, and results were validated against reverse transcription-nested polymerase chain reaction (RT-nested PCR) and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The colorimetric Au-nanoprobe assay is a simple yet reliable strategy to scrutinize myeloid leukemia patients at diagnosis and evaluate progression, with obvious advantages in terms of time and cost, particularly in low- to medium-income countries where molecular screening is not routinely feasible. Graphical abstract Gold nanoprobe for colorimetric detection of BCR-ABL1 fusion transcripts originating from the Philadelphia chromosome.

Investigating the effects of caffeine on executive functions using traditional Stroop and a new ecologically-valid virtual reality task, the Jansari assessment of Executive Functions (JEF©)

Objective: Caffeine has been shown to have effects on certain areas of cognition, but in executive functioning the research is limited and also inconsistent. One reason could be the need for a more sensitive measure to detect the effects of caffeine on executive function. This study used a new non-immersive virtual reality assessment of executive functions known as JEF© (the Jansari Assessment of Executive Function) alongside the ‘classic’ Stroop Colour- Word task to assess the effects of a normal dose of caffeinated coffee on executive function. Method: Using a double-blind, counterbalanced within participants procedure 43 participants were administered either a caffeinated or decaffeinated coffee and completed the ‘JEF©’ and Stroop tasks, as well as a subjective mood scale and blood pressure pre- and post condition on two separate occasions a week apart. JEF© yields measures for eight separate aspects of executive functions, in addition to a total average score. Results: Findings indicate that performance was significantly improved on the planning, creative thinking, event-, time- and action-based prospective memory, as well as total JEF© score following caffeinated coffee relative to the decaffeinated coffee. The caffeinated beverage significantly decreased reaction times on the Stroop task, but there was no effect on Stroop interference. Conclusion: The results provide further support for the effects of a caffeinated beverage on cognitive functioning. In particular, it has demonstrated the ability of JEF© to detect the effects of caffeine across a number of executive functioning constructs, which weren’t shown in the Stroop task, suggesting executive functioning improvements as a result of a ‘typical’ dose of caffeine may only be detected by the use of more real-world, ecologically valid tasks.

Credible or not : A study on the factors influencing consumers' credibility assessment of product placements on Instagram

Background: To align with the new trend of using social media in the marketing mix, product placement has been adapted to social media platforms as one strategy to create attention. Especially on Instagram, product placements have gained popularity among companies. While scholars have focused on measuring the effectiveness of the strategy, suggesting that credibility is one component necessary for success, a gap in the research is illuminated when focusing on what makes a product placement on Instagram credible. Previous studies regarding credibility and its relation to traditional media have concluded that there are some factors essential in consumers’ credibility evaluation process. Since social media differs from traditional media, there was a need to investigate the applicability of credibility to the social media platform Instagram. Purpose: The purpose of this thesis was to examine key factors of product placement on Instagram that influence credibility. Method: To meet the purpose of this thesis a study with a mixed method research design was conducted. The qualitative data was collected through semi-structured interviews with the intention to discover how consumers evaluate credibility. The scales and items developed from the findings of the qualitative study were tested using a questionnaire to identify which factors that have the most influence on consumers’ credibility assessment. Conclusions: The overall findings indicate that consumers evaluate credibility based upon source, message and receiver characteristics. The empirical evidence suggests that the Expertise of influencer, Professionalism of picture, Trustworthiness of influencer, Connection to influencer and Causes of irritation are the factors that have the most influence on consumers’ credibility assessment of product placement on Instagram. The findings further implies that it is not only the factor itself that influence, credibility can additionally be transferred from one factor to another.

Performance assessment of a vertical axis turbine in a marine current flume tank and CFD modelling

As advances in numerical modelling techniques support the increased confidence in predictions from computer simulations, the need remains to have experimental verification built into the design process. This paper outlines the experimental investigation carried out on a shielded vertical axis turbine in a marine environment. The experiments consist of performance measurements and the use of particle image velocimetry on a small scale device in a marine current flume. The results demonstrate that the performance of the device can be modelled numerically; in particular, the results show that the numerical model used can correctly predict the increase in performance with Reynolds number.