Headspace Analysis of Smokeless Powders: Development of Mass Calibration Methods using Microdrop Printing for Chromatographic and Ion Mobility Spectrometric Detection

Smokeless powder additives are usually detected by their extraction from post-blast residues or unburned powder particles followed by analysis using chromatographic techniques. This work presents the first comprehensive study of the detection of the volatile and semi-volatile additives of smokeless powders using solid phase microextraction (SPME) as a sampling and pre-concentration technique. Seventy smokeless powders were studied using laboratory based chromatography techniques and a field deployable ion mobility spectrometer (IMS). The detection of diphenylamine, ethyl and methyl centralite, 2,4-dinitrotoluene, diethyl and dibutyl phthalate by IMS to associate the presence of these compounds to smokeless powders is also reported for the first time. A previously reported SPME-IMS analytical approach facilitates rapid sub-nanogram detection of the vapor phase components of smokeless powders. A mass calibration procedure for the analytical techniques used in this study was developed. Precise and accurate mass delivery of analytes in picoliter volumes was achieved using a drop-on-demand inkjet printing method. Absolute mass detection limits determined using this method for the various analytes of interest ranged between 0.03 - 0.8 ng for the GC-MS and between 0.03 - 2 ng for the IMS. Mass response graphs generated for different detection techniques help in the determination of mass extracted from the headspace of each smokeless powder. The analyte mass present in the vapor phase was sufficient for a SPME fiber to extract most analytes at amounts above the detection limits of both chromatographic techniques and the ion mobility spectrometer. Analysis of the large number of smokeless powders revealed that diphenylamine was present in the headspace of 96% of the powders. Ethyl centralite was detected in 47% of the powders and 8% of the powders had methyl centralite available for detection from the headspace sampling of the powders by SPME. Nitroglycerin was the dominant peak present in the headspace of the double-based powders. 2,4-dinitrotoluene which is another important headspace component was detected in 44% of the powders. The powders therefore have more than one headspace component and the detection of a combination of these compounds is achievable by SPME-IMS leading to an association to the presence of smokeless powders.

Immunocytes of the Atlantic bottlenose dolphin (Tursiops truncatus) and West Indian manatee (Trichechus manatus latirostris) : morphologic characterizations and correlations between healthy and disease states under free-ranging and captive conditions

Interest in the health of marine mammals has increased due, in part, to the attention given to human impact on the marine environment. Recent mass strandings of the Atlantic bottlenose dolphin (Tursiops truncatus) and rising mortalities of the endangered Florida manatee (Trichechus manatus latirostris) have raised questions on the extent to which pollution, infectious disease, "stress," and captivity influence the immune system of these animals. This study has provided the first in-depth characterization of immunocytes in the peripheral blood of dolphins (n=180) and manatees (n=56). Immunocyte morphology and baseline values were determined in clinically normal animals under free-ranging, stranded and captive living conditions as well as by age and sex. Additionally, immuocyte population dynamics were characterized in sick animals. This was accomplished with traditional cytochemical techniques and new lymphocyte phenotyping methodology which was validated in this study. Traditional cytochemical techniques demonstrated that blood immunocyte morphology and cell numbers are similar to terrestrial mammals with some notable exceptions. The manatee heterophilic granulocyte is a morphologically unique cell and probably functions similarly to the typical mammalian neutrophil. Eosinophils were rarely found in manatees but were uncommonly high in healthy and sick dolphins. Basophils were not identified. Manatees had higher total lymphocyte numbers compared to dolphins and most terrestrial mammals. Lymphocyte subsets identified in healthy animals included Th, Tes, B and NK cells. Dolphin and manatee T and B cell values were higher than those reported in man and most terrestrial mammals. The manatee has extraordinarily high absolute numbers of circulating Th cells which suggests an enhanced immunological response capability. With few exceptions, immunocyte types and absolute numbers were not significantly different between free-ranging, stranded and captive categories or between sex and age categories. The evaluation of immunocyte dynamics in various disease states demonstrated a wide variation in cellular responses which provided new insights into innate, humoral and cell-mediated immunity in these species. Additionally, this study demonstrated that lymphocyte phenotyping has diagnostic significance and could be developed into a potential indicator of immunocompetence in both free-ranging and captive dolphin and manatee populations.

Improved image analysis based corrosion assessment using preprocessing techniques

The importance of non-destructive techniques (NDT) in structural health monitoring programmes is being critically felt in the recent times. The quality of the measured data, often affected by various environmental conditions can be a guiding factor in terms usefulness and prediction efficiencies of the various detection and monitoring methods used in this regard. Often, a preprocessing of the acquired data in relation to the affecting environmental parameters can improve the information quality and lead towards a significantly more efficient and correct prediction process. The improvement can be directly related to the final decision making policy about a structure or a network of structures and is compatible with general probabilistic frameworks of such assessment and decision making programmes. This paper considers a preprocessing technique employed for an image analysis based structural health monitoring methodology to identify sub-marine pitting corrosion in the presence of variable luminosity, contrast and noise affecting the quality of images. A preprocessing of the gray-level threshold of the various images is observed to bring about a significant improvement in terms of damage detection as compared to an automatically computed gray-level threshold. The case dependent adjustments of the threshold enable to obtain the best possible information from an existing image. The corresponding improvements are observed in a qualitative manner in the present study.

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.

Outcomes and Predictors of Mortality in Neurosurgical Patients at Mbarara Regional Referral Hospital

Background:

Knowing the scope of neurosurgical disease at Mbarara Hospital is critical for infrastructure planning, education and training. In this study, we aim to evaluate the neurosurgical outcomes and identify predictors of mortality in order to potentiate platforms for more effective interventions and inform future research efforts at Mbarara Hospital.

Methods:

This is retrospective chart review including patients of all ages with a neurosurgical disease or injury presenting to Mbarara Regional Referral Hospital (MRRH) between January 2012 to September 2015. Descriptive statistics were presented. A univariate analysis was used to obtain the odds ratios of mortality and 95% confidence intervals. Predictors of mortality were determined using multivariate logistic regression model.

Results:

A total of 1876 charts were reviewed. Of these, 1854 (had complete data and were?) were included in the analysis. The overall mortality rate was 12.75%; the mortality rates among all persons who underwent a neurosurgical procedure was 9.72%, and was 13.68% among those who did not undergo a neurosurgical procedure. Over 50% of patients were between 19 and 40 years old and the majority of were males (76.10%). The overall median length of stay was 5 days. Of all neurosurgical admissions, 87% were trauma patients. In comparison to mild head injury, closed head injury and intracranial hematoma patients were 5 (95% CI: 3.77, 8.26) and 2.5 times (95% CI: 1.64,3.98) more likely to die respectively. Procedure and diagnostic imaging were independent negative predictors of mortality (P <0.05). While age, ICU admission, admission GCS were positive predictors of mortality (P <0.05).

Conclusions:

The majority of hospital admissions were TBI patients, with RTIs being the most common mechanism of injury. Age, ICU admission, admission GCS, diagnostic imaging and undergoing surgery were independent predictors of mortality. Going forward, further exploration of patient characteristics is necessary to fully describe mortality outcomes and implement resource appropriate interventions that ultimately improve morbidity and mortality.

Surgical Procedure Characteristics and Risk of Sharps-Related Blood and Body Fluid Exposure.

OBJECTIVE To use a unique multicomponent administrative data set assembled at a large academic teaching hospital to examine the risk of percutaneous blood and body fluid (BBF) exposures occurring in operating rooms. DESIGN A 10-year retrospective cohort design. SETTING A single large academic teaching hospital. PARTICIPANTS All surgical procedures (n=333,073) performed in 2001-2010 as well as 2,113 reported BBF exposures were analyzed. METHODS Crude exposure rates were calculated; Poisson regression was used to analyze risk factors and account for procedure duration. BBF exposures involving suture needles were examined separately from those involving other device types to examine possible differences in risk factors. RESULTS The overall rate of reported BBF exposures was 6.3 per 1,000 surgical procedures (2.9 per 1,000 surgical hours). BBF exposure rates increased with estimated patient blood loss (17.7 exposures per 1,000 procedures with 501-1,000 cc blood loss and 26.4 exposures per 1,000 procedures with >1,000 cc blood loss), number of personnel working in the surgical field during the procedure (34.4 exposures per 1,000 procedures having ≥15 personnel ever in the field), and procedure duration (14.3 exposures per 1,000 procedures lasting 4 to <6 hours, 27.1 exposures per 1,000 procedures lasting ≥6 hours). Regression results showed associations were generally stronger for suture needle-related exposures. CONCLUSIONS Results largely support other studies found in the literature. However, additional research should investigate differences in risk factors for BBF exposures associated with suture needles and those associated with all other device types. Infect. Control Hosp. Epidemiol. 2015;37(1):80-87.

Prospective Estimation of Radiation Dose and Image Quality for Optimized CT Performance

X-ray computed tomography (CT) is a non-invasive medical imaging technique that generates cross-sectional images by acquiring attenuation-based projection measurements at multiple angles. Since its first introduction in the 1970s, substantial technical improvements have led to the expanding use of CT in clinical examinations. CT has become an indispensable imaging modality for the diagnosis of a wide array of diseases in both pediatric and adult populations [1, 2]. Currently, approximately 272 million CT examinations are performed annually worldwide, with nearly 85 million of these in the United States alone [3]. Although this trend has decelerated in recent years, CT usage is still expected to increase mainly due to advanced technologies such as multi-energy [4], photon counting [5], and cone-beam CT [6].

Despite the significant clinical benefits, concerns have been raised regarding the population-based radiation dose associated with CT examinations [7]. From 1980 to 2006, the effective dose from medical diagnostic procedures rose six-fold, with CT contributing to almost half of the total dose from medical exposure [8]. For each patient, the risk associated with a single CT examination is likely to be minimal. However, the relatively large population-based radiation level has led to enormous efforts among the community to manage and optimize the CT dose.

As promoted by the international campaigns Image Gently and Image Wisely, exposure to CT radiation should be appropriate and safe [9, 10]. It is thus a responsibility to optimize the amount of radiation dose for CT examinations. The key for dose optimization is to determine the minimum amount of radiation dose that achieves the targeted image quality [11]. Based on such principle, dose optimization would significantly benefit from effective metrics to characterize radiation dose and image quality for a CT exam. Moreover, if accurate predictions of the radiation dose and image quality were possible before the initiation of the exam, it would be feasible to personalize it by adjusting the scanning parameters to achieve a desired level of image quality. The purpose of this thesis is to design and validate models to quantify patient-specific radiation dose prospectively and task-based image quality. The dual aim of the study is to implement the theoretical models into clinical practice by developing an organ-based dose monitoring system and an image-based noise addition software for protocol optimization.

More specifically, Chapter 3 aims to develop an organ dose-prediction method for CT examinations of the body under constant tube current condition. The study effectively modeled the anatomical diversity and complexity using a large number of patient models with representative age, size, and gender distribution. The dependence of organ dose coefficients on patient size and scanner models was further evaluated. Distinct from prior work, these studies use the largest number of patient models to date with representative age, weight percentile, and body mass index (BMI) range.

With effective quantification of organ dose under constant tube current condition, Chapter 4 aims to extend the organ dose prediction system to tube current modulated (TCM) CT examinations. The prediction, applied to chest and abdominopelvic exams, was achieved by combining a convolution-based estimation technique that quantifies the radiation field, a TCM scheme that emulates modulation profiles from major CT vendors, and a library of computational phantoms with representative sizes, ages, and genders. The prospective quantification model is validated by comparing the predicted organ dose with the dose estimated based on Monte Carlo simulations with TCM function explicitly modeled.

Chapter 5 aims to implement the organ dose-estimation framework in clinical practice to develop an organ dose-monitoring program based on a commercial software (Dose Watch, GE Healthcare, Waukesha, WI). In the first phase of the study we focused on body CT examinations, and so the patient’s major body landmark information was extracted from the patient scout image in order to match clinical patients against a computational phantom in the library. The organ dose coefficients were estimated based on CT protocol and patient size as reported in Chapter 3. The exam CTDIvol, DLP, and TCM profiles were extracted and used to quantify the radiation field using the convolution technique proposed in Chapter 4.

With effective methods to predict and monitor organ dose, Chapters 6 aims to develop and validate improved measurement techniques for image quality assessment. Chapter 6 outlines the method that was developed to assess and predict quantum noise in clinical body CT images. Compared with previous phantom-based studies, this study accurately assessed the quantum noise in clinical images and further validated the correspondence between phantom-based measurements and the expected clinical image quality as a function of patient size and scanner attributes.

Chapter 7 aims to develop a practical strategy to generate hybrid CT images and assess the impact of dose reduction on diagnostic confidence for the diagnosis of acute pancreatitis. The general strategy is (1) to simulate synthetic CT images at multiple reduced-dose levels from clinical datasets using an image-based noise addition technique; (2) to develop quantitative and observer-based methods to validate the realism of simulated low-dose images; (3) to perform multi-reader observer studies on the low-dose image series to assess the impact of dose reduction on the diagnostic confidence for multiple diagnostic tasks; and (4) to determine the dose operating point for clinical CT examinations based on the minimum diagnostic performance to achieve protocol optimization.

Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.

Design, fabrication and characterization of resonant waveguide grating based optical biosensors

The absence of rapid, low cost and highly sensitive biodetection platform has hindered the implementation of next generation cheap and early stage clinical or home based point-of-care diagnostics. Label-free optical biosensing with high sensitivity, throughput, compactness, and low cost, plays an important role to resolve these diagnostic challenges and pushes the detection limit down to single molecule. Optical nanostructures, specifically the resonant waveguide grating (RWG) and nano-ribbon cavity based biodetection are promising in this context. The main element of this dissertation is design, fabrication and characterization of RWG sensors for different spectral regions (e.g. visible, near infrared) for use in label-free optical biosensing and also to explore different RWG parameters to maximize sensitivity and increase detection accuracy. Design and fabrication of the waveguide embedded resonant nano-cavity are also studied. Multi-parametric analyses were done using customized optical simulator to understand the operational principle of these sensors and more important the relationship between the physical design parameters and sensor sensitivities. Silicon nitride (SixNy) is a useful waveguide material because of its wide transparency across the whole infrared, visible and part of UV spectrum, and comparatively higher refractive index than glass substrate. SixNy based RWGs on glass substrate are designed and fabricated applying both electron beam lithography and low cost nano-imprint lithography techniques. A Chromium hard mask aided nano-fabrication technique is developed for making very high aspect ratio optical nano-structure on glass substrate. An aspect ratio of 10 for very narrow (~60 nm wide) grating lines is achieved which is the highest presented so far. The fabricated RWG sensors are characterized for both bulk (183.3 nm/RIU) and surface sensitivity (0.21nm/nm-layer), and then used for successful detection of Immunoglobulin-G (IgG) antibodies and antigen (~1μg/ml) both in buffer and serum. Widely used optical biosensors like surface plasmon resonance and optical microcavities are limited in the separation of bulk response from the surface binding events which is crucial for ultralow biosensing application with thermal or other perturbations. A RWG based dual resonance approach is proposed and verified by controlled experiments for separating the response of bulk and surface sensitivity. The dual resonance approach gives sensitivity ratio of 9.4 whereas the competitive polarization based approach can offer only 2.5. The improved performance of the dual resonance approach would help reducing probability of false reading in precise bio-assay experiments where thermal variations are probable like portable diagnostics.

Refining the diagnosis and EGFR status of non-small cell lung carcinoma in biopsy and cytologic material, using a panel of mucin staining, TTF-1, cytokeratin 5/6, and P63, and EGFR mutation analysis.

INTRODUCTION: The dichotomization of non-small cell carcinoma (NSCLC) subtype into squamous (SQCC) and adenocarcinoma (ADC) has become important in recent years and is increasingly required with regard to management. The aim of this study was to determine the utility of a panel of commercially available antibodies in refining the diagnosis on small biopsies and also to determine whether cytologic material is suitable for somatic EGFR genotyping in a prospectively analyzed series of patients undergoing investigation for suspected lung cancer. METHODS: Thirty-two consecutive cases of NSCLC were first tested using a panel comprising cytokeratin 5/6, P63, thyroid transcription factor-1, 34betaE12, and a D-PAS stain for mucin, to determine their value in refining diagnosis of NSCLC. After this test phase, two further pathologists independently reviewed the cases using a refined panel that excluded 34betaE12 because of its low specificity for SQCC, and refinement of diagnosis and concordance were assessed. Ten cases of ADC, including eight derived from cytologic samples, were sent for EGFR mutation analysis. RESULTS: There was refinement of diagnosis in 65% of cases of NSCLC to either SQCC or ADC in the test phase. This included 10 of 13 cases where cell pellets had been prepared from transbronchial needle aspirates. Validation by two further pathologists with varying expertise in lung pathology confirmed increased refinement and concordance of diagnosis. All samples were adequate for analysis, and they all showed a wild-type EGFR genotype. CONCLUSION: A panel comprising cytokeratin 5/6, P63, thyroid transcription factor-1, and a D-PAS stain for mucin increases diagnostic accuracy and agreement between pathologists when faced with refining a diagnosis of NSCLC to SQCC or ADC. These small samples, even cell pellets derived from transbronchial needle aspirates, seem to be adequate for EGFR mutation analysis.

Prevalence of biomicroscopic findings in the anterior segment and ocular adnexa among schoolchildren in Natal/Brazil

Objective: To determine the prevalence of ocular findings of the external structures and anterior segment of the eye, detected by biomicroscopic examination in schoolchildren in Natal (RN) - Brazil. Methods: After previous random selection, 1,024 pupils from elementary and secondary public and private schools in the city of Natal were evaluated from March to June 2001. All were submitted to preestablished standard research norms, consisting of identification, demographic information, ophthalmologic biomicroscopic examination, with slit lamp, performed by ophthalmologists from the “Onofre Lopes” University Hospital. Results: Alterations of the conjunctival and palpebral conditions were the most prevalent (10.4% and 6.2% respectively). Follicles (4.2%) and papillae (3.0%) were the frequent conjunctival lesions, while blepharitis (3.5%) and meibomitis (1.1%) were the most detected abnormalities in the eyelids. Upon examining the cornea, iris, lens and anterior vitreous, the most encountered findings were nubecula (0.5%), papillary membrane reliquiae (0.5%), posterior capsula opacity (0.8%) and hyaloid arteria reliquiae (2.0%). Conclusion: The most prevalent findings affecting the external structures of the eye such as eyelids and conjunctiva, consisted of blepharitis followed by follicular reaction of the conjunctiva. The most prevalent abnormalities in the cornea, iris, lens and anterior vitreous were nubecula, papillary membrane reliquiae, posterior capsular opacity and hyaloid arteria reliquiae, in that order

Nucleic Acid Diagnostics using Isotachophoresis and Isothermal Amplification

Thesis (Ph.D.)--University of Washington, 2016-08

Institutional entrepreneurship and techniques of inclusiveness in the creation of the Intergovernmental Platform on Biodiversity and Ecosystem Services

This article contributes to understanding the conditions of social-ecological change by focusing on the agency of individuals in the pathways to institutionalization. Drawing on the case of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), it addresses institutional entrepreneurship in an emerging environmental science-policy institution (ESPI) at a global scale. Drawing on ethnographic observations, semistructured interviews, and document analysis, we propose a detailed chronology of the genesis of the IPBES before focusing on the final phase of the negotiations toward the creation of the institution. We analyze the techniques and skills deployed by the chairman during the conference to handle the tensions at play both to prevent participants from deserting the negotiations arena and to prevent a lack of inclusiveness from discrediting the future institution. We stress that creating a new global environmental institution requires the situated exercise of an art of “having everybody on board” through techniques of inclusiveness that we characterize. Our results emphazise the major challenge of handling the fragmentation and plasticity of the groups of interest involved in the institutionalization process, thus adding to the theory of transformative agency of institutional entrepreneurs. Although inclusiveness might remain partly unattainable, such techniques of inclusiveness appear to be a major condition of the legitimacy and success of the institutionalization of a new global ESPI. Our results also add to the literature on boundary making within ESPIs by emphasizing the multiplicity and plasticity of the groups actually at stake.

Clinical utility of amyloid PET imaging in the differential diagnosis of atypical dementias and its impact on caregivers

La maladie d’Alzheimer (MA) se caractérise pathologiquement par l’accumulation de plaques amyloïde dans le cerveau. La tomographie par émission de positrons (TEP) permet d’imager les plaques amyloïde in vivo. Le but de ce projet est d’évaluer le rôle de la TEP amyloïde dans le processus diagnostique de la MA dans des cas de démences atypiques. Le deuxième but de ce projet est de déterminer l’impact de la révélation d’un diagnostic plus certain chez les proches aidants. 28 patients sans diagnostic malgré une investigation exhaustive ont été sélectionnées et imagées avec le traceur amyloïde 18F-NAV4694 (âge 59,3 ans, é-t. 5,8; MMSE 21.4, é-t 6.0). Les neurologues référents documentaient par la suite tout changement de niveau de certitude, de diagnostic, de traitement et/ou de prise en charge. Les proches aidants consentants ont été rencontrés subséquemment, et un questionnaire avec une échelle de Likert a été utilisé afin de documenter l’impact de l’imagerie leur perception de la maladie. Notre cohorte a été également divisée entre amyloïde positifs (14/28) et négatifs (14/28). Un changement de diagnostic a lieu dans 9/28 cas (32,1% :17.8% ont changé de MA à non-MA, 14,3% de non-MA à MA). Il y avait une augmentation significative (p<0,05) de 44% dans la certitude du neurologue suite à cet examen. Un changement de prise en charge a été obtenu dans 20/28 (71,4%) des cas. Bien que non significatifs statistiquement, un impact favorable sur les proches-aidants a été noté. Cette étude suggère que l’imagerie amyloïde a un rôle bénéfique dans les cas de démences atypiques n’ayant pu être élucidés avec les techniques d’investigations actuellement recommandées. De plus, le processus a été perçu positivement par les proches aidants, notamment en encourageant du temps de qualité avec leurs personnes chères. Ceci illustre un rôle prometteur des biomarqueurs, qui sont de plus en plus explorés.

Prevalence of biomicroscopic findings in the anterior segment and ocular adnexa among schoolchildren in Natal/Brazil

Objective: To determine the prevalence of ocular findings of the external structures and anterior segment of the eye, detected by biomicroscopic examination in schoolchildren in Natal (RN) - Brazil. Methods: After previous random selection, 1,024 pupils from elementary and secondary public and private schools in the city of Natal were evaluated from March to June 2001. All were submitted to preestablished standard research norms, consisting of identification, demographic information, ophthalmologic biomicroscopic examination, with slit lamp, performed by ophthalmologists from the “Onofre Lopes” University Hospital. Results: Alterations of the conjunctival and palpebral conditions were the most prevalent (10.4% and 6.2% respectively). Follicles (4.2%) and papillae (3.0%) were the frequent conjunctival lesions, while blepharitis (3.5%) and meibomitis (1.1%) were the most detected abnormalities in the eyelids. Upon examining the cornea, iris, lens and anterior vitreous, the most encountered findings were nubecula (0.5%), papillary membrane reliquiae (0.5%), posterior capsula opacity (0.8%) and hyaloid arteria reliquiae (2.0%). Conclusion: The most prevalent findings affecting the external structures of the eye such as eyelids and conjunctiva, consisted of blepharitis followed by follicular reaction of the conjunctiva. The most prevalent abnormalities in the cornea, iris, lens and anterior vitreous were nubecula, papillary membrane reliquiae, posterior capsular opacity and hyaloid arteria reliquiae, in that order

Development of radiotracers for nuclear imaging of poly(ADP-ribose) polymerase-1 and the translocator protein in glioblastoma.

Glioblastoma (GBM) is a highly aggressive and fatal brain cancer that is associated with a number of diagnostic, therapeutic, and treatment monitoring challenges. At the time of writing, inhibition of a protein called poly (ADP-ribose) polymerase-1 (PARP-1) in combination with chemotherapy was being investigated as a novel approach for the treatment of these tumours. However, human studies have encountered toxicity problems due to sub-optimal PARP-1 inhibitor and chemotherapeutic dosing regiments. Nuclear imaging of PARP-1 could help to address these issues and provide additional insight into potential PARP-1 inhibitor resistance mechanisms. Furthermore, nuclear imaging of the translocator protein (TSPO) could be used to improve GBM diagnosis, pre-surgical planning, and treatment monitoring as TSPO is overexpressed by GBM lesions in good contrast to surrounding brain tissue. To date, relatively few nuclear imaging radiotracers have been discovered for PARP-1. On the other hand, numerous tracers exist for TSPO many of which have been investigated in humans. However, these TSPO radiotracers suffer from either poor pharmacokinetic properties or high sensitivity to human TSPO polymorphism that can affect their binding to TSPO. Bearing in mind the above and the high attrition rates associated with advancement of radiotracers to the clinic, there is a need for novel radiotracers that can be used to image PARP-1 and TSPO. This thesis reports the pre-clinical discovery programme that led to the identification of two potent PARP-1 inhibitors, 4 and 17, that were successfully radiolabelled to generate the potential SPECT and PET imaging agents [123I]-4 and [18F]-17 respectively. Evaluation of these radiotracers in mice bearing subcutaneous human GBM xenografts using ex vivo biodistribution techniques revealed that the agents were retained in tumour tissue due to specific PARP-1 binding. This thesis also describes the pre-clinical in vivo evaluation of [18F]-AB5186, which is a novel radiotracer discovered previously within the research group with potential for PET imaging of TSPO. Using ex vivo autoradiography and PET imaging the agent was revealed to accumulate in intracranial human GBM tumour xenografts in good contrast to surrounding brain tissue, which was due to specific binding to TSPO. The in vivo data for all three radiolabelled compounds warrants further pre-clinical investigations with potential for clinical advancement in mind.