Early detection of delirium in older medical inpatients: prodrome, predictors and motor subtyping

Background Delirium is highly prevalent, especially in older patients. It independently leads to adverse outcomes, but remains under-detected, particularly hypoactive forms. Although early identification and intervention is important, delirium prevention is key to improving outcomes. The delirium prodrome concept has been mooted for decades, but remains poorly characterised. Greater understanding of this prodrome would promote prompt identification of delirium-prone patients, and facilitate improved strategies for delirium prevention and management. Methods Medical inpatients of ≥70 years were screened for prevalent delirium using the Revised Delirium Rating Scale (DRS--‐R98). Those without prevalent delirium were assessed daily for delirium development, prodromal features and motor subtype. Survival analysis models identified which prodromal features predicted the emergence of incident delirium in the cohort in the first week of admission. The Delirium Motor Subtype Scale-4 was used to ascertain motor subtype. Results Of 555 patients approached, 191 patients were included in the prospective study. The median age was 80 (IQR 10) and 101 (52.9%) were male. Sixty-one patients developed incident delirium within a week of admission. Several prodromal features predicted delirium emergence in the cohort. Firstly, using a novel Prodromal Checklist based on the existing literature, and controlling for confounders, seven predictive behavioural features were identified in the prodromal period (for example, increasing confusion; and being easily distractible). Additionally, using serial cognitive tests and the DRS-R98 daily, multiple cognitive and other core delirium features were detected in the prodrome (for example inattention; and sleep-wake cycle disturbance). Examining longitudinal motor subtypes in delirium cases, subtypes were found to be predominantly stable over time, the most prevalent being hypoactive subtype (62.3%). Discussion This thesis explored multiple aspects of delirium in older medical inpatients, with particular focus on the characterisation of the delirium prodrome. These findings should help to inform future delirium educational programmes, and detection and prevention strategies.

Video anomaly detection in real-time on a Power-Aware Heterogeneous Platform

FPGAs and GPUs are often used when real-time performance in video processing is required. An accelerated processor is chosen based on task-specific priorities (power consumption, processing time and detection accuracy), and this decision is normally made once at design time. All three characteristics are important, particularly in battery-powered systems. Here we propose a method for moving selection of processing platform from a single design-time choice to a continuous run time one.We implement Histogram of Oriented Gradients (HOG) detectors for cars and people and Mixture of Gaussians (MoG) motion detectors running across FPGA, GPU and CPU in a heterogeneous system. We use this to detect illegally parked vehicles in urban scenes. Power, time and accuracy information for each detector is characterised. An anomaly measure is assigned to each detected object based on its trajectory and location, when compared to learned contextual movement patterns. This drives processor and implementation selection, so that scenes with high behavioural anomalies are processed with faster but more power hungry implementations, but routine or static time periods are processed with power-optimised, less accurate, slower versions. Real-time performance is evaluated on video datasets including i-LIDS. Compared to power-optimised static selection, automatic dynamic implementation mapping is 10% more accurate but draws 12W extra power in our testbed desktop system.

Flow Regime Identification Methodology with Mcnp-X Code And Artificial Neural Network

This paper presents flow regimes identification methodology in multiphase system in annular, stratified and homogeneous oil-water-gas regimes. The principle is based on recognition of the pulse height distributions (PHD) from gamma-ray with supervised artificial neural network (ANN) systems. The detection geometry simulation comprises of two NaI(Tl) detectors and a dual-energy gamma-ray source. The measurement of scattered radiation enables the dual modality densitometry (DMD) measurement principle to be explored. Its basic principle is to combine the measurement of scattered and transmitted radiation in order to acquire information about the different flow regimes. The PHDs obtained by the detectors were used as input to ANN. The data sets required for training and testing the ANN were generated by the MCNP-X code from static and ideal theoretical models of multiphase systems. The ANN correctly identified the three different flow regimes for all data set evaluated. The results presented show that PHDs examined by ANN may be applied in the successfully flow regime identification.

Anomaly Detection in Noisy Images

Finding rare events in multidimensional data is an important detection problem that has applications in many fields, such as risk estimation in insurance industry, finance, flood prediction, medical diagnosis, quality assurance, security, or safety in transportation. The occurrence of such anomalies is so infrequent that there is usually not enough training data to learn an accurate statistical model of the anomaly class. In some cases, such events may have never been observed, so the only information that is available is a set of normal samples and an assumed pairwise similarity function. Such metric may only be known up to a certain number of unspecified parameters, which would either need to be learned from training data, or fixed by a domain expert. Sometimes, the anomalous condition may be formulated algebraically, such as a measure exceeding a predefined threshold, but nuisance variables may complicate the estimation of such a measure. Change detection methods used in time series analysis are not easily extendable to the multidimensional case, where discontinuities are not localized to a single point. On the other hand, in higher dimensions, data exhibits more complex interdependencies, and there is redundancy that could be exploited to adaptively model the normal data. In the first part of this dissertation, we review the theoretical framework for anomaly detection in images and previous anomaly detection work done in the context of crack detection and detection of anomalous components in railway tracks. In the second part, we propose new anomaly detection algorithms. The fact that curvilinear discontinuities in images are sparse with respect to the frame of shearlets, allows us to pose this anomaly detection problem as basis pursuit optimization. Therefore, we pose the problem of detecting curvilinear anomalies in noisy textured images as a blind source separation problem under sparsity constraints, and propose an iterative shrinkage algorithm to solve it. Taking advantage of the parallel nature of this algorithm, we describe how this method can be accelerated using graphical processing units (GPU). Then, we propose a new method for finding defective components on railway tracks using cameras mounted on a train. We describe how to extract features and use a combination of classifiers to solve this problem. Then, we scale anomaly detection to bigger datasets with complex interdependencies. We show that the anomaly detection problem naturally fits in the multitask learning framework. The first task consists of learning a compact representation of the good samples, while the second task consists of learning the anomaly detector. Using deep convolutional neural networks, we show that it is possible to train a deep model with a limited number of anomalous examples. In sequential detection problems, the presence of time-variant nuisance parameters affect the detection performance. In the last part of this dissertation, we present a method for adaptively estimating the threshold of sequential detectors using Extreme Value Theory on a Bayesian framework. Finally, conclusions on the results obtained are provided, followed by a discussion of possible future work.

Microcantilever sensors for biochemical detection and analysis

Biochemical agents, including bacteria and toxins, are potentially dangerous and responsible for a wide variety of diseases. Reliable detection and characterization of small samples is necessary in order to reduce and eliminate their harmful consequences. Microcantilever sensors offer a potential alternative to the state of the art due to their small size, fast response time, and the ability to operate in air and liquid environments. At present, there are several technology limitations that inhibit application of microcantilever to biochemical detection and analysis, including difficulties in conducting temperature-sensitive experiments, material inadequacy resulting in insufficient cell capture, and poor selectivity of multiple analytes. This work aims to address several of these issues by introducing microcantilevers having integrated thermal functionality and by introducing nanocrystalline diamond as new material for microcantilevers. Microcantilevers are designed, fabricated, characterized, and used for capture and detection of cells and bacteria. The first microcantilever type described in this work is a silicon cantilever having highly uniform in-plane temperature distribution. The goal is to have 100 μm square uniformly heated area that can be used for thermal characterization of films as well as to conduct chemical reactions with small amounts of material. Fabricated cantilevers can reach above 300C while maintaining temperature uniformity of 2−4%. This is an improvement of over one order of magnitude over currently available cantilevers. The second microcantilever type is a doped single crystal silicon cantilever having a thin coating of ultrananocrystalline diamond (UNCD). The primary application of such a device is in biological testing, where diamond acts as a stable, electrically isolated reaction surface while silicon layer provides controlled heating with minimum variations in temperature. This work shows that composite cantilevers of this kind are an effective platform for temperature-sensitive biological experiments, such as heat lysing and polymerase chain reaction. The rapid heat-transfer of Si-UNCD cantilever compromised the membrane of NIH 3T3 fibroblast and lysed the cell nucleus within 30 seconds. Bacteria cells, Listeria monocytogenes V7, were shown to be captured with biotinylated heat-shock protein on UNCD surface and 90% of all viable cells exhibit membrane porosity due to high heat in 15 seconds. Lastly, a sensor made solely from UNCD diamond is fabricated with the intention of being used to detect the presence of biological species by means of an integrated piezoresistor or through frequency change monitoring. Since UNCD diamond has not been previously used in piezoresistive applications, temperature-denpendent piezoresistive coefficients and gage factors are determined first. The doped UNCD exhibits a significant piezoresistive effect with gauge factor of 7.53±0.32 and a piezoresistive coefficient of 8.12×10^−12 Pa^−1 at room temperature. The piezoresistive properties of UNCD are constant over the temperature range of 25−200C. 300 μm long cantilevers have the highest sensitivity of 0.186 m-Ohm/Ohm per μm of cantilever end deflection, which is approximately half that of similarly sized silicon cantilevers. UNCD cantilever arrays were fabricated consisting of four sixteen-cantilever arrays of length 20–90 μm in addition to an eight-cantilever array of length 120 μm. Laser doppler vibrometry (LDV) measured the cantilever resonant frequency, which ranged as 218 kHz−5.14 MHz in air and 73 kHz−3.68 MHz in water. The quality factor of the cantilever was 47−151 in air and 18−45 in water. The ability to measure frequencies of the cantilever arrays opens the possibility for detection of individual bacteria by monitoring frequency shift after cell capture.

Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows

As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DCA, including antigen multiplier and moving time windows, are reported. The real-valued Negative Selection Algorithm (NSA) using constant-sized detectors and the C4.5 decision tree algorithm are used, to conduct a baseline comparison. The results suggest that the DCA is applicable to KDD 99 data set, and the antigen multiplier and moving time windows have the same effect on the DCA for this particular data set. The real-valued NSA with contant-sized detectors is not applicable to the data set. And the C4.5 decision tree algorithm provides a benchmark of the classification performance for this data set.

MICROFLUIDIC ASSAY PERFORMANCE ENHANCEMENT USING POROUS VOLUMETRIC DETECTION ELEMENTS FOR IMPEDEMETRIC AND OPTICAL SENSING

Microfluidic technologies have great potential to help create automated, cost-effective, portable devices for rapid point of care (POC) diagnostics in diverse patient settings. Unfortunately commercialization is currently constrained by the materials, reagents, and instrumentation required and detection element performance. While most microfluidic studies utilize planar detection elements, this dissertation demonstrates the utility of porous volumetric detection elements to improve detection sensitivity and reduce assay times. Impedemetric immunoassays were performed utilizing silver enhanced gold nanoparticle immunoconjugates (AuIgGs) and porous polymer monolith or silica bead bed detection elements within a thermoplastic microchannel. For a direct assay with 10 µm spaced electrodes the detection limit was 0.13 fM AuIgG with a 3 log dynamic range. The same assay was performed with electrode spacing of 15, 40, and 100 µm with no significant difference between configurations. For a sandwich assay the detection limit was10 ng/mL with a 4 log dynamic range. While most impedemetric assays rely on expensive high resolution electrodes to enhance planar senor performance, this study demonstrates the employment of porous volumetric detection elements to achieve similar performance using lower resolution electrodes and shorter incubation times. Optical immunoassays were performed using porous volumetric capture elements perfused with refractive index matching solutions to limit light scattering and enhance signal. First, fluorescence signal enhancement was demonstrated with a porous polymer monolith within a silica capillary. Next, transmission enhancement of a direct assay was demonstrated by infusing aqueous sucrose solutions through silica bead beds with captured silver enhanced AuIgGs yielding a detection limit of 0.1 ng/mL and a 5 log dynamic range. Finally, ex situ functionalized porous silica monolith segments were integrated into thermoplastic channels for a reflectance based sandwich assay yielding a detection limit of 1 ng/mL and a 5 log dynamic range. The simple techniques for optical signal enhancement and ex situ element integration enable development of sensitive, multiplexed microfluidic sensors. Collectively the demonstrated experiments validate the use of porous volumetric detection elements to enhance impedemetric and optical microfluidic assays. The techniques rely on commercial reagents, materials compatible with manufacturing, and measurement instrumentation adaptable to POC diagnostics.

Calibration of the detector flight models for the HERMES and SPIRIT nanosatellite missions

The High Energy Rapid Modular Ensemble of Satellites (HERMES) is a new mission concept involving the development of a constellation of six CubeSats in low Earth orbit with new miniaturized instruments that host a hybrid Silicon Drift Detector/GAGG:Ce based system for X-ray and γ-ray detection, aiming to monitor high-energy cosmic transients, such as Gamma Ray Bursts and the electromagnetic counterparts of gravitational wave events. The HERMES constellation will also operate together with the Australian-Italian SpIRIT mission, which will house a HERMES-like detector. The HERMES pathfinder mini-constellation, consisting of six satellites plus SpIRIT, is likely to be launched in 2023. The HERMES detectors are based on the heritage of the Italian ReDSoX collaboration, with joint design and production by INFN-Trieste and Fondazione Bruno Kessler, and the involvement of several Italian research institutes and universities. An application-specific, low-noise, low-power integrated circuit (ASIC) called LYRA was conceived and designed for the HERMES readout electronics. My thesis project focuses on the ground calibrations of the first HERMES and SpIRIT flight detectors, with a performance assessment and characterization of the detectors. The first part of this work addresses measurements and experimental tests on laboratory prototypes of the HERMES detectors and their front-end electronics, while the second part is based on the design of the experimental setup for flight detector calibrations and related functional tests for data acquisition, as well as the development of the calibration software. In more detail, the calibration parameters (such as the gain of each detector channel) are determined using measurements with radioactive sources, performed at different operating temperatures between -20°C and +20°C by placing the detector in a suitable climate chamber. The final part of the thesis involves the analysis of the calibration data and a discussion of the results.

Quality controls for the Mu2e electromagnetic calorimeter and R&D studies for the muon capture rate determination

According to the SM, while Lepton Flavour Violation is allowed in the neutral sector, Charged Lepton Flavour Violation (CLFV) processes are forbidden. The Mu2e Experiment at Fermilab will search for the CLFV process of neutrinoless conversion of a muon into an electron within the field of an Al nucleus. The Mu2e detectors and its state-of-the-art superconducting magnetic system are presented, with special focus put to the electromagnetic crystal calorimeter. The calorimeter is composed by two annular disks, each one hosting pure CsI crystals read-out by custom silicon photomultipliers (SiPMs). The SiPMs are amplified by custom electronics (FEE) and are glued to copper holders in group of 2 SiPMs and 2 FEE boards thus forming a crystal Readout Unit. These Readout Units are being tested at the Quality Control (QC) Station, whose design, realization and operations are presented in this work. The QC Station allows to determine the gain, the response and the photon detection efficiency of each unit and to evaluate the dependence of these parameters from the supply voltage and temperature. The station is powered by two remotely-controlled power supplies and monitored thanks to a Slow Control system which is also illustrated in this work. In this thesis, we also demonstrated that the calorimeter can perform its own measurement of the Mu2e normalization factor, i.e. the counting of the 1.8 MeV photon line produced in nuclear muon captures. A specific calorimeter sub-system called CAPHRI, composed by four LYSO crystals with SiPM readout, has been designed and tested. We simulated the capability of this system on performing this task showing that it can get a faster and more reliable measurement of the muon capture rates with respect to the current Mu2e detector dedicated to this measurement. The characterization of energy resolution and response uniformity of the four procured LYSO crystals are llustrated.

Detection of Brucella ovis in ovine from Paraíba State, in the Northeast region of Brazil

To determine the presence of Brucella ovis in ovine from Paraíba State, in the Northeast region of Brazil, 80 animals slaughtered in the public slaughterhouse of Patos city were used. Before slaughter, blood samples were collected by jugular venopuncture from each animal, and after slaughter, testicles, epidydimus and uterus were aseptically collected. For the serological diagnosis of B. ovis and B. abortus infections, the agar gel immunodiffusion (AGID) and Rose Bengal (RBT) tests were carried out, respectively. In addition, microbiological culture and polymerase chain reaction (PCR) were performed on testicle, epidydimus and uterus samples. Six animals (7.5%) tested positive for the presence of B. ovis antibodies and all animals tested negative for the presence of B. abortus antibodies. One AGID-positive animal tested positive at uterine swab culture. PCR was able to amplify DNA of Brucella spp. from the pool of testicle, epidydimus and uterus samples from AGID-positive animals. This is the first report of isolation and detection of B. ovis DNA by PCR in ovine from the Northeast region of Brazil.

Experimental Infection of the Opossum Didelphis aurita by Rickettsia felis, Rickettsia bellii, and Rickettsia parkeri and Evaluation of the Transmission of the Infection to Ticks Amblyomma cajennense and Amblyomma dubitatum

This work evaluated the infection of opossums (Didelphis aurita) by Rickettsia felis, Rickettsia bellii, and Rickettsia parkeri and their role as amplifier hosts for horizontal transmission to Amblyomma cajennense and/or Amblyomma dubitatum ticks. Infection in D. aurita was induced by intraperitoneal inoculation with R. felis (n = 4 opossums), R. bellii (n = 4), and R. parkeri (n = 2). Another group of six opossums were inoculated intraperitoneally with Leibovitz-15 sterile culture medium, representing the uninfected groups (n = 2 opossums simultaneously to each infected group). Opossum blood samples collected during the study were used for DNA extraction, followed by real-time polymerase chain reaction targeting the rickettsial gene gltA, hematology, and detection of Rickettsia spp.-reactive antibodies by indirect immunofluorescence assay. Opossums were infested with uninfected A. cajennense and/or A. dubitatum for 30 days postinoculation (DPI). Flat ticks molted from ticks fed on opossums were allowed to feed on uninfected rabbits, which were tested for seroconversion by immunofluorescence assay. Samples of flat ticks were also tested by real-time polymerase chain reaction. Inoculated opossums showed no clinical abnormalities. Antibodies to Rickettsia spp. were first detected at the second to fourth DPI, with detectable titers until the 150th DPI. Rickettsemia was detected only in one opossum inoculated with R. parkeri, at the eighth DPI. Only one A. cajennense tick (2.0%) previously fed on a R. parkeri-inoculated opossum became infected. None of the rabbits infested with opossum-derived ticks seroconverted. The study demonstrated that R. felis, R. bellii, and R. parkeri were capable to produce antibody response in opossums, however, with undetectable rickettsemia for R. felis and R. bellii, and very low rickettsemia for R. parkeri. Further studies must be done with different strains of these rickettsiae, most importantly the strains that have never gone through in vitro passages.

KeaA, a Dictyostelium kelch-domain protein that regulates the response to stress and development

Background: The protein kinase YakA is responsible for the growth arrest and induction of developmental processes that occur upon starvation of Dictyostelium cells. yakA-cells are aggregation deficient, have a faster cell cycle and are hypersensitive to oxidative and nitrosoative stress. With the aim of isolating members of the YakA pathway, suppressors of the death induced by nitrosoative stress in the yakA-cells were identified. One of the suppressor mutations occurred in keaA, a gene identical to DG1106 and similar to Keap1 from mice and the Kelch protein from Drosophila, among others that contain Kelch domains. Results: A mutation in keaA suppresses the hypersensitivity to oxidative and nitrosoative stresses but not the faster growth phenotype of yakA-cells. The growth profile of keaA deficient cells indicates that this gene is necessary for growth. keaA deficient cells are more resistant to nitrosoative and oxidative stress and keaA is necessary for the production and detection of cAMP. A morphological analysis of keaA deficient cells during multicellular development indicated that, although the mutant is not absolutely deficient in aggregation, cells do not efficiently participate in the process. Gene expression analysis using cDNA microarrays of wild-type and keaA deficient cells indicated a role for KeaA in the regulation of the cell cycle and pre-starvation responses. Conclusions: KeaA is required for cAMP signaling following stress. Our studies indicate a role for kelch proteins in the signaling that regulates the cell cycle and development in response to changes in the environmental conditions.

Occurrence of AFM(1) in urine samples of a Brazilian population and association with food consumption

This survey evaluated the presence of AFM(1) in human urine samples from a specific Brazilian population, as well as corn, peanut, and milk consumption measured by two types of food inquiry. Urine samples from donors who live in the city of Piracicaba, State of Sao Paulo, Brazil were analyzed to detect the presence of aflatoxin M(1) (AFM(1)). an aflatoxin B(1) metabolite, which may be used as aflatoxin B(1) exposure biomarker. The AFM(1) analysis was performed using immunoaffinity clean-up and detection by high-performance-liquid chromatography with fluorescence detector. A total of 69 samples were analyzed and 45 of them (65%) presented contaminations >= 1.8 pg ml(-1), which was the limit of quantification (LOQ). Seventy eight percent (n = 54) of the samples presented detectable concentrations of AFM(1) (>0.6 pg ml(-1)). The AFM(1) concentration among samples above LOQ ranged from 1.8 to 39.9 pg ml(-1). There were differences in food consumption profile among donors, although no association was found between food consumption and AFM(1) concentration in urine. The high frequency of positive samples suggests exposure of the populations studied to aflatoxins. (C) 2009 Elsevier Ltd. All rights reserved.

Determination of Hg and diet identification in otter (Lontra longicaudis) feces

An analytical procedure for the determination of Hg in otter (Lontra longicaudis) feces was developed, to separate fish scales for the identification of the animal diet. Samples were washed with ultra-pure water and the suspension was sampled and transferred for digestion. The solubilization was performed with nitric-perchloric acid mixture, and detection carried out by the atomic fluorescence spectrometry (AFS). The quality of the analytical procedure was assessed by analyzing in-house standard solutions and certified reference materials. Total Hg concentrations were in the range of 7.6-156 ng g(-1) (July 2004), 25.6-277 ng g(-1) (January 2005) and 14.6-744 ng g(-1) (May 2005) that is approximately the same order of magnitude for all samples collected in two reservoirs at the Tiete River, Brazil. Although Hg concentrations varied with sampling periods and diet, high levels were correlated to the percentage of carnivorous fish scales present in the otter feces. (c) 2007 Elsevier Ltd. All rights reserved.