Quantification of upper limb motor symptoms of Parkinson’s disease using a smartphone

Panda

Myocardial blood flow quantification by Rb-82 cardiac PET/CT: A detailed reproducibility study between two semi-automatic analysis programs.

BACKGROUND: Several analysis software packages for myocardial blood flow (MBF) quantification from cardiac PET studies exist, but they have not been compared using concordance analysis, which can characterize precision and bias separately. Reproducible measurements are needed for quantification to fully develop its clinical potential. METHODS: Fifty-one patients underwent dynamic Rb-82 PET at rest and during adenosine stress. Data were processed with PMOD and FlowQuant (Lortie model). MBF and myocardial flow reserve (MFR) polar maps were quantified and analyzed using a 17-segment model. Comparisons used Pearson's correlation ρ (measuring precision), Bland and Altman limit-of-agreement and Lin's concordance correlation ρc = ρ·C b (C b measuring systematic bias). RESULTS: Lin's concordance and Pearson's correlation values were very similar, suggesting no systematic bias between software packages with an excellent precision ρ for MBF (ρ = 0.97, ρc = 0.96, C b = 0.99) and good precision for MFR (ρ = 0.83, ρc = 0.76, C b = 0.92). On a per-segment basis, no mean bias was observed on Bland-Altman plots, although PMOD provided slightly higher values than FlowQuant at higher MBF and MFR values (P < .0001). CONCLUSIONS: Concordance between software packages was excellent for MBF and MFR, despite higher values by PMOD at higher MBF values. Both software packages can be used interchangeably for quantification in daily practice of Rb-82 cardiac PET.

Quantification of the human postural control system to perturbations

Human standing posture is inherently unstable. The postural control system (PCS), which maintains standing posture, is composed of the sensory, musculoskeletal, and central nervous systems. Together these systems integrate sensory afferents and generate appropriate motor efferents to adjust posture. The PCS maintains the body center of mass (COM) with respect to the base of support while constantly resisting destabilizing forces from internal and external perturbations. To assess the human PCS, postural sway during quiet standing or in response to external perturbation have frequently been examined descriptively. Minimal work has been done to understand and quantify the robustness of the PCS to perturbations. Further, there have been some previous attempts to assess the dynamical systems aspects of the PCS or time evolutionary properties of postural sway. However those techniques can only provide summary information about the PCS characteristics; they cannot provide specific information about or recreate the actual sway behavior. This dissertation consists of two parts: part I, the development of two novel methods to assess the human PCS and, part II, the application of these methods. In study 1, a systematic method for analyzing the human PCS during perturbed stance was developed. A mild impulsive perturbation that subjects can easily experience in their daily lives was used. A measure of robustness of the PCS, 1/MaxSens that was based on the inverse of the sensitivity of the system, was introduced. 1/MaxSens successfully quantified the reduced robustness to external perturbations due to age-related degradation of the PCS. In study 2, a stochastic model was used to better understand the human PCS in terms of dynamical systems aspect. This methodology also has the advantage over previous methods in that the sway behavior is captured in a model that can be used to recreate the random oscillatory properties of the PCS. The invariant density which describes the long-term stationary behavior of the center of pressure (COP) was computed from a Markov chain model that was applied to postural sway data during quiet stance. In order to validate the Invariant Density Analysis (IDA), we applied the technique to COP data from different age groups. We found that older adults swayed farther from the centroid and in more stochastic and random manner than young adults. In part II, the tools developed in part I were applied to both occupational and clinical situations. In study 3, 1/MaxSens and IDA were applied to a population of firefighters to investigate the effects of air bottle configuration (weight and size) and vision on the postural stability of firefighters. We found that both air bottle weight and loss of vision, but not size of air bottle, significantly decreased balance performance and increased fall risk. In study 4, IDA was applied to data collected on 444 community-dwelling elderly adults from the MOBILIZE Boston Study. Four out of five IDA parameters were able to successfully differentiate recurrent fallers from non-fallers, while only five out of 30 more common descriptive and stochastic COP measures could distinguish the two groups. Fall history and the IDA parameter of entropy were found to be significant risk factors for falls. This research proposed a new measure for the PCS robustness (1/MaxSens) and a new technique for quantifying the dynamical systems aspect of the PCS (IDA). These new PCS analysis techniques provide easy and effective ways to assess the PCS in occupational and clinical environments.

Quantification of variable palmar ligaments around the triquetrum-hamate joint determined by lunate type

The ligaments of the wrist are highly variable and poorly described, which is more obvious on the ulnar side of the wrist. Previous studies highlighted the potential differences within the ligaments of the wrist but no consensus has been reached. Poor tissue description and inconsistent use of terminology hindered the reproducibility of the results. Improved understanding of the morphological variations between carpal bones may facilitate improved understanding of the ligamentous structure within the wrist. This study aims to identify the potential variations between carpal bones that could be used to separate palmar ligamentous patterns around the triquetrum-hamate joint into subgroups within the sample population. Investigations were performed following a detailed nomenclature and a clear definition of ligamentous structures to facilitate detailed description and reproducible results. Quantitative analyses were conducted using 3D modelling technique. Histological sections were then analysed to identify the structure of each ligamentous attachment. Variable patterns of ligamentous attachments were identified. Differences were not only obvious between samples but also between the right and left hands of the same person. These identifications suggested that the palmar ligamentous patterns around the triquetrum-hamate joint are best described as a spectrum with a higher affinity of the triquetrum-hamate-capitate ligament and the lunate-triquetrum ligament to be associated with type I lunate wrists on one extreme and type II lunate wrists with the palmar triquetrum-hamate ligament, triquetrum-hamate-capitate ligament and palmar radius-lunate-triquetrum ligament attachments at the other extreme. Histological analyses confirmed pervious established work regarding the mechanical role of ligaments in wrist joint biomechanics. Also, there were no significant differences between the quantitative data obtained from the Genelyn-embalmed and unembalmed specimens (p>0.05). The current study demonstrated variable ligamentous patterns that suggest different bone restraints and two different patterns of motion. These findings support previous suggestions regarding separating the midcarpal joint into two distinct functional types. Type I wrists were identified with ligamentous attachments that are suggestive of rotating/translating hamate whilst type II wrists identified with ligamentous attachments that are suggestive of flexing/extending hamate motion based upon the patterns of the ligamentous attachments in relation to the morphological features of the underlying lunate type of the wrist. This opens the horizon for particular consideration and/or modification of surgical procedures, which may enhance the clinical management of wrist dysfunction.

Rapid detection and quantification of the marine toxic algae, Alexandrium minutum, using a super-paramagnetic immunochromatographic strip test

The dinoflagellates of Alexandrium genus are known to be producers of paralytic shellfish toxins that regularly impact the shellfish aquaculture industry and fisheries. Accurate detection of Alexandrium including A. minutum is crucial for environmental monitoring and sanitary issues. In this study, we firstly developed a quantitative lateral flow immunoassay (LFIA) using super-paramagnetic nanobeads for A. minutum whole cells. This dipstick assay relies on two distinct monoclonal antibodies used in a sandwich format and directed against surface antigens of this organism. No sample preparation is required. Either frozen or live cells can be detected and quantified. The specificity and sensitivity are assessed by using phytoplankton culture and field samples spiked with a known amount of cultured A. minutum cells. This LFIA is shown to be highly specific for A. minutum and able to detect reproducibly 105 cells/L within 30 min. The test is applied to environmental samples already characterized by light microscopy counting. No significant difference is observed between the cell densities obtained by these two methods. This handy super-paramagnetic lateral flow immnunoassay biosensor can greatly assist water quality monitoring programs as well as ecological research.

Quantification of the effects of architectural traits on dry mass production and light interception of tomato canopy under different temperature regimes using a dynamic functional-structural plant model

There is increasing interest in evaluating the environmental effects on crop architectural traits and yield improvement. However, crop models describing the dynamic changes in canopy structure with environmental conditions and the complex interactions between canopy structure, light interception, and dry mass production are only gradually emerging. Using tomato (Solanum lycopersicum L.) as a model crop, a dynamic functional-structural plant model (FSPM) was constructed, parameterized, and evaluated to analyse the effects of temperature on architectural traits, which strongly influence canopy light interception and shoot dry mass. The FSPM predicted the organ growth, organ size, and shoot dry mass over time with high accuracy (>85%). Analyses of this FSPM showed that, in comparison with the reference canopy, shoot dry mass may be affected by leaf angle by as much as 20%, leaf curvature by up to 7%, the leaf length: width ratio by up to 5%, internode length by up to 9%, and curvature ratios and leaf arrangement by up to 6%. Tomato canopies at low temperature had higher canopy density and were more clumped due to higher leaf area and shorter internodes. Interestingly, dry mass production and light interception of the clumped canopy were more sensitive to changes in architectural traits. The complex interactions between architectural traits, canopy light interception, dry mass production, and environmental conditions can be studied by the dynamic FSPM, which may serve as a tool for designing a canopy structure which is 'ideal' in a given environment.

Quantification of microbial communities in subsurface marine sediments of the Black Sea and off Namibia

Organic-rich subsurface marine sediments were taken by gravity coring up to a depth of 10 m below seafloor at six stations from the anoxic Black Sea and the Benguela upwelling system off Namibia during the research cruises Meteor 72-5 and 76-1, respectively. The quantitative microbial community composition at various sediment depths was analyzed using total cell counting, catalyzed reporter deposition fluorescence in situ hybridization (CARD FISH) and quantitative real-time PCR (Q-PCR). Total cell counts decreased with depths from 10(9) to 10(10) cells/mL at the sediment surface to 10(7)-10(9) cells/mL below one meter depth. Based on CARD FISH and Q-PCR analyses overall similar proportions of Bacteria and Archaea were found. The down-core distribution of prokaryotic and eukaryotic small subunit ribosomal RNA genes (16S and 18S rRNA) as well as functional genes involved in different biogeochemical processes was quantified using Q-PCR. Crenarchaeota and the bacterial candidate division JS-1 as well as the classes Anaerolineae and Caldilineae of the phylum Chloroflexi were highly abundant. Less abundant but detectable in most of the samples were Eukarya as well as the metal and sulfate-reducing Geobacteraceae (only in the Benguela upwelling influenced sediments). The functional genes cbbL, encoding for the large subunit of RuBisCO, the genes dsrA and aprA, indicative of sulfate-reducers as well as the mcrA gene of methanogens were detected in the Benguela upwelling and Black Sea sediments. Overall, the high organic carbon content of the sediments goes along with high cell counts and high gene copy numbers, as well as an equal abundance of Bacteria and Archaea.

Real-time PCR quantification and diversity analysis of the functional genes aprA and dsrA of sulfate-reducing prokaryotes in marine sediments of the Peru continental margin and the Black Sea

Sulfate-reducing prokaryotes (SRP) are ubiquitous and quantitatively important members in many ecosystems, especially in marine sediments. However their abundance and diversity in subsurface marine sediments is poorly understood. In this study, the abundance and diversity of the functional genes for the enzymes adenosine 5'-phosphosulfate reductase (aprA) and dissimilatory sulfite reductase (dsrA) of SRP in marine sediments of the Peru continental margin and the Black Sea were analyzed, including samples from the deep biosphere (ODP site 1227). For aprA quantification a Q-PCR assay was designed and evaluated. Depth profiles of the aprA and dsrA copy numbers were almost equal for all sites. Gene copy numbers decreased concomitantly with depth from around 10(8)/g sediment close to the sediment surface to less than 10(5)/g sediment at 5 mbsf. The 16S rRNA gene copy numbers of total bacteria were much higher than those of the functional genes at all sediment depths and used to calculate the proportion of SRP to the total Bacteria. The aprA and dsrA copy numbers comprised in average 0.5-1% of the 16S rRNA gene copy numbers of total bacteria in the sediments up to a depth of ca. 40 mbsf. In the zone without detectable sulfate in the pore water from about 40-121 mbsf (Peru margin ODP site 1227), only dsrA (but not aprA) was detected with copy numbers of less than 10(4)/g sediment, comprising ca. 14% of the 16S rRNA gene copy numbers of total bacteria. In this zone, sulfate might be provided for SRP by anaerobic sulfide oxidation. Clone libraries of aprA showed that all isolated sequences originate from SRP showing a close relationship to aprA of characterized species or form a new cluster with only distant relation to aprA of isolated SRP. For dsrA a high diversity was detected, even up to 121 m sediment depth in the deep biosphere.

Characterisation and quantification of changes in odorants from litter headspace of meat chickens fed diets varying in protein levels and additives

The effect of dietary crude protein (CP) and additives on odor flux from meat chicken litter was investigated using 180 day-old Ross 308 male chicks randomly allocated to five dietary treatments with three replicates of 12 birds each. A 5 × 3 factorial arrangement of treatments was employed. Factors were: diet (low CP, high CP, high CP+antibiotic, high CP+probiotic, high CP+saponin) and age (15, 29, 35 days). The antibiotic used was Zn bacitracin, the probiotic was a blend of three Bacillus subtilis strains and the saponin came from a blend of Yucca and Quillaja. Odorants were collected from litter headspace with a flux hood and measured using selective ion flow tube mass spectrometry (SIFT-MS). Litter moisture, water activity (Aw), and litter headspace odorant concentrations were correlated. The results showed that low CP group produced lower flux of dimethyl amine, trimethyl amine, H2S, NH3, and phenol in litter compared to high CP group (P < 0.05). Similarly, high CP+probiotic group produced lower flux of H2S (P < 0.05) and high CP+saponin group produced lower flux of trimethylamine and phenol in litter compared to high CP group (P < 0.05). The dietary treatments tended (P = 0.065) to have higher flux of methanethiol in high CP group compared to others. There was a diet × age interaction for litter flux of diacetyl, 3-hydroxy-2-butanone (acetoin), 3-methyl-1-butanol, 3-methylbutanal, ethanethiol, propionic acid, and hexane (P < 0.05). Concentrations of diacetyl, acetoin, propionic acid, and hexane in litter were higher from low CP group compared to all other treatments on d 35 (P < 0.05) but not on d 15 and 29. A high litter moisture increased water activity (P < 0.01) and favored the emissions of methyl mercaptan, hydrogen sulfide, dimethyl sulfide, ammonia, trimethyl amine, phenol, indole, and 3-methylindole over others. Thus, the low CP diet, Bacillus subtilis based probiotic and the blend of Yucca/Quillaja saponin were effective in reducing the emissions of some key odorants from meat chicken litter.

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

Biomarkers of Nitrosative Stress: Development and validation of a new analytical method for 3-Nitrotyrosine quantification

Background: The nitration of tyrosine residues in proteins is associated with nitrosative stress, resulting in the formation of 3-nitrotyrosine (3-NT). 3-NT levels in biological samples have been associated with numerous physiological and pathological conditions. For this reason, several attempts have been made in order to develop methods that accurately quantify 3-NT in biological samples. Regarding chromatographic methods, they seem to be very accurate, showing very good sensibility and specificity. However, accurate quantification of this molecule, which is present at very low concentrations both at physiological and pathological states, is always a complex task and a target of intense research. Objectives: We aimed to develop a simple, rapid, low-cost and sensitive 3-NT quantification method for use in medical laboratories as an additional tool for diagnosis and/or treatment monitoring of a wide range of pathologies. We also aimed to evaluate the performance of the HPLC-based method developed here in a wide range of biological matrices. Material and methods: All experiments were performed on a Hitachi LaChrom Elite® HPLC system and separation was carried out using a Lichrocart® 250-4 Lichrospher 100 RP-18 (5μm) column. The method was further validated according to ICH guidelines. The biological matrices tested were serum, whole blood, urine, B16 F-10 melanoma cell line, growth medium conditioned with the same cell line, bacterial and yeast suspensions. Results: From all the protocols tested, the best results were obtained using 0.5% CH3COOH:MeOH:H2O (15:15:70) as the mobile phase, with detection at wavelengths 215, 276 and 356 nm, at 25ºC, and using a flow rate of 1 mL/min. By using this protocol, it was possible to obtain a linear calibration curve (correlation coefficient = 1), limits of detection and quantification in the order of ng/mL, and a short analysis time (<15 minutes per sample). Additionally, the developed protocol allowed the successful detection and quantification of 3-NT in all biological matrices tested, with detection at 356 nm. Conclusion: The method described in this study, which was successfully developed and validated for 3-NT quantification, is simple, cheap and fast, rendering it suitable for analysis in a wide range of biological matrices.

Validation d’un procédé automatisé d’extraction sur phase solide de glandes digestives de moules pour l’identification et la quantification des dinophysistoxines en LC/ESI/SM2 par piégeage d’ions quadripolaire

This report presents a new extraction method of the dinophysistoxins (DTXs), confirmed by quantification using high-performance liquid chromatography coupled to mass spectrometry with an ion trap and electro spray interface (HPLC/ESI/MS2). The method originality consists on the adaptation of DTXs basic extraction procedure (liquid/ liquid) to a solid phase extraction (SPE) via a robotic station: ASPEC XLi The parameters of the automatization procedure were optimized to obtain the best DTXs recovery rate. These improvements were loaded with digestive gland mussel homogenat realized on a silica cartridge SPE, activated in hexane/chloroform (50:50), washed with hexane/chloroform (50:50) and extracted by an elution gradient (chloroform methanol (65:35) and methanol (100%)). This method was validated according to two normative referentials (linearity, detection quantification limits and accuracy…) : - The Guide of the Pharmacy industry: Analytical Validation, report of the commission SFSTP 1992 (French Corporation of the Sciences and Technical Pharmaceutical), - - The Procedure of validation of an alternative method in compare to a reference method. (AFNOR, 1998. NF V 03-110). Comparison with the classical liquid/liquid extraction and the automated method present clear advantages. In an analytical method the extraction is generally considered to be the most labor-intensive and error-prone step. This new procedure allowed us to increase throughput, to improve the reproducibility and to reduce the error risks due to the individual manual treatments.

Quantification of key biological processes determining the dynamics and the assessment of the anchovy population in the Bay of Biscay: growth, reproduction, demography and natural mortality.

333 p.

Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks

International audience

An in-house real-time polymerase chain reaction: standardisation and comparison with the Cobas Amplicor HBV monitor and Cobas AmpliPrep/Cobas TaqMan HBV tests for the quantification of hepatitis B virus DNA

This study aimed to standardise an in-house real-time polymerase chain reaction (rtPCR) to allow quantification of hepatitis B virus (HBV) DNA in serum or plasma samples, and to compare this method with two commercial assays, the Cobas Amplicor HBV monitor and the Cobas AmpliPrep/Cobas TaqMan HBV test. Samples from 397 patients from the state of São Paulo were analysed by all three methods. Fifty-two samples were from patients who were human immunodeficiency virus and hepatitis C virus positive, but HBV negative. Genotypes were characterised, and the viral load was measure in each sample. The in-house rtPCR showed an excellent success rate compared with commercial tests; inter-assay and intra-assay coefficients correlated with commercial tests (r = 0.96 and r = 0.913, p < 0.001) and the in-house test showed no genotype-dependent differences in detection and quantification rates. The in-house assay tested in this study could be used for screening and quantifying HBV DNA in order to monitor patients during therapy.