Community-acquired pneumonia in adult patients with special reference to rapid methods for etiological diagnosis

Aikuispotilaan kotisyntyisen keuhkokuumeen etiologinen diagnostiikka mikrobiologisilla pikamenetelmillä Tausta. Keuhkokuume on vakava sairaus, johon sairastuu Suomessa vuosittain n. 60 000 aikuista. Huolimatta siitä, että taudin hoito on kehittynyt, siihen liittyy yhä merkittävä, 6-15%:n kuolleisuus. Alahengitystieinfektion aiheuttajamikrobien tunnistaminen on myös edelleen haasteellista. Tavoitteet. Tämän työn tavoitteena oli tutkia Turun yliopistollisessa keskussairaalassa hoidettujen aikuispotilaiden keuhkokuumeen etiologiaa sekä selvittää uusien mikrobiologisten pikamenetelmi¬en hyödyllisyyttä taudinaiheuttajan toteamisessa. Aineisto. Osatöiden I ja III aineisto koostui 384 Turun yliopistollisen keskussairaalaan infektio-osastolla hoidetusta keuhkokuumepotilaasta. Osatyössä I tutkittiin keuhkokuumeen aiheuttaja¬mikrobeja käyttämällä perinteisten menetelmien lisäksi antigeeniosoitukseen ja PCR-tekniikkaan perustuvia pikamenetelmiä. Osatyö II käsitti 231 potilaasta koostuvan alaryhmän, jossa tutkittiin potilaiden nielun limanäytteestä rinovirusten ja enterovirusten esiintyvyyttä. Osatyössä III potilailta tutkittiin plasman C-reaktiivisen proteiinin (CRP) pitoisuus ensimmäisten viiden sairaalahoitopäi¬vän aikana. Laajoja tilastotieteellisiä analyysejä käyttämällä selvitettiin CRP:n käyttökelpoisuutta sairauden vaikeusasteen arvioinnissa ja komplikaatioiden kehittymisen ennustamisessa. Osatyössä IV 68 keuhkokuumepotilaan sairaalaan tulovaiheessa otetuista näytteistä määritettiin neutrofiilien pintareseptorien ekspressio. Osatyössä V analysoitiin sisätautien vuodeosastoilla vuosina 1996-2000 keuhkokuumepotilaille tehtyjen keuhkohuuhtelunäytteiden laboratoriotutkimustulokset. Tulokset. Keuhkokuumeen aiheuttaja löytyi 209 potilaalta, aiheuttajamikrobeja löydettiin kaikkiaan 230. Näistä aiheuttajista 135 (58.7%) löydettiin antigeenin osoituksella tai PCR-menetelmillä. Suu¬rin osa, 95 (70.4%), todettiin pelkästään kyseisillä pikamenetelmillä. Respiratorinen virus todettiin antigeeniosoituksella 11.1% keuhkokuumepotilaalla. Eniten respiratorisia viruksia löytyi vakavaa keuhkokuumetta sairastavilta potilailta (20.3%). 231 keuhkokuumepotilaan alaryhmässä todettiin PCR-menetelmällä picornavirus 19 (8.2%) potilaalla. Respiratorinen virus löytyi tässä potilasryh¬mässä kaiken kaikkiaan 47 (20%) potilaalta. Näistä 17:llä (36%) löytyi samanaikaisesti bakteerin aiheuttama infektio. CRP-tasot olivat sairaalaan tulovaiheessa merkitsevästi korkeammat vakavaa keuhkokuumetta (PSI-luokat III-V) sairastavilla potilailla kuin lievää keuhkokuumetta (PSI-luokat I-II) sairastavilla potilailla (p <0.001). Yli 100 mg/l oleva CRP-taso neljän päivän kuluttua sairaa¬laan tulosta ennusti keuhkokuumeen komplikaatiota tai huonoa hoitovastetta. Neutrofiilien komple¬menttireseptorin ekspressio oli pneumokokin aiheuttamaa keuhkokuumetta sairastavilla merkitse¬västi korkeampi kuin influenssan aiheuttamaa keuhkokuumetta sairastavilla. BAL-näytteistä vain yhdessä 71:stä (1.3%) todettiin diagnostinen bakteerikasvu kvantitatiivisessa viljelyssä. Uusilla menetelmilläkin keuhkokuumeen aiheuttaja löytyi vain 9.8% BAL-näytteistä. Päätelmät. Uusilla antigeeniosoitus- ja PCR-menetelmillä keuhkokuumeen etiologia voidaan saada selvitettyä nopeasti. Lisäksi näitä menetelmiä käyttämällä taudin aiheuttajamikrobi löytyi huomattavasti suuremmalta osalta potilaista kuin pelkästään tavanomaisia menetelmiä käyttämällä. Pikamenetelmien hyödyllisyys vaihteli taudin vaikeusasteen mukaan. Respiratorinen virus löytyi huomattavan usein keuhkokuumetta sairastavilta potilailta, ja näiden potilaiden taudinkuva oli usein vaikea. Tulovaiheen korkeaa CRP-tasoa voidaan käyttää lisäkeinona arvioitaessa keuhkokuumeen vaikeutta. CRP on erityisen hyödyllinen arvioitaessa hoitovastetta ja riskiä komplikaatioiden ke¬hittymiseen. Neutrofiilien komplementtireseptorin ekspression tutkiminen näyttää lupaavalta pi¬kamenetelmältä erottamaan bakteerien ja virusten aiheuttamat taudit toisistaan. Antimikrobihoitoa saavilla potilailla BAL-tutkimuksen löydökset olivat vähäiset ja vaikuttivat hoitoon vain harvoin.

Detection of caliciviruses associated with acute infantile gastroenteritis in Salvador, an urban center in Northeast Brazil

Acute gastroenteritis caused by viruses is one of the leading causes of infantile morbidity. The aim of the present study was to investigate the presence of human caliciviruses of the genera norovirus and sapovirus in children up to 3 years of age with acute gastroenteritis from low-income communities in the city of Salvador, Brazil. This study is an extension of previous work carried out to establish the profile of the most prevalent enteric pathogens present in these communities. In this report, 139 fecal samples, collected from July 2001 to January 2002 were analyzed by RT-PCR and 13 (9%) were positive for human caliciviruses. By sequencing, seven isolates were characterized as norovirus genogroup GII and one as sapovirus genotype GII/1. Sequencing of the previously detected group-A rotaviruses and human astroviruses was also performed and revealed the circulation of rotavirus group A genotypes G1P[8] and G9P[8], and human astrovirus genotypes 6, 7, and 8. No mixed infection was observed. Community-based studies provide geographically representative information on disease burden. However, there are only a few reports in developing countries concerning the genotypes of the most important gastroenteric viruses detected in such communities. The present findings demonstrate the wide diversity of genotypes of the most important viruses responsible for acute gastroenteritis circulating in low-income communities.

BotCloud Detection System

Leveraging cloud services, companies and organizations can significantly improve their efficiency, as well as building novel business opportunities. Cloud computing offers various advantages to companies while having some risks for them too. Advantages offered by service providers are mostly about efficiency and reliability while risks of cloud computing are mostly about security problems. Problems with security of the cloud still demand significant attention in order to tackle the potential problems. Security problems in the cloud as security problems in any area of computing, can not be fully tackled. However creating novel and new solutions can be used by service providers to mitigate the potential threats to a large extent. Looking at the security problem from a very high perspective, there are two focus directions. Security problems that threaten service user’s security and privacy are at one side. On the other hand, security problems that threaten service provider’s security and privacy are on the other side. Both kinds of threats should mostly be detected and mitigated by service providers. Looking a bit closer to the problem, mitigating security problems that target providers can protect both service provider and the user. However, the focus of research community mostly is to provide solutions to protect cloud users. A significant research effort has been put in protecting cloud tenants against external attacks. However, attacks that are originated from elastic, on-demand and legitimate cloud resources should still be considered seriously. The cloud-based botnet or botcloud is one of the prevalent cases of cloud resource misuses. Unfortunately, some of the cloud’s essential characteristics enable criminals to form reliable and low cost botclouds in a short time. In this paper, we present a system that helps to detect distributed infected Virtual Machines (VMs) acting as elements of botclouds. Based on a set of botnet related system level symptoms, our system groups VMs. Grouping VMs helps to separate infected VMs from others and narrows down the target group under inspection. Our system takes advantages of Virtual Machine Introspection (VMI) and data mining techniques.

Advances in therapeutic risk management through signal detection and risk minimisation tool analyses

Les quatre principales activités de la gestion de risque thérapeutique comportent l’identification, l’évaluation, la minimisation, et la communication du risque. Ce mémoire aborde les problématiques liées à l’identification et à la minimisation du risque par la réalisation de deux études dont les objectifs sont de: 1) Développer et valider un outil de « data mining » pour la détection des signaux à partir des banques de données de soins de santé du Québec; 2) Effectuer une revue systématique afin de caractériser les interventions de minimisation de risque (IMR) ayant été implantées. L’outil de détection de signaux repose sur la méthode analytique du quotient séquentiel de probabilité (MaxSPRT) en utilisant des données de médicaments délivrés et de soins médicaux recueillis dans une cohorte rétrospective de 87 389 personnes âgées vivant à domicile et membres du régime d’assurance maladie du Québec entre les années 2000 et 2009. Quatre associations « médicament-événement indésirable (EI) » connues et deux contrôles « négatifs » ont été utilisés. La revue systématique a été faite à partir d’une revue de la littérature ainsi que des sites web de six principales agences réglementaires. La nature des RMIs ont été décrites et des lacunes de leur implémentation ont été soulevées. La méthode analytique a mené à la détection de signaux dans l'une des quatre combinaisons médicament-EI. Les principales contributions sont: a) Le premier outil de détection de signaux à partir des banques de données administratives canadiennes; b) Contributions méthodologiques par la prise en compte de l'effet de déplétion des sujets à risque et le contrôle pour l'état de santé du patient. La revue a identifié 119 IMRs dans la littérature et 1,112 IMRs dans les sites web des agences réglementaires. La revue a démontré qu’il existe une augmentation des IMRs depuis l’introduction des guides réglementaires en 2005 mais leur efficacité demeure peu démontrée.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

Polimorfismos del gen Butirilcolinesterasa responsables de reacciones adversas en pacientes consumidores de “cocaína”

La butirilcolinesterasa humana (BChE; EC 3.1.1.8) es una enzima polimórfica sintetizada en el hígado y en el tejido adiposo, ampliamente distribuida en el organismo y encargada de hidrolizar algunos ésteres de colina como la procaína, ésteres alifáticos como el ácido acetilsalicílico, fármacos como la metilprednisolona, el mivacurium y la succinilcolina y drogas de uso y/o abuso como la heroína y la cocaína. Es codificada por el gen BCHE (OMIM 177400), habiéndose identificado más de 100 variantes, algunas no estudiadas plenamente, además de la forma más frecuente, llamada usual o silvestre. Diferentes polimorfismos del gen BCHE se han relacionado con la síntesis de enzimas con niveles variados de actividad catalítica. Las bases moleculares de algunas de esas variantes genéticas han sido reportadas, entre las que se encuentra las variantes Atípica (A), fluoruro-resistente del tipo 1 y 2 (F-1 y F-2), silente (S), Kalow (K), James (J) y Hammersmith (H). En este estudio, en un grupo de pacientes se aplicó el instrumento validado Lifetime Severity Index for Cocaine Use Disorder (LSI-C) para evaluar la gravedad del consumo de “cocaína” a lo largo de la vida. Además, se determinaron Polimorfismos de Nucleótido Simple (SNPs) en el gen BCHE conocidos como responsables de reacciones adversas en pacientes consumidores de “cocaína” mediante secuenciación del gen y se predijo el efecto delos SNPs sobre la función y la estructura de la proteína, mediante el uso de herramientas bio-informáticas. El instrumento LSI-C ofreció resultados en cuatro dimensiones: consumo a lo largo de la vida, consumo reciente, dependencia psicológica e intento de abandono del consumo. Los estudios de análisis molecular permitieron observar dos SNPs codificantes (cSNPs) no sinónimos en el 27.3% de la muestra, c.293A>G (p.Asp98Gly) y c.1699G>A (p.Ala567Thr), localizados en los exones 2 y 4, que corresponden, desde el punto de vista funcional, a la variante Atípica (A) [dbSNP: rs1799807] y a la variante Kalow (K) [dbSNP: rs1803274] de la enzima BChE, respectivamente. Los estudios de predicción In silico establecieron para el SNP p.Asp98Gly un carácter patogénico, mientras que para el SNP p.Ala567Thr, mostraron un comportamiento neutro. El análisis de los resultados permite proponer la existencia de una relación entre polimorfismos o variantes genéticas responsables de una baja actividad catalítica y/o baja concentración plasmática de la enzima BChE y algunas de las reacciones adversas ocurridas en pacientes consumidores de cocaína.

Detecting local adaptation in widespread grassland species - the importance of scale and local plant community

1 Adaptation of plant populations to local environments has been shown in many species but local adaptation is not always apparent and spatial scales of differentiation are not well known. In a reciprocal transplant experiment we tested whether: (i) three widespread grassland species are locally adapted at a European scale; (ii) detection of local adaptation depends on competition with the local plant community; and (iii) local differentiation between neighbouring populations from contrasting habitats can be stronger than differentiation at a European scale. 2 Seeds of Holcus lanatus, Lotus corniculatus and Plantago lanceolata from a Swiss, Czech and UK population were sown in a reciprocal transplant experiment at fields that exhibit environmental conditions similar to the source sites. Seedling emergence, survival, growth and reproduction were recorded for two consecutive years. 3 The effect of competition was tested by comparing individuals in weeded monocultures with plants sown together with species from the local grassland community. To compare large-scale vs. small-scale differentiation, a neighbouring population from a contrasting habitat (wet-dry contrast) was compared with the 'home' and 'foreign' populations. 4 In P. lanceolata and H. lanatus, a significant home-site advantage was detected in fitness-related traits, thus indicating local adaptation. In L. corniculatus, an overall superiority of one provenance was found. 5 The detection of local adaptation depended on competition with the local plant community. In the absence of competition the home-site advantage was underestimated in P. lanceolata and overestimated in H. lanatus. 6 A significant population differentiation between contrasting local habitats was found. In some traits, this small-scale was greater than large-scale differentiation between countries. 7 Our results indicate that local adaptation in real plant communities cannot necessarily be predicted from plants grown in weeded monocultures and that tests on the relationship between fitness and geographical distance have to account for habitat-dependent small-scale differentiation. Considering the strong small-scale differentiation, a local provenance from a different habitat may not be the best choice in ecological restoration if distant populations from a more similar habitat are available.

Proof of concept of automated mapping of weeds in arable fields

The project investigated whether it would be possible to remove the main technical hindrance to precision application of herbicides to arable crops in the UK, namely creating geo-referenced weed maps for each field. The ultimate goal is an information system so that agronomists and farmers can plan precision weed control and create spraying maps. The project focussed on black-grass in wheat, but research was also carried out on barley and beans and on wild-oats, barren brome, rye-grass, cleavers and thistles which form stable patches in arable fields. Farmers may also make special efforts to control them. Using cameras mounted on farm machinery, the project explored the feasibility of automating the process of mapping black-grass in fields. Geo-referenced images were captured from June to December 2009, using sprayers, a tractor, combine harvesters and on foot. Cameras were mounted on the sprayer boom, on windows or on top of tractor and combine cabs and images were captured with a range of vibration levels and at speeds up to 20 km h-1. For acceptability to farmers, it was important that every image containing black-grass was classified as containing black-grass; false negatives are highly undesirable. The software algorithms recorded no false negatives in sample images analysed to date, although some black-grass heads were unclassified and there were also false positives. The density of black-grass heads per unit area estimated by machine vision increased as a linear function of the actual density with a mean detection rate of 47% of black-grass heads in sample images at T3 within a density range of 13 to 1230 heads m-2. A final part of the project was to create geo-referenced weed maps using software written in previous HGCA-funded projects and two examples show that geo-location by machine vision compares well with manually-mapped weed patches. The consortium therefore demonstrated for the first time the feasibility of using a GPS-linked computer-controlled camera system mounted on farm machinery (tractor, sprayer or combine) to geo-reference black-grass in winter wheat between black-grass head emergence and seed shedding.

Detection and identification of species-specific bacteria associated with synanthropic mites

Internal bacterial communities of synanthropic mites Acarus siro, Dermatophagoides farinae, Lepidoglyphus destructor, and Tyrophagus putrescentiae (Acari: Astigmata) were analyzed by culturing and culture-independent approaches from specimens obtained from laboratory colonies. Homogenates of surface-sterilized mites were used for cultivation on non-selective agar and DNA extraction. Isolated bacteria were identified by sequencing of the 16S rRNA gene. PCR amplified 16S rRNA genes were analyzed by terminal restriction fragment length polymorphism analysis (T-RFLP) and cloning sequencing. Fluorescence in situ hybridization using universal bacterial probes was used for direct bacterial localization. T-RFLP analysis of 16S rRNA gene revealed distinct species-specific bacterial communities. The results were further confirmed by cloning and sequencing (284 clones). L. destructor and D. farinae showed more diverse communities then A. siro and T. putrescentiae. In the cultivated part of the community, the mean CFUs from four mite species ranged from 5.2 × 102 to 1.4 × 103 per mite. D. farinae had significantly higher CFUs than the other species. Bacteria were located in the digestive and reproductive tract, parenchymatical tissue, and in bacteriocytes. Among the clones, Bartonella-like bacteria occurring in A. siro and T. putresecentiae represented a distinct group related to Bartonellaceae and to Bartonella-like symbionts of ants. The clones of high similarity to Xenorhabdus cabanillasii were found in L. destructor and D. farinae, and one clone related to Photorhabdus temperata in A. siro. Members of Sphingobacteriales cloned from D. farinae and A. siro clustered with the sequences of “Candidatus Cardinium hertigii” and as a separate novel cluster.

A change detection approach to flood mapping in urban areas using TerraSAR-X

Very high-resolution Synthetic Aperture Radar sensors represent an alternative to aerial photography for delineating floods in built-up environments where flood risk is highest. However, even with currently available SAR image resolutions of 3 m and higher, signal returns from man-made structures hamper the accurate mapping of flooded areas. Enhanced image processing algorithms and a better exploitation of image archives are required to facilitate the use of microwave remote sensing data for monitoring flood dynamics in urban areas. In this study a hybrid methodology combining radiometric thresholding, region growing and change detection is introduced as an approach enabling the automated, objective and reliable flood extent extraction from very high-resolution urban SAR images. The method is based on the calibration of a statistical distribution of “open water” backscatter values inferred from SAR images of floods. SAR images acquired during dry conditions enable the identification of areas i) that are not “visible” to the sensor (i.e. regions affected by ‘layover’ and ‘shadow’) and ii) that systematically behave as specular reflectors (e.g. smooth tarmac, permanent water bodies). Change detection with respect to a pre- or post flood reference image thereby reduces over-detection of inundated areas. A case study of the July 2007 Severn River flood (UK) observed by the very high-resolution SAR sensor on board TerraSAR-X as well as airborne photography highlights advantages and limitations of the proposed method. We conclude that even though the fully automated SAR-based flood mapping technique overcomes some limitations of previous methods, further technological and methodological improvements are necessary for SAR-based flood detection in urban areas to match the flood mapping capability of high quality aerial photography.

ATD: a multiplatform for semiautomatic 3-D detection of kidneys and their pathology in real time

This research presents a novel multi-functional system for medical Imaging-enabled Assistive Diagnosis (IAD). Although the IAD demonstrator has focused on abdominal images and supports the clinical diagnosis of kidneys using CT/MRI imaging, it can be adapted to work on image delineation, annotation and 3D real-size volumetric modelling of other organ structures such as the brain, spine, etc. The IAD provides advanced real-time 3D visualisation and measurements with fully automated functionalities as developed in two stages. In the first stage, via the clinically driven user interface, specialist clinicians use CT/MRI imaging datasets to accurately delineate and annotate the kidneys and their possible abnormalities, thus creating “3D Golden Standard Models”. Based on these models, in the second stage, clinical support staff i.e. medical technicians interactively define model-based rules and parameters for the integrated “Automatic Recognition Framework” to achieve results which are closest to that of the clinicians. These specific rules and parameters are stored in “Templates” and can later be used by any clinician to automatically identify organ structures i.e. kidneys and their possible abnormalities. The system also supports the transmission of these “Templates” to another expert for a second opinion. A 3D model of the body, the organs and their possible pathology with real metrics is also integrated. The automatic functionality was tested on eleven MRI datasets (comprising of 286 images) and the 3D models were validated by comparing them with the metrics from the corresponding “3D Golden Standard Models”. The system provides metrics for the evaluation of the results, in terms of Accuracy, Precision, Sensitivity, Specificity and Dice Similarity Coefficient (DSC) so as to enable benchmarking of its performance. The first IAD prototype has produced promising results as its performance accuracy based on the most widely deployed evaluation metric, DSC, yields 97% for the recognition of kidneys and 96% for their abnormalities; whilst across all the above evaluation metrics its performance ranges between 96% and 100%. Further development of the IAD system is in progress to extend and evaluate its clinical diagnostic support capability through development and integration of additional algorithms to offer fully computer-aided identification of other organs and their abnormalities based on CT/MRI/Ultra-sound Imaging.

DGGE with genomic DNA: Suitable for detection of numerically important organisms but not for identification of the most abundant organisms

Identification of all important community members as well as of the numerically dominant members of a community are key aspects of microbial community analysis of bioreactor samples. A systematic study was conducted with artificial consortia to test whether denaturing gradient gel electrophoresis (DGCE) is a reliable technique to obtain such community data under conditions where results would not be affected by differences in DNA extraction efficiency from cells. A total of 27 consortia were established by mixing DNA extracted from Escherichia coli K12, Burkholderia cepacia and Stenotrophomonas maltophilia in different proportions. Concentrations of DNA of single organisms in the consortia were either 0.04, 0.4 or 4 ng/mu l. DGGE-PCR of genomic DNA with primer sets targeted at the V3 and V6-V8 regions of the 16S rDNA failed to detect the three community members in only 7% of consortia, but provided incorrect information about dominance or co-dominance for 85% and 89% of consortia with the primer sets for the V6-V8 and V3 regions, respectively. The high failure rate in detection of dominant B. cepacia with the primers for the V6-V8 region was attributable to a single nucleoticle primer mismatch in the target sequences of both, the forward and reverse primer. Amplification bias in PCR of E. coli and S. maltophilia for the V6-V8 region and for all three organisms for the V3 region occurred due to interference of genomic DNA in PCR-DGGE, since a nested PCR approach, where PCR-DGGE was started from mixtures of 16S rRNA genes of the organisms, provided correct information about the relative abundance of original DNA in the sample. Multiple bands were not observed in pure culture amplicons produced with the V6-V8 primer pair, but pure culture V3 DGGE profiles of E. coli, S. maltophilia and B. cepacia contained 5, 3 and 3 bands, respectively. These results demonstrate DGGE was suitable for identification of all important community members in the three-membered artificial consortium, but not for identification of the dominant organisms in this small community. Multiple DGGE bands obtained for single organisms with the V3 primer pair could greatly confound interpretation of DGGE profiles. (C) 2008 Elsevier Ltd. All rights reserved.

Population dynamics of genetically diverse Plasmodium falciparum lineages: community-based prospective study in rural Amazonia

Temporal changes in the prevalence of antigenic variants in Plasmodium falciparum populations have been interpreted as evidence of immune-mediated frequency-dependent selection, but evolutively neutral processes may generate similar patterns of serotype replacement. Over 4 years, we investigated the population dynamics of P. falciparum polymorphisms the community level by using 11 putatively neutral microsatellite markers. Plasmodium falciparum Populations were less diverse than sympatric P. vivax isolates, with less multiple-clone infections, lower number of alleles per locus and lower Virtual heterozygosity, but both species showed significant multilocus linkage disequilibrium. Evolutively neutral P. falciparum polymorphisms showed a high turnover rate, with few lineages persisting for several months in the population. Similar results had previously been obtained, in the same community, for sympatric P. vivax isolates. In contrast, the prevalence of the 2 dimorphic types of a major antigen, MSP-2, remained remarkably stable throughout the Study period. We Suggest that the relatively fast turnover of parasite lineages represents the typical population dynamics of neutral polymorphisms in small populations, with clear implications for the detection of frequency-dependent selection of polymorphisms.

Square wave adsorptive cathodic stripping voltarnmetry automated by sequential injection analysis - Potentialities and limitations exemplified by the determination of methyl parathion in water samples

This paper describes the development and evaluation of a sequential injection method to automate the determination of methyl parathion by square wave adsorptive cathodic stripping voltammetry exploiting the concept of monosegmented flow analysis to perform in-line sample conditioning and standard addition. Accumulation and stripping steps are made in the sample medium conditioned with 40 mmol L-1 Britton-Robinson buffer (pH 10) in 0.25 mol L-1 NaNO3. The homogenized mixture is injected at a flow rate of 10 mu Ls(-1) toward the flow cell, which is adapted to the capillary of a hanging drop mercury electrode. After a suitable deposition time, the flow is stopped and the potential is scanned from -0.3 to -1.0 V versus Ag/AgCl at frequency of 250 Hz and pulse height of 25 mV The linear dynamic range is observed for methyl parathion concentrations between 0.010 and 0.50 mgL(-1), with detection and quantification limits of 2 and 7 mu gL(-1), respectively. The sampling throughput is 25 h(-1) if the in line standard addition and sample conditioning protocols are followed, but this frequency can be increased up to 61 h(-1) if the sample is conditioned off-line and quantified using an external calibration curve. The method was applied for determination of methyl parathion in spiked water samples and the accuracy was evaluated either by comparison to high performance liquid chromatography with UV detection, or by the recovery percentages. Although no evidences of statistically significant differences were observed between the expected and obtained concentrations, because of the susceptibility of the method to interference by other pesticides (e.g., parathion, dichlorvos) and natural organic matter (e.g., fulvic and humic acids), isolation of the analyte may be required when more complex sample matrices are encountered. (C) 2007 Elsevier B.V. All rights reserved.