Comparison of Inoculation with the InoqulA and WASP Automated Systems with Manual Inoculation.

The quality of sample inoculation is critical for achieving an optimal yield of discrete colonies in both monomicrobial and polymicrobial samples to perform identification and antibiotic susceptibility testing. Consequently, we compared the performance between the InoqulA (BD Kiestra), the WASP (Copan), and manual inoculation methods. Defined mono- and polymicrobial samples of 4 bacterial species and cloudy urine specimens were inoculated on chromogenic agar by the InoqulA, the WASP, and manual methods. Images taken with ImagA (BD Kiestra) were analyzed with the VisionLab version 3.43 image analysis software to assess the quality of growth and to prevent subjective interpretation of the data. A 3- to 10-fold higher yield of discrete colonies was observed following automated inoculation with both the InoqulA and WASP systems than that with manual inoculation. The difference in performance between automated and manual inoculation was mainly observed at concentrations of >10(6) bacteria/ml. Inoculation with the InoqulA system allowed us to obtain significantly more discrete colonies than the WASP system at concentrations of >10(7) bacteria/ml. However, the level of difference observed was bacterial species dependent. Discrete colonies of bacteria present in 100- to 1,000-fold lower concentrations than the most concentrated populations in defined polymicrobial samples were not reproducibly recovered, even with the automated systems. The analysis of cloudy urine specimens showed that InoqulA inoculation provided a statistically significantly higher number of discrete colonies than that with WASP and manual inoculation. Consequently, the automated InoqulA inoculation greatly decreased the requirement for bacterial subculture and thus resulted in a significant reduction in the time to results, laboratory workload, and laboratory costs.

Single centre experience of the application of self navigated 3D whole heart cardiovascular magnetic resonance for the assessment of cardiac anatomy in congenital heart disease.

BACKGROUND: For free-breathing cardiovascular magnetic resonance (CMR), the self-navigation technique recently emerged, which is expected to deliver high-quality data with a high success rate. The purpose of this study was to test the hypothesis that self-navigated 3D-CMR enables the reliable assessment of cardiovascular anatomy in patients with congenital heart disease (CHD) and to define factors that affect image quality. METHODS: CHD patients ≥2 years-old and referred for CMR for initial assessment or for a follow-up study were included to undergo a free-breathing self-navigated 3D CMR at 1.5T. Performance criteria were: correct description of cardiac segmental anatomy, overall image quality, coronary artery visibility, and reproducibility of great vessels diameter measurements. Factors associated with insufficient image quality were identified using multivariate logistic regression. RESULTS: Self-navigated CMR was performed in 105 patients (55% male, 23 ± 12y). Correct segmental description was achieved in 93% and 96% for observer 1 and 2, respectively. Diagnostic quality was obtained in 90% of examinations, and it increased to 94% if contrast-enhanced. Left anterior descending, circumflex, and right coronary arteries were visualized in 93%, 87% and 98%, respectively. Younger age, higher heart rate, lower ejection fraction, and lack of contrast medium were independently associated with reduced image quality. However, a similar rate of diagnostic image quality was obtained in children and adults. CONCLUSION: In patients with CHD, self-navigated free-breathing CMR provides high-resolution 3D visualization of the heart and great vessels with excellent robustness.

Responding to Young People's Health Risks in Primary Care: A Cluster Randomised Trial of Training Clinicians in Screening and Motivational Interviewing.

OBJECTIVE: To evaluate the effectiveness of a complex intervention implementing best practice guidelines recommending clinicians screen and counsel young people across multiple psychosocial risk factors, on clinicians' detection of health risks and patients' risk taking behaviour, compared to a didactic seminar on young people's health. DESIGN: Pragmatic cluster randomised trial where volunteer general practices were stratified by postcode advantage or disadvantage score and billing type (private, free national health, community health centre), then randomised into either intervention or comparison arms using a computer generated random sequence. Three months post-intervention, patients were recruited from all practices post-consultation for a Computer Assisted Telephone Interview and followed up three and 12 months later. Researchers recruiting, consenting and interviewing patients and patients themselves were masked to allocation status; clinicians were not. SETTING: General practices in metropolitan and rural Victoria, Australia. PARTICIPANTS: General practices with at least one interested clinician (general practitioner or nurse) and their 14-24 year old patients. INTERVENTION: This complex intervention was designed using evidence based practice in learning and change in clinician behaviour and general practice systems, and included best practice approaches to motivating change in adolescent risk taking behaviours. The intervention involved training clinicians (nine hours) in health risk screening, use of a screening tool and motivational interviewing; training all practice staff (receptionists and clinicians) in engaging youth; provision of feedback to clinicians of patients' risk data; and two practice visits to support new screening and referral resources. Comparison clinicians received one didactic educational seminar (three hours) on engaging youth and health risk screening. OUTCOME MEASURES: Primary outcomes were patient report of (1) clinician detection of at least one of six health risk behaviours (tobacco, alcohol and illicit drug use, risks for sexually transmitted infection, STI, unplanned pregnancy, and road risks); and (2) change in one or more of the six health risk behaviours, at three months or at 12 months. Secondary outcomes were likelihood of future visits, trust in the clinician after exit interview, clinician detection of emotional distress and fear and abuse in relationships, and emotional distress at three and 12 months. Patient acceptability of the screening tool was also described for the intervention arm. Analyses were adjusted for practice location and billing type, patients' sex, age, and recruitment method, and past health risks, where appropriate. An intention to treat analysis approach was used, which included multilevel multiple imputation for missing outcome data. RESULTS: 42 practices were randomly allocated to intervention or comparison arms. Two intervention practices withdrew post allocation, prior to training, leaving 19 intervention (53 clinicians, 377 patients) and 21 comparison (79 clinicians, 524 patients) practices. 69% of patients in both intervention (260) and comparison (360) arms completed the 12 month follow-up. Intervention clinicians discussed more health risks per patient (59.7%) than comparison clinicians (52.7%) and thus were more likely to detect a higher proportion of young people with at least one of the six health risk behaviours (38.4% vs 26.7%, risk difference [RD] 11.6%, Confidence Interval [CI] 2.93% to 20.3%; adjusted odds ratio [OR] 1.7, CI 1.1 to 2.5). Patients reported less illicit drug use (RD -6.0, CI -11 to -1.2; OR 0·52, CI 0·28 to 0·96), and less risk for STI (RD -5.4, CI -11 to 0.2; OR 0·66, CI 0·46 to 0·96) at three months in the intervention relative to the comparison arm, and for unplanned pregnancy at 12 months (RD -4.4; CI -8.7 to -0.1; OR 0·40, CI 0·20 to 0·80). No differences were detected between arms on other health risks. There were no differences on secondary outcomes, apart from a greater detection of abuse (OR 13.8, CI 1.71 to 111). There were no reports of harmful events and intervention arm youth had high acceptance of the screening tool. CONCLUSIONS: A complex intervention, compared to a simple educational seminar for practices, improved detection of health risk behaviours in young people. Impact on health outcomes was inconclusive. Technology enabling more efficient, systematic health-risk screening may allow providers to target counselling toward higher risk individuals. Further trials require more power to confirm health benefits. TRIAL REGISTRATION: ISRCTN.com ISRCTN16059206.

High c-Met expression in stage I-II pancreatic adenocarcinoma: proposal for an immunostaining scoring method and correlation with poor prognosis.

AIMS: c-Met is an emerging biomarker in pancreatic ductal adenocarcinoma (PDAC); there is no consensus regarding the immunostaining scoring method for this marker. We aimed to assess the prognostic value of c-Met overexpression in resected PDAC, and to elaborate a robust and reproducible scoring method for c-Met immunostaining in this setting. METHODS AND RESULTS: c-Met immunostaining was graded according to the validated MetMab score, a classic visual scale combining surface and intensity (SI score), or a simplified score (high c-Met: ≥20% of tumour cells with strong membranous staining), in stage I-II PDAC. A computer-assisted classification method (Aperio software) was developed. Clinicopathological parameters were correlated with disease-free survival (DFS) and overall survival(OS). One hundred and forty-nine patients were analysed retrospectively in a two-step process. Thirty-seven samples (whole slides) were analysed as a pre-run test. Reproducibility values were optimal with the simplified score (kappa = 0.773); high c-Met expression (7/37) was associated with shorter DFS [hazard ratio (HR) 3.456, P = 0.0036] and OS (HR 4.257, P = 0.0004). c-Met expression was concordant on whole slides and tissue microarrays in 87.9% of samples, and quantifiable with a specific computer-assisted algorithm. In the whole cohort (n = 131), patients with c-Met(high) tumours (36/131) had significantly shorter DFS (9.3 versus 20.0 months, HR 2.165, P = 0.0005) and OS (18.2 versus 35.0 months, HR 1.832, P = 0.0098) in univariate and multivariate analysis. CONCLUSIONS: Simplified c-Met expression is an independent prognostic marker in stage I-II PDAC that may help to identify patients with a high risk of tumour relapse and poor survival.

MRI/TRUS fusion software-based targeted biopsy: the new standard of care?

The advent of multiparametric MRI has made it possible to change the way in which prostate biopsy is done, allowing to direct biopsies to suspicious lesions rather than randomly. The subject of this review relates to a computer-assisted strategy, the MRI/US fusion software-based targeted biopsy, and to its performance compared to the other sampling methods. Different devices with different methods to register MR images to live TRUS are currently in use to allow software-based targeted biopsy. Main clinical indications of MRI/US fusion software-based targeted biopsy are re-biopsy in men with persistent suspicious of prostate cancer after first negative standard biopsy and the follow-up of patients under active surveillance. Some studies have compared MRI/US fusion software-based targeted versus standard biopsy. In men at risk with MRI-suspicious lesion, targeted biopsy consistently detects more men with clinically significant disease as compared to standard biopsy; some studies have also shown decreased detection of insignificant disease. Only two studies directly compared MRI/US fusion software-based targeted biopsy with MRI/US fusion visual targeted biopsy, and the diagnostic ability seems to be in favor of the software approach. To date, no study comparing software-based targeted biopsy against in-bore MRI biopsy is available. The new software-based targeted approach seems to have the characteristics to be added in the standard pathway for achieving accurate risk stratification. Once reproducibility and cost-effectiveness will be verified, the actual issue will be to determine whether MRI/TRUS fusion software-based targeted biopsy represents anadd-on test or a replacement to standard TRUS biopsy.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

L'informatique: un outil remarquable pour l'enseignement de la médecine interne générale [The informatics: a remarkable tool for teaching general internal medicine].

INTERMED training implies a three week course, integrated in the "primary care module" for medical students in the first master year at the school of medicine in Lausanne. INTERMED uses an innovative teaching method based on repetitive sequences of e-learning-based individual learning followed by collaborative learning activities in teams, named Team-based learning (TBL). The e-learning takes place in a web-based virtual learning environment using a series of interactive multimedia virtual patients. By using INTERMED students go through a complete medical encounter applying clinical reasoning and choosing the diagnostic and therapeutic approach. INTERMED offers an authentic experience in an engaging and safe environment where errors are allowed and without consequences.

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Noves funcionalitats per desenvolupar el treball en grup a dins de l'ACME

La plataforma ACME (Avaluació Continuada i Millora de l’Ensenyament) va ser creada l’any 1998 per un grup de professors del departament d’Informàtica i Matemàtica Aplicada. L’ACME es va concebre com una plataforma d’e-learning, és a dir, un sistema que mitjançant l’ús d’Internet afavorís l’aprenentatge, permeten la interactivitat entre l’alumne i el professor. La creació de la plataforma ACME tenia com a objectiu reduir el fracàs dels alumnes en les assignatures de matemàtiques, però degut a l’èxit que va suposar en aquestes, es va decidir incorporar la metodologia de treball ACME a altres disciplines com la programació, les bases de dades, la química, l’economia, etc. de manera que actualment es poden desenvolupar activitats ACME en moltes disciplines. Actualment l’ACME s’utilitza com a complement a les classes presencials, on el professor exposa de manera magistral els conceptes i resol algun exercici a mode d’exemple, per a que després l’alumne, utilitzant la plataforma ACME, intenti resoldre els exercicis proposats pel professor.L’objectiu d’aquest projecte és desenvolupar l’anàlisi, disseny i implementació de les modificacions necessàries a incorporar a la plataforma ACME per tal de millorar el gestor de grups, els exercicis Excel i finalment permetre el treball en grup. El projecte consta de tres parts: millorar les interfícies del professor i de l’alumne, la millora del exercicis Excel i la resolució d’exercicis en grup

Módulo para gestionar el modelo de usuario y permisos, el sistema de archivos y el de noticias en la plataforma CoSpace

CoSpace és una plataforma web dissenyada per proporcionar un espai virtual d’interacció i col•laboració entre formadors en comunitats virtuals. Es va originar com a resultat de les necessitats addicionals que van sorgir quan els professors que treballen en temes educatius en context de diversitat (en àrees de llenguatge, matemàtiques i ciències) van necessitar una eina per afavorir o recolzar la interacció i la col•laboració entre ells per compartir idees, experiències, objectes virtuals d’aprenentatge, entre d’altres, des d’una perspectiva actual de l’ús de la tecnologia i des d’una visió més propera a l’usuari final. Aquest paradigma promou la idea que les aplicacions han de ser concebudes per a usuaris poc experts i tenint en compte els principis d’usabilitat i accessibilitat.L’abast del projecte està definit per la necessitat de gestió per part dels professors, de la informació del seu perfil personal, permetent als usuaris la creació, edició, consulta i eliminació d’aquesta informació. També la necessitat de compartir arxius, publicar notícies entre comunitats de pràctica i, finalment, de la necessitat de gestionar els permisos d’usuari per tal que gestionin mòduls de la plataforma

Integración de recursos digitales en las tareas de aprendizaje de lenguas: portafolios electrónicos y traducción asistida por ordenador

Las herramientas informáticas abren un amplio campo de posibilidades pedagógicas a las asignaturas de lengua. En el presente artículo se propone un modelo de combinación de recursos digitales (portafolios electrónicos y traducción asistida por ordenador) que refuerzan proyectos docentes del ámbito de las lenguas desde un enfoque pedagógico socioconstructivista. En algunos casos, las actividades se pueden integrar en proyectos reales. Por otra parte, los proyectos relacionados con el uso de estas herramientas pueden tener un enfoque multidisciplinar que implique tanto a los departamentos de las lenguas extranjeras y como a los de las lenguas maternas.

Modelagem Molecular: Uma Ferramenta para o Planejamento Racional de Fármacos em Química Medicinal

The molecular basis of modern therapeutics consist in the modulation of cell function by the interaction of microbioactive molecules as drug cells macromolecules structures. Molecular modeling is a computational technique developed to access the chemical structure. This methodology, by means of the molecular similarity and complementary paradigm, is the basis for the computer-assisted drug design universally employed in pharmaceutical research laboratories to obtain more efficient, more selective, and safer drugs. In this work, we discuss some methods for molecular modeling and some approaches to evaluate new bioactive structures in development by our research group.

CRM and higher education : developing a monitoring system to improve relationships in e-learning environments

Peer-reviewed

Broadening the CRM domain of application to higher educational (e-learning) environments

In this paper, we reflect about the broadening of the field of application of CRM from the business domain to a wider context of relationships in which the inclusion of non-profit making organizations seems natural. In particular, we focus on analyzing the suitability of adopting CRM processes by universities and higher educational institutions dedicated to e-learning. This is an issue that, in our opinion, has much potential but has received little attention in research so far.

Exploring new criteria to design materials for online education

Peer-reviewed