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Introducción. La hepatitis A es una enfermedad infectocontagiosa causada por un virus ARN no encapsulado de la familia Picornaviridae y del género Hepatovirus, que se trasmite por vía fecal-oral, bien sea de persona a persona o en epidemias originadas por una fuente común. Objetivo. Se estimo la seroprevalencia de anticuerpos de tipo IgG contra el virus de la hepatitis A en niños de 1 a 15 años, atendidos en un hospital universitario, como parte de un estudio cooperativo nacional. Métodos. Se realizó un estudio descriptivo y prospectivo, entre junio y noviembre de 2007. Los niveles de anticuerpos se detectaron mediante un inmunoensayo enzimático de micropartículas. A cada participante del estudio se le hizo una encuesta de riesgo con las variables objeto del estudio. Resultados. Se estudiaron 422 niños. La prevalencia global de anticuerpos contra el virus de la hepatitis A fue de 29,1%: 37,1% en el grupo de 5 a 9 años, 36,1%, en el de 10 a 15 y 13,8%, en el de 1 a 4 años. La mayor proporción de prevalencia de anticuerpos se encontró en los niños de estrato socioeconómico más bajo: 44,2% para el estrato 1 y 27,9% para el estrato 2. Discusión. En este estudio se encontró una seroprevalencia de anticuerpos para hepatitis A más baja en menores de 5 años, lo que puede indicar una transición del patrón epidemiológico hacia un nivel intermedio. La prevalencia fue mayor en los niños de estratos socioeconómicos bajos, lo que puede estar en relación con el hacinamiento y las malas prácticas de higiene.Introduction: Hepatitis A is an infectious disease caused by a non-encapsulated RNA virus of the Picornaviridae family, classified as Hepatovirus. It is transmitted by a fecal-oral route, either from person to person or in common source epidemics. Objective: The aim of this study was to estimate the seroprevalence of IgG antibodies against the hepatitis A virus in children aged 1-15 years, treated in a university hospital as part of a national collaborative study. Methods: A descriptive study was performed between June and November 2007. The antibody titers were detected by means of a Microparticle Capture Enzyme Immunoassay. A survey to identify risk factors was conducted for each participant, with additional variables under study. Results: We studied 422 children. The overall prevalence of antibodies against hepatitis A was 29.1%, with 37.1% in the group of 5 to 9 years of age, 36.1% for 10 to 15, and 13.8% for 1 to 4. The highest proportion of antibody prevalence was found in children of the lowest socioeconomic status, 44.2% for the stratum 1 and 27.9% for the stratum 2. Conclusion: The seroprevalence to hepatitis A virus was lower in children with less than five years of age, which is an indication of a transition of the epidemiological profile to an intermediate one. The prevalence was higher in children of low socioeconomic levels, which may be related to overcrowding and poor hygiene practices

La región objeto de este estudio se localiza al extremo sur central del Macizo de Santander, cordillera Oriental de Colombia. En una secuencia de sedimentitas del Cretáceo inferior y en posición concordante con la dirección de los estratos, se encuentra un horizonte de 2,4 m de espesor que contiene minerales de Pb y Zn; galena y esfalerita principalmente. Los sulfuros se presentan en forma de lentes, venas y diseminación en capas de arenitas, lodolitas y caliza dolomitizada. El material de ganga está representado por calcita, cuarzo, dolomita y pirita. En un área de 2,5 km de longitud y 500 m de ancho, se delimita una franja orientada en dirección NNW-SSE, en la cual se reconocen tres zonas con valores anómalos, principalmente en Pb, Zn, V y Mn, además de valores relativamente altos en Fe y F. La mineralización de Montenegro y las zonas con anomalías geoquímicas y geofísicas, se localizan en 300 m de la secuencia cretácea. Algunos de los rasgos geológicos reconocidos en el área de Montenegro, corresponden con los descritos en depósitos de metales base tipo Mississippi Valley.

An 18 years old male with acute myelocytic leukemia who developed leukemic meningitis with loss of vision and severe papiledema is reported. Postmortem examination showed marked leukemic infiltration of the optic nerves and optic chiasm. CNS involvement in leukemia is ana1ized and the literature is reviewed.

Twenty patients with cranial nerves tumors are seen and studied at the San Juan de Dios Hospital National University in Bogota during a period from January 1954 to December 1972. In the same time 612 primary CNS tumors and 103 metastasic were studied in this Center. Amonq the twenty cases, eighteen diagnosis of acoustic neurinoma were made; one case was a right trigeminal neurofibroma and the last one is a 22 year-old man suffering generalized neurofibromatosis including both vagus nerves. The clinical and paraclinical findings are analized making special emphasis in the CSF protein level and neuro-radiologic findings. The histopatholoqic changes are described briefly. A review of the literature is done.

A case of metastasis to the brain from a chondrosarcoma of the right tibia in a 48 y. o. male is presented. We found only one similar case in the literature, reported by Talerman in 1970.

La lepra tiene para su propagación, dos posibles medios hasta hoy conocidos: el contagio y la herencia. Nos proponemos hablar solamente de ésta, y, de los diferentes modos de reproducción, referirnos solamente al de la Karioquinesis. A primera vista puede aparecer erróneo, y hasta anacrónico, el uso del término herencia tratándose de ésta enfermedad, que tiene el carácter de microbiana, pero es necesario recordar también su carácter de cronocidad, y tener presente lo que sucede en la sífilis y en la tuberculosis a éste respecto.

El Distrito Minero de California está situado unos 50 km al noreste de Bucaramanga, en el Municipio de California, Departamento de Santander; es conocido y explotado para oro y plata desde la época de la Colonia. El área está constituida por rocas Pre-Devónicas de alto grado de metamorfismo, las cuales muestran carácter migmatítico. Esta secuencia es afectada por rocas intrusivas de edad Jura-Triásica, cuya composición varía de cuarzodiorita a cuarzomonzonita y granito. Facies porfiríticas más jóvenes son emplazadas dentro de las rocas preexistentes como diques y pequeños stocks. Un silo de pórfido dacítico se presenta dentro de sedimentos del Cretáceo Inferior. Los filones de cuarzo mineralizados, usualmente de color gris y con textura brechoide, se localizan en rocas ígneas y metamórficas. La intensidad de la alteración hidrotermal observada en estas rocas, aparentemente no depende de la composición sino principalmente del grado de fracturamiento. La mineralización consiste de oro, plata, pirita, cuarzo y menores cantidades de esfalerita, tetrahedrita, galena y calcopirita; varios filones contienen trazas de mineral de uranio. Con el fin de conocer más a fondo las posibilidades económicas de una extensa zona mineralizada, se limitó un área de 24 km2, en la cual se llevaron a cabo estudios detallados de geología y prospección geoquímica. Los resultados de este trabajo constituyen el propósito del presente informe.

Objective: Deep brain stimulation (DBS) is a surgical technique that alleviates motor symptoms in Parkinson's disease. Surgically implanted microelectrodes stimulate the basal ganglia to improve patients' symptoms. One of the training challenges for neurophysiologists is to identify during surgery the target area of the brain in which the electrodes must be implanted. Identification is based both on visual and auditory inspection of the microelectrode recordings (MERs) as they are lowered through the basal ganglia. We present the preliminary evaluation of DBSTrainer, a novel desktop application to train neurophysiologists in the identification of signals corresponding to different basal structures., Methods: A pilot study was conducted with neurologists and neurophysiologists at the Hospital Universitario La Paz (Madrid, Spain). After completing a series of tasks with the application, they were asked to complete an evaluation questionnaire. Usability was assessed using the System Usability Scale (SUS). Functionality, contents, and perceived usefulness were assessed using an ad-hoc Likert questionnaire following the e-MIS framework for surgical learning platforms., Results: 15 volunteers participated in the study. Obtained SUS score was 86.7 ± 0.47. Most positive aspects on functionality were platform design and interactivity. Contents were found realistic and aligned with learning outcomes. Minor problems were identified with signal loading times., Conclusions: This study provides preliminary evidence on the usefulness of DBSTrainer. It is, to our knowledge, the first Technology Enhanced Learning application to train neurophysiologists outside the operating room, and thus its introduction can have a real impact on patient safety and surgical outcomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Objectives: Innovative precision dietary procedures are required to promote healthy aging. This study aimed to evaluate the effects of a personalised strategy based on the inclusion of individualised foods and digital tools on overall health status and quality of life within a follow-up of 3 months in older adults with overweight or obesity., Methods: 127 men and women aged between 50 and 80 years with overweight/obesity participated in the study-between January 2020 and September 2020 at the Center for Nutrition Research-University of Navarra and IMDEA-ALIMENTACIÓN-and were randomly assigned to a usual-care group (standard recommendations) or precision group (precision nutrition strategy based on the inclusion of individualised foods and a mobile application). Anthropometry, body fat percentage, biochemical parameters, diet, and quality of life (SF-36 Health Survey) were assessed at baseline and after 3 months., Results: Both strategies were found to improve overall metabolic health; however, the precision approach demonstrated significantly better outcomes. The precision strategy reduced body weight at 3 months (-4.3 kg; p < 0.001) with significant improvements in body fat percentage, blood pressure and general metabolic health (glycated haemoglobin; alanine aminotransferase; aspartate aminotransferase; hepatic steatosis index) in comparison with the standard recommendations. The precision approach significantly enhanced the quality of life (SF-36) of individuals, with additional improvements in emotional well-being (p = 0.024) and vitality (p = 0.008). Adherence to the Mediterranean diet was significantly associated with a higher quality of life and vitality., Conclusion: These results support the benefit of precision nutrition approaches for promoting healthy aging and emotional well-being, enhancing the quality of life in aging populations, during the COVID-19 pandemic., (Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Aims/hypothesis: Type 2 diabetes is a highly heterogeneous disease for which new subgroups ('clusters') have been proposed based on disease severity: moderate age-related diabetes (MARD), moderate obesity-related diabetes (MOD), severe insulin-deficient diabetes (SIDD) and severe insulin-resistant diabetes (SIRD). It is unknown how disease severity is reflected in terms of quality of life in these clusters. Therefore, we aimed to investigate the cluster characteristics and cluster-wise evolution of quality of life in the previously defined clusters of type 2 diabetes., Methods: We included individuals with type 2 diabetes from the Maastricht Study, who were allocated to clusters based on a nearest centroid approach. We used logistic regression to evaluate the cluster-wise association with diabetes-related complications. We plotted the evolution of HbA 1c levels over time and used Kaplan-Meier curves and Cox regression to evaluate the cluster-wise time to reach adequate glycaemic control. Quality of life based on the Short Form 36 (SF-36) was also plotted over time and adjusted for age and sex using generalised estimating equations. The follow-up time was 7 years. Analyses were performed separately for people with newly diagnosed and already diagnosed type 2 diabetes., Results: We included 127 newly diagnosed and 585 already diagnosed individuals. Already diagnosed people in the SIDD cluster were less likely to reach glycaemic control than people in the other clusters, with an HR compared with MARD of 0.31 (95% CI 0.22, 0.43). There were few differences in the mental component score of the SF-36 in both newly and already diagnosed individuals. In both groups, the MARD cluster had a higher physical component score of the SF-36 than the other clusters, and the MOD cluster scored similarly to the SIDD and SIRD clusters., Conclusions/interpretation: Disease severity suggested by the clusters of type 2 diabetes is not entirely reflected in quality of life. In particular, the MOD cluster does not appear to be moderate in terms of quality of life. Use of the suggested cluster names in practice should be carefully considered, as the non-neutral nomenclature may affect disease perception in individuals with type 2 diabetes and their healthcare providers., (© 2024. The Author(s).)

We describe our experience in the remote management of women with gestational diabetes mellitus during the COVID-19 pandemic. We used a mobile phone application with artificial intelligence that automatically classifies and analyses the data (ketonuria, diet transgressions, and blood glucose values), making adjustment recommendations regarding the diet or insulin treatment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: The automation of glucose control has been an important goal of diabetes treatment for many decades. The first artificial pancreas experiences were in-hospital, closely supervised, small-scale, and short-term studies that demonstrated their superiority over continuous subcutaneous insulin infusion therapy. At present, long-term outpatient studies are being conducted in free-living scenarios., Areas of Uncertainty: The integration of multiple devices increases patients' burden and the probability of technical risks. Control algorithms must be robust to manage disturbance variables, such as physical exercise, meal composition, stress, illness, and circadian variations in insulin sensitivity. Extra layers of safety could be achieved through remote supervision. Dual-hormone systems reduce the incidence and duration of hypoglycemia, but the availability of stable pumpable glucagon needs to be solved. Faster insulin analogues are expected to improve all types of artificial pancreas., Therapeutic Advances: Artificial pancreas safety and feasibility are being demonstrated in outpatient studies. Artificial pancreas use increases the time of sensor-measured glucose in near-normoglycemia and reduces the risk of hyperglycemia and hypoglycemia. The benefits are observed both in single- and dual-hormone algorithms and in full- or semi-closed loop control. A recent meta-analysis including 41 randomized controlled trials showed that artificial pancreas use achieves a reduction of time in hyperglycemia (2 hours less than control treatment) and in hypoglycemia (20 minutes less); mean levels of continuous glucose sensor fell by 8.6 mg/dL over 24 hours and by 14.6 mg/dL overnight. The OpenAPS community uses Do It Yourself artificial pancreas in the real world since 2013, and a recent retrospective cross-over study (n = 20) compared continuous glucose sensor readings before and after initiation: mean levels of blood glucose fell by 7.4 mg/dL over 24 hours and time in range increased from 75.8% to 82.2% (92 minutes more)., Conclusions: The outpatient use of artificial pancreas is safe and improves glucose control in outpatients with type 1 diabetes compared with the use of any type of insulin-based treatment. The availability of open-source solutions and data sharing is needed to foster the development of new artificial pancreas approaches and to promote the wide use of Big Data tools for knowledge discovery, decision support, and personalization.

Background: Telemedicine is becoming increasingly important in Ecuador, especially in areas such as rural primary healthcare and medical education. Rural telemedicine programs in the country need to be strengthened by means of a technological platform adapted to local surroundings and offering advantages such as access to specialized care, continuing education, and so on, combined with modest investment requirements., Introduction: This present article presents the design of a Telemedicine Platform (TMP) for rural healthcare services in Ecuador and a preliminary technical validation with medical students and teachers., Materials and Methods: An initial field study was designed to capture the requirements of the TMP. In a second phase, the TMP was validated in an academic environment along three consecutive academic courses. Assessment was by means of user polls and analyzing user interactions as registered automatically by the platform. The TMP was developed using Web-based technology and open code software., Results: One hundred twenty-four students and 6 specialized faculty members participated in the study, conducting a total of 262 teleconsultations of clinical cases and 226 responses, respectively., Conclusion: The validation results show that the TMP is a useful communication tool for the documentation and discussion of clinical cases. Moreover, its usage may be recommended as a teaching methodology, to strengthen the skills of medical undergraduates. The results indicate that implementing the system in rural healthcare services in Ecuador would be feasible.

An ongoing clinical trial is testing the efficacy of web telematic support in a structured program for obesity treatment and diabetes prevention. Participants were recruited from two tertiary-care hospitals and randomized to receive either a telematic intervention (TI) supported by PREDIRCAM2 web platform or a non-telematic intervention (NTI). All receive 1-year follow-up. Both interventions consist of tailored dietary and exercise prescriptions, based on a Mediterranean dietary pattern and general WHO exercise recommendations for adults. At 6 months, both groups have received 7 contacts, 3 exclusively telematic for the TI group. This is a preliminary result intention-to-treat analysis. One hundred eighty-three participants were recruited, with a mean body mass index of 34.75 ± 2.75 kg/m 2 . General dropout rate at 6 months was 26.8%. Weight changes were statistically significant at months 3 and 6 compared to baseline, -2.915 ± 0.24 kg, -3.29 ± 0.36 kg, respectively (P < 0.001), but not statistically significant between the 3- and 6-month time points -0.37 ± 0.21 kg (P = 0.24). Mean group differences showed that the TI group lost 1.61 ± 1.88 kg more than the NTI group (P = 0.39). Waist, waist/hip ratio, resting heart rate, blood pressure, HbA1c, and low-density lipoprotein cholesterol also showed statistically significant changes at 6 months, with no significant differences between groups. Weight loss in the TI group shows similar results as the usual care NTI group for weight loss and control of obesity comorbidities. At completion of the clinical trial, these results will be reevaluated to assess the potential role of web support in weight-loss maintenance and its cost-effectiveness.

Background: In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to their daily living conditions. Artificial intelligence applications can help people with type 1 diabetes in decision making and allow them to react at time scales shorter than the scheduled face-to-face visits. This work presents a decision support system (DSS), based on glucose prediction, to assist patients in a mobile environment., Methods: The system's impact on therapeutic corrective actions has been evaluated in a randomized crossover pilot study focused on interprandial periods. Twelve people with type 1 diabetes treated with insulin pump participated in two phases: In the experimental phase (EP) patients used the DSS to modify initial corrective decisions in presence of hypoglycemia or hyperglycemia events. In the control phase (CP) patients were asked to follow decisions without knowing the glucose prediction. A telemedicine platform allowed participants to register monitoring data and decisions and allowed endocrinologists to supervise data at the hospital. The study period was defined as a postprediction (PP) time window., Results: After knowing the glucose prediction, participants modified the initial decision in 20% of the situations. No statistically significant differences were found in the PP Kovatchev's risk index change (-1.23 ± 11.85 in EP vs -0.56 ± 6.06 in CP). Participants had a positive opinion about the DSS with an average score higher than 7 in a usability questionnaire., Conclusion: The DSS had a relevant impact in the participants' decision making while dealing with T1DM and showed a high confidence of patients in the use of glucose prediction.

In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers-doctors and nurses-in this field.

Gestational diabetes (GDM) burden has been increasing progressively over the past years. Knowing that intrauterine exposure to maternal diabetes confers high risk for macrosomia as well as for future type 2 diabetes and obesity of the offspring, health care organizations try to provide effective control in spite of the limited resources. Artificial-intelligence-augmented telemedicine has been proposed as a helpful tool to facilitate an efficient widespread medical assistance to GDM. The aim of the study we present was to test the feasibility and acceptance of a mobile decision-support system for GDM, developed in the seventh framework program MobiGuide Project, which includes computer-interpretable clinical practice guidelines, access to data from the electronic health record as well as from glucose, blood pressure, and activity sensors. The results of this pilot study with 20 patients showed that the system is feasible. Compliance of patients with blood glucose monitoring was higher than that observed in a historical group of 247 patients, similar in clinical characteristics, who had been followed up for the 3 years prior to the pilot study. A questionnaire on the use of the telemedicine system showed a high degree of acceptance.

Background: The increasing number of patients with acquired brain injury and the current subjectivity of the conventional upper extremity (UE) assessment tests require new objective assessment techniques., Objective: This research proposes a novel objective motor assessment (OMA) methodology based on the Fugl-Meyer assessment (FMA). The goals are to automatically calculate the objective scores (OSs) of FMA-UE movements (as well as a global OS) and to interpret the estimated OSs., Methods: Fifteen patients participated in the study. The OMA algorithm was designed to detect small-scale variations in UE movements. The OSs for 14 FMA-UE movements and the global OSs were automatically calculated using the algorithm and evaluated by 2 therapists. The interpretation of the global OSs was performed at 3 levels: by item, movement and globally., Results: The global OSs calculated by our algorithm had a significant correlation with the therapists' scores (0.783 and 0.938, p <  0.01). All OSs for each movement were correlated with the scores given by the therapists. The correlation coefficient can reach values as high as 0.981 (p <  0.01)., Conclusions: We provide a new objective assessment tool for therapists to help them improve the diagnostic accuracy and to achieve a more personalized and potentially effective physical rehabilitation of brain injury patients.

Background: The growth of diabetes prevalence is causing an increasing demand in health care services which affects the clinicians' workload as medical resources do not grow at the same rate as the diabetic population. Decision support tools can help clinicians with the inspection of monitoring data, providing a preliminary analysis to ease their interpretation and reduce the evaluation time per patient. This paper presents Sinedie, a clinical decision support system designed to manage the treatment of patients with gestational diabetes. Sinedie aims to improve access to specialized healthcare assistance, to prevent patients from unnecessary displacements, to reduce the evaluation time per patient and to avoid gestational diabetes adverse outcomes., Methods: A web-based telemedicine platform was designed to remotely evaluate patients allowing them to upload their glycaemia data at home directly from their glucose meter, as well as report other monitoring variables like ketonuria and compliance to dietary treatment. Glycaemia values, not tagged by patients, are automatically labelled with their associated meal by a classifier based on the Expectation Maximization clustering algorithm and a C4.5 decision tree learning algorithm. Two finite automata are combined to determine the patient's metabolic condition, which is analysed by a rule-based knowledge base to generate therapy adjustment recommendations. Diet recommendations are automatically prescribed and notified to the patients, whereas recommendations about insulin requirements are notified also to the physicians, who will decide if insulin needs to be prescribed. The system provides clinicians with a view where patients are prioritized according to their metabolic condition. A randomized controlled clinical trial was designed to evaluate the effectiveness and safety of Sinedie interventions versus standard care and its impact in the professionals' workload in terms of the clinician's time required per patient; number of face-to-face visits; frequency and duration of telematics reviews; patients' compliance to self-monitoring; and patients' satisfaction., Results: Sinedie was clinically evaluated at "Parc Tauli University Hospital" in Spain during 17 months with the participation of 90 patients with gestational diabetes. Sinedie detected all situations that required a therapy adjustment and all the generated recommendations were safe. The time devoted by clinicians to patients' evaluation was reduced by 27.389% and face-to-face visits per patient were reduced by 88.556%. Patients reported to be highly satisfied with the system, considering it useful and trusting in being well controlled. There was no monitoring loss and, in average, patients measured their glycaemia 3.890 times per day and sent their monitoring data every 3.477days., Conclusions: Sinedie generates safe advice about therapy adjustments, reduces the clinicians' workload and helps physicians to identify which patients need a more urgent or more exhaustive examination and those who present good metabolic control. Additionally, Sinedie saves patients unnecessary displacements which contributes to medical centres' waiting list reduction., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Objectives: The MobiGuide project aimed to establish a ubiquitous, user-friendly, patient-centered mobile decision-support system for patients and for their care providers, based on the continuous application of clinical guidelines and on semantically integrated electronic health records. Patients would be empowered by the system, which would enable them to lead their normal daily lives in their regular environment, while feeling safe, because their health state would be continuously monitored using mobile sensors and self-reporting of symptoms. When conditions occur that require medical attention, patients would be notified as to what they need to do, based on evidence-based guidelines, while their medical team would be informed appropriately, in parallel. We wanted to assess the system's feasibility and potential effects on patients and care providers in two different clinical domains., Materials and Methods: We describe MobiGuide's architecture, which embodies these objectives. Our novel methodologies include a ubiquitous architecture, encompassing a knowledge elicitation process for parallel coordinated workflows for patients and care providers; the customization of computer-interpretable guidelines (CIGs) by secondary contexts affecting remote management and distributed decision-making; a mechanism for episodic, on demand projection of the relevant portions of CIGs from a centralized, backend decision-support system (DSS), to a local, mobile DSS, which continuously delivers the actual recommendations to the patient; shared decision-making that embodies patient preferences; semantic data integration; and patient and care provider notification services. MobiGuide has been implemented and assessed in a preliminary fashion in two domains: atrial fibrillation (AF), and gestational diabetes Mellitus (GDM). Ten AF patients used the AF MobiGuide system in Italy and 19 GDM patients used the GDM MobiGuide system in Spain. The evaluation of the MobiGuide system focused on patient and care providers' compliance to CIG recommendations and their satisfaction and quality of life., Results: Our evaluation has demonstrated the system's capability for supporting distributed decision-making and its use by patients and clinicians. The results show that compliance of GDM patients to the most important monitoring targets - blood glucose levels (performance of four measurements a day: 0.87±0.11; measurement according to the recommended frequency of every day or twice a week: 0.99±0.03), ketonuria (0.98±0.03), and blood pressure (0.82±0.24) - was high in most GDM patients, while compliance of AF patients to the most important targets was quite high, considering the required ECG measurements (0.65±0.28) and blood-pressure measurements (0.75±1.33). This outcome was viewed by the clinicians as a major potential benefit of the system, and the patients have demonstrated that they are capable of self-monitoring - something that they had not experienced before. In addition, the system caused the clinicians managing the AF patients to change their diagnosis and subsequent treatment for two of the ten AF patients, and caused the clinicians managing the GDM patients to start insulin therapy earlier in two of the 19 patients, based on system's recommendations. Based on the end-of-study questionnaires, the sense of safety that the system has provided to the patients was its greatest asset. Analysis of the patients' quality of life (QoL) questionnaires for the AF patients was inconclusive, because while most patients reported an improvement in their quality of life in the EuroQoL questionnaire, most AF patients reported a deterioration in the AFEQT questionnaire., Discussion: Feasibility and some of the potential benefits of an evidence-based distributed patient-guidance system were demonstrated in both clinical domains. The potential application of MobiGuide to other medical domains is supported by its standards-based patient health record with multiple electronic medical record linking capabilities, generic data insertion methods, generic medical knowledge representation and application methods, and the ability to communicate with a wide range of sensors. Future larger scale evaluations can assess the impact of such a system on clinical outcomes., Conclusion: MobiGuide's feasibility was demonstrated by a working prototype for the AF and GDM domains, which is usable by patients and clinicians, achieving high compliance to self-measurement recommendations, while enhancing the satisfaction of patients and care providers., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The management of postprandial glucose excursions in type 1 diabetes has a major impact on overall glycaemic control. In this work, we propose and evaluate various mechanistic models to characterize the disposal of meal-attributable glucose. Sixteen young volunteers with type 1 diabetes were subject to a variable-target clamp which replicated glucose profiles observed after a high-glycaemic-load ([Formula: see text]) or a low-glycaemic-load ([Formula: see text]) evening meal. [6,6-[Formula: see text]] and [U-[Formula: see text];1,2,3,4,5,6,6-[Formula: see text]] glucose tracers were infused to, respectively, mimic: (a) the expected post-meal suppression of endogenous glucose production and (b) the appearance of glucose due to a standard meal. Six compartmental models (all a priori identifiable) were proposed to investigate the remote effect of circulating plasma insulin on the disposal of those glucose tracers from the non-accessible compartments, representing e.g. interstitium. An iterative population-based parameter fitting was employed. Models were evaluated attending to physiological plausibility, posterior identifiability of their parameter estimates, accuracy-via weighted fitting residuals-and information criteria (i.e. parsimony). The most plausible model, best representing our experimental data, comprised: (1) a remote effect x of insulin active above a threshold [Formula: see text] = 1.74 (0.81-2.50) [Formula: see text] min[Formula: see text] [median (inter-quartile range)], with parameter [Formula: see text] having a satisfactory support: coefficient of variation CV = 42.33 (31.34-65.34) %, and (2) steady-state conditions at the onset of the experiment ([Formula: see text]) for the compartment representing the remote effect, but not for the masses of the tracer that mimicked endogenous glucose production. Consequently, our mechanistic model suggests non-homogeneous changes in the disposal rates for meal-attributable glucose in relation to plasma insulin. The model can be applied to the in silico simulation of meals for the optimization of postprandial insulin infusion regimes in type 1 diabetes.

Background: Physical activity (PA) is essential to prevent and to treat a variety of chronic diseases. The automated detection and quantification of PA over time empowers lifestyle interventions, facilitating reliable exercise tracking and data-driven counseling., Methods: We propose and compare various combinations of machine learning (ML) schemes for the automatic classification of PA from multi-modal data, simultaneously captured by a biaxial accelerometer and a heart rate (HR) monitor. Intensity levels (low / moderate / vigorous) were recognized, as well as for vigorous exercise, its modality (sustained aerobic / resistance / mixed). In total, 178.63 h of data about PA intensity (65.55 % low / 18.96 % moderate / 15.49 % vigorous) and 17.00 h about modality were collected in two experiments: one in free-living conditions, another in a fitness center under controlled protocols. The structure used for automatic classification comprised: a) definition of 42 time-domain signal features, b) dimensionality reduction, c) data clustering, and d) temporal filtering to exploit time redundancy by means of a Hidden Markov Model (HMM). Four dimensionality reduction techniques and four clustering algorithms were studied. In order to cope with class imbalance in the dataset, a custom performance metric was defined to aggregate recognition accuracy, precision and recall., Results: The best scheme, which comprised a projection through Linear Discriminant Analysis (LDA) and k-means clustering, was evaluated in leave-one-subject-out cross-validation; notably outperforming the standard industry procedures for PA intensity classification: score 84.65 %, versus up to 63.60 %. Errors tended to be brief and to appear around transients., Conclusions: The application of ML techniques for pattern identification and temporal filtering allowed to merge accelerometry and HR data in a solid manner, and achieved markedly better recognition performances than the standard methods for PA intensity estimation.

This paper introduces a new approach for upper limb neurorehabilitation based on customized devices for monitoring and interacting with virtual environments. A proof-of-concept test involving eight patients at the Guttmann Neurorehabilitation Hospital shows patient's good acceptance and usability scores and demonstrates the technically feasibility of the devices. The final goal is to achieve a more personalized, monitored, intensive and ecological rehabilitation procedures for ABI patients.

The availability of electronic health data favors scientific advance through the creation of repositories for secondary use. Data anonymization is a mandatory step to comply with current legislation. A service for the pseudonymization of electronic healthcare record (EHR) extracts aimed at facilitating the exchange of clinical information for secondary use in compliance with legislation on data protection is presented. According to ISO/TS 25237, pseudonymization is a particular type of anonymization. This tool performs the anonymizations by maintaining three quasi-identifiers (gender, date of birth, and place of residence) with a degree of specification selected by the user. The developed system is based on the ISO/EN 13606 norm using its characteristics specifically favorable for anonymization. The service is made up of two independent modules: the demographic server and the pseudonymizing module. The demographic server supports the permanent storage of the demographic entities and the management of the identifiers. The pseudonymizing module anonymizes the ISO/EN 13606 extracts. The pseudonymizing process consists of four phases: the storage of the demographic information included in the extract, the substitution of the identifiers, the elimination of the demographic information of the extract, and the elimination of key data in free-text fields. The described pseudonymizing system was used in three telemedicine research projects with satisfactory results. A problem was detected with the type of data in a demographic data field and a proposal for modification was prepared for the group in charge of the drawing up and revision of the ISO/EN 13606 norm.

Background: The acute impact of different types of physical activity on glycemic control in type 1 diabetes has not been well quantified., Objectives: Our objective was to estimate the rate of change (RoC) in glucose concentration induced acutely during the performance of structured exercise and at recovery in subjects with type 1 diabetes., Methods: We searched for original articles in the PubMed, MEDLINE, Scopus, and Cochrane databases. Search terms included type 1 diabetes, blood glucose, physical activity, and exercise. Eligible studies (randomized controlled trials and non-randomized experiments) encompassed controlled physical activity sessions (continuous moderate [CONT], intermittent high intensity [IHE], resistance [RESIST], and/or a resting reference [REST]) and reported excursions in glucose concentration during exercise and after its cessation. Data were extracted by graph digitization to compute two RoC measures from population profiles: RoCE during exercise and RoCR in recovery., Results: Ten eligible studies were found from 540 publications. Meta-analyses of exercise modalities versus rest yielded the following: RoCE -4.43 mmol/L h(-1) (p < 0.00001, 95% confidence interval [CI] -6.06 to -2.79) and RoCR +0.70 mmol/L h(-1) (p = 0.46, 95% CI -1.14 to +2.54) for CONT vs. REST; RoCE -5.25 mmol/L·h(-1) (p < 0.00001, 95 % CI -7.02 to -3.48) and RoCR +0.72 mmol/L h(-1) (p = 0.71, 95% CI -3.10 to +4.54) for IHE vs. REST; RoCE -2.61 mmol/L h(-1) (p = 0.30, 95% CI -7.55 to +2.34) and RoCR -0.02 mmol/L h(-1) (p = 1.00, 95% CI -7.58 to +7.53) for RESIST vs. REST., Conclusions: Novel RoC magnitudes RoCE, RoCR reflected rapid decays of glycemia during CONT exercise and gradual recoveries immediately afterwards. RESIST showed more constrained decays, whereas discrepancies were found for IHE.

The progressive ageing of population has turned the mild cognitive impairment (MCI) into a prevalent disease suffered by elderly. Consequently, the spatial disorientation has become a significant problem for older people and their caregivers. The ambient-assisted living applications are offering location-based services for empowering elderly to go outside and encouraging a greater independence. Therefore, this paper describes the design and technical evaluation of a location-awareness service enabler aimed at supporting and managing probable wandering situations of a person with MCI. Through the presence capabilities of the IP multimedia subsystem (IMS) architecture, the service will alert patient's contacts if a hazardous situation is detected depending on his location. Furthermore, information about the older person's security areas has been included in the user profile managed by IMS. In doing so, the service enabler introduced contribute to "context-awareness" paradigm allowing the adaptation and personalization of services depending on user's context and specific conditions or preferences.

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients' self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient's access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients' personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients' acceptance of the whole system., (© 2014 Diabetes Technology Society.)

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient's data using two different strategies to control nocturnal and postprandial periods., Research Design and Methods: We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min., Results: Time spent in normoglycemia (BG, 3.9-8.0 mmol/L) during the nocturnal period (12 a.m.-8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3-75%) with OL to 95.8% (73-100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0-21%) in the OL night to 0.0% (0.0-0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9-10.0 mmol/L) 58.3% (29.1-87.5%) versus 50.0% (50-100%)., Conclusions: A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia.

The aim of this study was to analyze the discourse of health managers on aspects related to delay in tuberculosis diagnosis. This was a qualitative research study, conducted with 16 Family Health Unit managers. The empirical data were obtained through semi-structured interviews. The analysis was based on the theoretical framework of the French school of discourse analysis. According to the managers' statements, the delay in tuberculosis diagnosis is related to patient and health service aspects. As for patient aspects, managers report fear, prejudice and lack of information as factors that may promote a delayed diagnosis. Regarding health service aspects, structural problems and lack of professional skills were reported. The discourse of managers should be considered to qualify tuberculosis control actions and to prevent delays in diagnosis.

Background: Healthy diet and regular physical activity are powerful tools in reducing diabetes and cardiometabolic risk. Various international scientific and health organizations have advocated the use of new technologies to solve these problems. The PREDIRCAM project explores the contribution that a technological system could offer for the continuous monitoring of lifestyle habits and individualized treatment of obesity as well as cardiometabolic risk prevention., Methods: PREDIRCAM is a technological platform for patients and professionals designed to improve the effectiveness of lifestyle behavior modifications through the intensive use of the latest information and communication technologies. The platform consists of a web-based application providing communication interface with monitoring devices of physiological variables, application for monitoring dietary intake, ad hoc electronic medical records, different communication channels, and an intelligent notification system. A 2-week feasibility study was conducted in 15 volunteers to assess the viability of the platform., Results: The website received 244 visits (average time/session: 17 min 45 s). A total of 435 dietary intakes were recorded (average time for each intake registration, 4 min 42 s ± 2 min 30 s), 59 exercises were recorded in 20 heart rate monitor downloads, 43 topics were discussed through a forum, and 11 of the 15 volunteers expressed a favorable opinion toward the platform. Food intake recording was reported as the most laborious task. Ten of the volunteers considered long-term use of the platform to be feasible., Conclusions: The PREDIRCAM platform is technically ready for clinical evaluation. Training is required to use the platform and, in particular, for registration of dietary food intake., (© 2013 Diabetes Technology Society.)

This paper proposes an agent-based model of the action of macrophages on the beta cells of the endocrine pancreas. The aim of this model is to simulate the processes of beta cell proliferation and apoptosis and also the process of phagocytosis of cell debris by macrophages, all of which are related to the onset of the autoimmune response in type 1 diabetes. We have used data from the scientific literature to design the model. The results show that the model obtains good approximations to real processes and could be used to shed light on some open questions concerning such processes.

Background: Closed-loop control algorithms in diabetes aim to calculate the optimum insulin delivery to maintain the patient in a normoglycemic state, taking the blood glucose level as the algorithm's main input. The major difficulties facing these algorithms when applied subcutaneously are insulin absorption time and delays in measurement of subcutaneous glucose with respect to the blood concentration., Methods: This article presents an inverse controller (IC) obtained by inversion of an existing mathematical model and validated with synthetic patients simulated with a different model and is compared with a proportional-integral-derivative controller., Results: Simulated results are presented for a mean patient and for a population of six simulated patients. The IC performance is analyzed for both full closed-loop and semiclosed-loop control. The IC is tested when initialized with the heuristic optimal gain, and it is compared with the performance when the initial gain is deviated from the optimal one (+/-10%)., Conclusions: The simulation results show the viability of using an IC for closed-loop diabetes control. The IC is able to achieve normoglycemia over long periods of time when the optimal gain is used (63% for the full closed-loop control, and it is increased to 96% for the semiclosed-loop control).

Background: The use of telemedicine for diabetes care has evolved over time, proving that it contributes to patient self-monitoring, improves glycemic control, and provides analysis tools for decision support. The timely development of a safe and robust ambulatory artificial pancreas should rely on a telemedicine architecture complemented with automatic data analysis tools able to manage all the possible high-risk situations and to guarantee the patient's safety., Methods: The Intelligent Control Assistant system (INCA) telemedical artificial pancreas architecture is based on a mobile personal assistant integrated into a telemedicine system. The INCA supports four control strategies and implements an automatic data processing system for risk management (ADP-RM) providing short-term and medium-term risk analyses. The system validation comprises data from 10 type 1 pump-treated diabetic patients who participated in two randomized crossover studies, and it also includes in silico simulation and retrospective data analysis., Results: The ADP-RM short-term risk analysis prevents hypoglycemic events by interrupting insulin infusion. The pump interruption has been implemented in silico and tested for a closed-loop simulation over 30 hours. For medium-term risk management, analysis of capillary blood glucose notified the physician with a total of 62 alarms during a clinical experiment (56% for hyperglycemic events). The ADP-RM system is able to filter anomalous continuous glucose records and to detect abnormal administration of insulin doses with the pump., Conclusions: Automatic data analysis procedures have been tested as an essential tool to achieve a safe ambulatory telemedical artificial pancreas, showing their ability to manage short-term and medium-term risk situations., (2009 Diabetes Technology Society.)

Purpose: Advanced information technologies joined to the increasing use of continuous medical devices for monitoring and treatment, have made possible the definition of a new telemedical diabetes care scenario based on a hand-held Personal Assistant (PA). This paper describes the architecture, functionality and implementation of the PA, which communicates different medical devices in a personal wireless network., Description of the System: The PA is a mobile system for patients with diabetes connected to a telemedical center. The software design follows a modular approach to make the integration of medical devices or new functionalities independent from the rest of its components. Physicians can remotely control medical devices from the telemedicine server through the integration of the Common Object Request Broker Architecture (CORBA) and mobile GPRS communications. Data about PA modules' usage and patients' behavior evaluation come from a pervasive tracing system implemented into the PA., Results and Discussion: The PA architecture has been technically validated with commercially available medical devices during a clinical experiment for ambulatory monitoring and expert feedback through telemedicine. The clinical experiment has allowed defining patients' patterns of usage and preferred scenarios and it has proved the Personal Assistant's feasibility. The patients showed high acceptability and interest in the system as recorded in the usability and utility questionnaires. Future work will be devoted to the validation of the system with automatic control strategies from the telemedical center as well as with closed-loop control algorithms.

We have characterized the DBF2 gene, encoding a protein kinase of the NDR family in Candida albicans, and demonstrate that this gene is essential for cell viability. Conditional mutants were constructed by using the MET3 promoter to analyse the phenotype of cells lacking this kinase. The absence of Dbf2 resulted in cells arrested as large-budded pairs that failed to contract the actomyosin ring, a function similar to that described for its Saccharomyces cerevisiae orthologue. In addition to its role in cytokinesis, Dbf2 regulates mitotic spindle organization and nuclear segregation as Dbf2-depleted cells have abnormal microtubules and severe defects in nuclear migration to the daughter cell, which results in a cell cycle block during mitosis. Taken together, these results imply that Dbf2 performs several functions during exit from mitosis and cytokinesis. Consistent with a role in spindle organization, the protein localizes to the mitotic spindle during anaphase, and it interacts physically with tubulin, as indicated by immunoprecipitation experiments. Finally, DBF2 depletion also resulted in impaired true hyphal growth.

Background: In Saccharomyces cerevisiae, nutrient limitation stimulates diploid cells to undergo DNA replication and meiosis, followed by the formation of four haploid spores. Septins are a family of proteins that assemble a ring structure at the mother-daughter neck during vegetative growth, where they control cytokinesis. In sporulating cells, the septin ring disassembles and septins relocalize to the prospore membrane., Results: Here, we demonstrate that nutrient limitation triggers a change in the localization of at least two vegetative septins (Cdc10 and Cdc11) from the bud neck to the microtubules. The association of Cdc10 and Cdc11 with microtubules persists into meiosis, and they are found associated with the meiotic spindle until the end of meiosis II. In addition, the meiosis-specific septin Spr28 displays similar behavior, suggesting that this is a common feature of septins. Septin association to microtubules is a consequence of the nutrient limitation signal, since it is also observed when haploid cells are incubated in sporulation medium and when haploid or diploid cells are grown in medium containing non-fermentable carbon sources. Moreover, during meiosis II, when the nascent prospore membrane is formed, septins moved from the microtubules to this membrane. Proper organization of the septins on the membrane requires the sporulation-specific septins Spr3 and Spr28., Conclusion: Nutrient limitation in S. cerevisiae triggers the sporulation process, but it also induces the disassembly of the septin bud neck ring and relocalization of the septin subunits to the nucleus. Septins remain associated with microtubules during the meiotic divisions and later, during spore morphogenesis, they are detected associated to the nascent prospore membranes surrounding each nuclear lobe. Septin association to microtubules also occurs during growth in non-fermentable carbon sources.

The growing availability of continuous data from medical devices in diabetes management makes it crucial to define novel information technology architectures for efficient data storage, data transmission, and data visualization. The new paradigm of care demands the sharing of information in interoperable systems as the only way to support patient care in a continuum of care scenario. The technological platforms should support all the services required by the actors involved in the care process, located in different scenarios and managing diverse information for different purposes. This article presents basic criteria for defining flexible and adaptive architectures that are capable of interoperating with external systems, and integrating medical devices and decision support tools to extract all the relevant knowledge to support diabetes care.

Background: Real-time continuous glucose monitoring (CGM) has recently been incorporated into routine diabetes management because of the potential advantages it offers for glycemic control. The aim of our study was to evaluate the impact of the use of real-time CGM together with a telemedicine system in hemoglobin A1c and glucose variability in patients with type 1 diabetes treated with insulin pumps., Methods: Ten patients (five women, 41.2 [range, 21-62] years old, duration of diabetes 14.9 [range, 3-52] years) were included in this randomized crossover study. Patients used the DIABTel telemedicine system throughout the study, and real-time CGM was used for 3 days every week during the intervention phase. At the end of the control phase, a blind 3-day CGM was performed. Glucose variability was evaluated using the Glucose Risk Index (GRI), a comparative analysis of continuous glucose values over two consecutive hours., Results: Hemoglobin A1c decreased significantly (8.1 +/- 1.1% vs. 7.3 +/- 0.8%; P = 0.007) after the intervention phase, while no changes were observed during the control phase. The mean number of daily capillary glucose readings was higher during the intervention phase (4.7 +/- 1.1 vs. 3.8 +/- 1.0; P < 0.01), because of an increase in random analyses (1.22 +/- 0.3 vs. 0.58 +/- 0.1; P < 0.01), and there was also a significant increase in the mean number of bolus doses per day (5.23 +/- 1.1 vs. 4.4 +/- 0.8; P < 0.05). The GRI was higher during the control phase than during the experimental phase (9.6 vs. 6.25; P < 0.05)., Conclusions: Real-time CGM in conjunction with the DIABTel system improves glycemic control and glucose stability in pump-treated patients with type 1 diabetes.

Objectives: INCA (Intelligent Control Assistant for Diabetes) is an EU funded project aimed at improving diabetes therapy by creating a personal closed-loop system interacting with telemedical remote control. This study aims at identifying and applying suitable methods for a cost-benefit analysis from the perspective of the payor for health services., Methods: For cost analysis MOSAIK-M was used, a method and tool for health information systems analysis and design. Two MOSAIK-M models were created describing conventional insulin pump based diabetes care (CSII), and INCA based diabetes care. Both models were parameterized with costs and simulated to determine yearly costs of diabetes management and treatment for a patient with no diabetes related complications. Probability of developing complications and their duration were determined based on the Archimedes model. It was parameterized with results of a clinical study concerning HbA1c-value changes using the INCA system compared with conventional CSII. The simulation results in form of years of disease within a 30-year time frame were multiplied with corresponding treatment costs., Results: Yearly costs of conventional insulin CSII for a diabetes type 1 patient are euro 5908 (German health care system). Using INCA based on the clinical study setting would raise yearly costs by euro 2233. 24% of the INCA costs are generated by the continuous blood glucose measurement device, 5% by IT devices and services. Considering also diabetes related complications in a 30-year time frame and HbA1c value reductions from 7.9 and 7.6% (conventional CSII) to 7.5 and 7.3% (INCA) reduces the additional costs of INCA to euro 2102 and euro 2162., Conclusions: The approach produces an estimation of a lower bound for cost savings concerning the treatment of diabetes related complications in a 30-year time frame. These savings alone do not prove cost efficiency of the INCA approach. Further work is needed to improve the approximation and to include indirect and intangible costs.

In Saccharomyces cerevisiae exit from mitosis requires the Cdc14 phosphatase to reverse CDK-mediated phosphorylation. Cdc14 is released from the nucleolus by the Cdc14 early anaphase release (FEAR) and mitotic exit network (MEN) pathways. In meiosis, the FEAR pathway is essential for exit from anaphase I. The MEN component Cdc15 is required for the formation of mature spores. To analyze the role of Cdc15 during sporulation, a conditional mutant in which CDC15 expression was controlled by the CLB2 promoter was used. Cdc15-depleted cells proceeded normally through the meiotic divisions but were unable to properly disassemble meiosis II spindles. The morphology of the prospore membrane was aberrant and failed to capture the nuclear lobes. Cdc15 was not required for Cdc14 release from the nucleoli, but it was essential to maintain Cdc14 released and for its nucleo-cytoplasmic transport. However, cells carrying a CDC14 allele with defects in nuclear export (Cdc14-DeltaNES) were able to disassemble the spindle and to complete spore formation, suggesting that the Cdc14 nuclear export defect was not the cause of the phenotypes observed in cdc15 mutants.

Background: The DIABTel system, a Web-based telemedicine application, integrates a whole communication system (glucometer, insulin pump, wireless hand-held assistant) for medical remote advice. We sought to evaluate, in terms of glycemic control, the DIABTel system in a randomized crossover clinical study., Methods: Ten patients with type 1 diabetes [5 women, age 40.6 (21-62) years, diabetes duration 14.7 (3-52) years] were included. During the 4-week active phase, data sent by patients were analyzed by the physician and modifications of the basal rate and bolus were advised in the following 24 hours. During the control phase, patients sent glucose data without any feedback from the medical center., Results: The mean numbers of daily glucose values and bolus sent by patients during the active period were 4.46 +/- 0.91 and 4.58 +/- 0.89, respectively. The personal digital assistant functionalities used more frequently by patients were (times per week) data visualization (8.1 +/- 6.8), data download from the insulin pump (6.8 +/- 3.3), and synchronization with the telemedicine server (8.5 +/- 4.9). After the experimental phase, serum fructosamine decreased significantly (393 +/- 32 vs 366 +/- 25 micromol/liter; p < 0.05) and hemoglobin A1c (HbA1c) tended to decrease (8.0 +/- 0.6 vs 7.78 +/- 0.6; p = 0.073), whereas no changes were observed during the control phase. The number of treatment modifications proposed and performed by the patients correlated with the change observed in HbA1c during the active phase (r = -0.729, p = 0.017)., Conclusions: The DIABTel system, a telemedicine system that includes a wireless personal assistant for remote treatment advising, allows better glycemic control in pump-treated patients with type 1 diabetes. To our knowledge, this is the first study that demonstrates improved glycemic control with the use of a telemedicine system that incorporates insulin delivery data.

M2DM (multi access services for telematic management of diabetes mellitus, ) is an EU-funded telemedicine project that aims at increasing the quality of diabetes care by improving communication between patients and caregivers. As part of this project, we have undertaken the initial work of describing the necessary requirements (framework) of an advanced educational component for M2DM in accordance with the latest Semantic Web concepts. This paper describes our proposed semantic framework for educational content management, customisation and delivery. A big internet challenge today is to find and push situation and user-specific quality knowledge to users based on their actual individual needs, circumstances and profiles at any given time. We believe that the semantic framework presented in this paper could be a good step towards meeting this challenge. Benefits for users, both developers and end users, of adopting such framework are also discussed. The ideas discussed in this paper could be easily adapted to other similar services besides M2DM and to different health topics besides diabetes mellitus.