Revealing structural evolution occurring from photo-initiated polymer network formation.

Photopolymerization is a key enabling technology offering spatial and temporal control to allow for future functional materials to be made to meet societal needs. However, gaining access to robust experimental techniques to describe the evolution of nanoscale morphology in photo-initiated polymeric systems has proven so far to be a challenging task. Here, we show that these physical transformations can be monitored and quantified at the nanoscale in situ and in real-time. It is demonstrated that the initial structural features of the liquid precursors significantly affect the final morphology and the physical properties of the resulting solid via the occurrence of local heterogeneities in the molecular mobility during the curing transformation. We have made visible how local physical arrestings in the liquid, associated with both cross-linking and vitrification, determine the length scale of the local heterogeneities forming upon curing, found to be in the 10-200 nm range.

Effects of Zostera marina on the patterns of spatial distribution of sediments and macrozoobenthos in the boreal lagoon of Furen (Hokkaido, Japan).

Understanding patterns of spatial variations in benthic seagrass assemblages is a central issue in seagrass ecology. However, how patterns of spatial variations in macrozoobenthos and associated sediments differ between vegetated and unvegetated areas remain largely unexplored. In the present study, two different habitats represented by dense Zostera marina beds (Zostera) and unvegetated sediments (Bare) were compared at three locations, 100's meters apart, located at progressive distance from the Furen river in the boreal lagoon of Furen (Hokkaido, Japan). We tested the hypothesis that Z. marina influences the patterns of spatial distribution of abiotic and biotic components along an environmental (estuarine) gradient. The results showed considerable differences between Zostera and Bare, as well as between and within locations, in the distribution of both sediment variables (mud, total organic carbon [TOC] and total nitrogen, acid volatile sulfide, chlorophyll-a and pheopigments) and macrozoobenthic assemblage metrics (total number of species [S], Shannon-Weiner diversity index [H'], total abundance and abundance of dominant species). TOC content, associated to a high mud content, was highest in Bare irrespective of differences between locations (all being above a critical TOC threshold of 3.6%), while S and H' were higher in Zostera than in Bare at all locations. Significant location x habitat effects were found in the abundance of dominant species, represented mainly by mollusks and crustaceans. Furthermore, the proportions of spatial variance were greater at the scale of replicates (meters apart) than at the scale of stations (10's meters apart) for both sediment variables and the dominant species. Importantly, for the dominant species the spatial variance at the smaller scale was much higher in Zostera than in Bare, indicating that at the scale of meters Zostera beds increase the patchiness in the spatial distribution of individuals compared to bare sediments. Overall, our results demonstrate that Z. marina has a strong effect on the spatial heterogeneity in the intensity of the ecological processes influencing patterns of sediment and macrozoobenthos distribution along an environmental gradient. The present study provides a general framework to evaluate patterns of spatial distribution across various scales within several hundreds of meters in seagrass-dominated, eutrophic coastal lagoons.

Model checking for clinical guidelines: an agent-based approach.

In this paper, we propose a new computer-based approach to model clinical guidelines, adopting the agent-based paradigm. We first show how clinical guidelines can be modelled in an agent like fashion in the specification language Promela of the model checker SPIN. Then, we describe the impact of such a move: by using SPIN model-checking facilities, one can automatically prove a wide range of properties concerning the modeled guidelines. As a proof of concept, we apply such a methodology to the clinical guidelines in GLARE, a domain-independent prototypical system for acquiring, representing and executing clinical guidelines, which has been built within a 7-year project with Azienda Ospedaliera San Giovanni Battista in Turin (one of the largest hospitals in Italy).

A telemedicine support for diabetes management: the T-IDDM project.

In the context of the EU funded Telematic Management of Insulin-Dependent Diabetes Mellitus (T-IDDM) project, we have designed, developed and evaluated a telemedicine system for insulin dependent diabetic patients management. The system relies on the integration of two modules, a Patient Unit (PU) and a Medical Unit (MU), able to communicate over the Internet and the Public Switched Telephone Network. Using the PU, patients are allowed to automatically download their monitoring data from the blood glucose monitoring device, and to send them to the hospital data-base; moreover, they are supported in their every day self monitoring activity. The MU provides physicians with a set of tools for data visualization, data analysis and decision support, and allows them to send messages and/or therapeutic advice to the patients. The T-IDDM service has been evaluated through the application of a formal methodology, and has been used by European patients and physicians for about 18 months. The results obtained during the project demonstration, even if obtained on a pilot study of 12 subjects, show the feasibility of the T-IDDM telemedicine service, and seem to substantiate the hypothesis that the use of the system could present an advantage in the management of insulin dependent diabetic patients, by improving communications and, potentially, clinical outcomes.

Cased-Based Reasoning for medical knowledge-based systems.

In this paper we present the results of the MIE/GMDS-2000 Workshop 'Case-Based Reasoning for Medical Knowledge-based Systems'. While in many domains Cased-Based Reasoning (CBR) has become a successful technique for knowledge-based systems, in the medical field attempts to apply the complete CBR cycle are rather exceptional. Some systems have recently been developed, which on the one hand use only parts of the CBR method, mainly the retrieval, and on the other hand enrich the method by a generalisation step to fill the knowledge gap between the specificity of single cases and general rules. And some systems rely on integrating CBR and other problem solving methodologies. In this paper we discuss the appropriateness of CBR for medical knowledge-based systems, point out problems, limitations and possible ways to cope with them.

Production of monoclonal antibody against Scrippsiella trochoidea cysts and its application to analysis during cyst formation and enzyme-linked immunosorbent assay.

A monoclonal antibody was produced by the fusion of mouse myeloma cells with spleen cells from a mouse immunized with the cysts of Scrippsiella trochoidea, marine phytoplankton. Immunofluorescence microscopic observation showed that the antibody reacted with the spines on the cyst but not with the vegetative cells and cyst walls. An enzyme-linked immunosorbent assay could be used to measure the cysts in muddy bottom sediments using the purified antibody conjugated with horseradish peroxidase.

Web-based telemedicine systems for home-care: technical issues and experiences.

The use of the Web for telemedicine applications seems nowadays a compulsory solution: the Web has become a standardized infrastructure for giving access to sophisticated telemedicine applications from virtually any machine and operating system. Such standardized communication platform guarantees accessibility and usability advantages to both customers and providers (patients and physicians). However, there are several issues that should be discussed in depth, with particular reference to all the applications related to the provision of care at distance, nowadays called telecare applications. In telecare applications the role of the patient becomes central, since he/she is actively involved in the process of managing care and treatments, and since he/she (or his/her families) is responsible for collecting some measurements and related information. In this paper we will discuss the general architectural and technical issues related to the development of Web-based systems for telecare applications, relying on the experience we gained within the telecare project T-IDDM (Telematic Management of Insulin Dependent Diabetes Mellitus), devoted to assist the management and home-monitoring of Type 1 Diabetes Mellitus patients.

Standing stock and production rate of phytoplankton and a red tide outbreak in a heavily eutrophic embayment, Dokai Bay, Japan.

The seasonal variation of phytoplankton biomass and primary productivity in a heavily eutrophic embayment, Dokai Bay, Japan, was determined. Dokai Bay was characterized by high phytoplankton biomass and productivity during summer and low phytoplankton biomass and productivity during other seasons. The results suggested that phytoplankton growth was limited by only irradiance and water temperature under the high nutrient concentrations available for phytoplankton growth in the entire year. Moreover, in spite of sufficient nutrient for phytoplankton growth in the entire year, a red tide occurred only in the summer period in this bay. Our results suggested that a red tide occurred by the high phytoplankton growth rate in the summer season, but in other periods surface phytoplankton was flushed out of the bay before forming the red tide, because phytoplankton growth rate was low and could not form the red tide due to low irradiance and low water temperature.

Meta-analysis of the effect of the use of computer-based systems on the metabolic control of patients with diabetes mellitus.

The purpose of this study was to evaluate, through a meta-analysis study, whether the use of computer-based systems reported in the literature improves the metabolic control of diabetic patients. On the retrieved papers, a set of meta-analysis studies were performed: first the difference of HbA1c between cases and controls at follow-up was evaluated (sign test); then the difference between cases and controls in the total variation of HbA1c from the beginning to the end of the trial was considered (method of effect sizes). The latter methodology was reapplied also on three more homogeneous article subgroups. The sign test was performed on 16 papers: in two of them, the HbA1c level was higher in the intervention group than in the control group at follow-up: it is unlikely that this is a random occurrence (p < 0.01). The method of effect sizes was first applied to 13 papers, as in the others some needed data were missing: the results obtained showed a statistically significant amelioration of metabolic control in the intervention group in comparison to the control group (p < 0.01). A progressive reinforcement of this outcome was obtained on the trial subgroups. Our study supports the hypothesis that the use of computer-based systems can be an effective means of improving metabolic control. The differential benefit obtained in the amelioration of HbA1c does not justify, by itself, the applicability of such systems into clinical practice; additional investigations should be carried out to evaluate the enhancement of other clinical and organizational indicators.

Exploiting multi-modal reasoning for knowledge management and decision support: an evaluation study.

We present the first evaluation results of a knowledge management and decision support system for Type I diabetes patients' care. Such system, meant to help physicians in therapy revision, relies on the integration of Rule Based Reasoning and Case Based Reasoning, and exploits both explicit and implicit knowledge. Reliability was positively judged by a group of expert diabetologists; an increase in its performances is foreseen as new knowledge will be acquired, through the system usage in clinical practice.

A multi-modal reasoning methodology for managing IDDM patients.

We present a knowledge management and decision support methodology for insulin dependent diabetes mellitus (IDDM) patients care. Such methodology exploits the integration of case based reasoning (CBR) and rule based reasoning (RBR), with the aim of helping physicians during therapy planning, by overcoming the intrinsic limitations shown by the independent application of the two reasoning paradigms. RBR provides suggestions on the basis of a situation detection mechanism that relies on formalized prior knowledge; CBR is used to specialize and dynamically adapt the rules on the basis of the patient's characteristics and of the accumulated experience. When the case library is not representative of the overall population, only RBR is applied to define a therapy for the input situation, which can then be retained, enriching the case library competence. The paper reports the first evaluation results, obtained both on simulated examples and on real patients. This work was developed within the EU funded telematic management of insulin dependent diabetes mellitus (T-IDDM) project, and is fully integrated in its web-based architecture.

Diabetic patients management exploiting case-based reasoning techniques.

In this paper we propose a case-based decision support tool, designed to help physicians in 1st type diabetes therapy revision through the intelligent retrieval of data related to past situations (or 'cases') similar to the current one. A case is defined as a set of variable values (or features) collected during a visit. We defined taxonomy of prototypical patients' conditions, or classes, to which each case should belong. For each input case, the system allows the physician to find similar past cases, both from the same patient and from different ones. We have implemented a two-steps procedure; (1) it finds the classes to which the input case could belong; (2) it lists the most similar cases from these classes, through a nearest neighbor technique, and provides some statistics useful for decision taking. The performance of the system has been tested on a data-base of 147 real cases, collected at the Policlinico S. Matteo Hospital of Pavia. The tool is fully integrated in the web-based architecture of the EU funded Telematic management of Insulin Dependent Diabetes Mellitus (T-IDDM) project.

Molecular analysis of ribosomal RNA gene of red tide algae obtained from the seto inland sea.

Eleven clones from five species of the planktonic microalgae, (Chattonella antiqua, Chattonella marina, Heterosigma akashiwo, Alexandrium catenella, and Scrippsiella trochoidea), which were collected from the Seto Inland Sea in Japan and from Thailand, were subjected to nucleotide sequence analysis of the D1/D2 domain of the large subunit (LSU) of their ribosomal RNA genes. After amplification by polymerase chain reaction using degenerated primers, whole-nucleotide sequences for the D1/D2 domains of the LSU rRNA gene of 11 microalgae were analyzed. Phylogenic tree analysis using these nucleotide sequences showed each species located in a cluster corresponding to its morphological classification. The nucleotide sequence data for Chattonella spp. suggest that multiple clones of both Chattonella antiqua and Chattonella marina are present in the Seto Inland Sea and that red tide blooms of Chattonella spp. in different years may have contained different clones.

Intelligent analysis of clinical time series: an application in the diabetes mellitus domain.

This paper describes the application of a method for the intelligent analysis of clinical time series in the diabetes mellitus domain. Such a method is based on temporal abstractions and relies on the following steps: (i) 'pre-processing' of raw data through the application of suitable filtering techniques: (ii) 'extraction' from the pre-processed data of a set of abstract episodes (temporal abstractions); and (iii) 'post-processing' of temporal abstractions; the post-processing phase results in a new set of features that embeds high level information on the patient dynamics. The derived features set is used to obtain new knowledge through the application of machine learning algorithms. The paper describes in detail the application of this methodology and presents some results obtained on simulated data and on a data-set of four diabetic patients monitored for > 1 year.

Building telemedicine systems for supporting decisions in diabetes care: a report from a running experience.

This paper describes some issues that should be investigated to implement telemedicine systems designed for effectively supporting decisions in diabetic patients management, namely situation assessment, information sharing, and knowledge management. The solutions and experiences carried on in this field within a European Union (EU)-funded project, called T-IDDM (Telematic Management of Insulin Dependent Diabetes Mellitus), are reported.

Integrating case based and rule based reasoning in a decision support system: evaluation with simulated patients.

We present a Web-based knowledge management and decision support system for Type I Diabetes patients' care. The tool exploits the integration of two methodologies, Case Based Reasoning and Rule Based Reasoning, and supports physicians in the definition of therapeutic strategies. Such a work is being integrated in the EU funded T-IDDM project architecture. In this paper we report a first evaluation obtained on simulated patients.

Protocol-based reasoning in diabetic patient management.

We propose a system for teleconsultation in Insulin Dependent Diabetes Mellitus (IDDM) management, accessible through the use of the net. The system is able to collect monitoring data, to analyze them through a set of tools, and to suggest a therapy adjustment in order to tackle the identified metabolic problems and to fit the patient's needs. The therapy revision has been implemented through the Episodic Skeletal Planning Methodi, it generates an advice and employs it to modify the current therapeutic protocol, presenting to the physician a set of feasible solutions, among which she can choose the new one.

Supporting decisions in diabetic patients management through case-based retrieval.

In this paper we present a tool for the intelligent retrieval of past cases to support Insulin Dependent Diabetes Mellitus patients therapy revision. This tool was designed for assisting physicians during periodical monitoring visits. Each case is represented through i) a collection of features that describe the patient's clinical state at the decision time, i.e. the control visit, ii) the decision taken in terms of therapy revision and iii) the outcome obtained on the metabolic control during the following monitoring period. A new case is first classified into a protypical monitoring situation, and then similar cases are retrieved and shown to the user. This tool is fully integrated in a Web-based distributed system for Diabetes Management, developed within in the EU project T-IDDM.