CytoAccess, a relational laboratory information management system for a clinical cytogenetics laboratory

We developed a CytoAccess laboratory management system based on the widely used Microsoft Access software to facilitate data processing, result reporting, and quality management for a full-service cytogenetics laboratory. The CytoAccess system consists of four functional modules. The data entry module is for logging in patient information. The result entry module is used to generate chromosome, fluorescent in situ hybridization (FISH), and array comparative genomic hybridization (aCGH) reports. The administrative module enables periodic monitoring of quality control and quality improvement (QA/QI) parameters and produces billing forms. The maintenance module allows users to update clinical demographics, report templates, code tables, and to refresh data links. We have integrated into this system over 15,000 chromosome and FISH results from prenatal, postnatal, and cancer cases for the past six years. This system is cost-effective, user-friendly, flexible in updating, and potentially adaptable for data mining.     

Management of Evolving Map Data: Data Structures and Algorithms Based on the Framework Map

A consensus framework map of a chromosome is the single most useful map of the chromosome, because of the amount of information it holds as well as the quality of the supporting data backing the putative order of its objects. We describe data structures and algorithms to assist in framework map maintenance and to answer queries about order and distance on genomic objects. We show how these algorithms are efficiently implemented in a client-server relational database. We believe that our data structures are particularly suitable for databases to support collaborative mapping efforts that use heterogeneous methodologies. We summarize two applications that use these algorithms: CHROMINFO, a database specifically designed for framework map maintenance; and the shared client-server database for the chromosome 12 genome center.     

Does Plant Species Richness Guarantee the Resilience of Local Medical Systems? A Perspective from Utilitarian Redundancy

Resilience is related to the ability of a system to adjust to disturbances. The Utilitarian Redundancy Model has emerged as a tool for investigating the resilience of local medical systems. The model determines the use of species richness for the same therapeutic function as a facilitator of the maintenance of these systems. However, predictions generated from this model have not yet been tested, and a lack of variables exists for deeper analyses of resilience. This study aims to address gaps in the Utilitarian Redundancy Model and to investigate the resilience of two medical systems in the Brazilian semi-arid zone. As a local illness is not always perceived in the same way that biomedicine recognizes, the term “therapeutic targets” is used for perceived illnesses. Semi-structured interviews with local experts were conducted using the free-listing technique to collect data on known medicinal plants, usage preferences, use of redundant species, characteristics of therapeutic targets, and the perceived severity for each target. Additionally, participatory workshops were conducted to determine the frequency of targets. The medical systems showed high species richness but low levels of species redundancy. However, if redundancy was present, it was the primary factor responsible for the maintenance of system functions. Species richness was positively associated with therapeutic target frequencies and negatively related to target severity. Moreover, information about redundant species seems to be largely idiosyncratic; this finding raises questions about the importance of redundancy for resilience. We stress the Utilitarian Redundancy Model as an interesting tool to be used in studies of resilience, but we emphasize that it must consider the distribution of redundancy in terms of the treatment of important illnesses and the sharing of information. This study has identified aspects of the higher and lower vulnerabilities of medical systems, adding variables that should be considered along with richness and redundancy.     

Integration of a barcode reader with a commercial flow cytometer.

This report describes the application and installation of a barcode reader on a standard EPICS Elite flow cytometer. The barcode reader system eliminates keyboard entry of sample information on the cytometer. The system automates the transfer of sample information already present in our laboratory database to the cytometer at run time. The system uses a standard "off-the-shelf" bar code wand with a personal computer keyboard interface and requires no additional software at run time. No typing of sample information is required by the operator at any stage of normal sample operation at the cytometer. All operations are automatically coded into the cytometry software using the macro functions of the software. Tubes are inserted into the tube reader and sample information is transferred automatically into the cytometer. We have found that the system allows rapid and continuous operation of routine clinical and research samples. This automated data entry also reduces the possibility of data input errors.     

Communications between bone cells and hematopoietic stem cells

The skeletal system, while characterized by a hard tissue component, is in fact an extraordinarily dynamic system, with disparate functions ranging from structural support, movement and locomotion and soft-organ protection, to the maintenance of calcium homeostasis. Amongst these functions, it has long been known that mammalian bones house definitive hematopoiesis. In fact, several data demonstrate that the bone microenvironment provides essential regulatory cues to the hematopoietic system. In particular, interactions between the bone-forming cells, or osteoblasts, and the most primitive Hematopoietic Stem Cells (HSC) have recently been defined. This review will focus mainly on the role of osteoblasts as HSC regulatory cells, discussing the signaling mechanisms and molecules currently thought to be involved in their modulation of HSC behavior. We will then review additional cellular components of the HSC niche, including endothelial cells and osteoclasts. Finally, we will discuss the potential clinical implications of our emerging understanding of the complex HSC microenvironment.     

全球外来入侵生物与植物有害生物数据库的比较评价

[目的]为了明确全球生物安全与植物保护领域内数据库建设进展和我国数据库的建设成效,对全球重要的外来入侵生物与植物有害生物数据库进行分类介绍和比较评价研究.[方法]根据数据库收录物种的地理范围、类群及数据库特色功能,对数据库进行分类.对重要数据库的主要功能进行简要介绍,设立多指标评价体系将我国数据库与国际优质数据库进行比...     

Integrated software system for improving medical equipment management

The evolution of biomedical technology has led to an extraordinary use of medical devices in health care delivery. During the last decade, clinical engineering departments (CEDs) turned toward computerization and application of specific software systems for medical equipment management in order to improve their services and monitor outcomes. Recently, much emphasis has been given to patient safety. Through its Medical Device Directives, the European Union has required all member nations to use a vigilance system to prevent the reoccurrence of adverse events that could lead to injuries or death of patients or personnel as a result of equipment malfunction or improper use. The World Health Organization also has made this issue a high priority and has prepared a number of actions and recommendations. In the present workplace, a new integrated, Windows-oriented system is proposed, addressing all tasks of CEDs but also offering a global approach to their management needs, including vigilance. The system architecture is based on a star model, consisting of a central core module and peripheral units. Its development has been based on the integration of 3 software modules, each one addressing specific predefined tasks. The main features of this system include equipment acquisition and replacement management, inventory archiving and monitoring, follow up on scheduled maintenance, corrective maintenance, user training, data analysis, and reports. It also incorporates vigilance monitoring and information exchange for adverse events, together with a specific application for quality-control procedures. The system offers clinical engineers the ability to monitor and evaluate the quality and cost-effectiveness of the service provided by means of quality and cost indicators. Particular emphasis has been placed on the use of harmonized standards with regard to medical device nomenclature and classification. The system's practical applications have been demonstrated through a pilot evaluation trial.     

Physiology of immune response genes

In addition to performing its major physiological function--a control of the immune response, the major gene complex: HLA system, also maintains a human genetic diversity. The latter provides optimal conditions for survival of human being as species. We submit modern data on genome and proteome mechanisms which are principal for maintenance of these functions.     

处理植物分类学描述语言的国际标准——DELTA系统

DELTA系统是澳大利亚Dallwitz等人经过多年研究发出的一套用于分类学描述语言编码的国际标准。本文对该系统的主要功能,即自然语言描述、检索表、数据矩阵的自动生成、标本鉴定和信息检索以及分支分类运算和表征分类运算所需数据格式的转换等做了综述性介绍,以期促进该软件在我国广大植物分类学工作者中的推广与使用。     

Portable Optical Epidural Needle-A CMOS-Based System Solution and Its Circuit Design

Epidural anesthesia is a common anesthesia method yet up to 10% of procedures fail to provide adequate analgesia. This is usually due to misinterpreting the tactile information derived from the advancing needle through the complex tissue planes. Incorrect placement also can cause dural puncture and neural injury. We developed an optic system capable of reliably identifying tissue planes surrounding the epidural space. However the new technology was too large and cumbersome for practical clinical use. We present a miniaturized version of our optic system using chip technology (first generation CMOS-based system) for logic functions. The new system was connected to an alarm that was triggered once the optic properties of the epidural were identified. The aims of this study were to test our miniaturized system in a porcine model and describe the technology to build this new clinical tool. Our system was tested in a porcine model and identified the epidural space in the lumbar, low and high thoracic regions of the spine. The new technology identified the epidural space in all but 1 of 46 attempts. Experimental results from our fabricated integrated circuit and animal study show the new tool has future clinical potential.     

Analysis and understanding of high-dimensionality data by means of multivariate data analysis

Multivariate analysis such as principal-components analysis (PCA) and partial-least-squares-discriminant analysis (PLS-DA) have been applied to peptidomics data from clinical urine samples subjected to LC/MS analysis. We show that it is possible to use these methods to get information from a complex set of clinical data. The aim of the work is to use this information as a first step in the further search for clinical biomarker data. It is possible to identify peptide-biomarker fingerprints related to disease diagnosis and progression. Further, we review clinical proteomics and pharmacogenomics data analyzed with the same multivariate approach.     

Whither genomics?

The flood of data from genome-wide analysis is transforming biology. We need to develop new, interdisciplinary approaches to convert these data into information about the components and structures of individual biological pathways and to use the resulting information to yield knowledge about general principles that explain the functions and evolution of life.     

A preliminary approach to creating an overview of lactoferrin multi-functionality utilizing a text mining method

Lactoferrin is a multi-functional metal-binding glycoprotein that exhibits many biological functions of interest to many researchers from the fields of clinical medicine, dentistry, pharmacology, veterinary medicine, nutrition and milk science. To date, a number of academic reports concerning the biological activities of lactoferrin have been published and are easily accessible through public data repositories. However, as the literature is expanding daily, this presents challenges in understanding the larger picture of lactoferrin function and mechanisms. In order to overcome the “analysis paralysis” associated with lactoferrin information, we attempted to apply a text mining method to the accumulated lactoferrin literature. To this end, we used the information extraction system GENPAC (provided by Nalapro Technologies Inc., Tokyo). This information extraction system uses natural language processing and text mining technology. This system analyzes the sentences and titles from abstracts stored in the PubMed database, and can automatically extract binary relations that consist of interactions between genes/proteins, chemicals and diseases/functions. We expect that such information visualization analysis will be useful in determining novel relationships among a multitude of lactoferrin functions and mechanisms. We have demonstrated the utilization of this method to find pathways of lactoferrin participation in neovascularization, Helicobacter pylori attack on gastric mucosa, atopic dermatitis and lipid metabolism.     

On-line integration of computer controlled diagnostic devices and medical information systems in undergraduate medical physics education for physicians

We designed and evaluated an innovative computer-aided-learning environment based on the on-line integration of computer controlled medical diagnostic devices and a medical information system for use in the preclinical medical physics education of medical students. Our learning system simulates the actual clinical environment in a hospital or primary care unit. It uses a commercial medical information system for on-line storage and processing of clinical type data acquired during physics laboratory classes. Every student adopts two roles, the role of ‘patient’ and the role of ‘physician’. As a ‘physician’ the student operates the medical devices to clinically assess ‘patient’ colleagues and records all results in an electronic ‘patient’ record. We also introduced an innovative approach to the use of supportive education materials, based on the methods of adaptive e-learning. A survey of student feedback is included and statistically evaluated.The results from the student feedback confirm the positive response of the latter to this novel implementation of medical physics and informatics in preclinical education. This approach not only significantly improves learning of medical physics and informatics skills but has the added advantage that it facilitates students’ transition from preclinical to clinical subjects.     

From Data to Decisions: Helping Crop Producers Build Their Actionable Knowledge

Recent advances in distributed information technologies are providing the means to capture and process abundant data, and to reveal associations between variables describing the crop-environment-management interaction. This review describes the determinants and moderating factors influencing how much value a crop producer and his or her advisor can derive from data, and information derived from data. We describe the social, technological, and entrepreneurial processes needed to progress the nonlinear pathway from data to an on-farm decision, and explore the meaning of actionable knowledge; that is, knowledge that can be acted upon and applied to solve a real-world problem. We argue that effective decision support is also a system that supports the learning needs of crop producers and their transactions with trusted advisors. Crop protection, the sub-set of crop management used to mitigate crop loss, is used to illustrate current approaches and technologies to support farmers' decisions. We describe how situational awareness and actionable knowledge could be improved through use of emerging platform technologies, advances in artificial intelligence, consideration of farmer decision style, knowledge capture and maintenance, and embedding technology in human-centered services. Implications for the conduct of research and development are discussed.     

Efficient and accurate experimental design for enzyme kinetics: Bayesian studies reveal a systematic approach

In areas such as drug development, clinical diagnosis and biotechnology research, acquiring details about the kinetic parameters of enzymes is crucial. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. We demonstrate that a Bayesian approach (the use of prior knowledge) can produce major gains quantifiable in terms of information, productivity and accuracy of each experiment. Developing the use of Bayesian Utility functions, we have used a systematic method to identify the optimum experimental designs for a number of kinetic model data sets. This has enabled the identification of trends between kinetic model types, sets of design rules and the key conclusion that such designs should be based on some prior knowledge of K(M) and/or the kinetic model. We suggest an optimal and iterative method for selecting features of the design such as the substrate range, number of measurements and choice of intermediate points. The final design collects data suitable for accurate modelling and analysis and minimises the error in the parameters estimated.     

From inverse problems in mathematical physiology to quantitative differential diagnoses

The improved capacity to acquire quantitative data in a clinical setting has generally failed to improve outcomes in acutely ill patients, suggesting a need for advances in computer-supported data interpretation and decision making. In particular, the application of mathematical models of experimentally elucidated physiological mechanisms could augment the interpretation of quantitative, patient-specific information and help to better target therapy. Yet, such models are typically complex and nonlinear, a reality that often precludes the identification of unique parameters and states of the model that best represent available data. Hypothesizing that this non-uniqueness can convey useful information, we implemented a simplified simulation of a common differential diagnostic process (hypotension in an acute care setting), using a combination of a mathematical model of the cardiovascular system, a stochastic measurement model, and Bayesian inference techniques to quantify parameter and state uncertainty. The output of this procedure is a probability density function on the space of model parameters and initial conditions for a particular patient, based on prior population information together with patient-specific clinical observations. We show that multimodal posterior probability density functions arise naturally, even when unimodal and uninformative priors are used. The peaks of these densities correspond to clinically relevant differential diagnoses and can, in the simplified simulation setting, be constrained to a single diagnosis by assimilating additional observations from dynamical interventions (e.g., fluid challenge). We conclude that the ill-posedness of the inverse problem in quantitative physiology is not merely a technical obstacle, but rather reflects clinical reality and, when addressed adequately in the solution process, provides a novel link between mathematically described physiological knowledge and the clinical concept of differential diagnoses. We outline possible steps toward translating this computational approach to the bedside, to supplement today's evidence-based medicine with a quantitatively founded model-based medicine that integrates mechanistic knowledge with patient-specific information.     

Textmining in support of knowledge discovery for vaccine development

Complete genome data of infectious microorganisms permit systematic computational sequence-based predictions and experimental testing of candidate vaccine epitopes. Both, predictions and the interpretation of experiments rely on existing information in the literature which is mostly manually extracted and curated. The growing amount of data and literature information has created a major bottleneck for the interpretation of results and maintenance of curated databases. The lack of suitable free-text information extraction, processing, and reporting tools prompted us to develop a knowledge discovery support system that enhances the understanding of immune response and vaccine development. The current prototype system, Gene expression/epitpopes/protein interaction (GEpi), focuses on molecular functions of HIV-infected T-cells and HIV epitope information, using textmining, and interrelation of biomolecular data from domain-specific databases with MEDLINE abstract-inferred information. Results showed that extraction and processing of molecular interaction, disease associations, and gene ontology-derived functional information generate intuitive knowledge reports that aid the interpretation of host-pathogen interaction. In contrast, epitope (word and sequence) information in MEDLINE abstracts is surprisingly sparse and often lacks necessary context information, such as HLA-restriction. Since the majority of epitope information is found in tables, figures, and legends of full-text articles, its extraction may not require sophisticated natural language processing techniques. Support of vaccine development through textmining requires therefore the timely development of domain-specific extraction rules for full-text articles, and a knowledge model for epitope-related information.     

DIG-1, a novel giant protein, non-autonomously mediates maintenance of nervous system architecture

Dedicated mechanisms exist to maintain the architecture of an animal's nervous system after development is completed. To date, three immunoglobulin superfamily members have been implicated in this process in the nematode Caenorhabditis elegans: the secreted two-Ig domain protein ZIG-4, the FGF receptor EGL-15 and the L1-like SAX-7 protein. These proteins provide crucial information for neuronal structures, such as axons, that allows them to maintain the precise position they acquired during development. Yet, how widespread this mechanism is throughout the nervous system, and what other types of factors underlie such a maintenance mechanism, remains poorly understood. Here, we describe a new maintenance gene, dig-1, that encodes a predicted giant secreted protein containing a large number of protein interaction domains. With 13,100 amino acids, the DIG-1 protein is the largest secreted protein identifiable in any genome database. dig-1 functions post-developmentally to maintain axons and cell bodies in place within axonal fascicles and ganglia. The failure to maintain axon and cell body position is accompanied by defects in basement membrane structure, as evidenced by electron microscopy analysis of dig-1 mutants. Expression pattern and mosaic analysis reveals that dig-1 is produced by muscles to maintain nervous system architecture, demonstrating that dig-1 functions non-autonomously to preserve the proper layout of neural structures. We propose that DIG-1 is a component of the basement membrane that mediates specific contacts between cellular surfaces and their environment through the interaction with a cell-type specific set of other maintenance factors.