Biomedical Research Articles

New Artificial Neural Network Models for Bio Medical Image Compression

This article presents an image compression method using feed-forward back-propagation neural networks (NNs). Marked progress has been made in the area of image compression in the last decade. Image compression removing redundant information in image data is a solution for storage and data transmission problems for huge amounts of data. NNs offer the potential for providing a novel solution to the problem of image compression by its ability to generate an internal data representation. A comparison among various feed-forward back-propagation training algorithms was presented with different compression ratios and different block sizes. The learning methods, the Levenberg Marquardt (LM) algorithm and the Gradient Descent (GD) have been used to perform the training of the network architecture and finally, the performance is evaluated in terms of MSE and PSNR using medical images. The decompressed results obtained using these two algorithms are computed in terms of PSNR and MSE along with performance plots and regression plots from which it can be observed that the LM algorithm gives more accurate results than the GD algorithm.

Genetic characteristics of coxsackievirus A16 isolated in Shenzhen from 2016 to 2017

Objective To investigate the genetic characteristics of VP1 genes carried by coxsackievirus A16 strains isolated from cases of hand foot and mouth disease (HFMD) in Shenzhen during 2016 to 2017. Methods Fecal and anal swab specimens were collected from patients with mild HFMD in four sentinel hospitals and the Institute of Pathogen Biology, Shenzhen Center for Disease Control and Prevention, China during 2016 to 2017. All specimens were tested for CVA16 viral RNA using real-time RT-PCR. The VP1 genes of 51 randomly selected CVA16 strains were amplified by RT-PCR and then sequenced using TaKaRa Biomedical Technology (Dalian). Bioinformatics software, including Mega6.02, BioEdit and DNAStar, was used for comparison and analysis of the VP1 genes. Results CVA16 strains in Shenzhen during 2016 to 2017 mainly belonged to B1a and B1b subtypes as well as an emerging subtype B3. The epidemic of B1b subtype was found in both 2016 (28 strains) and 2017 (19 strains), while the B1a subtype (two strains) was only detected in 2017. Two B3 subtype strains were detected in 2017. The strains of B1b subtype were closely related to the strains isolated in Shanghai (JQ314149), Wenzhou (KP289416) and Beijing (KU254598), while the B1a subtype strains were closely related to the strains isolated in Kunming (JQ316639) and Tailand (GQ184139). The B3 subtype strain was an emerging CVA16 epidemic strain in mainland China. Further comparison of the CVA16 epidemic strains in Shenzhen area during 2016 to 2017 with the CVA16 strains causing severe neurological symptoms showed that two amino acid mutations (S14N and M23L) were found in VP1 protein. Conclusions The epidemic strains of CVA16 were B1b subtype in Shenzhen area in 2016. However, B1a, B1b and the emerging B3 subtype strains were prevalent in 2017. Compared with the CVA16 strains causing severe neurological symptoms, the CVA16 strains circulating in Shenzhen during 2016 to 2017 carried two amino acid mutations inVP1 protein. Key words: Coxsackievirus A16; Hand, foot and mouth disease; Phylogenetic analysis

Experience in circumcision of children aged 3-6 years under the intervention of modern holistic medical model

Objective Under the intervention of modern holistic medical model, the subjective feelings and objective effects of parents and children in circumcision were studied in children aged 3-6 years. Methods A prospective study was conducted to select 2012 children aged 3 to 6 years who underwent circumcision at the First Affiliated Hospital of Kunming Medical University from August 2013 to May 2017. The patients were divided into control group and experimental group by completely randomized grouping, there were 1 006 cases in each group. The children in the control group were treated with a single biomedical model, which was completed according to the conventional flow-type operation. The children in the experimental group adopted the modern holistic medical model, and the full modern holistic medical model intervention was performed before, during and after the operation. The medical treatment process highlighted the overall humanistic care for the children. The age of the control group was (4.19±1.75) years old, and the age of the children in the experimental group was (4.26±1.68) years old. The operation time, the degree of surgical pain [with the pain visual analogue scale (VAS)], the postoperative complications (including postoperative hemorrhage, penile edema, infection, wound rupture), wound healing time, surgery satisfaction rate and fear level of children were compared between the two groups. Measurement data were expressed as mean±standard deviation (Mean±SD), t-test was used for comparison between groups; Chi-square test was used to compare the count data. Results In the control group, the operation time was (9.26±1.87) min, the surgical pain VAS was (2.59±0.72), postoperative bleeding was 38 (3.8%), severe penile edema was 78 (7.8%), and infection was 12 (1.2%), wound rupture was 32 cases (3.2%), the wound healing time was (20.4±2.56) d, and the surgical satisfaction rate was 67.4%. In the experimental group, the operation time of was (6.15±1.23) min, the surgical pain VAS was (1.71±0.54), postoperative bleeding was 6 cases (0.6%), severe penile edema was 12 cases (1.2%), and infection was 8 cases (0.8%), wound rupture was 2 cases (0.2%), the healing time was (15.2±3.16) d, and the operation satisfaction rate was 98.8%. The operation time, surgical pain VAS, postoperative bleeding, severe penile edema, wound splitting rate, healing time and surgical satisfaction rate were statistically significant (P 0.05). The fear level of children in the experimental group was superior to the control group at levels 0, 1, 2 and 3, the difference was statistically significant (P<0.05). Conclusions Under the intervention of modern holistic medical model, the child′s operation process is smooth, the children and parents have good subjective feelings, no obvious fear, good compliance, high satisfaction, good objective clinical effect, and positively improve the relationship between doctors and patients. The society has won a good reputation and deserves to be promoted clinically. Key words: Child, preschool; Circumcision, male; Modern holistic medical model

Design of a Rule Based Bio Medical Entity Extractor

The field of Biomedical Entity Extraction/ Identification plays a vital role in Bioinformatics and rapidly growing to meet the needs of different text mining tasks. Many biomedical entity extraction tools have been developed so far. This research work has focused to develop a Rule based Biomedical Entity Extraction and tested with PubMed Medline abstracts of Colon cancer and Alzheimer disease categories. The proposed Biomedical Entity Extractor gives promising result when compared with existing tools. The proposed method is incorporating of two phases such as preprocessing the input text document using NLP techniques and create the rules to find out the biomedical entities using regular expression. The results of Rule based Biomedical Entity Extractor are validated with the well-known Biomedical Genia tagger and Genecards Database. The method proposed in this paper almost good as genia tagger. The evaluation results on Colon cancer and Alzheimer disease abstracts corpus of Biomedical Entity Extraction achieve an accuracy of 92% and 88% respectively which identifies more number of entities compared to other existing tools.

Proyectos interuniversitarios y multidisciplinarios relacionados con el patógeno zoonótico Brucella abortus realizados en el CIB

Desde el año 2009, el Centro de Investigación en Biotecnología (CIB) del TEC ha venido desarrollando varios proyectos de investigación interuniversitarios y multidisciplinarios relacionados con la bacteria Brucella abortus. Estos proyectos se hicieron en conjunto con el Programa de Investigación en Enfermedades Tropicales (PIET) de la Escuela de Medicina Veterinaria de la Universidad Nacional (UNA) y el Centro de Investigación en Enfermedades Tropicales (CIET) de la Facultad de Microbiología de la Universidad de Costa Rica (UCR). La mayoría de estos proyectos contaron principalmente con financiamiento de los Fondos Especiales para la Educación Superior (FEES) del Consejo Nacional de Rectores (CONARE). Durante la última década, el financiamiento recibido del FEES, permitió crear y equipar el Laboratorio de Bacteriología en el CIB; realizar trabajos finales de graduación y tesis de licenciatura, maestría y doctorado, en las áreas de biotecnología, microbiología, medicina veterinaria y ciencias biomédicas. También se han publicado artículos científicos en revistas indexadas y se están elaborando manuscritos, como resultado de las tesis doctorales en ejecución.

A Privacy Preserving Approach to Feasibility Analyses on Distributed Data Sources in Biomedical Research.

Funding agencies and field experts promote reuse of scientific data and biomaterial beyond the scope of the original project. The availability of research data, however, is limited by the interest of original authors as well as the privacy rights of the study participants, especially in the biomedical sciences. On the other hand, for an available data set to be a useful contribution to the scientific community, it has to be findable and accessible with reasonable effort. Therefore, using the R Shiny library, we designed and implemented a software for data discovery and feasibility analyses with compliance to regulatory and contractual regulations. Due to its genericity, it was successfully tested with heterogeneous data sets and ultimately applied to the data and biomaterial of the German Center for Cardiovascular Research (DZHK). The resulting tool - named the Feasibility Explorer - is publicly available and can be used by researchers to get an overview of data and biomaterial available in the DZHK and to select collectives in the process of submitting a usage application. To implement the rights of participants and original authors, data is integrated by querying the informed consent and not persistently stored. All calculations on the data are performed server-sided and only aggregated information is send to a client, whereas the extent of information was strictly limited to a necessary minimum that allows an applicant to assess whether an application is worthwhile.

Spreadsheet Model Generator (SMOG): A Lightweight Tool for Object-Spreadsheet Mapping.

In the life science domain, experts are usually familiar with spreadsheet software and often use it in their daily work to collect and structure required domain knowledge. The processing and analysis of spreadsheet data is an important task that must be supported by efficient software solutions. A typical application scenario is for example an integration of spreadsheet data (specified or derived) in an ontology to provide reasoning or search. Different converter tools were developed to support a spreadsheet-to-ontology transformation. Such tools allow often only a relatively simple structure of the spreadsheet template or they require complex mapping processes to map the spreadsheet and ontological entities. In many cases, it is impossible to use the existing converter tools because the spreadsheet data must be processed first before the derived data can be integrated into the ontology. In such cases, an efficient and fast development of customized software solutions is of great importance. In this paper, we present a general spreadsheet processing framework to efficiently read and write spreadsheet data. The Spreadsheet Model Generator (SMOG) provides a simple mechanism to automatically generate the Java object model and mappings between object code and spreadsheet entities. Our solution greatly simplifies the implementation of spreadsheet access methods and enables an efficient development of spreadsheet-based applications. The SMOG has already been used successfully in several biomedical projects under real world conditions.

Protecting Biomedical Data Against Attribute Disclosure.

Modern medical research requires access to patient-level data of significant detail and volume. In this context, privacy concerns and legal requirements demand careful consideration. Data anonymization, which means that data is transformed to reduce privacy risks, is an important building block of data protection concepts. However, common methods of data anonymization often fail to protect data against inference of sensitive attribute values (also called attribute disclosure). Measures against such attacks have been developed, but it has been argued that they are of little practical relevance, as they involve significant data transformations which reduce output data utility to an unacceptable degree. In this article, we present an experimental study of the degree of protection and impact on data utility provided by different approaches for protecting biomedical data from attribute disclosure. We quantified the utility and privacy risks of datasets that have been protected using different anonymization methods and parameterizations. We put the results into relation with trivial baseline approaches, visualized them in the form of risk-utility curves and analyzed basic statistical properties of the sensitive attributes (e.g. the skewness of their distribution). Our results confirm that it is difficult to protect data from attribute disclosure, but they also indicate that it can be possible to achieve reasonable degrees of protection when appropriate methods are chosen based on data characteristics. While it is hard to give general recommendations, the approach presented in this article and the tools that we have used can be helpful for deciding how a given dataset can best be protected in a specific usage scenario.

Clinical application of capsaicin cough challenge test

The capsaicin cough provocation test is the most commonly used test to objectively evaluate cough sensitivity.The mechanism is simple and the test can be accepted by a lot of patients, which could evaluate the degree of cough, guide medicine, promote new drug development, seek for the cause.This article mainly reviews the clinical application of capsaicin cough test to assess degree of cough and guide treatment. Key words: Capsaicin; Diagnostic techniques, respiratory system; Nasal provocation tests; Cough; Technology assessment, biomedical; Diagnosis; Therapeutic uses; Review

Gonadotropin-releasing hormone agonists for the protection of ovarian function in premenopausal patients treated by chemotherapy: a meta-analysis

Objective To evaluate systematically the effectiveness of gonadotropin-releasing hormone agonist (GnRHa) administration before chemotherapy and/or during chemotherapy for the protection of ovarian function in premenopausal women. Methods PubMed, Cochrane Library, Medline, Embase, China Biomedical Literature Database, CNKI were searched to collect the clinical randomized control trail (RCT) of ovarian function protection in premenopausal women receiving chemotherapy by using GnRHa. RevMan5.3 software was used to analyze the incidence of early premature ovarian insufficiency (POI), menstrual recovery rate, pregnancy rate and other indicators. Results A total of 12 articles were included, including a total of 1 509 premenopausal women who received chemotherapy for malignant diseases. GnRHa combined with chemotherapy reduced the incidence of POI (OR = 0.36, 95% CI 0.23-0.56, P < 0.01) and improved the menstrual recovery rate during follow-up (OR = 2.49, 95% CI 1.72-3.60, P < 0.01). GnRHa combined with chemotherapy could increase the pregnancy rate of patients aged 35 years and older (OR = 2.04, 95% CI 1.08-3.83, P = 0.03). Conclusion GnRHa administration before chemotherapy and/or during chemotherapy may prevent the chemotherapy damage to ovarian function, reduce the incidence of POI, and improve the recovery rate of menstruation. Key words: Ovarian function protection; Gonadotropin-releasing hormone agonist; Drug therapy; Premature ovarian insufficiency; Meta-analysis

Training the biomedical workforce for long term career success

Training the biomedical workforce for long term career success

Education in Biomedical and Health Informatics: A European Perspective.

In higher education, programs in specialization in Health Informatics, Medical Informatics, Health Engineering are continuously growing. In this research, almost 1800 universities and colleges were checked in order to find related educational programs at all academic levels. Approximately 1000 academic leading degree programs in those domains have already been identified. The detailed records of the related educational programs will help to understand the current educational needs and priorities. Although, the growth of the related educational programs is not the same in each country.

Multi-task learning using NEural networks for biomedical text mining

Multi-task learning using NEural networks for biomedical text mining

Cardiac Tissue Engineering as Use Case to Connect Biomedical Research Laboratories to an Emerging Global Data Infrastructure.

Methods for cardiac tissue engineering and application in experiments are core technologies developed at the Institute of Pharmacology and Toxicology in Göttingen. As is the case in many academic research laboratories data capture and documentation may be improved to latest methods of digital research. A comprehensive information system infrastructure is the foundation of further advances toward automation of lab processes. A data management system concept is proposed and prototypically deployed that enables traceability of assets within the lab and reproducibility of published assays and results. The prototype integrates existing electronic lab notebook, experiment result database, and a newly introduced research data management system by means of a custom developed portal and integration component. The architecture concept and developed integration tools explore connection of routine experimental work in a biomedical research lab to a universal infrastructure of data.

Design of Biomedical Informatics Framework for Personalized Medicine in Healthcare Organizations.

To implement personalized medicine effectively at organizational level, it is vital to identify, organize, integrate and leverage multi-dimensional patient data from heterogeneous and distributed resources within an organization. This paper presents the design of a novel informatics framework, to identify, organize and integrate patient's clinical, genomics and environmental data from existing clinical and biomedical resources, and to explore how this patient's data can be leveraged by informatics tools to achieve the goal of personalized medicine.

Learning Portuguese Clinical Word Embeddings: A Multi-Specialty and Multi-Institutional Corpus of Clinical Narratives Supporting a Downstream Biomedical Task.

In this paper, we trained a set of Portuguese clinical word embedding models of different granularities from multi-specialty and multi-institutional clinical narrative datasets. Then, we assessed their impact on a downstream biomedical NLP task of Urinary Tract Infection disease identification. Additionally, we intrinsically evaluated our main model using an adapted version of Bio-SimLex for the Portuguese language. Our empirical results showed that the larger, coarse-grained model achieved a slightly better outcome when compared with the small, fine-grained model in the proposed task. Moreover, we obtained satisfactory results with Bio-SimLex intrinsic evaluation.

Biomedical Informatics Workforce in Croatia: Qualitative Analysis of Teachers' Opinions on Needs and Employment Opportunities.

We report a qualitative analysis of higher education biomedical informatics (BMI) teachers' opinions on the needs for BMI workforce and employment opportunities in the Croatian health care system. Needs were perceived as considerable; however this was not coupled with adequate employment opportunities. Barriers were identified to correcting this imbalance, including the failure of the health care system planners to recognise BMI experts as an important part of the workforce and lack of adequate educational opportunities.

IDOMEN: An Extension of Infectious Disease Ontology for MENingitis.

In sub-Saharan African countries the prevention and control of epidemic diseases requires the improvement of the surveillance system for these diseases. Biomedical ontologies are a growing field that can improve health information systems. Indeed biomedical ontologies allow semantic support, data integration, automated reasoning. We are building a meningitis ontology to assist filtering messages relevant to meningitis domain on social media in order to predict a possible epidemic. Indeed, the messages filtered are used for data and event extraction that serve as input for a meningitis surveillance system. In this paper we focused on the modeling and formalization of different perspectives of the meningitis disease such as biological perspective, clinical perspective, epidemiological and public health perspective. This paper presents the three modules in the global Infection Disease Ontology for Meningitis (IDOMEN) and at the end, we illustrate a case of reasoning with our ontology.

Linked Open Data in the Biomedical Information Area: A Keywords Analysis.

The objective of this paper was to determine the extent of the usage of "Linked Open Data" within biomedical literature. Applying PRISMA statement for literature reviews, forty-six papers were included in the analysis and keywords identified. Keywords have been classified according to MeSH categories, when possible. Twenty-three keywords had a frequency > one, 146 keywords had a frequency equal to one. Two MeSH categories were recurring. Future work includes applying association rules learning to keywords.

Web-Based Visualization of MeSH-Based PubMed/MEDLINE Statistics.

Statistical analysis of Medical Subject Headings (MeSH) descriptors to improve biomedical literature search is an active research area. Existing tools have limited interactive visualizations that are accessible to researchers investigating how their hypotheses compare to trends in the research literature. We present a web application that computes and provides an interactive visualization of basic frequencies and co-occurrence statistics of MeSH descriptors associated with a PubMed query.