Biomedical is biological application for human in pathological condition. More specifically, the biology applied for analysis of samples from blood or other biological products to contribute to the diagnosis as well as monitoring and treatment
Research, Biomedical

Introduction: Biomedical research has traditionally been the domain of developed countries. We aim to study the effects of the increased focus on biomedical and medical research on level 1-4 publications in several industrialised and newly industrialised countries endowed with petroleum and gas resources. Methods: We identified all level 1-4 publications from 01/01/1994 to 31/12/2013 via PubMed using advanced options. The population and GDP (current US$) data from 1994-2013 were obtained through data provided by the World Bank and the raw data was normalised based on these two indicators. Results: From 1994-2013, Saudi Arabia and Malaysia were responsible for the highest absolute number of level 1 to 4 biomedical and medical research publications with 2551 and 1951 publications respectively. When normalised to population, Kuwait and Qatar had the highest publication rates, with 7.84 and 3.99 publications per 100,000 inhabitants respectively in a five yearly average. Kuwait produced the largest number of publications per billion (current US$) of GDP, at 2.92 publications, followed by Malaysia at 2.82 publications in a five yearly average. Conclusion: The population size of a country as well as GDP can influence the number of level 1-4 publications in some countries. More importantly, effective government policy which stimulates research as well as a culture which actively promotes research as shown by Malaysia have proven to have a larger influence on the amount of level 1-4 biomedical and medical publications.
Biomedical Research

Current clinical evaluation of literature quality has various ways. Most of them lay special emphasis on the evaluation of the design quality, but the evaluation of the implementation process quality is not perfect. Especially data management is not fully emphasized during the enforcement of clinical trials. Data from clinical research were bases for evaluating clinical findings. Although strict specifications and requirements for data management might be strictly written clearly in research protocols, they were not embodied in current clinical research evidence evaluation system. Data management is an important part of implementing the whole clinical trial process, which is a comprehensive reflection of data collecting, logging, sorting, and managing. Its objective is to obtain high quality research data for statistical analysis, thereby coming to a true and reliable conclusion. In order to overall evaluating clinical design and implement, we suggest that present quality evaluation indicators of clinical trails should be completed, and add data management quality evaluation during the whole implement process. Data management plans, standards and requirements for data checking, and management regulations for disobeying data and exception data should be added in quality evaluation indicators for clinical research evidence. The effect of data management quality on clinical research evidence evaluation should be emphasized.
Biomedical Research ; Humans ; Research Design

The microarrays have revolutionised biomedical experimentation and diagnostics, enabling ordered high throughput analysis. During the past decade, classic solid phase substrates, such as microlitre plates, membrane filters and microscopic slides, were turn into high-density, chip-like structure. The concept of the arrayed library was central to this development which now extends from DNA to protein. The availability of such protein microarrays would facilitate the simultaneous analysis of thousands of interactions within a single experiment. They can be utilized for massively parallel testing of protein function or recognized their target polypeptide in complex biological solution. This article will focus on the current strategies used to generate protein microarray and their applications in biological research, medicine and diagnostics.
Biomedical Research ; Proteins ; analysis

No abstract available.
Biomedical Research ; Knowledge

Biomedical Research ; Publishing

Publication biases and collection limitations are the main disadvantages of a traditional meta-analysis based on aggregate patient data (APD) from published articles. Individual patient data (IPD) meta-analysis, as the gold standard of systematic review, is a possible alternative in this context. However, the publications relative to IPD meta-analyses are still rare compared with the traditional ones, especially in the research oriented to Chinese medicine (CM). In this article, the strengths and detailed functioning of IPD meta-analysis are described. Furthermore, the need for IPD meta-analysis to assess the treatments based on CM was also discussed. Compared with the traditional APD meta-analysis, the IPD meta-analysis might give a more accurate and unbiased assessment and is worth to be recommended to CM researchers.
Biomedical Research ; Humans ; Patients

Organoids ; Biomedical Research

Fractal, a mathematics concept, is used to describe an image of self-similarity and scale invariance. Some organisms have been discovered with the fractal characteristics, such as cerebral cortex surface, retinal vessel structure, cardiovascular network, and trabecular bone, etc. It has been preliminarily confirmed that the three-dimensional structure of cells cultured in vitro could be significantly enhanced by bionic fractal surface. Moreover, fractal theory in clinical research will help early diagnosis and treatment of diseases, reducing the patient's pain and suffering. The development process of diseases in the human body can be expressed by the fractal theories parameter. It is of considerable significance to retrospectively review the preparation and application of fractal surface and its diagnostic value in medicine. This paper gives an application of fractal and its theories in the medical science, based on the research achievements in our laboratory.
Biomedical Research ; Bionics ; Fractals ; Humans

Biomedical Research ; Humans ; Tai Ji