scholarly journals CRISPR Editing Technology in Biological and Biomedical Investigation

2017 ◽  
Vol 118 (11) ◽  
pp. 3586-3594 ◽  
Author(s):  
Martyn K. White ◽  
Rafal Kaminski ◽  
Won‐Bin Young ◽  
Pamela C. Roehm ◽  
Kamel Khalili
2018 ◽  
Vol 77 (15) ◽  
pp. 1389-1395 ◽  
Author(s):  
Ya. V. Nosova ◽  
Kh. I. Faruk ◽  
O. G. Avrunin

2018 ◽  
Vol 46 (5) ◽  
pp. 1768-1774 ◽  
Author(s):  
Biswajit Bora ◽  
A. Aguilera ◽  
Jalaj Jain ◽  
Gonzalo Avaria ◽  
Jose Moreno ◽  
...  

2010 ◽  
Vol 56 (1) ◽  
pp. 87-98
Author(s):  
Christopher Armstrong ◽  
Diarmuid Kavanagh ◽  
Sara Lal ◽  
Peter Rossiter

Combining Popular Game Consoles and OSGi to Investigate Autonomous In-The-Field Biomedical Data Acquisition and ManagementThe need and interest in conducting biomedical research outside the traditional laboratory is increasing. In the field testing such as in the participant's home or work environment is a growing consideration when undertaking biomedical investigation. This type of research requires at a minimum semi-autonomous computer systems that collect such data and send it back to the laboratory for processing and dissemination with the smallest amount of attendance by the participant or even the experimenter. A key aspect of supporting this type of research is the selection of the appropriate software and hardware components. These supporting systems need to be reliable, allow considerable customizability and be readily accessible but also able to be locked down. In this paper we report a set of requirements for the hardware and software for such a system. We then utilise these requirements to evaluate the use of game consoles as a hardware platform in comparison to other hardware choices. We finish by outline one particular aspect of the supporting software used to support the chosen hardware platform based on the OSGi framework.


2017 ◽  
Vol 118 (12) ◽  
pp. 4152-4162 ◽  
Author(s):  
Han Zhang ◽  
Nami McCarty

Author(s):  
Steven Forrester

In recent years, biomedical research has faced increased scrutiny over issues related to reproducibility and quality in scientific findings(1-3). In response to this scrutiny, funding institutions and journals have implemented top-down policies for grant and manuscript review. While a positive step forward, the long-term merit of these policies is questionable given their emphasis on completing a check-list of items instead of a fundamental re-assessment of how scientific investigation is conducted. Moreover, the top-down style of management used to institute these policies can be argued as being ineffective in engaging the scientific workforce to act upon these issues. To meet current and future biomedical needs, new investigative methods that emphasize collective-thinking, teamwork, shared knowledge and cultivate change from the bottom-up are warranted. Here, a perspective on a new approach to biomedical investigation within the individual laboratory that emphasizes collaboration and quality is discussed.


2017 ◽  
Vol 63 (5) ◽  
pp. 963-972 ◽  
Author(s):  
John P A Ioannidis ◽  
Patrick M M Bossuyt

Abstract BACKGROUND The large, expanding literature on biomarkers is characterized by almost ubiquitous significant results, with claims about the potential importance, but few of these discovered biomarkers are used in routine clinical care. CONTENT The pipeline of biomarker development includes several specific stages: discovery, validation, clinical translation, evaluation, implementation (and, in the case of nonutility, deimplementation). Each of these stages can be plagued by problems that cause failures of the overall pipeline. Some problems are nonspecific challenges for all biomedical investigation, while others are specific to the peculiarities of biomarker research. Discovery suffers from poor methods and incomplete and selective reporting. External independent validation is limited. Selection for clinical translation is often shaped by nonrational choices. Evaluation is sparse and the clinical utility of many biomarkers remains unknown. The regulatory environment for biomarkers remains weak and guidelines can reach biased or divergent recommendations. Removing inefficient or even harmful biomarkers that have been entrenched in clinical care can meet with major resistance. SUMMARY The current biomarker pipeline is too prone to failures. Consideration of clinical needs should become a starting point for the development of biomarkers. Improvements can include the use of more stringent methodology, better reporting, larger collaborative studies, careful external independent validation, preregistration, rigorous systematic reviews and umbrella reviews, pivotal randomized trials, and implementation and deimplementation studies. Incentives should be aligned toward delivering useful biomarkers.


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