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Brainwaves over and above medical diagnosis: Wider uses of electroencephalography inside idiopathic generic epilepsy.
ncorporation of drug-drug and drug-food interactions information.The mission of the National Center for Advancing Translational Science (NCATS) is to speed the development of drugs from discovery to approval to dissemination and implementation. The Medical University of South Carolina and the South Carolina Clinical and Translational Research Institute host a NCATS funded predoctoral T32 training grant (TL1) with a focus on translational research. Doctoral (PhD) trainees working at the bench usually have limited opportunity for clinical interactions to gain a clinical perspective on the diseases that are the focus of their dissertation research. To provide TL1 trainees with an opportunity to see how their research could be translated into improved patient care, we developed a mentored clinical exposure experience named the Translational Sciences Clinic. Trainees spend one-half day a week in a clinic related to their basic science research for one semester interacting with patients and clinical mentors and discuss the most recent literature related to the patient's clinical problem with their clinical mentor. Trainees deemed the rotation to be one of the most rewarding experiences that they had as a part of their predoctoral training. Participating clinical mentors were also very enthusiastic and agreed that they would be willing to mentor similar trainees again.
Personalized medicine has exposed wearable sensors as new sources of biomedical data which are expected to accrue annual data storage costs of approximately $7.2 trillion by 2020 (>2000 exabytes). To improve the usability of wearable devices in healthcare, it is necessary to determine the minimum amount of data needed for accurate health assessment.

Here, we present a generalizable optimization framework for determining the minimum necessary sampling rate for wearable sensors and apply our method to determine optimal optical blood volume pulse sampling rate. We implement
-tests, Bland-Altman analysis, and regression-based visualizations to identify optimal sampling rates of wrist-worn optical sensors.

We determine the optimal sampling rate of wrist-worn optical sensors for heart rate and heart rate variability monitoring to be 21-64 Hz, depending on the metric.

Determining the optimal sampling rate allows us to compress biomedical data and reduce storage needs and financial costs. We have used optical heart rate sensors as a case study for the connection between data volumes and resource requirements to develop methodology for determining the optimal sampling rate for clinical relevance that minimizes resource utilization. This methodology is extensible to other wearable sensors.
Determining the optimal sampling rate allows us to compress biomedical data and reduce storage needs and financial costs. read more We have used optical heart rate sensors as a case study for the connection between data volumes and resource requirements to develop methodology for determining the optimal sampling rate for clinical relevance that minimizes resource utilization. This methodology is extensible to other wearable sensors.
Access to cutting-edge technologies is essential for investigators to advance translational research. The Indiana Clinical and Translational Sciences Institute (CTSI) spans three major and preeminent universities, four large academic campuses across the state of Indiana, and is mandate to provide best practices to a whole state.

To address the need to facilitate the availability of innovative technologies to its investigators, the Indiana CTSI implemented the Access Technology Program (ATP). The activities of the ATP, or any program of the Indiana CTSI, are challenged to connect technologies and investigators on the multiple Indiana CTSI campuses by the geographical distances between campuses (1-4 hr driving time).

Herein, we describe the initiatives developed by the ATP to increase the availability of state-of-the-art technologies to its investigators on all Indiana CTSI campuses, and the methods developed by the ATP to bridge the distance between campuses, technologies, and investigators for the advancement of clinical translational research.

The methods and practices described in this publication may inform other approaches to enhance translational research, dissemination, and usage of innovative technologies by translational investigators, especially when distance or multi-campus cultural differences are factors to efficient application.
The methods and practices described in this publication may inform other approaches to enhance translational research, dissemination, and usage of innovative technologies by translational investigators, especially when distance or multi-campus cultural differences are factors to efficient application.
Failure to achieve accrual goals is a common problem in health-related research. Electronic health records represent a promising resource, offering the ability to identify a precisely defined cohort of patients who meet inclusion/exclusion criteria. However, challenges associated with the recruitment process remain and institutional policies vary.

We interviewed researchers, institutional review board chairs, and primary care physicians in North Carolina and Tennessee. Questions focused on strategies for initiating contact with potentially eligible patients, as well as recruitment letters asking recipients to opt in versus opt out of further communication.

When we asked about initiating contact with prospective participants, qualitative themes included trust, credibility, and established relationships; research efficiency and validity; privacy and autonomy; the intersection between research and clinical care; and disruption to physician-researcher and physician-patient relationships. All interviewees saeloping balanced approaches that respect patients and facilitate the advancement of science.
Rigor and reproducibility are two important cornerstones of medical and scientific advancement. Clinical and translational research (CTR) contains four phases (T1-T4), involving the translation of basic research to humans, then to clinical settings, practice, and the population, with the ultimate goal of improving public health. Here we provide a framework for rigorous and reproducible CTR.

In this paper we define CTR, provide general and phase-specific recommendations for improving quality and reproducibility of CTR with emphases on study design, data collection and management, analyses and reporting. We present and discuss aspects of rigor and reproducibility following published examples of CTR from the literature, including one example that shows the development path of different treatments that address anaplastic lymphoma kinase-positive (ALK+) non-small cell lung cancer (NSCLC).

It is particularly important to consider robust and unbiased experimental design and methodology for analysis and interpretation for clinical translation studies to ensure reproducibility before taking the next translational step.
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