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OBJECTIVE - Changes in microvascular perfusion have been reported in many diseases, yet the functional significance of altered perfusion is often difficult to determine. This is partly because commonly used techniques for perfusion measurement often rely on either indirect or by-hand approaches.
METHODS - We developed and validated a fully automated software technique to measure microvascular perfusion in videos acquired by fluorescence microscopy in the mouse gastrocnemius. Acute perfusion responses were recorded following intravenous injections with phenylephrine, SNP, or saline.
RESULTS - Software-measured capillary flow velocity closely correlated with by-hand measured flow velocity (R = 0.91, P < 0.0001). Software estimates of capillary hematocrit also generally agreed with by-hand measurements (R = 0.64, P < 0.0001). Detection limits range from 0 to 2000 μm/s, as compared to an average flow velocity of 326 ± 102 μm/s (mean ± SD) at rest. SNP injection transiently increased capillary flow velocity and hematocrit and made capillary perfusion more steady and homogenous. Phenylephrine injection had the opposite effect in all metrics. Saline injection transiently decreased capillary flow velocity and hematocrit without influencing flow distribution or stability. All perfusion metrics were temporally stable without intervention.
CONCLUSIONS - These results demonstrate a novel and sensitive technique for reproducible, user-independent quantification of microvascular perfusion.
© 2018 John Wiley & Sons Ltd.
OBJECTIVES - Registry-based clinical research in nephrolithiasis is critical to advancing quality in urinary stone disease management and ultimately reducing stone recurrence. A need exists to develop Health Insurance Portability and Accountability Act (HIPAA)-compliant registries that comprise integrated electronic health record (EHR) data using prospectively defined variables. An EHR-based standardized patient database-the Registry for Stones of the Kidney and Ureter (ReSKU™)-was developed, and herein we describe our implementation outcomes.
MATERIALS AND METHODS - Interviews with academic and community endourologists in the United States, Canada, China, and Japan identified demographic, intraoperative, and perioperative variables to populate our registry. Variables were incorporated into a HIPAA-compliant Research Electronic Data Capture database linked to text prompts and registration data within the Epic EHR platform. Specific data collection instruments supporting New patient, Surgery, Postoperative, and Follow-up clinical encounters were created within Epic to facilitate automated data extraction into ReSKU.
RESULTS - The number of variables within each instrument includes the following: New patient-60, Surgery-80, Postoperative-64, and Follow-up-64. With manual data entry, the mean times to complete each of the clinic-based instruments were (minutes) as follows: New patient-12.06 ± 2.30, Postoperative-7.18 ± 1.02, and Follow-up-8.10 ± 0.58. These times were significantly reduced with the use of ReSKU structured clinic note templates to the following: New patient-4.09 ± 1.73, Postoperative-1.41 ± 0.41, and Follow-up-0.79 ± 0.38. With automated data extraction from Epic, manual entry is obviated.
CONCLUSIONS - ReSKU is a longitudinal prospective nephrolithiasis registry that integrates EHR data, lowering the barriers to performing high quality clinical research and quality outcome assessments in urinary stone disease.
Numerous compounds stimulate rodent β-cell proliferation; however, translating these findings to human β-cells remains a challenge. To examine human β-cell proliferation in response to such compounds, we developed a medium-throughput in vitro method of quantifying adult human β-cell proliferation markers. This method is based on high-content imaging of dispersed islet cells seeded in 384-well plates and automated cell counting that identifies fluorescently labeled β-cells with high specificity using both nuclear and cytoplasmic markers. β-Cells from each donor were assessed for their function and ability to enter the cell cycle by cotransduction with adenoviruses encoding cell cycle regulators cdk6 and cyclin D3. Using this approach, we tested 12 previously identified mitogens, including neurotransmitters, hormones, growth factors, and molecules, involved in adenosine and Tgf-1β signaling. Each compound was tested in a wide concentration range either in the presence of basal (5 mM) or high (11 mM) glucose. Treatment with the control compound harmine, a Dyrk1a inhibitor, led to a significant increase in Ki-67 β-cells, whereas treatment with other compounds had limited to no effect on human β-cell proliferation. This new scalable approach reduces the time and effort required for sensitive and specific evaluation of human β-cell proliferation, thus allowing for increased testing of candidate human β-cell mitogens.
An open-source hyperpolarizer producing (13)C hyperpolarized contrast agents using parahydrogen induced polarization (PHIP) for biomedical and other applications is presented. This PHIP hyperpolarizer utilizes an Arduino microcontroller in conjunction with a readily modified graphical user interface written in the open-source processing software environment to completely control the PHIP hyperpolarization process including remotely triggering an NMR spectrometer for efficient production of payloads of hyperpolarized contrast agent and in situ quality assurance of the produced hyperpolarization. Key advantages of this hyperpolarizer include: (i) use of open-source software and hardware seamlessly allowing for replication and further improvement as well as readily customizable integration with other NMR spectrometers or MRI scanners (i.e., this is a multiplatform design), (ii) relatively low cost and robustness, and (iii) in situ detection capability and complete automation. The device performance is demonstrated by production of a dose (∼2-3 mL) of hyperpolarized (13)C-succinate with %P13C ∼ 28% and 30 mM concentration and (13)C-phospholactate at %P13C ∼ 15% and 25 mM concentration in aqueous medium. These contrast agents are used for ultrafast molecular imaging and spectroscopy at 4.7 and 0.0475 T. In particular, the conversion of hyperpolarized (13)C-phospholactate to (13)C-lactate in vivo is used here to demonstrate the feasibility of ultrafast multislice (13)C MRI after tail vein injection of hyperpolarized (13)C-phospholactate in mice.
BACKGROUND - Aversive olfactory classical conditioning has been the standard method to assess Drosophila learning and memory behavior for decades, yet training and testing are conducted manually under exceedingly labor-intensive conditions. To overcome this severe limitation, a fully automated, inexpensive system has been developed, which allows accurate and efficient Pavlovian associative learning/memory analyses for high-throughput pharmacological and genetic studies.
NEW METHOD - The automated system employs a linear actuator coupled to an odorant T-maze with airflow-mediated transfer of animals between training and testing stages. Odorant, airflow and electrical shock delivery are automatically administered and monitored during training trials. Control software allows operator-input variables to define parameters of Drosophila learning, short-term memory and long-term memory assays.
RESULTS - The approach allows accurate learning/memory determinations with operational fail-safes. Automated learning indices (immediately post-training) and memory indices (after 24h) are comparable to traditional manual experiments, while minimizing experimenter involvement.
COMPARISON WITH EXISTING METHODS - The automated system provides vast improvements over labor-intensive manual approaches with no experimenter involvement required during either training or testing phases. It provides quality control tracking of airflow rates, odorant delivery and electrical shock treatments, and an expanded platform for high-throughput studies of combinational drug tests and genetic screens. The design uses inexpensive hardware and software for a total cost of ∼$500US, making it affordable to a wide range of investigators.
CONCLUSIONS - This study demonstrates the design, construction and testing of a fully automated Drosophila olfactory classical association apparatus to provide low-labor, high-fidelity, quality-monitored, high-throughput and inexpensive learning and memory behavioral assays.
Copyright © 2015 Elsevier B.V. All rights reserved.
OBJECTIVE - Assessment of medical trainee learning through pre-defined competencies is now commonplace in schools of medicine. We describe a novel electronic advisor system using natural language processing (NLP) to identify two geriatric medicine competencies from medical student clinical notes in the electronic medical record: advance directives (AD) and altered mental status (AMS).
MATERIALS AND METHODS - Clinical notes from third year medical students were processed using a general-purpose NLP system to identify biomedical concepts and their section context. The system analyzed these notes for relevance to AD or AMS and generated custom email alerts to students with embedded supplemental learning material customized to their notes. Recall and precision of the two advisors were evaluated by physician review. Students were given pre and post multiple choice question tests broadly covering geriatrics.
RESULTS - Of 102 students approached, 66 students consented and enrolled. The system sent 393 email alerts to 54 students (82%), including 270 for AD and 123 for AMS. Precision was 100% for AD and 93% for AMS. Recall was 69% for AD and 100% for AMS. Students mentioned ADs for 43 patients, with all mentions occurring after first having received an AD reminder. Students accessed educational links 34 times from the 393 email alerts. There was no difference in pre (mean 62%) and post (mean 60%) test scores.
CONCLUSIONS - The system effectively identified two educational opportunities using NLP applied to clinical notes and demonstrated a small change in student behavior. Use of electronic advisors such as these may provide a scalable model to assess specific competency elements and deliver educational opportunities.
Copyright © 2015 Elsevier Inc. All rights reserved.
Cell-matrix adhesions are of great interest because of their contribution to numerous biological processes, including cell migration, differentiation, proliferation, survival, tissue morphogenesis, wound healing, and tumorigenesis. Adhesions are dynamic structures that are classically defined on two-dimensional (2D) substrates, though the need to analyze adhesions in more physiologic three-dimensional (3D) environments is being increasingly recognized. However, progress has been greatly hampered by the lack of available tools to analyze adhesions in 3D environments. To address this need, we have developed a platform for the automated analysis, segmentation, and tracking of adhesions (PAASTA) based on an open source MATLAB framework, CellAnimation. PAASTA enables the rapid analysis of adhesion dynamics and many other adhesion characteristics, such as lifetime, size, and location, in 3D environments and on traditional 2D substrates. We manually validate PAASTA and utilize it to quantify rate constants for adhesion assembly and disassembly as well as adhesion lifetime and size in 3D matrices. PAASTA will be a valuable tool for characterizing adhesions and for deciphering the molecular mechanisms that regulate adhesion dynamics in 3D environments.
Imaging mass spectrometry (IMS) has become a prime tool for studying the distribution of biomolecules in tissue. Although IMS data sets can become very large, computational methods have made it practically feasible to search these experiments for relevant findings. However, these methods lack access to an important source of information that many human interpretations rely upon: anatomical insight. In this work, we address this need by (1) integrating a curated anatomical data source with an empirically acquired IMS data source, establishing an algorithm-accessible link between them and (2) demonstrating the potential of such an IMS-anatomical atlas link by applying it toward automated anatomical interpretation of ion distributions in tissue. The concept is demonstrated in mouse brain tissue, using the Allen Mouse Brain Atlas as the curated anatomical data source that is linked to MALDI-based IMS experiments. We first develop a method to spatially map the anatomical atlas to the IMS data sets using nonrigid registration techniques. Once a mapping is established, a second computational method, called correlation-based querying, gives an elementary demonstration of the link by delivering basic insight into relationships between ion images and anatomical structures. Finally, a third algorithm moves further beyond both registration and correlation by providing automated anatomical interpretation of ion images. This task is approached as an optimization problem that deconstructs ion distributions as combinations of known anatomical structures. We demonstrate that establishing a link between an IMS experiment and an anatomical atlas enables automated anatomical annotation, which can serve as an important accelerator both for human and machine-guided exploration of IMS experiments.
PURPOSE - Ultrasound (US) overestimates stone size when compared with CT. The purpose of this work was to evaluate the overestimation of stone size with US in an in vitro water bath model and investigate methods to reduce overestimation.
MATERIALS AND METHODS - Ten human stones (3-12 mm) were measured using B-mode (brightness mode) US by a sonographer blinded to the true stone size. Images were captured and compared using both a commercial US machine and software-based research US device. Image gain was adjusted between moderate and high stone intensities, and the transducer-to-stone depth was varied from 6 to 10 cm. A computerized stone-sizing program was developed to outline the stone width based on a grayscale intensity threshold.
RESULTS - Overestimation with the commercial device increased with both gain and depth. Average overestimation at moderate and high gain was 1.9±0.8 and 2.1±0.9 mm, respectively (p=0.6). Overestimation increased an average of 22% with an every 2-cm increase in depth (p=0.02). Overestimation using the research device was 1.5±0.9 mm and did not vary with depth (p=0.28). Overestimation could be reduced to 0.02±1.1 mm (p<0.001) with the computerized stone-sizing program. However, a standardized threshold consistent across depth, system, or system settings could not be resolved.
CONCLUSION - Stone size is consistently overestimated with US. Overestimation increased with increasing depth and gain using the commercial machine. Overestimation was reduced and did not vary with depth, using the software-based US device. The computerized stone-sizing program shows the potential to reduce overestimation by implementing a grayscale intensity threshold for defining the stone size. More work is needed to standardize the approach, but if successful, such an approach could significantly improve stone-sizing accuracy and lead to automation of stone sizing.
β-Cell mass is a parameter commonly measured in studies of islet biology and diabetes. However, the rigorous quantification of pancreatic β-cell mass using conventional histological methods is a time-consuming process. Rapidly evolving virtual slide technology with high-resolution slide scanners and newly developed image analysis tools has the potential to transform β-cell mass measurement. To test the effectiveness and accuracy of this new approach, we assessed pancreata from normal C57Bl/6J mice and from mouse models of β-cell ablation (streptozotocin-treated mice) and β-cell hyperplasia (leptin-deficient mice), using a standardized systematic sampling of pancreatic specimens. Our data indicate that automated analysis of virtual pancreatic slides is highly reliable and yields results consistent with those obtained by conventional morphometric analysis. This new methodology will allow investigators to dramatically reduce the time required for β-cell mass measurement by automating high-resolution image capture and analysis of entire pancreatic sections.