Preliminary Efforts Directed Toward the Detection of Craving of Illicit Substances: The iHeal Project

Many behavioral interventions, whether for the management of chronic pain, overeating, medication adherence, or substance abuse, are ineffective outside of the clinic or office environments in which they are taught. This lack of utility has spawned interest in enabling technologies that are capable of detecting changes in affective state that potentially herald a transition to risky behaviors. We have therefore undertaken the preliminary development of “iHeal”, an innovative constellation of technologies that incorporates artificial intelligence, continuous biophysical monitoring, wireless connectivity, and smartphone computation. In its fully realized form, iHeal can detect developing drug cravings; as a multimedia device, it can also intervene as the cravings develop to prevent drug use. This manuscript describes preliminary data related to the iHeal Project and our experience with its use.United States. American Recovery and Reinvestment Act of 2009National Institutes of Health (U.S.

Oxycodone Ingestion Patterns in Acute Fracture Pain: a Pilot Study Using a Digital Pill

Background: Opioids are prescribed for acute pain as needed, but no data exists on how patients take opioids after discharge from the ED. This places the onus of dosing on the patient and contributes to variable prescribing by ED physicians. ED opioid prescriptions serve as a source for unintentional exposure and contribute to the opioid epidemic. We deployed a digital pill to measure opioid ingestion patterns in individuals discharged after acute fractures. Methods: This pilot study involved individuals without chronic opioid use (i.e. prescribed opioids \u3e 1 week) who were discharged from the ED following acute fracture. Participants were trained to use a digital pill system comprising a single pill (5 mg oxycodone tablet + radiofrequency emitter) and a hip mounted receiver. Upon contact with gastric contents, the digital pill transmitted a radio signal to the receiver, which relayed time of ingestion via cellular 3G signal in real-time to a cloud based server. Participants were instructed to take 1-2 oxycodone digital pills as needed every 8 hours for pain. Participants returned unused medication at orthopedic follow up or 1 week post discharge where any discrepancies between digital pill data and pill counts were reconciled. Results: We enrolled 10 participants (mean age 42). 50% of fractures were managed operatively and 50% were managed nonoperatively. The system recorded ingestions with 85% accuracy. Participants ingested a mean 43 mg oxycodone during the 1 week study period with dose de-escalation occurring after 24 hours. Participants ingested a mean 75.8% of their 1 week total dose in the first 72 hours. 40% of participants stopped taking opioids by 96 hours. 40% of participants remained on opioids 1 week after injury; all required operative treatment. Conclusions: This is the first study to determine opioid ingestion patterns in ED patients discharged with acute fracture pain. Participants self-tapered opioids after 24 hours, most ingestion occurred in the first 72 hours, and a substantial proportion (40%) stopped ingesting oxycodone by 96 hours. Our data shows individuals may require less opioid analgesics than previously considered for acute fracture pain. Additional studies should address ingestion patterns in other painful conditions and development of ED-based interventions to minimize outpatient opioid use while controlling pain

Digital Pills to Measure Opioid Ingestion Patterns in Emergency Department Patients With Acute Fracture Pain: A Pilot Study

BACKGROUND: Nonadherence to prescribed regimens for opioid analgesic agents contributes to increasing opioid abuse and overdose death. Opioids are frequently prescribed on an as-needed basis, placing the responsibility to determine opioid dose and frequency with the patient. There is wide variability in physician prescribing patterns because of the lack of data describing how patients actually use as-needed opioid analgesics. Digital pill systems have a radiofrequency emitter that directly measures medication ingestion events, and they provide an opportunity to discover the dose, timing, and duration of opioid therapy. OBJECTIVE: The purpose of this study was to determine the feasibility of a novel digital pill system to measure as-needed opioid ingestion patterns in patients discharged from the emergency department (ED) after an acute bony fracture. METHODS: We used a digital pill with individuals who presented to a teaching hospital ED with an acute extremity fracture. The digital pill consisted of a digital radiofrequency emitter within a standard gelatin capsule that encapsulated an oxycodone tablet. When ingested, the gastric chloride ion gradient activated the digital pill, transmitting a radiofrequency signal that was received by a hip-worn receiver, which then transmitted the ingestion data to a cloud-based server. After a brief, hands-on training session in the ED, study participants were discharged home and used the digital pill system to ingest oxycodone prescribed as needed for pain for one week. We conducted pill counts to verify digital pill data and open-ended interviews with participants at their follow-up appointment with orthopedics or at one week after enrollment in the study to determine the knowledge, attitudes, beliefs, and practices regarding digital pills. We analyzed open-ended interviews using applied thematic analysis. RESULTS: We recruited 10 study participants and recorded 96 ingestion events (87.3%, 96/110 accuracy). Study participants reported being able to operate all aspects of the digital pill system after their training. Two participants stopped using the digital pill, reporting they were in too much pain to focus on the novel technology. The digital pill system detected multiple simultaneous ingestion events by the digital pill system. Participants ingested a mean 8 (SD 5) digital pills during the study period and four participants continued on opioids at the end of the study period. After interacting with the digital pill system in the real world, participants found the system highly acceptable (80%, 8/10) and reported a willingness to continue to use a digital pill to improve medication adherence monitoring (90%, 9/10). CONCLUSIONS: The digital pill is a feasible method to measure real-time opioid ingestion patterns in individuals with acute pain and to develop real-time interventions if opioid abuse is detected. Deploying digital pills is possible through the ED with a short instructional course. Patients who used the digital pill accepted the technology

Real-Time Mobile Detection of Drug Use with Wearable Biosensors: A Pilot Study

While reliable detection of illicit drug use is paramount to the field of addiction, current methods involving self-report and urine drug screens have substantial limitations that hinder their utility. Wearable biosensors may fill a void by providing valuable objective data regarding the timing and contexts of drug use. This is a preliminary observational study of four emergency department patients receiving parenteral opioids and one individual using cocaine in a natural environment. A portable biosensor was placed on the inner wrist of each subject, to continuously measure electrodermal activity (EDA), skin temperature, and acceleration. Data were continuously recorded for at least 5 min prior to drug administration, during administration, and for at least 30 min afterward. Overall trends in biophysiometric parameters were assessed. Injection of opioids and cocaine use were associated with rises in EDA. Cocaine injection was also associated with a decrease in skin temperature. Opioid tolerance appeared to be associated with a blunted physiologic response as measured by the biosensor. Laterality may be an important factor, as magnitude of response varied between dominant and nondominant wrists in a single patient with bilateral wrist measurements. Changes in EDA and skin temperature are temporally associated with intravenous administration of opioids and cocaine; the intensity of response, however, may vary depending on history and extent of prior use.University of Massachusetts Medical School. Department of Emergency MedicineNational Institute on Drug AbuseNational Institutes of Health (U.S.) (Grant R01DA033769-01

Joint analysis of stressors and ecosystem services to enhance restoration effectiveness

With increasing pressure placed on natural systems by growing human populations, both scientists and resource managers need a better understanding of the relationships between cumulative stress from human activities and valued ecosystem services. Societies often seek to mitigate threats to these services through large-scale, costly restoration projects, such as the over one billion dollar Great Lakes Restoration Initiative currently underway. To help inform these efforts, we merged high-resolution spatial analyses of environmental stressors with mapping of ecosystem services for all five Great Lakes. Cumulative ecosystem stress is highest in near-shore habitats, but also extends offshore in Lakes Erie, Ontario, and Michigan. Variation in cumulative stress is driven largely by spatial concordance among multiple stressors, indicating the importance of considering all stressors when planning restoration activities. In addition, highly stressed areas reflect numerous different combinations of stressors rather than a single suite of problems, suggesting that a detailed understanding of the stressors needing alleviation could improve restoration planning. We also find that many important areas for fisheries and recreation are subject to high stress, indicating that ecosystem degradation could be threatening key services. Current restoration efforts have targeted high-stress sites almost exclusively, but generally without knowledge of the full range of stressors affecting these locations or differences among sites in service provisioning. Our results demonstrate that joint spatial analysis of stressors and ecosystem services can provide a critical foundation for maximizing social and ecological benefits from restoration investments. www.pnas.org/lookup/suppl/doi:10.1073/pnas.1213841110/-/DCSupplementa

The Impossibility of a Perfectly Competitive Labor Market

Using the institutional theory of transaction cost, I demonstrate that the assumptions of the competitive labor market model are internally contradictory and lead to the conclusion that on purely theoretical grounds a perfectly competitive labor market is a logical impossibility. By extension, the familiar diagram of wage determination by supply and demand is also a logical impossibility and the neoclassical labor demand curve is not a well-defined construct. The reason is that the perfectly competitive market model presumes zero transaction cost and with zero transaction cost all labor is hired as independent contractors, implying multi-person firms, the employment relationship, and labor market disappear. With positive transaction cost, on the other hand, employment contracts are incomplete and the labor supply curve to the firm is upward sloping, again causing the labor demand curve to be ill-defined. As a result, theory suggests that wage rates are always and everywhere an amalgam of an administered and bargained price. Working Paper 06-0

Rating impacts in a multi‐stressor world: a quantitative assessment of 50 stressors affecting the Great Lakes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116318/1/eap2015253717.pd

Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound

Lung ultrasound (LUS) is an important imaging modality used by emergency physicians to assess pulmonary congestion at the patient bedside. B-line artifacts in LUS videos are key findings associated with pulmonary congestion. Not only can the interpretation of LUS be challenging for novice operators, but visual quantification of B-lines remains subject to observer variability. In this work, we investigate the strengths and weaknesses of multiple deep learning approaches for automated B-line detection and localization in LUS videos. We curate and publish, BEDLUS, a new ultrasound dataset comprising 1,419 videos from 113 patients with a total of 15,755 expert-annotated B-lines. Based on this dataset, we present a benchmark of established deep learning methods applied to the task of B-line detection. To pave the way for interpretable quantification of B-lines, we propose a novel "single-point" approach to B-line localization using only the point of origin. Our results show that (a) the area under the receiver operating characteristic curve ranges from 0.864 to 0.955 for the benchmarked detection methods, (b) within this range, the best performance is achieved by models that leverage multiple successive frames as input, and (c) the proposed single-point approach for B-line localization reaches an F1-score of 0.65, performing on par with the inter-observer agreement. The dataset and developed methods can facilitate further biomedical research on automated interpretation of lung ultrasound with the potential to expand the clinical utility.Comment: 10 pages, 4 figure

Translational control analysis by translationally active RNA capture/microarray analysis (TrIP–Chip)

We have developed a new approach to systematically study post-transcriptional regulation in a small number of cells. Actively translating mRNAs are associated with polysomes and the newly synthesized peptide chains are closely associated with molecular chaperones such as hsp70s, which assist in the proper folding of nascent polypeptides into higher ordered structures. These chaperones provide an anchor with which to separate actively translating mRNAs associated with polysomes from free mRNAs. Affinity capture beads were developed to capture hsp70 chaperones associated with the polysome complexes. The isolated actively translating mRNAs were used for high-throughput expression profiling analysis. Feasibility was demonstrated using an in vitro translation system with known translationally regulated mRNA transcript thymidylate synthase (TS). We further developed the approach using HCT-116 colon cancer cells with both TS and p53 as positive controls. The steady-state levels of TS and p53 mRNAs were unaltered after 5-fluorouracil treatment as assessed by real-time qRT-PCR analysis. In contrast, the protein expression and polysome-associated mRNA levels of both genes were increased. These differences in translational rate were revealed with our new approach from 500 cells. This technology has the potential to make investigation of translational control feasible with limited quantities of clinical specimens

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD