671 research outputs found
Dynamic detection of electron spin accumulation in ferromagnet-semiconductor devices by ferromagnetic resonance
A distinguishing feature of spin accumulation in ferromagnet-semiconductor
devices is precession of the non-equilibrium spin population of the
semiconductor in a magnetic field. This is the basis for detection techniques
such as the Hanle effect, but these approaches become less effective as the
spin lifetime in the semiconductor decreases. For this reason, no electrical
Hanle measurement has been demonstrated in GaAs at room temperature. We show
here that by forcing the magnetization in the ferromagnet (the spin injector
and detector) to precess at the ferromagnetic resonance frequency, an
electrically generated spin accumulation can be detected from 30 to 300 K. At
low temperatures, the distinct Larmor precession of the spin accumulation in
the semiconductor can be detected by ferromagnetic resonance in an oblique
field. We verify the effectiveness of this new spin detection technique by
comparing the injection bias and temperature dependence of the measured spin
signal to the results obtained using traditional methods. We further show that
this new approach enables a measurement of short spin lifetimes (< 100 psec), a
regime that is not accessible in semiconductors using traditional Hanle
techniques.Comment: 4 figure
Predicting Emergency Department Volume Using Forecasting Methods to Create a “Surge Response” for Noncrisis Events
Objectives: This study investigated whether emergency department (ED) variables could be used in mathematical models to predict a future surge in ED volume based on recent levels of use of physician capacity. The models may be used to guide decisions related to on‐call staffing in non–crisis‐related surges of patient volume. Methods: A retrospective analysis was conducted using information spanning July 2009 through June 2010 from a large urban teaching hospital with a Level I trauma center. A comparison of significance was used to assess the impact of multiple patient‐specific variables on the state of the ED. Physician capacity was modeled based on historical physician treatment capacity and productivity. Binary logistic regression analysis was used to determine the probability that the available physician capacity would be sufficient to treat all patients forecasted to arrive in the next time period. The prediction horizons used were 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 8 hours, and 12 hours. Five consecutive months of patient data from July 2010 through November 2010, similar to the data used to generate the models, was used to validate the models. Positive predictive values, Type I and Type II errors, and real‐time accuracy in predicting noncrisis surge events were used to evaluate the forecast accuracy of the models. Results: The ratio of new patients requiring treatment over total physician capacity (termed the care utilization ratio [CUR]) was deemed a robust predictor of the state of the ED (with a CUR greater than 1 indicating that the physician capacity would not be sufficient to treat all patients forecasted to arrive). Prediction intervals of 30 minutes, 8 hours, and 12 hours performed best of all models analyzed, with deviances of 1.000, 0.951, and 0.864, respectively. A 95% significance was used to validate the models against the July 2010 through November 2010 data set. Positive predictive values ranged from 0.738 to 0.872, true positives ranged from 74% to 94%, and true negatives ranged from 70% to 90% depending on the threshold used to determine the state of the ED with the 30‐minute prediction model. Conclusions: The CUR is a new and robust indicator of an ED system’s performance. The study was able to model the tradeoff of longer time to response versus shorter but more accurate predictions, by investigating different prediction intervals. Current practice would have been improved by using the proposed models and would have identified the surge in patient volume earlier on noncrisis days.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92015/1/j.1553-2712.2012.01359.x.pd
Identification of a transporter complex responsible for the cytosolic entry of nitrogen-containing bisphosphonates
Nitrogen-containing-bisphosphonates (N-BPs) are widely prescribed to treat osteoporosis and other bone-related diseases. Although previous studies established that N-BPs function by inhibiting the mevalonate pathway in osteoclasts, the mechanism by which N-BPs enter the cytosol from the extracellular space to reach their molecular target is not understood. Here we implemented a CRISPRi-mediated genome-wide screen and identified SLC37A3 (solute carrier family 37 member A3) as a gene required for the action of N-BPs in mammalian cells. We observed that SLC37A3 forms a complex with ATRAID (all-trans retinoic acid-induced differentiation factor), a previously identified genetic target of N-BPs. SLC37A3 and ATRAID localize to lysosomes and are required for releasing N-BP molecules that have trafficked to lysosomes through fluid-phase endocytosis into the cytosol. Our results elucidate the route by which N-BPs are delivered to their molecular target, addressing a key aspect of the mechanism of action of N-BPs that may have significant clinical relevance
Global rural temperature trends
Using rural/urban land surface classifications derived from maps and satellite observed nighttime surface lights, global mean land surface air temperature time series were created using data from all weather observing stations in a global temperature data base and from rural stations only. The global rural temperature time series and trends are very similar to those derived from the full data set. Therefore, the well-known global temperature time series from in situ stations is not significantly impacted by urban warming
Global rural temperature trends
Using rural/urban land surface classifications derived from maps and satellite observed nighttime surface lights, global mean land surface air temperature time series were created using data from all weather observing stations in a global temperature data base and from rural stations only. The global rural temperature time series and trends are very similar to those derived from the full data set. Therefore, the well-known global temperature time series from in situ stations is not significantly impacted by urban warming
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Oral mucosal injury caused by mammalian target of rapamycin inhibitors: emerging perspectives on pathobiology and impact on clinical practice.
In recent years oral mucosal injury has been increasingly recognized as an important toxicity associated with mammalian target of rapamycin (mTOR) inhibitors, including in patients with breast cancer who are receiving everolimus. This review addresses the state-of-the-science regarding mTOR inhibitor-associated stomatitis (mIAS), and delineates its clinical characteristics and management. Given the clinically impactful pain associated with mIAS, this review also specifically highlights new research focusing on the study of the molecular basis of pain. The incidence of mIAS varies widely (2-78%). As reported across multiple mTOR inhibitor clinical trials, grade 3/4 toxicity occurs in up to 9% of patients. Managing mTOR-associated oral lesions with topical oral, intralesional, and/or systemic steroids can be beneficial, in contrast to the lack of evidence supporting steroid treatment of oral mucositis caused by high-dose chemotherapy or radiation. However, steroid management is not uniformly efficacious in all patients receiving mTOR inhibitors. Furthermore, technology does not presently exist to permit clinicians to predict a priori which of their patients will develop these lesions. There thus remains a strategic need to define the pathobiology of mIAS, the molecular basis of pain, and risk prediction relative to development of the clinical lesion. This knowledge could lead to novel future interventions designed to more effectively prevent mIAS and improve pain management if clinically significant mIAS lesions develop
Evaluating the pediatric mental health care continuum at an American health system
OBJECTIVE: To describe trends in the pediatric mental health care continuum and identify potential gaps in care coordination.
METHODS: We used electronic medical record data from October 2016 to September 2019 to characterize the prevalence of mental health issues in the pediatric population at a large American health system. This was a single institution case study. From the electronic medical record data, primary mental health discharge and readmission diagnoses were identified using
RESULTS: Major depressive disorder and other mood disorders comprised 49.6% and 89.4% of diagnoses in the emergency department and inpatient settings respectively compared to 9.0% of ambulatory care diagnoses and were among top reasons for readmission. Additionally, only 1% of all ambulatory care encounters had a care navigation component, whereas 86% of care navigation encounters were for mental health-associated reasons.
CONCLUSIONS: Major depressive disorder and other mood disorders were more common diagnoses in the emergency department and inpatient settings, which could signal gaps in care coordination. Bridging potential gaps in care coordination could reduce emergency department and inpatient utilization through increasing ambulatory care navigation resources, improving training, and restructuring financial incentives to facilitate ambulatory care diagnosis and management of major depressive disorder and mood disorders. Furthermore, health systems can use our descriptive analytic approach to serve as a reasonable measure of the current state of pediatric mental health care in their own patient population
Myonuclear Transcription is Responsive to Mechanical Load and DNA Content but Uncoupled from Cell Size During Hypertrophy
Myofibers increase size and DNA content in response to a hypertrophic stimulus, thus providing a physiological model with which to study how these factors affect global transcription. Using 5-ethynyl uridine (EU) to metabolically label nascent RNA, we measured a sevenfold increase in myofiber transcription during early hypertrophy before a change in cell size and DNA content. The typical increase in myofiber DNA content observed at the later stage of hypertrophy was associated with a significant decrease in the percentage of EU-positive myonuclei; however, when DNA content was held constant by preventing myonuclear accretion via satellite cell depletion, both the number of transcriptionally active myonuclei and the amount of RNA generated by each myonucleus increased. During late hypertrophy, transcription did not scale with cell size, as smaller myofibers (\u3c 1000 μm2) demonstrated the highest transcriptional activity. Finally, transcription was primarily responsible for changes in the expression of genes known to regulate myofiber size. These findings show that resident myonuclei possess a significant reserve capacity to up-regulate transcription during hypertrophy and that myofiber transcription is responsive to DNA content but uncoupled from cell size during hypertrophy
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