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Global Trends in Type 1 Diabetes in Adolescents and Young Adults (1990–2019)
Get PDFThe study by Gong et al. examines the increases in the incidence, prevalence, and burden trends of type 1 diabetes (T1D) in adolescents and young adults over a 30-year span (1990 – 2019) by age, sex, and geographical regions based on the data from the 204 countries and territories included in the Global Burden of Disease (GBD) collaborative.1 Burden is defined as a combination of mortality rates and disability adjusted life year (DALY) indexes. The results of this 3-decade study should be interpreted within the milieu of improvements in the diagnosis and treatment of T1D over this period as well as economic and political regional changes to inform further research, policy development, and advocacy to mitigate the disease burden
MRI Measurement of Cerebral Perfusion in Severe Congenital Heart Disease: Just the First Step
Get PDFTwo questions on the mind of many parents of children with complex congenital heart disease (CHD) are: Will my child survive? And, how will their life be affected? As diagnostic procedures, along with medical and surgical treatments, for these infants have improved over the recent decades, more and more of these children are surviving into adolescence and adulthood. Despite these advances in care, children with complex CHD are at higher risk of neurodevelopmental disability (NDD) and decreased quality of life (QOL) compared to their peers without CHD.1,
Outcomes of Hepatic Artery-Based Therapies and Systemic Multiagent Chemotherapy in Unresectable Colorectal Liver Metastases: A Systematic Review and Meta-analysis
Get PDFBackground: Treatment of unresectable colorectal liver metastases (UCRLM) includes locoregional and systemic therapy. A comprehensive analysis capturing long-term outcomes of these treatment options has not been performed. Objective: A systematic review and meta-analysis was performed to calculate pooled outcomes of hepatic artery infusion with systemic chemotherapy (HAI-S), transarterial chemoembolization with systemic chemotherapy (TACE-S), transarterial radioembolization with systemic chemotherapy (TARE-S), doublet (FOLFOX, FOLFIRI), and triplet chemotherapy (FOLFOXIRI). Methods: Outcomes included overall survival (OS), progression-free survival (PFS), rate of conversion to resection (CTR), and response rate (RR). Results: A total of 32, 7, 9, and 14 publications were included in the HAI-S, TACE-S, and TARE-S chemotherapy arms. The 6/12/24/36-month OS estimates for HAI-S, TACE-S, TARE-S, FOLFOX, FOLFIRI, and FOLFOXIRI were 97%/80%/54%/35%, 100%/83%/40%/14%, 82%/61%/34%/21%, 96%/83%/53%/36%, and 96%/93%/72%/55%. Similarly, the 6/12/24/36-month PFS estimates were 74%/44%/19%/14%, 66%/20%/9%/3%, 57%/23%/10%/3%, 69%/30%/12%/7%, and 88%/55%/18%/11%. The corresponding CTR and RR rates were 31, 20%, unmeasurable (TARE-S), 35, 53; and 49, 45, 45, 50, 80%, respectively. The majority of chemotherapy studies included first-line therapy and liver-only metastases, whereas most HAI-S studies were pretreated. On subgroup analysis in first-line setting with liver-only metastases, the HAI-S arm had comparable outcomes to FOLFOXIRI and outperformed doublet chemotherapy regimens. Although triplet chemotherapy appeared to outperform other arms, high toxicity and inclusion of potentially resectable patients must be considered while interpreting results. Conclusions: HAI-S and multiagent chemotherapy are effective therapies for UCRLM. To make definitive conclusions, a randomized trial with comparable patient characteristics and line of therapy will be required. The upcoming EA2222 PUMP trial may help to address this question
BST1047+1156: A (Failing) Ultradiffuse Tidal Dwarf in the Leo I Group
Get PDFWe use deep Hubble Space Telescope imaging to study the resolved stellar populations in BST1047+1156, a gas-rich, ultradiffuse dwarf galaxy found in the intragroup environment of the Leo I galaxy group. While our imaging reaches approximately two magnitudes below the tip of the red giant branch at the Leo I distance of 11 Mpc, we find no evidence for an old red giant sequence that would signal an extended star formation history for the object. Instead, we clearly detect the red and blue helium-burning sequences of its stellar populations, as well as the fainter blue main sequence, all indicative of a recent burst of star formation having taken place over the past 50-250 Myr. Comparing to isochrones for young metal-poor stellar populations, we infer this post-starburst population to be moderately metal-poor, with metallicity [M/H] in the range −1 to −1.5. The combination of a young, moderately metal-poor post starburst population and no old stars motivates a scenario in which BST1047 was recently formed during a weak burst of star formation in gas that was tidally stripped from the outskirts of the neighboring massive spiral M96. BST1047\u27s extremely diffuse nature, lack of ongoing star formation, and disturbed H i morphology all argue that it is a transitory object, a “failing tidal dwarf” in the process of being disrupted by interactions within the Leo I group. Finally, in the environment surrounding BST1047, our imaging also reveals the old, metal-poor ([M/H] = − 1.3 ± 0.2) stellar halo of M96 at a projected radius of 50 kpc
Sensitivity of Wavelet-Based Optical Flow Velocimetry (Wofv) to Common Experimental Error Sources
No full textThe influence of several potential error sources and non-ideal experimental effects on the accuracy of a wavelet-based optical flow velocimetry (wOFV) method when applied to tracer particle images is evaluated using data from a series of synthetic flows. Out-of-plane particle displacements, severe image noise, laser sheet thickness reduction, and image intensity non-uniformity are shown to decrease the accuracy of wOFV in a similar manner to correlation-based particle image velocimetry (PIV). For the error sources tested, wOFV displays a similar or slightly increased sensitivity compared to PIV, but the wOFV results are still more accurate than PIV when the magnitude of the non-ideal effects remain within expected experimental bounds. For the majority of test cases, the results are significantly improved by using image pre-processing filters and the magnitude of improvement is consistent between wOFV and PIV. Flow divergence does not appear to have an appreciable effect on the accuracy of wOFV velocity estimation, even though the underlying fluid transport equation on which wOFV is based implicitly assumes that the motion is divergence-free. This is a significant finding for the broader applicability of planar velocimetry measurements using wOFV. Finally, it is noted that the accuracy of wOFV is not reduced notably in regions of the image between tracer particles, as long as the overall seeding density is not too sparse i.e. below 0.02 particles per pixel. This explicitly demonstrates that wOFV (when applied to particle images) yields an accurate whole field measurement, and not only at or adjacent to the discrete particle locations
Breakthrough Conductivity Enhancement in Deep Eutectic Solvents Via Grotthuss-Type Proton Transport
No full textThere is an increasing demand for the development of ion-conducting electrolytes for energy storage systems. Much attention is directed toward deep eutectic solvents as potential candidates. In the search for highly conductive systems, the possibility of designing deep eutectic solvents with Grotthuss-type proton transport is widely overlooked. Herein, ethaline, a mixture of choline chloride and ethylene glycol is used in a 1:2 molar ratio, to induce a significant conductivity increase with the addition of water and sulfuric acid (H₂SO₄). The achieved breakthrough conductivity is analyzed experimentally and simulated with ab initio molecular dynamics (AIMD). At sufficient water content, an H-bonding network is formed that leads to a significant breakthrough conductivity based on H₂SO₄ derived proton transfer following the long-established Grotthuss proton transport mechanism. This result is substantiated by the positive deviation from the ideal KCl line in the Walden plot. Specifically, the data series positioned above the reference line indicates a Grotthuss mechanism in action. The AIMD simulations demonstrate proton transfer between water and ethylene glycol, supported by simulation frames captured at various times
Stress Testing Deep Learning Models for Prostate Cancer Detection on Biopsies and Surgical Specimens
No full textThe presence, location, and extent of prostate cancer is assessed by pathologists using H&E-stained tissue slides. Machine learning approaches can accomplish these tasks for both biopsies and radical prostatectomies. Deep learning approaches using convolutional neural networks (CNNs) have been shown to identify cancer in pathologic slides, some securing regulatory approval for clinical use. However, differences in sample processing can subtly alter the morphology between sample types, making it unclear whether deep learning algorithms will consistently work on both types of slide images. Our goal was to investigate whether morphological differences between sample types affected the performance of biopsy-trained cancer detection CNN models when applied to radical prostatectomies and vice versa using multiple cohorts (N = 1,000). Radical prostatectomies (N = 100) and biopsies (N = 50) were acquired from The University of Pennsylvania to train (80%) and validate (20%) a DenseNet CNN for biopsies Mᴮ radical prostatectomies Mᴿ and a combined dataset Mᴮ⁺ᴿ. On a tile level, Mᴮ and Mᴿ achieved F1 scores greater than 0.88 when applied to their own sample type but less than 0.65 when applied across sample types. On a whole-slide level, models achieved significantly better performance on their own sample type compared to the alternative model (p \u3c 0.05) for all metrics. This was confirmed by external validation using digitized biopsy slide images from a clinical trial [NRG Radiation Therapy Oncology Group (RTOG)] (NRG/RTOG 0521, N = 750) via both qualitative and quantitative analyses (p \u3c 0.05). A comprehensive review of model outputs revealed morphologically driven decision making that adversely affected model performance. Mᴮ appeared to be challenged with the analysis of open gland structures, whereas Mᴿ appeared to be challenged with closed gland structures, indicating potential morphological variation between the training sets. These findings suggest that differences in morphology and heterogeneity necessitate the need for more tailored, sample-specific (i.e. biopsy and surgical) machine learning models
Review of Treatment of Hepatitis C Among Persons who are Housing Insecure and Use Substances
No full textWith the advent of direct-acting antiviral agents (DAA), reduction of hepatitis C infection (HCV) has become a public health priority. The World Health Organization’s goal of global elimination of HCV by 2030 has brought to light the challenges in treating certain populations. This review examines the burden of HCV infection on unhoused individuals and people who use substances in the United States in the last five years, and presents best practices in patient care and treatment
Faculty Spotlight: An Interview with Dr. Christian Zorman
Get PDFDr. Chris Zorman is the associate Dean for research in the Case Western Reserve University School of Engineering and a professor in the Department of Electrical Engineering and Computer Science. His current research interests include microsystems and nanosystems. This interview has been edited for length and clarity with Dr. Zorman’s consent
FAIRification of Geospatial Data
Get PDFFAIRification (Findability, Accessibility, Interoperability, and Reusability) of geospatial and temporal data from the United States Geological Survey (USGS) is crucial for the continuance of the National Science Foundation (NSF) Engineering Research Center for Advancing Sustainable and Distributed Fertilizer Production (CASFER) whose aim is to aid in the development of eco-friendly fertilizers. The USGS data contains key information about water quality and contaminants, which are important metrics for our geospatial project since our work aims to track the contaminants\u27 flow and work towards their reduction and subsequent elimination. FAIR principles refer to - Findability, Accessibility, Interoperability, and Reusability. This is important for the safeguarding and preservation of the data collected. Often, the data that has been extracted and worked on will be needed by someone else in the same project for a different purpose. The person working on the data will have their philosophies behind naming and storing the data which could become a problem for anyone else trying to use the data down the line if they do not have a guidebook or a manual to the initial person’s pointers. This is why FAIRification of data is crucial in academia and industry. The FAIR principles have been designed to create a standardized and globally recognized nomenclature for the storage of data. Findability refers to assigning the data an identifier that is global and unique and the data is indexed in a searchable database. Accessibility means that the data can be retrieved by its identifier using a universally implementable protocol with authentication procedures wherever required. It also refers to the fact that the metadata will be accessible even when the data is not available. Interoperability means that the metadata uses a formal, accessible, and applicable language for knowledge representation and uses vocabularies that follow FAIR principles. Reusability refers to the fact that the metadata is extensively described with relevant attributes and released with a clear and accessible data usage license
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