bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved infrasound array processing with robust estimators
Authors: Bishop Jordan W , Fee David , Szuberla Curt A L 
Published: March 2020

SUMMARY
Infrasound array data are commonly used to detect and characterize infrasonic signals from a variety of natural and anthropogenic sources. Here we examine the effectiveness of robust regression estimators (L1-norm regression, M-estimators and least trimmed squares) for infrasound array processing, and compare them against standard array processing algorithms (least-squares estimation, frequency–wavenumber analysis and progressive multi-channel correlation) using a combination of real and synthetic data. Of particular interest is how each algorithm performs when one of the array elements produces data outliers. Synthetic tests on elements containing a clock error, constant values or only pink noise are performed, and we analyse the relative ability of the estimators to recover plane wave parameters. The L1-norm regression, M-estimate, frequency–wavenumber analysis and least trimmed squares estimates provided superior results than conventional least-squares estimation. Evaluation of least trimmed squares weights consistently identified the element with the simulated error, providing additional information on array performance. Least trimmed squares processing consistently identified an element with reversed polarity for Alaska Volcano Observatory array ADKI. International Monitoring System stations IS57 and IS55 were likewise processed. Data from an element of IS57, which had lower cross-correlation values than the remaining elements, were consistently identified as having outliers in array processing. An element with a timing error was identified in the analysis of IS55 data. These results suggest robust regression methods, in particular least trimmed squares, improve upon standard methods and should be used more widely, as they can provide robust array processing results and insight into array performance. Further, robust regression methods are not limited to infrasound array processing applications, and it is likely that they would also be effective for seismic array data.
Gangliosides modulate insulin secretion by pancreatic beta cells under glucose stress
Authors: Jennemann Richard , Kaden Sylvia , Volz Martina , Nordström Viola , Herzer Silke , Sandhoff Roger , Gröne Hermann-Josef 
Published: March 2020

AbstractIn pancreatic beta cells, the entry of glucose and downstream signaling for insulin release is regulated by the glucose transporter 2 (Glut2) in rodents. Dysfunction of the insulin-signaling cascade may lead to diabetes mellitus. Gangliosides, sialic acid-containing glycosphingolipids (GSLs), have been reported to modulate the function of several membrane proteins.Murine islets express predominantly sialylated GSLs, particularly the simple gangliosides GM3 and GD3 having a potential modulatory role in Glut2 activity. Conditional, tamoxifen-inducible gene targeting in pancreatic islets has now shown that mice lacking the glucosylceramide synthase (Ugcg), which represents the rate-limiting enzyme in GSL biosynthesis, displayed impaired glucose uptake and showed reduced insulin secretion. Consequently, mice with pancreatic GSL deficiency had higher blood glucose levels than respective controls after intraperitoneal glucose application. High-fat diet feeding enhanced this effect. GSL-deficient islets did not show apoptosis or ER stress and displayed a normal ultrastructure. Their insulin content, size and number were similar as in control islets. Isolated beta cells from GM3 synthase null mice unable to synthesize GM3 and GD3 also showed lower glucose uptake than respective control cells, corroborating the results obtained from the cell-specific model. We conclude that in particular the negatively charged gangliosides GM3 and GD3 of beta cells positively influence Glut2 function to adequately respond to high glucose loads.
The impact of broad-based vs targeted taxation on youth alcohol consumption in Lebanon
Authors: Chalak Ali , Ghandour Lilian , Anouti Sirine , Nakkash Rima , Yassin Nasser , Afifi Rima 
Published: March 2020

Abstract
This study aims to model youth’s off-premise alcohol demand and forecasts ethanol intake responsiveness to alcohol taxes. Using stated preference alcohol purchase data from a survey of 1024 university students in Lebanon, we derive price elasticities that we use to forecast the effects of two excise tax scenarios on overall ethanol intake. The first scenario imposes a broad-based 20% tax on all types of alcoholic beverages, and the second scenario imposes a targeted 20% tax only on the high ethanol content, while exempting the lower ethanol beverages. Overall, targeted taxes are found to achieve a reduction in ethanol intake that is nearly three times that achieved by broad taxes (15.7% vs 5.3%). For ‘past-month binge drinkers’, targeted taxes would decrease alcohol intake by 16.3%, while broad taxes increase it by 3.3%. Finally, ethanol intake among participants who prefer low ethanol content would decrease under targeted taxes by more than five times as much as under broad taxes. For ‘high-ethanol drinkers’, targeted taxes decrease alcohol intake by an even larger proportion than for ‘low-ethanol drinkers’ (19.0% vs 15.6%), while broad taxes increase their ethanol intake by ∼16.0%. This study contributes evidence that taxation policy substantially reduces alcohol consumption and that alcohol consumption patterns should be accounted for when designing taxes.
E-healthy diet literacy scale and its relationship with behaviors and health outcomes in Taiwan
Authors: Van Duong Tuyen , Chiu Chia-Hui , Lin Cheng-Yu , Chen Yi-Chun , Wong Te-Chih , Chang Peter W S , Yang Shwu-Huey 
Published: March 2020

AbstractThe study was to develop the e-healthy diet literacy (e-HDL) questionnaire based on the comprehensive health literacy (HL) conceptual framework, to examine the association among HL, e-HDL, health behaviors and outcomes. A nationwide study was conducted on 1342 adults aged 18 years and above, between April and September 2017. Multi-stage random sampling was used to recruit the participants from four regions and 19 cities and counties in Taiwan. HL and e-HDL were measured by HLS-SF12 and the e-healthy diet literacy questionnaire (e-HDLQ), respectively. Socio-demographics, behaviors (e.g. smoking, drinking and exercising) and health outcomes were also measured. Principal component analysis (PCA), linear regression models and logistic regression models were used. The mean age was 33.9 ± 11.4 years. The e-HDLQ was constructed with 11 items. A positive association between HL and e-HDL was found. In the multivariate analysis, HL and e-HDL were significantly lower in men and higher in those who used Facebook for searching information. HL was positively associated with the ability to pay for medication, and social status. The e-HDL was lower in older participants, and people who searched for healthy cooking, healthy food places or weight control, as compared with ones searched for nutritional therapies, while positively associated with education. Both HL and e-HDL were positively associated with health status and physical activities. In conclusion, the valid e-HDL survey tool was developed for general public use. The e-HDL strongly associated with HL, while both were determined by gender, online searching means and linked to health behaviors and outcomes.
Effects of a geriatric education program for emergency physicians: a mixed-methods study
Authors: Hesselink Gijs , Sir Özcan , Öztürk Ekin , Heiwegen Nikki , Olde Rikkert Marcel , Schoon Yvonne 
Published: March 2020

Abstract
Emergency physicians (EPs) often regard care for older adults as complex, while they lack sufficient geriatric skills. This study evaluates the effect of a geriatric education program on EPs’ geriatric knowledge, attitude and medical practice when treating older adults. A mixed-methods study was performed on EPs from two Dutch hospitals. Effects were measured by pre–post tests of EPs’ (n = 21) knowledge of geriatric syndromes and attitudes toward older adults, and by a retrospective pre–post analysis of 100 records of patients aged 70 years or more. Six EPs were purposively sampled and interviewed after completion of the education program. The program significantly improved EPs’ geriatric knowledge. EPs indicated that the program improved their ability and attentiveness to recognize frailty and geriatric syndromes. The program also significantly improved EPs’ attention for the older patient’s social history and circumstances (P = 0.04) but did not have a significant effect on medical decision making. EPs valued especially the case-based teaching and indicated that the interactive setting helped them to better understand and retain knowledge. Combined quantitative and qualitative data suggest that EPs benefit from geriatric emergency teaching. Future enhancement and evaluation of the geriatric education program is needed to confirm benefits to clinical practice and patient outcomes.
Research of cooling load & chiller selection in metro station
Authors: Wang Zhiyi , Zhong Jiachen , Pan Zudong 
Published: March 2020

Abstract
Air conditioning is of the most energy saving potential system in the metro station. This study analyzes the composition and characteristics of air conditioning cooling load in a metro station. The hourly distribution and the proportion of each cooling load are calculated. The results show that cooling load fluctuation of metro air conditioning is large, and the operating time of different load varies greatly. According to the air conditioning cooling load, the coefficient of performance of the fixed frequency screw, variable frequency screw, series countercurrent screw and magnetic bearing centrifugal chiller under the load of 20–100% are tested. The annual operating cost of four chillers is compared. Test results show that the magnetic bearing centrifugal chiller has a much higher coefficient of performance at part load and lower annual operating cost. Increased initial investment can be recovered in less than 2 years. The magnetic bearing centrifugal chiller is suitable as a cold source of air conditioning system in the metro station.
Maternal Secretor Status Affects Oral Rotavirus Vaccine Response in Breastfed Infants in Bangladesh
Authors: Williams Frank B , Kader Abdul , Colgate E Ross , Dickson Dorothy M , Carmolli Marya , Uddin Muhammad Ikhtear , Sharmin Salma , Islam Shahidul , Bhuiyan Taufiqur Rahman , Alam Masud , Nayak Uma , Mychaleckyj Josyf C , Petri William A , Haque Rashidul , Qadri Firdausi , Kirkpatrick Beth D , Lee Benjamin 
Published: March 2020

AbstractSecretor status controls mucosal histo–blood group antigen expression and is associated with susceptibility to rotavirus (RV) diarrhea, with nonsecretors less susceptible to symptomatic infection. The role of breast milk secretor status on oral live-attenuated RV vaccine response in breastfed infants has not been explored. In a monovalent G1P[8] RV vaccine (Rotarix) trial in Bangladesh, RV-specific plasma immunoglobulin A antibody seroconversion rates were higher among infants of maternal nonsecretors (39%) than infants of maternal secretors (23%; P = .001). Maternal status remained a significant predictor when correcting for infant status (P = .002). Maternal secretor status should be considered when interpreting oral RV vaccine responses in low- and middle-income settings.Clinical Trials Registration. NCT01375647.
Developing Quality Programs for Cell-Free DNA (cfDNA) Extraction from Peripheral Blood
Authors: Samoila Aliaksandra , Sosa Jose , Padilla Jessica , Wutkowski Michael , Vanness Katelynd , Viale Agnes , Berger Michael , Houck-Loomis Brian , Pessin Melissa , Peerschke Ellinor I 
Published: March 2020

Abstract

Background
Cell-free DNA (cfDNA) analysis using peripheral blood represents an exciting, minimally invasive technology for cancer diagnosis and monitoring. The reliability of testing is dependent on the accuracy and sensitivity of specific molecular analyses to detect tumor-associated genomic variants and on the quantity and quality of cfDNA available for testing. Specific guidelines for standardization and design of appropriate quality programs focused specifically on cfDNA isolation are lacking, as are standardized quality control reagents.

Content
This report describes and illustrates quality control and quality assurance processes, supported by generation of in-house quality control material, to ensure the reliability of the preanalytical phase of cfDNA analysis.

Summary
We have developed a robust quality program to support high-volume automated cfDNA extraction from peripheral blood by implementing processes and procedures designed to monitor the adequacy of specimen collection, specimen stability, efficiency of cfDNA extraction, and cfDNA quality.
Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks
Authors: Yu Kun-Hsing , Wang Feiran , Berry Gerald J , Ré Christopher , Altman Russ B , Snyder Michael , Kohane Isaac S 
Published: March 2020

AbstractObjectiveNon-small cell lung cancer is a leading cause of cancer death worldwide, and histopathological evaluation plays the primary role in its diagnosis. However, the morphological patterns associated with the molecular subtypes have not been systematically studied. To bridge this gap, we developed a quantitative histopathology analytic framework to identify the types and gene expression subtypes of non-small cell lung cancer objectively.Materials and MethodsWe processed whole-slide histopathology images of lung adenocarcinoma (n = 427) and lung squamous cell carcinoma patients (n = 457) in the Cancer Genome Atlas. We built convolutional neural networks to classify histopathology images, evaluated their performance by the areas under the receiver-operating characteristic curves (AUCs), and validated the results in an independent cohort (n = 125).ResultsTo establish neural networks for quantitative image analyses, we first built convolutional neural network models to identify tumor regions from adjacent dense benign tissues (AUCs &gt; 0.935) and recapitulated expert pathologists’ diagnosis (AUCs &gt; 0.877), with the results validated in an independent cohort (AUCs = 0.726-0.864). We further demonstrated that quantitative histopathology morphology features identified the major transcriptomic subtypes of both adenocarcinoma and squamous cell carcinoma (P &lt; .01).DiscussionOur study is the first to classify the transcriptomic subtypes of non-small cell lung cancer using fully automated machine learning methods. Our approach does not rely on prior pathology knowledge and can discover novel clinically relevant histopathology patterns objectively. The developed procedure is generalizable to other tumor types or diseases.
7 Artificial Intelligence and Machine Learning as a Predictive Tool for Acute Kidney Injury in Trauma and Severely Burned Patients
Authors: Falwell Stephanie M , Tran Nam K , Sen Soman , Palmieri Tina L , Greenhalgh David G , Rashidi Hooman 
Published: March 2020

Abstract

Introduction
Kidney injury doubles burn mortality—thus, early prediction of acute kidney injury (AKI) in the burn population could benefit from artificial intelligence (AI) and machine learning (ML). Our objective in this study was to build and assess the theoretical performances of such AI/ML algorithms and to develop generalizable models that could augment AKI recognition.

Methods
Two databases containing patients that received neutrophil gelatinase associated lipocalin (NGAL), creatinine, N-terminal pro-B-type natriuretic peptide (NT-proBNP) and urine output (UOP) measurements at admission were used to train, test, and generalize the AI/ML models. Models were first optimized in Cohort A for predicting AKI in Cohort B. Cohort A (n = 50) was based on a retrospective dataset of adult (age³18 years) burn patients, while Cohort B (n = 51) consisted of prospectively enrolled adult burned or non-burned trauma patients at risk for AKI. We employed a grid search and cross validation approach in building 68,100 unique ML models from five distinct ML approaches: logistic regression (LR), k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF), and deep neural networks (DNN) which enabled us to find the most accurate ML models.

Results
The best generalization accuracy (86%), sensitivity (91%), and specificity (85%) with NGAL alone was noted with LR, SVM and RF models. Generalizability prediction accuracy, sensitivity and specificity were respectively highest with the optimized DNN model (92%, 100%, and 90%) and the k-NN model (92%, 91%, and 93%) when tested with Cohort B using all four biomarkers. k-NN provided best generalization accuracy (84%) without NGAL using only NT-proBNP and creatinine, followed by DNN using creatinine only with an accuracy of 82%. AI/ML algorithms using results obtained at admission accelerated the average (SD) time to AKI prediction by 61.8 (32.5) hours.

Conclusions
NGAL is analytically superior to traditional AKI biomarkers such as creatinine and UOP. With machine learning, the AKI predictive capability of NGAL can be further enhanced and accelerated when combined with NT-proBNP, UOP, and creatinine.

Applicability of Research to Practice
Without NGAL, machine learning models continue to provide robust means in accelerating the prediction of AKI using both common and biomarkers of cardiorenal dysfunction.
42 CFTR Mediates Enteric Bacterial Translocation Post Severe Burn via ERK and Inflammatory Signaling
Authors: Liu Xinzhu , Shen Chuanan 
Published: March 2020

Abstract

Introduction
This research was to investigate the role of cystic fibrosis transmembrane conductance regulator (CFTR) in mediating enteric bacterial translocation (EBT) post severe burn as well as the signaling pathways involved.

Methods
A hypoxia treatment model of Caco-2 in vitro and a 30% TBSA full-thickness dermal burn mice model in vivo were established to explore the effect of major burn injury on intestinal epithelial barrier and the expression of CFTR and tight junction proteins. In addition, the DF508 mice (mice with F508del CFTR gene mutation) were used to analyze bacterial counts in extraintestinal organs and the expression of ZO-1, OCLN and E-cadherin. And CFTR specific inhibitor or down-regulation of CFTR in Caco-2 cells were used to explore the effect of CFTR on tight junction of intestinal cells. Furthermore, in the models above, MAPK pathway and inflammatory factors were detected to explore the mechanism. Finally, Vitamin D3 was used to pretreat mice before severe burn or Caco-2 cells before hypoxia. Bacterial counts in extraintestinal organs and the expression of CFTR, ZO-1, OCLN and P-ERK as well as the concentrations of inflammatory factors were detected.

Results
Our data showed a decrease of CFTR, concomitant with activation of ERK signaling, elevation of inflammatory factors (TNF-α, IL-1β and IL-8) and declined expression of ZO-1, occludin and E-cadherin, and a cellular mislocation of ZO-1 and OCLN post hypoxia. Furthermore, either administration of CFTR specific inhibitor or down-regulation of CFTR caused similar alterations as hypoxia did. Ileum of DF508 -/- and +/- mice exhibited increased inflammation, declined ZO-1, occludin and E-cadherin and EBT compared to +/+ mice. Moreover, vitamin D3 could reverse the junctional damage induced by hypoxia, thus preventing occurrence of EBT, possibly via up-regulating CFTR.

Conclusions
CFTR/ERK/inflammatory factors signaling was critical in modulating intestinal epithelial junction, accordingly regulating EBT. Vitamin D3 can protect intestinal epithelial barrier after severe burn, which may be associated with the up-regulation of CFTR, the inhibition of ERK pathway and decreased pro-inflammatory cytokine.

Applicability of Research to Practice
This research may be used in practice in the future to regulate the metabolism after severe burns.
47 Burn-induced Ileal Extracellular Matrix Upregulation Associated with Epithelial to Mesenchymal Transition
Authors: Cummins Claire B , Wang Xiaofu , Gu Yanping , Song Jusong , Radhakrishnan Ravi S 
Published: March 2020

Abstract

Introduction
Severe burns have long been associated with systemic inflammation and intestinal dysfunction. Recent evidence suggests that intestinal fibrosis may be responsible for intestinal dysfunction after burns. In response to inflammatory stimuli, intestinal epithelial cells may undergo epithelial-mesenchymal transition (EMT). EMT is a process by which epithelial cells acquire a mesenchymal-like phenotype, thereby compromising epithelial barrier function. EMT has been implicated in the pathogenesis of intestinal fibrosis. In the present study, we examined the cellular mechanism of burn-induced intestinal dysfunction.

Methods
Male BALA/c mice (8–12 weeks) received 30% total body surface area full-thickness scald burns or sham procedure. Ileal tissue was collected 5 days after burn for immunofluorescence (IF) and Western blot. Rat intestinal epithelial cell line IEC-6 was treated with cytokines and EMT marker proteins were analyzed by Western blot.

Results
IF data demonstrated that burn significantly increased extracellular matrix (ECM) protein laminin in ileal tissues, suggesting that burn injury induces ileal fibrogenesis. In IEC-6 cells treated with Tumor necrosis factor (TNF) α, IL-1β dose-dependently upregulated α-smooth muscle actin (α-SMA), a well known marker for myofibroblasts. ECM proteins fibronectin and laminin were found to be significantly increased after TNFα treatment. Tight junction protein E-cadherin was decreased after TNFα treatment. Futhermore, TNF receptor signaling antagonist R-7050 and SM7368 blocked TNFα-induced α-SMA upregulation.

Conclusions
Burn-induced mouse ileum ECM upregulation may be through TNFα-mediated EMT.

Applicability of Research to Practice
TNFα receptor antagonism could represent a potential pathway for drug development for treatment of burn-induced intestinal dysfunction.