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Key Points Question Can a database compiled from premarket approval statements for high-risk medical devices be used to characterize pediatric age indications as well as device types and specialties represented? Findings In this cross-sectional study including 297 premarket approval (PMA) documents for 149 unique devices, 102 devices (68%) contained a pediatric age indication that predominantly consisted of adolescent age (12 years to 21 years) indications. Meaning In this cross-sectional study quantifying and characterizing PMA documents, a gap was found in availability of pediatric medical devices, suggesting that most devices were developed for the adolescent pediatric population., Importance Medical device companies submit premarket approval (PMA) statements to the US Food and Drug Administration (FDA) for approval of the highest-risk class of devices. Devices indicated for the pediatric population that use the PMA pathway have not been well characterized or analyzed. Objective To identify and characterize high-risk devices with pediatric age indications derived from PMA statements. Design, Setting, and Participants In this cross-sectional study of PMA statements, those statements containing the words indicated or intended for medical devices listed in the FDA PMA database as of February 2020 were retrieved. Age indications were manually annotated in these approval statements via PubAnnotation. Based on the PMA identification from the PMA statements, device metadata including product codes, regulation numbers, advisory panels, and approval dates were queried. Main Outcomes and Measures The main outcome was discernment of the distribution of devices indicated for the pediatric population (neonate, infant, child, and adolescent). Secondary measures included outlining the clinical specialties, device types, and lag time between the initial approval date and the first date of an approval statement with a pediatric indication for generic device categories. Results A total of 297 documents for 149 unique devices were analyzed. Based on the manual age annotations, 102 devices with a pediatric indication, 10 with a neonate age indication, 32 with an infant age indication, 60 with a child age indication, and 94 with an adolescent age indication were identified. For indications for patients from age 17 to 18 years, the number of devices available nearly doubled from 42 devices to 81 devices. Although more than half of the surveyed devices had a pediatric age indication, many were available only for a limited range of the pediatric population (age 18-21 years). For indications for patients from age 0 to 17 years, the mean (SD) number of clinical specialties at each age was 7.27 (1.4), and 12 clinical specialties were represented from ages 18 to 21 years. Conclusions and Relevance In this cross-sectional study on device PMA statements, a gap was identified in both quantity and diversity of high-risk devices indicated for the pediatric population. Because the current scarcity of pediatric devices may limit therapeutic possibilities for children, this study represents a step toward quantifying this scarcity and identifying clinical specialties with the greatest need for pediatric device innovation and may help inform future device development efforts., This cross-sectional study identifies and characterizes high-risk devices with pediatric age indications derived from US Food and Drug Administration (FDA) premarket approval statements.

Imaging of musculoskeletal tissue dynamics is currently an exploratory field with the goal of aiding rehabilitation and performance evaluation of pathological or asymptomatic patients. In this pilot study, initial elasticity assessments of the biceps brachii were conducted in a novel crawling wave sonoelastography (CWS) system implemented on a research ultrasound instrument with graphical processing unit capabilities, displaying quantitative elasticity values at 4 frames per second. The CWS system computes the tissue stiffness with the generation of an interference pattern from external vibrators, which can overcome depth limitations of imaging systems with internal excitation sources. Validation on gelatin-based phantoms reported low bias of elasticity values (4.7%) at low excitation frequencies. Preliminary results on in vivo muscle characterization are in accordance with average elasticity values for relaxed and contracted tissues found in the literature, as well as for a range of weight loads.

Plantar soft tissue stiffness provides relevant information on biomechanical characteristics of the foot. Therefore, appropriate monitoring of foot elasticity could be useful for diagnosis, treatment or health care of people with complex pathologies such as a diabetic foot. In this work, the reliability of reverberant shear wave elastography (RSWE) applied to plantar soft tissue was investigated. Shear wave speed (SWS) measurements were estimated at the plantar soft tissue at the first metatarsal head, the third metatarsal head and the heel from both feet in five healthy volunteers. Experiments were repeated for a test-retest analysis with and without the use of gel pad using a mechanical excitation frequency range between 400 and 600 Hz. Statistical analysis was performed to evaluate the reliability of the SWS estimations. In addition, the results were compared against those obtained with a commercially available shear wave-based elastography technique, supersonic imaging (SSI). The results indicate a low coefficient of variation for test-retest experiments with gel pad (median: 5.59%) and without gel pad (median: 5.83%). Additionally, the values of the SWS measurements increase at higher frequencies (median values: 2.11 m/s at 400 Hz, 2.16 m/s at 450 Hz, 2.24 m/s at 500 Hz, 2.21 m/s at 550 Hz and 2.31 m/s at 600 Hz), consistent with previous reports at lower frequencies. The SWSs at the plantar soft tissue at the first metatarsal head, third metatarsal head and heel were found be significantly (p

Retro-fitting of post-combustion CO2 capture units to coal fired power plants is key to the transition to a net-zero CO2 emission reality. Different separation technologies have been found suitable for CO2 capture, but a more comprehensive approach is required to identify the most viable option among those commercially available. In this study we analyze the three most established technologies, namely absorption, adsorption and membrane separation, comparing both their exergetic efficiency and their total cost. This assessment provides an overview of the technical differences among the three capture routes and a realistic estimate of the expenditures associated with post-combustion CO2 capture, as of today.

Massively accumulated pharmacogenomics, chemogenomics, and side effect datasets offer an unprecedented opportunity for drug response prediction, drug target identification and drug side effect prediction. Existing computational approaches limit their scope to only one of these three tasks, inevitably overlooking the rich connection among them. Here, we propose DrugOrchestra, a deep multi-task learning framework that jointly predicts drug response, targets and side effects. DrugOrchestra leverages pre-trained molecular structure-based drug representation to bridge these three tasks. Instead of directly fine-tuning on an individual task, DrugOrchestra uses deep multi-task learning to obtain a phenotype-based drug representation by simultaneously fine-tuning on drug response, target and side effect prediction. By coupling these three tasks together, DrugOrchestra is able to make predictions for unseen drugs by only knowing their molecular structures. We constructed a heterogeneous drug discovery dataset of over 21k drugs by integrating 8 datasets across three tasks. Our method obtained significant improvement in comparison to methods that were trained on a single task or a single dataset. We further revealed the transferability across 8 datasets and 3 tasks, providing novel insights for understanding drug mechanisms.Availabilityhttps://github.com/jiangdada1221/DrugOrchestra

Skin diseases cause changes in the elasticity of the skin. Recently, a new ultrasound method which combines crawling waves elastography with a high-frequency ultrasound (HF-US) system was reported for the estimation of skin elasticity. This study applies crawling waves method with an HF-US system in homogeneous and heterogeneous phantoms with similar shear wave speeds found in the literature to validate this technique. In addition, estimation performance was compared between the Phase Derivative (PD) estimator and the Regularized Wave- length Average Velocity Estimator (R-WAVE). Results corroborate the feasibility of this method. Additionally, it suggests that R-WAVE estimator can provide better measurements than PD with a lower coefficient of variation and fewer artifacts.

Introduction Dulaglutide, a long-acting glucagon-like peptide-1 receptor agonist (GLP-1RA), became available in Italy in April 2016. The aim of ANDREW (Active Notes on Dulaglutide in the REal World), a multicenter, prospective, observational study, was to evaluate glycemic control and weight (co-primary outcomes) for up to 24 months in the real-life setting in consecutive outpatients with type 2 diabetes (T2D) who initiated dulaglutide. Co-secondary outcomes were durability of treatment effects on both glycated hemoglobin (HbA1c) and body weight. Methods Overall, 1584 subjects (696 women, 888 men) with T2D (mean age [± standard deviation] 61.7 ± 10.2 years; mean T2D duration 9.9 ± 6.9 years) were treated with dulaglutide (0.75 or 1.5 mg once weekly) between April 2016 and December 2019. Results A total of 1130 patients completed 12 months of follow-up, while 170 patients interrupted treatment before the 12-month endpoint. At 12 months, average HbA1c and average fasting plasma glucose (FPG) were significantly lower compared to baseline levels (− 10 mmol/mol and − 24.9 mg/dL, respectively), as were body weight (− 3.4 kg) and waist circumference (− 3.3 cm) values (all p

Chemoinformatics is an established discipline focusing on extracting, processing and extrapolating meaningful data from chemical structures. With the rapid explosion of chemical 'big' data from HTS and combinatorial synthesis, machine learning has become an indispensable tool for drug designers to mine chemical information from large compound databases to design drugs with important biological properties. To process the chemical data, we first reviewed multiple processing layers in the chemoinformatics pipeline followed by the introduction of commonly used machine learning models in drug discovery and QSAR analysis. Here, we present basic principles and recent case studies to demonstrate the utility of machine learning techniques in chemoinformatics analyses; and we discuss limitations and future directions to guide further development in this evolving field.

Gene functional enrichment is a mainstay of genomics, but it relies on manually curated databases of gene functions that are incomplete and unaware of the biological context. Here we present an alternative machine learning approach, Deep Functional Synthesis (DeepSyn), which moves beyond gene function databases to dynamically infer the functions of a gene set from its associated network of literature and data, conditioned on the disease and drug context of the current experiment. Using a knowledge graph with 3,048,803 associations between genes, diseases, drugs, and functions, DeepSyn obtained accurate performance (range 0.74 AUC to 0.96 AUC) on a variety of biological applications including drug target identification, gene set functional enrichment, and disease gene prediction.AvailabilityThe DeepSyn codebase is available on GitHub at http://github.com/wangshenguiuc/DeepSyn/ under an open source distribution license.

Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure activity relationships (QSAR), but have been eclipsed in performance by non-linear methods. Support vector machines (SVMs) and neural networks are currently among the most popular and accurate QSAR methods because they learn new representations of the data that greatly improve modelability. In this work we use shallow representation learning to improve the accuracy of L1 regularized logistic regression (LASSO) and meet the performance of Tanimoto SVM. We embedded chemical fingerprints in Euclidean space using Tanimoto (aka Jaccard) similarity kernel principal components analysis (KPCA), and compared the effects on LASSO and SVM model performance for predicting the binding activities of chemical compounds against 102 virtual screening targets. We observed similar performance and patterns of improvement for LASSO and SVM. We also empirically measured model training and cross validation times to show that KPCA used in concert with LASSO classification is significantly faster than linear SVM over a wide range of training set sizes. Our work shows that powerful linear QSAR methods can match nonlinear methods, and demonstrates a modular approach to non-linear classification that greatly enhances QSAR model prototyping facility, flexibility, and transferability.

OBJECTIVE: This study aimed to evaluate the surgical treatment of acute pancreatitis in Italy and to assess compliance with international guidelines. METHODS: A series of 1173 patients in 56 hospitals were prospectively enrolled and their data analysed. RESULTS: Twenty-nine patients with severe pancreatitis underwent surgical intervention. Necrosectomy was performed in 26 patients, associated with postoperative lavage in 70% of cases. A feeding jejunostomy was added in 37% of cases. Mortality was 21%. Of the patients with mild pancreatitis, 714 patients with a biliary aetiology were evaluated. Prophylactic treatment of relapses was carried out in 212 patients (36%) by cholecystectomy and in 161 using a laparoscopic approach. Preoperative endoscopic retrograde cholangiopancreatography was associated with cholecystectomy in 83 patients (39%). Forty-seven patients (22%) were treated at a second admission, with a median delay of 31 days from the onset of pancreatitis. Eighteen patients with severe pancreatitis underwent cholecystectomy 37.9 days after the first admission. There were no deaths. DISCUSSION: The results indicate poor compliance with published guidelines. In severe pancreatitis, early surgical intervention is frequently performed and enteral feeding is seldom used. Only a small number of patients with mild biliary pancreatitis undergo definitive treatment (i.e. cholecystectomy) within 4 weeks of the onset of pancreatitis.

Engaging, hands-on design experiences are key for formal and informal Science, Technology, Engineering, and Mathematics (STEM) education. Robotic and video game design challenges have been particularly effective in stimulating student interest, but equivalent experiences for the life sciences are not as developed. Here we present the concept of a "biotic game design project" to motivate student learning at the interface of life sciences and device engineering (as part of a cornerstone bioengineering devices course). We provide all course material and also present efforts in adapting the project's complexity to serve other time frames, age groups, learning focuses, and budgets. Students self-reported that they found the biotic game project fun and motivating, resulting in increased effort. Hence this type of design project could generate excitement and educational impact similar to robotics and video games., Can games teach life sciences device design? This article in our education series describes a "biotic game design course" to motivate student learning at the interface of life sciences and device engineering.

The Italian Association for the Study of the Pancreas released a diagnostic and therapeutic algorithm for acute pancreatitis in 1999.This study focused on the analysis of the therapeutic approach for the treatment of acute pancreatitis in Italy.One thousand, one hundred and seventy-three patients were recruited: 1006 patients (85.8%) had mild acute pancreatitis (MAP) and 167 (14.2%) had the severe acute pancreatitis (SAP); 161 patients showed pancreatic necrosis at computed tomography; 121 patients (10.3%) had sequelae and 36 (3.1%) died.Non-steroidal anti-inflammatory drugs and tramadol were used more frequently in patients with the MAP whereas opioids and the association schedules were used more frequently in patients with the SAP (P0.001). Gabexate mesilate was utilised in 831 out of 1173 patients (70.8%); in particular, gabexate mesilate was used in 70.6% patients with MAP and in 73.1% of those with SAP (P=0.521). The duration of the drug administration was significantly shorter in those having MAP than in those having the SAP (P0.001). The antibiotics most frequently used for the prophylaxis against infection from pancreatic necrosis (43.1%) were carbapenems. Only a small number of patients received enteral nutrition (4.7%). Endoscopic retrograde cholangiopancreatography was carried out in 344 of the 1173 patients (29.3%). Surgery was performed in 48 with SAP (19 had elective biliary surgery and 29 had pancreatic surgery).The results of this survey indicate a lack of compliance with the guidelines which regard the indications mainly for interventional endoscopy and surgery.

This paper describes the implementation of a mouse and window-driven Electron-Beam prober, intended for use by IC designers for debugging VLSI circuits. A worksation enables on-line access to the schematic, physical layout and test data, which is displayed in a format with which the designer is familiar so that little training is necessary to operate the system.

Introduction: The purpose of this study was to investigate the association between the mechanical properties of plantar soft tissue and diabetes status. Method: 51 (M/F: 21/30) participants with prediabetes onset (fasting blood sugar [FBS] level > 100 mg/dL), age >18 years, and no lower limb amputation were recruited after ethical approval was granted from Pontificia Universidad Catolica del Peru ethical review board. Ultrasound reverberant shear wave elastography was used to assess the soft tissue stiffness at the 1st metatarsal head (MTH), 3rd MTH, and the heel at both feet. Results: Spearman’s rank-order correlation (rho) test indicated a significant ( P < .05) positive correlations between FBS level and the plantar soft tissue shear wave speed at the 1st MTH: rho = 0.402 (@400 Hz), rho = 0.373 (@450 Hz), rho = 0.474 (@500 Hz), rho= 0.395 (@550 Hz), and rho = 0.326 (@600 Hz) in the left foot and rho = 0.364 (@450 Hz) in the right foot. Mann-Whitney U test indicated a significantly ( P < .05) higher shear wave speed in the plantar soft tissue with the following effect sizes (r) at the 1st MTH of the left foot at all tested frequencies: r = 0.297 (@450 Hz), r = 0.345 (@500 Hz), r = 0.322 (@550 Hz), and r = 0.275 (@600 Hz), and at the 1st MTH of right foot r = 0.286 (@400 Hz) in diabetes as compared with the age and body mass index matched prediabetes group. Conclusion: An association between fasting blood sugar level and the stiffness of the plantar soft tissue with higher values of shear wave speed in diabetes versus prediabetes group was observed. This indicated that the proposed approach can improve the assessment of the severity of diabetic foot complications with potential implications in patient stratification.

As no study has explored the impact of physical stress on hypothalamic‐pituitary‐gonadal axis hormones over a long period, the purpose of this study was to determine the effects of the football season period on plasma cortisol and testosterone concentrations and referee's physical performances. Physical tests and plasma cortisol and testosterone concentrations were assayed before the beginning of the training period, just after the training period, at the middle of the season, and at the end of the season, in 29 male football referees and 30 healthy control subjects. Results showed significant differences in hormone concentrations at the four‐time points evaluated. Plasma cortisol increased during the first training period from 15.8 ± 3.8 to 21.7 ± 5.1 µg/dl (p, Referees’ physical preparation improved their physical performances, assed by Yo‐Yo intermittent recovery test level 1 (YYIRT1), and running speed test. Significant differences in cortisol and testosterone levels at the four‐time points were observed. Plasma cortisol and testosterone levels significantly correlated with YYIRT1 and maximal oxygen consumption during the training period. The results underscore the importance of establishing training protocols to promote referee's positive physiological adaptations.

Background: An important role of soccer referees is to apply the rules of the game by observing the match closely. Thus, referees have to undertake training to keep up with play and attain an optimal position when making critical decisions. We analyzed the variation of the soccer referee physical performance during official championship. Methods: The referees were classified into three groups according to ages (16–20 years; 21–29 years; 30–45 years) and physical fitness variations were studied at the start (T0), at the middle (T1) and at the end of the competitive season (T2). In each period, Yo–Yo intermittent recovery test level 1 (YYIRT1) and 40 m sprint test were performed and VO2max assessed. Finally, the referees’s rating (i.e. the mean of numerically quantification of the performances received during the season) was also evaluated. Results: The mean distance covered by the referees during the YYIRT1 test increased significantly from T0 to T1 and T2, and from T1 to T2, in all age groups, with a higher effect observed for group 16–20 years in all testing periods. This group significantly improved YYIR1 performance and VO2max at T1and T2. Referee ages correlated with differences (Δ) in running speed test (40 m sprint test), of YYIRT1 and VO2max. Finally, the referees’ rating, based upon training, experience, performance and fitness assigned by qualified officials, ranged from 8.20 to 8.65. A positive correlation was found between the excellent rating and younger age (p = 0.015 by Chi-square test χ = 8.6). Conclusions: The young referees performed better physical performances than adult referees and obtained better assessments by qualified officials.

The effects of exercise training on lipid metabolism and coronary heart disease. Am J Physiol Heart Circ Physiol 319: H76-H88, 2020. First published May 22, 2020; doi:10.1152/ajpheart.00708. 2019.-Blood lipoproteins are formed by various amounts of cholesterol (C), triglycerides (TGs), phospholipids, and apolipoproteins (Apos). ApoA1 is the major structural protein of high-density lipoprotein (HDL), accounting for ~70% of HDL protein, and mediates many of the antiatherogenic functions of HDL. Conversely, ApoB is the predominant low-density lipoprotein (LDL) Apo and is an indicator of circulating LDL, associated with higher coronary heart disease (CHD) risk. Thus, the ratio of ApoB to ApoA1 (ApoB/ApoA1) is used as a surrogate marker of the risk of CHD related to lipoproteins. Elevated or abnormal levels of lipids and/or lipoproteins in the blood are a significant CHD risk factor, and several studies support the idea that aerobic exercise decreases CHD risk by partially lowering serum TG and LDL-cholesterol (LDL-C) levels and increasing HDL-C levels. Exercise also exerts an effect on HDL-C maturation and composition and on reverse C transport from peripheral cells to the liver to favor its catabolism and excretion. This process prevents atherosclerosis, and several studies showed that exercise training increases heart lipid metabolism and protects against cardiovascular disease. In these and other ways, it more and more appears that regular exercise, nutrition, and strategies to modulate lipid profile should be viewed as an integrated whole. The purpose of this review is to assess the effects of endurance training on the nontraditional lipid biomarkers, including ApoB, ApoA1, and ApoB/ApoA1, in CHD risk.

To test the hypothesis that football training would be accompanied by physiological adaptations and hormonal changes, we analyzed the effects of a whole football season on physical fitness and hormonal concentrations in youth football players. Male football players (n = 29, age 16.51 ± 0.7 years) in a regional professional league and male healthy control subjects (n = 30, age 17.1 ± 1 years) participated to the study. Blood cortisol, testosterone, and growth hormone (hGH) concentrations were assayed before the beginning of the training period (T0), just after the training period (T1), at the middle of the season (T2), and at the end of the season (T3). In each period physical tests and anthropometric measurements were also performed. Results showed significant differences in basal values of cortisol, testosterone, and growth hormone (hGH) in the four time points evaluated (P