scispace - formally typeset
Search or ask a question
Browse all papers

Journal ArticleDOI
22 Jan 2016-Science
TL;DR: The results shed light on sRNA biogenesis and its dietary regulation during posttesticular sperm maturation, and they also link tRNA fragments to regulation of endogenous retroelements active in the preimplantation embryo.
Abstract: Several recent studies link parental environments to phenotypes in subsequent generations. In this work, we investigate the mechanism by which paternal diet affects offspring metabolism. Protein restriction in mice affects small RNA (sRNA) levels in mature sperm, with decreased let-7 levels and increased amounts of 5′ fragments of glycine transfer RNAs (tRNAs). In testicular sperm, tRNA fragments are scarce but increase in abundance as sperm mature in the epididymis. Epididymosomes (vesicles that fuse with sperm during epididymal transit) carry RNA payloads matching those of mature sperm and can deliver RNAs to immature sperm in vitro. Functionally, tRNA-glycine-GCC fragments repress genes associated with the endogenous retroelement MERVL, in both embryonic stem cells and embryos. Our results shed light on sRNA biogenesis and its dietary regulation during posttesticular sperm maturation, and they also link tRNA fragments to regulation of endogenous retroelements active in the preimplantation embryo.

928 citations


Journal ArticleDOI
06 Oct 2020-JAMA
TL;DR: Among patients with COVID-19 and moderate or severe ARDS, use of intravenous dexamethasone plus standard care compared with standard care alone resulted in a statistically significant increase in the number of ventilator-free days over 28 days.
Abstract: Importance Acute respiratory distress syndrome (ARDS) due to coronavirus disease 2019 (COVID-19) is associated with substantial mortality and use of health care resources. Dexamethasone use might attenuate lung injury in these patients. Objective To determine whether intravenous dexamethasone increases the number of ventilator-free days among patients with COVID-19–associated ARDS. Design, Setting, and Participants Multicenter, randomized, open-label, clinical trial conducted in 41 intensive care units (ICUs) in Brazil. Patients with COVID-19 and moderate to severe ARDS, according to the Berlin definition, were enrolled from April 17 to June 23, 2020. Final follow-up was completed on July 21, 2020. The trial was stopped early following publication of a related study before reaching the planned sample size of 350 patients. Interventions Twenty mg of dexamethasone intravenously daily for 5 days, 10 mg of dexamethasone daily for 5 days or until ICU discharge, plus standard care (n =151) or standard care alone (n = 148). Main Outcomes and Measures The primary outcome was ventilator-free days during the first 28 days, defined as being alive and free from mechanical ventilation. Secondary outcomes were all-cause mortality at 28 days, clinical status of patients at day 15 using a 6-point ordinal scale (ranging from 1, not hospitalized to 6, death), ICU-free days during the first 28 days, mechanical ventilation duration at 28 days, and Sequential Organ Failure Assessment (SOFA) scores (range, 0-24, with higher scores indicating greater organ dysfunction) at 48 hours, 72 hours, and 7 days. Results A total of 299 patients (mean [SD] age, 61 [14] years; 37% women) were enrolled and all completed follow-up. Patients randomized to the dexamethasone group had a mean 6.6 ventilator-free days (95% CI, 5.0-8.2) during the first 28 days vs 4.0 ventilator-free days (95% CI, 2.9-5.4) in the standard care group (difference, 2.26; 95% CI, 0.2-4.38;P = .04). At 7 days, patients in the dexamethasone group had a mean SOFA score of 6.1 (95% CI, 5.5-6.7) vs 7.5 (95% CI, 6.9-8.1) in the standard care group (difference, −1.16; 95% CI, −1.94 to −0.38;P= .004). There was no significant difference in the prespecified secondary outcomes of all-cause mortality at 28 days, ICU-free days during the first 28 days, mechanical ventilation duration at 28 days, or the 6-point ordinal scale at 15 days. Thirty-three patients (21.9%) in the dexamethasone group vs 43 (29.1%) in the standard care group experienced secondary infections, 47 (31.1%) vs 42 (28.3%) needed insulin for glucose control, and 5 (3.3%) vs 9 (6.1%) experienced other serious adverse events. Conclusions and Relevance Among patients with COVID-19 and moderate or severe ARDS, use of intravenous dexamethasone plus standard care compared with standard care alone resulted in a statistically significant increase in the number of ventilator-free days (days alive and free of mechanical ventilation) over 28 days. Trial Registration ClinicalTrials.gov Identifier:NCT04327401

928 citations


Journal ArticleDOI
Mary E. Dickinson, Ann M. Flenniken, Xiao Ji1, Lydia Teboul2, Michael D. Wong, Jacqueline K. White3, Terrence F. Meehan4, Wolfgang Weninger5, Henrik Westerberg2, Hibret A. Adissu6, Candice N. Baker, Lynette Bower7, James M. Brown2, L. Brianna Caddle, Francesco Chiani8, Dave Clary7, James Cleak2, Mark J. Daly9, James M. Denegre, Brendan Doe3, Mary E. Dolan, Sarah M. Edie, Helmut Fuchs, Valerie Gailus-Durner, Antonella Galli3, Alessia Gambadoro8, Juan Gallegos10, Shiying Guo11, Neil R. Horner2, Chih-Wei Hsu, Sara Johnson2, Sowmya Kalaga, Lance C. Keith, Louise Lanoue7, Thomas N. Lawson2, Monkol Lek9, Monkol Lek12, Manuel Mark13, Susan Marschall, Jeremy Mason4, Melissa L. McElwee, Susan Newbigging6, Lauryl M. J. Nutter6, Kevin A. Peterson, Ramiro Ramirez-Solis3, Douglas J. Rowland7, Edward Ryder3, Kaitlin E. Samocha12, Kaitlin E. Samocha9, John R. Seavitt10, Mohammed Selloum13, Zsombor Szoke-Kovacs2, Masaru Tamura, Amanda G. Trainor7, Ilinca Tudose4, Shigeharu Wakana, Jonathan Warren4, Olivia Wendling13, David B. West14, Leeyean Wong, Atsushi Yoshiki, Daniel G. MacArthur9, Daniel G. MacArthur12, Glauco P. Tocchini-Valentini8, Xiang Gao11, Paul Flicek4, Allan Bradley3, William C. Skarnes3, Monica J. Justice, Helen Parkinson4, Mark W. Moore, Sara Wells2, Robert E. Braun, Karen L. Svenson, Martin Hrabé de Angelis15, Yann Herault13, Timothy J. Mohun16, Ann-Marie Mallon2, R. Mark Henkelman, Steve D.M. Brown2, David J. Adams3, Kevin C K Lloyd7, Colin McKerlie6, Arthur L. Beaudet10, Maja Bucan1, Stephen A. Murray 
22 Sep 2016-Nature
TL;DR: It is shown that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts and reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background.
Abstract: Approximately one-third of all mammalian genes are essential for life. Phenotypes resulting from knockouts of these genes in mice have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5,000 knockout mouse lines, here we identify 410 lethal genes during the production of the first 1,751 unique gene knockouts. Using a standardized phenotyping platform that incorporates high-resolution 3D imaging, we identify phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts.

928 citations


Journal ArticleDOI
TL;DR: Among patients with stage III epithelial ovarian cancer, the addition of hyperthermic intraperitoneal chemotherapy (HIPEC) to interval cytoreductive surgery resulted in longer recurrence‐free survival and overall survival than surgery alone and did not result in higher rates of side effects.
Abstract: Background Treatment of newly diagnosed advanced-stage ovarian cancer typically involves cytoreductive surgery and systemic chemotherapy. We conducted a trial to investigate whether the addition of hyperthermic intraperitoneal chemotherapy (HIPEC) to interval cytoreductive surgery would improve outcomes among patients who were receiving neoadjuvant chemotherapy for stage III epithelial ovarian cancer. Methods In a multicenter, open-label, phase 3 trial, we randomly assigned 245 patients who had at least stable disease after three cycles of carboplatin (area under the curve of 5 to 6 mg per milliliter per minute) and paclitaxel (175 mg per square meter of body-surface area) to undergo interval cytoreductive surgery either with or without administration of HIPEC with cisplatin (100 mg per square meter). Randomization was performed at the time of surgery in cases in which surgery that would result in no visible disease (complete cytoreduction) or surgery after which one or more residual tumors measu...

928 citations


Journal ArticleDOI
26 Mar 2015-Cell
TL;DR: Findings indicate that meal timing is crucial, with both intermittent fasting and adjusted diurnal rhythm of feeding improving health and function, in the absence of changes in overall intake.

928 citations


Journal ArticleDOI
TL;DR: A patient’s family pursues genetic testing that shows a “likely pathogenic” variant for the condition on the basis of a study in an original research publication, and a different variant is found that is determined to be pathogenic.
Abstract: On autopsy, a patient is found to have hypertrophic cardiomyopathy The patient’s family pursues genetic testing that shows a “likely pathogenic” variant for the condition on the basis of a study in an original research publication Given the dominant inheritance of the condition and the risk of sudden cardiac death, other family members are tested for the genetic variant to determine their risk Several family members test negative and are told that they are not at risk for hypertrophic cardiomyopathy and sudden cardiac death, and those who test positive are told that they need to be regularly monitored for cardiomyopathy on echocardiography Five years later, during a routine clinic visit of one of the genotype-positive family members, the cardiologist queries a database for current knowledge on the genetic variant and discovers that the variant is now interpreted as “likely benign” by another laboratory that uses more recently derived population-frequency data A newly available testing panel for additional genes that are implicated in hypertrophic cardiomyopathy is initiated on an affected family member, and a different variant is found that is determined to be pathogenic Family members are retested, and one member who previously tested negative is now found to be positive for this new variant An immediate clinical workup detects evidence of cardiomyopathy, and an intracardiac defibrillator is implanted to reduce the risk of sudden cardiac death

928 citations


Journal ArticleDOI
TL;DR: Issues from grading of acne to the topical and systemic management of the disease are reviewed and suggestions on use are provided based on available evidence.
Abstract: Acne is one of the most common disorders treated by dermatologists and other health care providers. While it most often affects adolescents, it is not uncommon in adults and can also be seen in children. This evidence-based guideline addresses important clinical questions that arise in its management. Issues from grading of acne to the topical and systemic management of the disease are reviewed. Suggestions on use are provided based on available evidence.

928 citations


Journal ArticleDOI
TL;DR: This siteless study design provides a foundation for large-scale pragmatic studies in which outcomes or adherence can be reliably assessed with user-owned devices and the probability of receiving an irregular pulse notification was low.
Abstract: Background Optical sensors on wearable devices can detect irregular pulses. The ability of a smartwatch application (app) to identify atrial fibrillation during typical use is unknown. Met...

928 citations


Proceedings Article
05 Dec 2016
TL;DR: Experiments on MRI image reconstruction under different sampling ratios in k-space demonstrate that the proposed novel ADMM-Net algorithm significantly improves the baseline ADMM algorithm and achieves high reconstruction accuracies with fast computational speed.
Abstract: Compressive Sensing (CS) is an effective approach for fast Magnetic Resonance Imaging (MRI). It aims at reconstructing MR image from a small number of under-sampled data in k-space, and accelerating the data acquisition in MRI. To improve the current MRI system in reconstruction accuracy and computational speed, in this paper, we propose a novel deep architecture, dubbed ADMM-Net. ADMM-Net is defined over a data flow graph, which is derived from the iterative procedures in Alternating Direction Method of Multipliers (ADMM) algorithm for optimizing a CS-based MRI model. In the training phase, all parameters of the net, e.g., image transforms, shrinkage functions, etc., are discriminatively trained end-to-end using L-BFGS algorithm. In the testing phase, it has computational overhead similar to ADMM but uses optimized parameters learned from the training data for CS-based reconstruction task. Experiments on MRI image reconstruction under different sampling ratios in k-space demonstrate that it significantly improves the baseline ADMM algorithm and achieves high reconstruction accuracies with fast computational speed.

928 citations


Journal ArticleDOI
28 May 2015-Nature
TL;DR: An intelligent trial-and-error algorithm is introduced that allows robots to adapt to damage in less than two minutes in large search spaces without requiring self-diagnosis or pre-specified contingency plans, and may shed light on the principles that animals use to adaptation to injury.
Abstract: An intelligent trial-and-error learning algorithm is presented that allows robots to adapt in minutes to compensate for a wide variety of types of damage. Autonomous mobile robots would be extremely useful in remote or hostile environments such as space, deep oceans or disaster areas. An outstanding challenge is to make such robots able to recover after damage. Jean-Baptiste Mouret and colleagues have developed a machine learning algorithm that enables damaged robots to quickly regain their ability to perform tasks. When they sustain damage — such as broken or even missing legs — the robots adopt an intelligent trial-and-error approach, trying out possible behaviours that they calculate to be potentially high-performing. After a handful of such experiments they discover, in less than two minutes, a compensatory behaviour that works in spite of the damage. Robots have transformed many industries, most notably manufacturing1, and have the power to deliver tremendous benefits to society, such as in search and rescue2, disaster response3, health care4 and transportation5. They are also invaluable tools for scientific exploration in environments inaccessible to humans, from distant planets6 to deep oceans7. A major obstacle to their widespread adoption in more complex environments outside factories is their fragility6,8. Whereas animals can quickly adapt to injuries, current robots cannot ‘think outside the box’ to find a compensatory behaviour when they are damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes9, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots6,8. A promising approach to reducing robot fragility involves having robots learn appropriate behaviours in response to damage10,11, but current techniques are slow even with small, constrained search spaces12. Here we introduce an intelligent trial-and-error algorithm that allows robots to adapt to damage in less than two minutes in large search spaces without requiring self-diagnosis or pre-specified contingency plans. Before the robot is deployed, it uses a novel technique to create a detailed map of the space of high-performing behaviours. This map represents the robot’s prior knowledge about what behaviours it can perform and their value. When the robot is damaged, it uses this prior knowledge to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a behaviour that compensates for the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new algorithm will enable more robust, effective, autonomous robots, and may shed light on the principles that animals use to adapt to injury.

928 citations


Proceedings Article
01 Feb 2018
TL;DR: In this paper, an end-to-end trainable model for image compression based on variational autoencoders is proposed, which incorporates a hyperprior to effectively capture spatial dependencies in the latent representation.
Abstract: We describe an end-to-end trainable model for image compression based on variational autoencoders. The model incorporates a hyperprior to effectively capture spatial dependencies in the latent representation. This hyperprior relates to side information, a concept universal to virtually all modern image codecs, but largely unexplored in image compression using artificial neural networks (ANNs). Unlike existing autoencoder compression methods, our model trains a complex prior jointly with the underlying autoencoder. We demonstrate that this model leads to state-of-the-art image compression when measuring visual quality using the popular MS-SSIM index, and yields rate-distortion performance surpassing published ANN-based methods when evaluated using a more traditional metric based on squared error (PSNR). Furthermore, we provide a qualitative comparison of models trained for different distortion metrics.

Posted Content
TL;DR: It is shown that some existing saliency methods are independent both of the model and of the data generating process, and methods that fail the proposed tests are inadequate for tasks that are sensitive to either data or model.
Abstract: Saliency methods have emerged as a popular tool to highlight features in an input deemed relevant for the prediction of a learned model. Several saliency methods have been proposed, often guided by visual appeal on image data. In this work, we propose an actionable methodology to evaluate what kinds of explanations a given method can and cannot provide. We find that reliance, solely, on visual assessment can be misleading. Through extensive experiments we show that some existing saliency methods are independent both of the model and of the data generating process. Consequently, methods that fail the proposed tests are inadequate for tasks that are sensitive to either data or model, such as, finding outliers in the data, explaining the relationship between inputs and outputs that the model learned, and debugging the model. We interpret our findings through an analogy with edge detection in images, a technique that requires neither training data nor model. Theory in the case of a linear model and a single-layer convolutional neural network supports our experimental findings.

Journal ArticleDOI
TL;DR: There are four stable TNBC subtypes characterized by the expression of distinct molecular profiles that have distinct prognoses, and novel subtype-specific targets that can be targeted in the future for the effective treatment of TNBCs are identified.
Abstract: Purpose: Genomic profiling studies suggest that triple-negative breast cancer (TNBC) is a heterogeneous disease. In this study, we sought to define TNBC subtypes and identify subtype-specific markers and targets. Experimental Design: RNA and DNA profiling analyses were conducted on 198 TNBC tumors [estrogen receptor (ER) negativity defined as Allred scale value ≤ 2] with >50% cellularity (discovery set: n = 84; validation set: n = 114) collected at Baylor College of Medicine (Houston, TX). An external dataset of seven publically accessible TNBC studies was used to confirm results. DNA copy number, disease-free survival (DFS), and disease-specific survival (DSS) were analyzed independently using these datasets. Results: We identified and confirmed four distinct TNBC subtypes: (i) luminal androgen receptor (AR; LAR), (ii) mesenchymal (MES), (iii) basal-like immunosuppressed (BLIS), and (iv) basal-like immune-activated (BLIA). Of these, prognosis is worst for BLIS tumors and best for BLIA tumors for both DFS (log-rank test: P = 0.042 and 0.041, respectively) and DSS (log-rank test: P = 0.039 and 0.029, respectively). DNA copy number analysis produced two major groups (LAR and MES/BLIS/BLIA) and suggested that gene amplification drives gene expression in some cases [FGFR2 (BLIS)]. Putative subtype-specific targets were identified: (i) LAR: androgen receptor and the cell surface mucin MUC1, (ii) MES: growth factor receptors [platelet-derived growth factor (PDGF) receptor A; c-Kit], (iii) BLIS: an immunosuppressing molecule (VTCN1), and (iv) BLIA: Stat signal transduction molecules and cytokines. Conclusion: There are four stable TNBC subtypes characterized by the expression of distinct molecular profiles that have distinct prognoses. These studies identify novel subtype-specific targets that can be targeted in the future for the effective treatment of TNBCs. Clin Cancer Res; 21(7); 1688–98. ©2014 AACR . See related commentary by Vidula and Rugo, p. 1511

Journal ArticleDOI
TL;DR: A systematic review of studies on CO VID-19 that included information on patients’ smoking status to evaluate the association between smoking and COVID-19 outcomes including the severity of the disease, the need for mechanical ventilation, theneed for intensive care unit (ICU) hospitalization and death.
Abstract: COVID-19 is a coronavirus outbreak that initially appeared in Wuhan, Hubei Province, China, in December 2019, but it has already evolved into a pandemic spreading rapidly worldwide,. As of 18 March 2020, a total number of 194909 cases of COVID-19 have been reported, including 7876 deaths, the majority of which have been reported in China (3242) and Italy (2505).However, as the pandemic is still unfortunately under progression, there are limited data with regard to the clinical characteristics of the patients as well as to their prognostic factors. Smoking, to date, has been assumed to be possibly associated with adverse disease prognosis, as extensive evidence has highlighted the negative impact of tobacco use on lung health and its causal association with a plethora of respiratory diseases. Smoking is also detrimental to the immune system and its responsiveness to infections, making smokers more vulnerable to infectious diseases. Previous studies have shown that smokers are twice more likely than non-smokers to contract influenza and have more severe symptoms, while smokers were also noted to have higher mortality in the previous MERS-CoV outbreak,.Given the gap in the evidence, we conducted a systematic review of studies on COVID-19 that included information on patients’ smoking status to evaluate the association between smoking and COVID-19 outcomes including the severity of the disease, the need for mechanical ventilation, the need for intensive care unit (ICU) hospitalization and death.The literature search was conducted on 17 March 2020, using two databases (PubMed, ScienceDirect), with the search terms: [‘smoking’ OR ‘tobacco’ OR ‘risk factors’ OR ‘smoker*’] AND [‘COVID-19’ OR ‘COVID 19’ OR ‘novel coronavirus’ OR ‘sars cov-2’ OR ‘sars cov 2’] and included studies published in 2019 and 2020. Further inclusion criteria were that the studies were in English and referred to humans. We also searched the reference lists of the studies included. A total of 71 studies were retrieved through the search, of which 66 were excluded after full-text screening, leaving five studies that were included. All of the studies were conducted in China, four in Wuhan and one across provinces in mainland China. The populations in all studies were patients with COVID-19, and the sample size ranged from 41 to 1099 patients. With regard to the study design, retrospective and prospective methods were used, and the timeframe of all five studies covered the first two months of the COVID-19 pandemic (December 2019, January 2020).Specifically, Zhou et al. studied the epidemiological characteristics of 191 individuals infected with COVID-19, without, however, reporting in more detail the mortality risk factors and the clinical outcomes of the disease. Among the 191 patients, there were 54 deaths, while 137 survived. Among those that died, 9% were current smokers compared to 4% among those that survived, with no statistically significant difference between the smoking rates of survivors and non-survivors (p=0.21) with regard to mortality from COVID-19.Similarly, Zhang et al. presented clinical characteristics of 140 patients with COVID-19. The results showed that among severe patients (n=58), 3.4% were current smokers and 6.9% were former smokers, in contrast to non-severe patients (n=82) among which 0% were current smokers and 3.7% were former smokers , leading to an OR of 2.23; (95% CI: 0.65–7.63; p=0.2).Huang et al. studied the epidemiological characteristics of COVID-19 among 41 patients. In this study, none of those who needed to be admitted to an ICU (n=13) was a current smoker. In contrast, three patients from the non-ICU group were current smokers, with no statistically significant difference between the two groups of patients (p=0.31), albeit the small sample size of the study.The largest study population of 1099 patients with COVID-19 was provided by Guan et al. from multiple regions of mainland China. Descriptive results on the smoking status of patients were provided for the 1099 patients, of which 173 had severe symptoms, and 926 had non-severe symptoms. Among the patients with severe symptoms, 16.9% were current smokers and 5.2% were former smokers, in contrast to patients with non-severe symptoms where 11.8% were current smokers and 1.3% were former smokers. Additionally, in the group of patients that either needed mechanical ventilation, admission to an ICU or died, 25.5% were current smokers and 7.6% were former smokers. In contrast, in the group of patients that did not have these adverse outcomes, only 11.8% were current smokers and 1.6% were former smokers. No statistical analysis for evaluating the association between the severity of the disease outcome and smoking status was conducted in that study.Finally, Liu et al. found among their population of 78 patients with COVID-19 that the adverse outcome group had a significantly higher proportion of patients with a history of smoking (27.3%) than the group that showed improvement or stabilization (3.0%), with this difference statistically significant at the p=0.018 level. In their multivariate logistic regression analysis, the history of smoking was a risk factor of disease progression (OR=14.28; 95% CI: 1.58–25.00; p= 0.018).We identified five studies that reported data on the smoking status of patients infected with COVID-19. Notably, in the largest study that assessed severity, there were higher percentages of current and former smokers among patients that needed ICU support, mechanical ventilation or who had died, and a higher percentage of smokers among the severe cases. However, from their published data we can calculate that the smokers were 1.4 times more likely (RR=1.4, 95% CI: 0.98–2.00) to have severe symptoms of COVID-19 and approximately 2.4 times more likely to be admitted to an ICU, need mechanical ventilation or die compared to non-smokers (RR=2.4, 95% CI: 1.43–4.04).In conclusion, although further research is warranted as the weight of the evidence increases, with the limited available data, and although the above results are unadjusted for other factors that may impact disease progression, smoking is most likely associated with the negative progression and adverse outcomes of COVID-19.

Journal ArticleDOI
27 Oct 2016-PLOS ONE
TL;DR: The presence of at least two distinct haplotypes within samples collected on maize in Nigeria and São Tomé suggests multiple introductions into the African continent.
Abstract: The fall armyworm Spodoptera frugiperda is a prime noctuid pest of maize on the American continents where it has remained confined despite occasional interceptions by European quarantine services in recent years The pest has currently become a new invasive species in West and Central Africa where outbreaks were recorded for the first time in early 2016 The presence of at least two distinct haplotypes within samples collected on maize in Nigeria and Sao Tome suggests multiple introductions into the African continent Implications of this new threat to the maize crop in tropical Africa are briefly discussed

Journal ArticleDOI
TL;DR: The pipeline is described in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol and several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.

Journal ArticleDOI
TL;DR: In an attempt to give an order of magnitude regarding CO2 valorization, the most important aspects of CO2 capture and green routes to produce H2 are summarized and economical aspects of the production of methanol and DME are critically assessed.
Abstract: The recent advances in the development of heterogeneous catalysts and processes for the direct hydrogenation of CO2 to formate/formic acid, methanol, and dimethyl ether are thoroughly reviewed, with special emphasis on thermodynamics and catalyst design considerations. After introducing the main motivation for the development of such processes, we first summarize the most important aspects of CO2 capture and green routes to produce H2. Once the scene in terms of feedstocks is introduced, we carefully summarize the state of the art in the development of heterogeneous catalysts for these important hydrogenation reactions. Finally, in an attempt to give an order of magnitude regarding CO2 valorization, we critically assess economical aspects of the production of methanol and DME and outline future research and development directions.

Journal ArticleDOI
Beatriz Pelaz1, Christoph Alexiou2, Ramon A. Alvarez-Puebla3, Frauke Alves4, Frauke Alves5, Anne M. Andrews6, Sumaira Ashraf1, Lajos P. Balogh, Laura Ballerini7, Alessandra Bestetti8, Cornelia Brendel1, Susanna Bosi9, Mónica Carril10, Warren C. W. Chan11, Chunying Chen, Xiaodong Chen12, Xiaoyuan Chen13, Zhen Cheng14, Daxiang Cui15, Jianzhong Du16, Christian Dullin4, Alberto Escudero1, Alberto Escudero17, Neus Feliu18, Mingyuan Gao, Michael D. George, Yury Gogotsi19, Arnold Grünweller1, Zhongwei Gu20, Naomi J. Halas21, Norbert Hampp1, Roland K. Hartmann1, Mark C. Hersam22, Patrick Hunziker23, Ji Jian24, Xingyu Jiang, Philipp Jungebluth25, Pranav Kadhiresan11, Kazunori Kataoka26, Ali Khademhosseini27, Jindřich Kopeček28, Nicholas A. Kotov29, Harald F. Krug30, Dong Soo Lee31, Claus-Michael Lehr32, Kam W. Leong33, Xing-Jie Liang34, Mei Ling Lim18, Luis M. Liz-Marzán10, Xiaowei Ma34, Paolo Macchiarini35, Huan Meng6, Helmuth Möhwald5, Paul Mulvaney8, Andre E. Nel6, Shuming Nie36, Peter Nordlander21, Teruo Okano, Jose Oliveira, Tai Hyun Park31, Reginald M. Penner37, Maurizio Prato9, Maurizio Prato10, Víctor F. Puntes38, Vincent M. Rotello39, Amila Samarakoon11, Raymond E. Schaak40, Youqing Shen24, Sebastian Sjöqvist18, Andre G. Skirtach5, Andre G. Skirtach41, Mahmoud Soliman1, Molly M. Stevens42, Hsing-Wen Sung43, Ben Zhong Tang44, Rainer Tietze2, Buddhisha Udugama11, J. Scott VanEpps29, Tanja Weil5, Tanja Weil45, Paul S. Weiss6, Itamar Willner46, Yuzhou Wu47, Yuzhou Wu5, Lily Yang, Zhao Yue1, Qian Zhang1, Qiang Zhang48, Xian-En Zhang, Yuliang Zhao, Xin Zhou, Wolfgang J. Parak1 
14 Mar 2017-ACS Nano
TL;DR: An overview of recent developments in nanomedicine is provided and the current challenges and upcoming opportunities for the field are highlighted and translation to the clinic is highlighted.
Abstract: The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic.

Proceedings Article
05 Dec 2016
TL;DR: This paper proposes to symmetrically link convolutional and de-convolutional layers with skip-layer connections, with which the training converges much faster and attains a higher-quality local optimum, making training deep networks easier and achieving restoration performance gains consequently.
Abstract: In this paper, we propose a very deep fully convolutional encoding-decoding framework for image restoration such as denoising and super-resolution. The network is composed of multiple layers of convolution and deconvolution operators, learning end-to-end mappings from corrupted images to the original ones. The convolutional layers act as the feature extractor, which capture the abstraction of image contents while eliminating noises/corruptions. Deconvolutional layers are then used to recover the image details. We propose to symmetrically link convolutional and deconvolutional layers with skip-layer connections, with which the training converges much faster and attains a higher-quality local optimum. First, the skip connections allow the signal to be back-propagated to bottom layers directly, and thus tackles the problem of gradient vanishing, making training deep networks easier and achieving restoration performance gains consequently. Second, these skip connections pass image details from convolutional layers to deconvolutional layers, which is beneficial in recovering the original image. Significantly, with the large capacity, we can handle different levels of noises using a single model. Experimental results show that our network achieves better performance than recent state-of-the-art methods.

Journal ArticleDOI
15 Dec 2015-JAMA
TL;DR: In this interim analysis of 315 patients with glioblastoma who had completed standard chemoradiation therapy, adding TTFields to maintenance temozolomide chemotherapy significantly prolonged progression-free and overall survival.
Abstract: Importance Glioblastoma is the most devastating primary malignancy of the central nervous system in adults. Most patients die within 1 to 2 years of diagnosis. Tumor-treating fields (TTFields) are a locoregionally delivered antimitotic treatment that interferes with cell division and organelle assembly. Objective To evaluate the efficacy and safety of TTFields used in combination with temozolomide maintenance treatment after chemoradiation therapy for patients with glioblastoma. Design, Setting, and Participants After completion of chemoradiotherapy, patients with glioblastoma were randomized (2:1) to receive maintenance treatment with either TTFields plus temozolomide (n = 466) or temozolomide alone (n = 229) (median time from diagnosis to randomization, 3.8 months in both groups). The study enrolled 695 of the planned 700 patients between July 2009 and November 2014 at 83 centers in the United States, Canada, Europe, Israel, and South Korea. The trial was terminated based on the results of this planned interim analysis. Interventions Treatment with TTFields was delivered continuously (>18 hours/day) via 4 transducer arrays placed on the shaved scalp and connected to a portable medical device. Temozolomide (150-200 mg/m 2 /d) was given for 5 days of each 28-day cycle. Main Outcomes and Measures The primary end point was progression-free survival in the intent-to-treat population (significance threshold of .01) with overall survival in the per-protocol population (n = 280) as a powered secondary end point (significance threshold of .006). This prespecified interim analysis was to be conducted on the first 315 patients after at least 18 months of follow-up. Results The interim analysis included 210 patients randomized to TTFields plus temozolomide and 105 randomized to temozolomide alone, and was conducted at a median follow-up of 38 months (range, 18-60 months). Median progression-free survival in the intent-to-treat population was 7.1 months (95% CI, 5.9-8.2 months) in the TTFields plus temozolomide group and 4.0 months (95% CI, 3.3-5.2 months) in the temozolomide alone group (hazard ratio [HR], 0.62 [98.7% CI, 0.43-0.89]; P = .001). Median overall survival in the per-protocol population was 20.5 months (95% CI, 16.7-25.0 months) in the TTFields plus temozolomide group (n = 196) and 15.6 months (95% CI, 13.3-19.1 months) in the temozolomide alone group (n = 84) (HR, 0.64 [99.4% CI, 0.42-0.98]; P = .004). Conclusions and Relevance In this interim analysis of 315 patients with glioblastoma who had completed standard chemoradiation therapy, adding TTFields to maintenance temozolomide chemotherapy significantly prolonged progression-free and overall survival. Trial Registration clinicaltrials.gov Identifier:NCT00916409

Journal ArticleDOI
TL;DR: This expert Consensus Statement, endorsed by the ENS-CCA, summarizes the latest advances in CCA, including classification, genetics and treatment, and provides recommendations for CCA management and priorities across basic, translational and clinical research.
Abstract: Cholangiocarcinoma (CCA) includes a cluster of highly heterogeneous biliary malignant tumours that can arise at any point of the biliary tree Their incidence is increasing globally, currently accounting for ~15% of all primary liver cancers and ~3% of gastrointestinal malignancies The silent presentation of these tumours combined with their highly aggressive nature and refractoriness to chemotherapy contribute to their alarming mortality, representing ~2% of all cancer-related deaths worldwide yearly The current diagnosis of CCA by non-invasive approaches is not accurate enough, and histological confirmation is necessary Furthermore, the high heterogeneity of CCAs at the genomic, epigenetic and molecular levels severely compromises the efficacy of the available therapies In the past decade, increasing efforts have been made to understand the complexity of these tumours and to develop new diagnostic tools and therapies that might help to improve patient outcomes In this expert Consensus Statement, which is endorsed by the European Network for the Study of Cholangiocarcinoma, we aim to summarize and critically discuss the latest advances in CCA, mostly focusing on classification, cells of origin, genetic and epigenetic abnormalities, molecular alterations, biomarker discovery and treatments Furthermore, the horizon of CCA for the next decade from 2020 onwards is highlighted

Journal ArticleDOI
08 Jul 2016-Science
TL;DR: Control over pore chemistry and size in metal coordination networks with hexafluorosilicate and organic linkers for the purpose of preferential binding and orderly assembly of acetylene molecules through cooperative host-guest and/or guest-guer interactions is reported.
Abstract: The trade-off between physical adsorption capacity and selectivity of porous materials is a major barrier for efficient gas separation and purification through physisorption. We report control over pore chemistry and size in metal coordination networks with hexafluorosilicate and organic linkers for the purpose of preferential binding and orderly assembly of acetylene molecules through cooperative host-guest and/or guest-guest interactions. The specific binding sites for acetylene are validated by modeling and neutron powder diffraction studies. The energies associated with these binding interactions afford high adsorption capacity (2.1 millimoles per gram at 0.025 bar) and selectivity (39.7 to 44.8) for acetylene at ambient conditions. Their efficiency for the separation of acetylene/ethylene mixtures is demonstrated by experimental breakthrough curves (0.73 millimoles per gram from a 1/99 mixture).

Journal ArticleDOI
TL;DR: The ITRF2014 is generated with an enhanced modeling of nonlinear station motions, including seasonal (annual and semiannual) signals of station positions and postseismic deformation for sites that were subject to major earthquakes.
Abstract: For the first time in the International Terrestrial Reference Frame (ITRF) history, the ITRF2014 is generated with an enhanced modeling of nonlinear station motions, including seasonal (annual and semiannual) signals of station positions and postseismic deformation for sites that were subject to major earthquakes. Using the full observation history of the four space geodetic techniques (very long baseline interferometry (VLBI), satellite laser ranging (SLR), Global Navigation Satellite Systems (GNSS), and Doppler orbitography and radiopositioning integrated by satellite (DORIS)), the corresponding international services provided reprocessed time series (weekly from SLR and DORIS, daily from GNSS, and 24 h session-wise from VLBI) of station positions and daily Earth Orientation Parameters. ITRF2014 is demonstrated to be superior to past ITRF releases, as it precisely models the actual station trajectories leading to a more robust secular frame and site velocities. The ITRF2014 long-term origin coincides with the Earth system center of mass as sensed by SLR observations collected on the two LAGEOS satellites over the time span between 1993.0 and 2015.0. The estimated accuracy of the ITRF2014 origin, as reflected by the level of agreement with the ITRF2008 (both origins are defined by SLR), is at the level of less than 3 mm at epoch 2010.0 and less than 0.2 mm/yr in time evolution. The ITRF2014 scale is defined by the arithmetic average of the implicit scales of SLR and VLBI solutions as obtained by the stacking of their respective time series. The resulting scale and scale rate differences between the two solutions are 1.37 (±0.10) ppb at epoch 2010.0 and 0.02 (±0.02) ppb/yr. While the postseismic deformation models were estimated using GNSS/GPS data, the resulting parametric models at earthquake colocation sites were applied to the station position time series of the three other techniques, showing a very high level of consistency which enforces more the link between techniques within the ITRF2014 frame. The users should be aware that the postseismic deformation models are part of the ITRF2014 products, unlike the annual and semiannual signals, which were estimated internally with the only purpose of enhancing the velocity field estimation of the secular frame.

Journal ArticleDOI
TL;DR: The data for GBS suggests that the immunologic mechanism can involve molecular mimicry, at least in some GBS variants, and it is likely that multiple mechanisms render the axon vulnerable.

Journal ArticleDOI
TL;DR: A review of the research carried out so far in determining and optimizing the process parameters of the FDM process can be found in this paper, where several statistical designs of experiments and optimization techniques used for the determination of optimum process parameters have been examined.
Abstract: Fused deposition modeling (FDM) is one of the most popular additive manufacturing technologies for various engineering applications. FDM process has been introduced commercially in early 1990s by Stratasys Inc., USA. The quality of FDM processed parts mainly depends on careful selection of process variables. Thus, identification of the FDM process parameters that significantly affect the quality of FDM processed parts is important. In recent years, researchers have explored a number of ways to improve the mechanical properties and part quality using various experimental design techniques and concepts. This article aims to review the research carried out so far in determining and optimizing the process parameters of the FDM process. Several statistical designs of experiments and optimization techniques used for the determination of optimum process parameters have been examined. The trends for future FDM research in this area are described.

Journal ArticleDOI
TL;DR: A conceptual models for the COVID-19 outbreak in Wuhan with the consideration of individual behavioural reaction and governmental actions is proposed, and it successfully captures the course of the COIDs, and thus sheds light on understanding the trends of the outbreak.

Journal ArticleDOI
TL;DR: Norovirus remains the leading cause of foodborne disease outbreaks, highlighting the continued need for food safety improvements targeting worker health and hygiene in food service settings.
Abstract: PROBLEM/CONDITION Foodborne diseases cause an estimated 48 million illnesses each year in the United States, including 9.4 million caused by known pathogens. Foodborne disease outbreak surveillance provides valuable insights into the agents and foods that cause illness and the settings in which transmission occurs. CDC maintains a surveillance program for collection and periodic reporting of data on the occurrence and causes of foodborne disease outbreaks in the United States. This surveillance system is the primary source of national data describing the numbers of illnesses, hospitalizations, and deaths; etiologic agents; implicated foods; contributing factors; and settings of food preparation and consumption associated with recognized foodborne disease outbreaks in the United States. REPORTING PERIOD 1998-2008. DESCRIPTION OF THE SYSTEM The Foodborne Disease Outbreak Surveillance System collects data on foodborne disease outbreaks, defined as the occurrence of two or more cases of a similar illness resulting from the ingestion of a common food. Public health agencies in all 50 states, the District of Columbia, U.S. territories, and Freely Associated States have primary responsibility for identifying and investigating outbreaks and use a standard form to report outbreaks voluntarily to CDC. During 1998-2008, reporting was made through the electronic Foodborne Outbreak Reporting System (eFORS). RESULTS During 1998-2008, CDC received reports of 13,405 foodborne disease outbreaks, which resulted in 273,120 reported cases of illness, 9,109 hospitalizations, and 200 deaths. Of the 7,998 outbreaks with a known etiology, 3,633 (45%) were caused by viruses, 3,613 (45%) were caused by bacteria, 685 (5%) were caused by chemical and toxic agents, and 67 (1%) were caused by parasites. Among the 7,724 (58%) outbreaks with an implicated food or contaminated ingredient reported, 3,264 (42%) could be assigned to one of 17 predefined commodity categories: fish, crustaceans, mollusks, dairy, eggs, beef, game, pork, poultry, grains/beans, oils/sugars, fruits/nuts, fungi, leafy vegetables, root vegetables, sprouts, and vegetables from a vine or stalk. The commodities implicated most commonly were poultry (18.9%; 95% confidence interval [CI] = 17.4-20.3) and fish (18.6%; CI = 17.2-20), followed by beef (11.9%; CI = 10.8-13.1). The pathogen-commodity pairs most commonly responsible for outbreaks were scombroid toxin/histamine and fish (317 outbreaks), ciguatoxin and fish (172 outbreaks), Salmonella and poultry (145 outbreaks), and norovirus and leafy vegetables (141 outbreaks). The pathogen-commodity pairs most commonly responsible for outbreak-related illnesses were norovirus and leafy vegetables (4,011 illnesses), Clostridium perfringens and poultry (3,452 illnesses), Salmonella and vine-stalk vegetables (3,216 illnesses), and Clostridium perfringens and beef (2,963 illnesses). Compared with the first 2 years of the study (1998-1999), the percentage of outbreaks associated with leafy vegetables and dairy increased substantially during 2006-2008, while the percentage of outbreaks associated with eggs decreased. INTERPRETATION Outbreak reporting rates and implicated foods varied by state and year, respectively; analysis of surveillance data for this 11-year period provides important information regarding changes in sources of illness over time. A substantial percentage of foodborne disease outbreaks were associated with poultry, fish, and beef, whereas many outbreak-related illnesses were associated with poultry, leafy vegetables, beef, and fruits/nuts. The percentage of outbreaks associated with leafy vegetables and dairy increased during the surveillance period, while the percentage associated with eggs decreased. PUBLIC HEALTH ACTIONS Outbreak surveillance data highlight the etiologic agents, foods, and settings involved most often in foodborne disease outbreaks and can help to identify food commodities and preparation settings in which interventions might be most effective. Analysis of data collected over several years of surveillance provides a means to assess changes in the food commodities associated most frequently with outbreaks that might occur following improvements in food safety or changes in consumption patterns or food preparation practices. Prevention of foodborne disease depends on targeted interventions at appropriate points from food production to food preparation. Efforts to reduce foodborne illness should focus on the pathogens and food commodities causing the most outbreaks and outbreak-associated illnesses, including beef, poultry, fish, and produce.

Journal ArticleDOI
TL;DR: A comprehensive overview of sparse representation is provided and an experimentally comparative study of these sparse representation algorithms was presented, which could sufficiently reveal the potential nature of the sparse representation theory.
Abstract: Sparse representation has attracted much attention from researchers in fields of signal processing, image processing, computer vision, and pattern recognition. Sparse representation also has a good reputation in both theoretical research and practical applications. Many different algorithms have been proposed for sparse representation. The main purpose of this paper is to provide a comprehensive study and an updated review on sparse representation and to supply guidance for researchers. The taxonomy of sparse representation methods can be studied from various viewpoints. For example, in terms of different norm minimizations used in sparsity constraints, the methods can be roughly categorized into five groups: 1) sparse representation with $l_{0}$ -norm minimization; 2) sparse representation with $l_{p}$ -norm ( $0 ) minimization; 3) sparse representation with $l_{1}$ -norm minimization; 4) sparse representation with $l_{2,1}$ -norm minimization; and 5) sparse representation with $l_{2}$ -norm minimization. In this paper, a comprehensive overview of sparse representation is provided. The available sparse representation algorithms can also be empirically categorized into four groups: 1) greedy strategy approximation; 2) constrained optimization; 3) proximity algorithm-based optimization; and 4) homotopy algorithm-based sparse representation. The rationales of different algorithms in each category are analyzed and a wide range of sparse representation applications are summarized, which could sufficiently reveal the potential nature of the sparse representation theory. In particular, an experimentally comparative study of these sparse representation algorithms was presented.

Journal ArticleDOI
TL;DR: The transcriptional activation and repression mechanisms by PPAR α, the spectrum of target genes and chromatin-binding maps from recent genome-wide studies, are discussed, paying particular attention to PPARα-regulation of hepatic fatty acid and plasma lipoprotein metabolism during nutritional transition, and of the inflammatory response.

Journal ArticleDOI
TL;DR: In this paper, the first electronic structure calculation performed on a quantum computer without exponentially costly precompilation is reported, where a programmable array of superconducting qubits is used to compute the energy surface of molecular hydrogen using two distinct quantum algorithms.
Abstract: We report the first electronic structure calculation performed on a quantum computer without exponentially costly precompilation. We use a programmable array of superconducting qubits to compute the energy surface of molecular hydrogen using two distinct quantum algorithms. First, we experimentally execute the unitary coupled cluster method using the variational quantum eigensolver. Our efficient implementation predicts the correct dissociation energy to within chemical accuracy of the numerically exact result. Second, we experimentally demonstrate the canonical quantum algorithm for chemistry, which consists of Trotterization and quantum phase estimation. We compare the experimental performance of these approaches to show clear evidence that the variational quantum eigensolver is robust to certain errors. This error tolerance inspires hope that variational quantum simulations of classically intractable molecules may be viable in the near future.