Miracle-dz/UniFAR-FTUs huggingface dataset:
BRAFV600E Mutation Does Not Significantly Affect the Efficacy of Radioiodine Therapy in Patients With Papillary Thyroid Carcinoma Without Known Distant Metastases

Purpose The BRAFV600E mutation is the most common and specific oncogenic event in papillary thyroid carcinoma (PTC). However, its role in radioiodine therapy decision making has yet to be established. This study aimed to evaluate the impact of the BRAFV600E mutation on the clinical response to radioiodine therapy. Methods This retrospective study included PTC patients who received total thyroidectomy with lymph node dissection, radioiodine therapy, and thyroid-stimulating hormone suppression between January 2012 and March 2016. Included patients were divided into 2 groups based on the BRAF mutation status. The association between the clinicopathological characteristics and the BRAFV600E mutation was evaluated. After a median follow-up of 37 months, the clinical outcome between these 2 groups was also compared based on the ongoing risk stratification. Results A total of 512 PTC patients without distant metastases were included, with a positive BRAF mutation in 338 patients. No significant association was observed between the BRAF mutation and clinicopathological characteristics, except for sex, tumor size, and extrathyroidal extension. The initial risk stratification between the positive and negative mutation groups revealed no significant difference (P = 0.845). At the end of follow-up, no significant difference regarding the clinical response to radioiodine therapy was demonstrated between these 2 groups for all patients or patients with high recurrence risk (P = 0.586 and P = 0.680, respectively). Conclusions The BRAFV600E mutation status may not impact the clinical response to radioiodine therapy for PTC patients without distant metastases.
Normal Similarity Network for Generative Modelling

Gaussian distributions are commonly used as a key building block in many generative models. However, their applicability has not been well explored in deep networks. In this paper, we propose a novel deep generative model named as Normal Similarity Network (NSN) where the layers are constructed with Gaussian-style filters. NSN is trained with a layer-wise non-parametric density estimation algorithm that iteratively down-samples the training images and capture the density of the down-sampled training images in the final layer. Additionally, we propose NSN-Gen for generating new samples from noise vectors by iteratively reconstructing feature maps in the hidden layers of NSN. Our experiments suggest encouraging results of the proposed model for a wide range of computer vision applications including image generation, styling and reconstruction from occluded images.
Environmental Variability and Macrophyte Assemblages in Coastal Lagoon Types of Western Greece (Mediterranean Sea)

Coastal lagoon types of Western Greece were allocated to a spectrum of meso to polyhaline chocked lagoons; poly to euhaline restricted lagoons; and euhaline restricted lagoons along the Ionian Sea coast. This diversity comprises wide ranges of physical, chemical and environmental parameters in a seasonal and annual scale, which explains the variability in the distribution of benthic macrophytes. Four different macrophyte assemblages were distinguished, characterized by annual or perennial species. Extensive statistical analysis showed that salinity and nitrate concentrations had a great impact on the composition and distribution of macrophyte assemblages into lagoon types that also changed their abundance on a seasonal and annual scale. During the monitoring period, an important salinity shift in a chocked lagoon might cause the gradual loss of Zostera noltii and its replacement by Ruppia cirrhosa. Restricted lagoons were characterized by higher species diversity, while the other three identified macrophyte assemblages were dominated by the angiosperms Ruppia cirrhosa and Cymodocea nodosa. This integrated study of coastal lagoons is likely to be broadly applicable, since it was based on important parameters affecting such ecosystems, and the provided links between macrophyte assemblages and abiotic factors are of critical importance to improve management and environmental policies.
Quantifying Climatic Impact on Reference Evapotranspiration Trends in the Huai River Basin of Eastern China

Reference evapotranspiration (ETref) is an important study object for hydrological cycle processes in the context of drought-flood risks of the Huai River Basin (HRB). In this study, the FAO-56 Penman–Monteith (PM) model was employed to calculate seasonal and annual ETref based on 137 meteorological station data points in HRB from 1961 to 2014. The Mann–Kendall (MK) trend analysis was adopted together with Theil–Sen’s estimator to detect tendencies of ETref and climate factors. Furthermore, a developed differential equation method based on the FAO-56 PM model was applied to quantify the sensitivities of ETref to meteorological factors and their contributions to ETref trends. The results showed that the ETref demonstrated a strong spatially heterogeneity in the whole HRB at each time scale. ETref showed a significant decreasing trend in the upper-middle HRB and Yi-Shu-Si River Basin, especially at the annual time scale, in growing season and summer, while a generally increasing trend in ETref was detected in the lower HRB, and the significance only showed in spring. These phenomena could be reasonably explained by a significantly increasing mean temperature (TA), a significantly decreasing wind speed (WS), solar radiation (SR), and a slightly decreasing relative humidity (RH). The most sensitive factor to ETref was RH in most sub-regions and most time scales, except in the growing season and summer. Based on the developed differential equation method, the dominant factor of the decreasing ETref was WS in the annual time scale, spring, autumn, and winter in most sub-regions, except the lower HRB, which then shifted to SR in the growing season and summer. However, in the lower HRB, the significantly decreasing RH was the most dominant factor, especially in the annual time scale, growing season, and spring, which might be responsible for the slightly increasing ETref there.
Selective reduction of CAD false-positive findings

Computer-Aided Detection (CAD) systems are becoming widespread supporting tools to radiologists' diagnosis, especially in screening contexts. However, a large amount of false positive (FP) alarms would inevitably lead both to an undesired possible increase in time for diagnosis, and to a reduction in radiologists' confidence in CAD as a useful tool. Most CAD systems implement as final step of the analysis a classifier which assigns a score to each entry of a list of findings; by thresholding this score it is possible to define the system performance on an annotated validation dataset in terms of a FROC curve (sensitivity vs. FP per scan). To use a CAD as a supportive tool for most clinical activities, an operative point has to be chosen on the system FROC curve, according to the obvious criterion of keeping the sensitivity as high as possible, while maintaining the number of FP alarms still acceptable. The strategy proposed in this study is to choose an operative point with high sensitivity on the CAD FROC curve, then to implement in cascade a further classification step, constituted by a smarter classifier. The key issue of this approach is that the smarter classifier is actually a meta-classifier of more then one decision system, each specialized in rejecting a particular type of FP findings generated by the CAD. The application of this approach to a dataset of 16 lung CT scans previously processed by the VBNACAD system is presented. The lung CT VBNACAD performance of 87.1% sensitivity to juxtapleural nodules with 18.5 FP per scan is improved up to 10.1 FP per scan while maintaining the same value of sensitivity. This work has been carried out in the framework of the MAGIC-V collaboration.
Remote sensing of the tropical rain forest boundary layer using pulsed Doppler lidar

Abstract. Within the framework of the Natural Environment Research Council (NERC) Oxidant and Particle Photochemical Processes (OP3) project, a pulsed Doppler lidar was deployed for a 3 month period in the tropical rain forest of Borneo to remotely monitor vertical and horizontal transport, aerosol distributions and clouds in the lower levels of the atmosphere. The Doppler velocity measurements reported here directly observe the mixing process and it is suggested that this is the most appropriate methodology to use in analysing the dispersion of canopy sourced species into the lower atmosphere. These data are presented with a view to elucidating the scales and structures of the transport processes, which effect the chemical and particulate concentrations in and above the forest canopy, for applications in the parameterisation of climate models.
Evidencing Protective and Risk Factors for Harmful Alcohol Drinking in Adolescence: A Prospective Analysis of Sport-Participation and Scholastic-Achievement in Older Adolescents from Croatia

Background: The prevalence of alcohol drinking (AD) in Croatian adolescents is alarming, but there is an evident lack of prospective analyses of the protective/risk factors of AD. This study aimed to prospectively investigate the relationships between scholastic and sport factors and harmful alcohol drinking (HD) in older adolescents. Methods: The participants (n = 644, 53.7% females) were 16 years of age at study baseline and were tested at baseline and again 20 months later (follow-up). The predictors included four variables of scholastic achievement and four factors evidencing involvement in sport. Criterion was AD observed on the Alcohol Use Disorders Identification Test (AUDIT), and results were later categorized into harmful drinking (HD) and non-harmful drinking (NHD). The HD at baseline, HD at follow-up and HD initiation during the study course were observed as criteria in logistic regression analyses, which were additionally controlled for confounders (age, gender, socioeconomic status, and conflict with parents). Results: With 22% and 29% adolescents who reported HD at baseline and follow-up, respectively, the prevalence of HD remains among the highest in Europe. Scholastic failure was systematically related to HD at baseline and follow-up, but scholastic variables did not predict HD initiation during the course of the study. The higher odds for HD at baseline were evidenced for current and former team sport athletes. Those who quit individual sport were more likely to engage in HD at follow-up. Longer involvement in sport (OR: 2.10, 95% CI: 1.18–3.72), higher sport result (OR: 3.15, 95% CI: 1.19–8.34), and quitting individual sport (OR: 13.13, 95% CI: 2.67–64.62) were predictive of HD initiation. Conclusions: The results indicated specific associations between sport factors with HD initiation, which is understandable knowing the high stress placed on young athletes in this period of life, mainly because of the forthcoming selection between junior (amateur) and senior (professional) level. The results did not allow interpretation of the cause-effect relationship between scholastic failure and HD in the studied period.
Lehmer Transform and its Theoretical Properties

We propose a new class of transforms that we call {\it Lehmer Transform} which is motivated by the {\it Lehmer mean function}. The proposed {\it Lehmer transform} decomposes a function of a sample into their constituting statistical moments. Theoretical properties of the proposed transform are presented. This transform could be very useful to provide an alternative method in analyzing non-stationary signals such as brain wave EEG.
Heterogeneity in the Relationship between Disinfection By-Products in Drinking Water and Cancer: A Systematic Review

The epidemiological evidence demonstrating the effect of disinfection by-products (DBPs) from drinking water on colon and rectal cancers is well documented. However, no systematic assessment has been conducted to assess the potential effect measure modification (EMM) in the relationship between DBPs and cancer. The objective of this paper is to conduct a systematic literature review to determine the extent to which EMM has been assessed in the relationship between DBPs in drinking water in past epidemiological studies. Selected articles (n = 19) were reviewed, and effect estimates and covariates that could have been used in an EMM assessment were gathered. Approximately half of the studies assess EMM (n = 10), but the majority of studies only estimate it relative to sex subgroups (n = 6 for bladder cancer and n = 2 both for rectal and colon cancers). Although EMM is rarely assessed, several variables that could have a potential modification effect are routinely collected in these studies, such as socioeconomic status or age. The role of environmental exposures through drinking water can play an important role and contribute to cancer disparities. We encourage a systematic use of subgroup analysis to understand which populations or territories are more vulnerable to the health impacts of DBPs.
Aztreonam-Avibactam Combination Restores Susceptibility of Aztreonam in Dual-Carbapenemase-Producing Enterobacteriaceae

Newly approved Food and Drug Administration (FDA) β-lactam-β-lactamase inhibitor (βL-βLI) inhibitor combinations such as ceftazidime-avibactam and meropenem-vaborbactam are potent inhibitors of class A carbapenemase (typified by KPC [Klebsiella pneumoniae carbapenemase]-like) (1, 2) but are ineffective against carbapenemase-producing Enterobacteriaceae (CPE) producing class B metallo-β-lactamases (MβLs) such as New Delhi metallo-β-lactamase (NDM) (1-4). ….
Thrombotic characteristics of extracellular vesicles derived from prostate cancer cells

Prostate cancer (PC) patients in advanced stages of the disease have high risk of blood coagulation complications. The procoagulant molecule Tissue factor (TF), and the fibrinolysis inhibitor plasminogen activator inhibitor‐1 PAI‐1 play important role in this complication. Extracellular vesicles (EV) shed from cancer cells may contribute to the regulation of TF and PAI‐1. The procoagulant activity of EV can be associated with the oncogenic and metastatic characteristics of their cells.
Personality Traits, Strategies for Coping with Stress and the Level of Internet Addiction—A Study of Polish Secondary-School Students

Among the many contributing factors in addictions there are also those describing the individual characteristics and ways of dealing with various life challenges. Despite numerous studies in this area, there is still no unambiguous data on the nature and specificity of this relationship in different age groups. The aim of the study was to assess the relationship between personality dimensions and strategies of coping with stress and the level of Internet addiction. The study was funded by the Ministry of Health under grant no. 93/HM/2015. The study was carried out in a group of 383 persons aged 15 to 19 (M = 16.6, SD = 0.77) attending secondary schools. The following research tools were used: Ten Item Personality Measure, Brief Cope and Internet Addiction Test. Both specific personality traits and styles of coping with stress are related to the addiction to the analysed medium. The personality traits most strongly associated with the risky Internet use were conscientiousness and emotional stability. An association was demonstrated between Internet addiction and the use of coping strategies, such as disengagement, substance use and self-blame. The results obtained demonstrate a major role of personality-related factors in the development of Internet addiction. The attitude to difficulties seems to be the key issue. The findings presented also make it possible to delineate the areas for improvement (e.g., through psychoeducational interventions) to protect young people from the risk of developing the addiction.
SNAP23–Kif5 complex controls mGlu1 receptor trafficking

Metabotropic glutamate receptors are expressed at excitatory synapses and control synaptic transmission in mammalian brain. These receptors are involved in numerous patho-physiological functions. However, little is known about the molecular determinants responsible for their intracellular transport and membrane targeting. Here we investigated the nature of the molecular motor and adaptor protein responsible for trafficking and membrane localization of the group I metabotropic glutamate mGlu1 postsynaptic receptor in cultured hippocampal neurons. In proteomic studies, we identified the synaptosome-associated protein 23 (SNAP23) and the molecular motor Kif5 kinesin as proteins interacting with mGlu1 receptor. We showed that SNAP23, but not Kif5, directly interacts with mGlu1 receptor carboxyl terminus. Using a recombination approach to impair or enhance the interaction between SNAP23 and Kif5, we found that the SNAP23-Kif5 complex controls the trafficking of mGlu1 receptor along microtubules. Additional fluorescence recovery after cleavage experiments allowed us to identify a role of the complex in the receptor cell surface targeting. In conclusion, our study indicates that along dendritic processes Kif5-SNAP23 complex contributes to proper mGlu1 receptor trafficking and cell surface expression.
Zinc toxicity to Daphnia magna in a two‐species microcosm can be predicted from single‐species test data: The effects of phosphorus supply and pH

Ecological interactions and abiotic stress factors may significantly affect species sensitivities to toxicants, and these are not incorporated in standard single‐species tests. The present study tests whether a model, calibrated solely on single‐species data, can explain abiotic stress factors in a two‐species microcosm, a test applied to the effects of nutritional stress (phosphorus [P] limitation) on zinc (Zn) toxicity to Daphnia magna. A population model was developed based on P‐ and Zn‐dependent algal and daphnid growth. Two separate two‐species (phytoplankton Pseudokirchneriella subcapitata and consumer D. magna) microcosm experiments with P × Zn factorial combinations and a different pH (7.3 and 7.8) were set up to validate the model. The 21‐d daphnid population size was considerably reduced by increased Zn and by decreased P supply, with a significant (p < 0.001) interaction between the 2 factors. The observed median effective concentration (EC50) of Zn on D. magna population size varied 12‐fold (25 to 310 μg Zn L−1), with the lowest EC50 values found at the highest pH and high P treatments. For both experiments, Zn toxicity to D. magna was correctly predicted within a factor of 2 for EC50 values, and this is explained by the model through 1) a higher phytoplankton Zn sensitivity at higher pH, affecting food supply to D. magna, and 2) an increased algal P content at higher Zn, offering a nutritional benefit to daphnids that counteracts direct Zn toxicity under P limitation. The present study illustrates that indirect effects of Zn via producer–consumer relationships can outweigh the direct toxic effects and that models calibrated solely on single‐species test data can help with interpreting these results in two‐species systems. Environ Toxicol Chem 2018;37:2153–2164. © 2018 SETAC
Dynamic Kelvinlets : Secondary Motions based on Fundamental Solutions of Elastodynamics

Fig. 1. Dynamic Kelvinlets: A punch animation is augmented with impact waves generated by dynamic Kelvinlets, a novel approach for computing volumetric deformations with real-time feedback based on analytical solutions of linear elastodynamics. Top row shows elastic waves propagated across the character’s fist and forearm after impact with an imaginary wall. Bottom row shows a close-up of the animation sequence. ©Disney/Pixar
An adaptive 3D region growing algorithm to automatically segment and identify thoracic aorta and its centerline using computed tomography angiography scans

Thoracic Aortic Aneurysm (TAA) is a localized swelling of the thoracic aorta. The progressive growth of an aneurysm may eventually cause a rupture if not diagnosed or treated. This necessitates the need for an accurate measurement which in turn calls for the accurate segmentation of the aneurysm regions. Computer Aided Detection (CAD) is a tool to automatically detect and segment the TAA in the Computer tomography angiography (CTA) images. The fundamental major step of developing such a system is to develop a robust method for the detection of main vessel and measuring its diameters. In this paper we propose a novel adaptive method to simultaneously segment the thoracic aorta and to indentify its center line. For this purpose, an adaptive parametric 3D region growing is proposed in which its seed will be automatically selected through the detection of the celiac artery and the parameters of the method will be re-estimated while the region is growing thorough the aorta. At each phase of region growing the initial center line of aorta will also be identified and modified through the process. Thus the proposed method simultaneously detect aorta and identify its centerline. The method has been applied on CT images from 20 patients with good agreement with the visual assessment by two radiologists.
Oral anticoagulation and left atrial thrombi resolution in nonrheumatic atrial fibrillation or flutter: A systematic review and meta‐analysis

Oral anticoagulation (OAC) is prescribed for left atrial thrombi (LAT) in nonrheumatic atrial fibrillation (AF) and/or atrial flutter (AFL). The study objective was to review the existing evidence regarding LAT resolution in nonrheumatic AF and/or AFL with OAC agents.
Post-editing Effort of a Novel With Statistical and Neural Machine Translation

We conduct the first experiment in the literature in which a novel is translated automatically and then post-edited by professional literary translators. Our case study is Warbreaker, a popular fantasy novel originally written in English, which we translate into Catalan. We translated one chapter of the novel (over 3,700 words, 330 sentences) with two data-driven approaches to Machine Translation (MT): phrase-based statistical MT (PBMT) and neural MT (NMT). Both systems are tailored to novels; they are trained on over 100 million words of fiction. In the post-editing experiment, six professional translators with previous experience in literary translation translate subsets of this chapter under three alternating conditions: from scratch (the norm in the novel translation industry), post-editing PBMT, and post-editing NMT. We record all the keystrokes, the time taken to translate each sentence, as well as the number of pauses and their duration. Based on these measurements, and using mixed-effects models, we study post-editing effort across its three commonly studied dimensions: temporal, technical and cognitive. We observe that both MT approaches result in increases in translation productivity: PBMT by 18%, and NMT by 36%. Post-editing also leads to reductions in the number of keystrokes: by 9% with PBMT, and by 23% with NMT. Finally, regarding cognitive effort, post-editing results in fewer (29 and 42% less with PBMT and NMT, respectively) but longer pauses (14 and 25%).
Computer-aided diagnosis of digital mammography images using unsupervised clustering and biclustering techniques

A new methodology for computer aided diagnosis in digital mammography using unsupervised classification and classdependent feature selection is presented. This technique considers unlabeled data and provides unsupervised classes that give a better insight into classes and their interrelationships, thus improving the overall effectiveness of the diagnosis. This technique is also extended to utilize biclustering methods, which allow for definition of unsupervised clusters of both pathologies and features. This has potential to provide more flexibility, and hence better diagnostic accuracy, than the commonly used feature selection strategies. The developed methods are applied to diagnose digital mammographic images from the Mammographic Image Analysis Society (MIAS) database and the results confirm the potential for improving the current diagnostic rates.