Miracle-dz/UniFAR-FTUs huggingface dataset:
ZMYND8 acetylation mediates HIF-dependent breast cancer progression and metastasis

Altered epigenetic reprogramming contributes to breast cancer progression and metastasis. How the epigenetic reader mediates breast cancer progression remains poorly understood. Here, we showed that the epigenetic reader zinc finger MYND-type containing 8 (ZMYND8) is induced by HIF-1 and HIF-2 in breast cancer cells and also upregulated in human breast tumors, and is correlated with poor survival of patients with breast cancer. Genetic deletion of ZMYND8 decreases breast cancer cell colony formation, migration, and invasion in vitro, and inhibits breast tumor growth and metastasis to the lungs in mice. The ZMYND8’s oncogenic effect in breast cancer requires HIF-1 and HIF-2. We further showed that ZMYND8 interacts with HIF-1&agr; and HIF-2&agr; and enhances elongation of the global HIF-induced oncogenic genes by increasing recruitment of BRD4 and subsequent release of paused RNA polymerase II in breast cancer cells. ZMYND8 acetylation at lysines 1007 and 1034 by p300 is required for HIF activation and breast cancer progression and metastasis. These findings uncover a primary epigenetic mechanism of HIF activation and HIF-mediated breast cancer progression, and discover a possible molecular target for the diagnosis and treatment of breast cancer.
Method of reproducibly predamaging float glass as a basis to determine the bending strength

Strength measurements on commercial float glass result in a wide range of randomly distributed values. Such a random statistical distribution leads, if extrapolated to low fracture probabilities, to unrealistically low strength values which cannot be taken as a basis for design. We introduce a method of reproducibly predamaging float glass. The glass surfaces which are under tensile stress are predamaged to an extent which is not achieved in normal practical applications. This predamaging reduces the bending strength and narrows the random range of measured values. The strength tests with the following statistical evaluation of the treated float glass specimens will more easily come up to the fracture behaviour of glass in practical use and can thus be adopted as a basis for the design of float glass according to a probabilistic approach
Increased superconductivity for CNT doped MgB2 sintered in 5T pulsed magnetic field

The superconductivity of carbon nanotube (CNT) doped MgB sintered in pulsed magnetic field (PMF) was investigated with Raman scattering measurements and Raman spectral fit analysis. Although the carbon (C) substitution for the boron (B) is increased for the sample sintered in PMF, its superconductivity is advanced comparing with the sample sintered without PMF. The improved critical transition temperature, , is attributed to the strengthening of the electron-phonon coupling (EPC) in MgB , as reflected by the broadened mode in the Raman spectra, because the carbon atoms are homogeneously distributed in the boron planes.
P2P-NET

We introduce P2P-NET, a general-purpose deep neural network which learns geometric transformations between point-based shape representations from two domains, e.g., meso-skeletons and surfaces, partial and complete scans, etc. The architecture of the P2P-NET is that of a bi-directional point displacement network, which transforms a source point set to a prediction of the target point set with the same cardinality, and vice versa, by applying point-wise displacement vectors learned from data. P2P-NET is trained on paired shapes from the source and target domains, but without relying on point-to-point correspondences between the source and target point sets. The training loss combines two uni-directional geometric losses, each enforcing a shape-wise similarity between the predicted and the target point sets, and a cross-regularization term to encourage consistency between displacement vectors going in opposite directions. We develop and present several different applications enabled by our general-purpose bidirectional P2P-NET to highlight the effectiveness, versatility, and potential of our network in solving a variety of point-based shape transformation problems.
Are Multidimensional Recurrent Layers Really Necessary for Handwritten Text Recognition?

Current state-of-the-art approaches to offline Handwritten Text Recognition extensively rely on Multidimensional Long Short-Term Memory networks. However, these architectures come with quite an expensive computational cost, and we observe that they extract features visually similar to those of convolutional layers, which are computationally cheaper. This suggests that the two-dimensional long-term dependencies, which are potentially modeled by multidimensional recurrent layers, may not be essential to achieve a good recognition accuracy, at least in the lower layers of the architecture. In this work, an alternative model is explored that relies only on convolutional and one-dimensional recurrent layers that achieves better or equivalent results than those of the current state-of-the-art architecture, and runs significantly faster. In addition, we observe that using random distortions during training as synthetic data augmentation dramatically improves the accuracy of our model. Thus, are multidimensional recurrent layers really necessary for Handwritten Text Recognition? Probably not.
In vivo imaging reveals that pregabalin inhibits cortical spreading depression and propagation to subcortical brain structures

Significance Spreading depression is proposed to underlie migraine with aura, a type of debilitating headache for which few pharmacological treatments are available. The pain drug pregabalin has demonstrated initial promising results for the treatment of migraine in the clinic. Utilizing animal models of congenital migraine and live brain imaging, we describe the cortical and subcortical migration of the spreading depression wave. Further, pregabalin is shown to be effective at suppressing spreading depression initiation, wave speed, and subcortical propagation, and also to affect nerve cell signalling directly. Overall, the study supports the therapeutic potential of pregabalin in both noncongenital migraineurs and patients with mild congenital migraine. Migraine is characterized by severe headaches that can be preceded by an aura likely caused by cortical spreading depression (SD). The antiepileptic pregabalin (Lyrica) shows clinical promise for migraine therapy, although its efficacy and mechanism of action are unclear. As detected by diffusion-weighted MRI (DW-MRI) in wild-type (WT) mice, the acute systemic administration of pregabalin increased the threshold for SD initiation in vivo. In familial hemiplegic migraine type 1 mutant mice expressing human mutations (R192Q and S218L) in the CaV2.1 (P/Q-type) calcium channel subunit, pregabalin slowed the speed of SD propagation in vivo. Acute systemic administration of pregabalin in vivo also selectively prevented the migration of SD into subcortical striatal and hippocampal regions in the R192Q strain that exhibits a milder phenotype and gain of CaV2.1 channel function. At the cellular level, pregabalin inhibited glutamatergic synaptic transmission differentially in WT, R192Q, and S218L mice. The study describes a DW-MRI analysis method for tracking the progression of SD and provides support and a mechanism of action for pregabalin as a possible effective therapy in the treatment of migraine.
Do Android taint analysis tools keep their promises?

In recent years, researchers have developed a number of tools to conduct taint analysis of Android applications. While all the respective papers aim at providing a thorough empirical evaluation, comparability is hindered by varying or unclear evaluation targets. Sometimes, the apps used for evaluation are not precisely described. In other cases, authors use an established benchmark but cover it only partially. In yet other cases, the evaluations differ in terms of the data leaks searched for, or lack a ground truth to compare against. All those limitations make it impossible to truly compare the tools based on those published evaluations. We thus present ReproDroid, a framework allowing the accurate comparison of Android taint analysis tools. ReproDroid supports researchers in inferring the ground truth for data leaks in apps, in automatically applying tools to benchmarks, and in evaluating the obtained results. We use ReproDroid to comparatively evaluate on equal grounds the six prominent taint analysis tools Amandroid, DIALDroid, DidFail, DroidSafe, FlowDroid and IccTA. The results are largely positive although four tools violate some promises concerning features and accuracy. Finally, we contribute to the area of unbiased benchmarking with a new and improved version of the open test suite DroidBench.
Pharmacist medication reviews to improve safety monitoring in primary care patients.

OBJECTIVE Patients prescribed psychotropic medications within primary care are at risk of suboptimal monitoring. It is unknown whether pharmacists can improve medication safety through targeted monitoring of at risk populations. Access Community Health Centers implemented a quality improvement pilot project that included pharmacists on an integrated care team to provide medication reviews for patients. Aims were to determine whether inclusion of a pharmacist performing medication reviews within a primary care behavioral health (PCBH) practice is feasible and facilitates safe medication use. METHOD Pharmacists performed medication reviews of the electronic health record for patients referred for psychiatry consultation. Reviews were performed 1-3 months following consultation and focused on medications with known suboptimal monitoring rates. Reviews were documented within the EHR and routed to the primary care provider. Primary outcome measures were change in percentage up-to-date on monitoring and AIMS assessment, and at risk of experiencing drug interaction(s) between baseline and 3 months postreview. Secondary outcome was provider opinion of medication reviews collected via electronic survey. RESULTS Reviews were performed for 144 patients. Three months postreview, percentage up-to-date on recommended monitoring increased 18% (p = .0001), at risk for drug interaction decreased 20% (p < .0001), and up-to-date on AIMS decreased 12% (p = .2113). The majority of surveyed providers wanted medication reviews to continue. CONCLUSION Pharmacist population-level monitoring within an integrated care team is feasible and associated with improved safety monitoring of psychotropic medications. Results identify key areas for improvement that other clinics considering integration of similar pharmacy services should consider. (PsycINFO Database Record
Food Insecurity and Cardiometabolic Risk Factors in Adolescents

Introduction Food insecurity is associated with poor cardiometabolic health in adults. The extent to which this relationship exists in adolescents has yet to be defined. The objective of this study was to examine the relationship between food insecurity and cardiometabolic risk factors in adolescents. Methods We evaluated the association between food insecurity and several cardiometabolic risk factors by using data collected from the Youth Risk Behavior Survey at the state and city levels. Logistic regression models adjusted for sex, race/ethnicity, grade, and neighborhood safety were used to determine the association between food insecurity and cardiometabolic risk factors among a weighted sample of 495,509 adolescents. Results Of the sample studied, 12.8% reported being food insecure. Food-insecure adolescents had more than a twofold increased odds of not eating breakfast on all 7 days (adjusted odds ratio [AOR] = 2.27; 95% confidence interval [CI], 1.61–3.21; P < .001), a 60% increased odds of reporting less than 8 hours per day of sleep (AOR = 1.60; 95% CI, 1.15–2.23; P = .006), a 65% increased odds of reporting current cigarette smoking (AOR = 1.65; 95% CI, 1.16–2.36; P = .006), and a 65 % increased odds of current alcohol consumption (AOR = 1.36; CI, 1.01–1.84; P = .04), compared with food-secure adolescents. Conclusion Among adolescents, in adjusted models, food insecurity was significantly associated with not consuming breakfast daily, getting less than 8 hours of sleep per day, currently smoking, and currently drinking alcohol. Food insecurity in adolescents may serve as an important precursor to poor cardiometabolic health.
POL-LWIR Vehicle Detection: Convolutional Neural Networks Meet Polarised Infrared Sensors

For vehicle autonomy, driver assistance and situational awareness, it is necessary to operate at day and night, and in all weather conditions. In particular, long wave infrared (LWIR) sensors that receive predominantly emitted radiation have the capability to operate at night as well as during the day. In this work, we employ a polarised LWIR (POL-LWIR) camera to acquire data from a mobile vehicle, to compare and contrast four different convolutional neural network (CNN) configurations to detect other vehicles in video sequences. We evaluate two distinct and promising approaches, two-stage detection (Faster-RCNN) and one-stage detection (SSD), in four different configurations. We also employ two different image decompositions: the first based on the polarisation ellipse and the second on the Stokes parameters themselves. To evaluate our approach, the experimental trials were quantified by mean average precision (mAP) and processing time, showing a clear trade-off between the two factors. For example, the best mAP result of 80.94 % was achieved using Faster-RCNN, but at a frame rate of 6.4 fps. In contrast, MobileNet SSD achieved only 64.51 % mAP, but at 53.4 fps.
Dietary oregano (Origanum vulgare L.) aqueous extract improves oxidative stability and consumer acceptance of meat enriched with CLA and n‐3 PUFA in broilers.

&NA; The effect of a dietary oregano aqueous extract on meat fatty acid profile, quality, and consumer acceptance in chickens fed a diet rich in polyunsaturated fatty acids (PUFA) was evaluated in 3 consecutive trials. For each trial, 171 day‐old Ross 308 chicks were randomly divided in replicates of 19 birds each and assigned to one of 3 experimental diets: 1) basal control diet, 2) basal diet supplemented with 0.2 g/kg of oregano aqueous extract, and 3) basal diet supplemented with 150 ppm of vitamin E (as positive control). To better analyze the antioxidant activity of both oregano and vitamin E, all the experimental diets were enriched with a fatty acid supplement consisting in a mixture of PUFA at the same dose (1.16 %) in both starter and finisher feeds. Oregano supplementation positively influenced (P < 0.05) broiler live performance. No differences were observed in physicochemical or proximal composition or in total fatty acid composition of breast meat. Dietary oregano influenced meat composition in terms of total phenolic content, antioxidant capacity, and thiobarbituric acid‐reactive substances, improving meat resistance to oxidation, compared to both other groups. During consumer tests, meat from the 3 dietary groups obtained the same liking score in a blind session. Under informed condition, consumer perception was positively influenced by labeling for all the considered attributes. Furthermore, consumers showed a higher expectation for meat derived from chickens fed the oregano extract when compared to that deriving from the other 2 groups. Results obtained in the present study allow stating that using oregano aqueous extract in diets enriched with PUFA can represent a valid solution to increase live weight of chickens, improve resistance to oxidation of meat, and positively influence consumer perception of poultry meat.
Data2Vis: Automatic Generation of Data Visualizations Using Sequence-to-Sequence Recurrent Neural Networks

Rapidly creating effective visualizations using expressive grammars is challenging for users who have limited time and limited skills in statistics and data visualization. Even high-level, dedicated visualization tools often require users to manually select among data attributes, decide which transformations to apply, and specify mappings between visual encoding variables and raw or transformed attributes. In this paper we introduce Data2Vis, an end-to-end trainable neural translation model for automatically generating visualizations from given datasets. We formulate visualization generation as a language translation problem, where data specifications are mapped to visualization specifications in a declarative language (Vega-Lite). To this end, we train a multilayered attention-based encoder–decoder network with long short-term memory (LSTM) units on a corpus of visualization specifications. Qualitative results show that our model learns the vocabulary and syntax for a valid visualization specification, appropriate transformations (count, bins, mean), and how to use common data selection patterns that occur within data visualizations. We introduce two metrics for evaluating the task of automated visualization generation (language syntax validity, visualization grammar syntax validity) and demonstrate the efficacy of bidirectional models with attention mechanisms for this task. Data2Vis generates visualizations that are comparable to manually created visualizations in a fraction of the time, with potential to learn more complex visualization strategies at scale.
Fall-related accidents among hikers in the Austrian Alps: a 9-year retrospective study

Objective To analyse the circumstances of fatal and non-fatal mountain hiking accidents caused by falls. Methods The study was designed as a retrospective analysis. Mountain hiking accidents caused by falls were documented during a 9-year period (2006–2014). After screening of all data for potential exclusion criteria the final sample size of 5368 accidents and 5665 victims was included into the analyses. Main outcome measures were details about accidents, victims, type of trail and surface. Results The annual number of accidents showed a continuous increase from 467 in 2006 to 700 in 2014. In total, 5.8% of all victims died during the 9-year period. 75.3% of the hikers fell during descent and 80.9% of the victims had their accident on a marked hiking trail or small path. The sex ratio for non-fatal accidents was 55% female and 45% male; for fatal accidents the female-to-male ratio was 28%:72%. Mean age of all victims was 52.5±17.5 years and victims of fatalities were about 5 years older compared with victims of non-fatal accidents (57.5±16.5 vs 52.2±17.5 years, P<0.01). Conclusion Descent is the most risky part for accidents caused by falls during mountain hiking. Male hikers are at greater risk for fatalities independent of age and this is associated with accidents occurring in pathless terrain. The death rate from falls was 6%. We recommend a critical self-assessment of the individual capabilities and mountain hiking skills and adequate planning of the hiking tours for mountain hikers.
Performance Evaluation of LoRa Considering Scenario Conditions

New verticals within the Internet of Things (IoT) paradigm such as smart cities, smart farming, or goods monitoring, among many others, are demanding strong requirements to the Radio Access Network (RAN) in terms of coverage, end-node’s power consumption, and scalability. The technologies employed so far to provide IoT scenarios with connectivity, e.g., wireless sensor network and cellular technologies, are not able to simultaneously cope with these three requirements. Thus, a novel solution known as Low Power - Wide Area Network (LP-WAN) has emerged as a promising alternative to provide with low-cost and low-power-consumption connectivity to end-nodes spread in a wide area. Concretely, the Long-Range Wide Area Network (LoRaWAN) technology is one of the LP-WAN platforms that is receiving greater attention from both the industry and the academia. For that reason, in this work, a comprehensive performance evaluation of LoRaWAN under different environmental conditions is presented. The results are obtained from three real scenarios, namely, urban, suburban, and rural, considering both dynamic and static conditions, hence a discussion about the most proper LoRaWAN physical-layer configuration for each scenario is provided. Besides, a theoretical coverage study is also conducted by the use of a radio planning tool considering topographic maps and a precise propagation model. From the attained results, it can be concluded that it is necessary to evaluate the propagation conditions of the deployment scenario prior to the system implantation in order to reach a compromise between the robustness of the network and the transmission data-rate.
Minimally invasive small intestinal exploration and targeted abdominal organ biopsy with a wound retraction device in 42 cats (2005‐2015)

OBJECTIVE To describe the surgical technique and evaluate short-term outcome after minimally invasive small intestinal exploration and targeted organ biopsy with a wound retractor device (WRD) in cats. STUDY DESIGN Multi-institutional retrospective study. ANIMALS Forty-two cats. METHODS A wound retractor was inserted into the abdomen on the ventral midline through a 2-4 cm incision at the level of the umbilicus. Short segments (6-10 cm long) of intestinal tract were sequentially exteriorized and explored through the WRD. Full thickness, small intestinal biopsies were obtained extracorporeally via the WRD. A commercially available single-port device was inserted through the WRD for laparoscopic exploration of the abdomen. RESULTS The majority of the small intestine could be exteriorized and explored through the WRD. In all cases, full thickness biopsies of the small intestine of diagnostic quality were obtained. The most common histological findings were inflammatory bowel disease (n = 16), intestinal lymphoma (n = 14), and eosinophilic enteritis (n = 7). Two cases required conversion to a traditional open laparotomy due to abdominal pathology diagnosed after placement of the WRD (abdominal adhesions and need for a splenectomy). Postoperative complications occurred in 4 of 39 cats (10.3%), leading to 2 deaths after discharge from the hospital. CONCLUSIONS AND CLINICAL RELEVANCE MISIETB with a WRD alone or combined with laparoscopy is a safe technique for small intestinal exploration and targeted abdominal organ biopsy in cats. Single-port laparoscopy can effectively be performed through the WRD for complete abdominal exploration and biopsy of abdominal organs.