Miracle-dz/UniFAR-FTUs huggingface dataset:
miR126-5p Downregulation Facilitates Axon Degeneration and NMJ Disruption via a Non–Cell-Autonomous Mechanism in ALS

Axon degeneration and disruption of neuromuscular junctions (NMJs) are key events in amyotrophic lateral sclerosis (ALS) pathology. Although the disease's etiology is not fully understood, it is thought to involve a non–cell-autonomous mechanism and alterations in RNA metabolism. Here, we identified reduced levels of miR126-5p in presymptomatic ALS male mice models, and an increase in its targets: axon destabilizing Type 3 Semaphorins and their coreceptor Neuropilins. Using compartmentalized in vitro cocultures, we demonstrated that myocytes expressing diverse ALS-causing mutations promote axon degeneration and NMJ dysfunction, which were inhibited by applying Neuropilin1 blocking antibody. Finally, overexpressing miR126-5p is sufficient to transiently rescue axon degeneration and NMJ disruption both in vitro and in vivo. Thus, we demonstrate a novel mechanism underlying ALS pathology, in which alterations in miR126-5p facilitate a non–cell-autonomous mechanism of motor neuron degeneration in ALS. SIGNIFICANCE STATEMENT Despite some progress, currently no effective treatment is available for amyotrophic lateral sclerosis (ALS). We suggest a novel regulatory role for miR126-5p in ALS and demonstrate, for the first time, a mechanism by which alterations in miR126-5p contribute to axon degeneration and NMJ disruption observed in ALS. We show that miR126-5p is altered in ALS models and that it can modulate Sema3 and NRP protein expression. Furthermore, NRP1 elevations in motor neurons and muscle secretion of Sema3A contribute to axon degeneration and NMJ disruption in ALS. Finally, overexpressing miR126-5p is sufficient to transiently rescue NMJ disruption and axon degeneration both in vitro and in vivo.
Decline in peripheral blood NKG2D+CD3+CD56+ NKT cells in metastatic colorectal cancer patients.

OBJECTIVE Colorectal cancer (CRC) is one of the main causes of cancer deaths in the world. This cancer can be divided into non-metastatic and metastatic CRC stages. CD3+CD56+ NKT cell subsets are a minor T cell subset in peripheral blood and conduct the killing of tumor cells in direct manner. Little is obvious about levels and surface markers of these cells such as NKG2D in different cancers, especially in CRC. METHODS We included 15 non-metastatic (low-grade), 11 non-metastatic (high-grade), 10 metastatic colorectal cancer patients and 18 healthy controls. The percentages of CD3+CD56+ NKT cells and NKG2D+CD56+ NKT cells from samples were analyzed by flow cytometry in peripheral blood mononuclear cells (PBMCs) of samples. RESULTS We found that there was a significantly lower number of NKG2D+CD3+CD56+ cells in peripheral blood of patients with metastatic colorectal cancer compared with normal controls (77.53 ± 5.79 % vs 90.74 ± 9.84 %; p<0.01). CONCLUSION The fact that frequency of NKG2D+CD56+ NKT cells was significantly lower in patients with metastatic colorectal cancer compared to healthy controls strengthens the hypothesis that NKT cells can play a substantial role in the protection against human colorectal cancer, and this opens up avenues for novel studies about elucidating the other aspects of tumor surveillance in CRC progression and immunotherapy (Tab. 2, Fig. 2, Ref. 46).
Correlation between metabolic syndrome and sleep apnea

The so-called “metabolic syndrome” (MS), constitutes a cluster of metabolic and cardiovascular abnormalities, including fasting glucose, blood pressure, triglycerides, high density lipoprotein cholesterol (HDL-C), and waist circumference that arise from insulin resistance. Obstructive sleep apnea (OSA) syndrome is characterized by recurrent episodes of partial or complete obstruction of the upper airway, involving cessation or significant decreased airflow, with intermittent hypoxemia, frequent arousals from sleep and recurrent oxyhemoglobin desaturations that interfere with normal sleep patterns generating difficulty falling asleep, unrefreshing sleep and loud snoring. The relation between these two entities is known as “Syndrome Z”, and there is no question about the impact of these risk factors on health and disease. This clinical condition presents a growing epidemic Worldwide, affecting approximately 60% of the general population with both MS and OSA due to the constant increase of body mass index in humans. This article presents evidence-based data that focuses on the direct relationship between MS and OSA.
Federal Land Ownership: Overview and Data

Numerous issues affecting federal land management are before Congress. They include the extent of federal ownership, and whether to decrease, maintain, or increase the amount of federal holdings; the condition of currently owned federal infrastructure and lands, and the priority of their maintenance versus new acquisitions; the optimal balance between land use and protection, and whether federal lands should be managed primarily to produce national or local benefits; and border control on federal lands along the southwest border.
The Thiazolobenzimidazole TBZE-029 Inhibits Enterovirus Replication by Targeting a Short Region Immediately Downstream from Motif C in the Nonstructural Protein 2C

ABSTRACT TBZE-029 {1-(2,6-difluorophenyl)-6-trifluoromethyl-1H,3H-thiazolo[3,4-a]benzimidazole} is a novel selective inhibitor of the replication of several enteroviruses. We show that TBZE-029 exerts its antiviral activity through inhibition of viral RNA replication, without affecting polyprotein processing. To identify the viral target of TBZE-029, drug-resistant coxsackievirus B3 (CVB3) was selected. Genotyping of resistant clones led to the identification of three amino acid mutations in nonstructural protein 2C, clustered at amino acid positions 224, 227, and 229, immediately downstream of NTPase/helicase motif C. The mutations were reintroduced, either alone or combined, into an infectious full-length CVB3 clone. In particular the mutations at positions 227 and 229 proved essential for the altered sensitivity of CVB3 to TBZE-029. Resistant virus exhibited cross-resistance to the earlier-reported antienterovirus agents targeting 2C, namely, guanidine hydrochloride, HBB [2-(alpha-hydroxybenzyl)-benzimidazole], and MRL-1237 {1-(4-fluorophenyl)-2-[(4-imino-1,4-dihydropyridin-1-yl)methyl]benzimidazole hydrochloride}. The ATPase activity of 2C, however, remained unaltered in the presence of TBZE-029.
Comparative Study of Bioactive Compounds and Antioxidant Activity of Schinus terebinthifolius RADDI Fruits and Leaves Essential Oils

This study focused on the physico-chemical characterization of Schinus terebinthifolius RADDI leaves and seeds essential oils and the evaluation of their antioxidant activity. Several volatiles components were identified by GC-MS. The major compound detected in leaves and fruits essential oils, was bicyclogermacrene (35.58 % and 23.56 %, respectively). Schinus terebinthifolius fruits essential oil showed lower total phenolic and flavonoids content but higher antiradical activity than the leaves one. This antioxidant activity characterizing Schinus terebinthifolius essential oils was high enough to consider the plant as a new and natural source of antioxidants.
Understanding Emotions: A Dataset of Tweets to Study Interactions between Affect Categories

Human emotions are complex and nuanced. Yet, an overwhelming majority of the work in automatically detecting emotions from text has focused only on classifying text into positive, negative, and neutral classes, and a much smaller amount on classifying text into basic emotion categories such as joy, sadness, and fear. Our goal is to create a single textual dataset that is annotated for many emotion (or affect) dimensions (from both the basic emotion model and the VAD model). For each emotion dimension, we annotate the data for not just coarse classes (such as anger or no anger) but also for fine-grained real-valued scores indicating the intensity of emotion (anger, sadness, valence, etc.). We use Best–Worst Scaling (BWS) to address the limitations of traditional rating scale methods such as interand intra-annotator inconsistency by employing comparative annotations. We show that the fine-grained intensity scores thus obtained are reliable (repeat annotations lead to similar scores). We choose Twitter as the source of the textual data we annotate because tweets are self-contained, widely used, public posts, and tend to be rich in emotions. The new dataset is useful for training and testing supervised machine learning algorithms for multi-label emotion classification, emotion intensity regression, detecting valence, detecting ordinal class of intensity of emotion (slightly sad, very angry, etc.), and detecting ordinal class of valence (or sentiment). We make the data available for the recent SemEval-2018 Task 1: Affect in Tweets, which explores these five tasks. The dataset also sheds light on crucial research questions such as: which emotions often present together in tweets? ; how do the intensities of the three negative emotions relate to each other? ; and how do the intensities of the basic emotions relate to valence?
Neocortical activity is stimulus- and scale-invariant

Mounting evidence supports the hypothesis that the cortex operates near a critical state, defined as the transition point between order (large-scale activity) and disorder (small-scale activity). This criticality is manifested by power law distribution of the size and duration of spontaneous cascades of activity, which are referred as neuronal avalanches. The existence of such neuronal avalanches has been confirmed by several studies both in vitro and in vivo, among different species and across multiple spatial scales. However, despite the prevalence of scale free activity, still very little is known concerning whether and how the scale-free nature of cortical activity is altered during external stimulation. To address this question, we performed in vivo two-photon population calcium imaging of layer 2/3 neurons in primary visual cortex of behaving mice during visual stimulation and conducted statistical analyses on the inferred spike trains. Our investigation for each mouse and condition revealed power law distributed neuronal avalanches, and irregular spiking individual neurons. Importantly, both the avalanche and the spike train properties remained largely unchanged for different stimuli, while the cross-correlation structure varied with stimuli. Our results establish that microcircuits in the visual cortex operate near the critical regime, while rearranging functional connectivity in response to varying sensory inputs.
Biosocial-academic profile and stress in first- and fourth-year nursing students.

OBJECTIVES To compare the biosocial and academic profile and stress levels between first- and last-year nursing students from a public university in Sao Paulo. METHODS This is an analytic and quantitative study. A biosocial and academic form and the instrument for Assessment of Stress in Nursing Students by Costa and Polak were applied to 83 students between February and March 2016. RESULTS Insufficient income and extracurricular activities contribute to higher levels of stress in both groups of students assessed. Fourth-year students showed higher levels of general stress, particularly generated by the factors: performance of practical activities, professional communication, environment and professional training. Time management produces higher stress in first-year students. CONCLUSIONS Fewbiosocial and academic features equally contribute for the stress levels in first- and last-year nursing students, but those in last-year present higher stress than students who are starting the course.
Does the economy matter? Economic perceptions and the vote in Australia

ABSTRACT Does the economy matter for how Australians vote in federal elections? International studies show an association between economic performance and elections, but research on Australia finds that the impact of the economy on voting is modest. What explains this relative absence of economic voting? How do Australians perceive the economy? And how do economic perceptions inform their decisions at the polls? Our results confirm the lack of an association between economic indicators and incumbent vote shares. Analyses of survey data from 1996 to 2013 show that political factors condition perceptions of economic performance, while preferences for – and perceptions of – the government's unified control over economic policy shape the influence of economic perceptions on voter choice. Overall, responsibility attributions are the key to economic voting in Australia.
Changes in Lumbopelvic Movement and Muscle Recruitment Associated with Prolonged Deep Squatting: A Pilot Study

This study examined the changes in spinal kinematics and muscle recruitment of the lumbopelvic region associated with prolonged squatting. Eight subjects with chronic nonspecific low back pain (LBP) and eight asymptomatic subjects (AS) performed squat-to-stand and reverse movements, before and immediately after 15 min deep-squatting. Within-group and between-group differences in lumbopelvic kinematics and electromyographic activity acquired in lumbar erector spinae (ES), gluteus maximus (GM), and vastus lateralis (VL) were analyzed. During squat-to-stand after squatting, the LBP group showed slower then faster lumbar movement in the second and third quartiles, respectively. In the second quartile, the AS group moved with a significantly greater lumbar angle. However, significantly greater bilateral GM activity (+4–4.5%) was found in the LBP group only. A more profound decrease in bilateral ES activity (−10%) was also shown in the LBP group, yet this was nonsignificant compared to the AS group (−4%). In the third quartile, only the LBP group moved with a significantly greater lumbar angle, together with a significant increase in bilateral ES (+6–8%) and GM muscle (+2–3%) activity. The findings of the altered pattern of joint kinematics and recruitment of the key lumbopelvic muscles displayed in the LBP group inform on the possible mechanisms that may contribute to the increased risk of developing lumbar dysfunctions for people who work in prolonged squatting postures.
Wyniki paliatywnej teleradioterapii chorych na niedrobnokomórkowego raka pluca

We present analysis of literature data on survival of patients with advanced NSCLC (non-small cell lung cancer) after palliative chest teleradiotherapy. We found that the average survival rate in this group of patients was between 4 to 12 months. One-year survival rate was from 14 to 49 % two-year survival rate 3 - 17 % and three-year survival rate 2 - 8 %. We found that differences in survival result mainly from heterogeneous patients groups. We discussed the controversial problem of influence of palliative chest teleradiotherapy on the overall survivals of patients with advanced NSCLC.
Compelling palatability of protein hydrolysates for Nile tilapia juveniles

This study aimed at determining the compelling palatability of different protein hydrolysates for Nile tilapia juveniles ( Oreochromis niloticus ). Four isoproteic (30% crude protein) and isoenergetic (3,200 kcal kg -1 ) experimental diets were formulated, with a 5% inclusion level of poultry hydrolysate protein (PHF), or swine liver hydrolysate protein (PHS), or feather hydrolysate protein (PHP) and a control treatment containing 5% of fishmeal (FPE). Four juveniles (2.9 ± 0.01 g) were distributed in 10 L tanks and fed four times a day, and before each feeding event, diets were drawn. The same amount of pellets from each diet was offered, and feeding behaviors were recorded during three minutes for each feeding event, referred to the time of capture of the first pellet, number of pellet rejections, and number of approximations without capturing pellets and quantity of consumed pellets. A significant effect ( P < 0.05) was observed regarding a higher consumption of pellets and palatability index for PHF, followed by PHS, FPE, and PHP. Therefore, it was concluded that PHF provided the highest compelling palatability for Nile tilapia juveniles, by displaying a 10.82% increase of the palatability index, 17% of final feed consumption, and presented a rejection number 6.89 times lower than FPE.
On the Application of Danskin's Theorem to Derivative-Free Minimax Optimization

Motivated by Danskin's theorem, gradient-based methods have been applied with empirical success to solve minimax problems that involve non-convex outer minimization and non-concave inner maximization. On the other hand, recent work has demonstrated that Evolution Strategies (ES) algorithms are stochastic gradient approximators that seek robust solutions. In this paper, we address black-box (gradient-free) minimax problems that have long been tackled in a coevolutionary setup. To this end and guaranteed by Danskin's theorem, we employ ES as a stochastic estimator for the descent direction. The proposed approach is validated on a collection of black-box minimax problems. Based on our experiments, our method's performance is comparable with its coevolutionary counterparts and favorable for high-dimensional problems. Its efficacy is demonstrated on a real-world application.
Exploring the Mechanism of the Clinical Encounter on Depressive Symptoms in Young Adults: A Path Analysis

ABSTRACT Elucidating mechanisms of how high quality clinical encounters with providers may alleviate depressive symptoms in young adults are critical to reduce psychological morbidity and disability. Guided by Street's Model of Health Communication (SMHC), this study explores the predictive relationships of the clinical encounter, which includes communication functions (patient-provider communication and patient self-appraisal of communication skills with provider) and proximal outcomes (patient activation; PA) to improve health outcomes (depressive symptoms) in young adults. This study of young adults (n = 60) employed path analysis to examine the overall model fit and direct and indirect effects of each variable on depressive symptoms. The final SMHC had excellent model fit (X2 = 2.26, p =.32, TLI =.99, CFI = 1.00, RMSEA =.05). Patient-provider communication and self-appraised communication skills with providers had indirect effects on depressive symptoms and a direct effect on PA; PA had a direct effect on depressive symptoms (R2 =.30, p <.01). Findings elucidate potential novel targets, amenable to behavioral intervention, to improve depressive symptoms within the clinical encounter, and provide a foundation for hypothesis-driven model testing among young adults with depressive symptoms.
A Dynamic Neural Network Approach to Generating Robot's Novel Actions: A Simulation Experiment

In this study, we investigate how a robot can generate novel and creative actions from its own experience of learning basic actions. Inspired by a machine learning approach to computational creativity, we propose a dynamic neural network model that can learn and generate robot's actions. We conducted a set of simulation experiments with a humanoid robot. The results showed that the proposed model was able to learn the basic actions and also to generate novel actions by modulating and combining those learned actions. The analysis on the neural activities illustrated that the ability to generate creative actions emerged from the model's nonlinear memory structure self-organized during training. The results also showed that the different way of learning the basic actions induced the self-organization of the memory structure with the different characteristics, resulting in the generation of different levels of creative actions. Our approach can be utilized in human-robot interaction in which a user can interactively explore the robot's memory to control its behavior and also discover other novel actions.
Subjects with cardiovascular disease or high disease risk are more sedentary and less active than their healthy peers

Objectives We investigated differences in objectively measured sedentary behaviour (SB) and physical activity (PA) levels in subjects with cardiovascular disease (CVD) diagnosis or high CVD risk compared with healthy controls. Methods The present study includes a subsample (n=1398, Health 2011 Study) of participants, who attended health examinations and wore a triaxial accelerometer (≥4 days). Patients with CVD were identified and CVD risk was calculated for others using Framingham Risk Score (FRS). Participants were categorised into groups: FRS<10%; FRS=10%–30%; FRS>30%/CVD. Raw acceleration data were analysed with mean amplitude deviation (MAD) and angle for posture estimation (APE). MAD corresponding to intensity of PA was converted to metabolic equivalents (MET) and categorised to light (1.5–2.9 METs) and moderate to vigorous PA (MVPA≥3.0 METs). APE recognises SB and standing. Results Daily accumulated time of >30 s MVPA bouts was higher in FRS<10% group (46 min) than in FRS>30%/CVD group (29 min) (p<0.001). FRS>30%/CVD group were more sedentary, their mean daily number of >10 min SB bouts (13.2) was higher than in FRS <10% group (11.5) (p=0.002). Conclusion Number and accumulated times of SB and PA bouts differed between the CVD risk groups. Causative research is required to assess the importance of SB and PA in prevention and rehabilitation of CVDs.
Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

Correctly identifying sleep stages is important in diagnosing and treating sleep disorders. This paper proposes a joint classification-and-prediction framework based on convolutional neural networks (CNNs) for automatic sleep staging, and, subsequently, introduces a simple yet efficient CNN architecture to power the framework. Given a single input epoch, the novel framework jointly determines its label (classification) and its neighboring epochs’ labels (prediction) in the contextual output. While the proposed framework is orthogonal to the widely adopted classification schemes, which take one or multiple epochs as contextual inputs and produce a single classification decision on the target epoch, we demonstrate its advantages in several ways. First, it leverages the dependency among consecutive sleep epochs while surpassing the problems experienced with the common classification schemes. Second, even with a single model, the framework has the capacity to produce multiple decisions, which are essential in obtaining a good performance as in ensemble-of-models methods, with very little induced computational overhead. Probabilistic aggregation techniques are then proposed to leverage the availability of multiple decisions. To illustrate the efficacy of the proposed framework, we conducted experiments on two public datasets: Sleep-EDF Expanded (Sleep-EDF), which consists of 20 subjects, and Montreal Archive of Sleep Studies (MASS) dataset, which consists of 200 subjects. The proposed framework yields an overall classification accuracy of 82.3% and 83.6%, respectively. We also show that the proposed framework not only is superior to the baselines based on the common classification schemes but also outperforms existing deep-learning approaches. To our knowledge, this is the first work going beyond the standard single-output classification to consider multitask neural networks for automatic sleep staging. This framework provides avenues for further studies of different neural-network architectures for automatic sleep staging.