Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypoglycaemic activity of 2-dodecyl-6-methoxycyclohexa-2,5-diene-1,4-dione in streptozotocin-induced diabetic mice through ameliorating metabolic function and regulating peroxisome proliferator-activated receptor γ

Introduction Diabetes mellitus is characterized by hyperglycaemia causing changes in plasma lipoproteins, which leads to insulin resistance, secretion defects or both. The present study aimed to evaluate the ability of 2-dodecyl-6-methoxy-cyclohexa-2,5-diene-1,4-dione (DMDD) isolated from Averrhoa carambola L. roots to lower hyperglycaemia and to investigate its potential mechanism in diabetic mice. Material and methods DMDD was isolated using a column chromatographic technique. Experimental mice were fed with a high-fat diet for a month and were intravenously injected with streptozotocin (80 mg/kg, single dose). Diabetic mice were orally administered DMDD (12.5, 25, 50 mg/kg) and 50 mg/kg pioglitazone for 15 days. Fasting blood glucose (FBG), fasting blood insulin (FINS), pancreatic insulin content, interleukin-6 (IL-6), tumour necrosis factor-α (TNF-α), as well as serum total cholesterol (TC), triglyceride (TG) and free fatty acid (FFA) were determined. Adipose tissue was assessed by histological examination, immunohistochemistry, western blot and reverse transcription-polymerase chain reaction methods. Results DMDD significantly increased the insulin level (all p < 0.05). In contrast, FBG, IL-6, TNF-α, TC, TG and FFA were significantly decreased (all p < 0.05). However, DMDD induced the activation of adipocyte peroxisome proliferator-activated receptor γ (PPAR-γ), confirmed by increased protein and mRNA expression of PPAR-γ. Conclusions DMDD possessed hypoglycaemic activity due to its potential mechanism involving PPARγ-mediated adipocyte endocrine regulation.
Transcriptional and epigenetic profiling of nutrient-deprived cells to identify novel regulators of autophagy

ABSTRACT Macroautophagy (hereafter autophagy) is a lysosomal degradation pathway critical for maintaining cellular homeostasis and viability, and is predominantly regarded as a rapid and dynamic cytoplasmic process. To increase our understanding of the transcriptional and epigenetic events associated with autophagy, we performed extensive genome-wide transcriptomic and epigenomic profiling after nutrient deprivation in human autophagy-proficient and autophagy-deficient cells. We observed that nutrient deprivation leads to the transcriptional induction of numerous autophagy-associated genes. These transcriptional changes are reflected at the epigenetic level (H3K4me3, H3K27ac, and H3K56ac) and are independent of autophagic flux. As a proof of principle that this resource can be used to identify novel autophagy regulators, we followed up on one identified target: EGR1 (early growth response 1), which indeed appears to be a central transcriptional regulator of autophagy by affecting autophagy-associated gene expression and autophagic flux. Taken together, these data stress the relevance of transcriptional and epigenetic regulation of autophagy and can be used as a resource to identify (novel) factors involved in autophagy regulation.
Automatic Modulation Recognition Using Deep Learning Architectures

In this paper, we present an automatic modulation recognition framework for the detection of radio signals in a communication system. The framework considers both a deep convolutional neural network (CNN) and a long short term memory network. Further, we propose a pre-processing signal representation that combines the in-phase, quadrature and fourth-order statistics of the modulated signals. The presented data representation allows our CNN and LSTM models to achieve 8% improvements on our testing dataset. We compare the recognition accuracy of the proposed recognition methods with existing methods under various SNR values. Experimental results show that our methods perform better than the existing methods.
Data Poisoning Attacks against Online Learning

We consider data poisoning attacks, a class of adversarial attacks on machine learning where an adversary has the power to alter a small fraction of the training data in order to make the trained classifier satisfy certain objectives. While there has been much prior work on data poisoning, most of it is in the offline setting, and attacks for online learning, where training data arrives in a streaming manner, are not well understood. In this work, we initiate a systematic investigation of data poisoning attacks for online learning. We formalize the problem into two settings, and we propose a general attack strategy, formulated as an optimization problem, that applies to both with some modifications. We propose three solution strategies, and perform extensive experimental evaluation. Finally, we discuss the implications of our findings for building successful defenses.
Knowledge of Periodontal Diseases, Oral Hygiene Practices, and Self-Reported Periodontal Problems among Pregnant Women and Postnatal Mothers Attending Reproductive and Child Health Clinics in Rural Zambia

Aim To determine the level of knowledge of periodontal diseases, practices regarding oral hygiene, and self-perceived periodontal problems among pregnant and postnatal women attending reproductive and child health clinics in rural districts of Zambia. Methodology This was a quantitative, questionnaire-based, descriptive, and cross-sectional study that recruited 410 women aged 15 to 43 years. Data were analyzed using SPSS v19.0 computer program. Results Participants knowledgeable of periodontal diseases were 62%; gingivitis signs included gum swelling (87.4%) and bleeding (93.3%). Of all participants, 95.6% practiced tooth brushing: twice/day (38.5%), using plastic toothbrush (95.6%), chewing stick (12.2%), toothpick (10.7%), dental floss (2.0%), and tongue cleaning (55.4%). Self-reported periodontal problems were bleeding gums (23.2%), gums that were reddish (10.5%), swollen (11.0%), painful (15.9%), and mobile teeth (3.4%). In logistic regression analysis, painful gums, reddish gums, and toothpick use were 21.9, 4.7, and 4.3 respectively, significantly more likely to cause gum bleeding on tooth brushing. Conclusions Most studied women had general knowledge of periodontal diseases but only few knew the cause. All participants performed tooth cleaning; however, majority did not know appropriate practices, and only few had periodontal problems. Integration of oral health to general health promotion and periodontal therapy to pregnant women at high risk is recommended.
Effect of dietary salt intake on epithelial Na+ channels (ENaCs) in the hypothalamus of Dahl salt‐sensitive rats

All three epithelial Na+ channel (ENaC) subunits (α, β, and γ) and the mineralocorticoid receptor (MR), a known regulator of ENaC, are located in vasopressin (VP) synthesizing magnocellular neurons in the hypothalamic supraoptic (SON) and paraventricular (PVN) nuclei. Our previous study showed that ENaC mediates a Na+ leak current that affects the steady‐state membrane potential of VP neurons. This study was conducted in Dahl salt‐sensitive (Dahl‐SS) rats to determine if any abnormal responses in the expression of ENaC subunits and MR occur in the hypothalamus and kidney in response to a high dietary salt intake. After 21 days of high salt consumption, Dahl‐SS rat resulted in a significant increase in γENaC expression and exhibited proteolytic cleavage of this subunit compared to Sprague–Dawley (SD) rats. Additionally, Dahl‐SS rats had dense somato‐dendritic γENaC immunoreactivity in VP neurons, which was absent in SD rats. In contrast, SD rats fed a high salt diet had significantly decreased αENaC subunit expression in the kidney and MR expression in the hypothalamus. Plasma osmolality measured daily for 22 days demonstrated that Dahl‐SS rats fed a high salt diet had a steady increase in plasma osmolality, whereas SD rats had an initial increase that decreased to baseline levels. Findings from this study demonstrate that Dahl‐SS rats lack a compensatory mechanism to down regulate ENaC during high dietary salt consumption, which may contribute to the development of hypertension.
Changes in membrane properties of rat deep cerebellar nuclear projection neurons during acquisition of eyeblink conditioning

Significance Although large ensembles of neurons have been found to change as a function of learning and memory, localizing those changes to the individual neurons directly involved in a specific task has been challenging. Using whole-cell recording of deep cerebellar nuclear neurons (DCN) and a transsynaptic viral tracer, we found motor learning induced significant changes in membrane properties of rat DCN projection neurons including a reduced after-hyperpolarization amplitude and shortened latency for both evoked DCN action potentials and rebound spikes. These learning-specific changes in DCN excitability have not previously been reported in any species or task. Previous studies have shown changes in membrane properties of neurons in rat deep cerebellar nuclei (DCN) as a function of development, but due to technical difficulties in obtaining viable DCN slices from adult animals, it remains unclear whether there are learning-related alterations in the membrane properties of DCN neurons in adult rats. This study was designed to record from identified DCN cells in cerebellar slices from postnatal day 25–26 (P25–26) rats that had a relatively mature sensory nervous system and were able to acquire learning as a result of tone–shock eyeblink conditioning (EBC) and to document resulting changes in electrophysiological properties. After electromyographic electrode implantation at P21 and inoculation with a fluorescent pseudorabies virus (PRV-152) at P22–23, rats received either four sessions of paired delay EBC or unpaired stimulus presentations with a tone conditioned stimulus and a shock unconditioned stimulus or sat in the training chamber without stimulus presentations. Compared with rats given unpaired stimuli or no stimulus presentations, rats given paired EBC showed an increase in conditioned responses across sessions. Whole-cell recordings of both fluorescent and nonfluorescent DCN projection neurons showed that delay EBC induced significant changes in membrane properties of evoked DCN action potentials including a reduced after-hyperpolarization amplitude and shortened latency. Similar findings were obtained in hyperpolarization-induced rebound spikes of DCN neurons. In sum, delay EBC produced significant changes in the membrane properties of juvenile rat DCN projection neurons. These learning-specific changes in DCN excitability have not previously been reported in any species or task.
Exposure to opposing views on social media can increase political polarization

Significance Social media sites are often blamed for exacerbating political polarization by creating “echo chambers” that prevent people from being exposed to information that contradicts their preexisting beliefs. We conducted a field experiment that offered a large group of Democrats and Republicans financial compensation to follow bots that retweeted messages by elected officials and opinion leaders with opposing political views. Republican participants expressed substantially more conservative views after following a liberal Twitter bot, whereas Democrats’ attitudes became slightly more liberal after following a conservative Twitter bot—although this effect was not statistically significant. Despite several limitations, this study has important implications for the emerging field of computational social science and ongoing efforts to reduce political polarization online. There is mounting concern that social media sites contribute to political polarization by creating “echo chambers” that insulate people from opposing views about current events. We surveyed a large sample of Democrats and Republicans who visit Twitter at least three times each week about a range of social policy issues. One week later, we randomly assigned respondents to a treatment condition in which they were offered financial incentives to follow a Twitter bot for 1 month that exposed them to messages from those with opposing political ideologies (e.g., elected officials, opinion leaders, media organizations, and nonprofit groups). Respondents were resurveyed at the end of the month to measure the effect of this treatment, and at regular intervals throughout the study period to monitor treatment compliance. We find that Republicans who followed a liberal Twitter bot became substantially more conservative posttreatment. Democrats exhibited slight increases in liberal attitudes after following a conservative Twitter bot, although these effects are not statistically significant. Notwithstanding important limitations of our study, these findings have significant implications for the interdisciplinary literature on political polarization and the emerging field of computational social science.
Ship Detection Using Compact Polarimetric SAR Based on the Notch Filter

Compact polarimetric data exploitation, especially in hybrid-polarimetric (HP) mode, is currently attracting increasing interest due to the new generation of synthetic aperture radar (SAR) systems. Recently, it has been demonstrated that the notch filter is useful for ship detection in either full- or dual-polarization (DP)-mode SAR images. In this paper, the notch filter investigation is further extended to HP SAR architecture for ship detection on the ocean surface. First, a version of the notch filter that is suitable for HP SAR is proposed based on the definition of the corresponding feature partial scattering vector from the covariance matrix of the HP SAR. Subsequently, a novel model characterizing the statistics of the notch distance of sea clutter in the HP mode is developed. Based on the statistical model, the threshold of constant false-alarm rate (CFAR) ship detection is theoretically and analytically derived, which allows the automatic and adaptive implementation for ship detection in varying sea backgrounds in practical applications. Experiments on the HP SAR data emulated from full-polarization L-band Aerospace Exploration Agency Advanced Land Observation Satellite Phased-Array type L-band SAR and C-band RADARSAT-2 SAR measurements validate not only the soundness of the proposed CFAR detection but also the high accuracy of the presented model in fitting HP SAR data. Furthermore, the notch filter and its CFAR realization provide the same benchmark for the comparison of the detectability of HP and conventional linear DP SAR data. Preliminary findings suggest that the detection performance of HP SAR is superior to that of DP SAR in ship observation. Therefore, the proposed CFAR method based on the notch filter provides a promising technique for the detection of ships using HP SAR data.
Rapid growth of organic aerosol nanoparticles over a wide tropospheric temperature range

Significance Aerosol particles can form and grow by gas-to-particle conversion and eventually act as seeds for cloud droplets, influencing global climate. Volatile organic compounds emitted from plants are oxidized in the atmosphere, and the resulting products drive particle growth. We measure particle growth by oxidized biogenic vapors with a well-controlled laboratory setup over a wide range of tropospheric temperatures. While higher temperatures lead to increased reaction rates and concentrations of highly oxidized molecules, lower temperatures allow additional, but less oxidized, species to condense. We measure rapid growth over the full temperature range of our study, indicating that organics play an important role in aerosol growth throughout the troposphere. Our finding will help to sharpen the predictions of global aerosol models. Nucleation and growth of aerosol particles from atmospheric vapors constitutes a major source of global cloud condensation nuclei (CCN). The fraction of newly formed particles that reaches CCN sizes is highly sensitive to particle growth rates, especially for particle sizes <10 nm, where coagulation losses to larger aerosol particles are greatest. Recent results show that some oxidation products from biogenic volatile organic compounds are major contributors to particle formation and initial growth. However, whether oxidized organics contribute to particle growth over the broad span of tropospheric temperatures remains an open question, and quantitative mass balance for organic growth has yet to be demonstrated at any temperature. Here, in experiments performed under atmospheric conditions in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN), we show that rapid growth of organic particles occurs over the range from −25 °C to 25 °C. The lower extent of autoxidation at reduced temperatures is compensated by the decreased volatility of all oxidized molecules. This is confirmed by particle-phase composition measurements, showing enhanced uptake of relatively less oxygenated products at cold temperatures. We can reproduce the measured growth rates using an aerosol growth model based entirely on the experimentally measured gas-phase spectra of oxidized organic molecules obtained from two complementary mass spectrometers. We show that the growth rates are sensitive to particle curvature, explaining widespread atmospheric observations that particle growth rates increase in the single-digit-nanometer size range. Our results demonstrate that organic vapors can contribute to particle growth over a wide range of tropospheric temperatures from molecular cluster sizes onward.
A well-preserved partial scapula from Japan and the reconstruction of the triosseal canal of plotopterids

The discovery of a well-preserved cranial end of a plotopterid scapula from the Early Oligocene Jinnobaru Formation in southwestern Japan has provided a fine example of its bone structure and has enabled the reconstruction of the triosseal canal (canalis triosseus) of the unique extinct penguin-like bird. It is believed that plotopterids performed penguin-like underwater propulsion using wings that were similar to those of penguins. Until this discovery, the lack of well-preserved plotopterid scapulae hindered reconstruction of the canalis triosseus, which is an important structure for the wing-upstroke. We reconstructed a composite model of the canalis triosseus based on the new scapula. The reconstructed size of the canal is as large as that in Emperor Penguins (Aptenodytes forsteri), suggesting that the bird had a large and powerful m. supracoracoideus, which is the essential muscle for the powered upstroke required for wing-propelled diving. Plotopterids likely have had the same functional requirement as penguins, the powerful wing-upstroke in the water. They must have also been capable swimmers. This scapula accounts for the structural difference between plotopterids and penguins in terms of the canalis triosseus. The large canalis triosseus of plotopterids was composed of the elongated acromion of the scapula, while penguins have a long processus acromialis claviculae for the same function.
Aging and Attentional Control: Examining the Roles of Mind-Wandering Propensity and Dispositional Mindfulness

Abstract Objectives: Aging is associated with declines in performance on certain laboratory tasks of attentional control. However, older adults tend to report greater mindful, present-moment attention and less mind-wandering (MW) than young adults. For older adults, high levels of these traits may be protective for attentional performance. This study examined age-related differences in global (i.e., full-task) and local (i.e., pre-MW) attentional control and explored the variance explained by MW and mindfulness. Methods: Cross-sectional comparisons were conducted on data from a previously reported sample of 75 older adults (ages, 60–75 years) and a new sample of 50 young adults (ages, 18–30 years). All participants completed a Go/No-Go task and a Continuous Performance Task with quasi-random MW probes. Results: There were few age-related differences in attentional control. Although MW was not associated with decrements in global performance, local performance measures revealed deleterious effects of MW, which were present across age groups. Older adults reported higher trait mindfulness and less MW than young adults, and these variables helped explain the lack of observed age-related differences in attentional control. Conclusions: Individual differences in dispositional mindfulness and MW propensity explain important variance in attentional performance across age. Increasing present-moment focus and reducing lapses in attention represent important targets for cognitive rehabilitation interventions. (JINS, 2018, 24, 876–888)
Does the use of cardiopulmonary resuscitation feedback devices improve the quality of chest compressions performed by doctors? A prospective, randomized, cross-over simulation study

Background The aim of the study was to compare the quality of chest compressions (CCs) carried out with and without the use of the TrueCPR device during simulated cardiopulmonary resuscitations conducted by trainee doctors. Methods The study was a prospective, randomized, cross-over simulation study. The study involved 65 trainee doctors who were tasked with performing a 2-min cycle of uninterrupted CCs under conditions of a simulated cardiopulmonary resuscitation of adults. CC were carried out in two scenarios: with and without TrueCPR chest compression support. Participants did not have experience in the use of CCs prior to this study. Results The depth of compressions in regard to CC techniques were varied by 45 mm (IQR 43–48) for manual CC and 53 mm (IQR 51–55) for the TrueCPR device (p < 0.001). The incidence of CCs with and without TrueCPR was: 112 (IQR 103–113) vs. 129 (IQR 122–135) compressions (p = 0.002). The degree of complete chest relaxation with the TrueCPR device was 95% (IQR 76–99) and without the device, 33% (IQR 29–38) (p < 0.001). Conclusions In the simulation study performed, the use of the TrueCPR device resulted in a significant improvement in the quality of CCs in relation to frequency and depth of CCs and correctness of chest relaxation.
Learning via Social Awareness: Improving a Deep Generative Sketching Model with Facial Feedback

In the quest towards general artificial intelligence (AI), researchers have explored developing loss functions that act as intrinsic motivators in the absence of external rewards. This paper argues that such research has overlooked an important and useful intrinsic motivator: social interaction. We posit that making an AI agent aware of implicit social feedback from humans can allow for faster learning of more generalizable and useful representations, and could potentially impact AI safety. We collect social feedback in the form of facial expression reactions to samples from Sketch RNN, an LSTM-based variational autoencoder (VAE) designed to produce sketch drawings. We use a Latent Constraints GAN (LC-GAN) to learn from the facial feedback of a small group of viewers, by optimizing the model to produce sketches that it predicts will lead to more positive facial expressions. We show in multiple independent evaluations that the model trained with facial feedback produced sketches that are more highly rated, and induce significantly more positive facial expressions. Thus, we establish that implicit social feedback can improve the output of a deep learning model.