Miracle-dz/UniFAR-FTUs huggingface dataset:
Alternating Modulation of Subthalamic Nucleus Beta Oscillations during Stepping

Gait disturbances in Parkinson's disease are commonly refractory to current treatment options and majorly impair patient's quality of life. Auditory cues facilitate gait and prevent motor blocks. We investigated how neural dynamics in the human subthalamic nucleus of Parkinsons's disease patients (14 male, 2 female) vary during stepping and whether rhythmic auditory cues enhance the observed modulation. Oscillations in the beta band were suppressed after ipsilateral heel strikes, when the contralateral foot had to be raised, and reappeared after contralateral heel strikes, when the contralateral foot rested on the floor. The timing of this 20–30 Hz beta modulation was clearly distinct between the left and right subthalamic nucleus, and was alternating within each stepping cycle. This modulation was similar, whether stepping movements were made while sitting, standing, or during gait, confirming the utility of the stepping in place paradigm. During stepping in place, beta modulation increased with auditory cues that assisted patients in timing their steps more regularly. Our results suggest a link between the degree of power modulation within high beta frequency bands and stepping performance. These findings raise the possibility that alternating deep brain stimulation patterns may be superior to constant stimulation for improving parkinsonian gait. SIGNIFICANCE STATEMENT Gait disturbances in Parkinson's disease majorly reduce patients' quality of life and are often refractory to current treatment options. We investigated how neural activity in the subthalamic nucleus of patients who received deep brain stimulation surgery covaries with the stepping cycle. 20–30 Hz beta activity was modulated relative to each step, alternating between the left and right STN. The stepping performance of patients improved when auditory cues were provided, which went along with enhanced beta modulation. This raises the possibility that alternating stimulation patterns may also enhance beta modulation and may be more beneficial for gait control than continuous stimulation, which needs to be tested in future studies.
Supervised Open Information Extraction

We present data and methods that enable a supervised learning approach to Open Information Extraction (Open IE). Central to the approach is a novel formulation of Open IE as a sequence tagging problem, addressing challenges such as encoding multiple extractions for a predicate. We also develop a bi-LSTM transducer, extending recent deep Semantic Role Labeling models to extract Open IE tuples and provide confidence scores for tuning their precision-recall tradeoff. Furthermore, we show that the recently released Question-Answer Meaning Representation dataset can be automatically converted into an Open IE corpus which significantly increases the amount of available training data. Our supervised model outperforms the existing state-of-the-art Open IE systems on benchmark datasets.
Antibacterial and Cytotoxic Potential of Biosynthesized Silver Nanoparticles by Some Plant Extracts

The provision of nanoparticles using biogenic material as a part of green chemistry is an attractive nanotechnology. The current research aimed to test the antimicrobial and cytotoxic efficacy of silver nanoparticles synthesized by extracts of Phoenix dactylifera, Ferula asafetida, and Acacia nilotica as reductant and stabilizing agents in silver nanoparticle formation. Synthesized nanoparticles were evaluated for their antimicrobial activity against Staphylococcus aureus (Gram-positive) and Pseudomonas aeruginosa and Escherichia coli (Gram-negative) using an agar well diffusion assay. Furthermore, cytotoxic ability was investigated against LoVo cells. The potential phyto-constituents of plant extracts were identified by Fourier-transform infrared spectroscopy (FT-IR) techniques. Field emission scanning electron microscopy (FE-SEM), transmission electron microscope (TEM), and zeta potential analyzed the size and morphology of the biogenic nanoparticles. The current study revealed the ability of the tested plant extract to convert silver ions to silver nanoparticles with an average size that ranged between 67.8 ± 0.3 and 155.7 ± 1.5 nm in diameter. Biogenic AgNPs showed significant antibacterial ability (10 to 32 mm diameter) and anticancer ability against a LoVo cell with IC50 ranged between 35.15–56.73 μg/mL. The innovation of the present study is that the green synthesis of NPs, which is simple and cost effective, provides stable nano-materials and can be an alternative for the large-scale synthesis of silver nanoparticles.
A multi-task framework with feature passing module for skin lesion classification and segmentation

Skin lesion classification and segmentation are highly correlated tasks. However, their relationship is not fully utilized in previous methods. In this paper, we propose a multi-task deep convolutional neural network architecture to solve the skin lesion classification and segmentation problem simultaneously. To take full advantage of features from different tasks and thus get richer knowledge about the sample, we design a feature passing module to pass messages between segmentation branch and classification branch. Since feature passing module is not always helpful and can be related with individual samples, gate functions are used for controlling messages transmission. Therefore, features from one task are learned and selectively passed to the other task, and vice versa, which effectively improves the performance of both tasks. We have evaluated the proposed method on ISBI-2017 challenge dataset, and the experimental results demonstrate the superiority and effectiveness of the proposed method, compared to our base model and other state-of-art methods.
Validity and Reliability of the Turkish Chronic Pain Acceptance Questionnaire

Background: Pain acceptance is the process of giving up the struggle with pain and learning to live a worthwhile life despite it. In assessing patients with chronic pain in Turkey, making a diagnosis and tracking the effectiveness of treatment is done with scales that have been translated into Turkish. However, there is as yet no valid and reliable scale in Turkish to assess the acceptance of pain. Aims: To validate a Turkish version of the Chronic Pain Acceptance Questionnaire developed by McCracken and colleagues. Study Design: Methodological and cross sectional study. Methods: A simple randomized sampling method was used in selecting the study sample. The sample was composed of 201 patients, more than 10 times the number of items examined for validity and reliability in the study, which totaled 20. A patient identification form, the Chronic Pain Acceptance Questionnaire, and the Brief Pain Inventory were used to collect data. Data were collected by face-to-face interviews. In the validity testing, the content validity index was used to evaluate linguistic equivalence, content validity, construct validity, and expert views. In reliability testing of the scale, Cronbach’s α coefficient was calculated, and item analysis and split-test reliability methods were used. Principal component analysis and varimax rotation were used in factor analysis and to examine factor structure for construct concept validity. Results: The item analysis established that the scale, all items, and item-total correlations were satisfactory. The mean total score of the scale was 21.78. The internal consistency coefficient was 0.94, and the correlation between the two halves of the scale was 0.89. Conclusion: The Chronic Pain Acceptance Questionnaire, which is intended to be used in Turkey upon confirmation of its validity and reliability, is an evaluation instrument with sufficient validity and reliability, and it can be reliably used to examine patients’ acceptance of chronic pain.
The Circle Problem of Gauss and the Divisor Problem of Dirichlet—Still Unsolved

Abstract Let r2(n) denote the number of representations of the positive integer n as a sum of two squares, and let d(n) denote the number of positive divisors of n. Gauss and Dirichlet were evidently the first mathematicians to derive asymptotic formulas for ∑n ⩽ xr2(n) and ∑n ⩽ xd(n), respectively, as x tends to infinity. But what is the error made in such approximations? Number theorists have been attempting to answer these two questions for over one and one-half centuries, and although we think that we essentially “know” what these errors are, progress in proving these conjectures has been agonizingly slow. Ramanujan had a keen interest in these problems, and although, to the best of our knowledge, he did not establish any bounds for the error terms, he did give us identities that have been used to derive bounds, and two further identities that might be useful, if we can figure out how to use them. In this paper, we survey what is known about these two famous unsolved problems, with a moderate emphasis on Ramanujan's contributions.
A Multimodal Translation-Based Approach for Knowledge Graph Representation Learning

Current methods for knowledge graph (KG) representation learning focus solely on the structure of the KG and do not exploit any kind of external information, such as visual and linguistic information corresponding to the KG entities. In this paper, we propose a multimodal translation-based approach that defines the energy of a KG triple as the sum of sub-energy functions that leverage both multimodal (visual and linguistic) and structural KG representations. Next, a ranking-based loss is minimized using a simple neural network architecture. Moreover, we introduce a new large-scale dataset for multimodal KG representation learning. We compared the performance of our approach to other baselines on two standard tasks, namely knowledge graph completion and triple classification, using our as well as the WN9-IMG dataset. The results demonstrate that our approach outperforms all baselines on both tasks and datasets.
Serum miR-29a and miR-122 as Potential Biomarkers for Non-Alcoholic Fatty Liver Disease (NAFLD).

BACKGROUND Non-Alcoholic Fatty Liver Disease (NAFLD) is an over accumulation of triglyceride in the liver without alcohol consumption. Its major cause is insulin resistance. Patients with NAFLD can develop liver fibrosis, cirrhosis and hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) are non-coding RNAs that regulate post-transcriptional gene silencing. Previous research reported that miR-29 family (a, b and c) and miR-122 have an important role in regulating insulin resistance related to NAFLD. OBJECTIVE The purpose of this study was to investigate that miR-29 and miR-122 can be possible biomarkers for non-invasive diagnosis of NAFLD. METHOD Serum samples were collected from 58 NAFLD patients and 34 healthy controls. MiRNAs were extracted from serum by using microRNA purification kit followed by polyuridylation, reverse transcription and quantitative real-time PCR. Also, we analyzed the correlation between miR-29 and miR-122 and level of liver inflammation in NAFLD patients. RESULTS We found that the serum miR-29a levels in NAFLD patients were significantly lower (P = 0.006) than the control group, while miR-29c levels were unchanged, and miR-29b levels were undetectable. However, we found that serum miR-122 levels in NAFLD patients were significantly higher (P < 0.001) than those found in the control group. For miR-29a, the area under curve (AUC) was 0.679 (P = 0.0065) with 60.87% sensitivity and 82.35% specificity. For miR-122, the AUC was 0.831 (P < 0.0001) with 75.00% sensitivity and 82.35% specificity. Interestingly, the levels of serum miR- 122 were significantly different between patients without steatohepatitis (NAS < 4) and steatohepatitis (NAS ≥ 4), indicating that the levels of miR-122 were related to the severity of NAFLD. CONCLUSION The levels of miR-29a and miR-122 might be beneficial and compelling as possible biomarkers for non-invasive diagnosis of NAFLD.
SemEval 2018 Task 2: Multilingual Emoji Prediction

This paper describes the results of the first Shared Task on Multilingual Emoji Prediction, organized as part of SemEval 2018. Given the text of a tweet, the task consists of predicting the most likely emoji to be used along such tweet. Two subtasks were proposed, one for English and one for Spanish, and participants were allowed to submit a system run to one or both subtasks. In total, 49 teams participated to the English subtask and 22 teams submitted a system run to the Spanish subtask. Evaluation was carried out emoji-wise, and the final ranking was based on macro F-Score. Data and further information about this task can be found at https://competitions.codalab. org/competitions/17344.
Efficacy of statin therapy in patients with acute respiratory distress syndrome/acute lung injury: a systematic review and meta-analysis.

OBJECTIVE Approximately 7.5% of patients admitted to Intensive Care Unit (ICU) of hospitals are likely diagnosed with acute lung injury (ALI) or acute respiratory distress syndrome (ALI/ARDS), and more than one-third of the affected patients die with this disease. Despite the improvement in patient care with the availability of mechanical ventilators, mortality among these patients is unabated. Even though many drugs proved effective in preclinical studies, none is efficacious clinically, and no pharmacological treatment is insight. Statins were reported to exert anti-inflammatory effects and it was suggested that these drugs may be useful in ALI/ARDS patients. However, the initial positive results with statins were not confirmed in later studies, raising doubts about their usefulness. In the present meta-analysis, we examined the efficacy of statins in ALI/ARDS patients. MATERIALS AND METHODS Various databases were searched to identify both randomized clinical trials and cohort studies, where statin users were compared to non-statin users. To increase the strength of the analysis, cohort studies and random clinical trials were combined in the present analysis. RevMan software from the Cochrane Collaboration was used to a conduct meta-analysis. RESULTS Baseline characteristics indicated that APACHE-III score to be lower in statin users, suggesting some beneficial effects. However, mortality and severe sepsis were unchanged following statin treatment. But results also showed reduced SOFA score and increased number of ventilator-free days among statin users, indicating that statins are likely to have some beneficial effects. CONCLUSIONS Statin treatment of ALI/ARDS patients seems to improve health in terms of organ failure and also by lowering the need for ventilation. However, the sample size is too small to accurately assess the effects on mortality and sepsis and further investigations are needed.
nSMase2 (Type 2-Neutral Sphingomyelinase) Deficiency or Inhibition by GW4869 Reduces Inflammation and Atherosclerosis in Apoe−/− Mice

Objective— Atherosclerosis is a chronic multifactorial and inflammatory disease of large and medium arteries and the leading cause of cardiovascular diseases worldwide. The aim of this study was to investigate whether and how the nSMase2 (type 2-neutral sphingomyelinase), a key enzyme of sphingolipid metabolism, may contribute to the development of atherosclerotic lesions. Approach and Results— The role of nSMase2 in atherosclerosis was investigated in Apoe−/−;Smpd3fro/fro mice, mutant for nSMase2, and in Apoe−/−;Smpd3+/+ mice intraperitoneally injected with GW4869, a pharmacological nSMase2 inhibitor. The defect or inhibition of nSMase2 resulted in a reduction of atherosclerotic lesions and a decrease in macrophage infiltration and lipid deposition, although cholesterolemia remained unchanged. nSMase2 inhibition decreased the inflammatory response of murine endothelial cells to oxLDL (oxidized low-density lipoprotein), as assessed by the significant reduction of MCP-1 (monocyte chemoattractant protein 1), ICAM-1 (intercellular adhesion molecule-1), and VCAM-1 (vascular cell adhesion molecule-1) mRNA expressions and macrophage recruitment. Likewise, in RAW264.7 or in macrophages isolated from Apoe−/−/Smpd3fro/fro or Apoe−/−/Smpd3+/+ mice stimulated by lipopolysaccharides, nSMase2 inhibition resulted in a decrease in the expression of inflammatory molecules. Mechanistically, the anti-inflammatory response resulting from nSMase2 inhibition involves Nrf2 (nuclear factor [erythroid-derived 2]-like 2 or NF-E2–related factor-2) activation in both endothelial cells and macrophages, as assessed by the lack of protective effect of GW4869 in endothelial cells silenced for Nrf2 by small interfering RNAs, and in lipopolysaccharide-stimulated macrophages issued from Nrf2-KO mice. Conclusions— The genetic deficiency or inhibition of nSMase2 strongly decreases the development of atherosclerotic lesions in Apoe−/− mice, by reducing inflammatory responses through a mechanism involving the Nrf2 pathway. Inhibitors of nSMase2 may, therefore, constitute a novel approach to slow down atherosclerosis progression.
ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention

Reasoning is a very important topic and has many important applications in the field of natural language processing. Semantic Evaluation (SemEval) 2018 Task 12 “The Argument Reasoning Comprehension” committed to research natural language reasoning. In this task, we proposed a novel argument reasoning comprehension system, ITNLP-ARC, which use Neural Networks technology to solve this problem. In our system, the LSTM model is involved to encode both the premise sentences and the warrant sentences. The attention model is used to merge the two premise sentence vectors. Through comparing the similarity between the attention vector and each of the two warrant vectors, we choose the one with higher similarity as our system’s final answer.
Multiplicative Tree-Structured Long Short-Term Memory Networks for Semantic Representations

Tree-structured LSTMs have shown advantages in learning semantic representations by exploiting syntactic information. Most existing methods model tree structures by bottom-up combinations of constituent nodes using the same shared compositional function and often making use of input word information only. The inability to capture the richness of compositionality makes these models lack expressive power. In this paper, we propose multiplicative tree-structured LSTMs to tackle this problem. Our model makes use of not only word information but also relation information between words. It is more expressive, as different combination functions can be used for each child node. In addition to syntactic trees, we also investigate the use of Abstract Meaning Representation in tree-structured models, in order to incorporate both syntactic and semantic information from the sentence. Experimental results on common NLP tasks show the proposed models lead to better sentence representation and AMR brings benefits in complex tasks.
Mindfulness Meditation Targets Transdiagnostic Symptoms Implicated in Stress-Related Disorders: Understanding Relationships between Changes in Mindfulness, Sleep Quality, and Physical Symptoms

Mindfulness-Based Stress Reduction (MBSR) is an 8-week meditation program known to improve anxiety, depression, and psychological well-being. Other health-related effects, such as sleep quality, are less well established, as are the psychological processes associated with therapeutic change. This prospective, observational study (n = 213) aimed to determine whether perseverative cognition, indicated by rumination and intrusive thoughts, and emotion regulation, measured by avoidance, thought suppression, emotion suppression, and cognitive reappraisal, partly accounted for the hypothesized relationship between changes in mindfulness and two health-related outcomes: sleep quality and stress-related physical symptoms. As expected, increased mindfulness following the MBSR program was directly correlated with decreased sleep disturbance (r = −0.21, p = 0.004) and decreased stress-related physical symptoms (r = −0.38, p < 0.001). Partial correlations revealed that pre-post changes in rumination, unwanted intrusive thoughts, thought suppression, experiential avoidance, emotion suppression, and cognitive reappraisal each uniquely accounted for up to 32% of the correlation between the change in mindfulness and change in sleep disturbance and up to 30% of the correlation between the change in mindfulness and change in stress-related physical symptoms. Results suggest that the stress-reducing effects of MBSR are due, in part, to improvements in perseverative cognition and emotion regulation, two “transdiagnostic” mental processes that cut across stress-related disorders.
Lactoferrin: A Powerful Antimicrobial Protein Present in Milk

Lactoferrin (Lf) is an iron-chelating glycoprotein present in milk and mucosal secretions, a component of the mammalian innate immune system. Lf is microbiostatic and microbicidal. Lf can reduce the bacterial expression of virulence factors, such as those involved in biofilm production and protease secretion. The high identity among mammalian Lf sequences facilitates its use in human and veterinary medicine. Lf of bovine origin is the principal Lf used due to its commercial availability through purification from milk whey; recombinant Lfs (bovine, human, and porcine) have been used as well. Lf is a stable protein that retains its physicochemical characteristics under gastric pH conditions, and in most cases it is bioactive even after digestion; thus, the incorporation of Lf into diets facilitates its administration to animals. The aim of this review is to examine original research in which the effects of bovine and porcine Lf on pathogens of domestic animals have been demonstrated through in vitro and in vivo assays, with the purpose of ascertaining the benefits that Lf provides in the treatment of infectious diseases.
Effects of Compounded Human Ghrelin in a Mouse Model of Pancreatic Carcinoma

Ghrelin is a peptide that is secreted from the stomach and plays a role in appetite, weight gain, and skeletal muscle composition. Thus, compounded human ghrelin is a candidate drug for improving nutritional status after pancreatic surgery. However, in patients with pancreatic carcinomas, adverse influences on the occult tumor growth of ghrelin-induced secretion are a concern. The present study describes the effects of the administration of compounded human ghrelin on weight gain and pancreatic cancer cell growth in a mouse model. Changes in body weight and tumor growth in a subcutaneously transplanted pancreatic carcinoma cell line in vivo (5-week-old BALB/c-nu/nu mice) were examined with or without the administration of compounded human ghrelin. Compounded human ghrelin was administered at 44 days after post-transplantation” Changes in weight were not significantly different between the control and compounded human ghrelin groups 8 days after compounded human ghrelin administration, and no association between weight and concentration of compounded human ghrelin was identified. Tumor growth after the administration of compounded human ghrelin was significantly lower than that of the control group, with the magnitude of the decrease being associated with increasing compounded human ghrelin concentration (p<0.05). At 6 and 8 days after compounded human ghrelin administration, increases in tumor weights of the control groups (0.5±0.3 g and 0.9±0.2 g, respectively) were significantly greater than those observed for groups receiving 3, 15, and 30 nmol per kg of compounded human ghrelin (0.1 and 0.2, 0.2 and 0.3, and 0.2 and 0.3, respectively). There were no adverse effects of compounded human ghrelin administration. Plasma leptin levels were significantly lower in cancer cells compared with the control vehicle (p<0.05), which was decreased in mice receiving 30nmol per kg of compounded human ghrelin in comparison with those receiving vehicle (p<0.05). Although the administration of compounded human ghrelin did not influence weight gain, compounded human ghrelin significantly inhibited pancreatic cancer cell growth and might inhibit plasma leptin levels.