Miracle-dz/UniFAR-FTUs huggingface dataset:
A new assessment of the kinematic distance to the Pleiades: based on radial velocities and proper motions only

Abstract We present a new determination of the distance to the Pleiades using the moving-cluster method, allowing for inclusion of the effects of expansion and rotation of the cluster. While rotation appears neglegible, we find a slight expansion of the cluster with a maximum velocity of 0.15 km s−1 and a distance modulus of (m − M)0 = 5.50 ± 0.13 mag. This is larger but compatible with the new Hipparcos distance modulus of 5.40 ± 0.03 mag. On the other hand, various distance moduli for the Pleiades are found in the literature, many resulting from isochrone fitting. They scatter around a value of 5.63 mag. Our results are also compatible with these measurements, within the error bars.
Added Value of Anti-CD74 Autoantibodies in Axial SpondyloArthritis in a Population With Low HLA-B27 Prevalence

Axial spondyloarthritis (axSpA) is often diagnosed late due to the non-specific nature of its main symptom [chronic back pain (CBP)] and to the paucity of diagnostic markers, particularly in regions with low HLA-B27 prevalence, such as the Middle-East. We tested the performance of IgG4 and IgA anti-CD74 antibodies as an early diagnostic marker for axSpA, compared with the performance of HLA-B27, in Lebanon. Sera of axSpA patients diagnosed by the rheumatologist and also fulfilling the imaging arm of the ASAS criteria (patients) and of blood donors (BD) (controls) were analyzed for HLA-B27, IgG4 and IgA anti-CD74, blinded to clinical characteristics. Receiver Operating Characteristic curves were constructed to identify an optimal cut-off point for anti-CD74 antibodies. Diagnostic properties were calculated (sensitivity, specificity, positive, and positive predictive values (PPV, NPV), Likelihood ratios) for each marker. Forty-nine axSpA patients and 102 BD were included in the final analysis. IgA anti-CD74 correlated poorly with axSpA (Area Under the Curve (AUC) 0.657), whereas IgG4 anti-CD74 had a good discriminative value (AUC 0.837). Respectively, for HLA-B27, IgG4 anti-CD74, and the combination of both, we found a sensitivity of 33-92-33%, specificity of 96-79-98%, PPV 80-68-89%, NPV 75-95-75%, and LR+ 8.2-4.4-16.5. IgG4 anti-CD 74 were positive in 88% of HLA-B27 negative axSpA patients, and correlated with BASDAI. In this first study in a population with low HLA-B27 prevalence, IgG4 anti-CD74 antibodies combined with HLA-B27 showed higher diagnostic value than HLA-B27 alone for early axSpA. IgG4 anti-CD74 should be considered for further evaluation as an early axSpA diagnostic marker in future dedicated research, particularly in patients with CBP.
Changes in Plasma von Willebrand Factor and Cellular Fibronectin in MRI-Defined Traumatic Microvascular Injury

The neuropathology of traumatic brain injury (TB) is diverse, including primary injury to neurons, axons, glial cells, vascular structures, and secondary processes, such as edema and inflammation that vary between individual patients. Traumatic microvascular injury is an important endophenotype of TBI-related injury. We studied patients who sustained a TBI requiring ER evaluation and had an MRI performed within 48 h of injury. We classified patients into 3 groups based on their MRI findings: (1) those that had evidence of traumatic microvascular injury on susceptibility or diffusion weighted MRI sequences without frank hemorrhage [Traumatic Vascular Injury (TVI) group; 20 subjects]. (2) those who had evidence of intraparenchymal, subdural, epidural, or subarachnoid hemorrhage [Traumatic Hemorrhage (TH) group; 26 subjects], and (3) those who had no traumatic injuries detected by MRI [MRI-negative group; 30 subjects]. We then measured plasma protein biomarkers of vascular injury [von Willebrand Factor (vWF) or cellular fibronectin (cFn)] and axonal injury (phosphorylated neurofilament heavy chain; pNF-H). We found that the TVI group was characterized by decreased expression of plasma vWF (p < 0.05 compared to MRI-negative group; p < 0.00001 compared to TH group) ≤48 h after injury. cFN was no different between groups ≤48 h after injury, but was increased in the TVI group compared to the MRI-negative (p < 0.00001) and TH (p < 0.00001) groups when measured >48 h from injury. pNF-H was increased in both the TH and TVI groups compared to the MRI-negative group ≤48 h from injury. When we used the MRI grouping and molecular biomarkers in a model to predict Glasgow Outcome Scale-Extended (GOS-E) score at 30–90 days, we found that inclusion of the imaging data and biomarkers substantially improved the ability to predict a good outcome over clinical information alone. These data indicate that there is a distinct, vascular-predominant endophenotype in a subset of patients who sustain a TBI and that these injuries are characterized by a specific biomarker profile. Further work to will be needed to determine whether these biomarkers can be useful as predictive and pharmacodynamic biomarkers for vascular-directed therapies after TBI.
Neuroscience and Biobehavioral Reviews Neural mechanisms of attending to items in working memory

Working memory, the ability to keep recently accessed information available for immediate manipulation, has been proposed to rely on two mechanisms that appear di ﬃ cult to reconcile: self-sustained neural ﬁ ring, or the opposite — activity-silent synaptic traces. Here we review and contrast models of these two mechanisms, and then show that both phenomena can co-exist within a uni ﬁ ed system in which neurons hold information in both activity and synapses. Rapid plasticity in ﬂ exibly-coding neurons allows features to be bound together into objects, with an important emergent property being the focus of attention. One memory item is held by persistent activity in an attended or “ focused ” state, and is thus remembered better than other items. Other, pre- viously attended items can remain in memory but in the background, encoded in activity-silent synaptic traces. This dual functional architecture provides a uni ﬁ ed common mechanism accounting for a diversity of perplexing attention and memory e ﬀ ects that have been hitherto di ﬃ cult to explain in a single theoretical framework.
Effects of Parental Autonomy Support and Teacher Support on Middle School Students’ Homework Effort: Homework Autonomous Motivation as Mediator

The present study tested whether students’ autonomous motivation mediated the association between adult support (parental autonomy support, teacher support) and students’ homework effort. A sample of 666 Chinese middle school students was recruited to complete the parental autonomy support questionnaire, teacher support questionnaire, homework autonomous motivation questionnaire and homework effort questionnaire. Structural equation modeling showed that both parental autonomy support and teacher support positively predicted mathematics homework effort, and mathematics homework autonomous motivation was a mediator in these associations. The present study reveals the importance of adult support and autonomous motivation, and has theoretical and practical implications.
Deficits in Social Behavior Precede Cognitive Decline in Middle-Aged Mice

An extensive literature details deterioration of multiple brain functions, especially memory and learning, during aging in humans and in rodents. In contrast, the decline of social functions is less well understood. It is presently not clear whether age-dependent deficits observed in social behavior mainly reflect the disruption of social networks activity or are simply secondary to a more general impairment of cognitive and executive functions in older individuals. To address this issue, we carried out a battery of behavioral tasks exploring different brain functions in young (3 months) and middle-aged wild-type mice (9 months). Consistent with previous reports, our results show no obvious differences between these two groups in most of the domains investigated including learning and memory. Surprisingly, in social tasks, middle-aged animals showed significantly reduced levels of interactions when exposed to a new juvenile mouse. In the absence of overt cognitive decline, our findings suggest that social impairments may precede the disruption of other brain functions and argue for a selective vulnerability of social circuits during aging.
Autoencoder Based Feature Selection Method for Classification of Anticancer Drug Response

Anticancer drug responses can be varied for individual patients. This difference is mainly caused by genetic reasons, like mutations and RNA expression. Thus, these genetic features are often used to construct classification models to predict the drug response. This research focuses on the feature selection issue for the classification models. Because of the vast dimensions of the feature space for predicting drug response, the autoencoder network was first built, and a subset of inputs with the important contribution was selected. Then by using the Boruta algorithm, a further small set of features was determined for the random forest, which was used to predict drug response. Two datasets, GDSC and CCLE, were used to illustrate the efficiency of the proposed method.
Machine Learning SNP Based Prediction for Precision Medicine

In the past decade, precision genomics based medicine has emerged to provide tailored and effective healthcare for patients depending upon their genetic features. Genome Wide Association Studies have also identified population based risk genetic variants for common and complex diseases. In order to meet the full promise of precision medicine, research is attempting to leverage our increasing genomic understanding and further develop personalized medical healthcare through ever more accurate disease risk prediction models. Polygenic risk scoring and machine learning are two primary approaches for disease risk prediction. Despite recent improvements, the results of polygenic risk scoring remain limited due to the approaches that are currently used. By contrast, machine learning algorithms have increased predictive abilities for complex disease risk. This increase in predictive abilities results from the ability of machine learning algorithms to handle multi-dimensional data. Here, we provide an overview of polygenic risk scoring and machine learning in complex disease risk prediction. We highlight recent machine learning application developments and describe how machine learning approaches can lead to improved complex disease prediction, which will help to incorporate genetic features into future personalized healthcare. Finally, we discuss how the future application of machine learning prediction models might help manage complex disease by providing tissue-specific targets for customized, preventive interventions.
C18H17NO6 and Its Combination with Scutellarin Suppress the Proliferation and Induce the Apoptosis of Human Glioma Cells via Upregulation of Fas-Associated Factor 1 Expression

Background Glioma is the most common malignant brain tumor and the patients are prone to poor prognosis. Due to limited treatments, new drug exploration has become a general trend. Therefore, the objective of this study is to investigate the effect of the new drugs C18H17NO6 and its combination with Scutellarin on glioma cells and the underlying mechanism. Method U251 and LN229 cells were administrated with C18H17NO6 and its combination with Scutellarin. The proliferation ability of glioma cells was determined by cell counting kit-8, plate clone formation assay, and EdU incorporation assay. The cell cycle and apoptosis detection were detected by flow cytometry. Moreover, TUNEL assay was also used for cell apoptosis analysis. Then, the transfer ability of cells was achieved through wound healing assay. Furthermore, polymerase chain reaction (PCR) test and western bolt analysis were used to detect the mRNA expression and protein expression, respectively. Lastly, immunofluorescence was for the purity identification of astrocyte. Result The results showed that, with the increasing dose of C18H17NO6, the cell inhibition rate, the cells in G1 phase, and the apoptosis rate were gradually increased, but the clone number, proliferation rate, and the cells in G2 and S phases were gradually decreased in comparison with control group. However, with the increase of C18H17NO6, the transferred rate of U251 and LN229 was not significantly augmented, expect that on U251 in C18H17NO6 5 μM group. In addition, Scutellarin 200 μM has little effect on proliferation, with the inhibition rate 10-20% and proliferation rate except U251 in Scutellarin 200 μM group similar to that in control group. Moreover, compared to control group, Scutellarin 300 μM increased the U251 cells in G2 and S phases and the apoptosis rate of LN229 but decreased the LN229 cells in G2 and S phases. Besides, in Scutellarin 200 μM group, the transfer ability of LN229 was inhibited, but not in U251. Furthermore, if C18H17NO6 was combined with Scutellarin 200/300μM, the proliferation and transferred ability were suppressed and the apoptosis was elevated in LN229 cell in comparison with C18H17NO6 alone. Dramatically, the combined effect on U251 was the exact opposite. Importantly, there was little toxicity on astrocyte under the dose of C18H17NO6 and Scutellarin in the study. In molecular level, the mRNA and protein expression of Fas-associated factor 1 (FAF1) expression in U251 and LN229 were upregulated by C18H17NO6 and its combination with Scutellarin, especially the protein expression. Conclusion C18H17NO6 could efficiently suppress cell proliferation and induce cell apoptosis in glioma cells, and its combination with Scutellarin had a promoting effect, in which the underlying mechanism referred to the upregulation of Fas-associated factor 1.
ECG Signal Denoising and Features Extraction Using Unbiased FIR Smoothing

Methods of the electrocardiography (ECG) signal features extraction are required to detect heart abnormalities and different kinds of diseases. However, different artefacts and measurement noise often hinder providing accurate features extraction. One of the standard techniques developed for ECG signals employs linear prediction. Referring to the fact that prediction is not required for ECG signal processing, smoothing can be more efficient. In this paper, we employ the p-shift unbiased finite impulse response (UFIR) filter, which becomes smooth by p < 0. We develop this filter to have an adaptive averaging horizon: optimal for slow ECG behaviours and minimal for fast excursions. It is shown that the adaptive UFIR algorithm developed in such a way provides better denoising and suboptimal features extraction in terms of the output signal-noise ratio (SNR). The algorithm is developed to detect durations and amplitudes of the P-wave, QRS-complex, and T-wave in the standard ECG signal map. Better performance of the algorithm designed is demonstrated in a comparison with the standard linear predictor, UFIR filter, and UFIR predictive filter based on real ECG data associated with normal heartbeats.
A new species of sardine, Sardinellapacifica from the Philippines (Teleostei, Clupeiformes, Clupeidae)

Abstract A new sardine, Sardinellapacificasp. n. , is described on the basis of 21 specimens collected from the Philippines. The new species closely resembles Sardinellafimbriata (Valenciennes, 1847), both species having lateral scales with centrally discontinuous striae, a dark spot on the dorsal-fin origin, more than 70 lower gill rakers on the first gill arch, the pelvic fin with eight rays, and 17 or 18 prepelvic and 12 or 13 postpelvic scutes. However, the new species is distinguished from the latter by lower counts of lateral scales, pseudobranchial filaments, and postpelvic scutes (38–41, 14–19 and 12–13, respectively vs. 44–46, 19–22 and 13–14), and a shorter lower jaw (10.4–11.6% of standard length vs. 11.1–12.2%). Sardinellapacificasp. n. is known only from the Philippines, whereas S.fimbriata is restricted to the Indian Ocean, although previously considered to be an Indo-West Pacific species, distributed from India to the Philippines.
Allopurinol potentiates the hepatoprotective effect of metformin and vitamin E in fructose-induced fatty liver in rats

Aim of the study Non-alcoholic fatty liver disease (NAFLD) is a challenging health problem. Hyperuricemia is a key player in the pathogenesis of NAFLD. This study investigated the effect of allopurinol (uric acid synthesis inhibitor) in combination with metformin and vitamin E in prevention of fructose induced-fatty liver in rats. Material and methods Rats were divided into 7 groups: control group, fructose group (model group of NAFLD), allopurinol-treated group, metformin-treated group, vitamin E-treated group, metformin plus vitamin E-treated group and a combination group (received allopurinol plus metformin plus vitamin E). Development of NAFLD was assessed biochemically by serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) as well as by histopathological examination. Oxidative stress parameters [reduced glutathione (GSH), superoxide dismutase (SOD), malondialdehyde (MDA)], and the inflammatory mediators tumor necrosis factor α (TNF-α) and inducible nitric oxide synthase (iNOS) were assessed, along with serum levels of uric acid and triglyceride (TG). Results Combination of allopurinol plus metformin plus vitamin E significantly attenuated fatty changes compared to their respective monotherapy. Interestingly, though all treated groups showed significant attenuation in the oxidative stress markers, TNF-α level and iNOS immunostaining in hepatic tissue, along with a significant decrease in the levels of uric acid and TG, the combination group showed a further significant decrease in the serum level of uric acid and iNOS immunostaining compared to other treated regimens. Conclusions Allopurinol synergistically increases the protective effect of metformin and vitamin E in treatment of NAFLD, namely via reduction of uric acid synthesis and iNOS expression.
The Differential Effects of Good Luck Belief on Cognitive Performance in Boys and Girls

There is evidence that inducing a luck-related superstition leads to better performance on a variety of motor dexterity and cognitive tasks. However, some replication efforts have failed to succeed. At the same time, our previous findings suggest that the effect of good luck belief on cognitive performance interacts with gender. The present research aimed at replicating the study with a sample of adolescents among whom the superstitious beliefs are particularly prevalent. The participants (N = 99) were allocated to either a control or experimental group, and were asked to solve eight problems focused on cognitive reflection, conjunction fallacy, denominator neglect, and probabilistic reasoning. The experimental manipulation negatively affected boys' performance. Yet, it facilitated performance in girls via increase in their self-efficacy, measured as subjective estimate of future success in the tasks. Thus, gender seems to moderate the effect of luck-related belief on solutions to cognitive problems, which are an important part of our day-to-day decisions. Given initial gender gap in the present tasks, the crucial question to be addressed in future research is possibility of gender being a proxy for prior competence. It would imply that good luck beliefs might help low scorers, for instance in becoming less anxious and more confident, but could be harmful for high scorers.
Law enforcement as politics by other means: lessons from countering revolutionary terrorism

This article demonstrates that law enforcement, as a counterterrorism instrument, is not only useful to disrupt terrorist activities by taking resources and manpower away from the terrorist group, but can also have a more political impact. Law enforcement pressure can divert the resources of a terrorist group away from political activity to mere survival or a private feud against the state. Drawing on cases studies of the Red Army Faction and the Weather Underground, two ways in which terrorist groups can become isolated from their support base as a result of law enforcement pressure will be illustrated.
Prevalence and Risk Factors of Reduced Bone Mineral Density in Systemic Lupus Erythematosus Patients: A Meta-Analysis

Background We aimed to conduct a meta-analysis concerning the frequency and risk factors of reduced bone mineral density (BMD) in systemic lupus erythematosus (SLE) with evidence from published studies. Methods A comprehensive literature search was conducted based on the EMBASE, Web of Science, PubMed, and Cochrane Library databases up to March 5th, 2017. Eligible studies reported any prevalence of reduced BMD in SLE patients. All risk factors with odds ratios or risk ratios associated with reduced BMD were extracted. Results 71 reports with 33527 SLE patients were included. Low BMD, osteopenia, and osteoporosis at any site were presented, respectively, in 45%, 38%, and 13% of the SLE patients. The prevalence of osteoporosis increased with the advancing of age, while U-shaped associations between age and the prevalence of low BMD and osteopenia were found. Lumbar spine was indicated to have higher prevalence of osteoporosis. Age, disease duration, drugs use, and many other factors were identified as predictors of reduced BMD. Conclusion Low BMD, osteoporosis, and osteopenia appeared to be prevalent in patients with SLE. Risk factors of reduced BMD were various.
Decellularized liver bioscaffold: a histological and immunohistochemical comparison between normal, fibrotic and hepatocellular carcinoma

Aim of the study Increasing demand for liver transplantation represents an important health burden. Decellularized liver bioscaffold can be a suitable alternative for whole organ transplantation. However, various pathologies can affect the structure of decellularized scaffolds. This work discusses differences between hepatic fibrosis (HF), hepatocellular carcinoma (HCC) and normal decellularized liver bioscaffolds. Material and methods Murine models of HF and HCC were created, livers from normal, HF and HCC were decellularized, and evaluation of decellularization was done using morphological, histological and DNA analysis examination. Also, immunohistochemical staining using collagen, laminin, fibronectin and alphafetoprotein was done. Deposition area and intensity of the used immunohistochemical staining in liver capsules and the staining deposition thickness in the blood vessels and hepatic capsule walls were measured for comparison between the three models. Results Normal, HF and HCC livers were decellularized efficiently as confirmed by histological and DNA estimation. HCC decellularized samples showed significantly higher collagen, fibronectin and laminin deposition in both capsule and blood vessels, followed by HF decellularized samples, which also showed the highest thickness of laminin deposition in both capsule and blood vessels, then the normal model, which recorded the lowest value. Alphafetoprotein positive cells were absent in normal and HF, with rare cells in HCC. Conclusions Even pathologic livers, HF and HCC, can be efficiently decellularized, showing normal morphology and architecture. However, HCC and HF showed significantly higher deposition of extracellular matrix proteins: collagen, fibronectin and laminin. The impact of these differences on physiological and immunological functions of the bioscaffold requires recellularization experiments.