Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Connexin and Pannexin Channels in Perinatal Brain Injury and Inflammation

Perinatal brain injury remains a major cause of death and life-long disability. Perinatal brain injury is typically associated with hypoxia-ischemia and/or infection/inflammation. Both hypoxia-ischemia and infection trigger an inflammatory response in the brain. The inflammatory response can contribute to brain cell loss and chronic neuroinflammation leading to neurological impairments. It is now well-established that brain injury evolves over time, and shows a striking spread from injured to previously uninjured regions of the brain. There is increasing evidence that this spread is related to opening of connexin hemichannels and pannexin channels, both of which are large conductance membrane channels found in almost all cell types in the brain. Blocking connexin hemichannels within the first 3 h after hypoxia-ischemia has been shown to improve outcomes in term equivalent fetal sheep but it is important to also understand the downstream pathways linking membrane channel opening with the development of injury in order to identify new therapeutic targets. Open membrane channels release adenosine triphosphate (ATP), and other neuroactive molecules, into the extracellular space. ATP has an important physiological role, but has also been reported to act as a damage-associated molecular pattern (DAMP) signal mediated through specific purinergic receptors and so act as a primary signal 1 in the innate immune system inflammasome pathway. More crucially, extracellular ATP is a key inflammasome signal 2 activator, with purinergic receptor binding triggering the assembly of the multi-protein inflammasome complex. The inflammasome pathway and complex formation contribute to activation of inflammatory caspases, and the release of inflammatory cytokines, including interleukin (IL)-1β, tumor necrosis factor (TNF)-α, IL-18, and vascular endothelial growth factor (VEGF). We propose that the NOD-like receptor protein-3 (NLRP3) inflammasome, which has been linked to inflammatory responses in models of ischemic stroke and various inflammatory diseases, may be one mechanism by which connexin hemichannel opening especially mediates perinatal brain injury.
SwitchAgg: A Further Step Towards In-Network Computation

Many distributed applications adopt a partition/aggregation pattern to achieve high performance and scalability. The aggregation process, which usually takes a large portion of the overall execution time, incurs large amount of network traffic and bottlenecks the system performance. To reduce network traffic, some researches take advantage of network devices to commit innetwork aggregation. However, these approaches use either special topology or middle-boxes, which cannot be easily deployed in current datacenters. The emerging programmable RMT switch brings us new opportunities to implement in-network computation task. However, we argue that the architecture of RMT switch is not suitable for in-network aggregation since it is designed primarily for implementing traditional network functions. In this paper, we first give a detailed analysis of in-network aggregation, and point out the key factor that affects the data reduction ratio. We then propose SwitchAgg, which is an innetwork aggregation system that is compatible with current datacenter infrastructures. We also evaluate the performance improvement we have gained from SwitchAgg. Our results show that, SwitchAgg can process data aggregation tasks at line rate and gives a high data reduction rate, which helps us to cut down network traffic and alleviate pressure on server CPU. In the system performance test, the job-completion-time can be reduced as much as 50%.
Modeling Information Retrieval by Formal Logic

Several mathematical frameworks have been used to model the information retrieval (IR) process, among them, formal logics. Logic-based IR models upgrade the IR process from document-query comparison to an inference process, in which both documents and queries are expressed as sentences of the selected formal logic. The underlying formal logic also permits one to represent and integrate knowledge in the IR process. One of the main obstacles that has prevented the adoption and large-scale diffusion of logic-based IR systems is their complexity. However, several logic-based IR models have been recently proposed that are applicable to large-scale data collections. In this survey, we present an overview of the most prominent logical IR models that have been proposed in the literature. The considered logical models are categorized under different axes, which include the considered logics and the way in which uncertainty has been modeled, for example, degrees of belief or degrees of truth. Accordingly, the main contribution of the article is to categorize the state-of-the-art logical models on a fine-grained basis, and for the considered models the related implementation aspects are described. Consequently, the proposed survey is finalized to better understand and compare the different logical IR models. Last, but not least, this article aims at reconsidering the potentials of logical approaches to IR by outlining the advances of logic-based approaches in close research areas.
2 Perceptual Effects of Inconsistency in Human Animations

The individual shape of the human body, including the geometry of its articulated structure and the distribution of weight over that structure, influences the kinematics of a person’s movements. How sensitive is the visual system to inconsistencies between shape and motion introduced by retargeting motion from one person onto the shape of another? We used optical motion capture to record five pairs of male performers with large differences in body weight, while they pushed, lifted, and threw objects. From these data, we estimated both the kinematics of the actions as well as the performer’s individual body shape. To obtain consistent and inconsistent stimuli, we created animated avatars by combining the shape and motion estimates from either a single performer or from different performers. Using these stimuli we conducted three experiments in an immersive virtual reality environment. First, a group of participants detected which of two stimuli was inconsistent. Performance was very low, and results were only marginally significant. Next, a second group of participants rated perceived attractiveness, eeriness, and humanness of consistent and inconsistent stimuli, but these judgements of animation characteristics were not affected by consistency of the stimuli. Finally, a third group of participants rated properties of the objects rather than of the performers. Here, we found strong influences of shape-motion inconsistency on perceived weight and thrown distance of objects. This suggests that the visual system relies on its knowledge of shape and motion and that these components are assimilated into an altered perception of the action outcome. We propose that the visual system attempts to resist inconsistent interpretations of human animations. Actions involving object manipulations present an opportunity for the visual system to reinterpret the introduced inconsistencies as a change in the dynamics of an object rather than as an unexpected combination of body shape and body motion.
The Three-Dimensional Signal Collection Field for Fiber Photometry in Brain Tissue

Fiber photometry is used to monitor signals from fluorescent indicators in genetically-defined neural populations in behaving animals. Recently, fiber photometry has rapidly expanded and it now provides researchers with increasingly powerful means to record neural dynamics and neuromodulatory action. However, it is not clear how to select the optimal fiber optic given the constraints and goals of a particular experiment. Here, using combined confocal/2-photon microscope, we quantitatively characterize the fluorescence collection properties of various optical fibers in brain tissue. We show that the fiber size plays a major role in defining the volume of the optically sampled brain region, whereas numerical aperture impacts the total amount of collected signal and, marginally, the shape and size of the collection volume. We show that ~80% of the effective signal arises from 105 to 106 μm3 volume extending ~200 μm from the fiber facet for 200 μm core optical fibers. Together with analytical and ray tracing collection maps, our results reveal the light collection properties of different optical fibers in brain tissue, allowing for an accurate selection of the fibers for photometry and helping for a more precise interpretation of measurements in terms of sampled volume.
WQR-UD: An online scheduling algorithm for FemtoClouds

FemtoClouds are computing platforms, implementing the Fog Computing paradigm, consisting in an ensemble of heterogeneous mobile devices whose users agree to run the tasks offloaded by other users. FemtoClouds are well suited for the execution of Bag-of-Tasks (BoTs) applications, but, being characterized by high resource heterogeneity and volatility, require the availability of scheduling techniques able to effectively deal with ensembles of independently-owned, heterogeneous devices that can suddenly leave the system. In this paper we propose WQR-UD, an online scheduling algorithm that, thanks to the combination of simple task and device selection policies (that do not require any information concerning the applications and the devices) with effective heterogeneity and volatility tolerance mechanisms, is able to effectively schedule a stream of BoT applications on FemtoCloud systems. We assess the ability of WQR-UD to meet its design goals by running an extensive simulation study for a large set of realistic operational scenarios. Our results clearly indicate that WQR-UD is able to effectively schedule a stream of BoT applications on FemtoCloud systems.
Dynamic Change of Gut Microbiota During Porcine Epidemic Diarrhea Virus Infection in Suckling Piglets

Porcine epidemic diarrhea (PED) is a disease that has a devastating effect on livestock. Currently, most studies are focused on comparing gut microbiota of healthy piglets and piglets with PED, resulting in gut microbial populations related to dynamic change in diarrheal piglets being poorly understood. The current study analyzed the characteristics of gut microbiota in porcine epidemic diarrhea virus (PEDV)-infected piglets during the suckling transition stage. Fresh fecal samples were collected from 1 to 3-week-old healthy piglets (n = 20) and PEDV infected piglets (n = 18) from the same swine farm. Total DNA was extracted from each sample and the V3–V4 hypervariable region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq platform. Statistically significant differences were observed in bacterial diversity and richness between the healthy and diarrheal piglets. Principal coordinates analysis (PCoA) showed structural segregation between diseased and healthy groups, as well as among 3 different age groups. The abundance of Escherichia-Shigella, Enterococcus, Fusobacterium, and Veillonella increased due to dysbiosis induced by PEDV infection. Notably, there was a remarkable age-related increase in Fusobacterium and Veillonella in diarrheal piglets. Certain SCFA-producing bacteria, such as Ruminococcaceae_UCG-002, Butyricimonas, and Alistipes, were shared by all healthy piglets, but were not identified in various age groups of diarrheal piglets. In addition, significant differences were observed between clusters of orthologous groups (COG) functional categories of healthy and PEDV-infected piglets. Our findings demonstrated that PEDV infection caused severe perturbations in porcine gut microbiota. Therefore, regulating gut microbiota in an age-related manner may be a promising method for the prevention or treatment of PEDV.
The English Plastic Bag Charge Changed Behavior and Increased Support for Other Charges to Reduce Plastic Waste

Plastic bags create large amounts of waste and cause lasting environmental problems when inappropriately discarded. In 2015, England introduced a mandatory five pence (US$0.06/€0.06) charge to customers for each single-use plastic bag taken from large stores. Combining a longitudinal survey (n = 1,230), supermarket observations (n = 3,764), and a longitudinal interview study (n = 43), we investigated people’s behavioral and attitudinal responses to the charge. We show that all age, gender, and income groups in England substantially reduced their plastic bag usage within 1 month after the charge was introduced, with interviewees highlighting the ease of bringing their own bags. Support for the bag charge also increased among all key demographic groups. Increased support for the plastic bag charge in turn predicted greater support for other charges to reduce plastic waste, suggesting a “policy spillover” effect. Results indicate a broad and positive effect of the bag charge, which appears to have catalyzed wider waste awareness among the British public. This may facilitate the introduction of other policies to eliminate avoidable single-use plastics and packaging.
Venom-Derived Peptide Modulators of Cation-Selective Channels: Friend, Foe or Frenemy

Ion channels play a key role in our body to regulate homeostasis and conduct electrical signals. With the help of advances in structural biology, as well as the discovery of numerous channel modulators derived from animal toxins, we are moving toward a better understanding of the function and mode of action of ion channels. Their ubiquitous tissue distribution and the physiological relevancies of their opening and closing suggest that cation channels are particularly attractive drug targets, and years of research has revealed a variety of natural toxins that bind to these channels and alter their function. In this review, we provide an introductory overview of the major cation ion channels: potassium channels, sodium channels and calcium channels, describe their venom-derived peptide modulators, and how these peptides provide great research and therapeutic value to both basic and translational medical research.
Early Identification and Intervention of Schizophrenia: Insight From Hypotheses of Glutamate Dysfunction and Oxidative Stress

Schizophrenia is a severe mental disorder which leads to functional deterioration. Early detection and intervention are vital for better prognosis. However, the diagnosis of schizophrenia still depends on clinical observation to date. Without reliable biomarkers, schizophrenia is difficult to detect in its early phase. Further, there is no approved medication for prodromal schizophrenia because current antipsychotics fail to show satisfactory efficacy and safety. Therefore, to develop an effective early diagnostic and therapeutic approach for schizophrenia, especially in its prodromal phase, is crucial. Glutamate signaling dysfunction and dysregulation of oxidative stress have been considered to play important roles in schizophrenic prodrome. The N-methyl-D-aspartate receptor (NMDAR) is one of three types of ionotropic glutamate receptors. In this article, we reviewed literature regarding NMDAR hypofunction, oxidative stress, and the linkage between both in prodromal schizophrenia. The efficacy of NMDAR enhancers such as D-amino acid oxidase inhibitor was addressed. Finally, we highlighted potential biomarkers related to NMDAR and oxidative stress regulation, and therefore suggested the strategies of early detection and intervention of prodromal schizophrenia. Future larger-scale studies combining biomarkers and novel drug development for early psychosis are warranted.
Dynamics of Non-visual Responses in Humans: As Fast as Lightning?

The eye drives non-visual (NV) responses to light, including circadian resetting, pupillary reflex and alerting effects. Initially thought to depend on melanopsin-expressing retinal ganglion cells (ipRGCs), classical photopigments play a modulatory role in some of these responses. As most studies have investigated only a limited number of NV functions, generally under conditions of relatively high light levels and long duration of exposure, whether NV functions share similar irradiance sensitivities and response dynamics during light exposure is unknown. We addressed this issue using light exposure paradigms spectrally and spatially tuned to target mainly cones or ipRGCs, and by measuring longitudinally (50 min) several NV responses in 28 men. We demonstrate that the response dynamics of NV functions are faster than previously thought. We find that the brain, the heart, and thermoregulation are activated within 1 to 5 min of light exposure. Further, we show that NV functions do not share the same response sensitivities. While the half-maximum response is only ∼48 s for the tonic pupil diameter, it is ∼12 min for EEG gamma activity. Most NV responses seem to be saturated by low light levels, as low as 90 melanopic lux. Our results also reveal that it is possible to maintain optimal visual performance while modulating NV responses. Our findings have real-life implications. On one hand, light therapy paradigms should be re-evaluated with lower intensities and shorter durations, with the potential of improving patients’ compliance. On the other hand, the significant impact of low intensity and short duration light exposures on NV physiology should make us reconsider the potential health consequences of light exposure before bedtime, in particular on sleep and circadian physiology.
Commentary: Identification of Mutation Regions on NF1 Responsible for High- and Low-Risk Development of Optic Pathway Glioma in Neurofibromatosis Type I

Citation: Anastasaki C, Gao F and Gutmann DH (2019) Commentary: Identification of Mutation Regions on NF1 Responsible for Highand Low-Risk Development of Optic Pathway Glioma in Neurofibromatosis Type I. Front. Genet. 10:115. doi: 10.3389/fgene.2019. 00115 Commentary: Identification of Mutation Regions on NF1 Responsible for Highand Low-Risk Development of Optic Pathway Glioma in Neurofibromatosis Type I
Forecasting Stock Market Movement Direction Using Sentiment Analysis and Support Vector Machine

Investor sentiment plays an important role on the stock market. User-generated textual content on the Internet provides a precious source to reflect investor psychology and predicts stock prices as a complement to stock market data. This paper integrates sentiment analysis into a machine learning method based on support vector machine. Furthermore, we take the day-of-week effect into consideration and construct more reliable and realistic sentiment indexes. Empirical results illustrate that the accuracy of forecasting the movement direction of the SSE 50 Index can be as high as 89.93% with a rise of 18.6% after introducing sentiment variables. And, meanwhile, our model helps investors make wiser decisions. These findings also imply that sentiment probably contains precious information about the asset fundamental values and can be regarded as one of the leading indicators of the stock market.
Antibody-Dependent Cellular Phagocytosis in Antiviral Immune Responses

Antiviral activities of antibodies may either be dependent only on interactions between the antibody and cognate antigen, as in binding and neutralization of an infectious virion, or instead may require interactions between antibody–antigen immune complexes and immunoproteins or Fc receptor expressing immune effector cells. These Fc receptor-dependent antibody functions provide a direct link between the innate and adaptive immune systems by combining the potent antiviral activity of innate effector cells with the diversity and specificity of the adaptive humoral response. The Fc receptor-dependent function of antibody-dependent cellular phagocytosis (ADCP) provides mechanisms for clearance of virus and virus-infected cells, as well as for stimulation of downstream adaptive immune responses by facilitating antigen presentation, or by stimulating the secretion of inflammatory mediators. In this review, we discuss the properties of Fc receptors, antibodies, and effector cells that influence ADCP. We also provide and interpret evidence from studies that support a potential role for ADCP in either inhibiting or enhancing viral infection. Finally, we describe current approaches used to measure antiviral ADCP and discuss considerations for the translation of studies performed in animal models. We propose that additional investigation into the role of ADCP in protective viral responses, the specific virus epitopes targeted by ADCP antibodies, and the types of phagocytes and Fc receptors involved in ADCP at sites of virus infection will provide insight into strategies to successfully leverage this important immune response for improved antiviral immunity through rational vaccine design.
Measurements of the top-quark mass and properties at CMS

Measurements of the top-quark mass and other top-quark properties are presented, obtained from the CMS data collected in 2011 and 2012 at centre-of-mass energies of 7 and 8 TeV. The mass of the top quark is measured using several methods and decay channels. The measurements of the top-quark properties include the W helicity in top-quark decays, the search for anomalous couplings, and the ratio of top-quarks decaying to bW over qW in order to gain information on |Vtb| using both and single-top quark event samples. The results are compared with predictions from the standard model as well as new physics models. The cross section of events produced in association with a W, Z boson or a photon is also measured.
Towards Hybrid Human-System Regulation: Understanding Children' SRL Support Needs in Blended Classrooms

This paper proposes a new approach to translate learner data into self-regulated learning support. Learning phases in blended classrooms place unique requirements on students' self-regulated learning (SRL). Learning path graphs merge moment-by-moment learning curves and learning phase data to understand student' SRL support needs. Results indicate 4 groups with different SRL support needs. Students in the self-regulated learning group are capable of learning without external regulation. In the teacher regulation group students need initial teacher regulation but rely on SRL thereafter. Students in the system regulation group require teacher and system regulation to learn. Finally, the advanced system support group is in need of support beyond the current level of system regulation. Based on these insights, the application of personalized dashboards and hybrid human-system regulation is further specified.