Miracle-dz/UniFAR-FTUs huggingface dataset:
Contextual Hybrid Session-Based News Recommendation With Recurrent Neural Networks

Recommender systems help users deal with information overload by providing tailored item suggestions to them. The recommendation of news is often considered to be challenging, since the relevance of an article for a user can depend on a variety of factors, including the user’s short-term reading interests, the reader’s context, or the recency or popularity of an article. Previous work has shown that the use of Recurrent Neural Networks is promising for the next-in-session prediction task, but has certain limitations when only recorded item click sequences are used as input. In this work, we present a contextual hybrid, deep learning based approach for session-based news recommendation that is able to leverage a variety of information types. We evaluated our approach on two public datasets, using a temporal evaluation protocol that simulates the dynamics of a news portal in a realistic way. Our results confirm the benefits of considering additional types of information, including article popularity and recency, in the proposed way, resulting in significantly higher recommendation accuracy and catalog coverage than other session-based algorithms. Additional experiments show that the proposed parameterizable loss function used in our method also allows us to balance two usually conflicting quality factors, accuracy and novelty.
Supplemental Figure Legends

Supplemental Fig. 2: Quantitative PCR analysis of proliferating and differentiated maGSC-derived NSCs. (A-D) Real-time PCR demonstrated the expression of neural precursor/radial glial markers nestin, BLBP, GLAST and Pax6 in proliferating maGSCderived NSCs and down-regulation of these markers in differentiated cells. (E-J) In differentiated cultures of maGSC-derived NSCs an increase of oligodendroglial (CNP), astrocytic (GFAP) and neuronal (ßIII-tubulin, VGlut1, Gad67, TH) markers could be detected, indicating tripotential differentiation.
Effects of inflammatory cytokines on the permeability of human lung microvascular endothelial cell monolayers and differential eosinophil transmigration.

BACKGROUND Rhinovirus (RV) infections can result in asthma exacerbations in both adults and children. Respiratory epithelium, the primary site of RV replication, responds to the viral infection by generating a variety of cytokines and chemokines capable of promoting airway inflammation and hence might increase asthma severity. Some of these mediators might also affect the permeability of underlying vascular endothelium. OBJECTIVE We hypothesized that RV infections can promote airway inflammation and thus asthma by enhancing local vascular permeability. METHODS Confluent human lung microvascular endothelial cell (HMVEC-L) monolayers were used as an in vitro model of vascular endothelium to determine whether cytokines associated with RV-induced infections are capable of modulating endothelial cell permeability as measured by means of transendothelial electrical resistance. Recombinant cytokines and chemokines were added to confluent HMVEC-L monolayers cultured on Transwell filters, and permeability was measured as decreased electrical resistance over time. Eosinophil transendothelial migration was assessed under the same experimental conditions. RESULTS TNF- alpha, IL-1 beta, and IFN- gamma significantly increased HMVEC-L permeability. In contrast, GM-CSF, G-CSF, IL-8, IL-6, and RANTES had no effect. Although incubation of HMVEC-L monolayers with either TNF-alpha or IL-1beta promoted eosinophil migration, IFN-gamma had no effect, indicating that enhanced permeability alone was not sufficient for eosinophil infiltration. CONCLUSION Select cytokines, generated in response to RV infection, can increase vascular permeability and might provide a mechanism by which RV infection can lead to edema, cellular infiltration, and inflammation and thus compromised airflow.
RERERE: Remote Embodied Referring Expressions in Real indoor Environments

One of the long-term challenges of robotics is to enable humans to communicate with robots about the world. It is essential if they are to collaborate. Humans are visual animals, and we communicate primarily through language, so human-robot communication is inevitably at least partly a vision-and-language problem. This has motivated both Referring Expression datasets, and Vision and Language Navigation datasets. These partition the problem into that of identifying an object of interest, or navigating to another location. Many of the most appealing uses of robots, however, require communication about remote objects and thus do not reflect the dichotomy in the datasets. We thus propose the first Remote Embodied Referring Expression dataset of natural language references to remote objects in real images. Success requires navigating through a previously unseen environment to select an object identified through general natural language. This represents a complex challenge, but one that closely reflects one of the core visual problems in robotics. A Navigator-Pointer model which provides a strong baseline on the task is also proposed.
Prevalence of Antibiotic and Heavy Metal Resistance Determinants and Virulence-Related Genetic Elements in Plasmids of Staphylococcus aureus

The use of antibiotics on a mass scale, particularly in farming, and their release into the environment has led to a rapid emergence of resistant bacteria. Once emerged, resistance determinants are spread by horizontal gene transfer among strains of the same as well as disparate bacterial species. Their accumulation in free-living as well as livestock and community-associated strains results in the widespread multiple-drug resistance among clinically relevant species posing an increasingly pressing problem in healthcare. One of these clinically relevant species is Staphylococcus aureus, a common cause of hospital and community outbreaks. Among the rich diversity of mobile genetic elements regularly occurring in S. aureus such as phages, pathogenicity islands, and staphylococcal cassette chromosomes, plasmids are the major mean for dissemination of resistance determinants and virulence factors. Unfortunately, a vast number of whole-genome sequencing projects does not aim for complete sequence determination, which results in a disproportionately low number of known complete plasmid sequences. To address this problem we determined complete plasmid sequences derived from 18 poultry S. aureus strains and analyzed the prevalence of antibiotic and heavy metal resistance determinants, genes of virulence factors, as well as genetic elements relevant for their maintenance. Some of the plasmids have been reported before and are being found in clinical isolates of strains typical for humans or human ones of livestock origin. This shows that livestock-associated staphylococci are a significant reservoir of resistance determinants and virulence factors. Nevertheless, nearly half of the plasmids were unknown to date. In this group we found a potentially mobilizable plasmid pPA3 being a unique example of accumulation of resistance determinants and virulence factors likely stabilized by a presence of a toxin–antitoxin system.
Divide or Commit – Revisiting the Role of Cell Cycle Regulators in Adult Hippocampal Neurogenesis

The adult dentate gyrus continuously generates new neurons that endow the brain with increased plasticity, helping to cope with changing environmental and cognitive demands. The process leading to the birth of new neurons spans several precursor stages and is the result of a coordinated series of fate decisions, which are tightly controlled by extrinsic signals. Many of these signals act through modulation of cell cycle (CC) components, not only to drive proliferation, but also for linage commitment and differentiation. In this review, we provide a comprehensive overview on key CC components and regulators, with emphasis on G1 phase, and analyze their specific functions in precursor cells of the adult hippocampus. We explore their role for balancing quiescence versus self-renewal, which is essential to maintain a lifelong pool of neural stem cells while producing new neurons “on demand. ” Finally, we discuss available evidence and controversies on the impact of CC/G1 length on proliferation versus differentiation decisions.
Synergetic Functional Nanocomposites Enhance Immunotherapy in Solid Tumors by Remodeling the Immunoenvironment

Checkpoint blockade immunotherapy has demonstrated significant clinical success in various malignant tumors. However, the therapeutic response is limited due to the immunosuppressive tumor microenvironment (ITM). In this study, a functional nanomaterial, layered double hydroxides (LDHs), carrying specific functional miR155 is developed to modulate ITM by synergistically repolarizing tumor associated macrophages (TAMs) to M1 subtype. LDH nanoparticles loaded with miR155 (LDH@155) exhibit superior ability in cellular uptake by murine macrophages, miR escape into the cytoplasm and TAMs specific delivery when introtumoral administration. Meanwhile, upon exposure to LDH@155, TAMs are significantly skewed to M1 subtype, which markedly inhibits myeloid‐derived suppressor cells (MDSCs) formation and stimulates T‐lymphocytes to secrete more interferon‐γ (IFN‐γ) cytokines in vitro. Introtumoral administration of LDH@155 reduces the percentage of TAMs and MDSCs in the tumor and elevates CD4+ and CD8+ T cell infiltration and activation, which can promote therapeutic efficiency of α‐PD‐1 antibody immunotherapy. Furthermore, it is found that LDH@155 significantly decreases the expression level of phosphorylated STAT3 and ERK1/2 and activates NF‐κB expression in TAMs, indicating that the STAT3, ERK1/2, and NF‐κB signaling pathways may involve in LDH@155‐induced macrophage polarization. Overall, the results suggest that LDH@155 nanoparticles may, in the future, function as a promising agent for cancer combinational immunotherapy.
Reducing the Hausdorff Distance in Medical Image Segmentation With Convolutional Neural Networks

The Hausdorff Distance (HD) is widely used in evaluating medical image segmentation methods. However, the existing segmentation methods do not attempt to reduce HD directly. In this paper, we present novel loss functions for training convolutional neural network (CNN)-based segmentation methods with the goal of reducing HD directly. We propose three methods to estimate HD from the segmentation probability map produced by a CNN. One method makes use of the distance transform of the segmentation boundary. Another method is based on applying morphological erosion on the difference between the true and estimated segmentation maps. The third method works by applying circular/spherical convolution kernels of different radii on the segmentation probability maps. Based on these three methods for estimating HD, we suggest three loss functions that can be used for training to reduce HD. We use these loss functions to train CNNs for segmentation of the prostate, liver, and pancreas in ultrasound, magnetic resonance, and computed tomography images and compare the results with commonly-used loss functions. Our results show that the proposed loss functions can lead to approximately 18–45% reduction in HD without degrading other segmentation performance criteria such as the Dice similarity coefficient. The proposed loss functions can be used for training medical image segmentation methods in order to reduce the large segmentation errors.
Stroke Dysbiosis Index (SDI) in Gut Microbiome Are Associated With Brain Injury and Prognosis of Stroke

Background: Significant dysbiosis occurs in the gut microbiome of stroke patients. Condensing these broad, complex changes into one index would greatly facilitate the clinical usage of gut microbiome data. Here, we formulated a gut microbiota index in patients with acute ischemic stroke based on their gut microbiota dysbiosis patterns and tested whether the index was correlated with brain injury and early outcome. Methods: A total of 104 patients with acute ischemic stroke and 90 healthy individuals were recruited, and their gut microbiotas were compared and to model a Stroke Dysbiosis Index (SDI), which representing stroke-associated dysbiosis patterns overall. Another 83 patients and 70 controls were recruited for validation. The association of SDI with stroke severity (National Institutes of Health Stroke Scale [NIHSS] score) and outcome (modified Rankin scale [mRS] score: favorable, 0–2; unfavorable, >2) at discharge was also assessed. A middle cerebral artery occlusion (MCAO) model was used in human flora-associated (HFA) animals to explore the causal relationship between gut dysbiosis and stroke outcome. Results: Eighteen genera were significantly different between stroke patients and healthy individuals. The SDI formula was devised based on these microbiome differences; SDI was significantly higher in stroke patients than in healthy controls. SDI alone discriminated stroke patients from controls with AUCs of 74.9% in the training cohort and 84.3% in the validation cohort. SDI was significantly and positively correlated with NIHSS score on admission and mRS score at discharge. Logistic regression analysis showed that SDI was an independent predictor of severe stroke (NIHSS ≥8) and early unfavorable outcome (mRS >2). Mice receiving fecal transplants from high-SDI patients developed severe brain injury with elevated IL-17+ γδ T cells in gut compared to mice receiving transplants from low-SDI patients (all P < 0.05). Conclusions: We developed an index to measure gut microbiota dysbiosis in stroke patients; this index was significantly correlated with patients' outcome and was causally related to outcome in a mouse model of stroke. Our model facilitates the potential clinical application of gut microbiota data in stroke and adds quantitative evidence linking the gut microbiota to stroke.
The “Writing Spiral”: A Practical Tool for Teaching Undergraduates to Write Publication-Quality Manuscripts

One of the perceived barriers to publishing with undergraduates (especially with undergraduates as first author; see Giuliano, 2019) is the concern that students lack the requisite writing skills to make a significant contribution. For example, several authors in a recent special issue devoted to publishing with undergraduates (see “Engaging Undergraduates in Publishable Research: Best Practices,” Frontiers in Psychology) discuss this challenge (e.g., McKelvie and Standing, 2018; Detweiler-Bedell and Detweiler-Bedell, 2019; Reavis and Thomas, 2019; Scisco et al., 2019). Unfortunately, despite the numerous individual articles describing tips for teaching writing in psychology (in journals such as Teaching of Psychology), as well as step-by-step books that teach students to improve their writing, there is no widely-accepted comprehensive resource to guide faculty in teaching psychological writing to students (see Ishak and Salter, 2017, for a review). The purpose of this paper is to address this gap, with a focus on teaching undergraduates to write publication-quality manuscripts. Although there are many important factors in teaching writing, one tool that I have developed—which students call “the writing spiral”—has been successfully used to guide numerous undergraduates through the publication process1. After describing the purpose and benefits of the writing spiral, I provide a detailed description of its contents in the hopes that interested readers might successfully incorporate some of this material into their own writing instruction2.
Reduced Interhemispheric White Matter Asymmetries in Medial Temporal Lobe Epilepsy With Hippocampal Sclerosis

Mesial temporal lobe epilepsy (MTLE), one of the most common types of refractory focal epilepsy, has shown white matter abnormalities both within and beyond the temporal lobe. In particular, the white matter abnormalities in the ipsilateral hemisphere are more obvious than those in the contralateral hemisphere in MTLE, that is, the abnormalities present asymmetrical characteristics. However, very few studies have characterized the white matter microstructure asymmetry in MTLE patients specifically. Thus, we performed diffusion tensor imaging (DTI) to investigate the white matter microstructure asymmetries of patients with MTLE with unilateral hippocampal sclerosis (MTLE-HS). We enrolled 25 MTLE-HS (left MTLE-HS group, n = 13; right MTLE-HS group, n = 12) and 26 healthy controls (HC). DTI data were analyzed by tract-based spatial statistics (TBSS) to test the hemispheric differences across the entire white matter skeleton. We also conducted a two-sample paired t-test for 21 paired region of interests (ROIs) parceled on the basis of the ICBM-DTI-81 white-matter label atlas of bilateral hemispheres to test the hemispheric differences. An asymmetry index (AI) was calculated to further quantify the differences between the left and right paired-ROIs. It was found that the asymmetries of white matter skeletons were significantly lower in the MTLE-HS groups than in the HC group. In particular, the asymmetry traits were moderately reduced in the RMTLE-HS group and obviously reduced in the LMTLE-HS group. In addition, AI was significantly different in the RMTLE-HS group from the LMTLE-HS or HC group in the limbic system and superior longitudinal fasciculus (SLF). The current study found that the interhemispheric white matter asymmetries were significantly reduced in the MTLE-HS groups than in the HC group. The interhemispheric white matter asymmetries are distinctly affected in left and right MTLE-HS groups. The differences in AI among RMTLE-HS, LMTLE-HS, and HC involved the limbic system and SLF, which may have some pragmatic implications for the diagnosis of MTLE and differentiating LMTLE-HS from RMTLE-HS.
Simple Particle Model for Low-Density Granular Flow Interacting with Ambient Fluid

To understand the time evolutions of frontal speed and shape in a low-density granular flow, we propose a simple particle model. This model solves the equation of motion for each particle and simulates the time evolution of low-density granular flow. Spherical particles constituting a low-density granular flow slide on a slope at a steeper angle than the angle of repose. The particle motion is determined based on three forces: gravity as the driving force, repulsive force due to particle collision, and drag force due to the particle interaction through the ambient fluid. Two-dimensional numerical simulations of this model are conducted on the slope: the x–y plane parallel to the slope and the x–z plane perpendicular to the slope. In the x–y plane, particles aggregate at the moving front of the granular flow, and subsequently, flow instability occurs as a wavy pattern. This flow pattern is caused by the interparticle interaction arising from the drag force. Additionally, a vortex convection of particles is formed inside the aggregations. Simultaneously, particle aggregation is also found at the moving front of the granular flow in the x–z plane. The aggregation resembles a head–tail structure, where the frontal angle against the slope approaches 60 ∘ from a larger angle as time progresses. Comparing the numerical result by varying the particle size reveals that the qualitative dynamics of the granular flow are independent of particle size. Although the model is not realistic, our study presents a new particle-based approach that elucidates the dynamics of low-density granular flow.
A Hardware–Software Blueprint for Flexible Deep Learning Specialization

This article describes the Versatile Tensor Accelerator (VTA), a programmable DL architecture designed to be extensible in the face of evolving workloads. VTA achieves “flexible specialization” via a parameterizable architecture, two-level Instruction Set Architecture (ISA), and a Just in Time (JIT) compiler.
DNMT Inhibitors Increase Methylation in the Cancer Genome

DNA methyltransferase inhibitors (DNMTi) decitabine and azacytidine are approved therapies for myelodysplastic syndrome and acute myeloid leukemia, and their combinations with other anticancer agents are being tested as therapeutic options for multiple solid cancers such as colon, ovarian, and lung cancer. However, the current therapeutic challenges of DNMTis include development of resistance, severe side effects and no or partial treatment responses, as observed in more than half of the patients. Therefore, there is a critical need to better understand the mechanisms of action of these drugs. In order to discover molecular targets of DNMTi therapy, we identified 638 novel CpGs with an increased methylation in response to decitabine treatment in HCT116 cell lines and validated the findings in multiple cancer types (e.g., bladder, ovarian, breast, and lymphoma) cell lines, bone marrow mononuclear cells from primary leukemia patients, as well as peripheral blood mononuclear cells and ascites from platinum resistance epithelial ovarian cancer patients. Azacytidine treatment also increased methylation of these CpGs in colon, ovarian, breast, and lymphoma cancer cell lines. Methylation at 166 identified CpGs strongly correlated (|r|≥ 0.80) with corresponding gene expression in HCT116 cell line. Differences in methylation at some of the identified CpGs and expression changes of the corresponding genes was observed in TCGA colon cancer tissue as compared to adjacent healthy tissue. Our analysis revealed that hypermethylated CpGs are involved in cancer cell proliferation and apoptosis by P53 and olfactory receptor pathways, hence influencing DNMTi responses. In conclusion, we showed hypermethylation of CpGs as a novel mechanism of action for DNMTi agents and identified 638 hypermethylated molecular targets (CpGs) common to decitabine and azacytidine therapy. These novel results suggest that hypermethylation of CpGs should be considered when predicting the DNMTi responses and side effects in cancer patients.
Relationship Between Neutralizing Antibodies Against Adeno-Associated Virus in the Vitreous and Serum: Effects on Retinal Gene Therapy

Purpose We determine the prevalence of neutralizing antibodies (NAbs) to adeno-associated virus (AAV) in the vitreous humor and serum of patients with vitreoretinal diseases and investigate the relationship between NAb titers in the vitreous humor and serum. Methods We analyzed NAbs to AAV serotypes 2, 5, 8, and 9 via in vitro neutralization in the vitreous humor and serum from 32 patients requiring vitrectomy for vitreoretinal diseases. The blood–retinal barrier (BRB) was evaluated for integrity based on preoperative examinations, with vitreous hemorrhage (VH) on funduscopy or dye leakage on fluorescein angiography observed indicating disruption. Results NAb levels were much lower in the vitreous humor than in the serum regardless of serotype. Patients with VH had higher levels of NAbs in the vitreous humor than those without VH. The NAb ratio (ratio between NAb titers in the serum and vitreous humor) was much lower in patients with epiretinal membrane with than in those without leakage. A significantly lower NAb ratio was noticed in patients with than in those without BRB disruptions. Conclusions The NAb ratio between levels in serum and vitreous humor varies according to the condition of the BRB. Therefore, in addition to measuring the serum NAb level, physicians should examine BRB integrity when planning retinal gene therapy. Translational Relevance This study provides substantial basis for retinal gene therapy using AAVs and how maintenance of BRB integrity in target diseases should be considered.