Miracle-dz/UniFAR-FTUs huggingface dataset:
Circular RNA Expression Profiling Identifies Prostate Cancer- Specific circRNAs in Prostate Cancer

Background/Aims: Prostate cancer (PCa) is one of the main cancers that damage males’ health severely with high morbidity and mortality, but there is still no ideal molecular marker for the diagnosis and prognosis of prostate cancer. Methods: To determine whether the differentially expressed circRNAs in prostate cancer can serve as novel biomarkers for prostate cancer diagnosis, we screened differentially expressed circRNAs using SBC-ceRNA array in 4 pairs of prostate tumor and paracancerous tissues. A circRNA-miRNA-mRNA regulatory network for the differential circRNAs and their host genes was constructed by Cytoscape3.5. 1 software. Quantitative real-time polymerase chain reaction analysis (qRT-PCR) was performed to confirm the microarray data. Results: We found 1021 differentially expressed circRNAs in PCa tumor using SBC-ceRNA array and confirmed the expression of circ_0057558, circ_0062019 and SLC19A1 in PCa cell lines and tumor tissues through qRT-PCR analysis. We demonstrated that combination of PSA level and two differentially expressed circRNAs showed significantly increased AUC, sensitivity and specificity (0.938, 84.5% and 90.9%, respectively) than PSA alone (AUC of serum PSA was 0.854). Moreover, circ_0057558 was correlated positively with total cholesterol. The functional network of circRNA-miRNA-mRNA analysis showed that circ_0057558 and circ_0034467 regulated miR-6884, and circ_0062019 and circ_0060325 regulated miR-5008. Conclusion: Our results demonstrated that differentially expressed circRNAs (circ_0062019 and circ_0057558) and host gene SLC19A1 of circ_0062019 could be used as potential novel biomarkers for prostate cancer.
Effects of imidazoline I2 receptor agonists on reserpine-induced hyperalgesia and depressive-like behavior in rats

Pharmacotherapies for fibromyalgia treatment are lacking. This study examined the antinociceptive and antidepressant-like effects of imidazoline I2 receptor (I2R) agonists in a reserpine-induced model of fibromyalgia in rats. Rats were treated for 3 days with vehicle or reserpine. The von Frey filament test was used to assess the antinociceptive effects of I2 receptor agonists, and the forced swim test was used to assess the antidepressant-like effects of these drugs. 2-BFI (3.2–10 mg/kg, intraperitoneally), phenyzoline (17.8–56 mg/kg, intraperitoneally), and CR4056 (3.2–10 mg/kg, intraperitoneally) all dose-dependently produced significant antinociceptive effects, which were attenuated by the I2R antagonist idazoxan. Only CR4056 significantly reduced the immobility time in the forced swim test in both vehicle-treated and reserpine-treated rats. These data suggest that I2R agonists may be useful to treat fibromyalgia-related pain and comorbid depression.
Individual barriers of tacit knowledge sharing within information system development projects

Information Systems Development Projects (ISDPs) are knowledge intensive in nature. They rely on knowledge in order for them to be conducted successfully. The type of knowledge that is used mostly within ISDPs is tacit knowledge which is within the members of ISDP team. It is a challenge to access this type of knowledge in order to be used for the benefit of the ISDP and ISDP team. This had led to a higher failure rate of ISDPs. Researchers conducted a grounded theory study in order to understand issues limits the individual members of ISDPs from sharing their tacit knowledge. A total of 17 semi-structured interviews were conducted. The qualitative data was analyzed using grounded theory data analysis. A total of nine barriers were identified which were based on the barriers that limits the individual members of ISDP. The barriers included time, poor communication and job security to name few.
QA2Explanation: Generating and Evaluating Explanations for Question Answering Systems over Knowledge Graph

In the era of Big Knowledge Graphs, Question Answering (QA) systems have reached a milestone in their performance and feasibility. However, their applicability, particularly in specific domains such as the biomedical domain, has not gained wide acceptance due to their “black box” nature, which hinders transparency, fairness, and accountability of QA systems. Therefore, users are unable to understand how and why particular questions have been answered, whereas some others fail. To address this challenge, in this paper, we develop an automatic approach for generating explanations during various stages of a pipeline-based QA system. Our approach is a supervised and automatic approach which considers three classes (i.e., success, no answer, and wrong answer) for annotating the output of involved QA components. Upon our prediction, a template explanation is chosen and integrated into the output of the corresponding component. To measure the effectiveness of the approach, we conducted a user survey as to how non-expert users perceive our generated explanations. The results of our study show a significant increase in the four dimensions of the human factor from the Human-computer interaction community.
VeriFlow: verifying network-wide invariants in real time

Networks are complex and prone to bugs. Existing tools that check configuration files and data-plane state operate offline at timescales of seconds to hours, and cannot detect or prevent bugs as they arise. Is it possible to check network-wide invariants in real time, as the network state evolves? The key challenge here is to achieve extremely low latency during the checks so that network performance is not affected. In this paper, we present a preliminary design, VeriFlow, which suggests that this goal is achievable. VeriFlow is a layer between a software-defined networking controller and network devices that checks for network-wide invariant violations dynamically as each forwarding rule is inserted. Based on an implementation using a Mininet OpenFlow network and Route Views trace data, we find that VeriFlow can perform rigorous checking within hundreds of microseconds per rule insertion.
Alexa, Are You Listening?

Smart speakers with voice assistants, like Amazon Echo and Google Home, provide benefits and convenience but also raise privacy concerns due to their continuously listening microphones. We studied people's reasons for and against adopting smart speakers, their privacy perceptions and concerns, and their privacy-seeking behaviors around smart speakers. We conducted a diary study and interviews with seventeen smart speaker users and interviews with seventeen non-users. We found that many non-users did not see the utility of smart speakers or did not trust speaker companies. In contrast, users express few privacy concerns, but their rationalizations indicate an incomplete understanding of privacy risks, a complicated trust relationship with speaker companies, and a reliance on the socio-technical context in which smart speakers reside. Users trade privacy for convenience with different levels of deliberation and privacy resignation. Privacy tensions arise between primary, secondary, and incidental users of smart speakers. Finally, current smart speaker privacy controls are rarely used, as they are not well-aligned with users' needs. Our findings can inform future smart speaker designs; in particular we recommend better integrating privacy controls into smart speaker interaction.
Tracing Cross Border Web Tracking

A tracking flow is a flow between an end user and a Web tracking service. We develop an extensive measurement methodology for quantifying at scale the amount of tracking flows that cross data protection borders, be it national or international, such as the EU28 border within which the General Data Protection Regulation (GDPR) applies. Our methodology uses a browser extension to fully render advertising and tracking code, various lists and heuristics to extract well known trackers, passive DNS replication to get all the IP ranges of trackers, and state-of-the art geolocation. We employ our methodology on a dataset from 350 real users of the browser extension over a period of more than four months, and then generalize our results by analyzing billions of web tracking flows from more than 60 million broadband and mobile users from 4 large European ISPs. We show that the majority of tracking flows cross national borders in Europe but, unlike popular belief, are pretty well confined within the larger GDPR jurisdiction. Simple DNS redirection and PoP mirroring can increase national confinement while sealing almost all tracking flows within Europe. Last, we show that cross boarder tracking is prevalent even in sensitive and hence protected data categories and groups including health, sexual orientation, minors, and others.
Does urbanization influence the diet of a large snake?

Abstract Urbanization facilitates synanthropic species such as rodents, which benefit the diets of many predators in cities. We investigated how urbanization affects the feeding ecology of dugites Pseudonaja affinis, a common elapid snake in south-west Western Australia. We predicted that urban snakes: 1) more frequently contain prey and eat larger meals, 2) eat proportionally more non-native prey, 3) eat a lower diversity of prey species, and 4) are relatively heavier, than non-urban dugites. We analyzed the diet of 453 specimens obtained from the Western Australian Museum and opportunistic road-kill collections. Correcting for size, sex, season, and temporal biases, we tested whether location influenced diet for our 4 predictions. Body size was a strong predictor of diet (larger snakes had larger prey present, a greater number of prey items, and a greater diversity of prey). We identified potential collection biases: urban dugites were relatively smaller (snout-vent length) than non-urban specimens, and females were relatively lighter than males. Accounting for these effects, urban snakes were less likely to have prey present in their stomachs and were relatively lighter than non-urban snakes. Other urban-adapted carnivores appear to benefit from urbanization through increased food supplementation, but we found the opposite of this: urban dugites were less likely to contain a meal, and their meals were smaller, indicating they did not make greater use of synanthropic species than was evident for non-urban snakes. In contrast to other carnivores, snakes do not appear to fit a consistent directional pattern for size differences between urban and non-urban populations.
Rutin Attenuates Vancomycin-Induced Nephrotoxicity by Ameliorating Oxidative Stress, Apoptosis, and Inflammation in Rats

Nephrotoxicity is the major limiting factor for the clinical use of vancomycin (VCM) for treatment of serious infections caused by multiresistant Gram-positive bacteria. This study investigated the renal protective activity of rutin in a rat model of VCM-induced kidney injury in male Wistar rats. ABSTRACT Nephrotoxicity is the major limiting factor for the clinical use of vancomycin (VCM) for treatment of serious infections caused by multiresistant Gram-positive bacteria. This study investigated the renal protective activity of rutin in a rat model of VCM-induced kidney injury in male Wistar rats. VCM administered intraperitoneally at 200 mg/kg twice daily for 7 successive days resulted in significant elevation of blood urea nitrogen and creatinine, as well as urinary N-acetyl-β-D-glucosaminidase. Coadministration of VCM with oral rutin at 150 mg/kg significantly reduced these markers of kidney damage. Rutin also significantly attenuated VCM-induced oxidative stress, inflammatory cell infiltration, apoptosis, and decreased interleukin-1β and tumor necrosis factor alpha levels (all P < 0.05 or 0.01) in kidneys. Renal recovery from VCM injury was achieved by rutin through increases in Nrf2 and HO-1 and a decrease in NF-κB expression. Our results demonstrated a protective effect of rutin on VCM-induced kidney injury through suppression of oxidative stress, apoptosis, and downregulation of the inflammatory response. This study highlights a role for oral rutin as an effective intervention to ameliorate nephrotoxicity in patients undergoing VCM therapy.
Adapting Neural Single-Document Summarization Model for Abstractive Multi-Document Summarization: A Pilot Study

Till now, neural abstractive summarization methods have achieved great success for single document summarization (SDS). However, due to the lack of large scale multi-document summaries, such methods can be hardly applied to multi-document summarization (MDS). In this paper, we investigate neural abstractive methods for MDS by adapting a state-of-the-art neural abstractive summarization model for SDS. We propose an approach to extend the neural abstractive model trained on large scale SDS data to the MDS task. Our approach only makes use of a small number of multi-document summaries for fine tuning. Experimental results on two benchmark DUC datasets demonstrate that our approach can outperform a variety of baseline neural models.
Ecology and evolution along environmental gradients

Ecology and evolution along environmental gradients Rüdiger RIESCH*, Martin PLATH, and David BIERBACH School of Biological Sciences, Centre for Ecology, Evolution and Behaviour, Royal Holloway University of London, Egham, Surrey TW20 0EX, UK, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China, and Department of Biology and Ecology of Fishes, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 310, Berlin, D-12587, Germany
The Emergence of loss of efficacy during Antidepressant Drug Treatment for Major Depressive Disorder: An Integrative Review of Evidence, Mechanisms, and Clinical Implications

The re-emergence (i.e. ‘breakthrough’) of depressive symptoms despite maintenance treatment of depression with antidepressant drugs is a complex clinical phenomenon referred to as tolerance. Herein we critically appraise evidence from both pre-clinical and clinical studies, focusing on putative mechanisms as well as clinical correlates and implications of the emergence tolerance during antidepressant treatment for major depressive disorder (MDD). It is firstly unclear to what extent this phenotype reflects a pharmacological effect of an antidepressant, is driven by non-adherence, is a marker of latent bipolarity or another comorbidity, a marker of neuroprogression of the underlying disorder or the intrusion of the impact of psychosocial variables into the clinical course. The operational definitions of tolerance and its related phenomena have also been largely inconsistent. Several protective clinical indicators have been proposed, including a rapid-cycling course and comorbid chronic anxiety, whilst poor treatment adherence, proneness to emotional blunting and subthreshold bipolarity have been identified as possible correlates of tolerance to antidepressant treatment in MDD. Putative neurobiological underpinnings include adaptations in the hypothalamic-pituitary-adrenal (HPA) axis and the serotonergic system. Due to the clinical and diagnostic challenges imposed by the emergence of tolerance to antidepressants, there is an urgent need for upcoming international guidelines to reach a consensus on operational definitions for this complex clinical phenomenon, thus enabling a more precise appreciation of the incidence and correlates of tolerance to antidepressants. Taken together, the present review underscores the need to cautiously weight benefits and risks prior to considering long-term antidepressant treatment for patients with MDD as tolerance may emerge in a subset of patients.
TEACHING/LEARNING PHYSICS: INTEGRATING RESEARCH INTO PRACTICE

In the physics teaching, frequently we use the discourse of the teacher and the solution of exercises as the main didactics resources. In most students, this does not seem to promote the construction of knowledge about the science and its nature. Following the proposal of the critical meaningful learning of Moreira, the application of the theory of conceptual fields of Vergnaud and the epistemological approaches derived from a non-standard view about science, we then asked: The intentional integration of traditional resources with the experimental resources, in one sequence of situations-problem of physics that put the student in cognitive action, will promote the conceptual learning? We have organized a sequence of didactic situations centred in problems, which refer to the situations regarding of the conceptual field that we have constructed from the physics. We incorporated to the traditional resources, three experimental resources (demonstration, simulation, experimental data) in a complementary manner and intentional. We assay this proposal in action research with a group of student-teacher in training during a course of Fundamentals of Physics, for learning concepts about kinematics; which lasted six weeks, with two classes of three hours each per week. The students worked in cognitive and practice action while the teacher mediated the learning process guided by the model learning of the physics laboratory work (MLPLaW). The student's learning outcomes in action were collected through: initial and final tests, observation of teacher researcher and working guide delivered to them. Among the most relevant results, we have found that students in the final test were able to recognize many of the situations we presented them, identify goals and make anticipations and be able to account for new or modified cognitive elements (compared to the initial test) which we assume were developed during teaching. Also, the student was willing to participate and monitor their learning process. They qualified as positive the incorporation of experimental resources in the process of their active construction of meanings, and became aware of the theory experiment-model relationship. This work confirms that the establishment of the field conceptual in terms of situations, concepts and representations is a suitable tool for the organization of teaching and assessing the progressivity of meaningful learning of concepts; as well as the integration of theory and experiment in physics teaching would promotes learning and the understanding of the nature of science.
Gabriel Graph for Dataset Structure and Large Margin Classification: A Bayesian Approach

This paper presents a geometrical approach for obtaining large margin classifiers. The method aims at exploring the geometrical properties of the dataset from the structure of a Gabriel graph, which represents pattern relations according to a given distance metric, such as the Euclidean distance. Once the graph is generated, geometric vec- tors, analogous to SVM's support vectors are obtained in order to yield the final large margin solution from a Gaussian mixture model approach. Preliminary experiments have shown that the solutions obtained with the proposed method are close to those obtained with SVMs.
Regular expression types for XML

We propose regular expression types as a foundation for statically typed XML processing languages. Regular expression types, like most schema languages for XML, introduce regular expression notations such as repetition (*), alternation (|), etc., to describe XML documents. The novelty of our type system is a semantic presentation of subtyping, as inclusion between the sets of documents denoted by two types. We give several examples illustrating the usefulness of this form of subtyping in XML processing.The decision problem for the subtype relation reduces to the inclusion problem between tree automata, which is known to be EXPTIME-complete. To avoid this high complexity in typical cases, we develop a practical algorithm that, unlike classical algorithms based on determinization of tree automata, checks the inclusion relation by a top-down traversal of the original type expressions. The main advantage of this algorithm is that it can exploit the property that type expressions being compared often share portions of their representations. Our algorithm is a variant of Aiken and Murphy's set-inclusion constraint solver, to which are added several new implementation techniques, correctness proofs, and preliminary performance measurements on some small programs in the domain of typed XML processing.
Habitat choice meets thermal specialization: Competition with specialists may drive suboptimal habitat preferences in generalists

Significance In contrast to the classically expected coupling between ecological specialization and low dispersal propensity, theory predicts that dispersal with habitat choice (i.e., individuals that choose habitats maximizing their performance) should evolve in specialists, while generalists should disperse more randomly. Here, we show in ciliate microcosms that thermal specialists indeed prefer optimal habitats, whereas surprisingly, generalists also perform habitat choice but with a preference for suboptimal habitats. To tackle the question of why generalists should prefer suboptimal habitats, we developed a metapopulation model and showed that competition between generalists and specialists may favor a preference for niche margins in generalists under environmental variability. Our results point out the importance of dispersal strategies for ecological and evolutionary dynamics. Limited dispersal is classically considered as a prerequisite for ecological specialization to evolve, such that generalists are expected to show greater dispersal propensity compared with specialists. However, when individuals choose habitats that maximize their performance instead of dispersing randomly, theory predicts dispersal with habitat choice to evolve in specialists, while generalists should disperse more randomly. We tested whether habitat choice is associated with thermal niche specialization using microcosms of the ciliate Tetrahymena thermophila, a species that performs active dispersal. We found that thermal specialists preferred optimal habitats as predicted by theory, a link that should make specialists more likely to track suitable conditions under environmental changes than expected under the random dispersal assumption. Surprisingly, generalists also performed habitat choice but with a preference for suboptimal habitats. Since this result challenges current theory, we developed a metapopulation model to understand under which circumstances such a preference for suboptimal habitats should evolve. We showed that competition between generalists and specialists may favor a preference for niche margins in generalists under environmental variability. Our results demonstrate that the behavioral dimension of dispersal—here, habitat choice—fundamentally alters our predictions of how dispersal evolve with niche specialization, making dispersal behaviors crucial for ecological forecasting facing environmental changes.