Miracle-dz/UniFAR-FTUs huggingface dataset:
A Therapeutic Approach to Nasopharyngeal Carcinomas by DNAzymes Targeting EBV LMP-1 Gene

Epstein-Barr virus (EBV)-encoded latent membrane protein 1 (LMP1) has been known to have oncogenic properties during latent infection in nasopharyngeal carcinoma (NPC). Genetic manipulation of LMP1 expression may provide a novel strategy for the treatment of NPC. DNAzymes are synthetic, single-stranded DNA catalysts that can be engineered to bind and cleave the target mRNA of a disease-causing gene. By targeting the LMP1 mRNA, we successfully obtained a phosphorothioate-modified ‘‘10–23’’ DNAzyme namely DZ1, through screening a series of DNAzymes. DZ1 could significantly down-regulate the expression of LMP1 in NPC cells, inhibit cell proliferation, metastasis, promote apoptosis and enhance radiosensitivity of NPC through interfering signal pathways which are abnormally activated by LMP1, including NF-κB, AP-1 and STAT3 signal pathways. Together, interfering LMP1 signaling pathway could be a promising strategy to target the malignant phenotypes of NPC.
Joint pose estimator and feature learning for object detection

A new learning strategy for object detection is presented. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform based on the signal of interest. Specifically, we train a detector with a standard AdaBoost procedure by using combinations of pose-indexed features and pose estimators instead of the usual image features. This allows the learning process to select and combine various estimates of the pose with features able to implicitly compensate for variations in pose. We demonstrate that a detector built in such a manner provides noticeable gains on two hand video sequences and analyze the performance of our detector as these data sets are synthetically enriched in pose while not increased in size.
The Impact of Public Infrastructure on Productivity: New Evidence for Australia

This paper presents new evidence on the impact of public infrastructure on the Australian economy. The contribution of the paper is three-fold. First, it estimates measures of multifactor productivity for each of the states and territories. Second, it employs a new data set on public infrastructure. Third, the paper applies detailed econometric investigations in an attempt to readdress the crucial econometric shortcomings of earlier studies. The analysis presented here is designed to investigate two widely-debated questions. First, whether aggregate time-series analysis is incapable of capturing infrastructure spillovers to productivity and, consequently, results in incredibly high estimates of infrastructure elasticity. Second, whether state-specific characteristics exhibit a significant role in explaining effects on productivity. To answer the first question, the study applies time-series regressions on both a national and state-by-state basis. Results from this approach confirm the implausibly large effect of infrastructure for the whole economy and four states. To examine the second issue, the paper develops a panel cointegration model which controls for state fixed effects. In sharp contrast with findings from aggregate time-series, results from the fixed effects approach are more plausible and robust to sensitivity tests. In another piece of evidence, estimation of an error-correction model reveals that a long-run identification and modelling of the relationship (i.e. a cointegration) re ects the important positive role of infrastructure on productivity. However, short-run dynamics provide no support for a positive effect which explains why earlier studies which employed differenced data found infrastructure has no discernible effect on productivity. In addition, applying a causality test suggests a long-run unidirectional causality running from public infrastructure to productivity.
Growth of Arabidopsis seedlings on high fungal doses of Piriformospora indica has little effect on plant performance, stress, and defense gene expression in spite of elevated jasmonic acid and jasmonic acid-isoleucine levels in the roots

The endophytic fungus Piriformospora indica colonizes the roots of many plant species including Arabidopsis and promotes their performance, biomass, and seed production as well as resistance against biotic and abiotic stress. Imbalances in the symbiotic interaction such as uncontrolled fungal growth result in the loss of benefits for the plants and activation of defense responses against the microbe. We exposed Arabidopsis seedlings to a dense hyphal lawn of P. indica. The seedlings continue to grow, accumulate normal amounts of chlorophyll, and the photosynthetic parameters demonstrate that they perform well. In spite of high fungal doses around the roots, the fungal material inside the roots was not significantly higher when compared with roots that live in a beneficial symbiosis with P. indica. Fifteen defense- and stress-related genes including PR2, PR3, PAL2, and ERF1 are only moderately upregulated in the roots on the fungal lawn, and the seedlings did not accumulate H2O2/radical oxygen species. However, accumulation of anthocyanin in P. indica-exposed seedlings indicates stress symptoms. Furthermore, the jasmonic acid (JA) and jasmonic acid-isoleucine (JA-Ile) levels were increased in the roots, and consequently PDF1.2 and a newly characterized gene for a 2-oxoglurate and Fe2+-dependent oxygenase were upregulated more than 7-fold on the dense fungal lawn, in a JAR1- and EIN3-dependent manner. We conclude that growth of A. thaliana seedlings on high fungal doses of P. indica has little effect on the overall performance of the plants although elevated JA and JA-Ile levels in the roots induce a mild stress or defense response.
Improvement of the Vitrification Method Suppressing the Disturbance of Meiotic Spindle and Chromosome Systems in Mature Oocytes

Vitrification method is widely used in oocyte cryopreservation for IVF but the birth rates are lower than that of the fresh oocyte. One of the known main reasons is structural instability of meiotic spindle and chromosome systems of mature oocyte. To get the best way for keeping competence of matured oocytes, we studied the best conditions for vitrification focused on equilibration times. The mature oocytes were underwent vitrification with current popular method and analyzed the survival rates, microtubule stability and DNA integrity. The survival rates of recovered oocyte are almost same between groups and are more than 93%. The structural configuration of meiotic spindle was well kept in 10 min equilibration group and the stability rate was almost same with that of control. The chromosomal breakdown was observed in all experimental groups, but the chromosomal stability was higher in 10 min equilibration group than the other groups. The 10 min equilibration group showed best condition compared with the other groups. Based on these results, the equilibration time is one of the key factors in successful keeping for competence of mature oocyte. Although, more fine analysis about the effects of physical stress on oocyte during vitrification is needed to define the optimal condition, it is suggested that the optimal equilibration time to get competent oocyte in mouse is 10 min. Information acquired this study may provide insight into intracellular structural events occurring in human oocytes after vitrification and application for cryopreservation of human oocyte.
Distributed Recovery of Actor Failures in Wireless Sensor and Actor Networks

Wireless sensor and actor networks (WSANs) additionally employ actor nodes within the wireless sensor network (WSN) which can process the sensed data and perform certain actions based on this collected data. In most applications, inter-actor coordination is required to provide the best response. This suggests that the employed actors should form and maintain a connected inter-actor network at all times. However, WSANs often operate unattended in harsh environments where actors can easily fail or get damaged. Such failures can partition the inter-actor network and thus eventually make the network useless. In order to handle such failures, we present a connected dominating set (CDS) based partition detection and recovery algorithm. The idea is to identify whether the failure of a node causes partitioning or not in advance. If a partitioning is to occur, the algorithm designates one of the neighboring nodes to initiate the connectivity restoration process. This process involves repositioning of a set of actors in order to restore the connectivity. The overall goal in this restoration process is to localize the scope of the recovery and minimize the movement overhead imposed on the involved actors. The effectiveness of the approach is validated through simulation experiments.
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Pituitary adenylate cyclase-activating polypeptide (PACAP) inhibits the slow afterhyperpolarizing current sIAHP in CA1 pyramidal neurons by activating multiple signaling pathways

The slow afterhyperpolarizing current (sIAHP) is a calcium‐dependent potassium current that underlies the late phase of spike frequency adaptation in hippocampal and neocortical neurons. sIAHP is a well‐known target of modulation by several neurotransmitters acting via the cyclic AMP (cAMP) and protein kinase A (PKA)‐dependent pathway. The neuropeptide pituitary adenylate cyclase activating peptide (PACAP) and its receptors are present in the hippocampal formation. In this study we have investigated the effect of PACAP on the sIAHP and the signal transduction pathway used to modulate intrinsic excitability of hippocampal pyramidal neurons. We show that PACAP inhibits the sIAHP, resulting in a decrease of spike frequency adaptation, in rat CA1 pyramidal cells. The suppression of sIAHP by PACAP is mediated by PAC1 and VPAC1 receptors. Inhibition of PKA reduced the effect of PACAP on sIAHP, suggesting that PACAP exerts part of its inhibitory effect on sIAHP by increasing cAMP and activating PKA. The suppression of sIAHP by PACAP was also strongly hindered by the inhibition of p38 MAP kinase (p38 MAPK). Concomitant inhibition of PKA and p38 MAPK indicates that these two kinases act in a sequential manner in the same pathway leading to the suppression of sIAHP. Conversely, protein kinase C is not part of the signal transduction pathway used by PACAP to inhibit sIAHP in CA1 neurons. Our results show that PACAP enhances the excitability of CA1 pyramidal neurons by inhibiting the sIAHP through the activation of multiple signaling pathways, most prominently cAMP/PKA and p38 MAPK. Our findings disclose a novel modulatory action of p38 MAPK on intrinsic excitability and the sIAHP, underscoring the role of this current as a neuromodulatory hub regulated by multiple protein kinases in cortical neurons. © 2013 The Authors. Hippocampus Published by Wiley Periodicals, Inc.
Screening Autoimmune Anti-neuronal Antibodies in Pediatric Patients with Suspected Autoimmune Encephalitis

Background and Purpose: The aim of this study was to identify and describe the pediatric autoimmune encephalitis cases positive for anti-neuronal antibody tests. Methods: Screening of six anti-neuronal antibodies in 23 children with suspected autoimmune encephalitis was performed by cell-based indirect immunofluorescence test with patients’ serum or cerebrospinal fluid. Results: Among the 23 cases enrolled here, eight patients (35%) were positive for the anti-N-methyl-d-aspartate (NMDA) receptor antibody and one patient (4%) was positive for the anti-contactin-associated protein-like 2 (CASPR2) antibody. In the anti-NMDA receptor antibody-positive group, seizure and movement disorders were the most prominent features and were present in all patients. A tumor was present in only one patient. Three patients with infant- and toddler-onset disease did not exhibit a classic multistage illness. In addition to seizure and dyskinesia, aphasia or mutism without severe consciousness impairment was present in all three patients. These atypical clinical presentations may suggest different pathomechanism of anti-NMDA receptor encephalitis among these age groups. The patient who was positive for the anti-CASPR2 antibody was an 8-year-old girl who presented with fever, encephalopathy, and seizure. Neuromyotonia or other dyskinesia was not present. Conclusions: Eight anti-NMDA receptor antibody positive patients and one CASPR2 positive patient were identified from the screening of six anti-neuronal antibodies in pediatric patients suspected with autoimmune encephalitis. Developmental regression specifically for language skills was suggested as one of the atypical clinical features in infants and toddler onset anti-NMDA receptor antibody positive patients.
A norm-concentration argument for non-convex regularisation

However, independent results in several areas indicate added value to non-convex norm regularisation, despite the existence of local optima. Work in statistics (Fan & Li, 2001) and signal reconstruction (Wipf & Rao, 2005) have established the oracle properties of non-convex regularisers. Good empirical results were also reported in signal processing (Chartland, 2007) and SVM classification (Weston et.al, 2003). Furthermore, using a family of non-convex norms that we shall refer to as fractional-norms in the rest of the paper, turned out to consistently outperform the L1 regulariser in real high-dimensional genomic data classification (Liu et.al, 2007), both in terms of error rates and interpretability. Related ideas, termed as ’zeronorm’ regularisation (Weston et.al, 2003) were also found useful in many other applications, though their success appeared to be data dependent. It is therefore of interest to gain a better understanding of the potential advantages of non-convex norm regularisers, which is our purpose.
Coordinate‐based activation likelihood estimation meta‐analysis of neuroimaging data: A random‐effects approach based on empirical estimates of spatial uncertainty

A widely used technique for coordinate‐based meta‐analyses of neuroimaging data is activation likelihood estimation (ALE). ALE assesses the overlap between foci based on modeling them as probability distributions centered at the respective coordinates. In this Human Brain Project/Neuroinformatics research, the authors present a revised ALE algorithm addressing drawbacks associated with former implementations. The first change pertains to the size of the probability distributions, which had to be specified by the used. To provide a more principled solution, the authors analyzed fMRI data of 21 subjects, each normalized into MNI space using nine different approaches. This analysis provided quantitative estimates of between‐subject and between‐template variability for 16 functionally defined regions, which were then used to explicitly model the spatial uncertainty associated with each reported coordinate. Secondly, instead of testing for an above‐chance clustering between foci, the revised algorithm assesses above‐chance clustering between experiments. The spatial relationship between foci in a given experiment is now assumed to be fixed and ALE results are assessed against a null‐distribution of random spatial association between experiments. Critically, this modification entails a change from fixed‐ to random‐effects inference in ALE analysis allowing generalization of the results to the entire population of studies analyzed. By comparative analysis of real and simulated data, the authors showed that the revised ALE‐algorithm overcomes conceptual problems of former meta‐analyses and increases the specificity of the ensuing results without loosing the sensitivity of the original approach. It may thus provide a methodologically improved tool for coordinate‐based meta‐analyses on functional imaging data. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.
Practical algorithms for subgroup detection in covert networks

In this paper, we present algorithms for subgroup detection and demonstrated them with a real-time case study of USS Cole bombing terrorist network. The algorithms are demonstrated in an application by a prototype system. The system finds associations between terrorist and terrorist organisations and is capable of determining links between terrorism plots occurred in the past, their affiliation with terrorist camps, travel record, funds transfer, etc. The findings are represented by a network in the form of an Attributed Relational Graph (ARG). Paths from a node to any other node in the network indicate the relationships between individuals and organisations. The system also provides assistance to law enforcement agencies, indicating when the capture of a specific terrorist will more likely destabilise the terrorist network. In this paper, we discuss the important application area related to subgroups in a terrorist cell using filtering of graph algorithms. The novelty of the algorithms can be easily found from the results they produce.
Probabilistic assessment of power systems

Reliability is an important issue in power systems and historically has been assessed using deterministic criteria and indexes. However, these approaches can be, and in many cases have been, replaced by probabilistic methods that are able to respond to the actual stochastic factors that influence the reliability of the system. In the days of global, completely integrated and/or nationalized electricity supply industries, the only significant objective was the reliability seen by actual end users. Also, the system was structured in a relatively simple way such that generation, transmission, and distribution could be assessed as a series of sequential hierarchical levels. Failures at any level could cause interruptions of supply to the end user. All planning and operational criteria were intended to minimize such interruptions within economic limits. The system has been, or is being, restructured and now many individual parties are involved, often competitively, including generators, network owners, network operators, energy suppliers, regulators, as well as the end users. Each of these parties has a need to know the quality and performance of the system sector or subsector for which they are responsible. Therefore, there is now a need for a range of reliability measures; the actual measure(s) needed varying between the different system parties. This paper addresses these issues and, in particular, reviews existing approaches and how these may be used and/or adapted to suit the needs and the required indexes of the new competitive industry and the different parties associated with it.
Glycogen Synthesis is Induced in Hypoxia by the Hypoxia-Inducible Factor and Promotes Cancer Cell Survival

The hypoxia-inducible factor 1 (HIF-1), in addition to genetic and epigenetic changes, is largely responsible for alterations in cell metabolism in hypoxic tumor cells. This transcription factor not only favors cell proliferation through the metabolic shift from oxidative phosphorylation to glycolysis and lactic acid production but also stimulates nutrient supply by mediating adaptive survival mechanisms. In this study we showed that glycogen synthesis is enhanced in non-cancer and cancer cells when exposed to hypoxia, resulting in a large increase in glycogen stores. Furthermore, we demonstrated that the mRNA and protein levels of the first enzyme of glycogenesis, phosphoglucomutase1 (PGM1), were increased in hypoxia. We showed that induction of glycogen storage as well as PGM1 expression were dependent on HIF-1 and HIF-2. We established that hypoxia-induced glycogen stores are rapidly mobilized in cells that are starved of glucose. Glycogenolysis allows these “hypoxia-preconditioned” cells to confront and survive glucose deprivation. In contrast normoxic control cells exhibit a high rate of cell death following glucose removal. These findings point to the important role of hypoxia and HIF in inducing mechanisms of rapid adaptation and survival in response to a decrease in oxygen tension. We propose that a decrease in pO2 acts as an “alarm” that prepares the cells to face subsequent nutrient depletion and to survive.
A new type of IRES within gag coding region recruits three initiation complexes on HIV-2 genomic RNA

Genomic RNA of primate lentiviruses serves both as an mRNA that encodes Gag and Gag-Pol polyproteins and as a propagated genome. Translation of this RNA is initiated by standard cap dependant mechanism or by internal entry of the ribosome. Two regions of the genomic RNA are able to attract initiation complexes, the 5′ untranslated region and the gag coding region itself. Relying on probing data and a phylogenetic study, we have modelled the secondary structure of HIV-1, HIV-2 and SIVMac coding region. This approach brings to light conserved secondary-structure elements that were shown by mutations to be required for internal entry of the ribosome. No structural homologies with other described viral or cellular IRES can be identified and lentiviral IRESes show many peculiar properties. Most notably, the IRES present in HIV-2 gag coding region is endowed with the unique ability to recruit up to three initiation complexes on a single RNA molecule. The structural and functional properties of gag coding sequence define a new type of IRES. Although its precise role is unknown, the conservation of the IRES among fast evolving lentiviruses suggests an important physiological role.