Miracle-dz/UniFAR-FTUs huggingface dataset:
Aptamers: Active Targeting Ligands for Cancer Diagnosis and Therapy

Aptamers, including DNA, RNA and peptide aptamers, are a group of promising recognition units that can specifically bind to target molecules and cells. Due to their excellent specificity and high affinity to targets, aptamers have attracted great attention in various fields in which selective recognition units are required. They have been used in biosensing, drug delivery, disease diagnosis and therapy (especially for cancer treatment). In this review, we summarized recent applications of DNA and RNA aptamers in cancer theranostics. The specific binding ability of aptamers to cancer-related markers and cancer cells ensured their high performance for early diagnosis of cancer. Meanwhile, the efficient targeting ability of aptamers to cancer cells and tissues provided a promising way to deliver imaging agents and drugs for cancer imaging and therapy. Furthermore, with the development of nanoscience and nanotechnology, the conjugation of aptamers with functional nanomaterials paved an exciting way for the fabrication of theranostic agents for different types of cancers, which might be a powerful tool for cancer treatment.
CADS: Continuous Authentication on Data Streams

We study processing and authentication of long-running queries on outsourced data streams. In this scenario, a data owner (DO) constantly transmits its data to a service provider (SP), together with additional authentication information. Clients register continuous range queries to the SP. Whenever the data change, the SP must update the results of all affected queries and inform the clients accordingly. The clients can verify the correctness of the results using the authentication information provided by the DO. Compared to conventional databases, stream environments pose new challenges such as the need for fast structure updating, support for continuous query processing and authentication, and provision for temporal completeness. Specifically, in addition to the correctness of individual results, the client must be able to verify that there are no missing results in between updates. We face these challenges through several contributions. Since there is no previous work, we first present a technique, called REF, that achieves correctness and temporal completeness but incurs false transmissions, i.e., the SP has to inform clients whenever there is a data update, even if their results are not affected. Then, we propose CADS, which minimizes the processing and transmission overhead through an elaborate indexing scheme and a virtual caching mechanism. Finally, we extend CADS to the case where multiple owners outsource their data to the same SP. The SP integrates all data in a single authentication process, independently of the number of DOs.
Self-explanation training improves proof comprehension

In this paper we report three experiments demonstrating that a simple booklet containing self explanation training, designed to focus students’ attention on logical relationships within a mathematical proof, can significantly improve their proof comprehension. Experiment 1 demonstrates that students who receive the training generate higher quality explanations and perform better (effect size d = 0.950) on a comprehension test. Experiment 2 demonstrates that self-explanation training increases students’ cognitive engagement and the frequency with which they move their attention around a proof. Experiment 3 demonstrates that a 15- minute in-lecture self-study intervention improves students’ proof comprehension, and that the effect persists over time. Thus we argue that ‘transition to proof’ courses should incorporate self-explanation training.
Semi-supervised biomedical relation classification using generalized expectation criteria

Semi-supervised learning is necessary for the extensive application of machine learning in practice. It can use unlabeled data to improve the performance of existing supervised machine learning method. In this work, we addressed the biomedical relation classification problem by utilizing a semi-supervised method which can train Maximum Entropy models according to Generalized Expectation criteria. In the proposed method, instead of "instance labeling" used in previous works, the "feature labeling" was applied to get the training data which can save lots of labeling time. A topic model was involved to choose the features for labeling. Experiment results show that the proposed method can dramatically improve the performance of biomedical relation classification through incorporating unlabeled data by feature labeling.
Bullying in schools: why it happens, how it makes young people feel and what we can do about it

In spite of decades of research and more recent guidance by Government, bullying in schools remains a serious concern to young people and to educational practitioners. This two year qualitative study explored the meanings eight teenagers gave to bullying they had experienced, and related this to an analysis of previous research and school policies about bullying. The findings from the study revealed that bullying affected the subjectivity of young people, including how they positioned themselves and believed themselves to be positioned by others. It also found previous research and school policies focused on the behavioural aspects of bullying, neglecting the subjective meanings that it had for those who experienced it. The research findings suggested that a more open approach by adults to what bullying means to individuals, and clearer guidance to teachers on how to work with them about subjective meanings, may provide a new direction in supporting young people who have been bullied.
Production of polyclonal antibodies to feline tumor necrosis factor

Two 13-amino-acid peptides were synthesized based on the putative feline tumor necrosis factor (FeTNF) sequence. The synthesized peptides were conjugated to keyhole limpet hemocyanin, emulsified in complete Freund's adjuvant, and injected into rabbits. The gene for FeTNF was cloned into the FLAG (International Biotechnologies Inc. [IBI], Kodak, New Haven, Conn.) fusion protein expression vector. The expressed fusion protein was purified by using the M-1 anti-FLAG octapeptide monoclonal antibody (IBI, Kodak). The fusion protein was emulsified in complete Freund's adjuvant and injected into chickens. The immune sera generated to the synthetic peptides and the fusion protein recognized the recombinant FeTNF fusion protein on Western or dot blot assay. The preimmune and immune sera were incubated with naturally occurring FeTNF (supernatants from lipopolysaccharide-stimulated cultured feline peritoneal exudate or peripheral mononuclear cells). The antibody raised to the recombinant FeTNF fusion protein and N-terminal synthetic peptide neutralized bioactivity of native FeTNF and recombinant human TNF. Preimmune sera did not have any neutralizing activity. The polyclonal antibodies were not specific for FeTNF, since both porcine and human recombinant TNF were neutralized by the fusion protein antibodies. The synthetic peptide antibodies recognized recombinant feline and equine TNF on a Western blot.
Development and implementation of an e-course and a remote laboratory for analog electronics study

This paper describes the different steps for the development of a remote laboratory for teaching analog electronics. The course was developed to support the face to face teaching and will upgrade the knowledge of engineers and technicians for the socioeconomic sector. In this paper, after describing the steps of design and scriptwriting of teaching materials, the operational amplifier is then studied for online lab work.
Mapping the global mRNA transcriptome during development of the murine first molar

The main objective of this study was to map global gene expression in order to provide information about the populations of mRNA species participating in murine tooth development at 24 h intervals, starting at the 11th embryonic day (E11.5) up to the 7th post-natal day (P7). The levels of RNA species expressed during murine tooth development were mesured using a total of 58 deoxyoligonucleotide microarrays. Microarray data was validated using real-time RT-PCR. Differentially expressed genes (p < 0.05) were subjected to bioinformatic analysis to identify cellular activities significantly associated with these genes. Using ANOVA the microarray data yielded 4362 genes as being differentially expressed from the 11th embryonic day (E11.5) up to 7 days post-natal (P7), 1921 of these being genes without known functions. The remaining 2441 genes were subjected to further statistical analysis using a supervised procedure. Bioinformatic analysis results for each time-point studied suggests that the main molecular functions associated with genes expressed at the early pre-natal stages (E12.5–E18.5) were cell cycle progression, cell morphology, lipid metabolism, cellular growth, proliferation, senescence and apoptosis, whereas most genes expressed at post-natal and secretory stages (P0–P7) were significantly associated with regulation of cell migration, biosynthesis, differentiation, oxidative stress, polarization and cell death. Differentially expressed genes (DE) not described earlier during murine tooth development; Inositol 1, 4, 5-triphosphate receptor 3 (Itpr3), metallothionein 1(Mt1), cyclin-dependent kinase 4 (Cdk4), cathepsin D (Ctsd), keratin complex 2, basic, gene 6a (Krt2-6a), cofilin 1, non-muscle (Cfl1), cyclin 2 (Ccnd2), were verified by real-time RT-PCR.
Small Molecule Inhibitors of CXCR4

CXCR4 is a G-protein-coupled receptor involved in a number of physiological processes in the hematopoietic and immune systems. The SDF-1/CXCR4 axis is significantly associated with several diseases, such as HIV, cancer, WHIM syndrome, rheumatoid arthritis, pulmonary fibrosis and lupus. For example, CXCR4 is one of the major co-receptors for HIV entry into target cells, while in cancer it plays an important role in tumor cell metastasis. Several promising CXCR4 antagonists have been developed to block SDF-1/CXCR4 interactions that are currently under different stages of development. The first in class CXCR4 antagonist, plerixafor, was approved by the FDA in 2008 for the mobilization of hematopoietic stem cells and several other drugs are currently in clinical trials for cancer, HIV, and WHIM syndrome. While the long-term safety data for the first generation CXCR4 antagonists are not yet available, several new compounds are under preclinical development in an attempt to provide safer and more efficient treatment options for HIV and cancer patients.
Towards Cultural-Scale Models of Full Text

This technical report consists of two components: an administrative report for the HathiTrust Research Center (HTRC) Advanced Collaborative Support (ACS) program and a research report on the variance of topic models trained over random samples of books in the Hathi Trust. Cultural-scale models of full text documents are prone to over-interpretation by researchers making unintentionally strong socio-linguistic claims without recognizing that even large digital libraries are merely samples of all the books ever produced. In this study, we test the sensitivity of the topic models to the sampling process by taking random samples of books in the Hathi Trust Digital Library within different Library of Congress Classification (LCC) areas. For each classification area, we train several topic models over the entire class with different random seeds, generating a set of spanning models. Then, we train topic models on random samples of books from the classification area, generating a set of sample models. Finally, we align topics from the sample models to the spanning models and measure the alignment distance and topic overlap. We find that sample models with a large sample size typically have an alignment distance that falls in the range of the alignment distance between spanning models. Unsurprisingly, as sample size increases, alignment distance decreases. We also find that the topic overlap increases as sample size increases. However, the decomposition of these measures by sample size differs by field and by number of topics. We speculate that these measures could be used to find classes which have a common "canon" discussed among all books in the area, as shown by high topic overlap and low alignment distance even in small sample sizes.
Design and development of image defogging system

The proposed work presents a prototype of novel method that comprises of a complete embedded system for the process of restoring the foggy images. Foggy conditions are considered to be a major source of accidents for vehicles. Use of a novel ‘Mean Channel Prior (MCP)’ algorithm for defogging gave more accurate results as compared with the earlier existing methodologies. The prototype of proposed system works with use of raspberry pi, camera and display screen. Use of low cost, low power processing core raspberry pi made it low power, portable and stand alone system. Results of MCP image defogging algorithm are compared with Dark Channel Prior (DCP), Median channel Prior (MCP) and Improved single image dehazing using dark channel prior (ISIDDCP) on the basis of two parameters: Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR).
Midazolam: An Effective Antiemetic After Cardiac Surgery—A Clinical Trial

Cardiac surgery has been associated with a significant incidence of postoperative nausea and vomiting (PONV). To assess the antiemetic property of midazolam, we undertook this double-blinded, randomized trial in 200 patients undergoing cardiac surgery involving cardiopulmonary bypass, and we compared its efficacy with that of ondansetron in preventing PONV. Assessments on the occurrence of PONV were made at regular intervals for the first 24 h after tracheal extubation, along with sedation and pain scoring. We report a 6% incidence of nausea and no incidence of vomiting in the midazolam group, compared with a 21% incidence of PONV in the ondansetron group(P <0.001). All 21 patients (18 women and 3 men) in the ondansetron group and none of the 6 patients (all women) in the midazolam group required a rescue anti-emetic drug (P < 0.001). The sedation scores and postoperative pain scores were comparable in both groups. We conclude that midazolam, instituted as a continuous infusion in a dose of 0.02 mg · kg−1 · h−1, is a more effective antiemetic than ondansetron in a dose of 0.1 mg/kg IV every 6 h for the prevention of PONV after cardiac surgery.
Cognitive Hybrid Division Duplex for Two-Tier Femtocell Networks

With the exponential increase in high rate traffic given by a new generation of wireless devices, data is expected to overwhelm cellular network capacity in the near future. Femtocell networks have been recently proposed as an efficient and cost-effective approach to provide unprecedented levels of network capacity and coverage. However, the dense and random deployment of femtocells and their uncoordinated operation raise important questions concerning interference pollution and spectrum allocation. Motivated by the flexible subchannel allocation capabilities of cognitive radio, we propose a cognitive hybrid division duplex (CHDD) that is suitable for heterogeneous networks in future mobile communication systems. Specifically, our CHDD scheme has a pair of frequency bands to perform frequency division duplex (FDD) on the macrocell, while time division duplex (TDD) is simultaneously operated in these bands by underlaid cognitive femtocells. By doing so, the proposed CHDD scheme exploits the advantages of both FDD and TDD schemes: operating in FDD at the macrocell tier controls inter-tier interference, whereas operating in TDD at the femtocell tier provides to femtocells the flexibility of adjusting uplink and downlink rates together with opportunistic access benefits. Using tools from stochastic geometry, we provide a methodology on how to design efficient switching mechanisms for cognitive TDD operation of femtocells. In particular, we derive closed-form expressions for the success probability and the area spectral efficiency of the proposed CHDD scheme when the macro tier is in downlink and uplink mode. Furthermore, we propose an open access policy as a means to improve the performance of macrocell transmissions. Our analysis and numerical results show the effectiveness of introducing cognition in femtocells so as to improve the system performance of two-tier femtocell networks.
Exploiting Wiktionary for Lightweight Part-of-Speech Tagging for Machine Learning Tasks

Part-of-speech (PoS) tagging is a crucial part in many natural language machine learning tasks. Current state-ofthe-art PoS taggers exhibit excellent qualitative performance, but also contribute heavily to the total runtime of text preprocessing and feature generation, which makes feature engineering a timeconsuming task. We propose a lightweight dictionary and heuristics based PoS tagger that exploits Wiktionary as its information source. We demonstrate that its application to natural language machine learning tasks considerably decreases the feature generation runtime, while not degrading the overall performance on these tasks. We compare the lightweight tagger to a stateof-the-art maximum entropy based PoS tagger in clustering and classification tasks and evaluate its performance on the Brown Corpus. Finally, we explore future research scenarios where our tagger and Wiktionary lookup enables efficient processing of big data due to the significant decrease in runtime. Keywords—Machine learning; feature engineering; natural language processing; part-of-speech tagging; big data.
Latent contextual indexing of annotated documents

In this paper we propose a simple and flexible framework to index context-annotated documents, e.g., documents with timestamps or georeferences, by contextual topics. A contextual topic is a distribution over document features with a particular meaning in the context domain, such as a repetitive event or a geographic phenomenon. Such a framework supports document clustering, labeling, and search, with respect to contextual knowledge contained in the document collection. To realize the framework, we introduce an approach to project documents into a context-feature space. Then, dimensionality reduction is used to extract contextual topics in this context-feature space. The topics can then be projected back onto the documents. We demonstrate the utility of our approach with a case study on georeferenced Wikipedia articles.
Caspase-3-Dependent Proteolytic Cleavage of Protein Kinase Cδ Is Essential for Oxidative Stress-Mediated Dopaminergic Cell Death after Exposure to Methylcyclopentadienyl Manganese Tricarbonyl

In the present study, we characterized oxidative stress-dependent cellular events in dopaminergic cells after exposure to an organic form of manganese compound, methylcyclopentadienyl manganese tricarbonyl (MMT). In pheochromocytoma cells, MMT exposure resulted in rapid increase in generation of reactive oxygen species (ROS) within 5–15 min, followed by release of mitochondrial cytochrome C into cytoplasm and subsequent activation of cysteine proteases, caspase-9 (twofold to threefold) and caspase-3 (15- to 25-fold), but not caspase-8, in a time- and dose-dependent manner. Interestingly, we also found that MMT exposure induces a time- and dose-dependent proteolytic cleavage of native protein kinase Cδ (PKCδ, 72–74 kDa) to yield 41 kDa catalytically active and 38 kDa regulatory fragments. Pretreatment with caspase inhibitors (Z-DEVD-FMK or Z-VAD-FMK) blocked MMT-induced proteolytic cleavage of PKCδ, indicating that cleavage is mediated by caspase-3. Furthermore, inhibition of PKCδ activity with a specific inhibitor, rottlerin, significantly inhibited caspase-3 activation in a dose-dependent manner along with a reduction in PKCδ cleavage products, indicating a possible positive feedback activation of caspase-3 activity by PKCδ. The presence of such a positive feedback loop was also confirmed by delivering the catalytically active PKCδ fragment. Attenuation of ROS generation, caspase-3 activation, and PKCδ activity before MMT treatment almost completely suppressed DNA fragmentation. Additionally, overexpression of catalytically inactive PKCδK376R(dominant-negative mutant) prevented MMT-induced apoptosis in immortalized mesencephalic dopaminergic cells. For the first time, these data demonstrate that caspase-3-dependent proteolytic activation of PKCδ plays a key role in oxidative stress-mediated apoptosis in dopaminergic cells after exposure to an environmental neurotoxic agent.
Efferent Visual Dysfunction From Multiple Sclerosis

Eye movement abnormalities are common in multiple sclerosis (MS) and may be a source of significant patient disability. Evaluation of a patient either suspected of having or diagnosed with MS is incomplete without a systematic evaluation of ocular motility. Abnormal eye movements may be the initial demyelinating event or arise during the chronic course of the disease. They are diagnostically useful and, at times, may be the only objective examination finding confirming a true disease state in patients with nonspecific complaints compatible with demyelination such as fatigue or paresthesias. Quantification with eye movement recording techniques can identify subclinical abnormalities and aid in the diagnosis of MS. An eye movement abnormality, reflecting a posterior fossa lesion that causes impaired mobility, may be a bedside finding predicting disability. Nearly any type of eye movement abnormality is possible as a consequence of demyelination but certain ocular motility deficits occur with high frequency. The most common, saccadic dysmetria and impairment of smooth pursuit, are nonspecific and indicative of cerebellar dysfunction. Saccadic dysmetria with overshooting (hypermetria) or abnormal vertical movements during horizontal saccades (directional dysmetria) are present in up to 40% of patients. Another common, characteristic, and highly-localizing abnormality is internuclear ophthalmoplegia (INO). Various forms of nystagmus are also well recognized. Rarely, ocular motor nerve or nuclear palsies, the dorsal midbrain syndrome, and saccadic intrusions may result from demyelinating disease.
Transition as Experienced by Close Relatives of People With Traumatic Brain Injury

ABSTRACT When someone is afflicted by a traumatic brain injury (TBI), it entails a sudden change in the lives of their close relatives. Relatives provide the primary support system for the person with TBI, and new living patterns have to be developed by the family to achieve balance in the new situation. There is an absence of studies focusing on the process of transition for people living close to a person with TBI, especially in a long-term relationship. The aim of this study, therefore, was to describe such transitions experienced by the close relatives of people with TBI. Five close relatives, all women, who lived with or close to a person with TBI in the northern part of Sweden, were interviewed. The data were analyzed in accordance with the qualitative interpretive method and performed in a series of steps to arrive at a description of the transition. The findings of the analysis are presented in 4 categories: the starting point of the transitions, transitions in pattern of daily life, transitions in relationship, and transitions in social life. The transitions of daily life for close relatives began suddenly as the person with TBI was injured unexpectedly. The relatives could feel lonely as former friends were gone or avoided them. How the person with TBI was met by other people strongly affected how the close relatives felt. Although they struggled to lessen the dependence of the person with TBI on them, they also felt anxious about how things would be if close relatives were no longer there for that person. The findings are discussed with reference to works by the philosophers Buber, Lévinas, and Lögstrup and theories of transition.