Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual Inhibition of Tumor Energy Pathway by 2-Deoxyglucose and Metformin Is Effective against a Broad Spectrum of Preclinical Cancer Models

Tumor cell proliferation requires both growth signals and sufficient cellular bioenergetics. The AMP-activated protein kinase (AMPK) pathway seems dominant over the oncogenic signaling pathway suppressing cell proliferation. This study investigated the preclinical efficacy of targeting the tumor bioenergetic pathway using a glycolysis inhibitor 2-deoxyglucose (2DG) and AMPK agonists, AICAR and metformin. We evaluated the in vitro antitumor activity of 2DG, metformin or AICAR alone, and 2DG in combination either with metformin or AICAR. We examined in vivo efficacy using xenograft mouse models. 2DG alone was not sufficient to promote tumor cell death, reflecting the limited efficacy showed in clinical trials. A combined use of 2DG and AICAR also failed to induce cell death. However, 2DG and metformin led to significant cell death associated with decrease in cellular ATP, prolonged activation of AMPK, and sustained autophagy. Gene expression analysis and functional assays revealed that the selective AMPK agonist AICAR augments mitochondrial energy transduction (OXPHOS) whereas metformin compromises OXPHOS. Importantly, forced energy restoration with methyl pyruvate reversed the cell death induced by 2DG and metformin, suggesting a critical role of energetic deprivation in the underlying mechanism of cell death. The combination of 2DG and metformin inhibited tumor growth in mouse xenograft models. Deprivation of tumor bioenergetics by dual inhibition of energy pathways might be an effective novel therapeutic approach for a broad spectrum of human tumors. Mol Cancer Ther; 10(12); 2350–62. ©2011 AACR.
Regularity of clinical medication in treatment of insomnia analyzed with data mining approach

Insomnia was the most common sleep problem among about one half of elder adults. Throughout centuries of clinical practice, treatment of this disease with traditional Chinese medicine (TCM) was being increasingly demonstrated advantage. Nevertheless, there are few documents concerning the composition rules of Chinese herbs according to pattern differentiation for treating insomnia. This present study focused on insomnia, collected and analyzed the literature in recent decades, applied data mining approach to explore the composition rules of Chinese herbs in formulae and the network of TCM pattern with them to form some regularities clinical medication in treating insomnia. Data mining approach is able to better explore the medication rule of insomnia which better able to guide the herbs clinical application and Chinese medicine research.
Experiments in Terabyte Searching, Genomic Retrieval and Novelty Detection for TREC 2004

In TREC2004, Dublin City University took part in three tracks, Terabyte (in collaboration with University College Dublin), Genomic and Novelty. In this paper we will discuss each track separately and present separate conclusions from this work. In addition, we present a general description of a text retrieval engine that we have developed in the last year to support our experiments into large scale, distributed information retrieval, which underlies all of the track experiments described in this document.
An admission control algorithm applied to video on demand system

The main mechanism of Video on Demand (VoD) system is based on the balance between the need from customs and the system resources. To guarantee high quality of services, VoD systems can employ admission control schemes to decide whether a new request for resource services will be offered or not. In this paper, an admission control algorithm is proposed to improve the performance of the VoD system by using a different probability method. The proposed admission control algorithm was simulated on NS2 platform. Simulation experimental results show that the proposed admission control algorithm in this paper is characterized by better reducing the blockage for the VoD system.
Packing the meeting summarization knapsack

Despite considerable work in automatic meeting summarization over the last few years, comparing results remains difficult due to varied task conditions and evaluations. To address this issue, we present a method for determining the best possible extractive summary given an evaluation metric like ROUGE. Our oracle system is based on a knapsack-packing framework, and though NP-Hard, can be solved nearly optimally by a genetic algorithm. To frame new research results in a meaningful context, we suggest presenting our oracle results alongside two simple baselines. We show oracle and baseline results for a variety of evaluation scenarios that have recently appeared in this field.
Perineurioma of the pancreas: a rare case.

CONTEXT Mesenchymal tumors of pancreas are rare. CASE REPORT We describe a case of perineurioma involving the body and tail of pancreas presenting as a slow growing abdominal lump. CONCLUSION Though perineurioma may arise from variety of anatomical sites including gastrointestinal tract, there is no previous report of perineurioma arising from the pancreas.
Neurochemical and Neuropharmacological Aspects of Circadian Disruptions: An Introduction to Asynchronization

Circadian disruptions are common in modern society, and there is an urgent need for effective treatment strategies. According to standard diagnostic criteria, most adolescents showing both insomnia and daytime sleepiness are diagnosed as having behavioral-induced sleep efficiency syndrome resulting from insomnia due to inadequate sleep hygiene. However, a simple intervention of adequate sleep hygiene often fails to treat them. As a solution to this clinical problem, the present review first overviews the basic neurochemical and neuropharmachological aspects of sleep and circadian rhythm regulation, then explains several circadian disruptions from similar viewpoints, and finally introduces the clinical notion of asynchronization. Asynchronization is designated to explain the pathophysiology/pathogenesis of exhibition of both insomnia and hypersomnia in adolescents, which comprises disturbances in various aspects of biological rhythms. The major triggers for asynchronization are considered to be a combination of light exposure during the night, which disturbs the biological clock and decreases melatonin secretion, as well as a lack of light exposure in the morning, which prohibits normal synchronization of the biological clock to the 24-hour cycle of the earth and decreases the activity of serotonin. In the chronic phase of asynchronization, involvement of both wake- and sleep-promoting systems is suggested. Both conventional and alternative therapeutic approaches for potential treatment of asynchronization are suggested.
Butterfly-like D-tree fusion strategy for real-time speech and music classification

Aimed at the problem of real-time speech and music discrimination, this paper proposes a frame-level classification method by using a novel “butterfly-like” fusion strategy based on decision tree (D-Tree). In our method, some homotypes of long-term features but in different time lengths are extracted to train each sub-classifier and make the fusion resultful. A testing experiment indicates our approach can achieve the desirable performance in reducing the misclassification and the imbalance of decision tree model. Meanwhile, superiorities in low overheads of computational complexity and memory resource make it competitive in practical applications.
Diffuse large B-cell lymphoma of the oral cavity

The authors report a case of diffuse large B-cell lymphoma (DLBL) of the oral cavity. The patient was a 73-year-old white man who first presented at the Division of Stomatology with a large nodular mass in the hard palate and a nodular lesion in the upper lip, which were diagnosed as DLBL. The patient was treated with eight cycles of CHOP chemotherapy (cyclophosphamide, doxorubicin, vincristine and prednisone), but the disease recurred 22 months after the end of the therapy. Both primary sites hard palate and upper lip were involved again and the patient was resubmitted to chemotherapy.
Landscape genomic insights into the historic migration of mountain hemlock in response to Holocene climate change.

PREMISE OF THE STUDY Untangling alternative historic dispersal pathways in long-lived tree species is critical to better understand how temperate tree species may respond to climatic change. However, disentangling these alternative pathways is often difficult. Emerging genomic technologies and landscape genetics techniques improve our ability to assess these pathways in natural systems. We address the question to what degree have microrefugial patches and long-distance dispersal been responsible for the colonization of mountain hemlock (Tsuga mertensiana) on the Alaskan Kenai Peninsula. METHODS We used double-digest restriction-associated DNA sequencing (ddRADseq) to identify genetic variants across eight mountain hemlock sample sites on the Kenai Peninsula, Alaska. We assessed genetic diversity and linkage disequilibrium using landscape and population genetics approaches. Alternative historic dispersal pathways were assessed using discriminant analysis of principle components and electrical circuit theory. KEY RESULTS A combination of decreasing diversity, high gene flow, and landscape connectivity indicates that mountain hemlock colonization on the Kenai Peninsula is the result of long-distance dispersal. We found that contemporary climate best explained gene flow patterns and that isolation by resistance was a better model explaining genetic variation than isolation by distance. CONCLUSIONS Our findings support the conclusion that mountain hemlock colonization is the result of several long-distance dispersal events following Pleistocene glaciation. The high dispersal capability suggests that mountain hemlock may be able to respond to future climate change and expand its range as new habitat opens along its northern distribution.
Error-free protection of EC point multiplication by modular extension

An implementation of a point multiplication function in an ellipticcurve cryptosystem can be attacked by fault injections in order to reveal the secret multiplier. A special kind of such an attack is the sign-change fault attack. Here the result of a point multiplication is changed in such a way that it is still a point on the curve. A well-known countermeasure against this kind of attack is to perform the point multiplication on a modular extension of the main curve by a small curve. Then the result is checked against the result of the same point multiplication recalculated on the small curve. The problem with this countermeasure is that the point at infinity on the small curve may be reached as an intermediate result with a non-negligible probability. In this case the comparison with the result on the small curve is either faulty or meaningless. We propose a variant of the modular extension countermeasure where the point at infinity is never reached as an intermediate result on the main or on the small curve.
Chromatin and epigenetic features of long-range gene regulation

The precise regulation of gene transcription during metazoan development is controlled by a complex system of interactions between transcription factors, histone modifications and modifying enzymes and chromatin conformation. Developments in chromosome conformation capture technologies have revealed that interactions between regions of chromatin are pervasive and highly cell-type specific. The movement of enhancers and promoters in and out of higher-order chromatin structures within the nucleus are associated with changes in expression and histone modifications. However, the factors responsible for mediating these changes and determining enhancer:promoter specificity are still not completely known. In this review, we summarize what is known about the patterns of epigenetic and chromatin features characteristic of elements involved in long-range interactions. In addition, we review the insights into both local and global patterns of chromatin interactions that have been revealed by the latest experimental and computational methods.
A Sensor Based Approach to Outdoor Illumination Estimation for Augmented Reality Applications on Mobile Devices

Realistic Augmented Reality applications require integrating virtual objects in the real world in a seamless visual way. The main problem to obtain a perfect visual augmentation is rendering the virtual objects with consistent illumination. In this paper, we present a novel approach to estimate outdoor illumination for Augmented Reality applications on mobile devices based on information acquired from sensors. We use an ambient light sensor to automatically detect in real-time the scene illuminance, which is used to simulate the actual lighting conditions. As outdoor illumination is mostly dependent on the weather, we derived the sky/sun illumination parameters from the light sensor data based on the IESNA sky model. The sunlight direction is estimated based on information from the GPS, date and time of the day. The result is a practical solution for outdoor illumination estimation handling light changes under natural conditions and applying them to the rendering of virtual objects in the real scene. Categories and Subject Descriptors (according to ACM CCS) : I.3. 7 [Computer Graphics]: Graphics systems and interfaces—Mixed/augmented reality
Probabilistic Regression Using Basis Function Models

Our goal is to accurately estimate the error in any prediction of a regression model. We propose a probabilistic regression framework for basis function regression models, which includes widely used kernel methods such as support vector machines and nonlinear ridge regression. The framework outputs a point specific estimate of the probability that the true regression surface lies between two user specified values, denoted by y1 and y2. More formally, given anyy2 > y1, we estimate the Pr(y1 ≤ y ≤ y2|x, f̂(x)), wherey is a true regression surface, x is the input, andf̂(x) is the basis function model. Thus the framework encompasses the less general standard error bar approach used in regression. We assume that the training data is independent and identically distributed (iid) from a stationary distribution, and make no specific distribution assumptions (e.g. no Gaussian or other specific distributions are assumed). Theory is presented showing that as the number of training points increases, estimates of Pr(y1 ≤ y ≤ y2|x, f̂(x)) approach the true value. Experimental evidence demonstrates that our framework gives reliable probability estimates, without sacrificing mean squared error regression accuracy.
Variability in Blazars: Clues from PKS 2155-304

Rapid variability on a time-scale much faster than the light-crossing time of the central supermassive black hole has been seen in TeV emission from the blazar PKS 2155−304. The most plausible explanation for this puzzling observation is that the radiating fluid in the relativistic jet is divided into a large number of subregions which move in random directions with relative Lorentz factors ≈γ � j . The random motions introduce new relativistic effects, over and above those due to the overall mean bulk Lorentz factorb of the jet. We consider two versions of this 'jets in a jet' model. In the first, the 'subjets' model, stationary regions in the mean jet frame emit relativistic subjets that produce the observed radiation. The variability time-scale is determined by the size of the subregions in the mean jet frame. This model, which is loosely based on magnetic reconnection, has great difficulty explaining the observations in PKS 2155−304. In the alternate 'turbulence' model, various subregions move relativistically in random directions and the variability time-scale is determined by the size of these regions in their own comoving frames. This model fits the data much more comfortably. Details such as what generates the turbulent motion, how particles are heated, and what the radiation process is, remain to be worked out. We consider collisions between TeV photons and soft photons and find that, in both the subjets and turbulence models, the mean bulk Lorentz factorb of the jet needs to be >25 to avoid the pair catastrophe.
Automatic Animation for Time‐Varying Data Visualization

This paper presents a digital storytelling approach that generates automatic animations for time‐varying data visualization. Our approach simulates the composition and transition of storytelling techniques and synthesizes animations to describe various event features. Specifically, we analyze information related to a given event and abstract it as an event graph, which represents data features as nodes and event relationships as links. This graph embeds a tree‐like hierarchical structure which encodes data features at different scales. Next, narrative structures are built by exploring starting nodes and suitable search strategies in this graph. Different stages of narrative structures are considered in our automatic rendering parameter decision process to generate animations as digital stories. We integrate this animation generation approach into an interactive exploration process of time‐varying data, so that more comprehensive information can be provided in a timely fashion. We demonstrate with a storm surge application that our approach allows semantic visualization of time‐varying data and easy animation generation for users without special knowledge about the underlying visualization techniques.
Variations on Acoustophoretic Microchannels: From the Facile to the Highly Capable

The lab-on-a-chip toolkit is replete with techniques for microparticle manipulation. The use of ultrasonic waves to impart forces on particles, referred to as acoustophoresis, is one particularly powerful yet gentle option. Traditionally, piezoelectric transducers have been coupled with acoustic resonators in order to sustain standing waves for aggregating, sorting, and sensing applications. However, there are several drawbacks to these setups. First, the construction techniques underpinning resonators tend to be expensive and laborious. Secondly, the acoustic impedance of piezoelectric transducers is much higher than the aqueous medium in which microparticles are suspended. This requires the use of impedance-matching layers to adequately couple acoustic energy into the medium. Finally, piezoelectric materials tend to be incompatible with traditional fabrication methods for microelectromechanical systems (MEMS). This can significantly impact the use of piezoelectric materials in more complex lab-on-a-chip type platforms where many processes beyond sample manipulation may be necessary. Over the past two decades, another type of transducer, known as the capacitive micromachined ultrasonic transducer (CMUT), has been challenging the dominance of the piezotransducer. However, this competition has been occurring primarily in the arenas of non-destructive testing and medical imaging. Given some of the unique attributes of CMUTs, it is surprising that they have yet to be fully realized in acoustophoresis, especially because acoustophoresis is popularly practiced within a microfluidic setting. We first present a highly cost-effective and cleanroom-free technique for prototyping piezo-equipped, transversal acoustophoretic resonators. Simple bifurcation and trifurcation microchannels suitable for acoustophoresis in microscopy applications are fabricated and demonstrated. The second focus of our research looks at the suitability of CMUT microarrays as platforms for acoustophoresis. We address the following: issues surrounding their implementation; modeling of potential resonator designs; and possibility of foregoing resonators altogether. Several CMUT devices are then fabricated and tested, using travelling-wave ultrasound to demonstrate aggregation within droplets as well as sequential capture and separation within flows. A unique phenomenon of bead aggregate palpation is encountered, the physical underpinnings of which are attributed to magnitude changes in lateral gradient forces with frequency. Finally, we attempt to perform standing wave manipulations of particles using the CMUT microarray, and describe the difficulties encountered in doing so.
Compiler support for lightweight context switching

We propose a new language-neutral primitive for the LLVM compiler, which provides efficient context switching and message passing between lightweight threads of control. The primitive, called Swapstack, can be used by any language implementation based on LLVM to build higher-level language structures such as continuations, coroutines, and lightweight threads. As part of adding the primitives to LLVM, we have also added compiler support for passing parameters across context switches. Our modified LLVM compiler produces highly efficient code through a combination of exposing the context switching code to existing compiler optimizations, and adding novel compiler optimizations to further reduce the cost of context switches. To demonstrate the generality and efficiency of our primitives, we add one-shot continuations to C++, and provide a simple fiber library that allows millions of fibers to run on multiple cores, with a work-stealing scheduler and fast inter-fiber sychronization. We argue that compiler-supported lightweight context switching can be significantly faster than using a library to switch between contexts, and provide experimental evidence to support the position.
A strategy for designing inhibitors of α ‐synuclein aggregation and toxicity as a novel treatment for Parkinson's disease and related disorders

Convergent biochemical and genetic evidence suggests that the formation of α‐synuclein (α‐syn) protein deposits is an important and, probably, seminal step in the development of Parkinson's disease (PD), dementia with Lewy bodies (DLB) and multiple system atrophy (MSA). It has been reported that transgenic animals overexpressing human α‐syn develop lesions similar to those found in the brain in PD, together with a progressive loss of dopaminergic cells and associated abnormalities of motor function. Inhibiting and/or reversing α‐syn self‐aggregation could, therefore, provide a novel approach to treating the underlying cause of these diseases. We synthesized a library of overlapping 7‐mer peptides spanning the entire α‐syn sequence, and identified amino acid residues 64‒100 of α‐syn as the binding region responsible for its self‐ association. Modified short peptides containing α‐syn amino acid sequences from part of this binding region (residues 69‒72), named α‐syn inhibitors (ASI), were found to interact with full‐ length α‐syn and block its assembly into both early oligomers and mature amyloid‐like fibrils. We also developed a cell‐permeable inhibitor of α‐syn aggregation (ASID), using the polyarginine peptide delivery system. This ASID peptide was able to inhibit the DNA damage induced by Fe(II) in neuronal cells transfected with α‐syn(A53T), a familial PD‐associated mutation. ASI peptides without this delivery system did not reverse levels of Fe(II)‐induced DNA damage. Furthermore, the ASID peptide increased (P<0.0005) the number of cells stained positive for Bcl‐2, while significantly (P<0.05) decreasing the percentage of cells stained positive for BAX. These short peptides could serve as lead compounds for the design of peptidomimetic drugs to treat PD and related disorders.