Miracle-dz/UniFAR-FTUs huggingface dataset:
Matrix metalloproteinase–activated doxorubicin prodrugs inhibit HT1080 xenograft growth better than doxorubicin with less toxicity

Matrix metalloproteinase (MMP)–activated prodrugs were formed by coupling MMP-cleavable peptides to doxorubicin. The resulting conjugates were excellent in vitro substrates for MMP-2, -9, and -14. HT1080, a fibrosarcoma cell line, was used as a model system to test these prodrugs because these cells, like tumor stromal fibroblasts, expressed several MMPs. In cultured HT1080 cells, simple MMP-cleavable peptides were primarily metabolized by neprilysin, a membrane-bound metalloproteinase. MMP-selective metabolism in cultured HT1080 cells was obtained by designing conjugates that were good MMP substrates but poor neprilysin substrates. To determine how conjugates were metabolized in animals, MMP-selective conjugates were given to mice with HT1080 xenografts and the distribution of doxorubicin was determined. These studies showed that MMP-selective conjugates were preferentially metabolized in HT1080 xenografts, relative to heart and plasma, leading to 10-fold increases in the tumor/heart ratio of doxorubicin. The doxorubicin deposited by a MMP-selective prodrug, compound 6, was more effective than doxorubicin at reducing HT1080 xenograft growth. In particular, compound 6 cured 8 of 10 mice with HT1080 xenografts at doses below the maximum tolerated dose, whereas doxorubicin cured 2 of 20 mice at its maximum tolerated dose. Compound 6 was less toxic than doxorubicin at this efficacious dose because mice treated with compound 6 had no detectable changes in body weight or reticulocytes, a marker for marrow toxicity. Hence, MMP-activated doxorubicin prodrugs have a much higher therapeutic index than doxorubicin using HT1080 xenografts as a preclinical model.
Physical Activity and Risk of Large Bowel Cancer in the Framingham Study 1

We examined the relation between self-reported physical activity and large bowel cancer in a prospective cohort of men and women who participated in the Framingham Study. Self-assessments of physical activity were available from the fourth biennial examination on a total of 1906 men and 2308 women aged 30 to 62 yr in 1954. The cohort was followed for up to 28 yr and yielded 152 cases (73 men, 79 women) of large bowel cancer. Inactivity was associated with an increased risk of large bowel cancer among men but not among women. The relative risk estimates for large bowel cancer among men in the middle and lowest fertiles of a physical activity index (compared with the highest tertile) were 1.4 (95% confi dence intervals, 0.8-2.6) and 1.8 (1.0-3.2), respectively. Among women the comparable estimates were 1.2 (0.7-2.1) and 1.1 (0.6-1.8), respec tively. These findings were unchanged after adjustment for body mass index, serum cholesterol, alcohol, and other potentially confounding variables. The narrow range of physical activity and the minimal heavy activity reported by women in this cohort may have limited our ability to detect an association between physical activity and large bowel cancer among women.
mPGES-1 Protects Against DOCA-Salt Hypertension via Inhibition of Oxidative Stress or Stimulation of NO/cGMP

Microsomal prostaglandin E synthase-1 (mPGES-1) is a recently characterized cytokine-inducible enzyme critically involved in pain and inflammatory response. However, its role in blood pressure regulation is still debatable. The present study was undertaken to examine the effect of mPGES-1 deletion on DOCA-salt hypertension. After 2 weeks of DOCA plus 1% NaCl as drinking fluid, hypertension and sodium retention were more severe in mPGES-1 knockout (KO) mice than in wild-type (WT) controls. The indices of oxidative stress including urinary 8-isprostane and renal thiobarbituric acid-reactive substances were only modestly increased or unchanged in the WT mice but more significantly increased in the KO mice after DOCA-salt. Conversely, in response to DOCA-salt, the indices of antioxidant systems including renal expression of superoxide dismutase-3 and urinary nitrate/nitrite excretion were all significantly elevated in the WT mice but remarkably suppressed in the KO mice. Tempol treatment (50 mg/kg per day) in DOCA-salt KO mice produced a marked attenuation of hypertension, sodium retention, and kidney injury. Immunoblotting demonstrated increased renal expression of mPGES-1 in DOCA-salt WT mice. DOCA-salt induced a nearly 5-fold increase in urinary PGE2 excretion in the WT mice, and this increase was completely abolished in the KO mice. Together, these results suggest that mPGES-1–derived PGE2 confers protection against DOCA-salt hypertension likely via inhibition of oxidative stress or stimulation of superoxide dismutase-3 and urinary nitrate/nitrite system.
Evolution of Nucleotide Punctuation Marks: From Structural to Linear Signals

We present an evolutionary hypothesis assuming that signals marking nucleotide synthesis (DNA replication and RNA transcription) evolved from multi- to unidimensional structures, and were carried over from transcription to translation. This evolutionary scenario presumes that signals combining secondary and primary nucleotide structures are evolutionary transitions. Mitochondrial replication initiation fits this scenario. Some observations reported in the literature corroborate that several signals for nucleotide synthesis function in translation, and vice versa. (a) Polymerase-induced frameshift mutations occur preferentially at translational termination signals (nucleotide deletion is interpreted as termination of nucleotide polymerization, paralleling the role of stop codons in translation). (b) Stem-loop hairpin presence/absence modulates codon-amino acid assignments, showing that translational signals sometimes combine primary and secondary nucleotide structures (here codon and stem-loop). (c) Homopolymer nucleotide triplets (AAA, CCC, GGG, TTT) cause transcriptional and ribosomal frameshifts. Here we find in recently described human mitochondrial RNAs that systematically lack mono-, dinucleotides after each trinucleotide (delRNAs) that delRNA triplets include 2x more homopolymers than mitogenome regions not covered by delRNA. Further analyses of delRNAs show that the natural circular code X (a little-known group of 20 translational signals enabling ribosomal frame retrieval consisting of 20 codons {AAC, AAT, ACC, ATC, ATT, CAG, CTC, CTG, GAA, GAC, GAG, GAT, GCC, GGC, GGT, GTA, GTC, GTT, TAC, TTC} universally overrepresented in coding versus other frames of gene sequences), regulates frameshift in transcription and translation. This dual transcription and translation role confirms for X the hypothesis that translational signals were carried over from transcriptional signals.
The Open University ’ s repository of research publications and other research outputs Consumer involvement : a new perspective

Involvement’s importance in marketing and consumer research is well established for twenty years. The concept has been linked to various consumer behavior and marketing constructs and has been used to classify products and advertising messages according to the level of involvement they arouse. Apart from its academic and research value, involvement has implications for practitioners. Thus involvement can be used to segment consumers into low, moderate and high involvement groups which can then be targeted with different promotional strategies. There is a plethora of views on involvement which need to be integrated in order to provide a thorough account which will facilitate researchers. This paper provides a coherent and summarizing synthesis of the extant literature on involvement and presents a new perspective of involvement by linking purchase involvement to channel choice.
Genomic Profiling of Viable and Proliferative Micrometastatic Cells from Early-Stage Breast Cancer Patients

Purpose: Metastases in distant organs are the major cause of death for cancer patients, and bone marrow is a prominent homing organ for early disseminated cancer cells. However, it remains still unclear which of these cells evolve into overt metastases. We therefore established a new approach based on the analysis of viable and proliferating cancer cells by single-cell comparative genomic hybridization. Experimental Design: The bone marrow of early-stage breast tumor patients (pN0M0) was screened for tumor cells by immunostaining. By applying special short-term culturing, we selected for viable and proliferative tumor cells. The short-term culturing allowed us to evaluate the proliferative potential of micrometastatic cells, which we had previously shown to represent an independent prognostic marker. We assessed genomic changes in single disseminated cancer cells by single-cell comparative genomic hybridization. Results: We found that these viable disseminated cancer cells already had a plethora of copy number changes in their genome. All of these cells showed chromosomal copy number changes with a substantial intercellular heterogeneity and differences to the matching primary tumors. Conclusions: The established experimental strategy might pave the way for the identification of metastatic stem cells in cancer patients. Our preliminary results support the new concept that early disseminated cancer cells evolve independently from their primary tumor.
3 D reconstruction from RGB and Depth Video

3D reconstruction has come a long way since the first attempts more than three decades ago. A variety of new algorithms have been proposed in the literature to solve various aspects of this complex problem. There are many different applications of 3D reconstruction with very diverse methodologies and goals. Our approach, however, is focused on reconstructing rigid objects from RGB and depth video sequences. The motivation for our research comes from the recent advancements in depth acquisition devices. Until recently, depth cameras were very rare, expensive and mostly used in research or very specific tasks. A new gaming peripheral named Kinect managed to reach mass market and achieve a price comparable to web cams. This device uses structured light to sense the depth of a scene in real time, and outputs an RGB image as well as a corresponding single-channel depth map. Although its original purpose was for pose recognition for gaming, a structured light camera can ease the task of 3D reconstruction. Although reconstruction is possible from a 2D RGB image, the depth of the image needs to be inferred, whereas with a depth map it is readily available.
Do 12-Week Yoga Program Influence Respiratory Function of Elderly Women?

Abstract Aging produces several respiratory limitations and reduces tolerance to physical efforts, sometimes leading to pulmonary diseases in the elderly. The literature draws attention to the possible benefits of Yoga practice among the elderly, presenting evidence for significant improvements in quality of life. It was hypothesized that yoga practice can improve respiratory function in the elderly. The effects of a yoga program on pulmonary volumes and respiratory muscle strength were verified in 36 elderly women divided into a yoga group [YG] (63.1 ± 13.3 years of age) and a control group (61.0 ± 6.9 years of age). Maximal inspiratory and expiratory pressure (MIP and MEP) were assessed by a manovacuometer and tidal volume (VT), vital capacity (VC) and minute ventilation (VE) were measured by a ventilometer. The program comprised 65 min sessions, 3 times/week during 12 weeks. The heart rate and respiratory rate decreased significantly in the YG (76-39 ± 8-03 vs. 74-61±10.26 bpm and 18.61 ± 3.15 vs. 16.72 ± 3.12 resp/min, respectively). In the YG, VT and VE increased significantly (0.55 ± 0.22 vs. 0.64 ± 0.2 ml and 9.19 ± 2.39 vs. 10.05 ± 2.11 ml, respectively), as well as VC (1.48 ± 0.45 vs. 2.03 ± 0.72 ml). Improvements were also found in MIP and MEP in the YG (62.17 ± 14.77 vs. 73.06 ± 20.16 cmH2O and 80.56 ± 23.94 vs. 86.39 ± 20.16 cmH2O, respectively). It was concluded that a 12-week yoga program significantly improves pulmonary function of aged women.
Four Methods for LIDAR Retrieval of Microscale Wind Fields

This paper evaluates four wind retrieval methods for micro-scale meteorology applications with volume and time resolution in the order of 30m3 and 5 s. Wind field vectors are estimated using sequential time-lapse volume images of aerosol density fluctuations. Suitably designed mono-static scanning backscatter LIDAR systems, which are sensitive to atmospheric density aerosol fluctuations, are expected to be ideal for this purpose. An important application is wind farm siting and evaluation. In this case, it is necessary to look at the complicated region between the earth’s surface and the boundary layer, where wind can be turbulent and fractal scaling from millimeter to kilometer. The methods are demonstrated using first a simple randomized moving hard target, and then with a physics based stochastic space-time dynamic turbulence model. In the latter case the actual vector wind field is known, allowing complete space-time error analysis. Two of the methods, the semblance method and the spatio-temporal method, are found to be most suitable for wind field estimation.
Multi-model diagnostics for various machining conditions: A similarity-based approach

In this paper, a similarity-based multi-model approach based on a pre-existing physically segmented hidden Markov model with continuous output (PSHMCO) is proposed for diagnostics and tool wear monitoring. The proposed approach helps to improve the estimation accuracy in cases that the machinery system undertakes different operating (machining) conditions. The proposed multi-model approach is compared with its single model variant on a tool wear monitoring dataset with various machining conditions. The results indicate that using a similarity function to identify and apply the most similar model out of multiple models can significantly improve the prediction performance compared to blindly utilizing a single general model while adequate training data is available.
Identification of a Receptor-Like Protein Kinase Gene Rapidly Induced by Abscisic Acid, Dehydration, High Salt, and Cold Treatments in Arabidopsis thaliana

A cDNA clone for a receptor-like protein kinase gene (RPK1) was isolated from Arabidopsis thaliana. The clone is 1952 bp long with 1623 bp of an open reading frame encoding a peptide of 540 amino acids. The deduced peptide (RPK1) contains four distinctive domains characteristic of receptor kinases: (a) a putative amino-terminal signal sequence domain; (b) a domain with five extracellular leucine-rich repeat sequences; (c) a membrane-spanning domain; and (d) a cytoplasmic protein kinase domain that contains all of the 11 subdomains conserved among protein kinases. The RPK1 gene is expressed in flowers, stems, leaves, and roots. Expression of the RPK1 gene is induced within 1 h after treatment with abscisic acid (ABA). The gene is also rapidly induced by several environmental stresses such as dehydration, high salt, and low temperature, suggesting that the gene is involved in a general stress response. The dehydration-induced expression is not impaired in aba-1, abi1–1, abi2–1, and abi3–1 mutants, suggesting that the dehydration-induced expression of the RPK1 gene is ABA-independent. A possible role of this gene in the signal transduction pathway of ABA and the environmental stresses is discussed.
App2Check: a Machine Learning-based System for Sentiment Analysis of App Reviews in Italian Language

Sentiment Analysis has nowadays a crucial role in social media analysis and, more generally, in analysing user opinions about general topics or user reviews about product/services, enabling a huge number of applications. Many methods and software implementing different approaches exist and there is not a clear best approach for Sentiment classification/quantification. We believe that performance reached by machine learning approaches is a key advantage to apply to sentiment analysis in order to reach a performance which is very close to the one obtained by group of humans, who evaluate subjective sentences such as user reviews. In this paper, we present the App2Check system, developed mainly applying supervised learning techniques, and the results of our experimental evaluation, showing that App2Check outperforms state-of-the-art research tools on user reviews in Italian language related to the evaluation of apps published to app stores.
Adaptive and iterative least squares support vector regression based on quadratic Renyi entropy

An adaptive and iterative LSSVR algorithm based on quadratic Renyi entropy is presented in this paper. LS-SVM loses the sparseness of support vector which is one of the important advantages of conventional SVM. The proposed algorithm overcomes this drawback. The quadratic Renyi entropy is the evaluating criterion for working set selection, and the size of working set is determined at the process of iteration adaptively. The regression parameters are calculated by incremental learning and the calculation of inversing a large scale matrix is avoided. So the running speed is improved. This algorithm reserves well the sparseness of support vector and improves the learning speed.
Non-Linear Data for Neural Networks Training and Testing

Highly nonlinear data sets are important in the field of artificial neural networks. It is not feasible to design a neural network and try to classify some real world data directly with that network. N-bit parity is one of the oldest data used to train and test neural networks. The simplest is the 2-bit parity also known as the XOR classification problem. Some researchers say that N-bit parity s set though highly nonlinear it is a simple task to learn by neural networks, others were drifted to tailor special purpose neural networks to solve only the N-bit parity problem without explaining why there is such a need. Is it possible to judge the N-bit parity is a simple data due to the fact that it can be modeled by a deterministic finite accepter? Moreover, should patterns that are in the form of context free which require a pushdown automaton, or context-sensitive and recursively enumerable that require a Turing machine be harder to learn by neural networks? The aim of this paper is to focus on and propose some complex nonlinear data to be used in training and testing of neural networks. The most important in these parity data is that the developer can tune the complexity of nonlinearity through various amounts of degrees; the user can select various numbers of categories, huge number of pattern samples, and many hybrid symbols. Testing for various neural networks and their generalization and ability to classify unseen patterns can be more effective. Experimental results on the classification of prime numbers showed that neural networks can learn the classification of prime numbers.
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images

The use of energy-minimizing curves, known as "snakes" to extract features of interest in images has been introduced by Kass, Witkin and Terzopoulos (1987). A balloon model was introduced by Cohen (1991) as a way to generalize and solve some of the problems encountered with the original method. A 3-D generalization of the balloon model as a 3-D deformable surface, which evolves in 3-D images, is presented. It is deformed under the action of internal and external forces attracting the surface toward detected edgels by means of an attraction potential. We also show properties of energy-minimizing surfaces concerning their relationship with 3-D edge points. To solve the minimization problem for a surface, two simplified approaches are shown first, defining a 3-D surface as a series of 2-D planar curves. Then, after comparing finite-element method and finite-difference method in the 2-D problem, we solve the 3-D model using the finite-element method yielding greater stability and faster convergence. This model is applied for segmenting magnetic resonance images. >
Tourism in Greece: Strategic Analysis and Challenges

This paper provides a strategic analysis of the competitiveness of Greek tourism. It illustrates the importance of tourism as an economic activity and analyses the current situation and structural problems of Greece as a destination. Although Greece offers unique nature, culture and heritage, the lack of differentiation of the tourism product as well as competitive disadvantages in marketing and planning cause an over-dependence on intermediaries for the promotion and distribution of the tourism product whilst jeopardising its quality. This affects the profitability and competitiveness of both the destination and its small and medium-sized tourism enterprises. The paper proposes a grand strategy as well as numerous strategic directions, objectives and tasks aiming to demonstrate the way ahead for Greek tourism. Several major opportunities emerge through the Olympic Games in 2004 as well as the major projects currently being undertaken which will enhance the infrastructure of the country. It is argued that a consistent tourism policy based on professional development and implemented through a Master Plan is urgently required. Strategies and methodologies need to be identified, whilst private enterprises need to increase their cooperation locally in order to enhance the quality and competitiveness of the product.
Parsing Images of Architectural Scenes

We address image parsing in the setting of architectural scenes. Our goal is to parse an image into regions of various types such as sky, foliage, buildings, and street. Furthermore we parse the building regions at a finer level of detail, identifying the positions of windows, doors, and rooflines, the colors of walls, and the spatial extent of particular buildings. Recognizing these individual elements is often impossible without the context provided by the initial parsing of the image, for instance a roofline is only defined in relation to the building below and the sky above. Our approach is driven by recognition of generic classes of visual appearance, e.g. for foliage. The generic recognition results boot-strap an image specific model that provides refined estimates to use for matting, segmentation, and more detailed parsing.
Small G protein Ral and its downstream molecules regulate endocytosis of EGF and insulin receptors

The involvement of Ral and its downstream molecules in receptor‐mediated endocytosis was examined. Expression of either RalG23V or RalS28N, which are known to be constitutively active and dominantnegative forms, respectively, in A431 cells blocked internalization of epidermal growth factor (EGF). Stable expression of RalG23V or RalS28N in CHO‐IR cells also inhibited internalization of insulin. Internalization of EGF and insulin was not affected by full‐length RalBP1 which is an effector protein of Ral, but was inhibited by its C‐terminal region which binds directly to Ral and POB1. POB1 is a binding protein of RalBP1 and has the Eps15 homology (EH) domain. Deletion mutants of POB1 inhibited internalization of EGF and insulin. However, internalization of transferrin was unaffected by Ral, RalBP1, POB1 and their mutants. Epsin and Eps15 have been reported to be involved in the regulation of endocytosis of the receptors for EGF and transferrin. The EH domain of POB1 bound directly to Epsin and Eps15. Taken together with the observation that EGF and insulin activate Ral, these results suggest that Ral, RalBP1 and POB1 transmit the signal from the receptors to Epsin and Eps15, thereby regulating ligand‐dependent receptor‐mediated endocytosis.