Miracle-dz/UniFAR-FTUs huggingface dataset:
Melanoma Cells Homing to the Brain: An In Vitro Model

We developed an in vitro contact through-feet blood brain barrier (BBB) model built using type IV collagen, rat astrocytes, and human umbilical vein endothelial cells (HUVECs) cocultured through Transwell porous polycarbonate membrane. The contact between astrocytes and HUVECs was demonstrated by electron microscopy: astrocytes endfeet pass through the 8.0 μm pores inducing HUVECs to assume a cerebral phenotype. Using this model we evaluated transmigration of melanoma cells from two different patients (M1 and M2) selected among seven melanoma primary cultures. M2 cells showed a statistically significant higher capability to pass across the in vitro BBB model, compared to M1. Expression of adhesion molecules was evaluated by flow cytometry: a statistically significant increased expression of MCAM, αvβ3, and CD49b was detected in M1. PCR array data showed that M2 had a higher expression of several matrix metalloproteinase proteins (MMPs) compared to M1. Specifically, data suggest that MMP2 and MMP9 could be directly involved in BBB permeability and that brain invasion by melanoma cells could be related to the overexpression of many MMPs. Future studies will be necessary to deepen the mechanisms of central nervous system invasion.
Schemes for learning and behaviour : a new expectancy model

This thesis presents a novel form of learning by reinforcement. Existing reinforcement learning algorithms rely on the provision of external reward signals to drive the learning algorithm. This new algorithm relies on reinforcing signals generated internally within the algorithm. The algorithm, SRS/E, described here generates expectancies ( -hypotheses), each of which gives rise to a specific prediction when the conditions relevant to the expectancy are encountered (the -experiment). The algorithm subsequently tests these predictions against actual events and so generates reinforcement signals to corroborate or reject individual expectancies. This procedure allows for self-contained, completely unsupervised learning to an extent not possible with previous reinforcement procedures. The SRS/E algorithm is derived from a number of postulates that constitute a new Dynamic Expectancy Model developed in this thesis. In contrast to the static policy map generated by existing Q-learning based reinforcement algorithms, which limit learning to one goal, the SRS/E algorithm generates a Dynamic Policy Map (DPM) from learned expectancies whenever a new goal is selected by the system. This new approach retains the advantages of reactivity to the environment inherent in existing reinforcement algorithms, while substantially increasing the system’s flexibili ty in responding to varying circumstances and requirements. Also in contrast to previous reinforcement systems, goals may be selected arbitrarily and are not limited to those which were associated with reward during the learning steps. This new method allows multiple goals to be pursued either simultaneously or sequentially. The single SRS/E implementation has been compared directly to the published results from of a family of reinforcement based algorithms, Dyna-PI, Dyna-Q and Dyna-Q+ (Sutton, 1990), themselves extensions to the groundbreaking Q-learning algorithm (Watkins, 1989). Under equivalent “ ideal learning conditions” the SRS/E algorithm was found to outperform the equivalent Dyna reinforcement program to learn a simple maze task by a factor of some 40:1. The SRS/E learning algorithm was also found to be robust when tested under controlled “noise” conditions. SRS/E was also compared directly to Sutton’s Dyna-Q+ algorithm on a range of alternative path and route blocking tasks and was found to offer a similar performance, but SRS/E employs a “biologically plausible” extinction mechanism, mirroring findings from animal behaviour research. Finally SRS/E was tested with experimental designs for “ latent learning” and “place learning”, drawn directly from animal learning research. Both are regarded as presenting severe challenges to conventional reinforcement learning theories. SRS/E performs well on both tasks, and in a manner consistent with findings from animal experiments.
A design life-cycle for the formal design of user interfaces

This paper aims at clarifying the articulation between the task models and system models encountered in CHI design practices. We demonstrate how the use of a formal task model may enhance the design of interactive systems, by providing quantitative results on which designers may base their decisions. We also demonstrate that it is possible to describe both task and system models within the same formal framework. This enables us firstly to formally prove that task and system models comply with each other, and secondly to perform quantitative analysis on the combination of task and system models. We propose a software design life cycle integrating formal task and system modelling. The approach is illustrated by a toy example which, despite its small size, allows us to develop both task and device models and to perform several iterations on the life cycle. The device and tasks are modelled using the Interactive Cooperative Objects (ICO) formalism, which is based on Petri nets and on the object-oriented approach. The formality of Petri nets allows for axiomatic validation of isolated and interacting subsystems.
Ribosomal S6 Kinase 2 (RSK2) Maintains Genomic Stability by Activating the Atm/p53-Dependent DNA Damage Pathway

Ribosomal S6 Kinase 2 (RSK2) is a member of the p90RSK family of serine/threonine kinases, which are widely expressed and respond to many growth factors, peptide hormones, and neurotransmitters. Loss-of function mutations in the RPS6KA3 gene, which encodes the RSK2 protein, have been implicated in Coffin-Lowry Syndrome (CLS), an X-linked mental retardation disorder associated with cognitive deficits and behavioral impairments. However, the cellular and molecular mechanisms underlying this neurological disorder are not known. Recent evidence suggests that defective DNA damage signaling might be associated with neurological disorders, but the role of RSK2 in the DNA damage pathway remains to be elucidated. Here, we show that Adriamycin-induced DNA damage leads to the phosphorylation of RSK2 at Ser227 and Thr577 in the chromatin fraction, promotes RSK2 nuclear translocation, and enhances RSK2 and Atm interactions in the nuclear fraction. Furthermore, using RSK2 knockout mouse fibroblasts and RSK2-deficient cells from CLS patients, we demonstrate that ablation of RSK2 impairs the phosphorylation of Atm at Ser1981 and the phosphorylation of p53 at Ser18 (mouse) or Ser15 (human) in response to genotoxic stress. We also show that RSK2 affects p53-mediated downstream cellular events in response to DNA damage, that RSK2 knockout relieves cell cycle arrest at the G2/M phase, and that an increased number of γH2AX foci, which are associated with defects in DNA repair, are present in RSK2-deficient cells. Taken together, our findings demonstrated that RSK2 plays an important role in the DNA damage pathway that maintains genomic stability by mediating cell cycle progression and DNA repair.
Peripheral Nerve Stimulation in Regional Anesthesia

Abstract Peripheral nerve stimulation has a long history in regional anesthesia. Despite the advent of ultrasound-guided peripheral nerve blockade, nerve stimulation remains a popular technique used alone or, now, in combination with ultrasound-guided techniques. In light of this evolving utility of nerve stimulation, this is an appropriate time to review the basic concepts and knowledge base of this historically important tool. Electrical nerve stimulation facilitates nerve localization, using threshold current as a surrogate for needle-to-nerve distance. Preferential activation of motor nerves is possible because motor nerve fibers are more readily activated with a shorter duration of current compared with sensory nerves. The association between current and needle-to-nerve distance predicts that less current is needed to evoke a motor response as the needle moves closer to the nerve. Thus, an elicited motor response at or below 0.5 mA is considered a common end point for successful neural blockade. However, current magnitude is neither 100% sensitive nor specific. Independent of technical ability, both the biological environment and the equipment used impact the current-distance relationship. Thus, successful electrical nerve stimulation is dependent on an anesthesiologist with a solid foundation in anatomy and a thorough understanding of electrophysiology.
Linear Prediction Using Refined Autocorrelation Function

This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.
The Yeast Proteome Database (YPD) and Caenorhabditis elegans Proteome Database (WormPD): comprehensive resources for the organization and comparison of model organism protein information

The Yeast Proteome Database (YPDtrade mark) has been for several years a resource for organized and accessible information about the proteins of Saccharomyces cerevisiae. We have now extended the YPD format to create a database containing complete proteome information about the model organism Caenorhabditis elegans (WormPDtrade mark). YPD and WormPD are designed for use not only by their respective research communities but also by the broader scientific community. In both databases, information gleaned from the literature is presented in a consistent, user-friendly Protein Report format: a single Web page presenting all available knowledge about a particular protein. Each Protein Report begins with a Title Line, a concise description of the function of that protein that is continually updated as curators review new literature. Properties and functions of the protein are presented in tabular form in the upper part of the Report, and free-text annotations organized by topic are presented in the lower part. Each Protein Report ends with a comprehensive reference list whose entries are linked to their MEDLINE s. YPD and WormPD are seamlessly integrated, with extensive links between the species. They are freely accessible to academic users on the WWW at http://www. proteome.com/databases/index.html, and are available by subscription to corporate users.
A 12-Bit 32 /spl mu/W Ratio-Independent Algorithmic ADC

This paper describes a ratio-independent algorithmic ADC architecture that requires a single differential amplifier and a comparator. The prototype 12-bit, 41.67 kS/s ADC with an active die area of 0.055 mm2 is implemented in a 0.13mum CMOS. The power dissipation is minimized using a dynamically biased operational amplifier. With a 32 muW power dissipation, the ADC achieves 80 dB SFDR and 60 dB SNDR, resulting in a power FOM of 0.9 pJ/conversion
Translation Model Adaptation by Resampling

The translation model of statistical machine translation systems is trained on parallel data coming from various sources and domains. These corpora are usually concatenated, word alignments are calculated and phrases are extracted. This means that the corpora are not weighted according to their importance to the domain of the translation task. This is in contrast to the training of the language model for which well known techniques are used to weight the various sources of texts. On a smaller granularity, the automatic calculated word alignments differ in quality. This is usually not considered when extracting phrases either. In this paper we propose a method to automatically weight the different corpora and alignments. This is achieved with a resampling technique. We report experimental results for a small (IWSLT) and large (NIST) Arabic/English translation tasks. In both cases, significant improvements in the BLEU score were observed.
Command strokes with and without preview: using pen gestures on keyboard for command selection

This paper presents a new command selection method that provides an alternative to pull-down menus in pen-based mobile interfaces. Its primary advantage is the ability forusers to directly select commands from a very large set without the need to traverse menu hierarchies. The proposed method maps the character strings representing the commands onto continuous pen-traces on a stylus keyboard. The user enters a command by stroking part of its character string. We call this method "command strokes. " We present the results of three experiments assessing the usefulness of the technique. The first experiment shows that command strokes are 1.6 times faster than the de-facto standard pull-down menus and that users find command strokes more fun to use. The second and third experiments investigate the effect of displaying a visual preview of the currently recognized command while the user is still articulating the command stroke. These experiments show that visual preview does not slow users down and leads to significantly lower error rates and shorter gestures when users enter new unpracticed commands.
Profit-Seeking Motives and Racist Policy in Tennessee’s Criminal Justice System: A Triangulative Analysis

Using triangulative research methodology, this article examines the impact of the criminal justice system and the prison industrial complex on disenfranchised African Americans and social inequality in Tennessee. The investigation critically examines the ethically questionable public-private business relationships and other arrangements that contribute to socially constructed economic policy instruments used to fulfill conservatives’ and White supremacists’ objectives for continual White domination in Tennessee. The substantive findings reveal how the criminal justice system impacts political, economic, and social inequality in the African American community. Due to their considerably diminished capabilities to achieve political and economic equality, one of the recommendations of the study is that streamlining the voting restoration process is necessary for rectifying felony disenfranchised, thereby restoring a fundamental ethos of citizenship to those who have lost their right to vote.
Novel Endogenous, Insulin-Stimulated Akt2 Protein Interaction Partners in L6 Myoblasts

Insulin resistance and Type 2 diabetes are marked by an aberrant response in the insulin signaling network. The phosphoinositide-dependent serine/threonine kinase, Akt2, plays a key role in insulin signaling and glucose uptake, most notably within skeletal muscle. Protein-protein interaction regulates the functional consequence of Akt2 and in turn, Akt2’s role in glucose uptake. However, only few insulin-responsive Akt2 interaction partners have been identified in skeletal muscle cells. In the present work, rat L6 myoblasts, a widely used insulin sensitive skeletal muscle cell line, were used to examine endogenous, insulin-stimulated Akt2 protein interaction partners. Akt2 co-immunoprecipitation was coupled with 1D-SDS-PAGE and fractions were analyzed by HPLC-ESI-MS/MS to reveal Akt2 protein-protein interactions. The pull-down assay displayed specificity for the Akt2 isoform; Akt1 and Akt3 unique peptides were not detected. A total of 49 were detected with a significantly increased (47) or decreased (2) association with Akt2 following insulin administration (n = 4; p<0.05). Multiple pathways were identified for the novel Akt2 interaction partners, such as the EIF2 and ubiquitination pathways. These data suggest that multiple new endogenous proteins may associate with Akt2 under basal as well as insulin-stimulated conditions, providing further insight into the insulin signaling network. Data are available via ProteomeXchange with identifier PXD002557.
Diffuse large B-cell lymphoma of the breast: prognostic factors and treatment outcomes

Background The breast is a rare site of extranodal involvement of diffuse large B-cell lymphoma (DLBCL). We aimed to assess the clinical characteristics, prognostic factors, and treatment outcomes of breast DLBCL. Patients and methods We retrospectively analyzed 113 patients (from our institution and the literature) between 1973 and 2014. The primary end point was overall survival (OS). Kaplan–Meier OS curves were compared with the log-rank test. Cox regression analysis was applied to determine the prognostic factors for OS, progression-free survival (PFS), local control (LC), and cause-specific survival (CSS). Results A total of 113 patients were included in the study: 42 cases from our hospital and 71 cases from 12 publications. The median age at diagnosis was 58 years. With a median follow-up time of 39.2 months, the estimated 5-year OS, PFS, LC, and CSS were 71.4%, 58.8%, 75.6%, and 74.9%, respectively. In multivariate analysis, more than four cycles of chemotherapy, having localized cancer, lumpectomy with or without axillary lymph node (ALN) dissection, and low to low-to-intermediate International Prognostic Index were favorable factors for OS. For PFS, significant prognostic factors were rituximab use, B symptoms, and tumor size. As for the local group, lumpectomy with or without ALN dissection and more than four cycles of chemotherapy were favorable factors for OS. Tumor size >4 cm and nonuse of rituximab were adverse factors for PFS. Twenty-one patients (18.6%) developed local relapse and 33 (29.2%) developed systemic relapse. Eight patients had central nervous system relapse (7.3%). Conclusion Our results reveal that local and extended staging criteria can reflect the different prognosis and treatment outcomes of breast DLBCL. Rituximab use, lumpectomy, and more than four cycles of chemotherapy are recommended as a treatment regimen. However, further study is warranted to validate our data.
Intelligent mesh scissoring using 3D snakes

Mesh partitioning and parts extraction have become key ingredients for many mesh manipulation applications both manual and automatic. In this paper, we present an intelligent scissoring operator for meshes which supports both automatic segmentation and manual cutting. Instead of segmenting the mesh by clustering, our approach concentrates on finding and defining the contours for cutting. This approach is based on the minima rule, which states that human perception usually divides a surface into parts along the contours of concave discontinuity of the tangent plane. The technique uses feature extraction to find such candidate feature contours. Subsequently, such a contour can be selected either automatically or manually, or the user may draw a 2D line to start the scissoring process. The given open contour is completed to form a loop around a specific part of the mesh, and this loop is used as the initial position of a 3D geometric snake. The snake moves by relaxation until it settles to define the final scissoring position. This process uses several fundamental geometric mesh attributes, such as curvature and centricity, and enables both automatic segmentation and an easy-to-use intelligent-scissoring operator.
Simultaneous analysis of ion and electron heat transport by power modulation in JET

Heating power modulation experiments using ion cyclotron resonance heating (ICRH) in the 3He minority scheme have been performed in the JET tokamak to investigate heat transport properties. This RF scheme provides a dominant localized ion heating, but also some electron heating, and therefore both ion and electron heat channels were modulated. This allows us to carry out a simultaneous transport analysis of ion and electron heat transport channels, including transient transport phenomena. This also provides an experimental assessment of the ICRH heat sources of the 3He scheme. The modulation approach, so far widely used for electron transport studies, has been validated for ion heat transport in these experiments and yields results on stiffness and threshold of the ion temperature gradient (ITG)-driven ion heat transport. The results for the electron channel demonstrate the importance of the ITG-driven, off-diagonal, contribution to electron heat transport in plasmas with significant ion heating.
Quantum corrections to the kinetic term in the Randall-Sundrum model

The effective action of the radion in the Randall–Sundrum model is analysed. When one loop effects stabilize the radion field, the cosmological evolution can be derived from a simple Friedman equation. Fine tunings are still needed to obtain the observed mass hierarchy and an invisible radion. Since kinetic terms are important for determining the radion mass, the finite quantum corrections from massless conformally coupled fermions are analysed and found to vanish at one loop order.
POSTER: Self-Healing Mechanisms for Software-Defined Networks

Operators perceive programmable networks brought by Software Defined Networks (SDN) as cornerstone to decrease the time to deploy new services, to augment the flexibility and to adapt network resources to customer needs at runtime. However, despite the vulnerabilities identified due that the intelligence is centralized on SDN, its research is more centered on forwarding traffic and reconfiguration issues, not considering to a great extent the fault management aspects of the control plane. This paper provides SDN with fault management capabilities by using autonomic principles like self-healing mechanisms. We propose a generic self-healing approach that relies on a Bayesian Networks for the diagnosis block and we applied this algorithm to a centralized SDN infrastructure to prove its functioning in the presence of faults.