Miracle-dz/UniFAR-FTUs huggingface dataset:
Systemic administration of GPI 15427, a novel poly(ADP-ribose) polymerase-1 inhibitor, increases the antitumor activity of temozolomide against intracranial melanoma, glioma, lymphoma.

PURPOSE Temozolomide (TMZ) is a DNA methylating agent that has shown promising antitumor activity in recent clinical trials against high grade gliomas, metastatic melanoma, and brain lymphoma. In this study, we tested whether systemic administration of GPI 15427, a novel poly(ADP-ribose) polymerase (PARP-1) inhibitor capable of crossing the blood-brain barrier, could enhance the efficacy of TMZ against metastatic melanoma, glioblastoma multiforme, and lymphoma growing in the brain. EXPERIMENTAL DESIGN Murine B16 melanoma or L5178Y lymphoma cells were injected intracranially in syngeneic mice. An orthotopic xenograft of the human SJGBM2 glioblastoma multiforme was implanted in nude mice. Animals were treated with TMZ + GPI 15427 using a schedule of 40 mg/kg/i.v. GPI 15427 + 100 mg/kg/i.p. TMZ for 3 days. The efficacy of drug treatment was assessed by: (a) the increase of mouse survival and life span; and (b) the suppression of melanoma metastases to lung after i.v. injection of B16 cells. RESULTS In all models, systemic administration of GPI 15427 shortly before TMZ significantly increased life span of tumor-bearing mice with respect to untreated controls or to groups treated with either GPI 15427 or TMZ only. Moreover, GPI 15427 increased the antimetastatic effect of TMZ. CONCLUSIONS These data indicate that systemic administration of the poly(ADP-ribose) polymerase-1 inhibitor GPI 15427 significantly enhances TMZ antitumor efficacy against solid or hematological neoplasias even when located at the central nervous system site.
Time-frequency theta and delta measures index separable components of feedback processing in a gambling task.

Previous work using gambling tasks indicate that the feedback negativity (FN) reflects primary or salient stimulus attributes (often gain vs. loss), whereas the feedback-P300 appears sensitive to secondary stimulus information. A recent time-frequency approach has characterized separable theta (3-7 Hz) and delta (0-3 Hz) feedback processes, independently sensitive to primary feedback attributes, specifically loss and gain outcomes, respectively. The current study extends this time-frequency work to evaluate both primary and secondary (relative outcome and outcome magnitude) feedback attributes. Consistent with previous reports, theta indexed an initial, lower-level response sensitive to the primary (most salient) feedback attributes (specifically losses), while delta was sensitive to both primary attributes (specifically gains) and assessed secondary stimulus features.
Soft matrix is a natural stimulator for cellular invasiveness

ECM softness (low stiffness comparable to soft tissues) alone is sufficient to prevent cell-to-cell adherens junction formation, up-regulate MMP secretion, promote MMP activity, and induce invadosome-like protrusion formation. Such findings suggest that cell invasion in vivo is a spontaneous cell behavior in response to ECM stiffness.
A Bayesian Sampling Approach to Exploration in Reinforcement Learning

We present a modular approach to reinforcement learning that uses a Bayesian representation of the uncertainty over models. The approach, BOSS (Best of Sampled Set), drives exploration by sampling multiple models from the posterior and selecting actions optimistically. It extends previous work by providing a rule for deciding when to re-sample and how to combine the models. We show that our algorithm achieves near-optimal reward with high probability with a sample complexity that is low relative to the speed at which the posterior distribution converges during learning. We demonstrate that BOSS performs quite favorably compared to state-of-the-art reinforcement-learning approaches and illustrate its flexibility by pairing it with a non-parametric model that generalizes across states.
Detecting Network Effects: Randomizing Over Randomized Experiments

Randomized experiments, or A/B tests, are the standard approach for evaluating the causal effects of new product features, i.e., treatments. The validity of these tests rests on the "stable unit treatment value assumption" (SUTVA), which implies that the treatment only affects the behavior of treated users, and does not affect the behavior of their connections. Violations of SUTVA, common in features that exhibit network effects, result in inaccurate estimates of the causal effect of treatment. In this paper, we leverage a new experimental design for testing whether SUTVA holds, without making any assumptions on how treatment effects may spill over between the treatment and the control group. To achieve this, we simultaneously run both a completely randomized and a cluster-based randomized experiment, and then we compare the difference of the resulting estimates. We present a statistical test for measuring the significance of this difference and offer theoretical bounds on the Type I error rate. We provide practical guidelines for implementing our methodology on large-scale experimentation platforms. Importantly, the proposed methodology can be applied to settings in which a network is not necessarily observed but, if available, can be used in the analysis. Finally, we deploy this design to LinkedIn's experimentation platform and apply it to two online experiments, highlighting the presence of network effects and bias in standard A/B testing approaches in a real-world setting.
Automatic Correction of Range Migration in SAR Imaging

A new technique is developed for the automatic correction of range migration in synthetic aperture radar imaging. In the range-Doppler domain, samples at a Doppler frequency constitute a Doppler slice. It is noted that, when there is no range migration, the Doppler slices have similar envelopes, i.e., the envelope of one Doppler slice roughly equals the envelope of another Doppler slice multiplied by a constant. Thus, range migration can be corrected by shifting the Doppler slices such that their envelopes are similar. The technique applies even when the radar moves irregularly or the target is moving.
Relaxin Ameliorates Hypertension and Increases Nitric Oxide Metabolite Excretion in Angiotensin II But Not N&ohgr;-Nitro-L-Arginine Methyl Ester Hypertensive Rats

Previous findings suggest a potential therapeutic action of relaxin, the putative vasodilatory signal of normal pregnancy, in some forms of cardiovascular disease. However, the mechanisms underlying the beneficial effects of relaxin have not been fully elucidated. The purpose of this study was to determine whether the vasodilatory effects of relaxin are dependent on activation of NO synthase. We examined the effect of relaxin in male Sprague-Dawley rats given angiotensin II (Ang II; 200 ng/kg per minute SC by minipump), the NO synthase inhibitor N&ohgr;-nitro-L-arginine methyl ester (L-NAME; 1.5 mg/100 g IV followed by 150 mg/L in drinking water), or vehicle for 3 weeks. After 7 days of Ang II or L-NAME, mean arterial pressure was elevated compared with baseline. Relaxin was administered (4 &mgr;g/h, SC by minipump) for the next 2 weeks of Ang II, L-NAME, or vehicle treatment. Two-week relaxin treatment alone slightly reduced mean arterial pressure in normotensive rats. Three weeks of either Ang II or L-NAME treatment alone produced hypertension, albuminuria, mild glomerular sclerosis, reduced nitric oxide metabolite excretion, and increased oxidative stress (excretion of hydrogen peroxide and thiobarbituric acid reactive substances and renal cortex nitrotyrosine abundance). Relaxin reduced mean arterial pressure, albumin excretion, and oxidative stress markers and preserved glomerular structure and nitric oxide metabolite excretion in Ang II–treated rats; however, relaxin did not attenuate these changes in the rats treated with L-NAME. None of the treatments affected protein abundance of neuronal or endothelial NO synthase in the kidney cortex. These data suggest that the vasodilatory effects of relaxin are dependent on a functional NO synthase system and increased NO bioavailability possibly because of a reduction in oxidative stress.
Fully Automatic Brain Tumor Segmentation from Multiple MR Sequences using Hidden Markov Fields and Variational

GAIN is an enhanced version of the original Grouping Artificial Immune Network that was developed for fully automated MRI brain segmentation. The model captures the main concepts by which the immune system recognizes pathogens and models the process in a numerical form. GAIN was adapted to support a variable number of input patterns for training and segmentation of tumors in MRI brain images and adapted to train on multiple images. The model was demonstrated to operate with multi-spectral MR data with an increase in accuracy compared to the single spectrum case. Using the BRATS High Grade 2013 dataset with the 2012 tissue labels for Edema and Tumor, the model’s Dice scores were compared to published results and proved to be as accurate as the best methods. Using the 4 labels from the BRATS 2013 data sets, a Dice overlap of 73% for the complete tumor region and 64% for the enhancing tumor region were obtained for the high grade BRATS images when applying preand post-processing. This was attained with speed optimizations allowing segmentation at 21s per case with post-processing of all 4 tissues.
Using a Blackboard to Integrate Multiple Activities and Achieve Strategic Reasoning for Mobile-Robot Navigation

We have designed a mobile robot system architecture that uses a blackboard to coordinate and integrate several real time activities. An activity is an organizational unit, or module, designed to perform a specific function, such as traversing a hallway, going down steps, crossing over an open channel on the floor, or tracking a landmark. An activity resembles a behavior in that it controls the robot to perform a specific task. It differs from a behavior in that it is designed to perform the specific task in a narrow application domain, whereas a behavior generally resembles a biological response-that is, an organism's response to a stimulus. The activity based blackboard system consists of two hierarchical layers for strategic and reactive reasoning: a blackboard database to keep track of the state of the world and a set of activities to perform real time navigation. >
Distributed algorithms for dynamic replication of data

We present two distributed algorithms for dynamic replication of a data-item in communication networks. The algorithms are adaptive in the sense that they change the replication scheme of the item (i.e. the set of processors at which the data-item is replicated), as the read-write pattern of the processors in the network changes. Each algorithm continuously moves the replication scheme towards an optimal one, where optimality is defined with respect to different objective functions. One algorithm optimizes the communication cost objective function, and the other optimizes the communication time. We also provide a lower bound on the performance of any dynamic replication algorithm.
Thrombotic thrombocytopenic purpura in a patient with systemic lupus erythematosus.

A case is presented of a 38-year-old woman who had been diagnosed ten years earlier as having systemic lupus erythematosus (SLE). She presented with classical signs and symptoms of thrombotic thrombocytopenic purpura (TTP). Plasmapheresis and prednisone treatment resulted in a complete remission. Possible associations with connective tissue diseases are reviewed.
Finding cycles and trees in sublinear time

We present sublinear‐time (randomized) algorithms for finding simple cycles of length at least k≥3 and tree‐minors in bounded‐degree graphs. The complexity of these algorithms is related to the distance of the graph from being Ck‐minor free (resp., free from having the corresponding tree‐minor). In particular, if the graph is Ω(1) ‐far from being cycle‐free (i.e., a constant fraction of the edges must be deleted to make the graph cycle‐free), then the algorithm finds a cycle of polylogarithmic length in time O˜(N) , where N denotes the number of vertices. This time complexity is optimal up to polylogarithmic factors.
Intratumoral Vascular Shunting: Biomarker of Clinical Outcome and Source of Circulating Tumor Cells?

Predicting which patients will benefit from radioembolization remains a challenge, as reliable prognostic indicators are not defined. Abnormal tumor vascular anatomy could not only impact the ability of cancer therapies to penetrate tumors, but may also contribute to a lesion’s metastatic potential. Specifically, intratumoral vascular shunts could allow circulating tumor cells to initiate metastases by allowing them to gain access to distant sites in the body, bypassing capillary beds. Here, we describe how tumoral angiogenesis occurs and how intratumoral vascular shunts may form.
Role of trust in e-business success

Success of an e‐business rests on many factors. One of the important contributors is trust. Trust is something that an e‐business must strive to achieve over a period of time. Acquiring customer trust depends on many things that an e‐business controls. However, customer's trust as such is not under the control of the e‐business. Some contributing factors for gaining customer trust are: appeal of the Web site, product or service offerings, branding, quality of service and trusted seals. Trust can be viewed from many angles such as transaction, information content, product, technology and institution. This paper analyses the role of trust from the transaction perspective and highlights the things that an e‐business could do for building customer trust.
VOTER INEQUALITY, TURNOUT AND INFORMATION EFFECTS IN A CROSS-NATIONAL PERSPECTIVE

The paper empirically tests the proposition that because of the unequal social distribution of politically relevant resources, some groups of citizens may be less successful in expressing their specifically political preferences in the vote than others. Hence, the electoral arena may give different people different degrees of political influence even when the formal equality of all citizens before the law is rigorously upheld in the electoral process. Survey data on voting behavior in 18 democratic party systems from the Comparative Study of Electoral Systems and Larry Bartels’s (1996) simulation procedure—now extended to the analysis of multiparty-systems, turnout effects and nonlinear information effects on the vote—are utilized to explore the question. The results show that social differences in both turnout and political knowledge may lead to the hypothesized political inequalities but their size is remarkably modest.
Ophiocerol, a novel macrocylic neolignan from the aquatic fungus Ophioceras dolichostomum YMF1.00988

From cultural filtrates of the freshwater fungus Ophioceras dolichostomum YMF1.00988 a novel neolignan with an unprecedented dibenzo-1,6-dioxacyclodecane carbon skeleton, ophiocerol (1), was isolated, and the known compounds isoamericanoic acid A (2) and caffeic acid (3) were identified. The structure of the novel compound was determined by interpretation of its spectroscopic data, including 1D and 2D, 1H and 13C NMR (COSY, HMQC, HMBC, NOESY), and MS. Compounds 1–3 were assayed for their nematicidal activity against Bursaphelenchus xylophilus as well as their antifungal activity against several plant pathogen fungi.
Revealing In-Block Nestedness: detection and benchmarking

As new instances of nested organization-beyond ecological networks-are discovered, scholars are debating the coexistence of two apparently incompatible macroscale architectures: nestedness and modularity. The discussion is far from being solved, mainly for two reasons. First, nestedness and modularity appear to emerge from two contradictory dynamics, cooperation and competition. Second, existing methods to assess the presence of nestedness and modularity are flawed when it comes to the evaluation of concurrently nested and modular structures. In this work, we tackle the latter problem, presenting the concept of in-block nestedness, a structural property determining to what extent a network is composed of blocks whose internal connectivity exhibits nestedness. We then put forward a set of optimization methods that allow us to identify such organization successfully, in synthetic and in a large number of real networks. These findings challenge our understanding of the topology of ecological and social systems, calling for new models to explain how such patterns emerge.
RFID Distance Bounding Protocols with Mixed Challenges

RFID systems suffer from different location-based attacks such as distance fraud, mafia fraud, and terrorist fraud. Among them mafia fraud is the most serious one as it can be mounted without the awareness of neither the reader nor the tag. In such an attack, the adversary acts as a man-in-the-middle who relays the signal between the two entities, possibly without knowing the specifications of the protocol used on the channel. Recently, distance bounding protocols measuring the round-trip times of messages exchanged between the reader and the tag have been designed to prevent this attack. Almost all the existing proposals are based on binary challenges, with no final signature, and provide a mafia fraud success probability equal to (3/4)n, where n is the number of rounds in the protocol, or require too much memory. In this article, we introduce new distance bounding protocols, based on binary mixed challenges, that converge toward the expected and optimal (1/2)n bound and which only require little memory.
Mining User Intentions from Medical Queries: A Neural Network Based Heterogeneous Jointly Modeling Approach

Text queries are naturally encoded with user intentions. An intention detection task tries to model and discover intentions that user encoded in text queries. Unlike conventional text classification tasks where the label of text is highly correlated with some topic-specific words, words from different topic categories tend to co-occur in medical related queries. Besides the existence of topic-specific words and word order, word correlations and the way words organized into sentence are crucial to intention detection tasks. In this paper, we present a neural network based jointly modeling approach to model and capture user intentions in medical related text queries. Regardless of the exact words in text queries, the proposed method incorporates two types of heterogeneous information: 1) pairwise word feature correlations and 2) part-of-speech tags of a sentence to jointly model user intentions. Variable-length text queries are first inherently taken care of by a fixed-size pairwise feature correlation matrix. Moreover, convolution and pooling operations are applied on feature correlations to fully exploit latent semantic structure within the query. Sentence rephrasing is finally introduced as a data augmentation technique to improve model generalization ability during model training. Experiment results on real world medical queries have shown that the proposed method is able to extract complete and precise user intentions from text queries.
Masking unmasked

The practice of masking the eyes when publishing clinical photographs has been used for many years in an attempt to make a person unidentifiable. Until recently, journal editors and authors concentrated on achieving anonymity, rather than gaining consent from patients, before publishing photographs showing clinical conditions. This is now considered to be unacceptable because it is almost impossible to make a patient completely anonymous and so fully informed consent should be obtained from patients before publishing clinical photographs. The Good practice in consent implementation guide published by the Department of Health also says that if a recording or photograph of a patient is to be used for any purpose other than the patient’s care, then written, informed consent must be sought from them. Informed consent for this purpose would mean giving the patient all of the relevant information to help him or her make an informed decision such as the medium, place and date of publication, and who is the likely audience. However, a quick look through a selection of current journals held in any medical library will show that eye-masking is still widely used. This study investigates the effectiveness of eye-masking in obscuring identity.
Structure, Stability, and Aggregation of Paired Helical Filaments from Tau Protein and FTDP-17 Mutants Probed by Tryptophan Scanning Mutagenesis*

By using tryptophan scanning mutagenesis, we observed the kinetics and structure of the polymerization of tau into paired helical filaments (PHFs) independently of exogenous reporter dyes. The fluorescence exhibits pronounced blue shifts due to burial of the residue inside PHFs, depending on Trp position. The effect is greatest near the center of the repeat domain, showing that the packing is tightest near the β-structure inducing hexapeptide motifs. The tryptophan response allows measurement of PHF stability made by different tau isoforms and mutants. Unexpectedly, the stability of PHFs is quite low (denaturation half-points ∼1.0 m GdnHCl), implying that incipient aggregation should be reversible and that the observed high stability of Alzheimer PHFs is due to other factors. The stability increases with the number of repeats and with tau mutants promoting β-structure, arguing for a gain of toxic function in frontotemporal dementias. Fluorescence resonance energy transfer (FRET) was used to analyze the distances of Tyr310 to tryptophans in different positions. The degree of FRET in the soluble protein was position-dependent, with highest signals within the second and third repeats but low or no signals further away. In PHFs most mutants showed FRET, indicating that tight packing results from assembly of tau into PHFs.
An Autonomic Neuroprosthesis: Noninvasive Electrical Spinal Cord Stimulation Restores Autonomic Cardiovascular Function in Individuals with Spinal Cord Injury

Abstract Despite autonomic dysfunction after spinal cord injury (SCI) being the major cause of death and a top health priority, the clinical management options for these conditions are limited to drugs with delayed onset and nonpharmacological interventions with equivocal effectiveness. We tested the capacity of electrical stimulation, applied transcutaneously over the spinal cord, to manage autonomic dysfunction in the form of orthostatic hypotension after SCI. We assessed beat-by-beat blood pressure (BP), stroke volume, and cardiac contractility (dP/dt; Finometer), as well as cerebral blood flow (transcranial Doppler) in 5 individuals with motor-complete SCI (4 cervical, 1 thoracic) during an orthostatic challenge with and without transcutaneous electrical stimulation applied at the TVII level. During the orthostatic challenge, all individuals experienced hypotension characterized by a 37 ± 4 mm Hg decrease in systolic BP, a 52 ± 10% reduction in cardiac contractility, and a 23 ± 6% reduction in cerebral blood flow (all p < 0.05), along with severe self-reported symptoms. Electrical stimulation completely normalized BP, cardiac contractility, cerebral blood flow, and abrogated all symptoms. Noninvasive transcutaneous electrical spinal cord stimulation may be a viable therapy for restoring autonomic cardiovascular control after SCI.