Miracle-dz/UniFAR-FTUs huggingface dataset:
RSK2 Protein Suppresses Integrin Activation and Fibronectin Matrix Assembly and Promotes Cell Migration*

Background: RSK2 alters cell migration and metastasis, but the mechanism is incompletely understood. Results: RSK2 inactivates integrins, increases filamin binding to integrin tails, alters actin distribution, increases migration, and decreases fibronectin matrix assembly. Conclusion: RSK2 mediates inactivation of integrins and thus modulates integrin functions. Significance: These findings provide a novel mechanism by which RSK2 affects migration and may lead to more selective ways to inhibit RSK2-dependent metastasis. Modulation of integrin activation is important in many cellular functions including adhesion, migration, and assembly of the extracellular matrix. RSK2 functions downstream of Ras/Raf and promotes tumor cell motility and metastasis. We therefore investigated whether RSK2 affects integrin function. We report that RSK2 mediates Ras/Raf inactivation of integrins. As a result, we find that RSK2 impairs cell adhesion and integrin-mediated matrix assembly and promotes cell motility. Active RSK2 appears to affect integrins by reducing actin stress fibers and disrupting focal adhesions. Moreover, RSK2 co-localizes with the integrin activator talin and is present at integrin cytoplasmic tails. It is thereby in a position to modulate integrin activation and integrin-mediated migration. Activation of RSK2 promotes filamin phosphorylation and binding to integrins. We also find that RSK2 is activated in response to integrin ligation to fibronectin. Thus, RSK2 could participate in a feedback loop controlling integrin function. These results reveal RSK2 as a key regulator of integrin activity and provide a novel mechanism by which it may promote cell migration and cancer metastasis.
Measurement Errors in Investment Equations

We use Monte Carlo simulations and real data to assess the performance of alternative methods that deal with measurement error in investment equations. Our experiments show that individual-fixed effects, error heteroscedasticity, and data skewness severely affect the performance and reliability of methods found in the literature. In particular, estimators that use higher-order moments are shown to return biased coefficients for (both) mismeasured and perfectly-measured regressors. These estimators are also very inefficient. Instrumental variables-type estimators are more robust and efficient, although they require fairly restrictive assumptions. We estimate empirical investment models using alternative methods. Real-world investment data contain firm-fixed effects and heteroscedasticity, causing high-order moments estimators to deliver coefficients that are unstable across different specifications and not economically meaningful. Instrumental variables methods yield estimates that are robust and seem to conform to theoretical priors. Our analysis provides guidance for dealing with the problem of measurement error under circumstances empirical researchers are likely to find in practice.
Brain responses in evaluating feedback stimuli with a social dimension

Previous studies on outcome evaluation and performance monitoring using gambling or simple cognitive tasks have identified two event-related potential (ERP) components that are particularly relevant to the neural responses to decision outcome. The feedback-related negativity (FRN), typically occurring 200–300 ms post-onset of feedback stimuli, encodes mainly the valence of outcome while the P300, which is the most positive peak between 200–600 ms, is related to various aspects of outcome evaluation. This study investigated the extent to which neural correlates of outcome evaluation involving perceptually complex feedback stimuli (i.e., female faces) are similar to those elicited by simple feedback. We asked participants to judge the attractiveness of blurred faces and then showed them unblurred faces as implicit feedback. The FRN effect can be identified in the ERP waveforms, albeit in a delayed 300–380 ms time window, with faces inconsistent with the initial judgment eliciting more negative-going responses than faces consistent with the judgment. However, the ERP waveforms did not show the typical pattern of P300 responses. With the principal component analysis (PCA), a clear pattern of P300 effects were revealed, with the P300 being more positive to faces consistent with the initial judgment than to faces inconsistent with the judgment, and more positive to attractive faces than to unattractive ones. The effect of feedback consistency did not interact with the effect of attractiveness in either the FRN or P300 component. These findings suggest that brain responses involved in processing complex feedback stimuli with a social dimension are generally similar to those involved in processing simple feedback stimuli in gambling or cognitive tasks, although appropriate means of data analysis are needed to reveal the typical ERP effects that may have been masked by sophisticated cognitive (and emotional) processes for complex stimuli.
How is spatial context learning integrated over signal versus noise? A primacy effect in contextual cueing

Over repeated exposure to particular visual search displays, subjects are able to implicitly extract regularities that then make search more efficient—a phenomenon known as contextual cueing. Here we explore how the learning involved in contextual cueing is formed, maintained, and updated over experience. During an initial training phase, a group of signal first subjects searched through a series of predictive displays (where distractor locations were perfectly correlated with the target location), followed with no overt break by a series of unpredictive displays (where repeated contexts were uncorrelated with target locations). A second noise first group of subjects encountered the unpredictive displays followed by the predictive displays. Despite the fact that both groups had the same overall exposure to signal and noise, only the signal first group demonstrated subsequent contextual cueing. This primacy effect indicates that initial experience can result in hypotheses about regularities in displays—or the lack thereof—which then become resistant to updating. The absence of regularities in early stages of training even blocked observers from learning predictive regularities later on.
Gauge Theory with Flavor from Fluxes

Cachazo and Vafa provided a proof of the equivalence of N = 1 dynamics obtained by deforming N = 2 SYM by addition of certain superpotential terms, with that of type IIB superstring on Calabi-Yau manifold with fluxes. We extend the proof to SYM with massive flavors in fundamental representation of gauge group. For the gauge group we consider U(N) and SO(N)/Sp(N) groups. When the adding tree level superpotential is square of adjoint chiral superfield we can derive AffleckDine-Seiberg potentials. By turning off the flux, we obtain Seiberg-Witten curves of N = 2 theories. ∗e-mail address : ookouchi@th.phys.titech.ac. jp
Comparison of research case definitions for carpal tunnel syndrome.

OBJECTIVE The aim of this study was to assess agreement between different case definitions of carpal tunnel syndrome (CTS) for epidemiological studies. METHODS We performed a literature search for papers suggesting case definitions for use in epidemiological studies of CTS. Using data elements based on symptom questionnaires, hand diagrams, physical examinations, and nerve conduction studies collected from 1107 newly-hired workers, each subject in the study was classified according to each of the case definitions selected from the literature. We compared each case definition to every other case definition, using the Kappa statistic to measure pair-wise agreement on whether each subject met the case definition. RESULTS We found six unique papers in a 20-year period suggesting a case definition of CTS for use in population-based studies. We extracted seven case definitions. Definitions included different parameters: (i) symptoms only, (ii) symptoms and physical examination, (iii) symptoms and either physical examination or median nerve conduction study, and (iv) symptoms and nerve conduction study. When applied to our study population, the prevalence of CTS using different case definitions ranged from 2.5-11.0%. The percentage of misclassification was between 1-10%, with generally acceptable levels of agreement (kappa values ranged from 0.30-0.85). CONCLUSIONS Different case definitions resulted in widely varying prevalences of CTS. Agreement between case definitions was generally good, particularly between those that required very specific symptoms or the combination of symptoms and physical examination or nerve conduction. The agreement observed between different case definitions suggests that the results can be compared across different research studies of risk factors for CTS.
Evaluation and Analysis of Heuristic Techniques for Vector Ordering of VLSI Test Sets

Vector ordering is an essential task in testing very large scale integration systems because it affects this process from two perspectives: 1) power consumption and 2) correlation among test data. The former feature is crucial and, if not properly controlled, may result in permanent failure of the device under test (DUT). The latter feature is also important because correlation is captured by coding schemes to efficiently compress test data and ease memory requirements of automatic test equipment (ATE) while reducing volume and lowering test application time. Vector ordering, however, is NP-complete. This paper presents an evaluation of different heuristic techniques for vector ordering using the 1985 and 1989 IEEE International Symposium on Circuits and Systems (ISCAS85 and ISCAS89, respectively) benchmark circuits in terms of run time and solution quality. For this application, it is shown that the best heuristic technique is not the one based on the famous Christofides or Lin-Kernighan criteria but on the multifragment technique. It has been shown that the selection of an appropriate heuristic can lead to an increase in the compression ratio of up to 178% and a reduction in the power consumption during test of up to 46%.
Determinants of left atrial size in patients with newly diagnosed untreated hypertension

The present study determined the relationships between ambulatory blood pressure, left ventricular mass, body mass index, and other clinical and demographic variables to left atrial size in previously untreated hypertensive and normotensive subjects. Left atrial size was measured uni-dimensionally using M-mode echocardiography in 58 newly diagnosed never-treated hypertensive patients (office blood pressure 149/96 ± 15/7 mmHg) and 28 normotensive control subjects (office blood pressure, 122/78 ± 8/8 mmHg). Left ventricular mass, septal and posterior wall thickness were significantly increased in hypertensive compared to normotensive subjects (230 ± 63 g versus 181 ± 45 g, 1.1 ± 0.2 cm versus 0.94 ± 0.2 cm, and 1.04 ± 0.2 cm versus 0.92 ± 0.2 cm respectively; all p < 0.001). Left ventricular internal diameter (4.9 ± 0.6 versus 4.8 ± 0.4 cm, p = 0.54) and left atrial size (3.74 ± 0.48 versus 3.70 ± 0.34 cm, p = 0.86) were not different between the two groups respectively. Body mass index, weight, left ventricular mass, wall thickness, and 24-h pulse pressure were significant correlates of left atrial size in the entire group and in the hypertensive subgroup. In the normotensive subgroup, body weight, body mass index, 24-h systolic and pulse pressure, and left ventricular mass were significant correlates. Multiple regression analyses in the entire group and the hypertensive subgroup alone showed that body mass index and left ventricular mass were the two best predictors of left atrial dimension. These data demonstrate that body mass index and left ventricular mass were the main correlates of left atrial size in patients with previously untreated stage I–II hypertension.
Intersection characteristics of end-to-end Internet paths and trees

This paper focuses on understanding the scale and the distribution of "state overhead'' (briefly load) that is incurred on the routers by various value-added network services, e.g., IP multicast and IP traceback. This understanding is essential to developing appropriate mechanisms and provisioning resources so that the Internet can support such value-added services in an efficient and scalable manner. We mainly consider the number of end-to-end paths or trees intersecting at a router to represent the amount of state overhead at that router. Hence, we analyze the router-level intersection characteristics of end-to-end Internet paths or trees to approximate the state overhead distribution in the Internet. For the reliability of our analysis, a representative, end-to-end router-level Internet map is essential. Although several maps are available, they are at best insufficient for our analysis. Therefore, in the first part of our work, we exert a measurement study to obtain a large size end-to-end router-level map conforming to our constraints. In the second part, we conduct various experiments using our map and shed some light on the scale and distribution of state overhead of value-added Internet services in both unicast and multicast environments.
Toward thermal flow-sensing with pL/s resolution

This paper focuses on the development of highly sensitive calorimetric flow sensors. Both the hydrodynamics of the flow channel, as well as the heat transfer are analyzed in detail. With the expressions for the hydraulic resistance of the flow channel and the hydraulic system requirements for the flow sensor, it is possible to optimize the design of the flow channel. It is theoretically shown why for small v the calorimetric flow sensor output is linear in v. Also it follows from theory that for a symmetrical configuration, in this linear regime the heater temperature is independent of v for constant heating power. This suggests that for low Reynolds Number King's Law has t obe modified. Different configurations and methods are analyzed: absolute, differential, two beam, three beam, CPA, CTA and TBA. The latter is a real thermal balance measurement and allows the use of non-linear sensing elements. From our experience with acoustical measurements it is possible to estimate practical attainable sensitivity. In combination with proper flow channel design, and a fabrication technology for narrow channels, it is shown that pL/s sensitivity is in reach.
NSAID Use and Risk of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: The Liver Cancer Pooling Project

Chronic inflammation plays a pivotal role in the pathogenesis of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), the two most common types of liver cancer. A number of prior experimental studies have suggested that nonsteroidal anti-inflammatory drugs (NSAIDs), including aspirin and ibuprofen, may potentially protect against liver cancer. However, no observational study has examined the association between aspirin duration and dose or other over-the-counter non-aspirin NSAIDs, such as ibuprofen, and liver cancer incidence. Furthermore, the association between NSAID use and risk of ICC is unclear. As part of the Liver Cancer Pooling Project, we harmonized data on 1,084,133 individuals (HCC = 679, ICC = 225) from 10 U.S.-based prospective cohort studies. Cox proportional hazards regression models were used to evaluate multivariable-adjusted HRs and 95% confidence intervals (CI). Current aspirin use, versus nonuse, was inversely associated with HCC (HR, 0.68; 95% CI, 0.57–0.81), which persisted when restricted to individuals not using non-aspirin NSAIDs and in a 5- and 10-year lag analysis. The association between aspirin use and HCC risk was stronger for users who reported daily use, longer duration use, and lower dosage. Ibuprofen use was not associated with HCC risk. Aspirin use was associated with a reduced ICC risk in men (HR, 0.64; 95% CI, 0.42–0.98) but not women (HR, 1.34; 95% CI, 0.89–2.01; Pinteraction = 0.01). The observed inverse association between aspirin use and liver cancer in our study, together with previous data, suggests the merit of future intervention studies of aspirin and other agents that affect chronic inflammatory pathways for HCC and possibly ICC. Cancer Prev Res; 8(12); 1156–62. ©2015 AACR.
Optimal multiuser spectrum management for digital subscriber lines

Crosstalk is a major issue in modern DSL systems such as ADSL and VDSL. Static spectrum management, the traditional way of ensuring spectral compatibility, employs spectral masks which can be overly conservative and lead to poor performance. In this paper we present a centralized algorithm for optimal spectrum management (OSM) in DSL. The algorithm uses a dual decomposition to solve the spectrum management problem in an efficient and computationally tractable way. The algorithm shows significant performance gains over existing DSM techniques, e.g. in a downstream ADSL scenario the centralized OSM algorithm can outperform a distributed DSM algorithm such as iterative waterfilling by up to 135%.
ipso-Hydroxylation and Subsequent Fragmentation: a Novel Microbial Strategy To Eliminate Sulfonamide Antibiotics

ABSTRACT Sulfonamide antibiotics have a wide application range in human and veterinary medicine. Because they tend to persist in the environment, they pose potential problems with regard to the propagation of antibiotic resistance. Here, we identified metabolites formed during the degradation of sulfamethoxazole and other sulfonamides in Microbacterium sp. strain BR1. Our experiments showed that the degradation proceeded along an unusual pathway initiated by ipso-hydroxylation with subsequent fragmentation of the parent compound. The NADH-dependent hydroxylation of the carbon atom attached to the sulfonyl group resulted in the release of sulfite, 3-amino-5-methylisoxazole, and benzoquinone-imine. The latter was concomitantly transformed to 4-aminophenol. Sulfadiazine, sulfamethizole, sulfamethazine, sulfadimethoxine, 4-amino-N-phenylbenzenesulfonamide, and N-(4-aminophenyl)sulfonylcarbamic acid methyl ester (asulam) were transformed accordingly. Therefore, ipso-hydroxylation with subsequent fragmentation must be considered the underlying mechanism; this could also occur in the same or in a similar way in other studies, where biotransformation of sulfonamides bearing an amino group in the para-position to the sulfonyl substituent was observed to yield products corresponding to the stable metabolites observed by us.
Signal Processing in Sequence Analysis: Advances in Eukaryotic Gene Prediction

Genomic sequence processing has been an active area of research for the past two decades and has increasingly attracted the attention of digital signal processing researchers in recent years. A challenging open problem in deoxyribonucleic acid (DNA) sequence analysis is maximizing the prediction accuracy of eukaryotic gene locations and thereby protein coding regions. In this paper, DNA symbolic-to-numeric representations are presented and compared with existing techniques in terms of relative accuracy for the gene and exon prediction problem. Novel signal processing-based gene and exon prediction methods are then evaluated together with existing approaches at a nucleotide level using the Burset/Guigo1996, HMR195, and GENSCAN standard genomic datasets. A new technique for the recognition of acceptor splice sites is then proposed, which combines signal processing-based gene and exon prediction methods with an existing data-driven statistical method. By comparison with the acceptor splice site detection method used in the gene-finding program GENSCAN, the proposed DSP-statistical hybrid technique reveals a consistent reduction in false positives at different levels of sensitivity, averaging a 43% reduction when evaluated on the GENSCAN test set.
Color Orchestra: Ordering Color Palettes for Interpolation and Prediction

Color theme or color palette can deeply influence the quality and the feeling of a photograph or a graphical design. Although color palettes may come from different sources such as online crowd-sourcing, photographs and graphical designs, in this paper, we consider color palettes extracted from fine art collections, which we believe to be an abundant source of stylistic and unique color themes. We aim to capture color styles embedded in these collections by means of statistical models and to build practical applications upon these models. As artists often use their personal color themes in their paintings, making these palettes appear frequently in the dataset, we employed density estimation to capture the characteristics of palette data. Via density estimation, we carried out various predictions and interpolations on palettes, which led to promising applications such as photo-style exploration, real-time color suggestion, and enriched photo recolorization. It was, however, challenging to apply density estimation to palette data as palettes often come as unordered sets of colors, which make it difficult to use conventional metrics on them. To this end, we developed a divide-and-conquer sorting algorithm to rearrange the colors in the palettes in a coherent order, which allows meaningful interpolation between color palettes. To confirm the performance of our model, we also conducted quantitative experiments on datasets of digitized paintings collected from the Internet and received favorable results.
A test of central coherence theory: Can adults with high-functioning autism or Asperger syndrome integrate fragments of an object?

Introduction. Visuoconceptual integration was explored as a test of central coherence theory (Frith, 1989). Individuals with autism are thought to have weak central coherence so the prediction was that these individuals would show an impaired ability to integrate visual information. Method. Two groups with autistic disorder were recruited: adults with either autism or Asperger syndrome. All were normally intelligent and were matched with members of the general population of Cambridge. A modified version of the Hooper Visual Organisation Test was used in which line drawings depicting simple objects had been cut into pieces and arranged in a puzzle-like fashion. The participants were required to conceptually integrate the fragments in order to identify the object. A second condition presented just a single piece of an object and participants were required to identify objects from a single piece. Results. Both clinical groups were significantly impaired in their ability to integrate pieces holistically, but they were unimpaired in their ability to identify an object from a single piece. Conclusion. Individuals with an autistic disorder are less able to integrate visual elements. Of the two clinical groups, the autism group had the greater deficit, and it applied to the majority of the group. Possible explanations for the clinical groups' weak central coherence are explored.