Miracle-dz/UniFAR-FTUs huggingface dataset:
Induction of apoptosis and differentiation in neuroblastoma and astrocytoma cells by the overexpression of Bin1, a novel myc interacting protein

Bin1 is a novel protein that specifically binds Myc and inhibits, at least in part, Myc transactivation. Bin1 seems to play a role in cell cycle control, acting as a tumor suppressor gene. Since MYC family genes play a regulatory role in the proliferation, differentiation, and apoptosis of the nervous system, we studied the effects of the overexpression of the Myc‐interacting protein, Bin1, in neuroblastoma and astrocytoma cell lines, which were chosen as neural cell system models. The major effects of BIN1 overexpression observed in undifferentiated neuroblastoma and astrocytoma cells were a significant reduction of cell growth, an increase in the G0/G1 cell population and the induction of apoptosis. The trigger of programmed cell death by Bin1 is described for the first time. Bin1 overexpression in undifferentiated cells did not induce any maturation process as neither neuronal nor astrocyte differentiation markers were upregulated in neuroblastoma and astrocytoma cells, respectively. On the other side, the effects of Bin1 overproduction in neuroblastoma and astrocytoma cells committed towards neuronal and astrocyte differentiation, respectively, were different from those observed in undifferentiated cells. Although we did not evidence any triggering of programmed cell death, we did notice a further induction towards more differentiated phenotypes. Our studies suggest that Bin1 overexpression in neuroblastoma and astrocytoma cells can result in one of the following pathways: (1) suppressed cell proliferation, (2) induced differentiation, or (3) apoptosis. Thus, it appears that Bin1 operates through different pathways that involve activation of different genes: the chosen pathway however will depend on the proliferating or differentiated state of the cell. J. Cell. Biochem. 74:313–322, 1999. © 1999 Wiley‐Liss, Inc.
Designing and comparing automated test oracles for GUI-based software applications

Test designers widely believe that the overall effectiveness and cost of software testing depends largely on the type and number of test cases executed on the software. This article shows that the test oracle, a mechanism that determines whether a software is executed correctly for a test case, also significantly impacts the fault detection effectiveness and cost of a test case. Graphical user interfaces (GUIs), which have become ubiquitous for interacting with today's software, have created new challenges for test oracle development. Test designers manually “assert” the expected values of specific properties of certain GUI widgets in each test case; during test execution, these assertions are used as test oracles to determine whether the GUI executed correctly. Since a test case for a GUI is a sequence of events, a test designer must decide: (1) what to assert; and (2) how frequently to check an assertion, for example, after each event in the test case or after the entire test case has completed execution. Variations of these two factors significantly impact the fault-detection ability and cost of a GUI test case. A technique to declaratively specify different types of automated GUI test oracles is described. Six instances of test oracles are developed and compared in an experiment on four software systems. The results show that test oracles do affect the fault detection ability of test cases in different and interesting ways: (1) Test cases significantly lose their fault detection ability when using “weak” test oracles; (2) in many cases, invoking a “thorough” oracle at the end of test case execution yields the best cost-benefit ratio; (3) certain test cases detect faults only if the oracle is invoked during a small “window of opportunity” during test execution; and (4) using thorough and frequently-executing test oracles can compensate for not having long test cases.
Stochastic Block BFGS: Squeezing More Curvature out of Data

We propose a novel limited-memory stochastic block BFGS update for incorporating enriched curvature information in stochastic approximation methods. In our method, the estimate of the inverse Hessian matrix that is maintained by it, is updated at each iteration using a sketch of the Hessian, i.e., a randomly generated compressed form of the Hessian. We propose several sketching strategies, present a new quasi-Newton method that uses stochastic block BFGS updates combined with the variance reduction approach SVRG to compute batch stochastic gradients, and prove linear convergence of the resulting method. Numerical tests on large-scale logistic regression problems reveal that our method is more robust and substantially outperforms current state-of-the-art methods.
Machine learning-based retrieval of benthic reflectance and Posidonia oceanica seagrass extent using a semi-analytical inversion of Sentinel-2 satellite data

ABSTRACT In the epoch of the human-induced climate change, seagrasses can mitigate the resulting negative impacts due to their carbon sequestration ability. The endemic and dominant in the Mediterranean Posidonia oceanica seagrass contains the largest stocks of organic carbon among all seagrass species, yet it undergoes a significant regression in its extent. Therefore, suitable quantitative assessment of its extent and optically shallow environment are required to allow good conservation and management practices. Here, we parameterise a semi-analytical inversion model which employs above-surface remote sensing reflectance of Sentinel-2A to derive water column and bottom properties in the Thermaikos Gulf, NW Aegean Sea, Greece (eastern Mediterranean). In the model, the diffuse attenuation coefficients are expressed as functions of absorption and backscattering coefficients. We apply a comprehensive pre-processing workflow which includes atmospheric correction using C2RCC (Case 2 Regional CoastColour) neural network, resampling of the lower spatial resolution Sentinel-2A bands to 10m/pixel, as well as empirical derivation of water bathymetry and machine learning-based classification of the resulting bottom properties using the Support Vector Machines. SVM-based classification of benthic reflectance reveals ~300 ha of P. oceanica seagrass between 2 and 16 m of depth, and yields very high producer and user accuracies of 95.3% and 99.5%, respectively. Sources of errors and uncertainties are discussed. All in all, recent advances in Earth Observation in terms of optical satellite technology, cloud computing and machine learning algorithms have created the perfect storm which could aid high spatio-temporal, large-scale seagrass habitat mapping and monitoring, allowing for its integration to the Analysis Ready Data era and ultimately enabling more efficient management and conservation in the epoch of climate change.
Seasonal prediction of high‐resolution temperature at 2‐m height over Mongolia during boreal winter using both coupled general circulation model and artificial neural network

The hindcast data of Pusan National University coupled general circulation model (PNU CGCM), a participant model of the Asia‐Pacific Economic Cooperation Climate Center (APCC) Multi‐Model Ensemble Climate Prediction System, and August–October sea‐surface temperature (SST) in the northern Barents–Kara Sea (BKI) and the sea‐ice extent (SIE) in the Chukchi Sea (East Siberian Sea index [ESI]) are used for predicting 20 × 20‐km‐resolution anomalous surface air temperature at 2‐m height (aT2m) over Mongolia for boreal winter. For this purpose, area‐averaged surface air temperature (TI) and sea‐level pressure (SLP) over Mongolia are defined. Then four large‐scale indices, TImdl and SHImdl obtained from PNU CGCM, and TIMLR and SHIMLR obtained from multiple linear regressions on BKI and ESI, are incorporated using the artificial neural network (ANN) method for the prediction and statistical downscaling to obtain the monthly and seasonal 20 × 20‐km‐resolution aT2m over Mongolia in winter. An additional statistical method, which uses BKI and ESI as predictors of TI and SHI together with dynamic prediction by the CGCM, is used because of the relatively low skill of seasonal predictions by most of the state‐of‐the‐art models and the multi‐model ensemble systems over high‐latitude landlocked Eurasian regions such as Mongolia. The results show that the predictabilities of monthly and seasonal 20 × 20‐km‐resolution aT2m over Mongolia in winter are improved by applying ANN to both statistical and dynamical predictions compared to utilizing only dynamic prediction. The predictability gained by the proposed method is also demonstrated by the probabilistic forecast implying that the method forecasts aT2m over Mongolia in winter reasonably well.
Relating coalgebraic notions of bisimulation: with applications to name-passing process calculi

A labelled transition system can be understood as a coalgebra for a particular endofunctor on the category of sets. Generalizing, we are led to consider coalgebras for arbitrary endofunctors on arbitrary categories. Bisimulation is a crucial notion in the theory of labelled transition systems. We identify four definitions of bisimulation on general coalgebras. The definitions all specialize to the same notion for the special case of labelled transition systems. We investigate general conditions under which the four notions coincide. As an extended example, we consider the semantics of name-passing process calculi (such as the pi-calculus), and present a new coalgebraic model for name-passing calculi.
Fluoride-induced interleukin-6 and interleukin-8 synthesis in human epithelial lung cells

Exposure to fluorides has been associated with asthmatic symptoms among workers in the aluminium industry. In a recent experimental study hydrogen fluoride (HF) was found to induce a weak inflammatory response in humans. In the present study the potential of sodium fluoride (NaF) and HF to induce cytokine response was examined and how these responses are modulated by Al3+ in a human epithelial lung cell line (A549). Dose-response experiments showed a maximal release of IL-6 and IL-8 at a concentration of 5 mM NaF 24 h after addition. The responses to HF were of a similar magnitude as for NaF. Time-course experiments showed a NaF-induced IL-6 response at 5 h, whereas an IL-8 response was observed after 10 h. Cycloheximide treatment completely abolished the NaF-induced cytokine responses. A marked increase in the mRNA level for IL-6 was observed already 2 h after exposure to 5 mM NaF, and presumably is a prerequisite for the subsequent increase of IL-6. The fluoride-induced effects on IL-6 and IL-8 release were strongly reduced by pretreatment with deferoxamine (an Al3+-chelator), and enhanced by addition of Al3+. This indicates that an AlF4 7-complex, a known activator of GTP-binding proteins, is involved in fluoride-induced IL-6 and IL-8 responses in A549 cells.
Effect of homocysteinylation on human high-density lipoproteins: a correlation with paraoxonase activity.

We investigated the effect of homocysteine (Hcy)-thiolactone on the activity of the enzyme paraoxonase (PON) associated with human high-density lipoprotein (HDL-PON). HDL were isolated from plasma of normolipidemic subjects. The increase in the levels of sulfhydryl groups (-SH) in HDL incubated with Hcy-thiolactone demonstrates that homocysteinylation of HDL occurs. The increase of -SH groups correlated with the basal values of HDL-PON activity (r = -0.73, P <.001, and r = -0.70, P <.002 using 10 micromol/L and 1 mmol/L Hcy-thiolactone, respectively) suggesting a relationship between the susceptibility of HDL to homocysteinylation and HDL-PON activity. A decrease in the activity of the enzyme HDL-PON was observed in homocysteinylated HDL (Hcy-HDL). The negative correlation established between the basal levels of HDL-PON activity and the percentage decrease of HDL-PON activity (r = -0.76, P <.001, and r = -0.86, P <.001 using 10 micromol/L or 1 mmol/L Hcy-thiolactone, respectively) suggests that subjects with higher HDL-PON activity have a lower decrease in PON activity with respect to subjects with lower HDL-PON activity. The positive correlation established between the percentage decrease of PON activity and the percentage increase of -SH groups in Hcy-HDL (r = 0.80, P <.001, and r = 0.76, P <.001 in HDL incubated in the presence of 10 micromol/L and 1 mmol/L Hcy-thiolactone, respectively) suggests that the modifications of HDL-PON activity are likely related to the compositional changes at the lipoprotein surface of Hcy-HDL. The enzyme PON contributes to the protective role of HDL against the oxidative damage and against toxicity exerted by Hcy involved in the development of atherosclerosis. Therefore the significant decrease of the enzyme activity in HDL incubated with Hcy-thiolactone suggests that homocysteinylation could render HDL less protective against oxidative damage and against toxicity of Hcy-thiolactone.
Activation of Type III Interferon Genes by Pathogenic Bacteria in Infected Epithelial Cells and Mouse Placenta

Bacterial infections trigger the expression of type I and II interferon genes but little is known about their effect on type III interferon (IFN-λ) genes, whose products play important roles in epithelial innate immunity against viruses. Here, we studied the expression of IFN-λ genes in cultured human epithelial cells infected with different pathogenic bacteria and in the mouse placenta infected with Listeria monocytogenes. We first showed that in intestinal LoVo cells, induction of IFN-λ genes by L. monocytogenes required bacterial entry and increased further during the bacterial intracellular phase of infection. Other Gram-positive bacteria, Staphylococcus aureus, Staphylococcus epidermidis and Enterococcus faecalis, also induced IFN-λ genes when internalized by LoVo cells. In contrast, Gram-negative bacteria Salmonella enterica serovar Typhimurium, Shigella flexneri and Chlamydia trachomatis did not substantially induce IFN-λ. We also found that IFN-λ genes were up-regulated in A549 lung epithelial cells infected with Mycobacterium tuberculosis and in HepG2 hepatocytes and BeWo trophoblastic cells infected with L. monocytogenes. In a humanized mouse line permissive to fetoplacental listeriosis, IFN-λ2/λ3 mRNA levels were enhanced in placentas infected with L. monocytogenes. In addition, the feto-placental tissue was responsive to IFN-λ2. Together, these results suggest that IFN-λ may be an important modulator of the immune response to Gram-positive intracellular bacteria in epithelial tissues.
Does Arbitrage Flatten Demand Curves for Stocks?

In textbook theory, demand curves for stocks are kept flat by riskless arbitrage between perfect substitutes. In reality, however, individual stocks do not have perfect substitutes. We develop a simple model of demand curves for stocks in which the risk inherent in arbitrage between imperfect substitutes deters risk-averse arbitrageurs from flattening demand curves. Consistent with the model, stocks without close substitutes experience higher price jumps upon inclusion into the S&P 500 Index. The results suggest that arbitrage is weaker and mispricing is likely to be more frequent and more severe among stocks without close substitutes.
Antigen-driven bystander suppression after oral administration of antigens

Suppression of experimental autoimmune encephalomyelitis (EAE) in Lewis rats by the oral administration of myelin basic protein (MBP) is mediated by CD8+ T cells that can be isolated from the spleens of MBP- fed animals. These cells adoptively transfer protection to naive animals subsequently immunized with MBP and complete Freund's adjuvant (CFA) and suppress in vitro MBP proliferative responses. Using a transwell system in which the modulator spleen cells from MBP-fed animals are separated by a semipermeable membrane from responder cells, MBP, or OVA-specific T cell lines, we have found that cell contact is not required for in vitro suppression to occur. In vitro suppression is dependent, however, upon antigen-specific triggering of modulator T cells. Once antigen-specific triggering occurs, suppression across the transwell is mediated by an antigen-nonspecific soluble factor that equally suppresses an MBP line or an ovalbumin (OVA) line. This phenomenon of antigen-driven bystander suppression was also demonstrated in vivo. Specifically, Lewis rats fed OVA which were then immunized with MBP/CFA plus OVA given separately subcutaneously were protected from EAE. Animals fed OVA and then immunized with MBP/CFA without OVA given subcutaneously were not protected. The protective effect of feeding OVA could be adoptively transferred by CD8+ T cells from OVA-fed animals into MBP/CFA plus OVA-injected animals. Feeding bovine serum albumin (BSA) or keyhole limpet hemocyanin did not suppress EAE in animals immunized with MBP/CFA plus OVA. EAE was suppressed, however, if BSA was fed and animals then immunized with MBP/CFA plus BSA given subcutaneously. Antigen-driven bystander suppression appears to be an important mechanism by which antigen- driven peripheral tolerance after oral administration of antigen is mediated, and presumably occurs in the microenvironment accounting for the antigen specificity of suppression generated by oral tolerization to antigens.
SiMa Cells for a Serotype Specific and Sensitive Cell-Based Neutralization Test for Botulinum Toxin A and E

Botulinum toxins (BoNTs), of which there are seven serotypes, are among the most potent neurotoxins, with serotypes A, B and E causing human botulism. Antitoxins form the first line of treatment for botulism, and functional, highly sensitive in vitro methods for toxin neutralization are needed to replace the current in vivo methods used for determination of antitoxin potency. In this preliminary proof of concept study, we report the development of a neutralization test using the neuroblastoma SiMa cell line. The assay is serotype specific for either BoNT/A or BoNT/E, which both cleave unique sequences on SNAP-25 within SiMa cells. The end point is simple immunodetection of cleaved SNAP-25 from cell lysates with antibodies detecting only the newly exposed sequence on SNAP-25. Neutralizing antibodies prevent the toxin-induced cleavage of SNAP-25. The toxin neutralization assay, with an EC50 of ~2 mIU/mL determined with a standardized reference antiserum, is more sensitive than the mouse bioassays. Relevance was demonstrated with commercial and experimental antitoxins targeting different functional domains, and of known in vivo neutralizing activities. This is the first report describing a simple, specific, in vitro cell-based assay for the detection of neutralizing antibodies against BoNT/A and BoNT/E with a sensitivity exceeding that of the mouse bioassay.
Masses, fat loads and estimated flight ranges of Skylarks Alauda arvensis captured during autumn migration in southern Italy

ABSTRACT From 1998 to 2015, 22 490 fully grown Skylarks were captured and ringed, using mist nets, from October to mid November, along the southern Tyrrhenian coast of Italy. We estimated fat loads and theoretical flight ranges for individual birds, using recorded body mass and visible fat score. The size-specific fat-free body mass, as the body mass of birds with no visible subcutaneous fat deposits, was estimated for all categories of wing length, verifying any differences between males and females identified using wing length; body mass (to 0.1 g) and visible fat score (values 0–6) were recorded in the field. Males were significantly heavier than females and more often had high scores of visible fat. Only a few birds had high fat scores (classes 5 and 6) and the proportion of individuals with no visible fat (class 0) was very low: most birds of both sexes fell into classes 3 or 4. Fat scores were positively correlated with the corresponding average body mass. The predicted flight range indicated that 70% of Skylarks captured would be unable to fly farther than 800 km: they would be able to reach their wintering grounds, spend the winter in Italy or reach the North African coast after a refuelling stop.
Beyond probabilistic record linkage: Using neural networks and complex features to improve genealogical record linkage

Probabilistic record linkage has been used for many years in a variety of industries, including medical, government, private sector and research groups. The formulas used for probabilistic record linkage have been recognized by some as being equivalent to the naïve Bayes classifier. While this method can produce useful results, it is not difficult to improve accuracy by using one of a host of other machine learning or neural network algorithms. Even a simple single-layer perceptron tends to outperform the naïve Bayes classifier—and thus traditional probabilistic record linkage methods—by a substantial margin. Furthermore, many record linkage system use simple field comparisons rather than more complex features, partially due to the limits of the probabilistic formulas they use. This paper presents an overview of probabilistic record linkage, shows how to cast it in machine learning terms, and then shows that it is equivalent to a naïve Bayes classifier. It then discusses how to use more complex features than simple field comparisons, and shows how probabilistic record linkage formulas can be modified to handle this. Finally, it demonstrates a huge improvement in accuracy through the use of neural networks and higher-level matching features, compared to traditional probabilistic record linkage on a large (80,000 pair) set of labeled pairs of genealogical records used by FamilySearch.org.
The Optimal Pricing of Pollution When Enforcement is Costly

We consider the pricing of a uniformly mixed pollutant when enforcement is costly with a model of optimal, possibly firm-specific, emissions taxes and their enforcement. We argue that optimality requires an enforcement strategy that induces full compliance by every firm. This holds whether or not regulators have complete information about firms’ abatement costs, the costs of monitoring them for compliance, or the costs of collecting penalties from noncompliant firms. Moreover, ignoring several unrealistic special cases, optimality requires discriminatory emissions taxes except when regulators are unable to observe firms’ abatement costs, the costs of monitoring individual firms, or any firm-specific characteristic that is known to be jointly distributed with either the firms’ abatement costs or their monitoring costs. In many pollution control settings, especially those that have been subject to various forms of environmental regulation in the past, regulators are not likely to be so ill-informed about individual firms. In these settings, policies that set or generate a uniform pollution price like conventional designs involving uniform taxes and competitive emission trading with freely-allocated or auctioned permits will not be efficient.
Historical Reliability: A Key to Differentiating Populations among Patients Presenting Signs of Multiple Personality Disorder

The clinical value of inconsistencies in the historical data of patients presenting with signs of multiple personality disorder was assessed. Three major inconsistencies in historical data were identzied in 23 patients who were admitted to a Dissociative Disorders Program with a diagnosis of Multiple Personality Disorder. This group showed psychological disturbance that was quite different from 23 patients with a similar discharge diagnosis but who did not exhibit inconsistencies in history. The former group reported less psychological disturbance and fewer dissociative experiences. Patients who are less credible by virtue of inconsistencies in their historical reports may belong to a different diagnostic group. The findings point to the need to chart history carefully in authenticating genuine cases.