Miracle-dz/UniFAR-FTUs huggingface dataset:
Targeting folate receptor alpha for cancer treatment

Promising targeted treatments and immunotherapy strategies in oncology and advancements in our understanding of molecular pathways that underpin cancer development have reignited interest in the tumor-associated antigen Folate Receptor alpha (FRα). FRα is a glycosylphosphatidylinositol (GPI)-anchored membrane protein. Its overexpression in tumors such as ovarian, breast and lung cancers, low and restricted distribution in normal tissues, alongside emerging insights into tumor-promoting functions and association of expression with patient prognosis, together render FRα an attractive therapeutic target. In this review, we summarize the role of FRα in cancer development, we consider FRα as a potential diagnostic and prognostic tool, and we discuss different targeted treatment approaches with a specific focus on monoclonal antibodies. Renewed attention to FRα may point to novel individualized treatment approaches to improve the clinical management of patient groups that do not adequately benefit from current conventional therapies.
Estimation of the transmission dynamics of Theileria equi and Babesia caballi in horses

SUMMARY For the evaluation of the epidemiology of Theileria equi and Babesia caballi in a herd of 510 horses in SW Mongolia, several mathematical models of the transmission dynamics were constructed. Because the field data contain information on the presence of the parasite (determined by PCR) and the presence of antibodies (determined by IFAT), the models cater for maternal protection with antibodies, susceptible animals, infected animals and animals which have eliminated the parasite and also allow for age-dependent infection in susceptible animals. Maximum likelihood estimation procedures were used to estimate the model parameters and a Monte Carlo approach was applied to select the best fitting model. Overall, the results are in line with previous experimental work, and add evidence that the epidemiology of T. equi differs from that of Babesia spp. The presented modelling approach provides a useful tool for the investigation of some vector-borne diseases and the applied model selection procedure avoids asymptotical assumptions that may not be adequate for the analysis of epidemiological field data.
Chemistry in Protoplanetary Disks: A Sensitivity Analysis

We study how uncertainties in the rate coefficients of chemical reactions in the RATE 06 database affect abundances and column densities of key molecules in protoplanetary disks. We randomly varied the gas-phase reaction rates within their uncertainty limits and calculated the time-dependent abundances and column densities using a gas-grain chemical model and a flaring steady state disk model. We find that key species can be separated into two distinct groups according to the sensitivity of their column densities to the rate uncertainties. The first group includes CO, C+, H+3, H2O, NH3, N2H+, and HCNH+. For these species the column densities are not very sensitive to the rate uncertainties, but the abundances in specific regions are. The second group includes CS, CO2, HCO+, H2CO, C2H, CN, HCN, HNC, and other, more complex species, for which high abundances and abundance uncertainties coexist in the same disk region, leading to larger scatters in column densities. However, even for complex and heavy molecules, the dispersion in their column densities is not more than a factor of ~4. We perform a sensitivity analysis of the computed abundances to rate uncertainties and identify those reactions with the most problematic rate coefficients. We conclude that the rate coefficients of about a hundred chemical reactions need to be determined more accurately in order to greatly improve the reliability of modern astrochemical models. This improvement should be an ultimate goal of future laboratory studies and theoretical investigations.
Sovereign Risk and the Effects of Fiscal Retrenchment in Deep Recessions

The authors analyze the effects of government spending cuts on economic activity in an environment of severe fiscal strain, as reflected by a sizeable risk premium on government debt. Specifically, they consider a "sovereign risk channel," through which sovereign default risk spills over to the rest of the economy, raising funding costs in the private sector. The authors' analysis is based on a variant of the model suggested by Curdia and Woodford (2009). It allows for costly financial intermediation and inter-household borrowing and lending in equilibrium, but maintains the tractability of the baseline New Keynesian model. They show that, if monetary policy is constrained in offsetting the effect of higher sovereign risk on private-sector borrowing conditions, the sovereign risk channel exacerbates indeterminacy problems: private-sector beliefs of a weakening economy can become self-fulfilling. Under these conditions, fiscal retrenchment can limit the risk of macroeconomic instability. In addition, if fiscal strain is very severe and monetary policy is constrained for an extended period, fiscal retrenchment may actually stimulate economic activity.
Rural Leaders, Rural Places: Problem, Privilege, and Possibility.

Correspondence concerning this article should be addressed to Kathleen Budge, Boise State University, Leadership Development Program, Boise, ID 83706. (kathleenbudge@boisestate.edu) Citation: Budge, K. (2006, December 18). Rural leaders, rural places: Problem, privilege, and possibility. Journal of Research in Rural Education, 21(13). Retrieved [date] from http://jrre.psu. edu/articles/2113.pdf Rural Leaders, Rural Places: Problem, Privilege, and Possibility
Recommender Systems for Literature Selection : A Competition between Decision Making and Memory Models

We examine the ability of five cognitive models to predict what publications scientists decide to read. The cognitive models are (i) the Publication Assistant, a literature recommender system that is based on a rational analysis of memory and the ACT-R cognitive architecture; (ii-iv) three simple decision heuristics, including two lexicographic ones called take-the-best and naïveLex, as well as unit-weight linear model, and (v) a more complex weighted-additive decision strategy called Franklin’s rule. In an experiment with scientists as participants, we pit these models against (vi) multiple regression. Among the cognitive models, take-thebest best predicts most scientists’ literature preferences best. Altogether, the study shows that individual differences in scientific literature selection may be accounted for by different decision-making strategies.
HS-133, a novel fluorescent phosphatidylinositol 3-kinase inhibitor as a potential imaging and anticancer agent for targeted therapy

As PI3K/Akt signaling is frequently deregulated in a wide variety of human tumors, PI3K inhibitors are an emerging class of drugs for cancer treatment. The monitoring of the drug behavior and distribution in the biological system can play an important role for targeted therapy and provide information regarding the response or resistance to available therapies. In this study, therefore, we have developed a family of xanthine derivatives, serving as a dual function exhibiting fluorescence, as well as inhibiting PI3K. Among them, HS-133 showed anti-proliferative effects and was monitored for its subcellular localization by a fluorescence microscopy. HS-133 suppressed the PI3K/Akt pathway and induced cell cycle arrest at the G0/G1 phase. The induction of apoptosis by HS-133 was confirmed by the increases of the cleaved PARP, caspase-3, and caspase-8. Furthermore, HS-133 decreased the protein expression of HIF-1α and VEGF, as well inhibited the tube formation and migration of the human umbilical vein endothelial cells. In vivo imaging also showed that tumors were visualized fluorescent with HS-133, and its oral administration significantly inhibited the growth of tumor in SkBr3 mouse xenograft models. Thus, we suggest that HS-133 may be used as a fluorescent anticancer agent against human breast cancer.
Strengths, Weaknesses, and Combinations of Model-based and Model-free Reinforcement Learning

Reinforcement learning algorithms are conventionally divided into two approaches: a model-based approach that builds a model of the environment and then computes a value function from the model, and a model-free approach that directly estimates the value function. The first contribution of this thesis is to demonstrate that, with similar computational resources, neither approach dominates the other. Explicitly, the model-based approach achieves a better performance with fewer environmental interactions, while the model-free approach reaches a more accurate solution asymptotically by using a larger representation or eligibility traces. The strengths offered by each approach are important for a reinforcement learning agent and, therefore, it is desirable to search for a combination of the two approaches and get the strengths of both. The main contribution of this thesis is to propose a new architecture in which a model-based algorithm forms an initial value function estimate and a model-free algorithm adds on to and improves the initial value function estimate. Experiments show that our architecture, called the Cascade Architecture, preserves the data efficiency of the model-based algorithm. Moreover, we prove that the Cascade Architecture converges to the original model-free solution and thus prevents any imperfect model from impairing the asymptotic performance. These results strengthen the case for combining model-based and model-free reinforcement learning.
A quick search method for audio and video signals based on histogram pruning

This paper proposes a quick method of similarity-based signal searching to detect and locate a specific audio or video signal given as a query in a stored long audio or video signal. With existing techniques, similarity-based searching may become impractical in terms of computing time in the case of searching through long-running (several-days' worth of) signals. The proposed algorithm, which is referred to as time-series active search, offers significantly faster search with sufficient accuracy. The key to the acceleration is an effective pruning algorithm introduced in the histogram matching stage. Through the pruning, the actual number of matching calculations can be reduced by 200 to 500 times compared with exhaustive search while guaranteeing exactly the same search result. Experiments show that the proposed method can correctly detect and locate a 15-s signal in a 48-h recording of TV broadcasts within 1 s, once the feature vectors are calculated and quantized. As extentions of the basic algorithm, efficient AND/OR search methods for searching for multiple query signals and a feature dithering method for coping with signal distortion are also discussed.
The luminosity function and surface brightness distribution of H I selected galaxies

We measure the z = 0 B-band optical luminosity function (LF) for galaxies selected in a blind H i survey. The total LF of the H i selected sample is flat, with Schechter parameters M � = 19.38 +1.02 0.62 + 5logh100 mag and � = 1.03 +0.25 0.15 , in good agreement with LFs of optically selected late-type galaxies. Bivariate distribution functions of several galaxy parameters show that the H i density in the local Universe is more widely spread over galaxies of different size, central surface brightness, and luminosity than is the optical luminosity density. The number density of very low surface brightness (> 24.0 magarcsec 2 ) gas-rich galaxies is considerably lower than that found in optical surveys designed to detect dim galaxies. This suggests that only a part of the population of LSB galaxies is gas rich and that the rest must be gas poor. However, we show that this gas-poor population must be cosmologically insignificant in baryon content. The contribution of gas-rich LSB galaxies (> 23.0 magarcsec 2 ) to the local cosmological gas and luminosity density is modest (18 +6 5 and 5 +2 2 per cent respectively); their contribution to matter is not well-determined, but probably < 11 per cent. These values are in excellent agreement with the low redshift results from the Hubble Deep Field.
The Metallicity of the Red Giant Branch in the Disk of NGC 6822

Deep J, H, and K′ images obtained with the Canada‐France‐Hawaii Telescope adaptive optics system are used to investigate the metallicity of red giant branch (RGB) stars in three fields in the disk of the Local Group dwarf irregular galaxy NGC 6822. The slope of the RGB on the (K, J−K) color‐magnitude diagrams indicates that [Fe/H] = -1.0 ± 0.3. The locus of the RGB is bluer than that of globular clusters with the same RGB slope by an amount that is consistent with the majority of RGB stars in these fields having an age near 3 Gyr. It is demonstrated that if RGB stars in NGC 6822 are this young, then the metallicity computed from the RGB slope may be ∼0.05 dex too low. Finally, the metallicity computed from the RGB slope is lower than spectroscopic‐based metallicities for young stars in NGC 6822, and it is concluded that Δ[Fe/H]/Δt = −0.2 ± 0.1 dex Gyr−1 in NGC 6822 during the past few gigayears.
GAMMA-RAY BURST LUMINOSITY FUNCTIONS BASED ON A NEWLY DISCOVERED CORRELATION BETWEEN PEAK SPECTRAL ENERGY AND V/Vmax

We have discovered a correlation between the observed peak spectral energy Epk,obs and the Euclidean value of 〈V/Vmax 〉 of gamma-ray bursts (GRBs). We present the evidence for the correlation in the GUSBAD catalog and use it to derive the luminosity function of GRBs without using any redshifts. The procedure involves dividing GUSBAD GRBs into five spectral classes based on their Epk,obs. The overall luminosity function is derived assuming that each of the spectral classes contributes a Gaussian luminosity function. Their central luminosity is derived from the observed Euclidean 〈V/Vmax 〉. We explore various forms for the GRB rate function GR(z) in predicting redshift distributions of GRBs detected by Swift. We find that GR(z) peaks at a higher redshift than the typical star formation history currently favored in the literature. We consider two examples of GR(z) that successfully predict the observed redshift distribution of Swift GRBs. With the luminosity functions in hand, we convert the Epk,obs − V/Vmax correlation into an Epk,obs − Liso correlation and a rest-frame Epk − Liso correlation. By comparing the Epk − Liso correlation with a published correlation based on GRBs with known Epk,obs and redshifts, we discuss the effect of Malmquist bias.
Age-related total gray matter and white matter changes in normal adult brain. Part I: volumetric MR imaging analysis.

BACKGROUND AND PURPOSE A technique of segmenting total gray matter (GM) and total white matter (WM) in human brain is now available. We investigated the effects of age and sex on total fractional GM (%GM) and total fractional WM (%WM) volumes by using volumetric MR imaging in healthy adults. METHODS Fifty-four healthy volunteers (22 men, 32 women) aged 20-86 years underwent dual-echo fast spin-echo MR imaging. Total GM, total WM, and intracranial space volumes were segmented by using MR image-based computerized semiautomated software. Volumes were normalized as a percentage of intracranial volume (%GM and %WM) to adjust for variations in head size. Age and sex effects were then assessed. RESULTS Both %GM and %WM in the intracranial space were significantly less in older subjects (> or =50 years) than in younger subjects (<50 years) (P <.0001 and P =.02, respectively). Consistently, %GM decreased linearly with age, beginning in the youngest subjects. %WM decreased in a quadratic fashion, with a greater rate beginning only in adult midlife. Although larger GM volumes were observed in men before adjustments for cranium size, no significant differences in %GM or %WM were observed between the sexes. CONCLUSION GM volume loss appears to be a constant, linear function of age throughout adult life, whereas WM volume loss seems to be delayed until middle adult life. Both appear to be independent of sex. Quantitative analysis of %GM and %WM volumes can improve our understanding of brain atrophy due to normal aging; this knowledge may be valuable in distinguishing atrophy of disease patterns from characteristics of the normal aging process.
Is Software Piracy a Middle Class Crime? Investigating the Inequality-Piracy Channel

This paper uses a sample of 71 countries in a cross-country context to empirically analyze the relationship between income distribution and software piracy rates. It measures income inequality by the Gini coefficient and alternatively by quintile shares. This analysis remedies previous econometric studies by controlling for a wide range of factors that potentially influence national piracy rates and employing an instrumental variables approach. Results indicate that income inequality is negatively associated with piracy rates but also that the impact of various income classes on piracy rates may depend on the geographic region where a country is located. Moreover, the model predicts an inverted U-shaped relationship between piracy and per capita income and reveals an apparent inverse relationship between individualism and software piracy. In addition, the results seem robust to the inclusion of additional covariants often employed in predicting piracy rates and the occurrence of property crime.
JOINT ANALYSIS OF X-RAY AND SUNYAEV–ZEL'DOVICH OBSERVATIONS OF GALAXY CLUSTERS USING AN ANALYTIC MODEL OF THE INTRACLUSTER MEDIUM

We perform a joint analysis of X-ray and Sunyaev–Zel'dovich effect data using an analytic model that describes the gas properties of galaxy clusters. The joint analysis allows the measurement of the cluster gas mass fraction profile and Hubble constant independent of cosmological parameters. Weak cosmological priors are used to calculate the overdensity radius within which the gas mass fractions are reported. Such an analysis can provide direct constraints on the evolution of the cluster gas mass fraction with redshift. We validate the model and the joint analysis on high signal-to-noise data from the Chandra X-ray Observatory and the Sunyaev–Zel'dovich Array for two clusters, A2631 and A2204.
Latent Tuberculosis: Models, Computational Efforts and the Pathogen’s Regulatory Mechanisms during Dormancy

Latent tuberculosis is a clinical syndrome that occurs after an individual has been exposed to the Mycobacterium tuberculosis (Mtb) Bacillus, the infection has been established and an immune response has been generated to control the pathogen and force it into a quiescent state. Mtb can exit this quiescent state where it is unresponsive to treatment and elusive to the immune response, and enter a rapid replicating state, hence causing infection reactivation. It remains a gray area to understand how the pathogen causes a persistent infection and it is unclear whether the organism will be in a slow replicating state or a dormant non-replicating state. The ability of the pathogen to adapt to changing host immune response mechanisms, in which it is exposed to hypoxia, low pH, nitric oxide (NO), nutrient starvation, and several other anti-microbial effectors, is associated with a high metabolic plasticity that enables it to metabolize under these different conditions. Adaptive gene regulatory mechanisms are thought to coordinate how the pathogen changes their metabolic pathways through mechanisms that sense changes in oxygen tension and other stress factors, hence stimulating the pathogen to make necessary adjustments to ensure survival. Here, we review studies that give insights into latency/dormancy regulatory mechanisms that enable infection persistence and pathogen adaptation to different stress conditions. We highlight what mathematical and computational models can do and what they should do to enhance our current understanding of TB latency.
Nigrosome 1 Detection at 3T MRI for the Diagnosis of Early-Stage Idiopathic Parkinson Disease: Assessment of Diagnostic Accuracy and Agreement on Imaging Asymmetry and Clinical Laterality

Nigrosomes are calbindin-poor zones within the substantia nigra pars compacta, and are the primary subregion where dopaminergic cells are lost in Parkinson disease. High-resolution 3D multiecho imaging was performed at 3T in 13 healthy subjects and 24 patients with idiopathic Parkinson disease confirmed by 18F-FP-CIT PET. Diagnostic sensitivity, specificity, and accuracy of the nigrosome 1 detection at 3T MR imaging was 100%, 84.6%, and 94.6%, respectively. Further, the clinical laterality was in high concordance with the laterality of the nigrosome 1 detection. BACKGROUND AND PURPOSE: In the early stages of idiopathic Parkinson disease, motor symptoms are usually asymmetric. We aimed to assess the feasibility of nigrosome 1 detection at 3T MR imaging to analyze the agreement of its asymmetry and clinical laterality. MATERIALS AND METHODS: High-resolution 3D multiecho imaging was performed at 3T MR imaging in 13 healthy subjects and 24 patients with idiopathic Parkinson disease confirmed by N-3-fluoropropyl-2-β-carbomethoxy-3-β-(4-iodophenyl) nortropane (18F-FP-CIT) PET. The nigrosome 1 detection findings by using the MR imaging data were rated as “normal,” “possibly abnormal,” and “abnormal” by 2 independent reviewers. The degree of 18F-FP-CIT binding was visually assessed in the caudate nucleus and putamen on PET images. Clinical laterality was evaluated by scores of the Unified Parkinson Disease Rating Scale, Part III. Asymmetry of the affected nigrosome 1 and the degree of 18F-FP-CIT binding were analyzed for agreement with clinical laterality. RESULTS: The diagnostic sensitivity, specificity, and accuracy of the nigrosome 1 detection at 3T MR imaging was 100%, 84.6%, and 94.6%, respectively. Interrater agreements for the abnormality and asymmetry of nigrosome 1 were excellent (κ = 0.863 and 0.835, respectively). In patients with idiopathic Parkinson disease, the agreement of asymmetry between clinical laterality and nigrosome 1 detection was good (κ = 0.724). The degree of the 18F-FP-CIT PET binding showed fair agreement (κ = 0.235) with clinical laterality. CONCLUSIONS: The abnormality involving nigrosome 1 can be detected at 3T MR imaging with an accuracy of 94.6%. The clinical laterality is in high concordance with the laterality of the nigrosome 1 detection at 3T (κ = 0.724).
Outcomes and Characteristics of Patients Undergoing Percutaneous Angioplasty Followed by Below-Knee or Above-Knee Amputation for Peripheral Artery Disease

Objective Little is known about long-term outcomes among patients who receive percutaneous angioplasty (PTA) for peripheral artery disease (PAD) then undergo below-knee or above-knee amputations. We sought to determine clinical outcomes associated with below-knee or above-knee amputation, along with possible explanatory factors and treatment strategies. Methods Using data from Taiwan’s National Health Insurance Research Database from 1997 to 2010, 7,568 adult patients were divided into three groups: lower extremity preserved (LE), below-knee amputation (BK) and above-knee amputation (AK). We assessed outcomes including major adverse cardiovascular events (MACE) and associated risk factors. Results Overall MACE was significantly higher in the AK group compared to the LE and BK groups, over a mean follow-up of 2.45 years (hazard ratio [HR]: 1.81; 95% confidence interval [CI]: 1.50–2.18 for AK vs. LE; HR: 1.67; 95% CI: 1.36–2.06 for AK vs. BK). However MACE were similar for the BK and LE groups (HR: 1.08; 95% CI: 0.98–1.20). Overall mortality was highest in the AK group (HR: 1.65, 95% CI: 1.34–2.04 for AK vs. BK). As for patient characteristics, atrial fibrillation was more prevalent in the AK group than in the BK group (17% vs. 7%). Independent risk factors associated with death after above- or below-knee amputation included advanced age, heart failure, dialysis, male gender and high patient volume. Conclusion The MACE rate was highest in the AK group, whereas the LE and BK groups were similar in this regard. Furthermore, overall mortality increased with larger area of amputation.