Miracle-dz/UniFAR-FTUs huggingface dataset:
Stage at diagnosis and survival in a multiethnic cohort of prostate cancer patients.

OBJECTIVES We evaluated the effects of socioeconomic status and comorbidity on stage of disease and survival among 1509 population-based prostate cancer patients. METHODS We applied logistic regression and Cox proportional hazards regression to data from Whites, African Americans, and Asian Americans who were diagnosed from 1987 to 1991. RESULTS Patients with existing comorbid conditions were less likely than those without these conditions to be diagnosed with advanced cancer. Compared with Whites, African Americans (odds ratio [OR] = 1.5; 95% confidence interval [CI] = 1.1, 2.2) and foreign-born Asian Americans (OR = 1.6; 95% CI = 1.0, 2.4) were more likely to be diagnosed with advanced cancer. Among men with localized disease, prostate cancer death rates were higher for African Americans than for Whites (death rate ratio = 2.3; 95% CI = 1.2, 4.7). CONCLUSIONS These findings support the need for further investigation of factors that affect access to and use of health care among African Americans and Asian Americans.
Performance enhancement of DS-CDMA system using overlapping sectors with interference avoidance

A cellular system with overlapping sectors is proposed to enhance system performance through interference avoidance. In such system, users lie within the coverage of more than one sector, yet each user only chooses one sector for signal transmission and reception. The choices of sectors among different users affect the interference level experienced by others. It is shown in this paper that their mutual interference is minimized by choosing a good sector combination. We investigate the potential benefits of proposed technique in two scenarios: an orthogonal and a non-orthogonal CDMA system. In the former case, spreading code allocation combined with sector selection reduces the required number of code to support all users compared to conventional non-overlapping sector system. For the non-orthogonal CDMA system, the enhancement takes the form of multiple access interference reduction. Simulations results show that its improvement is pronounced and can be further enhanced by increasing the number of overlapping sectors.
Energy, ecology and the distribution of microbial life

Mechanisms that govern the coexistence of multiple biological species have been studied intensively by ecologists since the turn of the nineteenth century. Microbial ecologists in the meantime have faced many fundamental challenges, such as the lack of an ecologically coherent species definition, lack of adequate methods for evaluating population sizes and community composition in nature, and enormous taxonomic and functional diversity. The accessibility of powerful, culture-independent molecular microbiology methods offers an opportunity to close the gap between microbial science and the main stream of ecological theory, with the promise of new insights and tools needed to meet the grand challenges humans face as planetary engineers and galactic explorers. We focus specifically on resources related to energy metabolism because of their direct links to elemental cycling in the Earth's history, engineering applications and astrobiology. To what extent does the availability of energy resources structure microbial communities in nature? Our recent work on sulfur- and iron-oxidizing autotrophs suggests that apparently subtle variations in the concentration ratios of external electron donors and acceptors select for different microbial populations. We show that quantitative knowledge of microbial energy niches (population-specific patterns of energy resource use) can be used to predict variations in the abundance of specific taxa in microbial communities. Furthermore, we propose that resource ratio theory applied to micro-organisms will provide a useful framework for identifying how environmental communities are organized in space and time.
A Fair Resource Allocation Algorithm for Peer-to-Peer Overlays

Over the past few years, peer-to-peer (P2P) systems have become very popular for constructing overlay networks of many nodes (peers) that allow users geographically distributed to share data and resources. One non-trivial question is how to distribute the data in a fair and fully decentralized manner among the peers. This is important because it can improve resource usage, minimize network latencies and reduce the volume of unnecessary traffic incurred in large-scale P2P systems. In this paper we present a technique for fair resource allocation in unstructured peer-to-peer systems. Our technique uses the fairness index of a distribution as a measure of fairness and shows how to optimize the fairness of the distribution using only local decisions. Load balancing is achieved by replicating documents across multiple nodes in the system. Our experimental results demonstrate that our technique is scalable, has low overhead and achieves good load balance even under skewed demand.
Online Display Advertising: Targeting and Obtrusiveness

We use data from a large-scale field experiment to explore what influences the effectiveness of online advertising. We find that matching an ad to website content and increasing an ad's obtrusiveness independently increase purchase intent. However, in combination, these two strategies are ineffective. Ads that match both website content and are obtrusive do worse at increasing purchase intent than ads that do only one or the other. This failure appears to be related to privacy concerns: the negative effect of combining targeting with obtrusiveness is strongest for people who refuse to give their income and for categories where privacy matters most. Our results suggest a possible explanation for the growing bifurcation in Internet advertising between highly targeted plain text ads and more visually striking but less targeted ads.
DW09849, a Selective Phosphatidylinositol 3-Kinase (PI3K) Inhibitor, Prevents PI3K Signaling and Preferentially Inhibits Proliferation of Cells Containing the Oncogenic Mutation p110α (H1047R)

Phosphatidylinositol 3-kinase, α isoform (PI3Kα) plays essential roles in cell metabolism, growth, and proliferation and has been validated as a promising anticancer target. In an effort to search for new PI3Kα-selective inhibitors, DW series compounds were designed and synthesized aiming to reduce the off-target effects of their parent compound PIK-75 [2-methyl-5-nitro-1-benzenesulfonic acid 2-[(6-bromoimidazo[1,2-a]pyridin-3-yl)methylene]-1-methylhydrazide], which was reported to selectively target PI3Kα. A series of compounds named DW series potently inhibited the kinase activity of PI3Kα with little activity against PI3K-related protein kinases and a panel of 15 tyrosine kinases. Similar to PIK-75, DW series compounds were more potent to inhibit PI3Kα among four class I PI3K isoforms, whereas a representative compound DW09849 [(E)-N′-((6-bromoimidazo[1,2-a]pyridin-3-yl)methylene)-N-ethyl-2-methyl-5-nitrobenzohydrazide] displayed distinct binding mode compared with PIK-75. Although DW series compounds inhibited proliferation of rhabdomyosarcoma RH30 cells at elevated 50% inhibitory concentrations (IC50) in comparison with PIK-75, they were more selective than PIK-75 to inhibit PI3K signaling in the cellular context. In particular, DW09849 significantly and persistently blocked PI3K/protein kinase B signaling in RH30 cells, which consequently arrested RH30 cells in the G1 phase. Moreover, DW09849 selectively suppressed the proliferation and clonogenesis of transformed RK3E/HR cells harboring oncogenic mutation of p110α H1047R, as well as a panel of human breast cancer cells containing mutated PI3Kα, which is consistent with the finding that DW09849 demonstrated preference against H1047R mutated PI3Kα in molecular docking stimulation. These results suggest that DW series compounds, especially DW09849, selectively targeting PI3Kα with less off-target effects than PIK-75, provide new clues for the design and discovery of new specific PI3Kα inhibitors for cancer therapy.
Anthocyanin-Rich Purple Corn Extract Inhibit Diabetes-Associated Glomerular Angiogenesis

Diabetic nephropathy (DN) is one of the major diabetic complications and the leading cause of end-stage renal disease. Abnormal angiogenesis results in new vessels that are often immature and play a pathological role in DN, contributing to renal fibrosis and disrupting glomerular failure. Purple corn has been utilized as a daily food and exerts disease-preventive activities. This study was designed to investigate whether anthocyanin-rich purple corn extract (PCE) prevented glomerular angiogenesis under hyperglycemic conditions. Human endothelial cells were cultured in conditioned media of mesangial cells exposed to 33 mM high glucose (HG-HRMC-CM). PCE decreased endothelial expression of vascular endothelial growth factor (VEGF) and hypoxia inducible factor (HIF)-1α induced by HG-HRMC-CM. Additionally, PCE attenuated the induction of the endothelial marker of platelet endothelial cell adhesion molecule (PECAM)-1 and integrin β3 enhanced in HG-HRMC-CM. Endothelial tube formation promoted by HG-HRMC-CM was disrupted in the presence of PCE. In the in vivo study employing db/db mice treated with 10 mg/kg PCE for 8 weeks, PCE alleviated glomerular angiogenesis of diabetic kidneys by attenuating the induction of VEGF and HIF-1α. Oral administration of PCE retarded the endothelial proliferation in db/db mouse kidneys, evidenced by its inhibition of the induction of vascular endothelium-cadherin, PECAM-1 and Ki-67. PCE diminished the mesangial and endothelial induction of angiopoietin (Angpt) proteins under hypeglycemic conditions. The induction and activation of VEGF receptor 2 (VEGFR2) were dampened by treating PCE to db/db mice. These results demonstrate that PCE antagonized glomerular angiogenesis due to chronic hyperglycemia and diabetes through disturbing the Angpt-Tie-2 ligand-receptor system linked to renal VEGFR2 signaling pathway. Therefore, PCE may be a potent therapeutic agent targeting abnormal angiogenesis in DN leading to kidney failure.
Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses

The design of convex, calibrated surrogate losses, whose minimization entails consistency with respect to a desired target loss, is an important concept to have emerged in the theory of machine learning in recent years. We give an explicit construction of a convex least-squares type surrogate loss that can be designed to be calibrated for any multiclass learning problem for which the target loss matrix has a low-rank structure; the surrogate loss operates on a surrogate target space of dimension at most the rank of the target loss. We use this result to design convex calibrated surrogates for a variety of subset ranking problems, with target losses including the precision@q, expected rank utility, mean average precision, and pairwise disagreement.
A Reinforcement Learning Algorithm for Agent-Based Modeling of Investment in Electricity Markets

We develop a reinforcement-learning algorithm to model investment in electricity markets, by extending the n-armed bandit algorithm, and prove its equilibrium properties. We show that there is a stationary state of the investment game in which no additional investment or retirement of plants takes place. We model a spot electricity market together with investment decisions. Our experiments suggest that in the long-run electricity markets will tend to be short of capacity, we further analyze the evolution of the technological mix of the market.
Evaluation and Design of Filters Using a Taylor Series Expansion

We describe a new method for analyzing, classifying, and evaluating filters that can be applied to interpolation filters as well as to arbitrary derivative filters of any order. Our analysis is based on the Taylor series expansion of the convolution sum. Our analysis shows the need and derives the method for the normalization of derivative filter weights. Under certain minimal restrictions of the underlying function, we are able to compute tight absolute error bounds of the reconstruction process. We demonstrate the utilization of our methods to the analysis of the class of cubic BC-spline filters. As our technique is not restricted to interpolation filters, we are able to show that the Catmull-Rom spline filter and its derivative are the most accurate reconstruction and derivative filters, respectively, among the class of BC-spline filters. We also present a new derivative filter which features better spatial accuracy than any derivative BC-spline filter, and is optimal within our framework. We conclude by demonstrating the use of these optimal filters for accurate interpolation and gradient estimation in volume rendering.
Evolution by Non-Convex Functionals

We establish a semi-group solution concept for flows that are generated by generalized minimizers of non-convex energy functionals. We use relaxation and convexification to define these generalized minimizers. The main part of this work consists in exemplary validation of the solution concept for a non-convex energy functional. For rotationally invariant initial data it is compared with the solution of the mean curvature flow equation. The basic example relates the mean curvature flow equation with a sequence of iterative minimizers of a family of non-convex energy functionals. Together with the numerical evidence this corroborates the claim that the non-convex semi-group solution concept defines, in general, a solution of the mean curvature equation.
Pure ductal carcinoma in situ: kinetic and morphologic MR characteristics compared with mammographic appearance and nuclear grade.

PURPOSE To retrospectively compare the kinetic and morphologic characteristics of pure ductal carcinoma in situ (DCIS) lesions depicted on dynamic contrast material-enhanced magnetic resonance (MR) images with the nuclear grade and conventional mammographic appearance of these lesions. MATERIALS AND METHODS This HIPAA-compliant retrospective study was institutional review board approved, and informed patient consent was waived. Seventy-eight patients with 79 histologically proved pure DCIS lesions were selected. There were 17 low-nuclear-grade, 26 intermediate-nuclear-grade, 30 high-nuclear-grade, and six unclassified lesions. Sixty-five lesions were classified as fine pleomorphic, fine linear, or fine linear-branching calcifications (n = 31); amorphous or indistinct calcifications (n = 18); noncalcified mass (n = 10); or occult (n = 6) at conventional (x-ray) mammography. One experienced radiologist analyzed lesion morphology and kinetic curve shape according to the Breast Imaging Reporting and Data System lexicon. Initial enhancement percentage, time to peak enhancement (T(peak)), and signal enhancement ratio (a measure of washout) were calculated for each lesion. RESULTS Of the 79 pure DCIS lesions, 20 (25%) exhibited enhancement plateau curves and 35 (44%) exhibited washout curves. The lesions with a masslike appearance on mammograms exhibited more suspicious kinetic characteristics (mean T(peak) approximately 2 minutes) than did the lesions with amorphous or indistinct calcifications (mean T(peak) = 4.4 minutes). There was no significant difference in enhancement kinetic properties across the nuclear grades. Lesion morphology was predominantly nonmass, with clumped or heterogeneous enhancement in a segmental or linear distribution. CONCLUSION The pure DCIS lesions exhibited washout, plateau, and persistent enhancement curves. Enhancement kinetic characteristics varied with mammographic appearance but not with nuclear grade. SUPPLEMENTAL MATERIAL http://radiology.rsnajnls. org/cgi/content/full/245/3/684/DC1.
TMEM16A is associated with voltage-gated calcium channels in mouse retina and its function is disrupted upon mutation of the auxiliary α2δ4 subunit

Photoreceptors rely upon highly specialized synapses to efficiently transmit signals to multiple postsynaptic targets. Calcium influx in the presynaptic terminal is mediated by voltage-gated calcium channels (VGCC). This event triggers neurotransmitter release, but also gates calcium-activated chloride channels (TMEM), which in turn regulate VGCC activity. In order to investigate the relationship between VGCC and TMEM channels, we analyzed the retina of wild type (WT) and Cacna2d4 mutant mice, in which the VGCC auxiliary α2δ4 subunit carries a nonsense mutation, disrupting the normal channel function. Synaptic terminals of mutant photoreceptors are disarranged and synaptic proteins as well as TMEM16A channels lose their characteristic localization. In parallel, calcium-activated chloride currents are impaired in rods, despite unaltered TMEM16A protein levels. Co-immunoprecipitation revealed the interaction between VGCC and TMEM16A channels in the retina. Heterologous expression of these channels in tsA-201 cells showed that TMEM16A associates with the CaV1.4 subunit, and the association persists upon expression of the mutant α2δ4 subunit. Collectively, our experiments show association between TMEM16A and the α1 subunit of VGCC. Close proximity of these channels allows optimal function of the photoreceptor synaptic terminal under physiological conditions, but also makes TMEM16A channels susceptible to changes occurring to calcium channels.
Defective embryogenesis with angiotensin II receptor antagonists in pregnancy

With advancement of maternal age, practitioners are more likely to care for women with pre-existing medical conditions. Drugs involved in such therapy may have a direct action on fetal wellbeing. It is essential that all who are involved in the care of women in child-bearing years have access to the knowledge of drug effects on the developing fetus. Essential hypertension occurs with increasing frequency as maternal age advances. Management in pregnancy provides many challenges for the obstetrician—ensuring that the pregnancy continues safely to a gestation providing optimal fetal survival while avoiding serious maternal complications. Many drugs are available for the management of essential hypertension, and if a mother conceives while on treatment, she can be reassured that most are not teratogenic. Treatment can then be reviewed in a specialist clinic enabling maintenance of blood pressure control during transfer onto medication most suitable for continuation in pregnancy. It has been well documented that angiotensin converting enzyme (ACE) inhibitors, while safe in the first trimester, pose significant risks to the fetus if their use is extended beyond this time, and therefore their use is contraindicated beyond 12 weeks of gestation. New drugs such as angiotensin II receptor antagonists affect the same pathway and are also postulated to have the same adverse effects. We report a case of the prolonged use of candesartan, a long acting angiotensin II receptor antagonist in pregnancy.
A Personalized CAI Courseware System

The network-based CAI (Computer Assisted Instruction) courseware system,Compared with the traditional one, has its advantages and disadvantages. After give an introduction to the ongoing development of distance learning and E-learning. This paper combined a hierarchical Level-Generate algorithm with the Data Mining theory, to provide the students with a personalized courseware system by building a CAI courseware tree. With courseware tree, the system can recommend useful materials to each student based on the performance of individual student. If the system computes the personality of each student, the complexity is higher and hard to implement. Thus, mining on students is necessary. Using Hamming distance theory, students were clustered into different groups based on the courseware they accessed. Computer Assisted Instruction, abbreviated as CAI, is now widely used in all kinds of educational applications, especially the distant learning and network-based tutor systems, while the network technology is prevailed all over the world. However, the distance learning and most applications of the courseware are restricted to traditional classroom and only used locally. The Internet profoundly changed the way people communicate and becomes available everywhere. The traditional teaching system is now challenged by the Internet and many researchers exert great effort on developing the network based learning systems to assistant the traditional classroom teaching. The network based CAI courseware, with its vivid appearance, interchangeable ability and the breakthrough of time and space, declares an evaluation to the traditional teaching model. During the past several years, researchers provide the educators with some tools that auxiliary the traditional teaching systems. In (1), C. Romero and S. Ventura survey the application of data mining to traditional educational systems, especially web-based well-known learning content management systems, and adaptive and intelligent web-based educational systems. The author firstly compared the difference between e-commerce and e-learning. The authors also distinguished between three different types of web-based education systems: particular web-based courses, well-known learning content management systems, and adaptive and intelligent web-based educational systems. Then, four kinds of data mining techniques were presented: statistics and visualization; clustering, classification and outlier detection; association rule mining and pattern mining; and text mining.
A new sesquiterpene lactone from Salvia plebeia

A new eudesmanolide, 1α-acetoxy-8α,9β-dihydroxy-2-oxo-eudesman-3,7(11)-dien-8,12-olide (2), together with a known eudesmanolide, 1α-acetoxy-8α-hydroxy-2-oxo-eudesman-3,7(11)-dien-8,12-olide (1), and a known flavone, 4′,5,7-trihydroxy-6-methoxyflavone (3), was isolated from the plant of Salvia plebeia. Three compounds were structurally elucidated by spectroscopic and chemical methods.
Preperceptual images, processing time, and perceptual units in auditory perception.

Publisher Summary The primary recognition process represents a synthesis of the preperceptual representation of these speech sounds. This chapter focuses on the temporal course of the primary recognition or synthesis process. It presents a schematic representation of the primary recognition process in the framework of an information-processing model. This representation of the recognition process rests on certain assumptions about the structure and function of the human information-processing system: (1) the preperceptual auditory image holds information about the stimulus and this information remain there until primary recognition has occurred, and (2) a description of this stimulus information is available in long-term memory so that recognition can occur. The primary recognition process finds the best match between the preperceptual image and the description in long-term memory. Recognition of the stimulus involves a transformation of the information in the preperceptual auditory image, resulting in a synthesized percept of the stimulus. The stimulus for recognizing speech is a sound pattern that can be described by fluctuations in sound pressure over time.