Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of Sepsis in Preterm Infants by Fecal Volatile Organic Compounds Analysis: A Proof of Principle Study

Objectives: Several studies associated altered gut microbiota composition in preterm infants with late-onset sepsis (LOS), up to days before clinical onset of sepsis. Microbiota analysis as early diagnostic biomarker is, however, in clinical practice currently not feasible because of logistic aspects and high costs. Therefore, we hypothesized that analysis of fecal volatile organic compounds (VOCs) may serve as noninvasive biomarker to predict LOS at a preclinical stage, because VOC reflect the composition and activity of intestinal microbial communities. Methods: In a prospective multicenter study, fecal samples were collected daily from infants with a gestational age of <30 weeks. VOC signatures of fecal samples from infants with LOS, collected up to 5 days before diagnosis, were analyzed by means of an electronic nose technology (Cyranose 320) and compared to matched controls. Results: Fecal VOC profiles of infants with LOS (n = 36) could be discriminated from controls (n = 40) at 3 days (area under the curve [±95% confidence interval], P value, sensitivity, specificity; 70.2 [52.2–88.3], 0.033, 57.1%, 61.5%), 2 days (77.7 [62.7–92.7], 0.050, 75.0%, 70.8%), and 1 day (70.4 [49.6–91.3], 0.037, 64.3%, 64.3%) before the onset of LOS. Conclusions: Fecal VOC profiles of preterm infants with LOS could be discriminated from matched controls, up to 3 days before clinical onset of the disease, underlining the hypothesis that intestinal microbiota may play an etiological role in LOS. Notably, VOC profiling is clinically feasible and the potential of this technique in the early detection of LOS needs to be confirmed in future studies.
Phase locking value revisited: teaching new tricks to an old dog

Objective. Despite the increase in calculation power over the last few decades, the estimation of brain connectivity is still a tedious task. The high computational cost of the algorithms escalates with the square of the number of signals evaluated, usually in the range of thousands. In this work we propose a re-formulation of a widely used algorithm that allows the estimation of whole brain connectivity in much smaller times. Approach. We start from the original implementation of phase locking value (PLV) and re-formulated it in a computationally very efficient way. What is more, this formulation stresses its strong similarity with coherence, which we used to introduce two new metrics insensitive to zero lag synchronization: the imaginary part of PLV (iPLV) and its corrected counterpart (ciPLV). Main results. The new implementation of PLV avoids some highly CPU-expensive operations and achieves a 100-fold speedup over the original algorithm. The new derived metrics were highly robust in the presence of volume conduction. Moreover, ciPLV proved capable of ignoring zero-lag connectivity, while correctly estimating nonzero-lag connectivity. Significance. Our implementation of PLV makes it possible to calculate whole-brain connectivity in much shorter times. The results of the simulations using ciPLV suggest that this metric is ideal to measure synchronization in the presence of volume conduction or source leakage effects.
Opposing ends of the spectrum: Exploring trust in scientific and religious authorities

Given the ethical questions that surround emerging science, this study is interested in studying public trust in scientific and religious authorities for information about the risks and benefits of science. Using data from a nationally representative survey of American adults, we employ regression analysis to better understand the relationships between several variables—including values, knowledge, and media attention—and trust in religious organizations and scientific institutions. We found that Evangelical Christians are generally more trusting of religious authority figures to tell the truth about the risks and benefits of science and technology, and only slightly less likely than non-Evangelicals to trust scientific authorities for the same information. We also found that many Evangelicals use mediated information and science knowledge differently than non-Evangelicals, with both increased knowledge and attention to scientific media having positive impacts on trust in scientific authorities among the latter, but not the former group.
Potent antitumor effect of TRAIL mediated by a novel adeno‐associated viral vector targeting to telomerase activity for human hepatocellular carcinoma

Adeno‐associated virus (AAV) has rapidly become a promising gene delivery vehicle for its excellent advantages of low pathogenicity and long‐term gene expression. However, lack of tissue specificity caused low efficiency of AAV transfer to target cells. The promoter of human telomerase reverse transcriptase (hTERT) has been implicated in mediating gene expression in cancer cells as hTERT is transcriptionally upregulated in most cancer cells. Thereby, the hTERT promoter becomes a good candidate to enhance the targeting efficiency of AAV in cancer cells. Tumor necrosis factor‐related apoptosis‐inducing ligand (TRAIL) functions as a soluble cytokine to selectively kill various cancer cells without toxicity to most normal cells. It remains to be determined whether the hTERT promoter can efficiently mediate TRAIL gene therapy in cancer cells using AAV vector.
Universal Growth in Production Economies

We study a simple variant of the von Neumann model of an expanding economy, in which multiple producers produce goods according to their production function. The players trade their goods at the market and then use the bundles acquired as inputs for the production in the next round. We show that a simple decentralized dynamic, where players update their bids proportionally to how useful the investments were in the past round, leads to growth of the economy in the long term (whenever growth is possible) but also creates unbounded inequality, i.e. very rich and very poor players emerge. We analyze several other phenomena, such as how the relation of a player with others influences its development and the Gini index of the system.
Innovative Plasmonic Nanostructures Based on Translation or Scale Invariance for Nano-Photonics

In this thesis innovative plasmonic nanostructures have been studied under many aspects, from the synthesis to the characterization and finite elements modeling. We focused on two kinds of ordered nanostructures: (i) those exhibiting bidimensional (2D) translational invariance and (ii) those possessing autosimilarity and fractal character. Three kinds of nanostructures characterized by 2D periodicity have been analyzed: nanoprism arrays (NPA), nanohole arrays (NHA) and quasishell arrays (QSA), whose building blocks are, respectively, metallic prisms with triangular-like base, holes passing through a metal thin film and metallic non-closed shells around a dielectric core. The first kind is the base for biosensors, and in this case an optimization study has been performed to maximize sensivity. The second one is the key for a fine control of the emission from excited Erbium ions, which overcomes the previous results obtained without nano-patterning. The third one is based on a novel approach to bi-metallic nanostructures fabrication, enabling the realization of plasmonic and magneto-plasmonic materials. The patterning at nano scales has been made cost-effective, as all these periodic systems are based on a cheap synthesis technique. Finally, nanostructures showing scale invariance, fractals, have been synthesized and thoroughly studied, both experimentally and with simulations. As a result, a universal role of correlation has been recognized in these plasmonic systems. Overall, this thesis gives insights on the physics underlying the plasmonic response of nanostructures which base their outstanding properties on symmetry, either on scaling or on translation.
Mechanisms of Reference Frame Selection in Spatial Term Use: Computational and Empirical Studies

Previous studies have shown that multiple reference frames are available and compete for selection during the use of spatial terms such as "above. " However, the mechanisms that underlie the selection process are poorly understood. In the current paper we present two experiments and a comparison of three computational models of selection to shed further light on the nature of reference frame selection. The three models are drawn from different areas of human cognition, and we assess whether they may be applied to a reference frame selection by examining their ability to account for both existing and new empirical data comprising acceptance rates, response times, and response time distributions. These three models are the competitive shunting model (Schultheis, ), the leaky competing accumulator (LCA) model (Usher & McClelland, ), and a lexical selection model (Howard, Nickels, Coltheart, & Cole-Virtue, ). Model simulations show that only the LCA model satisfactorily accounts for the empirical observations. The key properties of this model that seem to drive its success are its bounded linear activation function, its number and type of processing stages, and its use of decay. Uncovering these critical properties has important implications for our understanding not only of spatial term use, in particular, but also of conflict and selection in human cognition more generally.
The changing epidemiology of Ebstein’s anomaly and its relationship with maternal mental health conditions: a European registry-based study

Abstract Objectives The aim of this study was to describe the epidemiology of Ebstein’s anomaly in Europe and its association with maternal health and medication exposure during pregnancy. Design We carried out a descriptive epidemiological analysis of population-based data. Setting We included data from 15 European Surveillance of Congenital Anomalies Congenital Anomaly Registries in 12 European countries, with a population of 5.6 million births during 1982–2011. Participants Cases included live births, fetal deaths from 20 weeks gestation, and terminations of pregnancy for fetal anomaly. Main outcome measures We estimated total prevalence per 10,000 births. Odds ratios for exposure to maternal illnesses/medications in the first trimester of pregnancy were calculated by comparing Ebstein’s anomaly cases with cardiac and non-cardiac malformed controls, excluding cases with genetic syndromes and adjusting for time period and country. Results In total, 264 Ebstein’s anomaly cases were recorded; 81% were live births, 2% of which were diagnosed after the 1st year of life; 54% of cases with Ebstein’s anomaly or a co-existing congenital anomaly were prenatally diagnosed. Total prevalence rose over time from 0.29 (95% confidence interval (CI) 0.20–0.41) to 0.48 (95% CI 0.40–0.57) (p<0.01). In all, nine cases were exposed to maternal mental health conditions/medications (adjusted odds ratio (adjOR) 2.64, 95% CI 1.33–5.21) compared with cardiac controls. Cases were more likely to be exposed to maternal β-thalassemia (adjOR 10.5, 95% CI 3.13–35.3, n=3) and haemorrhage in early pregnancy (adjOR 1.77, 95% CI 0.93–3.38, n=11) compared with cardiac controls. Conclusions The increasing prevalence of Ebstein’s anomaly may be related to better and earlier diagnosis. Our data suggest that Ebstein’s anomaly is associated with maternal mental health problems generally rather than lithium or benzodiazepines specifically; therefore, changing or stopping medications may not be preventative. We found new associations requiring confirmation.
Patch-Based Low-Rank Minimization for Image Denoising

Patch-based sparse representation and low-rank approximation for image processing attract much attention in recent years. The minimization of the matrix rank coupled with the Frobenius norm data fidelity can be solved by the hard thresholding filter with principle component analysis (PCA) or singular value decomposition (SVD). Based on this idea, we propose a patch-based low-rank minimization method for image denoising, which learns compact dictionaries from similar patches with PCA or SVD, and applies simple hard thresholding filters to shrink the representation coefficients. Compared to recent patch-based sparse representation methods, experiments demonstrate that the proposed method is not only rather rapid, but also effective for a variety of natural images, especially for texture parts in images.
ISO 12189 standard for the preclinical evaluation of posterior spinal stabilization devices – I: Assembly procedure and validation

The International Standardization Organization introduced standard 12189 for the preclinical evaluation of the mechanical reliability of posterior stabilization devices. The well-known vertebrectomy model formalized in standard F1717 by the American Society for Testing and Materials was modified with the introduction of a modular anterior support made up of three calibrated springs, which allows to describe a more realistic scenario, closer to the effective clinical use, as well to test even very flexible and dynamic posterior stabilization implants. Despite these important improvements, ISO 12189 received very little attention in the literature. The aim of the work is to provide a systematic procedure for the assembly and validation of a finite element model capable of describing the experimental test according to ISO 12189. The validated finite element model is able to catch very well the effective stiffness of the unassembled and assembled constructs (percentage differences <2% and <10%, respectively). As concern the assembled construct, the experimentally measured and predicted strains were found in a good agreement (R2 > 0.75, root mean square error < 30%), but the procedure without precompression lead to much better results (R2 > 0.96, root mean square error < 10%). Given the prediction errors of the assembled construct fall within the experimental range of repeatability, the finite element model can be systematically implemented to support the mechanical design of a variety of spinal implants, to quantitatively investigate the load-sharing mechanism, as well as to investigate the loading conditions set by ISO 12189 standard.
Learning Time/Memory-Efficient Deep Architectures with Budgeted Super Networks

We propose to focus on the problem of discovering neural network architectures efficient in terms of both prediction quality and cost. For instance, our approach is able to solve the following tasks: learn a neural network able to predict well in less than 100 milliseconds or learn an efficient model that fits in a 50 Mb memory. Our contribution is a novel family of models called Budgeted Super Networks (BSN). They are learned using gradient descent techniques applied on a budgeted learning objective function which integrates a maximum authorized cost, while making no assumption on the nature of this cost. We present a set of experiments on computer vision problems and analyze the ability of our technique to deal with three different costs: the computation cost, the memory consumption cost and a distributed computation cost. We particularly show that our model can discover neural network architectures that have a better accuracy than the ResNet and Convolutional Neural Fabrics architectures on CIFAR-10 and CIFAR-100, at a lower cost.
UNDEAD: Detecting and preventing deadlocks in production software

Deadlocks are critical problems afflicting parallel applications, causing software to hang with no further progress. Existing detection tools suffer not only from significant recording performance overhead, but also from excessive memory and/or storage overhead. In addition, they may generate numerous false alarms. Subsequently, after problems have been reported, tremendous manual effort is required to confirm and fix these deadlocks. This paper designs a novel system, UnDead, that helps defeat deadlocks in production software. Different from existing detection tools, UnDead imposes negligible runtime performance overhead (less than 3 % on average) and small memory overhead (around 6%), without any storage consumption. After detection, UnDead automatically strengthens erroneous programs to prevent future occurrences of both existing and potential deadlocks, which is similar to the existing work—Dimmunix. However, UnDead exceeds Dimmunix with several orders of magnitude lower performance overhead, while eliminating numerous false positives. Extremely low runtime and memory overhead, convenience, and automatic prevention make UnDead an always-on detection tool, and a "band-aid" prevention system for production software.
Safety and Tolerability of Ultrasmall Superparamagnetic Iron Oxide Contrast Agent: Comprehensive Analysis of a Clinical Development Program

Background:Because of its cellular uptake pattern, ferumoxtran-10 may be potentially useful for the imaging of a variety of diseases (eg, atheroma, multiple sclerosis, stroke, renal graft rejection, glomerulonephritis and brain tumors, in addition to differentiation of metastatic and nonmetastatic lymph nodes). The aim of this article is to present a comprehensive review of the safety and tolerability of ferumoxtran-10 as reported during clinical development of the compound as an ultrasmall superparamagnetic iron oxide contrast agent for use in magnetic resonance imaging. Materials and Methods:The safety profile of ferumoxtran-10 was assessed using pooled data from 37 phase I to III clinical studies in 1777 adults (1663 received the contrast agent [1527 patients and 136 healthy volunteers], 75 received placebo, and 39 patients were enrolled but did not receive study medication). Results:At least one adverse event was reported in 23.2% of patients who received ferumoxtran-10. Adverse events were of mild-to-moderate severity in 86.3% of patients in the ferumoxtran-10 group. At least 1 event considered by the investigator to be related to study treatment was reported in 18.2% of patients in the ferumoxtran-10 group. The most commonly reported treatment-related adverse events were back pain, pruritus, headache, and urticaria. A total of 44 patients (2.6%) in the ferumoxtran-10 group reported 76 serious adverse event (SAE). Only 7 SAEs (0.42%) were considered to be treatment-related (anaphylactic shock, chest pain, dyspnea, skin rash, oxygen saturation decreased, and 2 cases of hypotension). There were 12 deaths, only one of which (anaphylactic shock) was considered to be related to ferumoxtran-10 which was administered by bolus injection of undiluted product, a mode of administration that is no longer recommended. Results in high-risk groups of patients including the elderly and those with hepatic, renal or cardiovascular disease seemed to show no cause for special clinical concern in these groups. Conclusions:Clinical experience to date therefore shows ferumoxtran-10 to be a well tolerated contrast agent.
Nucleate Pool Boiling Characteristics From a Horizontal Microheater Array

Title of Document: NUCLEATE POOL BOILING CHARACTERISTICS FROM A HORIZONTAL MICROHEATER ARRAY Christopher Henry, Ph.D., 2005 Directed By: Associate Professor, Jungho Kim, Department of Mechanical Engineering Pool boiling heat transfer measurements from different heater sizes and shapes were obtained in low-g (0.01 g) and high-g (1.7 g) aboard the NASA operated KC-135 aircraft. Boiling on 4 square heater arrays of different size (0.65 mm, 2.62 mm, 7.29 mm, 49 mm) was investigated. The heater arrays consist of 96 independent square heaters that were maintained at an isothermal boundary condition using control circuitry. A fractional factorial experimental method was designed to investigate the effects of bulk liquid subcooling, wall superheat, gravitational level, heater size and aspect ratio, and dissolved gas concentration on pool boiling behavior. In high-g, pool boiling behavior was found to be consistent with classical models for nucleate pool boiling in 1-g. For heater sizes larger than the isolated bubble departure diameter predicted from the Fritz correlation, the transport process was dominated by the ebullition cycle and the primary mechanisms for heat transfer were transient conduction and microconvection to the rewetting liquid in addition to latent heat transfer. For heater sizes smaller than this value, the boiling process is dominated by surface tension effects which can cause the formation of a single primary bubble that does not depart the heater surface and a strong reduction in heat transfer. In low-g, pool boiling performance is always dominated by surface tension effects and two mechanisms were identified to dominate heat and mass transport: 1) satellite bubble coalescence with the primary bubble which tends to occur at lower wall superheats and 2) thermocapillary convection at higher wall superheats and higher bulk subcoolings. Satellite bubble coalescence was identified to be the CHF mechanism under certain conditions. Thermocapillary convection caused a dramatic enhancement in heat transfer at higher subcoolings and is modeled analytically. Lastly, lower dissolved gas concentrations were found to enhance the heat transfer in low-g. At higher dissolved gas concentrations, bubbles grow larger and dryout a larger portion of the heater surface. NUCLEATE POOL BOILING CHARACTERISTICS FROM A HORIZONTAL MICROHEATER ARRAY By Christopher Douglas Henry Thesis or Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, College Park, in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2005 Advisory Committee: Associate Professor Jungho Kim, Chair Professor Marino Di Marzo Professor James Duncan Associate Professor Greg Jackson Associate Professor Gary Pertmer © Copyright by Christopher Douglas Henry 2005
Oncogenic Ras stimulates Eiger/TNF exocytosis to promote growth

Oncogenic mutations in Ras deregulate cell death and proliferation to cause cancer in a significant number of patients. Although normal Ras signaling during development has been well elucidated in multiple organisms, it is less clear how oncogenic Ras exerts its effects. Furthermore, cancers with oncogenic Ras mutations are aggressive and generally resistant to targeted therapies or chemotherapy. We identified the exocytosis component Sec15 as a synthetic suppressor of oncogenic Ras in an in vivo Drosophila mosaic screen. We found that oncogenic Ras elevates exocytosis and promotes the export of the pro-apoptotic ligand Eiger (Drosophila TNF). This blocks tumor cell death and stimulates overgrowth by activating the JNK-JAK-STAT non-autonomous proliferation signal from the neighboring wild-type cells. Inhibition of Eiger/TNF exocytosis or interfering with the JNK-JAK-STAT non-autonomous proliferation signaling at various steps suppresses oncogenic Ras-mediated overgrowth. Our findings highlight important cell-intrinsic and cell-extrinsic roles of exocytosis during oncogenic growth and provide a new class of synthetic suppressors for targeted therapy approaches.