Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute intermittent hypoxia with concurrent hypercapnia evokes P2X and TRPV1 receptor‐dependent sensory long‐term facilitation in naïve carotid bodies

Activity‐dependent plasticity can be induced in carotid body (CB) chemosensory afferents without chronic intermittent hypoxia (CIH) preconditioning by acute intermittent hypoxia coincident with bouts of hypercapnia (AIH‐Hc). Several properties of this acute plasticity are shared with CIH‐dependent sensory long‐term facilitation (LTF) in that induction is dependent on 5‐HT, angiotensin II, protein kinase C and reactive oxygen species. Several properties differ from CIH‐dependent sensory LTF; H2O2 appears to play no part in induction, whereas maintenance requires purinergic P2X2/3 receptor activation and is dependent on transient receptor potential vanilloid type 1 (TRPV1) receptor sensitization. Because P2X2/3 and TRPV1 receptors are located in carotid sinus nerve (CSN) terminals but not presynaptic glomus cells, a primary site of the acute AIH‐Hc induced sensory LTF appears to be postsynaptic. Our results obtained in vivo suggest a role for TRPV1‐dependent CB activity in acute sympathetic LTF. We propose that P2X‐TRPV1‐receptor‐dependent sensory LTF may constitute an important early mechanism linking sleep apnoea with hypertension and/or cardiovascular disease.
Maternal Concentrations of Persistent Organochlorine Pollutants and the Risk of Asthma in Offspring: Results from a Prospective Cohort with 20 Years of Follow-up

Background: Previous findings suggest that developmental exposures to persistent organochlorine pollutants (POPs) may be detrimental for the development of the immune system in the offspring. Whether these suspected immunoregulatory effects persist beyond early childhood remains unclear. Objectives: The objective of this study was to evaluate the association between maternal serum concentrations of POPs and the risk of asthma in offspring after 20 years of follow-up. Methods: A birth cohort with 965 women was formed in 1988–1989 in Aarhus, Denmark. Concentrations of six polychlorinated biphenyls (PCBs) (congeners 118, 138, 153, 156, 170, 180), hexachlorobenzene (HCB), and dichlorodiphenyldichloroethylene (p,p´-DDE) were quantified in maternal serum (n = 872) collected in gestation week 30. Information about offspring use of asthma medications was obtained from the Danish Registry of Medicinal Product Statistics. Results: Maternal serum concentrations of HCB and dioxin-like PCB-118 were positively associated with offspring asthma medication use after 20 years of follow-up (p for trend < 0.05). Compared with subjects in the first tertile of maternal concentration, those in the third tertile of PCB-118 had an adjusted hazard ratio (HR) of 1.90 (95% CI: 1.12, 3.23). For HCB the HR for the third versus the first tertile of maternal concentration was 1.92 (95% CI: 1.15, 3.21). Weak positive associations were also estimated for PCB-156 and the non-dioxin-like PCBs (PCBs 138, 153, 170, 180). No associations were found for p,p´-DDE. Conclusions: Maternal concentrations of PCB-118 and HCB were associated with increased risk of asthma in offspring followed through 20 years of age. Citation: Hansen S, Strøm M, Olsen SF, Maslova E, Rantakokko P, Kiviranta H, Rytter D, Bech BH, Hansen LV, Halldorsson TI. 2014. Maternal concentrations of persistent organochlorine pollutants and the risk of asthma in offspring: results from a prospective cohort with 20 years of follow-up. Environ Health Perspect 122:93–99; http://dx.doi. org/10.1289/ehp.1206397
Using MRUL to Improve Network Fairness

Internet routers generally see packets from a fast flow more often than a slow flow. This suggests that network fairness may be improved without per-flow information. In this paper, we propose a scheme using most recently used list (MRUL) - a list storing statistics of limited active flows that sorted in most recently seen first mode - to improve the fairness of RED. Based on the list, our proposed scheme jointly considers the identification and punish of the fast and unresponsive fast flows, and the protection of slow flows. Its performance improvements are demonstrated with extensive simulations. Different from the previous proposals, the complexity of our proposed scheme is proportional to the size of the MRUL list but not coupled with the queue buffer size or the number of active flows, so it is scalable and suitable for various routers.
Supporting real-time applications in an Integrated Services Packet Network: architecture and mechanism

This paper considers the support of real-time applications in an Integrated Services Packet Network (ISPN). We first review the characteristics of real-time applications. We observe that, contrary to the popular view that real-time applications necessarily require a fixed delay bound, some real-time applications are more flexible and can adapt to current network conditions. We then propose an ISPN architecture that supports two distinct kinds of real-time service: guaranteed service, which is the traditional form of real-time service discussed in most of the literature and involves pre-computed worst-case delay bounds, and predicted service which uses the measure performance of the network in computing delay bounds. We then propose a packet scheduling mechanism that can support both of these real-time services as well as accommodate datagram traffic. We also discuss two other aspects of an overall ISPN architecture: the service interface and the admission control criteria.
Research Applications of Proteolytic Enzymes in Molecular Biology

Proteolytic enzymes (also termed peptidases, proteases and proteinases) are capable of hydrolyzing peptide bonds in proteins. They can be found in all living organisms, from viruses to animals and humans. Proteolytic enzymes have great medical and pharmaceutical importance due to their key role in biological processes and in the life-cycle of many pathogens. Proteases are extensively applied enzymes in several sectors of industry and biotechnology, furthermore, numerous research applications require their use, including production of Klenow fragments, peptide synthesis, digestion of unwanted proteins during nucleic acid purification, cell culturing and tissue dissociation, preparation of recombinant antibody fragments for research, diagnostics and therapy, exploration of the structure-function relationships by structural studies, removal of affinity tags from fusion proteins in recombinant protein techniques, peptide sequencing and proteolytic digestion of proteins in proteomics. The aim of this paper is to review the molecular biological aspects of proteolytic enzymes and summarize their applications in the life sciences.
A predictive network architecture for a robust and smooth robot docking behavior

Robots and living beings exhibit latencies in their sensorimotor processing due to mechanical and electronic or neural processing delays. A reaction typically occurs to input stimuli of the past. This is critical not only when the environment changes (e.g. moving objects) but also when the agent itself moves. An agent that does not predict while moving may need to remain static between sensory input acquisition and output response to guarantee that the response is appropriate to the percept. We propose a biologically-inspired learning model of predictive sensorimotor integration to compensate for this latency. In this model, an Elman network is developed for sensory prediction and sensory filtering; a Continuous Actor-Critic Learning Automaton (CACLA) is trained for continuous action generation. For a robot docking experiment, this architecture improves the smoothness of the robot’s sensory input and therefore results in a faster and more accurate continuous approach behavior.
Corticotropin tests for hypothalamic-pituitary- adrenal insufficiency: a metaanalysis.

CONTEXT The diagnostic value of tests for detecting hypothalamic-pituitary adrenal insufficiency (HPAI) is controversial. OBJECTIVE Our objective was to compare standard-dose and low-dose corticotropin tests for diagnosing HPAI. DATA SOURCES We searched the PubMed database from 1966-2006 for studies reporting diagnostic value of standard-dose or low-dose corticotropin tests, with patient-level data obtained from original investigators. STUDY SELECTION Eligible studies had more than 10 patients. All subjects were evaluated because of suspicion for chronic HPAI, and patient-level data were available. We excluded studies with no accepted reference standard for HPAI (insulin hypoglycemia or metyrapone test) if test subjects were in the intensive care unit or if only normal healthy subjects were used as controls. DATA EXTRACTION We constructed receiver operator characteristic (ROC) curves using patient-level data from each study and then merged results to create summary ROC curves, adjusting for study size and cortisol assay method. Diagnostic value of tests was measured by calculating area under the ROC curve (AUC) and likelihood ratios. DATA SYNTHESIS Patient-level data from 13 of 23 studies (57%; 679 subjects) were included in the metaanalysis. The AUC were as follows: low-dose corticotropin test, 0.92 (95% confidence interval 0.89-0.94), and standard-dose corticotropin test, 0.79 (95% confidence interval 0.74-0.84). Among patients with paired data (seven studies, 254 subjects), diagnostic value of low-dose corticotropin test was superior to standard-dose test (AUC 0.94 and 0.85, respectively; P<0.001). CONCLUSIONS Low-dose corticotropin test was superior to standard-dose test for diagnosing chronic HPAI, although it has technical limitations.
Learning Shapes the Representation of Visual Categories in the Aging Human Brain

Abstract The ability to make categorical decisions and interpret sensory experiences is critical for survival and interactions across the lifespan. However, little is known about the human brain mechanisms that mediate the learning and representation of visual categories in aging. Here we combine behavioral measurements and fMRI measurements to investigate the neural processes that mediate flexible category learning in the aging human brain. Our findings show that training changes the decision criterion (i.e., categorical boundary) that young and older observers use for making categorical judgments. Comparing the behavioral choices of human observers with those of a pattern classifier based upon multivoxel fMRI signals, we demonstrate learning-dependent changes in similar cortical areas for young and older adults. In particular, we show that neural signals in occipito-temporal and posterior parietal regions change through learning to reflect the perceived visual categories. Information in these areas about the perceived visual categories is preserved in aging, whereas information content is compromised in more anterior parietal and frontal circuits. Thus, these findings provide novel evidence for flexible category learning in aging that shapes the neural representations of visual categories to reflect the observers' behavioral judgments.
Semi supervised deep kernel design for image annotation

It is commonly agreed that the success of support vector machines (SVMs), is highly dependent on the choice of particular similarity functions referred to as kernels. The latter are usually handcrafted or designed using appropriate optimization schemes. Multiple kernel learning (MKL) is one possible scheme that designs kernels as sparse or convex linear combinations of existing elementary functions. However, this results into shallow kernels, which are powerless to capture the right similarity between data, especially when content of these data is highly semantic. In this paper, we redefine multiple kernels using a deep architecture. In this new formulation, a global kernel is learned as a multi-layered linear combination of activation functions, each one involves a combination of several elementary or intermediate functions on multiple features. We propose three different settings to learn the weights of these kernel combinations; supervised, unsupervised and semi-supervised. When plugged into SVMs, the resulting deep multiple kernels show a gain, compared to shallow kernels, for the challenging task of image annotation using the ImageCLEF benchmark.
Brain extraction using geodesic active contours

Extracting the brain cortex from magnetic resonance imaging (MRI) head scans is an essential preprocessing step of which the accuracy greatly affects subsequent image analysis. The currently popular Brain Extraction Tool (BET) produces a brain mask which may be too smooth for practical use. This paper presents a novel brain extraction tool based on three-dimensional geodesic active contours, connected component analysis and mathematical morphology. Based on user-specified intensity and contrast levels, the proposed algorithm allows an active contour to evolve naturally and extract the brain cortex. Experiments on synthetic MRI data and scanned coronal and axial MRI image volumes indicate successful extraction of tight perimeters surrounding the brain cortex. Quantitative evaluations on both synthetic phantoms and manually labeled data resulted in better accuracy than BET in terms of true and false voxel assignment. Based on these results, we illustrate that our brain extraction tool is a robust and accurate approach for the challenging task of automatically extracting the brain cortex in MRI data.
The Effects of Phthalates on the Ovary

Phthalates are commonly used as plasticizers in the manufacturing of flexible polyvinyl chloride products. Large production volumes of phthalates and their widespread use in common consumer, medical, building, and personal care products lead to ubiquitous human exposure via oral ingestion, inhalation, and dermal contact. Recently, several phthalates have been classified as reproductive toxicants and endocrine-disrupting chemicals based on their ability to interfere with normal reproductive function and hormone signaling. Therefore, exposure to phthalates represents a public health concern. Currently, the effects of phthalates on male reproduction are better understood than the effects on female reproduction. This is of concern because women are often exposed to higher levels of phthalates than men through their extensive use of personal care and cosmetic products. In the female, a primary regulator of reproductive and endocrine function is the ovary. Specifically, the ovary is responsible for folliculogenesis, the proper maturation of gametes for fertilization, and steroidogenesis, and the synthesis of necessary sex steroid hormones. Any defect in the regulation of these processes can cause complications for reproductive and non-reproductive health. For instance, phthalate-induced defects in folliculogenesis and steroidogenesis can cause infertility, premature ovarian failure, and non-reproductive disorders. Presently, there is a paucity of knowledge on the effects of phthalates on normal ovarian function; however, recent work has established the ovary as a target of phthalate toxicity. This review summarizes what is currently known about the effects of phthalates on the ovary and the mechanisms by which phthalates exert ovarian toxicity, with a particular focus on the effects on folliculogenesis and steroidogenesis. Further, this review outlines future directions, including the necessity of examining the effects of phthalates at doses that mimic human exposure.
High-Resolution 3D Structure Determination of Kaliotoxin by Solid-State NMR Spectroscopy

High-resolution solid-state NMR spectroscopy can provide structural information of proteins that cannot be studied by X-ray crystallography or solution NMR spectroscopy. Here we demonstrate that it is possible to determine a protein structure by solid-state NMR to a resolution comparable to that by solution NMR. Using an iterative assignment and structure calculation protocol, a large number of distance restraints was extracted from 1H/1H mixing experiments recorded on a single uniformly labeled sample under magic angle spinning conditions. The calculated structure has a coordinate precision of 0.6 Å and 1.3 Å for the backbone and side chain heavy atoms, respectively, and deviates from the structure observed in solution. The approach is expected to be applicable to larger systems enabling the determination of high-resolution structures of amyloid or membrane proteins.
Guidelines for Reporting and Using Prediction Tools for Genetic Variation Analysis

Computational prediction methods are widely used for the analysis of human genome sequence variants and their effects on gene/protein function, splice site aberration, pathogenicity, and disease risk. New methods are frequently developed. We believe that guidelines are essential for those writing articles about new prediction methods, as well as for those applying these tools in their research, so that the necessary details are reported. This will enable readers to gain the full picture of technical information, performance, and interpretation of results, and to facilitate comparisons of related methods. Here, we provide instructions on how to describe new methods, report datasets, and assess the performance of predictive tools. We also discuss what details of predictor implementation are essential for authors to understand. Similarly, these guidelines for the use of predictors provide instructions on what needs to be delineated in the text, as well as how researchers can avoid unwarranted conclusions. They are applicable to most prediction methods currently utilized. By applying these guidelines, authors will help reviewers, editors, and readers to more fully comprehend prediction methods and their use.
On the origin and timing of Zika virus introduction in Brazil

Summary The timing and origin of Zika virus (ZIKV) introduction in Brazil has been the subject of controversy. Initially, it was assumed that the virus was introduced during the FIFA World Cup in June–July 2014. Then, it was speculated that ZIKV may have been introduced by athletes from French Polynesia (FP) who competed in a canoe race in Rio de Janeiro in August 2014. We attempted to apply mathematical models to determine the most likely time window of ZIKV introduction in Brazil. Given that the timing and origin of ZIKV introduction in Brazil may be a politically sensitive issue, its determination (or the provision of a plausible hypothesis) may help to prevent undeserved blame. We used a simple mathematical model to estimate the force of infection and the corresponding individual probability of being infected with ZIKV in FP. Taking into account the air travel volume from FP to Brazil between October 2013 and March 2014, we estimated the expected number of infected travellers arriving at Brazilian airports during that period. During the period between December 2013 and February 2014, 51 individuals travelled from FP airports to 11 Brazilian cities. Basing on the calculated force of ZIKV infection (the per capita rate of new infections per time unit) and risk of infection (probability of at least one new infection), we estimated that 18 (95% CI 12–22) individuals who arrived in seven of the evaluated cities were infected. When basic ZIKV reproduction numbers greater than one were assumed in the seven evaluated cities, ZIKV could have been introduced in any one of the cities. Based on the force of infection in FP, basic reproduction ZIKV number in selected Brazilian cities, and estimated travel volume, we concluded that ZIKV was most likely introduced and established in Brazil by infected travellers arriving from FP in the period between October 2013 and March 2014, which was prior to the two aforementioned sporting events.
Shallow-trench-isolation bounded single-photon avalanche diodes in commercial deep submicron CMOS technologies

This dissertation describes the first single-photon detection device to be manufactured in a commercial deep- submicron CMOS technology. It also describes novel self- timed peripheral circuits which optimize the performance of the new device. An extension of the new device for dual -color single-photon detection is investigated. Finally, an area- and power-efficient method for single-photon frequency upconversion is presented, analyzed, and experimentally examined. Single-photon avalanche diodes have been used in diverse applications, including three- dimensional laser radar, three-dimensional facial mapping, fluorescence-correlation techniques and time-domain tomography. Due to the high electric fields which these devices must sustain, they have traditionally been manufactured in custom processes, severely limiting their speed and the ability to integrate them in high-resolution imagers. By utilizing a process module originally designed to enhance the performance of CMOS transistors, we achieve highly planar junctions in an area-efficient manner. This results in SPADs exhibiting high fill factors, small pitch and ultrafast operation. Device miniaturization is accompanied by excessive noise, which was shown to emanate from trapped avalanche charges. Due to the fast recharging of the device, these charges are released in a subsequent charged phase of the device, causing correlated after- pulses. We present electrostatic and electrical simulation results, as well as a comprehensive characterization of the new device. We also show for the first time that by utilizing the two junctions included in the device, we can selectively detect photons of different wavelengths in the same pixel, as is desirable in cross-correlation experiments. This dissertation also describes an efficient new method for single-photon frequency upconversion. This is desirable for applications including quantum-key distribution and high-resolution near-infrared imaging. The new technique is based on electroluminescence in or near the multiplication region of the device, resulting from hot-carrier recombination. We model a proposed hybrid device and deduce the critical parameters for efficient upconversion. Lastly, we experimentally demonstrate that the electroluminescence yield from an InGaAs/InAlAs avalanche diode is sufficient for highly-efficient upconversion
Mating status correlates with dorsal brightness in some but not all poison frog populations

Abstract Sexual signals are important for intraspecific communication and mate selection, but their evolution may be driven by both natural and sexual selection, and stochastic processes. Strawberry poison frogs (Oophaga pumilio) show strong color divergence among populations, but coloration also varies among individuals of the same population. The importance of coloration for female mate choice has been studied intensely, and sexual selection seems to affect color divergence in strawberry poison frogs. However, the effect of coloration on mating success under field conditions has received very little attention. Furthermore, few studies examined how phenotypic variation among individuals of the same color morph affects mate selection under natural conditions. We measured the spectral reflectance of courting and noncourting individuals and their background substrates in three geographically separated populations. In one population (Sarapiquí, Costa Rica), we found that naturally occurring courting pairs of males and females had significantly brighter dorsal coloration than individual males and females not engaged in courtship interactions. Our field observations suggest that, in the wild, females prefer brighter males while the reason for the higher courtship activity of brighter females remains unclear. Overall our results imply that brightness differences among individuals of the same color morph may actually affect reproductive success in some populations of strawberry poison frogs.