Miracle-dz/UniFAR-FTUs huggingface dataset:
Stimulation of Neonatal and Adult Brain Neurogenesis by Subcutaneous Injection of Basic Fibroblast Growth Factor

Mounting evidence indicates that extracellular factors exert proliferative effects on neurogenetic precursors in vivo. Recently we found that systemic levels of basic fibroblast growth factor (bFGF) regulate neurogenesis in the brain of newborn rats, with factors apparently crossing the blood–brain barrier (BBB) to stimulate mitosis. To determine whether peripheral bFGF affects proliferation during adulthood, we focused on regions in which neurogenesis persists into maturity, the hippocampus and the forebrain subventricular zone (SVZ). In postnatal day 1 (P1) rats, 8 hr after subcutaneous injection (5 ng/gm body weight), bFGF increased [3H]thymidine incorporation 70% in hippocampal and SVZ homogenates and elicited twofold increases in mitotic nuclei in the dentate gyrus and the dorsolateral SVZ, detected by bromodeoxyuridine immunohistochemistry. Because ∼25% of proliferating hippocampal cells stimulated in vivoexpressed neuronal traits in culture, bFGF-induced mitosis may reflect increased neurogenesis. bFGF effects were not restricted to the perinatal period; hippocampal DNA synthesis was stimulated by peripheral factor in older animals (P7–P21), indicating the persistence of bFGF-responsive cells and activity of peripheral bFGF into late development. To begin defining underlying mechanisms, pharmacokinetic studies were performed in P28 rats; bFGF transferred from plasma to CSF rapidly, levels rising in both compartments in parallel, indicating that peripheral factor crosses the BBB during maturity. Consequently, we tested bFGF in adults; peripheral bFGF increased the number of mitotic nuclei threefold in the SVZ and olfactory tract, regions exhibiting persistent neurogenesis. Our observations suggest that bFGF regulates ongoing neurogenesis via a unique, endocrine-like pathway, potentially coordinating neuron number and body growth, and potentially providing new approaches for treating damaged brain during development and adulthood.
The cost‐efficiency and reliability of two methods for soil organic C accounting

Sequestering organic carbon (C) in soil can help to combat land degradation, improve food security, and mitigate greenhouse gas emissions and climate change. But we need reliable, cost‐efficient methods to assess, monitor, and verify the change. Here, we compared two methods for the direct measurement of soil organic C stocks and for monitoring the change. Our aims were to quantify the soil organic C stock in two carbon estimation areas, under cropping and grazing, using composite sampling with two designs and proximal sensing. We compared the two schemes in terms of the (a) accuracy of the estimated C stocks, the total cost, and the cost‐efficiency, calculated as the ratio of the accuracy of the estimate and the total cost, and (b) uncertainty of the estimated standard error of the estimated C stocks. We found that compositing was cheaper but more inaccurate than sensing. Sensing was 1.2 to 2.1 times more cost‐efficient than compositing. We also found that the uncertainty of the estimated standard errors from compositing was large and unreliable, which can hinder the quantification of a minimum detectable difference in organic C stocks. We show that the sensor‐derived spatially explicit data can also be used to map the C stocks, which can help to optimise the sampling design in subsequent monitoring rounds. Our findings have important implications for the development of C measurement and monitoring methodologies. Visible–near infrared and gamma attenuation sensing can accurately, cost‐efficiently, and reliably monitor and verify changes in soil C stocks.
Activation of the Steroid and Xenobiotic Receptor (Human Pregnane X Receptor) by Nontaxane Microtubule-Stabilizing Agents

Purpose: Because induction of drug efflux transporters is one of the major underlying mechanisms of drug resistance in cancer chemotherapy, and human pregnane X receptor (hPXR) is one of the principal “xenobiotic” receptors whose activation induces transporter and drug-metabolizing enzyme gene transcription, it would be ideal to develop chemotherapy drugs that do not activate hPXR. This report describes studies undertaken to explore the characteristics of hPXR stimulation and mechanisms of drug-receptor interactions in vitro with new anti-tubulin drugs. Experimental Design:In vitro transient transcription, glutathione S-transferase pull-down assays, and mammalian one-hybrid and two-hybrid systems were used to explore drug-receptor interactions. Loss of righting reflex was used to assess effects of drugs on PXR activity in vivo. Results: The current study showed that paclitaxel, discodermolide, and an analogue of epothilone B, BMS-247550, induced CYP3A4 protein expression in HepG2 hepatoma cells. Transient transcription assays of a luciferase reporter in the presence and absence of a GAL4-steroid and xenobiotic receptor (SXR) plasmid in HepG2 cells showed that these drugs activate hPXR. This was not true for the inactive analogue of paclitaxel, baccatin III, or for an analogue of epothilone A, analogue 5, none of which stabilizes microtubules. To determine the mechanisms by which paclitaxel, discodermolide, and BMS-247550 activate hPXR, a mammalian two-hybrid assay was done using VP16SRC-1 (coactivator) and GAL4-SXR. SRC-1 preferentially augmented the effects of these drugs on hPXR. Expression of SMRT (corepressor) but not NCoR suppressed the drug-induced activation of SXR by ∼50%, indicating a selectivity in corepressor interaction with hPXR. These drugs resulted in shortened duration of loss of righting reflex in vivo, indicating drug-induced activation of PXR in mice. Conclusion: These findings suggest that activation of hPXR with selective displacement of corepressors is an important mechanism by which microtubule-stabilizing drugs induce drug-metabolizing enzymes both in vitro and in vivo.
Relations Among Some Low-Rank Subspace Recovery Models

Recovering intrinsic low-dimensional subspaces from data distributed on them is a key preprocessing step to many applications. In recent years, a lot of work has modeled subspace recovery as low-rank minimization problems. We find that some representative models, such as robust principal component analysis (R-PCA), robust low-rank representation (R-LRR), and robust latent low-rank representation (R-LatLRR), are actually deeply connected. More specifically, we discover that once a solution to one of the models is obtained, we can obtain the solutions to other models in closed-form formulations. Since R-PCA is the simplest, our discovery makes it the center of low-rank subspace recovery models. Our work has two important implications. First, R-PCA has a solid theoretical foundation. Under certain conditions, we could find globally optimal solutions to these low-rank models at an overwhelming probability, although these models are nonconvex. Second, we can obtain significantly faster algorithms for these models by solving R-PCA first. The computation cost can be further cut by applying low-complexity randomized algorithms, for example, our novel filtering algorithm, to R-PCA. Although for the moment the formal proof of our filtering algorithm is not yet available, experiments verify the advantages of our algorithm over other state-of-the-art methods based on the alternating direction method.
Autocorrelation of the Seismic Wavefield at Newberry Volcano: Reflections From the Magmatic and Geothermal Systems

We show that seismic autocorrelations provide new depth constraints on upper crustal magmatic systems. Autocorrelations of both ambient noise recorded on seismometers and geophones and teleseismic earthquake coda recorded on seismometers elucidate the structure of Newberry Volcano. These autocorrelations result in the two‐way, body wave Green's function beneath a station. Within the caldera, a reproducible, coherent P wave reflection is inferred to come from the top of a magma body at ~2.5 km depth and maps with the lateral extent of an anomalously low‐velocity body imaged tomographically. On the west flank of the volcano, a reflection that deepens with distance from the caldera is inferred to result from a temperature‐dependent change in metamorphic facies and may map the thermal structure of the edifice. Our results show that the autocorrelation of diffuse seismic energy reconstructs reflections from seismically sharp boundaries associated with the upper crustal magmatic structure.
Recent Advances in Nanotechnology Applied to Biosensors

In recent years there has been great progress the application of nanomaterials in biosensors. The importance of these to the fundamental development of biosensors has been recognized. In particular, nanomaterials such as gold nanoparticles, carbon nanotubes, magnetic nanoparticles and quantum dots have been being actively investigated for their applications in biosensors, which have become a new interdisciplinary frontier between biological detection and material science. Here we review some of the main advances in this field over the past few years, explore the application prospects, and discuss the issues, approaches, and challenges, with the aim of stimulating a broader interest in developing nanomaterial-based biosensors and improving their applications in disease diagnosis and food safety examination.
Anion exchanger 2 is essential for spermiogenesis in mice

Na+-independent anion exchangers (AE) mediate electroneutral exchange of Cl- for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}{\mathrm{HCO}}_{3}^{-}\end{equation*}\end{document} ions across cell membranes, being involved in intracellular pH and cell volume regulation and in transepithelial hydroionic fluxes. Bicarbonate activation of adenylyl cyclase is known to be necessary for sperm motility and sperm capacitation, and a few studies have suggested a possible role of AE carriers in reproduction. Among the four AE genes identified in mammals thus far, only Ae2 (Slc4a2) has been determined to be expressed in the male reproductive system, especially in developing spermatozoa and in epididymal epithelium. Most AE genes drive alternative transcription, which in mouse Ae2 results in several Ae2 isoforms. Here, we generated mice carrying a targeted disruption of Ae2 that prevents the expression of the three AE2 isoforms (Ae2a, Ae2b1, and Ae2b2) normally found in mouse testes. Male Ae2-/- mice (but not female Ae2-/- mice) are infertile. Histopathological analysis of Ae2-/- testes shows an interruption of spermiogenesis, with only a few late spermatids and a complete absence of spermatozoa in the seminiferous tubules. The number of apoptotic bodies is increased in the seminiferous tubules and in the epididymis, which also shows squamous metaplasia of the epididymal epithelium. Our findings reveal an essential role of Ae2 in mouse spermiogenesis and stress the recently postulated involvement of bicarbonate in germ-cell differentiation through the bicarbonate-sensitive soluble-adenylyl-cyclase pathway.
Visual Servoing Path Planning for Cameras Obeying the Unified Model

Abstract This paper proposes a path planning visual servoing strategy for a class of cameras that includes conventional perspective cameras, fisheye cameras and catadioptric cameras as special cases. Specifically, these cameras are modeled by adopting a unified model recently proposed in the literature and the strategy consists of designing image trajectories for eye-in-hand robotic systems that allow the robot to reach a desired location while satisfying typical visual servoing constraints. To this end, the proposed strategy introduces the projection of the available image features onto a virtual plane and the computation of a feasible image trajectory through polynomial programming. Then, the computed image trajectory is tracked by using an image-based visual servoing controller. Experimental results with a fisheye camera mounted on a 6-d.o. f. robot arm are presented in order to illustrate the proposed strategy.
N-ethylmaleimide-sensitive factor is required for the synaptic incorporation and removal of AMPA receptors during cerebellar long-term depression

Cerebellar long-term depression (LTD) is a persistent attenuation of synaptic transmission at the parallel fiber–Purkinje cell synapse mediated by the removal of GluR2 subunit-containing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors. The removal of AMPA receptors requires protein kinase C phosphorylation of the GluR2 subunit within its carboxyl-terminal PSD-95/Discs Large/Zona Occludens-1 (PDZ) ligand and binding of the PDZ domain-containing protein, PICK1. The sequence of the GluR2 subunit is similar to that of the GluR3 and GluR4c subunits, which also contain PDZ ligands and protein kinase C consensus sites. Although GluR3 and GluR4c are also expressed in Purkinje cells, we have previously shown that cerebellar LTD is absent in GluR2–/– mice, suggesting that these subunits are unable to substitute functionally for GluR2. Here, we examine the apparent difference in the regulation of these AMPA receptor subunits by attempting to rescue LTD in GluR2–/– Purkinje cells with WT and mutant GluR2 and GluR3 subunits. Our results show that the selective interaction of the GluR2 subunit with the N-ethylmaleimide-sensitive factor protein is required for synaptic, but not extrasynaptic, incorporation of AMPA receptors as well as for their competence to undergo LTD. In addition, perfusion of a synthetic peptide that acutely disrupts the interaction of GluR2 with N-ethylmaleimide-sensitive factor selectively depletes GluR2-containing receptors from synapses and occludes LTD. These findings demonstrate that interaction of AMPA receptors with N-ethylmaleimide-sensitive factor plays a critical role in incorporation of AMPA receptors into synapses and for their subsequent removal during cerebellar LTD.
Content-Agnostic Malware Detection in Heterogeneous Malicious Distribution Graph

Malware detection has been widely studied by analysing either file dropping relationships or characteristics of the file distribution network. This paper, for the first time, studies a global heterogeneous malware delivery graph fusing file dropping relationship and the topology of the file distribution network. The integration offers a unique ability of structuring the end-to-end distribution relationship. However, it brings large heterogeneous graphs to analysis. In our study, an average daily generated graph has more than 4 million edges and 2.7 million nodes that differ in type, such as IPs, URLs, and files. We propose a novel Bayesian label propagation model to unify the multi-source information, including content-agnostic features of different node types and topological information of the heterogeneous network. Our approach does not need to examine the source codes nor inspect the dynamic behaviours of a binary. Instead, it estimates the maliciousness of a given file through a semi-supervised label propagation procedure, which has a linear time complexity w.r. t. the number of nodes and edges. The evaluation on 567 million real-world download events validates that our proposed approach efficiently detects malware with a high accuracy.
Computation of Upper-Bounds for Stochastic Context-Free Languages

Automatic speech understanding and automatic speech recognition extract different kinds of information from the input signal. The result of the former must be evaluated on the basis of the response of the system while the result of the latter is the word sequence which best matches the input signal. In both cases search has to be performed based on scores of interpretation hypotheses. A scoring method is presented based on stochastic context-free grammars. The method gives optimal upper-bounds for the computation of the "best" derivation trees of a sentence. This method allows language models to be built based on stochastic context-free grammars and their use with an admissible search algorithm that interprets a speech signal with left-to-right or middle-out strategies. Theoretical and computational aspects are discussed.
Continuous Inference in Graphical Models with Polynomial Energies

In this paper, we tackle the problem of performing inference in graphical models whose energy is a polynomial function of continuous variables. Our energy minimization method follows a dual decomposition approach, where the global problem is split into sub problems defined over the graph cliques. The optimal solution to these sub problems is obtained by making use of a polynomial system solver. Our algorithm inherits the convergence guarantees of dual decomposition. To speed up optimization, we also introduce a variant of this algorithm based on the augmented Lagrangian method. Our experiments illustrate the diversity of computer vision problems that can be expressed with polynomial energies, and demonstrate the benefits of our approach over existing continuous inference methods.
Analysis of inter-element mutual coupling in wireless antenna array using finite difference time domain method

The effect of inter-element mutual coupling in a typical wireless communication antenna array is studied using the finite difference time domain method. The array consists of 16 half-wavelength fat dipoles that are non-uniformly spaced. The result obtained by the array multiplication approach is compared with that obtained from the finite difference time domain method in order to show the influence of the inter-element mutual coupling.
Initial orbit determination based on sparse space-based angle measurement and genetic algorithm

This paper studies the initial orbit determination based on sparse space-based angle measurement and genetic algorithm. The double rho iteration model used by the space-based initial orbit determination is briefly introduced firstly. Because of problems of iteration divergences and self-solutions in the space-based initial orbit determination, the genetic algorithm of SGA and MPGA are then adopted to solve the problems. According to the research results, the space-based initial orbit determination generally got more satisfied solutions by the genetic algorithm than common iteration algorithms. Furthermore, the MPGA genetic algorithm is very effective to overcome the above drawbacks on the initial orbit determination based on sparse space-based angle measurement.
Comparison of leaf-on and leaf-off ALS data for mapping riparian tree species

Forest species composition is a fundamental indicator of forest study and management. However, describing forest species composition at large scales and of highly diverse populations remains an issue for which remote sensing can provide significant contribution, in particular, Airborne Laser Scanning (ALS) data. Riparian corridors are good examples of highly valuable ecosystems, with high species richness and large surface areas that can be time consuming and expensive to monitor with in situ measurements. Remote sensing could be useful to study them, but few studies have focused on monitoring riparian tree species using ALS data. This study aimed to determine which metrics derived from ALS data are best suited to identify and map riparian tree species. We acquired very high density leaf-on and leaf-off ALS data along the Sélune River (France). In addition, we inventoried eight main riparian deciduous tree species along the study site. After manual segmentation of the inventoried trees, we extracted 68 morphological and structural metrics from both leaf-on and leaf-off ALS point clouds. Some of these metrics were then selected using Sequential Forward Selection (SFS) algorithm. Support Vector Machine (SVM) classification results showed good accuracy with 7 metrics (0.77). Both leaf-on and leafoff metrics were kept as important metrics for distinguishing tree species. Results demonstrate the ability of 3D information derived from high density ALS data to identify riparian tree species using external and internal structural metrics. They also highlight the complementarity of leaf-on and leaf-off Lidar data for distinguishing riparian tree species.
Review of Monte Carlo modeling of light transport in tissues

Abstract. A general survey is provided on the capability of Monte Carlo (MC) modeling in tissue optics while paying special attention to the recent progress in the development of methods for speeding up MC simulations. The principles of MC modeling for the simulation of light transport in tissues, which includes the general procedure of tracking an individual photon packet, common light–tissue interactions that can be simulated, frequently used tissue models, common contact/noncontact illumination and detection setups, and the treatment of time-resolved and frequency-domain optical measurements, are briefly described to help interested readers achieve a quick start. Following that, a variety of methods for speeding up MC simulations, which includes scaling methods, perturbation methods, hybrid methods, variance reduction techniques, parallel computation, and special methods for fluorescence simulations, as well as their respective advantages and disadvantages are discussed. Then the applications of MC methods in tissue optics, laser Doppler flowmetry, photodynamic therapy, optical coherence tomography, and diffuse optical tomography are briefly surveyed. Finally, the potential directions for the future development of the MC method in tissue optics are discussed.
Speedpath analysis under parametric timing models

The clock frequency of a digital IC is limited by its slowest paths, designated by speedpaths. Given the extreme complexity involved in modeling modern IC technologies, often speedpath predictions provided by timing analysis tools are not correct. Therefore, several practical techniques have recently been proposed for design debugging, that combine silicon stepping of improved versions of a circuit with subsequent correlation between measured and predicted data. Addressing these issues, this paper proposes a set of techniques that enable the designer to obtain reduced subsets of paths, guaranteed to contain all the speedpaths of a given circuit or block. Such subsets can be computed either from timing models, prior to fabrication, or incorporating actual delay measurements from fabricated instances.
Effects of Solar Particle Event-Like Proton Radiation and/or Simulated Microgravity on Circulating Mouse Blood Cells

ABSTRACT Astronauts traveling in space missions outside of low Earth orbit will be exposed for longer times to a microgravity environment. In addition, the increased travel time involved in exploration class missions will result in an increased risk of exposure to significant doses of solar particle event (SPE) radiation. Both conditions could significantly affect the number of circulating blood cells. Therefore, it is critical to determine the combined effects of exposure to both microgravity and SPE radiation. The purpose of the present study was to assess these risks by evaluating the effects of SPE-like proton radiation and/or microgravity, as simulated with the hindlimb unloading (HU) system, on circulating blood cells using mouse as a model system. The results indicate that exposure to HU alone caused minimal or no significant changes in mouse circulating blood cell numbers. The exposure of mice to SPE-like proton radiation with or without HU treatment caused a significant decrease in the number of circulating lymphocytes, granulocytes and platelets. The reduced numbers of circulating lymphocytes, granulocytes, and platelets, resulting from the SPE-like proton radiation exposure, with or without HU treatment, in mice suggest that astronauts participating in exploration class missions may be at greater risk of developing infections and thrombotic diseases; thus, countermeasures may be necessary for these biological endpoints.