Emergence of CD26+ cancer stem cells with metastatic properties in colorectal carcinogenesis

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Fluorescent nanoparticles for sensing

Nanoparticle-based fluorescent sensors have emerged as a competitive alternative to small molecule sensors, due to their excellent fluorescence-based sensing capabilities. The tailorability of design, architecture, and photophysical properties has attracted the attention of many research groups, resulting in numerous reports related to novel nanosensors applied in sensing a vast variety of biological analytes. Although semiconducting quantum dots have been the best-known representative of fluorescent nanoparticles for a long time, the increasing popularity of new classes of organic nanoparticle-based sensors, such as carbon dots and polymeric nanoparticles, is due to their biocompatibility, ease of synthesis, and biofunctionalization capabilities. For instance, fluorescent gold and silver nanoclusters have emerged as a less cytotoxic replacement for semiconducting quantum dot sensors. This chapter provides an overview of recent developments in nanoparticle-based sensors for chemical and biological sensing and includes a discussion on unique properties of nanoparticles of different composition, along with their basic mechanism of fluorescence, route of synthesis, and their advantages and limitations

Fabrication of Ce-doped MnO2 decorated graphene sheets for fire safety applications of epoxy composites: flame retardancy, smoke suppression and mechanism

Ce-doped MnO2–graphene hybrid sheets were fabricated by utilizing an electrostatic interaction between Ce-doped MnO2 and graphene sheets. The hybrid material was analyzed by a series of characterization methods. Subsequently, the Ce-doped MnO2–graphene hybrid sheet was introduced into an epoxy resin, and the fire hazard behaviors of the epoxy nanocomposite were investigated. The results from thermogravimetric analysis exhibited that the incorporation of 2.0 wt% of Ce-doped MnO2–graphene sheets clearly improved the thermal stability and char residue of the epoxy matrix. In addition, the addition of Ce–MnO2–graphene hybrid sheets imparted excellent flame retardant properties to an epoxy matrix, as shown by the dramatically reduced peak heat release rate and total heat release value obtained from a cone calorimeter. The results of thermogravimetric analysis/infrared spectrometry, cone calorimetry and steady state tube furnace tests showed that the amount of organic volatiles and toxic CO from epoxy decomposition were significantly suppressed after incorporating Ce–MnO2–graphene sheets, implying that this hybrid material has reduced fire hazards. A plausible flame-retardant mechanism was hypothesized on the basis of the characterization of char residues and direct pyrolysis-mass spectrometry analysis: during the combustion, Ce–MnO2, as a solid acid, results in the formation of pyrolysis products with lower carbon numbers. Graphene sheets play the role of a physical barrier that can absorb the degraded products, thereby extend their contact time with the metal oxides catalyst, and then promote their propagate on the graphene sheets; meanwhile pyrolysis fragments with lower carbon numbers can be easily catalyzed in the presence of Ce–MnO2. The notable reduction in the fire hazards was mainly attributed to the synergistic action between the physical barrier effect of graphene and the catalytic effect of Ce–MnO2

First narrow-band search for continuous gravitational waves from known pulsars in advanced detector data

Spinning neutron stars asymmetric with respect to their rotation axis are potential sources of continuous gravitational waves for ground-based interferometric detectors. In the case of known pulsars a fully coherent search, based on matched filtering, which uses the position and rotational parameters obtained from electromagnetic observations, can be carried out. Matched filtering maximizes the signalto- noise (SNR) ratio, but a large sensitivity loss is expected in case of even a very small mismatch between the assumed and the true signal parameters. For this reason, narrow-band analysis methods have been developed, allowing a fully coherent search for gravitational waves from known pulsars over a fraction of a hertz and several spin-down values. In this paper we describe a narrow-band search of 11 pulsars using data from Advanced LIGO’s first observing run. Although we have found several initial outliers, further studies show no significant evidence for the presence of a gravitational wave signal. Finally, we have placed upper limits on the signal strain amplitude lower than the spin-down limit for 5 of the 11 targets over the bands searched; in the case of J1813-1749 the spin-down limit has been beaten for the first time. For an additional 3 targets, the median upper limit across the search bands is below the spin-down limit. This is the most sensitive narrow-band search for continuous gravitational waves carried out so far

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey

EssC:domain structures inform on the elusive translocation channels in the Type VII secretion system.

The membrane-bound protein EssC is an integral component of the bacterial Type VII secretion system (T7SS), which is a determinant of virulence in important Gram-positive pathogens. The protein is predicted to consist of an intracellular repeat of forkhead-associated (FHA) domains at the N-terminus, two transmembrane helices and three P-loop-containing ATPase-type domains, D1–D3, forming the C-terminal intracellular segment. We present crystal structures of the N-terminal FHA domains (EssC-N) and a C-terminal fragment EssC-C from Geobacillus thermodenitrificans, encompassing two of the ATPase-type modules, D2 and D3. Module D2 binds ATP with high affinity whereas D3 does not. The EssC-N and EssC-C constructs are monomeric in solution, but the full-length recombinant protein, with a molecular mass of approximately 169 kDa, forms a multimer of approximately 1 MDa. The observation of protomer contacts in the crystal structure of EssC-C together with similarity to the DNA translocase FtsK, suggests a model for a hexameric EssC assembly. Such an observation potentially identifies the key, and to date elusive, component of pore formation required for secretion by this recently discovered secretion system. The juxtaposition of the FHA domains suggests potential for interacting with other components of the secretion system. The structural data were used to guide an analysis of which domains are required for the T7SS machine to function in pathogenic Staphylococcus aureus. The extreme C-terminal ATPase domain appears to be essential for EssC activity as a key part of the T7SS, whereas D2 and FHA domains are required for the production of a stable and functional protein

Highly functionalized organic nitrates in the southeast United States : Contribution to secondary organic aerosol and reactive nitrogen budgets

Speciated particle-phase organic nitrates (pONs) were quantified using online chemical ionization MS during June and July of 2013 in rural Alabama as part of the Southern Oxidant and Aerosol Study. A large fraction of pONs is highly functionalized, possessing between six and eight oxygen atoms within each carbon number group, and is not the common first generation alkyl nitrates previously reported. Using calibrations for isoprene hydroxynitrates and the measured molecular compositions, we estimate that pONs account for 3% and 8% of total submicrometer organic aerosol mass, on average, during the day and night, respectively. Each of the isoprene-and monoterpenes-derived groups exhibited a strong diel trend consistent with the emission patterns of likely biogenic hydrocarbon precursors. An observationally constrained diel box model can replicate the observed pON assuming that pONs (i) are produced in the gas phase and rapidly establish gas-particle equilibrium and (ii) have a short particle-phase lifetime (similar to 2-4 h). Such dynamic behavior has significant implications for the production and phase partitioning of pONs, organic aerosol mass, and reactive nitrogen speciation in a forested environment.Peer reviewe