Optimization of fixation methods for observation of bacterial cell morphology and surface ultrastructures by atomic force microscopy

Fixation ability of five common fixation solutions, including 2.5% glutaraldehyde, 10% formalin, 4% paraformaldehyde, methanol/acetone (1:1), and ethanol/acetic acid (3:1) were evaluated by using atomic force microscopy in the present study. Three model bacteria, i.e., Escherichia coli, Pseudomonas putida, and Bacillus subtilis were applied to observe the above fixation methods for the morphology preservation of bacterial cells and surface ultrastructures. All the fixation methods could effectively preserve cell morphology. However, for preserving bacterial surface ultrastructures, the methods applying aldehyde fixations performed much better than those using alcohols, since the alcohols could detach the surface filaments (i.e., flagella and pili) significantly. Based on the quantitative and qualitative assessments, the 2.5% glutaraldehyde was proposed as a promising fixation solution both for observing morphology of both bacterial cell and surface ultrastructures, while the methonal/acetone mixture was the worst fixation solution which may obtain unreliable results

Role of Surface Area, Primary Particle Size, and Crystal Phase on Titanium Dioxide Nanoparticle Dispersion Properties

Characterizing nanoparticle dispersions and understanding the effect of parameters that alter dispersion properties are important for both environmental applications and toxicity investigations. The role of particle surface area, primary particle size, and crystal phase on TiO2 nanoparticle dispersion properties is reported. Hydrodynamic size, zeta potential, and isoelectric point (IEP) of ten laboratory synthesized TiO2 samples, and one commercial Degussa TiO2 sample (P25) dispersed in different solutions were characterized. Solution ionic strength and pH affect titania dispersion properties. The effect of monovalent (NaCl) and divalent (MgCl2) inert electrolytes on dispersion properties was quantified through their contribution to ionic strength. Increasing titania particle surface area resulted in a decrease in solution pH. At fixed pH, increasing the particle surface area enhanced the collision frequency between particles and led to a higher degree of agglomeration. In addition to the synthesis method, TiO2 isoelectric point was found to be dependent on particle size. As anatase TiO2 primary particle size increased from 6 nm to 104 nm, its IEP decreased from 6.0 to 3.8 that also results in changes in dispersion zeta potential and hydrodynamic size. In contrast to particle size, TiO2 nanoparticle IEP was found to be insensitive to particle crystal structure

DNA damage by lipid peroxidation products: implications in cancer, inflammation and autoimmunity

Oxidative stress and lipid peroxidation (LPO) induced by inflammation, excess metal storage and excess caloric intake cause generalized DNA damage, producing genotoxic and mutagenic effects. The consequent deregulation of cell homeostasis is implicated in the pathogenesis of a number of malignancies and degenerative diseases. Reactive aldehydes produced by LPO, such as malondialdehyde, acrolein, crotonaldehyde and 4-hydroxy-2-nonenal, react with DNA bases, generating promutagenic exocyclic DNA adducts, which likely contribute to the mutagenic and carcinogenic effects associated with oxidative stress-induced LPO. However, reactive aldehydes, when added to tumor cells, can exert an anticancerous effect. They act, analogously to other chemotherapeutic drugs, by forming DNA adducts and, in this way, they drive the tumor cells toward apoptosis. The aldehyde-DNA adducts, which can be observed during inflammation, play an important role by inducing epigenetic changes which, in turn, can modulate the inflammatory process. The pathogenic role of the adducts formed by the products of LPO with biological macromolecules in the breaking of immunological tolerance to self antigens and in the development of autoimmunity has been supported by a wealth of evidence. The instrumental role of the adducts of reactive LPO products with self protein antigens in the sensitization of autoreactive cells to the respective unmodified proteins and in the intermolecular spreading of the autoimmune responses to aldehyde-modified and native DNA is well documented. In contrast, further investigation is required in order to establish whether the formation of adducts of LPO products with DNA might incite substantial immune responsivity and might be instrumental for the spreading of the immunological responses from aldehyde-modified DNA to native DNA and similarly modified, unmodified and/or structurally analogous self protein antigens, thus leading to autoimmunity

Sediment source fingerprinting: benchmarking recent outputs, remaining challenges and emerging themes

Abstract: Purpose: This review of sediment source fingerprinting assesses the current state-of-the-art, remaining challenges and emerging themes. It combines inputs from international scientists either with track records in the approach or with expertise relevant to progressing the science. Methods: Web of Science and Google Scholar were used to review published papers spanning the period 2013–2019, inclusive, to confirm publication trends in quantities of papers by study area country and the types of tracers used. The most recent (2018–2019, inclusive) papers were also benchmarked using a methodological decision-tree published in 2017. Scope: Areas requiring further research and international consensus on methodological detail are reviewed, and these comprise spatial variability in tracers and corresponding sampling implications for end-members, temporal variability in tracers and sampling implications for end-members and target sediment, tracer conservation and knowledge-based pre-selection, the physico-chemical basis for source discrimination and dissemination of fingerprinting results to stakeholders. Emerging themes are also discussed: novel tracers, concentration-dependence for biomarkers, combining sediment fingerprinting and age-dating, applications to sediment-bound pollutants, incorporation of supportive spatial information to augment discrimination and modelling, aeolian sediment source fingerprinting, integration with process-based models and development of open-access software tools for data processing. Conclusions: The popularity of sediment source fingerprinting continues on an upward trend globally, but with this growth comes issues surrounding lack of standardisation and procedural diversity. Nonetheless, the last 2 years have also evidenced growing uptake of critical requirements for robust applications and this review is intended to signpost investigators, both old and new, towards these benchmarks and remaining research challenges for, and emerging options for different applications of, the fingerprinting approach

Search for strongly interacting massive particles generating trackless jets in proton-proton collisions at s = 13 TeV

A search for dark matter in the form of strongly interacting massive particles (SIMPs) using the CMS detector at the LHC is presented. The SIMPs would be produced in pairs that manifest themselves as pairs of jets without tracks. The energy fraction of jets carried by charged particles is used as a key discriminator to suppress efficiently the large multijet background, and the remaining background is estimated directly from data. The search is performed using proton-proton collision data corresponding to an integrated luminosity of 16.1 fb - 1 , collected with the CMS detector in 2016. No significant excess of events is observed above the expected background. For the simplified dark matter model under consideration, SIMPs with masses up to 100 GeV are excluded and further sensitivity is explored towards higher masses

Observation of a New Excited Beauty Strange Baryon Decaying to Ξb- π+π-

The Ξb-π+π- invariant mass spectrum is investigated with an event sample of proton-proton collisions at s=13 TeV, collected by the CMS experiment at the LHC in 2016-2018 and corresponding to an integrated luminosity of 140 fb-1. The ground state Ξb- is reconstructed via its decays to J/ψΞ- and J/ψΛK-. A narrow resonance, labeled Ξb(6100)-, is observed at a Ξb-π+π- invariant mass of 6100.3±0.2(stat)±0.1(syst)±0.6(Ξb-) MeV, where the last uncertainty reflects the precision of the Ξb- baryon mass. The upper limit on the Ξb(6100)- natural width is determined to be 1.9 MeV at 95% confidence level. The low Ξb(6100)- signal yield observed in data does not allow a measurement of the quantum numbers of the new state. However, following analogies with the established excited Ξc baryon states, the new Ξb(6100)- resonance and its decay sequence are consistent with the orbitally excited Ξb- baryon, with spin and parity quantum numbers JP=3/2-

Measurement of the inclusive and differential Higgs boson production cross sections in the decay mode to a pair of τ Leptons in pp collisions at sqrt[s]=13 TeV

Measurements of the inclusive and differential fiducial cross sections of the Higgs boson are presented, using the τ lepton decay channel. The differential cross sections are measured as functions of the Higgs boson transverse momentum, jet multiplicity, and transverse momentum of the leading jet in the event, if any. The analysis is performed using proton-proton collision data collected with the CMS detector at the LHC at a center-of-mass energy of 13  TeV and corresponding to an integrated luminosity of 138  fb^{-1}. These are the first differential measurements of the Higgs boson cross section in the final state of two τ leptons. In final states with a large jet multiplicity or with a Lorentz-boosted Higgs boson, these measurements constitute a significant improvement over measurements performed in other final states

Neutrino interaction classification with a convolutional neural network in the DUNE far detector

The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2–5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino energies above 2 GeV. When considering all electron neutrino and antineutrino interactions as signal, a selection purity of 90% is achieved. These event selections are critical to maximize the sensitivity of the experiment to CP-violating effects