Metabolic alterations during the growth of tumour spheroids

Solid tumours undergo considerable alterations in their metabolism of nutrients in order to generate sufficient energy and biomass for sustained growth and proliferation. During growth, the tumour microenvironment exerts a number of influences (e.g. hypoxia and acidity) that affect cellular biology and the flux or utilisation of fuels including glucose. The tumour spheroid model was used to characterise the utilisation of glucose and describe alterations to the activity and expression of key glycolytic enzymes during the tissue growth curve. Glucose was avidly consumed and associated with the production of lactate and an acidified medium, confirming the reliance on glycolytic pathways and a diminution of oxidative phosphorylation. The expression levels and activities of hexokinase, phosphofructokinase-1, pyruvate kinase and lactate dehydrogenase in the glycolytic pathway were measured to assess glycolytic capacity. Similar measurements were made for glucose-6-phosphate dehydrogenase, the entry point and regulatory step of the pentose-phosphate pathway (PPP) and for cytosolic malate dehydrogenase, a key link to TCA cycle intermediates. The parameters for these key enzymes were shown to undergo considerable variation during the growth curve of tumour spheroids. In addition, they revealed that the dynamic alterations were influenced by both transcriptional and posttranslational mechanisms

Metabolic alterations during the growth of tumour spheroids

Solid tumours undergo considerable alterations in their metabolism of nutrients in order to generate sufficient energy and biomass for sustained growth and proliferation. During growth, the tumour microenvironment exerts a number of influences (e.g. hypoxia and acidity) that affect cellular biology and the flux or utilisation of fuels including glucose. The tumour spheroid model was used to characterise the utilisation of glucose and describe alterations to the activity and expression of key glycolytic enzymes during the tissue growth curve. Glucose was avidly consumed and associated with the production of lactate and an acidified medium, confirming the reliance on glycolytic pathways and a diminution of oxidative phosphorylation. The expression levels and activities of hexokinase, phosphofructokinase-1, pyruvate kinase and lactate dehydrogenase in the glycolytic pathway were measured to assess glycolytic capacity. Similar measurements were made for glucose-6-phosphate dehydrogenase, the entry point and regulatory step of the pentose-phosphate pathway (PPP) and for cytosolic malate dehydrogenase, a key link to TCA cycle intermediates. The parameters for these key enzymes were shown to undergo considerable variation during the growth curve of tumour spheroids. In addition, they revealed that the dynamic alterations were influenced by both transcriptional and posttranslational mechanisms

Search for High-Mass Resonances Decaying to τν in pp Collisions at √s=13 TeV with the ATLAS Detector

A search for high-mass resonances decaying to τν using proton-proton collisions at √s=13 TeV produced by the Large Hadron Collider is presented. Only τ-lepton decays with hadrons in the final state are considered. The data were recorded with the ATLAS detector and correspond to an integrated luminosity of 36.1 fb−1. No statistically significant excess above the standard model expectation is observed; model-independent upper limits are set on the visible τν production cross section. Heavy W′ bosons with masses less than 3.7 TeV in the sequential standard model and masses less than 2.2–3.8 TeV depending on the coupling in the nonuniversal G(221) model are excluded at the 95% credibility level

Performance of missing transverse momentum reconstruction with the ATLAS detector using proton–proton collisions at √s = 13 TeV

The performance of the missing transverse momentum (EmissT) reconstruction with the ATLAS detector is evaluated using data collected in proton–proton collisions at the LHC at a centre-of-mass energy of 13 TeV in 2015. To reconstruct EmissT, fully calibrated electrons, muons, photons, hadronically decaying τ -leptons, and jets reconstructed from calorimeter energy deposits and charged-particle tracks are used. These are combined with the soft hadronic activity measured by reconstructed charged-particle tracks not associated with the hard objects. Possible double counting of contributions from reconstructed charged-particle tracks from the inner detector, energy deposits in the calorimeter, and reconstructed muons from the muon spectrometer is avoided by applying a signal ambiguity resolution procedure which rejects already used signals when combining the various EmissT contributions. The individual terms as well as the overall reconstructed EmissT are evaluated with various performance metrics for scale (linearity), resolution, and sensitivity to the data-taking conditions. The method developed to determine the systematic uncertainties of the EmissT scale and resolution is discussed. Results are shown based on the full 2015 data sample corresponding to an integrated luminosity of 3.2 fb−1

Operation and performance of the ATLAS Tile Calorimeter in Run 1

The Tile Calorimeter is the hadron calorimeter covering the central region of the ATLAS experiment at the Large Hadron Collider. Approximately 10,000 photomultipliers collect light from scintillating tiles acting as the active material sandwiched between slabs of steel absorber. This paper gives an overview of the calorimeter’s performance during the years 2008–2012 using cosmic-ray muon events and proton–proton collision data at centre-of-mass energies of 7 and 8TeV with a total integrated luminosity of nearly 30 fb−1. The signal reconstruction methods, calibration systems as well as the detector operation status are presented. The energy and time calibration methods performed excellently, resulting in good stability of the calorimeter response under varying conditions during the LHC Run 1. Finally, the Tile Calorimeter response to isolated muons and hadrons as well as to jets from proton–proton collisions is presented. The results demonstrate excellent performance in accord with specifications mentioned in the Technical Design Report

Measurement of the t¯tZ and t¯tW cross sections in proton-proton collisions at √s=13 TeV with the ATLAS detector

A measurement of the associated production of a top-quark pair (t¯t) with a vector boson (W, Z) in proton-proton collisions at a center-of-mass energy of 13 TeV is presented, using 36.1  fb−1 of integrated luminosity collected by the ATLAS detector at the Large Hadron Collider. Events are selected in channels with two same- or opposite-sign leptons (electrons or muons), three leptons or four leptons, and each channel is further divided into multiple regions to maximize the sensitivity of the measurement. The t¯tZ and t¯tW production cross sections are simultaneously measured using a combined fit to all regions. The best-fit values of the production cross sections are σt¯tZ=0.95±0.08stat±0.10syst pb and σt¯tW=0.87±0.13stat±0.14syst pb in agreement with the Standard Model predictions. The measurement of the t¯tZ cross section is used to set constraints on effective field theory operators which modify the t¯tZ vertex

Combined measurement of differential and total cross sections in the H → γγ and the H → ZZ* → 4ℓ decay channels at s=13 TeV with the ATLAS detector

A combined measurement of differential and inclusive total cross sections of Higgs boson production is performed using 36.1 fb−1 of 13 TeV proton–proton collision data produced by the LHC and recorded by the ATLAS detector in 2015 and 2016. Cross sections are obtained from measured H→γγ and H→ZZ*(→4ℓ event yields, which are combined taking into account detector efficiencies, resolution, acceptances and branching fractions. The total Higgs boson production cross section is measured to be 57.0−5.9 +6.0 (stat.) −3.3 +4.0 (syst.) pb, in agreement with the Standard Model prediction. Differential cross-section measurements are presented for the Higgs boson transverse momentum distribution, Higgs boson rapidity, number of jets produced together with the Higgs boson, and the transverse momentum of the leading jet. The results from the two decay channels are found to be compatible, and their combination agrees with the Standard Model predictions

Search for pairs of highly collimated photon-jets in pp collisions at √s = 13 TeV with the ATLAS detector

Results of a search for the pair production of photon-jets—collimated groupings of photons—in the ATLAS detector at the Large Hadron Collider are reported. Highly collimated photon-jets can arise from the decay of new, highly boosted particles that can decay to multiple photons collimated enough to be identified in the electromagnetic calorimeter as a single, photonlike energy cluster. Data from proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 36.7  fb−1, were collected in 2015 and 2016. Candidate photon-jet pair production events are selected from those containing two reconstructed photons using a set of identification criteria much less stringent than that typically used for the selection of photons, with additional criteria applied to provide improved sensitivity to photon-jets. Narrow excesses in the reconstructed diphoton mass spectra are searched for. The observed mass spectra are consistent with the Standard Model background expectation. The results are interpreted in the context of a model containing a new, high-mass scalar particle with narrow width, X, that decays into pairs of photon-jets via new, light particles, a. Upper limits are placed on the cross section times the product of branching ratios σ×B(X→aa)×B(a→γγ)2 for 200  GeV<mX<2  TeV and for ranges of ma from a lower mass of 100 MeV up to between 2 and 10 GeV, depending upon mX. Upper limits are also placed on σ×B(X→aa)×B(a→3π0)2 for the same range of mX and for ranges of ma from a lower mass of 500 MeV up to between 2 and 10 GeV

The analysis of relapse-free survival curves: implications for evaluating intensive systemic adjuvant treatment regimens for breast cancer

Results of adjuvant dose intensification studies in patients with localised breast cancer have raised questions regarding the clinical usefulness of this treatment strategy. Here, we develop and fit a natural history model for the time to clinical tumour recurrence as a function of the number of involved lymph nodes, and derive plausible predictions of the effects of dose intensification under various conditions. The time to tumour recurrence is assumed to depend on the residual postoperative micrometastatic burden of tumour, the fractional reduction of residual tumour burden (RTB) by treatment, and the rate of regrowth of the RTB to a clinically detectable size. It is assumed that a proportion of micrometastatic tumours are unresponsive to adjuvant chemotherapy even at maximal dose intensity. Data fitted included the San Antonio Cancer Institute (SACI) database of untreated patients, and CALGB #9082, a study comparing a highly intensive and moderately intensity adjuvant regimen in patients with 10+ positive axillary nodes. The proportion of tumours unresponsive to maximally intensive adjuvant treatment is estimated to be 48% (29–67%). The estimated log kill for intermediate-dose therapy from CALGB #9082 was 6.5 logs, compared with 9 logs or greater for high-dose therapy. The model is consistent with a modest but nonnegligible advantage of dose intensification compared with standard therapies in patients with sensitive tumours who have 10+ positive axillary nodes, and suggests that much of this clinical benefit could be achieved using intermediate levels of treatment intensification. The model further suggests that, in patients with fewer than 10 involved axillary nodes, any advantage of treatment intensification over standard therapy would be much reduced, because in patients with smaller tumour burdens of sensitive tumour, a larger proportion of cures achievable with intensified therapy could be achieved as well with standard therapy

Development of Bacterial Biofilms on Artificial Corals in Comparison to Surface-Associated Microbes of Hard Corals

Numerous studies have demonstrated the differences in bacterial communities associated with corals versus those in their surrounding environment. However, these environmental samples often represent vastly different microbial micro-environments with few studies having looked at the settlement and growth of bacteria on surfaces similar to corals. As a result, it is difficult to determine which bacteria are associated specifically with coral tissue surfaces. In this study, early stages of passive settlement from the water column to artificial coral surfaces (formation of a biofilm) were assessed. Changes in bacterial diversity (16S rRNA gene), were studied on artificially created resin nubbins that were modelled from the skeleton of the reef building coral Acropora muricata. These models were dip-coated in sterile agar, mounted in situ on the reef and followed over time to monitor bacterial community succession. The bacterial community forming the biofilms remained significantly different (R = 0.864 p<0.05) from that of the water column and from the surface mucus layer (SML) of the coral at all times from 30 min to 96 h. The water column was dominated by members of the α-proteobacteria, the developed community on the biofilms dominated by γ-proteobacteria, whereas that within the SML was composed of a more diverse array of groups. Bacterial communities present within the SML do not appear to arise from passive settlement from the water column, but instead appear to have become established through a selection process. This selection process was shown to be dependent on some aspects of the physico-chemical structure of the settlement surface, since agar-coated slides showed distinct communities to coral-shaped surfaces. However, no significant differences were found between different surface coatings, including plain agar and agar enhanced with coral mucus exudates. Therefore future work should consider physico-chemical surface properties as factors governing change in microbial diversity