AMP-activated protein kinase (AMPK) β subunits (β1 and β2) provide scaffolds for binding α and γ subunits and contain a carbohydrate-binding module important for regulating enzyme activity. We ...generated C57Bl/6 mice with germline deletion of AMPK β2 (β2 KO) and examined AMPK expression and activity, exercise capacity, metabolic control during muscle contractions, aminoimidazole carboxamide ribonucleotide (AICAR) sensitivity, and susceptibility to obesity-induced insulin resistance. We find that β2 KO mice are viable and breed normally. β2 KO mice had a reduction in skeletal muscle AMPK α1 and α2 expression despite up-regulation of the β1 isoform. Heart AMPK α2 expression was also reduced but this did not affect resting AMPK α1 or α2 activities. AMPK α1 and α2 activities were not changed in liver, fat, or hypothalamus. AICAR-stimulated glucose uptake but not fatty acid oxidation was impaired in β2 KO mice. During treadmill running β2 KO mice had reduced maximal and endurance exercise capacity, which was associated with lower muscle and heart AMPK activity and reduced levels of muscle and liver glycogen. Reductions in exercise capacity of β2 KO mice were not due to lower muscle mitochondrial content or defects in contraction-stimulated glucose uptake or fatty acid oxidation. When challenged with a high-fat diet β2 KO mice gained more weight and were more susceptible to the development of hyperinsulinemia and glucose intolerance. In summary these data show that deletion of AMPK β2 reduces AMPK activity in skeletal muscle resulting in impaired exercise capacity and the worsening of diet-induced obesity and glucose intolerance.
Supernova remnants (SNRs) interacting with molecular clouds are potentially exciting systems in which to detect evidence of cosmic ray acceleration. Prominent gamma-ray emission is produced via the ...decay of neutral pions when cosmic rays encounter nearby dense clouds. In many of the SNRs coincident with gamma-ray sources, the presence of OH (1720 MHz) masers is used to identify interaction with dense gas and to provide a kinematic distance to the system. In this Letter we use statistical tests to demonstrate that there is a correlation between these masers and a class of GeV- to TeV-energy gamma-ray sources coincident with interacting remnants. For pion decay the gamma-ray luminosity provides a direct estimate of the local cosmic ray density. We find the cosmic ray density is enhanced by one to two orders of magnitude over the local solar value, comparable to X-ray-induced ionization in these remnants. The inferred ionization rates are sufficient to explain non-equilibrium chemistry in the post-shock gas, where high columns of hydroxyl are observed.
The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, ...lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25–5.0 μg/mL) and/or carbendazim (0.8–1.6 μg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the “DeepFlow” neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for ‘mononucleates’, ‘binucleates’, ‘mononucleates with MN’ and ‘binucleates with MN’, respectively. Successful classifications of ‘trinucleates’ (90%) and ‘tetranucleates’ (88%) in addition to ‘other or unscorable’ phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.
Recent observations suggest that some high-velocity clouds may be confined by massive dark matter halos. In particular, the proximity and proposed dark matter content of the Smith Cloud make it a ...tempting target for the indirect detection of dark matter annihilation. We argue that the Smith Cloud may be a better target than some Milky Way dwarf spheroidal satellite galaxies and use gamma -ray observations from the Fermi Large Area Telescope to search for a dark matter annihilation signal. No significant gamma -ray excess is found coincident with the Smith Cloud, and we set strong limits on the dark matter annihilation cross section assuming a spatially extended dark matter profile consistent with dynamical modeling of the Smith Cloud. Notably, these limits exclude the canonical thermal relic cross section (~3 x 10 super(-26) cm super(3) s super(-1)) for dark matter masses lap30 GeV annihilating via the bb or tau super(+)tau super(-) channels for certain assumptions of the dark matter density profile; however, uncertainties in the dark matter content of the Smith Cloud may significantly weaken these constraints.
Purpose: Cancer cells can use X-linked inhibitor of apoptosis (XIAP) to evade apoptotic cues, including chemotherapy. The antitumor
potential of AEG35156, a novel second-generation antisense ...oligonucleotide directed toward XIAP, was assessed in human cancer
models when given as a single agent and in combination with clinically relevant chemotherapeutics.
Experimental Design: AEG35156 was characterized for its ability to cause dose-dependent reductions of XIAP mRNA and protein in vitro and in vivo , to sensitize cancer cell lines to death stimuli, and to exhibit antitumor activity in multiple human cancer xenograft models
as a single agent or in combination with chemotherapy.
Results: AEG35156 reduced XIAP mRNA levels with an EC 50 of 8 to 32 nmol/L and decreased XIAP protein levels by >80%. Loss of XIAP protein correlated with increased sensitization
to tumor necrosis factor–related apoptosis-inducing ligand (TRAIL)–mediated apoptosis in Panc-1 pancreatic carcinoma cells.
AEG35156 exhibited potent antitumor activity relative to control oligonucleotides in three human cancer xenograft models (prostate,
colon, and lung) and was capable of inducing complete tumor regression when combined with taxanes. Antitumor effects of AEG35156
correlated with suppression of tumor XIAP levels.
Conclusions: AEG35156 reduces XIAP levels and sensitizes tumors to chemotherapy. AEG35156 is presently under clinical assessment in multiple
phase I trials in cancer patients as a single agent and in combination with docetaxel in solid tumors or cytarabine/idarubicin
in leukemia.
Unlocking and quantifying fundamental biological processes through tissue microscopy requires accurate, in situ segmentation of all cells imaged. Currently, achieving this is complex and requires ...exogenous fluorescent labels that occupy significant spectral bandwidth, increasing the duration and complexity of imaging experiments while limiting the number of channels remaining to address the study’s objectives. We demonstrate that the excitation light reflected during routine confocal microscopy contains sufficient information to achieve accurate, label-free cell segmentation in 2D and 3D. This is achieved using a simple convolutional neural network trained to predict the probability that reflected light pixels belong to either nucleus, cytoskeleton, or background classifications. We demonstrate the approach across diverse lymphoid tissues and provide video tutorials demonstrating deployment in Python and MATLAB or via standalone software for Windows.
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•Cell segmentation of tissues can be achieved from reflected laser excitation light•Single-cell information is freely established for many tissue microscopy studies•Windows software is provided alongside extensive video tutorials and data
Across the biomedical sciences, there is an urgent need to move beyond qualitative imaging to quantitative, cell-based reporting of tissue microscopy data. Typically, cell segmentation requires fluorescent labeling of nucleus and cytoplasm, which limits the spectral bandwidth available for other reporter molecules. However, recent advances in deep-learning algorithms have transformed automated image classification, and this raises the possibility of proceeding with reduced image information. Here, we show that 2D and 3D cell segmentation of lymphoid tissues can be freely established from the reflected laser excitation light always present during routine confocal microscopy using entirely standard equipment.
Cell segmentation is an essential step in quantitative tissue microscopy. Wills et al. show this can be achieved simply using the reflected laser light always present during routine imaging by confocal microscopy. This frees up microscope channels and establishes single-cell information as an attainable start point for many tissue microscopy experiments.
The value of KI67 in breast cancer prognostication has been questioned due to concerns on the analytical validity of visual KI67 assessment and methodological limitations of published studies. Here, ...we investigate the prognostic value of automated KI67 scoring in a large, multicentre study, and compare this with pathologists' visual scores available in a subset of patients.
We utilised 143 tissue microarrays containing 15,313 tumour tissue cores from 8088 breast cancer patients in 10 collaborating studies. A total of 1401 deaths occurred during a median follow-up of 7.5 years. Centralised KI67 assessment was performed using an automated scoring protocol. The relationship of KI67 levels with 10-year breast cancer specific survival (BCSS) was investigated using Kaplan-Meier survival curves and Cox proportional hazard regression models adjusted for known prognostic factors.
Patients in the highest quartile of KI67 (>12 % positive KI67 cells) had a worse 10-year BCSS than patients in the lower three quartiles. This association was statistically significant for ER-positive patients (hazard ratio (HR) (95 % CI) at baseline = 1.96 (1.31-2.93); P = 0.001) but not for ER-negative patients (1.23 (0.86-1.77); P = 0.248) (P-heterogeneity = 0.064). In spite of differences in characteristics of the study populations, the estimates of HR were consistent across all studies (P-heterogeneity = 0.941 for ER-positive and P-heterogeneity = 0.866 for ER-negative). Among ER-positive cancers, KI67 was associated with worse prognosis in both node-negative (2.47 (1.16-5.27)) and node-positive (1.74 (1.05-2.86)) tumours (P-heterogeneity = 0.671). Further classification according to ER, PR and HER2 showed statistically significant associations with prognosis among hormone receptor-positive patients regardless of HER2 status (P-heterogeneity = 0.270) and among triple-negative patients (1.70 (1.02-2.84)). Model fit parameters were similar for visual and automated measures of KI67 in a subset of 2440 patients with information from both sources.
Findings from this large-scale multicentre analysis with centrally generated automated KI67 scores show strong evidence in support of a prognostic value for automated KI67 scoring in breast cancer. Given the advantages of automated scoring in terms of its potential for standardisation, reproducibility and throughput, automated methods appear to be promising alternatives to visual scoring for KI67 assessment.
The increasing number of drugs targeting specific proteins implicated in tumourigenesis and the commercial promotion of relatively affordable genome-wide analyses has led to an increasing expectation ...among patients with cancer that they can now receive effective personalised treatment based on the often complex genomic signature of their tumour. For such approaches to work in routine practice, the development of correspondingly complex biomarker assays through an appropriate and rigorous regulatory framework will be required. It is becoming increasingly evident that a re-engineering of clinical research is necessary so that regulatory considerations and procedures facilitate the efficient translation of these required biomarker assays from the discovery setting through to clinical application. This article discusses the practical requirements and challenges of developing such new precision medicine strategies, based on leveraging complex genomic profiles, as discussed at the Innovation and Biomarkers in Cancer Drug Development meeting (8th–9th September 2016, Brussels, Belgium).
•Premature rollout of assays and technologies without proper analytical validation is often done before it is clinically appropriate.•Expensive though non-fully validated technical solutions brings no added value to the health care systems.•The current process of developing and validating biomarkers and assays needs streamlining alongside the principles developed in this paper.•In the absence of regulatory framework for biomarker development, discipline and common sense processes and guidelines must be strictly followed.
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