2,402 research outputs found

    The mRNA expression of SETD2 in human breast cancer: Correlation with clinico-athological parameters

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    BACKGROUND: SET domain containing protein 2 (SETD2) is a histone methyltransferase that is involved in transcriptional elongation. There is evidence that SETD2 interacts with p53 and selectively regulates its downstream genes. Therefore, it could be implicated in the process of carcinogenesis. Furthermore, this gene is located on the short arm of chromosome 3p and we previously demonstrated that the 3p21.31 region of chromosome 3 was associated with permanent growth arrest of breast cancer cells. This region includes closely related genes namely: MYL3, CCDC12, KIF9, KLHL18 and SETD2. Based on the biological function of these genes, SETD2 is the most likely gene to play a tumour suppressor role and explain our previous findings. Our objective was to determine, using quantitative PCR, whether the mRNA expression levels of SETD2 were consistent with a tumour suppressive function in breast cancer. This is the first study in the literature to examine the direct relationship between SETD2 and breast cancer. METHODS: A total of 153 samples were analysed. The levels of transcription of SETD2 were determined using quantitative PCR and normalized against (CK19). Transcript levels within breast cancer specimens were compared to normal background tissues and analyzed against conventional pathological parameters and clinical outcome over a 10 year follow-up period. RESULTS: The levels of SETD2 mRNA were significantly lower in malignant samples (p = 0.0345) and decreased with increasing tumour stage. SETD2 expression levels were significantly lower in samples from patients who developed metastasis, local recurrence, or died of breast cancer when compared to those who were disease free for > 10 years (p = 0.041). CONCLUSION: This study demonstrates a compelling trend for SETD2 transcription levels to be lower in cancerous tissues and in patients who developed progressive disease. These findings are consistent with a possible tumour suppressor function of this gene in breast cancer

    Modelling socio-economic and energy data to generate business-as-usual scenarios for carbon emissions

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    The UK Government is legally committed to achieving an 80% reduction in carbon dioxide emissions compared with 1990 by 2050. The use of scenarios is wide ranging to inform policy development and forming a businessas-usual scenario helps to understand possible effects of different policy interventions. However, the term business-as-usual is frequently misused. We show how econo-physical business-as-usual scenarios can be developed by examining the historical behaviour of coefficients which manifest the relationship between components of an economy. We endogenise economic growth by mimicking national level policies that focus on a target level of unemployment. Our case-study demonstrates the ‘trendability’ of coefficients which for one example coefficient is replicated for Australia, Colombia, Taiwan and the USA. We manifest a gross domestic product growth of 2% falling to 1% which contrasts with an exogenous growth of 2.3% of a comparator business-as-usual scenario. We suggest that it may be possible to achieve a greater reduction in the business-asusual carbon dioxide emissions in the UK fifth carbon budget than currently projected.Arup’s internal Design and Technical Fun

    A Universal Model of Global Civil Unrest

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    Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, we analyze records of civil unrest of 170 countries during the period 1919-2008. We demonstrate that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics.Comment: 8 pages, 3 figure

    Inorganic Nitrate Promotes Glucose Uptake and Oxidative Catabolism in White Adipose Tissue through the XOR Catalyzed Nitric Oxide Pathway

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    An ageing global population combined with sedentary lifestyles and unhealthy diets has contributed to an increasing incidence of obesity and type 2 diabetes. These metabolic disorders are associated with perturbations to nitric oxide (NO) signaling and impaired glucose metabolism. Dietary inorganic nitrate, found in high concentration in green leafy vegetables, can be converted to NO in vivo and demonstrates anti-diabetic and anti-obesity properties in rodents. Alongside tissues including skeletal muscle and liver, white adipose tissue is also an important physiological site of glucose disposal. However, the distinct molecular mechanisms governing the effect of nitrate on adipose tissue glucose metabolism, and the contribution of this tissue to the glucose tolerant phenotype, remain to be determined. Using a metabolomic and stable-isotope labeling approach, combined with transcriptional analysis, we found that nitrate increases glucose uptake and oxidative catabolism in primary adipocytes and white adipose tissue of nitrate-treated rats. Mechanistically, we determine that nitrate induces these phenotypic changes in primary adipocytes through the xanthine oxidoreductase catalysed reduction of nitrate to nitric oxide and independently of Peroxisome Proliferator-Activated Receptor α. The nitrate-mediated enhancement of glucose uptake and catabolism in white adipose tissue may be a key contributor to the anti-diabetic effects of this anion

    Plasma metabolites distinguish dementia with Lewy bodies from Alzheimer’s disease: a cross-sectional metabolomic analysis

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    Copyright \ua9 2024 Pan, Donaghy, Roberts, Chouliaras, O’Brien, Thomas, Heslegrave, Zetterberg, McGuinness, Passmore, Green and Kane.Background: In multifactorial diseases, alterations in the concentration of metabolites can identify novel pathological mechanisms at the intersection between genetic and environmental influences. This study aimed to profile the plasma metabolome of patients with dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD), two neurodegenerative disorders for which our understanding of the pathophysiology is incomplete. In the clinical setting, DLB is often mistaken for AD, highlighting a need for accurate diagnostic biomarkers. We therefore also aimed to determine the overlapping and differentiating metabolite patterns associated with each and establish whether identification of these patterns could be leveraged as biomarkers to support clinical diagnosis. Methods: A panel of 630 metabolites (Biocrates MxP Quant 500) and a further 232 metabolism indicators (biologically informative sums and ratios calculated from measured metabolites, each indicative for a specific pathway or synthesis; MetaboINDICATOR) were analyzed in plasma from patients with probable DLB (n = 15; age 77.6 \ub1 8.2 years), probable AD (n = 15; 76.1 \ub1 6.4 years), and age-matched cognitively healthy controls (HC; n = 15; 75.2 \ub1 6.9 years). Metabolites were quantified using a reversed-phase ultra-performance liquid chromatography column and triple-quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode, or by using flow injection analysis in MRM mode. Data underwent multivariate (PCA analysis), univariate and receiving operator characteristic (ROC) analysis. Metabolite data were also correlated (Spearman r) with the collected clinical neuroimaging and protein biomarker data. Results: The PCA plot separated DLB, AD and HC groups (R2 = 0.518, Q2 = 0.348). Significant alterations in 17 detected metabolite parameters were identified (q ≤ 0.05), including neurotransmitters, amino acids and glycerophospholipids. Glutamine (Glu; q = 0.045) concentrations and indicators of sphingomyelin hydroxylation (q = 0.039) distinguished AD and DLB, and these significantly correlated with semi-quantitative measurement of cardiac sympathetic denervation. The most promising biomarker differentiating AD from DLB was Glu:lysophosphatidylcholine (lysoPC a 24:0) ratio (AUC = 0.92; 95%CI 0.809–0.996; sensitivity = 0.90; specificity = 0.90). Discussion: Several plasma metabolomic aberrations are shared by both DLB and AD, but a rise in plasma glutamine was specific to DLB. When measured against plasma lysoPC a C24:0, glutamine could differentiate DLB from AD, and the reproducibility of this biomarker should be investigated in larger cohorts

    Emergent Gauge Fields in Holographic Superconductors

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    Holographic superconductors have been studied so far in the absence of dynamical electromagnetic fields, namely in the limit in which they coincide with holographic superfluids. It is possible, however, to introduce dynamical gauge fields if a Neumann-type boundary condition is imposed on the AdS-boundary. In 3+1 dimensions, the dual theory is a 2+1 dimensional CFT whose spectrum contains a massless gauge field, signaling the emergence of a gauge symmetry. We study the impact of a dynamical gauge field in vortex configurations where it is known to significantly affect the energetics and phase transitions. We calculate the critical magnetic fields H_c1 and H_c2, obtaining that holographic superconductors are of Type II (H_c1 < H_c2). We extend the study to 4+1 dimensions where the gauge field does not appear as an emergent phenomena, but can be introduced, by a proper renormalization, as an external dynamical field. We also compare our predictions with those arising from a Ginzburg-Landau theory and identify the generic properties of Abrikosov vortices in holographic models.Comment: 19 pages, 14 figures, few comments added, version published in JHE

    Mechanical activation of vinculin binding to talin locks talin in an unfolded conformation

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    The force-dependent interaction between talin and vinculin plays a crucial role in the initiation and growth of focal adhesions. Here we use magnetic tweezers to characterise the mechano-sensitive compact N-terminal region of the talin rod, and show that the three helical bundles R1-R3 in this region unfold in three distinct steps consistent with the domains unfolding independently. Mechanical stretching of talin R1-R3 enhances its binding to vinculin and vinculin binding inhibits talin refolding after force is released. Mutations that stabilize R3 identify it as the initial mechano-sensing domain in talin, unfolding at ~5 pN, suggesting that 5 pN is the force threshold for vinculin binding and adhesion progression

    Prdm1 Regulates Thymic Epithelial Function To Prevent Autoimmunity

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    Autoimmunity is largely prevented by medullary thymic epithelial cells (TECs) through their expression and presentation of tissue-specific Ags to developing thymocytes, resulting in deletion of self-reactive T cells and supporting regulatory T cell development. The transcription factor Prdm1 has been implicated in autoimmune diseases in humans through genome-wide association studies and in mice using cell type–specific deletion of Prdm1 in T and dendritic cells. In this article, we demonstrate that Prdm1 functions in TECs to prevent autoimmunity in mice. Prdm1 is expressed by a subset of mouse TECs, and conditional deletion of Prdm1 in either Keratin 14– or Foxn1-expressing cells in mice resulted in multisymptom autoimmune pathology. Notably, the development of Foxp3+ regulatory T cells occurs normally in the absence of Blimp1. Importantly, nude mice developed anti-nuclear Abs when transplanted with Prdm1 null TECs, but not wild-type TECs, indicating that Prdm1 functions in TECs to regulate autoantibody production. We show that Prdm1 acts independently of Aire, a crucial transcription factor implicated in medullary TEC function. Collectively, our data highlight a previously unrecognized role for Prdm1 in regulating thymic epithelial function

    An introduction to genetic quality in the context of sexual selection

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    This special issue of Genetica brings together empirical researchers and theoreticians to present the latest on the evolutionary ecology of genetic quality in the context of sexual selection. The work comes from different fields of study including behavioral ecology, quantitative genetics and molecular genetics on a diversity of organisms using different approaches from comparative studies, mathematical modeling, field studies and laboratory experiments. The papers presented in this special issue primarily focus on genetic quality in relation to ( 1) sources of genetic variation, ( 2) polyandry, ( 3) new theoretical developments and ( 4) comprehensive reviews

    At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR-based tests? A systematic review of individual participant data

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    Background: Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA) using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity. / Methods: We conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv, and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS-2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites. / Results: Of 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from − 6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 and 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post-symptom onset. / Conclusions: RT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond 10 days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias, so the positivity rates are probably overestimated
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