The magnitude of educational disadvantage amongst indigenous minority groups in Australia.

Indigenous groups are amongst the most disadvantaged minority groups in the developed world. This paper examines the educational disadvantage of indigenous Australians by assessing academic performance at a relatively early age. We find that, by the age of 10, indigenous Australians are substantially behind non-indigenous Australians in academic achievement. Their relative performance deteriorates further over the next 2 years. School and locality do not appear to be important determinants of the indigenous to non-indigenous achievement gap. However, geographic remoteness, indigenous ethnicity and language use at home have a marked influence on educational achievement. A current focus of Australian indigenous policy is to increase school resources. Our results suggest that this will not eliminate indigenous educational disadvantage on its own

Suppression of uPA and uPAR Attenuates Angiogenin Mediated Angiogenesis in Endothelial and Glioblastoma Cell Lines

In our earlier reports, we showed that downregulation of uPA and uPAR inhibited glioma tumor angiogenesis in SNB19 cells, and intraperitoneal injection of a hairpin shRNA expressing plasmid targeting uPA and uPAR inhibited angiogenesis in nude mice. The exact mechanism by which inhibition of angiogenesis takes place is not clearly understood.In the present study, we have attempted to investigate the mechanism by which uPA/uPAR downregulation by shRNA inhibits angiogenesis in endothelial and glioblastoma cell lines. uPA/uPAR downregulation by shRNA in U87 MG and U87 SPARC co-cultures with endothelial cells inhibited angiogenesis as assessed by in vitro angiogenesis assay and in vivo dorsal skin-fold chamber model in nude mice. Protein antibody array analysis of co-cultures of U87 and U87 SPARC cells with endothelial cells treated with pU2 (shRNA against uPA and uPAR) showed decreased angiogenin secretion and angiopoietin-1 as well as several other pro-angiogenic molecules. Therefore, we investigated the role of angiogenin and found that nuclear translocation, ribonucleolytic and 45S rRNA synthesis, which are all critical for angiogenic function of angiogenin, were significantly inhibited in endothelial cells transfected with uPA, uPAR and uPA/uPAR when compared with controls. Moreover, uPA and uPAR downregulation significantly inhibited the phosphorylation of Tie-2 receptor and also down regulated FKHR activation in the nucleus of endothelial cells via the GRB2/AKT/BAD pathway. Treatment of endothelial cells with ruPA increased angiogenin secretion and angiogenin expression as determined by ELISA and western blotting in a dose-dependent manner. The amino terminal fragment of uPA down regulated ruPA-induced angiogenin in endothelial cells, thereby suggesting that uPA plays a critical role in positively regulating angiogenin in glioblastoma cells.Taken together, our results suggest that uPA/uPAR downregulation suppresses angiogenesis in endothelial cells induced by glioblastoma cell lines partially by downregulation of angiogenin and by inhibition of the angiopoietin-1/AKT/FKHR pathway

Notch and Senescence.

Cellular senescence, previously thought of as an autonomous tumour suppressor mechanism, is emerging as a phenotype and effector present throughout the life of an organism from embryogenesis to senile decline. Senescent cells have powerful non-autonomous effects upon multiple players within their microenvironment mainly through their secretory phenotype. How senescent cells co-ordinate numerous, sometimes functionally contrasting outputs through their secretome had previously been unclear. The Notch pathway, originally identified for its involvement in Drosophila wing development, has more recently been found to underpin diverse effects in human cancer. Here we discuss recent findings that suggest that Notch is intimately involved in the development of senescence and how it acts to co-ordinate the composition and functional effects of the senescence secretome. We also highlight the complex physical and functional interplay between Notch and p53, critical to both senescence and cancer. Understanding the interplay between Notch, p53 and senescence could allow us develop the therapeutics of the future for cancer and ageing

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

NOTCH1 mediates a switch between two distinct secretomes during senescence

Senescence, a persistent form of cell-cycle arrest, is often associated with a diverse secretome, which provides complex functionality for senescent cells within the tissue microenvironment. We show that oncogene-induced senescence is accompanied by a dynamic fluctuation of NOTCH1 activity, which drives a TGF-β-rich secretome, while suppressing the senescence-associated pro-inflammatory secretome through inhibition of C/EBPβ. NOTCH1 and NOTCH1-driven TGF-β contribute to 'lateral induction of senescence' through a juxtacrine NOTCH-JAG1 pathway. In addition, NOTCH1 inhibition during senescence facilitates upregulation of pro-inflammatory cytokines, promoting lymphocyte recruitment and senescence surveillance in vivo. As enforced activation of NOTCH1 signalling confers a near mutually exclusive secretory profile compared with typical senescence, our data collectively indicate that the dynamic alteration of NOTCH1 activity during senescence dictates a functional balance between these two distinct secretomes: one representing TGF-β and the other pro-inflammatory cytokines, highlighting that NOTCH1 is a temporospatial controller of secretome composition.This work was supported by the University of Cambridge, Cancer Research UK and Hutchison Whampoa. The M.N. laboratory is supported by Cancer Research UK Cambridge Institute Core Grant (C14303/A17197). M.H. was supported by CRUK Translational Medicine Research Fellowship and CRUK Clinician Scientist Fellowship (C52489/A19924). This work was also supported by a Wellcome Trust PRF (WT101835) to P.J.L., a Wellcome Trust Senior Fellowship to M.P.W. (108070/Z/15/Z), a Wellcome Trust Training Fellowship to N.J.M. (093964/Z/10/Z), and a Wellcome Trust Intermediate Fellowship (097162/Z/11/Z) to S.S. L.Z. was funded by the German Research Foundation (DFG; grants FOR2314 and SFB685), the Gottfried Wilhelm Leibniz Program, the European Research Council (projects ‘CholangioConcept’), the German Ministry for Education and Research (BMBF) (eMed-Multiscale HCC), the German Universities Excellence Initiative (third funding line: ‘future concept’), the German Center for Translational Cancer Research (DKTK) and the German–Israeli Cooperation in Cancer Research (DKFZ–MOST).This is the author accepted manuscript. The final version is available from Nature Publishing Group at http://dx.doi.org/10.1038/ncb3397

Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020-December 2021

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020–December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Summary Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

Background: Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods: We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. Results: We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Conclusions: As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals. © 2022, The Author(s)

Tracking SARS-CoV-2 mutations and variants through the COG-UK-Mutation Explorer

COG-UK Mutation Explorer (COG-UK-ME, https://sars2.cvr.gla.ac.uk/cog-uk/—last accessed date 16 March 2022) is a web resource that displays knowledge and analyses on SARS-CoV-2 virus genome mutations and variants circulating in the UK, with a focus on the observed amino acid replacements that have an antigenic role in the context of the human humoral and cellular immune response. This analysis is based on more than 2 million genome sequences (as of March 2022) for UK SARS-CoV-2 data held in the CLIMB-COVID centralised data environment. COG-UK-ME curates these data and displays analyses that are cross-referenced to experimental data collated from the primary literature. The aim is to track mutations of immunological importance that are accumulating in current variants of concern and variants of interest that could alter the neutralising activity of monoclonal antibodies (mAbs), convalescent sera, and vaccines. Changes in epitopes recognised by T cells, including those where reduced T cell binding has been demonstrated, are reported. Mutations that have been shown to confer SARS-CoV-2 resistance to antiviral drugs are also included. Using visualisation tools, COG-UK-ME also allows users to identify the emergence of variants carrying mutations that could decrease the neutralising activity of both mAbs present in therapeutic cocktails, e.g. Ronapreve. COG-UK-ME tracks changes in the frequency of combinations of mutations and brings together the curated literature on the impact of those mutations on various functional aspects of the virus and therapeutics. Given the unpredictable nature of SARS-CoV-2 as exemplified by yet another variant of concern, Omicron, continued surveillance of SARS-CoV-2 remains imperative to monitor virus evolution linked to the efficacy of therapeutics