Internationalisation and migrant academics: the hidden narratives of mobility

Internationalisation is a dominant policy discourse in higher education today. It is invariably presented as an ideologically neutral, coherent, disembodied, knowledgedriven policy intervention - an unconditional good. Yet it is a complex assemblage of values linked not only to economic growth and prosperity, but also to global citizenship, transnational identity capital, social cohesion, intercultural competencies and soft power (Clifford and Montgomery 2014; De Wit et al. 2015; Kim 2017; Lomer 2016; Stier 2004). Mobility is the sine qua non of the global academy (Sheller 2014). International movements, flows and networks are perceived as valuable transnational and transferable identity capital and as counterpoints to intellectual parochialism. Fluidity metaphors abound as an antidote to stasis e.g. flows, flux and circulations (Urry 2007). For some, internationalisation is conceptually linked to the political economy of neoliberalism and the spatial extension of the market, risking commodification and commercialisation (Matus and Talburt 2009). Others raise questions about what/whose knowledge is circulating and whether internationalisation is a form of re-colonisation and convergence that seeks to homogenise higher education systems (Stromquist 2007). Internationalisation policies and practices, it seems, are complex entanglements of economic, political, social and affective domains. They are mechanisms for driving the global knowledge 2 economy and the fulfilment of personal aspirations (Hoffman 2009). Academic geographical mobility is often conflated with social mobility and career advancement (Leung 2017). However, Robertson (2010: 646) suggested that ‘the romance of movement and mobility ought to be the first clue that this is something we ought to be particularly curious about.

Impact of Availability of Telehealth Programs on Documented HIV Viral Suppression: A Cluster-Randomized Program Evaluation in the Veterans Health Administration

Background: Telehealth may improve care for people with HIV who live far from HIV specialty clinics. We conducted a cluster-randomized evaluation to determine the impact of availability of HIV telehealth programs on documented viral suppression in Veterans Administration clinics. Methods: In 2015–2016, people who previously traveled to HIV specialty clinics were offered telehealth visits in nearby primary care clinics. Patients were cluster-randomized to immediate telehealth availability (n = 925 patients in service areas of 13 primary care clinics offering telehealth) or availability 1 year later (n = 745 patients in 12 clinics). Measures during the evaluation year included telehealth use among patients in areas where telehealth was available and documented HIV viral suppression (viral load performed and /mL). Impact of telehealth availability was determined using intention-to-treat (ITT) analyses that compared outcomes for patients in areas where telehealth was available with outcomes for patients where telehealth was not available, regardless of telehealth use. Complier average causal effects (CACEs) compared outcomes for telehealth users with outcomes for control patients with equal propensity to use telehealth, when available. Results: Overall, 120 (13.0%) patients utilized telehealth when it was available. Availability of telehealth programs led to small improvements in viral suppression in ITT analyses (78.3% vs 74.1%; relative risk [RR], 1.06; 95% confidence interval [CI], 1.01 to 1.11) and large improvements among telehealth users in CACE analyses (91.5% vs 80.0%; RR, 1.14; 95% CI, 1.01 to 1.30). Conclusions: Availability of telehealth programs improved documented viral suppression. HIV clinics should offer telehealth visits for patients facing travel burdens

Impact of Availability of Telehealth Programs on Documented HIV Viral Suppression: A Cluster-Randomized Program Evaluation in the Veterans Health Administration

Background: Telehealth may improve care for people with HIV who live far from HIV specialty clinics. We conducted a cluster-randomized evaluation to determine the impact of availability of HIV telehealth programs on documented viral suppression in Veterans Administration clinics. Methods: In 2015–2016, people who previously traveled to HIV specialty clinics were offered telehealth visits in nearby primary care clinics. Patients were cluster-randomized to immediate telehealth availability (n = 925 patients in service areas of 13 primary care clinics offering telehealth) or availability 1 year later (n = 745 patients in 12 clinics). Measures during the evaluation year included telehealth use among patients in areas where telehealth was available and documented HIV viral suppression (viral load performed and /mL). Impact of telehealth availability was determined using intention-to-treat (ITT) analyses that compared outcomes for patients in areas where telehealth was available with outcomes for patients where telehealth was not available, regardless of telehealth use. Complier average causal effects (CACEs) compared outcomes for telehealth users with outcomes for control patients with equal propensity to use telehealth, when available. Results: Overall, 120 (13.0%) patients utilized telehealth when it was available. Availability of telehealth programs led to small improvements in viral suppression in ITT analyses (78.3% vs 74.1%; relative risk [RR], 1.06; 95% confidence interval [CI], 1.01 to 1.11) and large improvements among telehealth users in CACE analyses (91.5% vs 80.0%; RR, 1.14; 95% CI, 1.01 to 1.30). Conclusions: Availability of telehealth programs improved documented viral suppression. HIV clinics should offer telehealth visits for patients facing travel burdens

Correlation of Cerebral Microdialysis with Non-Invasive Diffuse Optical Cerebral Hemodynamic Monitoring during Deep Hypothermic Cardiopulmonary Bypass

Neonates undergoing cardiac surgery involving aortic arch reconstruction are at an increased risk for hypoxic-ischemic brain injury. Deep hypothermia is utilized to help mitigate this risk when periods of circulatory arrest are needed for surgical repair. Here, we investigate correlations between non-invasive optical neuromonitoring of cerebral hemodynamics, which has recently shown promise for the prediction of postoperative white matter injury in this patient population, and invasive cerebral microdialysis biomarkers. We compared cerebral tissue oxygen saturation (StO2), relative total hemoglobin concentration (rTHC), and relative cerebral blood flow (rCBF) measured by optics against the microdialysis biomarkers of metabolic stress and injury (lactate–pyruvate ratio (LPR) and glycerol) in neonatal swine models of deep hypothermic cardiopulmonary bypass (DHCPB), selective antegrade cerebral perfusion (SACP), and deep hypothermic circulatory arrest (DHCA). All three optical parameters were negatively correlated with LPR and glycerol in DHCA animals. Elevation of LPR was found to precede the elevation of glycerol by 30–60 min. From these data, thresholds for the detection of hypoxic-ischemia-associated cerebral metabolic distress and neurological injury are suggested. In total, this work provides insight into the timing and mechanisms of neurological injury following hypoxic-ischemia and reports a quantitative relationship between hypoxic-ischemia severity and neurological injury that may inform DHCA management

Randomized prospective study evaluating tenofovir disoproxil fumarate prophylaxis against hepatitis B virus reactivation in anti-HBc-positive patients with rituximab-based regimens to treat hematologic malignancies: The Preblin study

BACKGROUND: Hepatitis B virus (HBV) reactivation in patients with resolved HBV infection (HBsAg negative, antiHBc positive) is uncommon, but potentially fatal. The role of HBV prophylaxis in this setting is uncertain. The aim of this study was to compare the efficacy of tenofovir disoproxil fumarate (TDF) prophylaxis versus close monitoring in antiHBc-positive, HBsAg-negative patients under treatment with rituximab (RTX)-based regimens for hematologic malignancy. METHODS: PREBLIN is a phase IV, randomized, prospective, open-label, multicenter, parallel-group trial conducted in 17 hospitals throughout Spain. Anti-HBc-positive, HBsAg-negative patients with undetectable HBV DNA were randomized to receive TDF 300 mg once daily (Group I) or observation (Group II). The primary endpoint was the percentage of patients showing HBV reactivation during 18 months following initiation of RTX treatment. Patients with detectable HBV DNA (Group III) received the same dose of TDF and were analyzed together with Group I to investigate TDF safety. RESULTS: Sixty-one patients were enrolled in the study, 33 in the TDF treatment group and 28 in the observation group. By ITT analysis, HBV reactivation was 0% (0/33) in the study group and 10.7% (3/28) in the observation group (p = 0.091). None of the patients in either group showed significant differences in liver function parameters between baseline and the last follow-up sample. TDF was generally well tolerated and there were no severe treatment-related adverse events. CONCLUSION: In patients with hematological malignancy and resolved hepatitis B infection receiving RTX-based regimens, HBV reactivation did not occur in patients given TDF prophylaxis

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)