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Abstract Glioblastoma is the most common and aggressive primary brain tumour in adults. The development of anti-brain cancer agents are challenged by the blood-brain barrier and the resistance conferred by the local tumour microenvironment. Heptamethine cyanine dyes (HMCDs) are a class of near-infrared fluorescence compounds that have recently emerged as promising agents for drug delivery. We conjugated palbociclib, a cyclin-dependent kinase (CDK) 4/6 inhibitor, to an HMCD, MHI-148, and conducted drug activity analysis on primary patient-derived glioblastoma cell lines. In addition to the expected cytostatic activity, our in vitro studies revealed that palbociclib-MHI-148 conjugate resulted in an almost 100-fold increase in cytotoxicity compared to palbociclib alone. This shift of palbociclib from cytostatic to cytotoxic when conjugated to MHI-148 was due to increased DNA damage, as indicated by an increase in γH2AX foci, followed by an increased expression of key extrinsic apoptosis genes, including TP53, TNFR1, TRAIL, FADD and caspase 8. In addition, we observed a time-dependent increase in the cell surface expression of TNFR1, consistent with an observed increase in the secretion TNFα, followed by TNFR1 endocytosis at 48 h. The treatment of patient GBM cells with the palbociclib-MHI-148 conjugate prevented TNFα-induced NFκB translocation, suggesting conjugate-induced TNFR1 signalling favoured the TNFR1-mediated apoptotic response rather than the pro-inflammatory response pathway. Notably, pharmacological inhibition of endocytosis of TNFR1, and siRNA-knockdown of TNFR1 reversed the palbociclib-MHI-148-induced cell death. These results show a novel susceptibility of glioblastoma cells to TNFR1-dependent apoptosis, dependent on inhibition of canonical NFκB signalling using our previously reported palbociclib-HMCD conjugate. Video Abstract

Jansson et al. design a high content screening system to target inflammation in human brain cells of the blood–brain barrier (pericytes and endothelial cells) to identify inflammatory modifiers. They identify cardiac glycosides as powerful regulators of neuroinflammatory pathways in brain barrier tissues such as vasculature, meninges and choroid plexus.

Live attenuated measles virus is one of the most efficient and safest vaccines available, making it an attractive candidate vector for a HIV/AIDS vaccine aimed at eliciting cell-mediated immune responses (CMI). Here we have characterized the potency of CMI responses generated in mice and non-human primates after intramuscular immunisation with a candidate recombinant measles vaccine carrying an HIV-1 insert encoding Clade B Gag, RT and Nef (MV1-F4). Eight Mauritian derived, MHC-typed cynomolgus macaques were immunised with 10(5) TCID(50) of MV1-F4, four of which were boosted 28 days later with the same vaccine. F4 and measles virus (MV)-specific cytokine producing T cell responses were detected in 6 and 7 out of 8 vaccinees, respectively. Vaccinees with either M6 or recombinant MHC haplotypes demonstrated the strongest cytokine responses to F4 peptides. Polyfunctional analysis revealed a pattern of TNFα and IL-2 responses by CD4+ T cells and TNFα and IFNγ responses by CD8+ T cells to F4 peptides. HIV-specific CD4+ and CD8+ T cells expressing cytokines waned in peripheral blood lymphocytes by day 84, but CD8+ T cell responses to F4 peptides could still be detected in lymphoid tissues more than 3 months after vaccination. Anti-F4 and anti-MV antibody responses were detected in 6 and 8 out of 8 vaccinees, respectively. Titres of anti-F4 and MV antibodies were boosted in vaccinees that received a second immunisation. MV1-F4 carrying HIV-1 Clade B inserts induces robust boostable immunity in non-human primates. These results support further exploration of the MV1-F4 vector modality in vaccination strategies that may limit HIV-1 infectivity.

Abstract Organophosphate (OP) toxicants remain an active threat to public health and to warfighters in the military. Current countermeasures require near immediate administration following OP exposure and are reported to have controversial efficacies. Acetylcholinesterase (AChE) fused to the human immunoglobulin 1 (IgG1) Fc domain (AChE‐Fc) is a potential bioscavenger for OP toxicants, but a reproducible AChE‐Fc biomanufacturing strategy remains elusive. This report is the first to establish a comprehensive laboratory‐scale bioprocessing strategy that can reproducibly produce AChE‐Fc and AChE(W86A)‐Fc which is a mutated AChE protein with reduced enzymatic activity. Characterization studies revealed that AChE‐Fc and AChE(W86A)‐Fc are N‐glycosylated dimeric fusion glycoproteins but only AChE‐Fc had the capability to bind to paraoxon (a model OP). This AChE‐Fc fusion glycoprotein bioprocessing strategy can be leveraged during industrial biomanufacturing development, while the research‐grade AChE‐Fc proteins can be used to determine the potential clinical relevance of the countermeasure against OP toxicants.

Objectives The aim of this systematic overview of reviews was to synthesise available evidence on inequalities in infectious disease based on three dimensions of inequalities; inclusion health groups, protected characteristics and socioeconomic inequalities.Methods We searched MEDLINE, Embase, Web of Science and OpenGrey databases in November 2021. We included reviews published from the year 2000 which examined inequalities in the incidence, prevalence or consequences of infectious diseases based on the dimensions of interest. Our search focused on tuberculosis, HIV, sexually transmitted infections, hepatitis C, vaccination and antimicrobial resistance. However, we also included eligible reviews of any other infectious diseases. We appraised the quality of reviews using the Assessment of Multiple Systematic Reviews V.2 (AMSTAR2) checklist. We conducted a narrative data synthesis.Results We included 108 reviews in our synthesis covering all the dimensions of inequalities for most of the infectious disease topics of interest, however the quality and volume of review evidence and consistency of their findings varied. The existing literature reviews provide strong evidence that people in inclusion health groups and lower socioeconomic status are consistently at higher risk of infectious diseases, antimicrobial resistance and incomplete/delayed vaccination. In the protected characteristics dimension, ethnicity, and sexual orientation are important factors contributing to inequalities across the various infectious disease topics included in this overview of reviews.Conclusion We identified many reviews that provide evidence of various types of health inequalities in different infectious diseases, vaccination, and antimicrobial resistance. We also highlight areas where reviews may be lacking. The commonalities in the associations and their directions suggest it might be worth targeting interventions for some high risk-groups that may have benefits across multiple infectious disease outcomes rather than operating purely in infectious disease siloes.

Background: Social prescribing encourages health-care and other professionals to refer patients to a link worker, who will develop a personalised plan to improve the patient’s health and well-being. We explore the feasibility of evaluating the service. Objective: The objective was to answer the following research questions. (1) What are the most important evaluation questions that an impact study could investigate? (2) What data are already available at a local or national level and what else would be needed? (3) Are there sites delivering at a large enough scale and in a position to take part in an impact study? (4) How could the known challenges to evaluation (e.g. information governance and identifying a control group) be addressed? Data sources: Data sources included MEDLINE ALL (via Ovid), searched from inception to 14 February 2019, and the first 100 hits of a Google (Google Inc., Mountain View, CA, USA) search. Review methods: Rapid systematic review – electronic searches up to February 2019. Studies included any study design or outcomes. Screening was conducted by one reviewer; eligibility assessment and data extraction were undertaken by two reviewers. Data were synthesised narratively. Qualitative interviews – data from 25 participants in different regions of England were analysed using a pragmatic framework approach across 12 areas including prior data collection, delivery sites, scale and processes of current service delivery, and known challenges to evaluation. Views of key stakeholders (i.e. patients and academics) were captured. Results: Rapid systematic review – 27 out of 124 studies were included. We identified outcomes and highlighted research challenges. Important evaluation questions included identification of the most appropriate (1) outcomes and (2) methods for dealing with heterogeneity. Qualitative interviews – social prescribing programmes are holistic in nature, covering domains such as social isolation and finance. Service provision is heterogeneous. The follow-on services that patients access are often underfunded or short term. Available data – there was significant heterogeneity in data availability, format and follow-up. Data were collected using a range of tools in ad hoc databases across sites. Non-attendance data were frequently not captured. Service users are more deprived and vulnerable than the overall practice population. Feasibility and potential limitations of an evaluation – current data collection is limited in determining the effectiveness of the link worker social prescribing model; therefore, uniform data collection across sites is needed. Standardised outcomes and process measures are required. Cost–utility analysis could provide comparative values for assessment alongside other NHS interventions. Limitations: This was a rapid systematic review that did not include a systematic quality assessment of studies. COVID-19 had an impact on the shape of the service. We were not able to examine the potential causal mechanisms in any detail. Conclusions: We describe possible future research approaches to determine effectiveness and cost-effectiveness evaluations; all are limited in their application. (1) Evaluation using currently available, routinely collected health-care, costing and outcomes data. (2) Evaluative mixed-methods research to capture the complexity of social prescribing through understanding heterogeneous service delivery across comparative settings. Cost-effectiveness evaluation using routinely available costing and outcomes data to supplement qualitative data. (3) Interventional evaluative research, such as a cluster randomised controlled trial focused on the link worker model. Cost-effectiveness data collected as part of the trial. Future work: Mature data are currently not available. There needs to be an agreement across schemes on the key outcomes that need to be measured, harmonisation of data collection, and follow-up referrals (how and when). Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in full in Health and Social Care Delivery Research; Vol. 10, No. 29. See the NIHR Journals Library website for further project information.

With few exceptions, the field of Machine Learning (ML) research has largely ignored the browser as a computational engine. Beyond an educational resource for ML, the browser has vast potential to not only improve the state-of-the-art in ML research, but also, inexpensively and on a massive scale, to bring sophisticated ML learning and prediction to the public at large. This paper introduces MLitB, a prototype ML framework written entirely in Javascript, capable of performing large-scale distributed computing with heterogeneous classes of devices. The development of MLitB has been driven by several underlying objectives whose aim is to make ML learning and usage ubiquitous (by using ubiquitous compute devices), cheap and effortlessly distributed, and collaborative. This is achieved by allowing every internet capable device to run training algorithms and predictive models with no software installation and by saving models in universally readable formats. Our prototype library is capable of training deep neural networks with synchronized, distributed stochastic gradient descent. MLitB offers several important opportunities for novel ML research, including: development of distributed learning algorithms, advancement of web GPU algorithms, novel field and mobile applications, privacy preserving computing, and green grid-computing. MLitB is available as open source software.