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How does our body detect and destroy foreign invaders? Why does the body attack itself in diseases such as diabetes? And what is cancer immunotherapy?
In vivo labelling resolves distinct temporal, spatial, and functional properties of tumour macrophages, and identifies subset-specific effects of PD-L1 blockade.
Tumour-associated macrophages (TAMs) are a universal feature of cancers but variably influence outcome and treatment responses. Here, we used a photoconvertible mouse to distinguish newly entering, monocyte-derived (md)TAMs that were enriched at the tumour core, from resident-like (r)TAMs that localised with fibroblasts at the tumour-normal interface. The mdTAM pool was highly dynamic and continually replenished by circulating monocytes. Upon tumour entry, these monocytes differentiated down two divergent fate trajectories distinguished by the expression of MHC class II. MHC-II+ mdTAMs were functionally distinct from MHC-II- mdTAMs, demonstrating increased capacity for endocytosis and FcγR-mediated phagocytosis, as well as pro-inflammatory cytokine production. Both mdTAM subsets showed reduced expression of inflammatory transcripts and increased expression of PD-L1 with increasing tumour dwell-time. Treatment with anti-PD-L1 skewed mdTAM differentiation towards the MHC-II+ fate and attenuated the anti-inflammatory effects of the tumour environment. Anti-PD-L1 enhanced mdTAM-CD4+ T-cell interactions, establishing an IFNγ-CXCL9/10-dependent positive feedback loop. Altogether, these data resolve distinct temporal, spatial and functional properties of TAMs, and provide evidence of subset-specific effects of PD-L1 blockade.
The TyphiNET data visualisation dashboard: unlocking Salmonella Typhi genomics data to support public health
Abstract Background Salmonella enterica subspecies enterica serovar Typhi (abbreviated as ‘Typhi’) is the bacterial agent of typhoid fever. Effective antimicrobial therapy reduces complications and mortality; however, antimicrobial resistance (AMR) is a major problem in many endemic countries. Prevention through vaccination is possible through recently-licensed typhoid conjugate vaccines (TCVs). National immunisation programs are currently being considered or deployed in several countries where AMR prevalence is known to be high, and the Gavi vaccine alliance has provided financial support for their introduction. Pathogen whole genome sequence data are a rich source of information on Typhi variants (genotypes or lineages), AMR prevalence, and mechanisms. However, this information is currently not readily accessible to non-genomics experts, including those driving vaccine implementation or empirical therapy guidance. Results We developed TyphiNET (https://www.typhi.net), an interactive online dashboard for exploring Typhi genotype and AMR distributions derived from publicly available pathogen genome sequences. TyphiNET allows users to explore country-level summaries such as the frequency of pathogen lineages, temporal trends in resistance to clinically relevant antimicrobials, and the specific variants and mechanisms underlying emergent AMR trends. User-driven plots and session reports can be downloaded for ease of sharing. Importantly, TyphiNET is populated by high-quality genome data curated by the Global Typhoid Pathogen Genomics Consortium, analysed using the Pathogenwatch platform, and identified as coming from non-targeted sampling frames that are suitable for estimating AMR prevalence amongst Typhi infections (no personal data is included in the platform). As of February 2024, data from a total of n = 11,836 genomes from 101 countries are available in TyphiNET. We outline case studies illustrating how the dashboard can be used to explore these data and gain insights of relevance to both researchers and public health policy-makers. Conclusions The TyphiNET dashboard provides an interactive platform for accessing genome-derived data on pathogen variant frequencies to inform typhoid control and intervention strategies. The platform is extensible in terms of both data and features, and provides a model for making complex bacterial genome-derived data accessible to a wide audience.
Unveiling sub-populations in critical care settings: a real-world data approach in COVID-19.
BackgroundDisease presentation and progression can vary greatly in heterogeneous diseases, such as COVID-19, with variability in patient outcomes, even within the hospital setting. This variability underscores the need for tailored treatment approaches based on distinct clinical subgroups.ObjectivesThis study aimed to identify COVID-19 patient subgroups with unique clinical characteristics using real-world data (RWD) from electronic health records (EHRs) to inform individualized treatment plans.Materials and methodsA Factor Analysis of Mixed Data (FAMD)-based agglomerative hierarchical clustering approach was employed to analyze the real-world data, enabling the identification of distinct patient subgroups. Statistical tests evaluated cluster differences, and machine learning models classified the identified subgroups.ResultsThree clusters of COVID-19 in patients with unique clinical characteristics were identified. The analysis revealed significant differences in hospital stay durations and survival rates among the clusters, with more severe clinical features correlating with worse prognoses and machine learning classifiers achieving high accuracy in subgroup identification.ConclusionBy leveraging RWD and advanced clustering techniques, the study provides insights into the heterogeneity of COVID-19 presentations. The findings support the development of classification models that can inform more individualized and effective treatment plans, improving patient outcomes in the future.
Simplifying medicine dosing for children by harmonising weight bands across therapeutic areas.
Generally, dose recommendations for children are expressed as fixed dosing increments related to bodyweight, known as weight bands. The weight bands recommended in WHO treatment guidelines vary between diseases, leading to complexity and potential dosing errors when treating children for multiple diseases simultaneously. The introduction of a harmonised weight banding approach for orally administered drugs across disease areas could streamline dosing for young children, but implementing such an approach would require changes in current dosing recommendations. In this Health Policy, we describe the process we conducted to: identify therapeutic areas for harmonisation of weight bands; propose a harmonised weight-banding system to align with current use of weight bands in antibiotic guidance; and simulate the expected effect of dose adjustments due to weight-band harmonisation. Each step of this process, along with the effect and feasibility of weight-band harmonisation was discussed with clinical, policy, and pharmacology experts convened by WHO, representing four therapeutic areas: tuberculosis, HIV, malaria, and hepatitis C. Dosing according to harmonised weight bands across the targeted therapeutic areas was found to be feasible and should be considered for implementation by WHO disease programmes through their appropriate normative processes.
Iron deficiency causes aspartate-sensitive dysfunction in CD8+ T cells.
Iron is an irreplaceable co-factor for metabolism. Iron deficiency affects >1 billion people and decreased iron availability impairs immunity. Nevertheless, how iron deprivation impacts immune cell function remains poorly characterised. We interrogate how physiologically low iron availability affects CD8+ T cell metabolism and function, using multi-omic and metabolic labelling approaches. Iron limitation does not substantially alter initial post-activation increases in cell size and CD25 upregulation. However, low iron profoundly stalls proliferation (without influencing cell viability), alters histone methylation status, gene expression, and disrupts mitochondrial membrane potential. Glucose and glutamine metabolism in the TCA cycle is limited and partially reverses to a reductive trajectory. Previous studies identified mitochondria-derived aspartate as crucial for proliferation of transformed cells. Despite aberrant TCA cycling, aspartate is increased in stalled iron deficient CD8+ T cells but is not utilised for nucleotide synthesis, likely due to trapping within depolarised mitochondria. Exogenous aspartate markedly rescues expansion and some functions of severely iron-deficient CD8+ T cells. Overall, iron scarcity creates a mitochondrial-located metabolic bottleneck, which is bypassed by supplying inhibited biochemical processes with aspartate. These findings reveal molecular consequences of iron deficiency for CD8+ T cell function, providing mechanistic insight into the basis for immune impairment during iron deficiency.
A roadmap of priority evidence gaps for the co-implementation of malaria vaccines and perennial malaria chemoprevention
Progress in malaria control will rely on deployment and effective targeting of combinations of interventions, including malaria vaccines and perennial malaria chemoprevention (PMC). Several countries with PMC programmes have introduced malaria vaccination into their essential programmes on immunizations, but empirical evidence on the impact of combining these two interventions and how best to co-implement them are lacking. At the American Society of Tropical Medicine and Hygiene 2023 annual meeting, a stakeholder meeting was convened to identify key policy, operational and research gaps for co-implementation of malaria vaccines and PMC. Participants from 11 endemic countries, including representatives from national malaria and immunization programmes, the World Health Organization, researchers, implementing organizations and funders attended. Identified evidence gaps were prioritized to select urgent issues to inform co-implementation. The output of these activities is a strategic roadmap of priority malaria vaccine and PMC co-implementation evidence gaps, and solutions to address them. The roadmap was presented to stakeholders for feedback at the 2024 Multilateral Initiative on Malaria meeting and revised accordingly. The roadmap outlines four key areas of work to address urgent evidence gaps for co-implementation: (1) support to the global and national policy process, (2) implementation support and research, (3) clinical studies, and (4) modelling. Together, these areas will provide practical guidance on the co-implementation of the interventions, and robust evidence to inform decision-making on how best to design, optimize and scale-up co-implementation in different contexts, including if and in what contexts the co-implementation is cost-effective, and the optimal schedule for co-implementation. This will work towards supporting the policy process on co-implementation of malaria vaccines and PMC, and achieving the most impactful use of available resources for the prevention of malaria in children.
Handheld Spatially Offset Raman Spectroscopy for rapid non-invasive detection of ethylene glycol and diethylene glycol in medicinal syrups.
We investigate the potential of Spatially Offset Raman Spectroscopy (SORS) as a rapid, non-invasive screening tool deployable in the field to detect diethylene glycol (DEG) and ethylene glycol (EG) in medicinal syrups within closed containers. Measurements were performed on neat propylene glycol (PG) and glycerol, key components of many medicinal syrups, as well as marketed medicinal syrup formulations spiked with DEG and EG at various concentration levels to assess the technique's limit of detection in real-life samples. SORS was able to detect these down to ∼0.5 % concentration level in neat PG for both DEG and EG compounds and ∼1 % concentration level for DEG and EG in neat glycerol. The DEG and EG detection thresholds for the marketed formulations measured through original bottles was ∼1 %, for Benylin (active ingredient: Glycerol) and Piriteze (active ingredient: Cetirizine Hydrochloride). For Calpol (active ingredient: Paracetamol) the detection limit was higher, ∼2 % for EG and ∼5 % for DEG. Although not reaching the International Pharmacopeial 0.1 % detection threshold currently required for purity checks for human consumption, the method can still be used to detect products where DEG or EG has been wrongly used instead of PG or glycerol or if present in large quantities. The technique could also be used for raw material identification testing to ensure no mislabelling has occurred in pre-production stages and as a screening device in distribution chains to detect major deviations from permitted content in non-diffusely scattering, clear formulations, to help prevent serious adverse outcomes, such as acute renal failure and deaths.
Virion Structure
Picornaviruses were the first animal viruses whose structure was determined in atomic detail and, as of October 2009, the Protein Data Bank (PDB) registered 53 structure depositions for picornaviruses. These data have contributed significantly to the understanding of picornavirus evolution, assembly, host-cell interaction, host adaptation, and antigenic variation and are providing the basis for novel therapeutic strategies. Subsequently classified as a picornavirus, the general morphology of FMDV could not be visualized until the advent of the electron microscope, when negative-stained images to a resolution of 4 to 5 nm revealed rather smooth round particles of ˜30 nm diameter. The current classification of picornaviruses is based on genome and protein sequence properties which are derived from the interplay of the error-prone replication mechanism of the virus with the process of natural selection. Differences in physical properties, such as buoyant density in cesium chloride and pH stability, underpinned the early classification of picornaviruses. Virus capsids recognize susceptible cells by attachment to specific receptors on the host cell membrane, thereby determining the host range and tropism of infection. The majority of antibodies are weak neutralizers that appear to operate by using the two arms of the antibody to cross-link different virus particles, causing aggregation.
Research Electronic Data Capture (REDCap) for Population-Based Data Collection in Low- and Middle-Income Countries: Opportunities, Challenges, and Solutions.
Health research requires high-quality data, and population-based health research comes with specific opportunities and challenges for data collection. Electronic data capture can mitigate some of the challenges of working with large populations in multiple, sometimes difficult-to-reach, locations. This viewpoint paper aims to describe experiences during the implementation of two mixed methods studies in Vietnam, Nepal, and Indonesia, focusing on understanding lived experiences of the COVID-19 pandemic across 3 countries and understanding knowledge and behaviors related to antibiotic use in Vietnam. We present the opportunities, challenges, and solutions arising through using Research Electronic Data Capture (REDCap) for designing, collecting, and managing data. Electronic data capture using REDCap made it possible to collect data from large populations in different settings. Challenges related to working in multiple languages, unstable internet connections, and complex questionnaires with nested forms. Some data collectors lacked the digital skills to comfortably use REDCap. To overcome these challenges, we included regular team meetings, training, supervision, and automated error-checking procedures. The main types of errors that remained were incomplete and duplicate records due to disruption during data collection. However, with immediate access to data, we were able to identify and troubleshoot these problems quickly, while data collection was still in progress. By detailing our lessons learned-such as the importance of iterative testing, regular intersite meetings, and customized modifications-we provide a roadmap for future projects to boost productivity, enhance data quality, and effectively conduct large-scale population-based research. Our suggestions will be beneficial for research teams working with electronic data capture for population-based data.
Crystallographic fragment screening reveals ligand hotspots in TRIM21 PRY-SPRY domain.
Tripartite motif-containing protein 21 (TRIM21), and particularly its PRY-SPRY protein interaction domain, plays a critical role in the immune response by recognizing intracellular antibodies targeting them for degradation. In this study, we performed a crystallographic fragment screening (CFS) campaign to identify potential small molecule binders targeting the PRY-SPRY domain of TRIM21. Our screen identified a total of 109 fragments binding to TRIM21 that were distributed across five distinct binding sites. These fragments have been designed to facilitate straightforward follow-up chemistry, making them ideal starting points for further chemical optimization. A subsequent fragment merging approach demonstrated improved activity. To enable functional validation of compounds with full length human TRIM21, we established a NanoBRET assay suitable for measuring target engagement to the main Fc binding site in life cells. The high-resolution structural data and observed binding modes across the different sites highlight the versatility of the PRY-SPRY domain as a target for small-molecule intervention. The presented data provide a solid foundation for structure-guided ligand design, enabling the rational design of more potent and selective compounds, with the goal to develop bivalent molecules such as Proteolysis Targeting Chimeras (PROTACs).
Characterising the Behaviour of a Structured PDE Model of the Cell Cycle in Contrast to a Corresponding ODE System.
Experimental results have shown that anti-cancer therapies, such as radiotherapy and chemotherapy, can modulate the cell cycle and generate cell cycle phase-dependent responses. As a result, obtaining a detailed understanding of the cell cycle is one possible path towards improving the efficacy of many of these therapies. Here, we consider a basic structured partial differential equation (PDE) model for cell progression through the cell cycle, and derive expressions for key quantities, such as the population growth rate and cell phase proportions. These quantities are shown to be periodic and, as such, we compare the PDE model to a corresponding ordinary differential equation (ODE) model in which the parameters are linked by ensuring that the long-term ODE behaviour agrees with the average PDE behaviour. By design, we find that the ODE model does an excellent job of representing the mean dynamics of the PDE model within just a few cell cycles. However, by probing the parameter space we find cases in which this mean behaviour is not a good measure of the PDE population growth. Our analytical comparison of two caricature models (one PDE and one ODE system) provides insight into cases in which the simple ODE model is an appropriate approximation to the PDE model.
Activity-Based Protein Profiling (ABPP) of Cellular DeISGylating Enzymes and Inhibitor Screening.
A detailed methodology platform is described for activity-based protein profiling (ABPP) of cellular deISGylating enzymes using a specific activity-based interferon-stimulated gene 15 (ISG15) probe. Manual and semi-automated workflows for medium- to high-throughput applications are outlined in this chapter, with western blotting and proteomics-based techniques as the main readouts. This methodology informs us of endogenous deISGylating enzyme expression and activity in a cellular context, including USP18, the type I interferon (IFN-I)-inducible deISGylase, and several constitutively expressed deubiquitinases (DUBs), such as USP5, USP14, USP16, and USP36, that exert cross-reactivity to ISG15. ISG15-ABPP also enables the identification and characterization of potent and selective deISGylating enzyme modulators.