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Eight Oxford scientists are amongst 50 of the UK's world-leading researchers elected to join the prestigious Fellowship of the Academy of Medical Sciences this year including from NDM: Professors Philip Bejon, Helen McShane, Richard Price, Alison Simmons and Sarah Walker.
Image-based consensus molecular subtyping in rectal cancer biopsies and response to neoadjuvant chemoradiotherapy.
The development of deep learning (DL) models to predict the consensus molecular subtypes (CMS) from histopathology images (imCMS) is a promising and cost-effective strategy to support patient stratification. Here, we investigate whether imCMS calls generated from whole slide histopathology images (WSIs) of rectal cancer (RC) pre-treatment biopsies are associated with pathological complete response (pCR) to neoadjuvant long course chemoradiotherapy (LCRT) with single agent fluoropyrimidine. DL models were trained to classify WSIs of colorectal cancers stained with hematoxylin and eosin into one of the four CMS classes using a multi-centric dataset of resection and biopsy specimens (n = 1057 WSIs) with paired transcriptional data. Classifiers were tested on a held out RC biopsy cohort (ARISTOTLE) and correlated with pCR to LCRT in an independent dataset merging two RC cohorts (ARISTOTLE, n = 114 and SALZBURG, n = 55 patients). DL models predicted CMS with high classification performance in multiple comparative analyses. In the independent cohorts (ARISTOTLE, SALZBURG), cases with WSIs classified as imCMS1 had a significantly higher likelihood of achieving pCR (OR = 2.69, 95% CI 1.01-7.17, p = 0.048). Conversely, imCMS4 was associated with lack of pCR (OR = 0.25, 95% CI 0.07-0.88, p = 0.031). Classification maps demonstrated pathologist-interpretable associations with high stromal content in imCMS4 cases, associated with poor outcome. No significant association was found in imCMS2 or imCMS3. imCMS classification of pre-treatment biopsies is a fast and inexpensive solution to identify patient groups that could benefit from neoadjuvant LCRT. The significant associations between imCMS1/imCMS4 with pCR suggest the existence of predictive morphological features that could enhance standard pathological assessment.
Spatio-temporal spread of artemisinin resistance in Southeast Asia
Current malaria elimination targets must withstand a colossal challenge–resistance to the current gold standard antimalarial drug, namely artemisinin derivatives. If artemisinin resistance significantly expands to Africa or India, cases and malaria-related deaths are set to increase substantially. Spatial information on the changing levels of artemisinin resistance in Southeast Asia is therefore critical for health organisations to prioritise malaria control measures, but available data on artemisinin resistance are sparse. We use a comprehensive database from the WorldWide Antimalarial Resistance Network on the prevalence of non-synonymous mutations in the Kelch 13 (K13) gene, which are known to be associated with artemisinin resistance, and a Bayesian geostatistical model to produce spatio-temporal predictions of artemisinin resistance. Our maps of estimated prevalence show an expansion of the K13 mutation across the Greater Mekong Subregion from 2000 to 2022. Moreover, the period between 2010 and 2015 demonstrated the most spatial change across the region. Our model and maps provide important insights into the spatial and temporal trends of artemisinin resistance in a way that is not possible using data alone, thereby enabling improved spatial decision support systems on an unprecedented fine-scale spatial resolution. By predicting for the first time spatio-temporal patterns and extents of artemisinin resistance at the subcontinent level, this study provides critical information for supporting malaria elimination goals in Southeast Asia.
Specific plasma microRNAs are associated with CD4+ T-cell recovery during suppressive antiretroviral therapy for HIV-1.
ObjectiveThis study investigated the association of plasma microRNAs before and during antiretroviral therapy (ART) with poor CD4+ T-cell recovery during the first year of ART.DesignMicroRNAs were retrospectively measured in stored plasma samples from people with HIV (PWH) in sub-Saharan Africa who were enrolled in a longitudinal multicountry cohort and who had plasma viral-load less than 50 copies/ml after 12 months of ART.MethodsFirst, the levels of 179 microRNAs were screened in a subset of participants from the lowest and highest tertiles of CD4+ T-cell recovery (ΔCD4) (N = 12 each). Next, 11 discordant microRNAs, were validated in 113 participants (lowest tertile ΔCD4: n = 61, highest tertile ΔCD4: n = 52). For discordant microRNAs in the validation, a pathway analysis was conducted. Lastly, we compared microRNA levels of PWH to HIV-negative controls.ResultsPoor CD4+ T-cell recovery was associated with higher levels of hsa-miR-199a-3p and hsa-miR-200c-3p before ART, and of hsa-miR-17-5p and hsa-miR-501-3p during ART. Signaling by VEGF and MET, and RNA polymerase II transcription pathways were identified as possible targets of hsa-miR-199a-3p, hsa-200c-3p, and hsa-miR-17-5p. Compared with HIV-negative controls, we observed lower hsa-miR-326, hsa-miR-497-5p, and hsa-miR-501-3p levels before and during ART in all PWH, and higher hsa-miR-199a-3p and hsa-miR-200c-3p levels before ART in all PWH, and during ART in PWH with poor CD4+ T-cell recovery only.ConclusionThese findings add to the understanding of pathways involved in persistent HIV-induced immune dysregulation during suppressive ART.
Interpretations of Studies on SARS-CoV-2 Vaccination and Post-acute COVID-19 Sequelae.
This article discusses causal interpretations of epidemiologic studies of the effects of vaccination on sequelae after acute severe acute respiratory syndrome coronavirus 2 infection. To date, researchers have tried to answer several different research questions on this topic. While some studies assessed the impact of postinfection vaccination on the presence of or recovery from post-acute coronavirus disease 2019 syndrome, others quantified the association between preinfection vaccination and postacute sequelae conditional on becoming infected. However, the latter analysis does not have a causal interpretation, except under the principal stratification framework-that is, this comparison can only be interpreted as causal for a nondiscernible stratum of the population. As the epidemiology of coronavirus disease 2019 is now nearly entirely dominated by reinfections, including in vaccinated individuals, and possibly caused by different Omicron subvariants, it has become even more important to design studies on the effects of vaccination on postacute sequelae that address precise causal questions and quantify effects corresponding to implementable interventions.
Exploring the pediatric nasopharyngeal bacterial microbiota with culture-based MALDI-TOF mass spectrometry and targeted metagenomic sequencing.
UNLABELLED: The nasopharynx is an important reservoir of disease-associated and antimicrobial-resistant bacterial species. This proof-of-concept study assessed the utility of a combined culture, matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), and targeted metagenomic sequencing workflow for the study of the pediatric nasopharyngeal bacterial microbiota. Nasopharyngeal swabs and clinical metadata were collected from Cambodian children during a hospital outpatient visit and then biweekly for 12 weeks. Swabs were cultured on chocolate and blood-gentamicin agar, and all colony morphotypes were identified by MALDI-TOF MS. Metagenomic sequencing was done on a scrape of all colonies from a chocolate agar culture and processed using the mSWEEP pipeline. One hundred one children were enrolled, yielding 620 swabs. MALDI-TOF MS identified 106 bacterial species/40 genera: 20 species accounted for 88.5% (2,190/2,474) of isolates. Colonization by Moraxella catarrhalis (92.1% of children on ≥1 swab), Haemophilus influenzae (87.1%), and Streptococcus pneumoniae (83.2%) was particularly common. In S. pneumoniae-colonized children, a median of two serotypes [inter-quartile range (IQR) 1-2, range 1-4] was detected. For the 21 bacterial species included in the mSWEEP database and identifiable by MALDI-TOF, detection by culture + MALDI-TOF MS and culture + mSWEEP was highly concordant with a median species-level agreement of 96.9% (IQR 86.8%-98.8%). mSWEEP revealed highly dynamic lineage-level colonization patterns for S. pneumoniae which were quite different to those for S. aureus. A combined culture, MALDI-TOF MS, targeted metagenomic sequencing approach for the exploration of the young child nasopharyngeal microbiome was technically feasible, and each component yielded complementary data. IMPORTANCE: The human upper respiratory tract is an important source of disease-causing and antibiotic-resistant bacteria. However, understanding the interactions and stability of these bacterial populations is technically challenging. We used a combination of approaches to determine colonization patterns over a 3-month period in 101 Cambodian children. The combined approach was feasible to implement, and each component gave complementary data to enable a better understanding of the complex patterns of bacterial colonization.
Heart rate variability as an indicator of autonomic nervous system disturbance in tetanus
AbstractAutonomic nervous system dysfunction (ANSD) is a significant cause of mortality in tetanus. Currently diagnosis relies on non-specific clinical signs. Heart rate variability (HRV) may indicate underlying autonomic nervous system activity and represents a potentially valuable non-invasive tool for ANSD diagnosis in tetanus. HRV was measured from 3 5-minute ECG recordings during a 24-hour period in a cohort patients with severe tetanus, all receiving mechanical ventilation. HRV measurements from all subjects - 5 with ANSD (Ablett Grade 4) and 4 patients without ANSD (Ablett Grade 3) - showed HRV was lower than reported ranges for healthy individuals. Comparing different severities of tetanus, raw data for both time and frequency measurements of HRV were reduced in those with ANSD compared to those without. Differences were statistically significant in all except root mean square standard deviation RMSSD (p=0.07) indicating HRV may be a valuable tool in ANSD diagnosis.
A Unified Framework for U-Net Design and Analysis
U-Nets are a go-to neural architecture across numerous tasks for continuous signals on a square such as images and Partial Differential Equations (PDE), however their design and architecture is understudied. In this paper, we provide a framework for designing and analysing general U-Net architectures. We present theoretical results which characterise the role of the encoder and decoder in a U-Net, their high-resolution scaling limits and their conjugacy to ResNets via preconditioning. We propose Multi-ResNets, U-Nets with a simplified, wavelet-based encoder without learnable parameters. Further, we show how to design novel U-Net architectures which encode function constraints, natural bases, or the geometry of the data. In diffusion models, our framework enables us to identify that high-frequency information is dominated by noise exponentially faster, and show how U-Nets with average pooling exploit this. In our experiments, we demonstrate how Multi-ResNets achieve competitive and often superior performance compared to classical U-Nets in image segmentation, PDE surrogate modelling, and generative modelling with diffusion models. Our U-Net framework paves the way to study the theoretical properties of U-Nets and design natural, scalable neural architectures for a multitude of problems beyond the square.
Multi-omics analysis reveals COVID-19 vaccine induced attenuation of inflammatory responses during breakthrough disease
AbstractThe immune mechanisms mediating COVID-19 vaccine attenuation of COVID-19 remain undescribed. We conducted comprehensive analyses detailing immune responses to SARS-CoV-2 virus in blood post-vaccination with ChAdOx1 nCoV-19 or a placebo. Samples from randomised placebo-controlled trials (NCT04324606 and NCT04400838) were taken at baseline, onset of COVID-19-like symptoms, and 7 days later, confirming COVID-19 using nucleic amplification test (NAAT test) via real-time PCR (RT-PCR). Serum cytokines were measured with multiplexed immunoassays. The transcriptome was analysed with long, short and small RNA sequencing. We found attenuation of RNA inflammatory signatures in ChAdOx1 nCoV-19 compared with placebo vaccinees and reduced levels of serum proteins associated with COVID-19 severity. KREMEN1, a putative alternative SARS-CoV-2 receptor, was downregulated in placebo compared with ChAdOx1 nCoV-19 vaccinees. Vaccination ameliorates reductions in cell counts across leukocyte populations and platelets noted at COVID-19 onset, without inducing potentially deleterious Th2-skewed immune responses. Multi-omics integration links a global reduction in miRNA expression at COVID-19 onset to increased pro-inflammatory responses at the mRNA level. This study reveals insights into the role of COVID-19 vaccines in mitigating disease severity by abrogating pro-inflammatory responses associated with severe COVID-19, affirming vaccine-mediated benefit in breakthrough infection, and highlighting the importance of clinically relevant endpoints in vaccine evaluation.
Turning high-throughput structural biology into predictive inhibitor design.
A common challenge in drug design pertains to finding chemical modifications to a ligand that increases its affinity to the target protein. An underutilized advance is the increase in structural biology throughput, which has progressed from an artisanal endeavor to a monthly throughput of hundreds of different ligands against a protein in modern synchrotrons. However, the missing piece is a framework that turns high-throughput crystallography data into predictive models for ligand design. Here, we designed a simple machine learning approach that predicts protein-ligand affinity from experimental structures of diverse ligands against a single protein paired with biochemical measurements. Our key insight is using physics-based energy descriptors to represent protein-ligand complexes and a learning-to-rank approach that infers the relevant differences between binding modes. We ran a high-throughput crystallography campaign against the SARS-CoV-2 main protease (MPro), obtaining parallel measurements of over 200 protein-ligand complexes and their binding activities. This allows us to design one-step library syntheses which improved the potency of two distinct micromolar hits by over 10-fold, arriving at a noncovalent and nonpeptidomimetic inhibitor with 120 nM antiviral efficacy. Crucially, our approach successfully extends ligands to unexplored regions of the binding pocket, executing large and fruitful moves in chemical space with simple chemistry.
Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors
We report the results of the COVID Moonshot, a fully open-science, crowdsourced, and structure-enabled drug discovery campaign targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease. We discovered a noncovalent, nonpeptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>490 ligand-bound x-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2400 compounds) for this campaign were shared rapidly and openly, creating a rich, open, and intellectual property–free knowledge base for future anticoronavirus drug discovery.
Discovery of PFI-6, a small-molecule chemical probe for the YEATS domain of MLLT1 and MLLT3.
Epigenetic proteins containing YEATS domains (YD) are an emerging target class in drug discovery. Described herein are the discovery and characterization efforts associated with PFI-6, a new chemical probe for the YD of MLLT1 (ENL/YEATS1) and MLLT3 (AF9/YEATS3). For hit identification, fragment-like mimetics of endogenous YD ligands (crotonylated histone-containing proteins), were synthesized via parallel medicinal chemistry (PMC) and screened for MLLT1 binding. Subsequent SAR studies led to iterative MLLT1/3 binding and selectivity improvements, culminating in the discovery of PFI-6. PFI-6 demonstrates good affinity and selectivity for MLLT1/3 vs. other human YD proteins (YEATS2/4) and engages MLLT3 in cells. Small-molecule X-ray co-crystal structures of two molecules, including PFI-6, bound to the YD of MLLT1/3 are also described. PFI-6 may be a useful tool molecule to better understand the biological effects associated with modulation of MLLT1/3.
Unexpected Noncovalent Off-Target Activity of Clinical BTK Inhibitors Leads to Discovery of a Dual NUDT5/14 Antagonist.
Cofactor mimicry represents an attractive strategy for the development of enzyme inhibitors but can lead to off-target effects due to the evolutionary conservation of binding sites across the proteome. Here, we uncover the ADP-ribose (ADPr) hydrolase NUDT5 as an unexpected, noncovalent, off-target of clinical BTK inhibitors. Using a combination of biochemical, biophysical, and intact cell NanoBRET assays as well as X-ray crystallography, we confirm catalytic inhibition and cellular target engagement of NUDT5 and reveal an unusual binding mode that is independent of the reactive acrylamide warhead. Further investigation of the prototypical BTK inhibitor ibrutinib also revealed potent inhibition of the largely unstudied NUDIX hydrolase family member NUDT14. By exploring structure-activity relationships (SARs) around the core scaffold, we identify a potent, noncovalent, and cell-active dual NUDT5/14 inhibitor. Cocrystallization experiments yielded new insights into the NUDT14 hydrolase active site architecture and inhibitor binding, thus providing a basis for future chemical probe design.
Imidazo[1,2-b]pyridazines as inhibitors of DYRK kinases.
Selective inhibitors of DYRK1A are of interest for the treatment of cancer, Type 2 diabetes and neurological disorders. Optimization of imidazo [1,2-b]pyridazine fragment 1 through structure-activity relationship exploration and in silico drug design efforts led to the discovery of compound 17 as a potent cellular inhibitor of DYRK1A with selectivity over much of the kinome. The binding mode of compound 17 was elucidated with X-ray crystallography, facilitating the rational design of compound 29, an imidazo [1,2-b]pyridazine with improved kinase selectivity with respect to closely related CLK kinases.
Discovery of a Potent, Selective, and Cell-Active SPIN1 Inhibitor.
The methyl-lysine reader protein SPIN1 plays important roles in various human diseases. However, targeting methyl-lysine reader proteins has been challenging. Very few cellularly active SPIN1 inhibitors have been developed. We previously reported that our G9a/GLP inhibitor UNC0638 weakly inhibited SPIN1. Here, we present our comprehensive structure-activity relationship study that led to the discovery of compound 11, a dual SPIN1 and G9a/GLP inhibitor, and compound 18 (MS8535), a SPIN1 selective inhibitor. We solved the cocrystal structure of SPIN1 in complex with 11, confirming that 11 occupied one of the three Tudor domains. Importantly, 18 displayed high selectivity for SPIN1 over 38 epigenetic targets, including G9a/GLP, and concentration dependently disrupted the interactions of SPIN1 and H3 in cells. Furthermore, 18 was bioavailable in mice. We also developed 19 (MS8535N), which was inactive against SPIN1, as a negative control of 18. Collectively, these compounds are useful chemical tools to study biological functions of SPIN1.
A Chemical Probe For Tudor Domain Protein Spindlin1 to Investigate Chromatin Functions
Modifications of histone tails, including lysine/arginine methylation, provide the basis of a 'chromatin or histone code'. Proteins that contain 'reader' domains can bind to these modifications and form specific effector complexes, which ultimately mediate chromatin function. The spindlin1 (SPIN1) protein contains three Tudor methyllysine/arginine reader domains and was identified as a putative oncogene and transcriptional co-activator. Here we report a SPIN1 chemical probe inhibitor with low nanomolar in vitro activity, exquisite selectivity on a panel of methyl reader and writer proteins, and with submicromolar cellular activity. X-ray crystallography showed that this Tudor domain chemical probe simultaneously engages Tudor domains 1 and 2 via a bidentate binding mode. Small molecule inhibition and siRNA knockdown of SPIN1, as well as chemoproteomic studies, identified genes which are transcriptionally regulated by SPIN1 in squamous cell carcinoma and suggest that SPIN1 may have a roll in cancer related inflammation and/or cancer metastasis.<br>
Temporal changes in SARS-CoV-2 clearance kinetics and the optimal design of antiviral pharmacodynamic studies: an individual patient data meta-analysis of a randomised, controlled, adaptive platform study (PLATCOV).
BackgroundEffective antiviral drugs prevent hospitalisation and death from COVID-19. Antiviral efficacy can be efficiently assessed in vivo by measuring rates of SARS-CoV-2 clearance estimated from serial viral genome densities quantitated in nasopharyngeal or oropharyngeal swab eluates. We conducted an individual patient data meta-analysis of unblinded arms in the PLATCOV platform trial to characterise changes in viral clearance kinetics and infer optimal design and interpretation of antiviral pharmacometric evaluations.MethodsSerial viral density data were analysed from symptomatic, previously healthy, adult patients (within 4 days of symptom onset) enrolled in a large multicentre, randomised, adaptive, pharmacodynamic, platform trial (PLATCOV) comparing antiviral interventions for SARS-CoV-2. Viral clearance rates over 1 week were estimated under a hierarchical Bayesian linear model with B-splines used to characterise temporal changes in enrolment viral densities and clearance rates. Bootstrap re-sampling was used to assess the optimal duration of follow-up for pharmacometric assessment, where optimal was defined as maximising the expected Z score when comparing effective antivirals with no treatment. PLATCOV is registered at ClinicalTrials.gov, NCT05041907.FindingsBetween Sept 29, 2021, and Oct 20, 2023, 1262 patients were randomly assigned in the PLATCOV trial. Unblinded data were available from 800 patients (who provided 16 818 oropharyngeal viral quantitative PCR [qPCR] measurements), of whom 504 (63%) were female. 783 (98%) patients had received at least one vaccine dose and 703 (88%) were fully vaccinated. SARS-CoV-2 viral clearance was biphasic (bi-exponential). The first phase (α) was accelerated by effective interventions. For all the effective interventions studied, maximum discriminative power (maximum expected Z score) was obtained when evaluating serial data from the first 5 days after enrolment. Over the 2-year period studied, median viral clearance half-lives estimated over 7 days shortened from 16·6 h (IQR 15·3 to 18·2) in September, 2021, to 9·2 h (8·0 to 10·6) in October, 2023, in patients receiving no antiviral drugs, equivalent to a relative reduction of 44% (95% credible interval [CrI] 19 to 64). A parallel reduction in viral clearance half-lives over time was observed in patients receiving antiviral drugs. For example, in the 158 patients assigned to ritonavir-boosted nirmatrelvir (3380 qPCR measurements), the median viral clearance half-life reduced from 6·4 h (IQR 5·7 to 7·3) in June, 2022, to 4·8 h (4·2 to 5·5) in October, 2023, a relative reduction of 26% (95% CrI -4 to 42).InterpretationSARS-CoV-2 viral clearance kinetics in symptomatic, vaccinated individuals accelerated substantially over 2 years of the pandemic, necessitating a change to how new SARS-CoV-2 antivirals are compared (ie, shortening the period of pharmacodynamic assessment). As of writing (October, 2023), antiviral efficacy in COVID-19 can be efficiently assessed in vivo using serial qPCRs from duplicate oropharyngeal swab eluates taken daily for 5 days after drug administration.FundingWellcome Trust.