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Software to create figures for publication. 2 files are used to create budget: I139cells and Weddell_carbon_budget_I139. These have dependencies in the B-SOSE Iteration 139 output, available online at http://sose.ucsd.edu/SO6/ITER139/. Please contact me or Matt Mazloff for details. FDE code uses the output of Weddell_carbon_budget to plot components of Figure 3 as well as Figure S2. Weddell analysis code has many dependencies (from B-SOSE and CCHDO hydrography), but shows how components of Figure 1 and S1 were plotted. Code for circumpolar analysis requires means of various B-SOSE (Iteration 122 and 139) terms output to be calculated. Please contact me with any questions.

BackgroundKlebsiella pneumoniae is a critically important pathogen in the Philippines. Isolates are commonly resistant to at least two classes of antibiotics, yet mechanisms and spread of its resistance are not well studied.MethodsA retrospective sequencing survey was performed on carbapenem-, extended spectrum beta-lactam- and cephalosporin-resistant Klebsiella pneumoniae isolated at 20 antimicrobial resistance (AMR) surveillance sentinel sites from 2015-2017. We characterized 259 isolates using biochemical methods, antimicrobial susceptibility testing, and whole genome sequencing (WGS). Known AMR mechanisms were identified. Potential outbreaks were investigated by detecting clusters from epidemiologic, phenotypic and genome-derived data.ResultsPrevalent AMR mechanisms detected include blaCTX-M-15 (76.8%) and blaNDM-1 (37.5%). An epidemic IncFII(Yp) plasmid carrying blaNDM-1 was also detected in 46 isolates from 6 sentinel sites and 14 different sequence types (ST). This plasmid was also identified as the main vehicle of carbapenem resistance in 2 previously unrecognized local outbreaks of ST348 and ST283 at 2 different sentinel sites. A third local outbreak of ST397 was also identified but without the IncFII(Yp) plasmid. Isolates in each outbreak site showed identical STs, K- and O-loci, and similar resistance profiles and AMR genes. All outbreak isolates were collected from blood of children aged ConclusionWGS provided an in-depth understanding of the epidemiology of AMR in the Philippines, which was not possible with only phenotypic and epidemiologic data. The identification of three previously unrecognized Klebsiella outbreaks highlights the utility of WGS in outbreak detection, as well as its importance in public health and in implementing infection control programs.summaryWhole genome sequencing identified three distinct previously unrecognized local outbreaks in a retrospective study in the Philippines, along with an epidemic plasmid carrying antimicrobial resistance genes, highlighting its importance in antimicrobial resistance surveillance, outbreak detection and infection control.

Performing whole genome sequencing (WGS) for the surveillance of antimicrobial resistance offers the ability to determine not only the antimicrobials to which rates of resistance are increasing, but also the evolutionary mechanisms and transmission routes responsible for the increase at local, national, and global scales. To derive WGS-based outputs, a series of processes are required, beginning with sample and metadata collection, followed by nucleic acid extraction, library preparation, sequencing, and analysis. Throughout this pathway there are many data-related operations required (informatics) combined with more biologically focused procedures (bioinformatics). For a laboratory aiming to implement pathogen genomics, the informatics and bioinformatics activities can be a barrier to starting on the journey; for a laboratory that has already started, these activities may become overwhelming. Here we describe these data bottlenecks and how they have been addressed in laboratories in India, Colombia, Nigeria, and the Philippines, as part of the National Institute for Health Research Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance. The approaches taken include the use of reproducible data parsing pipelines and genome sequence analysis workflows, using technologies such as Data-flo, the Nextflow workflow manager, and containerization of software dependencies. By overcoming barriers to WGS implementation in countries where genome sampling for some species may be underrepresented, a body of evidence can be built to determine the concordance of antimicrobial sensitivity testing and genome-derived resistance, and novel high-risk clones and unknown mechanisms of resistance can be discovered.

Antimicrobial resistance (AMR) is considered a global threat, and novel drug discovery needs to be complemented with systematic and standardized epidemiological surveillance. Surveillance data are currently generated using phenotypic characterization. However, due to poor scalability, this approach does little for true epidemiological investigations. There is a strong case for whole-genome sequencing (WGS) to enhance the phenotypic data. To establish global AMR surveillance using WGS, we developed a laboratory implementation approach that we applied within the NIHR Global Health Research Unit (GHRU) on Genomic Surveillance of Antimicrobial Resistance. In this paper, we outline the laboratory implementation at 4 units: Colombia, India, Nigeria, and the Philippines. The journey to embedding WGS capacity was split into 4 phases: Assessment, Assembly, Optimization, and Reassessment. We show that on-boarding WGS capabilities can greatly enhance the real-time processing power within regional and national AMR surveillance initiatives, despite the high initial investment in laboratory infrastructure and maintenance. Countries looking to introduce WGS as a surveillance tool could begin by sequencing select Global Antimicrobial Resistance Surveillance System (GLASS) priority pathogens that can demonstrate the standardization and impact genome sequencing has in tackling AMR.

The administration and governance of grant funding across global health organizations presents enormous challenges. Meeting these challenges is crucial to ensuring that funds are used in the most effective way to improve health outcomes, in line with the United Nations’ Sustainable Development Goal 3, “Ensure healthy lives and promote well-being for all at all ages.” The Good Financial Grant Practice (GFGP) Standard (ARS 1651) is the world’s first and, currently, only international standard for the financial governance and management of grant funding. Through consensus building and global harmonization between both low- and middle-income and high-income country players, the GFGP Standard has achieved a leveling impact: GFGP applies equally to, and can be implemented by, all types of organization, regardless of location, size, or whether they predominantly give or receive funding.GFGP can be used as a tool for addressing some of the challenges of the current funding model. Here, we describe our experiences and lessons learned from implementing GFGP across 4 diverse research institutions in India, Nigeria, Colombia, and the Philippines as part of our National Institute for Health Research Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance.

In this Supplement, we detail outputs of the National Institute for Health Research Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance project, covering practical implementation of whole-genome sequencing across our consortium, which consists of laboratories in Colombia, India, Nigeria, and the Philippines.

Highlights • Single-arm, single-centre, open-label phase I trial. • Stage III or low burden stage IV non-small cell lung cancer (NSCLC) (n = 21). • Treatment with MEK inhibitor selumetinib concomitantly with radiotherapy. • Combination feasible but outcomes poor and large incidence of pneumocystis jiroveci pneumonia., Background The RAS/RAF/MEK/ERK signalling pathway has a pivotal role in cancer proliferation and modulating treatment response. Selumetinib inhibits MEK and enhances effects of radiotherapy in preclinical studies. Patients and methods Single-arm, single-centre, open-label phase I trial. Patients with stage III NSCLC unsuitable for concurrent chemo-radiotherapy, or stage IV with dominant thoracic symptoms, were recruited to a dose-finding stage (Fibonacci 3 + 3 design; maximum number = 18) then an expanded cohort (n = 15). Oral selumetinib was administered twice daily (starting dose 50 mg) commencing 7 days prior to thoracic radiotherapy, then with radiotherapy (6–6.5 weeks; 60–66 Gy/30–33 fractions). The primary objective was to determine the recommended phase II dose (RP2D) of selumetinib in combination with thoracic radiotherapy. Results 21 patients were enrolled (06/2010–02/2015). Median age: 62y (range 50–73). M:F ratio 12(57%):9(43%). ECOG PS 0:1, 7(33%):14(67%). Stage III 16(76%); IV 5(24%). Median GTV 64 cm3 (range 1–224 cm3). 15 patients comprised the expanded cohort at starting dose. All 21 patients completed thoracic radiotherapy as planned and received induction chemotherapy. 13 (62%) patients received the full dose of selumetinib. In the starting cohort no enhanced radiotherapy-related toxicity was seen. Two patients had dose-limiting toxicity (1x grade 3 diarrhoea/fatigue and 1x pulmonary embolism). Commonest grade 3–4 adverse events: lymphopaenia (19/21 patients) and hypertension (7/21 patients). One patient developed grade 3 oesophagitis. No patients developed grade ≥3 radiation pneumonitis. Two patients were alive at the time of analysis (24 and 26 months follow-up, respectively). Main cause of first disease progression: distant metastases ± locoregional progression (12/21 [57.1%] patients). Six patients had confirmed/suspected pneumocystis jiroveci pneumonia. Conclusion We report poor outcome and severe lymphopenia in most patients treated with thoracic radiotherapy and selumetinib at RP2D in combination, contributing to confirmed/clinically suspected pneumocystis jiroveci pneumonia. These results suggest that this combination should not be pursued in a phase II trial. ClinicalTrials.gov reference: NCT01146756.

IntroductionLow-dose CT (LDCT) screening of high-risk smokers reduces lung cancer (LC) specific mortality. Determining screening eligibility using individualised risk may improve screening effectiveness and reduce harm. Here, we compare the performance of two risk prediction models (PLCOM2012 and Liverpool Lung Project model (LLPv2)) and National Lung Screening Trial (NLST) eligibility criteria in a community-based screening programme.MethodsEver-smokers aged 55–74, from deprived areas of Manchester, were invited to a Lung Health Check (LHC). Individuals at higher risk (PLCOM2012 score ≥1.51%) were offered annual LDCT screening over two rounds. LLPv2 score was calculated but not used for screening selection; ≥2.5% and ≥5% thresholds were used for analysis.ResultsPLCOM2012 ≥1.51% selected 56% (n=1429) of LHC attendees for screening. LLPv2 ≥2.5% also selected 56% (n=1430) whereas NLST (47%, n=1188) and LLPv2 ≥5% (33%, n=826) selected fewer. Over two screening rounds 62 individuals were diagnosed with LC; representing 87% (n=62/71) of 6-year incidence predicted by mean PLCOM2012 score (5.0%). 26% (n=16/62) of individuals with LC were not eligible for screening using LLPv2 ≥5%, 18% (n=11/62) with NLST criteria and 7% (n=5/62) with LLPv2 ≥2.5%. NLST eligible Manchester attendees had 2.5 times the LC detection rate than NLST participants after two annual screens (≈4.3% (n=51/1188) vs 1.7% (n=438/26 309); padjOR 2.50, 95% CI 1.11 to 5.64; p=0.028).ConclusionProspective comparisons of risk prediction tools are required to optimise screening selection in different settings. The PLCOM2012 model may underestimate risk in deprived UK populations; further research focused on model calibration is required.

BackgroundCOPD is a major cause of morbidity and mortality in populations eligible for lung cancer screening. We investigated the role of spirometry in a community-based lung cancer screening programme.MethodsEver smokers, age 55–74, resident in three deprived areas of Manchester were invited to a ‘Lung Health Check’ (LHC) based in convenient community locations. Spirometry was incorporated into the LHCs alongside lung cancer risk estimation (Prostate, Lung, Colorectal and Ovarian Study Risk Prediction Model, 2012 version (PLCOM2012)), symptom assessment and smoking cessation advice. Those at high risk of lung cancer (PLCOM2012 ≥1.51%) were eligible for annual low-dose CT screening over two screening rounds. Airflow obstruction was defined as FEV1/FVCResults99.4% (n=2525) of LHC attendees successfully performed spirometry; mean age was 64.1±5.5, 51% were women, 35% were current smokers. 37.4% (n=944) had airflow obstruction of which 49.7% (n=469) had no previous diagnosis of COPD. 53.3% of those without a prior diagnosis were symptomatic (n=250/469). After multivariate analysis, the detection of airflow obstruction without a prior COPD diagnosis was associated with male sex (adjOR 1.84, 95% CI 1.37 to 2.47; p1/FVC ratio (adjOR 4.19, 95% CI 2.95 to 5.95; padjOR 2.80, 95% CI 1.60 to 8.42; p=0.002).ConclusionsIncorporating spirometry into a community-based targeted lung cancer screening programme is feasible and identifies a significant number of individuals with airflow obstruction who do not have a prior diagnosis of COPD.

An impact evaluation of a pro-poor market system development programme, ‘Making Markets Work for the Poor’ (M4P), poses several methodological issues for evaluators. M4P interventions intend to change the contextual conditions in which stakeholders take business decisions so that it triggers change processes in the wider social system and ultimately benefits poor people. An impact evaluation design for such a programme thus needs to be robust enough to adequately capture these systemic outcomes, acknowledging dynamic changes in intervention delivery as well as in market conditions over time. Theory-based evaluation can provide learning and accountability when it incorporates methods that allow a critical reflection on the key causal steps in an intervention’s theory of change. We present our learnings about indicators and methods to reflect on the importance of the contributions to market system change of a large M4P programme in Ethiopia.

Systemic change is universally desirable and poorly defined. This article seeks to refine a practitioner-developed framework – Adopt-Adapt-Expand-Respond (AAER) – for conceptualising systemic change, and offers case studies to demonstrate its utility in planning for and measuring such change. To do so, the article firstly seeks to define the nature of a system and the components of change within that system. It also discusses the relevance of behaviour change among both actors and institutions in conceptualising systemic change. Finally, in exploring the utility of AAER throughout the implementation of development interventions, it examines the role of the framework in adaptive management: utilising data on observed changes to alter programme intervention tactics.

There is growing recognition of the potential of large-scale restoration in the Amazon as a “nature-based solution” to climate change. However, our knowledge of forest loss and recovery beyond Brazil is limited, and carbon emissions and accumulation have not been estimated for the whole biome. Combining a 33-year land cover dataset with estimates of above-ground biomass and carbon sequestration rates, we evaluate forest loss and recovery across nine Amazonian countries and at a local scale. We also estimate the role of secondary forests in offsetting old-growth deforestation emissions and explore the temporal trends in forest loss and recovery. We find secondary forests across the biome to have offset just 9.7% of carbon emissions from old-growth deforestation, despite occupying 27.6% of deforested land. However, these numbers varied between countries ranging from 9.0% in Brazil to 23.8% in Guyana for carbon offsetting, and 24.8% in Brazil to 56.9% in Ecuador for forest area recovery. We reveal a strong, negative spatial relationship between old-growth forest loss and recovery by secondary forests, showing that regions with the greatest potential for large-scale restoration are also those that currently have the lowest recovery (e.g. Brazil dominates deforestation and emissions but has the lowest recovery). Our findings identify three important challenges for policy makers: (1) incentivising large-scale restoration in highly deforested regions, (2) protecting secondary forests without disadvantaging landowners who depend on farm-fallow systems, and (3) preventing further deforestation. Combatting all of these successfully is essential to ensuring that the Amazon biome achieves its potential in mitigating anthropogenic climate change.

Background: \ud The SARS-CoV-2 delta (B.1.617.2) variant was first detected in England in March, 2021. It has since rapidly become the predominant lineage, owing to high transmissibility. It is suspected that the delta variant is associated with more severe disease than the previously dominant alpha (B.1.1.7) variant. We aimed to characterise the severity of the delta variant compared with the alpha variant by determining the relative risk of hospital attendance outcomes.\ud \ud Methods: \ud This cohort study was done among all patients with COVID-19 in England between March 29 and May 23, 2021, who were identified as being infected with either the alpha or delta SARS-CoV-2 variant through whole-genome sequencing. Individual-level data on these patients were linked to routine health-care datasets on vaccination, emergency care attendance, hospital admission, and mortality (data from Public Health England's Second Generation Surveillance System and COVID-19-associated deaths dataset; the National Immunisation Management System; and NHS Digital Secondary Uses Services and Emergency Care Data Set). The risk for hospital admission and emergency care attendance were compared between patients with sequencing-confirmed delta and alpha variants for the whole cohort and by vaccination status subgroups. Stratified Cox regression was used to adjust for age, sex, ethnicity, deprivation, recent international travel, area of residence, calendar week, and vaccination status.\ud \ud Findings: \ud Individual-level data on 43 338 COVID-19-positive patients (8682 with the delta variant, 34 656 with the alpha variant; median age 31 years [IQR 17–43]) were included in our analysis. 196 (2·3%) patients with the delta variant versus 764 (2·2%) patients with the alpha variant were admitted to hospital within 14 days after the specimen was taken (adjusted hazard ratio [HR] 2·26 [95% CI 1·32–3·89]). 498 (5·7%) patients with the delta variant versus 1448 (4·2%) patients with the alpha variant were admitted to hospital or attended emergency care within 14 days (adjusted HR 1·45 [1·08–1·95]). Most patients were unvaccinated (32 078 [74·0%] across both groups). The HRs for vaccinated patients with the delta variant versus the alpha variant (adjusted HR for hospital admission 1·94 [95% CI 0·47–8·05] and for hospital admission or emergency care attendance 1·58 [0·69–3·61]) were similar to the HRs for unvaccinated patients (2·32 [1·29–4·16] and 1·43 [1·04–1·97]; p=0·82 for both) but the precision for the vaccinated subgroup was low.\ud \ud Interpretation: \ud This large national study found a higher hospital admission or emergency care attendance risk for patients with COVID-19 infected with the delta variant compared with the alpha variant. Results suggest that outbreaks of the delta variant in unvaccinated populations might lead to a greater burden on health-care services than the alpha variant.\ud \ud Funding: \ud Medical Research Council; UK Research and Innovation; Department of Health and Social Care; and National Institute for Health Research.

Advanced genomics and sequencing technologies are increasingly becoming critical for global health applications such as pathogen and antimicrobial resistance (AMR) surveillance. Limited resources challenge capacity development in low- and middle-income countries (LMICs), with few countries having genomics facilities and adequately trained staff. Training research and public health experts who are directly involved in the establishment of such facilities offers an effective, but limited, solution to a growing need. Instead, training them to impart their knowledge and skills to others provides a sustainable model for scaling up the much needed capacity and capability for genomic sequencing and analysis locally with global impact. We designed and developed a Train-the-Trainer course integrating pedagogical aspects with genomic and bioinformatics activities. The course was delivered to 18 participants from 12 countries in Africa, Asia, and Latin America. A combination of teaching strategies culminating in a group project created a foundation for continued development at home institutions. Upon follow-up after 6 months, at least 40% of trainees had initiated training programs and collaborations to build capacity at local, national, and regional level. This work provides a framework for implementing a training and capacity building program for the application of genomics tools and resources in AMR surveillance.

The response of the global virus genomics community to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been unprecedented, with significant advances made towards the ‘real-time’ generation and sharing of SARS-CoV-2 genomic data. The rapid growth in virus genome data production has necessitated the development of new analytical methods that can deal with orders of magnitude of more genomes than previously available. Here, we present and describe Phylogenetic Assignment of Named Global Outbreak Lineages (pangolin), a computational tool that has been developed to assign the most likely lineage to a given SARS-CoV-2 genome sequence according to the Pango dynamic lineage nomenclature scheme. To date, nearly two million virus genomes have been submitted to the web-application implementation of pangolin, which has facilitated the SARS-CoV-2 genomic epidemiology and provided researchers with access to actionable information about the pandemic’s transmission lineages., Virus Evolution, 7 (2), ISSN:2057-1577

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections were rising during early summer 2021 in many countries as a result of the Delta variant. We assessed reverse transcription polymerase chain reaction swab positivity in the Real-time Assessment of Community Transmission–1 (REACT-1) study in England. During June and July 2021, we observed sustained exponential growth with an average doubling time of 25 days, driven by complete replacement of the Alpha variant by Delta and by high prevalence at younger, less-vaccinated ages. Prevalence among unvaccinated people [1.21% (95% credible interval 1.03%, 1.41%)] was three times that among double-vaccinated people [0.40% (95% credible interval 0.34%, 0.48%)]. However, after adjusting for age and other variables, vaccine effectiveness for double-vaccinated people was estimated at between ~50% and ~60% during this period in England. Increased social mixing in the presence of Delta had the potential to generate sustained growth in infections, even at high levels of vaccination.

Wetland ecosystems are critical to the regulation of the global carbon cycle, and there is a high demand for data to improve carbon sequestration and emission models and predictions. Decomposition of plant litter is an important component of ecosystem carbon cycling, yet a lack of knowledge on decay rates in wetlands is an impediment to predicting carbon preservation. Here, we aim to fill this knowledge gap by quantifying the decomposition of standardised green and rooibos tea litter over one year within freshwater and coastal wetland soils across four climates in Australia. We also captured changes in the prokaryotic members of the tea-associated microbiome during this process. Ecosystem type drove differences in tea decay rates and prokaryotic microbiome community composition. Decomposition rates were up to 2-fold higher in mangrove and seagrass soils compared to freshwater wetlands and tidal marshes, in part due to greater leaching-related mass loss. For tidal marshes and freshwater wetlands, the warmer climates had 7-16% less mass remaining compared to temperate climates after a year of decomposition. The prokaryotic microbiome community composition was significantly different between substrate types and sampling times within and across ecosystem types. Microbial indicator analyses suggested putative metabolic pathways common across ecosystems were used to breakdown the tea litter, including increased presence of putative methylotrophs and sulphur oxidisers linked to the introduction of oxygen by root in-growth over the incubation period. Structural equation modelling analyses further highlighted the importance of incubation time on tea decomposition and prokaryotic microbiome community succession, particularly for rooibos tea that experienced a greater proportion of mass loss between three and twelve months compared to green tea. These results provide insights into ecosystem-level attributes that affect both the abiotic and biotic controls of belowground wetland carbon turnover at a continental scale, while also highlighting new decay dynamics for tea litter decomposing under longer incubations. UIDB/04326/2020/ CEECINST/00114/2018 info:eu-repo/semantics/publishedVersion

Here we present a new implementation of Phylocanvas, written to incorporate WebGL (Web Graphics Library), a JavaScript API to render graphics in most modern web browsers without the use of plug-ins. WebGL allows GPU-accelerated image processing as part of the web page canvas thereby enabling Phylocanvas.gl to both render very large trees and allow interactivity via Javascript events. The primary result of this is that rendering the tree is much quicker compared to using the HTML canvas element allowing trees of 100K+ nodes to be displayed

BackgroundKlebsiella species, including the notable pathogen K. pneumoniae, are increasingly associated with antimicrobial resistance (AMR). Genome-based surveillance can inform interventions aimed at controlling AMR. However, its widespread implementation requires tools to streamline bioinformatic analyses and public health reporting.MethodsWe developed the web application Pathogenwatch, which implements analytics tailored to Klebsiella species for integration and visualization of genomic and epidemiological data. We populated Pathogenwatch with 16,537 public Klebsiella genomes to enable contextualization of user genomes. We demonstrated its features with 1,636 genomes from four low- and middle-income countries (LMICs) participating in the NIHR Global Health Research Unit (GHRU) on AMR.ResultsUsing Pathogenwatch, we found that GHRU genomes were dominated by a small number of epidemic drug-resistant clones of K. pneumoniae. However, differences in their distribution were observed (e.g. ST258/512 dominated in Colombia, ST231 in India, ST307 in Nigeria, ST147 in the Philippines). Phylogenetic analyses including public genomes for contextualization enabled retrospective monitoring of their spread. In particular, we identified hospital outbreaks, detected introductions from abroad, and uncovered clonal expansions associated with resistance and virulence genes. Assessment of loci encoding O-antigens and capsule in K. pneumoniae, which represent possible vaccine candidates, showed that three O-types (O1-O3) represented 88.9% of all genomes, whereas capsule types were much more diverse.ConclusionsPathogenwatch provides a free, accessible platform for real-time analysis of Klebsiella genomes to aid surveillance at local, national and global levels. We have improved representation of genomes from GHRU participant countries, further facilitating ongoing surveillance.40-word summaryPathogenwatch is a free web-application for analysis of Klebsiella genomes to aid surveillance at local, national and global levels. We improved the representation of genomes from middle-income countries through the Global Health Research Unit on AMR, further facilitating ongoing surveillance.FUNDINGThis work was supported by Official Development Assistance (ODA) funding from the National Institute of Health Research [grant number 16_136_111].This research was commissioned by the National Institute of Health Research using Official Development Assistance (ODA) funding. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.CONFLICT OF INTERESTThe authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest.

During the COVID-19 pandemic practical activities for undergraduate students have been severely disrupted. Activities in the field of computing, control, electrical and electronic engineering at the University of Sheffield have been taught during the autumn term of 2020/2021 academic year through socially distanced in-lab sessions, remote access to in-lab equipment, take-home kits, and other online methods. Students were asked to leave feedback for each activity using an anonymous online questionnaire, designed to capture their perceptions on their learning experience. Based on the responses received, a number of recommendations have been formulated to help practical educators make decisions on the modes of delivery of certain activities and for certain student cohorts, when pivoting to increased distance learning. Students indicated they would prefer to conduct some activities using take-home kits in the future, paving the way for beneficial long-term changes to the delivery of some practical activities beyond the times of the pandemic.

Summary In 2013, the Drug Supply Chain Security Act (DSCSA) was signed into law to address the growing threat of counterfeit drugs and to ensure prescription drugs remain safe and effective for patients. As part of this law, US pharmaceutical supply chain stakeholders are required to confirm the authorized status of trading partners for transactions and information disclosures, even when there is no prior business relationship. While larger Authorized Trading Partners (ATPs) have connectivity solutions in place, newer and smaller ATPs have not traditionally participated, including tens of thousands of dispensers. To unlock the full potential of the interoperable system mandated by the DSCSA, the authors tested eXtended ATP (XATP), a blockchain-backed framework for ATP authentication and enhanced verification in a real-world pharmacy with genuine drug packages. The objective of this research study was to prove that electronic authentication and enhanced verification can be achieved between ATPs using a mobile-based solution. Moreover, we tested accurate reading of drug and associated electronic med guides, flagging of expired and recalled drugs, and correct generation of documentation to support saleable returns. Methods This study involved two dispensers and three participating manufacturers. Dispensers were onboarded to a mobile application and used supporting documentation to authenticate their identities, and then scanned 2D drug barcodes to submit drug verification requests to manufacturers (including 11 additional, randomly selected manufacturers). Genuine and synthetic drug package barcodes were used to test workflows against genuine and synthetic manufacturer serialization data records. Manufacturers authenticated the identity of requesting dispensers with verifiable credentials and responded to verification requests. Results Enhanced drug verification was achieved, with 100% of requests successfully delivered to participating manufacturers and 88% of requests being delivered to other manufacturers (based on the pharmacist selection of random packages from the pharmacy). Drug verification matching against synthetic serialization data records resulted in 86% accuracy, with the 14% error rate attributed to human factors. All barcodes were successfully scanned and provided package-accurate data, and 97% of randomly selected packages successfully generated drug package inserts. All synthetic recalls and expired drugs were successfully flagged. Four of the manufacturers contacted were among the top 15 pharmaceutical manufacturers globally; all four responded. Conclusions The XATP framework provides a secure, reliable, and seamless remote method to conduct enhanced verification as required by law. Interoperability between manufacturers and dispensers with no prior business relationship can be achieved on ‘day zero’ using mobile devices that enable digital authentication and rapid barcode scanning. As users retain control of their own private keys, the framework also mitigates the single-point-of-attack risks associated with centrally managed systems.

The equine disease strangles, which is characterized by the formation of abscesses in the lymph nodes of the head and neck, is one of the most frequently diagnosed infectious diseases of horses around the world. The causal agent, Streptococcus equi subspecies equi , establishes a persistent infection in approximately 10 % of animals that recover from the acute disease. Such ‘carrier’ animals appear healthy and are rarely identified during routine veterinary examinations pre-purchase or transit, but can transmit S. equi to naïve animals initiating new episodes of disease. Here, we report the analysis and visualization of phylogenomic and epidemiological data for 670 isolates of S. equi recovered from 19 different countries using a new core-genome multilocus sequence typing (cgMLST) web bioresource. Genetic relationships among all 670 S. equi isolates were determined at high resolution, revealing national and international transmission events that drive this endemic disease in horse populations throughout the world. Our data argue for the recognition of the international importance of strangles by the Office International des Épizooties to highlight the health, welfare and economic cost of this disease. The Pathogenwatch cgMLST web bioresource described herein is available for tailored genomic analysis of populations of S. equi and its close relative S. equi subspecies zooepidemicus that are recovered from horses and other animals, including humans, throughout the world. This article contains data hosted by Microreact.

Genomic epidemiology has become an increasingly common tool for epidemic response. Recent technological advances have made it possible to sequence genomes rapidly enough to inform outbreak response, and cheaply enough to justify dense sampling of even large epidemics. With increased availability of sequencing it is possible for agile networks of sequencing facilities to collaborate on the sequencing and analysis of epidemic genomic data.In response to the ongoing SARS-CoV-2 pandemic in the United Kingdom, the COVID-19 Genomics UK (COG-UK) consortium was formed with the aim of rapidly sequencing SARS-CoV-2 genomes as part of a national-scale genomic surveillance strategy. The network consists of universities, academic institutes, regional sequencing centres and the four UK Public Health Agencies.We describe the development and deployment of Majora, an encompassing digital infrastructure to address the challenge of collecting and integrating both genomic sequencing data and sample-associated metadata produced across the COG-UK network. The system was designed and implemented pragmatically to stand up capacity rapidly in a pandemic caused by a novel virus. This approach has underpinned the success of COG-UK, which has rapidly become the leading contributor of SARS-CoV-2 genomes to international databases and has generated over 60,000 sequences to date.

Purpose: As part of the FDA’s DSCSA Pilot Project Program, UCLA and its solution partner, LedgerDomain (collectively referred to as the team hereafter), focused on building a complete, working blockchain-based system, BRUINchain, which would meet all the key objectives of the Drug Supply Chain Security Act (DSCSA) for a dispenser operating solely on commercial off-the-shelf (COTS) technology. Methods: The BRUINchain system requirements include scanning the drug package for a correctly formatted 2D barcode, flagging expired product, verifying the product with the manufacturer, and quarantining suspect and illegitimate products at the last mile: pharmacist to patient, the most complex area of the drug supply chain. The authors demonstrate a successful implementation where product-tracing notifications are sent automatically to key stakeholders, resulting in enhanced timeliness and reduction in paperwork burden. At the core of this effort was a blockchain-based solution to track and trace changes in custody of drug. As an immutable, time-stamped, near-real-time (50-millisecond latency), auditable record of transactions, BRUINchain makes it possible for supply chain communities to arrive at a single version of the truth. BRUINchain was tested with real data on real caregivers administering life-saving medications to real patients at one of the busiest pharmacies in the United States. Results: In addition to communicating with the manufacturer directly for verification, BRUINchain also initiated suspect product notifications. During the study, a 100% success rate was observed across scanning, expiration detection, and counterfeit detection; and paperwork reduction from approximately 1 hour to less than a minute. The authors demonstrate a successful implementation where product-tracing notifications are sent automatically to key stakeholders, resulting in enhanced timeliness and reduction in paperwork burden. At the core of this effort was a blockchain-based solution to track and trace changes in custody of drug. As an immutable, time-stamped, near-real-time (50-millisecond latency), auditable record of transactions, BRUINchain makes it possible for supply chain communities to arrive at a single version of the truth. BRUINchain was tested with real data on real caregivers administering life-saving medications to real patients at one of the busiest pharmacies in the United States. Conclusions: By automatically interrogating the manufacturer’s relational database with our blockchain-based system, our results indicate a projected DSCSA compliance cost of 17 cents per unit, and potentially much more depending on regulatory interpretation and speed of verification. We project that this cost could be reduced with manufacturers’ adoption of a highly performant, fully automated end-to-end system based on digital ledger technology (DLT). In an examination of the interoperability of such a system, we elaborate on its capacity to enable verification in real time without a human in the loop, the key feature driving lower compliance cost. With 4.2 billion prescriptions being dispensed each year in the United States, DLT would not only reduce the projected per-unit cost to 13 cents per unit (saving $183 million in annual labor costs), but also serve as a major bulwark against bad or fraudulent transactions, reduce the need for safety stock, and enhance the detection and removal of potentially dangerous drugs from the drug supply chain to protect U.S. consumers.

X-ray fluorescence (XRF) data from a series of high-pressure–high-temperature (HPHT) wells drilled in the Shearwater Field, UK Continental Shelf (UKCS) are presented. These data comprise a total of 789 samples across a series of eight study wells. Chemical stratigraphy was utilized in conjunction with other geological data (i.e. well logs, ditch cutting descriptions and biostratigraphic analyses) to aid real-time stratigraphic placement. Systematic changes in geochemical composition were identified and used to build a chemostratigraphic zonation to aid delineation of lithostratigraphic boundaries. The application of chemical stratigraphy provided a valuable source of data, particularly through critical ‘drill-in-liner’ sections that are devoid of conventional logging while drilling (LWD) data. The identification of key geochemical zones and provision of a synthetic gamma-ray (Synth GR) profile were utilized in the placement of key casing points and identification of challenging top reservoir picks (Fulmar Formation). These data also served as a backup during LWD tool failure resulting from excessive temperatures. The successive addition of geochemical data accumulated with each well-site exercise permitted continued refinement of the zonation framework, with derived Synth GR profiles exhibiting an extremely close relationship with subsequent wireline logs. Chemical stratigraphic data are shown to be robust and repeatable within the Shearwater Field, enabling close stratigraphic control through critical sections, whilst also providing a low-cost backup in the event of conventional logging tool failures.