Low-cost IoT-based sensor system: A case study on harsh environmental monitoring

Wireless Sensor Networks (WSNs) are promising technologies for exploiting in harsh environments such as can be found in the nuclear industry. Nuclear storage facilities can be considered harsh environments in that, amongst other variables, they can be dark, congested, and have high gamma radiation levels, which preclude operator access. These conditions represent significant challenges to sensor reliability, data acquisition and communications, power supplies, and longevity. Installed monitoring of parameters such as temperature, pressure, radiation, humidity, and hydrogen content within a nuclear facility may offer significant advantages over current baseline measurement options. This paper explores Commercial Off-The-Shelf (COTS) components to comprise an installed Internet of Things (IoT)-based multipurpose monitoring system for a specific nuclear storage situation measuring hydrogen concentration and temperature. This work addresses two major challenges of developing an installed remote sensing monitor for a typical nuclear storage scenario to detect both hydrogen concentrations and temperature: (1) development of a compact, cost-effective, and robust multisensor system from COTS components, and (2) validation of the sensor system for detecting temperature and hydrogen gas release. The proof of concept system developed in this study not only demonstrates the cost reduction of regular monitoring but also enables intelligent data management through the IoT by using ThingSpeak in a harsh environment

Genomic signatures of recent adaptation in a wild bumblebee.

Environmental changes threaten insect pollinators, creating risks for agriculture and ecosystem stability. Despite their importance, we know little about how wild insects respond to environmental pressures. To understand the genomic bases of adaptation in an ecologically important pollinator, we analyzed genomes of Bombus terrestris bumblebees collected across Great Britain. We reveal extensive genetic diversity within this population, and strong signatures of recent adaptation throughout the genome affecting key processes including neurobiology and wing development. We also discover unusual features of the genome, including a region containing 53 genes that lacks genetic diversity in many bee species, and a horizontal gene transfer from a Wolbachia bacteria. Overall, the genetic diversity we observe and how it is distributed throughout the genome and the population should support the resilience of this important pollinator species to ongoing and future selective pressures. Applying our approach to more species should help understand how they can differ in their adaptive potential, and to develop conservation strategies for those most at risk

SARS-CoV-2 sequencing collaboration in west Africa shows best practices.

Correspondence - No abstract available

Safety and Immunogenicity of Malaria Vectored Vaccines Given with Routine Expanded Program on Immunization Vaccines in Gambian Infants and Neonates: A Randomized Controlled Trial.

BACKGROUND: Heterologous prime-boost vaccination with chimpanzee adenovirus 63 (ChAd63) and modified vaccinia virus Ankara (MVA) encoding multiple epitope string thrombospondin-related adhesion protein (ME-TRAP) has shown acceptable safety and promising immunogenicity in African adult and pediatric populations. If licensed, this vaccine could be given to infants receiving routine childhood immunizations. We therefore evaluated responses to ChAd63 MVA ME-TRAP when co-administered with routine Expanded Program on Immunization (EPI) vaccines. METHODS: We enrolled 65 Gambian infants and neonates, aged 16, 8, or 1 week at first vaccination and randomized them to receive either ME-TRAP and EPI vaccines or EPI vaccines only. Safety was assessed by the description of vaccine-related adverse events (AEs). Immunogenicity was evaluated using IFNγ enzyme-linked immunospot, whole-blood flow cytometry, and anti-TRAP IgG ELISA. Serology was performed to confirm all infants achieved protective titers to EPI vaccines. RESULTS: The vaccines were well tolerated in all age groups with no vaccine-related serious AEs. High-level TRAP-specific IgG and T cell responses were generated after boosting with MVA. CD8+ T cell responses, previously found to correlate with protection, were induced in all groups. Antibody responses to EPI vaccines were not altered significantly. CONCLUSION: Malaria vectored prime-boost vaccines co-administered with routine childhood immunizations were well tolerated. Potent humoral and cellular immunity induced by ChAd63 MVA ME-TRAP did not reduce the immunogenicity of co-administered EPI vaccines, supporting further evaluation of this regimen in infant populations. CLINICAL TRIAL REGISTRATION: The clinical trial was registered on http://Clinicaltrials.gov (NCT02083887) and the Pan-African Clinical Trials Registry (PACTR201402000749217)

Origin of imported SARS-CoV-2 strains in The Gambia identified from whole genome sequences.

The SARS-CoV-2 disease, first detected in Wuhan, China, in December 2019 has become a global pandemic and is causing an unprecedented burden on health care systems and the economy globally. While the travel history of index cases may suggest the origin of infection, phylogenetic analysis of isolated strains from these cases and contacts will increase the understanding and link between local transmission and other global populations. The objective of this analysis was to provide genomic data on the first six cases of SARS-CoV-2 in The Gambia and to determine the source of infection. This ultimately provide baseline data for subsequent local transmission and contribute genomic diversity information towards local and global data. Our analysis has shown that the SARS-CoV-2 virus identified in The Gambia are of European and Asian origin and sequenced data matched patients' travel history. In addition, we were able to show that two COVID-19 positive cases travelling in the same flight had different strains of SARS-CoV-2. Although whole genome sequencing (WGS) data is still limited in sub-Saharan Africa, this approach has proven to be a highly sensitive, specific and confirmatory tool for SARS-CoV-2 detection

Genomic epidemiology of SARS-CoV-2 infections in The Gambia: an analysis of routinely collected surveillance data between March, 2020, and January, 2022

Background: COVID-19, caused by SARS-CoV-2, is one of the deadliest pandemics of the past 100 years. Genomic sequencing has an important role in monitoring of the evolution of the virus, including the detection of new viral variants. We aimed to describe the genomic epidemiology of SARS-CoV-2 infections in The Gambia. Methods: Nasopharyngeal or oropharyngeal swabs collected from people with suspected cases of COVID-19 and international travellers were tested for SARS-CoV-2 with standard RT-PCR methods. SARS-CoV-2-positive samples were sequenced according to standard library preparation and sequencing protocols. Bioinformatic analysis was done using ARTIC pipelines and Pangolin was used to assign lineages. To construct phylogenetic trees, sequences were first stratified into different COVID-19 waves (waves 1–4) and aligned. Clustering analysis was done and phylogenetic trees constructed. Findings: Between March, 2020, and January, 2022, 11 911 confirmed cases of COVID-19 were recorded in The Gambia, and 1638 SARS-CoV-2 genomes were sequenced. Cases were broadly distributed into four waves, with more cases during the waves that coincided with the rainy season (July–October). Each wave occurred after the introduction of new viral variants or lineages, or both, generally those already established in Europe or in other African countries. Local transmission was higher during the first and third waves (ie, those that corresponded with the rainy season), in which the B.1.416 lineage and delta (AY.34.1) were dominant, respectively. The second wave was driven by the alpha and eta variants and the B.1.1.420 lineage. The fourth wave was driven by the omicron variant and was predominantly associated with the BA.1.1 lineage. Interpretation: More cases of SARS-CoV-2 infection were recorded in The Gambia during peaks of the pandemic that coincided with the rainy season, in line with transmission patterns for other respiratory viruses. The introduction of new lineages or variants preceded epidemic waves, highlighting the importance of implementing well structured genomic surveillance at a national level to detect and monitor emerging and circulating variants. Funding: Medical Research Unit The Gambia at London School of Hygiene & Tropical Medicine, UK Research and Innovation, WHO

Global diversity and antimicrobial resistance of typhoid fever pathogens: insights from a meta-analysis of 13,000 Salmonella Typhi genomes

Background: The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). Methods: This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. Results: Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal ‘sentinel’ surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. Conclusions: The consortium’s aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies

Global diversity and antimicrobial resistance of typhoid fever pathogens: Insights from a meta-analysis of 13,000 Salmonella Typhi genomes

Background: The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). Methods: This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. Results: Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal ‘sentinel’ surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (=3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has becomedominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. Conclusions: The consortium’s aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies

Global diversity and antimicrobial resistance of typhoid fever pathogens : insights from a meta-analysis of 13,000 Salmonella Typhi genomes

DATA AVAILABILITY : All data analysed during this study are publicly accessible. Raw Illumina sequence reads have been submitted to the European Nucleotide Archive (ENA), and individual sequence accession numbers are listed in Supplementary file 2. The full set of n=13,000 genome assemblies generated for this study are available for download from FigShare: https://doi.org/10.26180/21431883. All assemblies of suitable quality (n=12,849) are included as public data in the online platform Pathogenwatch (https://pathogen.watch). The data are organised into collections, which each comprise a neighbour-joining phylogeny annotated with metadata, genotype, AMR determinants, and a linked map. Each contributing study has its own collection, browsable at https://pathogen.watch/collections/all?organismId= 90370. In addition, we have provided three large collections, each representing roughly a third of the total dataset presented in this study: Typhi 4.3.1.1 (https://pathogen.watch/collection/ 2b7mp173dd57-clade-4311), Typhi lineage 4 (excluding 4.3.1.1) (https://pathogen.watch/collection/ wgn6bp1c8bh6-clade-4-excluding-4311), and Typhi lineages 0-3 (https://pathogen.watch/collection/ 9o4bpn0418n3-clades-0-1-2-and-3). In addition, users can browse the full set of Typhi genomes in Pathogenwatch and select subsets of interest (e.g. by country, genotype, and/or resistance) to generate a collection including neighbour-joining tree for interactive exploration.SUPPLEMENTARY FILES : Available at https://elifesciences.org/articles/85867/figures#content. SUPPLEMENTARY FILE 1. Details of local ethical approvals provided for studies that were unpublished at the time of contributing data to this consortium project. Most data are now published, and the citations for the original studies are provided here. National surveillance programs in Chile (Maes et al., 2022), Colombia (Guevara et al., 2021), France, New Zealand, and Nigeria (Ikhimiukor et al., 2022b) were exempt from local ethical approvals as these countries allow sharing of non-identifiable pathogen sequence data for surveillance purposes. The US CDC Internal Review Board confirmed their approval was not required for use in this project (#NCEZID-ARLT- 10/ 20/21-fa687). SUPPLEMENTARY FILE 2. Line list of 13,000 genomes included in the study. SUPPLEMENTARY FILE 3. Source information recorded for genomes included in the study. ^Indicates cases included in the definition of ‘assumed acute illness’. SUPPLEMENTARY FILE 4. Summary of genomes by country. SUPPLEMENTARY FILE 5. Genotype frequencies per region (N, %, 95% confidence interval; annual and aggregated, 2010–2020). SUPPLEMENTARY FILE 6. Genotype frequencies per country (N, %, 95% confidence interval; annual and aggregated, 2010–2020). SUPPLEMENTARY FILE 7. Antimicrobial resistance (AMR) frequencies per region (N, %, 95% confidence interval; aggregated 2010–2020). SUPPLEMENTARY FILE 8. Antimicrobial resistance (AMR) frequencies per country (N, %, 95% confidence interval; annual and aggregated, 2010–2020). SUPPLEMENTARY FILE 9. Laboratory code master list. Three letter laboratory codes assigned by the consortium.BACKGROUND : The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). METHODS : This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. RESULTS : Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal ‘sentinel’ surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. CONCLUSIONS : The consortium’s aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies.Fellowships from the European Union (funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 845681), the Wellcome Trust (SB, Wellcome Trust Senior Fellowship), and the National Health and Medical Research Council.https://elifesciences.org/am2024Medical MicrobiologySDG-03:Good heatlh and well-bein