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Abstract The Ocean Carbon and Acidification Data System (OCADS) is a data management system at the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI). It manages a wide range of ocean carbon and acidification data, including chemical, physical, and biological observations collected from research vessels, ships of opportunity, and uncrewed platforms, as well as laboratory experiment results, and model outputs. Additionally, OCADS serves as a repository for related Global Ocean Observing System (GOOS) biogeochemistry Essential Ocean Variables (EOVs), e.g., oxygen, nutrients, transient tracers, and stable isotopes. OCADS endeavors to be one of the world’s leading providers of ocean carbon and acidification data, information, products, and services. To provide the best data management services to the ocean carbon and acidification research community, OCADS prioritizes adopting a customer-centric approach and gathering knowledge and expertise from the research community to improve its data management practices. OCADS aims to make all ocean carbon and acidification data accessible via a single portal, and welcomes submissions from around the world: https://www.ncei.noaa.gov/products/ocean-carbon-acidification-data-system/.

PurposeMedulloblastomas are the most common primary malignant brain tumors in children. They are divided into molecular subgroups: WNT-activated, SHH-Activated, TP53 mutant or wild type, and non-WNT/non-SHH (Groups 3 and 4). WNT-activated medulloblastomas are usually caused by mutations in the CTNNB1 gene (85%–90%), and most remaining cases of CTNNB1 wild type are thought to be caused by germline mutations in APC. So far, the frequencies of CTNNB1 have been reported mainly in North American and European populations. The aim of this study was to report the frequency of CTNNB1 mutations in WNT-activated medulloblastomas in a Latin-Iberian population and correlate with their clinicopathological characteristics.MethodsA total of 266 medulloblastomas from seven different institutions from Brazil (n=211), Portugal (n=38), and Argentina (n=17) were evaluated. Following RNA and DNA isolation from formalin-fixed, paraffin-embedded (FFPE) tumor tissues, the molecular classification and CTNNB1 mutation analysis were performed by nCounter and Sanger sequencing, respectively.ResultsWNT-activated medulloblastomas accounted for 15% (40/266) of the series. We observed that 73% of WNT-activated medulloblastomas harbored CTNNB1 mutations. CTNNB1 wild-type cases (27%) were more prevalent in female individuals and suggested to be associated with a worse outcome. Among the CTNNB1 wild-type cases, the available analysis of family history revealed two cases with familiar adenomatous polyposis, harboring APC germline variants.ConclusionWe observed a lower incidence of CTNNB1 mutations in WNT-activated medulloblastomas in our Latin-Iberian cohort compared to frequencies previously described in other populations. Considering that CTNNB1 wild-type cases may exhibit APC germline mutations, our study suggests a higher incidence (~30%) of hereditary WNT-activated medulloblastomas in the Latin-Iberian population.

Plant viruses depend on host cellular factors for their replication and movement. There are cellular proteins that change their localization and/or expression and have a proviral role or antiviral activity and interact with or target viral proteins. Identification of those proteins and their roles during infection is crucial for understanding plant–virus interactions and to design antiviral resistance in crops. Important host proteins have been identified using approaches such as tag-dependent immunoprecipitation or yeast two hybridization that require cloning individual proteins or the entire virus. However, the number of possible interactions between host and viral proteins is immense. Therefore, an alternative method is needed for proteome-wide identification of host proteins involved in host–virus interactions. Here, we present cell fractionation coupled with mass spectrometry as an option to identify protein–protein interactions between viruses and their hosts. This approach involves separating subcellular organelles using differential and/or gradient centrifugation from virus-free and virus-infected cells (1) followed by comparative analysis of the proteomic profiles obtained for each subcellular organelle via mass spectrometry (2). After biological validation, prospect host proteins with proviral or antiviral roles can be subject to fundamental studies in the context of basic biology to shed light on both virus replication and cellular processes. They can also be targeted via gene editing to develop virus-resistant crops.

Homicide prediction is a challenging task due to the spatio-temporal sparsity of these crime events. In this paper we report the results of using several approaches to mitigate this sparsity condition in machine learning models specially tailored towards modeling homicides events. Since spatial resolution is a direct determinant of sparsity, we focus on the performance of these models across different resolutions of interest to police authorities. We use a simple count model as benchmark and propose some enhancements of it directed towards improving prediction performance. We then compare the results to more complex models motivated by manifold learning and graph signal processing methods. We found that the simple benchmark models are as good as state of the art models for low resolution, but, as resolution increases, the performance of machine learning models outperform the benchmark. These results provide a rationality for the use of state of the art machine learning models for homicide prediction at the high resolution of interest for the deployment of police resources.

Abstract The advent of immune-checkpoint inhibitors (ICI) in modern oncology has significantly improved survival in several cancer settings. A subgroup of women with breast cancer (BC) has immunogenic infiltration of lymphocytes with expression of programmed death-ligand 1 (PD-L1). These patients may potentially benefit from ICI targeting the programmed death 1 (PD-1)/PD-L1 signaling axis. The use of tumor-infiltrating lymphocytes (TILs) as predictive and prognostic biomarkers has been under intense examination. Emerging data suggest that TILs are associated with response to both cytotoxic treatments and immunotherapy, particularly for patients with triple-negative BC. In this review from The International Immuno-Oncology Biomarker Working Group, we discuss (a) the biological understanding of TILs, (b) their analytical and clinical validity and efforts toward the clinical utility in BC, and (c) the current status of PD-L1 and TIL testing across different continents, including experiences from low-to-middle-income countries, incorporating also the view of a patient advocate. This information will help set the stage for future approaches to optimize the understanding and clinical utilization of TIL analysis in patients with BC.

Effective data management plays a key role in oceanographic research as cruise-based data, collected from different laboratories and expeditions, are commonly compiled to investigate regional to global oceanographic processes. Here we describe new and updated best practice data standards for discrete chemical oceanographic observations, specifically those dealing with column header abbreviations, quality control flags, missing value indicators, and standardized calculation of certain properties. These data standards have been developed with the goals of improving the current practices of the scientific community and promoting their international usage. These guidelines are intended to standardize data files for data sharing and submission into permanent archives. They will facilitate future quality control and synthesis efforts and lead to better data interpretation. In turn, this will promote research in ocean biogeochemistry, such as studies of carbon cycling and ocean acidification, on regional to global scales. These best practice standards are not mandatory. Agencies, institutes, universities, or research vessels can continue using different data standards if it is important for them to maintain historical consistency. However, it is hoped that they will be adopted as widely as possible to facilitate consistency and to achieve the goals stated above.

In this paper, we outline the need for a coordinated international effort toward the building of an open-access Global Ocean Oxygen Database and ATlas (GO2DAT) complying with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). GO2DAT will combine data from the coastal and open ocean, as measured by the chemical Winkler titration method or by sensors (e.g., optodes, electrodes) from Eulerian and Lagrangian platforms (e.g., ships, moorings, profiling floats, gliders, ships of opportunities, marine mammals, cabled observatories). GO2DAT will further adopt a community-agreed, fully documented metadata format and a consistent quality control (QC) procedure and quality flagging (QF) system. GO2DAT will serve to support the development of advanced data analysis and biogeochemical models for improving our mapping, understanding and forecasting capabilities for ocean O2 changes and deoxygenation trends. It will offer the opportunity to develop quality-controlled data synthesis products with unprecedented spatial (vertical and horizontal) and temporal (sub-seasonal to multi-decadal) resolution. These products will support model assessment, improvement and evaluation as well as the development of climate and ocean health indicators. They will further support the decision-making processes associated with the emerging blue economy, the conservation of marine resources and their associated ecosystem services and the development of management tools required by a diverse community of users (e.g., environmental agencies, aquaculture, and fishing sectors). A better knowledge base of the spatial and temporal variations of marine O2 will improve our understanding of the ocean O2 budget, and allow better quantification of the Earth’s carbon and heat budgets. With the ever-increasing need to protect and sustainably manage ocean services, GO2DAT will allow scientists to fully harness the increasing volumes of O2 data already delivered by the expanding global ocean observing system and enable smooth incorporation of much higher quantities of data from autonomous platforms in the open ocean and coastal areas into comprehensive data products in the years to come. This paper aims at engaging the community (e.g., scientists, data managers, policy makers, service users) toward the development of GO2DAT within the framework of the UN Global Ocean Oxygen Decade (GOOD) program recently endorsed by IOC-UNESCO. A roadmap toward GO2DAT is proposed highlighting the efforts needed (e.g., in terms of human resources).

Virus evolution is the change in the genetic structure of a viral population over time and results in the emergence of new viral variants, strains, and species with novel biological properties, including adaptation to new hosts. There are host, vector, environmental, and viral factors that contribute to virus evolution. To achieve or fine tune compatibility and successfully establish infection, viruses adapt to a particular host species or to a group of species. However, some viruses are better able to adapt to diverse hosts, vectors, and environments. Viruses generate genetic diversity through mutation, reassortment, and recombination. Plant viruses are exposed to genetic drift and selection pressures by host and vector factors, and random variants or those with a competitive advantage are fixed in the population and mediate the emergence of new viral strains or species with novel biological properties. This process creates a footprint in the virus genome evident as the preferential accumulation of substitutions, insertions, or deletions in areas of the genome that function as determinants of host adaptation. Here, with respect to plant viruses, we review the current understanding of the sources of variation, the effect of selection, and its role in virus evolution and host adaptation.

The terms genome engineering, genome editing, and gene editing, refer to modifications (insertions, deletions, substitutions) in the genome of a living organism. The most widely used approach to genome editing nowadays is based on Clustered Regularly Interspaced Short Palindromic Repeats and associated protein 9 (CRISPR-Cas9). In prokaryotes, CRISPR-Cas9 is an adaptive immune system that naturally protects cells from DNA virus infections. CRISPR-Cas9 has been modified to create a versatile genome editing technology that has a wide diversity of applications in medicine, agriculture, and basic studies of gene functions. CRISPR-Cas9 has been used in a growing number of monocot and dicot plant species to enhance yield, quality, and nutritional value, to introduce or enhance tolerance to biotic and abiotic stresses, among other applications. Although biosafety concerns remain, genome editing is a promising technology with potential to contribute to food production for the benefit of the growing human population. Here, we review the principles, current advances and applications of CRISPR-Cas9-based gene editing in crop improvement. We also address biosafety concerns and show that humans have been exposed to Cas9 protein homologues long before the use of CRISPR-Cas9 in genome editing.

Abstract Background Maize lethal necrosis is caused by a synergistic co-infection of Maize chlorotic mottle virus (MCMV) and a specific member of the Potyviridae, such as Sugarcane mosaic virus (SCMV), Wheat streak mosaic virus (WSMV) or Johnson grass mosaic virus (JGMV). Typical maize lethal necrosis symptoms include severe yellowing and leaf drying from the edges. In Kenya, we detected plants showing typical and atypical symptoms. Both groups of plants often tested negative for SCMV by ELISA. Methods We used next-generation sequencing to identify viruses associated to maize lethal necrosis in Kenya through a metagenomics analysis. Symptomatic and asymptomatic leaf samples were collected from maize and sorghum representing sixteen counties. Results Complete and partial genomes were assembled for MCMV, SCMV, Maize streak virus (MSV) and Maize yellow dwarf virus-RMV (MYDV-RMV). These four viruses (MCMV, SCMV, MSV and MYDV-RMV) were found together in 30 of 68 samples. A geographic analysis showed that these viruses are widely distributed in Kenya. Phylogenetic analyses of nucleotide sequences showed that MCMV, MYDV-RMV and MSV are similar to isolates from East Africa and other parts of the world. Single nucleotide polymorphism, nucleotide and polyprotein sequence alignments identified three genetically distinct groups of SCMV in Kenya. Variation mapped to sequences at the border of NIb and the coat protein. Partial genome sequences were obtained for other four potyviruses and one polerovirus. Conclusion Our results uncover the complexity of the maize lethal necrosis epidemic in Kenya. MCMV, SCMV, MSV and MYDV-RMV are widely distributed and infect both maize and sorghum. SCMV population in Kenya is diverse and consists of numerous strains that are genetically different to isolates from other parts of the world. Several potyviruses, and possibly poleroviruses, are also involved.

Potyviruses (family Potyviridae, genus Potyvirus) are the result of an initial radiation event that occurred 6,600 years ago. The genus currently consists of 167 species that infect monocots or dicots, including domesticated and wild plants. Potyviruses are transmitted in a non-persistent way by more than 200 species of aphids. As indicated by their wide host range, worldwide distribution, and diversity of their vectors, potyviruses have an outstanding capacity to adapt to new hosts and environments. However, factors that confer adaptability are poorly understood. Viral RNA-dependent RNA polymerases introduce nucleotide substitutions that generate genetic diversity. We hypothesized that selection imposed by hosts and vectors creates a footprint in areas of the genome involved in host adaptation. Here, we profiled genomic and polyprotein variation in all species in the genus Potyvirus. Results showed that the potyviral genome is under strong negative selection. Accordingly, the genome and polyprotein sequence are remarkably stable. However, nucleotide and amino acid substitutions across the potyviral genome are not randomly distributed and are not determined by codon usage. Instead, substitutions preferentially accumulate in hypervariable areas at homologous locations across potyviruses. At a frequency that is higher than that of the rest of the genome, hypervariable areas accumulate non-synonymous nucleotide substitutions and sites under positive selection. Our results show, for the first time, that there is correlation between host range and the frequency of sites under positive selection. Hypervariable areas map to the N terminal part of protein P1, N and C terminal parts of helper component proteinase (HC-Pro), the C terminal part of protein P3, VPg, the C terminal part of NIb (RNA-dependent RNA polymerase), and the N terminal part of the coat protein (CP). Additionally, a hypervariable area at the NIb-CP junction showed that there is variability in the sequence of the NIa protease cleavage sites. Structural alignment showed that the hypervariable area in the CP maps to the N terminal flexible loop and includes the motif required for aphid transmission. Collectively, results described here show that potyviruses contain fixed hypervariable areas in key parts of the genome which provide mutational robustness and are potentially involved in host adaptation.

The WMO-IOC Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) has devised a coordination mechanism for the fit-for-purpose delivery of an end-to-end system, from ocean observations to met-ocean operational services. This paper offers a complete overview of the activities carried out by JCOMM and the status of the achievements up to 2018. The JCOMM stakeholders consist of the research and operational institutions of WMO members and the IOC member states, which mandated JCOMM to devise an international strategy to move toward the achievement of the United Nations Sustainable Development Goals. The three areas of activity are the Observation Program Area (OPA), the Data Management Program Area (DMPA) and the Services and Forecasting Services Program Area (SFSPA), and several expert teams have been established to contribute to the international coordination efforts. OPA is organized into observing networks connected by different observing technologies, DMPA organizes the overall near-real time and delayed mode data assembly, and the delivery methodology and architecture, and the SFSPA coordinates the met-ocean services resulting from the observations and data management. Future developments should enhance coordination in these three program areas by considering the inclusion of new and emergent observing technologies, the interoperability of met-ocean data assembly centers and the establishment of efficient research to operations protocols, in addition to better fit-for-purpose customized services in both the public and private sectors.

Viruses are dependent on host factors at all parts of the infection cycle, such as translation, genome replication, encapsidation, and cell-to-cell and systemic movement. RNA viruses replicate their genome in compartments associated with the endoplasmic reticulum, chloroplasts, and mitochondria or peroxisome membranes. In contrast, DNA viruses replicate in the nucleus. Viral infection causes changes in plant gene expression and in the subcellular localization of some host proteins. These changes may support or inhibit virus accumulation and spread. Here, we review host proteins that change their subcellular localization in the presence of a plant virus. The most frequent change is the movement of host cytoplasmic proteins into the sites of virus replication through interactions with viral proteins, and the protein contributes to essential viral processes. In contrast, only a small number of studies document changes in the subcellular localization of proteins with antiviral activity. Understanding the changes in the subcellular localization of host proteins during plant virus infection provides novel insights into the mechanisms of plant–virus interactions and may help the identification of targets for designing genetic resistance to plant viruses.

Orthotospoviruses are plant-infecting members of the family Tospoviridae (order Bunyavirales), have a broad host range and are vectored by polyphagous thrips in a circulative-propagative manner. Because diverse hosts and vectors impose heterogeneous selection constraints on viral genomes, the evolutionary arms races between hosts and their pathogens might be manifested as selection for rapid changes in key genes. These observations suggest that orthotospoviruses contain key genetic components that rapidly mutate to mediate host adaptation and vector transmission. Using complete genome sequences, we profiled genomic variation in orthotospoviruses. Results show that the three genomic segments contain hypervariable areas at homologous locations across species. Remarkably, the highest nucleotide variation mapped to the intergenic region of RNA segments S and M, which fold into a hairpin. Secondary structure analyses showed that the hairpin is a dynamic structure with multiple functional shapes formed by stems and loops, contains sites under positive selection and covariable sites. Accumulation and tolerance of mutations in the intergenic region is a general feature of orthotospoviruses and might mediate adaptation to host plants and insect vectors.

Plant viruses use cellular factors and resources to replicate and move. Plants respond to viral infection by several mechanisms, including innate immunity, autophagy, and gene silencing, that viruses must evade or suppress. Thus, the establishment of infection is genetically determined by the availability of host factors necessary for virus replication and movement and by the balance between plant defense and viral suppression of defense responses. Host factors may have antiviral or proviral activities. Proviral factors condition susceptibility to viruses by participating in processes essential to the virus. Here, we review current advances in the identification and characterization of host factors that condition susceptibility to plant viruses. Host factors with proviral activity have been identified for all parts of the virus infection cycle: viral RNA translation, viral replication complex formation, accumulation or activity of virus replication proteins, virus movement, and virion assembly. These factors could be targets of gene editing to engineer resistance to plant viruses.

Positive-strand RNA viruses replicate their genomes in membrane-bound replication compartments. Brome mosaic virus (BMV) replicates in vesicular invaginations of the endoplasmic reticulum membrane. BMV has served as a productive model system to study processes like virus-host interactions, RNA replication and recombination. Here we present multiple lines of evidence showing that the structure of the viral RNA replication compartments plays a fundamental role and that recruitment of parental RNAs to a common replication compartment is a limiting step in intermolecular RNA recombination. We show that a previously defined requirement for an RNA recruitment element on both parental RNAs is not to function as a preferred crossover site, but in order for individual RNAs to be recruited into the replication compartments. Moreover, modulating the form of the replication compartments from spherular vesicles (spherules) to more expansive membrane layers increased intermolecular RNA recombination frequency by 200- to 1000-fold. We propose that intermolecular RNA recombination requires parental RNAs to be recruited into replication compartments as monomers, and that recruitment of multiple RNAs into a contiguous space is much more common for layers than for spherules. These results could explain differences in recombination frequencies between viruses that replicate in association with smaller spherules versus larger double-membrane vesicles and convoluted membranes.

Plant viruses are inducers and targets of antiviral RNA silencing. To condition susceptibility, most plant viruses encode silencing suppressor proteins that interfere with antiviral RNA silencing. The NSs protein is an RNA silencing suppressor in orthotospoviruses, such as the tomato spotted wilt virus (TSWV). The mechanism of RNA silencing suppression by NSs and its role in virus infection and movement are poorly understood. Here, we cloned and tagged TSWV NSs and expressed it from a GFP-tagged turnip mosaic virus (TuMV-GFP) carrying either a wild-type or suppressor-deficient (AS9) helper component proteinase (HC-Pro). When expressed in cis, NSs restored pathogenicity and promoted systemic infection of suppressor-deficient TuMV-AS9-GFP in Nicotiana benthamiana and Arabidopsis thaliana. Inactivating mutations were introduced in NSs RNA-binding domain one. A genetic analysis with active and suppressor-deficient NSs, in combination with wild-type and mutant plants lacking essential components of the RNA silencing machinery, showed that the NSs insert is stable when expressed from a potyvirus. NSs can functionally replace potyviral HC-Pro, condition virus susceptibility, and promote systemic infection and symptom development by suppressing antiviral RNA silencing through a mechanism that partially overlaps that of potyviral HC-Pro. The results presented provide new insight into the mechanism of silencing suppression by NSs and its effect on virus infection.

In eukaryotes, ARGONAUTE proteins (AGOs) associate with microRNAs (miRNAs), short interfering RNAs (siRNAs), and other classes of small RNAs to regulate target RNA or target loci. Viral infection in plants induces a potent and highly specific antiviral RNA silencing response characterized by the formation of virus-derived siRNAs. Arabidopsis thaliana has ten AGO genes of which AGO1, AGO2, and AGO7 have been shown to play roles in antiviral defense. A genetic analysis was used to identify and characterize the roles of AGO proteins in antiviral defense against Turnip mosaic virus (TuMV) in Arabidopsis. AGO1, AGO2 and AGO10 promoted anti-TuMV defense in a modular way in various organs, with AGO2 providing a prominent antiviral role in leaves. AGO5, AGO7 and AGO10 had minor effects in leaves. AGO1 and AGO10 had overlapping antiviral functions in inflorescence tissues after systemic movement of the virus, although the roles of AGO1 and AGO10 accounted for only a minor amount of the overall antiviral activity. By combining AGO protein immunoprecipitation with high-throughput sequencing of associated small RNAs, AGO2, AGO10, and to a lesser extent AGO1 were shown to associate with siRNAs derived from silencing suppressor (HC-Pro)-deficient TuMV-AS9, but not with siRNAs derived from wild-type TuMV. Co-immunoprecipitation and small RNA sequencing revealed that viral siRNAs broadly associated with wild-type HC-Pro during TuMV infection. These results support the hypothesis that suppression of antiviral silencing during TuMV infection, at least in part, occurs through sequestration of virus-derived siRNAs away from antiviral AGO proteins by HC-Pro. These findings indicate that distinct AGO proteins function as antiviral modules, and provide a molecular explanation for the silencing suppressor activity of HC-Pro.

As the 2022 mpox outbreak spread worldwide, protection against smallpox has become a focus of interest because smallpox vaccination might provide some protection against monkeypox virus (1). Massive vaccination with [...]

Masonry structures are the most prevalent type of buildings worldwide, and a significant portion are situated in seismic-prone areas. Thus, detailed information regarding their seismic strength and vulnerability is needed. The complexity of studying masonry structures lies in defining accurate and efficient models for representing masonry walls. In this context, there is a need for simplified methods that allow the modeling of masonry walls within a 3D structure. This work presents a methodology to define effective masonry properties from numerical analyses on representative volumes, using a damage model informed by experimental tests on units and mortar. These effective material properties serve as input parameters to model masonry walls within a macro-model approach, aiming to accurately capture the in-plane behavior and damage mechanisms with limited computational cost. The methodology is verified with experimental results and applied to real case studies in Cuenca, Ecuador.