Food and Agriculture Organization of the United Nations

The IMD pathway is an innate immune signalling pathway regulating antibacterial humoral defence responses, and is highly conserved among diverse insects and other organisms. However, genomic studies among hemipterans suggested that certain insects from this order may lack the Imd gene, a key component of the IMD immune pathway. Our previous work identified Imd in the brown-winged green stinkbug Plautia stali, which showed low sequence homology to other insect Imd genes but exhibited functionality in the IMD pathway. Using the P. stali Imd sequence as a query, we surveyed genomic data of the common bedbug Cimex lectularius and the brown marmorated stinkbug Halyomorpha halys, both of which were thought to lack an Imd gene, and identified Imd-like gene sequences in each. RNA interference experiments demonstrated that, in both species, these Imd-like genes function similarly to the canonical Imd gene. 3D protein structure predictions confirmed that, despite extensive sequence divergence, the Imd-like translation products were structurally similar to Imd proteins of other organisms. High levels of sequence diversity and positive selection were observed with some Imd-like genes of bedbugs and stinkbugs, suggesting an ongoing evolutionary arms race between insect hosts and their microbial symbionts. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-025-02641-4.

Wetlands provide essential ecosystem services in Africa, yet their extent and fragmentation remain poorly understood. Here we classify African wetlands at 10 m resolution, using seasonal composite imagery and a random forest algorithm. We estimate a total wetland area of 947,750 km² (10% of global wetlands), comprising 46% marshes, 25% swamps, 22% peatlands, 5% seasonal wetlands, and 2% mangroves. Wetland fragmentation is strongly associated with high population densities in countries such as Nigeria, Liberia, Guinea, Egypt, Algeria, and Kenya. African wetlands store an estimated 54 ± 11 Gt of carbon, surpassing Europe’s 12–31 Gt. If drained, they could release 260 MtC yr⁻¹, nearly ten times the carbon sequestration of pristine wetlands (27 MtC yr⁻¹). These findings provide a crucial foundation for sustainable wetland management and policy development.

Small‐scale fisheries often lack historical shark and ray catch information, hampering their management. We reconstructed historical catch trends and current fishing pressure by combining local ecological knowledge, satellite‐based vessel counts, and a short‐term landing‐site survey. To test the effectiveness of this method, we focused on the Bijagós Archipelago (Guinea‐Bissau, West Africa), where historical fisheries data are lacking. Benthic rays (stingrays [Dasyatidae] and butterfly rays [Gymnura spp.]), benthopelagic rays (duckbill eagle rays [Aetomylaeus bovinus] and cownose rays [Rhinoptera marginata]), guitarfish (Glaucostegus and Rhinobatos spp.), requiem sharks (Carcharhinidae), and hammerhead sharks (Sphyrna spp.) declined in abundance by 81.5–96.7% (species dependent) from 1960 to 2020. Fishing effort increased annually: fishing trip duration by 42.0% (SE 3.4), numbers of fishing vessels at sea as perceived by fishers by 36.3% (1.0) (1960–2020), and number of vessels by 12.0% (1.1) (2007–2022). We estimated that in 2020, fishing vessels collectively captured 61–264 sharks and 522–2194 rays per day in the archipelago, depending on the proportion of the fishing fleet that was active (i.e., low fleet activity of 18% and high fleet activity of 80%). We advocate for reducing shark and ray catches by regulating fleet size, reinforcing boundaries of protected areas, and collecting fisher‐dependent information on shark and ray landings to safeguard these vulnerable species and coastal livelihoods. We demonstrated the effectiveness of using this 3‐pronged approach to provide baseline data on shark fisheries, a common challenge in areas with small‐scale fisheries and limited research capacity.

Background Minimum Dietary Diversity for Women (MDD-W) has been identified as a promising indicator for monitoring diets globally. MDD-W questionnaires have been integrated into, amongst others, the Demographic and Health Surveys (DHS) and the Gallup World Poll (GWP). Disagreement between estimates of healthy diet metrics for the same country collected in the same year is not desirable. Objectives To determine the measurement agreement of MDD-W estimates collected through DHS and GWP (i.e., precision), to assess the impact of survey characteristics on potential discordance, and to examine the comparative validity of the brief data collection instruments used to estimate MDD-W (i.e., accuracy). Methods Using meta-data from DHS and GWP, we quantified the percentage points (pp) difference in food group consumption and MDD-W prevalence. Furthermore, we qualitatively examined the differences of four survey characteristics: food groups and sentinel foods used in the MDD-W questionnaire, sampling framework, survey timing, and data collection modality. In addition, using data from two non-inferiority studies in Ethiopia – which used either a weighed food record (WFR) or quantitative 24-hour recall (24-HR) as the reference method – we simulated the total magnitude of errors associated with non-quantitative open or list-based 24-HRs, and subsequently compared the pp differences in simulated food group consumption and MDD-W prevalence. Results MDD-W estimates from the GWP were significantly higher than those from the DHS in five of nine country-year sets, one difference was non-significant, and three estimates could not be statistically compared due to lack of reporting on margins of error. The absolute difference between MDD-W estimates from the DHS and GWP were >|5| pp for all country-year sets (range: -17 to + 21 pp). There was poor agreement between the DHS and GWP questionnaires regarding the choice and number of sentinel foods used for each food group in the same country (range: 21 to 65%). In general, GWP data collection covered fewer months and questionnaires were enumerated in fewer languages than the DHS, but the number of sentinel foods used per food group was more standardized across countries. Simulations indicated that the magnitude of errors associated with pilot tested non-quantitative open and extensive list-based 24-HRs were marginally lower than sentinel list-based 24-HRs in Ethiopia. Conclusion For global monitoring, standards must be defined for the preferred data collection instrument and survey platform for each healthy diet metric. This would facilitate cross-country comparability and help mitigate misinterpretations of change over time within countries and the selective reporting of national statistics. A harmonized methodology for developing, pilot testing, and continuously updating sentinel food lists is needed to further improve the accuracy of MDD-W questionnaires.

Climate change and malnutrition are two of the greatest barriers to sustainable development. Yet, to date, they have been considered almost exclusively in isolation of one another. However, climate change and malnutrition are interlinked. For example, in the context of agrifood systems, climate change affects the availability, accessibility, affordability, and quality of food, as well as the health and livelihoods of people, especially the most vulnerable. At the same time, agrifood systems contribute to greenhouse gas emissions, natural resource degradation, and biodiversity loss. Therefore, a great opportunity lies in solutions that can be mutually reinforcing of climate change mitigation and adaptation measures and good nutrition. Evidence shows there are a multitude of integrated actions that demonstrate this potential positive benefit on both climate and nutrition outcomes, yet impact is not guaranteed. This chapter describes how considering joint action to address multiple SDGs, in particular SDG2 and SDG13, can accelerate efforts to achieve sustainable development.

Background Limited universally‐adopted data standards in veterinary medicine hinder data interoperability and therefore integration and comparison; this ultimately impedes the application of existing information‐based tools to support advancement in diagnostics, treatments, and precision medicine. Hypothesis/Objectives A single, coherent, logic‐based standard for documenting breed names in health, production, and research‐related records will improve data use capabilities in veterinary and comparative medicine. Animals No live animals were used. Methods The Vertebrate Breed Ontology (VBO) was created from breed names and related information compiled from the Food and Agriculture Organization of the United Nations, breed registries, communities, and experts, using manual and computational approaches. Each breed is represented by a VBO term that includes breed information and provenance as metadata. VBO terms are classified using description logic to allow computational applications and Artificial Intelligence–readiness. Results VBO is an open, community‐driven ontology representing over 19 500 livestock and companion animal breed concepts covering 49 species. Breeds are classified based on community and expert conventions (e.g., cattle breed) and supported by relations to the breed's genus and species indicated by National Center for Biotechnology Information (NCBI) Taxonomy terms. Relationships between VBO terms (e.g., relating breeds to their foundation stock) provide additional context to support advanced data analytics. VBO term metadata includes synonyms, breed identifiers/codes, and attributed cross‐references to other databases. Conclusion and Clinical Importance The adoption of VBO as a standard for breed names in databases and veterinary electronic health records enhances veterinary data interoperability and computability, supporting precision medicine.

A new method for field evaluation of soybean red crown rot was developed based on the percentage of reddish to black discolored subepidermal area on a root peel (ca 6 cm long, 0.58–0.90 mm thick) from two sites on the primary root (near the soil surface) per plant that had turned. The size of the discolored area on the peel from 61 plants in 2022 and 74 plants in 2023 was positively correlated with the amount of DNA of the pathogen (Calonectria ilicicola) in the peel; thus, the proportion of discolored area was an indicator of the degree of colonization. More than 50% of the peel was discolored on severely colonized plants. We propose a new severity index: No discoloration means no disease, up to 50% discolored means mild disease, and more than 50% means severe disease.

This article presents the first published peatland map for Costa Rica. A probabilistic approach using vegetation, ecosystem, and soil datasets was used to predict the distribution and extent of peatlands found below 700 m in elevation. High-elevation sites found in the Talamanca Mountains were manually identified using satellite imagery; those peatlands are small in size (< 0.05 km²). Our analysis produced an estimated low-elevation peatland extent of 1433 km² and a high-elevation peatland extent of 23.08 km², yielding an estimated total extent of 1456 km² for Costa Rica. This figure falls close to the middle of previously published extent estimates for this country, which vary widely (577–2670 km²). An agreement analysis between previously published maps and this new product is also presented. Plotting the peatland area of Costa Rica in a climate space (mean annual precipitation vs. precipitation seasonality) highlights key climatic differences between our peatland types/regions, hinting at broad-scale effects of climate-landscape interactions. As for the probability map therein, we stress that its accuracy is limited by data availability and quality, as well as ground-referencing information. Still, the new product can provide guidance for land management, policymaking, and future science endeavors. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-025-03126-0.

Species’ traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe. We find three consistent trait differences between locally dominant and rare species across all biomes; dominant species are taller, have softer wood and higher loading on the multivariate stem strategy axis (related to narrow tracheids and thick bark). The difference between traits of dominant and rare species is more strongly driven by temperature compared to water availability, as temperature might affect a larger number of traits. Therefore, climate change driven global temperature rise may have a strong effect on trait differences between dominant and rare tree species and may lead to changes in species abundances and therefore strong community reassembly.

While at the global level, water stress does not seem to present a serious threat to the sustainability of freshwater withdrawal and use, the situation appears much grimmer if a closer look is given to the status of the freshwater resources at basin and sub-basin levels. Unfortunately, such information is often not available to water managers and decision-makers, due both to the scarcity of sufficient data and also to the lack of methods capable of transforming the existing data into usable information. Hence, disaggregating water stress at basin and sub-basin levels is fundamental to provide a finer view of both its causes and effects, allowing the targeting of interventions at areas with high water stress and sectors with high water use. The spatial disaggregation of SDG indicator 6.4.2 by major river basin already implemented at a global scale showed the existence of a water stress belt running across the globe approximately between 10 and 45 degrees north, with a few other areas above and below it. The value of SDG indicator 6.4.2 at the country level is influenced by its size: the larger the country, the more the national average masks local variability. When the disaggregation is performed at sub-basin level, there is the possibility that the same amount of water is counted twice or even more (double counting), as it flows from one sub-basin to the neighbouring ones. Current water accounting methods do not allow this issue to be overcome. This causes an underestimation of water stress and an overestimation of the water resources available for human use in a given area. This paper presents a new methodology to assess SDG indicator 6.4.2 (water stress) seasonally and at the sub-basin level, addressing double counting by factoring in water demands between upstream and downstream sub-basins. This approach supports more informed water management. A corresponding plugin for the WEAP tool was developed, tested in the Senegal River basin countries, and is available online with a user manual in English, French, and Spanish.

Rhizopus microsporus is an opportunistic fungus that causes pneumonia and gastroenteritis in humans. This report describes two cases of mycotic gastritis caused by R. microsporus in Japanese Black calves. They exhibited diarrhea, wasting, and astasia. At necropsy, adhesion was observed between the abomasum and the abdominal wall (No. 1), and between the rumen and the spleen (No. 2). Histopathologically, severe necrosis with many mucoraceous fungi was observed in the abomasum (No. 1) and the rumen (No. 2), with fibrous granulation tissue forming in each adhered region. Molecular analysis identified both fungi as R. microsporus. Thymus hypoplasia was likely a predisposing factor, facilitating infection alongside the injury due to gastric catheter use and complications of white muscle disease.

Here, we aimed to construct a biological saccharification process that combines the steps of enzyme production and enzymatic saccharification using an aerobic fungus Trichoderma reesei, an excellent cellulase producer. Sugar production consists of the growth phase at 28 °C and the saccharification phase at 50 °C. Final sugar yields from alkali-treated rice straw and microcrystalline cellulose using the T. reesei M2-1 strain were greatly affected by mycelial inoculum size and growth phase periods. The optimization of these factors yielded 74.5 % and 60.6 % of sugar from the alkali-treated rice straw and microcrystalline cellulose, respectively, at 120 h of the biological saccharification process. In comparison with the process employing anaerobic microorganisms, a relatively higher yield of sugars was achieved within a shorter period and the use of non-GM fungal strain. However, large variability in sugar yields based on feedstocks suggests imperceptible differences in initial conditions.

Anthrax remains a neglected zoonotic disease of critical public and animal health significance in Zambia, particularly in regions with active human-wildlife-livestock interfaces such as the Western, Southern and Eastern provinces of Zambia. This study explores the socio-ecological drivers of anthrax transmission and examines the role of legal and illegal wildlife trade value chains in sustaining outbreaks. Secondly, the study explores the methodology used to investigate community knowledge, perceptions, and the impacts of anthrax through focus group discussions (FGDs) and a hybrid approach combining traditional thematic analysis with artificial intelligence (AI) tools. The research was framed within the interpretivist paradigm, aiming to understand shared experiences and socio-cultural contexts. The study utilized focus groups to encourage interaction and generate rich, collective insights. The hybrid approach allowed for data analysis that combined researcher-led reflexivity with AI-driven thematic analysis. Findings reveal diverse levels of awareness about anthrax, widespread misconceptions, and the influence of cultural beliefs on health behaviours. Communities linked anthrax outbreaks to interactions with wildlife and the illegal game meat trade, highlighting the complex interplay of ecological, economic, and behavioural factors in disease dynamics. Additionally, the study underscores the socioeconomic toll of anthrax, including livestock losses, disrupted livelihoods, and food insecurity, compounded by inadequate public health and veterinary responses. The insights gained from this research emphasize the need for multi-sectoral interventions tailored to the specific needs of these communities.

Our map represents the first successful large-area fusion of OpenStreetMap and Copernicus data at a spatial resolution of 10 m or finer and can be applied globally. We addressed varying label noise and feature space quality, utilizing artificial intelligence and advanced computing. Our method relies solely on openly available data streams and methods, eliminating training data acquisition or the need for additional expert knowledge for such purpose. We extracted land use labels from OpenStreetMap and remote sensing data to create a contiguous land use map of the European Union as of March 2020. OpenStreetMap tags were translated into land use labels, directly mapping 61.8% of the Union’s area. These labels served as training data for a classification model, predicting land use in remaining areas. Country-specific deep learning convolutional neural networks and Sentinel-2 feature space composites of 2020 at 10 m resolution were employed. The overall map accuracy is 89%, with class-specific accuracies ranging from 77% to 99%. The data set is available for download from https://doi.org/10.11588/data/IUTCDN and visualization at https://osmlanduse.org.

While global efforts to operationalise soil spectroscopy are progressing, cooperation is needed to fully its potential for generating digital soil information to support sustainable soil management worldwide. The Global Soil Laboratory Network's soil spectroscopy initiative (GLOSOLAN-Spec), led by the Food and Agriculture Organization of the United Nations (FAO) through its Global Soil Partnership (GSP), is dedicated to the further development and adoption of soil spectroscopy by fostering international collaboration via a scientific community of practice to produce accurate and reliable soil information for sustainable soil management and decision-making. To support this effort, we, a global consortium of soil scientists under the auspices of the International Union of Soil Sciences (IUSS) and GLOSOLAN-Spec, aim to address seven key challenges hindering the adoption of soil spectroscopy worldwide. Here, we offer perspectives on what is needed to advance soil spectroscopy as a routine soil analysis method, emphasising its potential to generate new and reliable spatial and temporal soil data.

Lactoferrin (LF: also known as lactotransferrin) is a mammalian iron-binding glycoprotein that is highly homologous to serum transferrin (also known as serotransferrin) and egg-white ovalbumin (also known as conalbumin). LF is found in exocrine secretions, such as milk and tears, and is implicated as a host defense protein because of its direct antibacterial (bacteriostatic and bactericidal) and immunomodulatory activities. The antibacterial activity of LF depends in part on its ability to sequester iron ions, which are essential for bacterial growth. The LF molecule consists of two globular domains, termed the N-lobe and the C-lobe. Although the three-dimensional structure of each lobe is highly conserved, and each lobe contains an iron ion binding site, the functional properties of each lobe are not identical. The N-lobe of LF is mainly responsible for its antimicrobial activity by interacting with negatively charged biomolecules. In contrast, the C-lobe exhibits several biological functions of therapeutic interest, such as antiviral activity against influenza A virus and hepatitis C virus, as well as anti-angiogenic, wound healing, and bone anabolic activities. In this review, we provide an overview of the biological roles of LF that are characteristic of its C-lobe, exploring the available structural information on how the C-lobe interacts with target biomolecules and LF receptors.

Onions (Allium cepa L.) accumulate fructans, which are fructose polymers, in their bulbs as reserve carbohydrates and as a source of energy for sprouting. Onions with high fructan content and slow fructan degradation by hydrolysis are considered suitable for long-term storage. We have previously found that ‘Pole Star’ accumulates fewer fructans than ‘Kita-momiji 2000’ in their bulbs. In this study, we attempted to clarify the differences in storage characteristics, fructan content, and fructan metabolizing enzyme activities between the two cultivars during storage. Sprouting was not observed in the bulbs of ‘Kita-momiji 2000’ stored at 15 °C for up to 20 weeks, whereas it was observed in ‘Pole Star’ from around 14 weeks. The fructan content during storage showed a gradual decrease in the inner and outer scales of the bulbs in ‘Kita-momiji 2000’, whereas a rapid decrease was observed in ‘Pole Star’. In the basal plate, the fructan contents in ‘Kita-momiji 2000’ were higher than those in ‘Pole Star’ after 16 weeks of storage. Fructan metabolizing enzyme activities were low and constant in ‘Kita-momiji 2000’, whereas their activities increased in ‘Pole Star’ during storage. The low fructan content of ‘Pole Star’ was thought to be due to the high activity of fructan metabolizing enzymes, but the variation of fructan content was difficult to clearly explain using the balance of fructan hydrolase and synthase activities alone.