Highly Pathogenic Avian Influenza (HPAI) has risen globally since the early 2000s, causing economic impacts on industries, government, ecosystems, and society. A systematic literature review (SLR) following PRISMA guidelines was conducted to document and quantify the economic and financial impacts of HPAI. Data on economic methods, impact parameters and control strategy assessments were extracted. Impact estimates were converted into 2024 values and expressed as impact per agricultural GDP, per capita and average annual income. A framework categorising impact types was developed and quality was assessed using an adapted Consolidation Health Economic Evaluation Reporting Standards (CHEERS) protocol. Eighty-five papers covering 27 countries and 14 methodological approaches were analysed. Financial losses ranged from $1.14 million in USA, New York (1925) to $3881.87 million in Nigeria (2014-2016), with the later representing 0.43% of agricultural GDP, or $4.14 per person or approximately 280,000 annual incomes. Control strategies evaluated include vaccination, regionalisation, pre-emptive culling, surveillance, trade restrictions and bird housing orders. The framework identifies 135 impact parameters affecting the poultry industry, government, public health, other businesses and environment. Across all sectors direct costs dominate the literature, while direct consequential costs, indirect consequential costs and non-financial impacts remain relatively underexplored. Substantial quality variability was found with critical gaps in data transparency, incomplete costs and lack of standardisation of methods. This framework provides a vital comprehensive structure for future economic assessments, facilitating cross-study comparisons, enabling cost-benefit analyses of control strategies, and supporting more informed policy and investment decisions.
As a first attempt, this study evaluated the application of dielectric barrier discharge ionization high-resolution mass spectrometry (DBDI-HRMS) for the rapid volatilomic characterization of goat cheese, achieving a reliable analysis within a few seconds. Specifically, volatile profiles were determined by DBDI-HRMS in soft and semihard cheeses from lactating Murciano-Granadina goats fed ensiled white grape pomace (WGP) or black grape pomace (BGP) by-products as partial replacements for alfalfa hay in the control (CTR) diet. Following the volatilomic acquisition, a non-parametric ANOVA was performed to identify significant differences in aroma-related compounds. Compared to CTR-cheeses, the WGP- and BGP-cheeses exhibited the most pronounced variations in volatile organic compounds (VOCs), especially after 30 and 60 days of ripening. The main differences were in aldehydes and ketones, i.e., pentanal/methylbutanal, pentanone/methylbutanal, and methylhexanal/heptanone. Significant changes were also observed in branched-chain fatty acids and related esters, i.e., methylnonanoic acid/methylethyl heptanoic acid and ethyl decanoate/isobutyl octanoate. The CTR-cheeses were characterized instead by a higher relative abundance of specific VOCs, i.e., nonenal/nonadienol and dimethyl-pentenoic acid/ heptenoic acid. Overall, this trial proved DBDI-HRMS to be a promising rapid and high-throughput technology for detecting changes in odor-active compounds across cheese ripening. Additionally, it highlighted that recycled winery biomass into goat diet seems to modulate the cheese volatilomic profile, likely due to the biomass reshaping microbial-driven metabolic pathways, which effects were particularly evident in the intermediate and late ripening stages.
Highly pathogenic avian influenza A(H5N1) viruses of clade 2.3.4.4b continue to spread globally, causing major outbreaks in wild birds and poultry. In Africa, however, genomic data remain limited, restricting understanding of viral introduction routes and circulation patterns. Here, we report the whole-genome characterisation of an HPAI A(H5N1) virus detected in a common tern (Sterna hirundo) found dead on the Namibian coast during the most recent avian influenza outbreak recorded in the country. Viral RNA was subjected to whole-genome sequencing using the Illumina Viral Surveillance Panel v2 on a NextSeq 1000 platform. Complete or near-complete sequences were obtained for all eight genome segments and deposited in GenBank. Phylogenetic analyses, performed using African clade 2.3.4.4b H5Nx sequences and the closest related sequences identified through database searches, showed that the Namibian virus belonged to clade 2.3.4.4b and clustered within the EA-2024-DI.2 subgenotype. Across all segments, the virus grouped with contemporary European EA-2024-DI.2 viruses circulating during the 2024-2025 epidemic wave, supporting a likely Eurasian origin. For six of the eight segments, it also clustered closely with an EA-2024-DI.2 virus detected in a gull-billed tern in Uganda in December 2024. Molecular analysis identified a polybasic haemagglutinin cleavage site consistent with high pathogenicity and a mutational profile broadly similar to contemporary EA-2024-DI.2 viruses. The HA substitution, associated in previous studies with increased binding to mammalian-type α2-6 receptors, may warrant further investigation. These findings highlight the role of migratory seabirds in H5N1 dissemination and reinforce the need for strengthened genomic surveillance in African wild birds and poultry.
The European Council adopted Directive 2024/1434 to strengthen the market standards for honey and improve the labelling. To combat honey fraud, the council recommended intensified controls and innovative methods to detect honey adulteration and mislabeling. To this aim, analytical capabilities of head space gas chromatography ion mobility spectrometry (HS-GC-IMS) were explored. Specifically, we sought to ascertain whether HS-GC-IMS, when combined with statistics, serves as a practical option for verifying the floral origin of Italian monofloral honey. We directly analyzed a total of 136 Italian monofloral honeys, harvested in 2022 and 2023, from seven floral sources (acacia, dandelion, chestnut, rhododendron, citrus, sunflower, and linden). The samples were previously authenticated by the combination of sensory analysis and physiochemical assessments. The preprocessed data were submitted to principal component analysis (PCA) for an explorative assessment of the HS-GC-IMS discriminant capabilities. Afterwards, the PLS-DA based-machine learning classifier achieved 93.10%, 90.0%, and 98.75% for accuracy, sensitivity, and specificity, respectively.Finally, the most distinct volatiles in each monofloral honey were annotated using headspace solid-phase microextraction gas chromatography ion mobility spectrometry and mass spectrometry prototype (HS-SPME-GC-IMS-MS). This new prototype with dual-detection systems is reported herein for the first time to annotate the volatile organic compounds of different monofloral honey.These results proved i) the potential utility of this synergistic hybrid approach, employing HS-GC-IMS as an analytical tool coupled to machine learning based categorization, that captures the aroma of the honey for authentication purposes; ii) the pioneering capability of HS-SPME-GC-IMS-MS to successfully annotate volatile compounds of honey.
Progress in treating oomycete infections of animals has been slow. Much relevant biological and therapeutic knowledge originates from plant pathology and agricultural science, while medical and veterinary literature develops independently. This review integrates these fields to highlight key knowledge gaps and translational opportunities in animal health. Oomycetes are eukaryotic Stramenopiles, distinct from true fungi; their hyphae are diploid and coenocytic, with cellulose and glucan cell walls. They reproduce via motile zoospores and durable oospores, enabling environmental persistence. Although best known as plant pathogens, Pythium insidiosum and Lagenidium spp. infect mammals, while Aphanomyces astaci and A. invadans cause serious disease in crustaceans and fish. Infection begins when zoospores enter damaged skin or mucosa, inducing eosinophil-rich pyogranulomatous inflammation before extending into deeper tissues and vessels. Host responses are often ineffective because oomycetes skew immunity toward a non-protective Th2 pathway. Standard antifungal agents have limited efficacy due to the absence of ergosterol. Management relies on surgical resection supported by antimicrobial and immunomodulatory therapy. Prognosis is guarded in dogs but more favourable in cats and horses, with immunotherapy providing benefit, especially in equine cases. Emerging strategies include agricultural biocides such as metalaxyl-M, nanoparticle drug delivery, hyperbaric oxygen therapy and the potential use of cyazofamid, which has yet to be evaluated in animals. Diagnosis involves histopathology, culture on selective media, MALDI-TOF testing and PCR with sequencing. Oomycete infections lie at the interface of plant pathology, veterinary medicine, aquaculture, immunology and mycology. Cross-disciplinary research is essential to improve diagnostic and therapeutic options for these neglected pathogens.
