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This paper focuses on the role of fertilizers within regional nutrient cycles. Bio-based fertilizers can contribute to regional nutrient circularity, but the question remains whether production and consumption of bio-based fertilizers is beneficial to the farmer and the environment. Therefore, both farmers' private costs and environmental externalities should be taken into account. We formulate a farm-level multi-objective optimization model by considering a range of fertilizers, their costs and the environmental consequences associated with their production and use. The cost-minimization approach is applied to a conceptualized Flemish leek farmer aiming to safeguard nutrient uptake while being constrained by nutrient standards and the availability of on-farm residues. Our results suggest that mineral fertilizers have an important role in the fertilizer mix despite their environmental externalities. Nevertheless, there is also a role for bio-based fertilizers. These results have implications for farmers and policymakers wishing to internalize fertilizer externalities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Diseases caused by Capripoxviruses (CaPVs) are of great economic importance in sheep, goats, and cattle. Since CaPV strains are serologically indistinguishable and genetically highly homologous, typing of closely related strains can only be achieved by whole-genome sequencing. In this chapter, we describe a robust, cost-effective, and widely applicable protocol for reconstructing (nearly) complete CaPV genomes directly from clinical samples or commercial vaccine batches in less than a week. Taking advantage of the genetic similarity of CaPVs, a set of pan-CaPVs long-range PCRs was developed that covers the entire genome with only a limited number of tiled amplicons. The resulting amplicons can be sequenced on all currently available high-throughput sequencing platforms. As an example, we have included a detailed protocol for performing nanopore sequencing and a pipeline for assembling the resulting tiled amplicon data., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Importance: Lumpy skin disease virus (LSDV) has a complex epidemiology involving multiple strains, recombination, and vaccination. Its DNA genome provides limited genetic variation to trace outbreaks in space and time. Sequencing of LSDV whole genomes has also been patchy at global and regional scales. Here, we provide the first fine-grained whole genome sequence sampling of a constrained LSDV outbreak (southeastern Europe, 2015-2017), which we analyze along with global publicly available genomes. We formally evaluate the past occurrence of recombination events as well as the temporal signal that is required for calibrating molecular clock models and subsequently conduct a time-calibrated spatially explicit phylogeographic reconstruction. Our study further illustrates the importance of accounting for recombination events before reconstructing global and regional dynamics of DNA viruses. More LSDV whole genomes from endemic areas are needed to obtain a comprehensive understanding of global LSDV dispersal dynamics., Competing Interests: The authors declare no conflict of interest.

Importance: Democratizing artificial intelligence (AI) enables model development by clinicians with a lack of coding expertise, powerful computing resources, and large, well-labeled data sets., Objective: To determine whether resource-constrained clinicians can use self-training via automated machine learning (ML) and public data sets to design high-performing diabetic retinopathy classification models., Design, Setting, and Participants: This diagnostic quality improvement study was conducted from January 1, 2021, to December 31, 2021. A self-training method without coding was used on 2 public data sets with retinal images from patients in France (Messidor-2 [n = 1748]) and the UK and US (EyePACS [n = 58 689]) and externally validated on 1 data set with retinal images from patients of a private Egyptian medical retina clinic (Egypt [n = 210]). An AI model was trained to classify referable diabetic retinopathy as an exemplar use case. Messidor-2 images were assigned adjudicated labels available on Kaggle; 4 images were deemed ungradable and excluded, leaving 1744 images. A total of 300 images randomly selected from the EyePACS data set were independently relabeled by 3 blinded retina specialists using the International Classification of Diabetic Retinopathy protocol for diabetic retinopathy grade and diabetic macular edema presence; 19 images were deemed ungradable, leaving 281 images. Data analysis was performed from February 1 to February 28, 2021., Exposures: Using public data sets, a teacher model was trained with labeled images using supervised learning. Next, the resulting predictions, termed pseudolabels, were used on an unlabeled public data set. Finally, a student model was trained with the existing labeled images and the additional pseudolabeled images., Main Outcomes and Measures: The analyzed metrics for the models included the area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, and F1 score. The Fisher exact test was performed, and 2-tailed P values were calculated for failure case analysis., Results: For the internal validation data sets, AUROC values for performance ranged from 0.886 to 0.939 for the teacher model and from 0.916 to 0.951 for the student model. For external validation of automated ML model performance, AUROC values and accuracy were 0.964 and 93.3% for the teacher model, 0.950 and 96.7% for the student model, and 0.890 and 94.3% for the manually coded bespoke model, respectively., Conclusions and Relevance: These findings suggest that self-training using automated ML is an effective method to increase both model performance and generalizability while decreasing the need for costly expert labeling. This approach advances the democratization of AI by enabling clinicians without coding expertise or access to large, well-labeled private data sets to develop their own AI models.

Ensuring global food security and environmental sustainability is dependent upon the contribution of the world's hundred million smallholder farms, but the contributions of smallholder farms to global agricultural greenhouse gas (GHG) emissions have been understudied. We developed a localized agricultural life cycle assessment (LCA) database to calculate GHG emissions and made the first extensive assessment of the smallholder farms' GHG emission reduction potentials by coupling crop and livestock production (CCLP), a redesign of current practices toward sustainable agriculture in China. CCLP can reduce the GHG emission intensity by 17.67%, with its own feed and manure returning to the field as an essential path. Scenario analysis verified that greater GHG emission reduction (28.09%-41.32%) will be achieved by restructuring CCLP. Therefore, this mixed farming is a mode with broader benefits to provide sustainable agricultural practices for reducing GHG emissions fairly., Competing Interests: The authors declare no competing interests., (© 2023 The Author(s).)

The high economic impact and zoonotic potential of avian influenza call for detailed investigations of dispersal dynamics of epidemics. We integrated phylogeographic and epidemiologic analyses to investigate the dynamics of a low pathogenicity avian influenza (H3N1) epidemic that occurred in Belgium during 2019. Virus genomes from 104 clinical samples originating from 85% of affected farms were sequenced. A spatially explicit phylogeographic analysis confirmed a dominating northeast to southwest dispersal direction and a long-distance dispersal event linked to direct live animal transportation between farms. Spatiotemporal clustering, transport, and social contacts strongly correlated with the phylogeographic pattern of the epidemic. We detected only a limited association between wind direction and direction of viral lineage dispersal. Our results highlight the multifactorial nature of avian influenza epidemics and illustrate the use of genomic analyses of virus dispersal to complement epidemiologic and environmental data, improve knowledge of avian influenza epidemiologic dynamics, and enhance control strategies.

From 2017 to 2019, several vaccine-like recombinant strains of lumpy skin disease virus (LSDV) were discovered in Kazakhstan and neighbouring regions of Russia and China. Shortly before their emergence, the authorities in Kazakhstan launched a mass vaccination campaign with the Neethling-based Lumpivax vaccine. Since none of the other countries in the affected region had used a homologous LSDV vaccine, it was soon suspected that the Lumpivax vaccine was the cause of these unusual LSDV strains. In this study, we performed a genome-wide molecular analysis to investigate the composition of two Lumpivax vaccine batches and to establish a possible link between the vaccine and the recent outbreaks. Although labelled as a pure Neethling-based LSDV vaccine, the Lumpivax vaccine appears to be a complex mixture of multiple CaPVs. Using an iterative enrichment/assembly strategy, we obtained the complete genomes of a Neethling-like LSDV vaccine strain, a KSGP-like LSDV vaccine strain and a Sudan-like GTPV strain. The same analysis also revealed the presence of several recombinant LSDV strains that were (almost) identical to the recently described vaccine-like LSDV strains. Based on their InDel/SNP signatures, the vaccine-like recombinant strains can be divided into four groups. Each group has a distinct breakpoint pattern resulting from multiple recombination events, with the number of genetic exchanges ranging from 126 to 146. The enormous divergence of the recombinant strains suggests that they arose during seed production. The recent emergence of vaccine-like LSDV strains in large parts of Asia is, therefore, most likely the result of a spillover from animals vaccinated with the Lumpivax vaccine.

May-Thurner syndrome (MTS) is an anatomical variant that results in compression of the left common iliac vein by the right common iliac artery. Although often asymptomatic, lower extremity swelling/edema, deep venous thrombosis, post-thrombotic syndrome, and eventual lymphedema (due to long-standing venous obstruction) can develop. The clinical management of patients presenting for lymphedema surgery with concomitant or undiagnosed MTS is not well described., Methods: This review investigates two patients who were evaluated for unilateral lower extremity lymphedema, both of whom were subsequently diagnosed with MTS. Standard imaging (including lymphoscintigraphy, indocyanine green lymphangiography, and magnetic resonance venography) were performed to identify proximal venous obstruction. Treatment was accomplished using vascular surgical management, including stenting of the iliac vein before lymphedema reconstruction with vascularized lymph node transfer and multiple lymphovenous bypass., Results: Both patients we examined in this review had improvement of lymphedema with vascular surgical management. Literature review reveals that MTS has an incidence as high as 20% in the population, although commonly unidentified due to lack of symptomatology., Conclusions: There are no studies documenting the incidence of MTS in patients referred for lymphedema surgical management. Routine studies should be obtained to screen for proximal venous obstruction in patients presenting for surgical management of lower extremity lymphedema. Additional research is needed regarding the approach to managing patients with both MTS and lymphedema. Careful observational and prospective studies may elucidate the appropriate time interval between venous stenting and lymphedema microsurgical reconstruction., (Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of The American Society of Plastic Surgeons.)

The diseases caused by capripoxviruses (CaPVs) are of major economic concern in sheep, goat and cattle as they are inexorably spreading into non-endemic regions. As CaPV strains are serologically indistinguishable and genetically highly homologous, typing closely related strains can only be achieved by whole genome sequencing. Unfortunately the number of publicly available genomes remains low as most sequencing methods rely on virus isolation. Therefore, we developed a robust, cost-effective and widely applicable method that allows to generate (nearly) complete CaPV genomes directly from clinical samples or commercial vaccine batches. A set of pan-CaPVs long-range PCRs spanning the entire genome was designed to generate PCR amplicons that can be sequenced on commonly used high-throughput sequencing platforms: MiSeq (Illumina), RSII (PacBio) and MinION (Oxford Nanopore Technologies). The robustness of the LR-PCR strategy was evaluated for all 3 members of CaPV directly from a variety of samples, including clinical samples (N = 7), vaccine batches (N = 6), and virus isolates (N = 2). The sequencing method described here allows to reconstruct (nearly) complete CaPV genomes in less than a week and will aid researchers studying closely-related CaPV strains worldwide., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Lumpy skin disease virus (LSDV) causes a severe, systemic, and economically important disease in cattle. Here, we report coding-complete sequences of recombinant LSDVs from four outbreaks in October and November 2020 in northeastern Vietnam.

Porcine reproductive and respiratory syndrome virus (PRRSV) is the causative agent of one of the most widespread and economically devastating diseases in the swine industry. Typing circulating PRRSV strains by means of sequencing is crucial for developing adequate control strategies. Most genetic studies only target the highly variable open reading frame (ORF) 5, for which an extensive database is available. In this study, we performed whole-genome sequencing (WGS) on a collection of 124 PRRSV-1 positive serum samples that were collected over a 5-year period (2015-2019) in Belgium. Our results show that (nearly) complete PRRSV genomes can be obtained directly from serum samples with a high success rate. Analysis of the coding regions confirmed the exceptionally high genetic diversity, even among Belgian PRRSV-1 strains. To gain more insight into the added value of WGS, we performed phylogenetic cluster analyses on separate ORF datasets as well as on a single, concatenated dataset (CDS) containing all ORFs. A comparison between the CDS and ORF clustering schemes revealed numerous discrepancies. To explain these differences, we performed a large-scale recombination analysis, which allowed us to identify a large number of potential recombination events that were scattered across the genome. As PRRSV does not contain typical recombination hot-spots, typing PRRSV strains based on a single ORF is not recommended. Although the typing accuracy can be improved by including multiple regions, our results show that the full genetic diversity among PRRSV strains can only be captured by analysing (nearly) complete genomes. Finally, we also identified several vaccine-derived recombinant strains, which once more raises the question of the safety of these vaccines.

Infectious bronchitis virus (IBV, genus Gammacoronavirus) causes an economically important and highly contagious disease in chicken. Random primed RNA sequencing was applied to two IBV positive clinical samples and one in ovo-passaged virus. The virome of a cloacal swab pool was dominated by IBV (82% of viral reads) allowing de novo assembly of a GI-13 lineage complete genome with 99.95% nucleotide identity to vaccine strain 793B. In addition, substantial read counts (16% of viral reads) allowed the assembly of a near-complete chicken astrovirus genome, while lower read counts identified the presence of chicken calicivirus and avian leucosis virus. Viral reads in a respiratory/intestinal tissue pool were distributed between IBV (22.53%), Sicinivirus (Picornaviridae, 24%), and avian leucosis virus (37.04%). A complete IBV genome with 99.95% nucleotide identity to vaccine strain H120 (lineage GI-1), as well as a near-complete avian leucosis virus genome and a partial Sicinivirus genome were assembled from the tissue sample data. Lower read counts identified chicken calicivirus, Avibirnavirus (infectious bursal disease virus, assembling to 98.85% of segment A and 69.66% of segment B closely related to D3976/1 from Germany, 2017) and avian orthoreovirus, while three avian orthoavulavirus 1 reads confirmed prior real-time RT-PCR result. IBV sequence variation analysis identified both fixed and minor frequency variations in the tissue sample compared to its in ovo-passaged virus. Metagenomic methods allow the determination of complete coronavirus genomes from clinical chicken samples while providing additional insights in RNA virus sequence diversity and coinfecting viruses potentially contributing to pathogenicity., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)