A dynamic framework for calculating the biomass of fattening pigs with an application in estimating the burden of porcine reproductive and respiratory syndrome in the Netherlands.

Gaining insight into the size and composition of national pig populations can support decisions on disease control, welfare, and environmental sustainability. However, if one needs to draw meaningful comparisons between the performance of various production systems or countries, a method for standardization is required. One approach to achieve this is by means of biomass estimation.

Economic assessment of animal disease burden in Senegalese small ruminants.

Small ruminant production in sub-Saharan Africa is limited by a range of constraints, including animal health issues. This study aimed at estimating the impact of these issues on the small ruminant production in Senegal in a holistic manner, using an approach developed by the Global Burden of Animal Diseases (GBADs) programme. The estimation focused on the mixed crop-livestock system, representing a large proportion (>60 %) of the small ruminant population in the country.

Case report: Single gene testing and comprehensive genomic profiling in non-small cell lung cancer-a case series of divergent results from a large reference laboratory.

Clinical management of non-small cell lung cancer (NSCLC) requires accurate identification of tumor-specific genetic alterations to inform treatment options. Historically, providers have relied on single-gene testing (SGT) for actionable variants due to a perception of cost-effectiveness and/or efficient turnaround time compared to next-generation sequencing (NGS). However, not all actionable variants may be evaluated through SGT modalities, and an SGT approach can exhaust valuable tissue needed for more comprehensive analyses.

Using priorities between human and livestock bacterial antimicrobial resistance (AMR) to identify data gaps in livestock AMR surveillance.

Background: Bacterial antimicrobial resistance (AMR) is a global threat to both humans and livestock. Despite this, there is limited global consensus on data-informed, priority areas for intervention in both sectors. We compare current livestock AMR data collection efforts with other variables pertinent to human and livestock AMR to identify critical data gaps and mutual priorities.