Resolution of Historically Discordant Ames Test Negative / Rodent Carcinogenicity Positive N-nitrosamines using a Sensitive, OECD-aligned Design.

The in vitro Bacterial Reverse Mutation (Ames) Test is crucial for evaluating the mutagenicity of pharmaceutical impurities. For N-nitrosamines (NAs) historical data indicated that for certain members of this chemical class the outcomes of the Ames Test did not correlate with their associated rodent carcinogenicity outcomes. This has resulted in negative outcomes in an OECD aligned Ames Test alone (standard or enhanced) no longer being considered sufficient by regulatory authorities to assess potential carcinogenic risk of NAs if present as impurities in drug products.

Vascular complications after a multiligament knee reconstruction: A case report highlighting the role of preoperative imaging.

Vascular injuries are serious complications of multiligament knee injuries and can result in catastrophic outcomes. These injuries can range from intimal flaps with no compromise of the distal perfusion to a complete occlusion or transection requiring emergent vascular intervention. Several diagnostic tests, including the measurement of the ankle-brachial index (ABI), conventional angiography, and computed tomography angiography (CTA), are commonly used as diagnostic tools to identify vascular injuries in the context of a multiligament knee injury.

Treatment of latent tuberculosis infection in migrants in primary care secondary care.

Background: Control of latent tuberculosis infection (LTBI) is a priority in the World Health Organization strategy to eliminate TB. Many high-income, low TB incidence countries have prioritised LTBI screening and treatment in recent migrants. We tested whether a novel model of care, based entirely within primary care, was effective and safe compared to secondary care.

Should my recommendation letter be written by artificial intelligence?

Letters of recommendation are increasingly important for the residency match. We assessed whether an artificial intelligence (AI) tool could help in writing letters of recommendation by analyzing recommendation letters written by 3 academic staff and AI duplicate versions for 13 applicants. The preferred letters were selected by 3 blinded orthopedic program directors based on a pre-determined set of criteria.