The rise of large language models (LLMs) has sparked debates over their environmental impacts, with some studies suggesting they have a high carbon footprint, while others claim they can promote sustainability.
A comparative analysis shows that LLMs can have a lower environmental impact than human labor, especially in the U.S., with certain LLMs being significantly more efficient in terms of energy, carbon emissions, and costs.
Despite the potential benefits of using LLMs over human workers, economic and practical considerations likely mean a combination of both in the workforce, and further research is needed to assess the long-term sustainability of increasingly larger LLMs.
- Human norovirus (HuNoV) is the leading cause of acute gastroenteritis, and traditional rapid tests for it have low sensitivity and can't quantify virus levels effectively.
- A new technique combining immunomagnetic enrichment (IM) with lateral flow immunochromatography (LFIC) was developed to enhance detection, achieving a limit of detection of 1.56 × 10 copies/mL and accurately identifying common HuNoV genotypes without cross-reacting with other viruses.
- Testing 87 fecal samples demonstrated that the new IM-LFIC method had a high agreement with RT-qPCR results, indicating its potential as a rapid and sensitive option for point-of-care testing for HuNoV. *
Tuberculosis (TB) is a common infectious disease caused by Mycobacterium tuberculosis (M.tb), and macrophages serve as the primary natural host of M.tb.