Can volatile organic metabolites be used to simultaneously assess microbial and mite contamination level in cereal grains and coffee beans?

A novel approach based on headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-ToFMS) was developed for the simultaneous screening of microbial and mite contamination level in cereals and coffee beans. The proposed approach emerges as a powerful tool for the rapid assessment of the microbial contamination level (ca. 70 min versus ca. 72 to 120 h for bacteria and fungi, respectively, using conventional plate counts), and mite contamination (ca. 70 min versus ca. 24 h). A full-factorial design was performed for optimization of the SPME experimental parameters. The methodology was applied to three types of rice (rough, brown, and white rice), oat, wheat, and green and roasted coffee beans. Simultaneously, microbiological analysis of the samples (total aerobic microorganisms, moulds, and yeasts) was performed by conventional plate counts. A set of 54 volatile markers was selected among all the compounds detected by GC×GC-ToFMS. Principal Component Analysis (PCA) was applied in order to establish a relationship between potential volatile markers and the level of microbial contamination. Methylbenzene, 3-octanone, 2-nonanone, 2-methyl-3-pentanol, 1-octen-3-ol, and 2-hexanone were associated to samples with higher microbial contamination level, especially in rough rice. Moreover, oat exhibited a high GC peak area of 2-hydroxy-6-methylbenzaldehyde, a sexual and alarm pheromone for adult mites, which in the other matrices appeared as a trace component. The number of mites detected in oat grains was correlated to the GC peak area of the pheromone. The HS-SPME/GC×GC-ToFMS methodology can be regarded as the basis for the development of a rapid and versatile method that can be applied in industry to the simultaneous assessment the level of microbiological contamination and for detection of mites in cereals grains and coffee beans

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population