Could the aroma of spices produce a cross-modal enhancement of food saltiness and contribute to reducing salt intake?

BACKGROUND: As a result of its correlation with cardiovascular diseases, salt intake must be reduced. According to multi-sensory integration, aroma plays an important role in saltiness enhancement; this could enable a food's salt content to be reduced without losing acceptance. We therefore studied the effect of three spices, Curcuma longa, Laurus nobilis L. and Petroselinum crispum L., on saltiness enhancement through sensory tests on consumers. This was followed by olfactometric analysis with the aim of relating the effect to the spices' aromatic composition. RESULTS: According to the odour-induced salty taste enhancement (OISE) mean values, bay leaf and turmeric had the highest effect on saltiness enhancement, at a similar level to dry-cured ham aroma, wherwas parsley had a significantly lower OISE value. Only one odour-active compound (OAC), eugenol, showed a direct correlation with the spices' OISE values. Turmeric primarily had OACs with sweet aroma, whereas bay leaf had more OACs belonging to the spicy-aroma category. CONCLUSION: The three spices, turmeric, bay leaf and parsley, investigated in the present study appear to enhance the salty taste of mashed potato with a low salt content. The results suggest that an interaction effect among OACs with different aromatic ranges may exist. Therefore, when the global OAC modified frequency value, grouped according to aroma range, was considered, the sweet range appears to counteract the effect of the spicy aroma on saltiness. © 2024 Society of Chemical Industry.

Use of Linear Ion Traps in Data-Independent Acquisition Methods Benefits Low-Input Proteomics.

The need for a better understanding of cellular heterogeneity has pushed mass spectrometry technologies to the analysis of single-cell and single-cell-type proteomes, although several challenges still limit their widespread implementation. Among the efforts toward single-cell and low-input analyses, there is the adoption of data-independent acquisition methods to increase analytical sensitivity. Here, we revisited the use of linear ion traps mass analyzers in data-independent acquisition methods and demonstrate their benefits to boost peptide and protein identifications in low-input proteomes.

QCloud2: An Improved Cloud-based Quality-Control System for Mass-Spectrometry-based Proteomics Laboratories.

QCloud is a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, and automated data processing. Since its release, QCloud has facilitated automated quality control for proteomics experiments in many laboratories. QCloud provides a quick and effortless evaluation of instrument performance that helps to overcome many analytical challenges derived from clinical and translational research. Here we present an improved version of the system, QCloud2. This new version includes enhancements in the scalability and reproducibility of the quality-control pipelines, and it features an improved front end for data visualization, user management, and chart annotation. The QCloud2 system also includes programmatic access and a standalone local version.

Isotopologue Multipoint Calibration for Proteomics Biomarker Quantification in Clinical Practice.

Targeted proteomics has become the method of choice for biomarker validation in human biopsies due to its high sensitivity, reproducibility, accuracy, and precision. However, for targeted proteomics to be transferred to clinical routine there is the need to reduce its complexity, make its procedures simpler, increase its throughput, and improve its analytical performance. Here we present the Isotopologue Multipoint Calibration (ImCal) quantification strategy, which uses a mix of isotopologue peptides to generate internal multipoint calibration curves for each individual sample and to accurately quantify biomarker peptides in clinical applications without the need of expert supervision. ImCal relies on the use of five different isotopically-labelled peptides of different nominal mass mixed at different concentrations to be used as an internal calibration curve for each endogenous peptide. The use of internal multipoint calibration curves is well-suited for the generation of ready-to-use biomarker kits for clinical applications as it is compatible with both high- and low-resolution mass spectrometers and different levels of endogenous peptide, it eliminates the need for blank matrixes required in external curves, it allows the evaluation of matrix effects and the valid quantification range in each individual sample, and it does not require expert adjustment. We used the ImCal method to quantify HER2 in 35 breast cancer formalin-fixed paraffin-embedded patient samples, revealing a high degree of heterogeneity among patients, which contrasts with the homogeneous immunohistochemistry patient classification. Our work illustrates how an improvement of mass spectrometry methods for biomarker quantification can provide fine-grain patient stratification, and thus better disease diagnostic and prognosis.

QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories.

The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0.