A Comparison of PCA-LDA and PLS-DA Techniques for Classification of Vibrational Spectra

Vibrational spectroscopies provide information about the biochemical and structural environment of molecular functional groups inside samples. Over the past few decades, Raman and infrared-absorption-based techniques have been extensively used to investigate biological materials under different pathological conditions. Interesting results have been obtained, so these techniques have been proposed for use in a clinical setting for diagnostic purposes, as complementary tools to conventional cytological and histological techniques. In most cases, the differences between vibrational spectra measured for healthy and diseased samples are small, even if these small differences could contain useful information to be used in the diagnostic field. Therefore, the interpretation of the results requires the use of analysis techniques able to highlight the minimal spectral variations that characterize a dataset of measurements acquired on healthy samples from a dataset of measurements relating to samples in which a pathology occurs. Multivariate analysis techniques, which can handle large datasets and explore spectral information simultaneously, are suitable for this purpose. In the present study, two multivariate statistical techniques, principal component analysis-linear discriminate analysis (PCA-LDA) and partial least square-discriminant analysis (PLS-DA) were used to analyse three different datasets of vibrational spectra, each one including spectra of two different classes: (i) a simulated dataset comprising control-like and exposed-like spectra, (ii) a dataset of Raman spectra measured for control and proton beam-exposed MCF10A breast cells and (iii) a dataset of FTIR spectra measured for malignant non-metastatic MCF7 and metastatic MDA-MB-231 breast cancer cells. Both PCA-LDA and PLS-DA techniques were first used to build a discrimination model by using calibration sets of spectra extracted from the three datasets. Then, the classification performance was established by using test sets of unknown spectra. The achieved results point out that the built classification models were able to distinguish the different spectra types with accuracy between 93% and 100%, sensitivity between 86% and 100% and specificity between 90% and 100%. The present study confirms that vibrational spectroscopy combined with multivariate analysis techniques has considerable potential for establishing reliable diagnostic models

From Microbial Ecology to Innovative Applications in Food Quality Improvements: the Case of Sourdough as a Model Matrix.

Since millennia, humankind has exploited microbial diversity associated to give foodmatrices in order to obtain fermented foods and beverages, resulting in products with improvedquality and extended shelf life. This topic has received deserved and continuous interest in thescientific community, for the reason of its significance as a driver of innovation in the food and beveragesector. In this review paper, using sourdough as a model matrix, we provide some insights into thefield, testifying the relevance as a transdisciplinary subject. Firstly, we encompassed the prokaryoticand eukaryotic microbial diversity associated with the sourdough ecosystems. The importance ofthis micro-biodiversity in the light of flour-related chemical diversity was examined. Finally, wehighlighted the increasing interest in microbial-based applications oriented toward biocontrol solutionin the field of sourdough-based products (i.e., bread)

Microbial Resources and Innovation in the Wine Production Sector

Microbial starter cultures represent a fundamental level of innovation in the wine sector. Selected yeast strains are routinely used to achieve the needed biomass preparation to accelerate and steer alcoholic fermentation in grape must. The use of starter cultures to induce malolactic fermentation in wine relies on the characterisation and propagation of suitable strains of lactic acid bacteria. Furthermore, the selection of new strains, the renewal of management of microbial resources and new technologies allow continuous improvements in oenology, which may increase the beneficial aspects of wine. In this review, with the aim to stimulate microbial-driven, consumer-oriented advances in the oenological sector, we propose an overview of recent trends in this field that are reported by following the classical separation into 'product innovation' and 'process innovation'. Hence, we shall highlight i) the possible positive innovative impacts of microbial resources on the safety and the sensorial and functional properties of wine (product innovation) and ii) the potential microbial-based improvements allowing the reduction of time/costs and the environmental impacts associated with winemaking (process innovation)

Influence of wind-induced effects on laser disdrometer measurements: Analysis and compensation strategies

Nowadays, laser disdrometers constitute a very appealing tool for measuring surface precipitation properties, by virtue of their capability to estimate not only the rainfall amount and intensity, but also the number, the size and the velocity of falling drops. However, disdrometric measures are affected by various sources of error being some of them related to environmental conditions. This work presents an assessment of Thies Clima laser disdrometer performance with a focus on the relationship between wind and the accuracy of the disdrometer output products. The 10-min average rainfall rate and total rainfall accumulation obtained by the disdrometer are systematically compared with the collocated measures of a standard tipping bucket rain gauge, the FAK010AA sensor, in terms of familiar statistical scores. A total of 42 rainy events, collected in a mountainous site of Southern Italy (Montevergine observatory), are used to support our analysis. The results show that the introduction of a new adaptive filtering in the disdrometric data processing can reduce the impact of sampling errors due to strong winds and heavy rain conditions. From a quantitative perspective, the novel filtering procedure improves by 8% the precipitation estimates with respect to the standard approach widely used in the literature. A deeper examination revealed that the signature of wind speed on raw velocity-diameter spectrographs gradually emerges with the rise of wind strength, thus causing a progressive increase of the wrongly allocated hydrometeors (which reaches 70% for wind speed greater than 8 m s−1). With the aid of reference rain-gauge rainfall data, we designed a second simple methodology that makes use of a correction factor to mitigate the wind-induced bias in disdrometric rainfall estimates. The resulting correction factor could be applied as an alternative to the adaptive filtering suggested by this study and may be of practical use when dealing with disdrometric data processing

Non-Saccharomyces Commercial Starter Cultures: Scientific Trends, Recent Patents and Innovation in the Wine Sector.

For 15 years, non-Saccharomyces starter cultures represent a new interesting segment in the dynamic field of multinationals and national companies that develop and sell microbial-based biotechnological solutions for the wine sector. Although the diversity and the properties of non-Saccharomyces species/strains have been recently fully reviewed, less attention has been deserved to the commercial starter cultures in term of scientific findings, patents, and their innovative appli-cations. Considering the potential reservoir of biotechnological innovation, these issues represent an under-estimated possible driver of coordination and harmonization of research and development activities in the field of wine microbiology. After a wide survey, we encompassed 26 different commercial yeasts starter cultures formulated in combination with at least one non-Saccharomyces strain. The most recent scientific advances have been explored delving into the oenological significance of these commercial starter cultures. Finally, we propose an examination of patent literature for the main yeasts species commercialised in non-Saccharomyces based products. We highlight the presence of asymmetries among scientific findings and the number of patents concerning non-Saccharomyces-based commercial products for oenological purposes. Further in-vestigations on these microbial resources might open new perspectives and stimulate attractive in-novations in the field of wine-making biotechnologies

On-line tracking of the human gut microbial metabolism: high-throughput screening during colonic in-vitro fermentation

The human gut encloses a large community of bacteria producing a wide range of volatile organic compounds (VOCs) when fermenting undigestible substrates. This study aims to provide a high throughput method to study in real-time the gut microbial volatilome when the microbiota process undigestible dietary substrates. Background: Small metabolites from the human gut microbiota are recognized as the intermediates of the microbiome-host cross-talk [1]. The research on the human gut metabolome is mainly based on discrete sampling representing discontinuous ‘snapshot’ of these complex biological systems [2]. The aim of this research work is to enhance the current understanding of the dynamics of the gut microbiota by integrating non-invasive and continuous analytical methods with in-vitro gut simulators, to monitor in real-time, the progression of small molecules released into the headspace [2,3] Methodology: Automated Head space-Solid Phase Micro Extraction coupled with Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) and Static Headspace- Proton Transfer Reaction-Time of Flight-Mass Spectrometry (SHS-PTR-ToF-MS) are used for the purpose of this investigation. The objective is to screen and monitor a specific set of masses of interest, to gain system level mechanistic insights on primary metabolism of the gut microbial consortia. Results: This methodology enabled the continuous monitoring of multiple metabolites in time, including short-chain fatty acids (SCFAs) and medium-chain fatty acids (MCFAs) derived from 24h oat bran fermentation. A mixture of -odd and -even chain acids were co-released into the culture headspace after 4 hours of fermentation and their relative abundance increased in time over 24 hours. The production of multiple MCFAs from the substrate is most likely a community optimization strategy to maximize ATP production from oat degradation by means of reverse beta-oxidation which involves the utilization of fermentation intermediates, such as propanol and acetate. Furthermore, the untargeted screening allowed the detection of low abundant sulfur metabolites, thiophenes, which, to our knowledge, were never investigated before as gut microbial metabolites (GMMs). Conclusion: By integrating non-invasive and continuous analytical methods with an in-vitro gut simulator, it was possible to monitor in real-time the progression of two important class of small molecules released by the microbial consortia into the headspace. The collected information can be jointly integrated to shed light on the dynamics of bacterial foraging of complex undigestible substrates (e.g. bran from cereals). Overall, these results confirm the idea to consider the bacterial headspace as a highly dynamic chemical system that contains information on microbial community behavio