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Intense label-free surface-enhanced Raman scattering (SERS) spectra of serum samples were rapidly obtained on Ag plasmonic paper substrates upon 785 nm excitation. Spectra from the hepatocellular carcinoma (HCC) patients showed consistent differences with respect to those of the control group. In particular, uric acid was found to be relatively more abundant in patients, while hypoxanthine, ergothioneine, and glutathione were found as relatively more abundant in the control group. A repeated double cross-validation (RDCV) strategy was applied to optimize and validate principal component analysis-linear discriminant analysis (PCA-LDA) models. An analysis of the RDCV results indicated that a PCA-LDA model using up to the first four principal components has a good classification performance (average accuracy was 81%). The analysis also allowed confidence intervals to be calculated for the figures of merit, and the principal components used by the LDA to be interpreted in terms of metabolites, confirming that bands of uric acid, hypoxanthine, ergothioneine, and glutathione were indeed used by the PCA-LDA algorithm to classify the spectra. Supplementary Information The online version contains supplementary material available at 10.1007/s00216-020-03093-7.

COVID-19 is a global threat that has spread since the end of 2019, causing severe clinical sequelae and deaths, in the context of a world pandemic. The infection of the highly pathogenetic and infectious SARS-CoV-2 coronavirus has been proven to exert systemic effects impacting the metabolism. Yet, the metabolic pathways involved in the pathophysiology and progression of COVID-19 are still unclear. Here, we present the results of a mass spectrometry-based targeted metabolomic analysis on a cohort of 52 hospitalized COVID-19 patients, classified according to disease severity as mild, moderate, and severe. Our analysis defines a clear signature of COVID-19 that includes increased serum levels of lactic acid in all the forms of the disease. Pathway analysis revealed dysregulation of energy production and amino acid metabolism. Globally, the variations found in the serum metabolome of COVID-19 patients may reflect a more complex systemic perturbation induced by SARS-CoV-2, possibly affecting carbon and nitrogen liver metabolism.

The quantification of cranial sexual dimorphism (CSD) among modern humans is relevant in evolutionary studies of morphological variation and in a forensic context. Despite the abundance of quantitative studies of CSD, few have specifically examined intra-sex variability. Here we quantify CSD in a geographically homogeneous sample of adult crania, which includes Italian individuals from the 19th and 20th centuries. Cranial morphology is described with 92 3D landmarks analyzed using Procrustean geometric morphometrics (PGMM). Size and shape variables are used to compare morphological variance between sexes in the whole cranium and four individual regions. The same variables, plus Procrustes form, are used to quantify average sex differences and explore classification accuracy. Our results indicate that: (a) as predicted by Wainer's rule, males present overall more variance in size and shape, albeit this is statistically significant only for total cranial size; (b) differences between sexes are dominated by size and to a lesser extent by Procrustes form; (c) shape only accounts for a minor proportion of variance; (d) the cranial base shows almost no dimorphism for shape; and (e) facial Procrustes form is the most accurate predictor of skeletal sex. Overall, this study suggests developmental factors underlying differences in CSD among cranial regions; stresses the need for population-specific models that describe craniofacial variation as the basis for models that facilitate the estimation of sex in unidentified skeletal remains; and provides one of the first confirmations of "Wainer's rule" in relation to sexual dimorphism in mammals specific to the human cranium.

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Beer is a popular alcoholic beverage worldwide, traditionally made from water, barley and hop (Humulus lupulus L.) strobili. The strobili contain lupulin glands whose components (mostly bitter acids and polyphenols) confer unique and locally different flavours to beer types. It is therefore relevant for brewers and consumers to precisely know the geographical origin of hop plants used for high-quality beer. Hop plants belonging to the variety Hallertau Perle, grown in two locations, Cavalese and Imèr, of the Trentino Region (Italy) were analysed to establish a direct relationship between the chemical elements detected in soil and in plant parts. Chemical elements were determined by X-ray fluorescence and inductively coupled plasma mass spectrometry in soil, leaf and strobili samples from Cavalese and Imèr. The data from the two areas were compared by a nonparametric test (Mann-Whitney) and multivariate statistics (principal component analysis and partial least squares discriminant analysis). The geochemical characterization and the statistical analyses showed different concentrations of major and trace elements in soil and plant parts from the two areas. A reliable correlation could be established between some elements in soil and strobili samples, that is Nb, Fe, Rb and Zr for Cavalese and Mg, Ni, Zn and Zr for Imèr. These elements could therefore be used as geochemical fingerprints to identify the geographical origin of strobili from the two study areas, an approach useful to verify the origin of hop plants for the production of high-quality beer.

BACKGROUNDEcuador exports two major types of cocoa beans, the highly regarded and lucrative National, known for its fine aroma, and the CCN-51 clone type, used in bulk for mass chocolate products. In order to discourage exportation of National cocoa adulterated with CCN-51, a fast and objective methodology for distinguishing between the two types of cocoa beans is needed.RESULTSThis study reports a methodology based on computer vision, which makes it possible to recognize these beans and determine the percentage of their mixture. The methodology was challenged with 336 samples of National cocoa and 127 of CCN-51. By excluding the samples with a low fermentation level and white beans, the model discriminated with a precision higher than 98%. The model was also able to identify and quantify adulterations in 75 export batches of National cocoa and separate out poorly fermented beans.CONCLUSIONA scientifically reliable methodology able to discriminate between Ecuadorian National and CCN-51 cocoa beans and their mixtures was successfully developed. (c) 2017 Society of Chemical Industry

Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination statistics in censored survival data.To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s).We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration.The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were substantially smaller than unadjusted values. The study-specific standard deviation of baseline age was strongly associated with the unadjusted C-index and D-index but not significantly associated with the age-adjusted indices.The proposed estimators improve meta-analysis comparisons, are easy to implement and give a more meaningful clinical interpretation.? 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

20 pages, 6 figures, 5 tables, supporting information https://dx.doi.org/10.1371/journal.pone.0160678.-- We have obtained the GenBank Accession numbers for all the sequences used in the work (GenBank from KX051564 to KX051577 and from KX002245 to KX002255), Gorgonian species show a high morphological variability in relation to the environment in which they live. In coastal areas, parameters such as temperature, light, currents, and food availability vary significantly with depth, potentially affecting morphology of the colonies and the structure of the populations, as well as their connectivity patterns. In tropical seas, the existence of connectivity between shallow and deep populations supported the hypothesis that the deep coral reefs could potentially act as (reproductive) refugia fostering re-colonization of shallow areas after mortality events. Moreover, this hypothesis is not so clear accepted in temperate seas. Eunicella singularis is one of the most common gorgonian species in Northwestern Mediterranean Sea, playing an important role as ecosystem engineer by providing biomass and complexity to the coralligenous habitats. It has a wide bathymetric distribution ranging from about 10m to 100 m. Two depth-related morphotypes have been identified, differing in colony morphology, sclerite size and shape, and occurrence of symbiotic algae, but not inmitochondrial DNA haplotypes. In the present study the genetic structure of E. singularis populations along a horizontal and bathymetric gradient was assessed using microsatellites and ITS1 sequences. Restricted gene flow was found at 30-40 m depth between the two Eunicella morphotypes. Conversely, no genetic structuring has been found among shallow water populations within a spatial scale of ten kilometers. The break in gene flow between shallow and deep populations contributes to explain the morphological variability observed at different depths.Moreover, the limited vertical connectivity hinted that the refugia hypothesis does not apply to E. singularis. Re-colonization of shallow water populations, occasionally affected by mass mortality events, should then be mainly fueled by larvae from other shallow water populations, AG was funded by a I3P contract of the Consejo Superior de Investigaciones Cientificas (Ref. I3P-BPD2005). SR wants to thank the support of the Generalitat de Catalunya to MERS (2014 SGR-1356) and the Marie Curie International Outgoing Fellowship (ANIMAL FOREST HEALTH, project number 327845). The study was funded by a 2003-2004 INTERREG project between Catalonia-Languedoc Rouissillon ''Pirineus Mediterrànis: La muntanya que uneix'' of the CSIC and CNRS, of the 2009-2013 European project LIFE+ INDEMARES ''Inventario y designación de la red natura 2000 en áreas marinas del estado español'' (LIFE07/NAT/E/000732) of the European Union, and by a PRIN 2010-2011 project (prot. 2010Z8HJ5M) on 'Coastal bioconstructions: structure, function and management' Italian Ministry of Education, Univeristy and Research

This study investigates tourist behaviour in the Canton of Ticino Switzerland, a geographically dispersed destination, by analysing use patterns of a ‘destination card’ sold by the local destination management organization. Destination cards offer free or highly discounted entry into partner attractions and activities often coupled with free public transport access in the area. Within this context, the study sought to determine if evidence of concentrated behaviour existed, either spatially or by activity. Cluster analysis revealed four discrete market segments. Three of them showed a high degree of spatial concentration in their movements, augmented by some clearly defined activity preferences. The fourth showed no clear pattern, travelling widely throughout the Canton and sampling a range of activities. Hence, the combination of transport and attractions’ entrance appeals to two different user groups, one looking to gain access to attractions and one seeking ease of transport. Discriminant analysis further supported the results with defining the determinant variables of the cluster membership and confirmed that the point of sales has an important role in identifying the consumption of activities and the extension of the area visited. Thus, to conceptualize the decision process in an intra-destination level, the spatial structure of the destination seems to play a greater influence on behaviour than its product structure. The paper illustrates how analysis of destination card data can assist destinations in better understanding their markets and discusses potential research opportunities that can generate real marketing benefits. A number of recommendations especially for destination managers and tourism operators are also identified to enhance the information gathered. Product bundling, regional cooperation and strategic marketing opportunities at sales points are suggested in this context to further incentivize tourist mobility.

Exhaled breath condensate (EBC) collection is a noninvasive method to investigate lung diseases. EBC is usually collected with commercial/custom-made condensers, but the optimal condensing temperature is often unknown. As such, the physical and chemical properties of exhaled metabolites should be considered when setting the temperature, therefore requiring validation and standardization of the collecting procedure. EBC is frequently used in nuclear magnetic resonance (NMR)-based metabolomics, which unambiguously recognizes different pulmonary pathological states. Here we applied NMR-based metabolomics to asthmatic and healthy EBC samples collected with two commercial condensers operating at -27.3 and -4.8 °C. Thirty-five mild asthmatic patients and 35 healthy subjects were included in the study, while blind validation was obtained from 20 asthmatic and 20 healthy different subjects not included in the primary analysis. We initially analyzed the samples separately and assessed the within-day, between-day, and technical repeatabilities. Next, samples were interchanged, and, finally, all samples were analyzed together, disregarding the condensing temperature. Partial least-squares discriminant analysis of NMR spectra correctly classified samples, without any influence from the temperature. Input variables were either integral bucket areas (spectral bucketing) or metabolite concentrations (targeted profiling). We always obtained strong regression models (95%), with high average-quality parameters for spectral profiling (R(2) = 0.84 and Q(2) = 0.78) and targeted profiling (R(2) = 0.91 and Q(2) = 0.87). In particular, although targeted profiling clustering is better than spectral profiling, all models reproduced the relative metabolite variations responsible for class differentiation. This warrants that cross comparisons are reliable and that NMR-based metabolomics could attenuate some specific problems linked to standardization of EBC collection.

Compared with non-invasive species, invasive plant species may benefit from certain advantageous traits, for example, higher photosynthesis capacity and resource/energy-use efficiency. These traits can be preadapted prior to introduction, but can also be acquired through evolution following introduction to the new range. Disentangling the origins of these advantageous traits is a fundamental and emerging question in invasion ecology. We conducted a multiple comparative experiment under identical environmental condition with the invasive haplotype M lineage of the wetland grass Phragmites australis and compared the ecophysiological traits of this invasive haplotype M in North America with those of the European ancestor and the conspecific North American native haplotype E lineage, P. australis ssp. americanus. The invasive haplotype M differed significantly from the native North American conspecific haplotype E in several ecophysiological and morphological traits, and the European haplotype M had a more efficient photosynthetic apparatus than the native North American P. australis ssp. americanus. Within the haplotype M lineage, the introduced North American P. australis exhibited different biomass allocation patterns and resource/energy-use strategies compared to its European ancestor group. A discriminant analysis of principal components separated the haplotype M and the haplotype E lineages completely along the first canonical axis, highly related to photosynthetic gas-exchange parameters, photosynthetic energy-use efficiency and payback time. The second canonical axis, highly related to photosynthetic nitrogen use efficiency and construction costs, significantly separated the introduced P. australis in North America from its European ancestor. Synthesis. We conclude that the European P. australis lineage was preadapted to be invasive prior to its introduction, and that the invasion in North America is further stimulated by rapid post-introduction evolution in several advantageous traits. The multicomparison approach used in this study could be an effective approach for distinguishing preadaptation and post-introduction evolution of invasive species. Further research is needed to link the observed changes in invasive traits to the genetic variation and the interaction with the environment. Disentangling the origins of the advantageous traits is a fundamental and emerging question in invasion ecology. We compared the ecophysiological traits of the invasive haplotype M of Phragmites australis in North America with those in Europe and the conspecific North American native haplotype E lineage, P. australis ssp. americanus. The invasive haplotype M differed significantly from the native North American conspecific haplotype E in several ecophysiological and morphological traits, and the European haplotype M had a more efficient photosynthetic apparatus than the native North American P. australis ssp. americanus. Within the haplotype M lineage, the introduced North American P. australis exhibited different biomass allocation patterns and resource/energy-use strategies compared to its European ancestor group. A discriminant analysis of principal components (DAPC) significantly separated the three groups. We conclude that the European P. australis lineage was preadapted to be invasive prior to its introduction, and that the invasion in North America is further stimulated by rapid post-introduction evolution in several advantageous traits.

AIM: Celiac disease (CD) is a multifactorial autoimmune disease induced by ingestion of gluten in genetically predisposed individuals. Despite technological progress, the diagnosis of CD is still based on duodenal biopsy as it was 50 years ago. In this study we analysed the expression of CD-associated genes in small bowel biopsies of patients and controls in order to explore the multivariate pathway of the expression profile of CD patients. Then, using multivariant discriminant analysis, we evaluated whether the expression profiles of these genes in peripheral blood monocytes (PBMs) differed between patients and controls. PARTICIPANTS: Thirty-seven patients with active and 11 with treated CD, 40 healthy controls and 9 disease controls (Crohn's disease patients) were enrolled. RESULTS: Several genes were differentially expressed in CD patients versus controls, but the analysis of each single gene did not provided a comprehensive picture. A multivariate discriminant analysis showed that the expression of 5 genes in intestinal mucosa accounted for 93% of the difference between CD patients and controls. We then applied the same approach to PBMs, on a training set of 20 samples. The discriminant equation obtained was validated on a testing cohort of 10 additional cases and controls, and we obtained a correct classification of all CD cases and of 91% of the control samples. We applied this equation to treated CD patients and to disease controls and obtained a discrimination of 100%. CONCLUSIONS: The combined expression of 4 genes allows one to discriminate between CD patients and controls, and between CD patients on a gluten-free diet and disease controls. Our results contribute to the understanding of the complex interactions among CD-associated genes, and they may represent a starting point for the development of a molecular diagnosis of celiac disease.

The classification problem in the case that groups are known and both labeled and unlabeled data are available is analyzed. The classification rule is ERCIM WG on Computing & Statistics⃝c 99 ES07 Room B18 MIXTURE MODELS Chair: Christian Hennig Monday 19.12.2011 10:55 - 12:35 CFE-ERCIM 2011 Parallel Session N – ERCIM derived using Gaussian mixtures, with covariance matrices fixed according to a multiple testing procedure, which allows us to choose among four alternatives: heteroscedasticity, homometroscedasticity (common eigenvalue matrices between groups), homotroposcedasticity (common eigen- vector matrices between groups), and homoscedasticity. The mixture models are then fitted using either only the labeled data or all available ones (labeled and unlabeled) adopting the EM and the CEM algorithms in the latter case. Applications on real data are provided in order to show the classification performance of the proposed procedure.

The mineral particles are classified in different textural classes according to their size. Reflectance spectrometry and reflectance spectra can be valid instruments to classify soil according to their texture. This is possible using different statistical methods, as for example, discriminant analysis. However, others multivariate methods, like multinomial logistic regression can be used, but the presence of multicollinearity between explicative variables could affects the estimation of the parameters. To solve this problem we propose an alternative way to apply the multinomial logit model and we compare its performance to the classical method and to discriminant analysis results.

Purpose: This study is intended to investigate the reliability of different incident duration prediction models for real time application with a view to contribute to the development of a decision aid tool within the incident management process context where rough incident duration estimates are currently provided by traffic operators or police on the basis of their skill and past experience. Methods: Five predictive models, ranging from parametric models, to non-parametric and neural network models, have been considered and compared evaluating their capacity of predicting incident duration. The data set used in this study for developing and testing the prediction models includes 237 incident events and contains information about the incident characteristics, the personnel and equipment involved to clear the incident and the related response times, including the beginning and ending time of the incident. Results: Testing results have demonstrated that the proposed models are able to achieve good performance in terms of prediction accuracy especially for incidents with duration less than 90 min. This finding is partly due to the fact that the dataset has a relatively small number of severe incidents. Furthermore a linear combination of predictions from models was applied with negligible gain in accuracy. Conclusions: A deeper investigation is suggested for a future work to evaluate potential improvements from the application of other combination methods. Moreover each proposed model is able to reach best performance for incidents within a particular duration range. Thus a preliminary incident classification scheme could be more convenient in order to select the more appropriate prediction model. © The Author(s) 2010.

To help improve sex assessment from skeletal remains, the present study considers the diagnostic value of the sacral base (basis osseus sacri) based on its planar image and related metric data. For this purpose, 114 adult sacra of known sex and age from two early 20th century Italian populations were examined, the first from Bologna, northern Italy (n = 76), and the second from Sassari, Sardinia (n = 38). Digital photos of the sacral base were taken with each bone in a standardized orientation. Technical drawing software was used to trace its profile and to measure related dimensions (area, perimeter, and breadth of S1 and total breadth of the sacrum). The measurements were subjected to discriminant and classification function analyses. The sex prediction success of 93.2% for the Bolognese sample, 81.6% for the Sassarese sample, and 88.3% for the pooled sample indicates that the first sacral vertebra is a good character for sex determination.

An optimal maintenance program for electrical power system components should be based on their reliability. Since, for components characterized by high reliability and cost such as HV circuit breakers, available statistical data are in limited number, a physical model for their ageing is opportune. In the paper a Predictive Maintenance Program (PMP), for determining when a HV circuit‐breaker should be rebuilt, is formalized; it is based upon an adequate stochastic model of electrical wear associated with breaking operations due to system faults. In the model, both fault times and amplitudes are described by means of random variables, in order to deduce a reliability function used as input data for a Bayesian discriminant analysis which dynamically estimates, also in the presence of observation errors, the state of the component, determining the optimal times to perform a maintenance action.

Males and females of many avian species may show no plumage dimorphism, but often can be sexed by differences in body measurements. Sex determination of many Cory's Shearwaters Calonectris diomedea, was possible by multiplying bill length by bill depth. In this study, discriminant analysis of six measurements (bill length, bill depth, wing, tail, tarsus and mass) was performed on Cory's Shearwaters breeding on Linosa Island (Sicilian Channel), Italy and the efficiency of sex determination was compared with the univariate method. Results show the advantages of the discriminant functions. Bill depth is the best parameter (up to 92% correct classification), followed by mass (84% correct classification); using mass is simple and causes less disturbance to the birds. Received 10 August 2000, accepted 2 February 2001.

In this paper two main approaches to discriminant analysis are considered with respect to the use of either the probabilistic models or the factorial methods. It is shown that they tend to satisfy equivalent statistical criteria. A choice among several discriminant methods should take into account the a priori information on the population structure which determines the sampling sheme to be adopted. To this purpose, a distinction is made between probabilistic or factorial discriminant methods under the prospective hypothesis and probabilistic or factorial discriminant methods under the retrospective hypothesis. In the frame of prospective studies we consider the First Order Independence Model and the Non-Symmetric Factorial Discriminant Aanalysis; in the frame of retrospective studies the Null-Order Independence Model and the Baricentric Discriminant Analysis.