Caratteristiche qualitative delle carni bovine

Lo scopo di questo elaborato di tesi è stato quello di condurre uno studio preliminare volto ad indagare le principali caratteristiche qualitative delle carni bovine in funzione dell’origine e dell’età degli animali. Nel corso della sperimentazione sono stati analizzati 24 campioni di carne bovina ottenuti da animali di origine francese ed italiana di età compresa fra 15 e 23 mesi, acquistati presso la grande distribuzione o acquisiti direttamente dalle aziende produttrici. Da ciascun campione sono state ricavate delle porzioni di 6 mm di spessore impiegate, a loro volta, per la preparazione di sotto-campioni da sottoporre a determinazione di pH, colore, Expressible Moisture (EM %) e sforzo di taglio. Nell’ambito di ciascun parametro, l’insieme dei dati è stato analizzato mediante analisi statistica di tipo descrittivo. Successivamente, calcolata la matrice delle correlazioni fra i parametri oggetto di studio i dati sono stati elaborati mediante analisi multivariata con il metodo delle componenti principali (Principal Component Analysis, PCA) allo scopo di verificare se fosse possibile discriminare la qualità della carne in funzione dell’origine e dell’età degli animali. Quanto emerso evidenzia come non sia possibile discriminare la qualità dei campioni di carne bovina, sia acquistati al dettaglio presso la grande distribuzione che acquisiti direttamente dalle aziende produttrici, sulla base delle informazioni riportate in etichetta circa l’età e l’origine degli animali. Ciò può trovare spiegazione nella molteplicità di fattori intrinseci (specie, razza o tipo genetico, genere, età e peso degli animali alla macellazione) ed estrinseci (fasi pre- e post-macellazione) in grado di svolgere un ruolo rilevante nel determinare la qualità della carne. Pertanto, future ricerche dovranno essere intraprese per individuare quali parametri possano essere considerati più idonei a valorizzare la qualità tecnologica e sensoriale delle carni bovine.

The Bern psychopathology scale for the assessment of system-specific psychotic symptoms

The translation from psychiatric core symptoms to brain functions and vice versa is a largely unresolved issue. In particular, the search for disorders of single brain regions explaining classical symptoms has not yielded the expected results. Based on the assumption that the psychopathology of psychosis is related to a functional imbalance of higher-order brain systems, the authors focused on three specific candidate brain circuitries, namely the language, and limbic and motor systems. These domains are of particular interest for understanding the disastrous communication breakdown during psychotic disorders. Core symptoms of psychosis were mapped on these domains by shaping their definitions in order to match the related brain functions. The resulting psychopathological assessment scale was tested for interrater reliability and internal consistency in a group of 168 psychotic patients. The items of the scale were reliable and a principal component analysis (PCA) was best explained by a solution resembling the three candidate systems. Based on the results, the scale was optimized as an instrument to identify patient subgroups characterized by a prevailing dysfunction of one or more of these systems. In conclusion, the scale is apt to distinguish symptom domains related to the activity of defined brain systems. PCA showed a certain degree of independence of the system-specific symptom clusters within the patient group, indicating relative subgroups of psychosis. The scale is understood as a research instrument to investigate psychoses based on a system-oriented approach. Possible immediate advantages in the clinical application of the understanding of psychoses related to system-specific symptom domains are also discussed.

Neural networks engaged in tactile object manipulation: patterns of expression among healthy individuals

Somatosensory object discrimination has been shown to involve widespread cortical and subcortical structures in both cerebral hemispheres. In this study we aimed to identify the networks involved in tactile object manipulation by principal component analysis (PCA) of individual subjects. We expected to find more than one network.

Investigation of different apple cultivars by high resolution magic angle spinning NMR. A feasibility study

(1)H HR-MAS NMR spectroscopy was applied to apple tissue samples deriving from 3 different cultivars. The NMR data were statistically evaluated by analysis of variance (ANOVA), principal component analysis (PCA), and partial least-squares-discriminant analysis (PLS-DA). The intra-apple variability of the compounds was found to be significantly lower than the inter-apple variability within one cultivar. A clear separation of the three different apple cultivars could be obtained by multivariate analysis. Direct comparison of the NMR spectra obtained from apple tissue (with HR-MAS) and juice (with liquid-state HR NMR) showed distinct differences in some metabolites, which are probably due to changes induced by juice preparation. This preliminary study demonstrates the feasibility of (1)H HR-MAS NMR in combination with multivariate analysis as a tool for future chemometric studies applied to intact fruit tissues, e.g. for investigating compositional changes due to physiological disorders, specific growth or storage conditions.

Distinct DNA methylation patterns in cirrhotic liver and hepatocellular carcinoma

Abberrant DNA methylation is one of the hallmarks of cancerogenesis. Our study aims to delineate differential DNA methylation in cirrhosis and hepatic cancerogenesis. Patterns of methylation of 27,578 individual CpG loci in 12 hepatocellular carcinomas (HCCs), 15 cirrhotic controls and 12 normal liver samples were investigated using an array-based technology. A supervised principal component analysis (PCA) revealed 167 hypomethylated loci and 100 hypermethylated loci in cirrhosis and HCC as compared to normal controls. Thus, these loci show a "cirrhotic" methylation pattern that is maintained in HCC. In pairwise supervised PCAs between normal liver, cirrhosis and HCC, eight loci were significantly changed in all analyses differentiating the three groups (p < 0.0001). Of these, five loci showed highest methylation levels in HCC and lowest in control tissue (LOC55908, CELSR1, CRMP1, GNRH2, ALOX12 and ANGPTL7), whereas two loci showed the opposite direction of change (SPRR3 and TNFSF15). Genes hypermethylated between normal liver to cirrhosis, which maintain this methylation pattern during the development of HCC, are depleted for CpG islands, high CpG content promoters and polycomb repressive complex 2 (PRC2) targets in embryonic stem cells. In contrast, genes selectively hypermethylated in HCC as compared to nonmalignant samples showed an enrichment of CpG islands, high CpG content promoters and PRC2 target genes (p < 0.0001). Cirrhosis and HCC show distinct patterns of differential methylation with regards to promoter structure, PRC2 targets and CpG islands.

Automatic Reduction of Artifacts in EEG-Signals

Electroencephalograms (EEG) are often contaminated with high amplitude artifacts limiting the usability of data. Methods that reduce these artifacts are often restricted to certain types of artifacts, require manual interaction or large training data sets. Within this paper we introduce a novel method, which is able to eliminate many different types of artifacts without manual intervention. The algorithm first decomposes the signal into different sub-band signals in order to isolate different types of artifacts into specific frequency bands. After signal decomposition with principal component analysis (PCA) an adaptive threshold is applied to eliminate components with high variance corresponding to the dominant artifact activity. Our results show that the algorithm is able to significantly reduce artifacts while preserving the EEG activity. Parameters for the algorithm do not have to be identified for every patient individually making the method a good candidate for preprocessing in automatic seizure detection and prediction algorithms.

Remote sensing of volcanic plumes using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER).

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) has been used to quantify SO2 emissions from passively degassing volcanoes. This dissertation explores ASTER’s capability to detect SO2 with satellite validation, enhancement techniques and extensive processing of images at a variety of volcanoes. ASTER is compared to the Mini UV Spectrometer (MUSe), a ground based instrument, to determine if reasonable SO2 fluxes can be quantified from a plume emitted from Lascar, Chile. The two sensors were in good agreement with ASTER proving to be a reliable detector of SO2. ASTER illustrated the advantages of imaging a plume in 2D, with better temporal resolution than the MUSe. SO2 plumes in ASTER imagery are not always discernible in the raw TIR data. Principal Component Analysis (PCA) and Decorrelation Stretch (DCS) enhancement techniques were compared to determine how well they highlight a variety of volcanic plumes. DCS produced a consistent output and the composition of the plumes was easy to identify from explosive eruptions. As the plumes became smaller and lower in altitude they became harder to distinguish using DCS. PCA proved to be better at identifying smaller low altitude plumes. ASTER was used to investigate SO2 emissions at Lascar, Chile. Activity at Lascar has been characterized by cyclic behavior and persistent degassing (Matthews et al. 1997). Previous studies at Lascar have primarily focused on changes in thermal infrared anomalies, neglecting gas emissions. Using the SO2 data along with changes in thermal anomalies and visual observations it is evident that Lascar is at the end an eruptive cycle that began in 1993. Declining gas emissions and crater temperatures suggest that the conduit is sealing. ASTER and the Ozone Monitoring Instrument (OMI) were used to determine the annual contribution of SO2 to the troposphere from the Central and South American volcanic arcs between 2000 and 2011. Fluxes of 3.4 Tg/a for Central America and 3.7 Tg/a for South America were calculated. The detection limits of ASTER were explored. The results a proved to be interesting, with plumes from many of the high emitting volcanoes, such as Villarrica, Chile, not being detected by ASTER.

Prediction of soil organic carbon for Ethiopian highlands using soil spectroscopy

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used.The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9),Maybar (84. 0.57, 2.5),Megech (85, 0.15, 2.6), andWondoGenet (86, 0.52, 2.7) indicating that themodels were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

THE ASSOCIATION BETWEEN CANCER-RELATED-FATIGUE, RESPONSE TO FATIGUE TREATMENT, AND CYTOKINES AND THEIR RECEPTORS, IN PATIENTS WITH ADVANCED CANCER

Background: Inflammation is implicated in the development of cancer related fatigue (CRF). However there is limited literature on the mediators of inflammation (namely), cytokines and their receptors, associated with clinically significant fatigue and response to treatment. Methods: We reviewed 37 advanced cancer patients with fatigue (≥4/10), who participated in two Randomized Controlled Trials, of anti-inflammatory agents (Thalidomide and Dexamethasone) for CRF. Responders showed improvement in FACIT-F subscale at the end of study (Day 15). Baseline patient characteristics and symptoms were assessed by FACIT-F, ESAS; serum cytokines [IL-1β and receptor antagonist (IL-1RA), IL-6, IL-6R, TNF-α and sTNF-R1 and R2, IL-8, IL-10, IL-17] levels measured by Luminex. Data were analyzed using principal component analysis (PCA) [reporting cumulative variance (variance) for the first four components] to determine their association with fatigue and response to treatment. Results: Females were 54%. Mean (SD) was as follows for age, 61(14); baseline FACIT (F) scores, 21.4(8.6); ESAS Fatigue item, 6.5(1.9); and FACIT-F change, 6.4(9.7); ESAS (fatigue) change, -2 (2.41). Baseline median in pg/mL for IL-6, TNF-α, IL-1β were 31.9; 18.9; 0.55, respectively. Change in IL-6 negatively correlated with change in FACIT-F scores (p=0.02). Baseline CRF (FACIT-F score) was associated with IL-6, IL-6R and IL-17, Variance = 78% whereas IL-10, IL-1RA, TNF-α and IL-1β were associated with improvement of CRF, Variance=74%. Conversely, IL-6 and IL-8 were associated with no improvement or worsening of CRF, Variance= 93%. Conclusions: Change in IL-6 negatively correlated with change in FACIT-F scores. IL-6, IL-6R and IL-17 are associated with CRF while IL-6 and IL-8 were associated with no improvement of CRF. Further studies are warranted confirm our findings.

Circulating microRNA profiling in patients with advanced non-squamous NSCLC receiving bevacizumab/erlotinib followed by platinum-based chemotherapy at progression (SAKK 19/05).

OBJECTIVES Molecular subclassification of non small-cell lung cancer (NSCLC) is essential to improve clinical outcome. This study assessed the prognostic and predictive value of circulating micro-RNA (miRNA) in patients with non-squamous NSCLC enrolled in the phase II SAKK (Swiss Group for Clinical Cancer Research) trial 19/05, receiving uniform treatment with first-line bevacizumab and erlotinib followed by platinum-based chemotherapy at progression. MATERIALS AND METHODS Fifty patients with baseline and 24 h blood samples were included from SAKK 19/05. The primary study endpoint was to identify prognostic (overall survival, OS) miRNA's. Patient samples were analyzed with Agilent human miRNA 8x60K microarrays, each glass slide formatted with eight high-definition 60K arrays. Each array contained 40 probes targeting each of the 1347 miRNA. Data preprocessing included quantile normalization using robust multi-array average (RMA) algorithm. Prognostic and predictive miRNA expression profiles were identified by Spearman's rank correlation test (percentage tumor shrinkage) or log-rank testing (for time-to-event endpoints). RESULTS Data preprocessing kept 49 patients and 424 miRNA for further analysis. Ten miRNA's were significantly associated with OS, with hsa-miR-29a being the strongest prognostic marker (HR=6.44, 95%-CI 2.39-17.33). Patients with high has-miR-29a expression had a significantly lower survival at 10 months compared to patients with a low expression (54% versus 83%). Six out of the 10 miRNA's (hsa-miRN-29a, hsa-miR-542-5p, hsa-miR-502-3p, hsa-miR-376a, hsa-miR-500a, hsa-miR-424) were insensitive to perturbations according to jackknife cross-validation on their HR for OS. The respective principal component analysis (PCA) defined a meta-miRNA signature including the same 6 miRNA's, resulting in a HR of 0.66 (95%-CI 0.53-0.82). CONCLUSION Cell-free circulating miRNA-profiling successfully identified a highly prognostic 6-gene signature in patients with advanced non-squamous NSCLC. Circulating miRNA profiling should further be validated in external cohorts for the selection and monitoring of systemic treatment in patients with advanced NSCLC.

Visible near infra-red (VisNIR) spectroscopy for predicting soil organic carbon in Ethiopia

Over the past few decades, the advantages of the visible-near infra-red (VisNIR) diffuse reflectance spectrometer (DRS) method have enabled prediction of soil organic carbon (SOC). In this study, SOC was predicted using regression models for samples taken from three sites (Gununo, Maybar and Anjeni) in Ethiopia. SOC was characterized in laboratory using conventional wet chemistry and VisNIR-DRS methods. Principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS) models were developed using Unscrambler X 10.2. PCA results show that the first two components accounted for a minimum of 96% variation which increased for individual sites and with data treatments. Correlation (r), coefficient of determination (R2) and residual prediction deviation (RPD) were used to rate four models built. PLS model (r, R2, RPD) values for Anjeni were 0.9, 0.9 and 3.6; for Gununo values 0.6, 0.3 and 1.2; for Maybar values 0.6, 0.3 and 0.9, and for the three sites values 0.7, 0.6 and 1.5, respectively. PCR model values (r, R2, RPD) for Anjeni were 0.9, 0.8 and 2.7; for Gununo values 0.5, 0.3 and 1; for Maybar values 0.5, 0.1 and 0.7, and for the three sites values 0.7, 0.5 and 1.2, respectively. Comparison and testing of models shows superior performance of PLS to PCR. Models were rated as very poor (Maybar), poor (Gununo and three sites) and excellent (Anjeni). A robust model, Anjeni, is recommended for prediction of SOC in Ethiopia.

Geographic variation in floral allometry suggests repeated transitions between selfing and outcrossing in a mixed mating plant

• Premise of the study: Isometric and allometric scaling of a conserved floral plan could provide a parsimonious mechanism for rapid and reversible transitions between breeding systems. This scaling may occur during transitions between predominant autogamy and xenogamy, contributing to the maintenance of a stable mixed mating system. • Methods: We compared nine disjunct populations of the polytypic, mixed mating species Oenothera flava (Onagraceae) to two parapatric relatives, the obligately xenogamous species O. acutissima and the mixed mating species O. triloba. We compared floral morphology of all taxa using principal component analysis (PCA) and developmental trajectories of floral organs using ANCOVA homogeneity of slopes. • Key results: The PCA revealed both isometric and allometric scaling of a conserved floral plan. Three principal components (PCs) explained 92.5% of the variation in the three species. PC1 predominantly loaded on measures of floral size and accounts for 36% of the variation. PC2 accounted for 35% of the variation, predominantly in traits that influence pollinator handling. PC3 accounted for 22% of the variation, primarily in anther–stigma distance (herkogamy). During O. flava subsp. taraxacoides development, style elongation was accelerated relative to anthers, resulting in positive herkogamy. During O. flava subsp. flava development, style elongation was decelerated, resulting in zero or negative herkogamy. Of the two populations with intermediate morphology, style elongation was accelerated in one population and decelerated in the other. • Conclusions: Isometric and allometric scaling of floral organs in North American Oenothera section Lavauxia drive variation in breeding system. Multiple developmental paths to intermediate phenotypes support the likelihood of multiple mating system transitions.

Climate sensitivity of Mediterranean pine growth reveals distinct east-west dipole

The European Mediterranean region is governed by a characteristic climate of summer drought that is likely to increase in duration and intensity under predicted climate change. However, large-scale network analyses investigating spatial aspects of pre-instrumental drought variability for this biogeographic zone are still scarce. In this study we introduce 54 mid- to high-elevation tree-ring width (TRW) chronologies comprising 2186 individual series from pine trees (Pinus spp.). This compilation spans a 4000-km east–west transect from Spain to Turkey, and was subjected to quality control and standardization prior to the development of site chronologies. A principal component analysis (PCA) was applied to identify spatial growth patterns during the network's common period 1862–1976, and new composite TRW chronologies were developed and investigated. The PCA reveals a common variance of 19.7% over the 54 Mediterranean pine chronologies. More interestingly, a dipole pattern in growth variability is found between the western (15% explained variance) and eastern (9.6%) sites, persisting back to 1330 AD. Pine growth on the Iberian Peninsula and Italy favours warm early growing seasons, but summer drought is most critical for ring width formation in the eastern Mediterranean region. Synoptic climate dynamics that have been in operation for the last seven centuries have been identified as the driving mechanism of a distinct east–west dipole in the growth variability of Mediterranean pines.

Morphological variation within the diatom taxon Cyclotella comensis and its importance for quantitative temperature reconstructions

1. The morphologically complex taxon Cyclotella comensis Grunow had no clear relationship with environmental parameters in a study using sediment surface samples from the Swiss Alps. The morphological heterogeneity of the taxon was investigated by applying a principal component analysis (PCA) to 9000 presence/absence descriptions of valves from surface samples of six lakes from different altitudes (15 characteristics, 100 valves each lake). The PCA allowed the classification of six morphs, which differed mainly in size and length of striae. Photographs of the morphs are shown in this paper. 2. Sixty-eight sediment surface samples were analysed using these newly defined six morphs. Summer temperature explained a major part of the variance between the morphs as assessed by a redundancy analysis (RDA). Summer temperature optima and tolerances were estimated using weighted averaging. 3. The influence of the revised C. comensis taxonomy on the diatom inferred summer temperature of a high alpine lake is discussed in a multiproxy context for the past 800 years.

Análisis de componentes principales con datos georreferenciados : una aplicación en agricultura de precisión

La utilización de nuevas tecnologías asociadas a la agricultura de precisión permite capturar información de múltiples variables en gran cantidad de sitios georreferenciados dentro de lotes en producción. Las covariaciones espaciales de las propiedades del suelo y el rendimiento del cultivo pueden evaluarse a través del análisis de componentes principales clásico (PCA). No obstante, como otros métodos multivariados descriptivos, el PCA no ha sido desarrollado explícitamente para datos espaciales. Nuevas versiones de análisis multivariado permiten contemplar la autocorrelación espacial entre datos de sitios vecinos. En este trabajo se aplican y comparan los resultados de dos técnicas multivariadas, el PCA y MULTISPATI-PCA. Este último incorpora la información espacial a través del cálculo del índice de Moran entre los datos de un sitio y el dato promedio de sus vecinos. Los resultados mostraron que utilizando MULTISPATI-PCA se detectaron correlaciones entre variables que no fueron detectadas con el PCA. Los mapas de variabilidad espacial construidos a partir de la primera componente de ambas técnicas fueron similares; no así los de la segunda componente debido a cambios en la estructura de co-variación identificada, al corregir la variabilidad por la autocorrelación espacial de los datos. El método MULTISPATI-PCA constituye una herramienta importante para el mapeo de la variabilidad espacial y la identificación de zonas homogéneas dentro de lotes.