Detecting the effects of predator-induced stress on the global metabolism of an ungulate prey using fecal metabolomic fingerprinting.

Few field tests have assessed the effects of predator-induced stress on prey fitness, particularly in large carnivore-ungulate systems. Because traditional measures of stress present limitations when applied to free-ranging animals, new strategies and systemic methodologies are needed. Recent studies have shown that stress and anxiety related behaviors can influence the metabolic activity of the gut microbiome in mammal hosts, and these metabolic alterations may aid in identification of stress. In this study, we used NMR-based fecal metabolomic fingerprinting to compare the fecal metabolome, a functional readout of the gut microbiome, of cattle herds grazing in low vs. high wolf-impacted areas within three wolf pack territories. Additionally, we evaluated if other factors (e.g., cattle nutritional state, climate, landscape) besides wolf presence were related to the variation in cattle metabolism. By collecting longitudinal fecal samples from GPS-collared cattle, we found relevant metabolic differences between cattle herds in areas where the probability of wolf pack interaction was higher. Moreover, cattle distance to GPS-collared wolves was the factor most correlated with this difference in cattle metabolism, potentially reflecting the variation in wolf predation risk. We further validated our results through a regression model that reconstructed cattle distances to GPS-collared wolves based on the metabolic difference between cattle herds. Although further research is needed to explore if similar patterns also hold at a finer scale, our results suggests that fecal metabolomic fingerprinting is a promising tool for assessing the physiological responses of prey to predation risk. This novel approach will help improve our knowledge of the consequences of predators beyond the direct effect of predation.

Fecal Metabolomics as a Novel Noninvasive Method for Short-Term Stress Monitoring in Beef Cattle.

Traditional measures of short-term stress response such as fecal glucocorticoid metabolites (FGM) are widely used in controlled settings to quantify the intensity of stimulation to which cattle are exposed. However, FGMs present several methodological and interpretation pitfalls when applied on animals in free-ranging conditions. In this study, we proposed an NMR-based fecal metabolomics strategy for noninvasive stress detection in beef cattle. Using a longitudinal sample collection, we monitored the changes in the fecal metabolome and FGM concentrations before and after an acute stressful event. Our results showed that while the fecal metabolome changed as a function of stress (p < 0.001), the mean concentrations of FGM did not change (Levene's test: F-ratio: 0.87, p-value: 0.44). Furthermore, we showed that the interanimal variability observed in the stress response was correlated with the individual fecal microbiota. This result was in line with recent findings, indicating the gut microbiome as a crucial mediator of stress response. We conclude that NMR-based fecal metabolomics proved to be a reliable methodology to assess stress response and that its future applicability to studies for stress monitoring in range animals may be more appropriate than FGM analysis.

Dropwort-induced metabolic reprogramming restrains YAP/TAZ/TEAD oncogenic axis in mesothelioma.

BACKGROUND: Over the past decade, newly designed cancer therapies have not significantly improved the survival of patients diagnosed with Malignant Pleural Mesothelioma (MPM). Among a limited number of genes that are frequently mutated in MPM several of them encode proteins that belong to the HIPPO tumor suppressor pathway. METHODS: The anticancer effects of the top flower standardized extract of Filipendula vulgaris (Dropwort) were characterized in "in vitro" and "in vivo" models of MPM. At the molecular level, two "omic" approaches were used to investigate Dropwort anticancer mechanism of action: a metabolomic profiling and a phosphoarray analysis. RESULTS: We found that Dropwort significantly reduced cell proliferation, viability, migration and in vivo tumor growth of MPM cell lines. Notably, Dropwort affected viability of tumor-initiating MPM cells and synergized with Cisplatin and Pemetrexed in vitro. Metabolomic profiling revealed that Dropwort treatment affected both glycolysis/tricarboxylic acid cycle as for the decreased consumption of glucose, pyruvate, succinate and acetate, and the lipid metabolism. We also document that Dropwort exerted its anticancer effects, at least partially, promoting YAP and TAZ protein ubiquitination. CONCLUSIONS: Our findings reveal that Dropwort is a promising source of natural compound(s) for targeting the HIPPO pathway with chemo-preventive and anticancer implications for MPM management.

Simulated microgravity promotes the formation of tridimensional cultures and stimulates pluripotency and a glycolytic metabolism in human hepatic and biliary tree stem/progenitor cells.

Many pivotal biological cell processes are affected by gravity. The aim of our study was to evaluate biological and functional effects, differentiation potential and exo-metabolome profile of simulated microgravity (SMG) on human hepatic cell line (HepG2) and human biliary tree stem/progenitor cells (hBTSCs). Both hBTSCs and HepG2 were cultured in a weightless and protected environment SGM produced by the Rotary Cell Culture System (Synthecon) and control condition in normal gravity (NG). Self-replication and differentiation toward mature cells were determined by culturing hBTSCs in Kubota's Medium (KM) and in hormonally defined medium (HDM) tailored for hepatocyte differentiation. The effects on the expression and cell exo-metabolome profiles of SMG versus NG cultures were analyzed. SMG promotes tridimensional (3D) cultures of hBTSCs and HepG2. Significative increase of stemness gene expression (p < 0.05) has been observed in hBTSCs cultured in SMG when compared to NG condition. At the same time, the expression of hepatocyte lineage markers in hBTSCs differentiated by HDM was significantly lower (p < 0.05) in SMG compared to NG, demonstrating an impaired capability of hBTSCs to differentiate in vitro toward mature hepatocytes when cultured in SMG condition. Furthermore, in HepG2 cells the SMG caused a lower (p < 0.05 vs controls) transcription of CYP3A4, a marker of late-stage (i.e. Zone 3) hepatocytes. Exo-metabolome NMR-analysis showed that both cell cultures consumed a higher amount of glucose and lower glutamate in SMG respect to NG (p < 0.05). Moreover, hBTSCs media cultures resulted richer of released fermentation (lactate, acetate) and ketogenesis products (B-hydroxybutyrate) in SGM (p < 0.05) than NG. While, HepG2 cells showed higher consumption of amino acids and release of ketoacids (3-Methyl-2-oxovalerate, 2-oxo-4-methyl-valerate) and formiate with respect to normogravity condition (p < 0.05). Based on our results, SMG could be helpful for developing hBTSCs-derived liver devices. In conclusion, SMG favored the formation of hBTSCs and HepG2 3D cultures and the maintenance of stemness contrasting cell differentiation; these effects being associated with stimulation of glycolytic metabolism. Interestingly, the impact of SMG on stem cell biology should be taken into consideration for workers involved in space medicine programs.

Gut microbiota signatures in cystic fibrosis: Loss of host CFTR function drives the microbiota enterophenotype.

BACKGROUND: Cystic fibrosis (CF) is a disorder affecting the respiratory, digestive, reproductive systems and sweat glands. This lethal hereditary disease has known or suspected links to the dysbiosis gut microbiota. High-throughput meta-omics-based approaches may assist in unveiling this complex network of symbiosis modifications. OBJECTIVES: The aim of this study was to provide a predictive and functional model of the gut microbiota enterophenotype of pediatric patients affected by CF under clinical stability. METHODS: Thirty-one fecal samples were collected from CF patients and healthy children (HC) (age range, 1-6 years) and analysed using targeted-metagenomics and metabolomics to characterize the ecology and metabolism of CF-linked gut microbiota. The multidimensional data were low fused and processed by chemometric classification analysis. RESULTS: The fused metagenomics and metabolomics based gut microbiota profile was characterized by a high abundance of Propionibacterium, Staphylococcus and Clostridiaceae, including Clostridium difficile, and a low abundance of Eggerthella, Eubacterium, Ruminococcus, Dorea, Faecalibacterium prausnitzii, and Lachnospiraceae, associated with overexpression of 4-aminobutyrate (GABA), choline, ethanol, propylbutyrate, and pyridine and low levels of sarcosine, 4-methylphenol, uracil, glucose, acetate, phenol, benzaldehyde, and methylacetate. The CF gut microbiota pattern revealed an enterophenotype intrinsically linked to disease, regardless of age, and with dysbiosis uninduced by reduced pancreatic function and only partially related to oral antibiotic administration or lung colonization/infection. CONCLUSIONS: All together, the results obtained suggest that the gut microbiota enterophenotypes of CF, together with endogenous and bacterial CF biomarkers, are direct expression of functional alterations at the intestinal level. Hence, it's possible to infer that CFTR impairment causes the gut ecosystem imbalance.This new understanding of CF host-gut microbiota interactions may be helpful to rationalize novel clinical interventions to improve the affected children's nutritional status and intestinal function.

Metabolomics: Challenges and Opportunities in Systems Biology Studies.

Metabolomics has the capability of providing predisposition, diagnostic, prognostic, and therapeutic biomarker profiles of individual patients, since a large number of metabolites can be measured in an unbiased manner from biological samples. In this setting, 1H-Nuclear Magnetic Resonance (NMR) spectroscopy of biofluids such as plasma, urine, and fecal water offers the opportunity to identify patterns of biomarker changes that reflects the physiological or pathological status of an individual patient.In this chapter, we show as a metabolomics study can be used to diagnose a disease, classifying patients as healthy or as pathological taking into account individual variability.

Che-1 sustains hypoxic response of colorectal cancer cells by affecting Hif-1α stabilization.

BACKGROUND: Solid tumours are less oxygenated than normal tissues. Consequently, cancer cells acquire to be adapted to a hypoxic environment. The poor oxygenation of solid tumours is also a major indicator of an adverse cancer prognosis and leads to resistance to conventional anticancer treatments. We previously showed the involvement of Che-1/AATF (Che-1) in cancer cell survival under stress conditions. Herein we hypothesized that Che-1 plays a role in the response of cancer cells to hypoxia. METHODS: The human colon adenocarcinoma HCT116 and HT29 cell lines undepleted or depleted for Che-1 expression by siRNA, were treated under normoxic and hypoxic conditions to perform studies regarding the role of this protein in metabolic adaptation and cell proliferation. Che-1 expression was detected using western blot assays; cell metabolism was assessed by NMR spectroscopy and functional assays. Additional molecular studies were performed by RNA seq, qRT-PCR and ChIP analyses. RESULTS: Here we report that Che-1 expression is required for the adaptation of cells to hypoxia, playing an important role in metabolic modulation. Indeed, Che-1 depletion impacted on HIF-1α stabilization, thus downregulating the expression of several genes involved in the response to hypoxia and affecting glucose metabolism. CONCLUSIONS: We show that Che-1 a novel player in the regulation of HIF-1α in response to hypoxia. Notably, we found that Che-1 is required for SIAH-2 expression, a member of E3 ubiquitin ligase family that is involved in the degradation of the hydroxylase PHD3, the master regulator of HIF-1α stability.

3T multiparametric MRI of the prostate: Does intravoxel incoherent motion diffusion imaging have a role in the detection and stratification of prostate cancer in the peripheral zone?

PURPOSE: To evaluate the potential added value of the intravoxel incoherent motion model to conventional multiparametric magnetic resonance protocol in order to differentiate between healthy and neoplastic prostate tissue in the peripheral zone. MATERIAL AND METHODS: Mono-exponential and bi-exponential fits were used to calculate ADC and IVIM parameters in 53 patients with peripheral zone biopsy proved tumor. Inferential statistics analysis was performed on T2, ADC and IVIM parameters (D, D*, f) comparing healthy and neoplastic tissues. Linear discriminant analysis was performed for the conventional parameters (T2 and ADC), the IVIM parameters (molecular diffusion coefficient (D), perfusion-related diffusion coefficient (D*), and perfusion fraction (f) and the combined T2-weighted imaging/DWI and IVIM parameters (T2, ADC, D, D* and f). A correlation with Gleason scores was achieved. RESULTS: The values of T2, ADC and D were significantly lower in cancerous tissues (2749.82 ± 1324.67 ms, 0.76 ± 0.27 × 10(-3)mm(2)/s and 0.99 ± 0.38 × 10(-3)mm(2)/s respectively) compared to those found in the healthy tissues (3750.70 ± 1735.37 ms, 1.39 ± 0.48 × 10(-3)mm(2)/s and 1.77 ± 0.36 × 10(-3)mm(2)/s respectively); D* parameter was significantly increased in neoplastic compared to healthy tissue (15.56 ± 12.91 × 10(-3)mm(2)/s and 10.25 ± 10.52 × 10(-3)mm(2)/s respectively). The specificity, sensitivity and accuracy of the T2-weighted imaging/DWI and IVIM parameters were 100, 96 and 98%, respectively, compare to 88, 92 and 90% and 96, 92 and 94 for T2-weighted imaging/ADC and IVIM alone. CONCLUSIONS: IVIM parameters increase the specificity and sensitivity in the evaluation of peripheral zone prostate cancer. A statistical difference between low grade tumors and high grade tumors has been demostrated in that ADC, D and D* dataset; in particular, D has been found to have the highest significativity.

(1)H NMR Metabolomic Footprinting Analysis for the In Vitro Screening of Potential Chemopreventive Agents.

Metabolomics is the quantification and analysis of the concentration profiles of low-molecular-weight compounds present in biological samples. In particular metabolic footprinting analysis, based on the monitoring of metabolites consumed from and secreted into the growth medium, is a valuable tool for the study of pharmacological and toxicological effects of drugs. Mass spectrometry and nuclear magnetic resonance (NMR) are the two main complementary techniques used in this field. Although less sensitive, NMR gives a direct fingerprint of the system, and the spectra obtained contain metabolic information that can be distilled by chemometric techniques. In this chapter, we present how metabolomic footprinting can be used to assess in vitro a potential chemopreventive molecule as metformin.

¹H-NMR-Based Metabolomic Study for Identifying Serum Profiles Associated with the Response to Etanercept in Patients with Rheumatoid Arthritis.

OBJECTIVE: A considerable proportion of patients with rheumatoid arthritis (RA) do not have a satisfactory response to biological therapies. We investigated the use of metabolomics approach to identify biomarkers able to anticipate the response to biologics in RA patients. METHODS: Due to gender differences in metabolomic profiling, the analysis was restricted to female patients starting etanercept as the first biological treatment and having a minimum of six months' follow-up. Each patient was evaluated by the same rheumatologist before and after six months of treatment. At this time, the clinical response (good, moderate, none) was determined according to the EUropean League Against Rheumatism (EULAR) criteria, based on both erythrocyte sedimentation rate (EULAR-ESR) and C-reactive protein (EULAR-CRP). Sera collected prior and after six months of etanercept were analyzed by 1H-nuclear magnetic resonance (NMR) spectroscopy in combination with multivariate data analysis. RESULTS: Twenty-seven patients were enrolled: 18 had a good/moderate response and 9 were non responders according to both EULAR-ESR and EULAR-CRP after six months of etanercept. Metabolomic analysis at baseline was able to discriminate good, moderate, and non-responders with a very good predictivity (Q2 = 0.68) and an excellent sensitivity, specificity, and accuracy (100%). In good responders, we found an increase in isoleucine, leucine, valine, alanine, glutamine, tyrosine, and glucose levels and a decrease in 3-hydroxybutyrate levels after six months of treatment with etanercept with respect to baseline. CONCLUSION: Our study confirms the potential of metabolomic analysis to predict the response to biological agents. Changes in metabolic profiles during treatment may help elucidate their mechanism of action.

Performance Assessment in Fingerprinting and Multi Component Quantitative NMR Analyses.

An interlaboratory comparison (ILC) was organized with the aim to set up quality control indicators suitable for multicomponent quantitative analysis by nuclear magnetic resonance (NMR) spectroscopy. A total of 36 NMR data sets (corresponding to 1260 NMR spectra) were produced by 30 participants using 34 NMR spectrometers. The calibration line method was chosen for the quantification of a five-component model mixture. Results show that quantitative NMR is a robust quantification tool and that 26 out of 36 data sets resulted in statistically equivalent calibration lines for all considered NMR signals. The performance of each laboratory was assessed by means of a new performance index (named Qp-score) which is related to the difference between the experimental and the consensus values of the slope of the calibration lines. Laboratories endowed with a Qp-score falling within the suitable acceptability range are qualified to produce NMR spectra that can be considered statistically equivalent in terms of relative intensities of the signals. In addition, the specific response of nuclei to the experimental excitation/relaxation conditions was addressed by means of the parameter named NR. NR is related to the difference between the theoretical and the consensus slopes of the calibration lines and is specific for each signal produced by a well-defined set of acquisition parameters.

Metformin-induced metabolic reprogramming of chemoresistant ALDHbright breast cancer cells.

Metabolic remodeling is a hallmark of cancer progression and may affect tumor chemoresistance. Here we investigated by 1H-NMR/PCA analysis the metabolic profile of chemoresistant breast cancer cell subpopulations (ALDHbright cells) and their response to metformin, a promising anticancer metabolic modulator. The purified ALDHbright cells exhibited a different metabolic profile as compared to their chemosensitive ALDHlow counterparts. Metformin treatment strongly affected the metabolism of the ALDHbright cells thereby affecting, among the others, the glutathione metabolism, whose upregulation is a feature of progenitor-like, chemoresistant cell subpopulations. Globally, metformin treatment reduced the differences between ALDHbright and ALDHlow cells, making the former more similar to the latter. Metformin broadly modulated microRNAs in the ALDHbright cells, with a large fraction of them predicted to target the same metabolic pathways experimentally identified by 1H-NMR. Additionally, metformin modulated the levels of c-MYC and IRS-2, and this correlated with changes of the microRNA-33a levels. In summary, we observed, both by 1H-NMR and microRNA expression studies, that metformin treatment reduced the differences between the chemoresistant ALDHbright cells and the chemosensitive ALDHlow cells. This works adds on the potential therapeutic relevance of metformin and shows the potential for metabolic reprogramming to modulate cancer chemoresistance.

Metabolomics approach in allergic and rheumatic diseases.

Metabolomics is the analysis of the concentration profiles of low molecular weight compounds present in biological fluids. Metabolites are nonpeptide molecules representing the end products of cellular activity. Therefore, changes in metabolite concentrations reveal the range of biochemical effects induced by a disease or its therapeutic intervention. Metabolomics has recently become feasible with the accessibility of new technologies, including mass spectrometry and high-resolution proton nuclear magnetic resonance, and has already been applied to several disorders. Indeed, it has the advantage of being a nontargeted approach for identifying potential biomarkers, which means that it does not require a preliminary knowledge of the substances to be studied. In this review, we summarize the main studies in which metabolomic approach was used in some allergic (asthma, atopic dermatitis) and rheumatic diseases (rheumatoid arthritis, systemic lupus erythematosus) to explore the feasibility of this technique as a novel diagnostic tool in these complex disorders.

Metabolomics in rheumatic diseases: the potential of an emerging methodology for improved patient diagnosis, prognosis, and treatment efficacy.

Metabolomics belongs to the family of "-omics" sciences, also comprised of genomics, transcriptomics, and proteomics, all of which share the advantage of a non-targeted approach for identifying biomarkers and profiling the patient. This means that they do not require a preliminary knowledge of the substances to be studied. Moreover, even small quantities of biological fluids or tissues may be utilized for analysis. Metabolomic procedure has become feasible only recently with the advent and accessibility of new high-throughput technologies, including mass spectrometry and nuclear magnetic resonance. The methodology generally involves three defining steps: 1) the acquisition of experimental data, 2) the multivariate statistical analysis, and 3) the projection of the acquired information (profiles) to construct the patient map. Metabolomic analysis has been applied to several disorders: as far as rheumatic diseases are concerned, a few studies have focused on rheumatoid arthritis, spondyloarthritis, systemic lupus erythematosus, and osteoarthritis. Both murine models and clinical data have shown the potential of this novel tool to contribute to deciding a diagnosis, discriminate between patients based on disease activity, and even predict the response to a particular treatment. The present review fully reports these findings and offers a critical view of the challenges still to be met.

Metformin elicits anticancer effects through the sequential modulation of DICER and c-MYC.

Diabetic patients treated with metformin have a reduced incidence of cancer and cancer-related mortality. Here we show that metformin affects engraftment and growth of breast cancer tumours in mice. This correlates with the induction of metabolic changes compatible with clear anticancer effects. We demonstrate that microRNA modulation underlies the anticancer metabolic actions of metformin. In fact, metformin induces DICER expression and its effects are severely impaired in DICER knocked down cells. Conversely, ectopic expression of DICER recapitulates the effects of metformin in vivo and in vitro. The microRNAs upregulated by metformin belong mainly to energy metabolism pathways. Among the messenger RNAs downregulated by metformin, we found c-MYC, IRS-2 and HIF1alpha. Downregulation of c-MYC requires AMP-activated protein kinase-signalling and mir33a upregulation by metformin. Ectopic expression of c-MYC attenuates the anticancer metabolic effects of metformin. We suggest that DICER modulation, mir33a upregulation and c-MYC targeting have an important role in the anticancer metabolic effects of metformin.

Metabolism and cell shape in cancer: a fractal analysis.

Fractal analysis in cancer cell investigation provided meaningful insights into the relationship between morphology and phenotype. Some reports demonstrated that changes in cell shape precede and trigger dramatic modifications in both gene expression and enzymatic function. Nonetheless, metabolomic pattern in cells undergoing shape changes have been not still reported. Our study was aimed to investigate if modifications in cancer cell morphology are associated to relevant transition in tumour metabolome, analyzed by nuclear magnetic resonance spectroscopy and principal component analysis. MCF-7 and MDA-MB-231 breast cancer cells, exposed to an experimental morphogenetic field, undergo a dramatic change in their membrane profiles. Both cell lines recover a more rounded shape, loosing spindle and invasive protrusions, acquiring a quite "normal" morphology. This result, quantified by fractal analysis, shows that normalized bending energy (a global shape characterization expressing the amount of energy needed to transform a specific shape into its lowest energy state) decreases after 48 h. Later on, a significant shift from a high to a low glycolytic phenotype was observed on both cell lines: glucose flux begins to drop off at 48 h, leading to reduced lactate accumulation, and fatty acids and citrate synthesis slow-down after 72 h. Moreover, de novo lipidogenesis is inhibited and nucleotide synthesis is reduced, as indicated by the positive correlation between glucose and formate. In conclusion, these data indicate that the reorganization of cell membrane architecture, induced by environmental cues, is followed by a relevant transition of the tumour metabolome, suggesting cells undergo a dramatic phenotypic reversion.

Metabolic analysis of the removal of formic acid by unacclimated activated sludge.

This paper investigates the removal of formic acid by unacclimated biomass from a municipal activated sludge wastewater treatment plant. The biomass was initially able to remove formic acid, but its removal rate and Oxygen Uptake Rate (OUR) decreased with time, until formic acid removal stopped before the formic acid had been exhausted. Formaldehyde was removed in a similar way, whereas the same biomass was simultaneously able to grow and store PHAs when acetic acid was used as substrate. Batch tests with glycine and (13)C NMR analysis were performed, showing that unacclimated biomass was not able to synthesize all the metabolic intermediates from formic acid alone. At least glycine needed to be externally supplemented, in order to activate the serine synthesis pathway. A small amount of formic acid removal in the absence of growth was also possible through formaldehyde formation and its further conversion to formalin (1,2-formaldehyde dimer), whereas no PHAs were formed.

Classification of prostatic diseases by means of multivariate analysis on in vivo proton MRSI and DCE-MRI data.

Multivariate analysis has been applied on proton magnetic resonance spectroscopic imaging ((1)H-MRSI) and dynamic contrast enhanced MRI (DCE-MRI) data of patients with different prostatic diseases such as chronic inflammation, fibrosis and adenocarcinoma. Multivariate analysis offers a global view of the entire range of information coming from both the imaging and spectroscopic side of NMR technology, leading to an integrated picture of the system relying upon the entire metabolic and dynamic profile of the studied samples. In this study, we show how this approach, applied to (1)H-MRSI/DCE-MRI results, allows us to differentiate among the various prostatic diseases in a non-invasive way with a 100% accuracy. These findings suggest that multivariate analysis of (1)H-MRSI/DCE-MRI can significantly improve the diagnostic accuracy for these pathological entities. From a more theoretical point of view, the complementation of a single biomarker approach with an integrated picture of the entire metabolic and dynamic profile allows for a more realistic appreciation of pathological entities.

pH effects on the conformational preferences of amyloid beta-peptide (1-40) in HFIP aqueous solution by NMR spectroscopy.

The structure and aggregation state of amyloid beta-peptide (Abeta) in membrane-like environments are important determinants of pathological events in Alzheimer's disease. In fact, the neurotoxic nature of amyloid-forming peptides and proteins is associated with specific conformational transitions proximal to the membrane. Under certain conditions, the Abeta peptide undergoes a conformational change that brings the peptide in solution to a "competent state" for aggregation. Conversion can be obtained at medium pH (5.0-6.0), and in vivo this appears to take place in the endocytic pathway. The combined use of (1)H NMR spectroscopy and molecular dynamics-simulated annealing calculations in aqueous hexafluoroisopropanol simulating the membrane environment, at different pH conditions, enabled us to get some insights into the aggregation process of Abeta, confirming our previous hypotheses of a relationship between conformational flexibility and aggregation propensity. The conformational space of the peptide was explored by means of an innovative use of principal component analysis as applied to residue-by-residue root-mean-square deviations values from a reference structure. This procedure allowed us to identify the aggregation-prone regions of the peptide.

Dissecting drug and vehicle metabolic effects in rats by a metabonomic approach.

A combined application of high resolution (1)H NMR spectroscopy and multivariate statistical techniques focused on establishing a consistent statistical approach to metabonomic studies was tested. The data reduction, which is preliminary to the application of multivariate analysis to NMR spectra, was carried out by means of two complementary methods: pure Pattern Recognition (PR) and Assigned Signal Analysis (ASA). The simultaneous use of both approaches allowed us to obtain additional information in the analysis of metabonomic data, compared to the use of PR alone. This additional information consists in the possibility of a biochemical interpretation of the effects induced by treatment with xenobiotics, such as drugs or drug vehicles, on the metabolic networks of the systems under investigation. This approach allowed us to ascertain that a single-dose treatment with ST1959 vehicled by Sesame oil affects the production of hepatic glucose associated to an increment of the amino acid ketogenic process.