Metabolomics approach to studying minimally processed peach (Prunus persica) fruit

Fresh-cut fruit products for both retail and food service applications have increasingly appeared in the market place in recent years. Among different fruit types, peaches can be used and are highly appreciated as fresh-cut product although their commercial success is limited due to their short shelf-life and the quick onset of wounding-related physiological reactions. In this work we analyzed the technological and physiological changes induced by fresh-cut preparation in three different types of peach cultivars: 'Fayette' (melting), 'Wilhelmina' (non-melting) and 'Ghiaccio3' (stony hard). We performed a metabolite targeting profiling to focus on the changes in organic acid levels, important components of fruit taste and organoleptic quality of peaches. Interestingly, 'Ghiaccio3' showed an increase of several organic acids after cutting while 'Fayette' and 'Wilhelmina' showed unchanged amounts or a general reduction. Cutting induces a similar pattern of change in important metabolites (i.e., dehydroascorbate, alanine) in all the three peach types while other metabolites (i.e., citric acid) appeared to be differentially regulated in the considered peach cultivars

Modeling brain connectivity dynamics in functional Magnetic Resonance Imaging via Particle Filtering

Interest in the studying of functional connections in the brain has grown considerably in the last decades, as many studies have pointed out that alterations in the interaction among brain areas can play a role as markers of neurological diseases. Most studies in this field treat the brain network as a system of connections stationary in time, but dynamic features of brain connectivity can provide useful information, both on physiology and pathological conditions of the brain. In this paper, we propose the application of a computational methodology, named Particle Filter (PF), to study non-stationarities in brain connectivity in functional Magnetic Resonance Imaging (fMRI). The PF algorithm estimates time-varying hidden parameters of a first-order linear time-varying Vector Autoregressive model (VAR) through a Sequential Monte Carlo strategy. On simulated time series, the PF approach effectively detected and enabled to follow time-varying hidden parameters and it captured causal relationships among signals. The method was also applied to real fMRI data, acquired in presence of periodic tactile or visual stimulations, in different sessions. On these data, the PF estimates were consistent with current knowledge on brain functioning. Most importantly, the approach enabled to detect statistically significant modulations in the cause-effect relationship between brain areas, which correlated with the underlying visual stimulation pattern presented during the acquisition

Semiautomated Evaluation of the Primary Motor Cortex in Patients with Amyotrophic Lateral Sclerosis at 3T

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Semiautomated evaluation of the primary motor cortex in patients with amyotrophic lateral sclerosis at 3t

Amyotrophic lateral sclerosis is a neurodegenerative disease involving the upper and lower motor neurons. In amyotrophic lateral sclerosis, pathologic changes in the primary motor cortex include Betz cell depletion and the presence of reactive iron-loaded microglia, detectable on 7T MR images as atrophy and T2*-hypointensity. Our purposes were the following: 1) to investigate the signal hypointensity-to-thickness ratio of the primary motor cortex as a radiologic marker of upper motor neuron involvement in amyotrophic lateral sclerosis with a semiautomated method at 3T, 2) to compare 3T and 7T results, and 3) to evaluate whether semiautomated measurement outperforms visual image assessment

The Role of Spleen and Liver Elastography and Color-Doppler Ultrasound in the Assessment of Transjugular Intrahepatic Portosystemic Shunt Function

The reference standard for assessing transjugular intrahepatic portosystemic shunt (TIPS) function is venography with portosystemic pressure gradient (PPG) measurement. This procedure is invasive and expensive; thus, we assessed the feasibility, reproducibility and diagnostic accuracy of color-Doppler ultrasound (CDUS) and spleen and liver stiffness (LS) measurements for identifying TIPS dysfunction. Twenty-four patients (15 undergoing TIPS placement and nine undergoing TIPS revision) consecutively underwent CDUS examination and LS and spleen stiffness (SS) determination by transient elastography (TE) and point shear-wave elastography (pSWE). All parameters were taken before TIPS placement/revision (1\u201315 d before) and 24 h after, just before revision by venography. pSWE inter-observer agreement was assessed by intra-class correlation coefficient (ICC). CDUS and elastographic data were correlated (Pearson coefficient) with pressure gradients (hepatic venous pressure gradient [HVPG], PPG). Main determinants of TIPS dysfunction were investigated by linear regression. Forty-nine paired examinations were performed in total: 49 (100%) SS reliable measurements by pSWE and 38 (88%) by TE. The ICC for pSWE values was 0.90 (95% confidence interval [CI] 0.81\u20120.94). SS values significantly correlated with HVPG and PPG (R = 0.51, p = 0.01). The area under the Receiver-Operating Characteristic (AUROC) curve of SS for diagnosing TIPS dysfunction was 0.86 (95% CI 0.70\u20120.96) using a 25 kPa cutoff. At multivariate analysis, the flow direction of the intrahepatic portal vein branches and SS values were independently associated to TIPS dysfunction. The intrahepatic portal vein branches flow direction and SS value are two simple, highly sensitive parameters accurately excluding TIPS dysfunction. SS measurement by pSWE is feasible, reproducible and both positively and significantly correlates with HVPG and PPG values

Quality assessment, variability and reproducibility of anatomical measurements derived from T1-weighted brain imaging: The RIN–Neuroimaging Network case study

Initiatives for the collection of harmonized MRI datasets are growing continuously, opening questions on the reliability of results obtained in multi-site contexts. Here we present the assessment of the brain anatomical variability of MRI-derived measurements obtained from T1-weighted images, acquired according to the Standard Operating Procedures, promoted by the RIN-Neuroimaging Network. A multicentric dataset composed of 77 brain T1w acquisitions of young healthy volunteers (mean age = 29.7 ± 5.0 years), collected in 15 sites with MRI scanners of three different vendors, was considered. Parallelly, a dataset of 7 “traveling” subjects, each undergoing three acquisitions with scanners from different vendors, was also used. Intra-site, intra-vendor, and inter-site variabilities were evaluated in terms of the percentage standard deviation of volumetric and cortical thickness measures. Image quality metrics such as contrast-to-noise and signal-to-noise ratio in gray and white matter were also assessed for all sites and vendors. The results showed a measured global variability that ranges from 11% to 19% for subcortical volumes and from 3% to 10% for cortical thicknesses. Univariate distributions of the normalized volumes of subcortical regions, as well as the distributions of the thickness of cortical parcels appeared to be significantly different among sites in 8 subcortical (out of 17) and 21 cortical (out of 68) regions of i nterest in the multicentric study. The Bland-Altman analysis on “traveling” brain measurements did not detect systematic scanner biases even though a multivariate classification approach was able to classify the scanner vendor from brain measures with an accuracy of 0.60 ± 0.14 (chance level 0.33)

Evaluation of iron overload in nigrosome 1 via quantitative susceptibility mapping as a progression biomarker in prodromal stages of synucleinopathies

Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies, such as Parkinson's disease (PD), which are characterized by the loss of dopaminergic neurons in substantia nigra, associated with abnormal iron load. The assessment of presymptomatic biomarkers predicting the onset of neurodegenerative disorders is critical for monitoring early signs, screening patients for neuroprotective clinical trials and understanding the causal relationship between iron accumulation processes and disease development. Here, we used Quantitative Susceptibility Mapping (QSM) and 7T MRI to quantify iron deposition in Nigrosome 1 (N1) in early PD (ePD) patients, iRBD patients and healthy controls and investigated group differences and correlation with disease progression. We evaluated the radiological appearance of N1 and analyzed its iron content in 35 ePD, 30 iRBD patients and 14 healthy controls via T2*-weighted sequences and susceptibility (χ) maps. N1 regions of interest (ROIs) were manually drawn on control subjects and warped onto a study-specific template to obtain probabilistic N1 ROIs. For each subject the N1 with the highest mean χ was considered for statistical analysis. The appearance of N1 was rated pathological in 45% of iRBD patients. ePD patients showed increased N1 χ compared to iRBD patients and HC but no correlation with disease duration, indicating that iron load remains stable during the early stages of disease progression. Although no difference was reported in iron content between iRBD and HC, N1 χ in the iRBD group increases as the disease evolves. QSM can reveal temporal changes in N1 iron content and its quantification may represent a valuable presymptomatic biomarker to assess neurodegeneration in the prodromal stages of PD

Multi-centre and multi-vendor reproducibility of a standardized protocol for quantitative susceptibility Mapping of the human brain at 3T

Quantitative Susceptibility Mapping (QSM) is an MRI-based technique allowing the non-invasive quantification of iron content and myelination in the brain. The RIN – Neuroimaging Network established an optimized and harmonized protocol for QSM across ten sites with 3T MRI systems from three different vendors to enable multicentric studies. The assessment of the reproducibility of this protocol is crucial to establish susceptibility as a quantitative biomarker. In this work, we evaluated cross-vendor reproducibility in a group of six traveling brains. Then, we recruited fifty-one volunteers and measured the variability of QSM values in a cohort of healthy subjects scanned at different sites, simulating a multicentric study. Both voxelwise and Region of Interest (ROI)-based analysis on cortical and subcortical gray matter were performed. The traveling brain study yielded high structural similarity (∼0.8) and excellent reproducibility comparing maps acquired on scanners from two different vendors. Depending on the ROI, we reported a quantification error ranging from 0.001 to 0.017 ppm for the traveling brains. In the cohort of fifty-one healthy subjects scanned at nine different sites, the ROI-dependent variability of susceptibility values, of the order of 0.005–0.025 ppm, was comparable to the result of the traveling brain experiment. The harmonized QSM protocol of the RIN – Neuroimaging Network provides a reliable quantification of susceptibility in both cortical and subcortical gray matter regions and it is ready for multicentric and longitudinal clinical studies in neurological and pychiatric diseases