Trace Metals in Pork Meat Products Marketed in Italy: Occurrence and Health Risk Characterization

This study provides valuable information on the levels of various trace metals (Pb, Cd, Hg, Zn, Cu, Cr) in meat products (baked ham, raw ham, mortadella, cured sausage, würstel, salami) from South Italy and calculates potential health risk toxicity associated with their consumption for the total population and for children. In the samples studied metal concentrations are within the permissible legal limits (Cd: 0.01–0.03 μg g−1 w.w., Hg: 0.01–0.02 μg g−1 w.w., Zn: 5.71–7.32 μg g−1 w.w., Cu: 1.08–1.21 μg g−1 w.w., Cr: 0.15–0.23 μg g−1 w.w.), except for Pb (Pb: 0.22–0.38 μg g−1 w.w.). The estimated intake values are within the provisional tolerable daily intake limits for toxic metals and recommended daily intake values for essential metals in both tested groups. The noncarcinogenic risk values of the individual metals indicate that there is no health risk, but their combined effects might constitute a potential risk for children. Furthermore, the cumulative cancer risk of all samples studied exceeds the recommended threshold risk limit (> 10−4) in both total population and children, indicating a risk of potential health problems for consumers especially for children, who are more vulnerable to toxic metal exposure

Purple sulfur bacteria fix N-2 via molybdenum-nitrogenase in a low molybdenum Proterozoic ocean analogue

Biological N-2 fixation was key to the expansion of life on early Earth. The N-2-fixing microorganisms and the nitrogenase type used in the Proterozoic are unknown, although it has been proposed that the canonical molybdenum-nitrogenase was not used due to low molybdenum availability. We investigate N-2 fixation in Lake Cadagno, an analogue system to the sulfidic Proterozoic continental margins, using a combination of biogeochemical, molecular and single cell techniques. In Lake Cadagno, purple sulfur bacteria (PSB) are responsible for high N-2 fixation rates, to our knowledge providing the first direct evidence for PSB in situ N-2 fixation. Surprisingly, no alternative nitrogenases are detectable, and N-2 fixation is exclusively catalyzed by molybdenum-nitrogenase. Our results show that molybdenum-nitrogenase is functional at low molybdenum conditions in situ and that in contrast to previous beliefs, PSB may have driven N-2 fixation in the Proterozoic ocean. N-2 fixation was key to the expansion of life on Earth, but which organisms fixed N-2 and if Mo-nitrogenase was functional in the low Mo early ocean is unknown. Here, the authors show that purple sulfur bacteria fix N-2 using Mo-nitrogenase in a Proterozoic ocean analogue, despite low Mo conditions

Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set

Many patients with multiple sclerosis (MS) experience information processing speed (IPS) deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid screening test. Magnetic resonance imaging (MRI) has markedly improved the understanding of the mechanisms associated with cognitive deficits in MS. However, which structural MRI markers are the most closely related to cognitive performance is still unclear. We used the multicenter 3T-MRI data set of the Italian Neuroimaging Network Initiative to extract multimodal data (i.e., demographic, clinical, neuropsychological, and structural MRIs) of 540 MS patients. We aimed to assess, through machine learning techniques, the contribution of brain MRI structural volumes in the prediction of IPS deficits when combined with demographic and clinical features. We trained and tested the eXtreme Gradient Boosting (XGBoost) model following a rigorous validation scheme to obtain reliable generalization performance. We carried out a classification and a regression task based on SDMT scores feeding each model with different combinations of features. For the classification task, the model trained with thalamus, cortical gray matter, hippocampus, and lesions volumes achieved an area under the receiver operating characteristic curve of 0.74. For the regression task, the model trained with cortical gray matter and thalamus volumes, EDSS, nucleus accumbens, lesions, and putamen volumes, and age reached a mean absolute error of 0.95. In conclusion, our results confirmed that damage to cortical gray matter and relevant deep and archaic gray matter structures, such as the thalamus and hippocampus, is among the most relevant predictors of cognitive performance in MS

A Semiautomatic Method for Multiple Sclerosis Lesion Segmentation on Dual-Echo MR Imaging: Application in a Multicenter Context

BACKGROUND AND PURPOSE: The automatic segmentation of MS lesions could reduce time required for image processing together with inter- and intraoperator variability for research and clinical trials. A multicenter validation of a proposed semiautomatic method for hyperintense MS lesion segmentation on dual-echo MR imaging is presented. MATERIALS AND METHODS: The classification technique used is based on a region-growing approach starting from manual lesion identification by an expert observer with a final segmentation-refinement step. The method was validated in a cohort of 52 patients with relapsing-remitting MS, with dual-echo images acquired in 6 different European centers. RESULTS: We found a mathematic expression that made the optimization of the method independent of the need for a training dataset. The automatic segmentation was in good agreement with the manual segmentation (dice similarity coefficient = 0.62 and root mean square error = 2 mL). Assessment of the segmentation errors showed no significant differences in algorithm performance between the different MR scanner manufacturers (P > .05). CONCLUSIONS: The method proved to be robust, and no center-specific training of the algorithm was required, offering the possibility for application in a clinical setting. Adoption of the method should lead to improved reliability and less operator time required for image analysis in research and clinical trials in MS

Design and validation of a DNA-microarray for phylogenetic analysis of bacterial communities in different oral samples and dental implants

The quali-quantitative characterization of the oral microbiota is crucial for an exhaustive knowledge of the oral ecology and the modifications of the microbial composition that occur during periodontal pathologies. In this study, we designed and validated a new phylogenetic DNA-microarray (OralArray) to quickly and reliably characterize the most representative bacterial groups that colonize the oral cavity. The OralArray is based on the Ligation Detection Reaction technology associated to Universal Arrays (LDR-UA), and includes 22 probe sets targeted to bacteria belonging to the phyla Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, Fusobacteria, and Spirochaete. The tool is characterized by high specificity, sensitivity and reproducibility. The OralArray was successfully tested and validated on different oral samples (saliva, lingual plaque, supragingival plaque, and healing cap) collected from 10 healthy subjects. For each specimen, a microbial signature was obtained, and our results established the presence of an oral microbial profile specific for each subject. Moreover, the tool was applied to evaluate the efficacy of a disinfectant treatment on the healing caps before their usage. The OralArray is, thus, suitable to study the microbiota associated with various oral sites and to monitor changes arising from therapeutic treatments

Resting-state functional MRI in multicenter studies on multiple sclerosis: a report on raw data quality and functional connectivity features from the Italian Neuroimaging Network Initiative

The Italian Neuroimaging Network Initiative (INNI) is an expanding repository of brain MRI data from multiple sclerosis (MS) patients recruited at four Italian MRI research sites. We describe the raw data quality of resting-state functional MRI (RS-fMRI) time-series in INNI and the inter-site variability in functional connectivity (FC) features after unified automated data preprocessing. MRI datasets from 489 MS patients and 246 healthy control (HC) subjects were retrieved from the INNI database. Raw data quality metrics included temporal signal-to-noise ratio (tSNR), spatial smoothness (FWHM), framewise displacement (FD), and differential variation in signals (DVARS). Automated preprocessing integrated white-matter lesion segmentation (SAMSEG) into a standard fMRI pipeline (fMRIPrep). FC features were calculated on pre-processed data and harmonized between sites (Combat) prior to assessing general MS-related alterations. Across centers (both groups), median tSNR and FWHM ranged from 47 to 84 and from 2.0 to 2.5, and median FD and DVARS ranged from 0.08 to 0.24 and from 1.06 to 1.22. After preprocessing, only global FC-related features were significantly correlated with FD or DVARS. Across large-scale networks, age/sex/FD-adjusted and harmonized FC features exhibited both inter-site and site-specific inter-group effects. Significant general reductions were obtained for somatomotor and limbic networks in MS patients (vs. HC). The implemented procedures provide technical information on raw data quality and outcome of fully automated preprocessing that might serve as reference in future RS-fMRI studies within INNI. The unified pipeline introduced little bias across sites and appears suitable for multisite FC analyses on harmonized network estimates

Mineral analysis of complete dog and cat foods in the UK and compliance with European guidelines

Mineral content of complete pet food is regulated to ensure health of the companion animal population. Analysis of adherence to these regulatory guidelines has not been conducted. Here, mineral composition of complete wet (n = 97) and dry (n = 80) canine and feline pet food sold in the UK was measured to assess compliance with EU guidelines. A majority of foods complied with ≥8 of 11 guidelines (99% and 83% for dry and wet food, respectively), but many failed to provide nutritional minimum (e.g. Cu, 20% of wet food) or exceeded nutritional maximum (e.g. Se, 76% of wet food). Only 6% (6/97) of wet and 38% (30/80) of dry food were fully compliant. Some foods (20–30% of all analysed) had mineral imbalance, such as not having the recommended ratio of Ca:P (between 1:1 to 2:1). Foods with high fish content had high levels of undesirable metal elements such as arsenic. This study highlights broad non-compliance of a range of popular pet foods sold in the UK with EU guidelines (94% and 61% of wet and dry foods, respectively). If fed exclusively and over an extended period, a number of these pet foods could impact the general health of companion animals