Biodegradation study of some food packaging biopolymers based on PVA

Abstract Polymers are a common choice as protective materials since they combine flexibility, variable sizes and shapes, relatively light weight, stability, resistance to breaking, barrier properties and perceived high-quality image with cost-effectiveness. Currently, mainly non-biodegradable petroleum-based synthetic polymers are used as packaging materials for foods, because of their availability, low cost and functionality. However, biopolymers can be made from renewable resources without the environmental issues of petroleum-based polymers and with the additional advantage of being available from renewable sources or as by-products or waste-products from the food and agriculture industries. The aim of this study was to test some food packaging biopolymers based on PVA. In this respect, some biopolymers for food packaging applications were subjected to biodegradation tests by covering the tested samples with soil. The samples were incubated in known temperature and humidity conditions. The experiment lasted 45 days, after that the samples were washed, weighed and the biodegradation degree was calculated. The obtained results shows that PVA is a promising material for food packaging usage, as it is made from renewable resources and it is environmentally friendly.Â

From land to glass. An integrated approach for quality and traceability assessment of top Italian wines

The wine sector in Italy is a significant contributor to the country's economy. Furthermore, Italy is renowned for producing some of the world's most excellent wines. For these reasons, the wine industry is susceptible to frauds, such as reporting false origin claims in labels. In this context, this paper aims to provide traceability and quality tool to recognise wines from different Italian regions, i.e. Calabria, Piemonte, Sicily and Veneto, from selected winemakers that reach the Top 10% in almost three international rankings. The multi-elemental analysis of soil and wine samples by ICP-MS and their chemometric treatments have identified Ni, Cs, Li, Ca, Ba, Pb, Rb, Sb, Fe and U as the most informative variables to reach optimal classification of samples. The analytical data have been used to develop an original managerial framework to leverage Pareto's Principle for effective brand-land management in the top wine segment

Embedding Temporal Convolutional Networks for Energy-efficient PPG-based Heart Rate Monitoring

Photoplethysmography (PPG) sensors allow for non-invasive and comfortable heart rate (HR) monitoring, suitable for compact wrist-worn devices. Unfortunately, motion artifacts (MAs) severely impact the monitoring accuracy, causing high variability in the skin-to-sensor interface. Several data fusion techniques have been introduced to cope with this problem, based on combining PPG signals with inertial sensor data. Until now, both commercial and reasearch solutions are computationally efficient but not very robust, or strongly dependent on hand-tuned parameters, which leads to poor generalization performance. In this work, we tackle these limitations by proposing a computationally lightweight yet robust deep learning-based approach for PPG-based HR estimation. Specifically, we derive a diverse set of Temporal Convolutional Networks for HR estimation, leveraging Neural Architecture Search. Moreover, we also introduce ActPPG, an adaptive algorithm that selects among multiple HR estimators depending on the amount of MAs, to improve energy efficiency. We validate our approaches on two benchmark datasets, achieving as low as 3.84 beats per minute of Mean Absolute Error on PPG-Dalia, which outperforms the previous state of the art. Moreover, we deploy our models on a low-power commercial microcontroller (STM32L4), obtaining a rich set of Pareto optimal solutions in the complexity vs. accuracy space

A multi-analytical approach to studying the chemical composition of typical carbon sink samples

Peatlands in southern South America (Tierra del Fuego region, TdF) play a key role in the ecological dynamics of Patagonia. It is, therefore, necessary to increase our knowledge and awareness of their scientific and ecological value to ensure their conservation. This study aimed to assess the differences in the distribution and accumulation of elements in peat deposits and Sphagnum moss from the TdF. Chemical and morphological characterization of the samples was carried out using various analytical techniques, and total levels of 53 elements were determined. Furthermore, a chemometric differentiation based on the elemental content of peat and moss samples was performed. Some elements (Cs, Hf, K, Li, Mn, Na, Pb, Rb, Si, Sn, Ti and Zn) showed significantly higher contents in moss samples than in peat samples. In contrast, only Mo, S and Zr were significantly higher in peat samples than in moss samples. The results obtained highlight the ability of moss to accumulate elements and to act as a means to facilitate the entry of elements into peat samples. The valuable data obtained in this multi-methodological baseline survey can be used for more effective conservation of biodiversity and preservation of the ecosystem services of the TdF

Molecular Subtypes of Extra-pulmonary Neuroendocrine Carcinomas Identified by the Expression of Neuroendocrine Lineage-Specific Transcription Factors

Extra-pulmonary neuroendocrine carcinomas (EPNEC) represent a group of rare and heterogenous neoplasms with adverse clinical outcome. Their molecular profile is largely unexplored. Our aim was to investigate if the major transcriptional drivers recently described in high-grade pulmonary neuroendocrine carcinomas characterize distinct molecular and clinical subgroups of EPNEC. Gene expression of ASCL1, NEUROD1, DLL3, NOTCH1, INSM1, MYCL1, POU2F3, and YAP1 was investigated in a series of 54 EPNEC (including 10 cases with mixed components analyzed separately) and in a group of 48 pulmonary large cell neuroendocrine carcinomas (P-LCNEC). Unsupervised hierarchical cluster analysis classified the whole series into four major clusters. P-LCNEC were classified into two major clusters, the first ASCL1/DLL3/INSM1-high and the second (including four EPNEC) ASCL1/DLL3-low but INSM1-high. The remaining EPNEC cases were sub-classified into two other clusters. The first showed INSM1-high and alternative ASCL1/DLL3 or NEUROD1 high expression. The second was characterized mainly by MYCL1 and YAP1 overexpression. In the ten cases with mixed histology, ASCL1, DLL3, INSM1, and NEUROD1 genes were significantly upregulated in the neuroendocrine component. Higher gene-expression levels of NOTCH1 and INSM1 were associated with lower pT stage and negative nodal status. Low INSM1 gene expression was associated with shorter overall survival in the entire case series (p = 0.0017) and with a trend towards significance in EPNEC, only (p = 0.06). In conclusion, our results show that EPNEC possess distinct neuroendocrine-lineage-specific transcriptional profiles; moreover, low INSM1 gene expression represents a novel potential unfavorable prognostic marker in high-grade NECs including those in extra-pulmonary location

New Evidences on the Process Sensitivity of Some Renewable Blends Based on Starch considering Their Melt Rheological Properties

The degradability and processability of new renewable materials based on starch and PVOH were studied using the melt flow index (MFI) method by measuring the melt rheological properties which depend not only on the extrusion conditions and material formulation but also on the macromolecule characteristics which can be modified by chemical degradation. These results were correlated with other material properties like color and cross-linking degree. The obtained results show that flowing in the melted state of the studied materials is accompanied by a second process of chains chemical degradation. It was observed that, at the same level of additivation, under identical extrusion conditions, the melted blends with corn starch as main component are highly mechanically sensitive and degrade mostly by chains scission and those with PVOH as major component are highly temperature sensitive and degrade mainly by cross-linking. The obtained results show also that each PVOH-starch blend requires particular formulation and individual windows of melt processing conditions. These results are a good proof that the MFI method is a good path to study the degradability and moldability of process sensitive polymeric materials like those based on starch and PVOH

Commercial hemp seed oils: a multimethodological characterization

Nine commercial hemp seed oils from different countries were studied using a multimethodological approach to obtain information about their quality and chemical composition. Due to the lack of a specific regulation for hemp seed oils, quality parameters used in the case of olive oils (free acidity, peroxides number, spectrophotometer parameters) and anisidine number were measured and compared with those reported for extra virgin olive oil (EVOO). Free acidity and peroxides number showed a great variability, ranging from 0.4 to 17.24% and from 4.32 to 22.14 meqO2/kg, respectively, whereas the anisidine number ranged from 0.11 to 3.58. K232 value turned out to be generally below the limit reported for EVOO, whereas K270 and ΔK values were higher, with respect to EVOO limits, due to the high amount of tri-unsaturated fatty chains. Colorimetric analysis showed a peculiar curve trend that could represent the fingerprint of this product. Untargeted nuclear magnetic resonance methodology allowed to measure the amount of fatty chains, ω-6:ω-3 ratio, β-sitosterol, and aldehydes. The ω-6:ω-3 ratio turned out to be, in some cases, different from that reported on the bottle labels. Finally, lipoperoxidation assays were also carried out under different storage (light and temperature) and time exposure conditions, confirming that the exposure to direct light is the condition that interferes more with the product quality

Chemico-biological characterization of Torpedino Di Fondi® tomato fruits. A comparison with San Marzano cultivar at two ripeness stages

Torpedino di Fondi (TF) is a hybrid tomato landrace developed in Sicily and recently introduced in the south Lazio area along with the classical San Marzano (SM) cultivar. The present study aimed at characterizing TF tomatoes at both pink and red ripening stages, and at comparing them with traditional SM tomatoes. A multidisciplinary approach consisting of morphological, chemical (FT‐ICR MS, NMR, HPLC, and spectrophotometric methods), and biological (antioxidant and antifungal in vitro activity) analyses was applied. Morphological analysis confirmed the mini‐ San Marzano nature and the peculiar crunchy and solid consistency of TF fruits. Pink TF tomatoes displayed the highest content of hydrophilic antioxidants, like total polyphenols (0.192 mg/g), tannins (0.013 mg/g), flavonoids (0.204 mg/g), and chlorophylls a (0.344 mg/g) and b (0.161 mg/g), whereas red TF fruits were characterized by the highest levels of fructose (3000 mg/100 g), glucose (2000 mg/100 g), tryptophan (2.7 mg/100 g), phenylalanine (13 mg/100 g), alanine (25 mg/100 g), and total tri‐unsaturated fatty acids (13% mol). Red SM fruits revealed the greatest content of lipophilic antioxidants, with 1234 mg/g of total carotenoids. In agreement with phenolics content, TF cultivar showed the greatest antioxidant activity. Lastly, red TF inhibited Candida species (albicans, glabrata and krusei) growth

A Multimethodological Characterization of Cannabis sativa L. Inflorescences from Seven Dioecious Cultivars Grown in Italy: The Effect of Different Harvesting Stages

The chemical profile of the female inflorescence extracts from seven Cannabis sativa L. dioecious cultivars (Carmagnola, Fibranova, Eletta Campana, Antal, Tiborszallasi, Kompolti, and Tisza) was monitored at three harvesting stages (4, 14, and 30 September), reaching from the be ginning of flowering to end of flowering/beginning of seed formation, using untargeted nuclear magnetic resonance (NMR) and targeted (ultra-high-performance liquid chromatography (UHPLC) and spectrophotometry) analyses. The tetrahydrocannabinol content was always below the legal limits (<0.6%) in all the analyzed samples. The NMR metabolite profile (sugars, organic acids, amino acids, and minor compounds) subjected to principal components analysis (PCA) showed a strong variability according to the harvesting stages: samples harvested in stage I were characterized by a high content of sucrose and myo-inositol, whereas the ones harvested in stage II showed high levels of succinic acid, alanine, valine, isoleucine, phenylalanine, and threonine. Samples harvested in stage III were characterized by high levels of glucose, fructose, choline, trigonelline, malic acid, formic acid, and some amino acids. The ratio between chlorophylls and carotenoids content indicated that all plants grew up exposed to the sun, the Eletta Campana cultivar having the highest pigment amount. Tiborszallasi cultivar showed the highest polyphenol content. The highest antioxidant activity was generally observed in stage II. All these results suggested that the Cannabis sativa L. inflorescences of each analyzed dioecious hemp cultivar presented a peculiar chemical profile affected by the harvesting stage. This information could be useful for producers and industries to harvest inflorescences in the appropriate stage to obtain samples with a peculiar chemical profile suitable for proper applications.15s