Surface Nucleation of Dispersed Droplets in Double Semicrystalline Immiscible Blends with Different Matrices

When a minor semicrystalline phase is dispersed in an immiscible blend with another polymer in the form of isolated droplets, its crystallization behavior is dominated by nucleation. In particular, nucleation can occur in the bulk volume of the phase (homogeneous nucleation), at the surface of possible nucleating foreign impurities, or at the interface with the matrix polymer. Dispersed poly(butene-1) (PB) and polycaprolactone (PCL) droplet phases are employed in various matrices (isotactic polypropylene (iPP), high density polyethylene (HDPE), poly(vinylidene fluoride) (PVDF) and poly(butylene succinate) (PBS)). The effect of matrix self-nucleation on the crystallization of the dispersed droplet phase is then probed. It is shown for all the investigated polymer blends that increasing the matrix crystallization temperature (T-c) via self-nucleation favors droplet nucleation at the interface, leading to a corresponding increase in the droplets'; T-c. Interestingly, distinct nucleation effects are observed when different polymer matrices are compared. The highest nucleating efficiency is displayed by the polymer pairs, which are known to exhibit epitaxial crystallization from previous literature, namely PB/iPP and PCL/HDPE. The order of nucleation efficiency of the other matrices is thought to be linked with the extent of crystallographic matching between the substrate and nucleating crystals.W.W. thanks the China Scholarship Council (CSC) for funding his Ph.D scholarship. The authors acknowledge the financial support from the BIODEST project; this project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 778092. G.L. and A.J.M. acknowledge the financial support from the National Key R&D Program of China (2017YFE0117800). Open Access Funding provided by Universita degli Studi di Genova within the CRUI-CARE Agreement

Small Subcutaneous Soft Tissue Tumors (<5 cm) Can Be Sarcomas and Contrast-Enhanced Ultrasound (CEUS) Is Useful to Identify Potentially Malignant Masses

Subcutaneous masses smaller than 5 cm can be malignant, in contrast with the international guidelines. Ultrasound (US) and magnetic resonance imaging (MRI) are useful to distinguish a potentially malignant mass from the numerous benign soft tissue (ST) lesions. Contrast-enhanced ultrasound (CEUS) was applied in ST tumors, without distinguishing the subcutaneous from the deep lesions. We evaluated CEUS and MRI accuracy in comparison to histology in differentiating malignant from nonmalignant superficial ST masses, 50% smaller than 5 cm. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) with their 95% confidence intervals (CI) were calculated. Of malignant cases, 44.4% measured &le;5 cm. At univariate analysis, no statistically significant differences emerged between benign and malignant tumors in relation with clinical characteristics, except for relationship with the deep fascia (p = 0.048). MRI accuracy: sensitivity 52.8% (CI 37.0, 68.0), specificity 74.1% (CI 55.3, 86.8), PPV 73.1% (CI 53.9, 86.3), and NPV 54.1% (CI 38.4, 69.0). CEUS accuracy: sensitivity 75% (CI 58.9, 86.3), specificity 37% (CI 21.5, 55.8), PPV 61.4% (CI 46.6, 74.3), and NPV 52.6% (CI 31.7, 72.7). CEUS showed a sensitivity higher than MRI, whereas PPV and NPV were comparable. Also, masses measuring less than 5 cm can be malignant and referral criteria for centralization could be revised

The Healthy Fatty Index Allows for Deeper Insights into the Lipid Composition of Foods of Animal Origin When Compared with the Atherogenic and Thrombogenicity Indexes

The aim of this research was to validate the effectiveness of the Healthy Fatty Index (HFI) regarding some foods of animal origin (meat, processed, fish, milk products, and eggs) typical of the Western diet and to compare these results with two consolidated indices (atherogenic-AI, and thrombogenic-TI) in the characterization of the nutritional features of their lipids. The fatty acids profile (% of total fatty acids and mg/100 g) of 60 foods, grouped in six subclasses, was used. The AI, TI, and HFI indexes were calculated, and the intraclass correlation coefficients and the degree of agreement were evaluated using different statistical approaches. The results demonstrated that HFI, with respect to AI and TI, seems better able to consider the complexity of the fatty acid profile and the different fat contents. HFI and AI are the two most diverse indices, and they can provide different food classifications. AI and IT exhibit only a fair agreement in regards to food classification, confirming that such indexes are always to be considered indissolubly and never separately, in contrast to the HFI, which can stand alone