Eco-Sustainable Silk Fibroin/Pomegranate Peel Extract Film as an Innovative Green Material for Skin Repair

Skin disorders are widespread around the world, affecting people of all ages, and oxidative stress represents one of the main causes of alteration in the normal physiological parameters of skin cells. In this work, we combined a natural protein, fibroin, with antioxidant compounds extracted in water from pomegranate waste. We demonstrate the effective and facile fabrication of bioactive and eco-sustainable films of potential interest for skin repair. The blended films are visually transparent (around 90%); flexible; stable in physiological conditions and in the presence of trypsin for 12 days; able to release the bioactive compounds in a controlled manner; based on Fickian diffusion; and biocompatible towards the main skin cells, keratinocytes and fibroblasts. Furthermore, reactive oxygen species (ROS) production tests demonstrated the high capacity of our films to reduce the oxidative stress induced in cells, which is responsible for various skin diseases.     

15‐Methylene‐Eburnamonine Kills Leukemic Stem Cells and Reduces Engraftment in a Humanized Bone Marrow Xenograft Mouse Model of Leukemia

Recent studies suggest that leukemia stem cells (LSCs) play a critical role in the initiation, propagation, and relapse of leukemia. Herein we show that (?)‐15‐methylene‐eburnamonine, a derivative of the alkaloid (?)‐eburnamonine, is cytotoxic against acute and chronic lymphocytic leukemias (ALL and CLL) and acute myelogenous leukemia (AML). The agent also decreases primary LSC frequency in vitro. The cytotoxic effects appear to be mediated via the oxidative stress pathways. Furthermore, we show that the compound kills AML, ALL, and CLL stem cells. By the use of a novel humanized bone marrow murine model of leukemia (huBM/NSG), it was found to decrease progenitor cell engraftment.     

Docosahexaenoic Acid Levels in Blood and Metabolic Syndrome in Obese Children: Is There a Link?

Prevalence of metabolic syndrome is increasing in the pediatric population. Considering the different existing criteria to define metabolic syndrome, the use of the International Diabetes Federation (IDF) criteria has been suggested in children. Docosahexaenoic acid (DHA) has been associated with beneficial effects on health. The evidence about the relationship of DHA status in blood and components of the metabolic syndrome is unclear. This review discusses the possible association between DHA content in plasma and erythrocytes and components of the metabolic syndrome included in the IDF criteria (obesity, alteration of glucose metabolism, blood lipid profile, and blood pressure) and non-alcoholic fatty liver disease in obese children. The current evidence is inconsistent and no definitive conclusion can be drawn in the pediatric population. Well-designed longitudinal and powered trials need to clarify the possible association between blood DHA status and metabolic syndrome.     

Direct and Indirect Effect of TGFβ on Treg Transendothelial Recruitment in HCC Tissue Microenvironment

The balance between anti-tumor and tumor-promoting immune cells, such as CD4+ Th1 and regulatory T cells (Tregs), respectively, is assumed to dictate the progression of hepatocellular carcinoma (HCC). The transforming growth factor beta (TGFβ) markedly shapes the HCC microenvironment, regulating the activation state of multiple leukocyte subsets and driving the differentiation of cancer associated fibroblasts (CAFs). The fibrotic (desmoplastic) reaction in HCC tissue strongly depends on CAFs activity. In this study, we attempted to assess the role of TGFβ on transendothelial migration of Th1-oriented and Treg-oriented CD4+ T cells via a direct or indirect, CAF-mediated mechanisms, respectively. We found that the blockage of TGFβ receptor I-dependent signaling in Tregs resulted in impaired transendothelial migration (TEM) of these cells. Interestingly, the secretome of TGFβ-treated CAFs inhibited the TEM of Tregs but not Th1 cells, in comparison to the secretome of untreated CAFs. In addition, we found a significant inverse correlation between alpha-SMA and FoxP3 (marker of Tregs) mRNA expression in a microarray analysis involving 78 HCCs, thus suggesting that TGFβ-activated stromal cells may counteract the trafficking of Tregs into the tumor. The apparent dual behavior of TGFβ as both pro- and anti-tumorigenic cytokines may add a further level of complexity to the mechanisms that regulate the interactions among cancerous, stromal, and immune cells within HCC, as well as other solid tumors, and contribute to better manipulation of the TGFβ signaling as a therapeutic target in HCC patients.     

Validation of a Lab-on-Chip Assay for Measuring Sorafenib Effectiveness on HCC Cell Proliferation

Hepatocellular carcinoma (HCC) is a highly lethal cancer, and although a few drugs are available for treatment, therapeutic effectiveness is still unsatisfactory. New drugs are urgently needed for hepatocellular carcinoma (HCC) patients. In this context, reliable preclinical assays are of paramount importance to screen the effectiveness of new drugs and, in particular, measure their effects on HCC cell proliferation. However, cell proliferation measurement is a time-consuming and operator-dependent procedure. The aim of this study was to validate an engineered miniaturized on-chip platform for real-time, non-destructive cell proliferation assays and drug screening. The effectiveness of Sorafenib, the first-line drug mainly used for patients with advanced HCC, was tested in parallel, comparing the gold standard 96-well-plate assay and our new lab-on-chip platform. Results from the lab-on-chip are consistent in intra-assay replicates and comparable to the output of standard crystal violet proliferation assays for assessing Sorafenib effectiveness on HCC cell proliferation. The miniaturized platform presents several advantages in terms of lesser reagents consumption, operator time, and costs, as well as overcoming a number of technical and operator-dependent pitfalls. Moreover, the number of cells required is lower, a relevant issue when primary cell cultures are used. In conclusion, the availability of inexpensive on-chip assays can speed up drug development, especially by using patient-derived samples to take into account disease heterogeneity and patient-specific characteristics.     

Novel Simple Conjugation Chemistries for Decoration of GMMA with Heterologous Antigens

Outer Membrane Vesicles (OMV) constitute a promising platform for the development of efficient vaccines. OMV can be decorated with heterologous antigens (proteins or polysaccharides), becoming attractive novel carriers for the development of multicomponent vaccines. Chemical conjugation represents a tool for linking antigens, also from phylogenetically distant pathogens, to OMV. Here we develop two simple and widely applicable conjugation chemistries targeting proteins or lipopolysaccharides on the surface of Generalized Modules for Membrane Antigens (GMMA), OMV spontaneously released from Gram-negative bacteria mutated to increase vesicle yield and reduce potential reactogenicity. A Design of Experiment approach was used to identify optimal conditions for GMMA activation before conjugation, resulting in consistent processes and ensuring conjugation efficiency. Conjugates produced by both chemistries induced strong humoral response against the heterologous antigen and GMMA. Additionally, the use of the two orthogonal chemistries allowed to control the linkage of two different antigens on the same GMMA particle. This work supports the further advancement of this novel platform with great potential for the design of effective vaccines.     

Multiple clusterings of heterogeneous information networks

Machine Learning - Traditional clustering algorithms focus on a single clustering result; as such, they cannot explore potential diverse patterns of complex real world data. To deal with this...     

Kernel ridge regression for out-of-sample mapping in supervised manifold learning

Manifold learning methods for unsupervised nonlinear dimensionality reduction have proven effective in the visualization of high dimensional data sets. When dealing with classification tasks, supervised extensions of manifold learning techniques, in which class labels are used to improve the embedding of the training points, require an appropriate method for out-of-sample mapping.In this paper we propose multi-output kernel ridge regression (KRR) for out-of-sample mapping in supervised manifold learning, in place of general regression neural networks (GRNN) that have been adopted by previous studies on the subject. Specifically, we consider a supervised agglomerative variant of Isomap and compare the performance of classification methods when the out-of-sample embedding is based on KRR and GRNN, respectively. Extensive computational experiments, using support vector machines and k-nearest neighbors as base classifiers, provide statistical evidence that out-of-sample mapping based on KRR consistently dominates its GRNN counterpart, and that supervised agglomerative Isomap with KRR achieves a higher accuracy than direct classification methods on most data sets.