Biodegradability Study of the Biosurfactant Contained in a Crude Extract from Corn Steep Water

Over the last few years, the global biosurfactant market has raised due to the increasing awareness among consumers, for the use of biological or bio-based products. Because of their composition, it can be speculated that these are more biocompatible and more biodegradable than their chemical homologous. However, at the moment, no studies exist in the literature about the biodegradability of biosurfactants. In this work, a biosurfactant contained in a crude extract, obtained from a corn wet-milling industry stream that ferments spontaneously in the presence of lactic acid bacteria, was subjected to a biodegradation study, without addition of external microbial biomass, under different conditions of temperature (5–45 °C), biodegradation time (15–55 days), and pH (5–7). For that, a Box–Behnken factorial design was applied, which allowed to predict the percentage of biodegradation for the biosurfactant contained in the crude extract, between the range of the independent variables selected in the study, obtaining biodegradation values between 3 and 80%. The percentage of biodegradation for the biosurfactant was calculated based on the increase in the surface tension of samples of the crude extract. Furthermore, it was also possible to predict the variation in t_1/2 for the biosurfactant (time to achieve the 50% of biodegradation) under different conditions.     

Target Score—A Proteomics Data Selection Tool Applied to Esophageal Cancer Identifies GLUT1-Sialyl Tn Glycoforms as Biomarkers of Cancer Aggressiveness

Esophageal cancer (EC) is a life-threatening disease, demanding the discovery of new biomarkers and molecular targets for precision oncology. Aberrantly glycosylated proteins hold tremendous potential towards this objective. In the current study, a series of esophageal squamous cell carcinomas (ESCC) and EC-derived circulating tumor cells (CTCs) were screened by immunoassays for the sialyl-Tn (STn) antigen, a glycan rarely expressed in healthy tissues and widely observed in aggressive gastrointestinal cancers. An ESCC cell model was glycoengineered to express STn and characterized in relation to cell proliferation and invasion in vitro. STn was found to be widely present in ESCC (70% of tumors) and in CTCs in 20% of patients, being associated with general recurrence and reduced survival. Furthermore, STn expression in ESCC cells increased invasion in vitro, while reducing cancer cells proliferation. In parallel, an ESCC mass spectrometry-based proteomics dataset, obtained from the PRIDE database, was comprehensively interrogated for abnormally glycosylated proteins. Data integration with the Target Score, an algorithm developed in-house, pinpointed the glucose transporter type 1 (GLUT1) as a biomarker of poor prognosis. GLUT1-STn glycoproteoforms were latter identified in tumor tissues in patients facing worst prognosis. Furthermore, healthy human tissues analysis suggested that STn glycosylation provided cancer specificity to GLUT1. In conclusion, STn is a biomarker of worst prognosis in EC and GLUT1-STn glycoforms may be used to increase its specificity on the stratification and targeting of aggressive ESCC forms.     

Lipofilling in Breast Oncological Surgery: A Safe Opportunity or Risk for Cancer Recurrence?

Lipofilling (LF) is a largely employed technique in reconstructive and esthetic breast surgery. Over the years, it has demonstrated to be extremely useful for treatment of soft tissue defects after demolitive or conservative breast cancer surgery and different procedures have been developed to improve the survival of transplanted fat graft. The regenerative potential of LF is attributed to the multipotent stem cells found in large quantity in adipose tissue. However, a growing body of pre-clinical evidence shows that adipocytes and adipose-derived stromal cells may have pro-tumorigenic potential. Despite no clear indication from clinical studies has demonstrated an increased risk of cancer recurrence upon LF, these observations challenge the oncologic safety of the procedure. This review aims to provide an updated overview of both the clinical and the pre-clinical indications to the suitability and safety of LF in breast oncological surgery. Cellular and molecular players in the crosstalk between adipose tissue and cancer are described, and heterogeneous contradictory results are discussed, highlighting that important issues still remain to be solved to get a clear understanding of LF safety in breast cancer patients.     

A New Tool to Study Parkinsonism in the Context of Aging: MPTP Intoxication in a Natural Model of Multimorbidity

The diurnal rodent Octodon degus (O. degus) is considered an attractive natural model for Alzheimer’s disease and other human age-related features. However, it has not been explored so far if the O. degus could be used as a model to study Parkinson’s disease. To test this idea, 10 adult male O. degus were divided into control group and MPTP-intoxicated animals. Motor condition and cognition were examined. Dopaminergic degeneration was studied in the ventral mesencephalon and in the striatum. Neuroinflammation was also evaluated in the ventral mesencephalon, in the striatum and in the dorsal hippocampus. MPTP animals showed significant alterations in motor activity and in visuospatial memory. Postmortem analysis revealed a significant decrease in the number of dopaminergic neurons in the ventral mesencephalon of MPTP animals, although no differences were found in their striatal terminals. We observed a significant increase in neuroinflammatory responses in the mesencephalon, in the striatum and in the hippocampus of MPTP-intoxicated animals. Additionally, changes in the subcellular expression of the calcium-binding protein S100β were found in the astrocytes in the nigrostriatal pathway. These findings prove for the first time that O. degus are sensitive to MPTP intoxication and, therefore, is a suitable model for experimental Parkinsonism in the context of aging.     

Stereospecific distribution of fatty acids in triacylglycerols of olive oils

The positional distribution of fatty acids (FA) in triacylglycerols (TAG) of 47 virgin olive oils from diverse cultivars grown in distinct areas of North‐Eastern Italy was studied. Few data were previously available on oils from these geographical areas. The effects of climatic and geographical conditions on the stereospecific distribution of TAG in olive oil were confirmed. Moreover, the results of the stereospecific analysis were used to evaluate the preferential esterification position of each FA on the basis of the degree of unsaturation and the chain length. The data of the stereospecific analysis of olive oil TAG can contribute to the determination of the selectivity of olive fruit acyltransferases for distinct FA.     

Providing security and fault tolerance in P2P connections between clouds for mHealth services

The mobile health (mHealth) and electronic health (eHealth) systems are useful to maintain a correct administration of health information and services. However, it is mandatory to ensure a secure data transmission and in case of a node failure, the system should not fall down. This fact is important because several vital systems could depend on this infrastructure. On the other hand, a cloud does not have infinite computational and storage resources in its infrastructure or would not provide all type of services. For this reason, it is important to establish an interrelation between clouds using communication protocols in order to provide scalability, efficiency, higher service availability and flexibility which allow the use of services, computing and storage resources of other clouds. In this paper, we propose the architecture and its secure protocol that allows exchanging information, data, services, computing and storage resources between all interconnected mHealth clouds. The system is based on a hierarchic architecture of two layers composed by nodes with different roles. The routing algorithm used to establish the connectivity between the nodes is the shortest path first (SPF), but it can be easily changed by any other one. Our architecture is highly scalable and allows adding new nodes and mHealth clouds easily, while it tries to maintain the load of the cloud balanced. Our protocol design includes node discovery, authentication and fault tolerance. We show the protocol operation and the secure system design. Finally we provide the performance results in a controlled test bench.     

A greedy randomized adaptive search procedure for the point-feature cartographic label placement

The point-feature cartographic label placement problem (PFCLP) is an NP-hard problem, which appears during the production of maps. The labels must be placed in predefined places avoiding overlaps and considering cartographic preferences. Owing to its high complexity, several heuristics have been presented searching for approximated solutions. This paper proposes a greedy randomized adaptive search procedure (GRASP) for the PFCLP that is based on its associated conflict graph. The computational results show that this metaheuristic is a good strategy for PFCLP, generating better solutions than all those reported in the literature in reasonable computational times.     

A review on the combination of binary classifiers in multiclass problems

Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.     

Lagrangean relaxation with clusters for point-feature cartographic label placement problems

This paper presents two new mathematical formulations for the point-feature cartographic label placement problem (PFCLP) and a new Lagrangean relaxation with clusters (LagClus) to provide bounds to these formulations. The PFCLP can be represented by a conflict graph and the relaxation divides the graph in small subproblems (clusters) that are easily solved. The edges connecting clusters are relaxed in a Lagrangean way and a subgradient algorithm improves the bounds. The LagClus was successfully applied to a set of instances up to 1000 points providing the best results of those reported in the literature.     

Malicious uses of blockchains by malware: from the analysis to Smart-Zephyrus

The permanent availability and relative obscurity of blockchains is the perfect ground for using them for malicious purposes. However, the use of blockchains by malwares has not been characterized yet. This paper analyses the current state of the art in this area. One of the lessons learned is that covert communications for malware have received little attention. To foster further defence-oriented research, a novel mechanism (dubbed Smart-Zephyrus) is built leveraging smart contracts written in Solidity. Our results show that it is possible to hide 4 Kb of secret in 41 s. While being expensive (around USD 1.82 per bit), the provided stealthiness might be worth the price for attackers.