New Poly(N-isopropylacrylamide-butylacrylate) Copolymer Biointerfaces and Their Characteristic Influence on Cell Behavior In Vitro

Designing and obtaining new synthetic smart biointerfaces with specific and controlled characteristics relevant for applications in biomedical and bioengineering domains represents one of the main challenges in these fields. In this work, Matrix-Assisted Pulsed Laser Evaporation (MAPLE) is used to obtain synthetic biointerfaces of poly(N-isopropyl acrylamide-butyl acrylate) p(NIPAM-BA) copolymer with different characteristics (i.e., roughness, porosity, wettability), and their effect on normal HEK 293 T and murine melanoma B16-F1 cells is studied. For this, the influence of various solvents (chloroform, dimethylsulfoxide, water) and fluence variation (250–450 mJ/cm²) on the morphological, roughness, wettability, and physico–chemical characteristics of the coatings are evaluated by atomic force microscopy, scanning electron microscopy, contact angle measurements, Fourier-transform-IR spectroscopy, and X-ray photoelectron spectroscopy. Coatings obtained by the spin coating method are used for reference. No significant alteration in the chemistry of the surfaces is observed for the coatings obtained by both methods. All p(NIPAM-BA) coatings show hydrophilic character, with the exception of those obtained with chloroform at 250 mJ/cm². The surface morphology is shown to depend on both solvent type and laser fluence and it ranges from smooth surfaces to rough and porous ones. Physico–chemical and biological analysis reveal that the MAPLE deposition method with fluences of 350–450 mJ/cm² when using DMSO solvent is more appropriate for bioengineering applications due to the surface characteristics (i.e., pore presence) and to the good compatibility with normal cells and cytotoxicity against melanoma cells.     

miRNA Expression Profiling in Subcutaneous Adipose Tissue of Monozygotic Twins Discordant for HIV Infection: Validation of Differentially Expressed miRNA and Bioinformatic Analysis

Combined AntiRetroviral Treatments (cARTs) used for HIV infection may result in varied metabolic complications, which in some cases, may be related to patient genetic factors, particularly microRNAs. The use of monozygotic twins, differing only for HIV infection, presents a unique and powerful model for the controlled analysis of potential alterations of miRNAs regulation consequent to cART treatment. Profiling of 2578 mature miRNA in the subcutaneous (SC) adipose tissue and plasma of monozygotic twins was investigated by the GeneChip^® miRNA 4.1 array. Real-time PCR and ddPCR experiments were performed in order to validate differentially expressed miRNAs. Target genes of deregulated miRNAs were predicted by the miRDB database (prediction score > 70) and enrichment analysis was carried out with g:Profiler. Processes in SC adipose tissue most greatly affected by miRNA up-regulation included (i) macromolecular metabolic processes, (ii) regulation of neurogenesis, and (iii) protein phosphorylation. Furthermore, KEGG analysis revealed miRNA up-regulation involvement in (i) insulin signaling pathways, (ii) neurotrophin signaling pathways, and (iii) pancreatic cancer. By contrast, miRNA up-regulation in plasma was involved in (i) melanoma, (ii) p53 signaling pathways, and (iii) focal adhesion. Our findings suggest a mechanism that may increase the predisposition of HIV⁺ patients to insulin resistance and cancer.     

Application of GC–MSD and LC–MS/MS for the determination of priority pesticides in baby foods in Serbian market

Babies and small children are especially sensitive population to the exposure to environmental contaminants. Their small mass and developing systems, including brain development may show adverse health effects from even low levels of contamination on a chronic or single dose case. In this paper one extraction method and two chromatographic techniques for the determination of pesticide residues in baby food were evaluated. A liquid chromatography–tandem mass spectrometry technique combined with electrospray ionization (ESI), (LC–MS/MS) and gas chromatography–mass spectrometry detection (GC–MSD) technique were applied in the detection of 50 pesticides in baby food. So-called QuEChERS (quick, easy, cheap, effective, rugged and safe) method was used as a sample preparation procedure. The recoveries were investigated at three levels (5, 10 and 50 μg/kg) and the results obtained showed compliance with the contemporary EU requirements with a few exceptions. LOQs for most of the tested pesticides were below the EU MRLs (10 μg/kg), except deltamethrin, cypermethrin, fenvalerate, phosalone and beta-cyfluthrin (LOQs were 10 μg/kg). Both techniques were applied in the analysis of 50 samples of baby food manufactured in Serbia.     

The Expression of Active CD11b Monocytes in Blood and Disease Progression in Amyotrophic Lateral Sclerosis

Monocytes expressing the inflammation suppressing active CD11b, a beta2 integrin, may regulate neuroinflammation and modify clinical outcomes in amyotrophic lateral sclerosis (ALS). In this single site, retrospective study, peripheral blood mononuclear cells from 38 individuals living with ALS and 20 non-neurological controls (NNC) were investigated using flow cytometry to study active CD11b integrin classical (CM), intermediate (IM) and non-classical (NCM) monocytes during ALS progression. Seventeen ALS participants were sampled at the baseline (V1) and at two additional time points (V2 and V3) for longitudinal analysis. Active CD11b+ CM frequencies increased steeply between the baseline and V3 (ANOVA repeated measurement, p < 0.001), and the V2/V1 ratio negatively correlated with the disease progression rate, similar to higher frequencies of active CD11b+ NCM at the baseline (R = −0.6567; p = 0.0031 and R = 0.3862; p = 0.0168, respectively). CD11b NCM, clinical covariates and neurofilament light-chain plasma concentration at the baseline predicted shorter survival in a multivariable and univariate analysis (CD11b NCM—HR: 1.05, CI: 1.01–1.11, p = 0.013. Log rank: above median: 43 months and below median: 21.22 months; p = 0.0022). Blood samples with the highest frequencies of active CD11b+ IM and NCM contained the lowest concentrations of soluble CD11b. Our preliminary data suggest that the levels of active CD11b+ monocytes and NCM in the blood predict different clinical outcomes in ALS.     

Cancer-Related Cachexia: The Vicious Circle between Inflammatory Cytokines,Skeletal Muscle,Lipid Metabolism and the Possible Role of Physical Training

Cachexia is a multifactorial and multi-organ syndrome that is a major cause of morbidity and mortality in late-stage chronic diseases. The main clinical features of cancer-related cachexia are chronic inflammation, wasting of skeletal muscle and adipose tissue, insulin resistance, anorexia, and impaired myogenesis. A multimodal treatment has been suggested to approach the multifactorial genesis of cachexia. In this context, physical exercise has been found to have a general effect on maintaining homeostasis in a healthy life, involving multiple organs and their metabolism. The purpose of this review is to present the evidence for the relationship between inflammatory cytokines, skeletal muscle, and fat metabolism and the potential role of exercise training in breaking the vicious circle of this impaired tissue cross-talk. Due to the wide-ranging effects of exercise training, from the body to the behavior and cognition of the individual, it seems to be able to improve the quality of life in this syndrome. Therefore, studying the molecular effects of physical exercise could provide important information about the interactions between organs and the systemic mediators involved in the overall homeostasis of the body.     

Assessing the health research’s social impact: a systematic review

Scientometrics - In recent year, a growing attention is dedicated to the assessment of research’s social impact. While prior research has often dealt with results of research, the last decade...     

Modeling of dibenzothiophene oxidative desulfurization using response surface methodology

The effect of reaction temperature, mixing speed and oxidant to catalyst volume ratio, including their interactions on the oxidative desulfurization of dibenzothiophene by using response surface methodology was studied. Hydrogen peroxide was used as oxidant and acetic acid as catalyst. The obtained model accurately predicts conversion of dibenzothiophene and the best conversion of 98.7% was observed at temperature 70°C, mixing speed of 1250 rpm and oxidant to catalyst volume ratio of 1:1. At high temperatures, a major limitation of the desulfurization process is the mass transfer and the high mixing speed is needed to achieve an efficient process.     

Optimal attacks on qubit-based Quantum Key Recycling

Quantum Key Recycling (QKR) is a quantum cryptographic primitive that allows one to reuse keys in an unconditionally secure way. By removing the need to repeatedly generate new keys, it improves communication efficiency. ?kori? and de Vries recently proposed a QKR scheme based on 8-state encoding (four bases). It does not require quantum computers for encryption/decryption but only single-qubit operations. We provide a missing ingredient in the security analysis of this scheme in the case of noisy channels: accurate upper bounds on the required amount of privacy amplification. We determine optimal attacks against the message and against the key, for 8-state encoding as well as 4-state and 6-state conjugate coding. We provide results in terms of min-entropy loss as well as accessible (Shannon) information. We show that the Shannon entropy analysis for 8-state encoding reduces to the analysis of quantum key distribution, whereas 4-state and 6-state suffer from additional leaks that make them less effective. From the optimal attacks we compute the required amount of privacy amplification and hence the achievable communication rate (useful information per qubit) of qubit-based QKR. Overall, 8-state encoding yields the highest communication rates.     

Data clustering based on quantum synchronization

Natural Computing - There exists a specific class of methods for data clustering problem inspired by synchronization of coupled oscillators. This approach requires an extension of the classical...     

Analysis of medications change in Parkinson’s disease progression data

Parkinson’s disease is a neurodegenerative disorder that affects people worldwide. Careful management of patient’s condition is crucial to ensure the patient’s independence and quality of life. This is achieved by personalized treatment based on individual patient’s symptoms and medical history. The aim of this study is to determine patient groups with similar disease progression patterns coupled with patterns of medications change that lead to the improvement or decline of patients’ quality of life symptoms. To this end, this paper proposes a new methodology for clustering of short time series of patients’ symptoms and prescribed medications data, and time sequence data analysis using skip-grams to monitor disease progression. The results demonstrate that motor and autonomic symptoms are the most informative for evaluating the quality of life of Parkinson’s disease patients. We show that Parkinson’s disease patients can be divided into clusters ordered in accordance with the severity of their symptoms. By following the evolution of symptoms for each patient separately, we were able to determine patterns of medications change which can lead to the improvement or worsening of the patients’ quality of life.