Assessment of a protease inhibitor peptide for anti-ageing

Ageing and skin exposure to UV radiation induces production and activation of matrix metalloproteinases (MMPs) and human neutrophil elastase (HNE). These enzymes are known to break down the extracellular matrix (ECM) which leads to wrinkle formation. Here, we demonstrated the potential of a solid-in-oil nanodispersion containing a competitive inhibitor peptide of HNE mixed with hyaluronic acid (HA), displaying 158 nm of mean diameter, to protect the skin against the ageing effects. Western blot analysis demonstrated that activation of MMP-1 in fibroblasts by HNE treatment is inhibited by the solid-in-oil nanodispersion containing the peptide and HA. The results clearly demonstrate that solid-in-oil nanodispersion containing the HNE inhibitor peptide is a promising strategy for anti-ageing effects. This effect can be seen particularly by ECM regulation by affecting fibroblasts. The formulation also enhances the formation of thicker bundles of actin filaments.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Lower NPAS3 expression during the later stages of abnormal lung development in rat congenital diaphragmatic hernia

Purpose Congenital diaphragmatic hernia (CDH) is characterized by a developmental defect in the diaphragm, pulmonary hypoplasia and pulmonary hypertension. NPAS3 is a PAS domain transcription factor regulating Drosophila tracheogenesis. NPAS3 null mice develop pulmonary hypoplasia in utero and die after birth due to respiratory failure. We aimed to evaluate NPAS3 expres- sion during normal and abnormal lung development due to CDH. Methods CDH was induced by administering 100 mg/ml nitrofen to time-pregnant dams on embryonic day (E) 9 of gestation. Lungs were isolated on E15, E18 and E21 and NPAS3 localization was determined by immunohisto- chemistry and quantified using Western blotting. Results We found that only E21 hypoplastic CDH lungs have reduced expression of NPAS3 in the terminal sac- cules. Western blotting confirmed the down-regulation of NPAS3 protein in the nitrofen-induced hypoplastic lungs. Conclusions We demonstrate for the first time that ni- trofen-induced hypoplastic CDH lungs have reduced NPAS3 expression in the terminal saccules during the later stages of abnormal lung development. Our findings suggest that NPAS3 is associated with pulmonary hypoplasia in CDH.

Micro- and mesoporous structures as drug delivery carriers for salicylic acid

The potential of salicylic acid (SA) encapsulated in porous materials as drug delivery carriers for cancer treatment was studied. Different porous structures, the microporous zeolite NaY, and the mesoporous SBA-15 and MCM-41 were used as hosts for the anti-inflammatory drug. Characterization with different techniques (FTIR, UV/vis, TGA, 1H NMR, and 13C CPMAS NMR) demonstrated the successful loading of SA into the porous hosts. The mesoporous structures showed to be very efficient to encapsulate the SA molecule. The obtained drug delivery systems (DDS) accommodated 0.74 mmol (341 mg/gZEO) in NaY and 1.07 mmol (493 mg/gZEO) to 1.23 mmol (566 mg/gZEO) for SBA-15 and MCM-41, respectively. Interactions between SA molecules and pore structures were identified. A fast and unrestricted liberation of SA at 10 min of the dissolution assay was achieved with 29.3, 46.6, and 50.1 µg/mL of SA from NaY, SBA-15, and MCM-41, respectively, in the in vitro drug release studies (PBS buffer pH 7.4, 37 °C). Kinetic modeling was used to determine the release patterns of the DDS. The porous structures and DDS were evaluated on Hs578T and MDA-MB-468 breast cancer cell lines viability. The porous structures are nontoxic to cancer cells. Cell viability reduction was only observed after the release of SA from MCM- 41 followed by SBA-15 in both breast cancer cell lines.

Pulse wave velocity distribution in a cohort study: from arterial stiffness to early vascular aging

BACKGROUND: By contrast with other southern European people, north Portuguese population registers an especially high prevalence of hypertension and stroke incidence. We designed a cohort study to identify individuals presenting accelerated and premature arterial aging in the Portuguese population. METHOD: Pulse wave velocity (PWV) was measured in randomly sampled population dwellers aged 18-96 years from northern Portugal, and used as a marker of early vascular aging (EVA). Of the 3038 individuals enrolled, 2542 completed the evaluation. RESULTS: Mean PWV value for the entire population was 8.4?m/s (men: 8.6?m/s; women: 8.2?m/s; P??10?m/s). Logistic regression models indicated gender differences concerning the risk of developing large artery damage, with women having the same odds of PWV above 10?m/s 10 years later than men. CONCLUSION: The population PWV values were higher than expected in a low cardiovascular risk area (Portugal). High prevalence rates of EVA and noteworthy large artery damage in young ages were found.

An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

Comorbid depression and anxiety effects on pregnancy and neonatal outcome

The effects of comorbid depression and anxiety were compared to the effects of depression alone and anxiety alone on pregnancy mood states and biochemistry and on neonatal outcomes in a large multi-ethnic sample. At the prenatal period the comorbid and depressed groups had higher scores than the other groups on the depression measure. But, the comorbid group had higher anxiety, anger and daily hassles scores than the other groups, and they had lower dopamine levels. As compared to the non-depressed group, they also reported more sleep disturbances and relationship problems. The comorbid group also experienced a greater incidence of prematurity than the depressed, the high anxiety and the non-depressed groups. Although the comorbid and anxiety groups were lower birthweight than the non-depressed and depressed groups, the comorbid group did not differ from the depressed and anxiety groups on birth length. The neonates of the comorbid and depressed groups had higher cortisol and norepinephrine and lower dopamine and serotonin levels than the neonates of the anxiety and non-depressed groups as well as greater relative right frontal EEG. These data suggest that for some measures comorbidity of depression and anxiety is the worst condition (e.g., incidence of prematurity), while for others, comorbidity is no more impactful than depression alone.

Pregnancy massage reduces prematurity, low birthweight and postpartum depression

Pregnant women diagnosed with major depression were given 12 weeks of twice per week massage therapy by their significant other or only standard treatment as a control group. The massage therapy group women versus the control group women not only had reduced depression by the end of the therapy period, but they also had reduced depression and cortisol levels during the postpartum period. Their newborns were also less likely to be born prematurely and low birthweight, and they had lower cortisol levels and performed better on the Brazelton Neonatal Behavioral Assessment habituation, orientation and motor scales.

Prenatal dopamine and neonatal behavior and biochemistry

Depressed pregnant women (N=126) were divided into high and low prenatal maternal dopamine (HVA) groups based on a tertile split on their dopamine levels at 20 weeks gestation. The high versus the low dopamine group had lower Center for Epidemiological Studies-Depression Scale (CES-D) scores, higher norepinephrine levels at the 20-week gestational age visit and higher dopamine and serotonin levels at both the 20- and the 32-week gestational age visits. The neonates of the mothers with high versus low prenatal dopamine levels also had higher dopamine and serotonin levels as well as lower cortisol levels. Finally, the neonates in the high dopamine group had better autonomic stability and excitability scores on the Brazelton Neonatal Behavior Assessment Scale. Thus, prenatal maternal dopamine levels appear to be negatively related to prenatal depression scores and positively related to neonatal dopamine and behavioral regulation, although these effects are confounded by elevated serotonin levels.