The effect of acetylsalicylic acid dosed at bedtime on the anti-aggregation effect in patients with coronary heart disease and arterial hypertension: A randomized, controlled trial

Background: Acetylsalicylic acid (ASA) is one of the basic drugs used in the secondary prevention ofcoronary artery disease (CAD), and in most cases it is taken in the morning in one daily dose. It is suggestedthat the morning peak of platelet aggregation is responsible for the occurrence of myocardial infarctionsand strokes. Hence, the aim of the study was to observe the effect of ASA (morning vs. evening)dosing on the anti-aggregative effect of platelets in patients with CAD and arterial hypertension (AH).Methods: The study involved 175 patients with CAD and AH. Patients were randomly assigned toone of two study groups, taking ASA in the morning or in the evening. The patients had two visits, onebaseline and another after 3 months from changing the time of ASA dosage. The platelet aggregationwas determined using the VerifyNow analyzer.Results: In the ASA evening group, a significant reduction in platelet aggregation was obtained. Inthe ASA morning group, a significant difference in response to ASA was observed, depending on sex. Inmen, the reactivity of platelets decreased, but in women it increased.Conclusions: In the group of patients with CAD and AH, bedtime ASA dosing is associated witha significant reduction in platelet aggregation. The response to ASA may differ between sexes. The benefitgained by changing the drug administration from the morning to the evening is greater in women

Exploring Subcellular Responses of Prostate Cancer Cells to X-Ray Exposure by Raman Mapping

Understanding the response of cancer cells to ionising radiation is a crucial step in modern radiotherapy. Raman microspectroscopy, together with Partial Least Squares Regression (PLSR) analysis has been shown to be a powerful tool for monitoring biochemical changes of irradiated cells on the subcellular level. However, to date, the majority of Raman studies have been performed using a single spectrum per cell, giving a limited view of the total biochemical response of the cell. In the current study, Raman mapping of the whole cell area was undertaken to ensure a more comprehensive understanding of the changes induced by X-ray radiation. On the basis of the collected Raman spectral maps, PLSR models were constructed to elucidate the time-dependent evolution of chemical changes induced in cells by irradiation, and the performance of PLSR models based on whole cell averages as compared to those based on average Raman spectra of cytoplasm and nuclear region. On the other hand, prediction of X-ray doses for individual cellular component showed that cytoplasmic and nuclear regions should be analysed separately. Finally, the advantage of the mapping technique over single point measurements was verified by a comparison of the corresponding PLSR models

Raman spectroscopy of urinary extracellular vesicles to stratify patients with chronic kidney disease in type 2 diabetes

In this study, we verified the hypothesis that Raman signature of urinary extracellular vesicles (UEVs) can be used to stratify patients with diabetes at various stages of chronic kidney disease (CKD). Patients with type 2 diabetes diagnosed with different stages of CKD and healthy subjects were enrolled in the study. UEVs were isolated using low-vacuum filtration followed by ultracentrifugation. Correlation analysis, multiple linear regression and principal component analysis were used to find differences between spectral fingerprints of UEVs derived from both groups of patients. Electron microscopy and nanoparticle tracking analysis were applied to characterize the size and morphology of UEVs. We observed significant correlations between selected Raman bands measured for UEVs and clinical parameters. We found significant differences in the area under the specific bands originating mainly from proteins and lipids between the study groups. Based on the tryptophan and amide III bands, we were able to predict the estimated glomerular filtration rate (eGFR). Principal component analysis, partial least squares regression (PLSR) and correlation analysis of the UEV Raman spectra supported the results obtained from the direct analysis of Raman spectra. Our analysis revealed that PLSR and a regression model including tryptophan and amide III bands allows to estimate the value of eGFR

Structure and Biological Properties of Surface-Engineered Carbon Nanofibers

The aim of this work was to manufacture, using the electrospinning technique, polyacrylonitrile- (PAN-) based carbon nanofibers in the form of mats for biomedical applications. Carbon nanofibers obtained by carbonization of the PAN nanofibers to 1000°C (electrospun carbon nanofibers (ECNF)) were additionally oxidized in air at 800°C under reduced pressure (electrospun carbon nanofibers oxidized under reduced pressure (ECNFV)). The oxidative treatment led to partial removal of a structurally less-ordered carbon phase from the near-surface region of the carbon nanofibers. Both types of carbon fibrous mats were studied using scanning electron microscopy (SEM), high-resolution transmission electron microscopy (TEM), XRD, and Raman spectroscopy. The morphology, microstructure, and surface properties of both materials were analyzed. The oxidative treatment of carbon nanofibers significantly changed their surface morphology and physical properties (wettability, surface electrical resistance). Biological tests (genotoxicity, fibroblast, and human osteoblast-like MG63 cultures) were carried out in contact with both materials. Genotoxicity study conducted by means of comet assays revealed significant differences between both carbon nanofibers. Fibroblasts contacted with the as-received carbon nanofibers (ECNF) showed a significantly higher level of DNA damage compared to control and oxidized carbon nanofibers (ECNFV). The ECNFV nanofibers were not cytotoxic, whereas ECNF nanofibers contacted with both types of cells indicated a cytotoxic effect. The ECNFV introduced into cell culture did not affect the repair processes in the cells contacting them

The Impact of Preprocessing Methods for a Successful Prostate Cell Lines Discrimination Using Partial Least Squares Regression and Discriminant Analysis Based on Fourier Transform Infrared Imaging

Fourier transform infrared spectroscopy (FT-IR) is widely used in the analysis of the chemical composition of biological materials and has the potential to reveal new aspects of the molecular basis of diseases, including different types of cancer. The potential of FT-IR in cancer research lies in its capability of monitoring the biochemical status of cells, which undergo malignant transformation and further examination of spectral features that differentiate normal and cancerous ones using proper mathematical approaches. Such examination can be performed with the use of chemometric tools, such as partial least squares discriminant analysis (PLS-DA) classification and partial least squares regression (PLSR), and proper application of preprocessing methods and their correct sequence is crucial for success. Here, we performed a comparison of several state-of-the-art methods commonly used in infrared biospectroscopy (denoising, baseline correction, and normalization) with the addition of methods not previously used in infrared biospectroscopy classification problems: Mie extinction extended multiplicative signal correction, Eiler’s smoothing, and probabilistic quotient normalization. We compared all of these approaches and their effect on the data structure, classification, and regression capability on experimental FT-IR spectra collected from five different prostate normal and cancerous cell lines. Additionally, we tested the influence of added spectral noise. Overall, we concluded that in the case of the data analyzed here, the biggest impact on data structure and performance of PLS-DA and PLSR was caused by the baseline correction; therefore, much attention should be given, especially to this step of data preprocessing

Highly effective protocol for differentiation of induced pluripotent stem cells (iPS) into melanin-producing cells

Melanin is a black/brown pigment present in abundance in human skin. Its main function is photo-protection of underlying tissues from harmful UV light. Natural sources of isolated human melanin are limited; thus, in vitro cultures of human cells may be a promising source of human melanin. Here, we present an innovative in vitro differentiation protocol of induced pluripotent stem cells (iPS) into melanin-producing cells, delivering highly pigmented cells in quantity and quality incomparably higher than any other methods previously described. Pigmented cells constitute over 90% of a terminally differentiated population and exhibit features characteristic for melanocytes, i.e., expression of specific markers such as MITF-M (microphthalmia-associated transcription factor isoform M), TRP-1 (tyrosinase-related protein 1), and TYR (tyrosinase) and accumulation of black pigment in organelles closely resembling melanosomes. Black pigment is unambiguously identified as melanin with features corresponding to those of melanin produced by typical melanocytes. The advantage of our method is that it does not require any sophisticated procedures and can be conducted in standard laboratory conditions. Moreover, our protocol is highly reproducible and optimized to generate high-purity melanin-producing cells from iPS cells; thus, it can serve as an unlimited source of human melanin for modeling human skin diseases. We speculate that FGF-8 might play an important role during differentiation processes toward pigmented cells