Testing Antimicrobial Properties of Selected Short Amyloids

Amyloids and antimicrobial peptides (AMPs) have many similarities, e.g., both kill microorganisms by destroying their membranes, form aggregates, and modulate the innate immune system. Given these similarities and the fact that the antimicrobial properties of short amyloids have not yet been investigated, we chose a group of potentially antimicrobial short amyloids to verify their impact on bacterial and eukaryotic cells. We used AmpGram, a best-performing AMP classification model, and selected ten amyloids with the highest AMP probability for our experimental research. Our results indicate that four tested amyloids: VQIVCK, VCIVYK, KCWCFT, and GGYLLG, formed aggregates under the conditions routinely used to evaluate peptide antimicrobial properties, but none of the tested amyloids exhibited antimicrobial or cytotoxic properties. Accordingly, they should be included in the negative datasets to train the next-generation AMP prediction models, based on experimentally confirmed AMP and non-AMP sequences. In the article, we also emphasize the importance of reporting non-AMPs, given that only a handful of such sequences have been officially confirmed.     

The Association between the Bisphenols Residues in Amniotic Fluid and Fetal Abnormalities in Polish Pregnant Women—Its Potential Clinical Application

The present study aimed to investigate the relationship between the concentrations of bisphenols residues in the amniotic fluid (AF) samples collected during amniocentesis and fetal chromosomal abnormalities in pregnant women. A total of 33 pregnant Polish women aged between 24 and 44 years, and screened to detect high risk for chromosomal defects in the first trimester, were included in this study. Samples were collected from these patients during routine diagnostic and treatment procedures at mid-gestation. The concentrations of various bisphenols residues in the samples were determined by liquid chromatography coupled with triple quadrupole tandem mass spectrometry (LC-ESI-QqQ-MS/MS). Residues of eight analytes (BPS, BPF, BPA, BPAF, BADGE, BADGE•2H₂O, BADGE•H₂O•HCl and BADGE•2HCl) were detected in amniotic fluid samples in the range 0.69 ng/mL to 3.38 ng/mL. Fetuses with chromosomal abnormalities showed a slightly higher frequency of occurrence of selected bisphenols residues in the AF samples collected between 15–26 weeks of pregnancies. Finally, the proposed method was applied in the simultaneous determination of several endocrine-disrupting chemicals from bisphenol group in 33 human AF samples. BADGE•H2O•HCl has been identified in the AF samples taken from women older than average in the examined group. The number of detected compounds has been significant for the following analytes: BPS, BPAF, BADGE•H₂O•HCl and BADGE. The proposed method may be an attractive alternative for application in large-scale human biomonitoring studies.     

Is attention all you need for intraday Forex trading?

The main objective of this paper is to analyse whether the Transformer neural network, which has become one of the most influential algorithms in Artificial Intelligence over the last few years, exhibits predictive capabilities for high-frequency Forex data. The prediction task is to classify short-term Forex movements for six currency pairs and five different time intervals from 60 to 720 min. We find that the Transformer exhibits high predictive power in the context of intraday Forex trading. This performance is slightly better than for the carefully selected benchmark – ResNet-LSTM, which currently is a state-of-the-art algorithm. Since intraday Forex trading based on deep learning models is largely unexplored, we offer insight on which currency pair and time interval are amenable to devising a profitable trading strategy. We also show that high predictive accuracy can be misleading in real world trading for short time intervals, as models trained on OHLC data tend to report the highest accuracy when the spread cost is the highest. This renders assessment based on typical machine learning metrics overly optimistic. Therefore, it is critical to backtest frequent intraday Forex trading strategies with realistic cost assumptions, which is rarely the case in empirical literature. Lastly, sensitivity analysis shows that the length of the time interval used for training does not play a critical role in the Transformer's predictive capabilities, whereas features derived from technical analysis are essential.     

Determination of Omega Fatty Acid Profiles in Egg Yolk by HILIC-LC-MS and GC-MS

The paper presents the analysis of the profile composition of fatty acids in the molecules of phosphatidylcholine and phosphatidylethanolamine, by using hydrophilic interaction liquid chromatography and gas chromatography coupled with mass spectrometry. The profiles of 15 phosphatidylcholine and 8 phosphatidylethanolamine species were analyzed with a newly developed hydrophilic interaction liquid chromatography (HILIC)–electrospray ionization (ESI)–tandem mass spectroscopy (MS/MS) method, by using a new stationary bonded phase. The application of the new method in control and experimental groups of egg yolk revealed significant differences in the composition of phospholipid species containing mainly polyunsaturated fatty acids. Additionally, using GC-MS, the profile of fatty acids in four groups with different dietary supplementation of hens was analyzed and 20 fatty acids in egg yolks were determined. Monounsaturated fatty acids were found in higher amounts than saturated fatty acids and polyunsaturated fatty acids in egg yolks. Oleic acid (18:1) was the major monounsaturated fatty acid in egg yolk while palmitic acid (16:0) was the major saturated fatty acid. Linoleic acid (18:2), arachidonic acid (20:4), and docosahexaenoic acid (22:6) reached the highest levels among the polyunsaturated fatty acids.     

Varied Composition of Tocochromanols in Different Types of Bran: Rye,Wheat, Oat,Spelt, Buckwheat,Corn, and Rice

The profiles of tocopherol (T) and tocotrienol (T3) homologues in 37 samples of seven different types of bran (rye, wheat, oat, spelt, buckwheat, rice, and corn), available on the Polish market, were studied. Tocochromanols were identified and quantified by reverse phase-high-performance liquid chromatograph/fluorescence detector and reverse phase-ultra performance liquid chromatography-electrospray ionization/mass spectrometry. Only rice bran contained all eight tocochromanol types. Corn bran lacked β-T3; rye, wheat, oat, and spelt bran lacked γ-T3 and δ-T3; and buckwheat bran lacked β-T3, γ-T3, and δ-T3. In buckwheat and corn bran tocopherols predominated (98 and 78%, respectively); whereas rye, wheat, oat, spelt, and rice bran were rich in tocotrienols (78, 76, 66, 87, and 66%, respectively). The average total tocochromanol contents in the oat, corn, spelt, buckwheat, wheat, rye, and rice bran were 5.5, 16.2, 15.8, 14.7, 12.8, 10.7, and 9.1 mg/100 g of dry weight, respectively. Tocochromanol concentrations in samples of the same type bran from different sources varied considerably. Better labeling of bran products to reflect this variation would assist with control of vitamin E daily dietary requirements.     

Determination of Antioxidant Activity and Polyphenols Content in Chips by Raman and IR Spectroscopy

The application of vibrational spectroscopy for the determination of total polyphenols content, antioxidant activity, colour parameters, and fat level in chips originated from yellow-, red- and purple-fleshed potato varieties is reported. Raman, infrared (IR) and near-infrared (NIR) spectra of the laboratory-prepared chips were collected. Combining spectral data with the results of reference analyses, partial least squares regression models were built. To characterise and compare the elaborated models, the relative standard errors of prediction were calculated for calibration and validation sets. In the case of total phenolics quantification by Raman/IR/NIR techniques, these errors (%) amounted to 4.0/7.0/7.1 and 6.4/8.5/8.4 for calibration and validation samples, respectively, whereas they were 4.9/7.7/4.8 and 6.6/8.3/6.8 for antioxidant activity. The obtained results demonstrate that both infrared and Raman spectroscopy can effectively replace commonly used extraction methods. It follows that Raman spectroscopy has the highest potential to be adopted for the online potato-derived product analysis.     

An Advanced Analysis of Cloud Computing Concepts Based on the Computer Science Ontology

Our primary research hypothesis stands on a simple idea: The evolution of top-rated publications on a particular theme depends heavily on the progress and maturity of related topics. And this even when there are no clear relations or some concepts appear to cease to exist and leave place for newer ones starting many years ago. We implemented our model based on Computer Science Ontology (CSO) and analyzed 44 years of publications. Then we derived the most important concepts related to Cloud Computing (CC) from the scientific collection offered by Clarivate Analytics. Our methodology includes data extraction using advanced web crawling techniques, data preparation, statistical data analysis, and graphical representations. We obtained related concepts after aggregating the scores using the Jaccard coefficient and CSO Ontology. Our article reveals the contribution of Cloud Computing topics in research papers in leading scientific journals and the relationships between the field of Cloud Computing and the interdependent subdivisions identified in the broader framework of Computer Science.