Comparative Analysis of Amino Acid Profiles in Patients with Glioblastoma and Meningioma Using Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS).

Brain tumors account for 1% of all cancers diagnosed de novo. Due to the specificity of the anatomical area in which they grow, they can cause significant neurological disorders and lead to poor functional status and disability. Regardless of the results of biochemical markers of intracranial neoplasms, they are currently of no diagnostic significance. The aim of the study was to use LC-ESI-MS/MS in conjunction with multivariate statistical analyses to examine changes in amino acid metabolic profiles between patients with glioblastoma, meningioma, and a group of patients treated for osteoarthritis of the spine as a control group. Comparative analysis of amino acids between patients with glioblastoma, meningioma, and the control group allowed for the identification of statistically significant differences in the amino acid profile, including both exogenous and endogenous amino acids. The amino acids that showed statistically significant differences (lysine, histidine, α-aminoadipic acid, phenylalanine) were evaluated for diagnostic usefulness based on the ROC curve. The best results were obtained for phenylalanine. Classification trees were used to build a model allowing for the correct classification of patients into the study group (patients with glioblastoma multiforme) and the control group, in which cysteine turned out to be the most important amino acid in the decision-making algorithm. Our results indicate amino acids that may prove valuable, used alone or in combination, toward improving the diagnosis of patients with glioma and meningioma. To better assess the potential utility of these markers, their performance requires further validation in a larger cohort of samples.

Predicting Antitumor Activity of Anthrapyrazole Derivatives using Advanced Machine Learning Techniques.

BACKGROUND: Anthrapyrazoles are a new class of antitumor agents and successors to anthracyclines possessing a broad range of antitumor activity in various model tumors. OBJECTIVE: The present study introduces novel QSAR models for the prediction of antitumor activity of anthrapyrazole analogues. METHODS: The predictive performance of four machine learning algorithms, namely artificial neural networks, boosted trees, multivariate adaptive regression splines, and random forest, was studied in terms of variation of the observed and predicted data, internal validation, predictability, precision, and accuracy. RESULTS: ANN and boosted trees algorithms met the validation criteria. It means that these procedures may be able to forecast the anticancer effects of the anthrapyrazoles studied. Evaluation of validation metrics, calculated for each approach, indicated the artificial neural network (ANN) procedure as the algorithm of choice, especially with regard to the obtained predictability as well as the lowest value of mean absolute error. The designed multilayer perceptron (MLP)-15-7-1 network displayed a high correlation between the predicted and the experimental pIC50 value for the training, test, and validation set. A conducted sensitivity analysis enabled an indication of the most important structural features of the studied activity. CONCLUSION: The ANN strategy combines topographical and topological information and can be used for the design and development of novel anthrapyrazole analogues as anticancer molecules.

Quantitative Structure-Activity Relationship Analysis of Isosteviol-Related Compounds as Activated Coagulation Factor X (FXa) Inhibitors.

Stevioside, one of the natural sweeteners extracted from stevia leaves, and its derivatives are considered to have numerous beneficial pharmacological properties, including the inhibition of activated coagulation factor X (FXa). FXa-PAR signaling is a possible therapeutic target to enhance impaired metabolism and insulin resistance in obesity. Thus, the goal of the investigation was a QSAR analysis using multivariate adaptive regression splines (MARSplines) applied to a data set of 20 isosteviol derivatives bearing thiourea fragments with possible FXa inhibitory action. The best MARS submodel described a strong correlation between FXa inhibitory activity and molecular descriptors, such as: B01[C-Cl], E2m, L3v, Mor06i, RDF070i and HATS7s. Five out of six descriptors included in the model are geometrical descriptors quantifying three-dimensional aspects of molecular structure, which indicates that the molecular three-dimensional conformation is of high significance for the MARSplines modeling procedure and obviously for FXa inhibitory activity. High model performance was confirmed through an extensive validation protocol. The results of the study not only confirmed the enhancement in pharmacological activity by the presence of chlorine in a phenyl ring, but also, and primarily, may provide the basis for searching for new active isosteviol analogues, which may serve as drugs or health-beneficial food additives in patients suffering from obesity and comorbidities.

Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Antitumor Activity of Anthrapyrazole Derivatives.

An approach using multivariate adaptive regression splines (MARSplines) was applied for quantitative structure-activity relationship studies of the antitumor activity of anthrapyrazoles. At the first stage, the structures of anthrapyrazole derivatives were subjected to geometrical optimization by the AM1 method using the Polak-Ribiere algorithm. In the next step, a data set of 73 compounds was coded over 2500 calculated molecular descriptors. It was shown that fourteen independent variables appearing in the statistically significant MARS model (i.e., descriptors belonging to 3D-MoRSE, 2D autocorrelations, GETAWAY, burden eigenvalues and RDF descriptors), significantly affect the antitumor activity of anthrapyrazole compounds. The study confirmed the benefit of using a modern machine learning algorithm, since the high predictive power of the obtained model had proven to be useful for the prediction of antitumor activity against murine leukemia L1210. It could certainly be considered as a tool for predicting activity against other cancer cell lines.

Selected Drug-Likeness Properties of 2-Arylidene-indan-1,3-dione Derivatives-Chemical Compounds with Potential Anti-Cancer Activity.

2-Arylidene-indan-1,3-done derivatives have very different properties, thanks to which they find various applications in science, medicine, and industry. Selected derivatives show antiviral, antibacterial, and anti-inflammatory activity. This paper presents a procedure for the synthesis of a series of indan-1,3-dione derivatives that present antiproliferative activity. The aim of the work was to develop a method of simple synthesis and purification, evaluate the fulfillment of the Lipinski's and Veber's rule, and determine the potential scope of application of the obtained series of compounds. The structure of the synthesized compounds was confirmed, and their lipophilicity was determined using experimental and computational methods. Their antiproliferative activity against selected cell lines was tested in accordance with the MTT protocol; the ability to bind to albumin was tested, and the parameters related to the toxicity of substances in silico were determined. The selected compounds which showed antiproliferative activity were strongly bound to albumin and, in most cases, met the Lipinski's and Veber's rule. Thus, the obtained results suggest that 2-arylidene-indan-1,3-done derivatives appear to be good candidates for drugs with a potential leading structure for further development.

Surface properties of stationary phases with embedded polar group based on secondary interaction, zeta potential measurement and linear solvatation energy relationship studies.

The chromatographic properties of six non-commercially available stationary phases with ester or phosphodiester functional groups embedded into alkyl chain were studied. Zeta potential values of stationary phases suspended in water, organic solvent and their mixtures were measured. Moreover, the selectivity coefficients were calculated on the basis of the retention factor for the test solutes. Separations were performed under hydrophilic interaction liquid chromatographic conditions. Hydrophobic and polar properties of the investigated columns were compared. Based on the chromatographic properties, polar embedded packing materials were classified. Also two phases with different spacer but the same embedded polar group and alkyl chain (Amino-P-C18 and Diol-P-C18) were used for comparison with homemade materials. Amino-P-C18 stationary phase exhibits positive values of zeta potential which is in accordance with the observed anion exchange properties. The highest negative values of zeta potential were observed for Diol-P-C18, together with cation exchange properties. The highest methylene selectivity, polar selectivity and configurational selectivity were observed for the stationary phase with an ester bond and a phenyl group.

Comparison of Pteridine Normalization Methods in Urine for Detection of Bladder Cancer.

Pterin compounds belong to the group of biomarkers for which an increase in interest has been observed in recent years. Available literature data point to this group of compounds as potential biomarkers for cancer detection, although the biochemical justification for this claim is not yet fully understood. The aim of this study was to evaluate the usefulness of pterin compounds in the diagnosis of bladder cancer, with particular emphasis on the role of creatinine and the specific gravity of urine as factors for normalizing the concentration of pterin compounds in urine. The standardization of the concentration of pterin compounds to urine specific gravity allows the building of better classification models for screening patients with potential cancer of the bladder. Of the compounds that make up the pterin profile, isoxanthopterin appears to be a compound that can potentially be described as a biomarker of bladder cancer.

Fermentation parameters and conditions affecting levan production and its potential applications in cosmetics.

Levan is a polysaccharide composed of fructose units with ß-2,6-glycoside bonds. Microorganisms synthesize levan by levansucrase as a mixture of low- and high-molecular-weight fractions. Due to its properties, it has a wide range of applications in cosmetics, pharmaceuticals, food and medicine; it appears that the molecular weight of levan might impact its industrial use. To obtain one fraction of levan after biotransformation, ethanol precipitation with an increasing volume of alcohol was conducted. This precipitation process was also optimized. Several types of analyses were used. Low-molecular-weight levan was evaluated for toxicity in a normal human dermal fibroblast cell line and hemolytic potential on human erythrocytes. Levan was found to be non-cytotoxic and non-hemolytic in concentrations ranging from 0.01 to 1.00 mg/ml. Moreover, levan demonstrated antioxidant potential expressed as an ability to inhibit of oil/water emulsion oxidation and DPPH radical scavenging.

Indandione and Its Derivatives - Chemical Compounds with High Biological Potential.

Indandione is a hydrocarbon classified as bicyclic aromatic ß-diketone. It can be applied in many fields of science and industry. It is successfully used as a substrate in organic synthesis, pharmaceutical sciences and as a substrate for the production of dyes. Indandione derivatives and analogs are useful in medicine, chemistry and the judiciary. Among the indandione derivatives can find compounds that have interesting properties and many of them have biological activity (incl. anticancer, anticoagulation, anti-inflamatory, antimicrobial activities). Based on the indan-1,3-dione structure created acetylcholinesterase inhibitors. Indan-1,3-dione derivatives are also used as a derivating agent for the analysis of fatty aldehydes and a substance that is an element of dye-sensitized solar cells. This work presents a brief overview of construction, properties and activities of indandione and its derivatives. This work describes selected indandione derivatives that have properties useful in medicine and industry with particular regard to the anticoagulants and neuroprotective activities in AD.