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Purpose Study on curcumin dissolved in natural deep eutectic solvents (NADES) was aimed at exploiting their beneficial properties as drug carriers. Methods The concentration of dissolved curcumin in NADES was measured. Simulated gastrointestinal fluids were used to determine the concentration of curcumin and quantum chemistry computations were performed for clarifying the origin of curcumin solubility enhancement in NADES. Results NADES comprising choline chloride and glycerol had the highest potential for curcumin dissolution. This system was also successfully applied as an extraction medium for obtaining curcuminoids from natural sources, as well as an effective stabilizer preventing curcumin degradation from sunlight. The solubility of curcumin in simulated gastrointestinal fluids revealed that the significant increase of bioavailability takes place in the small intestinal fluid. Conclusions Suspension of curcumin in NADES offers beneficial properties of this new liquid drug formulation starting from excreting from natural sources, through safe storage and ending on the final administration route. Therefore, there is a possibility of using a one-step process with this medium. The performed quantum chemistry computations clearly indicated the origin of the enhanced solubility of curcumin in NADES in the presence of intestinal fluids. Direct intermolecular contacts leading to hetero-molecular pairs with choline chloride and glycerol are responsible for elevating the bulk concentration of curcumin. Choline chloride plays a dominant role in the system and the complexes formed with curcumin are the most stable among all possible homo- and hetero-molecular pairs that can be found in NADES-curcumin systems.

The DF-MP2 quantum chemistry method was applied to a description of the stacking interactions of uracil and cytosine with five model amino acid residues, namely histidine (HIS), phenylalanine (PHE), tyrosine (TYR), tryptophan (TRP) and an arginyl moiety (ARG). The BSSE and complete basis set corrections were taken into account. Both uracil (U) and cytosine (C) may strongly interact with amino acid residues. The stacking energy is very sensitive to both the nature of the interacting monomers and their spatial conformations. However, usually considerable configurational degrees of freedom are observed, leading to similar stacking energies. The overall order of optimized stacking complexes corresponds to the following sequence: C-TRP (-16.0 kcal mol(-1)) > U-TRP (-13.5 kcal mol(-1)) > U-TYR (-12.2 kcal mol(-1)) > U-HIS (-8.7 kcal mol(-1)) > U-PHE (-7.7 kcal mol(-1)) > C-PHE (-6.6 kcal mol(-1)). Cytosine may also strongly attract HIS and TYR via stacking interactions but the corresponding minima were not found since hydrogen-bonded pairs are result of gradient optimizations. Besides, stacking imposes an increase in aromatic character on both analyzed pyrimidines. This is consistently described by changes of both energetic and structural aromaticty indices. There are also observed changes in aromaticities of amino acid residues but the predictions by the harmonic oscillator model of aromaticity (HOMA) index and nucleus-independent chemical shifts (NICS) are inconsistent. Finally, there is also an interesting observation with respect to the extrapolation of the stacking energies: the same quality of complete basis set limits may be obtained without actual calculations on the aug-cc-pVQZ basis set and application of the extrapolation procedure twice gives substantially the same complete basis set results within 0.1 kcal mol(-1).

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Dicarboxylic acids (DiAs) are probably among of the most popular cocrystal formers. Due to the high hydrophilicity and nontoxicity, they are promising solubilizers of active pharmaceutical ingredients (APIs). Although DiAs appear to be highly capable of forming multicomponent crystals with various compounds, some systems reported in the literature are physical mixtures of the solid state without forming stable intermolecular complex. In this study, an accurate cocrystal screening model was developed based on the MARSplines (Multivariate Adaptive Regression Splines) methodology and easily computable descriptors driven simply from the SMILES codes. Additionally, the data set was enriched with several new mixtures of sulfamethazine. As demonstrated, this sulfonamide can form new multicomponent crystals with oxalic, malonic, and maleic acids. In the case of the latter system, a significant 10-fold solubility advantage was observed. The whole data set comprised 608 cocrystals and 104 systems hardy miscible in the solid state, denoted as simple eutectics. The final 7-factor equation was subjected to external and internal validation procedures, which indicated its high predicting power. The reliability of the proposed approach can be illustrated by the proper classification probability of cocrystals reaching 91%. The classification quality of simple binary eutectics was found to be only slightly worse (TN% = 81%).

The multiparameter model comprising 1D and 2D QSPR/QSAR descriptors was proposed and validated for phenolic acid binary systems. This approach is based on the optimization of regression coefficients for maximization of the percentage of true positives in the pool of systems comprising either simple binary eutectics or cocrystals. The training set consisted of 58 eutectics and 168 cocrystals. The solid dispersions collection used for model generation comprised literature data enriched with our new experimental results. From all 1445 descriptors computable in PaDEL, only 13 orthogonal descriptors with the highest predicting power were taken into account. The analysis revealed the importance of the parameters characterizing atom types (naaN, SHsOH, SsssN, nHeteroRing, maxHBint6, C1SP2), autocorrelation functions (ATSC1i, AATSC1v, MATS8m, GATS1i), and also other molecule structure measures (WTPT-5, MLFER_A, MDEN-22). The proposed approach is very simple and requires only information about the structure encoded in canonical SMILES string. The inversion of the problem of cocrystal screening and focusing on the homogeneous group of coformers for cocrystallization with a variety of drugs rather than seeking coformers for a particular active pharmaceutical ingredient proved to be very efficient. This led to very valuable clues for selection of pairs for cocrystallization with a probability of about 80%.

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Heart rate variability biofeedback (HRV-BFB) has been shown as useful tool to manage stress in various populations. The present study was designed to investigate whether the biofeedback-based stress management tool consisting of rhythmic breathing, actively self-generated positive emotions and a portable biofeedback device induce changes in athletes' HRV, EEG patterns, and self-reported anxiety and self-esteem. The study involved 41 healthy male athletes, aged 16-21 (mean 18.34 ± 1.36) years. Participants were randomly divided into two groups: biofeedback and control. Athletes in the biofeedback group received HRV biofeedback training, athletes in the control group didn't receive any intervention. During the randomized controlled trial (days 0-21), the mean anxiety score declined significantly for the intervention group (change-4 p < 0.001) but not for the control group (p = 0.817). In addition, as compared to the control, athletes in biofeedback group showed substantial and statistically significant improvement in heart rate variability indices and changes in power spectra of both theta and alpha brain waves, and alpha asymmetry. These changes suggest better self-control in the central nervous system and better flexibility of the autonomic nervous system in the group that received biofeedback training. A HRV biofeedback-based stress management tool may be beneficial for stress reduction for young male athletes.