Aggregation patterns of curcumin and piperine mixtures in different polar media.

This work reports a thorough molecular dynamics investigation on the aggregation patterns of curcumin and piperine in water, ethanol and a mixture of both solvents. The low solubility of curcumin in water results in a rapid formation of very stable dimers for both keto and enol tautomers. In agreement with a higher solubility, piperine molecules move closer and farther apart several times during the simulation, which indicates the formation of a less stable dimer in water. In contrast, both curcumin and piperine are soluble in ethanol and, thus, dimers can hardly be formed in this media. In comparison with a pure-water solvent, a 30 : 70 mixture of ethanol and water significantly reduces the probability of formation of most dimers of curcumin and piperine molecules. The simulations show that larger clusters may be complex structures, but the formation of stacks (in the case of piperine and enol tautomer of curcumin) and cages (when the keto tautomer of curcumin is involved) are not rare. Furthermore, it is shown that each single molecule presents a certain degree of mobility in the cluster, especially on the surface, but without leading to dissociation.

Patient needs four years after first psychiatric hospitalization in a Brazilian cohort.

Knowledge about the needs of psychiatric patients is essential for mental health care planning. However, research on met and unmet needs is still scarce, particularly in low- and middle-income countries. This study aimed to describe the patients' needs (met and unmet) at least four years after their first psychiatric hospitalization and to verify the role of demographic and clinical features as possible predictors of these needs. Patients who had their first psychiatric admission between January 1, 2006 and December 31, 2007 at an inpatient unit in the city of Ribeirão Preto, Brazil, were eligible to participate in the study. Patients were contacted and face-to-face interviews were conducted by psychologists using the Camberwell Assessment of Need. Data were analyzed using zero-inflated negative binomial regression model. Of 933 eligible patients, 333 were interviewed. The highest level of needs was related to welfare benefits (32.4%, unmet=25.5%), followed by household skills (30.3%, unmet=3.0%), psychotic symptoms (29.4%, unmet=9.0%), psychological distress (27.6%, unmet=8.4%), physical health (24.3%, unmet=5.4%), daytime activities (19.5%, unmet=16.5%), and money (16.8%, unmet=9.0%). Fewer years of schooling, living with relatives, and unemployment at the moment of the first admission were significantly associated with a higher number of both met and unmet needs in the follow-up. Unmet needs were also more often reported by patients living alone. In conclusion, socioeconomic indicators were the best predictors of needs. The unmet needs related to welfare benefits point to the need for specific social and health policies.

Modeling microsolvation clusters with electronic-structure calculations guided by analytical potentials and predictive machine learning techniques.

We propose a new methodology to study, at the density functional theory (DFT) level, the clusters resulting from the microsolvation of alkali-metal ions with rare-gas atoms. The workflow begins with a global optimization search to generate a pool of low-energy minimum structures for different cluster sizes. This is achieved by employing an analytical potential energy surface (PES) and an evolutionary algorithm (EA). The next main stage of the methodology is devoted to establish an adequate DFT approach to treat the microsolvation system, through a systematic benchmark study involving several combinations of functionals and basis sets, in order to characterize the global minimum structures of the smaller clusters. In the next stage, we apply machine learning (ML) classification algorithms to predict how the low-energy minima of the analytical PES map to the DFT ones. An early and accurate detection of likely DFT local minima is extremely important to guide the choice of the most promising low-energy minima of large clusters to be re-optimized at the DFT level of theory. In this work, the methodology was applied to the Li+Krn (n = 2-14 and 16) microsolvation clusters for which the most competitive DFT approach was found to be the B3LYP-D3/aug-pcseg-1. Additionally, the ML classifier was able to accurately predict most of the solutions to be re-optimized at the DFT level of theory, thereby greatly enhancing the efficiency of the process and allowing its applicability to larger clusters.

Aggregation of coronene: the effect of carboxyl and amine functional groups.

The aggregation of coronene is relevant to understand the formation of carbon nanomaterials, including graphene quantum dots (GQDs) that show exceptional photophysical properties. This article evaluates the influence of carboxyl and amine substituting groups on the aggregation of coronene by performing a global optimization study based on a new potential energy surface. The structures of clusters with substituted coronene are similar to those formed by un-substituted monomers, that is, stacked (non-stacked) motifs are favoured for small-size (large-size) clusters. Nonetheless, the presence of carboxyl and amine groups leads to an increase of the number of local minima of comparable energy. The clusters with substituted monomers have also shown to enhance the attractive component interaction, which can be attributed to weak induction and charge transfer effects and to stronger electrostatic contributions. Moreover, the calculated height of magic-number structures of the clusters in this work is compatible with the morphology of the GQDs reported in the literature.

Patient needs four years after first psychiatric hospitalization in a Brazilian cohort

Knowledge about the needs of psychiatric patients is essential for mental health care planning. However, research on met and unmet needs is still scarce, particularly in low- and middle-income countries. This study aimed to describe the patients' needs (met and unmet) at least four years after their first psychiatric hospitalization and to verify the role of demographic and clinical features as possible predictors of these needs. Patients who had their first psychiatric admission between January 1, 2006 and December 31, 2007 at an inpatient unit in the city of Ribeirão Preto, Brazil, were eligible to participate in the study. Patients were contacted and face-to-face interviews were conducted by psychologists using the Camberwell Assessment of Need. Data were analyzed using zero-inflated negative binomial regression model. Of 933 eligible patients, 333 were interviewed. The highest level of needs was related to welfare benefits (32.4%, unmet=25.5%), followed by household skills (30.3%, unmet=3.0%), psychotic symptoms (29.4%, unmet=9.0%), psychological distress (27.6%, unmet=8.4%), physical health (24.3%, unmet=5.4%), daytime activities (19.5%, unmet=16.5%), and money (16.8%, unmet=9.0%). Fewer years of schooling, living with relatives, and unemployment at the moment of the first admission were significantly associated with a higher number of both met and unmet needs in the follow-up. Unmet needs were also more often reported by patients living alone. In conclusion, socioeconomic indicators were the best predictors of needs. The unmet needs related to welfare benefits point to the need for specific social and health policies.

A thermodynamic view on the microsolvation of ions by rare gas: application to Li+ with argon.

We present a thermodynamic perspective of the microsolvation of ions by rare gas atoms, which is based on parallel tempering Monte Carlo (PTMC) simulations. This allows the establishment of a clear relationship between the structure of the solvation shells and the heat capacity (CV) as a function of the number of individual solvent species. The dependence of CV on the temperature allows the identification of the internal structure rearrangements and the onset of partial or total melting of the clusters. As an application, we have employed the PTMC technique to study the thermodynamic properties of clusters resulting from the microsolvation of Li+ by argon atoms. Specifically, calculations have been carried out for the clusters Li+Arn (n = 4-18, 33, 34, and 38) by applying two different potential energy surfaces (PESs): one includes only two-body interactions, while the other also incorporates three-body contributions. Whenever possible, we compare the present thermodynamic results with global optimization studies carried out previously (F. V. Prudente, J. M. C. Marques and F. B. Pereira, Phys. Chem. Chem. Phys., 2017, 19, 25707; W. S. Jesus et al., Int. J. Quantum Chem., 2019, 119, e25860). We conclude that the melting process arises for lower temperatures when the model PES accounts for three-body interactions. Additionally, we characterize the melting processes of the first and second solvation shells. For some specific clusters, structural rearrangements of the most external argon atoms are observed at very low temperatures.

A FABP4-PPARγ signaling axis regulates human monocyte responses to electrophilic fatty acid nitroalkenes.

Nitro-fatty acids (NO2-FA) are electrophilic lipid mediators derived from unsaturated fatty acid nitration. These species are produced endogenously by metabolic and inflammatory reactions and mediate anti-oxidative and anti-inflammatory responses. NO2-FA have been postulated as partial agonists of the Peroxisome Proliferator-Activated Receptor gamma (PPARγ), which is predominantly expressed in adipocytes and myeloid cells. Herein, we explored molecular and cellular events associated with PPARγ activation by NO2-FA in monocytes and macrophages. NO2-FA induced the expression of two PPARγ reporter genes, Fatty Acid Binding Protein 4 (FABP4) and the scavenger receptor CD36, at early stages of monocyte differentiation into macrophages. These responses were inhibited by the specific PPARγ inhibitor GW9662. Attenuated NO2-FA effects on PPARγ signaling were observed once cells were differentiated into macrophages, with a significant but lower FABP4 upregulation, and no induction of CD36. Using in vitro and in silico approaches, we demonstrated that NO2-FA bind to FABP4. Furthermore, the inhibition of monocyte FA binding by FABP4 diminished NO2-FA-induced upregulation of reporter genes that are transcriptionally regulated by PPARγ, Keap1/Nrf2 and HSF1, indicating that FABP4 inhibition mitigates NO2-FA signaling actions. Overall, our results affirm that NO2-FA activate PPARγ in monocytes and upregulate FABP4 expression, thus promoting a positive amplification loop for the downstream signaling actions of this mediator.

Aggregation enhancement of coronene molecules by seeding with alkali-metal ions.

Microsolvation constitutes the first step in the formation of cluster structures of molecules that surround a solute in the bulk and it allows for a deep insight into the relationship between the structure of the solvation shells and other physical properties. We propose semiempirical potential energy functions that are able to describe the interaction between K+ or Cs+ with coronene. Such functions were calibrated through the comparison with accurate estimations of the interaction between the cation and the planar hydrocarbon, obtained by means of ab initio electronic-structure calculations. By employing the potential energy functions and an evolutionary algorithm (EA), we have investigated the structure and energetics of the clusters resulting from the microsolvation of either K+ or Cs+ with coronene molecules. The reliability of the results for smaller clusters was checked by performing geometry re-optimization exploiting a suitable DFT level of theory. This has allowed for the characterization of the first solvation shells of planar molecules of coronene around an alkali-metal ion. It has also been found that the presence of metal ion impurities considerably enhances the formation of small coronene clusters leading to much stronger binding energies for heterogeneous with respect to homogeneous aggregates. These clusters could represent relevant species involved in the early stages of soot nucleation.

Molecular Dynamics Insights for Screening the Ability of Polymers to Remove Pesticides from Water.

The use of pesticides in agriculture is known to have environmental impacts, namely it leads to underground and spring water contamination. Thus, it turns out that nowadays general-endeavor towards the sustainability of farmer production requires novel strategies to capture pesticides from water and soils. We propose a methodology based on molecular dynamics simulations to identify polymers that are potentially featured to be applied for pesticide remediation in water and soils. We have employed cymoxanil (CYM), glufosinate ammonium (GLF), imidacloprid (IMI) and mancozeb (MAN) as pesticides, and have tested polymers with different characteristics as removing agents. Specifically, we have investigated oligomers of polypropylene (PP), poly(acrylic acid) protonated (PAAH) and deprotonated (PAA), and chitosan protonated (CTH) and deprotonated (CT). It has been found that all oligomers show a certain degree of selectivity concerning the interaction with the tested pesticides.

Two alkaline motifs in the Lactobacillus salivarius Lv72 OppA surface are important to its adhesin function.

Glycosaminoglycans are involved in the attachment of Lactobacillus salivarius Lv72, a strain of vaginal origin, to HeLa cell cultures, indicating that they play a fundamental role in the attachment of mutualistic bacteria to the epithelium lining cavities where the normal microbiota thrives. The bacterial OppA protein has been proposed as an adhesin involved in this adherence since, once purified, it significantly interferes with attachment of the lactobacilli to HeLa cell cultures. In this article, the role of OppA is confirmed through the determination of its location at the cell surface and its ability to promote Lactobacillus casei and Lactococcus lactis adherence to eukaryotic cell cultures upon cloning and expression of oppA in these bacteria. The OppA sequence showed five potential domains for glycosaminoglycan-binding, and structural modelling of the protein showed that two of them were located in the vicinity of an OppA superficial groove whose width approached the diameter of the helical form of heparin in solution. Their involvement in the binding was demonstrated through substitution of critical basic amino acids by acidic ones, which resulted in loss of affinity for heparan sulphate and chondroitin sulphate depending on the domain mutated, suggesting that there might be a certain degree of specialisation. In addition, circular dichroism analysis showed that the spectrum changes induced by OppA-heparan sulphate binding were attenuated by the variant proteins, indicating that these motifs are the OppA recognition domains for the eukaryotic cell surface.

Alternative RNA splicing of leucocyte tissue transglutaminase in coeliac disease.

Tissue transglutaminase is a ubiquitous and multifunctional protein that contributes to several processes such as apoptosis/survival, efferocytosis, inflammation and tissue repairing under physiological and pathological conditions. Several activities can be associated with well-established functional domains; in addition, four RNA alternative splice variants have been described, characterized by sequence divergences and residues deletion at the C-terminal domains. Tissue transglutaminase is recognized as the central player in the physiopathology of coeliac disease (CD) mainly through calcium-dependent enzymatic activities. It can be hypothesized that differential regulation of tissue transglutaminase splice variants expression in persons with CD contributes to pathology by altering the protein functionality. We characterized the expression pattern of RNA alternative splice variants by RT-PCR in peripheral cells from patients with CD under free gluten diet adhesion; we considered inflammatory parameters and specific antibodies as markers of the stage of disease. We found significant higher expression of both the full length and the shortest C-truncated splice variants in leucocytes from patients with CD in comparison with healthy individuals. As tissue transglutaminase expression and canonical enzymatic activity are linked to inflammation, we studied the RNA expression of inflammatory cytokines in peripheral leucocytes of persons with CD in relation with splice variants expression; interestingly, we found that recently diagnosed patients showed significant correlation between both the full length and the shortest alternative spliced variants with IL-1 expression. Our results points that regulation of alternative splicing of tissue transglutaminase could account for the complex physiopathology of CD.

A global optimization perspective on molecular clusters.

Although there is a long history behind the idea of chemical structure, this is a key concept that continues to challenge chemists. Chemical structure is fundamental to understanding most of the properties of matter and its knowledge for complex systems requires the use of state-of-the-art techniques, either experimental or theoretical. From the theoretical view point, one needs to establish the interaction potential among the atoms or molecules of the system, which contains all the information regarding the energy landscape, and employ optimization algorithms to discover the relevant stationary points. In particular, global optimization methods are of major importance to search for the low-energy structures of molecular aggregates. We review the application of global optimization techniques to several molecular clusters; some new results are also reported. Emphasis is given to evolutionary algorithms and their application in the study of the microsolvation of alkali-metal and Ca2+ ions with various types of solvents.This article is part of the themed issue 'Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces'.

Improved evolutionary algorithm for the global optimization of clusters with competing attractive and repulsive interactions.

We propose improvements to our evolutionary algorithm (EA) [J. M. C. Marques and F. B. Pereira, J. Mol. Liq. 210, 51 (2015)] in order to avoid dissociative solutions in the global optimization of clusters with competing attractive and repulsive interactions. The improved EA outperforms the original version of the method for charged colloidal clusters in the size range 3 ≤ N ≤ 25, which is a very stringent test for global optimization algorithms. While the Bernal spiral is the global minimum for clusters in the interval 13 ≤ N ≤ 18, the lowest-energy structure is a peculiar, so-called beaded-necklace, motif for 19 ≤ N ≤ 25. We have also applied the method for larger sizes and unusual quasi-linear and branched clusters arise as low-energy structures.

A Detailed Study on the Low-Energy Structures of Charged Colloidal Clusters.

The target of this investigation is the systematic characterization of the low-energy structures of charged colloidal clusters that may be important to understand the self-assembling process of biomolecules. The aggregation of charged colloidal particles is governed by the attractive short-ranged Morse potential and the Yukawa repulsive tail to describe the long-range charge effect. A global optimization strategy, based on our own evolutionary algorithm, was adopted to discover the low-energy structures of colloidal clusters composed of up to 20 particles. A detailed analysis of the low-energy structures involving charged particles shows that the appearance of the Bernal spiral as the most stable motif occurs, first, at N = 6, but it is favored for larger clusters (N ≥ 13); for 6 ≤ N ≤ 12, there is a competition between the spiral (which is favored for higher charges) and more spherical-like structures. Finally, we study binary clusters composed by two sets of differently charged colloidal particles. Although a great diversity of low-energy structures is observed (especially for aggregates with one of the components in excess), the global minimum is disputed by three structural motifs depending on the composition of the cluster and, in some cases, on the range of the Morse potential.

High sucrose consumption induces memory impairment in rats associated with electrophysiological modifications but not with metabolic changes in the hippocampus.

High sugar consumption is a risk factor for metabolic disturbances leading to memory impairment. Thus, rats subject to high sucrose intake (HSu) develop a metabolic syndrome and display memory deficits. We now investigated if these HSu-induced memory deficits were associated with metabolic and electrophysiological alterations in the hippocampus. Male Wistar rats were submitted for 9 weeks to a sucrose-rich diet (35% sucrose solution) and subsequently to a battery of behavioral tests; after sacrifice, their hippocampi were collected for ex vivo high-resolution magic angle spinning (HRMAS) metabolic characterization and electrophysiological extracellular recordings in slices. HSu rats displayed a decreased memory performance (object displacement and novel object recognition tasks) and helpless behavior (forced swimming test), without altered locomotion (open field). HRMAS analysis indicated a similar hippocampal metabolic profile of HSu and control rats. HSu rats also displayed no change of synaptic transmission and plasticity (long-term potentiation) in hippocampal Schaffer fibers-CA1 pyramid synapses, but had decreased amplitude of long-term depression in the temporoammonic (TA) pathway. Furthermore, HSu rats had an increased density of inhibitory adenosine A1 receptors (A1R), that translated into a greater potency of A1R in Schaffer fiber synapses, but not in the TA pathway, whereas the endogenous activation of A1R in HSu rats was preserved in the TA pathway but abolished in Schaffer fiber synapses. These results suggest that HSu triggers a hippocampal-dependent memory impairment that is not associated with altered hippocampal metabolism but is probably related to modified synaptic plasticity in hippocampal TA synapses.

Low-energy structures of benzene clusters with a novel accurate potential surface.

The benzene-benzene (Bz-Bz) interaction is present in several chemical systems and it is known to be crucial in understanding the specificity of important biological phenomena. In this work, we propose a novel Bz-Bz analytical potential energy surface which is fine-tuned on accurate ab initio calculations in order to improve its reliability. Once the Bz-Bz interaction is modeled, an analytical function for the energy of the Bzn clusters may be obtained by summing up over all pair potentials. We apply an evolutionary algorithm (EA) to discover the lowest-energy structures of Bzn clusters (for n=2-25), and the results are compared with previous global optimization studies where different potential functions were employed. Besides the global minimum, the EA also gives the structures of other low-lying isomers ranked by the corresponding energy. Additional ab initio calculations are carried out for the low-lying isomers of Bz3 and Bz4 clusters, and the global minimum is confirmed as the most stable structure for both sizes. Finally, a detailed analysis of the low-energy isomers of the n = 13 and 19 magic-number clusters is performed. The two lowest-energy Bz13 isomers show S6 and C3 symmetry, respectively, which is compatible with the experimental results available in the literature. The Bz19 structures reported here are all non-symmetric, showing two central Bz molecules surrounded by 12 nearest-neighbor monomers in the case of the five lowest-energy structures.

Presynaptic adenosine A2A receptors dampen cannabinoid CB1 receptor-mediated inhibition of corticostriatal glutamatergic transmission.

BACKGROUND AND PURPOSE: Both cannabinoid CB1 and adenosine A2A receptors (CB1 receptors and A2A receptors) control synaptic transmission at corticostriatal synapses, with great therapeutic importance for neurological and psychiatric disorders. A postsynaptic CB1 -A2A receptor interaction has already been elucidated, but the presynaptic A2A receptor-mediated control of presynaptic neuromodulation by CB1 receptors remains to be defined. Because the corticostriatal terminals provide the major input to the basal ganglia, understanding the interactive nature of converging neuromodulation on them will provide us with novel powerful tools to understand the physiology of corticostriatal synaptic transmission and interpret changes associated with pathological conditions. EXPERIMENTAL APPROACH: Pharmacological manipulation of CB1 and A2A receptors was carried out in brain nerve terminals isolated from rats and mice, using flow synaptometry, immunoprecipitation, radioligand binding, ATP and glutamate release measurement. Whole-cell patch-clamp recordings were made in horizontal corticostriatal slices. KEY RESULTS: Flow synaptometry showed that A2A receptors were extensively co-localized with CB1 receptor-immunopositive corticostriatal terminals and A2A receptors co-immunoprecipitated CB1 receptors in these purified terminals. A2A receptor activation decreased CB1 receptor radioligand binding and decreased the CB1 receptor-mediated inhibition of high-K(+) -evoked glutamate release in corticostriatal terminals. Accordingly, A2A receptor activation prevented CB1 receptor-mediated paired-pulse facilitation and attenuated the CB1 receptor-mediated inhibition of synaptic transmission in glutamatergic synapses of corticostriatal slices. CONCLUSIONS AND IMPLICATIONS: Activation of presynaptic A2A receptors dampened CB1 receptor-mediated inhibition of corticostriatal terminals. This constitutes a thus far unrecognized mechanism to modulate the potent CB1 receptor-mediated presynaptic inhibition, allowing frequency-dependent enhancement of synaptic efficacy at corticostriatal synapses.

Microsolvation of the potassium ion with aromatic rings: comparison between hexafluorobenzene and benzene.

We employ a recently developed methodology to study structural and energetic properties of the first solvation shells of the potassium ion in nonpolar environments due to aromatic rings, which is important to understand the selectivity of several biochemical phenomena. Our evolutionary algorithm is used in the global optimization study of clusters formed of K(+) solvated with hexafluorobenzene (HFBz) molecules. The global intermolecular interaction for these clusters has been decomposed in HFBz-HFBz and in K(+)-HFBz contributions, using a potential model based on different decompositions of the molecular polarizability of hexafluorobenzene. Putative global minimum structures of microsolvation clusters up to 21 hexafluorobenzene molecules were obtained and compared with the analogous K(+)-benzene clusters reported in our previous work (J. Phys. Chem. A 2012, 116, 4947-4956). We have found that both K(+)-(Bz)n and K(+)-(HFBz)n clusters show a strong magic number around the closure of the first solvation shell. Nonetheless, all K(+)-benzene clusters have essentially the same first solvation shell geometry with four solvent molecules around the ion, whereas the corresponding one for K(+)-(HFBz)n is completed with nine HFBz species, and its structural motif varies as n increases. This is attributed to the ion-solvent interaction that has a larger magnitude for K(+)-Bz than in the case of K(+)-HFBz. In addition, the ability of having more HFBz than Bz molecules around K(+) in the first solvation shell is intimately related to the inversion in the sign of the quadrupole moment of the two solvent species, which leads to a distinct ion-solvent geometry of approach.

Alkali-ion microsolvation with benzene molecules.

The target of this investigation is to characterize by a recently developed methodology, the main features of the first solvation shells of alkaline ions in nonpolar environments due to aromatic rings, which is of crucial relevance to understand the selectivity of several biochemical phenomena. We employ an evolutionary algorithm to obtain putative global minima of clusters formed with alkali-ions (M(+)) solvated with n benzene (Bz) molecules, i.e., M(+)-(Bz)(n). The global intermolecular interaction has been decomposed in Bz-Bz and in M(+)-Bz contributions, using a potential model based on different decompositions of the molecular polarizability of benzene. Specifically, we have studied the microsolvation of Na(+), K(+), and Cs(+) with benzene molecules. Microsolvation clusters up to n = 21 benzene molecules are involved in this work and the achieved global minimum structures are reported and discussed in detail. We observe that the number of benzene molecules allocated in the first solvation shell increases with the size of the cation, showing three molecules for Na(+) and four for both K(+) and Cs(+). The structure of this solvation shell keeps approximately unchanged as more benzene molecules are added to the cluster, which is independent of the ion. Particularly stable structures, so-called "magic numbers", arise for various nuclearities of the three alkali-ions. Strong "magic numbers" appear at n = 2, 3, and 4 for Na(+), K(+), and Cs(+), respectively. In addition, another set of weaker "magic numbers" (three per alkali-ion) are reported for larger nuclearities.

On the use of big-bang method to generate low-energy structures of atomic clusters modeled with pair potentials of different ranges.

The efficiency of the so-called big-bang method for the optimization of atomic clusters is analysed in detail for Morse pair potentials with different ranges; here, we have used Morse potentials with four different ranges, from long- ρ = 3) to short-ranged ρ = 14) interactions. Specifically, we study the efficacy of the method in discovering low-energy structures, including the putative global minimum, as a function of the potential range and the cluster size. A new global minimum structure for long-ranged ρ = 3) Morse potential at the cluster size of n= 240 is reported. The present results are useful to assess the maximum cluster size for each type of interaction where the global minimum can be discovered with a limited number of big-bang trials.