Towards fully ab initio simulation of atmospheric aerosol nucleation.

Atmospheric aerosol nucleation contributes to approximately half of the worldwide cloud condensation nuclei. Despite the importance of climate, detailed nucleation mechanisms are still poorly understood. Understanding aerosol nucleation dynamics is hindered by the nonreactivity of force fields (FFs) and high computational costs due to the rare event nature of aerosol nucleation. Developing reactive FFs for nucleation systems is even more challenging than developing covalently bonded materials because of the wide size range and high dimensional characteristics of noncovalent hydrogen bonding bridging clusters. Here, we propose a general workflow that is also applicable to other systems to train an accurate reactive FF based on a deep neural network (DNN) and further bridge DNN-FF-based molecular dynamics (MD) with a cluster kinetics model based on Poisson distributions of reactive events to overcome the high computational costs of direct MD. We found that previously reported acid-base formation rates tend to be significantly underestimated, especially in polluted environments, emphasizing that acid-base nucleation observed in multiple environments should be revisited.

Molecular vibrational spectral simulation connects theoretical cluster structure identification and vibrational spectral evidence.

Structure identification of molecular clusters has long been a fundamental and challenging issue for cluster science. The traditional theoretical optimization on the potential energy surface heavily depends on the levels of theory and sometimes diverse identifications were reported. A solution to these disputations is to reinspect the theoretical results with the experimental data such as vibrational predissociation spectra with high sensitivity to the molecular cluster structures. Herein, the combination of global low-lying structure search and vibrational predissociation spectral simulation is proposed as an accurate and reliable approach for cluster structure identification, by which the assignments can be validated using experimental measurements. The qualitative agreement between simulated and measured vibrational spectra lends solid experimental evidence to the assignment of the cluster structures. Taking NH4+(H2O)n (n = 2-4) as an example, we have unambiguously identified their structures and directly demonstrated the coexistence of two NH4+(H2O)4 isomers (with 3 and 4 water molecules directly linked to NH4+, respectively), which were debatable in previous studies. The developed methods would pave the way to the structure determination of the molecular clusters.

A high-accuracy machine-learning water model for exploring water nanocluster structures.

Water, the most important molecule on the Earth, possesses many essential and unique physical properties that are far from completely understood, partly due to serious difficulties in identifying the precise microscopic structures of water. Hence, identifying the structures of water nanoclusters is a fundamental and challenging issue for studies on the relationship between the macroscopic physical properties of water and its microscopic structures. For large-scale simulations (at the level of nm and ns) of water nanoclusters, a calculation method with simultaneous accuracy at the level of quantum chemistry and efficiency at the level of an empirical potential method is in great demand. Herein, a machine-learning (ML) water model was utilized to explore the microscopic structural features at different length scales for water nanoclusters with a size up to several nm. The ML water model can be employed to efficiently predict the structures of water nanoclusters with a similar accuracy to that of density functional theory and with substantially lower computational resource demands. To validate the low-lying structure search results with experimental spectral results, an ML water model combined with velocity autocorrelation function analysis was used to simulate the vibrational spectra of water nanoclusters with up to thousands of water molecules. By comparing the simulated and experimentally recorded vibrational spectra, the atomic structures determined by a simulation based on the ML water model are all verified. To demonstrate its ability to represent water's structural evolution at large length and time scales, the ML water model was employed to model the structural evolution during the crystal-liquid transition, and the phase transition temperatures of water clusters with different sizes were precisely predicted. The ML water model provides an efficient theoretical calculation tool for exploring the structures and physical properties of water and their relationships, especially for clusters with relatively large sizes and processes with relatively long durations.

Exploring TCGA database for identification of potential prognostic genes in stomach adenocarcinoma.

BACKGROUND: Stomach adenocarcinoma (STAD) is the fifth most prevalent cancer in the world and ranks third among cancer-related deaths worldwide. The tumour microenvironment (TME) plays an important role in tumorigenesis, development, and metastasis. Hence, we calculated the immune and stromal scores to find the potential prognosis-related genes in STAD using bioinformatics analysis. METHODS: The ESTIMATE algorithm was used to calculate the immune/stromal scores of the STAD samples. Functional enrichment analysis, protein-protein interaction (PPI) network analysis, and overall survival analysis were then performed on differential genes. And we validated these genes using data from the Gene Expression Omnibus database. Finally, we used the Human Protein Atlas (HPA) databases to verify these genes at the protein levels by IHC. RESULTS: Data analysis revealed correlation between stromal/immune scores and the TNM staging system. The top 10 core genes extracted from the PPI network, and primarily involved in immune responses, extracellular matrix, and cell adhesion. There are 31 genes have been validated with poor prognosis and 16 genes were upregulated in tumour tissues compared with normal tissues at the protein level. CONCLUSIONS: In summary, we identified genes associated with the tumour microenvironment with prognostic implications in STAD, which may become potential therapeutic markers leading to better clinical outcomes.

Enhancement of Atmospheric Nucleation by Highly Oxygenated Organic Molecules: A Density Functional Theory Study.

New particle formation (NPF) by gas-particle conversion is the main source of atmospheric aerosols. Highly oxygenated organic molecules (HOMs) and sulfuric acid (SA) are important NPF participants. 2-Methylglyceric acid (MGA), a kind of HOMs, is a tracer of isoprene-derived secondary organic aerosols. The nucleation mechanisms of MGA with SA were studied using density functional theory and atmospheric cluster dynamics simulation in this study, along with that of MGA with methanesulfonic acid (MSA) as a comparison. Our theoretical works indicate that the (MGA)(SA) and (MGA)(MSA) clusters are the most stable ones in the (MGA) i(SA) j ( i = 1-2, j = 1-2) and (MGA) i(MSA) j ( i = 1-2, j = 1-2) clusters, respectively. Both the formation rates of (MGA)(SA) and (MGA)(MSA) clusters are quite large and could have significant contributions to NPF. The results imply that the homomolecular nucleation of MGA is unlikely to occur in the atmosphere, and MGA and SA can effectively contribute to heteromolecular nucleation mainly in the form of heterodimers. MSA exhibits properties similar to SA in its ability to form clusters with MGA but is slightly weaker than SA.

Hydration of 3-hydroxy-4,4-dimethylglutaric acid with dimethylamine complex and its atmospheric implications.

Atmospheric aerosols have a tremendous influence on visibility, climate, and human health. New particle formation (NPF) is a crucial source of atmospheric aerosols. At present, certain field observations and experiments have discovered the presence of 3-hydroxy-4,4-dimethylglutaric acid (HDMGA), which may participate in NPF events. However, the nucleation mechanism of HDMGA has not been clearly understood. In addition, dimethylamine (DMA) is an important precursor of nucleation. The nucleation mechanism involving HDMGA and DMA has not been studied. In this study, the most stable structures of (HDMGA)(H2O)n (n = 0-3) and (HDMGA)(DMA)(H2O)n (n = 0-3) were obtained by using M06-2X coupled with the 6-311++G(3df,3pd) basis set. The α-carboxyl group is directly attached to the amino group in all the most stable configurations. Proton transfer enhances the strength of a hydrogen bond, as well as promotes the generation of a global minimum structure. Temperature has a considerable influence on the distribution of isomers for (HDMGA)(DMA)(H2O)3 as compared to the other investigated clusters. The Gibbs free energy values reveal that most of the clusters can exist in NPF, except for (HDMGA)(H2O)1. The process of adding a cluster of (H2O)n more likely occurs in the atmosphere than gradually adding a single water molecule.

Interaction of oxalic acid with methylamine and its atmospheric implications.

Oxalic acid, which is one of the most common dicarboxylic acids, is expected to be an important component of atmospheric aerosols. However, the contribution of oxalic acid to the generation of new particles is still poorly understood. In this study, the structural characteristics and thermodynamics of (C2H2O4)(CH3NH2) n (n = 1-4) were investigated at the PW91PW91/6-311++G(3df,3pd) level of theory. We found that clusters formed by oxalic acid and methylamine are relatively stable, and the more the atoms participating in the formation of a ring-like structure, the more stable is the cluster. In addition, via the analysis of atmospheric relevance, it can be revealed that clusters of (C2H2O4)(CH3NH2) n (n = 1-4) have a noteworthy concentration in the atmosphere, which indicates that these clusters could be participating in new particle formation. Moreover, by comparison with (H2C2O4)(NH3) n (n = 1-6) species, it can be seen that oxalic acid is more readily bound to methylamine than to ammonia, which promotes nucleation or new particle formation. Finally, the Rayleigh scattering properties of clusters of (C2H2O4)(CH3NH2) n (n = 1-4) were investigated for the first time to determine their atmospheric implications.

Hydration of the methanesulfonate-ammonia/amine complex and its atmospheric implications.

Methanesulfonate (MSA-), found in substantial concentrations in the atmosphere, is expected to enhance aerosol nucleation and the growth of nanoparticles, but the details of methanesulfonate clusters are poorly understood. In this study, MSA- was chosen along with ammonia (NH3) or three common amines and water (H2O) to discuss the roles of ternary homogeneous nucleation and ion-induced nucleation in aerosol formation. We studied the structural characteristics and thermodynamics of the clusters using density functional theory at the PW91PW91/6-311++G(3df,3pd) level. The analysis of noncovalent interactions predicts that the amines can form more stable clusters with MSA- than NH3, in agreement with the results from structures and thermodynamics; however, the enhancement in stability for amines is not large enough to overcome the difference in the concentrations of NH3 and amines under typical atmospheric conditions. In addition, the favorable free energies of formation for the (MSA-)(NH3/amines)(H2O) n (n = 0-3) clusters at 298.15 K show that MSA- could contribute to the aerosol nucleation process with binding NH3/amines and H2O up to n = 3. There are strong temperature and humidity dependences for the formation of complexes; higher humidity and temperature promote the formation of larger hydrates. Finally, for the (MSA-)(NH3/amines)(H2O) n clusters, the evaporation rates were determined to further investigate the atmospheric implications.

π-Hydrogen Bonding of Aromatics on the Surface of Aerosols: Insights from Ab Initio and Molecular Dynamics Simulation.

Molecular level insight into the interaction between volatile organic compounds (VOCs) and aerosols is crucial for improvement of atmospheric chemistry models. In this paper, the interaction between adsorbed toluene, one of the most significant VOCs in the urban atmosphere, and the aqueous surface of aerosols was studied by means of combined molecular dynamics simulations and ab initio quantum chemistry calculations. It is revealed that toluene can be stably adsorbed on the surface of aqueous droplets via hydroxyl-π hydrogen bonding between the H atoms of the water molecules and the C atoms in the aromatic ring. Further, significant modifications on the electrostatic potential map and frontier molecular orbital are induced by the solvation effect of surface water molecules, which would affect the reactivity and pathway of the atmospheric photooxidation of toluene. This study demonstrates that the surface interactions should be taken into consideration in the atmospheric chemical models on oxidation of aromatics.

Bidirectional Interaction of Alanine with Sulfuric Acid in the Presence of Water and the Atmospheric Implication.

Amino acids are recognized as important components of atmospheric aerosols, which impact on the Earth's climate directly and indirectly. However, much remains unknown about the initial events of nucleation. In this work, the interaction of alanine [NH2CH(CH3)COOH or Ala], one of the most abundant amino acids in the atmosphere, with sulfuric acid (SA) and water (W) has been investigated at the M06-2X/6-311++G(3df, 3pd) level of theory. We have studied thermodynamics of the hydrated (Ala)(SA) core system with up to four water molecules. We found that Ala, with one amino group and one carboxyl group, can interact with H2SO4 and H2O in two directions and that it has a high cluster stabilizing effect similar to that of ammonia, which is one of the key nucleation precursor. The corresponding Gibbs free energies of the (Ala)(SA)(W)n (n = 0-4) clusters formation at 298.15 K predicted that Ala can contribute to the stabilization of small binary clusters. Our results showed that the hydrate distribution is temperature-dependent and that a higher humidity and temperature can contribute to the formation of hydrated clusters.

Three-Dimensional Assignment of the Structures of Atomic Clusters: an Example of Au8M (M=Si, Ge, Sn) Anion Clusters.

Identification of different isomer structures of atomic and molecular clusters has long been a challenging task in the field of cluster science. Here we present a three-dimensional (3D) assignment method, combining the energy (1D) and simulated (2D) spectra to assure the assignment of the global minimum structure. This method is more accurate and convenient than traditional methods, which only consider the total energy and first vertical detachment energies (VDEs) of anion clusters. There are two prerequisites when the 3D assignment method is ultilized. First, a reliable global minimum search algorithm is necessary to explore enough valleys on the potential energy surface. Second, trustworthy simulated spectra are necessary, that is to say, spectra that are in quantitative agreement. In this paper, we demonstrate the validity of the 3D assignment method using Au8M(-) (M=Si, Ge, Sn) systems. Results from this study indicate that the global minimum structures of Au8Ge(-) and Au8Sn(-) clusters are different from those described in previous studies.

Stability of Hydrated Methylamine: Structural Characteristics and H2N···H-O Hydrogen Bonds.

Methylamine is the simplest aliphatic amine found in human urine, blood, and tissues. It is thought to play a significant part in central nervous system disturbances observed during renal and hepatic disease. In this work we have investigated the methylamine hydration clusters using a basin hopping (BH) algorithm with the density functional theory (DFT). The results presented herein yield a detailed understanding of the structure and stability for a system consisting of one methylamine molecule and up to seven waters: the most stable geometries arise from a fusion of tetramer or pentamer rings; by the geometrical parameters and topological parameters analysis, the strengths of the H2N···H-O hydrogen bonds of the global minima increase as the sizes of clusters increase, except for n = 5 where there is a slight fluctuation. This work may shed light on the form mechanism of methylamine existing in organisms and the hydration structures of larger molecules containing amino functional groups and their interaction with the water molecules nearby.

PDTC attenuate LPS-induced kidney injury in systemic lupus erythematosus-prone MRL/lpr mice.

Lipopolysaccharide (LPS) from bacteria can accelerate and exacerbate lupus nephritis (LN) and induce infiltrating inflammatory cells in kidney in animal models. Pyrrolidine dithiocarbamate (PDTC) is known to exert anti-inflammatory effects. Monocyte chemoattractant protein-1(MCP-1) is upregulated by various stimuli, including LPS, high glucose, and hyperosmolality. However, the molecular mechanisms of transcriptional regulation of the MCP-1 protein expression with LPS are poorly understood. Expression of MCP-1 was examined by western blot and enzyme-linked immunosorbent assay, respectively. The activity of nuclear factor (NF)-kappaB was measured by western blot. These mice have uncontrolled proliferation of T cells, an impaired response to T cell mitogen and produce autoantibodies against nuclear antigens, including DNA. We found that after LPS treatment for 14 weeks, LPS increased MCP-1 protein expression in kidney, which was significantly suppressed by antioxidant PDTC. The expression of NF-κB, pERK, pJNK and MCP-1 were increased, pp38 expression was decreased significantly, concomitantly with sera anti-dsDNA, MCP-1 and the acceleration of severity of autoimmune kidney injury. LPS induce markedly neutrophil infiltration in the glomerulus, especially around the mesangial region. PDTC reduced the number of infiltrating inflammatory cells and severity of kidney injury via inhibiting NF-κB and p38 MAPK activity. They also markedly prevented LPS-induced pJNK and MCP-1. Therefore, MCP-1 may be responsible for the recruitment and activation of leukocytes in diseased kidneys in female MRL/lpr mice. In this study, the long-term administration of PDTC had impacts on the prevention of end-stage organ damage induced by LPS treated. We demonstrated that PDTC inhibited LPS-induced monocyte migration and attenuated LPS-induced p38 MAPK activation. Based on these data we infer that PDTC inhibits LPS-induced MCP-1 expression, secretion and function through inhibition of NF-κB and p38 MAPK activity. Our study suggests that MAPK is an important therapeutic target of monocyte recruitment and accumulation within the glomerulus in inflammatory renal disease. These results suggest that PDTC protects against kidney inflammation of SLE at least in part via NF-κB and MAPK signaling pathways induction, and that inhibitory action on anti-dsDNA may be associated with the protective mechanism of PDTC. In summary, PDTC pretreatment attenuates LPS-induced kidney injury in female MRL/lpr mice through regulating NF-κB and MAPK signaling pathways. Our results indicate that LPS induces MCP-1 mainly through activating NF-κB and its downstream MAPK, and that such effect was inhibited by PDTC, suggesting the efficacy of PDTC in preventing kidney fibrosis in lupus-prone mice. Therefore, appropriate inhibition of NF-κB activation may attenuate the kidney injury in lupus-prone mice.

[Effects of mitogen-activated protein kinases signaling pathway proteins on kidney injury in mice exposed subchronically to cadmium].

OBJECTIVE: To explore the effects of mitogen activated protein kinase (MAPK) and extracellular signal-regulated kinases (ERK) on kidney injury in female BALB/c mice exposed to cadmium. METHOD: Twenty-one female BALB/c mice were randomly divided into 3 groups, i.e. control group, low Cd exposure group (2.5 µmol/kg) and high Cd exposure group (10 µmol/kg) were exposed to normal saline, 2.5, 10 µmol/kg Cd, respectively, 3 times a week for 14 weeks. The kidney slice were stained by HE, PAS and Masson staining to observe the morphological changes. The expression levels of pERK, ERK, pp38, p38, pJNK and JNK proteins in kidneys were tested by Western blot assay. RESULTS: The ratios of pERK/ERK, pp38/p38, pJNK/JNK in high Cd group were higher than those in the control group (P < 0.05). The ratio of pERK/ERK in low Cd group was higher than control group (P < 0.05). The expression levels of bcl-2, bax proteins and the ratio of bcl-2 to bax in Cd exposure groups decreased significantly, as compared with the control group (P < 0.05). The impairment of renal glomeruli and tubules were observed in HE, PAS and Masson staining slices of kidneys in mice exposed to Cd. CONCLUSION: CdCl2 may induced renal injury by affecting the expression levels of MAPK.

[Effect of exposure to higher decabrominated diphenyl ether (PBDE-209) on learning and memory functions of BALB/c mice].

OBJECTIVE: To investigate the effects of exposure to decabrominated diphenyl ether (PBDE-209) on learning and memory of BALB/c mice. METHODS: Eighteen female BALB/c mice were randomized divided into 3 groups and gavaged with peanut oil in the control groups and 300, 1500 mg x kg(-1)xd(-1) PBDE-209 in peanut oil daily in two exposed groups respectively for 4 weeks. The learning and memory ability of mice were tested by the Morris water maze and the shuttling box respectively. The body weight and organs index were measured and the acetylcholinesterase and butyrylcholinesterase activity in brain were determined. The liver histopathological examination was performed. RESULTS: The heart index in high dose PBDE-209 group was higher than that of the low dose PBDE-209 group (P < 0.05). The results of Morris water maze showed that escape latency period was significantly shorter than the control group (F = 3.134, P < 0.05). The swimming time in the second quadrant of low dose PBDE-209 group was (15.78 +/- 10.92) s, significantly shorter compared with the swimming time in the second quadrant of the control group's [(28.80 +/- 8.67) s] (P < 0.05). There was no significant difference in the times of active avoidance in the shuttling between three groups (F = 3.423, P = 0.06). There were no significant differences in acetylcholinesterase and butyrylcholinesterase activity in brain of PBDE-209 groups compared with the control group (P > 0.05). Histologically liver damages in structure such as adipose degeneration and swelling were observed in PBDE groups. CONCLUSION: Exposure to PBDE-209 slightly impairs the space learning and memory ability of BALB/c mice, and it has some hepatotoxicity.