Mechanistic and data-driven perspectives on plant uptake of organic pollutants.

Establishing reliable predictive models for plant uptake of organic pollutants is crucial for environmental risk assessment and guiding phytoremediation efforts. This study compiled an expanded dataset of plant cuticle-water partition coefficients (Kcw), a useful indicator for plant uptake, for 371 data points of 148 unique compounds and various plant species. Quantum/computational chemistry software and tools were utilized to compute various molecular descriptors, aiming to comprehensively characterize the properties and structures of each compound. Three types of models were developed to predict Kcw: a mechanism-driven pp-LFER model, a data-driven machine learning model, and an integrated mechanism-data-driven model. The mechanism-data-driven GBRT-ppLFER model exhibited superior performance, achieving RMSEtrain = 0.133 and RMSEtest = 0.301 while maintaining interpretability. The Shapley Additive Explanation analysis indicated that pp-LFER parameters, ESPI, FwRadicalmax, ExtFP607, and RDF70s are the key factors influencing plant uptake in the GBRT-ppLFER model. Overall, pp-LFER parameter, ESPI, and ExtFP607 show positive effects, while the remaining factors exhibit negative effects. Partial dependency analysis further indicated that plant uptake is not solely determined by individual factors but rather by the combined interactions of multiple factors. Specifically, compounds with ppLFER parameter >4, ESPI > -25.5, 0.098 < FwRadicalmax <0.132, and 2 < RFD70s < 3, are generally more readily taken up by plants. Besides, the predicted Kcw values from the GBRT-ppLFER model were effectively employed to estimate the plant-water partition coefficients and bioconcentration factors across different plant species and growth media (water, sand, and soil), achieving an outstanding performance with an RMSE of 0.497. This study provides effective tools for assessing plant uptake of organic pollutants and deepens our understanding of plant-environment-compound interactions.

Investigation of Biomaterial Ink Viscosity Properties and Optimization of the Printing Process Based on Pattern Path Planning.

Extruded bioprinting is widely used for the biomanufacturing of personalized, complex tissue structures, which requires biomaterial inks with a certain viscosity to enable printing. However, there is still a lack of discussion on the controllable preparation and printability of biomaterial inks with different viscosities. In this paper, biomaterial inks composed of gelatin, sodium alginate, and methylcellulose were utablesed to investigate the feasibility of adjustment of rheological properties, thereby analyzing the effects of different rheological properties on the printing process. Based on the response surface methodology, the relationship between the material components and the rheological properties of biomaterial inks was discussed, followed by the prediction of the rheological properties of biomaterial inks. The prediction accuracies of the power-law index and consistency coefficient could reach 96% and 79%, respectively. The material group can be used to prepare biomaterial inks with different viscosity properties in a wide range. Latin hypercube sampling and computational fluid dynamics were used to analyze the effects of different rheological properties and extrusion pressure on the flow rate at the nozzle. The relationship between the rheological properties of the biomaterial ink and the flow rate was established, and the simulation results showed that the changes in the rheological properties of the biomaterial ink in the high-viscosity region resulted in slight fluctuations in the flow rate, implying that the printing process for high-viscosity biomaterial inks may have better versatility. In addition, based on the characteristics of biomaterial inks, the printing process was optimized from the planning of the print pattern to improve the location accuracy of the starting point, and the length accuracy of filaments can reach 99%. The effect of the overlap between the fill pattern and outer frame on the print quality was investigated to improve the surface quality of complex structures. Furthermore, low- and high-viscosity biomaterial inks were tested, and various printing protocols were discussed for improving printing efficiency or maintaining cell activity. This study provides feasible printing concepts for a wider range of biomaterials to meet the biological requirements of cell culture and tissue engineering.

Endophytic Bacillus sp. R1 and Its Roles in Assisting Phytoremediation and Alleviating the Toxicity of Aluminum Combined Phenanthrene Contaminations in Brassica napus.

The release of organic and inorganic contaminants into soil from industry, agriculture, and urbanization has become a major issue of international concern, particularly the heavy metals such as aluminum (Al) and the chemical phenanthrene (PHE). Due to their potential toxicity and non-biodegrade in the environment, efficient remediation methods are urgently needed. Recently, research has comprehensively discussed using plants and their endophytes in bioremediation efforts. Endophytic Bacillus sp. R1, isolated from Brassica napus permanently contaminated with Al and PHE, has growth-promoting properties and can efficiently detoxify these contaminants. The pot experiment indicated that compared to the Al combined PHE contaminated soil alone treatment, the R1 treatment led to increased Al accumulation in canola roots across different levels of PHE, Al, and combined PHE and Al contamination. However, Al accumulation in canola shoots and seeds remained unchanged for all treatments. Moreover, PHE in canola roots and shoots was decreased by R1 inoculation and thereby reducing 26.12-60.61% PHE translocated into canola seeds. Additionally, R1 inoculation significantly increased the proportion of extractable Al and, decreased the proportion of acid-soluble inorganic Al and humic-acid Al, but did not affect the concentration of organically complexed Al. In summary, endophyte R1 can degrade PHE, improve canola roots' Al uptake by increasing soil available Al, and scavenge the reactive oxygen species through production of antioxidant enzymes to help alleviate the toxicity of canola co-contaminated with aluminum and phenanthrene.

Magnetically Responsive Superhydrophobic Surface with Reversibly Switchable Wettability: Fabrication, Deformation, and Switching Performance.

Responsive surfaces with reversibly switchable wettability have attracted widespread attention due to their diverse range of potential applications in the past few years. As a representative example, the magnetically actuated dynamic regulation structured surfaces provide a convenient and unique approach to achieving remote control and instantaneous response. However, (quasi)quantitative design strategies and economical fabrication methods with high precision for magnetically responsive surfaces with both superhydrophobicity and superior wetting switchability still remain challenging. In this work, a manufacturing technique for high-aspect-ratio magnetically responsive superhydrophobic surfaces (MRSSs) via the integration of micromilling, replica molding, and coating modification is proposed. The geometrical parameters of magnetic micropillar arrays (MMAs) on the surface are specially designed on the basis of the Cassie-Wenzel (C-W) transition critical condition in order to guarantee the initial superhydrophobicity of the surface. Benefiting from the reconfigurable microstructures of MMAs in response to magnetic fields (i.e., shifting between upright and curved states), the wettability and adhesion of MRSSs can be reversibly switched. The smart wetting controllability presented on MRSSs is proven to be largely determined by the geometrical parameters and deformation capacity of the micropillars, while the visible wetting switching is mainly ascribed to the variation in wetting regimes of droplets. The modification of the superhydrophobic coatings on the micropillar top is also demonstrated to be capable of further enhancing the initial hydrophobicity and switchable wettability of surfaces, producing water droplets with a volume of 4-6 µL to exhibit the reversible switch from low adhesive superhydrophobicity to high adhesive hydrophilicity. In addition to providing an alternative fabrication strategy, this work also presents a set of design concepts for more applicable and sensitive MRSSs, offering a reference to both fundamental research and practical applications.

[Prognosis of patients planned and unplanned admission to the intensive care unit after surgery: a comparative study].

OBJECTIVE: To compare and analyze the effect of unplanned versus planned admission to the intensive care unit (ICU) on the prognosis of high-risk patients after surgery, so as to provide a clinical evidence for clinical medical staff to evaluate whether the postoperative patients should be transferred to ICU or not after surgery. METHODS: The clinical data of patients who were transferred to ICU after surgery admitted to the Affiliated Hospital of Guizhou Medical University from January to December in 2021 were retrospectively analyzed, including gender, age, body mass index, past history (whether combined with hypertension, diabetes, pulmonary disease, cardiac disease, renal failure, liver failure, hematologic disorders, tumor, etc.), acute physiology and chronic health evaluation II (APACHE II), elective surgery, pre-operative hospital consultation, length of surgery, worst value of laboratory parameters within 24 hours of ICU admission, need for invasive mechanical ventilation (IMV), duration of IMV, length of ICU stay, total length of hospital stay, ICU mortality, in-hospital mortality, and survival status at 30th day postoperative. The unplanned patients were further divided into the immediate transfer group and delayed transfer group according to the timing of their ICU entrance after surgery, and the prognosis was compared between the two groups. Cox regression analysis was used to find the independent risk factors of 30-day mortality in patients transferred to ICU after surgery. RESULTS: Finally, 377 patients were included in the post-operative admission to the ICU, including 232 in the planned transfer group and 145 in the unplanned transfer group (42 immediate transfers and 103 delayed transfers). Compared to the planned transfer group, patients in the unplanned transfer group had higher peripheral blood white blood cell count (WBC) at the time of transfer to the ICU [×109/L: 10.86 (7.09, 16.68) vs. 10.11 (6.56, 13.27)], longer total length of hospital stay [days: 23.00 (14.00, 34.00) vs. 19.00 (12.00, 29.00)], and 30-day post-operative mortality was higher [29.66% (43/145) vs. 17.24% (40/232)], but haemoglobin (Hb), arterial partial pressure of carbon dioxide (PaCO2), oxygenation index (PaO2/FiO2), and IMV requirement rate were lower [Hb (g/L): 95.00 (78.00, 113.50) vs. 98.00 (85.00, 123.00), PaCO2 (mmHg, 1 mmHg ≈ 0.133 kPa): 36.00 (29.00, 41.50) vs. 39.00 (33.00, 43.00), PaO2/FiO2 (mmHg): 197.00 (137.50, 283.50) vs. 238.00 (178.00, 350.25), IMV requirement rate: 82.76% (120/145) vs. 93.97% (218/232)], all differences were statistically significant (all P < 0.05). Kaplan-Meier survival curve showed that the 30-day cumulative survival rate after surgery was significantly lower in the unplanned transfer group than in the planned transfer group (Log-Rank test: χ2 = 7.659, P = 0.006). Univariate Cox regression analysis showed that unplanned transfer, APACHE II score, whether deeded IMV at transfer, total length of hospital stay, WBC, blood K+, and blood lactic acid (Lac) were associated with 30-day mortality after operation (all P < 0.05). Multifactorial Cox analysis showed that unplanned transfer [hazard ratio (HR) = 2.45, 95% confidence interval (95%CI) was 1.54-3.89, P < 0.001], APACHE II score (HR = 1.03, 95%CI was 1.00-1.07, P = 0.031), the total length of hospital stay (HR = 0.86, 95%CI was 0.83-0.89, P < 0.001), the need for IMV on admission (HR = 4.31, 95%CI was 1.27-14.63, P = 0.019), highest Lac value within 24 hours of transfer to the ICU (HR = 1.17, 95%CI was 1.10-1.24, P < 0.001), and tumor history (HR = 3.12, 95%CI was 1.36-7.13, P = 0.007) were independent risk factors for patient death at 30 days post-operative, and the risk of death was 2.45 times higher in patients unplanned transferred than in those planned transferred. Subgroup analysis showed that patients in the delayed transfer group had significantly longer IMV times than those in the immediate transfer group [hours: 43.00 (11.00, 121.00) vs. 17.50 (2.75, 73.00), P < 0.05]. CONCLUSIONS: The 30-day mortality, WBC and total length of hospital stay were higher in patients who were transferred to ICU after surgery, and PaO2/FiO2 was lower. Unplanned transfer, oncology history, use of IMV, APACHE II score, total length of hospital stay, and Lac were independent risk factors for patient death at 30 days postoperatively, and patients with delayed transfer to ICU had longer IMV time.

Improving predictions and understanding of primary and ultimate biodegradation rates with machine learning models.

This study aimed to develop machine learning based quantitative structure biodegradability relationship (QSBR) models for predicting primary and ultimate biodegradation rates of organic chemicals, which are essential parameters for environmental risk assessment. For this purpose, experimental primary and ultimate biodegradation rates of high consistency were compiled for 173 organic compounds. A significant number of descriptors were calculated with a collection of quantum/computational chemistry software and tools to achieve comprehensive representation and interpretability. Following a pre-screening process, multiple QSBR models were developed for both primary and ultimate endpoints using three algorithms: extreme gradient boosting (XGBoost), support vector machine (SVM), and multiple linear regression (MLR). Furthermore, a unified QSBR model was constructed using the knowledge transfer technique and XGBoost. Results demonstrated that all QSBR models developed in this study had good performance. Particularly, SVM models exhibited high level of goodness of fit (coefficient of determination on the training set of 0.973 for primary and 0.980 for ultimate), robustness (leave-one-out cross-validated coefficient of 0.953 for primary and 0.967 for ultimate), and external predictive ability (external explained variance of 0.947 for primary and 0.958 for ultimate). The knowledge transfer technique enhanced model performance by learning from properties of two biodegradation endpoints. Williams plots were used to visualize the application domains of the models. Through SHapley Additive exPlanations (SHAP) analysis, this study identified key features affecting biodegradation rates. Notably, MDEO-12, APC2D1_C_O, and other features contributed to primary biodegradation, while AATS0v, AATS2v, and others inhibited it. For ultimate biodegradation, features like No. of Rotatable Bonds, APC2D1_C_O, and minHBa were contributors, while C1SP3, Halogen Ratio, GGI4, and others hindered the process. Also, the study quantified the contributions of each feature in predictions for individual chemicals. This research provides valuable tools for predicting both primary and ultimate biodegradation rates while offering insights into the mechanisms.

The influence of virtual environment on thermal perception: physical reaction and subjective thermal perception on outdoor scenarios in virtual reality.

Positive thermal perception can affect users' climate-controlling behavior, indirectly reducing a building's operational carbon emissions. Studies show that some visual elements, such as window sizes and light colors, can influence thermal perception. However, until recently there has been little interest in the interaction of thermal perception and outdoor visual scenarios or natural elements like water or trees, and little quantitative evidence has been found associating visual natural elements and thermal comfort. This experiment explores and quantifies the extent to which visual scenarios outdoors affect thermal perception. The experiment used a double-blind clinical trial. All tests were done in a stable laboratory environment to eliminate temperature changes, and scenarios were shown through a virtual reality (VR) headset. Forty-three participants were divided into three groups randomly, separately watched VR-outdoor scenarios with natural elements, VR-indoor scenarios, and a control scenario of the real laboratory, then finished a subjective questionnaire conducted to evaluate their thermal, environmental, and overall perceptions while their physical data (heart rate, blood pressure, pulse) was real-time recorded. Results show that visual scenarios could significantly influence thermal perception (Cohen's d between groups > 0.8). Significant positive correlations were found between key thermal perception index, thermal comfort, and visual perception indexes including visual comfort, pleasantness, and relaxation (all PCCs ≤ 0.01). Outdoor scenarios, with better visual perception, rank higher average scores (M ± SD = 1.0 ± 0.7) in thermal comfort than indoor groups (average M ± SD = 0.3 ± 1.0) while the physical environment remains unchanged. This connection between thermal and environmental perception can be used in building design. By being visually exposed to pleasing outdoor environments, the positive thermal perception will increase, and thus reduce building energy consumption. Designing positive visual environments with outdoor natural elements is not only a requirement for health but also a feasible path toward a sustainable net-zero future.

A Second-Order Crank-Nicolson Leap-Frog Scheme for the Modified Phase Field Crystal Model with Long-Range Interaction.

In this paper, we construct a fully discrete and decoupled Crank-Nicolson Leap-Frog (CNLF) scheme for solving the modified phase field crystal model (MPFC) with long-range interaction. The idea of CNLF is to treat stiff terms implicity with Crank-Nicolson and to treat non-stiff terms explicitly with Leap-Frog. In addition, the scalar auxiliary variable (SAV) method is used to allow explicit treatment of the nonlinear potential, then, these technique combines with CNLF can lead to the highly efficient, fully decoupled and linear numerical scheme with constant coefficients at each time step. Furthermore, the Fourier spectral method is used for the spatial discretization. Finally, we show that the CNLF scheme is fully discrete, second-order decoupled and unconditionally stable. Ample numerical experiments in 2D and 3D are provided to demonstrate the accuracy, efficiency, and stability of the proposed method.

The complete chloroplast genome sequence of Lithocarpus longinux (Fagaceae).

Lithocarpus longinux (Hu) Chun ex Y.C.Hsu & H.Wei Jen is a Critically Endangered tree distributed in Ma-li-po county in the Southeastern Yunnan Province China. Less than ten individuals have been found since the species was established 70 years ago. In this study, we assembled and annotated the complete chloroplast genome of L. longinux. The complete chloroplast genome of the species is 161,420 bp in length and has a GC content of 36.8%, including one large single-copy region (LSC, 90,409 bp), one small single-copy region (SSC, 19,255 bp), and two copies of inverted repeat regions (IRs, 25,878 bp). A total of 112 unique genes were detected, including 81 protein-coding genes, 29 tRNA genes, and 4 rRNA genes. Phylogenetic analysis of 31 representative chloroplast genomes of the Fagales suggests Lithocarpus is monophyletic with strong bootstrap support and that L. longinux is closely related to L. balansae.

Endophyte-assisted phytoremediation: mechanisms and current application strategies for soil mixed pollutants.

Phytoremediation uses plants and associated microbes to remove pollutants from the environment and is considered a promising bioremediation method. Compared with well-described single contaminant treatments, the number of studies reporting phytoremediation of soil mixed pollutants has increased recently. Endophytes, including bacteria and fungi, exhibit beneficial traits for the promotion of plant growth, stress alleviation, and biodegradation. Moreover, endophytes either directly or indirectly assist host plants to survive high concentrations of organic and inorganic pollutants in the soil. Endophytic microorganisms can also regulate the plant metabolism in different ways, exhibiting a variety of physiological characteristics. This review summarizes the taxa and physiological properties of endophytic microorganisms that may participate in the detoxification of contaminant mixtures. Furthermore, potential biomolecules that may enhance endophyte mediated phytoremediation are discussed. The practical applications of pollutant-degrading endophytes and current strategies for applying this valuable bio-resource to soil phytoremediation are summarized.

Research on the Relationship between Cutting Force and Machined Surface Quality in Micro Ball End-Milling of Potassium Dihydrogen Phosphate Crystal.

Potassium dihydrogen phosphate (KDP or KH2PO4) crystal is widely used as terminal frequency converters in inertial confinement fusion (ICF). However, KDP crystal is a typical difficult-to-cut optical crystal with the characteristic of soft-brittle. In this work, the relationship between cutting force and processed surface quality in micro ball end-milling of KDP crystal with various depth of cut and spindle speed is studied by carried out the micro-milling experiments. Fast Fourier Transform (FFT) algorithm is used to diagnose the recorded cutting force. The periodic change of cutting force and the cutting force after filtering noises can be got through FFT analysis. Through calculating the correlation coefficients between the static component of thrust force and roughness value Ra of machined grooves, as well as the peak-valley (P-V) value of thrust force and dimensional error of machined grooves, the roughness value Ra and dimensional error of machined grooves would be predicted by monitoring the static component and P-V value of the thrust force, respectively. The relatively large spindle speed helps to reduce the roughness value Ra. The spindle speed with moderate value is recommended to reduce the dimensional error of machined groove because the dimensional error of machined groove will increase when the spindle speed is small enough (causing brittle cutting) or large enough (reducing cutting stability).

A DFT study of water adsorption on rutile TiO2 (110) surface: The effects of surface steps.

The associative and dissociative adsorption of water molecules at low-coverage situations on rutile TiO2 (110) surface with step defects was investigated by the density functional theory calculations. Structural optimization of the hydroxylated/hydrated configurations at step edges along the 11̄1 crystal directions and the dynamic process of water dissociation were discussed to get a better description of the water/TiO2 interface. Our results indicate that steps on the TiO2 (110) surface could be an active site for water dissociation. The results of geometry optimization suggest that the stability of hydroxylated configuration is largely dependent on the locations of the H species and the recombination of water molecules from hydroxyls is observed in the fully hydroxylated condition. However, these hydroxyls can be stabilized by the associatively absorbed water nearby by forming competitive intermolecular hydrogen bonds. The dynamics of water dissociation and hydrogen diffusion were studied by the first principles molecular dynamics simulation and our results suggest that the hydrogen released by water dissociation can be transferred among the adsorbates, such as the unsaturated oxygen atoms-H2O-hydroxyl (TiO-H2O-OH) complex at step edges, or gradually diffuses to the bulk water system in the form of hydronium (H3O(+)) at higher water coverage.

Molecular mechanics of the cooperative adsorption of a Pro-Hyp-Gly tripeptide on a hydroxylated rutile TiO2(110) surface mediated by calcium ions.

The interaction of amino acids with inorganic materials at interfaces plays an important role in enhancing the biocompatibility of titanium-based alloys. The adsorption of a tripeptide, i.e. Pro-Hyp-Gly, on the hydroxylated rutile TiO2(110) surface was investigated by the MD simulations. The changes in free energy during the adsorption of both the tripeptide and calcium ions were calculated by using the PMF method in order to obtain the adsorption strength. The results suggested that the adsorption of the tripeptide on the TiO2 surface through the carboxyl groups in glycine residues can be more stable compared with other binding conformations. Special attention was focused on the cooperative adsorption of the tripeptide with the assistance of calcium ions. Calcium ions preferred to absorb at the tetradentate or monodentate sites on the negatively charged TiO2 surface. As a result of the strong attraction between the carboxyl group and calcium ions, the tripeptide can be pulled down to the surface by following the trajectory of the calcium ions, forming an indirect interaction with a sandwich structure of peptide-cation-TiO2. However, this indirect interaction could eventually transform to the direct adsorption of the tripeptide on the TiO2 surface with higher binding energy. The results may help to interpret the adsorption of peptides on inorganic materials in aqueous solution with ions.

Effect of surface roughness on the initial response of MC3T3-E1 cells cultured on polished titanium alloy.

Surface roughness has been considered as an important influencing factor for cell response. The aim of this study was to find out whether MC3T3-E1 cells, a mouse osteoblast-like cell line, can sense the amplitudes of surface topography of titanium alloy (Ti6Al4V), and if surface-dependent cell morphology would be presented on the substrata with varied roughness. A series of polished samples (Ra: 0.30~1.80 µm) were prepared to produce macroscopically parallel grooves using different grades of silicon carbide sandpaper (#100, #320, #600, #1000 and #2000). The experimental results indicated that the behavior and morphology of cells largely depended on the substrata where they were cultured. More efficient proliferation of MC3T3-E1 cells was shown on the surfaces with Ra of 0.50~1.00 µm, with respect to either the rougher or the smoother specimens. Furthermore, MC3T3-E1 cells seeded on the Ti6Al4V surfaces within this narrow range responded to the increasing surface roughness with increased proliferation. Contact guidance of cells could be observed on the rougher specimens (Ra: 0.80~1.00 µm), whereas more random orientations were exhibited for the adsorbed cells on the smoother surfaces (Ra: 0.50~0.60 µm).

Molecular dynamics simulations of collagen adsorption onto grooved rutile surface: the effects of groove width.

The early adsorption stages of collagen onto nano-grooved rutile surface without hydroxylation were studied using molecular dynamics and steered MD simulations. On the basis of plane rutile (110), two kinds of models have been adopted: single groove and parallel grooves along [1-11] crystal orientation with various width dimensions. Initially, collagens were parallel or perpendicular to the groove orientation, respectively, in order to investigate the influence of groove width on collagen adsorption. The simulation result suggests that surface grooves could exert a strong effect on collagen adsorption: when collagen was parallel to the groove direction, adsorption was favored if the groove width matched well with the dimension of collagen. However, adsorption strength may decrease as the groove width expanded. As for the condition of collagen perpendicular to the groove orientation, collagen was difficult to bend and insert into grooves in the free adsorption procedure. But the steered MD simulation results reveal that more energy was consumed for collagen to insert into narrower grooves which may be interpreted as strong barrier for adsorption. We believe that adsorption will be favored if appropriate dimension match between dimension of collagen and the groove width was approached.

Adsorption of arginine-glycine-aspartate tripeptide onto negatively charged rutile (110) mediated by cations: the effect of surface hydroxylation.

Classical molecular dynamics (MD) simulations were employed to investigate the adsorption behaviors of arginine-glycine-aspartate (RGD) tripeptide onto the negatively charged hydroxylated/nonhydroxylated rutile (110) surfaces, mediated by biologically important cations (Na+ or Ca2+). The simulation results indicate that the inherent nature of the cation determines its binding strength, thereby regulating the adsorption geometry of the peptide. The sparse hydroxyl groups on the nonhydroxylated rutile diminish the probability of H-bond formation between RGD and the surface, resulting in an early desorption of the peptide even with a mediating Na+ ion. In contrast, the negatively charged aspartate (Asp) side chain is bridged to the negatively charged hydroxylated rutile by an inner-sphere Na+ ion, in coordination with the Asp-rutile hydrogen bonds at the anchoring sites. The inner- and outer-sphere Ca2+ ions are demonstrated to be capable of "trapping" RGD on both hydroxylated and nonhydroxylated rutile, in the absence of hydrogen bonds with the surface. The strongly bound inner-sphere mediating Ca2+ ion exerts a "gluing" effect on the Asp side chain, producing a tightly packed RGD-rutile complex, whereas a less localized distribution density of the outer-sphere mediating Ca2+ ion results in a higher mobility of the Asp side chain. The intramolecular interaction is suggested to facilitate the structural stability of RGD adsorbed on the negative rutile in a "horseshoe" configuration.

Modeling the interaction between integrin-binding peptide (RGD) and rutile surface: the effect of cation mediation on Asp adsorption.

The binding of a negatively charged residue, aspartic acid (Asp) in tripeptide arginine-glycine-aspartic acid, onto a negatively charged hydroxylated rutile (110) surface in aqueous solution, containing divalent (Mg(2+), Ca(2+), or Sr(2+)) or monovalent (Na(+), K(+), or Rb(+)) cations, was studied by molecular dynamics (MD) simulations. The results indicate that ionic radii and charges will significantly affect the hydration, adsorption geometry, and distance of cations from the rutile surface, thereby regulating the Asp/rutile binding mode. The adsorption strength of monovalent cations on the rutile surface in the order Na(+) > K(+) > Rb(+) shows a "reverse" lyotropic trend, while the divalent cations on the same surface exhibit a "regular" lyotropic behavior with decreasing crystallographic radii (the adsorption strength of divalent cations: Sr(2+) > Ca(2+) > Mg(2+)). The Asp side chain in NaCl, KCl, and RbCl solutions remains stably H-bonded to the surface hydroxyls and the inner-sphere adsorbed compensating monovalent cations act as a bridge between the COO(-) group and the rutile, helping to "trap" the negatively charged Asp side chain on the negatively charged surface. In contrast, the mediating divalent cations actively participate in linking the COO(-) group to the rutile surface; thus the Asp side chain can remain stably on the rutile (110) surface, even if it is not involved in any hydrogen bonds with the surface hydroxyls. Inner- and outer-sphere geometries are all possible mediation modes for divalent cations in bridging the peptide to the rutile surface.

Molecular understanding of conformational dynamics of a fibronectin module on rutile (110) surface.

The conformational dynamics of the 10th type-III module of fibronectin (FN-III(10)) adsorbed on the perfect and three reduced rutile TiO(2)(110) surfaces with different types of defects was investigated by molecular dynamics (MD) simulations. Stable protein-surface complexes were presented in the four simulated models and were derived from the contributions of direct and indirect interactions of various functional groups in FN-III(10) with the metal oxide layers. A detailed analysis to characterize the overall structural stability of the adsorbed FN-III(10) molecule suggests that the bonding strength and the loss of protein secondary structure vary widely, depending on the topology of the substrate surface. The additional adsorption sites exhibiting higher activity, provided by the reduced surfaces, are responsible for the stronger FN-III(10)-TiO(2) interactions, but too high an interaction energy will cause a severe conformational deformation and therefore a significant loss of bioactivity of the adsorbed protein.

Peptide-TiO(2) interaction in aqueous solution: conformational dynamics of RGD using different water models.

Adsorption behavior and dynamics of Arg-Gly-Asp (RGD) tripeptides with different orientations onto the rutile TiO(2) (110) surface in water solution were systematically investigated by molecular dynamics (MD) simulations, using two different water models, TIP3P (transferable intermolecular potential 3P) and SPC/E (extended simple point charge). Possible RGD-TiO(2) binding modes in the form of hydrogen-bonding interactions, involving the amide groups (NH(3)(+) or NH(2)(+), NH(2)) and surface oxygen atoms were identified. The behavior of RGD in contact with the TiO(2) layer was elucidated in detail by the analysis of atom-atom distances, backbone dihedral angles and hydration layers distributed over the interface. The simulation results suggest that, the attachment modes of tripeptides with the same starting arrangement are similar when solvated in TIP3P and SPC/E water, but the conformational stability of the amino sequence is somewhat sensitive to the adopted solvent model. Moreover, the intensity of peptide-surface interaction varies widely depending on the initial arrangement of the RGD sequence.

RGD tripeptide onto perfect and grooved rutile surfaces in aqueous solution: adsorption behaviors and dynamics.

Molecular dynamics (MD) simulations were performed to investigate the adsorption behavior and dynamics of Arg-Gly-Asp (RGD) tripeptide onto the rutile TiO(2) (110) perfect and grooved surfaces in aqueous solution. The simulation results suggest that, driven by the electrostatic attractions between charged groups of the tripeptide and opposite-type charges of the surface atoms, RGD substitutes the adsorbed water molecules and binds to TiO(2) surface strongly through direct interactions of carboxyl oxygen (O(coo(-))) atoms with nearby titanium atoms in the interface, in agreement with some experimental observations and theoretical data. Once bonded to both perfect and grooved surfaces, RGD tripeptides show a reasonable propensity to remain there with the carboxyl groups providing anchors to the substrate surface, while the amide groups (NH(3)(+) and NH(2)) with larger separations from the attached portions, undergo relatively remarkable fluctuations during the whole simulation time. The trajectories for atom-surface distances, backbone dihedral angles and root-mean-squared deviations from the initial structure have revealed less mobility and more stable adsorption of RGD onto grooved surface than onto perfect surface, which is confirmed again by greater values of adsorption energy for available grooved surfaces.