Templated Nucleation of Clotrimazole and Ketoprofen on Polymer Substrates.

The use of different template surfaces in crystallization experiments can directly influence the nucleation kinetics, crystal growth, and morphology of active pharmaceutical ingredients (APIs). Consequently, templated nucleation is an attractive approach to enhance crystal nucleation kinetics and preferentially nucleate desired crystal polymorphs for solid-form drug molecules, particularly large and flexible molecules that are difficult to crystallize. Herein, we investigate the effect of polymer templates on the crystal nucleation of clotrimazole and ketoprofen with both experiments and computational methods. Crystallization was carried out in toluene solvent for both APIs with a template library consisting of 12 different polymers. In complement to the experimental studies, we developed a computational workflow based on molecular dynamics (MD) and derived descriptors from the simulations to score and rank API-polymer interactions. The descriptors were used to measure the energy of interaction (EOI), hydrogen bonding, and rugosity (surface roughness) similarity between the APIs and polymer templates. We used a variety of machine learning models (14 in total) along with these descriptors to predict the crystallization outcome of the polymer templates. We found that simply rank-ordering the polymers by their API-polymer interaction energy descriptors yielded 92% accuracy in predicting the experimental outcome for clotrimazole and ketoprofen. The most accurate machine learning model for both APIs was found to be a random forest model. Using these models, we were able to predict the crystallization outcomes for all polymers. Additionally, we have performed a feature importance analysis using the trained models and found that the most predictive features are the energy descriptors. These results demonstrate that API-polymer interaction energies are correlated with heterogeneous crystallization outcomes.

Tale of Two Polymorphs: Investigating the Structural Differences and Dynamic Relationship between Nirmatrelvir Solid Forms (Paxlovid).

Two anhydrous polymorphs of the novel antiviral medicine nirmatrelvir were discovered during the development of Paxlovid, Pfizer's oral Covid-19 treatment. A comprehensive experimental and computational approach was necessary to distinguish the two closely related polymorphs, herein identified as Forms 1 and 4. This approach paired experimental methods, including powder X-ray diffraction and single-crystal X-ray diffraction, solid-state experimental methods, thermal analysis, solid-state nuclear magnetic resonance and Raman spectroscopy with computational investigations comprising crystal structure prediction, Gibbs free energy calculations, and molecular dynamics simulations of the polymorphic transition. Forms 1 and 4 were ultimately determined to be enantiotropically related polymorphs with Form 1 being the stable form above the transition temperature of ∼17 °C and designated as the nominated form for drug development. The work described in this paper shows the importance of using highly specialized orthogonal approaches to elucidate the subtle differences in structure and properties of similar solid-state forms. This synergistic approach allowed for unprecedented speed in bringing Paxlovid to patients in record time amidst the pandemic.

Evaluation of bacterial anti-adhesion and sustained antimicrobial abilities of chlorhexidine gluconate-loaded phase-transited lysozyme nanoparticle suspension on dentine: An ex vivo study.

AIM: To evaluate the effect of chlorhexidine gluconate-loaded phase-transited lysozyme (CHG@PTL) coating on inhibiting bacterial adhesion and biofilm formation in an ex vivo root canal dentine model. METHODOLOGY: The physicochemical and structural characteristics of CHG@PTL nanoparticle suspension and its coating formed on the dentine surface were analysed by thioflavin T fluorescence assay, transmission electron microscopy and confocal laser scanning microscopy (CLSM). The sustained chlorhexidine release profile of the CHG@PTL coating on the dentine surface was compared with that of the 2% CHG solution. By comparing with phosphate-buffered saline, 1% sodium hypochlorite and 2% CHG solutions, the sustained antibacterial ability of the CHG@PTL coating and its effects on adhesion and biofilm formation of three types of bacteria (E. faecalis, S. mutans, and A. viscous) were analysed in ex vivo root canal dentine models using the serial plate transfer test (SPTT) and CLSM with live/dead bacterial staining, respectively. RESULTS: CHG promoted the lysozyme protein to form a higher proportion of ß-sheet structure during phase transition. In the CHG@PTL nanoparticle suspension, characteristic drug-loaded nanospheres with a high concentration of CHG molecules inside and an outer PTL nanofilm were observed, and they formed a thinner and tighter coating on the dentine surface. The CHG@PTL coating on the dentine surface showed a significantly higher cumulative release amount of chlorhexidine than that of 2% CHG (p < .05). The results of SPTT showed that the CHG@PTL coating had a longer antibacterial duration than the control groups. After 12 h of incubation, a higher number of bacteria were agglutinated on the CHG@PTL coating surface compared to the control groups (p < .05). After 7 days of incubation, the number of agglutinated bacteria significantly decreased. At two time points, the percentage of dead bacteria on the CHG@PTL coating surface was the highest among all experimental groups based on CLSM observation (over 99.9% for all three bacteria, p < .001). CONCLUSIONS: CHG@PTL nanoparticle suspension could form an antimicrobial coating on the surface of dentine with a novel 'agglutinating bacteria and sterilizing' mode.

Regulatory effect of graphene on growth and carbon/nitrogen metabolism of maize (Zea mays L.).

BACKGROUND: Leakage of graphene into the environment has resulted from its increasing use. Although the impact of graphene on ecosystems is already in full swing, information regarding its impact on plants is lacking. In particular, the effects of graphene on plant growth and development vary, and basic information on the regulation of carbon and nitrogen metabolism is missing. In the current study, the way in which graphene (0, 25, 50, 100, and 200 g kg-1 ) affects maize seedlings was studied in terms of morphological and biochemical indicators. The purpose of this study was to understand better how graphene regulates plant carbon and nitrogen metabolism and to understand its interactions with leaf structure and plant growth. RESULTS: The results showed that 50 g kg-1 graphene increased plant height, stem diameter, leaf area, and dry weight; however, this was inhibited by the high level of graphene (200 g kg-1 ). Further studies indicated that different concentrations of graphene could increase leaf thickness and vascular bundle area as well as the net photosynthetic rate (Pn) of leaves; 25 and 50 g kg-1 graphene enhanced the leaves stomatal conductance (Cond), transpiration rate (Tr), intercellular carbon dioxide (Ci), and chlorophyll content. Higher concentrations decreased the above indicators. At 50 g kg-1 , graphene increased the activity of carbon/nitrogen metabolism enzymes by increasing carbon metabolites (fructose, sucrose, and soluble sugars) and soluble proteins (nitrogen metabolites). These enzymes included sucrose synthase (SS), sucrose phosphate synthase (SPS), nitrate reductase (NR), glutamine synthase (GS), and glutamate synthase (GOGAT). CONCLUSION: These results indicate that graphene can regulate the activities of key enzymes involved in carbon and nitrogen metabolism effectively and supplement nitrogen metabolism through substances produced by carbon metabolism by improving photosynthetic efficiency, thus maintaining the balance between carbon and nitrogen and promoting plant growth and development. The relationship between these indexes explained the mechanism by which graphene supported the growth of maize seedlings by enhancing photosynthetic carbon metabolism and maintaining metabolic balance. For maize seedling growth, graphene treatment with 50 g kg-1 soil is recommended. © 2023 Society of Chemical Industry.

Absolute Configuration Determination of Chiral API Molecules by MicroED Analysis of Cocrystal Powders Formed Based on Cocrystal Propensity Prediction Calculations.

Establishing the absolute configuration of chiral active pharmaceutical ingredients (APIs) is of great importance. Single crystal X-ray diffraction (scXRD) has traditionally been the method of choice for such analysis, but scXRD requires the growth of large crystals, which can be challenging. Here, we present a method for determining absolute configuration that does not rely on the growth of large crystals. By examining microcrystals formed with chiral probes (small chiral compounds such as amino acids), absolute configuration can be unambiguously determined by microcrystal electron diffraction (MicroED). Our streamlined method employs three steps: (1) virtual screening to identify promising chiral probes, (2) experimental cocrystal screening and (3) structure determination by MicroED and absolute configuration assignment. We successfully applied this method to analyze two chiral API molecules currently on the market for which scXRD was not used to determine absolute configuration.

Emerging Landscape of Computational Modeling in Pharmaceutical Development.

Computational chemistry applications have become an integral part of the drug discovery workflow over the past 35 years. However, computational modeling in support of drug development has remained a relatively uncharted territory for a significant part of both academic and industrial communities. This review considers the computational modeling workflows for three key components of drug preclinical and clinical development, namely, process chemistry, analytical research and development, as well as drug product and formulation development. An overview of the computational support for each step of the respective workflows is presented. Additionally, in context of solid form design, special consideration is given to modern physics-based virtual screening methods. This covers rational approaches to polymorph, coformer, counterion, and solvent virtual screening in support of solid form selection and design.

Novel Physics-Based Ensemble Modeling Approach That Utilizes 3D Molecular Conformation and Packing to Access Aqueous Thermodynamic Solubility: A Case Study of Orally Available Bromodomain and Extraterminal Domain Inhibitor Lead Optimization Series.

Drug design with patient centricity for ease of administration and pill burden requires robust understanding of the impact of chemical modifications on relevant physicochemical properties early in lead optimization. To this end, we have developed a physics-based ensemble approach to predict aqueous thermodynamic crystalline solubility, with a 2D chemical structure as the input. Predictions for the bromodomain and extraterminal domain (BET) inhibitor series show very close match (0.5 log unit) with measured thermodynamic solubility for cases with low crystal anisotropy and good match (1 log unit) for high anisotropy structures. The importance of thermodynamic solubility is clearly demonstrated by up to a 4 log unit drop in solubility compared to kinetic (amorphous) solubility in some cases and implications thereof, for instance on human dose. We have also demonstrated that incorporating predicted crystal structures in thermodynamic solubility prediction is necessary to differentiate (up to 4 log unit) between solubility of molecules within the series. Finally, our physics-based ensemble approach provides valuable structural insights into the origins of 3-D conformational landscapes, crystal polymorphism, and anisotropy that can be leveraged for both drug design and development.

Guiding Lead Optimization for Solubility Improvement with Physics-Based Modeling.

Although there are a number of computational approaches available for the aqueous solubility prediction, a majority of those models rely on the existence of a training set of thermodynamic solubility measurements or/and fail to accurately account for the lattice packing contribution to the solubility. The main focus of this study is the validation of the application of a physics-based aqueous solubility approach, which does not rely on any prior knowledge and explicitly describes the solid-state contribution, in order to guide the improvement of poor solubility during the lead optimization. A superior performance of a quantum mechanical (QM)-based thermodynamic cycle approach relative to a molecular mechanical (MM)-based one in application to the optimization of two pharmaceutical series was demonstrated. The QM-based model also provided insights into the source of poor solubility of the lead compounds, allowing the selection of the optimal strategies for chemical modification and formulation. It is concluded that the application of that approach to guide solubility improvement at the late discovery and/or early development stages of the drug design proves to be highly attractive.

Identification and Genotypic Characterization of Potentially Pathogenic Acanthamoeba Isolated from Tap Water in Wuxi, China.

Members of genus Acanthamoeba are widely distributed in the environment. Some are pathogenic and cause keratitis and fatal granulomatous amoebic encephalitis. In this study, we isolated an Acanthamoeba CJW/W1 strain from tap water in Wuxi, Jiangsu Province, China. Its 18S rDNA was sequenced and a phylogenetic tree was constructed. The isolated cysts belonged to morphologic group II. Comparison of 18S rDNA sequences of CJW/W1 strain and other isolates showed high similarity (99.7%) to a clinical isolate Asp, KA/E28. A phylogeny analysis confirmed this isolate belonged to the pathogenic genotype T4, the most common strain associated with Acanthamoeba-related diseases. This is the first report of an Acanthamoeba strain isolated from tap water in Wuxi, China. Acanthamoeba could be a public health threat to the contact lens wearers and, therefore, its prevalence should be monitored.

A computational view of the change in the geometric and electronic properties of perovskites caused by the partial substitution of Pb by Sn.

Recently, solar cells with hybrid organic-inorganic lead halide perovskites have achieved a great success and their power conversion efficiency reaches about 17.9%. For practical applications, one has to avoid the toxicology issue of lead, to develop lead-free perovskite solar cells by using metal substitution. It has been shown that tin is one of possible candidates as a replacement for lead. Herein, a step-by-step protocol based on the first-principles calculations is performed to investigate the geometrical and electronic properties of mixed Sn and Pb perovskite MAPbxSn1-xI3 with different crystal symmetries. At first, a GGA functional with the inclusion of the van der Waals interaction, vdW-DF3, is used to optimize the geometries and it reproduces closely the unit cell volume. Then, a more accurate hybrid functional PBE0 combined with the spin-orbit coupling effect is used to perform electronic-structure calculations. The calculated results reveal that the band gaps of MAPbxSn1-xI3 are sensitive to the ratio of Sn/Pb, and are proportional to the x component, consistent with the previous reports. Further investigations show that the crystal symmetry can also modify the band gap in an order of Pnma > I4cm > P4mm at x = 0.5. The random rotation of organic cations, which makes the band alignments in the compounds, facilitates the separation and transfer of holes and electrons. Interestingly, the computed binding energies of the unrelaxed exciton have the same trend as band gaps, which decreases with decreasing x, the binding energies of MAPb0.5Sn0.5I3 also decrease as the crystal symmetry decreases, implying a faster exciton dissociation with lower x and lower symmetry at an ambient temperature.

Mechanisms of large Stokes shift and aggregation-enhanced emission of osmapentalyne cations in solution: combined MD simulations and QM/MM calculations.

Osmapentalyne cations synthesized recently show remarkable optical properties, such as near-infrared emission, unusual large Stokes shift and aggregation-enhanced emission. Here, the mechanisms behind those novel optical behaviors are revealed from the combined molecular dynamics simulations and hybrid quantum mechanics/molecular mechanics calculations. The results demonstrate that the large Stokes shift in the gas phase comes from a photoexcitation-induced deformation of the osmium plane, whereas in solution it corresponds to the variation of osmium ring symmetry. Although the central chromophore ring dominates the absorption and emission processes, the protecting groups PPh3 join the emission. As osmapentalyne cations are aggregated together in solution, the radical distribution functions of their mass-central distances display several peaks immersed in a broad envelope due to different aggregation pathways. However, the chromophore centers are protected by the PPh3 groups, the aggregation structures do not affect the Stokes shift too much, and the calculated aggregate-enhanced emission is consistent with experimental measurements.

Brain-Computer Interface for Patients with Spinal Cord Injury: A Bibliometric Study.

BACKGROUND: Spinal cord injury (SCI) is a debilitating condition with profound implications on patients' quality of life. Recent advancements in brain-computer interface (BCI) technology have provided novel opportunities for individuals with paralysis due to SCI. Consequently, research on the application of BCI for treating SCI has received increasing attention from scholars worldwide. However, there is a lack of rigorous bibliometric studies on the evolution and trends in this field. Hence, the present study aimed to use bibliometric methods to investigate the current status and emerging trends in the field of applying BCI for treating SCI and thus identify novel therapeutic options for SCI. METHODS: We conducted a comprehensive review of the relevant literature on BCI applications for treating SCI published between 2005 and 2024 by using the Web of Science Core Collection database. To facilitate visualization and quantitative analysis of the published literature, we used VOSviewer and CiteSpace software tools. These tools enabled the assessment of co-authorships, co-occurrences, citations, and co-citations in the selected literature, thereby providing an overview of the current trends and predictive insights into the field. RESULTS: The literature search yielded 714 publications from the Web of Science Core Collection database. The findings indicated a significant upward trend in the number of publications, yielding a total of 24,804 citations, with an average citation rate of 34.74 per publication and an H-index of 75. Research contributions were identified from 54 countries/regions, and the United States, China, and Germany emerged as the predominant contributors. A total of 1114 research institutions contributed to the retrieved literature, with Harvard Medical School, Brown University, and Northwestern University producing the highest number of publications. The published literature was predominantly distributed across 258 academic journals, and the Journal of Neural Engineering was the most frequently utilized publication source. Hochberg, Leigh, Henderson, Jaimie, and Collinger were the prominent authors in this field. CONCLUSIONS: In recent years, there has been a steep increase in research on the use of BCI for treating SCI. Existing research focuses on the application of BCI for improving rehabilitation and quality of life of patients with SCI. Interdisciplinary collaboration is the current trend in this field.

Development and Comprehensive Benchmark of a High-Quality AMBER-Consistent Small Molecule Force Field with Broad Chemical Space Coverage for Molecular Modeling and Free Energy Calculation.

Biomolecular simulations have become an essential tool in contemporary drug discovery, and molecular mechanics force fields (FFs) constitute its cornerstone. Developing a high quality and broad coverage general FF is a significant undertaking that requires substantial expert knowledge and computing resources, which is beyond the scope of general practitioners. Existing FFs originate from only a limited number of groups and organizations, and they either suffer from limited numbers of training sets, lower than desired quality because of oversimplified representations, or are costly for the molecular modeling community to access. To address these issues, in this work, we developed an AMBER-consistent small molecule FF with extensive chemical space coverage, and we provide Open Access parameters for the entire modeling community. To validate our FF, we carried out benchmarks of quantum mechanics (QM)/molecular mechanics conformer comparison and free energy perturbation calculations on several benchmark data sets. Our FF achieves a higher level of performance at reproducing QM energies and geometries than two popular open-source FFs, OpenFF2 and GAFF2. In relative binding free energy calculations for 31 protein-ligand data sets, comprising 1079 pairs of ligands, the new FF achieves an overall root-mean-square error of 1.19 kcal/mol for ΔΔG and 0.92 kcal/mol for ΔG on a subset of 463 ligands without bespoke fitting to the data sets. The results are on par with those of the leading commercial series of OPLS FFs.

Effect of Polymer Additives on the Crystal Habit of Metformin HCl.

The crystal habit can have a profound influence on the physical properties of crystalline materials, and thus controlling the crystal morphology is of great practical relevance across many industries. Herein, this work investigates the effect of polymer additives on the crystal habit of metformin HCl with both experiments and computational methods with the aim of developing a combined screening approach for crystal morphology engineering. Crystallization experiments of metformin HCl are conducted in methanol and in an isopropanol-water mixture (8:2 V/V). Polyethylene glycol, polyvinylpyrrolidone, Tween80, and hydroxypropyl methylcellulose polymer additives are used in low concentrations (1-2% w/w) in the experiments to study the effect they have on modifying the crystal habit. Additionally, this work has developed computational methods to characterize the morphology "landscape" and quantifies the overall effect of solvent and additives on the predicted crystal habits. Further analysis of the molecular dynamics simulations is used to rationalize the effect of additives on specific crystal faces. This work demonstrates that the effects of additives on the crystal habit are a result of their absorption and interactions with the slow growing {100} and {020} faces.

Selecting a stable solid form of remdesivir using microcrystal electron diffraction and crystal structure prediction.

Therapeutic options in response to the coronavirus disease 2019 (COVID-19) outbreak are urgently needed. In this communication, we demonstrate how to support selection of a stable solid form of an antiviral drug remdesivir in quick time using the microcrystal electron diffraction (MicroED) technique and a cloud-based and artificial intelligence implemented crystal structure prediction platform. We present the MicroED structures of remdesivir forms II and IV and conclude that form II is more stable than form IV at ambient temperature in agreement with experimental observations. The combined experimental and theoretical study can serve as a template for formulation scientists in the pharmaceutical industry.

Virtual Coformer Screening by Crystal Structure Predictions: Crucial Role of Crystallinity in Pharmaceutical Cocrystallization.

One of the most popular strategies of the optimization of drug properties in the pharmaceutical industry appears to be a solid form changing into a cocrystalline form. A number of virtual screening approaches have been previously developed to allow a selection of the most promising cocrystal formers (coformers) for an experimental follow-up. A significant drawback of those methods is related to the lack of accounting for the crystallinity contribution to cocrystal formation. To address this issue, we propose in this study two virtual coformer screening approaches based on a modern cloud-computing crystal structure prediction (CSP) technology at a dispersion-corrected density functional theory (DFT-D) level. The CSP-based methods were for the first time validated on challenging cases of indomethacin and paracetamol cocrystallization, for which the previously developed approaches provided poor predictions. The calculations demonstrated a dramatic improvement of the virtual coformer screening performance relative to the other methods. It is demonstrated that the crystallinity contribution to the formation of paracetamol and indomethacin cocrystals is a dominant one and, therefore, should not be ignored in the virtual screening calculations. Our results encourage a broad utilization of the proposed CSP-based technology in the pharmaceutical industry as the only virtual coformer screening method that directly accounts for the crystallinity contribution.

Overcoming the difficulties of predicting conformational polymorph energetics in molecular crystals via correlated wavefunction methods.

Molecular crystal structure prediction is increasingly being applied to study the solid form landscapes of larger, more flexible pharmaceutical molecules. Despite many successes in crystal structure prediction, van der Waals-inclusive density functional theory (DFT) methods exhibit serious failures predicting the polymorph stabilities for a number of systems exhibiting conformational polymorphism, where changes in intramolecular conformation lead to different intermolecular crystal packings. Here, the stabilities of the conformational polymorphs of o-acetamidobenzamide, ROY, and oxalyl dihydrazide are examined in detail. DFT functionals that have previously been very successful in crystal structure prediction perform poorly in all three systems, due primarily to the poor intramolecular conformational energies, but also due to the intermolecular description in oxalyl dihydrazide. In all three cases, a fragment-based dispersion-corrected second-order Møller-Plesset perturbation theory (MP2D) treatment of the crystals overcomes these difficulties and predicts conformational polymorph stabilities in good agreement with experiment. These results highlight the need for methods which go beyond current-generation DFT functionals to make crystal polymorph stability predictions truly reliable.

Effects of at-home bleaching and resin infiltration treatments on the aesthetic and psychological status of patients with dental fluorosis: A prospective study.

OBJECTIVE: This study aims to evaluate the effect of the combination approach of at-home bleaching (HB) and resin infiltration (RI) techniques on different severity degrees of dental fluorosis (DF) and further analyze the psychological changes caused by HB and RI in patients. METHOD: Twenty-two patients (4 males, 18 females, 27.8 ±â€¯1.6 yrs) with 186 fluorotic teeth were included in this study and classified into mild (N = 56), moderate (N = 100) and severe (N = 30) DF groups according to the Dean's index. The treatment effects on patients with DF were assessed by questionnaires including the changes in patients' subjective evaluation of their teeth and psychological status before and after treatments. Standardized digital photographs were taken at each time point of the treatment process, including baseline (T1), after bleaching (T2), immediately after RI treatment (T3) and more than six months after RI treatment (T4). The color alterations (ΔE) between the fluorotic (F2) and the surrounding relatively sound areas (F1) were analyzed. RESULTS: Bad tooth appearance caused 13.64% of patients often depressed, frustrated, or disappointed, whereas 72.72% occasionally had these feelings. After treatment, the satisfaction of DF patients regarding tooth appearance increased from 0% (satisfied) to 58.82% (satisfied) and 23.53% (very satisfied). Moreover, these treatments improved all patients' confidence in smiling, laughing and showing their teeth. The percentage of fluorotic teeth with ΔE values more than 3.0 and 3.7 units decreased gradually from T1 stage to T3 stage in mild and moderate DF groups (p < 0.05), whereas the ΔE value in T3 stage was significantly lower than that of T2 stage in severe DF group (p < 0.05). In T4 stage, no significant difference was observed in the ΔE values between T4 and T3 stages (p > 0.05). CONCLUSION: This study shows the obvious positive aesthetic effect of HB and RI treatment on different severity degrees of DF and the great improvements in psychological discomforts. CLINICAL SIGNIFICANCE: The combination treatment of RI and low concentration HB gel improves the aesthetics of DF and may have a stable effect after 6-months follow-up, suggesting that this approach is a valuable clinical choice for dentists to treat DF.

Expression and distribution of three transient receptor potential vanilloid(TRPV) channel proteins in human odontoblast-like cells.

Odontoblasts have been suggested to contribute to nociceptive sensation in the tooth via expression of the transient receptor potential (TRP) channels. The TRP channels as a family of nonselective cation permeable channels play an important role in sensory transduction of human. In this study, we examined the expression of transient receptor potential vanilloid-1 (TRPV1), transient receptor potential vanilloid-2 (TRPV2) and transient receptor potential vanilloid-3 (TRPV3) channels in native human odontoblasts (HODs) and long-term cultured human dental pulp cells with odontoblast phenotyoe (LHOPs) obtained from healthy wisdom teeth with the use of immunohistochemistry (IHC), immunofluorescence (IF), quantitative real-time polymerase chain reaction (qRT-PCR),western blotting (WB) and immunoelectron microscopy (IEM) assay. LHOPs samples were made into ultrathin sections, mounted on nickel grids, floated of three TRPV antibodies conjugated with 10 nm colloidal gold particles and observed under IEM at 60,000 magnifications. The relative intracellular distributions of these three channels were analyzed quantitatively on IEM images using a robust sampling, stereological estimation and statistical evaluation method. The results of IHC and IF convinced that TRPV1, TRPV2 and TRPV3 channels were expressed in native HODs and (LHOPs). The result of qRT-PCR and WB confirmed that the gene and protein expression of TRPV1, TRPV2, and TRPV3 channels and TRPV1 mRNA are more abundantly expressed than TRPV2 and TRPV3 in HODs (P < 0.05). Quantitative analysis of IEM images showed that the relative intracellular distributions of these three channels are similar, and TRPV1, TRPV2 and TRPV3 proteins were preferential labeled in human odontoblast processes, mitochondria, and endoplasmic reticulum. Thus, HODs could play an important role in mediating pulp thermo-sensation due to the expression of these three TRPV channels. The difference of relative intracellular distributions of three channels suggests that special structures such as processes may have an important role to sensing of the outer stimuli first.

Aggregation-Induced Emission Mechanism of Dimethoxy-Tetraphenylethylene in Water Solution: Molecular Dynamics and QM/MM Investigations.

Molecular dynamics simulations and combined quantum mechanics and molecular mechanics calculations are employed to investigate dimethoxy-tetraphenylethylene (DMO-TPE) molecules in water solution for their detailed aggregation process and the mechanism of aggregation-induced emission. The molecular dynamics simulations show that the aggregates start to appear in the nanosecond time scale, and small molecular aggregates appear at low concentration; whereas the large aggregates with a chain-type structure appear at high concentration, and the intramolecular rotation is largely restricted by a molecular aggregated environment. The average radical distribution demonstrates that the waters join the aggregation process and that two types of hydrogen bonds between DMO-TPE and water molecules are built with the peaks at about 0.5 and 0.7 nm, respectively. The spectral features further reveal that the aggregates dominantly present J-type aggregation although they fluctuate between J-type and H-type at a given temperature. The statistical absorption, emission spectra, and the aggregation-induced emission enhancement with respect to the solution concentration agree well with the experimental measurements, indicating the significant effect of molecular environments on the molecular properties.