Meta-Analysis of Flipped Learning Effects in Nursing Education.

BACKGROUND: This study is a meta-analysis confirming the effect size of clinical competence, critical thinking ability, self-directedness, and learning satisfaction, the outcome variables of flipped learning applied to nursing education. METHODS: We selected 18 related studies that analyzed data using CMA (Comprehensive Meta-Analysis 2.2). RESULTS: The effect size of the entire study was Hedges' g = 0.68 (95% CI = 0.43~0.92). The heterogeneity of the overall effect size was I2 = 90.7% (Q = 246.67, p < 0.001); critical thinking ability had an effect size of Hedges' g = 0.87, learning satisfaction of Hedges' g = 0.79, clinical competence of Hedges' g = 0.53, and self-directedness of Hedges' g = 0.37. The differences were statistically significant. CONCLUSION: Flipped learning can effectively improve nursing students' clinical competence, critical thinking ability, self-direction, and learning satisfaction.

Electrochemical Reduction of O2 in Ca2+ -Containing DMSO: Role of Roughness and Single Crystal Structure.

In this study, the oxygen reduction reaction (ORR) in Ca2+ -containing dimethyl sulfoxide (DMSO) at well-ordered and rough electrode surfaces is compared by using cyclic voltammetry, differential electrochemical mass spectrometry, rotating ring disk electrode, and atomic force microscopy measurements. Slightly soluble CaO2 is the main product during early ORR on gold electrodes; after completion of a monolayer of CaO and/or CaO2 , which is formed in parallel and in competition to the peroxide, only superoxide is formed. When the monolayer is completely closed on smooth annealed Au, no further reduction occurs, whereas on rough Au a defect-rich layer allows for continuous formation of superoxide. CaO2 formed either via two subsequent 1  e - transfer steps or by disproportionation of superoxide may be deposited on top of the CaO/CaO2 adsorbate layer. The slow dissolution of the peroxide particles is demonstrated by AFM. Whereas a smooth CaO/CaO2 -covered electrode shows severe deactivation and a CaO/CaO2 -covered rough electrode allows for diffusion-limited superoxide formation, on single crystals peroxide formation is more pronounced. The reason is most likely the lack of nucleation sites for the blocking CaO/CaO2 layer. RRDE investigations showed sluggish reoxidation kinetics of the dissolved peroxide, which are most likely due to ion pairing with Ca2+ . The apparent transfer coefficient is estimated by using variation of the electrode roughness, confirming the result of the usual Tafel analysis and indicating an equilibrated first 1  e - transfer.

In situ friction study of Ag Underpotential deposition (UPD) on Au(111) in aqueous electrolyte.

The electrodeposition of silver on Au(111) was investigated using lateral force microscopy (LFM) in Ag+ containing sulfuric acid. Friction force images show that adsorbed sulfate forms 3 × 7 R 19 . 1 ∘ structure ( θ s u l f a t e = 0 . 2 ) on Au(111) prior to Ag underpotential deposition (UPD) and ( 3 × 3 R 30 ∘ ) structure ( θ s u l f a t e = 0 . 33 ) on a complete monolayer or bilayer of Ag. Variation of friction with normal load shows a non-monotonous dependence, which is caused by increasing penetration of the tip into the sulfate adlayer. In addition, the friction force is influenced by the varying coverage and mobility of Ag atoms on the surface. Before Ag coverage reaches the critical value, the deposited silver atoms may be mobile enough to be dragged by the movement of AFM tip. Possible penetration of the tip into the UPD layer at very high loads is discussed as a model for self-healing wear. However, when the coverage of Ag is close to 1, the deposited Ag atoms are tight enough to resist the influence of the AFM tip and the tip penetrates only into the sulfate adlayer.

The Mediating Effect of Insecure Adult Attachment on the Relationship between Smartphone Addiction and Self-Directed Learning in University Students.

(1) Purpose: This study aimed to explore the mediating effect of insecure adult attachment on the relationship between smartphone addiction and self-directed learning in university students. (2) Methods: In total, 235 university students participated in this study. Data analysis was carried out through a three-stage verification procedure: Sobel test using technical statistics, Pearson correlation, and multiple regression analysis. (3) Results: Smartphone addiction was positively correlated with insecure adult attachment, attachment anxiety, and self-directed learning, whereas self-directed learning had a significant negative correlation with insecure adult attachment and attachment anxiety. Insecure adult attachment had a mediating effect on the relationship between smartphone addiction and self-directed learning. (4) Conclusion: Higher levels of smartphone addiction indicated higher levels of insecure adult attachment and reduced self-directed learning ability. Therefore, while the prevention of smartphone addiction is critical for improving self-directed learning skills, programs should be developed to foster the formation of secure adult attachment among university students.

Finding prognostic gene pairs for cancer from patient-specific gene networks.

BACKGROUND: Molecular characterization of individual cancer patients is important because cancer is a complex and heterogeneous disease with many possible genetic and environmental causes. Many studies have been conducted to identify diagnostic or prognostic gene signatures for cancer from gene expression profiles. However, some gene signatures may fail to serve as diagnostic or prognostic biomarkers and gene signatures may not be found in gene expression profiles. METHODS: In this study, we developed a general method for constructing patient-specific gene correlation networks and for identifying prognostic gene pairs from the networks. A patient-specific gene correlation network was constructed by comparing a reference gene correlation network from normal samples to a network perturbed by a single patient sample. The main difference of our method from previous ones includes (1) it is focused on finding prognostic gene pairs rather than prognostic genes and (2) it can identify prognostic gene pairs from gene expression profiles even when no significant prognostic genes exist. RESULTS: Evaluation of our method with extensive data sets of three cancer types (breast invasive carcinoma, colon adenocarcinoma, and lung adenocarcinoma) showed that our approach is general and that gene pairs can serve as more reliable prognostic signatures for cancer than genes. CONCLUSIONS: Our study revealed that prognosis of individual cancer patients is associated with the existence of prognostic gene pairs in the patient-specific network and the size of a subnetwork of the prognostic gene pairs in the patient-specific network. Although preliminary, our approach will be useful for finding gene pairs to predict survival time of patients and to tailor treatments to individual characteristics. The program for dynamically constructing patient-specific gene networks and for finding prognostic gene pairs is available at http://bclab.inha.ac.kr/pancancer.

Interlaboratory Comparison of Hydrogen-Deuterium Exchange Mass Spectrometry Measurements of the Fab Fragment of NISTmAb.

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is an established, powerful tool for investigating protein-ligand interactions, protein folding, and protein dynamics. However, HDX-MS is still an emergent tool for quality control of biopharmaceuticals and for establishing dynamic similarity between a biosimilar and an innovator therapeutic. Because industry will conduct quality control and similarity measurements over a product lifetime and in multiple locations, an understanding of HDX-MS reproducibility is critical. To determine the reproducibility of continuous-labeling, bottom-up HDX-MS measurements, the present interlaboratory comparison project evaluated deuterium uptake data from the Fab fragment of NISTmAb reference material (PDB: 5K8A ) from 15 laboratories. Laboratories reported ∼89 800 centroid measurements for 430 proteolytic peptide sequences of the Fab fragment (∼78 900 centroids), giving ∼100% coverage, and ∼10 900 centroid measurements for 77 peptide sequences of the Fc fragment. Nearly half of peptide sequences are unique to the reporting laboratory, and only two sequences are reported by all laboratories. The majority of the laboratories (87%) exhibited centroid mass laboratory repeatability precisions of ⟨ sLab⟩ ≤ (0.15 ± 0.01) Da (1σx̅). All laboratories achieved ⟨sLab⟩ ≤ 0.4 Da. For immersions of protein at THDX = (3.6 to 25) °C and for D2O exchange times of tHDX = (30 s to 4 h) the reproducibility of back-exchange corrected, deuterium uptake measurements for the 15 laboratories is σreproducibility15 Laboratories( tHDX) = (9.0 ± 0.9) % (1σ). A nine laboratory cohort that immersed samples at THDX = 25 °C exhibited reproducibility of σreproducibility25C cohort( tHDX) = (6.5 ± 0.6) % for back-exchange corrected, deuterium uptake measurements.

First Report of Two Colletotrichum Species Associated with Bitter Rot on Apple Fruit in Korea - C. fructicola and C. siamense.

Bitter rot caused by the fungal genus Colletotrichum is a well-known, common disease of apple and causes significant yield loss. In 2013, six fungal strains were isolated from Fuji apple fruits exhibiting symptoms of bitter rot from Andong, Korea. These strains were identified as Colletotrichum fructicola and C. siamense based on morphological characteristics and multilocus sequence analysis of the internal transcribed spacer rDNA, actin, calmodulin, chitin synthase, and glyceraldehyde-3-phosphate dehydrogenase Pathogenicity tests confirmed the involvement of C. fructicola and C. siamense in the development of disease symptoms on apple fruits. This is the first report of C. fructicola and C. siamense causing bitter rot on apple fruit in Korea.

Estimation of Hydrogen-Exchange Protection Factors from MD Simulation Based on Amide Hydrogen Bonding Analysis.

Hydrogen exchange (HX) studies have provided critical insight into our understanding of protein folding, structure, and dynamics. More recently, hydrogen exchange mass spectrometry (HX-MS) has become a widely applicable tool for HX studies. The interpretation of the wealth of data generated by HX-MS experiments as well as other HX methods would greatly benefit from the availability of exchange predictions derived from structures or models for comparison with experiment. Most reported computational HX modeling studies have employed solvent-accessible-surface-area based metrics in attempts to interpret HX data on the basis of structures or models. In this study, a computational HX-MS prediction method based on classification of the amide hydrogen bonding modes mimicking the local unfolding model is demonstrated. Analysis of the NH bonding configurations from molecular dynamics (MD) simulation snapshots is used to determine partitioning over bonded and nonbonded NH states and is directly mapped into a protection factor (PF) using a logistics growth function. Predicted PFs are then used for calculating deuteration values of peptides and compared with experimental data. Hydrogen exchange MS data for fatty acid synthase thioesterase (FAS-TE) collected for a range of pHs and temperatures was used for detailed evaluation of the approach. High correlation between prediction and experiment for observable fragment peptides is observed in the FAS-TE and additional benchmarking systems that included various apo/holo proteins for which literature data were available. In addition, it is shown that HX modeling can improve experimental resolution through decomposition of in-exchange curves into rate classes, which correlate with prediction from MD. Successful rate class decompositions provide further evidence that the presented approach captures the underlying physical processes correctly at the single residue level. This assessment is further strengthened in a comparison of residue resolved protection factor predictions for staphylococcal nuclease with NMR data, which was also used to compare prediction performance with other algorithms described in the literature. The demonstrated transferable and scalable MD based HX prediction approach adds significantly to the available tools for HX-MS data interpretation based on available structures and models.

A collaborative visual analytics suite for protein folding research.

Molecular dynamics (MD) simulation is a crucial tool for understanding principles behind important biochemical processes such as protein folding and molecular interaction. With the rapidly increasing power of modern computers, large-scale MD simulation experiments can be performed regularly, generating huge amounts of MD data. An important question is how to analyze and interpret such massive and complex data. One of the (many) challenges involved in analyzing MD simulation data computationally is the high-dimensionality of such data. Given a massive collection of molecular conformations, researchers typically need to rely on their expertise and prior domain knowledge in order to retrieve certain conformations of interest. It is not easy to make and test hypotheses as the data set as a whole is somewhat "invisible" due to its high dimensionality. In other words, it is hard to directly access and examine individual conformations from a sea of molecular structures, and to further explore the entire data set. There is also no easy and convenient way to obtain a global view of the data or its various modalities of biochemical information. To this end, we present an interactive, collaborative visual analytics tool for exploring massive, high-dimensional molecular dynamics simulation data sets. The most important utility of our tool is to provide a platform where researchers can easily and effectively navigate through the otherwise "invisible" simulation data sets, exploring and examining molecular conformations both as a whole and at individual levels. The visualization is based on the concept of a topological landscape, which is a 2D terrain metaphor preserving certain topological and geometric properties of the high dimensional protein energy landscape. In addition to facilitating easy exploration of conformations, this 2D terrain metaphor also provides a platform where researchers can visualize and analyze various properties (such as contact density) overlayed on the top of the 2D terrain. Finally, the software provides a collaborative environment where multiple researchers can assemble observations and biochemical events into storyboards and share them in real time over the Internet via a client-server architecture. The software is written in Scala and runs on the cross-platform Java Virtual Machine. Binaries and source code are available at http://www.aylasoftware.org and have been released under the GNU General Public License.

Structural and functional characterization of BaiA, an enzyme involved in secondary bile acid synthesis in human gut microbe.

Despite significant influence of secondary bile acids on human health and disease, limited structural and biochemical information is available for the key gut microbial enzymes catalyzing its synthesis. Herein, we report apo- and cofactor bound crystal structures of BaiA2, a short chain dehydrogenase/reductase from Clostridium scindens VPI 12708 that represent the first protein structure of this pathway. The structures elucidated the basis of cofactor specificity and mechanism of proton relay. A conformational restriction involving Glu42 located in the cofactor binding site seems crucial in determining cofactor specificity. Limited flexibility of Glu42 results in imminent steric and electrostatic hindrance with 2'-phosphate group of NADP(H). Consistent with crystal structures, steady state kinetic characterization performed with both BaiA2 and BaiA1, a close homolog with 92% sequence identity, revealed specificity constant (kcat /KM ) of NADP(+) at least an order of magnitude lower than NAD(+) . Substitution of Glu42 with Ala improved specificity toward NADP(+) by 10-fold compared to wild type. The cofactor bound structure uncovered a novel nicotinamide-hydroxyl ion (NAD(+) -OH(-) ) adduct contraposing previously reported adducts. The OH(-) of the adduct in BaiA2 is distal to C4 atom of nicotinamide and proximal to 2'-hydroxyl group of the ribose moiety. Moreover, it is located at intermediary distances between terminal functional groups of active site residues Tyr157 (2.7 Å) and Lys161 (4.5 Å). Based on these observations, we propose an involvement of NAD(+) -OH(-) adduct in proton relay instead of hydride transfer as noted for previous adducts.

Design, synthesis and biological studies of survivin dimerization modulators that prolong mitotic cycle.

Survivin, a member of the inhibitor of apoptosis protein (IAP) family proteins, has essential roles in cell division and inhibition of apoptosis. Several clinical studies in cancer patients have shown that the elevated levels of survivin correlate with aggressiveness of the disease and resistance to radiation and chemotherapeutic treatments. Survivin is an integral component of chromosomal passenger complex (CPC) where it binds to borealin and INCENP through its dimerization interface. Thus, disruption of functional survivin along its dimer interface with a small molecule is hypothesized to inhibit the proliferation of cancer cells and sensitize them to therapeutic agents and radiation. Recently, a small molecule (Abbott8) was reported to bind at the dimerization interface of survivin. Further development of this compound was accomplished by computational modeling of the molecular interactions along the dimerization interface, which has led to the design of promising survivin dimerization modulators. Two of the most potent survivin modulators, LLP3 and LLP9 at concentrations between 50 and 100nM, caused delay in mitotic progression and major mitotic defects in proliferating human umbilical vein endothelial cells (HUVEC) and prostate cancer cells (PC3).

Mapping conformational dynamics of proteins using torsional dynamics simulations.

All-atom molecular dynamics simulations are widely used to study the flexibility of protein conformations. However, enhanced sampling techniques are required for simulating protein dynamics that occur on the millisecond timescale. In this work, we show that torsional molecular dynamics simulations enhance protein conformational sampling by performing conformational search in the low-frequency torsional degrees of freedom. In this article, we use our recently developed torsional-dynamics method called Generalized Newton-Euler Inverse Mass Operator (GNEIMO) to study the conformational dynamics of four proteins. We investigate the use of the GNEIMO method in simulations of the conformationally flexible proteins fasciculin and calmodulin, as well as the less flexible crambin and bovine pancreatic trypsin inhibitor. For the latter two proteins, the GNEIMO simulations with an implicit-solvent model reproduced the average protein structural fluctuations and sample conformations similar to those from Cartesian simulations with explicit solvent. The application of GNEIMO with replica exchange to the study of fasciculin conformational dynamics produced sampling of two of this protein's experimentally established conformational substates. Conformational transition of calmodulin from the Ca(2+)-bound to the Ca(2+)-free conformation occurred readily with GNEIMO simulations. Moreover, the GNEIMO method generated an ensemble of conformations that satisfy about half of both short- and long-range interresidue distances obtained from NMR structures of holo to apo transitions in calmodulin. Although unconstrained all-atom Cartesian simulations have failed to sample transitions between the substates of fasciculin and calmodulin, GNEIMO simulations show the transitions in both systems. The relatively short simulation times required to capture these long-timescale conformational dynamics indicate that GNEIMO is a promising molecular-dynamics technique for studying domain motion in proteins.

Impairment of glioma stem cell survival and growth by a novel inhibitor for Survivin-Ran protein complex.

PURPOSE: Glioblastoma multiforme (GBM) is a devastating disease. Recent studies suggest that the stem cell properties of GBM contribute to the development of therapy resistance. EXPERIMENTAL DESIGN: The expression of Survivin and Ran was evaluated by immunohistochemistry with GBM tissues, and quantitative reverse transcriptase (qRT)-PCR and immunocytochemistry with patient-derived GBM sphere cultures. With a computational structure-based drug design, 11 small-molecule compounds were designed, synthesized, and evaluated as inhibitor candidates for the molecular interaction of Survivin protein. The molecular mechanism of the lead compound, LLP-3, was determined by Western blot, ELISA, in situ proximity ligation assay, and immunocytochemistry. The effects of LLP-3 treatment on GSCs were evaluated both in vitro and in vivo. Quantitative immunohistochemistry was carried out to compare Survivin expression in tissues from 44 newly diagnosed and 31 recurrent post-chemoradiation GBM patients. Lastly, the sensitivities of temozolomide-resistant GBM spheres to LLP-3 were evaluated in vitro. RESULTS: Survivin and Ran were strongly expressed in GBM tissues, particularly in the perivasculature, and also in patient-derived GSC cultures. LLP-3 treatment disrupted the Survivin-Ran protein complex in cancer cells and abolished the growth of patient-derived GBM spheres in vitro and in vivo. This inhibition was dependent on caspase activity and associated with p53 status of cells. Immunohistochemistry showed that Survivin expression is significantly increased in recurrent GBM compared with newly diagnosed tumors, and temozolomide-resistant GBM spheres exhibited high sensitivities to LLP-3 treatment. CONCLUSIONS: Disruption of the Survivin-Ran complex by LLP-3 abolishes survival and growth of GSCs both in vitro and in vivo, indicating an attractive novel therapeutic approach for GBM.

Structure refinement of protein low resolution models using the GNEIMO constrained dynamics method.

The challenge in protein structure prediction using homology modeling is the lack of reliable methods to refine the low resolution homology models. Unconstrained all-atom molecular dynamics (MD) does not serve well for structure refinement due to its limited conformational search. We have developed and tested the constrained MD method, based on the generalized Newton-Euler inverse mass operator (GNEIMO) algorithm for protein structure refinement. In this method, the high-frequency degrees of freedom are replaced with hard holonomic constraints and a protein is modeled as a collection of rigid body clusters connected by flexible torsional hinges. This allows larger integration time steps and enhances the conformational search space. In this work, we have demonstrated the use of torsional GNEIMO method without using any experimental data as constraints, for protein structure refinement starting from low-resolution decoy sets derived from homology methods. In the eight proteins with three decoys for each, we observed an improvement of ~2 Å in the rmsd in coordinates to the known experimental structures of these proteins. The GNEIMO trajectories also showed enrichment in the population density of native-like conformations. In addition, we demonstrated structural refinement using a "freeze and thaw" clustering scheme with the GNEIMO framework as a viable tool for enhancing localized conformational search. We have derived a robust protocol based on the GNEIMO replica exchange method for protein structure refinement that can be readily extended to other proteins and possibly applicable for high throughput protein structure refinement.

Equipartition Principle for Internal Coordinate Molecular Dynamics.

The principle of equipartition of (kinetic) energy for all-atom Cartesian molecular dynamics states that each momentum phase space coordinate on the average has ½kT of kinetic energy in a canonical ensemble. This principle is used in molecular dynamics simulations to initialize velocities, and to calculate statistical properties such as entropy. Internal coordinate molecular dynamics (ICMD) models differ from Cartesian models in that the overall kinetic energy depends on the generalized coordinates and includes cross-terms. Due to this coupled structure, no such equipartition principle holds for ICMD models. In this paper we introduce non-canonical modal coordinates to recover some of the structural simplicity of Cartesian models and develop a new equipartition principle for ICMD models. We derive low-order recursive computational algorithms for transforming between the modal and physical coordinates. The equipartition principle in modal coordinates provides a rigorous method for initializing velocities in ICMD simulations thus replacing the ad hoc methods used until now. It also sets the basis for calculating conformational entropy using internal coordinates.

Simultaneous binding of two peptidyl ligands by a SRC homology 2 domain.

Src homology 2 (SH2) domains mediate protein-protein interactions by recognizing phosphotyrosine (pY)-containing sequences of target proteins. In all of the SH2 domain-pY peptide interactions described to date, the SH2 domain binds to a single pY peptide. Here, determination of the cocrystal structure of the N-terminal SH2 domain of phosphatase SHP-2 bound to a class IV peptide (VIpYFVP) revealed a noncanonical 1:2 (protein-peptide) complex. The first peptide binds in a canonical manner with its pY side chain inserted in the usual binding pocket, while the second pairs up with the first to form two antiparallel ß-strands that extend the central ß-sheet of the SH2 domain. This unprecedented binding mode was confirmed in the solution phase by NMR experiments and shown to be adopted by pY peptides derived from cellular proteins. Site-directed mutagenesis and surface plasmon resonance studies revealed that the binding of the first peptide is pY-dependent, but phosphorylation is not required for the second peptide. Our findings suggest a potential new function for the SH2 domain as a molecular clamp to promote dimerization of signaling proteins.

Folding of small proteins using constrained molecular dynamics.

The focus of this paper is to examine whether conformational search using constrained molecular dynamics (MD) method is more enhanced and enriched toward "native-like" structures compared to all-atom MD for the protein folding as a model problem. Constrained MD methods provide an alternate MD tool for protein structure prediction and structure refinement. It is computationally expensive to perform all-atom simulations of protein folding because the processes occur on a time scale of microseconds. Compared to the all-atom MD simulation, constrained MD methods have the advantage that stable dynamics can be achieved for larger time steps and the number of degrees of freedom is an order of magnitude smaller, leading to a decrease in computational cost. We have developed a generalized constrained MD method that allows the user to "freeze and thaw" torsional degrees of freedom as fit for the problem studied. We have used this method to perform all-torsion constrained MD in implicit solvent coupled with the replica exchange method to study folding of small proteins with various secondary structural motifs such as, α-helix (polyalanine, WALP16), ß-turn (1E0Q), and a mixed motif protein (Trp-cage). We demonstrate that constrained MD replica exchange method exhibits a wider conformational search than all-atom MD with increased enrichment of near-native structures. "Hierarchical" constrained MD simulations, where the partially formed helical regions in the initial stretch of the all-torsion folding simulation trajectory of Trp-cage were frozen, showed a better sampling of near-native structures than all-torsion constrained MD simulations. This is in agreement with the zipping-and-assembly folding model put forth by Dill and co-workers for folding proteins. The use of hierarchical "freeze and thaw" clustering schemes in constrained MD simulation can be used to sample conformations that contribute significantly to folding of proteins.

Characterization of molecular recognition of STAT3 SH2 domain inhibitors through molecular simulation.

Signal transducer and activator of transcription 3 (STAT3) is an anti-cancer target protein due to its over-activation in tumor cells. The Tyr705-phosphorylated (pTyr) STAT3 binds to the pTyr-recognition site of its Src Homology 2 (SH2) domain of another STAT3 monomer to form a homo-dimer, which then causes cellular anti-apoptosis, proliferation, and tumor invasion. Recently, many STAT3 SH2 dimerization inhibitors have been discovered via both computational and experimental methods. To systematically assess their binding affinities and specificities, for eight representative inhibitors, we utilized molecular docking, molecular dynamics simulation, and ensuing energetic analysis to compare their binding characteristics. The inhibitors' binding free energies were calculated via MMPB(GB)SA, and the STAT3 SH2 binding "hot spots" were evaluated through binding energy decomposition and hydrogen bond (H-bond) distribution analysis. Several conclusions can be drawn: (1) the overall enthalpy-entropy compensation paradigm is preserved for the STAT3 SH2/ligand binding thermodynamics; (2) at one end of the binding spectrum, two compounds bind to SH2 due to their minimum entropic penalties that result from their relative rigidities and increased dynamics of SH2 upon their binding; at the other end of the binding spectrum, one compound shows a typical weak binder behavior due to its loose binding in the SH2's strongest enthalpy-contributing binding subsite; (3) hydrogen bonding seems a strong indicator to evaluate the SH2/ligand binding potency, which echoes a finding that CH/π non-classical H-bond is responsible for some pTyr peptides binding to their corresponding SH2 domains; (4) STAT3 SH2 domain possesses three binding "hot spots": pTyr705-binding pocket with polar residues and contributing the largest binding enthalpy (two-thirds); Leu706 subsite which is the most dynamic and hardest to target; a hydrophobic side pocket which is unique to STAT3 and very targetable, which may offer unique opportunity to design STAT3-specific inhibitors, particularly with fragment-based approach.

Outcome predictors of initial treatment with topical lubricant and parafunctional habit control in burning mouth syndrome (BMS).

Burning mouth syndrome (BMS) is a common chronic pain condition which mainly affects elderly women. The concomitant prescription of topical lubricants with oral parafunctional habit control has been reported as an effective initial approach for patients with BMS. In this study, we have investigated outcome predictors of this initial treatment in patients with BMS. One hundred forty patients with BMS (12 men and 128 women, mean age 59.9±10.7 years) were instructed to avoid oral parafunctions and to use topical lubricant for 2 weeks. The patients were sub-grouped according to psychological status, salivary flow rate, presence of psychiatric medications, symptom area and duration, symptom severity, presence of oral parafunctions, and accompanying oral complaints. The changes in symptoms were analyzed and compared between sub-groups. Subjects with T-scores≤50 for each psychological symptom dimension, a flow rate of stimulated whole saliva (SWS)>0.5 ml/min, no psychiatric medications, and a greater degree of initial symptoms (VAS≥5) displayed greater decreases in symptoms compared with their counterparts. In conclusion, psychological status, psychiatric medications, flow rate SWS, and initial symptom severity can be outcome predictors of the initial treatment approach for patients with BMS.