Microcomputed tomography void analysis after cement cleanup methods.

STATEMENT OF PROBLEM: Cement at the restorative margin after implementation of the manufacturer's recommended procedure for cement cleanup has not been extensively evaluated. PURPOSE: The purpose of this in vitro study was to use microcomputed tomography (µCT) to evaluate the number, volume, and width of voids left at the margin when dental cement is cleaned during the cementation process as per 2 manufacturer-prescribed methods for cement cleanup by evaluating a self-adhesive resin cement and a resin-modified glass ionomer cement. MATERIAL AND METHODS: Twenty molar Ivorine Typodont prepared teeth were scanned, and lithium disilicate crowns were milled and cemented to the prepared teeth as per the manufacturer-recommended cementation process. Two methods of cement cleanup were performed: the excess cement was tack-polymerized with a polymerization light, or a delay of 3 minutes was used for the excess cement to reach partial polymerization, and the excess cement was removed with a sharp sickle scaler. These 2 methods of cement cleanup were performed with 2 cements: a resin-modified glass ionomer cement and a self-adhesive resin. Each specimen was then scanned with a µCT machine. The buccal margin of each specimen, from mesiobuccal line angle to distobuccal line angle, was examined, and the number, volume, and width of any voids remaining at the margin open to the environment were measured. For statistical analysis, the specimens were first grouped by method of cement cleanup and then grouped by cement type. The Wilcoxon ranked sum test was implemented because of the lack of a normal distribution and the heterogeneity of the data (α=.05). RESULTS: No statistically significant difference was found in the median number of voids, median volume of voids, or median width per void between the 2 cleanup methods, irrespective of cement type (P>.05). Significant differences were found in the median number of voids, median volume of voids, and median width per void when comparing cement types, irrespective of cement cleanup methods (P<.05). CONCLUSIONS: The choice of cement may be more important than the method of cement cleanup when considering voids left at the margin. Microcomputed tomography is an excellent nondestructive tool for volumetric measurements of voids at the margin.

Effect of Chain Length Dispersity on the Mobility of Entangled Polymers.

While nearly all theoretical and computational studies of entangled polymer melts have focused on uniform samples, polymer synthesis routes always result in some dispersity, albeit narrow, of distribution of molecular weights (D_{M}=M_{w}/M_{n}∼1.02-1.04). Here, the effects of dispersity on chain mobility are studied for entangled, disperse melts using a coarse-grained model for polyethylene. Polymer melts with chain lengths set to follow a Schulz-Zimm distribution for the same average M_{w}=36 kg/mol with D_{M}=1.0 to 1.16, were studied for times of 600-800 µs using molecular dynamics simulations. This time frame is longer than the time required to reach the diffusive regime. We find that dispersity in this range does not affect the entanglement time or tube diameter. However, while there is negligible difference in the average mobility of chains for the uniform distribution D_{M}=1.0 and D_{M}=1.02, the shortest chains move significantly faster than the longest ones offering a constraint release pathway for the melts for larger D_{M}.

A multi-chain polymer slip-spring model with fluctuating number of entanglements: Density fluctuations, confinement, and phase separation.

Coarse grained simulation approaches provide powerful tools for the prediction of the equilibrium properties of polymeric systems. Recent efforts have sought to develop coarse-graining strategies capable of predicting the non-equilibrium behavior of entangled polymeric materials. Slip-link and slip-spring models, in particular, have been shown to be capable of reproducing several key aspects of the linear response and rheology of polymer melts. In this work, we extend a previously proposed multi-chain slip-spring model in a way that correctly incorporates the effects of the fluctuating environment in which polymer segments are immersed. The model is used to obtain the equation of state associated with the slip-springs, and the results are compared to those of related numerical approaches and an approximate analytical expression. The model is also used to examine a polymer melt confined into a thin film, where an inhomogeneous distribution of polymer segments is observed, and the corresponding inhomogeneities associated with density fluctuations are reflected on the spatial slip-spring distribution.

Missing teeth and pediatric obstructive sleep apnea.

BACKGROUND: Missing teeth in early childhood can result in abnormal facial morphology with narrow upper airway. The potential association between dental agenesis or early dental extractions and the presence of obstructive sleep apnea (OSA) was investigated. METHODS: We reviewed clinical data, results of polysomnographic sleep studies, and orthodontic imaging studies of children with dental agenesis (n = 32) or early extraction of permanent teeth (n = 11) seen during the past 5 years and compared their findings to those of age-, gender-, and body mass index-matched children with normal teeth development but tonsilloadenoid (T&A) hypertrophy and symptoms of OSA (n = 64). RESULTS: The 31 children with dental agenesis and 11 children with early dental extractions had at least 2 permanent teeth missing. All children with missing teeth (n = 43) had clinical complaints and signs evoking OSA. There was a significant difference in mean apnea-hypopnea indices (AHI) in the three dental agenesis, dental extraction, and T&A studied groups (p < 0.001), with mean abnormal AHI lowest in the pediatric dental agenesis group. In the children with missing teeth (n = 43), aging was associated with the presence of a higher AHI (R (2) = 0.71, p < 0.0001). CONCLUSION: Alveolar bone growth is dependent on the presence of the teeth that it supports. The dental agenesis in the studied children was not part of a syndrome and was an isolated finding. Our children with permanent teeth missing due to congenital agenesis or permanent teeth extraction had a smaller oral cavity, known to predispose to the collapse of the upper airway during sleep, and presented with OSA recognized at a later age. Due to the low-grade initial symptomatology, sleep-disordered breathing may be left untreated for a prolonged period with progressive worsening of symptoms over time.

A multichain polymer slip-spring model with fluctuating number of entanglements for linear and nonlinear rheology.

A theoretically informed entangled polymer simulation approach is presented for description of the linear and non-linear rheology of entangled polymer melts. The approach relies on a many-chain representation and introduces the topological effects that arise from the non-crossability of molecules through effective fluctuating interactions, mediated by slip-springs, between neighboring pairs of macromolecules. The total number of slip-springs is not preserved but, instead, it is controlled through a chemical potential that determines the average molecular weight between entanglements. The behavior of the model is discussed in the context of a recent theory for description of homogeneous materials, and its relevance is established by comparing its predictions to experimental linear and non-linear rheology data for a series of well-characterized linear polyisoprene melts. The results are shown to be in quantitative agreement with experiment and suggest that the proposed formalism may also be used to describe the dynamics of inhomogeneous systems, such as composites and copolymers. Importantly, the fundamental connection made here between our many-chain model and the well-established, thermodynamically consistent single-chain mean-field models provides a path to systematic coarse-graining for prediction of polymer rheology in structurally homogeneous and heterogeneous materials.

Identifying viral integration sites using SeqMap 2.0.

UNLABELLED: Retroviral integration has been implicated in several biomedical applications, including identification of cancer-associated genes and malignant transformation in gene therapy clinical trials. We introduce an efficient and scalable method for fast identification of viral vector integration sites from long read high-throughput sequencing. Individual sequence reads are masked to remove non-genomic sequence, aligned to the host genome and assembled into contiguous fragments used to pinpoint the position of integration. AVAILABILITY AND IMPLEMENTATION: The method is implemented in a publicly accessible web server platform, SeqMap 2.0, containing analysis tools and both private and shared lab workspaces that facilitate collaboration among researchers. Available at http://seqmap.compbio.iupui.edu/.

Fully atomistic simulations of the response of silica nanoparticle coatings to alkane solvents.

Molecular dynamics simulations are used to study the effect of passivating ligands of varying lengths grafted to a nanoparticle and placed in various alkane solvents. Average height and density profiles for methyl-terminated alkoxylsilane ligands (-O-Si(OH)(2)(CH(2))(n)CH(3), with n = 9, 17, and 35) attached to a 5-nm-diameter amorphous silica nanoparticle with coverages of between 1.0 and 3.0 chains/nm(2) are presented for explicitly modeled, short-chain hydrocarbon solvents and for implicit good and poor solvents. Three linear solvents, C(10)H(22) (decane), C(24)H(50), and C(48)H(96), and a branched solvent, squalene, were studied. An implicit poor solvent captured the effect of the longest chain length solvent at lower temperatures, while its temperature dependence was similar to that of the branched solvent squalene. In contrast, an implicit good solvent produced coating structures that were far more extended than those found in any of the explicit solvents tested and showed little dependence on temperature. Coatings equilibrated in explicit solvents were more compact in longer-chain solvents because of autophobic dewetting. Changes in the coating density profiles were more pronounced as the solvent chain length was increased from decane to C(24)H(50) than from C(24)H(50) to C(48)H(98) for all coatings. The response of coatings in squalene was not significantly different from that of the linear chain of equal mass. Significant interpenetration of the solvent chains with the brush coating was observed only for the shortest grafted chains in decane. In all cases, the methyl terminal group was not confined to the coating edge but was found throughout the entire coating volume, from the core to the outermost shell. Increasing the temperature from 300 to 500 K led to greater average brush heights, but the dependence was weak.

Toward Bottom-Up Understanding of Transport in Concentrated Battery Electrolytes.

Bottom-up understanding of transport describes how molecular changes alter species concentrations and electrolyte voltage drops in operating batteries. Such an understanding is essential to predictively design electrolytes for desired transport behavior. We herein advocate building a structure-property-performance relationship as a systematic approach to accurate bottom-up understanding. To ensure generalization across salt concentrations as well as different electrolyte types and cell configurations, the property-performance relation must be described using Newman's concentrated solution theory. It uses Stefan-Maxwell diffusivity, ij , to describe the role of molecular motions at the continuum scale. The key challenge is to connect ij to the structure. We discuss existing methods for making such a connection, their peculiarities, and future directions to advance our understanding of electrolyte transport.

Pushing and Pulling: A Dual pH Trigger Controlled by Varying the Alkyl Tail Length in Heme Coordinating Peptide Amphiphiles.

Some organisms in nature that undergo anaerobic respiration utilize 1D nanoscale arrays of densely packed cytochromes containing the molecule heme. The assemblies can be mimicked with 1D nanoscale fibrils composed of peptide amphiphiles designed to coordinate heme in dense arrays. To create such materials and assemblies, it is critical to understand the assembly process and what controls the various aspects of hierarchical assembly. MD simulations suggest that shorter alkyl chains on the peptide lead to more dynamic structures than the peptides with longer chains that yield kinetically trapped states. The hydration parameters manifest themselves experimentally through the observation of a dual pH trigger, which controls the peptide assembly rate, the heme binding affinity, and heme organization kinetics. Great strides in understanding the relative complexity of the self-assembly process in relation to incorporating a functional moiety like heme opens up many possibilities in developing abiotic assemblies for bioelectronic devices and assemblies.

In silico functional profiling of human disease-associated and polymorphic amino acid substitutions.

An important challenge in translational bioinformatics is to understand how genetic variation gives rise to molecular changes at the protein level that can precipitate both monogenic and complex disease. To this end, we compiled datasets of human disease-associated amino acid substitutions (AAS) in the contexts of inherited monogenic disease, complex disease, functional polymorphisms with no known disease association, and somatic mutations in cancer, and compared them with respect to predicted functional sites in proteins. Using the sequence homology-based tool SIFT to estimate the proportion of deleterious AAS in each dataset, only complex disease AAS were found to be indistinguishable from neutral polymorphic AAS. Investigation of monogenic disease AAS predicted to be nondeleterious by SIFT were characterized by a significant enrichment for inherited AAS within solvent accessible residues, regions of intrinsic protein disorder, and an association with the loss or gain of various posttranslational modifications. Sites of structural and/or functional interest were therefore surmised to constitute useful additional features with which to identify the molecular disruptions caused by deleterious AAS. A range of bioinformatic tools, designed to predict structural and functional sites in protein sequences, were then employed to demonstrate that intrinsic biases exist in terms of the distribution of different types of human AAS with respect to specific structural, functional and pathological features. Our Web tool, designed to potentiate the functional profiling of novel AAS, has been made available at http://profile.mutdb.org/.

Free energy calculations of the functional selectivity of 5-HT2B G protein-coupled receptor.

G Protein-Coupled Receptors (GPCRs) mediate intracellular signaling in response to extracellular ligand binding and are the target of one-third of approved drugs. Ligand binding modulates the GPCR molecular free energy landscape by preferentially stabilizing active or inactive conformations that dictate intracellular protein recruitment and downstream signaling. We perform enhanced sampling molecular dynamics simulations to recover the free energy surfaces of a thermostable mutant of the GPCR serotonin receptor 5-HT2B in the unliganded form and bound to a lysergic acid diethylamide (LSD) agonist and lisuride antagonist. LSD binding imparts a ∼110 kJ/mol driving force for conformational rearrangement into an active state. The lisuride-bound form is structurally similar to the apo form and only ∼24 kJ/mol more stable. This work quantifies ligand-induced conformational specificity and functional selectivity of 5-HT2B and presents a platform for high-throughput virtual screening of ligands and rational engineering of the ligand-bound molecular free energy landscape.

What is the role of sleep in physician burnout?

None: The occurrence of physician burnout is widespread among clinicians and academic faculty, who report indicators such as low quality of life and poor work-life balance. Chronic insufficient sleep, whether due to extended work hours, circadian misalignment, or unrecognized sleep disorders, is a critically important risk factor for burnout that is overlooked and under-studied, and interventions to promote healthy sleep may reduce burnout susceptibility among attending physicians. While strategies to reduce burnout among resident and attending physicians have been under-evaluated, evidence suggests a need to address burnout at both individual and organizational levels. Solutions have been offered that are applicable to many stakeholders, including employers; payers; licensing and certification boards; state and federal regulatory agencies; and physicians and researchers. As more studies are undertaken to evaluate how these approaches impact burnout, two questions need to be addressed: (1) What is the role of sleep in the crisis of burnout, specifically among attendings, who are particularly under-studied? (2) Is restoration of healthy sleep the fundamental mechanism by which burnout interventions work? It is essential for key stakeholders to consider the role of sleep, sleepiness, and sleep disorders in order to optimize any efforts to mitigate the present crisis in physician burnout, particularly among attending physicians, an understudied group.

Sleep, fatigue and burnout among physicians: an American Academy of Sleep Medicine position statement.

None: Physician burnout is a serious and growing threat to the medical profession and may undermine efforts to maintain a sufficient physician workforce to care for the growing and aging patient population in the United States. Burnout involves a host of complex underlying associations and potential for risk. While prevalence is unknown, recent estimates of physician burnout are quite high, approaching 50% or more, with midcareer physicians at highest risk. Sleep deprivation due to shift-work schedules, high workload, long hours, sleep interruptions, and insufficient recovery sleep have been implicated in the genesis and perpetuation of burnout. Maladaptive attitudes regarding sleep and endurance also may increase the risk for sleep deprivation among attending physicians. While duty-hour restrictions have been instituted to protect sleep opportunity among trainees, virtually no such effort has been made for attending physicians who have completed their training or practicing physicians in nonacademic settings. It is the position of the American Academy of Sleep Medicine that a critical need exists to evaluate the roles of sleep disruption, sleep deprivation, and circadian misalignment in physician well-being and burnout. Such evaluation may pave the way for the development of effective countermeasures that promote healthy sleep, with the goal of reducing burnout and its negative impacts such as a shrinking physician workforce, poor physician health and functional outcomes, lower quality of care, and compromised patient safety.

An integrated approach to inferring gene-disease associations in humans.

UNLABELLED: One of the most important tasks of modern bioinformatics is the development of computational tools that can be used to understand and treat human disease. To date, a variety of methods have been explored and algorithms for candidate gene prioritization are gaining in their usefulness. Here, we propose an algorithm for detecting gene-disease associations based on the human protein-protein interaction network, known gene-disease associations, protein sequence, and protein functional information at the molecular level. Our method, PhenoPred, is supervised: first, we mapped each gene/protein onto the spaces of disease and functional terms based on distance to all annotated proteins in the protein interaction network. We also encoded sequence, function, physicochemical, and predicted structural properties, such as secondary structure and flexibility. We then trained support vector machines to detect gene-disease associations for a number of terms in Disease Ontology and provided evidence that, despite the noise/incompleteness of experimental data and unfinished ontology of diseases, identification of candidate genes can be successful even when a large number of candidate disease terms are predicted on simultaneously. AVAILABILITY: www.phenopred.org.

Evaluation of features for catalytic residue prediction in novel folds.

Structural genomics projects are determining the three-dimensional structure of proteins without full characterization of their function. A critical part of the annotation process involves appropriate knowledge representation and prediction of functionally important residue environments. We have developed a method to extract features from sequence, sequence alignments, three-dimensional structure, and structural environment conservation, and used support vector machines to annotate homologous and nonhomologous residue positions based on a specific training set of residue functions. In order to evaluate this pipeline for automated protein annotation, we applied it to the challenging problem of prediction of catalytic residues in enzymes. We also ranked the features based on their ability to discriminate catalytic from noncatalytic residues. When applying our method to a well-annotated set of protein structures, we found that top-ranked features were a measure of sequence conservation, a measure of structural conservation, a degree of uniqueness of a residue's structural environment, solvent accessibility, and residue hydrophobicity. We also found that features based on structural conservation were complementary to those based on sequence conservation and that they were capable of increasing predictor performance. Using a family nonredundant version of the ASTRAL 40 v1.65 data set, we estimated that the true catalytic residues were correctly predicted in 57.0% of the cases, with a precision of 18.5%. When testing on proteins containing novel folds not used in training, the best features were highly correlated with the training on families, thus validating the approach to nonhomologous catalytic residue prediction in general. We then applied the method to 2781 coordinate files from the structural genomics target pipeline and identified both highly ranked and highly clustered groups of predicted catalytic residues.

Polymers at Liquid/Vapor Interface.

Polymers confined to the liquid/vapor interface are studied using molecular dynamics simulations. We show that for polymers which are weakly immiscible with the solvent, the density profile perpendicular to the liquid/vapor interface is strongly asymmetric. On the vapor side of the interface, the density distribution falls off as a Gaussian with a decay length on the order of the bead diameter, whereas on the liquid side, the density profile decays as a simple exponential. This result differs from that of a polymer absorbed from a good solvent with the density profile decaying as a power law. As the surface coverage increases, the average end-to-end distance and chain mobility systematically decreases toward that of the homopolymer melt.

Coarse-Grained Modeling of Polyethylene Melts: Effect on Dynamics.

The distinctive viscoelastic behavior of polymers results from a coupled interplay of motion on multiple length and time scales. Capturing the broad time and length scales of polymer motion remains a challenge. Using polyethylene (PE) as a model macromolecule, we construct coarse-grained (CG) models of PE with three to six methyl groups per CG bead and probe two critical aspects of the technique: pressure corrections required after iterative Boltzmann inversion (IBI) to generate CG potentials that match the pressure of reference fully atomistic melt simulations and the transferability of CG potentials across temperatures. While IBI produces nonbonded pair potentials that give excellent agreement between the atomistic and CG pair correlation functions, the resulting pressure for the CG models is large compared with the pressure of the atomistic system. We find that correcting the potential to match the reference pressure leads to nonbonded interactions with much deeper minima and slightly smaller effective bead diameter. However, simulations with potentials generated by IBI and pressure-corrected IBI result in similar mean-square displacements (MSDs) and stress autocorrelation functions G(t) for PE melts. While the time rescaling factor required to match CG and atomistic models is the same for pressure- and non-pressure-corrected CG models, it strongly depends on temperature. Transferability was investigated by comparing the MSDs and stress autocorrelation functions for potentials developed at different temperatures.

Identification of similar regions of protein structures using integrated sequence and structure analysis tools.

BACKGROUND: Understanding protein function from its structure is a challenging problem. Sequence based approaches for finding homology have broad use for annotation of both structure and function. 3D structural information of protein domains and their interactions provide a complementary view to structure function relationships to sequence information. We have developed a web site http://www.sblest.org/ and an API of web services that enables users to submit protein structures and identify statistically significant neighbors and the underlying structural environments that make that match using a suite of sequence and structure analysis tools. To do this, we have integrated S-BLEST, PSI-BLAST and HMMer based superfamily predictions to give a unique integrated view to prediction of SCOP superfamilies, EC number, and GO term, as well as identification of the protein structural environments that are associated with that prediction. Additionally, we have extended UCSF Chimera and PyMOL to support our web services, so that users can characterize their own proteins of interest. RESULTS: Users are able to submit their own queries or use a structure already in the PDB. Currently the databases that a user can query include the popular structural datasets ASTRAL 40 v1.69, ASTRAL 95 v1.69, CLUSTER50, CLUSTER70 and CLUSTER90 and PDBSELECT25. The results can be downloaded directly from the site and include function prediction, analysis of the most conserved environments and automated annotation of query proteins. These results reflect both the hits found with PSI-BLAST, HMMer and with S-BLEST. We have evaluated how well annotation transfer can be performed on SCOP ID's, Gene Ontology (GO) ID's and EC Numbers. The method is very efficient and totally automated, generally taking around fifteen minutes for a 400 residue protein. CONCLUSION: With structural genomics initiatives determining structures with little, if any, functional characterization, development of protein structure and function analysis tools are a necessary endeavor. We have developed a useful application towards a solution to this problem using common structural and sequence based analysis tools. These approaches are able to find statistically significant environments in a database of protein structure, and the method is able to quantify how closely associated each environment is to a predicted functional annotation.

Individual differences in the consideration of future consequences scale correlate with sleep habits, sleep quality, and GPA in university students.

The present study examined relationships between individual differences in the consideration of future consequences, sleep habits and sleep quality, and academic achievement in a sample of 231 undergraduates, 156 women and 75 men, whose ages ranged from 18 to 41 years (M = 19.0 yr., SD=2.82). Individuals were recruited from two introductory courses and two upper-division courses, one each in the fields of biology and psychology. An 8-page questionnaire was administered to assess variables relating to personality, sleep habits and quality, and grade point average (GPA). Each volunteer was given extra credit in their respective courses for participation. Higher scores on the Consideration of Future Consequences scale were associated with self-reported measures of more regular sleep schedules, greater satisfaction with sleep, a reduced likelihood of oversleeping, and higher grade point averages. Moreover, oversleeping was significantly correlated with both scale scores and GPA.