An Ensemble-Based Protocol for the Computational Prediction of Helix-Helix Interactions in G Protein-Coupled Receptors using Coarse-Grained Molecular Dynamics

The accurate identification of the specific points of interaction between G protein-coupled receptor (GPCR) oligomers is essential for the design of receptor ligands targeting oligomeric receptor targets. A coarse-grained molecular dynamics computer simulation approach would provide a compelling means of identifying these specific protein–protein interactions and could be applied both for known oligomers of interest and as a high-throughput screen to identify novel oligomeric targets. However, to be effective, this in silico modeling must provide accurate, precise, and reproducible information. This has been achieved recently in numerous biological systems using an ensemble-based all-atom molecular dynamics approach. In this study, we describe an equivalent methodology for ensemble-based coarse-grained simulations. We report the performance of this method when applied to four different GPCRs known to oligomerize using error analysis to determine the ensemble size and individual replica simulation time required. Our measurements of distance between residues shown to be involved in oligomerization of the fifth transmembrane domain from the adenosine A2A receptor are in very good agreement with the existing biophysical data and provide information about the nature of the contact interface that cannot be determined experimentally. Calculations of distance between rhodopsin, CXCR4, and β1AR transmembrane domains reported to form contact points in homodimers correlate well with the corresponding measurements obtained from experimental structural data, providing an ability to predict contact interfaces computationally. Interestingly, error analysis enables identification of noninteracting regions. Our results confirm that GPCR interactions can be reliably predicted using this novel methodology

Demonstration of multi-channel 80 Gbit/s integrated transmitter and receiver for wavelength-division multiplexing passive optical network and fronthauling applications

The performance evaluation of a multi-channel transmitter that employs an arrayed reflective electroabsorption modulator-based photonic integrated circuit and a low-power driver array in conjunction with a multi-channel receiver incorporating a pin photodiode array and integrated arrayed waveguide grating is reported. Due to their small footprint, low power consumption and potential low cost, these devices are attractive solutions for future mobile fronthaul and next generation optical access networks. A BER performance of <10(-9) at 10.3 Gbit/s per channel is achieved over 25 km of standard single mode fibre. The transmitter/receiver combination can achieve an aggregate bit rate of 82.4 Gbit/s when eight channels are active

Hit-to-lead and lead optimization binding free energy calculations for G protein-coupled receptors

We apply the hit-to-lead ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and lead-optimization TIES (thermodynamic integration with enhanced sampling) methods to compute the binding free energies of a series of ligands at the A1 and A2A adenosine receptors, members of a subclass of the GPCR (G protein-coupled receptor) superfamily. Our predicted binding free energies, calculated using ESMACS, show a good correlation with previously reported experimental values of the ligands studied. Relative binding free energies, calculated using TIES, accurately predict experimentally determined values within a mean absolute error of approximately 1 kcal mol−1. Our methodology may be applied widely within the GPCR superfamily and to other small molecule–receptor protein systems

Validation of low-dose lung cancer PET-CT protocol and PET image improvement using machine learning

PURPOSE: To conduct a simplified lesion-detection task of a low-dose (LD) PET-CT protocol for frequent lung screening using 30% of the effective PETCT dose and to investigate the feasibility of increasing clinical value of low-statistics scans using machine learning. METHODS: We acquired 33 SD PET images, of which 13 had actual LD (ALD) PET, and simulated LD (SLD) PET images at seven different count levels from the SD PET scans. We employed image quality transfer (IQT), a machine learning algorithm that performs patch-regression to map parameters from low-quality to high-quality images. At each count level, patches extracted from 23 pairs of SD/SLD PET images were used to train three IQT models - global linear, single tree, and random forest regressions with cubic patch sizes of 3 and 5 voxels. The models were then used to estimate SD images from LD images at each count level for 10 unseen subjects. Lesion-detection task was carried out on matched lesion-present and lesion-absent images. RESULTS: LD PET-CT protocol yielded lesion detectability with sensitivity of 0.98 and specificity of 1. Random forest algorithm with cubic patch size of 5 allowed further 11.7% reduction in the effective PETCT dose without compromising lesion detectability, but underestimated SUV by 30%. CONCLUSION: LD PET-CT protocol was validated for lesion detection using ALD PET scans. Substantial image quality improvement or additional dose reduction while preserving clinical values can be achieved using machine learning methods though SUV quantification may be biased and adjustment of our research protocol is required for clinical use

A comparison of 18F-FDG PET/MR with PET/CT in pulmonary tuberculosis

PURPOSE: PET/computed tomography (CT) has been shown to detect lesions in patients with pulmonary tuberculosis (PTB) and may be useful for assessing PTB disease in clinical research studies. However, radiation dose is of concern for clinical research in individuals with an underlying curable disease. This study aimed to determine whether PET/MR is equivalent to PET/CT in PTB. MATERIALS AND METHODS: Ten patients with microbiologically confirmed PTB were recruited. Patients received 129.0±4.1 MBq of fluorine-18-fluorodeoxyglucose. Five of the 10 patients underwent a PET/MR scan, followed by PET/CT. The remaining five were first imaged on the PET/CT, followed by the PET/MRI. PET acquisition began at 66.7±14.4 min (mean±SD) after injection when performing PET/MR first (PET/CT: 117.2±5.6 min) and 92.4±7.6 min when patients were imaged on PET/MR second (PET/CT: 61.1±3.9 min). PET data were reconstructed iteratively with Ordinary-Poisson Ordered-Subset Expectation-Maximization and reconstruction parameters were matched across the two scanners. A visual lesion detection task and a standardized uptake value (SUV) analysis were carried out. The CT Hounsfield unit values of PTB lesions were also compared with MR-based attenuation correction mu-map tissue classes. RESULTS: A total of 108 PTB lesions were detected on PET/MR and 112 on PET/CT. SUV analysis was carried out on 50 of these lesions that were observed with both modalities. Mean standardized uptake value (SUVmean) and maximum standardized uptake value (SUVmax) were significantly lower on PET/MR (SUVmean: 2.6±1.4; SUVmax: 4.3±2.5) than PET/CT (SUVmean: 3.5±1.5; SUVmax: 5.3±2.4). CONCLUSION: PET/MR visual performance was shown to be comparable to PET/CT in terms of the number of PTB lesions detected. SUVs were significantly lower on PET/MR. Dixon-based attenuation correction underestimates the linear attenuation coefficient of PTB lesions, resulting in lower SUVs compared with PET/CT. However, the use of PET/MR to measure the response of lung lesions to assess response to treatment in research studies is unlikely to be affected by these differences in quantification

Atypical audiovisual speech integration in infants at risk for autism

The language difficulties often seen in individuals with autism might stem from an inability to integrate audiovisual information, a skill important for language development. We investigated whether 9-month-old siblings of older children with autism, who are at an increased risk of developing autism, are able to integrate audiovisual speech cues. We used an eye-tracker to record where infants looked when shown a screen displaying two faces of the same model, where one face is articulating/ba/and the other/ga/, with one face congruent with the syllable sound being presented simultaneously, the other face incongruent. This method was successful in showing that infants at low risk can integrate audiovisual speech: they looked for the same amount of time at the mouths in both the fusible visual/ga/− audio/ba/and the congruent visual/ba/− audio/ba/displays, indicating that the auditory and visual streams fuse into a McGurk-type of syllabic percept in the incongruent condition. It also showed that low-risk infants could perceive a mismatch between auditory and visual cues: they looked longer at the mouth in the mismatched, non-fusible visual/ba/− audio/ga/display compared with the congruent visual/ga/− audio/ga/display, demonstrating that they perceive an uncommon, and therefore interesting, speech-like percept when looking at the incongruent mouth (repeated ANOVA: displays x fusion/mismatch conditions interaction: F(1,16) = 17.153, p = 0.001). The looking behaviour of high-risk infants did not differ according to the type of display, suggesting difficulties in matching auditory and visual information (repeated ANOVA, displays x conditions interaction: F(1,25) = 0.09, p = 0.767), in contrast to low-risk infants (repeated ANOVA: displays x conditions x low/high-risk groups interaction: F(1,41) = 4.466, p = 0.041). In some cases this reduced ability might lead to the poor communication skills characteristic of autism

A pentapeptide as minimal antigenic determinant for MHC class I-restricted T lymphocytes

Peptides that are antigenic for T lymphocytes are ligands for two receptors, the class I or II glycoproteins that are encoded by genes in the major histocompatibility complex, and the idiotypic / chain T-cell antigen receptor1–9. That a peptide must bind to an MHC molecule to interact with a T-cell antigen receptor is the molecular basis of the MHC restriction of antigen-recognition by T lymphocytes10,11. In such a trimolecular interaction the amino-acid sequence of the peptide must specify the contact with both receptors: agretope residues bind to the MHC receptor and epitope residues bind to the T-cell antigen receptor12,13. From a compilation of known antigenic peptides, two algorithms have been proposed to predict antigenic sites in proteins. One algorithm uses linear motifs in the sequence14, whereas the other considers peptide conformation and predicts antigenicity for amphipathic -helices15,16. We report here that a systematic delimitation of an antigenic site precisely identifies a predicted pentapeptide motif as the minimal antigenic determinant presented by a class I MHC molecule and recognized by a cytolytic T lymphocyte clone

Engaging Undergraduates in Science Research: Not Just About Faculty Willingness.

Despite the many benefits of involving undergraduates in research and the growing number of undergraduate research programs, few scholars have investigated the factors that affect faculty members' decisions to involve undergraduates in their research projects. We investigated the individual factors and institutional contexts that predict faculty members' likelihood of engaging undergraduates in their research project(s). Using data from the Higher Education Research Institute's 2007-2008 Faculty Survey, we employ hierarchical generalized linear modeling to analyze data from 4,832 science, technology, engineering, and mathematics (STEM) faculty across 194 institutions to examine how organizational citizenship behavior theory and social exchange theory relate to mentoring students in research. Key findings show that faculty who work in the life sciences and those who receive government funding for their research are more likely to involve undergraduates in their research project(s). In addition, faculty at liberal arts or historically Black colleges are significantly more likely to involve undergraduate students in research. Implications for advancing undergraduate research opportunities are discussed

Analysis of factors influencing the ultrasonic fetal weight estimation

Objective: The aim of our study was the evaluation of sonographic fetal weight estimation taking into consideration 9 of the most important factors of influence on the precision of the estimation. Methods: We analyzed 820 singleton pregnancies from 22 to 42 weeks of gestational age. We evaluated 9 different factors that potentially influence the precision of sonographic weight estimation ( time interval between estimation and delivery, experts vs. less experienced investigator, fetal gender, gestational age, fetal weight, maternal BMI, amniotic fluid index, presentation of the fetus, location of the placenta). Finally, we compared the results of the fetal weight estimation of the fetuses with poor scanning conditions to those presenting good scanning conditions. Results: Of the 9 evaluated factors that may influence accuracy of fetal weight estimation, only a short interval between sonographic weight estimation and delivery (0-7 vs. 8-14 days) had a statistically significant impact. Conclusion: Of all known factors of influence, only a time interval of more than 7 days between estimation and delivery had a negative impact on the estimation