From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery.

PURPOSE: Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has the potential to enable this by automatically contouring the tumor and guiding resection in real time. However, evaluation of such models with respect to pathology outcomes is necessary for their successful translation into clinical practice. METHODS: Sixteen deep learning models based on established architectures in the literature are trained on 7318 ultrasound images from 33 patients. Models are ranked by an expert based on their contours generated from images in our test set. Generated contours from each model are also analyzed using recorded cautery trajectories of five navigated BCS cases to predict margin status. Predicted margins are compared with pathology reports. RESULTS: The best-performing model using both quantitative evaluation and our visual ranking framework achieved a mean Dice score of 0.959. Quantitative metrics are positively associated with expert visual rankings. However, the predictive value of generated contours was limited with a sensitivity of 0.750 and a specificity of 0.433 when tested against pathology reports. CONCLUSION: We present a clinical evaluation of deep learning models trained for intraoperative tumor segmentation in breast-conserving surgery. We demonstrate that automatic contouring is limited in predicting pathology margins despite achieving high performance on quantitative metrics.

RNA folding using quantum computers.

The 3-dimensional fold of an RNA molecule is largely determined by patterns of intramolecular hydrogen bonds between bases. Predicting the base pairing network from the sequence, also referred to as RNA secondary structure prediction or RNA folding, is a nondeterministic polynomial-time (NP)-complete computational problem. The structure of the molecule is strongly predictive of its functions and biochemical properties, and therefore the ability to accurately predict the structure is a crucial tool for biochemists. Many methods have been proposed to efficiently sample possible secondary structure patterns. Classic approaches employ dynamic programming, and recent studies have explored approaches inspired by evolutionary and machine learning algorithms. This work demonstrates leveraging quantum computing hardware to predict the secondary structure of RNA. A Hamiltonian written in the form of a Binary Quadratic Model (BQM) is derived to drive the system toward maximizing the number of consecutive base pairs while jointly maximizing the average length of the stems. A Quantum Annealer (QA) is compared to a Replica Exchange Monte Carlo (REMC) algorithm programmed with the same objective function, with the QA being shown to be highly competitive at rapidly identifying low energy solutions. The method proposed in this study was compared to three algorithms from literature and, despite its simplicity, was found to be competitive on a test set containing known structures with pseudoknots.

Lipid21: Complex Lipid Membrane Simulations with AMBER.

We extend the modular AMBER lipid force field to include anionic lipids, polyunsaturated fatty acid (PUFA) lipids, and sphingomyelin, allowing the simulation of realistic cell membrane lipid compositions, including raft-like domains. Head group torsion parameters are revised, resulting in improved agreement with NMR order parameters, and hydrocarbon chain parameters are updated, providing a better match with phase transition temperature. Extensive validation runs (0.9 µs per lipid type) show good agreement with experimental measurements. Furthermore, the simulation of raft-like bilayers demonstrates the perturbing effect of increasing PUFA concentrations on cholesterol molecules. The force field derivation is consistent with the AMBER philosophy, meaning it can be easily mixed with protein, small molecule, nucleic acid, and carbohydrate force fields.

Modeling and mutagenesis of amino acid residues critical for CO2 hydration by specialized NDH-1 complexes in cyanobacteria.

The uptake of inorganic carbon in cyanobacteria is facilitated by an energetically intensive CO2-concentrating mechanism (CCM). This includes specialized Type-1 NDH complexes that function to couple photosynthetic redox energy to CO2 hydration forming the bicarbonate that accumulates to high cytoplasmic concentrations during the operation of the CCM, required for effective carbon fixation. Here we used a Synechococcus PCC7942 expression system to investigate the role of conserved histidine and cysteine residues in the CupB (also designated, ChpX) protein, which has been hypothesized to participate in a vectoral CO2 hydration reaction near the interface between CupB protein and the proton-pumping subunits of the NDH-1 complex. A homology model has been constructed and most of the targeted conserved residues are in the vicinity of a Zn ion modeled to form the catalytic site of deprotonation and CO2 hydration. Growth and CO2 uptake assays show that the most severe defects in activity among the targeted residues are due to a substitution of the predicted Zn ligand, CupB-His86. Mutations at other sites produced intermediate effects. Proteomic analysis revealed that some amino acid substitution mutations of CupB caused the induction of bicarbonate uptake proteins to a greater extent than complete deletion of CupB, despite growth under CO2-enriched conditions. The results are discussed in terms of hypotheses on the catalytic function of this unusual enzyme.

mRNA codon optimization with quantum computers.

Reverse translation of polypeptide sequences to expressible mRNA constructs is a NP-hard combinatorial optimization problem. Each amino acid in the protein sequence can be represented by as many as six codons, and the process of selecting the combination that maximizes probability of expression is termed codon optimization. This work investigates the potential impact of leveraging quantum computing technology for codon optimization. A Quantum Annealer (QA) is compared to a standard genetic algorithm (GA) programmed with the same objective function. The QA is found to be competitive in identifying optimal solutions. The utility of gate-based systems is also evaluated using a simulator resulting in the finding that while current generations of devices lack the hardware requirements, in terms of both qubit count and connectivity, to solve realistic problems, future generation devices may be highly efficient.

Occupational radiation exposure in doctors: an analysis of exposure rates over 25 years.

OBJECTIVES: Healthcare professionals' occupational exposure to ionising radiation may be increasing due to increasing use of imaging and image-guided intervention. This study aims to assess the occupational exposure of doctors over a 25-year period at an NHS teaching hospital. METHODS: Dosemeter measurements were collected prospectively from 1995 to 2019. Two retrospective analyses were performed over time (first including all measurements, second excluding "zero-dose" measurements), and by speciality. Group comparisons were undertaken using multilevel linear regression; a p-value <0.05 was deemed significant. RESULTS: 8,892 measurements (3,983 body, 1,514 collar, 649 eye, 2,846 hand), of which 3,350 were non-zero measurements (1,541 body, 883 collar, 155 eye, 771 hand), were included. Whole dataset analysis found a significant decrease in exposure for radiologists and cardiologists, as measured by body, hand and collar dosemeters over the last 25 years (p < 0.01 for all). The non-zero readings reflect the whole cohort analysis except in the case of eye dosemeters, which showed a significant decrease in exposure for cardiologists (p < 0.01), but a significant increase for radiologists and surgeons/anaesthetists (p < 0.01 for both). CONCLUSIONS: Whilst ionising radiation remains an occupational risk for doctors, the overall decreasing trend in occupational exposure is reassuring. However, a significant rise in eye dose for radiologists, surgeons and anaesthetists is concerning, and close monitoring is required to prevent future issues. ADVANCES IN KNOWLEDGE: This paper is one of few evaluating the occupational radiation exposure to doctors over a 25-year period, showing that although most dosemeter measurements reflect decreasing exposure, the increase in eye exposure warrants caution.

Genomic characterization of three novel Desulfobacterota classes expand the metabolic and phylogenetic diversity of the phylum.

We report on the genomic characterization of three novel classes in the phylum Desulfobacterota. One class (proposed name Candidatus 'Anaeroferrophillalia') was characterized by heterotrophic growth capacity, either fermentatively or utilizing polysulfide, tetrathionate or thiosulfate as electron acceptors. In the absence of organic carbon sources, autotrophic growth via the Wood-Ljungdahl (WL) pathway and using hydrogen or Fe(II) as an electron donor is also inferred for members of the 'Anaeroferrophillalia'. The second class (proposed name Candidatus 'Anaeropigmentia') was characterized by its capacity for growth at low oxygen concentration, and the capacity to synthesize the methyl/alkyl carrier CoM, an ability that is prevalent in the archaeal but rare in the bacterial domain. Pigmentation is inferred from the capacity for carotenoid (lycopene) production. The third class (proposed name Candidatus 'Zymogenia') was characterized by fermentative heterotrophic growth capacity, broad substrate range and the adaptation of some of its members to hypersaline habitats. Analysis of the distribution pattern of all three classes showed their occurrence as rare community members in multiple habitats, with preferences for anaerobic terrestrial, freshwater and marine environments over oxygenated (e.g. pelagic ocean and agricultural land) settings. Special preference for some members of the class Candidatus 'Zymogenia' for hypersaline environments such as hypersaline microbial mats and lagoons was observed.

A systems approach for institutional CBME adoption at Queen's University.

The Royal College of Physicians and Surgeons of Canada (RCPSC) has begun the transition to Competency by Design (CBD), a new curricular model for residency education that 'ensure[s] competence, but teaches for excellence'. By 2022, all Canadian specialty programs are anticipated to have completed the CBD cohort process which includes workshops facilitated by a Royal College Clinician Educator. Queen's University in Ontario, Canada, was granted approval by the RCPSC to embark upon an accelerated path to competency-based medical education (CBME) for all our postgraduate specialties. This accelerated path allowed us to take an institutional approach for CBME implementation and ensure that all specialities were part of a system-wide change. Our unique institution-wide approach to CBD is the first of its kind across Canada. From both a theoretical and practical perspective we undertook CBME using a systems approach that allowed us to build the foundations for CBME, implement the change, and plan for sustainability. This has created opportunities to bridge and connect the various programs involved in the implementation of CBME on Queen's campus. The systems approach was an essential part of our strategy to develop a community dedicated to ensuring a successful CBME implementation.

Bergamot Polyphenols Improve Dyslipidemia and Pathophysiological Features in a Mouse Model of Non-Alcoholic Fatty Liver Disease.

There is a need for continued drug development for nonalcoholic steatohepatitis (NASH). Bergamot is a plant whose fruit juice is enriched with flavonoids and phenolic compounds which improves dyslipidemia and markers of systemic inflammation in patients with Metabolic Syndrome. The aim of this study was to perform a preclinical "proof of concept" study of Bergamot polyphenolic formulation (BPF99) for the treatment of NASH. A disease reversal study was performed in the diet-induced animal model of NAFLD (DIAMOND). Groups of 8 weeks old mice were randomly assigned to receive chow diet, high fat diet with sugar in drinking water (Western diet- WD). Mice on WD were further randomized to continue on WD gavaged with vehicle or continue on WD with additional gavage of BPF99 (50 mg/kg) after 16 weeks of diet. Mice were euthanized after 11 additional weeks. The primary endpoint was resolution of NASH. Secondary endpoints included changes in individual histological features, body weight, liver enzymes, dyslipidemia, markers of oxidative stress and molecular markers of disease activity and fibrosis. The results showed that BPF99 reduced ALT (mean 71.6 vs 44.6 IU/l, p < 0.01), triglycerides (38.8 vs 28.1 mg/dl, p < 0.05), LDL-C (39.2 vs 23.7 mg/dl, p < 0.001). It significantly improved NASH resolution (p < 0.001) and the SAF scores (p < 0.05) while the NAS improvement approached significance. BPF99 reduced markers of oxidative stress, along with reduced JNK and p38 MAP kinase activity. BPF99 did not reduce the number of mice with fibrosis but improved collagen proportional area (p < 0.04) and procollagen I and III expression. Collectively our results showed that BPF99 resolves NASH and ameliorates key histological and pathophysiological features of NASH along with improvement in ALT and dyslipidemia in the DIAMOND mice.

Real-time electromagnetic navigation for breast-conserving surgery using NaviKnife technology: A matched case-control study.

Breast-conserving surgery (BCS) is a mainstay in breast cancer treatment. For nonpalpable breast cancers, current strategies have limited accuracy, contributing to high positive margin rates. We developed NaviKnife, a surgical navigation system based on real-time electromagnetic (EM) tracking. The goal of this study was to confirm the feasibility of intraoperative EM navigation in patients with nonpalpable breast cancer and to assess the potential value of surgical navigation. We recruited 40 patients with ultrasound visible, single, nonpalpable lesions, undergoing BCS. Feasibility was assessed by equipment functionality and sterility, acceptable duration of the operation, and surgeon feedback. Secondary outcomes included specimen volume, positive margin rate, and reoperation outcomes. Study patients were compared to a control group by a matched case-control analysis. There was no equipment failure or breach of sterility. The median operative time was 66 (44-119) minutes with NaviKnife vs 65 (34-158) minutes for the control (P = .64). NaviKnife contouring time was 3.2 (1.6-9) minutes. Surgeons rated navigation as easy to setup, easy to use, and useful in guiding nonpalpable tumor excision. The mean specimen volume was 95.4 ± 73.5 cm3 with NaviKnife and 140.7 ± 100.3 cm3 for the control (P = .01). The positive margin rate was 22.5% with NaviKnife and 28.7% for the control (P = .52). The re-excision specimen contained residual disease in 14.3% for NaviKnife and 50% for the control (P = .28). Our results demonstrate that real-time EM navigation is feasible in the operating room for BCS. Excisions performed with navigation result in the removal of less breast tissue without compromising postive margin rates.

X-ray Crystallographic and Molecular Dynamic Analyses of Drosophila melanogaster Embryonic Muscle Myosin Define Domains Responsible for Isoform-Specific Properties.

Drosophila melanogaster is a powerful system for characterizing alternative myosin isoforms and modeling muscle diseases, but high-resolution structures of fruit fly contractile proteins have not been determined. Here we report the first x-ray crystal structure of an insect myosin: the D melanogaster skeletal muscle myosin II embryonic isoform (EMB). Using our system for recombinant expression of myosin heavy chain (MHC) proteins in whole transgenic flies, we prepared and crystallized stable proteolytic S1-like fragments containing the entire EMB motor domain bound to an essential light chain. We solved the x-ray crystal structure by molecular replacement and refined the resulting model against diffraction data to 2.2 Å resolution. The protein is captured in two slightly different renditions of the rigor-like conformation with a citrate of crystallization at the nucleotide binding site and exhibits structural features common to myosins of diverse classes from all kingdoms of life. All atom molecular dynamics simulations on EMB in its nucleotide-free state and a derivative homology model containing 61 amino acid substitutions unique to the indirect flight muscle isoform (IFI) suggest that differences in the identity of residues within the relay and the converter that are encoded for by MHC alternative exons 9 and 11, respectively, directly contribute to increased mobility of these regions in IFI relative to EMB. This suggests the possibility that alternative folding or conformational stability within these regions contribute to the observed functional differences in Drosophila EMB and IFI myosins.

Verification of a Rapidly Multiplexed Circuit for Scalable Action Potential Recording.

This report presents characterizations of in vivo neural recordings performed with a CMOS multichannel neural recording chip that uses rapid multiplexing directly at the electrodes, without any pre-amplification or buffering. Neural recordings were taken from a 16-channel microwire array implanted in rodent cortex, with comparison to a gold-standard commercial bench-top recording system. We were able to record well-isolated threshold crossings from 10 multiplexed electrodes and typical local field potential waveforms from 16, with strong agreement with the standard system (average SNR = 2.59 and 3.07 respectively). For 10 electrodes, the circuit achieves an effective area per channel of 0.0077 mm2, which is >5x smaller than typical multichannel chips. Extensive characterizations of noise and signal quality are presented and compared to fundamental theory, as well as results from in vivo and in vitro experiments. By demonstrating the validation of rapid multiplexing directly at the electrodes, this report confirms it as a promising approach for reducing circuit area in massively-multichannel neural recording systems, which is crucial for scaling recording site density and achieving large-scale sensing of brain activity with high spatiotemporal resolution.

Delivering on the promise of competency based medical education - an institutional approach.

The Royal College of Physicians and Surgeons of Canada (RCPSC) adopted a plan to transform, over a seven-year horizon (2014-2021), residency education across all specialties to competency-based medical education (CBME) curriculum models. The RCPSC plan recommended implementing a more responsive and accountable training model with four discrete stages of training, explicit, specialty specific entrustable professional activities, with associated milestones, and a programmatic approach to assessment across residency education. Embracing this vision, the leadership at Queen's University (in Kingston, Ontario, Canada) applied for and was granted special permission by the RCPSC to embark on an accelerated institutional path. Over a three-year period, Queen's took CBME from concept to reality through the development and implementation of a comprehensive strategic plan. This perspective paper describes Queen's University's approach of creating a shared institutional vision, outlines the process of developing a centralized CBME executive team and twenty-nine CBME program teams, and summarizes proactive measures to ensure program readiness for launch. In so doing, Queen's created a community of support and CBME expertise that reinforces shared values including fostering co-production, cultivating responsive leadership, emphasizing diffusion of innovation, and adopting a systems-based approach to transformative change.

Simulating Water Exchange to Buried Binding Sites.

Traditional molecular dynamics (MD) simulations of proteins, which relies on integration of Newton's equations of motion, cannot efficiently equilibrate water occupancy for buried cavities in proteins. This leads to slow convergence of thermodynamic averages for such systems. We have addressed this challenge by efficiently integrating standard Metropolis Monte Carlo (MC) translational water moves with MD in the AMBER simulation package. The translational moves allow water to easily enter or exit buried sites in a thermodynamically correct way during a simulation. To maximize efficiency, the algorithm avoids moves that only interchange waters within the bulk around the protein instead focusing on moves that can transfer water between bulk and the protein interior. In addition, a steric grid allows avoidance of moves that would lead to obvious steric clashes, and a fast grid-based energy evaluation is used to reduce the number of expensive full energy calculations. The potential energy distribution produced using MC/MD was found to be statistically indistinguishable from that of control simulations using only MD, and the algorithm effectively equilibrated water across steric barriers and into binding pockets that are not accessible with pure MD. The MC/MD method introduced here should be of increasing utility for applications spanning protein folding, the elucidation of protein mechanisms, and free energy calculations for computer-aided drug design. It is available in version 18 release of the widely disseminated AMBER simulation package.

pH-dependent conformational dynamics of beta-secretase 1: A molecular dynamics study.

Beta-secretase 1 (BACE-1) is an aspartyl protease implicated in the overproduction of ß-amyloid fibrils responsible for Alzheimer disease. The process of ß-amyloid genesis is known to be pH dependent, with an activity peak between solution pH of 3.5 and 5.5. We have studied the pH-dependent dynamics of BACE-1 to better understand the pH dependent mechanism. We have implemented support for graphics processor unit (GPU) accelerated constant pH molecular dynamics within the AMBER molecular dynamics software package and employed this to determine the relative population of different aspartyl dyad protonation states in the pH range of greatest ß-amyloid production, followed by conventional molecular dynamics to explore the differences among the various aspartyl dyad protonation states. We observed a difference in dynamics between double-protonated, mono-protonated, and double-deprotonated states over the known pH range of higher activity. These differences include Tyr 71-aspartyl dyad proximity and active water lifetime. This work indicates that Tyr 71 stabilizes catalytic water in the aspartyl dyad active site, enabling BACE-1 activity.

Acquisition of Neural Action Potentials Using Rapid Multiplexing Directly at the Electrodes.

Neural recording systems that interface with implanted microelectrodes are used extensively in experimental neuroscience and neural engineering research. Interface electronics that are needed to amplify, filter, and digitize signals from multichannel electrode arrays are a critical bottleneck to scaling such systems. This paper presents the design and testing of an electronic architecture for intracortical neural recording that drastically reduces the size per channel by rapidly multiplexing many electrodes to a single circuit. The architecture utilizes mixed-signal feedback to cancel electrode offsets, windowed integration sampling to reduce aliased high-frequency noise, and a successive approximation analog-to-digital converter with small capacitance and asynchronous control. Results are presented from a 180 nm CMOS integrated circuit prototype verified using in vivo experiments with a tungsten microwire array implanted in rodent cortex. The integrated circuit prototype achieves <0.004 mm² area per channel, 7 µW power dissipation per channel, 5.6 µVrms input referred noise, 50 dB common mode rejection ratio, and generates 9-bit samples at 30 kHz per channel by multiplexing at 600 kHz. General considerations are discussed for rapid time domain multiplexing of high-impedance microelectrodes. Overall, this work describes a promising path forward for scaling neural recording systems to numbers of electrodes that are orders of magnitude larger.

GPU-Accelerated Molecular Dynamics and Free Energy Methods in Amber18: Performance Enhancements and New Features.

We report progress in graphics processing unit (GPU)-accelerated molecular dynamics and free energy methods in Amber18. Of particular interest is the development of alchemical free energy algorithms, including free energy perturbation and thermodynamic integration methods with support for nonlinear soft-core potential and parameter interpolation transformation pathways. These methods can be used in conjunction with enhanced sampling techniques such as replica exchange, constant-pH molecular dynamics, and new 12-6-4 potentials for metal ions. Additional performance enhancements have been made that enable appreciable speed-up on GPUs relative to the previous software release.

Fast and flexible gpu accelerated binding free energy calculations within the amber molecular dynamics package.

Alchemical free energy (AFE) calculations based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD-based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER. © 2018 Wiley Periodicals, Inc.

Ligand Binding Pathways and Conformational Transitions of the HIV Protease.

It is important to determine the binding pathways and mechanisms of ligand molecules to target proteins to effectively design therapeutic drugs. Molecular dynamics (MD) is a promising computational tool that allows us to simulate protein-drug binding at an atomistic level. However, the gap between the time scales of current simulations and those of many drug binding processes has limited the usage of conventional MD, which has been reflected in studies of the HIV protease. Here, we have applied a robust enhanced simulation method, Gaussian accelerated molecular dynamics (GaMD), to sample binding pathways of the XK263 ligand and associated protein conformational changes in the HIV protease. During two of 10 independent GaMD simulations performed over 500-2500 ns, the ligand was observed to successfully bind to the protein active site. Although GaMD-derived free energy profiles were not fully converged because of insufficient sampling of the complex system, the simulations still allowed us to identify relatively low-energy intermediate conformational states during binding of the ligand to the HIV protease. Relative to the X-ray crystal structure, the XK263 ligand reached a minimum root-mean-square deviation (RMSD) of 2.26 Å during 2.5 µs of GaMD simulation. In comparison, the ligand RMSD reached a minimum of only ∼5.73 Å during an earlier 14 µs conventional MD simulation. This work highlights the enhanced sampling power of the GaMD approach and demonstrates its wide applicability to studies of drug-receptor interactions for the HIV protease and by extension many other target proteins.