External validation of an artificial intelligence solution for the detection of elbow fractures and joint effusions in children.

PURPOSE: The purpose of this study was to conduct an external validation of an artificial intelligence (AI) solution for the detection of elbow fractures and joint effusions using radiographs from a real-life cohort of children. MATERIALS AND METHODS: This single-center retrospective study was conducted on 758 radiographic sets (1637 images) obtained from consecutive emergency room visits of 712 children (mean age, 7.27 ± 3.97 [standard deviation] years; age range, 7 months and 10 days to 15 years and 10 months), referred for a trauma of the elbow. For each set, fracture and/or effusion detection by eleven senior radiologists (reference standard) and AI solution was recorded. Diagnostic performance of the AI solution was measured via four different approaches: fracture detection (presence/absence of fracture as binary variable), fracture enumeration, fracture localization and lesion detection (fracture and/or a joint effusion used as constructed binary variable). RESULTS: The sensitivity of the AI solution for each of the four approaches was >89%. Greatest sensitivity of the AI solution was obtained for lesion detection (95.0%; 95% confidence interval: 92.1-96.9). The specificity of the AI solution ranged between 63% (for lesion detection) and 77% (for fracture detection). For all four approaches, the negative predictive values were >92% and the positive predictive values ranged between 54% (for fracture enumeration and localization) and 73% (for lesion detection). Specificity was lower for plastered children for all approaches (P < 0.001). CONCLUSION: The AI solution demonstrates high performances for detecting elbow's fracture and/or joint effusion in children. However, in our context of use, 8% of the radiographic sets ruled-out by the algorithm concerned children with a genuine traumatic elbow lesion.

Hydrogen Evolution Reaction on Single-Atom Pt Doped in Ni Matrix under Strong Alkaline Condition.

Pt catalyst has been considered as the state-of-the-art catalyst for hydrogen evolution reaction (HER) under acid condition. However, its catalytic kinetics under alkaline conditions is not well-understood. Herein, we report a Ni-Pt(SAs) (SAs = single atoms) catalyst with Pt atomically dispersed in a Ni matrix, and it possesses an impressive HER performance with an overpotential as low as 210 mV at 500 mA cm-2 in strong alkaline electrolyte (7 M KOH), which is much higher than Pt nanoparticle-modified Ni catalyst (Ni-Pt(NPs)). Kinetics analysis reveals that Pt doping in the Ni matrix can accelerate the Volmer step on the Ni-Pt surface. Moreover, Ni-Pt(SAs) displays a more favorable kinetics for H2 formation reaction at high current density than Ni-Pt(NPs). Theoretical calculations reveal that atomically dispersed Pt weakens the adsorption of both H and OH on the surface of Ni-Pt electrode and promotes H2 formation from surface H on Ni-Pt(SAs).

COVID-19-associated hepatic artery pseudoaneurysms.

Cases of coronary and pulmonary artery pseudoaneurysms secondary to COVID-19 have been reported in the literature and are supposed to be secondary to inflammatory and vasculitis processes linked to a viral multisystem inflammatory syndrome. Although the incidence of COVID-19-associated liver injury ranges from 14% to 53% in hospitalized patients, COVID-19-associated hepatic artery pseudoaneurysms have never been reported so far. We present the case of a patient whose follow-up CT after cryoablation of renal cell carcinoma revealed seven fusiform pseudoaneurysms of the two hepatic arteries secondary to COVID-19. Anticoagulant or anti-inflammatory treatments were not introduced. Vascular lesions were unchanged on the 3-month follow-up CT. At 6-month CT, the proximal pseudoaneurysm was replaced by a proximal occlusion of the accessory RHA.

External validation of a commercially available deep learning algorithm for fracture detection in children.

PURPOSE: The purpose of this study was to conduct an external validation of a fracture assessment deep learning algorithm (Rayvolve®) using digital radiographs from a real-life cohort of children presenting routinely to the emergency room. MATERIALS AND METHODS: This retrospective study was conducted on 2634 radiography sets (5865 images) from 2549 children (1459 boys, 1090 girls; mean age, 8.5 ± 4.5 [SD] years; age range: 0-17 years) referred by the pediatric emergency room for trauma. For each set was recorded whether one or more fractures were found, the number of fractures, and their location found by the senior radiologists and the algorithm. Using the senior radiologist diagnosis as the standard of reference, the diagnostic performance of deep learning algorithm (Rayvolve®) was calculated via three different approaches: a detection approach (presence/absence of a fracture as a binary variable), an enumeration approach (exact number of fractures detected) and a localization approach (focusing on whether the detected fractures were correctly localized). Subgroup analyses were performed according to the presence of a cast or not, age category (0-4 vs. 5-18 years) and anatomical region. RESULTS: Regarding detection approach, the deep learning algorithm yielded 95.7% sensitivity (95% CI: 94.0-96.9), 91.2% specificity (95% CI: 89.8-92.5) and 92.6% accuracy (95% CI: 91.5-93.6). Regarding enumeration and localization approaches, the deep learning algorithm yielded 94.1% sensitivity (95% CI: 92.1-95.6), 88.8% specificity (95% CI: 87.3-90.2) and 90.4% accuracy (95% CI: 89.2-91.5) for both approaches. Regarding age-related subgroup analyses, the deep learning algorithm yielded greater sensitivity and negative predictive value in the 5-18-years age group than in the 0-4-years age group for the detection approach (P < 0.001 and P = 0.002) and for the enumeration and localization approaches (P = 0.012 and P = 0.028). The high negative predictive value was robust, persisting in all of the subgroup analyses, except for patients with casts (P = 0.001 for the detection approach and P < 0.001 for the enumeration and localization approaches). CONCLUSION: The Rayvolve® deep learning algorithm is very reliable for detecting fractures in children, especially in those older than 4 years and without cast.

Electron transfer in extended systems: characterization by periodic density functional theory including the electronic coupling.

We describe a new computer implementation of electron transfer (ET) theory in extended systems treated by periodic density functional theory (DFT), including the calculation of the electronic coupling transition element VAB. In particular, the development opens up the full characterization of electron transfer in the solid state. The approach is valid for any single-determinant wavefunction with localized character representing the electronic structure of the system, from Hartree-Fock (HF) theory, to density functional theory (DFT), hybrid DFT theory, DFT+U theory, and constrained DFT (cDFT) theory. The implementation in CP2K reuses the high-performance functions of the code. The computational cost is equivalent to only one iteration of an HF calculation. We present test calculations for electron transfer in a number of systems, including a 1D-model of ferric oxide, hematite Fe2O3, rutile TiO2, and finally bismuth vanadate BiVO4.

Maximal orbital analysis of molecular wavefunctions.

We describe a new way to decompose one-electron orbitals of a molecule into atom-centered or fragment-centered orbitals by an approach that we call "maximal orbital analysis" (MOA). The MOA analysis is based on the corresponding orbital transformation (COT) that has the unique mathematical property of maximizing any sub-trace of the overlap matrix, in Hilbert metric sense, between two sets of nonorthogonal orbitals. Here, one set comprises the molecule orbitals (Hartree-Fock, Kohn-Sham, complete-active-space, or any set of orthonormal molecular orbitals), the other set comprises the basis functions associated with an atom or a group of atoms. We show in prototypical molecular systems such as a water dimer, metal carbonyl complexes, and a mixed-valent transition metal complex, that the MOA orbitals capture very well key aspects of wavefunctions and the ensuing chemical concepts that govern electronic interactions in molecules. © 2019 Wiley Periodicals, Inc.

Synthesis and Anisotropic Electrocatalytic Activity of Covellite Nanoplatelets with Fixed Thickness and Tunable Diameter.

Size- and shape-dependent electrochemical activity of nanostructures reveals relationships between nanostructure design and electrochemical performance. However, electrochemical performance of aspect-ratio-tunable quasi-two-dimensional (2D) nanomaterials with anisotropic properties has not been fully investigated. We prepared monodispersed hexagonal covellite (CuS) nanoplatelets (NPls) of fixed thickness (∼2 nm) but broadly tunable diameter (from 8 to >100 nm). These span a range of aspect ratios, from ∼4 to >50, connecting quasi-isotropic and quasi-2D regimes. Tests of electrochemical activity of the NPls for the oxygen reduction reaction in alkaline solution showed improved activity with increasing diameter. Combining experimental results with density functional theory calculations, we attribute size-dependent enhancement to anisotropy of conductivity and electrochemical activity. The lowest computed oxygen adsorption energy was on Cu sites exposed by cleaving covellite along (001) planes through tetrahedrally coordinated Cu atoms. The specific surface area of these planes, which are the top and bottom surfaces of the NPls, remains constant with changing diameter, for fixed NPl thickness. However, charge transport through the electrocatalyst film improves with increasing NPl diameter. These CuS NPl-carbon nanocatalysts provide inspiration for creating well-controlled layered nanomaterials for electrochemical applications and open up opportunities to design new electrocatalysts using transition-metal sulfides.

Single-Amino Acid Modifications Reveal Additional Controls on the Proton Pathway of [FeFe]-Hydrogenase.

The proton pathway of [FeFe]-hydrogenase is essential for enzymatic H2 production and oxidation and is composed of four residues and a water molecule. A computational analysis of this pathway in the [FeFe]-hydrogenase from Clostridium pasteurianum revealed that the solvent-exposed residue of the pathway (Glu282) forms hydrogen bonds to two residues outside of the pathway (Arg286 and Ser320), implying that these residues could function in regulating proton transfer. In this study, we show that substituting Arg286 with leucine eliminates hydrogen bonding with Glu282 and results in an ∼3-fold enhancement of H2 production activity when methyl viologen is used as an electron donor, suggesting that Arg286 may help control the rate of proton delivery. In contrast, substitution of Ser320 with alanine reduces the rate ∼5-fold, implying that it either acts as a member of the pathway or influences Glu282 to permit proton transfer. Interestingly, quantum mechanics/molecular mechanics and molecular dynamics calculations indicate that Ser320 does not play a structural role or indirectly influence the barrier for proton movement at the entrance of the channel. Rather, it may act as an additional proton acceptor for the pathway or serve in a regulatory role. While further studies are needed to elucidate the role of Ser320, collectively these data provide insights into the complex proton transport process.

[For metaethics nursing. Some indications Introductory]. / Pour une métaéthique des soins infirmiers. Quelques indications introductives.

In our scientific and cultural context, clinical ethics and organizational ethics play a crucial role in the field of nursing care, but they need a so-called meta-ethics whose aim is to verify and to justify their use of concepts and procedures. Such a meta-ethics lets appear a fundamental competence - empathy, in a very specific meaning - and a meta-principle that regulates the application of classical biomedical principles.

The nature of photogenerated charge separation among different crystal facets of BiVO4 studied by density functional theory.

Charge separation among different crystal facets of a semiconductor has been observed experimentally, but the underlying reasons behind this phenomenon are unknown. In this work, the activation energies of carrier hopping and the mobility of electron/hole transport along seven low-index crystal orientations of bulk BiVO4 have been calculated using a small polaron model. The calculated mobility and our previous experimental results reveal that there is a parallel relationship between the carrier mobility along the crystal axis and the carrier preferred accumulation on the corresponding crystal facets. It is proposed that the mobility of electrons (or holes) along the crystal axis [hkl] might be essentially related to the charge separation among the indices of corresponding facets (hkl); namely, the mobility of electrons (or holes) along the crystal axis [hkl] is the largest among all possible crystal axes, and the photogenerated electrons (or holes) tend to be accumulated on the indices of the corresponding facet (hkl) when the surface factors like surface band bending, surface energetic differences, etc. are not considered.

Water-assisted proton delivery and removal in bio-inspired hydrogen production catalysts.

Electrocatalysts for H2 production are envisioned to play an important role in renewable energy utilization systems. Nickel-based catalysts featuring pendant amines functioning as proton relays in the second coordination sphere of the metal center have led to catalysts achieving turnover frequencies as high as 10(7) s(-1) for H2 production. The fastest rates are observed when water is present in solution, with rates up to 10(3) times faster than those found in dry solvent. The focus of this paper is to provide mechanistic insight into the unexpected enhancement due to water. Addition of H2 to [Ni(P(Cy)2N(R')2)2](2+) was previously shown to give three isomers of a Ni(0) product with two protonated amines, where the N-H can be endo or exo to the Ni. By investigating the deprotonation of these two N-protonated Ni(0) intermediates resulting from the addition of H2 to [Ni(P(Cy)2N(R')2)2](2+), we observe by NMR spectroscopy studies an enhancement in the rate of deprotonation for protons positioned on the pendant amine next to the metal (endo) vs. protons that are positioned away from the metal (exo). Computational studies suggest that for smaller bases, the desolvation energy of the exogenous base is the primary contribution limiting the rate of endo deprotonation, while steric accessibility and facile proton movement also contribute. For more bulky bases, steric accessibility can play the dominant role. The significant reduction in these barriers observed in the presence of water has important implications for disfavoring less productive catalytic pathways and increasing catalytic rates.

Toward molecular catalysts by computer.

CONSPECTUS: Rational design of molecular catalysts requires a systematic approach to designing ligands with specific functionality and precisely tailored electronic and steric properties. It then becomes possible to devise computer protocols to design catalysts by computer. In this Account, we first review how thermodynamic properties such as redox potentials (E°), acidity constants (pKa), and hydride donor abilities (ΔGH(-)) form the basis for a framework for the systematic design of molecular catalysts for reactions that are critical for a secure energy future. We illustrate this for hydrogen evolution and oxidation, oxygen reduction, and CO conversion, and we give references to other instances where it has been successfully applied. The framework is amenable to quantum-chemical calculations and conducive to predictions by computer. We review how density functional theory allows the determination and prediction of these thermodynamic properties within an accuracy relevant to experimentalists (∼0.06 eV for redox potentials, ∼1 pKa unit for pKa values, and 1-2 kcal/mol for hydricities). Computation yielded correlations among thermodynamic properties as they reflect the electron population in the d shell of the metal center, thus substantiating empirical correlations used by experimentalists. These correlations point to the key role of redox potentials and other properties (pKa of the parent aminium for the proton-relay-based catalysts designed in our laboratory) that are easily accessible experimentally or computationally in reducing the parameter space for design. These properties suffice to fully determine free energies maps and profiles associated with catalytic cycles, i.e., the relative energies of intermediates. Their prediction puts us in a position to distinguish a priori between desirable and undesirable pathways and mechanisms. Efficient catalysts have flat free energy profiles that avoid high activation barriers due to low- and high-energy intermediates. The criterion of a flat energy profile can be mathematically resolved in a functional in the reduced parameter space that can be efficaciously calculated by means of the correlation expressions. Optimization of the functional permits the prediction by computer of design points for optimum catalysts. Specifically, the optimization yields the values of the thermodynamic properties for efficient (high rate and low overpotential) catalysts. We are on the verge of design of molecular electrocatalysts by computer. Future efforts must focus on identifying actual ligands that possess these properties. We believe that this can also be achieved through computation, using Taft-like relationships linking molecular composition and structure with electron-donating ability and steric effects. We note also that the approach adopted here of using free energy maps to decipher catalytic pathways and mechanisms does not account for kinetic barriers associated with elementary steps along the catalytic pathway, which may make thermodynamically accessible intermediates kinetically inaccessible. Such an extension of the approach will require further computations that, however, can take advantage of Polanyi-like linear free energy relationships linking activation barriers and reaction free energies.

Safety and efficacy of natalizumab in Belgian multiple sclerosis patients: subgroup analysis of the natalizumab observational program.

Natalizumab (Tysabri(®)) is highly efficacious in controlling disease activity in relapsing multiple sclerosis (MS) patients. As it is one of the more recent therapies for MS, there remains a need for long-term safety and efficacy data of natalizumab in a clinical practice setting. The Tysabri observational program (TOP) is an open-label, multicenter, multinational, prospective observational study, aiming to recruit up to 6,000 patients with relapsing-remitting MS from Europe, Canada and Australia. The objectives of this study are to collect long-term safety and efficacy data on disease activity and disability progression. We report here the interim results of the 563 patients included in TOP between December 2007 and 2012 from Belgium. This patient cohort was older at baseline, had longer disease duration, higher neurological impairment, and a higher baseline annualized relapse rate, when compared to patients included in the pivotal phase III AFFIRM trial. Nevertheless, the efficacy of natalizumab was comparable. The annualized relapse rate on treatment was reduced by 90.70 % (p < 0.0001) with a cumulative probability of relapse of 26.87 % at 24 months. The cumulative probabilities of sustained disability improvement and progression at 24 months were 25.68 and 9.01 %, respectively. There were no new safety concerns over the follow-up period. Two cases of progressive multifocal leukoencephalopathy were diagnosed. Our results are consistent with other observational studies in the post-marketing setting.

Ultrafast Estimation of Electronic Couplings for Electron Transfer between π-Conjugated Organic Molecules.

Simulation of charge transport in organic semiconducting materials requires the development of strategies for very fast yet accurate estimation of electronic coupling matrix elements for electron transfer between organic molecules (transfer integrals, Hab). A well-known relation that is often exploited for this purpose is the approximately linear dependence of electronic coupling with respect to the overlap of the corresponding diabatic state wave functions for a given donor-acceptor pair. Here we show that a single such relation can be established for a large number of different π-conjugated organic molecules. In our computational scheme the overlap of the diabatic state wave function is simply estimated by the overlap of the highest singly occupied molecular orbital of donor and acceptor, projected on a minimum valence shell Slater-type orbital (STO) basis with optimized Slater decay coefficients. After calibration of the linear relation, the average error in Hab as obtained from the STO orbital overlap is a factor of 1.9 with respect to wave function-theory validated DFT calculations for a diverse set of π-conjugated organic dimers including small arenes, arenes with S, N, and O heteroatoms, acenes, porphins, and buckyballs. The crucial advantage of the scheme is that the STO orbital overlap calculation is analytic. This leads to speedups of 6 orders of magnitude with respect to reference DFT calculations, with little loss of accuracy in the regime relevant to charge transport in organics.

Molecular dynamics study of the proposed proton transport pathways in [FeFe]-hydrogenase.

Possible proton transport pathways in Clostridium pasteurianum (CpI) [FeFe]-hydrogenase were investigated with molecular dynamics simulations. This study was undertaken to evaluate the functional pathway and provide insight into the hydrogen bonding features defining an active proton transport pathway. Three pathways were evaluated, two of which consist of water wires and one of predominantly amino acid residues. Our simulations suggest that protons are not transported through water wires. Instead, the five-residue motif (Glu282, Ser319, Glu279, H2O, Cys299) was found to be the likely pathway, consistent with previously made experimental observations. The pathway was found to have a persistent hydrogen bonded core (residues Cys299 to Ser319), with less persistent hydrogen bonds at the ends of the pathway for both H2 release and H2 uptake. Single site mutations of the four residues have been shown experimentally to deactivate the enzyme. The theoretical evaluation of these mutations demonstrates redistribution of the hydrogen bonds in the pathway, resulting in enzyme deactivation. Finally, coupling between the protein dynamics near the proton transport pathway and the redox partner binding regions was also found as a function of H2 uptake and H2 release states, which may be indicative of a correlation between proton and electron movement within the enzyme.

Ab initio molecular dynamics simulation of proton hopping in a model polymer membrane.

We report the results of ab initio molecular dynamics simulations of a model Nafion polymer membrane initially equilibrated using classical molecular dynamics simulations. We studied three hydration levels (λ) of 3, 9, and 15 H2O/SO3(-) corresponding to dry, hydrated, and saturated fuel cell membrane, respectively. The barrier for proton transfer from the SO3(-)-H3O(+) contact ion pair to a solvent-separated ion pair decreased from 2.3 kcal/mol for λ = 3 to 0.8 kcal/mol for λ = 15. The barrier for proton transfer between two water molecules was in the range from 0.7 to 0.8 kcal/mol for the λ values studied. The number of proton shuttling events between a pair of water molecules is an order of magnitude more than the number of proton hops across three distinct water molecules. The proton diffusion coefficient at λ = 15 is about 0.9 × 10(-5) cm(2)/s, which is in good agreement with experiment and our previous quantum hopping molecular dynamics simulations.

Evaluation of the Role of Water in the H2 Bond Formation by Ni(II)-Based Electrocatalysts.

We investigate the role of water in the H-H bond formation by a family of nickel molecular catalysts that exhibit high rates for H2 production in acetonitrile solvent. A key feature leading to the high reactivity is the Lewis acidity of the Ni(II) center and pendant amines in the diphosphine ligand that function as Lewis bases, facilitating H-H bond formation or cleavage. Significant increases in the rate of H2 production have been reported in the presence of added water. Our calculations show that molecular water can displace an acetonitrile solvent molecule in the first solvation shell of the metal. One or two water molecules can also participate in shuttling a proton that can combine with a metal hydride to form the H-H bond. However the participation of the water molecules does not lower the barrier to H-H bond formation. Thus these calculations suggest that the rate increase due to water in these electrocatalysts is not associated with the elementary step of H-H bond formation or cleavage but rather with the proton delivery steps. We attribute the higher barrier in the H-H bond formation in the presence of water to a decrease in direct interaction between the protic and hydridic hydrogen atoms forced by the water molecules.