Reproducibility of inverse gas chromatography under infinite dilution: Results and interpretations of an interlaboratory study.

Over the last years, inverse gas chromatography (IGC) proved to be a versatile and sensitive analytical technique for physicochemical properties. However, the comparability of results obtained by different users and devices remains a topic for debate. This is the first time, an interlaboratory study using different types of IGC instruments is reported. Eight organizations with different IGC devices defined a common lab measurement protocol to analyse two standard materials, silica and lactose. All data was collected in a standard result form and has been treated identically with the objective to identify experimentally observed differences and not potentially different data treatments. The calculated values of the dispersive surface energy vary quite significantly (silica: 22 mJ/m2 - 34 mJ/m2, lactose 37 mJ/m2 - 51 mJ/m2) and so do the ISP values and retention volumes for both materials. This points towards significant and seemingly undiscovered differences in the operation of the instruments and the obtained underlying primary data, even under the premise of standard conditions. Variations are independent of the instrument type and uncertainties in flow rates or the injected quantities of probe molecules may be potential factors for the differences. This interlaboratory study demonstrates that the IGC is a very sensitive analytical tool, which detects minor changes, but it also shows that for a proper comparison, the measurement conditions have to be checked with great care. A publicly available standard protocol and material, for which this study can be seen as a starting point, is still needed to judge on the measurements and the resulting parameters more objectively.

Comparison and Incorporation of Reasoning and Learning Approaches for Cancer Therapy Research.

Representing knowledge in a comprehensible and maintainable way and transparently providing inferences thereof are important issues, especially in the context of applications related to artificial intelligence in medicine. This becomes even more obvious if the knowledge is dynamically growing and changing and when machine learning techniques are being involved. In this paper, we present an approach for representing knowledge about cancer therapies collected over two decades at St.-Johannes-Hospital in Dortmund, Germany. The presented approach makes use of InteKRator, a toolbox that combines knowledge representation and machine learning techniques, including the possibility of explaining inferences. An extended use of InteKRator's reasoning system will be introduced for being able to provide the required inferences. The presented approach is general enough to be transferred to other data, as well as to other domains. The approach will be evaluated, e. g., regarding comprehensibility, accuracy and reasoning efficiency.

Thermal transport in kinked nanowires through simulation.

The thermal conductance of nanowires is an oft-explored quantity, but its dependence on the nanowire shape is not completely understood. The behaviour of the conductance is examined as kinks of varying angular intensity are included into nanowires. The effects on thermal transport are evaluated through molecular dynamics simulations, phonon Monte Carlo simulations and classical solutions of the Fourier equation. A detailed look is taken at the nature of heat flux within said systems. The effects of the kink angle are found to be complex, influenced by multiple factors including crystal orientation, details of transport modelling, and the ratio of mean free path to characteristic system lengths. The effect of varying phonon reflection specularity on the heat flux is also examined. It is found that, in general, the flow of heat through systems simulated through phonon Monte Carlo methods is concentrated into a channel smaller than the wire dimensions, while this is not the case in the classical solutions of the Fourier model.

Characterization of polar surface groups on siliceous materials by inverse gas chromatography and the enthalpy-entropy compensation effect.

Surface-modified porous silica is a well-established composite material. To improve its embedding and application behavior, adsorption studies of various probe molecules have been performed using the technique of inverse gas chromatography (IGC). For this purpose, IGC experiments were carried out in the infinite dilution mode on macro-porous micro glass spheres before and after surface modification with (3-mercaptopropyl)trimethoxysilane. To provide information about the polar interactions between probe molecules and the silica surface, in particular, eleven polar molecules have been injected. In summary, the free surface energy for pristine silica ( γ S t o t a l = 229 mJ/m2) and for (3-mercaptopropyl)trimethoxysilane-modified silica ( γ S t o t a l = 135 mJ/m2) indicates a reduced wettability after surface modification. This is due to the reduction of the polar component of the free surface energy ( γ S S P ) from 191 mJ/m2 to 105 mJ/m2. Simultaneously, with the reduction of surface silanol groups caused by surface modification of silica and, therefore, the decrease in polar interactions, a substantial loss of Lewis acidity was observed by various IGC approaches. Experiments with all silica materials have been conducted at temperatures in the range from 90°C to 120°C to determine the thermodynamic parameters, such as adsorption enthalpy ( Δ H a d s ) and adsorption entropy ( Δ S a d s ), using the Arrhenius regression procedure evaluating the IGC data. With the help of the enthalpy-entropy compensation, two types of adsorption complexes are assumed between polar probe molecules and the silica surface because of different isokinetic temperatures. Identical adsorption complexes with an isokinetic temperature of 370°C have been assigned to alkanes and weakly interacting polar probes such as benzene, toluene, dichloromethane, and chloroform. Polar probe molecules with typical functional groups such as OH, CO, and CN, having the ability to form hydrogen bonds to the silica surface, exhibit a lower isokinetic temperature of 60°C. Quantum chemical calculations of the probe molecules on a non-hydroxylated and hydroxylated silica cluster supported the formation of hydrogen bonds in the case of a strong polar adsorption complex with a bonding distance of 1.7 nm-1.9 nm to the silica surface.

Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference.

Despite marked progress in the management of atrial fibrillation (AF), detecting AF remains difficult and AF-related complications cause unacceptable morbidity and mortality even on optimal current therapy. This document summarizes the key outcomes of the 8th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA). Eighty-three international experts met in Hamburg for 2 days in October 2021. Results of the interdisciplinary, hybrid discussions in breakout groups and the plenary based on recently published and unpublished observations are summarized in this consensus paper to support improved care for patients with AF by guiding prevention, individualized management, and research strategies. The main outcomes are (i) new evidence supports a simple, scalable, and pragmatic population-based AF screening pathway; (ii) rhythm management is evolving from therapy aimed at improving symptoms to an integrated domain in the prevention of AF-related outcomes, especially in patients with recently diagnosed AF; (iii) improved characterization of atrial cardiomyopathy may help to identify patients in need for therapy; (iv) standardized assessment of cognitive function in patients with AF could lead to improvement in patient outcomes; and (v) artificial intelligence (AI) can support all of the above aims, but requires advanced interdisciplinary knowledge and collaboration as well as a better medico-legal framework. Implementation of new evidence-based approaches to AF screening and rhythm management can improve outcomes in patients with AF. Additional benefits are possible with further efforts to identify and target atrial cardiomyopathy and cognitive impairment, which can be facilitated by AI.

A transferable recommender approach for selecting the best density functional approximations in chemical discovery.

Approximate density functional theory has become indispensable owing to its balanced cost-accuracy trade-off, including in large-scale screening. To date, however, no density functional approximation (DFA) with universal accuracy has been identified, leading to uncertainty in the quality of data generated from density functional theory. With electron density fitting and Δ-learning, we build a DFA recommender that selects the DFA with the lowest expected error with respect to the gold standard (but cost-prohibitive) coupled cluster theory in a system-specific manner. We demonstrate this recommender approach on the evaluation of vertical spin splitting energies of transition metal complexes. Our recommender predicts top-performing DFAs and yields excellent accuracy (about 2 kcal mol-1) for chemical discovery, outperforming both individual Δ-learning models and the best conventional single-functional approach from a set of 48 DFAs. By demonstrating transferability to diverse synthesized compounds, our recommender potentially addresses the accuracy versus scope dilemma broadly encountered in computational chemistry.

Ligand additivity relationships enable efficient exploration of transition metal chemical space.

To accelerate the exploration of chemical space, it is necessary to identify the compounds that will provide the most additional information or value. A large-scale analysis of mononuclear octahedral transition metal complexes deposited in an experimental database confirms an under-representation of lower-symmetry complexes. From a set of around 1000 previously studied Fe(II) complexes, we show that the theoretical space of synthetically accessible complexes formed from the relatively small number of unique ligands is significantly (∼816k) larger. For the properties of these complexes, we validate the concept of ligand additivity by inferring heteroleptic properties from a stoichiometric combination of homoleptic complexes. An improved interpolation scheme that incorporates information about cis and trans isomer effects predicts the adiabatic spin-splitting energy to around 2 kcal/mol and the HOMO level to less than 0.2 eV. We demonstrate a multi-stage strategy to discover leads from the 816k Fe(II) complexes within a targeted property region. We carry out a coarse interpolation from homoleptic complexes that we refine over a subspace of ligands based on the likelihood of generating complexes with targeted properties. We validate our approach on nine new binary and ternary complexes predicted to be in a targeted zone of discovery, suggesting opportunities for efficient transition metal complex discovery.

Immunohistochemical markers for histopathological diagnosis and differentiation of acute cutaneous graft-versus-host disease.

Graft-versus-host disease (GvHD) is a major complication following stem-cell or solid-organ transplantation. Accurate diagnosis of cutaneous GvHD is challenging, given that drug eruptions and viral rashes may present with similar clinical/histological manifestations. Specific markers are not available. We performed the histological examination of biopsy samples from acute GvHD (aGvHD; n = 54), Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN; n = 27), maculopapular drug eruption (MDE; n = 26) and healthy controls (n = 26). Samples of aGvHD showed a decrease in Langerhans cells (LC, p = 0.0001) and an increase in macrophages (MΦ, p = 0.0001) compared to healthy skin. Compared to SJS/TEN, MDE and healthy skin, aGvHD biopsies contained greater numbers of CD4+ and CD8+ T cells. The majority of CD4+ T-helper cells were localized in the upper dermis, whereas cytotoxic CD8+ T cells were found in the epidermis. Increased numbers of CD56+ natural killer (NK) cells in the upper dermis of aGvHD skin (p = 0.007) were not observed in controls or SJS/TEN and MDE. There were no differences in elafin staining between aGvHD and the latter two conditions. Acute GvHD appears to have a distinct inflammatory cell profile (T cells/NK cells) that may aid establishing in a more accurate diagnosis, especially when used to rule out differential diagnoses such as SJS/TEN or MDE.

Machine Learning Approaches toward Orbital-free Density Functional Theory: Simultaneous Training on the Kinetic Energy Density Functional and Its Functional Derivative.

Orbital-free approaches might offer a way to boost the applicability of density functional theory by orders of magnitude in system size. An important ingredient for this endeavor is the kinetic energy density functional. Snyder et al. [ Phys. Rev. Lett. 2012, 108, 253002] presented a machine learning approximation for this functional achieving chemical accuracy on a one-dimensional model system. However, a poor performance with respect to the functional derivative, a crucial element in iterative energy minimization procedures, enforced the application of a computationally expensive projection method. In this work we circumvent this issue by including the functional derivative into the training of various machine learning models. Besides kernel ridge regression, the original method of choice, we also test the performance of convolutional neural network techniques borrowed from the field of image recognition.

Towards Macroporous α-Al2O3-Routes, Possibilities and Limitations.

This article combines a systematic literature review on the fabrication of macroporous α-Al2O3 with increased specific surface area with recent results from our group. Publications claiming the fabrication of α-Al2O3 with high specific surface areas (HSSA) are comprehensively assessed and critically reviewed. An account of all major routes towards HSSA α-Al2O3 is given, including hydrothermal methods, pore protection approaches, dopants, anodically oxidized alumina membranes, and sol-gel syntheses. Furthermore, limitations of these routes are disclosed, as thermodynamic calculations suggest that γ-Al2O3 may be the more stable alumina modification for ABET > 175 m2/g. In fact, the highest specific surface area unobjectionably reported to date for α-Al2O3 amounts to 16-24 m2/g and was attained via a sol-gel process. In a second part, we report on some of our own results, including a novel sol-gel synthesis, designated as mutual cross-hydrolysis. Besides, the Mn-assisted α-transition appears to be a promising approach for some alumina materials, whereas pore protection by carbon filling kinetically inhibits the formation of α-Al2O3 seeds. These experimental results are substantiated by attempts to theoretically calculate and predict the specific surface areas of both porous materials and nanopowders.

Geometry optimization using Gaussian process regression in internal coordinate systems.

Locating the minimum energy structure of molecules, typically referred to as geometry optimization, is one of the first steps of any computational chemistry calculation. Earlier research was mostly dedicated to finding convenient sets of molecule-specific coordinates for a suitable representation of the potential energy surface, where a faster convergence toward the minimum structure can be achieved. More recent approaches, on the other hand, are based on various machine learning techniques and seem to revert to Cartesian coordinates instead for practical reasons. We show that the combination of Gaussian process regression with those coordinate systems employed by state-of-the-art geometry optimizers can significantly improve the performance of this powerful machine learning technique. This is demonstrated on a benchmark set of 30 small covalently bonded molecules.

Machine Learning in Computational Chemistry: An Evaluation of Method Performance for Nudged Elastic Band Calculations.

The localization of transition states and the calculation of reaction pathways are routine tasks of computational chemists but often very CPU-intense problems, in particular for large systems. The standard algorithm for this purpose is the nudged elastic band method, but it has become obvious that an "intelligent" selection of points to be evaluated on the potential energy surface can improve its convergence significantly. This article summarizes, compares, and extends known strategies that have been heavily inspired by the machine learning developments of recent years. It presents advantages and disadvantages and provides an unbiased comparison of neural network based approaches, Gaussian process regression in Cartesian coordinates, and Gaussian approximation potentials. We test their performance on two example reactions, the ethane rotation and the activation of carbon dioxide on a metal catalyst, and provide a clear ranking in terms of usability for future implementations.

Functionalization of porous siliceous materials, Part 2: Surface characterization by inverse gas chromatography.

Surface modification of porous glass beads by ethanol-based 3-mercaptopropyltrimethoxysilane (MPTMS) grafting solutions is directly evidenced by nitrogen adsorption, elemental analysis, thermogravimetry, infrared and 29Si CP MAS NMR spectroscopy. Furthermore, the energetic characterization of the surface is essential to understand comprehensively the physico-chemical interactions between the pristine and MPTMS-modified surface and its gas/liquid-phase environment. In this study, inverse gas chromatography (IGC) is used to characterize the surface properties of porous glass (PG). By means of IGC at infinite dilution (IGC-ID), the dispersive component of the surface energy (γsd), the enthalpy and entropy of adsorption of C6-C10 hydrocarbon probes were determined at temperatures between 30 and 120 °C. The specific component of the surface energy (γssp) at the temperature of 120 °C has been obtained via the Van Oss theory and a least-squares procedure evaluating the IGC data of 8 polar probe molecules collectively. After surface silylation, the total surface energy (γst) decreased from 402 to 255 mJ/m² indicating both a reduced wettability and an increased hydrophobicity of the MPTMS-modified PG. Moreover, the acidity/basicity parameters according to the Van Oss and the Gutmann approach indicated that the acidity of the PG surface decreases by MPTMS grafting. Using n-octane and isopropanol probes, IGC at finite concentration (IGC-FC) was applied to obtain their adsorption isotherms and subsequently the BET specific surface areas. In addition, the surface heterogeneity of the studied PGs was also computed. The energy distribution functions of adsorption sites were monomodal (peak maximum at about 22 kJ/mol) for the n-octane probe, while isopropanol revealed a bimodal distribution function (maxima at about 18 and 25 kJ/mol) on both pristine and MPTMS-modified PG. Furthermore, the proportion of high energy sites (apparently assigned to SiOH groups) has been reduced by surface modification from 65% to only 35% despite a high surface coverage of ˜10 MPTMS species/nm2. These findings are in agreement with the results of 29Si CP MAS NMR measurements and are supported by DFT calculations on the adsorption of isopropanol and n-octane on the surface of a silica cluster model.

Conservation of Hot Thermal Spin-Orbit Population of 2P Atoms in a Cold Quantum Fluid Environment.

The 0.4 K internal temperature of superfluid helium nanodroplets is believed to guarantee a corresponding ground-state population of dopant atoms and molecules inside this cryogenic matrix. We have recorded 6s ← 5p excitation spectra of indium atoms in helium droplets and found two absorption bands separated by about 2000 cm-1, a value close to the spin-orbit (SO) splitting of the In 2P ground state. The intensities of the bands agree with a thermal population of the 2P1/2 and 2P3/2 states at 870 K, the temperature of the In pick-up cell. Applying femtosecond pump-probe spectroscopy, we found the same dynamical response of the helium solvation shell after the photoexcitation of the two bands. He-density functional theory simulations of the excitation spectra are in agreement with the bimodal structure. Our findings show that the population of SO levels of hot dopants is conserved after pick-up inside the superfluid droplet. Implications for the interpretation of experiments on molecular aggregates are discussed.

Femtosecond photoexcitation dynamics inside a quantum solvent.

The observation of chemical reactions on the time scale of the motion of electrons and nuclei has been made possible by lasers with ever shortened pulse lengths. Superfluid helium represents a special solvent that permits the synthesis of novel classes of molecules that have eluded dynamical studies so far. However, photoexcitation inside this quantum solvent triggers a pronounced response of the solvation shell, which is not well understood. Here, we present a mechanistic description of the solvent response to photoexcitation of indium (In) dopant atoms inside helium nanodroplets (HeN), obtained from femtosecond pump-probe spectroscopy and time-dependent density functional theory simulations. For the In-HeN system, part of the excited state electronic energy leads to expansion of the solvation shell within 600 fs, initiating a collective shell oscillation with a period of about 30 ps. These coupled electronic and nuclear dynamics will be superimposed on intrinsic photoinduced processes of molecular systems inside helium droplets.

Chiral Separation via Molecular Sieving: A Computational Screening of Suitable Functionalizations for Nanoporous Graphene.

In a recent study [Angew. Chem. Int. Ed., 2014, 53, 9957-9960] a new concept of chiral separation has been suggested, which is based on functionalized, nanoporous sheets of graphene. In this follow-up article we discuss the underlying principle in greater detail and make suggestions for suitable pore functionalizations with respect to a selection of chiral prototype molecules. Considering drug molecules as future targets for a chiral separation via membranes, the necessary pore sizes represent a big challenge for standard methods of computational chemistry. Therefore, we test two common force fields (GAFF, CGenFF) as well as a semiempirical tight-binding approach recently developed by the Grimme group (GFN-xTB) against the computationally much more expensive density functional theory. We identify the GFN-xTB method as the most suitable approach for future simulations of functionalized pores for the given purpose, as it is able to produce reaction pathways in very good agreement with density functional theory, even in cases where force fields tend to an extreme overestimation of barrier heights.

Pharmacokinetics and safety results from the Phase 3 randomized, open-label, study of intravenous posaconazole in patients at risk of invasive fungal disease.

OBJECTIVES: A two-part (Phase 1B/3), sequential, open-label, multicentre study evaluated the pharmacokinetics (PK) and safety of intravenous (iv) posaconazole given as antifungal prophylaxis to neutropenic patients with AML or myelodysplastic syndrome (MDS) or to recipients at risk of invasive fungal disease (IFD) after allogeneic HSCT. METHODS: Patients (N = 237) received 300 mg of posaconazole iv twice daily on day 1, followed by 300 mg of posaconazole iv once daily for 4-28 days. After at least 5 days, patients were randomly assigned to receive posaconazole oral suspension, 400 mg twice daily or 200 mg three times daily, to complete a 28 day treatment course. Primary PK parameters were steady-state average concentration over the dosing interval (Cavg) and posaconazole trough levels (Cmin). RESULTS: Mean posaconazole Cmin was 1320 ng/mL (day 6) and 1297 ng/mL (day 8); steady-state Cmin was 1090 ng/mL (day 10). Mean steady-state posaconazole Cavg was 1500 ng/mL (day 10 or 14) and was similar in HSCT recipients (1560 ng/mL) and AML/MDS patients (1470 ng/mL). The most commonly reported treatment-related adverse events were diarrhoea (8%), nausea (5%) and rash (5%). IFD was reported in 3/237 patients (1%; 2 proven, 1 probable). CONCLUSIONS: Intravenous posaconazole at 300 mg was well tolerated, resulted in adequate steady-state systemic exposure and was associated with a low incidence of IFD in this population at high risk. TRIAL REGISTRY AND NUMBER: ClinicalTrials.gov, NCT01075984.

The new EU regulation on in vitro diagnostics: potential issues at the interface of medicines and companion diagnostics.

The new European regulation for in vitro diagnostics (IVD) divides the certification of IVD including companion diagnostics (CDx) by notified bodies (NB) from the market authorization of medicines. With the new regulation, CDx will require conformity assessment which is expected to include clinical evidence by NB. This is a significant change from the current situation: until now most IVD have been certified based on their manufacturers' assessment. For one medicine assessed by the EMA, certification of several different CDx by different NB is possible. As the benefit-risk balance of the medicine may depend on the performance (e.g., sensitivity and specificity) of its CDx, a close cooperation of EMA and NB will be necessary. The availability of detailed information on CDx used in the pivotal clinical trials for the medicine's authorization will become crucial for the assessment of alternative or competing CDx.