Reactivation strength during cued recall is modulated by graph distance within cognitive maps.

Declarative memory retrieval is thought to involve reinstatement of neuronal activity patterns elicited and encoded during a prior learning episode. Furthermore, it is suggested that two mechanisms operate during reinstatement, dependent on task demands: individual memory items can be reactivated simultaneously as a clustered occurrence or, alternatively, replayed sequentially as temporally separate instances. In the current study, participants learned associations between images that were embedded in a directed graph network and retained this information over a brief 8 min consolidation period. During a subsequent cued recall session, participants retrieved the learned information while undergoing magnetoencephalographic recording. Using a trained stimulus decoder, we found evidence for clustered reactivation of learned material. Reactivation strength of individual items during clustered reactivation decreased as a function of increasing graph distance, an ordering present solely for successful retrieval but not for retrieval failure. In line with previous research, we found evidence that sequential replay was dependent on retrieval performance and was most evident in low performers. The results provide evidence for distinct performance-dependent retrieval mechanisms, with graded clustered reactivation emerging as a plausible mechanism to search within abstract cognitive maps.

An acute bout of high-intensity exercise affects nocturnal sleep and sleep-dependent memory consolidation.

Acute exercise has been shown to affect long-term memory and sleep. However, it is unclear whether exercise-induced changes in sleep architecture are associated with enhanced memory. Recently, it has been shown that exercise followed by a nap improved declarative memory. Whether these effects transfer to night sleep and other memory domains has not yet been studied. Here, we investigate the influence of exercise on nocturnal sleep architecture and associations with sleep-dependent procedural and declarative memory consolidation. Nineteen subjects (23.68 ± 3.97 years) were tested in a balanced cross-over design. In two evening sessions, participants either exercised (high-intensity interval training) or rested immediately after encoding two memory tasks: (1) a finger tapping task and (2) a paired-associate learning task. Subsequent nocturnal sleep was recorded by polysomnography. Retrieval was conducted the following morning. High-intensity interval training lead to an increased declarative memory retention (p = 0.047, d = 0.40) along with a decrease in REM sleep (p = 0.012, d = 0.75). Neither procedural memory nor NREM sleep were significantly affected. Exercise-induced changes in N2 showed a positive correlation with procedural memory retention which did not withstand multiple comparison correction. Exploratory analyses on sleep spindles and slow wave activity did not reveal significant effects. The present findings suggest an exercise-induced enhancement of declarative memory which aligns with changes in nocturnal sleep architecture. This gives additional support for the idea of a potential link between exercise-induced sleep modifications and memory formation which requires further investigation in larger scaled studies.

Quantification of PVC plasticizer mixtures by compact proton NMR spectroscopy and indirect hard modeling.

A novel approach is introduced for the fast, reliable, and low-cost recognition and quantification of plasticizers in plasticizers mixtures. It uses benchtop 1H NMR spectroscopy and indirect hard modeling, a mechanistic multivariate regression technique. The approach is demonstrated on five different PVC plasticizers having similar spectral signatures in proton NMR spectra. With only 16 scans per spectrum, i.e., 2 min 40 s measurement time, quantification limits down to 0.14 mg mL-1, or 0.35 wt% plasticizer in PVC, were achieved. Apart from the rapid data acquisition, the use of spectral hard modeling enabled the quantification of plasticizer mixtures while using only 4 to 6 training samples per component. Despite strongly overlapping signals in the NMR spectra, various plasticizers were differentiated and quantified, as exemplarily demonstrated for binary mixtures. A commercial PVC specimen with three different layers was also examined, confirming the applicability of benchtop NMR spectroscopy. Additionally, the use of the proposed method to validate official regulations concerning the plasticizer content in PVC is assessed. The presented results demonstrate that the combination of benchtop NMR and spectral hard modeling is a very promising analytical tool for rapid PVC plasticizer recognition and quantification with high analytical throughput. Moreover, the results indicate a high potential for benchtop NMR and spectral hard modeling for microchemical analysis, even for complex samples.

Standardization and Control of Grignard Reactions in a Universal Chemical Synthesis Machine using online NMR.

A big problem with the chemistry literature is that it is not standardized with respect to precise operational parameters, and real time corrections are hard to make without expert knowledge. This lack of context means difficult reproducibility because many steps are ambiguous, and hence depend on tacit knowledge. Here we present the integration of online NMR into an automated chemical synthesis machine (CSM aka. "Chemputer" which is capable of small-molecule synthesis using a universal programming language) to allow automated analysis and adjustment of reactions on the fly. The system was validated and benchmarked by using Grignard reactions which were chosen due to their importance in synthesis. The system was monitored in real time using online-NMR, and spectra were measured continuously during the reactions. This shows that the synthesis being done in the Chemputer can be dynamically controlled in response to feedback optimizing the reaction conditions according to the user requirements.

Artificial neural networks for quantitative online NMR spectroscopy.

Industry 4.0 is all about interconnectivity, sensor-enhanced process control, and data-driven systems. Process analytical technology (PAT) such as online nuclear magnetic resonance (NMR) spectroscopy is gaining in importance, as it increasingly contributes to automation and digitalization in production. In many cases up to now, however, a classical evaluation of process data and their transformation into knowledge is not possible or not economical due to the insufficiently large datasets available. When developing an automated method applicable in process control, sometimes only the basic data of a limited number of batch tests from typical product and process development campaigns are available. However, these datasets are not large enough for training machine-supported procedures. In this work, to overcome this limitation, a new procedure was developed, which allows physically motivated multiplication of the available reference data in order to obtain a sufficiently large dataset for training machine learning algorithms. The underlying example chemical synthesis was measured and analyzed with both application-relevant low-field NMR and high-field NMR spectroscopy as reference method. Artificial neural networks (ANNs) have the potential to infer valuable process information already from relatively limited input data. However, in order to predict the concentration at complex conditions (many reactants and wide concentration ranges), larger ANNs and, therefore, a larger training dataset are required. We demonstrate that a moderately complex problem with four reactants can be addressed using ANNs in combination with the presented PAT method (low-field NMR) and with the proposed approach to generate meaningful training data. Graphical abstract.

Phosphorus Pool Composition in Soils and Sediments of Transitional Ecotones under the Influence of Agriculture.

Transitional ecotones such as vegetated buffer strips, stream banks, and streambeds retain phosphorus (P) in the immediate surroundings of farmland. Yet the fate of P in these ecotones remains unclear. Our objectives were to (i) test the difference in the P pool composition of soil and sediment between sites surrounded by agriculture and forestry and (ii) test whether specific P pools differ among transitional ecotones. Phosphorus pools (by a modified Hedley fractionation scheme) and the degree of P saturation (DPS) were determined in 33 soil and sediment samples from eight farmland and three forest sites. At farmland sites, total P in soil and sediment was more than twofold higher as compared to forestry sites. The proportion of labile inorganic P (Pi) and the DPS were significantly larger in transitional ecotones close to farmland. We further used normalized values for comparing the respective ecotones at the sites. The deviation of each transitional ecotone relative to the respective site average revealed that the normalized total P concentration and proportions of labile and moderately labile Pi were significantly smaller in bed sediment adjacent to farmland as compared to respective stream bank and buffer strip soil, whereas the stable Ca-Pi proportion was larger. The results reflected a decreased Pi sorption capacity in combination with Pi desorption and transfer of Pi into secondary Ca-Pi minerals in bed sediment. In summary, the influence of agriculture increases labile P pools in soil and sediment, which are then subject to a succession of dynamic processes resulting in a partial loss of Pi to the aqueous phase as well as fixation of Pi in the Ca-Pi pool.

Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals.

Modular plants using intensified continuous processes represent an appealing concept for the production of pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes; besides, it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and is based on a compact nuclear magnetic resonance (NMR) spectrometer. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including robust evaluation of sensor data. Beyond monitoring the product quality, online NMR data was used in a new iterative optimization approach to maximize the plant profit and served as a reliable reference for the calibration of a near-infrared (NIR) spectrometer. The overall approach was demonstrated on a commercial-scale pilot plant using a metal-organic reaction with pharmaceutical relevance. Graphical abstract.

Two-photon interference in the telecom C-band after frequency conversion of photons from remote quantum emitters.

Efficient fibre-based long-distance quantum communication via quantum repeaters relies on deterministic single-photon sources at telecom wavelengths, potentially exploiting the existing world-wide infrastructures. For upscaling the experimental complexity in quantum networking, two-photon interference (TPI) of remote non-classical emitters in the low-loss telecom bands is of utmost importance. Several experiments have been conducted regarding TPI of distinct emitters, for example, using trapped atoms1, ions2, nitrogen vacancy centres3,4, silicon vacancy centres5, organic molecules6 and semiconductor quantum dots7,8. However, the spectral range was far from the highly desirable telecom C-band. Here, we exploit quantum frequency conversion to realize TPI at 1,550 nm with single photons stemming from two remote quantum dots. We thereby prove quantum frequency conversion9-11 as a bridging technology and a precise and stable mechanism to erase the frequency difference between independent emitters. On resonance, a TPI visibility of 29 ± 3% has been observed, limited only by the spectral diffusion processes of the individual quantum dots12,13. The local fibre network used covers several rooms between two floors of the building. Even the addition of up to 2 km of fibre channel shows no influence on the TPI visibility, proving the photon wavepacket distortion to be negligible. Our studies pave the way to establish long-distance entanglement distribution between remote solid-state emitters including interfaces with various quantum hybrid systems14-16.

Online low-field NMR spectroscopy for process control of an industrial lithiation reaction-automated data analysis.

Monitoring specific chemical properties is the key to chemical process control. Today, mainly optical online methods are applied, which require time- and cost-intensive calibration effort. NMR spectroscopy, with its advantage being a direct comparison method without need for calibration, has a high potential for enabling closed-loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and rough environments for process monitoring and advanced process control strategies. We present a fully automated data analysis approach which is completely based on physically motivated spectral models as first principles information (indirect hard modeling-IHM) and applied it to a given pharmaceutical lithiation reaction in the framework of the European Union's Horizon 2020 project CONSENS. Online low-field NMR (LF NMR) data was analyzed by IHM with low calibration effort, compared to a multivariate PLS-R (partial least squares regression) approach, and both validated using online high-field NMR (HF NMR) spectroscopy. Graphical abstract NMR sensor module for monitoring of the aromatic coupling of 1-fluoro-2-nitrobenzene (FNB) with aniline to 2-nitrodiphenylamine (NDPA) using lithium-bis(trimethylsilyl) amide (Li-HMDS) in continuous operation. Online 43.5 MHz low-field NMR (LF) was compared to 500 MHz high-field NMR spectroscopy (HF) as reference method.

"Click" analytics for "click" chemistry - A simple method for calibration-free evaluation of online NMR spectra.

Driven mostly by the search for chemical syntheses under biocompatible conditions, so called "click" chemistry rapidly became a growing field of research. The resulting simple one-pot reactions are so far only scarcely accompanied by an adequate optimization via comparably straightforward and robust analysis techniques possessing short set-up times. Here, we report on a fast and reliable calibration-free online NMR monitoring approach for technical mixtures. It combines a versatile fluidic system, continuous-flow measurement of 1H spectra with a time interval of 20s per spectrum, and a robust, fully automated algorithm to interpret the obtained data. As a proof-of-concept, the thiol-ene coupling between N-boc cysteine methyl ester and allyl alcohol was conducted in a variety of non-deuterated solvents while its time-resolved behaviour was characterized with step tracer experiments. Overlapping signals in online spectra during thiol-ene coupling could be deconvoluted with a spectral model using indirect hard modeling and were subsequently converted to either molar ratios (using a calibration-free approach) or absolute concentrations (using 1-point calibration). For various solvents the kinetic constant k for pseudo-first order reaction was estimated to be 3.9h-1 at 25°C. The obtained results were compared with direct integration of non-overlapping signals and showed good agreement with the implemented mass balance.

Model-based strategy for cell culture seed train layout verified at lab scale.

Cell culture seed trains-the generation of a sufficient viable cell number for the inoculation of the production scale bioreactor, starting from incubator scale-are time- and cost-intensive. Accordingly, a seed train offers potential for optimization regarding its layout and the corresponding proceedings. A tool has been developed to determine the optimal points in time for cell passaging from one scale into the next and it has been applied to two different cell lines at lab scale, AGE1.HN AAT and CHO-K1. For evaluation, experimental seed train realization has been evaluated in comparison to its layout. In case of the AGE1.HN AAT cell line, the results have also been compared to the formerly manually designed seed train. The tool provides the same seed train layout based on the data of only two batches.

Mechanistic insight from activation parameters for the reaction of a ruthenium hydride complex with CO2 in conventional solvents and an ionic liquid.

Detailed kinetic studies were performed on the reaction of [Ru(II)(terpy)(bpy)H](+) (terpy = 2,2',6',2″-terpyridine; bpy = 2,2'-bipyridine) with CO(2) in conventional solvents (water, methanol, and ethanol) and in the ionic liquid [emim][NTf(2)] ([emim] = 1-ethyl-3-methyl-imidazolium; [NTf(2)] = bistrifluoromethylsulfonylamide). Second-order rate constants and activation parameters (ΔH(‡), ΔS(‡), and ΔV(‡)) were determined for the reaction in all solvents. The second-order rate constants correlate with the acceptor number of the solvent, whereas the activation parameters support the associative nature of the reaction. The results in water, especially the activation entropy (+14 ± 2 J K(-1) mol(-1)) and activation volume (-5.9 ± 0.6 cm(3) mol(-1)), differ significantly from those found for the other solvents.

Fast substitution reactions of Pt(II) in different ionic liquids. reactivity control by anionic components.

The effect of several imidazolium-based ionic liquids on the rate and mechanism of the substitution reaction of [Pt(terpyridine)Cl](+) with thiocyanate was investigated as a function of thiocyanate concentration and temperature under pseudo-first-order conditions using stopped-flow and other kinetic techniques. The obtained rate constants and activation parameters showed good agreement with the ion-pair stabilization energies between the anions of the ionic liquids and the cationic Pt(II) complex derived from density-functional theory calculations (RB3LYP/LANL2DZp) and with parameters derived from the linear solvation energy relationship set by the Kamlet-Taft beta parameter, which is a measure of a solvent's hydrogen bonding acceptor ability. In general, the substitution reactions followed an associative mechanism as found for conventional solvents, but the observed rate constants showed a significant dependence on the nature of the anionic component of the ionic liquid used as solvent. The second order rate constant measured in [emim][NTf(2)] is 2000 times higher than the one measured in [emim][EtOSO(3)]. This difference is much larger than observed for a neutral entering nucleophile studied before.

Mechanistic studies on fast ligand substitution reactions of Pt(II) in different ionic liquids: role of solvent polarity and ion-pair formation.

The effect of several imidazolium-based ionic liquids on the mechanism of a classical ligand substitution reaction of [Pt(terpyridine)Cl] (+) with thiourea was investigated. A detailed kinetic study as a function of the nucleophile concentration and temperature was undertaken under pseudo-first-order conditions using stopped-flow techniques. Polarity measurements were performed for the employed ionic liquids on the basis of solvatochromic effects, and they show similarities with conventional polar solvents. Density-functional theory calculations (RB3LYP/LANL2DZp) were employed to predict the ion-pair stabilization energy between the ionic components of the ionic liquids and/or between the anions of the ionic liquids and the cationic Pt (II) complex. These data illustrate how the anions of the ionic liquids can affect the investigated substitution reaction. In general, the substitution mechanism in ionic liquids was found to have an associative character similar to that in conventional solvents. The observed deviations reflect the influence of the ionic liquid on the interaction between the anionic component of the liquid and the positively charged complex.

Rapid ligand substitution reactions in ionic liquids studied by stopped-flow technique.

Detailed kinetic studies on ligand substitution reactions of [M(II)(terpy)Cl](+) complexes (M = Pt, Pd; terpy = 2,2':6',2''-terpyridine) with thiourea as entering nucleophile were for the first time performed in the imidazolium based ionic liquid [emim][NTf(2)] using stopped-flow techniques, opening the route to study fast reactions of transition metal complexes in ionic liquids.