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This research employs two computational methods to simulate shear deformation of molecular crystals; it calculates slip barriers, finds rotational twinning, and predicts polymorphic transitions.

We demonstrate the successful application of the state-of-the-art AstraZeneca in-house and XtalPi cloud-based virtual polymorph screening workflows in support of stable form selection of crystallin...

The influence of milling diaqua-bis(omeprazolate)-magnesium dihydrate (DABOMD), an active pharmaceutical ingredient (API), was investigated. DABOMD was processed in a planetary ball mill at different milling times, from 1 to 300 min. The milling process resulted in a prominent comminution (size reduction) and amorphization of the API. DABOMD amorphization was identified with various characterization techniques including thermogravimetric analysis, differential scanning calorimetry, powder X-ray diffraction, and attenuated total reflection-Fourier transform infrared spectroscopy. The solid–solid crystalline to amorphous phase transformation is driven by compression, shear stresses, and heat generated in the planetary ball mill. This leads to distortion and breakage of hydrogen bonds, release of water molecules from the crystalline lattice of DABOMD and the accumulation of defects, and eventually a collapse of the crystalline order. Model fitting of the kinetics of comminution and the amorphization of DABOMD revealed a series of events: a rapid comminution at the start of milling driven by crystal cleavage of DABOMD, followed by partial amorphization, which is driven by rapid water diffusion, and subsequently, a slow steady comminution and amorphization.

Application of computational methods to understanding and predicting properties of analogues for drug discovery has enjoyed a long history of success. However, the drug development space (post-cand...

RATIONALE: Aggression, comorbid with neuropsychiatric disorders, exhibits with diverse clinical presentations and places a significant burden on patients, caregivers and society. This diversity is observed because aggression is a complex behavior that can be ethologically demarcated as either appetitive (rewarding) or reactive (defensive), each with its own behavioral characteristics, functionality, and neural basis that may transition from adaptive to maladaptive depending on genetic and environmental factors. There has been a recent surge in the development of preclinical animal models for studying appetitive aggression-related behaviors and identifying the neural mechanisms guiding their progression and expression. However, adoption of these procedures is often impeded by the arduous task of manually scoring complex social interactions. Manual observations are generally susceptible to observer drift, long analysis times, and poor inter-rater-reliability, and are further incompatible with the sampling frequencies required of modern neuroscience methods. OBJECTIVES: In this review we discuss recent advances in the preclinical study of appetitive aggression in mice, paired with our perspective on the potential for machine learning techniques in producing automated, robust, scoring of aggressive social behavior. We discuss critical considerations for implementing valid computer classifications within behavioral pharmacological studies. KEY RESULTS: Open-source automated classification platforms can match or exceed the performance of human observers, while removing the confounds of observer drift, bias, and inter-rater reliability. Furthermore, unsupervised approaches can identify previously uncharacterized aggression-related behavioral repertoires in model species. DISCUSSION AND CONCLUSIONS: Advances in open source computational approaches hold promise for overcoming current manual annotation caveats while also introducing and generalizing computational neuroethology to the greater behavioral neuroscience community. We propose that currently available open-source approaches are sufficient for overcoming the main limitations preventing wide adoption of machine learning within the context of pre-clinical aggression behavioral research.

An l-proline cocrystal of celecoxib was identified based on a computational approach for predicting crystal mechanical properties in order to significantly reduce the punch sticking propensity of c...

The report presents findings from a workshop where researchers, students, tourism industry representatives, policy makers and entrepreneurs from the Arctic discussed the challenges of overtourism, the impact of COVID-19 and visions for restarting tourism. A key for sustainable management of tourism is that actors are aware that they are part of a wide ranging tourism system that affects how they can tackle ensuing crisis or challenges such as overtourism and undertourism. The COVID-19 hit tourism hard across the Arctic although there are also regional differences. The pandemic revealed the vulnerability of the tourism product and opened a space for reconsidering tourism growth and the negative impacts of tourism on climate, biodiversity and communities. The report argues for the need to build tourism based on tourism-community collaboration.

In electrochemical energy storage devices (ESDs), organic electrolytes are typically used for wide operational potential window, yet they suffer with cost, environmental, flammability issues, and low ionic conductivity when compared with water-based electrolytes. Hence, for large-scale applications that require high power and safety, presently there is no true solution. Though water-based electrolytes have higher ionic conductivities, and are cost-effective and nonflammable, their high self-discharge rate with organic/carbon-based electrodes impedes their commercialization. It is found out that highly concentrated polymer electrolytes on the concept of "water-in-salt electrolyte" lead to extremely low leakage current within the electrochemical stability window (ESW) of water, thus solving the issue of self-discharge in organic/carbon-based ESDs. Herein, potassium polyacrylate (PAAK) is prepared as "water-in-polymer salt electrolyte" (WIPSE) and tested for one of most abundant wood-based biopolymer lignin and polyimide as positive and negative electrodes, respectively, in both half-cell and full-cell. The device shows an open-circuit voltage drops Funding Agencies|Proof-of-Concept project "Paper Batteries" - Knut and Alice Wallenberg (KAW) foundation; "high-voltage aqueous electrolytes" - Knut and Alice Wallenberg (KAW) foundation; "Wood Wallenberg Science Center" - Knut and Alice Wallenberg (KAW) foundation; Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linkoping University [2009-00971]; Wallenberg Scholar grants from KAW

The European North has long attracted travelers, the selling point often being the availability of nature and wilderness. Recent developments, however, suggest a greater variety of tourism motivations, including new products such as dogsled tours, aurora borealis watching, snowmobiling, and stays at ice hotels. Many of these firms use names containing the term ‘Arctic' or similar terminology related to imaginations of the Far North. The chosen terminology is considered one example of the process of ‘Arctification'. However, there is a limitation in descriptive knowledge about the overall Arctification of the region’s tourism industry. Hence, this article aims to illustrate the Arctification of the tourism industry by mapping the changing geographies of firm names. Through its results, the study aims to contribute an understanding of how firm naming is part of the tourism production, and how this influences the reimaging and delineation of regions. The study uses a descriptive quantitative approach, extracting data from the Retriever Business database. The results show a clear development of tourism firms increasingly using Arctic terminology in their firm names. Also, the tourism firms’ locations show patterns of spatial differences related to the region’s natural environment, population density, infrastructure, and the firms’ age.

This work presents an updated solid-form discovery approach to the polymorphism of the antiarrhythmic drug mexiletine hydrochloride, in which experimental and computational techniques are combined to provide a rigorous characterization of the solid-form landscape of this compound. The resulting solid forms were characterized by powder and single-crystal X-ray diffraction, IR spectroscopy, differential scanning calorimetry, and 13C solid-state NMR. This approach reveals five solid-form types of mexiletine hydrochloride. Forms 1, 2, and 3 are mutually enantiotropically related anhydrous polymorphs, with Form 1 the room temperature stable form, Form 2 the high-temperature form, and Form 3 the thermodynamically stable polymorph between 148 and 167 °C. The final two forms termed Types A and B comprise two large families of isomorphous channel solvates, including a fourth nonsolvated form isostructural to the Type A solvates. We report 11 modifications of each solvate, in which a diverse range of solvents are included in the channels, without changing the fundamental structure of the drug framework. These experimental results go hand-in-hand with computational crystal structure prediction (using the AstraZeneca crystal structure prediction approach), which together suggest that it is unlikely further nonsolvated forms, at least with Z′ = 1, will be discovered under ambient conditions.

This paper discusses in what sense an over-represented multi-word pattern in a corpus of translated texts can be said to be typical of translated text. The purpose of the discussion is to assess, from a quantitative as well as from a qualitative perspective, the status of translational collocation data retrieved through data-driven methods from a comparable and parallel aligned cor¬pus of English and Swedish original and translated texts. The study focuses on the explicitation of clausal relations in translations from English into Swedish. In some cases, lexical and grammatical contrast lead to explicita¬tion, but in others explicitation is due to different factors.

Pharmaceuticals in their crystalline state may display a range of dynamics that can affect their physicochemical properties and chemical stability. With pharmaceutical cocrystals continuing to gain attention, there is an opportunity to investigate how the dynamics are changing in these new solid forms. Here, we investigate the dynamics in efavirenz, an anti-HIV drug, and a series of its cocrystals using a combination of DFT calculations and solid-state magic-angle spinning (MAS) NMR spectroscopy. We show that the crystalline form of efavirenz has a highly dynamic cyclopropyl group, and displays additional rocking motion. In contrast, the dynamics in the efavirenz cocrystals appear to be tamed, with the cyclopropyl group in the (efavirenz)(L-proline) cocrystal being the most constrained, and these constraints originating from a more favourable crystal packing in the cocrystals.

Funder: RCUK | Biotechnology and Biological Sciences Research Council (BBSRC); doi: https://doi.org/10.13039/501100000268, Funder: No personal funding for this project, Funder: GlaxoSmithKline foundation (GSK); doi: https://doi.org/10.13039/501100002066, Funder: Shionogi (Shionogi & Co. Ltd.); doi: https://doi.org/10.13039/501100005612, Impaired cognitive flexibility in visual reversal-learning tasks has been observed in a wide range of neurological and neuropsychiatric disorders. Although both human and animal studies have implicated striatal D2-like and D1-like receptors (D2R; D1R) in this form of flexibility, less is known about the contribution they make within distinct sub-regions of the striatum and the different phases of visual reversal learning. The present study investigated the involvement of D2R and D1R during the early (perseverative) phase of reversal learning as well as in the intermediate and late stages (new learning) after microinfusions of D2R and D1R antagonists into the nucleus accumbens core and shell (NAcC; NAcS), the anterior and posterior dorsomedial striatum (DMS) and the dorsolateral striatum (DLS) on a touchscreen visual serial reversal-learning task. Reversal learning was improved after dopamine receptor blockade in the nucleus accumbens; the D1R antagonist, SCH23390, in the NAcS and the D2R antagonist, raclopride, in the NAcC selectively reduced early, perseverative errors. In contrast, reversal learning was impaired by D2R antagonism, but not D1R antagonism, in the dorsal striatum: raclopride increased errors in the intermediate phase after DMS infusions, and increased errors across phases after DLS infusions. These findings indicate that D1R and D2R modulate different stages of reversal learning through effects localised to different sub-regions of the striatum. Thus, deficits in behavioral flexibility observed in disorders linked to dopamine perturbations may be attributable to specific D1R and D2R dysfunction in distinct striatal sub-regions.

Change initiatives in organizations often fail because people are neither committed to nor convinced they can implement the change successfully. The change challenge is a practical problem for most leaders. The vast literature on change management offers insights into obstacles to change and how to overcome them, and the emerging literature on readiness for change offers a plethora of instruments for how to assess it, though primarily in health care settings. However, there is limited advice about how to design workshops around new initiatives in organizations to increase readiness for change. To address this problem, we developed a model of the drivers of change readiness, based on survey data from 374 participants in 69 independently facilitated workshops to test hypotheses. The findings show which constructs have the most predictive power. These results have important implications for how to design and facilitate workshops that increase participants’ readiness for change. The study makes several contributions to the theory and practice of creating shared readiness for change.

A pharmaceutical exhibits differing dynamics in crystallographically distinct pyrrolidine rings despite being nearly related by symmetry, with one performing ring inversions while the other is constrained to torsional librations. Using 13C solid-state magic-angle spinning (MAS) NMR and DFT calculations, we show that this contrast originates from C-H···H-C close contacts and less efficient C-H···π intermolecular interactions observed in the transition state of the constrained pyrrolidine ring, highlighting the influence of the crystallographic environment on the molecular motion.\ud \ud

Rationale Dopamine D2-like receptors (D2R) are important drug targets in schizophrenia and Parkinson’s disease, but D2R ligands also cause cognitive inflexibility such as poor reversal learning. The specific role of D2R in reversal learning remains unclear. Objectives We tested the hypotheses that D2R agonism impairs reversal learning by blocking negative feedback and that antagonism of D1-like receptors (D1R) impairs learning from positive feedback. Methods Male Lister Hooded rats were trained on a novel visual reversal learning task. Performance on “probe trials”, during which the correct or incorrect stimulus was presented with a third, probabilistically rewarded (50% of trials) and therefore intermediate stimulus, revealed individual learning curves for the processes of positive and negative feedback. The effects of D2R and D1R agonists and antagonists were evaluated. A separate cohort was tested on a spatial probabilistic reversal learning (PRL) task after D2R agonism. Computational reinforcement learning modelling was applied to choice data from the PRL task to evaluate the contribution of latent factors. Results D2R agonism with quinpirole dose-dependently impaired both visual reversal and PRL. Analysis of the probe trials on the visual task revealed a complete blockade of learning from negative feedback at the 0.25 mg/kg dose, while learning from positive feedback was intact. Estimated parameters from the model that best described the PRL choice data revealed a steep and selective decrease in learning rate from losses. D1R antagonism had a transient effect on the positive probe trials. Conclusions D2R stimulation impairs reversal learning by blocking the impact of negative feedback. Electronic supplementary material The online version of this article (10.1007/s00213-019-05296-y) contains supplementary material, which is available to authorized users.

The micronization process of new compounds is usually performed based on an empirical basis with a limited understanding of input material properties and potential challenges. This study focuses on...

Aberrant social behavior is a core feature of many neuropsychiatric disorders, yet the study of complex social behavior in freely moving rodents is relatively infrequently incorporated into preclinical models. This likely contributes to limited translational impact. A major bottleneck for the adoption of socially complex, ethology-rich, preclinical procedures are the technical limitations for consistently annotating detailed behavioral repertoires of rodent social behavior. Manual annotation is subjective, prone to observer drift, and extremely time-intensive. Commercial approaches are expensive and inferior to manual annotation. Open-source alternatives often require significant investments in specialized hardware and significant computational and programming knowledge. By combining recent computational advances in convolutional neural networks and pose-estimation with further machine learning analysis, complex rodent social behavior is primed for inclusion under the umbrella of computational neuroethology.Here we present an open-source package with graphical interface and workflow (Simple Behavioral Analysis, SimBA) that uses pose-estimation to create supervised machine learning predictive classifiers of rodent social behavior, with millisecond resolution and accuracies that can out-perform human observers. SimBA does not require specialized video acquisition hardware nor extensive computational background. Standard descriptive statistical analysis, along with graphical region of interest annotation, are provided in addition to predictive classifier generation. To increase ease-of-use for behavioural neuroscientists, we designed SimBA with accessible menus for pre-processing videos, annotating behavioural training datasets, selecting advanced machine learning options, robust classifier validation functions and flexible visualizations tools. This allows for predictive classifier transparency, explainability and tunability prior to, and during, experimental use. We demonstrate that this approach is flexible and robust in both mice and rats by classifying social behaviors that are commonly central to the study of brain function and social motivation. Finally, we provide a library of poseestimation weights and behavioral predictive classifiers for resident-intruder behaviors in mice and rats. All code and data, together with detailed tutorials and documentation, are available on theSimBA GitHub repository.Graphical abstractSimBA graphical interface (GUI) for creating supervised machine learning classifiers of rodent social behavior.(a)Pre-process videos. SimBA supports common video pre-processing functions (e.g., cropping, clipping, sampling, format conversion, etc.) that can be performed either on single videos, or as a batch.(b)Managing poseestimation data and creating classification projects. Pose-estimation tracking projects in DeepLabCut and DeepPoseKit can be either imported or created and managed within the SimBA graphical user interface, and the tracking results are imported into SimBA classification projects.SimBA also supports userdrawn region-of-interests (ROIs) for descriptive statistics of animal movements, or as features in machine learning classification projects.(c)Create classifiers, perform classifications, and analyze classification data. SimBA has graphical tools for correcting poseestimation tracking inaccuracies when multiple subjects are within a single frame, annotating behavioral events from videos, and optimizing machine learning hyperparameters and discrimination thresholds. A number of validation checkpoints and logs are included for increased classifier explainability and tunability prior to, and during, experimental use. Both detailed and summary data are provided at the end of classifier analysis. SimBA accepts behavioral annotations generated elsewhere (such as through JWatcher) that can be imported into SimBA classification projects.(d)Visualize classification results. SimBA has several options for visualizing machine learning classifications, animal movements and ROI data, and analyzing the durations and frequencies of classified behaviors.See theSimBA GitHub repositoryfor a comprehensive documentation and user tutorials.

The crystal structure of diaquabis(omeprazolate)magnesium dihydrate (DABOMD) in the solid state has been determined using single-crystal X-ray diffraction. Single crystals of DABOMD were obtained by slow crystallization in ethanol with water used as an antisolvent. The crystal structure shows a dihydrated salt comprising a magnesium cation coordinating two omeprazolate anions and two water molecules (W1) that are strongly bound to magnesium. In addition, two further water molecules (W2) are more weakly hydrogen-bonded to the pyridine nitrogen atom of each omeprazolate anion. The crystal structure was utilized to estimate key material properties for DABOMD, including crystal habit and mechanical properties, which are required for improved understanding and prediction of the behaviour of particles during pharmaceutical processing such as milling. The results from the material properties calculations indicate that DABOMD exhibits a hexagonal morphology and consists of a flat slip plane through the (100) face. It can be classed as a soft material based on elastic constant calculation and exhibits a two-dimensional hydrogen-bonding framework. Based on the crystal structure, habit and mechanical properties, it is anticipated that DABOMD will experience large disorder accompanied by plastic deformation during milling.

Diels–Alder reactions have been accomplished with ethylene as the dienophile through the use of inverse-electron demand Diels–Alder chemistry. As a key aspect of the chemistry, the dienes are part of tri- or dicationic superelectrophilic systems. Theoretical calculations reveal that the highly charged superelectrophiles possess exceptionally low lying LUMOs, and this facilitates the cycloaddition chemistry with ethylene. The chemistry has been used to prepare a series of tetrahydroquinoline products. This represents the first application of superelectrophilic activation in a cycloaddition reaction, and a new method of utilizing ethylene as a C2 building block.

NMR crystallography is a powerful tool with applications in structural characterization and crystal structure verification, to name two. However, applying this tool presents several challenges, especially for industrial users, in terms of consistency, workflow, time consumption, and the requirement for a high level of understanding of experimental solid-state NMR and GIPAW-DFT calculations. Here, we have developed a series of fully parameterized scripts for use in Materials Studio and TopSpin, based on the .magres file format, with a focus on organic molecules (e.g. pharmaceuticals), improving efficiency, robustness, and workflow. We separate these tools into three major categories: performing the DFT calculations, extracting & visualizing the results, and crystallographic modelling. These scripts will rapidly submit fully parameterized CASTEP jobs, extract data from the calculations, assist in visualizing the results, and expedite the process of structural modelling. Accompanied with these tools is a description on their functionality, documentation on how to get started and use the scripts, and links to video tutorials for guiding new users. Through the use of these tools, we hope to facilitate NMR crystallography and to harmonize the process across users.

The key figure-of-merit for materials in stationary energy storage applications, such as large-scale energy storage for buildings and grids, is the cost per kilo per electrochemical cycle, rather than the energy density. In this regard, forest-based biopolymers such as lignin, are attractive, as they are abundant on Earth. Here, we explored lignin as an electroactive battery material, able to store two electrons per hydroquinone aromatic ring, with the targeted operation in aqueous electrolytes. The impact of the sulfonation level of lignin on the performance of its composite electrode with carbon was investigated by considering three lignin derivatives: lignosulfonate (LS), partially desulfonated lignosulfonate (DSLS), and fully desulfonated lignin (KL, lignin produced by the kraft process). Partial desulfonation helped in better stability of the composite in aqueous media, simultaneously favoring its water processability. In this way, a route to promote ionic conductivity within the lignin/carbon composite electrodes was developed, facilitating the access to the entire bulk of the volumetric electrodes. Electrochemical performance of DSLS/C showed highly dominant Faradaic contribution (66%) towards the total capacity, indicating an efficient mixed ionic-electronic transport within the lignin-carbon phase, displaying a capacity of 38 mAh/g at 0.25 A/g and 69% of capacity retention after 2200 cycles at a rate of 1 A/g.

Growth data and modulus of elasticity (MOE) of 11 different pine species and hybrids were examined at six sites in three regions in South Africa. Growth traits and three MOE variables were measured at three years of age in order to evaluate whether other potential pine species were more suitable than the current commercial species. There were strong observed species differences for all three MOE variables both within and across the four sites measured for wood properties, with across-site MOE ranging from 3.03 to 6.40 GPa. Green density varied among species, and an assumed constant green density of 1 000 kg m–3 underestimated MOE for species with a very high green density; similarly, for species with a very low green density, MOE was overestimated. Although survival was poor at several sites, the data shows that there are alternative pine species that exhibit comparable growth rates to the current commercial species. For estimating MOE, it is concluded that assuming a constant green density generally does not affect the species ranking, but if the aim is to find the ‘true’ MOE, sampling in the field to determine the appropriate green density is needed.

NMR crystallographic techniques are used to validate a structure of β-piroxicam determined from powder X-ray diffraction (PXRD) with a relatively poor R-factor. Geometry optimisation of PXRD- and single-crystal XRD- derived structures results in convergence to the same energy of the structures, with minimal atomic displacements, and good agreement of gauge-included projector augmented wave (GIPAW) calculated and experimentally determined NMR 1H, 13C and 15N chemical shifts and 14N quadrupolar parameters. Calculations on isolated molecules combined with 2D magic-angle spinning (MAS) 1H double-quantum (DQ) and 14N-1H NMR experiments confirm the 3D packing arrangement of β-piroxicam. NMR crystallography is shown to be an effective means of validating crystal structures that might otherwise be considered sceptically on the basis of diffraction data alone.\ud \ud

Unknown chromatographic peaks, potential impurities, were observed in a series of related compounds. This led to the identification and characterization of tautomeric equilibria. Structural elucidation was required to understand the potential impurity profile, thus impacting method development for quality control. In this work, characterization of the chemical structures, AZ13581258 and AZD5718, and equilibria of the tautomeric forms was performed using a range of advanced analytical techniques such as preparative chromatography, nuclear magnetic resonance (NMR), chromatographic detection by mass spectrometry (MS), MSMS, and ultraviolet spectroscopy (UV). Predictions using density functional theory (DFT) further explains and confirms the tautomer equilibria through predictions of reaction barrier energies, UV-spectra and NMR data. These investigations led to fully understand the impurity profile and to the development of a quality control method for AZD5718 drug substance and drug product. In conclusion, ring-chain tautomeric structures are predominately formed under acidic conditions, and the additional peaks observed in LC during organic impurity determination were found to originate from ring-chain closed tautomers in equilibria with the parent open form compound. Hence, the closed and open tautomer forms should all be considered as the same compound.

The crystal structure of the Form A polymorph of N-cyclopropyl-3-fluoro-4-methyl-5-[3-[[1-[2-[2-(methylamino) ethoxy] phenyl] cyclopropyl] amino]-2-oxo-pyrazin-1-yl] benzamide (i.e., AZD7624), determined using single-crystal X-ray diffraction (scXRD) at 100 K, contains two molecules in the asymmetric unit (Z' = 2) and has regions of local static disorder. This substance has been in phase IIa drug development trials for the treatment of chronic obstructive pulmonary disease, a disease which affects over 300 million people and contributes to nearly 3 million deaths annually. While attempting to verify the crystal structure using nuclear magnetic resonance crystallography (NMRX), we measured C-13 solid-state NMR (SSNMR) spectra at 295 K that appeared consistent with Z' = 1 rather than Z' = 2. To understand this surprising observation, we used multinuclear SSNMR (H-1, C-13, N-15), gauge-including projector augmented-wave density functional theory (GIPAW DFT) calculations, crystal structure prediction (CSP), and powder XRD (pXRD) to determine the room temperature crystal structure. Due to the large size of AZD7624 (ca. 500 amu, 54 distinct C-13 environments for Z' = 2), static disorder at 100 K, and (as we show) dynamic disorder at ambient temperatures, NMR spectral assignment was a challenge. We introduce a method to enhance confidence in NMR assignments by comparing experimental C-13 isotropic chemical shifts against site-specific DFT-calculated shift distributions established using CSP-generated crystal structures. The assignment and room temperature NMRX structure determination process also included measurements of C-13 shift tensors and the observation of residual dipolar coupling between C-13 and N-14. CSP generated ca. 90 reasonable candidate structures (Z' = 1 and Z' = 2), which when coupled with GIPAW DFT results, room temperature pXRD, and the assigned SSNMR data, establish Z' = 2 at room temperature. We find that the polymorphic Form A of AZD7624 is maintained at room temperature, although dynamic disorder is present on the NMR timescale. Of the CSP-generated structures, 2 are found to be fully consistent with the SSNMR and pXRD data; within this pair, they are found to be structurally very similar (RMSD16 = 0.30 angstrom). We establish that the CSP structure in best agreement with the NMR data possesses the highest degree of structural similarity with the scXRD-determined structure (RMSD16 = 0.17 angstrom), and has the lowest DFT-calculated energy amongst all CSP-generated structures with Z' = 2.

This is a study of coaching behaviors both as reported by executive coaches, consultants, and managers and by the coaches' clients. We present a conceptual model of coaching behaviors that is comprehensive, intuitive, and easily quantifiable. We then introduce a questionnaire, based on the model, that has been in use for several decades. The latest version of this Coaching Behaviors Questionnaire can help researchers generate evidence about perceived behaviors in the coaching relationship. In fact, we report on an initial large-scale study of coaching behaviors using the questionnaire among 537 coaches, 196 consultants, and 559 manager-coaches as well as 221 clients of coaching. The study demonstrates significant differences in perceived behavior by subjects who differ in age, gender, and nationality. Significant differences are also found for those that identify themselves as "managers" versus "consultants" versus "coaches" and for those looking at the behaviors from the other side of the relationship, the clients of coaching. Some of the differences can be attributed to the fact that more experienced coaches will perceive themselves to develop different coaching behaviors. It is shown how an instrument such as this could be used to have observers rate coaching behaviors and even, ultimately, assess the skills of those practicing such coaching behaviors.

A tetracationic electrophile has been generated in superacid and shown to undergo an arylation reaction with benzene. A cyclization product is also obtained in the absence of benzene, presumably from a tricationic intermediate. Using low-temperature NMR, the tetracationic species is directly observed from a FSO3H-SbF5-SO2ClF solution. Similar chemistry is described with a system involving penta- and tetracationic intermediates. These highly ionized structures and their chemistry were also examined by DFT calculation.

A new force field, here called AZ-FF, aimed at being used for crystal structure predictions, has been developed. The force field is transferable to a new type of chemistry without additional training or modifications. This makes the force field very useful in the prediction of crystal structures of new drug molecules since the time-consuming step of developing a new force field for each new molecule is circumvented. The accuracy of the force field was tested on a set of 40 drug-like molecules and found to be very good where observed crystal structures are found at the top of the ranked list of tentative crystal structures. Re-ranking with dispersion-corrected density functional theory (DFT-D) methods further improves the scoring. After DFT-D geometry optimization the observed crystal structure is found at the leading top of the ranking list. DFT-D methods and force field methods have been evaluated for use in predicting properties such as phase transitions upon heating, mechanical properties or intrinsic crystalline solubility. The utility of using crystal structure predictions and the associated material properties in risk assessment in connection with form selection in the drug development process is discussed.

Serotonin (5-hydroxytryptamine, or 5-HT) and 5-HT receptors are involved in a heterogeneous and interconnected set of neuropsychological processes that support aspects of cognition. One such aspect is cognitive flexibility that can be tested in experimental settings across species. Impaired cognitive flexibility is a clinically relevant hallmark of many neuropsychiatric disorders and appears to be related to imbalances in serotonergic neurotransmission. Translational endeavors have provided opportunities to understand etiologies and refine treatments for disorders characterized by cognitive inflexibility; such findings also present significant opportunities to demonstrate performance enhancements in healthy individuals. In this chapter we focus on pharmacological studies that indicate the relevance of 5-HT in cognitive flexibility in both human participants and experimental animals. This includes 5-HT depletion studies, which can show cross-species reproducibility in impairing cognitive flexibility. We discuss drug studies that target serotonergic transmission and show remarkable efficacy for improving cognitive flexibility in animals. Yet the effect on cognitive flexibility by methods aimed to reduce 5-HT availability has at times been equivocal, and we highlight potentially important caveats that may contribute to translational difficulties of the positive pharmacological effects in experimental animals. Future directions for experiments that may address such issues are discussed.

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Rationale Dysregulation of the serotonin (5-HT) system is a pathophysiological component in major depressive disorder (MDD), a condition closely associated with abnormal emotional responsivity to positive and negative feedback. However, the precise mechanism through which 5-HT tone biases feedback responsivity remains unclear. 5-HT2C receptors (5-HT2CRs) are closely linked with aspects of depressive symptomatology, including abnormalities in reinforcement processes and response to stress. Thus, we aimed to determine the impact of 5-HT2CR function on response to feedback in biased reinforcement learning. Methods We used two touchscreen assays designed to assess the impact of positive and negative feedback on probabilistic reinforcement in mice, including a novel valence-probe visual discrimination (VPVD) and a probabilistic reversal learning procedure (PRL). Systemic administration of a 5-HT2CR agonist and antagonist resulted in selective changes in the balance of feedback sensitivity bias on these tasks. Results Specifically, on VPVD, SB 242084, the 5-HT2CR antagonist, impaired acquisition of a discrimination dependent on appropriate integration of positive and negative feedback. On PRL, SB 242084 at 1 mg/kg resulted in changes in behaviour consistent with reduced sensitivity to positive feedback. In contrast, WAY 163909, the 5-HT2CR agonist, resulted in changes associated with increased sensitivity to positive feedback and decreased sensitivity to negative feedback. Conclusions These results suggest that 5-HT2CRs tightly regulate feedback sensitivity bias in mice with consequent effects on learning and cognitive flexibility and specify a framework for the influence of 5-HT2CRs on sensitivity to reinforcement. Electronic supplementary material The online version of this article (10.1007/s00213-018-4907-7) contains supplementary material, which is available to authorized users.