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This paper explores the application of affect control theory (ACT) to the study of morality. A concise statement of ACT sets the stage for presenting examples of applying the theory to morality. This includes exploring the moral implications or overtones of social concepts (social identities, behaviors, traits, and settings); computer simulations of impressions created by moral and immoral events; and a discussion of several studies directly applying ACT to morality. The paper concludes with a detailed discussion of what ACT can contribute to moral psychology and the sociology of morality.

Compartmentalized chemical reactions at the microscale are important in biotechnology, yet monitoring the molecular content at these small scales is challenging. To address this challenge, we integrate a compact, reconfigurable reaction cell featuring electrochemical functionality with high‐resolution NMR spectroscopy. We demonstrate the operation of this system by monitoring the activity of enzymes immobilized in chemically distinct layers within a multi‐layered chitosan hydrogel assembly. As a benchmark, we observed the parallel activities of urease (Urs), catalase (Cat), and glucose oxidase (GOx) by monitoring reagent and product concentrations in real‐time. Simultaneous monitoring of an independent enzymatic process (Urs) together with a cooperative process (GOx + Cat) was achieved, with chemical conversion modulation of the GOx + Cat process demonstrated by varying the order in which the hydrogel was assembled., We integrate a compact, reconfigurable reaction cell featuring electrochemical functionality with high‐resolution NMR spectroscopy. This system is used to monitor the activity of enzymes immobilized in chemically distinct layers within a multi‐layered chitosan hydrogel assembly. We observed the parallel activities of urease, catalase, and glucose oxidase by monitoring reagent and product concentrations in real‐time.

Combining microfluidic devices with nuclear magnetic resonance (NMR) has the potential of unlocking their vast sample handling and processing operation space for use with the powerful analytics provided by NMR. One particularly challenging class of integrated functional elements from the perspective of NMR are conductive structures. Metallic electrodes could be used for electrochemical sample interaction for example, yet they can cause severe NMR spectral and SNR degradation. These issues are more entangled at the micro-scale since the distorted volume occupies a higher ratio of the sample volume. In this study, a combination of simulation and experimental validation was used to identify an electrode geometry that, in terms of NMR spectral parameters, performs as well as for the case when no electrodes are present. By placing the metal tracks in the side-walls of a microfluidic channel, we found that NMR RF excitation performance was actually enhanced, without compromising B0 homogeneity. Monitoring in situ deposition of chitosan in the microfluidic platform is presented as a proof-of-concept demonstration of NMR characterisation of an electrochemical process.

A labeling strategy for in vivo $^{19}$F-MRI (magnetic resonance imaging) based on highly fluorinated, short hydrophilic peptide probes, is developed. As dual-purpose probes, they are functionalized further by a fluorophore and an alkyne moiety for bioconjugation. High fluorination is achieved by three perfluoro-tert-butyl groups, introduced into asparagine analogues by chemically stable amide bond linkages. d-amino acids and β-alanine in the sequences endow the peptide probes with low cytotoxicity and high serum stability. This design also yielded unstructured peptides, rendering all 27 $^{19}$F substitutions chemically equivalent, giving rise to a single $^{19}$F-NMR resonance with

Band selectivity to address specific resonances in a spectrum enables one to encode individual settings for diffusion experiments. In a single experiment, this could include different gradient strengths (enabling coverage of a larger range of diffusion constants), different diffusion delays, or different gradient directions (enabling anisotropic diffusion measurement). In this report a selective variant of the bipolar pulsed gradient, eddy-current delay (BPP-LED) experiment enabling selective encoding of three resonances was implemented. As proof-of-principle, the diffusion encoding gradient amplitude was assigned a range dependent on the selected signal, thereby allowing the extraction of the diffusion coefficient for water and a tripeptide (Met-Ala-Ser) with optimal settings in a single experiment.

In this prospective paper we consider the opportunities and challenges of miniaturized nuclear magnetic resonance. As the title suggests, (irreverently borrowing from E.F. Schumacher's famous book), miniaturized NMR will feature a few small windows of opportunity for the analyst. We look at what these are, speculate on some open opportunities, but also comment on the challenges to progress., 9 pages, 4 figures, Accept 2019 Journal of Magnetic Resonance

Nuclear magnetic resonance at low field strength is an insensitive spectroscopic technique, precluding portable applications with small sample volumes, such as needed for biomarker detection in body fluids. Here we report a compact double resonant chip stack system that implements in situ dynamic nuclear polarisation of a 130 nL sample volume, achieving a signal enhancement of 54 w.r.t. the thermal equilibrium level at a microwave power level of 0.5W. This work overcomes instrumental barriers to the use of NMR detection for point-of-care applications.

Compartmentalized chemical reactions at the microscale are interesting from many perspectives including (multi)functional surfaces and biotechnology. Monitoring the molecular content as a measure of functional performance at these small scales is challenging. As a means to address this challenge, we leverage microtechnology and biocompatible materials to integrate a compact, reconfigurable reaction cell featuring electrochemical functionality with high-resolution nuclear magnetic resonance spectroscopy (NMR). We demonstrate the operation of this system by monitoring the activity of enzymes immobilized in chemically distinct layers within a multi-layered chitosan hydrogel assembly. As a benchmark, we observed the parallel activities of urease (Urs), catalase (Cat), and glucose oxidase (GOx) by recording NMR spectra to extract reagent and product concentrations in real-time. As a result, simultaneous monitoring of a cooperative enzymatic process (GOx + Cat) together with an independent process (Urs) is achieved. Using Michaelis-Menten progress curve analysis of the NMR data, kinetic data is extracted: in the case of GOx, the Michaelis constants (KM) are consistent with previous reports, while for Urs, deviations are observed, attributed to an inhibitory effect under our reaction conditions. The system therefore enables the construction of complex reaction cascades with spatial control, as would be interesting in, for example, metabolic engineering and multiplexed sensing applications.

Nuclear magnetic resonance at low field strength is an insensitive spectroscopic technique, precluding portable applications with small sample volumes, such as needed for biomarker detection in body fluids. Here we report a compact double resonant chip stack system that implements in situ dynamic nuclear polarisation of a 130 nL sample volume, achieving signal enhancements of up to − 60 w.r.t. the thermal equilibrium level at a microwave power level of 0.5 W. This work overcomes instrumental barriers to the use of NMR detection for point-of-care applications.

BackgroundThe novel coronavirus SARS-CoV-2 (COVID-19) emerged in December 2019 in Wuhan, China and has spread since then to around 210 countries and territories by April 2020. Consequently, countries have adopted physical distance measures in an attempt to mitigate the uncontrolled spread of the virus. A critical question for policymakers to inform evidence-based practice is if and how physical distance measures slowed the propagation of COVID-19 in the early phase of the pandemic.MethodsThis study aims to quantify the effects of physical distance mitigation measures on the propagation of the COVID-19 pandemic. Data from John Hopkins University on confirmed cases and testing data from the Our World in Data were used in an interrupted time series analysis to estimate the effects of physical distance measures on the growth rates of the pandemic in 12 countries of Asia, Africa, and Europe.FindingsWe found that physical distance measures produced a significant decrease in the growth rates of the COVID-19 pandemic in five countries (Austria, Belgium, Italy, Malaysia, and South Korea). The test-positivity rate was significant in understanding the slowing growth rate of COVID-19 cases caused by the mitigation measures, as it provides important context that is missing from analysis based only on confirmed case data.InterpretationPhysical distance interventions effectively slowed the progression of the COVID-19 pandemic. The results of this study could inform infectious disease mitigation policies based on physical distance measures by quantifying the differential health outcomes of a pandemic with and without physical distance interventions.RESEARCH IN CONTEXTEvidence before this studyThe SARS-CoV-2 is a new virus identified in December 2019 in the province of Wuhan, China and as never before, a remarkable number of studies and reports have been released since the start of the pandemic. Several studies have used confirmed COVID-19 cases to estimate the growth rate of the pandemic. However, many studies have discussed limitations of including only confirmed cases attributable to the lack of information about testing protocols and testing rates among different countries. Finally, some researchers proposed the analysis of reported deaths by COVID-19 as a potential solution. However, this metric results in biased estimates because deaths by COVID-19 are known to be underreported.Added value of this studyWe designed and implemented analytic methods based on our previous research applied to different infectious disease epidemics, to add evidence related to the impact of non-pharmaceutical containment strategies on the temporal progression of the COVID-19 pandemic. Specifically, this study adds quantitative evidence about the effects of physical distance measures on limiting the propagation of COVID-19 pandemics in different countries. Additionally, we included testing data in the analysis to assess intra- and inter-country variation in testing growth rates. We hypothesized that the test-positivity rate is an approximation to the incidence of the COVID-19 pandemics in countries with high testing rates. Additionally, we hypothesize that a significant decrease in the pandemic over time could be identified by a significant decrease in the confirmed cases along with a significant decrease in the test-positivity rate. Our results quantified the potential effects of physical distance interventions on the COVID-19 pandemic progression under different levels of testing and enforcement of mitigation policies.Implications of all the available evidenceOur analysis could lead to better approaches for estimating the effects of physical distance measures on the time course of infectious diseases. In addition, our analysis highlights the potential bias of estimated COVID-19 growth rates based only on confirmed cases. The results from our study could inform strategies for mitigating the COVID-19 or other future pandemics, especially in countries in an earlier stage of a pandemic.

We implemented continuous-flow SABRE NMR spectroscopy on a chip, unlocking low-volume chemosensing of strongly diluted analytes., Complex mixtures, commonly encountered in metabolomics and food analytics, are now routinely measured by nuclear magnetic resonance (NMR) spectroscopy. Since many samples must be measured, one-dimensional proton (1D 1H) spectroscopy is the experiment of choice. A common challenge in complex mixture 1H NMR spectroscopy is spectral crowding, which limits the assignment of molecular components to those molecules in relatively high abundance. This limitation is exacerbated when the sample quantity itself is limited and concentrations are reduced even further during sample preparation for routine measurement. To address these challenges, we report a novel microfluidic NMR platform integrating signal enhancement via parahydrogen induced hyperpolarisation. The platform simultaneously addresses the challenges of handling small sample quantities through microfluidics, the associated decrease in signal given the reduced sample quantity by Signal Amplification by Reversible Exchange (SABRE), and overcoming spectral crowding by taking advantage of the chemosensing aspect of the SABRE effect. SABRE at the microscale is enabled by an integrated PDMS membrane alveolus, which provides bubble-free hydrogen gas contact with the sample solution. With this platform, we demonstrate high field NMR chemosensing of microliter sample volumes, nanoliter detection volumes, and micromolar concentrations corresponding to picomole molecular sensitivity.

Magnetic resonance tomography typically applies the Fourier transform to k-space signals repeatedly acquired from a frequency encoded spatial region of interest, therefore requiring a stationary object during scanning. Any movement of the object results in phase errors in the recorded signal, leading to deformed images, phantoms, and artifacts, since the encoded information does not originate from the intended region of the object. However, if the type and magnitude of movement is known instantaneously, the scanner or the reconstruction algorithm could be adjusted to compensate for the movement, directly allowing high quality imaging with non-stationary objects. This would be an enormous boon to studies that tie cell metabolomics to spontaneous organism behaviour, eliminating the stress otherwise necessitated by restraining measures such as anesthesia or clamping. In the present theoretical study, we use a phantom of the animal model C. elegans to examine the feasibility to automatically predict its movement and position, and to evaluate the impact of movement prediction, within a sufficiently long time horizon, on image reconstruction. For this purpose, we use automated image processing to annotate body parts in freely moving C. elegans, and predict their path of movement. We further introduce an MRI simulation platform based on bright field videos of the moving worm, combined with a stack of high resolution transmission electron microscope (TEM) slice images as virtual high resolution phantoms. A phantom provides an indication of the spatial distribution of signal-generating nuclei on a particular imaging slice. We show that adjustment of the scanning to the predicted movements strongly reduces distortions in the resulting image, opening the door for implementation in a high-resolution NMR scanner., PLoS Computational Biology, 15 (12), ISSN:1553-734X, ISSN:1553-7358

Detection of prostate cancer (PCa) and distinguishing indolent versus aggressive forms of the disease is a critical clinical challenge. The current clinical test is circulating prostate-specific antigen levels, which faces particular challenges in cancer diagnosis in the range of 4 to 10 ng/mL. Thus, a concerted effort toward building a noninvasive biomarker panel has developed. In this report, the hypothesis that nuclear magnetic resonance (NMR)-derived metabolomic profiles measured in the urine of biopsy-negative versus biopsy-positive individuals would nominate a selection of potential biomarker signals was investigated. 1H NMR spectra of urine samples from 317 individuals (111 biopsy-negative, 206 biopsy-positive) were analyzed. A double cross-validation partial least squares-discriminant analysis modeling technique was utilized to nominate signals capable of distinguishing the two classes. It was observed that after variable selection protocols were applied, a subset of 29 variables produced an area under the curve (AUC) value of 0.94 after logistic regression analysis, whereas a “master list” of 18 variables produced a receiver operating characteristic ROC) AUC of 0.80. As proof of principle, this study demonstrates the utility of NMR-based metabolomic profiling of urine biospecimens in the nomination of PCa-specific biomarker signals and suggests that further investigation is certainly warranted.

We describe a novel stacked split-ring type microwave (MW) resonator that is integrated into a 10 mm by 10 mm sized microfluidic chip. A straightforward and scalable batch fabrication process renders the chip suitable for single-use applications. The resonator volume can be conveniently loaded with liquid sample via microfluidic channels patterned into the mid layer of the chip. The proposed MW resonator offers an alternative solution for compact in-field measurements, such as low-field magnetic resonance (MR) experiments requiring convenient sample exchange. A microstrip line was used to inductively couple MWs into the resonator. We characterised the proposed resonator topology by electromagnetic (EM) field simulations, a field perturbation method, as well as by return loss measurements. Electron paramagnetic resonance (EPR) spectra at X-band frequencies were recorded, revealing an electron-spin sensitivity of View the MathML source3.7·1011spins·Hz-1/2G-1 for a single EPR transition. Preliminary time-resolved EPR experiments on light-induced triplet states in pentacene were performed to estimate the MW conversion efficiency of the resonator.

Nuclear magnetic resonance based measurements of small molecule mixtures continues to be confronted with the challenge of spectral assignment. While multi-dimensional experiments are capable of addressing this challenge, the imposed time constraint becomes prohibitive, particularly with the large sample sets commonly encountered in metabolomic studies. Thus, one-dimensional spectral assignment is routinely performed, guided by two-dimensional experiments on a selected sample subset; however, a publicly available graphical interface for aiding in this process is currently unavailable. We have collected spectral information for 360 unique compounds from publicly available databases including chemical shift lists and authentic full resolution spectra, supplemented with spectral information for 25 compounds collected in-house at a proton NMR frequency of 900 MHz. This library serves as the basis for MetaboID, a Matlab-based user interface designed to aid in the one-dimensional spectral assignment process. The tools of MetaboID were built to guide resonance assignment in order of increasing confidence, starting from cursory compound searches based on chemical shift positions to analysis of authentic spike experiments. Together, these tools streamline the often repetitive task of spectral assignment. The overarching goal of the integrated toolbox of MetaboID is to centralize the one dimensional spectral assignment process, from providing access to large chemical shift libraries to providing a straightforward, intuitive means of spectral comparison. Such a toolbox is expected to be attractive to both experienced and new metabolomic researchers as well as general complex mixture analysts.

The in vivo analysis of a model organism, such as the nematode Caenorhabditis elegans, en‐ ables fundamental biomedical studies, including development, genetics, and neurobiolo‐ gy. In recent years, microfluidics technology has emerged as an attractive and enabling tool for the study of the multicellular organism. Advances in the application of microflui‐ dics to C. elegans assays facilitate the manipulation of nematodes in high-throughput for‐ mat and allow for the precise spatial and temporal control of their environment. In this chapter, we aim to illustrate the current microfluidic approaches for the investigation of behavior and neurobiology in C. elegans and discuss the trends of future development.

We present a completely revised generation of a modular micro-NMR detector, featuring an active sample volume of ��� 100 nL, and an improvement of 87% in probe efficiency. The detector is capable of rapidly screening different samples using exchangeable, applicationspecific, MEMS-fabricated, microfluidic sample containers. In contrast to our previous design, the sample holder chips can be simply sealed with adhesive tape, with excellent adhesion due to the smooth surfaces surrounding the fluidic ports, and so withstand pressures of ���2.5 bar, while simultaneously enabling high spectral resolution up to 0.62 Hz for H2 O, due to its optimised geometry. We have additionally reworked the coil design and fabrication processes, replacing liquid photoresists by dry film stock, whose final thickness does not depend on accurate volume dispensing or precise levelling during curing. We further introduced mechanical alignment structures to avoid time-intensive optical alignment of the chip stacks during assembly, while we exchanged the laser-cut, PMMA spacers by diced glass spacers, which are not susceptible to melting during cutting. Doing so led to an overall simplification of the entire fabrication chain, while simultaneously increasing the yield, due to an improved uniformity of thickness of the individual layers, and in addition, due to more accurate vertical positioning of the wirebonded coils, now delimited by a post base plateau. We demonstrate the capability of the design by acquiring a1 H spectrum of ��� \11 nmol sucrose dissolved in D2 O, where we achieved a linewidth of 1.25 Hz for the TSP reference peak. Chemical shift imaging experiments were further recorded from voxel volumes of only ��� 1.5nL, which corresponded to amounts of just 1.5 nmol per voxel for a 1 M concentration. To extend the micro-detector to other nuclei of interest, we have implemented a trap circuit, enabling heteronuclear spectroscopy, demonstrated by two 1H/13 C 2D HSQC experiments. �� 2016 Spengler et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

In an effort to address the variable correspondence problem across large sample cohorts common in metabolomic/metabonomic studies, we have developed a prealignment protocol that aims to generate spectral segments sharing a common target spectrum. Under the assumption that a single reference spectrum will not correctly represent all spectra of a data set, the goal of this approach is to perform local alignment corrections on spectral regions which share a common "most similar" spectrum. A natural beneficial outcome of this procedure is the automatic definition of spectral segments, a feature that is not common to all alignment methods. This protocol is shown to specifically improve the quality of alignment in (1)H NMR data sets exhibiting large intersample compositional variation (e.g., pH, ionic strength). As a proof-of-principle demonstration, we have utilized two recently developed alignment algorithms specific to NMR data, recursive segment-wise peak alignment and interval correlated shifting, and applied them to two data sets composed of 15 aqueous cell line extract and 20 human urine (1)H NMR profiles. Application of this protocol represents a fundamental shift from current alignment methodologies that seek to correct misalignments utilizing a single representative spectrum, with the added benefit that it can be appended to any alignment algorithm.

The metabolism of an organism is regulated at the cellular level, yet is strongly influenced by its environment. The precise metabolomic study of living organisms is currently hampered by measurement sensitivity; most metabolomic measurement techniques involve some compromise, whereby averaging is performed over a volume significantly larger than a single cell, or require the invasion of the organism, or an arrested state of the organism. Nuclear magnetic resonance (NMR) is an inherently noninvasive chemometric and imaging method, and hence, in principle, suitable for metabolomic measurements. The digital twin of metabolomics is computational systems biology, such that NMR microscopy is potentially a viable approach to joining the theoretical and experimental explorations of the metabolomic and behavioural responses of organisms. In this study, we consider the challenge of performing in vivo NMR-based metabolomics on the small organism Caenorhabditis elegans, point he way towards possible solutions created using techniques specific to micro-electromechanical systems (MEMS) fabrication, and highlight currently insurmountable challenges.

3D glassy carbon structures with percolated macropores are obtained by pyrolysis of chemically synthesized cryogels featuring tunable porosity. These batch-fabricated structures are used as scaffolds for culturing neural stem cells (NSCs) and are characterized by magnetic resonance imaging (MRI). With the aid of MRI, the successful cultivation of NSCs on a glassy carbon surface and the precise 3D locations of these cell clusters within the opaque scaffold are demonstrated. MRI also yields pore morphology and porosity analyses, pre- and post-pyrolysis. This integrated approach yields a complete 3D dataset of the NSC network, which enables the visual inspection of the morphological details of individual cell clusters without disturbing them or destroying the scaffold. Reported experimental methodology is expected to have an impact on studies designed to understand the mechanism of neurodegenerative disease (ND) development, and can serve as a protocol for the culture of various other types of cells that display compatibility with glassy carbon surfaces.

Carbon is conventionally not associated with magnetism, causing much of the discussion of its perspectives in nanotechnology to be centred on its electron-transport properties. Among the few existing examples of magnetic carbon production, none has found a direct route into scalable micro- and nanofabrication. Here we introduce a magnetic form of carbon whose precursor polymers can be lithographically patterned into micro- and nano-structures prior to pyrolysis. This unreactive and thermally robust material features a strong, room-temperature magnetism owing to a large number of unpaired electron spins with restricted mobility, which is achieved by controlling the progression of bond dissociation and formation during pyrolysis. The micro-manufacture of pyrolytic magnetic carbon, having (3.5±0.7)×1015 spins/mg, can immediately benefit a number of spintronic and magnetic-microelectromechanical system applications, and the fabrication of composite magnetic materials. The material could also complement the magnetic resonance spectroscopy and imaging techniques. Additionally, this contribution sheds light on the controversial theories concerning the existence and mechanism of magnetic phenomena in carbon.

The hierarchical heterogeneous architecture of bone imposes significant challenges to structural and dynamic studies conducted by traditional biophysical techniques. High-resolution solid-state nuclear magnetic resonance (SSNMR) spectroscopy is capable of providing detailed atomic-level structural insights into such traditionally challenging materials. However, the relatively long data-collection time necessary to achieve a reliable signal-to-noise ratio (S/N) remains a major limitation for the widespread application of SSNMR on bone and related biomaterials. In this study, we attempt to overcome this limitation by employing the paramagnetic relaxation properties of copper(II) ions to shorten the (1)H intrinsic spin-lattice (T(1)) relaxation times measured in natural-abundance (13)C cross-polarization (CP) magic-angle-spinning (MAS) NMR experiments on bone tissues for the purpose of accelerating the data acquisition time in SSNMR. To this end, high-resolution solid-state (13)C CPMAS experiments were conducted on type I collagen (bovine tendon), bovine cortical bone, and demineralized bovine cortical bone, each in powdered form, to measure the (1)H T(1) values in the absence and in the presence of 30 mM Cu(II)(NH(4))(2)EDTA. Our results show that the (1)H T(1) values were successfully reduced by a factor of 2.2, 2.9, and 3.2 for bovine cortical bone, type I collagen, and demineralized bone, respectively, without reducing the spectral resolution and thus enabling faster data acquisition. In addition, paramagnetic quenching of particular (13)C NMR resonances on exposure to Cu(2+) ions in the absence of mineral was also observed, potentially suggesting the relative proximity of three main amino acids in the protein backbone (glycine, proline, and alanine) to the bone mineral surface.

A better understanding of molecular pathways involved in malignant transformation of head and neck squamous cell carcinoma (HNSCC) is essential for the development of novel and efficient anti-cancer drugs. To delineate the global metabolism of HNSCC, we report (1)H NMR-based metabolic profiling of HNSCC cells from five different patients that were derived from various sites of the upper aerodigestive tract, including the floor of mouth, tongue and larynx. Primary cultures of normal human oral keratinocytes (NHOK) from three different donors were used for comparison. (1)H NMR spectra of polar and non-polar extracts of cells were used to identify more than thirty-five metabolites. Principal component analysis performed on the NMR data revealed a clear classification of NHOK and HNSCC cells. HNSCC cells exhibited significantly altered levels of various metabolites that clearly revealed dysregulation in multiple metabolic events, including Warburg effect, oxidative phosphorylation, energy metabolism, TCA cycle anaplerotic flux, glutaminolysis, hexosamine pathway, osmo-regulatory and anti-oxidant mechanism. In addition, significant alterations in the ratios of phosphatidylcholine/lysophosphatidylcholine and phosphocholine/glycerophosphocholine, and elevated arachidonic acid observed in HNSCC cells reveal an altered membrane choline phospholipid metabolism (MCPM). Furthermore, significantly increased activity of phospholipase A(2) (PLA(2)), particularly cytosolic PLA(2) (cPLA(2)) observed in all the HNSCC cells confirm an altered MCPM. In summary, the metabolomic findings presented here can be useful to further elucidate the biological aspects that lead to HNSCC, and also provide a rational basis for monitoring molecular mechanisms in response to chemotherapy. Moreover, cPLA(2) may serve as a potential therapeutic target for anti-cancer therapy of HNSCC.

Japanese and financial corporate strategy is typically characterised by the focus on the long term. The threat of “Fortress Europe” has largely been responsible for the surge in direct investment into the EC ahead of 1992. The internationalisation of the world economy and the emphasis on R&D and investment by Japanese manufacturers helps to offset fears that the presence of Japanese manufacturers is akin to a “Trojan Horse” waiting to ride roughshod over their sclerotic European competitors. On the financial side, the issue of “reciprocity” between EC and Japanese institutions has yet to be resolved. Nevertheless, recent developments such as German reunification and Eastern European liberalisation will substantially increase the demand for capital. Here Japan, as the world's leading creditor nation, has a role to play and already many Japanese financial institutions are focusing their attention on financial centres such as Frankfurt and Paris.

Involving patients in treatment decisions may reduce premature antidepressant treatment terminations and improve clinical and health economic outcomes. However, a first step is to determine what information to provide to patients to facilitate their decision making. The authors therefore identified, valued, and ranked factors of antidepressant treatment selection that are relevant to patients and compared them with the opinions of general practitioners.Matching surveys were developed for patients and physicians with feedback from focus groups. In the patient group, participation was requested from consecutive patients at four family practice sites in Nova Scotia, Canada. Surveys were mailed to 247 randomly selected general practitioners.Surveys were completed by 127 patients and 110 physicians, representing return rates of 70% and 46%, respectively. The most valued of the 12 differentiating factors when selecting an antidepressant, ranked first by both patients and physicians, was common side effects. Also ranked highly by both groups were precautions with antidepressant use, physician antidepressant experience, and discontinuation problems. Groups differed in their ranking of uncommon serious side effects, time since antidepressants were marketed, cost, and dosing schedule. The ranking distributions were significantly different for six of 12 factors between patients and general practitioners (Wilcoxon ranked-sum test). Patient experience with antidepressants did not influence factor value.The data demonstrate moderate disagreement between patients and general practitioners regarding the relative value of antidepressant selection factors. The effect of this disagreement on treatment adherence and other outcomes requires further investigation, as improving patient-physician concordance regarding antidepressant choices may lead to improved treatment acceptance.