Inhibition of indoleamine 2,3-dioxygenase in mixed lymphocyte reaction affects glucose influx and enzymes involved in aerobic glycolysis and glutaminolysis in alloreactive T-cells

Indoleamine 2,3-dioxygenase (IDO) suppresses adaptive immunity. T-cell proliferation and differentiation to effector cells require increased glucose consumption, aerobic glycolysis and glutaminolysis. The effect of IDO on the above metabolic pathways was evaluated in alloreactive T-cells. Mixed lymphocyte reaction (MLR) in the presence or not of the IDO inhibitor, 1-DL-methyl-tryptophane (1-MT), was used. In MLRs, 1-MT decreased tryptophan consumption, increased cell proliferation, glucose influx and lactate production, whereas it decreased tricarboxylic acid cycle activity. In T-cells, from the two pathways that could sense tryptophan depletion, i.e. general control nonrepressed 2 (GCN2) kinase and mammalian target of rapamycin complex 1, 1-MT reduced only the activity of the GCN2 kinase. Additionally 1-MT treatment of MLRs altered the expression and/or the phosphorylation state of glucose transporter-1 and of key enzymes involved in glucose metabolism and glutaminolysis in alloreactive T-cells in a way that favors glucose influx, aerobic glycolysis and glutaminolysis. Thus in alloreactive T-cells, IDO through activation of the GCN2 kinase, decreases glucose influx and alters key enzymes involved in metabolism, decreasing aerobic glycolysis and glutaminolysis. Acting in such a way, IDO could be considered as a constraining factor for alloreactive T-cell proliferation and differentiation to effector T-cell subtypes.

Nonequilibrium hysteresis and spin relaxation in the mixed-anisotropy dipolar-coupled spin-glass LiHo0.5Er0.5F4

We present a study of the model spin-glass LiHo0.5Er0.5F4 using simultaneous ac susceptibility, magnetization, and magnetocaloric effect measurements along with small angle neutron scattering (SANS) at sub-Kelvin temperatures. All measured bulk quantities reveal hysteretic behavior when the field is applied along the crystallographic c axis. Furthermore, avalanchelike relaxation is observed in a static field after ramping from the zero-field-cooled state up to 200–300 Oe. SANS measurements are employed to track the microscopic spin reconfiguration throughout both the hysteresis loop and the related relaxation. Comparing the SANS data to inhomogeneous mean-field calculations performed on a box of one million unit cells provides a real-space picture of the spin configuration. We discover that the avalanche is being driven by released Zeeman energy, which heats the sample and creates positive feedback, continuing the avalanche. The combination of SANS and mean-field simulations reveal that the conventional distribution of cluster sizes is replaced by one with a depletion of intermediate cluster sizes for much of the hysteresis loop.

On the Methyl-Transfer Reaction in Crystalline Methyl 2-(Methylthio)benzenesulfonate: a Thermally Induced Non-Topochemical Solid-State Reaction

The rearrangement of methyl 2-(methylthio)benzenesulfonate (1) to the zwitterionic 2-(dimethyl-sulfonium)benzenesulfonate (2) is known to proceed in solution by intermolecular Me transfers. The same rearrangement has been observed to occur in crystalline 1, but the crystal structure shows that the molecular packing is not conducive to intermolecular Me transfer. The reaction has been carried out with mixed crystals composed of 1 and deuteriomethylated (D6)-l. By fast-atom-bombardment mass spectroscopy, it has been shown that the product consists of a 1:2:1 mixture of the non-, tri-, and hexadeuterated species, the mixture expected, if the solid-state reaction proceeds by intermolecular Me transfers. From this result, together with the slower rates of conversion in the single crystal compared with the melt, it can be concluded that the reaction must occur not topochemically but rather at defects such as microcavities, surfaces, and other irregularities in the ordered crystal arrangement.

Slow conduction in mixed cultured strands of primary ventricular cells and stem cell-derived cardiomyocytes

Modern concepts for the treatment of myocardial diseases focus on novel cell therapeutic strategies involving stem cell-derived cardiomyocytes (SCMs). However, functional integration of SCMs requires similar electrophysiological properties as primary cardiomyocytes (PCMs) and the ability to establish intercellular connections with host myocytes in order to contribute to the electrical and mechanical activity of the heart. The aim of this project was to investigate the properties of cardiac conduction in a co-culture approach using SCMs and PCMs in cultured cell strands. Murine embryonic SCMs were pooled with fetal ventricular cells and seeded in predefined proportions on microelectrode arrays to form patterned strands of mixed cells. Conduction velocity (CV) was measured during steady state pacing. SCM excitability was estimated from action potentials measured in single cells using the patch clamp technique. Experiments were complemented with computer simulations of conduction using a detailed model of cellular architecture in mixed cell strands. CV was significantly lower in strands composed purely of SCMs (5.5 ± 1.5 cm/s, n = 11) as compared to PCMs (34.9 ± 2.9 cm/s, n = 21) at similar refractoriness (100% SCMs: 122 ± 25 ms, n = 9; 100% PCMs: 139 ± 67 ms, n = 14). In mixed strands combining both cell types, CV was higher than in pure SCMs strands, but always lower than in 100% PCM strands. Computer simulations demonstrated that both intercellular coupling and electrical excitability limit CV. These data provide evidence that in cultures of murine ventricular cardiomyocytes, SCMs cannot restore CV to control levels resulting in slow conduction, which may lead to reentry circuits and arrhythmias.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.

Securing one's livelihood. Philanthropy in a mixed economy of welfare in the early 20th century

Since the late 19th century different social actors have played an important role in providing social security in Switzerland. Cooperatives, philanthropic organisations, social insurances, and the poor relief of the communes were all part of a "mixed economy of welfare". This article examines how the different actors in this "mixed economy" worked together, and asks what forms of help they supplied. It raises the question of whether a dichotomy between public and private forms of relief can be traced in the Swiss case. Did democratically legitimised processes of redistribution shape the social security system? Or was social security rather funded by private relief programs? The author argues that in the early 20th century, a complex public-private mix structured the Swiss welfare state and the poor often depended on both public and private funding. In this system, financially potent philanthropic organisations successfully contested the legal power of public actors.

Feasibility of resting-state microstates neurofeedback

Despite major progress, currently available treatment options for patients suffering from schizophrenia remain suboptimal. Antipsychotic medication is one such option, and is helpful in acute phases of the disease. However, antipsychotics cause significant side-effects that often require additional medication, and can even trigger the discontinuation of treatment. Taken together, along with the fact that 20-30% of patients are medication-resistant, it is clear that new medical care options should be developed for patients with schizophrenia. Besides medication, an emerging option to treat psychiatric symptoms is through the use of neurofeedback. This technique has proven efficacy for other disorders and, more importantly, has also proven to be feasible in patients with schizophrenia. One of the major advantages of this approach is that it allows for the influence of brain states that otherwise would be inaccessible; i.e. the physiological markers underlying psychotic symptoms. EEG resting-state microstates are a very interesting electrophysiological marker of schizophrenia symptoms. Precisely, a specific class of resting-state microstates, namely microstate class D, has consistently been found to show a temporal shortening in patients with schizophrenia compared to controls, and this shortening is correlated with the presence positive psychotic symptoms. Under the scope of biological psychiatry, appropriate treatment of psychotic symptoms can be expected to modify the underlying physiological markers accompanying behavioral manifestations of a disease. We reason that if abnormal temporal parameters of resting-state microstates seem to be related to positive symptoms in schizophrenia, regulating this EEG feature might be helpful as a treatment for patients. The goal of this thesis was to prove the feasibility of microstate class D contribution self-regulation via neurofeedback. Given that no other study has attempted to regulate microstates via neurofeedback, we first tested its feasibility in a population of healthy subjects. In the first paper we describe the methodological characteristics of the neurofeedback protocol and its implementation. Neurofeedback performance was assessed by means of linear mixed effects modeling, which provided a complete profile of the neurofeedback’s training response within and between-subjects. The protocol included 20 training sessions, and each session contained three conditions: baseline (resting-state) and two active conditions: training (auditory feedback upon self-regulation performance) and transfer (self-regulation with no feedback). With linear modeling we obtained performance indices for each of them as follows: baseline carryover (baseline increments time-dependent) and learning and aptitude for each of the active conditions. Learning refers to the increase/decrease of the microstate class D contribution, time-dependent during each active condition, and aptitude refers to the constant difference of the microstate class D contribution between each active condition and baseline independent of time. The indices provided are discussed in terms of tailoring neurofeedback treatment to individual profiles so that it can be applied in future studies or clinical practice. In our sample of participants, neurofeedback proved feasible, as all participants at least showed positive results in one of the aforementioned learning indices. Furthermore, between-subjects we observed that the contribution of microstate class D across-sessions increased by 0.42% during baseline, 1.93% during training trials, and 1.83% during transfer. This range is expected to be effective in treating psychotic symptoms in patients. In the second paper presented in this thesis, we explored the possible predictors of neurofeedback success among psychological variables measured with questionnaires. An interesting finding was the negative correlation between “motivational incongruence” and some of the neurofeedback performance indices. Even though this finding requires replication, we discuss it in terms of the interfering effects of incompatible psychological processes with neurofeedback training requirements. In the third paper, we present a meta-analysis on all available studies that have related resting-state microstate abnormalities and schizophrenia. We obtained medium effect sizes for two microstate classes, namely C and D. Combining the meta-analysis results with the fact that microstate class D abnormalities are correlated with the presence of positive symptoms in patients with schizophrenia, these results add further support for the training of this precise microstate. Overall, the results obtained in this study encourage the implementation of this protocol in a population of patients with schizophrenia. However, future studies will have to show whether patients will be able to successfully self-regulate the contribution of microstate class D and, if so, whether this regulation will have an impact on symptomatology.