Pharmacogenomics in Psychiatric Disorders

The broad arsenal of psychotropic medications is characterised by significant interindividual variability in clinical response and adverse effects, stringent monitoring requirements, potential drug-drug interactions, difficult long-term adherence and high costs. Pharmacogenomics investigates the correlation between genetic polymorphisms and responsiveness to drugs and could provide a valuable guide to fulfill the promise of personalized therapy in the context of the genomic medicine era, by tailoring treatment based on the patient’s specific genetic markers. The present paper overviews the current advances in the clinical applications of pharmacogenomics to individualized psychotropic therapy.Material and methods. The relevant recent pharmacogenomics literature is selected and analysed in order to illustrate the impact on the clinical outcomes and quality of life in psychiatric patients of the genetic variants in the neurotransmitter receptors (dopamine and serotonin), metabolic pathways of drugs (cytochrome CYP450 2D6 and 2C19) and  the human leukocyte antigen system. The paper focuses on some of the major psychotropic drug classes, such as: antipsychotics, antidepressants and mood stabilizers. Validation of statistically significant pharmacogenomics relationships has enabled the development and market approval of some predictive tests which are already integrated into some psychotropic drugs label. Results and discussions. Predictive pharmacogenomics tests have changed the classical approach of prescription  “trial-and error” and “one dose fits all patients” towards personalized therapy. In addition, in new therapeutic candidates’ clinical development, pharmacogenomics practically guides the clinical studies design, by substantially reducing the failure rates, costs and exposure risks of non-responders patients to new drugs. Current translation barriers of predictive pharmacogenomic tests from bench to clinical practice are also discussed. Conclusion. The paper emphasizes the current progress and future prospects in the field of pharmacogenomics as a guide to personalized therapy of psychiatric disorders, by: a) pretreatment selection of the right drug, prescribed in its optimized dose, to the right patient, according to one’s specific genetic biomarkers; b) by improved clinical trials design based on genetic stratification of patients’ population into responders versus non-responders, especially in the costly phases III and IV.</p

Simulation and optimisation of terahertz emission from InGaAs and InP photoconductive switches

We simulate the terahertz emission from laterally-biased InGaAs and InP using a three-dimensional carrier dynamics model in order to optimise the semiconductor material. Incident pump-pulse parameters of current Ti:Sapphire and Er:fibre lasers are chosen, and the simulation models the semiconductor's bandstructure using parabolic Gamma, L and X valleys, and heavy holes. The emitted terahertz radiation is propagated within the semiconductor and into free space using a model based on the Drude-Lorentz dielectric function. As the InGaAs alloy approaches InAs an increase in the emitted power is observed, and this is attributed to a greater electron mobility. Additionally, low-temperature grown and ion-implanted InGaAs are modelled using a finite carrier trapping time. At sub-picosecond trapping times the terahertz bandwidth is found to increase significantly at the cost of a reduced emission power.Comment: 9 pages, 7 figure

Astronomical spectrograph calibration with broad-spectrum frequency combs

Broadband femtosecond-laser frequency combs are filtered to spectrographically resolvable frequency-mode spacing, and the limitations of using cavities for spectral filtering are considered. Data and theory are used to show implications to spectrographic calibration of high-resolution, astronomical spectrometers

Nonlinear Femtosecond Pulse Reshaping in Waveguide Arrays

We observe nonlinear pulse reshaping of femtosecond pulses in a waveguide array due to coupling between waveguides. Amplified pulses from a mode-locked fiber laser are coupled to an AlGaAs core waveguide array structure. The observed power-dependent pulse reshaping agrees with theory, including shortening of the pulse in the central waveguide

Broadband velocity modulation spectroscopy of HfF^+: towards a measurement of the electron electric dipole moment

Precision spectroscopy of trapped HfF^+ will be used in a search for the permanent electric dipole moment of the electron (eEDM). While this dipole moment has yet to be observed, various extensions to the standard model of particle physics (such as supersymmetry) predict values that are close to the current limit. We present extensive survey spectroscopy of 19 bands covering nearly 5000 cm^(-1) using both frequency-comb and single-frequency laser velocity-modulation spectroscopy. We obtain high-precision rovibrational constants for eight electronic states including those that will be necessary for state preparation and readout in an actual eEDM experiment.Comment: 13 pages, 7 figures, 3 table

Cavity-enhanced direct frequency comb spectroscopy

Cavity-enhanced direct frequency comb spectroscopy combines broad spectral bandwidth, high spectral resolution, precise frequency calibration, and ultrahigh detection sensitivity, all in one experimental platform based on an optical frequency comb interacting with a high-finesse optical cavity. Precise control of the optical frequency comb allows highly efficient, coherent coupling of individual comb components with corresponding resonant modes of the high-finesse cavity. The long cavity lifetime dramatically enhances the effective interaction between the light field and intracavity matter, increasing the sensitivity for measurement of optical losses by a factor that is on the order of the cavity finesse. The use of low-dispersion mirrors permits almost the entire spectral bandwidth of the frequency comb to be employed for detection, covering a range of ~10% of the actual optical frequency. The light transmitted from the cavity is spectrally resolved to provide a multitude of detection channels with spectral resolutions ranging from a several gigahertz to hundreds of kilohertz. In this review we will discuss the principle of cavity-enhanced direct frequency comb spectroscopy and the various implementations of such systems. In particular, we discuss several types of UV, optical, and IR frequency comb sources and optical cavity designs that can be used for specific spectroscopic applications. We present several cavity-comb coupling methods to take advantage of the broad spectral bandwidth and narrow spectral components of a frequency comb. Finally, we present a series of experimental measurements on trace gas detections, human breath analysis, and characterization of cold molecular beams.Comment: 36 pages, 27 figure

Statistical learning methods as a basis for skillful seasonal temperature forecasts in Europe

A statistical learning approach to produce seasonal temperature forecasts in western Europe and Scandinavia was implemented and tested. The leading principal components (PCs) of sea surface temperature (SST) and the geopotential at the 150-hPa level (GPT) were derived from reanalysis datasets and used at different lags (from one to five seasons) as predictors. Random sampling of both the fitting years and the potential predictors together with the Least Absolute Shrinkage and Selection Operator regression (LASSO) was used to create a large ensemble of statistical models. Applying the models to independent test years shows that the ensemble performs well over the target areas and that the ensemble mean is more accurate than the best individual ensemble member on average. Skillful results were especially found for summer and fall, with the anomaly correlation coefficient values ranging between 0.41 and 0.68 for these seasons. The correct simulation of decadal trends, using sufficiently long time series for fitting (70 years), and the use of lagged predictors increased the prediction skill. The decadal-scale variability of SST, most importantly the Atlantic multidecadal oscillation (AMO), and different PCs of GPT are the most important individual predictors among all predictors. Both SST and GPT bring equally much predictive power, although their importance is different in different seasons.Peer reviewe