Study of the helicity dependence of pi 0 photoproduction on proton at MAMI

The excitation spectrum is one of the fundamental properties of every spatially extended system. The excitations of the building blocks of normal matter, i.e., protons and neutrons (nucleons), play an important role in our understanding of the low energy regime of the strong interaction. Due to the large coupling, perturbative solutions of quantum chromodynamics (QCD) are not appropriate to calculate long-range phenomena of hadrons. For many years, constituent quark models were used to understand the excitation spectra. Recently, calculations in lattice QCD make first connections between excited nucleons and the fundamental field quanta (quarks and gluons). Due to their short lifetime and large decay width, excited nucleons appear as resonances in scattering processes like pion nucleon scattering or meson photoproduction. In order to disentangle individual resonances with definite spin and parity in experimental data, partial wave analyses are necessary. Unique solutions in these analyses can only be expected if sufficient empirical information about spin degrees of freedom is available. The measurement of spin observables in pion photoproduction is the focus of this thesis. The polarized electron beam of the Mainz Microtron (MAMI) was used to produce high-intensity, polarized photon beams with tagged energies up to 1.47 GeV. A "frozen-spin" Butanol target in combination with an almost 4π detector setup consisting of the Crystal Ball and the TAPS calorimeters allowed the precise determination of the helicity dependence of the γp → π0p reaction. In this thesis, as an improvement of the target setup, an internal polarizing solenoid has been constructed and tested. A magnetic field of 2.32 T and homogeneity of 1.22×10−3 in the target volume have been achieved. The helicity asymmetry E, i.e., the difference of events with total helicity 1/2 and 3/2 divided by the sum, was determined from data taken in the years 2013-14. The subtraction of background events arising from nucleons bound in Carbon and Oxygen was an important part of the analysis. The results for the asymmetry E are compared to existing data and predictions from various models. The results show a reasonable agreement to the models in the energy region of the ∆(1232)-resonance but large discrepancies are observed for energy above 600 MeV. The expansion of the present data in terms of Legendre polynomials, shows the sensitivity of the data to partial wave amplitudes up to F-waves. Additionally, a first, preliminary multipole analysis of the present data together with other results from the Crystal Ball experiment has been as been performed.

Phytocannabinoids beyond the Cannabis plant - do they exist?

It is intriguing that during human cultural evolution man has detected plant natural products that appear to target key protein receptors of important physiological systems rather selectively. Plants containing such secondary metabolites usually belong to unique chemotaxa, induce potent pharmacological effects and have typically been used for recreational and medicinal purposes or as poisons. Cannabis sativa L. has a long history as a medicinal plant and was fundamental in the discovery of the endocannabinoid system. The major psychoactive Cannabis constituent Delta(9)-tetrahydrocannabinol (Delta(9)-THC) potently activates the G-protein-coupled cannabinoid receptor CB(1) and also modulates the cannabinoid receptor CB(2). In the last few years, several other non-cannabinoid plant constituents have been reported to bind to and functionally interact with CB receptors. Moreover, certain plant natural products, from both Cannabis and other plants, also target other proteins of the endocannabinoid system, such as hydrolytic enzymes that control endocannabinoid levels. In this commentary we summarize and critically discuss recent findings.

Prevalence and impact of cannabis use disorders in adolescents with early onset first episode psychosis

Previous studies on the impact of cannabis use disorders (CU) on outcome in psychosis were predominantly based on non representative samples, often have not controlled for confounders and rarely focused on adolescent patients. Thus, the aims of the present study were to assess: (i) prevalence of CU; (ii) baseline and pretreatment differences between CU and those without CU (NCU); (iii) the impact of baseline and course of CU on 18-month outcomes in a representative cohort of adolescents with early onset first episode psychosis (EOP).

Cannabis use disorder and age at onset of psychosis--a study in first-episode patients

INTRODUCTION Age at onset of psychosis (AAO) may be younger in patients with cannabis use disorders (CUD) compared to those without CUD (NCUD). Previous studies included CUD co-morbid with other substance use disorders (SUD), and many did not control for confounders. METHODS Controlling for relevant confounders, differences in AAO between patients with and without CUD excluding those with any other SUD were analyzed in a large representative file audit of 625 first-episode psychosis (FEP) patients (age 14 to 29years) admitted to the Early Psychosis Prevention and Intervention Centre in Melbourne, Australia. RESULTS Three quarters of the 625 FEP patients had a CUD. Cannabis use started before psychosis onset in 87.6% of patients. AAO was not significantly different between CUD (without other SUD, n=201) and NCUD (n=157). However, AAO was younger in those with early CUD (starting age 14 or younger) compared to NCUD (F(1)=5.2; p=0.024; partial η(2)=0.026). Earlier age at onset of cannabis use predicted earlier age at onset of psychosis (β=-0.49, R(2)-change=0.25, p<0.001). CONCLUSION Only CUD starting age 14 or younger was associated with an earlier AAO at a small effect size. These findings suggest that CUD may exert an indirect effect on brain maturation resulting in earlier AAO potentially only in cannabis sensitive subjects.

Strategies for evaluating the economic value of drugs in alcohol dependence treatment

To assess existing health economic strategies, which are used to evaluate the economic value of drugs to treat alcohol dependence (AD) such as acamprosate, naltrexone and any other pharmaceuticals.

Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients

To derive tests for randomness, nonlinear-independence, and stationarity, we combine surrogates with a nonlinear prediction error, a nonlinear interdependence measure, and linear variability measures, respectively. We apply these tests to intracranial electroencephalographic recordings (EEG) from patients suffering from pharmacoresistant focal-onset epilepsy. These recordings had been performed prior to and independent from our study as part of the epilepsy diagnostics. The clinical purpose of these recordings was to delineate the brain areas to be surgically removed in each individual patient in order to achieve seizure control. This allowed us to define two distinct sets of signals: One set of signals recorded from brain areas where the first ictal EEG signal changes were detected as judged by expert visual inspection ("focal signals") and one set of signals recorded from brain areas that were not involved at seizure onset ("nonfocal signals"). We find more rejections for both the randomness and the nonlinear-independence test for focal versus nonfocal signals. In contrast more rejections of the stationarity test are found for nonfocal signals. Furthermore, while for nonfocal signals the rejection of the stationarity test increases the rejection probability of the randomness and nonlinear-independence test substantially, we find a much weaker influence for the focal signals. In consequence, the contrast between the focal and nonfocal signals obtained from the randomness and nonlinear-independence test is further enhanced when we exclude signals for which the stationarity test is rejected. To study the dependence between the randomness and nonlinear-independence test we include only focal signals for which the stationarity test is not rejected. We show that the rejection of these two tests correlates across signals. The rejection of either test is, however, neither necessary nor sufficient for the rejection of the other test. Thus, our results suggest that EEG signals from epileptogenic brain areas are less random, more nonlinear-dependent, and more stationary compared to signals recorded from nonepileptogenic brain areas. We provide the data, source code, and detailed results in the public domain.