Components of Behavioral Activation Therapy for Depression Engage Specific Reinforcement Learning Mechanisms in a Pilot Study

Background: Behavioral activation is an evidence-based treatment for depression. Theoretical considerations suggest that treatment response depends on reinforcement learning mechanisms. However, which reinforcement learning mechanisms are engaged by and mediate the therapeutic effect of behavioral activation remains only partially understood, and there are no procedures to measure such mechanisms. Objective: To perform a pilot study to examine whether reinforcement learning processes measured through tasks or self-report are related to treatment response to behavioral activation. Method: The pilot study enrolled 13 outpatients (12 completers) with major depressive disorder, from July of 2018 through February of 2019, into a nine-week trial with BA. Psychiatric evaluations, decision-making tests and self-reported reward experience and anticipations were acquired before, during and after the treatment. Task and self-report data were analysed by using reinforcement-learning models. Inferred parameters were related to measures of depression severity through linear mixed effects models. Results: Treatment effects during different phases of the therapy were captured by specific decision-making processes in the task. During the weeks focusing on the active pursuit of reward, treatment effects were more pronounced amongst those individuals who showed an increase in Pavlovian appetitive influence. During the weeks focusing on the avoidance of punishments, treatment responses were more pronounced in those individuals who showed an increase in Pavlovian avoidance. Self-reported anticipation of reinforcement changed according to formal RL rules. Individual differences in the extent to which learning followed RL rules related to changes in anhedonia. Conclusions: In this pilot study both task-and self-report-derived measures of reinforcement learning captured individual differences in treatment response to behavioral activation. Appetitive and aversive Pavlovian reflexive processes appeared to be modulated by separate psychotherapeutic interventions, and the modulation strength covaried with response to specific interventions. Self-reported changes in reinforcement expectations are also related to treatment response

Beurteilung der Anbauwürdigkeit unterschiedlicher Herkünfte von Saflor (Carthamus tinctorius) und Leindotter (Camelina sativa) zur Speiseölgewinnung unter den Bedingungen des Ökologischen Landbaus in Mitteleuropa

Der Anbau von Ölpflanzen im Ökologischen Landbau Mitteleuropas beschränkt sich auf Raps und Sonnenblumen und erfolgt derzeit auf einem geringen Anteil der biologisch bewirtschafteten Fläche. Als alternative Ölpflanzenarten lassen Saflor und Leindotter für den Einsatz im Ökologischen Landbau eine besondere Eignung erwarten. 2002 wurden in einer zweiortigen Prüfung auf Mikroparzellen unter insgesamt nahezu 1000 Genotypen (Genbank-Akzessionen, Sorten, Zuchtstämme) beider Arten hierzu geeignete Formen gesucht. Neben der Resistenz gegen verschiedene Krankheiten wurden weitere agronomisch relevante Merkmale, ein daraus errechneter Index sowie das Parzellengewicht erhoben. Bei beiden Arten wurden für viele Merkmale eine große Variabilität sowie hohe Heritabilitäten gefunden. Insbesondere für Saflor war dies der Fall, wo die am besten adaptierten Herkünfte des geprüften Weltsortimentes - von wenigen Ausnahmen abgesehen - aus Europa stammten. Auch bei Leindotter konnten überlegene Formen identifiziert werden, die sich jedoch mehrheitlich unter dem Material außerhalb der GUS-Staaten befanden

Selektion anbauwürdiger Saflor-Formen für den Ökologischen Landbau aus einem zweijährigen Screening-Experiment

Als alternative Ölpflanze mit hervorragender Speiseölqualität könnte Saflor für den ökologischen Landbau dort in Frage kommen, wo Raps und Sonnenblumen weniger hohe Erträge zu liefern imstande sind. In der vorliegenden Studie sollte die Anbauwürdigkeit des Saflors unter den Bedingungen des Ökologischen Landbaues mit einem Screening von 741 ausgewählten Formen dieser Art überprüft werden. Das Experiment fand 2002 an zwei Standorten statt. Eine hieraus getroffene Auswahl von 65 geeigneten Herkünften wurde 2003 in einer dreiortigen Leistungsprüfung weiter getestet. 2002 wurden sowohl bei morphologischen als auch agronomisch wichtigen Merkmalen große Unterschiede zwischen den Herkünften gefunden. Besonders in der Anfälligkeit für verschiedene Krankheiten zeigte das Material eine große Variabilität. Neben ertragslosen Formen konnten eine Reihe von Genotypen mit ausreichendem Kornansatz geerntet werden, die zusätzlich im Mittel einen Kernanteil bis zu 40% aufwiesen. Das weitergeprüfte Material zeigte 2003 eine mit den Daten aus 2002 gut übereinstimmende Krankheitsanfälligkeit. Es kann hieraus gefolgert werden, dass es bei Saflor anbauwürdige Formen gibt, die auch unter unseren eher humiden Klimabedingungen noch ausreichende Leistungen erbringen können

Enhanced Performance of Dye-Sensitized Solar Cells based on TiO2 Nanotube Membranes using Optimized Annealing Profile

We use free-standing TiO2 nanotube membranes that are transferred onto FTO slides in front-side illuminated dye-sensitized solar cells (DSSCs). We investigate the key parameters for solar cell arrangement of self-ordered anodic TiO2 nanotube layers on the FTO substrate and namely the influence of the annealing procedure on the DSSC light conversion efficiency. The results show that using an optimal temperature annealing profile can significantly enhance the DSSC efficiency (in our case 9.8 %), as it leads to a markedly lower density of trapping states in the tube oxide, and thus to strongly improved electron transport properties

Tomographic reconstruction with a generative adversarial network

This paper presents a deep learning algorithm for tomographic reconstruction (GANrec). The algorithm uses a generative adversarial network (GAN) to solve the inverse of the Radon transform directly. It works for independent sinograms without additional training steps. The GAN has been developed to fit the input sinogram with the model sinogram generated from the predicted reconstruction. Good quality reconstructions can be obtained during the minimization of the fitting errors. The reconstruction is a self-training procedure based on the physics model, instead of on training data. The algorithm showed significant improvements in the reconstruction accuracy, especially for missing-wedge tomography acquired at less than 180° rotational range. It was also validated by reconstructing a missing-wedge X-ray ptychographic tomography (PXCT) data set of a macroporous zeolite particle, for which only 51 projections over 70° could be collected. The GANrec recovered the 3D pore structure with reasonable quality for further analysis. This reconstruction concept can work universally for most of the ill-posed inverse problems if the forward model is well defined, such as phase retrieval of in-line phase-contrast imaging

General Protein Diffusion Barriers Create Compartments within Bacterial Cells

In eukaryotes, the differentiation of cellular extensions such as cilia or neuronal axons depends on the partitioning of proteins to distinct plasma membrane domains by specialized diffusion barriers. However, examples of this compartmentalization strategy are still missing for prokaryotes, although complex cellular architectures are also widespread among this group of organisms. This study reveals the existence of a protein-mediated membrane diffusion barrier in the stalked bacterium Caulobacter crescentus. We show that the Caulobacter cell envelope is compartmentalized by macromolecular complexes that prevent the exchange of both membrane and soluble proteins between the polar stalk extension and the cell body. The barrier structures span the cross-sectional area of the stalk and comprise at least four proteins that assemble in a cell-cycle-dependent manner. Their presence is critical for cellular fitness because they minimize the effective cell volume, allowing faster adaptation to environmental changes that require de novo synthesis of envelope proteins

Boosting Anti-Inflammatory Potency of Zafirlukast by Designed Polypharmacology

Multitarget design offers access to bioactive small molecules with potentially superior efficacy and safety. Particularly multifactorial chronic inflammatory diseases demand multiple pharmacological interventions for stable treatment. By minor structural changes, we have developed a close analogue of the cysteinyl-leukotriene receptor antagonist zafirlukast that simultaneously inhibits soluble epoxide hydrolase and activates peroxisome proliferator-activated receptor \u3b3. The triple modulator exhibits robust anti-inflammatory activity in vivo and highlights the therapeutic potential of designed multitarget agents

Mapping the Pore Architecture of Structured Catalyst Monoliths from Nanometer to Centimeter Scale with Electron and X-ray Tomographies

The hierarchical pore systems of Pt/Al2O3 exhaust gas aftertreatment catalysts were analyzed with a collection of correlative imaging techniques to monitor changes induced by hydrothermal aging. Synergistic imaging with laboratory X-ray microtomography, synchrotron radiation ptychographic X-ray computed nanotomography, and electron tomography allowed quantitative observation of the catalyst pore architecture from centimeter to nanometer scale. Thermal aging at 750 °C in air and hydrothermal aging at 1050 °C in 10% H2O/air caused increasing structural degradation, which manifested as widespread sintering of Pt particles, increased volume and quantity of macropores (>20 nm), and reduction in effective surface area coupled with decreasing volume and frequency of mesopores (2-20 nm) and micropores (<2 nm). Electron tomography unraveled the three-dimensional (3D) structure with high resolution allowing visualization of meso- and macropores but with samples of maximum 300 nm thickness. To complement this, hard X-ray ptychographic tomography produced quantitative 3D electron density maps of 5 μm diameter samples with spatial resolution <50 nm, effectively filling the resolution gap between electron tomography and hard X-ray microtomography. The obtained 3D volumes are an essential input for future computational modeling of fluid dynamics, mass transport, or diffusion properties and may readily complement bulk one-dimensional porosimetry measurements or simulated porosity