Volumetric Prefrontal Cortex Alterations in Patients With Alcohol Dependence and the Involvement of Self‐Control

Background: Aspects of self-control such as sensation seeking and impaired impulse control have been implicated in alcohol dependence (ALC). Conversely, sensation seeking has been ascribed a possible protective role in stress-related psychopathologies. We therefore examined gray matter (GM) morphology in individuals with ALC, focusing on differences in prefrontal regions that have been associated with self-control. Additionally, we accounted for differences in lifetime alcohol intake regarding self-control measures and cortical structures in ALC patients. Methods: With voxel-based morphometry (VBM) focusing on prefrontal a priori defined regions of interest, we assessed a group of 62 detoxified ALC patients and 62 healthy controls (HC). ALC patients were subsequently divided into high (n = 9) and low consumers (n = 53). Self-control was assessed by use of the Barratt Impulsiveness Scale and the Sensation Seeking Scale. Results: Compared to HC, ALC had significantly less GM volume in bilateral middle frontal gyrus (MFG) and right medial prefrontal cortex as well as in the right anterior cingulate. High-consuming ALC showed smaller GM in right orbitofrontal cortex as well as lower sensation seeking scores than low consumers. In low-consuming ALC, right MFG-GM was positively associated with magnitude of sensation seeking; particularly, larger MFG-GM correlated with greater thrill and adventure seeking. Conclusion: Thus, our findings (i) indicate deficient GM volume in prefrontal areas related to self-control and (ii) might accentuate the phenotypic divergence of ALC patients and emphasize the importance of the development of individual treatment options

Insula and striatum activity in effort-related monetary reward processing in gambling disorder: The role of depressive symptomatology

The neurobiological underpinnings of effort-related monetary reward processing of gambling disorder have not been previously studied. To date neuroimaging studies lack in large sample sizes and as a consequence less attention has been given to brain reward processing that could potentially be attributed to comorbid conditions such as depressive mood state. We assessed monetary reward processing using an effort-dependent task during 3 tesla functional magnetic resonance imaging. We investigated a large sample of male, right-handed, slot-machine-playing disordered gamblers (DGs; N = 80) as well as age- and smoking-matched male healthy controls (HCs; N = 89). Depressive symptoms were assessed using the Beck Depression Inventory (BDI). DGs and HCs were divided into subgroups (“high” and “low”) based on their BDI scores. Effort-related monetary reward processing did not differ between the complete groups of HCs and DGs. Brain activation during receipt of monetary reward though revealed a significant Group × BDI interaction: DGs with higher BDI scores compared to DGs with lower BDI scores showed greater brain activity in the right insula cortex and dorsal striatum while no differences were observed for HCs with higher versus lower BDI scores. Our results suggest that effort-related aspects of monetary motivation, i.e. when monetary output is tied to performance, are not altered in DG. Additionally, our findings strengthen the need for subgroup comparisons in future investigations of the disorder as part of a personalized medicine approach

Prediction of Antioxidant Activity of Cherry Fruits from UAS Multispectral Imagery Using Machine Learning

In this research, a model for the estimation of antioxidant content in cherry fruits from multispectral imagery acquired from drones was developed, based on machine learning methods. For two consecutive cultivation years, the trees were sampled on different dates and then analysed for their fruits’ radical scavenging activity (DPPH) and Folin–Ciocalteu (FCR) reducing capacity. Multispectral images from unmanned aerial vehicles were acquired on the same dates with fruit sampling. Soil samples were collected throughout the study fields at the end of the season. Topographic, hydrographic and weather data also were included in modelling. First-year data were used for model-fitting, whereas second-year data for testing. Spatial autocorrelation tests indicated unbiased sampling and, moreover, allowed restriction of modelling input parameters to a smaller group. The optimum model employs 24 input variables resulting in a 6.74 root mean square error. Provided that soil profiles and other ancillary data are known in advance of the cultivation season, capturing drone images in critical growth phases, together with contemporary weather data, can support site- and time-specific harvesting. It could also support site-specific treatments (precision farming) for improving fruit quality in the long-term, with analogous marketing perspectives

Artificial extracellular matrix scaffolds of mobile molecules enhance maturation of human stem cell-derived neurons

Human induced pluripotent stem cell (hiPSC) technologies offer a unique resource for modeling neurological diseases. However, iPSC models are fraught with technical limitations including abnormal aggregation and inefficient maturation of differentiated neurons. These problems are in part due to the absence of synergistic cues of the native extracellular matrix (ECM). We report on the use of three artificial ECMs based on peptide amphiphile (PA) supramolecular nanofibers. All nanofibers display the laminin-derived IKVAV signal on their surface but differ in the nature of their non-bioactive domains. We find that nanofibers with greater intensity of internal supramolecular motion have enhanced bioactivity toward hiPSC-derived motor and cortical neurons. Proteomic, biochemical, and functional assays reveal that highly mobile PA scaffolds caused enhanced β1-integrin pathway activation, reduced aggregation, increased arborization, and matured electrophysiological activity of neurons. Our work highlights the importance of designing biomimetic ECMs to study the development, function, and dysfunction of human neurons