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Gastric mucosal abnormality as well as risk of pancreatic cancers: the population-based stomach biopsy cohort research within Norway.
Promoting Secure Attachment Relationships in Foster Families with the Attachment and Biobehavioral Catch-Up (ABC) Intervention Due to a history of early adversity, foster children often show difficulties in the development of new attachment relationships. The Attachment and Biobehavioral Catch-Up Intervention (ABC) aims to promote sensitive caregiving and the development of secure attachment relationships in foster families by addressing the critical needs of foster children. The ABC intervention was implemented in Germany for the first time. The efficacy of the intervention was tested in a sample of N = 34 foster families with foster children between the ages of 6 to 24 months. Foster parents reported on parenting stress and on attachment behaviors of the child in a diary. Parenting quality was assessed in a semi-structured play situation and attachment quality was assessed with the Strange Situation Procedure. Foster parents showed higher levels of sensitivity post training (p less then .001), they reported an increase in secure attachment behaviors in their foster children (p less then .05), and the distribution of attachment relationships classified as secure (59 %) and disorganized (12 %) was comparable to distributions found in biological, middle class samples. Although these results still need further validation by larger control group studies, they give a first indication that the ABC program might be an effective tool to support the development of secure attachment relationships in foster families in Germany.Introduction We hypothesized that diabetic patients without mild cognitive impairment would present deficiencies in visuospatial incidental/intentional memory processing and alterations in the underlying EEG alpha, theta and gamma patterns.Methods Non-diabetic, diabetic-controlled, and diabetic-uncontrolled patients underwent a visuospatial incidental-intentional memory test under simultaneous recording of temporal, parietal, and frontal EEG. The test required patients to solve a maze, with eight objects irrelevant to the task, embedded in it, after an interference instruction, participants were asked to recall the positions of the objects (incidental test). Finally, the participants were explicitly told to study the object positions, and then were asked to recall the objects again (intentional test). Power from baseline, incidental learning, incidental memory, and intentional learning conditions was obtained in alpha, theta, and low-gamma bands. Comparisons were made across groups and conditions for each ban in frontal areas. These EEG power changes were absent in diabetic patients. The reduced accuracy of diabetic patients in intentional visuospatial learning was associated with different EEG learning-related patterns.ABSTRACTEmerging evidence suggests the role of vitamin D in brain health and its implication in the pathogenesis of cognitive impairment. The Aim of this review is to summarize current evidence on neuroimaging changes seen in vitamin D deficient individuals. Cross-sectional and longitudinal studies have consistently found an association between low serum 25 hydroxyvitamin D and cognitive impairment. Furthermore, investigating the association between serum 25 hydroxyvitamin D and neuroimaging abnormalities could provide an insight into the potential mechanisms underlying the association with cognitive impairment. Animal studies have demonstrated structural changes in the cerebral cortex and hippocampus of vitamin D deficient mice. Neuroimaging studies of the brain have shown increased white matter hyperintensities in periventricular, cortical, and juxtacortical areas and grey matter atrophy of the hippocampus, anterior cingulate cortex, and left calcarine sulcus in elderly with vitamin D deficiency.This paper proposes a new algorithm for prophage loci prediction in bacteria. Prophages are defined in Bioinformatics as viral nucleotide sequences that are found intermixed with host nucleotide sequences in bacteria. The proposed algorithm uses machine learning patterns and processing methodologies in order to provide a highly efficient system for loci prediction, thereby reducing the time-space complexity required unlike others of its class. In the training phase, a pattern database is constructed from raw nucleotide sequences of both bacteria and viruses obtained from a training set. In the prediction phase, the aforementioned database is used along with Particle Swarm Optimization (PSO) to predict the probable loci of prophages in a test set of bacterial nucleotide sequences. Testing this method on raw sequences consisting of both partial and complete nucleotide sequences of various bacteria has yielded good results in predicting the loci of prophages in them. This algorithm and connected processes compare favorably in terms of predictive performance with others of its class such as PhiSpy and ProphET, while outperforming others in terms of raw processing speed, suggesting that a data-centric approach can yield comparable results while using a fraction of the resources.Molecular docking is a fast and efficient computational method for the prediction of the binding mode and binding affinity between a ligand and a target protein at the atomic level. However, the performance of current docking programs is less than satisfactory. Herein, with a focus on free programs and scoring functions, the performances of LeDock and three standalone scoring functions were tested by 195 high-quality protein-ligand complexes. Results showed that the success rate for the best pose of the free available docking program LeDock achieved 89.20%, indicative of a strong sampling power. Based on the poses generated by LeDock, a comparative evaluation on other three non-commercial scoring functions, including DSX (DrugScore X), PoseScore and X-score was performed. Among all the evaluated scoring functions, DSX and X-score exhibited the best scoring power and ranking power, respectively. CCG-203971 The performances of LeDock, DSX and X-score were similar in docking power test, which was much better than the PoseScore. Accordingly, it was suggested that the combination of pose sampling by LeDock with rescoring by DSX or X-score could improve the prediction accuracy of molecular docking and applied in the lead discovery.
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