Modulation of time in Parkinson's disease: a review and perspective on cognitive rehabilitation

Time cognition is an essential function of human life, and the impairment affects a variety of behavioral patterns. Neuropsychological approaches have been widely demonstrated that Parkinson's disease (PD) impairs time cognitive processing. Many researchers believe that time cognitive deficits are due to the basal ganglia, including the striatum or subthalamic nucleus, which is the pathomechanism of PD, and are considered to produce only transient recovery due to medication effects. In this perspective, we focus on a compensatory property of brain function based on the improved time cognition independent of basal ganglia recovery and an overlapping structure on the neural network based on an improved inhibitory system by time cognitive training, in patients with PD. This perspective may lead to restoring multiple functions through single function training.

[Convenient Approach to Improve Correlation between Geometry and Dosimetric Parameters for Automatic Segmentation in Radiotherapy]

OBJECTIVE

To design a series of geometric indexes, which can improve the correlation between geometric parameters and dosimetric parameters.

METHODS

48 cases of upper abdomen were selected. Manual and automatic segmentation were performed for two organs at risk, which were stomach and duodenum. Three overlapping structures, which were the overlaps with target expanded by 5 mm, 10 mm and 20 mm, were generated for each organ at risk. The geometric parameters of overlapping structures were calculated. The relationship between these geometric parameters and the dosimetric parameters of organs was investigated.

RESULTS

When the geometric parameters of overlapping structures related to the target expand 5 mm, 10 mm and 20 mm were larger than 0.4, 0.6 and 0.8 respectively, the maximum dose differences of manual and automatic segmentation were less than 3 Gy. For the case with no overlaps between the organs and the target expansions, the overlap structure corresponding to target expanding 20 mm were recommended for safety considerations.

CONCLUSIONS

For organs at risk in the upper abdomen, the overlapping geometric parameters were closely related to the maximum dose of organs. Overlapping geometric parameters could predict whether the difference of maximum dose caused by automaticsegmentation was clinically acceptable or not.

Overlapping Structures Detection in Protein-Protein Interaction Networks Using Community Detection Algorithm Based on Neighbor Clustering Coefficient

With the rapid development of bioinformatics, researchers have applied community detection algorithms to detect functional modules in protein-protein interaction (PPI) networks that can predict the function of unknown proteins at the molecular level and further reveal the regularity of cell activity. Clusters in a PPI network may overlap where a protein is involved in multiple functional modules. To identify overlapping structures in protein functional modules, this paper proposes a novel overlapping community detection algorithm based on the neighboring local clustering coefficient (NLC). The contributions of the NLC algorithm are threefold: (i) Combine the edge-based community detection method with local expansion in seed selection and the local clustering coefficient of neighboring nodes to improve the accuracy of seed selection; (ii) A method of measuring the distance between edges is improved to make the result of community division more accurate; (iii) A community optimization strategy for the excessive overlapping nodes makes the overlapping structure more reasonable. The experimental results on standard networks, Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks and PPI networks show that the NLC algorithm can improve the Extended modularity (EQ) value and Normalized Mutual Information (NMI) value of the community division, which verifies that the algorithm can not only detect reasonable communities but also identify overlapping structures in networks.