Our results show better post-DC improvements in the CBF of patients receiving CP < 12 weeks after DC, compared to those receiving CP ≥ 12 weeks after DC. Therefore, early CP has potential benefits for cerebral perfusion.

Gene coexpression patterns can reveal gene collections with functional consistency. This study systematically constructs regulatory networks for pituitary tumours by integrating gene coexpression, transcriptional and posttranscriptional regulation. Through network analysis, we elaborate the incidence mechanism of pituitary adenoma. The Pearson's correlation coefficient was utilized to calculate the level of gene coexpression. By comparing pituitary adenoma samples with normal samples, pituitary adenoma-specific gene coexpression patterns were identified. For pituitary adenoma-specific coexpressed genes, we integrated transcription factor (TF) and microRNA (miRNA) regulation to construct a complex regulatory network from the transcriptional and posttranscriptional perspectives. Network module analysis identified the synergistic regulation of genes by miRNAs and TFs in pituitary adenoma. We identified 142 pituitary adenoma-specific active genes, including 43 TFs and 99 target genes of TFs. Functional enrichment of these 142 genes revealed that the occurrence of pituitary adenoma induced abnormalities in intracellular metabolism and angiogenesis process. These 142 genes were also significantly enriched in adenoma pathway. Module analysis of the systematic regulatory network found that three modules contained elements that were closely related to pituitary adenoma, such as FGF2 and SP1, as well as transcription factors and miRNAs involved in the tumourigenesis. These results show that in the occurrence of pituitary adenoma, miRNA, TF and genes interact with each other. Based on gene expression, the proposed method integrates interaction information from different levels and systematically explains the occurrence of pituitary tumours. It facilitates the tracing of the origin of the disease and can provide basis for early diagnosis of complex diseases or cancer without obvious symptoms.

In the effort to make robot-assisted upper limb passive movement training effective for neurologic injuries suffered from stroke and spinal cord injury (SCI), a new fuzzy adaptive closed-loop supervisory control method for passive joint movement training is proposed. Firstly, high-level supervisory controller for the desired passive range of motion (PROM) is designed based on the impaired limb’s joint motion recovery, and then low-level closed-loop position tracking controller is presented to drive the robot stably and smoothly to stretch the impaired limb to move along the predefined trajectory. The suggested strategy was applied to the four degrees of freedom (DOF) Whole Arm Manipulator (WAM) rehabilitation robot to evaluate its performance. Experimental results carried out on the 4-DOF WAM rehabilitation robot show the effectiveness and potentialities of the fuzzy adaptive passive movement control in clinical application.