The generation of new neurons in the adult mammalian hippocampus is thought to play a role in repairing the brain after injury. Here, we show that 7 d after focal cerebral ischemia, newly divided cells in the dentate gyrus of adult rats increased to approximately sevenfold, compared with sham controls. In the same area, this enhanced dentate neurogenesis was associated with activation of inducible nitric oxide synthase (iNOS). Inhibition of iNOS by aminoguanidine prevented ischemia-induced neurogenesis in the dentate gyrus. In null mutant mice lacking the iNOS gene, increased neurogenesis was not observed after focal cerebral ischemia. This study demonstrates that expression of iNOS is necessary for ischemia-stimulated cell birth in the dentate gyrus and indicates that activation of iNOS may provide a possible strategy for functional recovery from cerebral ischemic insult.

As a major challenge and opportunity for traditional manufacturing, intelligent manufacturing is facing the needs of sustainable development in future. Sustainability assessment undoubtedly plays a pivotal role for future development of intelligent manufacturing. Aiming at this, the paper presents the digital twin driven information architecture of sustainability assessment oriented for dynamic evolution under the whole life cycle based on the classic digital twin mapping system. The sustainability assessment method segment of the architecture includes indicator system building, indicator value determination, indicator importance degree determination and intelligent manufacturing project assessing. A novel approach for treating the ambiguity of expert' judgment in indicator value determination by introducing trapezoidal fuzzy number into analytic hierarchy process is proposed, while the complexity of the influence relationship among the indicators is processed by the integration of complex networks modeling and PROMETHEE II for the indicator importance degree determination. A two-stage evidence combination model based on evidence theory is built for intelligent manufacturing project assessing lastly. The presented digital-twin-driven information architecture and the sustainability assessment method is tested and validated on a study of sustainability assessment of 8 intelligent manufacturing projects of an air conditioning enterprise. The results of the presented method were validated by comparing them with the results of the fuzzy and rough extension of the PROMETHEE II, TOPSIS and VIKOR methods, indicator importance degree determining method by entropy and indicator value determining method by accurate expert scoring.

The design, planning, and implementation of intelligent manufacturing are mainly carried out from the perspectives of meeting the needs of mass customization, improving manufacturing capacity, and innovating business pattern currently. Environmental and social factors should be systematically integrated into the life cycle of intelligent manufacturing. In view of this, a green performance evaluation methodology of intelligent manufacturing driven by digital twin is proposed in this paper. Digital twin framework, which constructs the bidirectional mapping and real-time data interaction between physical entity and digital model, provides the green performance evaluation with a total factor virtual image of the whole life cycle to meet the monitoring and simulation requirements of the evaluation information source and demand. Driven by the digital twin framework, a novel hybrid MCDM model based on fuzzy rough-sets AHP, multistage weight synthesis, and PROMETHEE II is proposed as the methodology for the green performance evaluation of intelligent manufacturing. The model is tested and validated on a study of the green performance evaluation of remote operation and maintenance service project evaluation for an air conditioning enterprise. Testing demonstrates that the proposed hybrid model driven by digital twin can enable a stable and reasonable evaluation result. A sensitivity analysis was carried out by means of 27 scenarios, the results of which showed a high degree of stability.

Targeting of dorsal root ganglia by diabetes could account for the selective sensory abnormalities that patients with early diabetic polyneuropathy develop. In this work, we addressed survival, phenotype and gene expression in sensory neurones in lumbar dorsal root ganglia in a long-term model of experimental streptozotocin-induced diabetes in rats, designed to reflect human disease. Motor and sensory conduction slowing developed early, by the 2-month time point. At 2 months, sensory neurones had no detectable alterations in their calibre or gene expression, assessed using quantitative in situ hybridization studies for mRNA markers that included alpha CGRP, beta CGRP, NFM, t alpha 1-tubulin, SP, VIP, B50 (GAP43), galanin, somatostatin, PACAP, HSP27, c-jun, SNAP 25, p75, TrkA, TrkB and TrkC. By 12 months, however, diabetics had developed neurone perikaryal and distal axon atrophy, accompanied by generalized downregulation of mRNA expression, particularly of CGRP transcripts, PACAP, SP, NFM, p75, trkA and trkC. With the exception of HSP-27, no elevation in mRNAs that increase after injury, such as VIP, galanin, CCK, PACAP, B50 and t alpha 1-tubulin, was observed and constitutive levels, when detectable, trended towards lower rather than increased levels. There was relative preservation of neurone numbers at 12 months; only a non-significant trend towards fewer diabetic neurones was detected using a rigorous and systematic physical dissector counting approach through the entire L5 ganglia. There was no change in the relative populations of CGRP- and SP-immunoreactive neurones. Our findings indicate that even long-term experimental diabetes is associated with relative preservation of sensory neurone populations, but the neurones are atrophic and their gene expression is altered. This pattern of change differs from that following axotomy, implies a degenerative rather than an injury phenotype and has important implications for how such neurones might be rescued.

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