Besides secondary injury at the lesional site, Traumatic brain injury (TBI) can cause a systemic inflammatory response, which may cause damage to initially unaffected organs and potentially further exacerbate the original injury. Here we investigated plasma levels of important inflammatory mediators, oxidative activity of circulating leukocytes, particularly focusing on neutrophils, from TBI subjects and control subjects with general trauma from 6 hours to 2 weeks following injury, comparing with values from uninjured subjects. We observed increased plasma level of inflammatory cytokines/molecules TNF-α, IL-6 and CRP, dramatically increased circulating leukocyte counts and elevated expression of TNF-α and iNOS in circulating leukocytes from TBI patients, which suggests a systemic inflammatory response following TBI. Our data further showed increased free radical production in leukocyte homogenates and elevated expression of key oxidative enzymes iNOS, COX-2 and NADPH oxidase (gp91phox) in circulating leukocytes, indicating an intense induction of oxidative burst following TBI, which is significantly greater than that in control subjects with general trauma. Furthermore, flow cytometry assay proved neutrophils as the largest population in circulation after TBI and showed significantly up-regulated oxidative activity and suppressed phagocytosis rate for circulating neutrophils following brain trauma. It suggests that the highly activated neutrophils might play an important role in the secondary damage, even outside the injured brain. Taken together, the potent systemic inflammatory response induced by TBI, especially the intensively increase oxidative activity of circulating leukocytes, mainly neutrophils, may lead to a systemic damage, dysfunction/damage of bystander tissues/organs and even further exacerbate secondary local damage. Controlling these pathophysiological processes may be a promising therapeutic strategy and will protect unaffected organs and the injured brain from the secondary damage.

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Neuronal calcium-activated potassium channels of the BK type are activated by membrane depolarization and intracellular Ca2+ ions. It has been suggested that these channels may play a key neuroprotective role during and after brain ischemia, but this hypothesis has so far not been tested by selective BK-channel manipulations in vivo. To elucidate the in vivo contribution of neuronal BK channels in acute focal cerebral ischemia, we performed middle cerebral artery occlusion (MCAO) in mice lacking BK channels (homozygous mice lacking the BK channel alpha subunit, BK−/−). MCAO was performed in BK−/− and WT mice for 90 minutes followed by a 7-hour-reperfusion period. Coronal 1 mm thick sections were stained with 2,3,5-triphenyltetrazolium chloride to reveal the infarction area. We found that transient focal cerebral ischemia by MCAO produced larger infarct volume, more severe neurological deficits, and higher post-ischemic mortality in BK−/− mice compared to WT littermates. However, the regional cerebral blood flow was not significantly different between genotypes as measured by Laser Doppler (LD) flowmetry pre-ischemically, intra-ischemically, and post-ischemically, suggesting that the different impact of MCAO in BK−/− vs. WT was not due to vascular BK channels. Furthermore, when NMDA was injected intracerebrally in non-ischemic mice, NMDA-induced neurotoxicity was found to be larger in BK−/− mice compared to WT. Whole-cell patch clamp recordings from CA1 pyramidal cells in organotypic hippocampal slice cultures revealed that BK channels contribute to rapid action potential repolarization, as previously found in acute slices. When these cultures were exposed to ischemia-like conditions this induced significantly more neuronal death in BK−/− than in WT cultures. These results indicate that neuronal BK channels are important for protection against ischemic brain damage.

Compared to the pencil-beam algorithm, the Monte-Carlo (MC) algorithm is more accurate for dose calculation but time-consuming in proton therapy. To solve this problem, this study uses deep learning to provide fast 3D dose prediction for prostate cancer patients treated with intensity-modulated proton therapy (IMPT). Methods: A novel recurrent U-net (RU-net) architecture was trained to predict the 3D dose distribution. Doses, CT images, and beam spot information from IMPT plans were used to train the RU-net with a five-fold cross-validation. However, predicting the complicated dose properties of the IMPT plan is difficult for neural networks. Instead of the peak-monitor unit (MU) model, this work develops the multi-MU model that adopted more comprehensive inputs and was trained with a combinational loss function. The dose difference between the prediction dose and Monte Carlo (MC) dose was evaluated with gamma analysis, dice similarity coefficient (DSC),and dose-volume histogram (DVH) metrics.The MC dropout was also added to the network to quantify the uncertainty of the model. Results: Compared to the peak-MU model, the multi-MU model led to smaller mean absolute errors (3.03% vs. 2.05%, p = 0.005), higher gamma-passing rate (2 mm, 3%: 97.42% vs. 93.69%, p = 0.005), higher dice similarity coefficient, and smaller relative DVH metrics error (clinical target volume (CTV) D 98% : 3.03% vs. 6.08%, p = 0.017; in Bladder V30: 3.08% vs. 5.28%, p = 0.028; and in Bladder V20: 3.02% vs. 4.42%, p = 0.017). Considering more prior knowledge, the multi-MU model had better-predicted accuracy with a prediction time of less than half a second for each fold. The mean uncertainty value of the multi-MU model is 0.46%, with a dropout rate of 10%. Conclusion: This method was a nearly real-time IMPT dose prediction algorithm with accuracy comparable to the pencil beam (PB) analytical algorithms used in prostate cancer. This RU-net might be used in plan robustness optimization and robustness evaluation in the future.