Comparsion between Intravenous Delivered Human Fetal Bone Marrow Mesenchymal Stromal Cells and Mononuclear Cells in the Treatment of Rat Cerebral Infarct.

Objective To compare the effecacy of human mesenchymal stromal cell (hMSC) with human mononuclear cell (hMNC) in treating rat cerebral infarct.Methods The SD rat models of cerebral infarct were established by distal middle cerebral artery occlusion (dMCAO). Rats were divided into four groups: sham,ischemia vehicle,MSC,and MNC transplantation groups. For the transplantation group,1×106 hMSCs or hMNCs were intravascularly transplanted into the tail vein 1 hour after the ischemia onset. The ischemia vehicle group received dMCAO surgery and intravascular saline injection 1,3,5,and 7 days after the ischemia onset,and then behavioral tests were performed. At 48 h after the ischemia onset,the abundance of Iba- 1,the symbol of activated microglia,was evaluated in the peri-ischemia striatum area; meanwhile,the neurotrophic factors such as glial cell line-derived neurotrophic factor (GDNF) and brain-derived neurotrophic factor (BDNF) in ipsilateral peri-ischemia striatum area were also measured. Results The relative infarct volume in ischemia vehicle group,hMSC group,and hMNC transplantation group were (37.85±4.40)%,(33.41±3.82)%,and (30.23±3.63)%,respectively. The infarct volumes of MSC group (t=2.100,P=0.034) and MNC group (t=2.109,P=0.0009) were significantly smaller than that of ischemia vehicle group,and that of MNC group was significantly smaller than that of MSC group (t=1.743,P=0.043). One day after transplantation,the score of ischemia vehicle group in limb placing test was (4.32±0.71)%,which was significantly lower than that in sham group (9.73±0.36)% (t=2.178,P=8.61×10-11). The scores of MSC and MNC group,which were (5.09±0.62)% (t=2.1009,P=0.024) and (5.90±0.68)% (t=2.1008,P=0.0001),respectively,were significantly higher than that of ischemia vehicle group; also,the score of MNC group was significantly higher than that of MSC group(t=2.1009,P=0.0165). The contralateral forelimb scores of MSC and MNC groups in beam walking test were (5.56±0.86)% (t=2.120,P=0.020) and (5.13±0.95)% (t=2.131,P=0.003),were both significantly lower than that of ischemia vehicle group [(6.47±0.61)%]. Three days after the transplantation,the limb placing test score of MNC group [(6.91±1.10)%] was significantly higher than that of ischemia vehicle group (5.80±0.82)% (t=2.110,P=0.027). The score of MSC group [(6.30±0.77)%] showed no statistic difference with that of ischemia vehicle group(t=2.101,P=0.199).The contralateral forelimb scores of MNC group in beam walking test [(4.34±0.58)%] was significantly lower than that of ischemia vehicle group [(5.31±0.65)%] (t=2.100,P=0.006) and MSC group [(4.92±0.53)%] (t=2.100,P=0.041); there was no statistic difference between MSC group and ischemia vehicle group (t=2.109,P=0.139). The relative abundance of Iba- 1 in sham,ischemia vehicle,MSC,and MNC groups was 1.00+0.00,1.72±0.21,1.23±0.08,and 1.48±0.06,respectively. The Iba-1 relative abundance of ischemia vehicle group was significantly higher than that of sham group (t=2.262,P=2.9×10-6). The Iba-1 relative abundances of both MSC (t=2.178,P=3.91×10-5)and MNC (t=2.200,P=0.007)groups were significantly lower than that of ischemia vehicle group. It was also significantly lower in MNC group than in MSC group also (t=2.120,P=7.09×10-6). Three days after transplantation,the BDNF and GDNF levels of MSC group,which were (531.127±73.176)pg/mg (t=2.109,P=0.003)and(127.780±16.733)pg/mg(t=2.100,P=2.76×10-5),respectively,were significantly higher than those of ischemia vehicle group,which were (401.988±89.006)pg/mg and (86.278±14.832) pg/mg,respectively. The BDNF and GDNF levels of MNC group,which were (627.429±65.646)pg/mg (t=2.144,P=0.017) and (153.117±20.443)pg/mg (t=2.109,P=0.010),respectively,were all significantly higher than that of MSC group. At day 7,the BDNF and GDNF levels of MSC group,which were (504.776±83.282)pg/mg (t=2.101,P=0.005) and (81.641±11.019)pg/mg (t=2.100,P=0.002),respectively,were significantly higher than those of ischemia vehicle group,which were (389.257±70.440)pg/mg and (64.322±9.855) pg/mg,respectively. The BDNF and GDNF levels of MNC group,which were (589.068±63.323)pg/mg (t=2.100,P=0.027) and (102.161±19.932)pg/mg (t=2.144,P=0.017),respectively,were all significantly higher than that of MSC group. Conclusions Both hMSC and hMNC are beneficial to the ischemia-damaged brain when they are intravascularly transplanted within 1 h after the onset of ischemia. The anti-inflammation ability and secretion of neurotrophic factors are the underlying mechanisms of the therapeutic effects. MNC is more effective than MSC in reducing infarct area and improving behaviors,which might be explained by the fact that MNC induces more GDNF and BDNF in brain than MSC.

The establishment and validation of a prediction model for traumatic intracranial injury patients: a reliable nomogram.

Objective: Traumatic brain injury (TBI) leads to death and disability. This study developed an effective prognostic nomogram for assessing the risk factors for TBI mortality. Method: Data were extracted from an online database called "Multiparameter Intelligent Monitoring in Intensive Care IV" (MIMIC IV). The ICD code obtained data from 2,551 TBI persons (first ICU stay, >18 years old) from this database. R divided samples into 7:3 training and testing cohorts. The univariate analysis determined whether the two cohorts differed statistically in baseline data. This research used forward stepwise logistic regression after independent prognostic factors for these TBI patients. The optimal variables were selected for the model by the optimal subset method. The optimal feature subsets in pattern recognition improved the model prediction, and the minimum BIC forest of the high-dimensional mixed graph model achieved a better prediction effect. A nomogram-labeled TBI-IHM model containing these risk factors was made by nomology in State software. Least Squares OLS was used to build linear models, and then the Receiver Operating Characteristic (ROC) curve was plotted. The TBI-IHM nomogram model's validity was determined by receiver operating characteristic curves (AUCs), correction curve, Hosmer-Lemeshow test, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision-curve analysis (DCA). Result: The eight features with a minimal BIC model were mannitol use, mechanical ventilation, vasopressor use, international normalized ratio, urea nitrogen, respiratory rate, and cerebrovascular disease. The proposed nomogram (TBI-IHM model) was the best mortality prediction model, with better discrimination and superior model fitting for severely ill TBI patients staying in ICU. The model's receiver operating characteristic curve (ROC) was the best compared to the seven other models. It might be clinically helpful for doctors to make clinical decisions. Conclusion: The proposed nomogram (TBI-IHM model) has significant potential as a clinical utility in predicting mortality in TBI patients.

Plasma pituitary adenylate cyclase-activating polypeptide concentrations and mortality after acute spontaneous basal ganglia hemorrhage.

BACKGROUND: Plasma pituitary adenylate cyclase activating polypeptide (PACAP) concentrations are elevated after traumatic brain injury. We assessed the prognostic value of PACAP for short-term and long-term mortality of acute intracerebral hemorrhage (ICH) patients. METHODS: A total of 150 patients and 150 age- and gender- matched healthy controls were recruited. The plasma PACAP concentrations were measured using sandwich immunoassays. ICH severity was assessed using hematoma volume and National Institutes of Health Stroke Scale (NIHSS) score. The end points included 1-week mortality and 6-month mortality. The relationships between plasma PACAP concentrations and ICH severity and the end points were analyzed statistically. RESULTS: Plasma PACAP concentrations were statistically significantly higher in the ICH patients than in the healthy controls and were correlated positively with hematoma volumes and NIHSS scores using a multivariate linear regression. Multivariate analysis results indicated that plasma PACAP concentration was an independent predictor of 1-week mortality, 6-month mortality and 6-month overall survival. It also had high predictive value based on receiver operating characteristic curve. CONCLUSIONS: Plasma PACAP concentrations are increased and are highly associated with the severity of ICH; PACAP may be a good predictor of short-term and long-term mortality of ICH.