Besides its wide range of action as a proinflammatory cytokine in the immune system, interleukin-6 (IL-6) has also attracted much attention due to its influence on the nervous system. In the present study we show that the designer fusion protein H-IL-6, consisting of IL-6 and its specific receptor IL-6R-␣, but not IL-6 alone, mediates both neuro-as well as gliogenesis. Using immunocytochemistry, Western blot, and patch-clamp recording, we demonstrate that H-IL-6 induces the differentiation of neural stem cells (NSCs) specifically into glutamate-responsive neurons and two morphological distinctive astroglia cell types. H-IL-6 -activated neurogenesis seems to be induced by the MAPK/CREB (mitogenactivated protein kinase/cAMP response element-binding protein) cascade, whereas gliogenesis is mediated via the STAT-3 (signal transducers and activators of transcription protein-3) signaling pathway. Our finding that IL-6 mediates both processes depending on its specific soluble receptor sIL-6R-␣ has implications for the potential treatment of neurodegenerative diseases. INTRODUCTIONIn recent years it has been noted that the adult brain has "self-repair-capacity" to replace lost neurons in several selected regions of the CNS such as the olfactory bulb, hippocampus, adult human subependymal zone, and the cortex. Active neurogenesis occurs in the subgranular zone (SGZ) of the hippocampal dentate gyrus, and in the subventricular zone (SVZ) of the lateral ventricles (Kempermann and Gage, 1999;Gage, 2000;Okano, 2002). Neural stem cells (NSCs) within these neurogenic regions can self-renew, proliferate, and differentiate into neurons or glia, providing a reservoir for replacement of cells lost during normal cell turnover and after brain injury. Newborn neurons and glia then migrate to appropriate regions in the brain and integrate into neuronal circuits (Brazel and Rao, 2004;Campos, 2004;Ming and Song, 2005;Reynolds and Rietze, 2005). Recent findings show that impairment of neurogenesis is sufficient to deteriorate learning and memory, hinting that abnormalities in the proliferation and differentiation of NSCs could play a role in the pathogenesis of cognitive disorders such as Alzheimer's disease (Shors, 2004). The question facing modern medicine is how best to use NSCs to produce functional recovery in neurodegenerative disorders in the aging brain (Arvidsson et al., 2002;Sugaya, 2005;Tanne, 2005).The interleukin-6 (IL-6) receptor family is comprised of multisubunit receptors associated with a common receptor subunit, the transmembrane protein gp130 (Taga and Kishimoto, 1997;Heinrich et al., 2003). Natural soluble forms of those integral-membrane receptors have been described for numerous cytokines (Jones and Rose-John, 2002). Although most of them act as antagonists by competing for their ligands with the membrane bound receptors, the soluble IL-6R (sIL-6R), which is generated by limited proteolysis (shedding) or alternative splicing, behaves as an agonist (Jones and Rose-John, 2002;Rose-John and Neurath, 2004). Thus, the co...

N-methyl-D-aspartate (NMDA) receptors (NMDARs) are implicated in synaptic plasticity and modulation of glutamatergic excitatory transmission. Effect of NMDAR activation on inhibitory GABAergic transmission remains largely unknown. Here, we report that a brief application of NMDA could induce two distinct actions in CA1 pyramidal neurons in mouse hippocampal slices: 1) an inward current attributed to activation of postsynaptic NMDARs; and 2) fast phasic synaptic currents, namely spontaneous inhibitory postsynaptic currents (sIPSCs), mediated by GABA(A) receptors in pyramidal neurons. The mean amplitude of sIPSCs was also increased by NMDA. This profound increase in the sIPSC frequency and amplitude was markedly suppressed by the sodium channel blocker TTX, whereas the frequency and mean amplitude of miniature IPSCs were not significantly affected by NMDA, suggesting that NMDA elicits repetitive firing in GABAergic interneurons, thereby leading to GABA release from multiple synaptic sites of single GABAergic axons. We found that the NMDAR open-channel blocker MK-801 injected into recorded pyramidal neurons suppressed the NMDA-induced increase of sIPSCs, which raises the possibility that the firing of interneurons may not be the sole factor and certain retrograde messengers may also be involved in the NMDA-mediated enhancement of GABAergic transmission. Our results from pharmacological tests suggest that the nitric oxide signaling pathway is mobilized by NMDAR activation in CA1 pyramidal neurons, which in turn retrogradely facilitates GABA release from the presynaptic terminals. Thus NMDARs at glutamatergic synapses on both CA1 pyramidal neurons and interneurons appear to exert feedback and feedforward inhibition for determining the spike timing of the hippocampal microcircuit.

Background:Accurate prognostic estimation for esophageal cancer (EC) patients plays an important role in the process of clinical decision-making. The objective of this study was to develop an effective model to predict the 5-year survival status of EC patients using machine learning (ML) algorithms. Methods:We retrieved the information of patients diagnosed with EC between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) Program, including 24 features. A total of 8 ML models were applied to the selected dataset to classify the EC patients in terms of 5-year survival status, including 3 newly developed gradient boosting models (GBM), XGBoost, CatBoost, and LightGBM, 2 commonly used tree-based models, gradient boosting decision trees (GBDT) and random forest (RF), and 3 other ML models, artificial neural networks (ANN), naive Bayes (NB), and support vector machines (SVM).A 5-fold cross-validation was used in model performance measurement. Results: After excluding records with missing data, the final study population comprised 10,588 patients.Feature selection was conducted based on the χ 2 test, however, the experiment results showed that the complete dataset provided better prediction of outcomes than the dataset with removal of non-significant features. Among the 8 models, XGBoost had the best performance [area under the receiver operating characteristic (ROC) curve (AUC): 0.852 for XGBoost, 0.849 for CatBoost, 0.850 for LightGBM, 0.846 for GBDT, 0.838 for RF, 0.844 for ANN, 0.833 for NB, and 0.789 for SVM]. The accuracy and logistic loss of XGBoost were 0.875 and 0.301, respectively, which were also the best performances. In the XGBoost model, the SHapley Additive exPlanations (SHAP) value was calculated and the result indicated that the four features:reason no cancer-directed surgery, Surg Prim Site, age, and stage group had the greatest impact on predicting the outcomes. Conclusions:The XGBoost model and the complete dataset can be used to construct an accurate prognostic model for patients diagnosed with EC which may be applicable in clinical practice in the future.