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Abstract-Co-training, a paradigm of semi-supervised learning, is promised to alleviate effectively the shortage of labeled examples in supervised learning. The standard two-view co-training requires the dataset to be described by two views of features, and previous studies have shown that co-training works well if the two views satisfy the sufficiency and independence assumptions. In practice, however, these two assumptions are often not known or ensured (even when the two views are given). More commonly, most supervised datasets are described by one set of attributes (one view). Thus, they need be split into two views in order to apply the standard twoview co-training. In this paper, we first propose a novel approach to empirically verify the two assumptions of co-training given two views. Then, we design several methods to split single view datasets into two views, in order to make co-training work reliably well. Our empirical results show that, given a whole or a large labeled training set, our view verification and splitting methods are quite effective. Unfortunately, co-training is called for precisely when the labeled training set is small. However, given small labeled training sets, we show that the two co-training assumptions are difficult to verify, and view splitting is unreliable. Our conclusions for co-training's effectiveness are mixed. If two views are given, and known to satisfy the two assumptions, co-training works well. Otherwise, based on small labeled training sets, verifying the assumptions or splitting single view into two views are unreliable, thus it is uncertain whether the standard co-training would work or not.

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The incidence of neurodegenerative diseases including Alzheimer's and Parkinson's disease has markedly increased over the past few decades. Oxidative stress is considered to be a common pathophysiological condition resulting in neurotoxicity. Lycium barbarum polysaccharide (LBP) is the major active component of Lycium barbarum L., which exhibit potent antioxidant activity. The current study investigated the neuroprotective effects of LBP in H2O2-treated PC12 cells in vitro and in CoCl2-treated rats in vivo. It was determined that LBP concentration-dependently reversed the H2O2-induced increase in reactive oxygen species (ROS) levels, decrease in cell viability, increase in TUNEL-stained cells, increase in caspase-3 and −9 activity and decrease in mitochondrial membrane potential, indicating the amelioration of mitochondrial apoptosis. Furthermore, LBP inhibited the H2O2-induced decrease in nuclear factor erythroid 2-related factor 2 (Nrf)2 and heme oxygenase (HO)-1 expression and binding of Nrf2 to the promoters of HO-1. Silencing of Nrf2 and inhibition of HO-1 by zinc protoporphyrin IX (ZnPP) reversed the protective effects of LBP against H2O2-resulted neurotoxicity in PC12 cells. In CoCl2-treated rats, it was demonstrated that LBP decreased brain tissue apoptosis, reduced the time spent by rats finding the platform site, decreased escape latencies and reduced the distance traveled to find the platform. In addition, LBP inhibited the CoCl2-induced decrease of Nrf2 and HO-1 expression. Administration of ZnPP also suppressed the protective effects of LBP against CoCl2-resulted neurotoxicity in rats. Thus, the current study indicated that LBP exhibits protective effects against neurotoxicity by upregulating Nrf2/HO-1 signaling. These data may increase understanding regarding the neuroprotective activities of LBP.