No abstract

No abstract

A proprioceptive representation of eye position exists in area 3a of primate somatosensory cortex (Wang X, Zhang M, Cohen IS, Goldberg ME. Nat Neurosci 10: 640-646, 2007). This eye position signal is consistent with a fusimotor response (Taylor A, Durbaba R, Ellaway PH, Rawlinson S. J Physiol 571: 711-723, 2006) and has two components during a visually guided saccade task: a short-latency phasic response followed by a tonic response. While the early phasic response can be excitatory or inhibitory, it does not accurately reflect the eye's orbital position. The late tonic response appears to carry the proprioceptive eye position signal, but it is not clear when this component emerges and whether the onset of this signal is reliable. To test the temporal dynamics of the tonic proprioceptive signal, we used an oculomotor smooth pursuit task in which saccadic eye movements and phasic proprioceptive responses are suppressed. Our results show that the tonic proprioceptive eye position signal consistently lags the actual eye position in the orbit by ~60 ms under a variety of eye movement conditions. To confirm the proprioceptive nature of this signal, we also studied the responses of neurons in a vestibuloocular reflex (VOR) task in which the direction of gaze was held constant; response profiles and delay times were similar in this task, suggesting that this signal does not represent angle of gaze and does not receive visual or vestibular inputs. The length of the delay suggests that the proprioceptive eye position signal is unlikely to be used for online visual processing for action, although it could be used to calibrate an efference copy signal.

No abstract

The positive and unlabeled (PU) learning problem focuses on learning a classifier from positive and unlabeled data. Some methods have been developed to solve the PU learning problem. However, they are often limited in practical applications, since only binary classes are involved and cannot easily be adapted to multi-class data. Here we propose a onestep method that directly enables multi-class model to be trained using the given input multi-class data and that predicts the label based on the model decision. Specifically, we construct different convex loss functions for labeled and unlabeled data to learn a discriminant function F . The theoretical analysis on the generalization error bound shows that it is no worse than k √ k times of the fully supervised multi-class classification methods when the size of the data in k classes is of the same order. Finally, our experimental results demonstrate the significance and effectiveness of the proposed algorithm in synthetic and real-world datasets.

No abstract

Background. p38 mitogen-activated protein kinase (MAPK) plays a crucial role in regulating signaling pathways implicated in inflammatory processes leading to diabetic nephropathy (DN). This study aimed to examine p38 MAPK activation in DN and determine whether beraprost sodium (BPS) ameliorates DN by inhibiting inflammation and p38 MAPK signaling pathway in diabetic rats. Methods. Forty male Sprague Dawley (SD) rats were randomly divided into the normal control group, type 2 diabetic group, and BPS treatment group. At the end of the 8-week experiment, we measured renal pathological changes and the activation of the p38 MAPK signaling pathway and inflammation. Result. After BPS treatment, renal function, 24-hour urine protein, lipid profiles, and blood glucose level were improved significantly; meanwhile, inflammation and the expression of p38 MAPK signaling pathway in the diabetic kidney were attenuated. Conclusions. BPS significantly prevented type 2 diabetes induced kidney injury characterized by renal dysfunction and pathological changes. The protective mechanisms are complicated but may be mainly attributed to the inhibition of the p38 MAPK signaling pathway and inflammation in the diabetic kidney.

No abstract