Multi-target recognition and positioning using robots in orchards is a challenging task in modern precision agriculture owing to the presence of complex noise disturbance, including wind disturbance, changing illumination, and branch and leaf shading. To obtain the target information for a bud-cutting robotic operation, we employed a modified deep learning algorithm for the fast and precise recognition of banana fruits, inflorescence axes, and flower buds. Thus, the cutting point on the inflorescence axis was identified using an edge detection algorithm and geometric calculation. We proposed a modified YOLOv3 model based on clustering optimization and clarified the influence of front-lighting and backlighting on the model. Image segmentation and denoising were performed to obtain the edge images of the flower buds and inflorescence axes. The spatial geometry model was constructed on this basis. The center of symmetry and centroid were calculated for the edges of the flower buds. The equation for the position of the inflorescence axis was established, and the cutting point was determined. Experimental results showed that the modified YOLOv3 model based on clustering optimization showed excellent performance with good balance between speed and precision both under front-lighting and backlighting conditions. The total pixel positioning error between the calculated and manually determined optimal cutting point in the flower bud was 4 and 5 pixels under the front-lighting and backlighting conditions, respectively. The percentage of images that met the positioning requirements was 93 and 90%, respectively. The results indicate that the new method can satisfy the real-time operating requirements for the banana bud-cutting robot.

Vitamin D deficiency is associated with the increase of circulating cholesterol in the people of northern China by enhancing hepatic cholesterol biosynthesis, which was linked to the reduction of transcriptional activity of VDR.

Kainate-type glutamate receptors play critical roles in excitatory synaptic transmission and synaptic plasticity in the brain. GluK1 and GluK2 possess fundamentally different capabilities in surface trafficking as well as synaptic targeting in hippocampal CA1 neurons. Here we find that the excitatory postsynaptic currents (EPSCs) are significantly increased by the chimeric GluK1(SPGluK2) receptor, in which the signal peptide of GluK1 is replaced with that of GluK2. Coexpression of GluK1 signal peptide completely suppresses the gain in trafficking ability of GluK1(SPGluK2), indicating that the signal peptide represses receptor trafficking in a trans manner. Furthermore, we demonstrate that the signal peptide directly interacts with the amino-terminal domain (ATD) to inhibit the synaptic and surface expression of GluK1. Thus, we have uncovered a trafficking mechanism for kainate receptors and propose that the cleaved signal peptide behaves as a ligand of GluK1, through binding with the ATD, to repress forward trafficking of the receptor.

The detrimental role of hepatic lipotoxicity has been well-implicated in the pathogenesis of NAFLD. Previously, we reported that inhibiting autophagy aggravated saturated fatty acid (SFA)-induced hepatotoxicity. Insulin, a physiological inhibitor of autophagy, is commonly increased within NAFLD mainly caused by insulin resistance. We therefore hypothesized that insulin augments the sensitivity of hepatocyte to SFA-induced lipotoxicity. The present study was conducted via employing human and mouse hepatocytes, which were exposed to SFAs, insulin, or their combination. Unexpectedly, our results indicated that insulin protected hepatocytes against SFA-induced lipotoxicity, based on the LDH, MTT, and nuclear morphological measurements, and the detection from cleaved-Parp-1 and -caspase-3 expressions. We subsequently clarified that insulin led to a rapid and short-period inhibition of autophagy, which was gradually recovered after 1 h incubation in hepatocytes, and such extent of inhibition was insufficient to aggravate SFA-induced lipotoxicity. The mechanistic study revealed that insulin-induced alleviation of ER stress contributed to its hepatoprotective role. Pre-treating hepatocytes with insulin significantly stimulated phosphorylated-Akt and reversed SFA-induced up-regulation of p53. Chemical inhibition of p53 by pifithrin-α robustly prevented palmitate-induced cell death. The PI3K/Akt pathway blockade by its special antagonist abolished the protective role of insulin against SFA-induced lipotoxicity and p53 up-regulation. Furthermore, we observed that insulin promoted intracellular TG deposits in hepatocytes in the present of palmitate. However, blocking TG accumulation via genetically silencing DGAT-2 did not prevent insulin-protected lipotoxicity. Our study demonstrated that insulin strongly protected against SFA-induced lipotoxicity in hepatocytes mechanistically through alleviating ER stress via a PI3K/Akt/p53 involved pathway but independently from autophagy.