Abstract-Convolutional network techniques have recently achieved great success in vision based detection tasks. This paper introduces the recent development of our research on transplanting the fully convolutional network technique to the detection tasks on 3D range scan data. Specifically, the scenario is set as the vehicle detection task from the range data of Velodyne 64E lidar. We proposes to present the data in a 2D point map and use a single 2D end-to-end fully convolutional network to predict the objectness confidence and the bounding boxes simultaneously. By carefully design the bounding box encoding, it is able to predict full 3D bounding boxes even using a 2D convolutional network. Experiments on the KITTI dataset shows the state-ofthe-art performance of the proposed method.

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In insects, juvenile hormone (JH) and the steroid hormone ecdysone have opposing effects on regulation of the larval-pupal transition. Although increasing evidence suggests that JH represses ecdysone biosynthesis during larval development, the mechanism underlying this repression is not well understood. Here, we demonstrate that the expression of the Krüppel homolog 1 (Kr-h1), a gene encoding a transcription factor that mediates JH signaling, in ecdysone-producing organ prothoracic gland (PG) represses ecdysone biosynthesis by directly inhibiting the transcription of steroidogenic enzymes in both and Application of a JH mimic on ex vivo cultured PGs from and larvae induces expression and inhibits the transcription of steroidogenic enzymes. In addition, PG-specific knockdown of promotes-while overexpression hampers-ecdysone production and pupariation. We further find that Kr-h1 inhibits the transcription of steroidogenic enzymes by directly binding to their promoters to induce promoter DNA methylation. Finally, we show that Kr-h1 does not affect DNA replication in PG cells and that the reduction of PG size mediated by overexpression can be rescued by feeding ecdysone. Taken together, our data indicate direct and conserved Kr-h1 repression of insect ecdysone biosynthesis in response to JH stimulation, providing insights into mechanisms underlying the antagonistic roles of JH and ecdysone.

Recent explosion of biological data brings a great challenge for the traditional methods. With increasing scale of large data sets, much advanced tools are required for the depth interpretation problems. As a rapid-developing technology, metabolomics can provide a useful method to discover the pathogenesis of diseases. This study was explored the dynamic changes of metabolic profiling in cells model and Balb/C nude-mouse model of prostate cancer, to clarify the therapeutic mechanism of berberine, as a case study. Here, we report the findings of comprehensive metabolomic investigation of berberine on prostate cancer by high-throughput ultra performance liquid chromatography-mass spectrometry coupled with pattern recognition methods and network pathway analysis. A total of 30 metabolite biomarkers in blood and 14 metabolites in prostate cancer cell were found from large-scale biological data sets (serum and cell metabolome), respectively. We have constructed a comprehensive metabolic characterization network of berberine to protect against prostate cancer. Furthermore, the results showed that berberine could provide satisfactory effects on prostate cancer via regulating the perturbed pathway. Overall, these findings illustrated the power of the ultra performance liquid chromatography-mass spectrometry with the pattern recognition analysis for large-scale biological data sets may be promising to yield a valuable tool that insight into the drug action mechanisms and drug discovery as well as help guide testable predictions.

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Oxygen-to-oxygen coupling, direct H-abstraction and oxygen-to-(α)carbon nucleophilic substitution processes have been investigated for both the singlet and triplet self-reaction of C(2)H(5)O(2) radicals at the CCSD(T)/cc-pVDZ//B3LYP/6-311G(2d,2p) level to evaluate the reaction mechanisms, possible products and rate constants. The calculated results show that the title reaction mainly occurs through the singlet oxygen-to-oxygen coupling mechanism with the formation of entrance tetroxide intermediates, and the most dominant product is C(2)H(5)O + HO(2) + CH(3)CHO (P5) generated in channel R5. Beginning from the radical products of P5 (C(2)H(5)O, HO(2)) and reactant (C(2)H(5)O(2)), five secondary reactions HO(2) + HO(2) (a), HO(2) + C(2)H(5)O (b), C(2)H(5)O + C(2)H(5)O (c), HO(2) + C(2)H(5)O(2) (d), and C(2)H(5)O + C(2)H(5)O(2) (e) mainly proceed on the triplet potential energy surface. Among these reactions, (a), (b), and (d) are kinetically favorable because of lower barrier heights. The calculated rate constants of channel R5 between 200 and 295 K are almost independent of the temperature, which is in agreement with the experimental report. With regard to the final products distribution, CH(3)CHO, C(2)H(5)OH, C(2)H(5)OOH, H(2)O(2), and (3)O(2) are predicted to be major, whereas C(2)H(5)OOC(2)H(5) should be in minor amount.

Screening the active compounds of herbal medicines is of importance to modern drug discovery. In this work, an integrative strategy was established to discover the effective compounds and their therapeutic targets using Phellodendri Amurensis cortex (PAC) aimed at inhibiting prostate cancer as a case study. We found that PAC could be inhibited the growth of xenograft tumours of prostate cancer. Global constituents and serum metabolites were analysed by UPLC-MS based on the established chinmedomics analysis method, a total of 54 peaks in the spectrum of PAC were characterised in vitro and 38 peaks were characterised in vivo. Among the 38 compounds characterised in vivo, 29 prototype components were absorbed in serum and nine metabolites were identified in vivo. Thirty-four metabolic biomarkers were related to prostate cancer, and PAC could observably reverse these metabolic biomarkers to their normal level and regulate the disturbed metabolic profile to a healthy state. A chinmedomics approach showed that ten absorbed constituents, as effective compounds, were associated with the therapeutic effect of PAC. In combination with bioactivity assays, the action targets were also predicted and discovered. As an illustrative case study, the strategy was successfully applied to high-throughput screening of active compounds from herbal medicine.