神经递质和调质参与导水管周围灰质痛觉调控的研究进展

导水管周围灰质(periaqueductal gray,PAG)在疼痛的调控过程中处于一个不可或缺的位置.其不仅是痛觉信息上行传递的重要部位,还是疼痛抑制系统的重要组成部分.在PAG,包括γ-氨基丁酸(γ-aminobutyric acid,GABA)、5-羟色胺(5-hydroxytryptamine,5-HT)和谷氨酸(glutamate,Glu)在内的神经递质以及内源性阿片肽(endogenous opioid peptides,EOP)和内源性大麻素(endocannabinoid,e CB)为代表的神经调质都参与了PAG对疼痛的信息传递以及调节.本文重点综述GABA、5-HT、Glu、EOP和eCB在PAG参与疼痛生理调控机制的研究进展,以期为中枢神经系统的镇痛研究提供一定的理论基础.     

“绿色革命”新进展:赤霉素与氮营养双重调控的表观修饰助力水稻高产高效育种

以半矮秆育种为代表的“绿色革命”极大地提高了作物产量,但也带来氮营养利用效率降低的严重问题。“绿色革命”主要基于调控赤霉素的代谢和信号转导而实现。前期的研究发现,赤霉素信号转导关键因子DELLA蛋白通过调控GRF4而负调控氮素的吸收利用,为半矮秆品系氮利用效率低的问题提供了解决方案。最近的一项研究进一步揭示了GA信号途径与氮响应交叉互作的新机制。该研究发现水稻(Oryza sativa)NGR5是氮素调控分蘖数目的一个关键基因,其表达受氮诱导。通过招募PRC2,NGR5对D14和OsSPL14等分蘖抑制基因所在位点进行H3K27me3甲基化修饰,从而抑制其表达。而在半矮秆背景下超表达NGR5可以提高低氮水平下的水稻产量。NGR5同时也被发现为赤霉素受体GID1的一个新靶标,受到其负调控。该研究发现了调控赤霉素信号通路的新机制,并对高产高效的新一代“绿色革命”育种实践具有重要启示。     

Solution structure of the N‐terminal domain of DC‐UbP/UBTD2 and its interaction with ubiquitin

DC‐UbP/UBTD2 is a ubiquitin (Ub) domain‐containing protein first identified from dendritic cells, and is implicated in ubiquitination pathway. The solution structure and backbone dynamics of the C‐terminal Ub‐like (UbL) domain were elucidated in our previous work. To further understand the biological function of DC‐UbP, we then solved the solution structure of the N‐terminal domain of DC‐UbP (DC‐UbP_N) and studied its Ub binding properties by NMR techniques. The results show that DC‐UbP_N holds a novel structural fold and acts as a Ub‐binding domain (UBD) but with low affinity. This implies that the DC‐UbP protein, composing of a combination of both UbL and UBD domains, might play an important role in regulating protein ubiquitination and delivery of ubiquitinated substrates in eukaryotic cells.     

Fast, efficient and selective deprotection of the tert-butoxycarbonyl (Boc) group using HCl/dioxane (4 m).

Fast, efficient and selective deprotection of the tert-butoxycarbonyl (Boc) group of various amino acids and peptides was achieved by using hydrogen chloride (4 m) in anhydrous dioxane solution for 30 min at room temperature. In the cases studied in our laboratory, this protocol provided superior selectivity to deprotect Nalpha-Boc groups in the presence of tert-butyl esters and tert-butyl ethers, including thio-tert-butyl ethers, but not phenolic tert-butyl ethers.     

Diet of the Indochinese silvered langur (Trachypithecus germaini) in Kien Luong Karst area,Kien Giang Province

The Indochinese silvered langur (Trachypithecus germaini) is distributed to the west of Mekong River in Cambodia, Lao PDR, Thailand and Vietnam. During a two‐year study, from May 2014 to May 2016, we collected 320.44 hr of behavior, with 17,040 feeding bouts recorded (142 hr) for T. germaini on Chua Hang Karst Mountain, Kien Luong District, Kien Giang Province, Vietnam. Feeding accounted for 45% of the Indochinese silvered langurs’ activity budget. The plant diet of the Indochinese silvered langurs was principally composed of young leaves (58%), followed by mature leaves (9.5%), fruits (22.7%), flowers (4.7%), buds (3.3%), petioles (1.2%), and other (0.5%). A total of 58 plant species were fed on by the silvered langurs, and leaves of eight species (Phyllathus reticulatus, Ficus rumphii, Ficus tinctoria, Ficus microcarpa, Cayratia trifolia, Streblus ilicifolia, Combretum latifolium, and Streblus asper) were fed on throughout the year. P. reticulatus was most frequently eaten (13.9% feeding time, n = 1,733). Food selection differed significantly between months and seasons. The Indochinese silvered langurs ate 27 plant species in the wet season compared with 23 plant species in the dry season. Leaf chemical composition of two food categories, 16 eaten species (with 10 most frequently consumed species and six least consumed species), and four noneaten species, were analyzed. Feeding samples from eaten species in the Indochinese silvered langurs's diet contained lower amounts of condensed tannin, lignin, protein, ash, and lipids, but a higher amount of total sugar compared with samples from noneaten species. Furthermore, the most frequently consumed species contained lower amounts of lignin compared with the less frequently consumed species. Using a generalized linear model with five variables, including neutral detergent fiber (NDF), total sugar, lignin, lipid, and calcium (Ca) indicated that NDF positively correlated and lignin content negatively correlated with feeding records in the diet of these langur.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

Compatible Models of Carbon Content of Individual Trees on a Cunninghamia lanceolata Plantation in Fujian Province,China

We tried to establish compatible carbon content models of individual trees for a Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantation from Fujian province in southeast China. In general, compatibility requires that the sum of components equal the whole tree, meaning that the sum of percentages calculated from component equations should equal 100%. Thus, we used multiple approaches to simulate carbon content in boles, branches, foliage leaves, roots and the whole individual trees. The approaches included (i) single optimal fitting (SOF), (ii) nonlinear adjustment in proportion (NAP) and (iii) nonlinear seemingly unrelated regression (NSUR). These approaches were used in combination with variables relating diameter at breast height (D) and tree height (H), such as D, D²H, DH and D&H (where D&H means two separate variables in bivariate model). Power, exponential and polynomial functions were tested as well as a new general function model was proposed by this study. Weighted least squares regression models were employed to eliminate heteroscedasticity. Model performances were evaluated by using mean residuals, residual variance, mean square error and the determination coefficient. The results indicated that models with two dimensional variables (DH, D²H and D&H) were always superior to those with a single variable (D). The D&H variable combination was found to be the most useful predictor. Of all the approaches, SOF could establish a single optimal model separately, but there were deviations in estimating results due to existing incompatibilities, while NAP and NSUR could ensure predictions compatibility. Simultaneously, we found that the new general model had better accuracy than others. In conclusion, we recommend that the new general model be used to estimate carbon content for Chinese fir and considered for other vegetation types as well.