Differential effects of circadian typology on sleep-related symptoms,physical fatigue and psychological well-being in relation to resilience

Various physiological and psychological functions are influenced by circadian typology (CT), which was reported to be related to resilience. However, few studies have assessed the effects of CT in relation to resilience. The aim of the present study was to assess the influence of CT on sleep-related symptoms, physical fatigue and psychological well-being in relation to resilience. The present study included a total of 1794 healthy hospital employees, and they completed the Morningness–Eveningness Questionnaire, Connor–Davidson Resilience Scale, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, Fatigue Severity Scale, Hospital Anxiety and Depression Scale and World Health Organization Quality of Life Scale Abbreviated Version. Subjects with evening type showed lower sleep quality, more daytime sleepiness and physical fatigue than neither types and morning types. Additionally, evening types were more depressed and anxious and reported a poorer quality of life. CT was found to be a significant predictor of sleep quality, but CT was minimally associated with physical fatigue and psychological well-being in the regression analysis. Instead, resilience was substantially related to all of the variables measured. In conclusion, CT independently predicts sleep quality, but the effects of CT on physical fatigue and psychological well-being are negligible compared to those of resilience.     

Mass Collaboration in Earthquake Risk Management

The mechanism of mass collaboration in risk management was studied during the Sichuan earthquake under a Web-based “PeopleFinder” project, where information is contributed and shared among mass contributors. The case study is provided by a great earthquake that happened in Wenchuan County, Sichuan Province, of southwestern China at 2:28 p.m. on May 12, 2008. We witnessed and experienced the rescue and relief efforts for the great earthquake. In this article, two fundamental frameworks are developed to study the mechanism of mass collaboration. Mass collaboration is proven to be effective in a big public crisis such as the Sichuan earthquake.     

N-糖蛋白去糖基化酶（PNGase）的研究进展

N-糖蛋白去糖基化酶（PNGase）是一种广泛存在于真菌、植物、哺乳动物中的去糖基化酶，可以水解N-糖蛋白或 N-糖肽上天冬酰胺与寡糖链连接的化学键，并释放出完整的N-寡糖。PNGase在生物体内参与蛋白质降解、器官发育、个体生长等过程。人PNGase基因功能缺陷会导致先天性去糖基化障碍，小鼠PNGase缺陷会导致胚胎致死性，线虫PNGase缺陷使其寿命下降。本文对PNGase在不同物种的分布、蛋白质结构、酶学功能及生物学功能进行阐述，为PNGase的生理病理功能及致病机制的基础研究提供思路，为PNGase作为糖生物学工具酶或药物开发的创新应用研究奠定基础。     

Force to Divide: Structural and Mechanical Requirements for Actomyosin Ring Contraction

One of the unresolved questions in the field of cell division is how the actomyosin cytoskeleton remains structurally organized while generating the contractile force to divide one cell into two. In analogy to the actomyosin-based force production mechanism in striated muscle, it was originally proposed that contractile stress in the actomyosin ring is generated via a sliding filament mechanism within an organized sarcomere-like array. However, over the last 30 years, ultrastructural and functional studies have noted important distinctions between cytokinetic structures in dividing cells and muscle sarcomeres. Myosin-II motor activity is not always required, and there is evidence that actin depolymerization contributes to contraction. In this Review, the architecture and contractile dynamics of the actomyosin ring at the cell division plane will be discussed. We will report the interdisciplinary advances in the field as well as their integration into a mechanistic understanding of contraction in cell division and in other biological processes that rely on an actomyosin-based force-generating system.     

美沙酮维持治疗188例海洛因成瘾者的临床疗效分析

目的：了解188例海洛因成瘾者在本门诊治疗的情况以及美沙酮口服液治疗188例海洛因成瘾者的观察分析。方法：收集本门诊由国家工作组制定的申请表及基线调查表188份,均由门诊医生实名登记和调查。结果：通过美沙维持治疗,患者和其家属均表示认可和接受,均认为是有效,治疗方法是可行的。结论：患者恢复了自信,可维持正常人的生活,67.2%的静脉注射海洛因的患者减少了注射的次数,降低了感染爱滋病的机率（见表1,P〈0.01）。但同时,如何使患者维持治疗时间的长久,需要家庭、社会多方面的支持等因素有待探讨。     

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.