Characterizing the temporally stable structure of community evolution in intra-urban origin-destination networks

Intra-urban origin-destination (OD) network communities evolve throughout the day, indicating changing groups of closely connected regions. Under this variation, groups of regions with high consistency of community affiliation characterize the temporally stable structure of the evolution process, aiding in comprehending urban dynamics. However, how to quantify this consistency and identify these groups are open questions. In this study, we introduce the consensus OD network to quantify the consistency of community affiliation among regions. Furthermore, the temporally stable community decomposition method is proposed to identify groups of regions with high internal and low external consistency (named "stable groups"), where each group consists of temporally stable cores and attaching peripheries. Wuhan taxi data is used to verify our methods. On the hourly time scale, eleven stable groups containing 82.9% of regions are identified. This high percentage suggests that dynamic communities can be well organized via cores. Moreover, stable groups are spatially closed and more likely to distribute within a single district and separated by water bodies. Cores exhibit higher POI entropy and more healthcare and shopping services than peripheries. Our methods and empirical findings contribute to some practical issues, such as urban area division, polycentric evaluation and construction, and infectious disease control

Which sample type is better for Xpert MTB/RIF to diagnose adult and pediatric pulmonary tuberculosis?

OBJECTIVE: This review aimed to identify proper respiratory-related sample types for adult and pediatric pulmonary tuberculosis (PTB), respectively, by comparing performance of Xpert MTB/RIF when using bronchoalveolar lavage (BAL), induced sputum (IS), expectorated sputum (ES), nasopharyngeal aspirates (NPAs), and gastric aspiration (GA) as sample. METHODS: Articles were searched in Web of Science, PubMed, and Ovid from inception up to 29 June 2020. Pooled sensitivity and specificity were calculated, each with a 95% confidence interval (CI). Quality assessment and heterogeneity evaluation across included studies were performed. RESULTS: A total of 50 articles were included. The respective sensitivity and specificity were 87% (95% CI: 0.84-0.89), 91% (95% CI: 0.90-0.92) and 95% (95% CI: 0.93-0.97) in the adult BAL group; 90% (95% CI: 0.88-0.91), 98% (95% CI: 0.97-0.98) and 97% (95% CI: 0.95-0.99) in the adult ES group; 86% (95% CI: 0.84-0.89) and 97% (95% CI: 0.96-0.98) in the adult IS group. Xpert MTB/RIF showed the sensitivity and specificity of 14% (95% CI: 0.10-0.19) and 99% (95% CI: 0.97-1.00) in the pediatric ES group; 80% (95% CI: 0.72-0.87) and 94% (95% CI: 0.92-0.95) in the pediatric GA group; 67% (95% CI: 0.62-0.72) and 99% (95% CI: 0.98-0.99) in the pediatric IS group; and 54% (95% CI: 0.43-0.64) and 99% (95% CI: 0.97-0.99) in the pediatric NPA group. The heterogeneity across included studies was deemed acceptable. CONCLUSION: Considering diagnostic accuracy, cost and sampling process, ES was a better choice than other sample types for diagnosing adult PTB, especially HIV-associated PTB. GA might be more suitable than other sample types for diagnosing pediatric PTB. The actual choice of sample types should also consider the needs of specific situations

Machine Learning in Cardio-Oncology: New Insights from an Emerging Discipline

A growing body of evidence on a wide spectrum of adverse cardiac events following oncologic therapies has led to the emergence of cardio-oncology as an increasingly relevant interdisciplinary specialty. This also calls for better risk-stratification for patients undergoing cancer treatment. Machine learning (ML), a popular branch discipline of artificial intelligence that tackles complex big data problems by identifying interaction patterns among variables, has seen increasing usage in cardio-oncology studies for risk stratification. The objective of this comprehensive review is to outline the application of ML approaches in cardio-oncology, including deep learning, artificial neural networks, random forest and summarize the cardiotoxicity identified by ML. The current literature shows that ML has been applied for the prediction, diagnosis and treatment of cardiotoxicity in cancer patients. In addition, role of ML in gender and racial disparities for cardiac outcomes and potential future directions of cardio-oncology are discussed. It is essential to establish dedicated multidisciplinary teams in the hospital and educate medical professionals to become familiar and proficient in ML in the future.</p

COVID-19 causes record decline in global CO2 emissions

The considerable cessation of human activities during the COVID-19 pandemic has affected global energy use and CO2 emissions. Here we show the unprecedented decrease in global fossil CO2 emissions from January to April 2020 was of 7.8% (938 Mt CO2 with a +6.8% of 2-{\sigma} uncertainty) when compared with the period last year. In addition other emerging estimates of COVID impacts based on monthly energy supply or estimated parameters, this study contributes to another step that constructed the near-real-time daily CO2 emission inventories based on activity from power generation (for 29 countries), industry (for 73 countries), road transportation (for 406 cities), aviation and maritime transportation and commercial and residential sectors emissions (for 206 countries). The estimates distinguished the decline of CO2 due to COVID-19 from the daily, weekly and seasonal variations as well as the holiday events. The COVID-related decreases in CO2 emissions in road transportation (340.4 Mt CO2, -15.5%), power (292.5 Mt CO2, -6.4% compared to 2019), industry (136.2 Mt CO2, -4.4%), aviation (92.8 Mt CO2, -28.9%), residential (43.4 Mt CO2, -2.7%), and international shipping (35.9Mt CO2, -15%). Regionally, decreases in China were the largest and earliest (234.5 Mt CO2,-6.9%), followed by Europe (EU-27 & UK) (138.3 Mt CO2, -12.0%) and the U.S. (162.4 Mt CO2, -9.5%). The declines of CO2 are consistent with regional nitrogen oxides concentrations observed by satellites and ground-based networks, but the calculated signal of emissions decreases (about 1Gt CO2) will have little impacts (less than 0.13ppm by April 30, 2020) on the overserved global CO2 concertation. However, with observed fast CO2 recovery in China and partial re-opening globally, our findings suggest the longer-term effects on CO2 emissions are unknown and should be carefully monitored using multiple measures

Constraint of a ruthenium-carbon triple bond to a five-membered ring

含过渡金属碳三键(M≡C)的金属卡拜化合物是许多有机反应的催化剂或关键中间体。对其合成及性质的研究是金属有机化学的热点之一。由于卡拜碳的sp杂化方式，大部分金属卡拜化合物均为链状结构（卡拜碳键角理想值为180 °），环内金属卡拜化合物因存在很大的环张力而难于合成。夏海平教授课题组发展了由链状多炔（称之为碳龙）构筑碳龙配合物的高效方法（Nature Communications, 2017, 8, 1912），实现了锇杂戊搭炔/烯及其衍生物的一锅法合成。现在，他们把该方法进一步拓展到了第二过渡系金属钌，通过碳龙与市售的RuCl2(PPh3)3反应一锅合成了钌杂戊搭炔I。本研究是碳龙化学的进一步延伸和发展，首次把碳龙化学的金属中心由锇拓展到了其它金属，展示了碳龙化学广阔的发展空间。该研究工作在夏海平教授指导下完成，能源材料化学协同创新中心（iChEM）博士后卓庆德和张弘副教授为共同第一作者。iChEM博士后周小茜、博士生陈志昕、林剑锋、卓凯玥、硕士康慧君、林鑫磊参与了部分实验工作。博士生华煜晖负责理论计算。【Abstract】The incorporation of a metal-carbon triple bond into a ring system is challenging because of the linear nature of triple bonds. To date, the synthesis of these complexes has been limited to those containing third-row transition metal centers, namely, osmium and rhenium. We report the synthesis and full characterization of the first cyclic metal carbyne complex with a second-row transition metal center, ruthenapentalyne. It shows a bond angle of 130.2(3)° around the sp-hybridized carbyne carbon, which represents the recorded smallest angle of second-row transition metal carbyne complexes, as it deviates nearly 50° from the original angle (180°). Density functional theory calculations suggest that the inherent aromatic nature of these metallacycles with bent Ru≡C–C moieties enhances their stability. Reactivity studies showed striking observations, such as ambiphilic reactivity, a metal-carbon triple bond shift, and a [2 + 2] cycloaddition reaction with alkyne and cascade cyclization reactions with ambident nucleophiles.This research was supported by the National Key R&D Program of China (2017YFA0204902) and the National Natural Science Foundation of China (nos. 21490573,21332002, and 21561162001). 研究工作得到国家自然科学基金项目（21490573、21332002 和21561162001）和国家重点研发计划（2017YFA0204902）的资助

Biological and genomic analysis of a symbiotic nitrogen fixation defective mutant in Medicago truncatula

Medicago truncatula has been selected as one of the model legume species for gene functional studies. To elucidate the functions of the very large number of genes present in plant genomes, genetic mutant resources are very useful and necessary tools. Fast Neutron (FN) mutagenesis is effective in inducing deletion mutations in genomes of diverse species. Through this method, we have generated a large mutant resource in M. truncatula. This mutant resources have been used to screen for different mutant using a forward genetics methods. We have isolated and identified a large amount of symbiotic nitrogen fixation (SNF) deficiency mutants. Here, we describe the detail procedures that are being used to characterize symbiotic mutants in M. truncatula. In recent years, whole genome sequencing has been used to speed up and scale up the deletion identification in the mutant. Using this method, we have successfully isolated a SNF defective mutant FN007 and identified that it has a large segment deletion on chromosome 3. The causal deletion in the mutant was confirmed by tail PCR amplication and sequencing. Our results illustrate the utility of whole genome sequencing analysis in the characterization of FN induced deletion mutants for gene discovery and functional studies in the M. truncatula. It is expected to improve our understanding of molecular mechanisms underlying symbiotic nitrogen fixation in legume plants to a great extent

Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology