Collective credit allocation in science

Collaboration among researchers is an essential component of the modern scientific enterprise, playing a particularly important role in multidisciplinary research. However, we continue to wrestle with allocating credit to the coauthors of publications with multiple authors, because the relative contribution of each author is difficult to determine. At the same time, the scientific community runs an informal field-dependent credit allocation process that assigns credit in a collective fashion to each work. Here we develop a credit allocation algorithm that captures the coauthors’ contribution to a publication as perceived by the scientific community, reproducing the informal collective credit allocation of science. We validate the method by identifying the authors of Nobel-winning papers that are credited for the discovery, independent of their positions in the author list. The method can also compare the relative impact of researchers working in the same field, even if they did not publish together. The ability to accurately measure the relative credit of researchers could affect many aspects of credit allocation in science, potentially impacting hiring, funding, and promotion decisions.Reflecting the increasing complexity of modern research, in the last decades, collaboration among researchers became a standard path to discovery (1). Collaboration plays a particularly important role in multidisciplinary research that requires expertise from different scientific fields (2). As the number of coauthors of each publication increases, science’s credit system is under pressure to evolve (3–5). For single-author papers, which were the norm decades ago, credit allocation is simple: the sole author gets all of the credit. This rule, accepted since the birth of science, fails for multiauthor papers (6). The lack of a robust credit allocation system that can account for the discrepancy between researchers’ contribution to a particular body of work and the credit they obtain, has prompted some to state that “multiple authorship endangers the author credit system” (7). This situation is particularly acute in multidisciplinary research (8, 9), when communities with different credit allocation traditions collaborate (10). Furthermore, a detailed understanding of the rules underlying credit allocation is crucial for an accurate assessment of each researcher’s scientific impact, affecting hiring, funding, and promotion decisions.Current approaches to allocating scientific credit fall in three main categories. The first views each author of a multiauthor publication as the sole author (11, 12), resulting in inflated scientific impact for publications with multiple authors. This system is biased toward researchers with multiple collaborations or large teams, customary in experimental particle physics or genomics. The second assumes that all coauthors contribute equally to a publication, allocating fractional credit evenly among them (13, 14). This approach ignores the fact that authors’ contributions are never equal and hence dilutes the credit of the intellectual leader. The third allocates scientific credit according to the order or the role of coauthors, interpreting a message agreed on within the respective discipline (15–17). For example, in biology, typically the first and the last author(s) get the lion’s share of the credit, and in some areas of physical sciences, the author list reflects a decreasing degree of contribution. An extreme case is offered by experimental particle physics, where the author list is alphabetic, making it impossible to interpret the author contributions without exogenous information. Finally, there is an increasing trend to allocate credit based on the specific contribution of each author (18, 19), specified in the contribution declaration required by some journals (20, 21). However, each of these approaches ignores the most important aspect of credit allocation: notwithstanding the agreed on order, credit allocation is a collective process (22–24), which is determined by the scientific community rather than the coauthors or the order of the authors in a paper. This phenomena is clearly illustrated by the 2012 Nobel prize in physics that was awarded based on discoveries reported in publications whose last authors were the laureates (25, 26), whereas the 2007 Nobel prize in physics was awarded to the third author of a nine-author paper (27) and the first author of a five-author publication (28). Clearly the scientific community operates an informal credit allocation system that may not be obvious to those outside of the particular discipline.The leading hypothesis of this work is that the information about the informal credit allocation within science is encoded in the detailed citation pattern of the respective paper and other papers published by the same authors on the same subject. Indeed, each citing paper expresses its perception of the scientific impact of a paper’s coauthors by citing other contributions by them, conveying implicit information about the perceived contribution of each author. Our goal is to design an algorithm that can capture in a discipline-independent fashion the way this informal collective credit allocation mechanism develops.     

孤儿核受体Nur77参与AopE-/-小鼠颈动脉易损斑块的形成

目的:研究孤儿核受体Nur77在AopE-/-小鼠动脉粥样硬化易损斑块形成中的作用。方法:AopE-/-小鼠左肾动脉和左颈总动脉联合部分结扎建立颈动脉易损斑块模型,采用HE染色观察斑块病理学改变,免疫荧光染色结合激光扫描共聚焦显微镜技术观察斑块中Nur77蛋白的表达。同时,体外培养小鼠巨噬细胞系RAW264.7,在氧化低密度脂蛋白(oxLDL)及其主要成分7-酮胆固醇(7-ketocholesterol,7-KC)或者游离胆固醇(FC),以及炎症介质(LPS、IL-1β)等条件刺激下,应用蛋白免疫印迹技术(Western blot)检测Nur77蛋白表达变化。结果:AopE-/-小鼠颈动脉易损斑块局部有Nur77蛋白高表达,而oxLDL及其组成成分(7-KC和FC)以及某些炎症介质(如LPS、IL-1β等)均能在RAW264.7细胞中诱导Nur77蛋白表达上调。结论:孤儿核受体Nur77可能在动脉粥样硬化易损斑块发展进程中发挥着重要作用。     

Impact of pulsed electromagnetic field therapy on vascular function and blood pressure in hypertensive individuals

The present study investigated the impact of 12 weeks of pulsed electromagnetic field (PEMF) therapy on peripheral vascular function, blood pressure (BP), and nitric oxide in hypertensive individuals. Thirty hypertensive individuals (SBP > 130 mm Hg and/or MAP > 100 mm Hg) were assigned to either PEMF group (n = 15) or control group (n = 15). During pre‐assessment, participants underwent measures of flow‐mediated dilation (FMD), BP, and blood draw for nitric oxide (NO). Subsequently, they received PEMF therapy 3x/day for 12 weeks and, at conclusion, returned to the laboratory for post‐assessment. Fifteen participants from the PEMF group and 11 participants from the control group successfully completed the study protocol. After therapy, the PEMF group demonstrated significant improvements in FMD and FMD_NOR (normalized to hyperemia), but the control group did not (P = .05 and P = .04, respectively). Moreover, SBP, DBP, and MAP were reduced, but the control group did not (P = .04, .04, and .03, respectively). There were no significant alterations in NO in both groups (P > .05). Twelve weeks of PEMF therapy may improve BP and vascular function in hypertensive individuals. Additional studies are needed to identify the mechanisms by which PEMF affects endothelial function.     

提高对新型冠状病毒感染诊治的认识

新型冠状病毒(novel coronavirus,nCoV)是指此前未在人体中发现的冠状病毒,常有人类以外的哺乳动物作为其储存宿主和中间宿主.目前报道的nCoV包括严重急性呼吸综合征冠状病毒(severe acute respiratory syndrome coronavirus,SARS-CoV)、中东呼吸综合征冠状病毒(Middle East respiratory syndrome coronavirus,MERS-CoV)和新近发现的2019新型冠状病毒(2019 novel coronavirus,2019-nCoV).nCoV可引起严重急性呼吸道感染(severe acute respiratory infection,SARI)、急性呼吸窘迫综合征、感染性休克、肾脏衰竭等危重疾病状态,提高临床医师对nCoV感染诊治的认识是当务之急.提高门诊分诊和早期识别能力、加强医院感染的防控、提高对重症患者的综合救治能力,以及加强临床研究是应对nCoV感染疫情的关键.     

Molecular Cloning and Characterization of Rhesus Monkey Platelet Glycoprotein Ibα, a major ligand-binding subunit of GPIb-IX-V complex

Introduction

Through binding to von Willebrand factor (VWF), platelet glycoprotein (GP) Ibα, the major ligand-binding subunit of the GPIb-IX-V complex, initiates platelet adhesion and aggregation in response to exposed VWF or elevated fluid-shear stress. There is little data regarding non-human primate platelet GPIbα. This study cloned and characterized rhesus monkey (Macaca Mullatta) platelet GPIbα.

Materials and Methods

DNAMAN software was used for sequence analysis and alignment. N/O-glycosylation sites and 3-D structure modelling were predicted by online OGPET v1.0, NetOGlyc 1.0 Server and SWISS-MODEL, respectively. Platelet function was evaluated by ADP- or ristocetin-induced platelet aggregation.

Results

Rhesus monkey GPIbα contains 2,268 nucleotides with an open reading frame encoding 755 amino acids. Rhesus monkey GPIbα nucleotide and protein sequences share 93.27% and 89.20% homology respectively, with human. Sequences encoding the leucine-rich repeats of rhesus monkey GPIbα share strong similarity with human, whereas PEST sequences and N/O-glycosylated residues vary. The GPIbα−binding residues for thrombin, filamin A and 14-3-3ζ are highly conserved between rhesus monkey and human. Platelet function analysis revealed monkey and human platelets respond similarly to ADP, but rhesus monkey platelets failed to respond to low doses of ristocetin where human platelets achieved 76% aggregation. However, monkey platelets aggregated in response to higher ristocetin doses.

Conclusions

Monkey GPIbα shares strong homology with human GPIbα, however there are some differences in rhesus monkey platelet activation through GPIbα engagement, which need to be considered when using rhesus monkey platelet to investigate platelet GPIbα function.