Drawing upon self-determination theory and the person–environment interaction perspective, we examine how employee competitive attitude and competitive behavior can be influenced by both personal characteristics and team climate, which in turn leads to different work outcomes, as demonstrated in two studies. Study 1 developed measures for competitive attitude and competitive behavior. Study 2 collected data from salespeople in a large insurance company in three waves. The results showed that employee competitive attitude and behavior could be predicted by personality. Moreover, employee competitive attitude and behavior were related to sales performance in differential ways via job crafting, and these mediated relationships could be moderated by team climate. These findings support the two-component dynamic model combining competitive attitude and behavior, which helps promote understanding of the dynamics of competition and its consequences at the individual level. Theoretical and practical implications are also discussed.While competition has become increasingly fierce in organizations and in the broader market, the research on competition at an individual level is limited. Most existing research focuses on trait competitiveness. We argue that employee competitiveness can be state-like and can be demonstrated as an attitude toward and behavior representative of competition. We therefore propose a dynamic model with two separate components:  Competition and/or competitive advantage have been considered the most important survival method for individuals, organizations, and society . It is eHowever, competition in human beings is more complicated than we think. People high in trait competition may not have to demonstrate competitive behavior, while those low in trait competition may have to show competitive behaviors. The studies examining competitive behavior and its mechanisms and marginal conditions at the micro level are still lacking. We know little about how trait competition, competitive attitude, and competitive behavior relate to each other, and there have been no measures estimating competitive attitude and competitive behavior. This study will address these issues.In particular, we propose a dual-dynamic model of competitive attitude and competitive behavior and examine how competitive attitude and behavior relate to trait competition as an individual factor and competitive climate as an environmental factor in an effort to discover how their interactions might influence the performance in workplace. We will first review the literature and then propose our research model and hypotheses.Although competition is a very common phenomenon, its definition is not consistent. There are two main perspectives: one focuses on limited resources, and the other focuses on social status. According to the perspective of limited resources, competition is framed as a concept that describes a situation where individuals or organizations via for limited resources or rewards . In thisAnother perspective on competition is based on social comparison. People have an innate drive to be the best. They take horizontal social comparison and try their best to transcend others. Researchers claim that people enjoy prevailing over others . This isActually, both perspectives view competition as a means to outperform others and survive effectively. This leads to a link between competition and performance and, eventually, a belief that people with highly competitive traits can be more successful.The relationship between competition and performance is based on the logic of zero-sum contests in which two or more agencies go head-to-head, and one wins at the expense of the other . AccordiTrait competitiveness is a kind of personality that refers to “the enjoyment of interpersonal competition and the desire to win and be better than others” , p. 41. However, the previous research findings about the relationship between trait competitiveness and performance are mixed. While some research found that trait competitiveness was positively correlated with individual and company performance e.g., , other rSome researchers have identified some external, contextual factors such as competitive climate  that modH1: Trait competitiveness is an antecedent factor of competitive attitude and competitive behavior.competitive attitude as a belief concerning whether an individual likes competition. In addition, we define competitive behavior as the actual actions people take or are inclined to take in a specific job or life environment to compete for resources or succeed over others. These two concepts are related to competition but are distinct from trait competitiveness. While trait competitiveness refers more to a static individual disposition, competitive attitude, and behavior involve a dynamic psychological status: they are changeable, cultivatable, and can vary across different contexts  and competitive attitude/behavior . Thus, we propose the following hypotheses:On the other hand, as we mentioned above, competitive attitude and behavior are more proximal to performance (via job crafting). Moreover, according to the person–environment (P–E) fit perspective, an individual’s personal characteristics and environmental factors interact to influence individual’s attitude and behavior . We furtH4a: Competitive climate will interact with competitive attitude to influence personal job crafting such that, under the high level of competitive climate, the relationship between competitive attitude and job crafting will be stronger.H4b: Competitive climate will interact with competitive behavior to influence personal job crafting such that, in a highly competitive climate, the relationship between competitive behavior and job crafting will be stronger.H5a: Competitive climate will moderate the indirect effect in Hypothesis 3a such that it is stronger for individuals in a highly competitive climate (vs. those in a less competitive climate).H5b: Competitive climate will moderate the indirect effect in Hypothesis 3b such that it is stronger for individuals in a highly competitive climate (vs. those in a less competitive climate).Figure We performed two studies to test our research model. Study 1 developed a measure of competitive attitude and competitive behavior and tested its reliability, structure, and concurrent validity. Study 2 tested the effect of competitive attitude and competitive behavior on performance and investigated the mediating effect of job crafting and the moderating effect of competitive climate using multiwave, multisource data. This research was in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of School of Psychological and Cognitive Sciences at Peking University. For both studies, the data were collected online. In this case, the written informed consent was not obtained from each participant. Instead, we showed all participants their rights on a smartphone or computer screen before the start of the questionnaire and told them that if they truly understood their rights and wanted to participate in the study, they could push the button on the bottom of the screen to start. In this way, we obtained the participants’ electronic informed consent.Participants for exploratory factor analysis (EFA) were 155 employees who worked for an insurance company. Each employee received a link via smartphone and was asked to fill out the questionnaire on their phone. Their average age was 24.72 years old, 78 males (50.3%).SD = 5.04), 154 females (74%).Participants for confirmative factor analysis (CFA) were recruited by snowballing online via smart phone. They first received a link. They were then informed their rights and asked if they wanted to participate in the survey in exchange for 1-dollar reward and feedback about their competitiveness. In total, there were 208 employees from a variety of industries such as IT, manufacturing, construction, finance and banking, education, and others, covering the spectrum of competition in different industries that participated in the study. Their average age was 35.06 years  to 7 .Based on the definition and our main concern that focusing on the difference of attitude and behavior from trait competitiveness, we developed the measurement of competitive attitude and competitive behavior. Six graduate students and one professor in industrial and organizational psychology worked together to generate the original items and decide which item was suitable for each scale. An item was accepted for inclusion only when all group members agreed. Finally, each of two scales included five items  to 7 .Trait competitiveness was measured using a scale developed by Type A behavior pattern is used to describe those persons who are “aggressively involved in a chronic, incessant struggle to achieve more in less and less time, and if required to do so, against the opposing efforts of other things or other persons” , p. 67. 2 = 64.61, p < 0.00), and each item loaded onto the assumptive factor with a salient loading (loading > 0.30), no item should be removed. The results preliminarily confirmed the structure of competitive attitude and competitive behavior scales.Since we developed a new scale for both competitive attitude and competitive behavior based on our definition of each term, we first conducted the exploratory factor analysis (EFA) with all 10 items of competitive attitude and competitive behavior scales using SPSS 22.0. The results showed that the Kaiser–Meyer–Olkin measure of sampling adequacy was 0.85, indicating that the data were suitable for factor analysis. Parallel analysis indicated that two factors were significant and should be retained: Factor 1 had an eigenvalue of 4.66 (46.59% of the variance) and factor 2 had an eigenvalue of 2.70 (27.00% of the variance). As the good-of-fit test was significant , comparative fit Index = 0.98, goodness of fit index = 0.92, and normed fit index = 0.96. All the results were statistically acceptable. These results suggested that the two scales had a good structural validity.Then we tested the conceptual structure of the measurement by confirmative factor analysis (CFA). The analysis was performed using LISREL 8.7. The results . Their average job tenure was 12.53 months (SD = 15.22).Salespeople who worked for an insurance company and sold life insurance via telephone were recruited to be participants. We collaborated with the company to estimate its competitive climate. Each employee received a link via smart phone so that they could participate in the survey online. They were informed of their rights and the benefits of participation and that they could quit at any time. They were asked to fill out the questionnaire on their smartphone twice, with a 1-month interval between the response dates. We obtained a sample of 283 employees, 148 males (52.3%); their mean average age was 24.83 years  to 7 .The competitive climate was measured by a scale developed by totally disagree) to 7 .Job crafting was measured by the Job Crafting Scale developed by z-score) from all insurance products sold by each employee in our sample. We received standardized sales records rather than raw data due to the proprietary and sensitive nature of the latter.Employees’ objective performance was measured at Time 3 using their archival sales performance records for the 1-month period following the Time 2 survey. This sales performance record was the standardized value of sales , participants finished the online survey including trait competitiveness, competitive attitude, and competitive behavior. They also provided their demographic information, including gender, age, and tenure. At Time 2 (the early beginning of next month), employees completed the job crafting and competition climate scales via their smartphone, again with a special link. At Time 3, the end of the second month, we collected the sales performance data  for each employee from the company.rs between 0.35 and 0.60, p = 0.01). Moreover, competitive attitude and competitive behavior at Time 1 were significantly correlated with job crafting at Time 2  and performance at Time 3 . Additionally, competitive attitude and competitive behavior were only moderately correlated to each other, providing further evidence that they are empirically distinct from each other. Next, we test our research hypotheses one by one.The descriptive statistics, correlations, and reliability coefficients among study variables are reported in Table B = 0.34, SE = 0.06, p = 0.00, 95% CI ) and competitive behavior  were significantly related to trait competitiveness and accounted for additional 8% and 15% of variance, respectively. These results support Hypothesis 1, suggesting that trait competitiveness can be an antecedent of competitive attitude and behavior.We used a hierarchical regression to test the effect of trait competitiveness on competitive attitude and competitive behavior. The unstandardized coefficient estimates are reported in Table F = 2.29, p = 0.08). The incongruence line curved upward . This suggested that the incongruence line was U-shaped, and that the lowest point of job crafting was not the extremity. That is, any deviation from the congruence line did not decrease job crafting. Therefore, Hypothesis 2a was not supported.Next, we performed polynomial regressions  to examiB = 0.11, SE = 0.04, p = 0.01, 95% CI ), competitive behavior , and their interaction term  were positively related to job crafting. But the coefficient of interaction term was not significant. Therefore, Hypothesis 2c was partially supported.Hypothesis 2c suggested that job crafting would be higher when both the levels of competitive attitude and behavior are high. The results of regression showed that, after controlling for gender, age, and tenure, competitive attitude (p = 0.44) along the incongruence line when the curvature is negative , meaning the line was inversely U-shaped , competitive behavior , and their interaction term  were positive. But the interaction term was not significant. Therefore, Hypothesis 2d was partially supported.Hypothesis 2d suggested that performance would be higher when the levels of competitive attitude and behavior are high. The results of regression showed the coefficients of competitive attitude . In Model 3, job crafting was positively but marginally correlated with performance  when competitive behavior (T1) was entered into the regression analysis. The mediating effect of job crafting on the relationship between competitive behavior and performance was significant . Hypothesis 3a was supported.We conducted hierarchical regression analyses to examine the moderated mediating effects with PROCESS in SPSS (22.0.0.0), and the results are presented in Table B = 0.09, SE = 0.04, p = 0.03, 95% CI ). The simple slope test showed that when the competitive climate was high (Mean + SD), the relationship between job crafting and competitive attitude was stronger  than when the competitive climate was low  . Additionally, job crafting (T2) was positively correlated with performance  when competitive behavior (T1) was entered into the regression. The mediating effect of job crafting on the relationship between competitive behavior and performance was significant . Hypothesis 3b was supported.Similarly, competitive behavior (T1) was significantly and positively correlated with performance . The simple slope test showed that when the competitive climate was high, the relationship between job crafting and competitive behavior was stronger  than when the competitive climate was low . The interaction plot is presented in Figure Moreover, the moderating effect of the competitive climate on the relationship between competitive behavior and job crafting in step 2 was significant  fit perspective claims that people actively interact with the environment and adjust behaviors to adapt to the environment . ConsistFourth, our findings explain the path that links trait competitiveness, competitive attitude and behavior, job crafting, and the job performance. In particular, our findings demonstrate that job crafting  can explThe present research also has some limitations that need to be addressed. First, although we have obtained some preliminary evidence for the reliability and validity of the two new measures of competitive attitude and competitive behavior, their usefulness across multiple samples still needs to be examined. This is particularly important because they are both dynamic psychological variables that may change from time to time.Second, this research was conducted in an insurance company. The insurance industry is quite different from other industries because of the fierce competition. Whether or not the findings can be replicated in other industries needs to be established. However, we argue that because of the feature of fierce competition in insurance industry, the findings from this industry are more salient. Further research should test the generality of the findings from the current research.Third, the differentiation of the trait competitiveness from competitive attitude and competitive behavior should be further tested in future studies. More evidence needs to be obtained to demonstrate the distinctions between trait-like variable measure and dynamic variable measures.Fourth, both studies in the current research use correlational methods. Although the second study used a time-lagged design with multiwave data, the causality relationship among the tested variables remains unclear. Further research should address this issue by using experimental method or other causality research design.Finally, we note that our Hypothesis 2a was not supported. This hypothesis predicted a congruence effect of competitive attitude and behavior on job crafting. However, the results suggested that the congruence and incongruence line were U-shaped. That is, when both competitive attitude and behavior were either high or low simultaneously, job crafting was moderate, whereas when both competitive attitude and behavior were at the middle level, job crafting was the lowest. One possible explanation is that there are some other factors that influence job crafting, and job crafting only partially mediated the relationship of competitive attitude and behavior with job performance. Future research should test why this happens. Nevertheless, some points are still clear: (1) when both competitive attitude and behavior are high, job crafting reaches the highest level, and (2) when one of the two components – competitive attitude and competitive behavior – is high, job crafting is still quite high. In addition, Hypothesis 2c and 2d were only partially supported. The results just showed a promoting tendency of competitive attitude and competitive behavior to job crafting (or performance), but the interaction coefficients of regression were not significant. The alternative explanation was that competitive attitude and competitive behavior might work out separately and directly on job crafting and performance, according to our dual-component model. Future research should incorporate more efforts to clarify whether competitive attitude and competitive behavior take effect independently or interactively.The findings from the present research can be useful in practice in many ways. For example, organizations can recruit those people high in competitive attitude and competitive behavior, though they may be low in trait competitiveness, in an effort to seek high performance. Moreover, organizations can strengthen their competitive climate to serve as a powerful environmental force  to driveAs for individuals, it is true that not everyone has a high level of trait competitiveness. Does it mean these people will definitively lose in a competition? Fortunately, according to the P–E fit perspective  and the HW and LW proposed the research idea and made the research design. HW, LW, and CL collected the data and prepared the manuscript. CL and LW ran the data analysis.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


None of these were significantly different from the parental Newcastle disease virus (NDV) LaSota strain (p > 0.05). Vaccination of white leghorn chickens at one day of age with 106 EID50 rNDV-IBV-T/B provided 90% protection against virulent IBV M41 challenge at three weeks of age, which was significantly higher than the protection of the control group vaccinated with phosphate-buffered saline (PBS) (p < 0.05). The ciliostasis scores of rNDV-IBV-T/B-vaccinated and LaSota-vaccinated groups were 4.2 and 37.6, respectively, which indicated that rNDV-IBV-T/B vaccination reduced the pathogenicity of IBV toward the trachea. Furthermore, real-time RT-PCR assay showed that the rNDV-IBV-T/B vaccination resulted in low levels of viral load (647.80 ± 49.65 RNA copies) in the trachea four days post-challenge, which is significantly lower than groups vaccinated with PBS (8591.25 ± 311.10 RNA copies) or LaSota (7742.60 ± 298.50 RNA copies) (p < 0.05). Meanwhile, the same dose of rNDV-IBV-T/B vaccination provided complete protection against velogenic NDV F48E9 challenge. These results demonstrate that the rNDV-IBV-T/B strain is a promising vaccine candidate to control both IB and ND simultaneously. Furthermore, epitope-based live vector vaccines provide an alternative strategy for the development of cost-effective and, broadly, cross-protective vaccines.Infectious bronchitis (IB) and Newcastle disease (ND) are two major infectious diseases that are a threat to the domestic poultry industry. In this study, we successfully generated a recombinant LaSota candidate vaccine strain, rNDV-IBV-T/B, which expresses a short, synthetic, previously identified IBV S1 multi-epitope cassette using the reverse genetic system. The recombinant virus was propagated in nine-day-old embryonated chicken eggs for 20 passages and genetic stability was confirmed by whole genome DNA sequencing. The recombinant virus had a hemagglutination (HA) titer of 2 Nidovirales, family Coronaviridae, genus Gammacoronavirus. IBV causes upper respiratory illness, nephritic syndrome, and a drop in egg production in layer chickens [Avian infectious bronchitis (IB) is an acute and highly contagious viral respiratory disease of chickens. IB occurs worldwide and causes substantial economic losses in the poultry industry ,2,3,4,5.chickens . The morchickens ,7,8,9,10Orthoavulavirus of the family Paramyxoviridae, often referred to as Newcastle disease virus (NDV) [Currently, novel serotype and variant IBV have emerged due to rapid mutation rates, viral recombination, and host selection pressure, which have resulted in IB prevention becoming a global challenge ,12. Vaccus (NDV) , which hus (NDV) ,17. Thesus (NDV) ,19,20,21In recent years, epitope-based vaccines have been widely studied for their advantages, including safety, genetic stability, ease of production, and the ability to elicit immune responses against multi serotype pathogens. ,23. ThusThe technology of the reverse genetic system (RGS) for NDV was established in Europe two decades ago, which has been successfully applied to research on pathogenicity, replication regulatory mechanisms, and vaccine vectors . MeanwhiThe aim of this study was to develop a live vaccine using recombinant NDV expressing previously identified IBV multi-epitope cassette. The protective efficacy of the recombinant NDV vaccine was evaluated by heterologous IBV and velogenic NDV challenge. The findings could provide an alternative and promising strategy for the development of a cost-effective and extensively immune-protective vaccine for the control of ND and IB. 50) of a virus in harvested allantoic fluid was calculated by the Reed and Muench mathematical technique [The chicken embryonic fibroblast cell line (DF-1) and baby hamster kidney fibroblasts clone 13 cell line (BHK-21) were obtained from the American Type Culture Collection . They were grown in Dulbecco’s minimal essential medium (DMEM) containing 10% fetal bovine serum (FBS). Fertile white leghorn SPF embryonated eggs were purchased from the Beijing Merial Vital Laboratory Animal Technology Co., Ltd. The recombinant avirulent NDV LaSota strain was developed previously in our laboratory by a reverse genetics system ,36. The echnique . All expWe employed NDV as virus vector and rescued the recombinant NDV expressing an IBV S1 protein multi-epitope cassette via a reverse genetics system. Briefly, five overlapping cDNA fragments covering the complete genome of the NDV LaSota strain were amplified by RT-PCR using genomic RNA as a template. The five cDNA fragments were subsequently assembled into a modified pBR322 vector under the control of the T7 promotor and followed by a partial Hepatitis D virus (HDV) ribozyme and T7 terminator, resulting in a full-length cDNA clone, named pBR-LS.The IBV S1 multi-epitope cassette S-T/B, constructed previously, was inserted between P and M genes in the LaSota genome as an additional transcriptional unit . The fulThe recombinant LaSota virus, named rNDV-IBV-T/B, P1-P20 passages were detected by reverse transcription polymerase chain reaction (RT-PCR) and all the passages rNDV-IBV-T/B whole genome were analyzed by DNA sequencing . Briefly, RNA was extracted from allantoic fluid of rNDV-IBV-T/B-infected chick embryos  and reverse transcribed to cDNA with AMV Reverse Transcriptase  and random primers  at 42 °C for 30 min. To amplify the target gene IBV multi-epitope cassette, RT-PCR was performed using 2 µL of rNDV-IBV-T/B cDNA, 10 µmol each of the primers , 10 µL PCR Master Mix (2X)  in a total volume of 20 µL. PCR cycling procedure began with an initial hold at 95 °C for 10 min, followed by 30 cycles containing 94 °C for 20 s, 53 °C for 30 s and 72 °C for 20 s and a final step of 72 °C for 10 min. RT-PCR amplification product was examined by agarose-gel electrophoresis.50) assay on DF-1 cells in 96-well plates, and the 50% egg infective dose (EID50) assay in nine-day-old SPF chicken embryos, according to A Basic Laboratory Manual for the Small-Scale Production and Testing of I-2 Newcastle Disease Vaccine [http://www.oie.int/en/standard-setting/terrestrial-manual).The infectivity of the recombinant virus rNDV-IBV-T/B and parental LaSota strain were characterized using the standard hemagglutination test (HA) and the 50% tissue infectious dose  of 1 with P1 and P20 passages of rNDV-IBV-T/B and the parental virus LaSota strain. DF1 cells were harvested 36 h post-infection, lysed, and proteins were separated on a 10% SDS polyacrylamide gel (SDS-PAGE) under denaturing conditions. After electrophoresis, proteins were transferred onto polyvinylidene fluoride (PVDF) filter membrane. Then, the membrane was incubated in 5% skim milk with PBST buffer  for 1 h at room temperature, followed by incubation with a 1:5000 dilution of rabbit anti-IBV strain polyclonal antibody or mouse monoclonal NDV NP protein antibody in PBST buffer for 1 h at 37 °C. After triplicate washes with PBST buffer, the PVDF membrane was incubated with an HRP-conjugated goat anti-rabbit or rabbit anti-mouse secondary antibody. The protein was visualized using the Pierce ECL substrate kit  and imaged using a Tanon 5200 automatic chemiluminescence image analysis system .g for 20 min to remove the debris and collect the supernatant. Four milliliters of rNDV-IBV-T/B were layered on top of a step gradient of 60%, 50%, 40%, and 25% w/v sucrose prepared in Milli-Q water. Ultracentrifugation was carried out at 120,000 ×g in a SW41 Ti rotor  for 4 h, at 4 °C. The virus-containing band between the 40% and 50% sucrose layers was collected and 5 μl of rNDV-IBV-T/B virus was placed onto the shiny side of an EM grid and then adsorbed for ~3 min. The grid was stained immediately after virus adsorption 3 times with 2% uranyl acetate for 45 s. After negative staining, observation was by an 80 kV FEI Tecnai Spirit TEM T12 (Thermo Fisher) at 98,000× magnification.The rNDV-IBV-T/B was propagated in nine-day-old SPF chicken embryos and purified by sucrose gradient centrifugation according to a previous report . Briefly6 EID50 per chicken, and groups C and D were inoculated with LaSota at the same dose via the oculonasal route. The control groups E and F were inoculated with PBS by the same route.To analyze the protective efficacy of the rNDV-IBV-T/B vaccine against NDV and IBV infection, a total of 90 one-day-old SPF white leghorn chicks were randomly divided into six groups and housed in negative pressure isolators with sterile water and enough feed. Groups A and B were administered with rNDV-IBV-T/B at dose of 106 EID50 of the IBV M41 strain via the oculonasal route, and groups B and D, and control group F were challenged with 106 EID50 of the velogenic NDV strain F48E9 by the same route. The lethal dose of the challenge virus had been determined by an experimental chicken infection study. Five challenged chickens from groups A and C, and control group E were subjected to ciliostasis tests at 4 days post-challenge (dpc). The other chickens of each group were monitored daily for symptoms and mortality for another two weeks. The immune-protection and challenge experiments were conducted in triplicate.Three weeks post-vaccination, groups A and C, and control group E were challenged with 102 EID50 of M41 strain, followed by incubation for 1 h at 37 °C. Neutralizing antibody titer was estimated by inoculating nine-day-old SPF embryonated chicken eggs with the incubated virus-serum mixture via the allantoic cavity route. PBS was used as the negative control. The embryonated eggs were examined daily for 5 days. VN titers were defined as the reciprocal of the highest dilution without any mortality and IBV specific lesions on chicken embryos. All the assays were performed in triplicate and VN titers were expressed as the mean ± SEM.In order to evaluate the antibody responses elicited by rNDV-IBV-T/B, the vaccinated chickens were bled through the wing veins, and sera were isolated for serological tests 21 days post-immunization. HI assays were conducted in V-bottomed microwell plates according to the standard protocol of the OIE Manual to determine the level of antibody titers mounted against NDV in chickens vaccinated by rNDV-IBV-T/B. . Ten serTo evaluate the efficacy of rNDV-IBV-T/B in preventing shedding of IBV in immunized chickens, tracheal swab samples were randomly taken from five chickens from each group 4 dpc. RNA was extracted using an using a High Pure RNA Isolation Kit  according to the manufacturer’s instructions. The primers, probe, and PCR conditions for the assay used to detect IBV RNA using RT-qPCR were previously described in the literature ,42. TaqmThe ciliostasis activity of the tracheal explants was examined on 10 tracheal ring explants per chicken (5 chickens of each group) 5 dpc. The tracheas were carefully removed and examined for ciliary activity within 2 h after collection as described in the referenced papers ,44. Briep values < 0.05 were considered statistically significant. The data are expressed as the means ± SEM.GraphPad Prism v5.01 was used for statistical analysis. One-way ANOVA with repeated measures was used to evaluate the effect of the vaccines through HI and VN tests. The survival rates of immune protection experiments were determined by log-rank tests, 2. The cell lysates were harvested, filtered, and inoculated into SPF embryonated chicken eggs. The rNDV-IBV-T/B was serially passaged 20 times (P20), and the sequence of the full-length multi-epitope cassette S-T/B was examined by RT-PCR (The multi-epitope cassette A containy RT-PCR C and seqOne MOI of two different passages (P1 and P20) of rNDV-IBV-T/B and the parental strain LaSota were used to infect DF1 cells for 24 h, and the cell lysates were harvested and analyzed by Western blot using rabbit polyclonal anti-IBV serum and a mouse monoclonal anti-NDV/NP antibody. The protein expressed from the IBV S1 protein multi-epitope cassette and the NDV NP protein were found at ~35 and 53 kDa bands in P1 and P20 of rNDV-IBV-T/B lysates, however, the parental virus strain LaSota only had the ~53 kDa NP protein band , confirm50 titers of the parental virus LaSota and rNDV-IBV-T/B reached 6.5 × 108/ml and 6.7 × 108/mL, respectively. The TCID50 titer of rNDV-IBV-T/B (3.7 × 107/mL) was slightly higher than that of LaSota (3.6 × 107/mL) at 48 h post-infection. The HA titers of LaSota and rNDV-IBV-T/B were the same (210). The statistical analysis of EID50, TCID50, and HA results indicated that there were no significant differences between rNDV-IBV-T/B and the parental LaSota virus (p > 0.05). The recombinant NDV remained stable, with no apparent changes in MDT and virus titers after 20t passages in SPF chicken embryonated eggs. Furthermore, rNDV-IBV-T/B has a lower ICPI (0.05) than LaSota (0.10) (p > 0.05).To determine whether inserting the IBV S1 protein multi-epitope cassette into the NDV LaSota genome affects the biological properties of the recombinant virus, the growth characteristics and pathogenicity after 20 passages of rNDV-IBV-T/B were evaluated through virus titration, MDT, and ICPI tests in vitro and in vivo. The titers of the recombinant virus, determined either in embryonated eggs or in DF-1 cells, were comparable to those of the parental LaSota strain. The EIDa (0.10) . These rTo observe the morphology of the recombinant virus rNDV-IBV-T/B, the 20th passage (P20) of rNDV-IBV-T/B and parental LaSota virions were purified by sucrose density gradient centrifugation. Following negative staining, virions were observed by TEM at 98,000× magnification. The rNDV-IBV-T/B virus appeared as circles or ovals about 100 to 150 nm in diameter. The envelope located on the surface layer of the virus can be clearly observed, which is consistent with the morphology of LaSota . TEM indp < 0.05)  . This rep < 0.05). The VN antibodies induced by rNDV-IBV-T/B administration could effectively neutralize heterologous IBV strain, indicating that the recombinant vaccine could protect against heterologous IBV challenge.Virus neutralization (VN) assays were performed according to the standard protocol of OIE. The VN titer of rNDV-IBV-T/B group against IBV M41 strain showed approximately 6.82 ± 0.26, which was significantly higher than the LaSota and PBS groups’ (no VN activity detected) (p < 0.05). The rNDV-IBV-T/B immunized group exhibited protective efficacy equivalent to the parental LaSota group (p < 0.05). The same protection rate was observed in two additional immune-protection tests conducted in parallel. These results confirm that chickens vaccinated with rNDV-IBV-T/B vaccine are substantially protected against NDV and IBV challenge.To evaluate the efficacy of the multi-epitope vaccine in protecting against IBV and NDV, one-day-old SPF chicks were immunized with rNDV-IBV-T/B virus or PBS via the oculonasal route. At three weeks post-immunization, the chickens were challenged with lethal doses of the NDV F48E9 strain or IBV M41 strain. Chickens inoculated with PBS manifested clinical symptoms on day two post NDV challenge, and all these chickens died within four days. Compared to chickens immunized with parental LaSota and chickens inoculated with PBS, chickens immunized with rNDV-IBV-T/B showed no apparent symptoms post NDV challenge (ta group A. The clta group B. In conp < 0.05) (p < 0.05). It is probable that rNDV-IBV-T/B effectively activated the immune response and suppressed viral replication to protect chickens against lethal dose of IBV challenge.Tracheal swab samples taken from five chickens of IBV challenge groups on 4 dpc were analyzed for IBV virions shedding via Taqman probe Real-time qRT-PCR (expressed as means ± SEM). Chickens vaccinated with rNDV-IBV-T/B showed low levels of viral load (647.80 ± 49.65) in the trachea, which was significantly lower than those inoculated with PBS (8591.25 ± 311.10) or LaSota (7742.60 ± 298.50) ( < 0.05) . The resThe ciliostasis scores between chickens immunized with rNDV-IBV-T/B, LaSota, and PBS control after a lethal dose of IBV challenge were calculated . The maxInfectious bronchitis (IB) and Newcastle disease (ND) are two major infectious diseases of the poultry production industry. Especially in layer and breeder chickens, a decline in egg production alone can cause significant economic losses. However, IBV and NDV live vaccines probably mutually interfere with concurrent immunization ,46,47. FpV-S1B+S1T could provide effective protection against a lethal dose of homologous IBV SH1208 challenge [p > 0.05). In previous study, the immune-protection experiment demonstrated that multi epitope-based DNA vaccine hallenge ,32. ThisThe immune-protection experiment showed that a single immunization of one-day-old chicks with rNDV-IBV-T/B could protect 100% and 90% chicks against lethal doses of F48E9 and M41 strain, respectively. The IBV protection rate was analogous to that of a recombinant NDV expressing the full-length S protein of the IBV M41 strain, reported by Shirvani, et al. ,55. WhetAbozeid et al.  reportedIn summary, the findings of this study support that NDV is an outstanding vaccine vector for expressing an IBV multi-epitope protein as a bivalent vaccine against NDV and IBV. Furthermore, the rNDV-IBV-T/B provides an alternative strategy for the development of a cost-effective and extensively immune-protective vaccine for the control of variant IBV infection.


Stable water isotopes are employed as hydrological tracers to quantify the diverse implications of atmospheric moisture for climate. They are widely used as proxies for studying past climate changes, e.g., in isotope records from ice cores and speleothems. Here, we present a new isotopic dataset of both near-surface vapour and ocean surface water from the North Pole to Antarctica, continuously measured from a research vessel throughout the Atlantic and Arctic Oceans during a period of two years. Our observations contribute to a better understanding and modelling of water isotopic composition. The observations reveal that the vapour deuterium excess within the atmospheric boundary layer is not modulated by wind speed, contrary to the commonly used theory, but controlled by relative humidity and sea surface temperature only. In sea ice covered regions, the sublimation of deposited snow on sea ice is a key process controlling the local water vapour isotopic composition. Water isotope modelling is an important tool in climate reconstructions, but there remain gaps in our understanding of the effects upon oxygen and hydrogen isotope fractionation, and thus the source of the deposited signal. Here, the authors present a dataset assembled over two years that shows deuterium excess is controlled by humidity and sea surface temperature, and oxygen and hydrogen isotopes as well as deuterium excess are controlled by sublimation of snow in sea-ice regions. Therefore, they can be used as integrated tracers of hydrological processes in the atmosphere. Their relative abundances compared with 18O and δ2H (see the Methods section), have been measured and used for many applications in climate-related studies, e.g., as proxies for past temperature1 and precipitation3 changes, variations of atmospheric moisture source conditions and transport pathways5.Stable water isotopologues 18O and δ2H. The deuterium excess6, hereafter d-excess, has been defined to quantify the kinetic effects (see the Methods section), such as those occurring during oceanic evaporation6 or snow formation from supersaturated vapour at low atmospheric temperatures7. Merlivat and Jouzel8, hereafter referred to as MJ79, developed a first theoretical model of isotope fractionation processes during evaporation from the ocean surface, which is still widely used. Applying their theoretical concept to the Earth’s global water cycle, MJ79 introduced the so-called “closure assumption”, assuming an equality of the isotopic composition of the net evaporated flux and the initial moist air above the ocean surface. According to this model, the strength of the d-excess signal in vapour is related to the relative humidity of the near-surface air with respect to the saturation vapour pressure at the ocean surface (RHsea), as well as to the sea surface temperature (SST). The theoretical considerations by MJ79 led to different interpretations of past d-excess variations recorded in polar ice cores. They have been used as proxies of changes of the moisture source relative humidity9 or SST12. The latter interpretation requires the assumption of negligible relative humidity variations during past climate changes, which has been recently challenged13. Regionally limited water vapour isotopic observations document a primary influence of the relative humidity on d-excess variability, while the influence of SST remains difficult to assess in this context16. Based on the evaporation theory and observations at the microphysical scale at the atmosphere–ocean interface, the model by MJ79 also considers an impact of wind speed on kinetic fractionation processes during evaporation and subsequently on the d-excess in the atmospheric vapour19. The importance of this wind-speed effect could not be validated so far by vapour d-excess observations performed only in coastal stations like Bermuda or Iceland15, and is therefore still under debate.During phase changes, equilibrium and kinetic fractionation processes differently affect δ20 and to be reflected in the water isotopic composition23. Current understanding of the impact of sea ice on the vapour isotopic composition is, however, still limited by the number of observations available in sea ice covered areas25.In polar regions, variations in sea ice extent are supposed to affect regional precipitation amounts27. Our measurements, together with theoretical calculations and atmospheric simulations, allow for the first time the assessment of the variability of the water isotopic signal on the first order  and on the second order  under various climate conditions. For the process of oceanic evaporation, our dataset is consistent with the role of meteorological RHsea and SST, but rules out the theoretically assumed influence of wind speed on the d-excess of the initial vapour. Furthermore, the sublimation of snow deposited on top of sea ice is identified as a crucial process determining the near-surface vapour isotopic composition in sea ice-covered areas.Here, we present a unique new dataset of ship-based in situ isotopic measurements of vapour and ocean surface water, conducted with an identical instrumental setup over 2 years for a large range of oceanic surface conditions at the basin scale of the Atlantic and Arctic Oceans, contrary to previous measurements more confined in area and timeOur observations, recorded on-board of the research vessel Polarstern, cover the period 29 June 2015 to 30 June 2017 and extend over a large range of latitudes in the Atlantic sector , from the North Pole in the Arctic to the Weddell Sea in coastal Antarctica (see the Methods section for details).−1) and δ18O (−8.4‰) values are reported in the Inter Tropical Convergence Zone (ITCZ) in November 2015, April 2016, December 2016 and April 2017. Over open-sea regions, d-excess values are generally contained between −10 and +10 ‰, apart from rare short events up to +15 ‰, while in the ITCZ region, only positive values of d-excess are observed. Temperature, humidity and δ18O progressively decrease from the ITCZ towards the mid and high latitudes of both hemispheres. In sea ice-covered polar regions, low δ18O and high d-excess values are observed: in areas of compact sea ice coverage, minima in air temperature, specific humidity and δ18O are reached , together with a maximum in d-excess (+22.3‰). Similar extreme isotopic values are reported in August 2016 for a partial sea ice coverage, while the vessel was located in the vicinity of the Greenland ice sheet, close to the outlet of the Nioghalvfjerdsbrae glacier (latitude 79° N).All atmospheric measurements and simulated values are presented at a 6-h temporal resolution see Fig. . The hig18O signal in surface seawater. The distribution of δ18O values is coherent to the GISS compilation28. The average δ18O value for all our oceanic samples is −0.7‰. In the mid-latitudes, values between −0.7 and 0.9‰ have been measured. The highest values are measured in the tropical bands, where evaporation dominates precipitation29, with a maximum value of 1.1‰ reached in the south tropical Atlantic, east of the Brazilian coast. In some parts of the Arctic region , strongly negative values (down to −5.4‰) are measured, which could be due to the influence of the isotopically depleted waters originating from the large Siberian rivers, transported southwards along the eastern Greenland coast by the transpolar current. On the eastern part of the Fram Strait, as well as the Barents and Norwegian Seas, the δ18O values stay similar to mid-latitude values, even in sea ice-covered areas , without any very isotopically depleted water masses contrary to the Arctic Ocean. The d-excess values of surface oceanic samples do not present clear latitudinal variations  for the complete observational period , specific humidity , δ18O  and δ2H  and good for the second-order d-excess signal .Outputs from an atmospheric general circulation model with an explicit diagnostic of stable water isotopes  nudged to meteorology (see the Methods section) are compared with the observations. The atmospheric isotopic measurements are very well reproduced by one of the simulations  is distributed along the ice-free Atlantic region, from 81° N, near Svalbard, to 74° S in the Amundsen Sea . The corresponding dataset . In our observations, the d-excess values in near-surface vapour are anti-correlated with RHsea and correlated with SST . A multivariable linear regression of d-excess against both parameters indicates that constant d-excess values are distributed along oblique lines in an RHsea/SST diagram sea in %, and SST in °C. We note that this empirically estimated function includes both spatial and seasonal temporal changes in the evaporation conditions. While it covers a large range of meteorological conditions in the Atlantic sector, caution should be taken to apply this empirical function to isotopic data sampled in very different spatial or temporal domains.A large range of meteorological conditions is covered by the observations from the open ocean, with very dry (+ 41%) to supersaturated (+ 125%) RHsee Fig. . We obtasea and SST on the d-excess signal, we sort our observational dataset into several categories, where both RHsea and SST vary within a small range only. In each of these categories, no relationship can be observed between the wind speed and the d-excess values. Under the assumption that the measured d-excess values are caused by kinetic fractionation occurring during local oceanic evaporation, our results indicate that these fractionation processes are independent of the concurrent wind speed.To investigate the influence of the wind speed on the d-excess signal, we first focus on the distribution of observed d-excess values against wind speed  with distinct kinetic fractionation coefficients for both regimes. Three different parameterisations of the kinetic fractionation are applied in our calculations. In the first parameterisation, a discontinuity is assumed in the kinetic fractionation coefficients at the wind-speed threshold of 7 m s−1, as suggested by MJ79. The two other parameterisations use constant kinetic fractionation coefficients, identical to those applied either below or above this wind-speed threshold (see details in the Methods section). Our calculations imply a local closure assumption by considering only the local variations of RHsea, temperature, wind speeds and oceanic surface water isotopic composition, neglecting any potential mixing of local vapour with advected air masses or convection.Next, we compare our open-ocean water isotopic measurements with calculations of the atmospheric boundary layer water vapour isotopic composition, based on the MJ79 evaporation model. In this model, an influence of wind speed on the kinetic fractionation during evaporation is considered, as wind will affect the surface roughness by generating waves, which in turn might alter the evaporation flux. Based on laboratory experiments18O and δ2H values of all calculations are comparable, but do not match the observations . With a parameterisation of the kinetic fractionation coefficients using the constant values of the rough wind regime, most observed d-excess values at open sea are correctly reproduced . This bias of ~5‰ disappears for the highest d-excess values when constant kinetic fractionation coefficients equivalent to a rough wind regime . The isoGCM does not require any closure assumption, as it takes the mixing of locally evaporated vapour with advected moisture explicitly into account. Thus, it should in principle fit better to the observations than the MJ79 model calculations. For vapour over an open ocean, assuming two distinct evaporative regimes, with kinetic fractionation coefficients depending on the wind speed and a critical wind threshold of 7 m sThe analysis of measured in situ d-excess values, the different calculations based on the MJ79 theoretical model and the simulations with a complex isoGCM all indicate that the variations of the atmospheric boundary layer d-excess values over the ocean surface are not modulated by wind speed, contrary to the suggestions made by MJ79. The d-excess values can be best explained by assuming constant kinetic fractionation coefficients in fractionation calculations, with the values that we originally used for a rough wind regime only.19. From our analyses, we cannot make any conclusive statement about the validity of the model, as we did not performed comparable (laboratory) experiments directly above the water surface. However, our results clearly indicate that the MJ79 model should not be applied in its original form for the calculation of isotopic changes in atmospheric vapour well above the ocean, e.g., as done in current isoGCMs. The wind and wave-type range investigated for the MJ79 model approach might not necessarily represent the diversity of surface oceanic conditions observed at sea. For example, a rough ocean surface with high waves might also be caused by swell, and does not have to be directly linked to high wind speeds occurring at the same time. Based on our new dataset, we rather suggest to modify the MJ79 model and use constant kinetic fractionation coefficients instead of wind-speed-dependent values. This conclusion is supported by the recently reported lack of wind-speed influence on the water vapour d-excess signal measured at coastal stations in Bermuda and the south coast of Iceland15.Our results are based on observations within the boundary layer, ~30 m above the skin layer, at which the evaporation takes place. On the opposite, the wind speed-dependent kinetic fractionation parameterisation of MJ79 is based on wind tunnel experiments performed for a limited range of wind speeds and wave typesN = 854 simultaneous vapour isotopic and meteorological observations).Next, we focus on a subset of data gathered at high latitudes, where sea ice has been surrounding Polarstern . The corresponding dataset contains measurements from both the Arctic and Antarctic regions  and does not improve when separating Arctic from Antarctic data for the analysis. A decrease of RHsea is observed with increasing sea ice coverage, related to an air temperature decrease, while the SST values cannot be lower than about −1.8 °C .A recent studysee Fig. . HoweverN = 840 comparison points with observations; see Fig. 18O and d-excess are small and do not agree with the measurements . In the second simulation, the measured low δ18O and high d-excess values of vapour over sea ice-covered areas are better simulated  is based on a subset of our observational data and thus does not represent a strict independent proof for the importance of snow sublimation as a source for the isotopic composition of the vapour. We rate it as a first-order approach to include snow on sea ice for future isotope modelling studies. Further observational data are certainly necessary to validate and improve this parameterisation, e.g., to take the flushing of the snow by seawater in fragmented sea ice areas into account, as well as potential isotopic fractionation effects during the sublimation of the snow.To identify the potential cause of this effect, we compare our measurements to two isoGCM simulations  are matched by both isoGCM simulations, independently of the parameterisation of sublimation above sea ice. Advection of isotopically depleted vapour from the Greenland ice sheet towards the research vessel could create a signal overprinting the local vapour isotopic composition. The model simulates sublimation over Greenland with the same surface source for both parameterisations, contrary to the sublimation taking place on the sea ice, and would provide the same isotopic composition in both simulations. However, such influence of katabatic winds on our dataset is generally limited, both around Greenland and Antarctica. Within the sea ice-covered area, air masses originating from coastal regions, as filtered for the open ocean, represent ~8% of the dataset. Our results concerning the sea-ice influence on d-excess do not change when filtering data points potentially influenced by such continental air masses (not shown here).During August 2016, measurements on the research vessel have been performed in an area with only a partial sea ice coverage in the vicinity of the Greenland ice sheet, close to the outlet of the Nioghalvfjerdsbrae glacier (latitude 79° N). Very depleted isotopic values of near-surface vapour measured during this period  and temperature (Tair) at 29 m above sea surface and water temperature (SST) at 5 m below sea surface. Air pressure (P) is measured at an altitude of 19 m, but expressed at sea level. The calibrated and validated datasets are available at a 10-min averaged temporal resolution on PANGAEA Open Access library34 and have been averaged at a 6-h temporal resolution in this study.Routinely measured meteorological data from Polarstern are used in this study. The related sensors are located at different heights: wind speeds and wind directions are measured at 39 m above sea surface, relative humidity (RHsea) is not directly measured but has been approximated35 from the observed relative humidity RHair at 29 m, corrected by the ratio of specific humidity at saturation between the temperatures at this elevation and at the sea surface (Tair and SST)sat(T) is the specific humidity at saturation for a given temperature T and qsat(SST) is calculated for seawater at salinity 35 PSU36. For intercomparison with other sea surface water vapour isotopic measurement campaigns27, this calculation is performed using the air temperature and relative humidity corrected from the altitude at 10 m.The relative humidity of the near-surface air with respect to the saturation vapour pressure at the ocean surface (RH−1) are retrieved at the Polarstern locations from the Met Office Operational Sea Surface Temperature and Ice Analysis (OSTIA)37 products at a 0.25° × 0.25° horizontal resolution. The original dataset has a 1-h temporal resolution and has been averaged at a 6-h temporal resolution. A comparison with the Polarstern SST measurements at 5-m depth for the period 29 June 2015 to 31 January 2017 gives a very good agreement between both datasets .For the complete measurement period, the skin SSTs  of the sample and of the Vienna Standard Mean Ocean Water (VSMOW2)39, respectively:Isotopic compositions of samples are reported using the δ-notion, where R6:The deuterium excess values are computed based on the commonly used definition18O and δ2H values of water vapour at a temporal resolution of ~1 s. The ambient air inlet for this instrument is located at 29 m above the sea level, connected to the analyser through an ~25 -m-long tubing heated at 65 °C. The humidity mixing ratio is converted into specific humidity measured by the CRDS analyser (qCRDS) and corrected by a linear function derived from the direct comparison with specific humidity values derived from the meteorological observations (qmeteo) on-board the Polarstern, during the complete measurement period from 1-h resolution datasets: qmeteo = 0.75 × qCRDS − 0.17 . qmeteo is calculated based on RHair, Tair and P. The precision of specific humidity measurements is estimated at 0.1 g kg−1 from the comparison of both datasets.A Cavity Ring Down Spectroscopy (CRDS) analyser  has been running continuously on-board of the research vessel Polarstern since the 29 June 2015, recording humidity mixing ratio, δ18O values between −7.8‰ and −40.7‰). Recommendations for long-term calibration of CRDS water vapour isotopic analysers were followed41. Therefore, our system allows two types of calibration. Firstly, the concentration dependence35 of the raw isotope measurements is corrected. Secondly, repeated corrections of the deviation of the measurements from the VSMOW-SLAP scale42 are performed by the computation of calibration curves based on the measurements of the water standards, thereby allowing correction of the instrumental drift.For instrument calibration of the isotopic values, a custom-made system is used, vaporising water isotopic standards injected in liquid form and mixed with dry air provided by high-pressure gas cylinders. Four different liquid isotopic standards are used, covering the range of the expected ambient air values , σ(δ18O) and σ(δ2H), respectively) higher than 2500 ppm, 1.5‰ and 5‰. We compute a first 14-day running average and eliminate all measurements that deviate from this running average by more than 1.5‰, 5‰ and 8‰ for δ18O, δ2H and d-excess, respectively. The observed variabilities of these selected measurements of all liquid standards are shown in Supplementary Fig. Calibration curves are applied to the raw data to correct deviations from the VSMOW-SLAP scale. These calibration curves are calculated based on the repeated measurement of every liquid standard for 30 min every 25 h . To avoid any memory effects, averaged values and standard deviations of the standard isotopic composition are computed over the last 15 min of each injection only. Several filtration and correction steps . For comparison with other parameters, an interpolation of this dataset has been used at a 6-h resolution.Isotopic composition of the surface oceanic water has been measured from daily taken samples since 30 June 2015, filled in narrow-mouth low-density polyethylene 20- or 30-mL plastic bottles, sealed with Parafilm M and stored at +4 °C from the end of the expedition until the measurement. Measurements are done with IRMS and equilibration technique at the isotope laboratory of AWI Potsdam35. We thus express the boundary layer vapour isotopic ratio (RBL) as a function of the surface seawater isotopic ratio (RSW), taking both equilibrium and kinetic fractionation coefficients αeq and αk and RHsea into account:eq values44. RSW is determined by the interpolated values of the isotopic composition measured in daily sampled surface oceanic water.For all the observations performed above the open ocean, we compute the corresponding theoretical water vapour isotopic composition in the atmospheric boundary layer over an open ocean based on the MJ79 model under the closure assumption. We assume it to be equal to the isotopic composition of the evaporation fluxref), the kinetic fractionation coefficients (1H2H16O) for a smooth or a rough wind regime are used for wind speed, respectively, below or above the threshold of 7 m s−1. We respectively apply kinetic fractionation coefficients45: smooth and MJ79rough), the kinetic fractionation coefficients are set constant and independent of the wind speed, either to the value of a smooth or a rough wind regime.We use three different parameterisations for the kinetic fractionation coefficients dependency on wind speed. In the first simulation  and 31 vertical levels. The model is nudged to ERA-interim surface pressure, temperature, vorticity and divergence fields47 to ensure that the simulated large-scale atmospheric flow is modelled in agreement with the ECMWF reanalysis data on all analysed timescales during the years 2015–2017. For each time step of 6 h, isoGCM simulation results of near-surface vapour amount and its isotopic composition are extracted from the model grid cell encompassing the position of Polarstern. In the vertical direction, this grid cell extends from the surface to ~60 m above the surface. Two different ECHAM5-wiso simulations are performed, all covering the period from January 2015 to July 2017 after a 12-month spin-up period.In this study, isoGCM simulations are performed with the ECHAM5-wiso modelexp), different kinetic fractionation coefficients during evaporation over open water are applied depending on wind speed: constant coefficients for a smooth wind regime, and wind speed-dependent coefficients for a rough wind regime are used for wind speeds below or above the threshold of 7 m s−1, respectively48. Over sea ice-covered areas, bare ice is prescribed with an isotopic composition of ocean surface water, based on a global gridded data compilation of δ18O in seawater49.In the first simulation , constant fractionation coefficients for δ18O and δ2H, suggested for a rough wind regime35, are applied under all different meteorological conditions for evaporation processes. Over sea ice-covered areas, a 2 -cm-deep snow layer pad is assumed on top of any sea ice-covered grid-cell fraction, to account for accumulation and sublimation of snow on sea ice. The isotopic composition of the bare sea ice is assumed to be equal to the composition of surface ocean waters, neglecting a potential small fractionation process occurring during the formation of sea ice. The prescribed surface ocean δ18O and δ2H values are taken from a reference global gridded dataset compilation49. The isotopic composition of the snow layer is determined by the isotopic composition of the accumulated snowfall. During sublimation processes, no fractionation of the snow is assumed. This treatment of snow on sea ice as a single-layer bucket model is equivalent to treatment of snow on land surfaces in ECHAM5-wiso. The deposited snow in the model is locally controlled, without taking any advection of sea ice or snow drift into account. In reality, the isotopic composition of the sea ice surface will not only be determined by the isotope signal of bare ice or snow on top of the sea ice, but also by further processes altering the sea ice surface. For example, sea spray or breaking waves might substantially alter the isotopic composition of a snow-covered sea ice surface, especially for regions with only a minor area fraction covered by sea ice. These effects will lead to a further mixing of the isotopic signal of the original fallen snow with the isotopic composition of the surrounding ocean surface waters. To account for such processes in ECHAM5-wiso, the isotopic composition of the sea ice surface is assumed as 18O or δ2H, δsea ice surface the isotopic composition of the sea ice surface, δsnow bucket the isotopic composition of the snow bucket on sea ice, δocean the isotopic composition of the surrounding ocean surface water and f as the fraction of sea ice in each grid cell. This empirical formula is based on a comparison of measured and simulated δ18O and d-excess values for the period from August to October 2015 and applied for the data-model comparison over the whole measurement period of this study , we consider the corresponding measurements as influenced by surface processes over the open ocean. Vice versa, the isotope data corresponding to sea ice-covered areas are selected by including all measurements, where the ERA-interim sea ice coverage in the grid cell surrounding the research vessel Polarstern is higher than 0%. The locations of all filtered datasets are displayed in Supplementary Fig. Supplementary InformationPeer Review File


The growth hormone (GH) plays a key role in the regulation of metabolic processes in an organism. Determination of the correct structure and functioning of the growth hormone receptor (GHR) allowed for a more detailed research of its post-receptor regulators, which substantially influences its signal transduction. This review is focused on the description of the post-receptor inhibitors of the GHR-JAK2-STAT pathway, which is one of the most important pathways in the transduction of the somatotropic axis signal. The aim of this review is the short characterization of the main post-receptor inhibitors, such as: cytokine-inducible SH2-containing protein (CIS), Suppressors of Cytokine Signaling (SOCS) 1, 2 and 3, sirtuin 1 (SIRT1), protein inhibitors of activated STAT (PIAS) 1, 3 and PIAS4, protein tyrosine phosphatases (PTP) 1B and H1, Src homology 2 (SH2) domain containing protein tyrosine phosphatase (SHP) 1, 2 and signal regulatory protein (SIRP) α1. The equilibrium between these regulators activity and inhibition is of special concern because, as many studies showed, even slight imbalance may disrupt the GH activity causing serious diseases. The regulation of the described inhibitors expression and activity may be a point of interest for pharmaceutical industry. GH1 and GH2) and three placental lactogens  that are located in the chromosome 17 [GH1 is stated in the anterior part of pituitary, which is responsible for the action of this hormone at the endocrine level, but it is found also in numerous tissues and cells, in which GH acts in an auto/paracrine manner [Growth hormone (GH), one of the major hormones of the somatotropic axis, is a 191-amino acid protein found in many isoforms [osome 17 . In adule manner . The rege manner . Howevere manner ,7,8, lepe manner , cortiste manner  or klothe manner . Many fae manner ,14.The role of GH in organism is mostly related to body growth and development. However, the range of actions of GH is pleiotropic. GH participates in the regulation of, for example, metabolism, immunology and reproduction. Both inhibition and enhancement of the GH activity may be harmful for the organism. Consequences of its deficiency include short stature, decreased bone mineral density and concentration, decreased muscle strength, thin skin and hair, delayed puberty and increased adiposity and hepatic steatosis along with impaired cognitive ability in several fields ,16. On tGrowth hormone receptor (GHR) has been classified as a class 1 signaling molecule since the crystal structure of GHR-GH complex was revealed as 2:1 ratio between the receptor and hormone  Figure . It was The GHR is responsible for regulation of many processes including erythropoiesis, myelopoiesis, lactation, growth and metabolism. This is a single membrane pass receptor with the characteristic structure of the extracellular domain built of two fibronectin III-like modules. These modules with seven stranded β-sandwich structure are the centers of ligands binding. The common element of this class of receptors is the Box 1 motif which is present on the intracellular domain. Box 1 plays a crucial role in the transduction of the GHR signal. Binding of GH to its receptor causes a rapid binding of Janus kinase 2 (JAK2) to Box 1 via the N-terminal 4.1, Ezrin, Radixin, Moesin (FERM) domain  and the STAT proteins are present in varied structural forms, e.g., monomers, homodimers and heterodimers . InitialSTAT5β gene causing deficiency of IGF-1, which expression is strictly correlated with STAT5β [Among the STATs, STAT5β plays the most important role in the transduction of GH signal into a cell. Udy et al. , who conh STAT5β . In IGF-h STAT5β ,58.The aim of this review is to present factors that can modulate the activity of the GHR-JAK2-STAT pathway which has the most pronounced role in the somatotropic axis signal transduction. The review is focused on the post-receptor regulators of GHR transduction pathway, which affect the axis in an inhibitory manner, such as cytokine-inducible SH2-containing protein (CIS), suppressor of cytokine signaling (SOCS) 1, SOCS2, SOCS3, sirtuin 1 (SIRT1), signal regulatory protein α1 (SIRPα1), protein inhibitor of activated STAT (PIAS), protein tyrosine phosphatase-1B (PTP-1B), PTP-H1, SH2 domain containing protein tyrosine phosphatase-1 (SHP-1) and SHP-2.SOCS are also known as STAT-induced STAT inhibitory proteins (SSI) and their expression is induced by an activation of the JAK-STAT signaling pathway. Hitherto, 8 members of the SOCS family have been described: CIS and SOCS1–7 . The SOCSOCS2 gene deletion. Aforementioned team demonstrated that SOCS2 knock-out (KO) mice were significantly larger than wild-type (WT) mice. The difference in weight gain became significant after weaning and, moreover, was associated with significant increase in bone length and proportional increase in weight of most organs. Authors stated that the activity of the somatotropic axis deprived of SOCS2 regulation was enhanced, resulting in, among others, increased level of IGF-1 mRNA expression in heart, lungs or spleen. However, there was no significant increase of this gene expression in bones, adipose tissue, muscle and liver, which is quite surprising in the light of other researchers’ results [It was shown that four SOCS proteins participate in the GH signal inhibition: CIS and SOCS1–3. As it was stated in many studies, expression of aforementioned SOCS proteins are induced by the GH action ,66,67, a results ,70.CIS gene expression the first peak of the mRNA level was observed after 60 min and later increased between 4th and 24th h after the GH administration reaching the peak of the 10 times of its initial value. The varied kinetics of SOCS proteins genes expression and so their different inhibitory pattern on GH signal transduction may be due to differences in their structure. SOCS1 and SOCS3, unlike SOCS2 and CIS, have a small kinase inhibitory region (KIR domain) located at N-terminus [CIS and SOCS1–3 proteins exhibit a varied mechanism of action, different pattern of expression and intensity of inhibitory effect in response to different cytokines and GH action. Adams et al.  conductiterminus ,73, whicIn the regulation of the activity of GHR pathway, all engaged SOCS proteins  have the same mechanism of phosphorylation inhibition of STATs by the competitive binding to phosphotyrosines of the GHR . The SOCAs it was mentioned above, CIS and SOCS2 also bind to receptor phosphotyrosine and in this case the mechanism of GH signaling inhibition is based on the competitive to STATs binding to the GHR complex . The inhMoreover, several mechanisms modulating action of SOCS proteins have been discovered. Peltola et al.  demonstrSaccharomyces cerevisiae gene silent information regulator 2 (Sir2). In humans, seven sirtuins (SIRT1–7) that regulate varied metabolic pathways have been found [In mammals sirtuins are a family of nicotinamide adenine dinucleotide (NAD+) dependent enzymes that show homology to en found . The mosen found ,87,88. Ten found .It was also found that SIRT1 can inhibit GH signaling. Yamamoto et al.  investigThe inhibitory effect of SIRT1 was observed also on STAT3 protein activity. Nie et al.  conductePIAS is a family consisting of four multifunctional proteins (PIAS1–4). PIAS proteins play an important role in the modulation of multiple signaling pathways through different molecular mechanisms ,93. The Ctenopharyngodon idella), whereas PIAS1 overexpression induced inhibition of STAT5-mediated promoter activity. The results may indicate the existence of the negative feedback loop between somatotropic axis and PIAS1 protein in the grass carp.The only available report about the role of PIAS in the somatotropic axis signaling is derived from the studies conducted on fish model . AccordiLiu et al.  stated tThe inhibitory effect of PIAS proteins on STAT DNA binding activity can be achieved by several possible mechanisms. Firstly, the binding of PIAS proteins to STAT dimer may mask the DNA binding domain of STAT. Secondly, PIAS proteins may bind to STATs and prevent their dimerization . PIASs cThe studies on the PIAS action without DNA binding inhibition were conducted by Liu et al. . The resLiu et al.  demonstrChung et al.  conducteThe next factors regulating the somatotropic axis activity are the protein tyrosine phosphatases. Pasquali et al.  identifi−/−) and compared the impact of standard and high-fat diets. The body weight and fatness were similar in the females from the liver-specific PTP-1B−/− and control groups. In animals fed standard diet, after 48 h of fasting the GH resistance state developed and an intraperitoneal GH administration led to stimulation of the JAK-STAT signaling pathway. At the same conditions the mutants showed significantly higher GH-induced phosphorylation of JAK2 and expression of the SOCS3 gene. However, the STAT3, STAT5 and ERK1/2 phosphorylation and SOCS2 gene expression were similar in both groups. Significantly higher level of mechanistic target of rapamycin (mTOR) phosphorylation was observed in mutants 5 min after the GH administration. Under the high-fat diet condition, the GH-induced phosphorylation of STAT5 was significantly higher in liver-specific PTP-1B−/− mice, but did not change in the control group. The authors pointed out that the deletion of the PTP-1B gene in the liver leads to significant changes in the GH signal transduction as well as to the increased phosphorylation of JAK2 and STAT5, and expression of SOCS3 gene.Likewise other researchers conducted studies on the PTP-1B KO mice and observed significant growth disturbances. Escrivá et al.  stated tPasquali et al.  observedPTPN6 gene. Its presence was stated, inter alia, in the bone marrow, including the hematopoietic cells [Src homology 2 (SH2) domain containing protein tyrosine phosphatase (SHP-1) is encoded by the ic cells  and meseic cells . In the ic cells  or oligoic cells . SHP-1 aic cells . Using tic cells  demonstric cells . Hackettic cells  stated aic cells , conductPTPN11 gene. SHP-2 is built of two chains, each of which contains three domains: one tyrosine phosphatase domain and two SH2 domains (C-SH2 and N-SH2) [SHP-2 (Src homology phosphatase 2), also called tyrosine-protein phosphatase non-receptor type 11 (PTPN11), protein tyrosine phosphatase 1D (PTP-1D) or protein-tyrosine phosphatase 2C (PTP-2C), is an enzyme that is encoded in human by the d N-SH2) . SHP-2 id N-SH2) , both asd N-SH2) . SHP-2 pd N-SH2)  investigd N-SH2) . The resd N-SH2) , the SHPThere are various mechanisms regulating SHP-2 catalytic activity. The first one is connected with dual activity of N-SH2 domain . The N-SPTPN11 gene [PTPN11 gene, which affects the proteins involved in the interaction of N-SH2 and PTP domains resulting in chronic stabilization of the active conformation of the SHP-2 molecule, and thus the gain-of- inhibitory function [The important role of the SHP-2 in the regulation of the GH signal transduction is confirmed by two syndromes, Noonan (NS) and Leopard (LS) syndrome, which are primarily caused by mutation in the N11 gene ,123. ManN11 gene ,124,125.function .Signal regulatory proteins (SIRPs) are glycoproteins characterized by the presence of immunoglobulin-like domains located extracellularly. In contrast to SIRPβ subgroup, SIRPα1 has a cytoplasmic domain containing four immunoreceptor tyrosine-based motifs (ITIM) and a proline rich region . By the Considering the pleiotropic role of the somatotropic axis in the whole organism, studies aimed at understanding its regulatory mechanisms seem very important. In this review, the several physiological inhibitors of the GHR-JAK2-STAT pathway, which act through numerous different mechanisms , have been presented. The understanding of the physiological role of the GHR-JAK2-STAT pathway may have a profound importance for current medicine. It is well known that GHR regulates many cellular pathways involved in survival, proliferation, metastasis, epithelial to mesenchymal transition, apoptosis and cell cycle, but its hyperactivation may increase the risk of cancer in general . GHR actBesides the modulation of the equilibrium between activity and inhibition of the described GHR-JAK2-STAT pathway inhibitors, the medical approach directed to new synthetic inhibitors of this pathway’s main components (JAK2 and STATs) is of the wide medical interest. Many of JAK’s and STAT’s inhibitors have being currently tested in various conditions from asthma to malignancies, myeloproliferative diseases or autoimmune conditions. The emergence of a new class of therapeutics targeted at the JAKs , which have been already approved by the Food and Drug Administration (FDA), is of a great importance in modern animal and human medicine. The next challenge of the pharmaceutical industry is the development of the STAT inhibitors with clinical relevance . Therefo


Background: Several studies have shown that non-renal factors such as corticosteroids may increase plasma cystatin C levels without affecting kidney function. However, the mechanisms underlying this are unclear. We hypothesized that corticosteroids may increase cystatin C levels in the plasma by promoting its production in tissues. In the present study, we aimed to test our hypothesis in rats by investigating the effect of corticosteroids on cystatin C production in tissues and the glomerular filtration rate (GFR), as measured by the gold standard method .Results: Dexamethasone treatment was associated with much higher concentrations of cystatin C in all organ tissue homogenates tested. Dexamethasone increased plasma cystatin C levels in rats, without any decrease in renal inulin clearance. The impact of dexamethasone on plasma and organ tissue cystatin C levels was abolished by RU486, indicating the effect was glucocorticoid receptor-mediated.Conclusions: Our study provides direct evidence that corticosteroids may increase cystatin C levels in the plasma by promoting its production, without any decrease in GFR. The glomerular filtration rate (GFR) is the key element in establishing a prognosis-predicting model, risk stratification, and drug–dose adjustment tools because impaired renal function adversely affects survival, prognosis, and drug pharmacokinetics ,2. CystaDexamethasone sodium phosphate (DEX) was kindly provided by CSPC Pharma . Mifepristone (RU486) and inulin were purchased from Sigma-Aldrich . EDTA and aprotinin was kindly provided by the Beijing North Institute of Biological Technology . A Rat Cystatin C Immunoassay Elisa Kit  was purchased from R&D systems (Germany).ad libitum access to food and water. All rats were housed for one week to allow them to adapt to their environment before the study protocols were initiated. All experimental protocols were approved by the Institutional Animal Care and Use Committee of Hebei Medical University (SCXK 2018-004). The rats were managed in accordance with the guidelines for Animal Care and Use of Hebei Medical University.A total of eighteen male Sprague–Dawley (SD) rats  of body weight in the range 280–320 g were housed in a temperature-controlled environment, exposed to a natural photoperiod (light/dark cycle of 12:12 h), and given n = 6/group), as follows: (i) CON: rats received the vehicle  as a control; (ii) DEX: rats received DEX  for 2 days; (iii) DEX + RU486: rats received RU486  for 2 days. RU486 was administered 1 h prior to DEX to block the glucocorticoid receptors [The SD rats were randomly divided into three groups  was determined as recently described . BrieflyFrozen tissues were homogenized, then a BCA Protein Assay Kit  was used for the quantitative determination of total protein concentration in the supernatants. Plasma and tissue supernatants were diluted to suitable concentrations and measured using an ELISA assay kit .post hoc Tukey’s test was performed. p values of <.05 were considered statistically significant .All data are presented as means ± standard error of means (SEM). Statistical analyses were performed using the SPSS statistical package . Kruskal–Wallis test was conducted if data of groups were not normally distributed. If variances were homogenous, p < .05, p < .05, Following two days of treatment, rats that received DEX had much higher cystatin C levels in their plasma compared with those treated with vehicle . Consistent with the findings for cystatin C levels in plasma, the effect of DEX on cystatin C levels in the tissue homogenates was also abolished by RU486 (To test the effect of DEX on the production of cystatin C in tissues, we collected five organ tissue homogenates, from the kidneys, brain, intestines, liver, and lungs. Cystatin C levels were consistently higher in DEX-treated rats compared with those treated with the control (by RU486 .In the present study, we found that the corticosteroid dexamethasone significantly increased cystatin C levels in the plasma of rats and also in tissues, including the kidneys, brain, intestines, liver, and lungs. However, dexamethasone had no impact on GFR as determined by inulin clearance.Over the past few decades, many methods have been developed to assess GFR; most of these are creatinine-based equations ,2. The mIn addition to glucocorticoid treatment, many other non-renal factors have been reported as having an impact on serum cystatin C levels . These nIn conclusion, the data from our study showed that corticosteroids can promote the production of cystatin C in various body tissues, resulting in elevated plasma cystatin C levels, without any negative affect on GFR.Many physiological processes in addition to GFR, such as generation, tubular reabsorption or secretion, and extra-renal elimination can affect the levels of endogenous GFR markers. Measuring changes in the urinary excretion of endogenous markers can help to assess these physiological processes. For example, urinary creatinine excretion can be measured to help interpret unexpected values for creatinine-based eGFR. Unlike creatinine, the absence of urinary excretion of cystatin C makes it impossible to interpret GFR estimates based upon cystatin C. Therefore, our data suggest that cystatin C levels should be interpreted together with the knowledge of several non-renal factors, such as obesity, inflammation, diabetes, proteinuria, or drugs that may impact plasma cystatin C levels. More importantly, clinicians should incorporate serum creatinine levels or serum creatinine-based eGFR results to assist in the interpretation of serum cystatin C and cystatin-C-based eGFR, especially when unexpected eGFR values are encountered.