M = 16.91, SD = 0.99), who were competing in the national football championship. The results indicated that cognitive appraisal partially mediated the relationship between competitive stressors and emotions: athletes who perceived stressors as a challenge, tended to feel more control over the situation and more resourceful (coping perception), leading to a more positive emotional experience, while those perceiving the stressors as a threat were more prone to experience less control and more negative emotions. This mediation model was moderated by athletes’ competitive level (U17 or U19), as the role of challenge perception was more pronounced in the U19 team, while the relationship between threat perception and less control was only observed for the U17 team. In sum, the data reveals the importance of cognitive appraisal in young football athletes’ adaptation to competitive stressors, bolstering the theoretical models in this area and the importance of psychologists to consider these variables during intervention, particularly cognitive appraisal.This study analysed the adaptation of football athletes to competitive stressors regarding the upcoming match. For that, the study adopted a cross-sectional methodology using a critical incident approach. The participants were 352 young male football athletes, aged between 15 and 19 years ( Stress is a prominent topic in daily life because of its impact on individuals’ living contexts, being well-known some harmful effect on physical and mental health . Stress stressors that trigger the situation, how the situation is evaluated by the individual , and the feelings that emerge from the situation. In other words, there are four key variables involved in the adaptive process: the stressors, the cognitive appraisal of the stressful situation, the athletes’ ability to cope with stress, and the emotions arising from those situations. Regarding stressors, there is evidence that athletes face numerous stressors, as is the case of pressure to perform, social expectations, fear of opponents or injuries, fear of making mistakes, among others  coping in terms of personal resources to cope with the demands of the event; (c) control regarding the stressful event; and, (d) future expectations, that is the extent to which the situation can change for the better or worse, taking into account the athletes’ personal goals  challenge, in which the athlete appraises the situation as stimulating and anticipates gains; (b) threat, in which the athlete anticipates that something negative may occur in the future; (c) benefit, in which the athlete identifies the situation as advantageous; and, (c) loss or damage, in which the athlete identifies the situation as harmful or damaging . Next, tal goals . Taken tal goals . This diThe analysis of how athletes appraise the stressors allows for a deeper understanding of the stress experience , which, The relations established between stressors, cognitive appraisal, and the emotions associated with the stressful experience have been considered by transactional  and inteThe process of cognitive appraisal has consequences on athletes’ emotions, which represents the third variable in the analysis in this study. Emotions are understood as psychophysiological reactions resulting from the interaction with the environment, being inherently linked to cognitive appraisal . In factIn sum, this study comprises three variables that are central in the understanding of human adaptation to stress, and their role in the analysis was conceptually determined: competitive stressors  were conceived as antecedent variables (predictor variable), the cognitive appraisal was as a mediator, and emotions were as a consequent variable (criterion variable). Thus, it is expected that:H1. The relationship between competitive stressors and emotions is mediated by primary and secondary cognitive appraisal. Specifically, it is expected a negative pattern of adaptation to stressors in this way: (a) higher perception of stressors predicts negative patterns of cognitive appraisal , which, in turn, predicts a more negative emotional experience and a less positive emotional experience; and it is expected a positive pattern of adaptation to stressors in this way: (b) lower perception of stressors predicts positive patterns of cognitive appraisal , which, in turn, predicts a more positive and less negative emotional experience.Some studies indicate that the relationship between cognitive appraisal and emotions is not as linear and automatic as previously thought e.g., . Thus, iIndeed, previous literature has found significant age differences in how athletes perceive and deal with stressful events in sports contexts. For example, H2. The relationship between competitive stressors and emotions is mediated by primary and secondary cognitive appraisal (as stated in H1) and is moderated by athletes’ competitive level (U17 and U19). Specifically, it is expected that the negative pattern of adaptation to stressors predicted on H1  is stronger in younger athletes (U17), and the positive pattern of adaptation to stressors  is stronger on older athletes (U19).In sum, filling an important gap in the literature  by pursuM = 16.91, SD = 0.99). In terms of competitive level, 189 (54%) were in the U17 teams (ages between 16 and 17 years old) and 163 (46%) in the U19 team (ages between 18 and 19 years old). Regarding the number of collective titles won by the athletes, 268 (76%) reported at least one title, while 84 (24%) did not obtain any title. The mean of years of practice in official competitions was 9.14 (SD = 2.19), ranging from 1 to 15 years.The study involved 352 male young soccer athletes included in the Portuguese national championship of soccer, with ages for total sample ranging from 15 to 19 years old . The 24 statements were divided into six dimensions (4 items each): (a) competitive readiness: stress related to the athlete’s concern about not being well prepared for competing ; (b) performance: stress related to athlete’s concern about having a bad performance or a performance below expectations ; (c) errors: stress related to the athlete’s concern about failing or making mistakes in important moments of competitions ; (d) social expectations: stress related to athlete’s concern related to not corresponding to what is expected of them and receiving negative evaluations from others ; (e) opponents: stress related to athlete’s concern about competing with high qualified opponents ; and (f) injuries: stress related to athlete’s concern about the possibility of getting injured . The final score of perceived stress was computed through the average of the items’ scores of each dimension. Confirmatory factor analysis was performed to test construct validity and the instrument showed good psychometric properties in this study: χ2 (234) = 594.81, p < 0.001; χ2/df = 2.54; RMSEA = 0.066, C.I. ; SRMR = 0.073; CFI = 0.919; TLI = 0.904.The Questionnaire of Competitive Stressors in Sport QCSS;  was usedNot at all; 6 = Very much). It evaluates two dimensions: (a) the primary cognitive appraisal; and (b) the secondary cognitive appraisal. In the first section , athletes indicate the importance and personal significance of the match in question, including three subscales (3 items each): (a) importance perception: indicates the importance attributed by the athlete to the upcoming match ; (b) threat perception: indicates the extent to which the athlete evaluates the upcoming match as disruptive and negative ; and (c) challenge perception: indicates the extent to which the upcoming match is evaluated as stimulating and exciting by the athlete . Regarding secondary cognitive appraisal, athletes evaluated the resources they believe they possess to deal with and solve the situation in question, across two dimensions: (a) coping perception: indicates the extent to which the athlete feels he/she has the resources to deal with the demands of the upcoming match ; and (b) control perception: indicates the extent to which the athlete feels he/she has the power to decide about what to do in the upcoming match . The final score is computed through the mean of the items’ scores in each dimension, with higher values meaning higher scores in each dimension. Confirmatory factor analysis was performed to test construct validity and the instrument showed good psychometric properties in this study: χ2 (80) = 139.538, p < 0.000; χ2/df = 1.744; RMSEA = 0.046, C.I. ; SRMR = 0.044; CFI = 0.975; TLI = 0.968.The Primary and Secondary Cognitive Appraisal Scale PSCAS;  was usedNot at all to 4 = Extremely). Athletes fulfilled the instrument by thinking about their feelings at that specific moment regarding the upcoming match. The final score is obtained through the mean of the items’ scores of each dimension, with higher values meaning a greater emotional experience of the dimension in question. Confirmatory factor analysis was performed to test construct validity and the instrument showed good psychometric properties in this study: χ2 (178) = 406.185, p < 0.000; χ2/df = 2.282; RMSEA = 0.060, C.I. ; SRMR = 0.086; CFI = 0.952; TLI = 0.943.The Sport Emotion Questionnaire [SEQ; translated and adapted from The study was first submitted and approved by the Ethics Committee of the first authors’ University (SECSH-0162015). In this study, a convenience sample was used considering the following inclusion criteria: (a) language (Portuguese speakers), (b) athletes were in conditions to compete in the next upcoming match, and (c) gender , (d) competitive level (part of the U17 or U19 teams), and (e) competitive level . Once the clubs accepted to be part of the study, athletes were contacted to participate. Because U17 and U19 teams were chosen, some athletes were underage (below 18 years old). In these cases, permission was first granted from their legal guardians. After legal guardians (when applicable) and athletes agreed to participate, the data collection was scheduled.Data collection followed a critical incident approach cf. , which iBefore answering the research protocol, athletes had to read the study’s instructions and goals and sign the informed consent forms. In the case of underage athletes, the informed consent was signed by their parents or coaches. Next, the athletes answered the evaluation protocol, consisting of the demographic information and the instruments explained below. The questionnaire was completed individually in an appropriate room made available by each sports club. It lasted between 15 and 25 min. Athletes’ participation was voluntary and anonymously, and the confidentiality of the collected data was ensured.n = 352). An online a priori sample size calculator for structural equation models was used to define the appropriate sample size for the proposed model . Correlations and VIF coefficients were used to assess for the multicollinearity assumption, and no indications of multicollinearity were found . Therefore, all assumptions were met.Regarding the statistical assumptions to conduct Structural Equation Modeling, we checked for normality cf.  and multThis study’s first analysis aimed to assess athletes’ psychological experience before an important match. To do so, descriptive analyses were conducted to check for the relations among the variables .®. To ensure that the proposed partial mediation was the model that fit the data best, it was compared against the direct model  and the alternative total mediation model (similar to the proposed model but without any direct effects from competitive stressors to emotions included). In order to simplify the models by decreasing the number of parameters to estimate (cf. 2); (b) Root mean square error of approximation , structural equation modeling was used in AMOS Softwaremate cf. , first-on RMSEA; , considen RMSEA; ; (c) Stan RMSEA; ; (d) Tucn RMSEA;  and Compn RMSEA; , for whin RMSEA; . Bootstr® using bootstrap technique and multigroup modeling . Competitive readiness and social expectations are negatively related to control perception. On the other hand, performance was positively related to excitement (positive emotion), and opponents were negatively related to the same positive emotions.Concerning the relationship between cognitive appraisal and emotions, threat perception was positively related to negative emotions and negatively related to positive emotions. On the other hand, the more athletes perceived the competition to be a challenge, the more positive their emotions (excitement and happiness), the higher their anxiety, and the lower their negative emotions (dejection and anger). Coping and control perceptions were also positively related to positive emotions. The coping perception was also found to be negatively related to negative emotions.To analyze the mediating role of cognitive appraisal in the relationship between competitive stressors and emotions, three different models were tested: (1) the direct model, which establishes a direct relationship between competitive stressors and cognitive appraisal of negative and positive emotions cf. ; (2) the2 = 9.92; Δdf = 2; p = 0.007), and then the direct model . This result supported H1, meaning that the cognitive appraisal mediated the relationship between competitive stressors and emotions. According to the results, this mediation was partial.Thus, the partial mediation model’s coefficients were further analyzed. The model explained the variance of the perception of threat by 10%, challenge perception by 1%, control perception by 7%, and coping perception by 17%. Moreover, 17% of the negative emotions’ variance and 37% of positive emotions’ variance were explained by the predictor and mediator variables.The direct effects cf.  showed tThe indirect and total effects are displayed in This analysis aimed to compare the model with the best fit  amongst U17 and U19 competitive levels. The central assumption was that the model would be invariant and that the model would behave similarly for both groups.pΔχ2 > 0.05 . However, the ΔCFI = −0.003, is a key criterion for the hypothesis of invariance of the measurement model not to be rejected because of the ΔCFI < −0.01.The first step consisted of comparing the invariance of the measurement model for the two groups; this was done by comparing the model with fixed weights against the unconstrained model . Measurement model invariance would be achieved if 2 > 0.05  and or i2 > 0.05 . Table 42 = 36.87, p = 0.005), which indicates that the competitive level acts as a moderator of the presented partial mediation model. This result supported H2, meaning that the relationship between competitive stressors and emotions was mediated by cognitive appraisal and moderated by athletes’ competitive level. The differences among groups are displayed in Z = 3.04, p = 0.001) is significantly stronger; as is the case, the relationship between threat perception and control perception is significant . Regarding the U19 group, two new relationships arise: higher perceived competitive stressors predicts lower coping perception , and higher perceptions of control predicted more negative emotions . When comparing to the U17 athletes, the relationship between perceived competitive stressors and perceptions of control , and between challenge and control perceptions , coping perception , and negative emotions  were stronger in the U19 group.Thus, assuming the invariance of the measurement model, the second step was to assess the invariance of the structural model. Therefore, assuming the measurement model to be correct, the structural model is different among the two groups . The relationship between competitive stressors, cognitive appraisal, and emotions was tested and compared among two competitive levels. The results indicated that performance and errors were important stressors. Regarding the mediation of cognitive appraisal between competitive stressors and emotions, two main aspects should be reinforced. First, higher perception of competitive stressors corresponded to higher experiences of negative emotions; in the same way, higher perception of competitive stressors corresponded to higher threat perception that, in turn, corresponded to less coping perception and lower experiences of positive emotions and higher experiences of negative emotions (confirming the negative pattern of adaptation to competitive stressors).On the contrary, higher challenge perception corresponded to higher control perception and coping perception, higher experiences of positive emotions, and lower experiences of negative emotions (confirming the positive pattern of adaptation to competitive stressors). These results were found for the partial mediation model, confirming that the relationship between competitive stressors and emotions is mediated by the cognitive appraisal, confirming H1, although not all structural paths in the model were significant. It is also important to note that competitive level assumed a moderating role in these relationships among variables, confirming H2, although the structural paths are somewhat complex to interpret. Specifically, for U17 athletes, a negative relationship was found between threat perception and perceptions of coping and control, meaning that higher threat predicted less ability to cope and control the competitive stressors related to the upcoming match. For the U19 athletes, the set of significant relations increased, showing that a higher perception of competitive stressors predicted a lower perception of control  and a lower perception of coping. Moreover, significant increases in challenge perception predicted higher control perception .Taking a closer look at the results and explicitly analyzing the stressors, we verified that that performance and errors were the highest sources of stress in sports, which is consistent with previous research e.g., . AthleteHowever, previous literature testing the Transactional Model of Stress also suggests that cognitive appraisal can help to mitigate these effects if athletes are able to interpret the situation as mainly challenging, which makes them cope positively with the sources of stress  and, as The results showed that the competitive level acted as a moderator, meaning that the partial mediation model presented some nuances based on athletes’ competitive level. Indeed, the U17 group, in comparison with the U19 group, assumed a more negative pattern of evaluating the competitive stressors by perceiving higher threat perception that decreased their perceptions of coping and control over the competitive stressors. The U19 group, in comparison with the U17, assumed a higher perception of competitive stressors that decreased both mechanisms of secondary cognitive appraisal; however, the U19 group seemed to mobilize a more challenging perception of competitive stressors that increased both the coping and control perceptions. In other words, the U17 seemed to evaluate the competitive stressors more threatfully, and the U19 seemed more aware of competitive stressors but evaluated the competitive stressors in a more challenging way (as expected). The increase of competitive stressors perception by U19 athletes can be related to an augment of competitive difficulty (which we could expect because they were competing at a higher competitive level), but they also seem to mobilize more challenge mechanisms. In contrast, the U17 athletes seem to be more preoccupied with negative aspects of competition which can deteriorate their mechanisms of coping and control. The role of competitive level in adaptation to stressors at younger ages is not easy to determine in literature. Previous studies provide evidence that the athletes’ age (and their respective competitive level in youth sports) are not related to psychological variables , while oOne limitation of this study is the cross-sectional design, which is an obstacle to inferring causality. However, it is essential to note that: (1) the proposed model has a strong theoretical basis, and (2) the use of a critical incident approach requires athletes to be questioned about a significant event at a very close time before the event. Indeed, athletes were questioned 48–24 h before the match, and (3) the importance of the event was ensured by using the final stages of the national championships, in which the teams’ ranking were still being decided. Nonetheless, it would be interesting to replicate the study with a longitudinal design to explore further the causal relationship between competitive stressors, cognitive appraisal, and emotional experiences. Also important, it would be useful to collect data besides self-reported measures from athletes by accumulating performance and skill execution indicators of athletes in competition and even in training sessions. The increase of time periods of evaluation aligned with a broader collecting of measures in distinct situations will provide a better understanding of how stressors, cognitive appraisal, and emotions interact to each other and explain how athletes adapt to sports demands.Regarding the antecedent factors, literature suggests that athletes’ characteristics  may influence the adaptation process e.g., . This stThe results have relevant implications for practice, particularly for sports psychologists. First, it highlights the importance of considering cognitive processes in stress adaptation, helping athletes generate challenging evaluations of the sporting events to better cope with them and experience more positive emotions. On the other hand, the study also emphasizes the need for stress management training because teaching athletes different strategies to cope with stressors may reduce their perceptions of threat when facing important stressful events. Specifically, goal-setting strategies can help athletes increase control over their performance (this was the major source of stress), and mental plans and imagery can help athletes deal better with competitive errors (the second major source of stress). Athletes can use these strategies before competitions by establishing specific and realistic goals and by defining positive thoughts to use when dealing with significant errors during competitions . BesidesConcluding, this study highlights the importance of considering how athletes perceive and cognitively evaluate competitive stressors to understand their emotional experience and how they adapt to a stressful event. Specifically, it showed that athletes who perceive competitive stressors as more challenging (and less threatening) assume more control over the demands and demonstrate to have more resources (coping perception) to deal with them, leading to more positive (and less negative) emotions. Moreover, it was also shown that these effects have stronger or weaker effects based on athletes’ competitive level.This study was conducted in the Psychology Research Centre (CIPsi/UM) of the School of Psychology, University of Minho and in the Research Centre for Human Development of the Faculty of Education and Psychology, Universidade Católica Portuguesa.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Ethics Committee, School of Psychology, University of Minho. Ethics approval reference: SECSH-0162015. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.ARG was responsible for conceptualization, methodology, resources, writing – review and editing, and supervision. CS was responsible for methodology, formal analysis, and writing – review and editing. CM helped with the formal analysis and was responsible for writing – original draft. RC was responsible for investigation and helped writing the original draft. All authors contributed to the article and approved the submitted version.


CLC, CCDC21, S100A13, and GCNT1) as putatively causal (p<0.05) regulators of IgE levels. GCNT1 —which is a top result in the MR analysis of expression in relation to asthma and allergic diseases—plays a role in regulating T helper type 1 cell homing, lymphocyte trafficking, and B cell differentiation. Our findings build upon prior knowledge of IgE regulation and provide a deeper understanding of underlying molecular mechanisms. The IgE-associated genes that we identified—particularly those implicated in MR analysis—can be explored as promising therapeutic targets for asthma and IgE-related diseases.Measurement of circulating immunoglobulin E (IgE) concentration is helpful for diagnosing and treating asthma and allergic diseases. Identifying gene expression signatures associated with IgE might elucidate novel pathways for IgE regulation. To this end, we performed a discovery transcriptome-wide association study to identify differentially expressed genes associated with circulating IgE levels in whole-blood derived RNA from 5,345 participants in the Framingham Heart Study across 17,873 mRNA gene-level transcripts. We identified 216 significant transcripts at a false discovery rate <0.05. We conducted replication using the meta-analysis of two independent external studies: the Childhood Asthma Management Program (n=610) and the Genetic Epidemiology of Asthma in Costa Rica Study (n=326); we then reversed the discovery and replication cohorts, which revealed 59 significant genes that replicated in both directions. Gene ontology analysis revealed that many of these genes were implicated in immune function pathways, including defense response, inflammatory response, and cytokine production. Mendelian randomization (MR) analysis revealed four genes ( Immunoglobulin E (IgE) is an antibody produced by B cells located in lymph nodes in response to antigenic stimuli and its production requires T helper type 2 (Th2) cells . Once reSTAT6, FCER1A, IL13, IL4/RAD50, and the major histocompatibility complex (MHC) loci that are associated with circulating IgE concentrations (Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) at the trations . Investitrations –11. Virktrations . To datea priori that IgE-associated transcriptomic changes impact IgE regulation, which in turn play a role in the pathology of IgE-related diseases, such as asthma and allergic diseases. First, we performed a discovery TWAS of IgE in 5345 Framingham Heart Study (FHS) participants. To validate our results, we conducted replication based on the meta-analysis of two independent external studies: the Childhood Asthma Management Program (CAMP) and the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS). We then reversed the discovery and replication sets. Second, we conducted Mendelian randomization (MR) to determine the direction of effect and infer causal relations between gene expression and circulating IgE levels. Two-sample MR analyses were then used to infer causal relations between IgE-related gene expression and IgE-related diseases, including asthma and allergy, by linking genetic variants associated with gene expression (i.e. cis-eQTLs) with GWAS of asthma and allergy, respectively  and Third Generation (Exam 1: 2002-2005) cohort participants. Total IgE measurements were performed using the Phadia Immunocap 100 system, in which an anti-IgE antibody is bound to a solid-phase carrier followed by fluoroenzyme-based quantitative measurement of total IgE with high precision and reproducibility .Gene expression was measured on FHS Offspring (Exam 8: 2005-2008) and Third Generation (Exam 2: 2008-2011) cohort participants. Whole blood samples (2.5 ml) were collected in PAXgene™ tubes . mRNA expression was profiled using the Affymetrix Human Exon 1.0 ST GeneChip  platform that includes 18,000 gene-level transcripts. The data normalization was described previously .lmekin package in R was used to analyze associations between gene expression  and serum total IgE concentration after adjusting for age, sex, smoking status , pack-years, technical covariates including batch effects   (FCER1A), rs1059513 (STAT6), rs1295686 (IL13), rs2523809 (HLA-G), rs2517754 (HLA-A), and rs2858331 (HLA-DQA2)  when the MR test for mRNA → IgE was significant (mRNA→IgEP < 0.05), and IgE → mRNA was not significant (IgE→mRNA ≥P 0.05).We used a two-stage least squares (2SLS) Mendelian randomization (MR) method to estimate the causal relationships between gene expression and IgE measured in 5345 FHS participants. Bi-directional MR analyses were performed to test if expression drives IgE concentration , using the top ble (IV) , or if Icis-eQTLs associated with gene transcripts associated with circulating IgE levels as instrumental variables, MR analyses were used to test if gene expression drives asthma/allergy .Two-sample MR was used to identify putatively causal mRNAs for both asthma and allergic diseases using the MRbase package in R. Estimated associations and effect sizes between SNPs and asthma and allergic diseases were based on UK Biobank GWAS of asthma and allergic diseases  phenotypes, respectively . Using cgsea-msigdb.org/gsea/msigdb/annotate.jsp), which determines whether an a priori defined gene set shows statistically significant, concordant differences between two biological states. Using an FDR q-value <0.05, we identified key biological pathways among the replicated genes associated with serum IgE concentration.Pathway analysis using Gene Ontology (GO) terms was conducted using the online Gene Set Enrichment Analysis tool  –20 and tth percentile were removed to select only the most informative probes . Principal components (PCs) of gene expression were generated using the “getPCAFunc” function from the R package “iCheck” (version 0.6).In both CAMP and GACRS whole-blood gene expression profiles were generated with probes from the Illumina HumanHT-12 v4 Expression BeadChip  that passed stringent and commonly used quality control (QC) metrics . we apple probes . A single probes . Express10transformed IgE concentration as a continuous variable, using the “glmwrapper” function from the iCheck package with adjustment for age, sex, and the first two principal components. The Benjamini-Hochberg method was specified to control the false discovery rate with the q-value set to 0.05. The final dataset in GACRS included 25060 gene probes that passed QC from 326 subjects with available data and suitable samples; in CAMP 24972 gene probes from 610 participants were available. All probes measured in CAMP were also measured in GACRS.In both CAMP and GACRS, independent generalized linear regression models were run to test the association between each gene probe and logThe results from CAMP and GACRS were meta-analyzed using the inverse normal method to combine p-values from the R package metaRNASeq . Analysep<2.80×10-6 . The top thirty genes associated with serum IgE concentration are presented in Clinical characteristics of FHS participants  and the replication cohorts  are presented in p<2.80×10-6). The attenuation of association is because eosinophil count was correlated with IgE level . Eosinophils drive IgE production and reflect the causal pathway of IgE production. Our findings indicate that the mechanisms by which genes influence IgE concentration—and presumably IgE-related diseases—are mediated by eosinophils; thus, adjusting for eosinophils may be an overadjustment. There was concordance of effect estimates (betas) for the IgE-gene expression results with versus without adjustment for eosinophils , as only 205 of the 216 significant genes in FHS were available for analysis in the replication cohorts. Forest plots of the top five genes in this replicated gene set are provided in Out of 216 unique transcripts at FDR<0.05 from discovery in FHS, 59 unique transcripts replicated in the meta-analyzed results from GACRS and CAMP Table 3.TRERF1 and ACOT11 were each linked to two separate transcripts). We defined replication as p<4.39×10-4 (0.05/114); all 114 significant transcripts from discovery in GACRS/CAMP replicated in FHS  is much larger than in GACRS and CAMP . The larger sample size provides greater power to identify significant results in FHS than in the other two cohorts at a given FDR threshold (216 vs. 135 significant transcripts at FDR<0.05).Gene ontology analysis was performed on the 59 genes that bi-directionally replicated between FHS and GACRS/CAMP. Multiple genes from this gene set were associated with pathways involved in inflammation and other immune system responses Table 4.p<5×10-8) from the updated IgE GWAS is reported in cis-eQTLs for the MR analysis. We conducted bi-directional MR to test causal relations between expression levels of the 185 genes and circulating IgE levels. We identified four genes—CLC, CCDC21, S100A13, and GCNT1—as putatively causal for IgE at mRNA→IgEP < 0.05 using the top cis-eQTL for each gene as an instrument variable (A Manhattan plot and a Q-Q plot (lambda 1.017) displaying the updated FHS IgE GWAS results are provided in IgE→mRNAP ≥ 0.05)   Table 6.GCNT1, a putatively causal gene for IgE concentration as implicated in our MR analysis of gene expression in relation to IgE levels  as nominally significant (mRNA→IgEP < 0.05) causal regulators of IgE concentration without reverse causal effect (IgE->mRNAP > 0.05), suggesting that individual gene transcripts that are associated with IgE concentration likely contribute causally to IgE regulation. Admittedly, the MR results should be interpreted with caution in the absence of functional validation. Among the four putatively causal genes is CLC , which is overexpressed in eosinophils that are stimulated following binding of IgE  transferase 1) , is necessary not only for the synthesis of P-selectin ligands in neutrophils and T helper 1 (Th1) cells but also for the homing of Th1 cells into sites of inflammation  . GCNT1 iammation . Additio-glycans , 29. TheGCNT1 deficient mice have neutrophilia and increased susceptibility to tuberculosis infection. The increased susceptibility of GCNT1 deficient mice to infection was largely driven by exacerbated neutrophil counts, which led to lung lesions, inflammation, and other pathologic features in the lungs of affected mice  that belongs to the centrosome-associated family of proteins. S100A13 is a calcium binding gene that encodes for a protein  belonging to the S100 family of proteins that are involved in a broad range of intracellular and extracellular functions. Extracellular S100 proteins often play crucial roles in regulating immune homeostasis and inflammation . This finding suggests that these eosinophil-linked genes may play a role in IgE production and IgE-related disorders such as asthma and allergy. After adjustment for eosinophil count, 12 genes remained significantly associated with IgE in the FHS cohort. Among the 12 genes, ANXA1, IL5RA, and CD200R1 were replicated in the GACRS/CAMP cohorts. IL5RA also tested causal for asthma by MR. Strong correlations of IL5RA with eosinophils were observed in previous studies , we reviewed published literature and transcriptomic resources to check their transcriptional and translational (protein) properties in mucosal tissue. We found that CLC and S100A13 were among the top genes showing differential expression in airway epithelium in asthma , accession number phs000007.The data presented in the study are deposited in the dbGaP repository (The studies involving human participants were reviewed and approved by Institutional Review Board at Boston University Medical Center, Boston, MA. The patients/participants provided their written informed consent to participate in this study.KR and TH wrote the manuscript. TH, S-JH, RK, and JL-S conducted the majority of analyses. All authors contributed to the article and approved the submitted version.


Ice cores and offshore sedimentary records demonstrate enhanced ice loss along Antarctic coastal margins during millennial-scale warm intervals within the last glacial termination. However, the distal location and short temporal coverage of these records leads to uncertainty in both the spatial footprint of ice loss, and whether millennial-scale ice response occurs outside of glacial terminations. Here we present a >100kyr archive of periodic transitions in subglacial precipitate mineralogy that are synchronous with Late Pleistocene millennial-scale climate cycles. Geochemical and geochronologic data provide evidence for opal formation during cold periods via cryoconcentration of subglacial brine, and calcite formation during warm periods through the addition of subglacial meltwater originating from the ice sheet interior. These freeze-flush cycles represent cyclic changes in subglacial hydrologic-connectivity driven by ice sheet velocity fluctuations. Our findings imply that oscillating Southern Ocean temperatures drive a dynamic response in the Antarctic ice sheet on millennial timescales, regardless of the background climate state. Piccione et al find evidence for Antarctic ice sheet instability driven by millennial cycles in Southern Ocean temperature, providing clues for the mechanisms that link climate change and rapid Antarctic ice loss events. Modern observations3 of retreating ice near marine-terminating ice sheet margins demonstrate the potential for rapid AIS mass fluctuations brought on by changing Southern Ocean temperature4 . The key link between this ocean-thermal forcing and ice sheet mass lies in the delivery of heat to the ice sheet margins, which affect ice shelves and grounding lines. Ice sheet stability is regulated by ice shelves5 and grounding line positions6, which are vulnerable to thinning and retreat when contacted by warm ocean waters. Ice sheet models suggest that ice shelf decay can result in enhanced flow of grounded ice up to 1000 km upstream of the grounding lines of large outlet glaciers and ice streams7. On millennial timescales this feedback could cause substantial velocity changes in these fast-flowing ice drainage pathways8, ultimately affecting continent-wide ice sheet mass balance9.One of the persistent challenges involved in both reconstructions and projections of global mean sea level is determining what sectors of the Antarctic Ice Sheet (AIS) are vulnerable to significant retreat, the timescales of such retreat, and the conditions that trigger ice loss events10 the mean state ocean circulation responsible for cross-equatorial heat transport from the Southern Hemisphere to the Northern Hemisphere. Changes to the intensity of AMOC result in out-of-phase polar temperature cycles11 recorded by isotopic climate proxies in ice cores, identified as Dansgaard-Oeschger cycles in the Greenland ice core records and Antarctic Isotope Maxima (AIM) events in Antarctic ice core records. This oceanic teleconnection, called the bipolar seesaw, also affects atmospheric circulation by regulating the temperature gradient between the middle and high latitudes12, which shifts the intertropical convergence zone north when AMOC rate is high (Northern Hemisphere/Southern Hemisphere warm/cold periods) and south when AMOC rate is decreased (Northern Hemisphere/ Southern Hemisphere cold/warm periods)13. As the intertropical convergence zone migrates southwards during AIM events, Southern Hemisphere westerly winds experience parallel latitudinal shifts and strengthening14, causing upwelling of relatively warm circumpolar deep waters onto the Antarctic continental shelf15. Antarctic marginal ice is affected by these upwelling cycles, which deliver circumpolar deep waters to the base of ice shelves and grounding lines, triggering enhanced basal melting and retreat during Southern Hemisphere millennial warm periods4.Millennial-scale Southern Ocean temperature oscillations are driven by a feedback between ocean-atmosphere teleconnections that is modulated by Atlantic Meridional Overturn Circulation (AMOC):9 and modern observations3 indicate that the AIS is susceptible to ice loss through ocean-thermal forcing, regional differences in ice bed topography, drainage geometry, and ice thickness16 in peripheral sectors of Antarctica may lead to geographic differences in grounding line vulnerability, adding spatiotemporal complexity to ice sheet response. Millennial-scale climate oscillations also vary in intensity depending on the background climate state, where large continental ice sheets during glacial periods17 and enhanced atmospheric CO2 concentrations during full interglacial conditions19 dampen the amplitude of millennial-scale climate variability. In contrast, intermediate climate states are characterized by more frequent, larger magnitude changes in polar temperature20. Therefore, geologic evidence of AIS evolution across a wide geographic range and diverse climate states is necessary to support simulations of suborbital changes in ice mass. However, existing geologic records documenting millennial-scale AIS mass loss23 are limited to bipolar-seesaw events during the last two glacial terminations, are constrained by low-resolution age models, and are restricted spatially to the Weddell Sea Embayment and offshore sediments. This leaves the regional extent and magnitude of AIS response to suborbital climate change unconstrained.Although ice sheet modelsHere, we present observations from an archive of subglacial hydrologic evolution recorded by chemical precipitates that formed >900 km apart beneath the East Antarctic Ice Sheet (EAIS), over a combined >100 kyr period during the Late Pleistocene. This dataset provides a sequence of high-resolution U-series age constraints of ice sheet evolution in response to millennial-scale climate change. Mineralogic and geochemical variations in subglacial precipitates provide evidence for periodic changes in subglacial hydrologic connectivity between the AIS interior and margin that occur contemporaneously with bipolar seesaw-related Southern Hemisphere climate cycles. Combining precipitate data with a reduced-complexity model of ice sheet thermodynamics, we demonstrate a link between subglacial hydrologic conditions and millennial-scale changes in ice sheet velocity.24, The moraine is located ca. 20 km downstream of the polar plateau, with debris derived locally from Beacon Supergroup and the Ferrar Group25. Sample PRR50489 was found at Elephant Moraine , a supraglacial moraine in a blue ice area of Transantarctic Mountains, where ~100 ka of ice sublimation has released debris from basal ice of the East Antarctic ice sheet27, which also consists predominantly of rocks from Beacon and Ferrar28. Precipitates form in subglacial water, and are transported to the ice surface within upward-flowing sections of glacier ice before being exposed on the surface as the surrounding ice sublimates25. The exhumation of precipitates within basal ice sections makes it difficult to precisely locate their formation site. However, constraints on ice velocities and sublimation rates can be used to place their most likely formation area within ca. 10 km of where they were collected. For example, the length of time for the emergence of basal debris to MAM is estimated to be at least 35 ka25. Considering the youngest radiometric U-series age obtained for sample MA113 (25.44 ka), there was little time for the precipitate to travel over horizontal distances, supporting a formation area proximal to the MAM. A similar emergence time of ca. 40–50 ka can be estimated for PRR50489, but a greater minimum formation time (147 Ka) allows the possibility of a longer horizontal distance traveled. However, if we assume a basal transport velocity scaled similarly to other EAIS basal ice24, PRR50489 could have traveled only 10 km of horizontal distance in 100 kyr. Hence, we infer that both samples MA113 and PRR50489 likely formed in basal overdeepenings found within several kilometers upstream of EM and MAM16, which offer suitable settings for precipitate formation because they would allow subglacial water bodies to persist over long time periods  Fig. . Sample 30 and beneath the Laurentide ice sheet31, PRR50489 and MA113 do not display characteristics indicative of formation by regelation or in a basal film, and instead require cm-scale or deeper subglacial cavities that remain open on >10 kyr timescales. Textures within each of these samples indicate that opal and calcite form via two different mechanisms. Calcite layers nucleate on the substrate and form acicular  and oxygen (δ18OVSMOW) isotopic compositions of opal and calcite-forming waters are distinct for both PRR50489  are similar to the δ18O of ice proximal to the region where samples were exhumed36, suggesting that these waters originate as basal meltwater formed closer to the ice sheet margin. Another distinguishing characteristic of opal and calcite-forming waters are their cerium anomalies (Ce*), a proxy for redox conditions37   from both samples are 13C-depleted (−23‰ for PRR50489 and −18‰ for MA113) suggesting that carbon is sourced from similarly 13C-depleted subglacial organic matter (~−26‰ in PRR50489) that is oxidized during microbial respiration. Similarly 13C-depleted carbon is observed in other EAIS basal aqueous systems39. For water closed off from the atmosphere, microbial respiration can function as the only significant source of CO2. This CO2 undergoes hydrolysis to H2CO3 and is utilized in the chemical weathering of the substrate. In an area with bedrock dominated by silicate materials, most or all of the HCO3− in the system will result from silicate weathering reactions, which would result in δ13C of dissolved inorganic carbon within 3‰ of δ13C of the source carbon41. The ~5‰ offset between δ13CCaCO3 of PRR50489 and MA113 can be caused either by a slightly different organic source or contact with bedrock that contains carbonate.To understand the link between ocean-atmosphere-cryosphere teleconnections and the mineralogy of subglacial precipitates, we first utilize geochemical and isotopic measurements to characterize the precipitate source fluids. The carbon  Figs. . In mostals Fig. . The car13C and δ18O compositional space that suggest mixing between two isotopically distinct fluids with different solute concentrations : a composition comparable to that of sub-AIS brines42. Similar mixing relationships are observed between the 87Sr/86Sr and δ18O composition of opals and calcite 44. In addition to the aforementioned similarities between the opal endmember and MDV brines, δ234Uo and bulk rare earth element compositions of MDV brines45 . Monomineralic opal layers represent periods of amorphous Si saturation, which can occur in subglacial environments through cryoconcentration50. Supplementary Fig. 2 brine, where, unlike the result predicted from any other surface waters, the deficiency of carbon in the brine precludes calcite precipitation. Since geochemical data suggest calcite precipitation from an oxidized, carbon-rich, and isotopically distinct glacial meltwater, we explore conditions under which calcite saturates upon mixing of EAIS basal meltwater with CaCl2 brine. Mixing the Casey Station jökulhlaup water with opal-forming brines, we identify a strong supersaturation in calcite over a broad range of mixing proportions  is overcome by an increase in the dynamic ice thinning associated with grounding line retreat in response to Southern Ocean warming. The dynamic effect driving ice sheet evolution in response to ocean-thermal forcing on grounding lines is incorporated into our simplified model of shear heating through the ice surface slope, which steepens when the ice in the Ross Embayment thins during grounding line retreat (AIM warm phases) and becomes shallower when ice sheet thickness in the Ross Embayment increases during grounding line advances . Our model framework assumes that ice thickness at the foothills of the TAM, which is by itself driven by the position of the grounding line in the Ross Embayment, is a linear function of the isotopic records of climate from either WDC (MA113) or EDC (PRR50489) ice cores  between millennial climate cycles and ice sheet thickness changes.To produce basal freeze-melt cycles that are temporally correlated with precipitate opal-calcite transitions Figs. , 3e, the65. Although many unconstrained physical parameters of the ice sheet system make direct quantification of climate thresholds beyond the scope of this manuscript, we can compare opal-calcite timeseries data with ice core records to place approximate bounds on the climate state required to elicit a millennial-scale ice sheet response. Our RCMIST simulations describe a minimum ice sheet thickness change –which corresponds with a value in ice core isotopic records needed to generate a millennial-scale subglacial hydrologic response  were measured by UCSC Stable Isotope Laboratory using a Themo Scientific Kiel IV carbonate device and MAT 253 isotope ratio mass spectrometer. Referencing δ13CCO3 and δ18OCO3 to Vienna PeeDee Belemnite (VPDB) is calculated by two-point correction to externally calibrated Carrara Marble ‘CM12’ and carbonatite NBS-1874. Externally calibrated coral “Atlantis II”75 was measured for independent quality control. Typical reproducibility of replicates was significantly better than 0.05‰ for δ13CCO3 and 0.1‰ for δ18OCO3.Carbonate isotope ratios (δ13Corg), inorganic carbon (IC) was extracted with 1 M buffered acetic acid (pH 4.5), followed by repeated water rinses to completely remove the buffered acetic acid and residual cations from the sample IC. These IC-extracted sample residues were then freeze-dried, weighed, encapsulated in tin, and analyzed for carbon (C) stable isotope ratios and concentrations by the University of California Santa Cruz Stable Isotope Laboratory using a CE Instruments NC2500 elemental analyzer coupled to a ThermoScientific DELTAplus XP isotope ratio mass spectrometer via a ThermoScientific Conflo III. Measurements are corrected to VPDB for δ13C. Measurements are corrected for size effects, blank-mixing effects, and drift effects. Typical reproducibility is significantly better than 0.1‰ for δ13Corg.To measure organic carbon isotope ratios 79. Briefly, 2–3 mg opal samples were loaded into nickel reaction tubes and heated for 2 h at 250 °C at high vacuum. Samples were then repeatedly pre-fluorinated at room temperature with 30 mbar aliquots of BrF5 until <1 mbar of non-condensable gas was present. A 30× stoichiometric excess of BrF5 was added to the nickel tubes and sealed. The nickel tubes were then heated at 600 °C for 16 h to quantitatively produce O2. The generated O2 gas is then sequentially released into the cleanup line, cryogenically cleaned and frozen onto a 5 Å mole sieve trap immersed in liquid nitrogen, equilibrated at room temperature with the IRMS dual-inlet sample-side bellows and measured for δ18O against a reference tank of known δ18O composition (24.3‰). Opal δ18O is reported based on daily corrections made to four primary silicate standards , spanning ~13‰, and have been recently calibrated to the VSMOW2-SLAP2 scale80. Three secondary standards , UCD-DFS .Opal layers were analyzed at the Stanford University Stable Isotope Biogeochemistry Laboratory for δ88Sr is measured on the Axial Faraday cup, while 87Sr86,Sr85,Rb, and 84Sr are measured on the low cups. Accuracy of the 87Sr/86Sr measurements is evaluated using Sr standard SRM987 compared to a long-term laboratory average value of 0.71024, with a typical reproducibility of ±0.00004.Sr isotopic measurements were made at the UCSC Keck Isotope Laboratory. Sr compositions are measured on a TIMS in a one sequence static measurement: 83; element concentrations were processed with the trace-element data reduction schemes (DRS) in semiquantitative mode, which subtracts baselines and corrects for drift in signal.Laser ablation inductively coupled plasma–mass spectrometry (LA ICP-MS) analyses were conducted at the Facility for Isotope Research and Student Training (FIRST) at Stony Brook University. Analyses were made using a 213 UV New Wave laser system coupled to an Agilent 7500cx quadrupole ICP-MS. The National Institute of Standards and Technology (NIST) 612 standard was used for approximate element concentrations using signal intensity ratios. Laser data were reduced in iolite49. The high ion concentrations of subglacial fluids necessitates the use of the Pitzer specific ion interaction approach, which allows PHREEQC to model the aqueous speciation and the mineral saturation index of brines, and has been shown to yield results44 consistent with the subzero database FREZCHEM84. Our modeling approach to simulating opal-calcite transitions can be describe in three parts: (1) Identify the water composition and conditions under which opal will precipitate and calcite will not; (2) Identify the composition and volume of water required to mix with opal-forming fluids to produce calcite; (3) Utilize the δ18O and δ13C isotopic composition of calcite and opal, along with the known or inferred composition of mixing waters  as shallow subsurface waters95, deep groundwaters96, and surface waters99, most notably feeding Lake Vanda100 and Don Juan Pond(DJP)102. Ca-Cl-rich brines also occupy regions that were previously covered by the North American89 and Fennoscandian ice sheet103, implying that they are a natural product of fluid isolation beneath ice sheets. Therefore, CaCl2 brines are a plausible composition for brine beneath the EAIS. The most geochemically well characterized MDV brines are those that feed DJP, therefore, we explore opal precipitation by equilibrating DJP brine with ice, calcite, and opal at a range of temperatures between −5 and 5 °C. At full concentration, DJP brine causes melting of the overlying ice due to its exceptionally high ionic strength, resulting in significant dilution of the original solution, which inhibits opal precipitation  derived from a reservoir with an 87Sr/86Sr of 0.71. These data are consistent with a brine that weathers silicate minerals over long periods, and a meltwater that drives silicate weathering with a very different provenance over a relatively short time duration. The δ13C of the calcite (−23‰) . Results show that without at least 30% meltwater the mixture too diluted with respect to Ca and HCO3− to precipitate calcite. PHREEQC mixing models successfully produced discrete pulses of calcite with mixtures between 30 and 80% meltwater; conditions under which the admixture is undersaturated with respect to opal because the solution is too dilute with respect to Si and is supersaturated with respect to calcite leading to precipitation  Figs. , 5d alsoon of Sr % derived18O . As such, we calculate the formation waters composition as: α = /(1000 + δ18Owater).For both the calcite and opal oxygen isotope data, the formation water δ8O Figs. , 5 is ca13C vs. δ18O space, define a trend that suggests they form through admixture with an 13C- and 18O-depleted water. The carbon concentration dependent mixing curve that best fits that calcite data alone requires that the isotopically depleted endmember, what we’ll refer to here as the meltwater endmember carries a higher DIC than the isotopically heavier water, which we’ll now refer to as the brine endmember. In Fig. 18O composition of the brine endmember and that the δ13C composition matches marine carbon derived from the substrate (−0‰), the latter of which is recorded by sodic carbonates suspected of forming from brines in the Lewis Cliff area106. Under such assumptions the carbon ratio between meltwater and brine is 97:3 for PRR50489 . While feasible, this is a less appealing solution, as a δ13C of −15‰ does not match the composition of any specific carbon source and would require a mixture of waters. The data presented here suggests that over the ~100 ka of aggregate sample precipitation, there are two consistent endmember waters: an intermediate to reduced brine that is locally derived (star in second quadrant, Fig. Calcite data, in δ489 Fig.  and 80:2489 Fig. , a resulFurther information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


This paper aims to explore the response of a floating icesheet to a load moving in a curved path. We investigate the effect of turning on the wave patterns and strain distribution, and explore scenarios where turning increases the wave amplitude and strain in the ice, possibly leading to crack formation, fracturing and eventual ice failure. The mathematical model used here is the linearized system of differential equations introduced in Dinvay et al. . The equations are solved using the Fourier transform in space, and the Laplace transform in time. The model is tested against existing results for comparison, and several cases of load trajectories involving turning and decelerating are tested. Observations of such waves using satellite synthetic-aperture radar (SAR) imagery reveal ship-wave like patterns which compare favorably with results from earlier theoretical work4. In some cases, these ice roads are the only economical means of transportation to reach remote communities in the North. These routes are also of major importance for mining operations in several northern locations which depend on high-volume low-cost shipping of tools, equipment and lore.The study of hydro-elastic waves has a long history going back to the 1950’s and was prompted by attempts to systematically use solid ice covers as a means of mechanized transportation. In cold regions today, some winter truck routes are partially over ice-covered lakes, as this routing provides a low-cost alternative to building asphalt roads running along the lakeshores5.Authorities in the northern regions follow various plans for opening and closing ice roads, maintaining safety by checking ice thickness, temperature and consistency, weather conditions, and planning routes based on local conditions and operational experience. Maximal permitted loading is in many cases based on Gold’s formula which relates the thickness of the ice cover to the allowable load based largely on empirical observations of ice failure or non-failure under various loading conditionsIn the case of heavy moving loads, the speed of the load is also an important factor in maintaining safety of ice roads. Indeed, it is well known that large speeds can create resonant waves in the ice cover, and under certain conditions of speed, ice thickness, and water depth, the deflection under a vehicle traveling on a floating ice sheet may be amplified considerably. Under operational conditions, a speed limit of 15 mph (24 km/h) is often imposed, and an important component of ice road safety is proper instruction of truck operators.Exceeding the speed limit may lead to crack formation, and especially near the shore to so-called blowouts. Blowouts are usually caused by pressure buildup due to constructive interference of waves excited by heavy moving vehicles during shore approaches. Once a blow-out hole has formed, subsequent traffic must be rerouted.3, the importance of incorporating transients was already highlighted in7. Non-constant load speeds are included in a few studies12, and in particular it was shown that a decelerating load could lead to constructive interference of waves which could exceed the critical stress and thereby lead to crack formation12. While some studies examine non-homogeneous ice conditions14 and damping properties of the ice cover20 which can be a major factor in ice failure, the present study is focused on the effect of changes in speed and in particular changes in the direction of propagation of the moving load.While many early studies involving moving loads relied on constant load speedstraight path, such as shown in Fig. curved path on the waves created by the moving load. As already intimated above, curved vehicle trajectories are of interest because turning may sometimes be unavoidable due to routing problems, obstacles on the ice or localized ice failures. As will be shown in the body of this article, turning may also lead to constructive interference which may be more dangerous than slowing down.In the existing literature on theoretical modeling of hydroelastic waves induced by a moving load the focus has been exclusively on loads moving in a H, covered by a thin elastic solid of density 21. For the purpose of describing hydro-elastic waves, one may assume irrotational flow, so that the flow in the fluid foundation is described by a potential h of the elastic solid is small compared to both the depth and a typical wavelength. This simplification allows us to use a common coordinate system for the fluid and solid, and we specify that the fluid-solid interface is located at We consider an inviscid, incompressible fluid of density Using Hooke’s law together with the second Kirchhoff hypothesis , the boundary condition at the solid-fluid interface can be written in terms of the hydroelastic parameter g and the fluid density h, the Young modulus E and the Poisson ratio b in  denotes the pressure imposed by the load.In this equation, mentclass2pt{minimThe second term in Eq.  takes ac23. In terms of the interface deflection 8 based on the approach used in25. The first equation is a linearized version of the kinematic boundary condition. The operator 1/K is defined as the inverse ofIn virtually all cases where the ice can safely support a load, the deflection of the ice sheet is on the order of a few centimeters which is small compared to all other length scales in the problem. As a result, it is generally a good approximation to consider the linear wave dynamics given by the linearized form of the equations. A particularly useful version of the equations is written in terms of the so-called Dirichlet Neumann operator K and 26.It is shown in the Appendix, how the operators entclass1pt{minima of Eqs.  accurateThe system can be solved using the Laplace transform m is given by the inverse Laplace transform As is customary, an expression for m(t) is given in explicit form, the general solution can be written asIn some works, the load is assumed to be rectangular, but due to the inclusion of rotary inertia and the scale separation between the load and the wavelength of the excited waves, one my also consider a point load. In the present case, since the load is following a curved path, it is most expedient to use either a point load, or a symmetric Gaussian distribution which will be rotation-invariant under the change in orientation which occurs while turning. Assuming for the moment that we are dealing with a point load with mass For reasons that will be apparent later it is convenient to keep the solution as two separate integrals, but it can also be written in the tidy formThis integral can be solved analytically in some cases, but in general it has to be evaluated numerically. In the case of a Gaussian load distribution, the integrand will contain the term 27. In order to obtain the maximum strain, one may use the maximum eigenvalue of the Hessian matrix h/2 where we recall that h is the thickness of the ice sheet. Since the evaluation of the strain involves second derivatives, a point load will lead to singularities, so that it is best in this case to use a Gaussian weight distribution.Given a solution In order to compute the deflection of the ice sheet due to a moving load, the various integrals given above need to be evaluated. In addition, since the spatial operators are given in terms of Fourier multipliers, the FFT and inverse FFT are used. For this purpose, we define a discrete wavenumber vector While it is possible to use a point load without any problem, the computations are more stable (in particular when approximating the strain) so all results here are given for a load with a circular Gaussian weight distribution.The integration procedure is explained by looking at an example of a path with two parts. Consider a straight path parametrized by solution  into twoIf we define the integrals over Of course, depending on the situation, one may split the integral at any point along the path, and one could even define the solution at any time using an iterative process on discrete time steps. Another way to proceed is to also compute on Figs. , 4 and 527. In that work, the ice cover is fixed to vertical walls at the boundary, so that some deviation is to be expected. Nevertheless, comparing the results from the present study to the strain computed in27, one may conclude that the results line up quite well, at least for the central line First, in order to test our solution strategy and the numerical implementation, we compare the strain computed based on our solutions with the results obtained inh, fluid depth H, and flexural rigidity 29).In a situation with a given set of parameters, in particular ice thickness First, we display the “ship wave pattern” excited by a load moving in a straight path , resonances in the hydro-elastic system create waves propagating independently of the load. Especially in near-shore locations, these waves can create dangerous ice excursions as the waves may interact with the shoreline, and the reflections can interfere constructively with the still incoming waves. This may lead to so-called blowouts, often in the near-shore region. Due to blowouts and other obstacles, rerouting of traffic may become necessary. In what follows, we examine the safety of turning on the ice.If many inexperienced drivers such as tourists use the ice roads, it can have an impact on the overall safety of the roads. All ice roads require strict speed limits which range from 4 mph (6.5 km/h) on very shallow lakes to 15 mph (24 km/h) on most roads and up to 22 mph (35 km/h) on deep lakesWe consider an idealized case where a vehicle travels at a relatively high speed of 22 mph (35 km/h) a speed that might be considered safe on a deep lake. If the vehicle enters a shallower area either nearshore or due to a shoal in the lake, it might be in a position where the critical speed is much lower.2.If there is a blow-out region or an obstacle ahead, the vehicle will either have to slow down or turn in order to avoid the obstacle. Imagine that at 8.9 mph (14.4 km/h) the driver contemplates turning. Because of the decreasing depth, the critical speed is now only 7 mph (11.3 km/h), so the vehicle travels at supercritical speed. For the sake of being explicit, we look at the case of a 1000 kg vehicle on an ice cover of thickness From the plots shown in Fig. The subject of this paper has been the description of wave patterns induced by loads moving on ice sheets in curved paths. It was shown how the model (2)–(3) can be solved explicitly for a load traveling in a curved path. While the present work concentrated on point loads and Gaussian distributed loads, any other footprint and weight distribution of load can be handled by our approach. Loads moving in a straight path and in a circular path have been considered, but the method laid out here applies to an arbitrary curved load path.4, and slowing down followed by turning may in some cases be dangerous even in conditions which would be otherwise considered safe. Indeed it has been shown that changes in direction can have a significant effect on the strain in the ice induced by the waves excited by the moving load.It is well known that on ice roads, speed related blowouts may occur. Ice roads are particularly treacherous near the shore, as the critical speed is smaller due to smaller depth, and wave reflecting off the shore may combine with waves generated by a moving vehicle to crack the ice. Even for expert operators, keeping below the critical speed may be difficult at times, as the most important factor is the depth of the water beneath the ice. If conditions are right the critical speed can drop as low as 10 km/h


During medial opening wedge high tibial osteotomy (MOWHTO), sometimes the plate tends to be positioned anteromedially. The plate position can affect the length of the proximal screw, which significantly affects stability after osteotomy. Therefore, research on the correlation among plate position, screw length, and clinical outcomes is needed.This retrospective review examines 196 knees in 175 patients who underwent MOWHTO from May 2012 to December 2018, for symptomatic medial compartment osteoarthritis with a varus alignment of > 5°. We evaluated the anteroposterior plate position, length of proximal screw, and postoperative computed tomography (CT). We reviewed patients’ clinical outcome scores, presence of lateral hinge fracture, neurovascular complications, and infection. The correlation among proximal plate position, proximal screw length, and clinical outcomes was evaluated using Pearson’s correlation analysis. A subgroup analysis by screw angle (> 48 ° or < 48 °) was also performed using chi-square test and Student t-test.P < .001), as were screw angle and length . Medial plating (< 48°) can use a longer proximal screw; nevertheless, no significant difference occurred in clinical outcomes between the two groups. Also, no differences occurred in complication rate, including hinge fracture.The mean proximal plate position was 16.28%  of the proximal tibia’s anterior-to-posterior distance ratio, and the proximal screw length averaged 63.8 mm . Proximal posteromedial plate position and proximal screw length were significantly correlated (r2 = 0.667, With more medially positioned plating during MOWHTO, we can use longer proximal screws. However, there was no significant difference in clinical outcomes and the incidence of lateral hinge fractures regardless of plate position and screw length. High tibial osteotomy (HTO) is an effective surgical treatment option for mild-to-moderate medial compartment osteoarthritis (OA) of the knee and varus deformity , 2. The Early rehabilitation after MOWHTO has been encouraged to prevent deep vein thrombosis, recover range of motion (ROM), and prevent disuse osteoporosis which is associated with the patient’s rapid return to daily life –14. For Although some biomechanical studies and finite-element analyses were reported , there wHowever, there is no study on clinical outcomes according to the plate position using the same plate design and gap-filling methods. Therefore, the aim of this study was to evaluate the clinical outcomes correlated with plate position and screw length. If there is a strong relationship between the plate position and the length of the proximal screw, it can be used as a reference for determining the exact plate position during operation. We hypothesize that the medial positioned plate allows for longer proximal screws than the anteromedial plate, and it can lead to better clinical outcomes.This retrospective review included 266 knees in 231 patients who underwent MOWHTO from May 2012 to December 2018, for symptomatic medial compartment OA with varus alignment of > 5°. Inclusion criteria were as follows: (1) primary degenerative medial compartment OA (≦ Kellgren-Lawrence (K-L) grade 3) and (2) varus deformity of the lower extremity more than 5 degrees of hip-knee-ankle (HKA) angle. Exclusion criteria were as follows: (1) MOWHTO related to ligament reconstruction (9 knees), (2) revision MOWHTO (2 knees), (3) K-L grade IV with cartilage regeneration procedure (11 knees), (4) previous osteomyelitis history (1 knee), (5) No postoperative CT images (34 knees), (6) The follow-up period of < 2 years (13 knees) . For this retrospective study, informed consent was exempted by investigational review board of Samsung Medical Center.The surgical technique followed the procedure previously described by Kyung and Ryu et al. , 20. TwoThe patients were allowed to walk with crutches and toe-touch weight bearing on the operated limb immediately after the operation, and full ROM exercises began on postoperative Day 2. From postoperative Week 2, the patients were instructed to increase the amount of weight bearing on the operated limb gradually throughout the next 4 weeks , 23. ThePostoperative CT scans were achieved at 3 days after surgery. All CT data were acquired using the same CT scanner  slice thickness was 0.625 mm, and the collimation was 16 × 0.625 mm. Two trained orthopedic surgeons (DJR and SJP) evaluated the plate position in the proximal fragment and the screw angle in the axial CT views. We selected the axial cut where the three proximal screw heads and the plate junction were most visible. Proximal screw length was reviewed using the operative document. To estimate the proximal plate position and screw angle, we used the calculation method introduced by Lee et al.  To measure the proximal plate position, the axial CT image was represented as a percentile from 0 (anterior) to 100 (posterior). Fig. a A posteWe divided the patients into two groups for subgroup analysis according to screw angle based on previous studies , 18: theTo examine the clinical outcomes, we evaluated the mean Lysholm score, International Knee Documentation Committee (IKDC) subjective score, and Tegner activity score preoperatively and at the final 2-year follow-up. We also reviewed the medical record and postoperative CT and X-rays during the follow-up period to investigate lateral hinge fracture, neurovascular injury, and infection.Two independent trained orthopedic surgeons (DJR and SJP) measured the radiographic parameters at intervals of three weeks between the measurements. We used the intraclass correlation coefficient (ICC) to determine intra- and inter-observer reliability, considering ICC values of > 0.75 to be good . We usedP < .05 at a confidence interval of 95%. We used SPSS version 25.0  for the data analysis.To analyze the correlation among proximal plate position, proximal screw length, and clinical outcomes, we performed Pearson’s correlation analysis. In addition, we used a 2 × 2 chi-square test and Student t-test to evaluate the differences between the subgroups according to plate position  . We perfP < .001), as were screw angle and length .Detailed patient demographics are summarized in Table Clinical outcomes improved in all patients compared to preoperative measurements. The mean Lysholm, IKDC subjective, and Tegner activity scores were 46.4 ± 22.8, 37.3 ± 18.2, and 2.6 ± 1.5, respectively, preoperatively and were 73.3 ± 21.0, 61.2 ± 19.0, 3.7 ± 1.4, respectively, at final follow-up ; nevertheless, we found no significant differences in clinical outcomes between the groups Table . In addiThe most important finding of this study is that there were no differences in clinical outcomes, including clinical scores and lateral hinge fractures, regardless of plate position or proximal screw length. Therefore, our hypothesis was not validated.Previously, several biomechanical studies have been conducted examining the effect of plate position. Takeuchi et al.  performeHowever, clinical studies reported different results. Lee et al. have reported no significant clinical or radiological outcomes regardless of plate position and screw length . HoweverInserting the proximal screw in the direction of the lateral hinge can reduce the stress on this lateral hinge , 29, 30.However, it is not easy to fix the plate by contouring it towards the medial side of the proximal tibia. Because of the inherent mismatch between the proximal and distal centers in the osteotomized tibia, it was difficult to position the conventional T-shaped plate medially . Also, fOur study has several limitations. First, because of the retrospective design, the anatomical data of the patients who did not have a postoperative CT was unavailable; therefore, selection bias may have affected the results. Second, two senior surgeons performed the surgeries. Although both used the same surgical method, one of the senior authors used navigation, and the other performed the MOWHTO in a conventional way. Although there is not much effect on mechanical stability, there may be some effect on the clinical score . Third, With more medially positioned plating during MOWHTO, we can use longer proximal screws. The plate is likely positioned anteriorly when the proximal locking screw length is quite shorter than the pre-operative plan. In this case, we consider adjusting the plate position more medially. However, there was no significant difference in clinical outcomes and the incidence of lateral hinge fractures regardless of plate position and screw length.


Furthermore, control experiments with creatinine and gliadin failed to bind the immobilized papain, indicating the specific detection of Cystatin C.A carbon nanowire-modified surface with interdigitated electrode (IDE) sensing system was introduced to identify abdominal aortic aneurysm biomarker “papain,” also known as cysteine protease, used as the capture probe to identify Cystatin C. Papain was immobilized through the covalent integration of amine group on papain and the carboxyl group with carbon nanowire. This papain-modified electrode surface was utilized to detect the different concentrations of Cystatin C (100 pg/mL to 3.2 ng/mL). The interaction between papain and Cystatin C was monitored using a picoammeter, and the response curves were compared. With increasing Cystatin C concentrations, the total current levels were gradually increased with a linear range from 200 pg/mL to 3.2 ng/mL, and the current differences were plotted and the detection limit of Cystatin C was calculated as 200 pg/mL. The averaging of three independent experiments ( Abdominal aortic aneurysm (AAA) is a fatal arterial disease, defined by an abnormal bulge in the artery wall. AAA is generally developed by the weakened artery due to injury, infection, or congenital defect in the connective tissue of the artery , 2. VariCystatin C is the endogenous inhibitor of the elastolytic enzymes cathepsins, which are expressed ubiquitously in most of the tested cells. Research has found that the expression of Cystatin C is reduced in patients with atherosclerotic lesions and AAA. Furthermore, the Cystatin C level was significantly lower in AAA patients than in patients with non-AAA , 15, andBiosensors have been categorized by the type of transducer used, such as colorimetric, electrochemical, piezoelectric, and fluorescence biosensors –23. AmonThe electrode surface was obtained from Metrohm (Switzerland) for interdigitated electrode (IDE) analysis. Cystatin C, papain, N-hydroxysuccinimide (NHS), phosphate buffer saline (PBS), and ethyl-3-(3-dimethyl-aminopropyl) carbodiimide (EDC), potassium hydroxide (KOH), and serum albumin were ordered from Sigma Aldrich .The IDE surface was modified into a carbon nanowire for attaching the capture probe, papain. Initially, the electrode surface was cleaned with distilled water and then treated with diluted (1%) KOH for 7 min followed by washing with distilled water to eliminate the unbound KOH. After that, 1% of diluted APTES in ethanol was added on the surface and kept overnight. The next day, the APTES-coated electrode surface was cleaned with 30% of ethanol thoroughly to remove the unbound APTES. And then, 1 g of carbon nanowire was dispersed and dropped on the APTES-modified electrode and kept for 1 h and then washed with PBS buffer. Furthermore, the electrode surface was incubated in EDC and NHS mixture  for 1 h. Excess EDC-NHS was washed off with PBS, and then, 2 mg/mL of diluted papain was dropped and allowed to rest for 1 h to allow the papain binding on carbon nanowire. This papain modified electrode was utilized to quantify the Cystatin C level by using current-volt measurements.2 of diluted PBS for 30 min. And then, different concentrations of 100, 200, 400, 800, 1600, and 3200 pg/mL of Cystatin C were dropped individually on the papain-immobilized electrode surface and placed for 30 min. After washing the surface with PBS, the electric signal was measured. The response curves by current-volt measurements were recorded to monitor papain and Cystatin C interaction.Cystatin C was detected on the carbon nanowire-papain-modified IDE surface. To get the specific interaction of Cystatin C and papain, the uncovered activated carbon nanowire was covered with 1% PEG-NHControl experiments with creatinine and gliadin were conducted to identify the specific detection of Cystatin C on the papain modified electrode surface. For this experiment, control proteins at 3.2 ng/mL were added on a papain immobilized electrode and the electric signal was recorded. Furthermore, a control experiment was also conducted without papain. For this experiment, Cystatin C was placed on carbon nanowire (without papain) and then the current flow was recorded. The response cure was compared with the specific binding of Cystatin C with papain.2 and Cystatin C were recorded for comparison. All experimental conditions were at room temperature and with a wet sensing surface. Washings were performed between each surface modification or interaction. The current was given from 0–2 V at an interval of 0.1 V which was used in the whole experiment.Furthermore, to confirm the reproducibility of the papain-modified electrode, the same experiments were conducted with five different batches of electrodes and the current response for each immobilization; APTES, CNW, papain, PEG-NH2, was added on the papain modified electrode surface, and there were no significant changes in response. This might be due to the high occupancy of papain on the carbon nanowire surface  biomarker, “Cystatin C,” was detected on the carbon nanowire-modified electrode surface.  surface .R2 value of 0.9878  were conducted to identify the specific detection of Cystatin C on the papain-modified electrode surface. As in 2, and the cystatin C with different electrodes. This result confirms the reproducibility of the papain-modified electrode. This system is quite feasible with the same operating set-up for analysing clinically relevant real samples. With the similar sensing system on different modifications, the genuine detections have been demonstrated as the evidence using human serum [Furthermore, to confirm the reproducibility of the papain-modified electrode, the same experiments were conducted with five different batches of electrodes. As shown in an serum , 36, 37.Abdominal aortic aneurysm (AAA) is defined by an abnormal bulge in the artery wall and the burst with AAA cause excess bleeding, which is fatal. This research work designed a sensing system to detect AAA biomarker, “Cystatin C” with the cysteine protease, papain, by the current-volt measurements. To immobilize the papain, the carbon nanowire was attached on the electrode through amine modification, and then, papain was attached on through the covalent binding. Different cystatin C ranges were detected on the papain-modified electrode surface, and the limit of detection was found at 200 pg/mL. In addition, control proteins did not show any significant current increment, indicating the specific detection of Cystatin C. This study provides information for the identification of Cystatin C and generates the sensing platform with other clinical biomarkers.