N = 344) in the United States were randomly assigned to view one of four handwashing messages or a control message before completing self-report measures of attitudes, emotions, readiness to change, and behavioral intentions around handwashing. Simple handwashing messages were presented with different framings, including a simple exchange message, a gain message, a social norm appeal, and a guilt appeal. Results revealed that message type influenced handwashing behavioral intentions and emotions. Post-hoc comparisons revealed that the simple exchange message produced significantly higher intentions than other messages and that only the simple exchange message significantly differed from the control message on emotions regarding handwashing. Mediational analyses showed handwashing emotions fully mediated the relationship between messaging and handwashing intentions. This mediation effect was moderated by age, such that it occurred for the younger and middle age participants, but not older participants. These results suggest that even simple, brief, and easily conveyable messages can positively impact behavioral intentions around handwashing during the early stages of a health crisis. Consistent with recent research comparing affective and cognitive pathways for health behavior, the mediational analysis suggests that effect of the simple exchange message on intentions was due to increased positive emotions around handwashing.Handwashing has been widely recommended to reduce the spread of COVID-19. Despite this, handwashing behavior remains low in the general public. Social marketing has been employed as a successful health promotion strategy for changing many health behaviors in the past. The present study examines if message framing influences the effectiveness of a handwashing health promotion messages at the early stages of the COVID-19 pandemic. In a between-subjects cross-sectional experiment, participants ( The Novel Coronavirus 2019 (COVID-19) has undeniably affected life in the United States and around the world. The United States has suffered from increased unemployment, disruptions to educational and leisure activities, and economic struggles. The United States has disproportionately high rates of morbidity and mortality due to COVID-19; despite having only 4% of the world's population, as of July 2020 the United States is responsible for 25% of the world's COVID-19 cases ].The present study also utilizes the Transtheoretical Model (TTM) to examine handwashing behavioral intention. The TTM is a model that describes behavior as traveling through a series of stages—precontemplation, contemplation, preparation, action, maintenance, and termination –29. WhilFinally, due to extensive media coverage of age differences in the effects of COVID-19 age was considered as a possible moderating variable. Discussions around the greater danger of COVID-19 to older Americans may have resulted in the false belief that younger people do not need to increase behaviors like handwashing to the same extent of older people. Previous studies on beliefs about preventative pandemic behaviors demonstrate this; college-aged participants believed that children and the elderly were most vulnerable to disease, and that teens and young adults were less at risk for contracting a pandemic influenza . In the The present study compares four different social marketing messages for increasing handwashing attitudes, readiness to change, emotions, and behavioral intentions in order to better understand the most effective way to facilitate adherence to handwashing guidelines during the COVID-19 pandemic. Based on these social marketing principles, new messages were created for this study. Further, the study explores whether attitudes or emotions may serve as mediators of the effect of the messages on behavioral intentions and readiness to change. The study also examines the possibility that age moderates the effectiveness of the handwashing messages. Some variables included in this study, such as the demographic items, handwashing attitudes, emotions, intentions, and readiness to change, have been presented in a paper by Clemens et al. . The preThe present between-subjects cross-sectional design experiment utilized Qualtrics to randomly display a simple message manipulation in order to determine the effect of message type on measures capturing handwashing related attitudes, readiness to change, emotions, and behavioral intentions. All methods and measures were approved by the University of (name redacted for blind review) Social, Behavioral, and Educational institutional review board (IRB protocol number: 300597) and were conducted in compliance with the guidelines of the American Psychological Association.N = 344) were recruited via Prolific (an online participant recruitment system) until available budget was exhausted. All participants received monetary compensation for their time. Of these participants, 54.1% identified as women, 43.9% identified as men, and 1.5% identified as another gender or preferred not to disclose their gender. Participants ranged in age from 18 to 74 . Participants represented 44 of the 50 United States and were 68% White, 16% Asian/Asian-American, 5% Black, 5% Latinx, and 6% two or more races. For participant income level, 23.7% reported household income lower than $30,000, 37.5% reported between $30,000 and 69.999, 18.9% reported between $70,000 and 99,999, and 19.9% reported income of $100,000 or more. Participants were recruited via Prolific to represent, as closely as possible, the general population of the United States.Participants  simply read, “Press the arrow to continue.” The different messages can be viewed in n = 66), a social norms approach (n = 68), a simple exchange message (n = 65), and a guilt appeal (n = 70).Participants were randomly assigned to view one of five messages at the beginning of the study. Messages included either one of four handwashing message approaches described earlier: gain framing, social norm, guilt appeal, and exchange or a fifth control message. All five messages were shown with identical graphics. The control message (strongly agree to (7) strongly disagree. Items asked participants to rate the importance and effectiveness of handwashing in preventing COVID-19. Items used in this measure demonstrated acceptable internal consistency with a Spearman-Brown reliability coefficient of 0.78.Participants' attitudes toward handwashing were evaluated using a two-item measure. Items such as “handwashing is important” were scored on a seven-point Likert scale ranging from (1) strongly disagree to (7) strongly agree. This scale demonstrated strong internal consistency (α = 0.83).Handwashing emotions were measured using five items assessing discrete emotions related to handwashing. Scale items included emotions of both positive and negative valences, such as “I am proud of washing my hands” and “I would feel guilty if I did not wash my hands.” Items were scored using a seven-point Likert scale ranging from (1) never to (5) always. The scale demonstrated high internal consistency (α = 0.80).Handwashing intentions were measured using six items targeting intention to wash one's hands in scenarios recommended by the CDC and according to the guidelines they provided, such as “after blowing your nose, coughing or sneezing” and “for at least 20 seconds each time.” Items were reported on a five-point Likert scale ranging from (1) Participants' stage of change was determined using a single item modeled on the work of . Participost-hoc tests were conducted when tests violated the assumption of homogeneity of variance. The PROCESS macro for SPSS  = 4.38, p = 0.002, and emotions, Welch's F = 3.11, p = 0.017, but had no statistical impact on handwashing attitudes or readiness to change. As displayed in post-hoc comparisons revealed that the social exchange message produced significantly higher intentions than the control message, gain message, or guilt appeal, and was the only message type to change intention compared to the control message. Similarly, post-hoc comparisons revealed that only the exchange message significantly differed from the control message on emotions regarding handwashing .Preliminary analyses showed that standard ANOVA tests violated the assumption of homogeneity of variance. As such, Welch ANOVA, which does not assume equal variance, was employed. Significant omnibus tests were followed up with Games–Howell Mediational analyses  were theCritically, this mediation effect was moderated by age, such that it occurred for the younger [95% CI (−0.29 to −0.06]), and middle age participants [95% CI (−0.23 to −0.05)], but not older participants [95% CI (−0.15 to 0.02)]. That is, the conditional process analysis, indicated that the exchange message escalated feelings about handwashing which, in turn, increased handwashing intentions for younger and middle-aged adults. This model resulted in a significant index of moderated-mediation, 95% CI (0.01 to 0.13) . ExploraThis study demonstrates that the type of exchange theory-based social marketing message influences handwashing emotions and behavioral intentions, but does not significantly impact handwashing attitudes or readiness to change. Participants who were shown a simple exchange message, a message where a clear benefit and avoided consequence were given, were found to have more positive handwashing emotions and to have higher intentions to wash their hands than those shown other messages or a control message.This study also suggests different message types housed under the exchange theory can produce different results. The first objective of this study was to compare the ability of four different approaches (vs. a control condition) of presenting a simple handwashing message to change intentions and readiness to change. This aligns with findings from previous handwashing message studies, such as that by , which fThere are other possible reasons why the simple exchange message was found most influential. It is possible the spread of COVID-19 and the subsequent stay-at-home orders in the US created a natural experiment in which the exchange message was most effective. People were overwhelmingly at home, and the inconvenience and time spent washing hands may have been less of a barrier. Further, the social norms message might have resonated less because people were more separated from their social groups. The guilt appeal may have not been as effective because negative emotional appeals like guilt appeals can often have the opposite effect. Individuals instead ignore the message if it comes across as too powerful or too weak , 40. NegThe second objective of this study involved considering handwashing attitudes and emotions as statistical mediators of the relationship between message reception and handwashing intentions. Thus, the mechanisms by which messaging impacted behavioral intentions were explored. Handwashing emotions, but not attitudes, were found to be a significant mediator of the relationship. This finding is consistent with research comparing affective and cognitive pathways for health behavior, in that the mediation analysis suggests that effect of the exchange message on intentions was due to increased positive emotions around handwashing . The medLastly, as one of the objectives for this study, age was included in the mediational model as a possible moderator. Results suggest that while the exchange message increased handwashing emotions, which then increased handwashing intentions, this only occurred for younger and middle-aged participants. Older adults were not significantly influenced by this message to emotions pathway, perhaps because older participants already reported higher intentions to wash their hands. This finding suggests that social exchange messages for increasing handwashing will be most effective for individuals, such as younger and middle age individuals, with lower initial intentions to wash their hands regularly.The present study may provide insights about handwashing intentions that could be used in various settings in the future; such insights could inform handwashing messages to address the seasonal flu, influence message types in businesses or restaurants. Future studies could also help inform best-practice approaches for large-scale handwashing interventions in the event of another pandemic. The results of the present study also suggest that a theory-based, social marketing approach could be utilized for a successful health messaging campaign.The authors must acknowledge potential limitations as well as the strengths described above. Participants were recruited through a third-party recruitment service and were not specifically selected to match the demographic breakdown of the population of the United States. As such, the generalizability to different racial/ethnic populations is reduced. Future studies should examine the effectiveness of these social marketing frames in diverse samples. Additionally, given the atmosphere surrounding COVID-19 in the United States when the questionnaire was administered, participants may have been more receptive to the messages because of saturation of handwashing messaging in all media. The study also utilized self-report measures of behavioral intentions and did not determine how message type translates into actual handwashing behavior. The authors acknowledge limitations exist due to the few constructs used to measure important outcomes; the instrument only contains two items for attitudes, and one item for the stages of change. Due to the rapidity needed to create the questionnaire at the beginning of the pandemic, the authors also acknowledge it was not pre-tested. The present study may be influenced by the specific recruitment procedures involved in data collection, such as use of an online survey instrument, incentives, and self-reported measures. However, this approach was beneficial for obtaining timely data from a national sample on this critical issue during a pandemic, when face-to-face research was restricted. The authors also acknowledge that the messages shown to participants in the online questionnaire are only a few possible framings. It is unknown how different framings might compare to the messages shown in this study. Further exploration is warranted to understand how message framing like loss framing and fear appeals may be viewed by individuals during a pandemic. Additional studies may also benefit from increased sample sizes to improve generalizability.These findings have implications for health messaging during public health emergencies. These results suggest that even simple, brief, and easily conveyable messages are able to positively impact behavioral intentions around handwashing during the early stages of a health crisis. Simple exchange messages may be particularly useful in increasing handwashing intentions for individuals with previously low intentions because of their ability to increase emotions toward the behavior. This also suggests that these types of messages may be successful in delivering social marketing messages about handwashing when there is already high awareness in the United States, as they do not rely on changing attitudes or other cognitive variables. Further, based on the mediational analyses, it appears that health messages designed to increase handwashing would benefit by directly targeting emotions.This study has several strengths that make it an important addition to the scientific community. The authors are unaware of any scientific literature that specifically examine social marketing frames and handwashing messages in the context of COVID-19. This is also the only study the authors are aware of that examines handwashing messages using the Transtheoretical Model during the context of a pandemic. Finally, these data also add to the literature by showing that emotions, but not attitudes, statistically mediate the effect of social exchange messages on handwashing intentions.https://osf.io/835p7/?view_only=6370596c6787415db68e27a4e81816ab.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: The studies involving human participants were reviewed and approved by University of Toledo Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.JM was involved in the original design concept of the study, development of handwashing messages, data cleaning, and questionnaire design. KC was involved in the original design and formal data analysis of the study, and developed tables for the manuscript. KF was involved in the original design concept, questionnaire design, and supervision of the study. AG was involved in original design, study supervision, and data analysis. All authors participated in full review and editing of the final manuscript.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.


To study CSF biomarkers of Alzheimer disease (AD) analyzed by fully automated Elecsys immunoassays compared to neuropathologic gold standards and to compare their accuracy to plasma phosphorylated tau (p-tau181) measured with a novel single molecule array method.We studied antemortem Elecsys-derived CSF biomarkers in 45 individuals who underwent standardized postmortem assessments of AD and non-AD neuropathologic changes at autopsy. In a subset of 26 participants, we also analyzed antemortem levels of plasma p-tau181 and neurofilament light (NfL). Reference biomarker values were obtained from 146 amyloid-PET–negative healthy controls (HC).1-42 (Aβ1-42) also accurately distinguished pathology-confirmed AD from non-AD dementia . In pathology-specific analyses, intermediate to high Thal amyloid phases were best detected by CSF Aβ1-42 , while intermediate to high scores for Consortium to Establish a Registry for Alzheimer's Disease neuritic plaques and Braak tau stages were best detected by CSF p-tau181 . Optimal Elecsys biomarker cutoffs were derived at 1,097, 229, and 19 pg/mL for Aβ1-42, t-tau, and p-tau181. In the plasma subsample, both plasma p-tau181 (AUC 0.91 [0.86–0.96]) and NfL (AUC 0.93 [0.87–0.99]) accurately distinguished those with pathology-confirmed AD (n = 14) from HC. However, only p-tau181 distinguished AD from non-AD dementia cases  and showed a similar, although weaker, pathologic specificity for neuritic plaques (AUC 0.75 [0.52–0.98]) and Braak stage (AUC 0.71 [0.44–0.98]) as CSF p-tau181.All CSF biomarkers clearly distinguished pathology-confirmed AD dementia (n = 27) from HC (area under the curve [AUC] 0.86–1.00). CSF total tau (t-tau), p-tau181, and their ratios with β-amyloidElecsys-derived CSF biomarkers detect AD neuropathologic changes with very high discriminative accuracy in vivo. Preliminary findings support the use of plasma p-tau181 as an easily accessible and scalable biomarker of AD pathology.This study provides Class II evidence that fully automated CSF t-tau and p-tau181 measurements discriminate between autopsy-confirmed AD and other dementias. Yet, the international Alzheimer’s Association Quality Control Program for CSF and blood biomarkers has shown large variability (>15%) of the commonly used manual plate-based ELISAs for AD biomarker quantification in CSF across several laboratories.4 A major step toward widespread clinical use of CSF biomarkers has been the development of standardized measurements through fully automated platforms with high test-retest reliability (<5%) and low laboratory- and kit-associated variability such as the Roche Elecsys electrochemiluminescence immunoassays,5 which show excellent concordance with the manual ELISAs6 and have been well validated against Aβ PET.7-10The recent guidelines of the National Institute on Aging–Alzheimer’s Association (NIA-AA) Research Framework now define Alzheimer disease (AD) as a biological entity for which an in vivo diagnosis is no longer based solely on clinical diagnostic criteria but requires supporting evidence from PET or fluid biomarkers of AD-typical β-amyloid (Aβ) and tau pathology.11-15 and have been shown to distinguish between AD and other neurodegenerative disorders with high diagnostic accuracy comparable to that of CSF and PET-based measures of tau pathology.11-16The recent development of assays to measure phosphorylated tau in blood offers an alternative opportunity to assess AD pathology in a cost-effective, highly accessible, and scalable manner. Plasma concentrations of tau phosphorylated at threonine 181 (p-tau181) correlate highly with CSF measures of p-tau181 and with PET measures of Aβ and tau pathology17-21 or the novel plasma p-tau181 biomarkers22 against neuropathologic gold standards. Specifically, to date, no neuropathologic validation exists of the fully automated Elecsys-derived Aβ and tau biomarker measurements, and currently recommended cutoffs for these standardized measures are based on concordance studies with Aβ-PET or clinical criteria.7-23However, relatively few studies have thus far aimed to validate the established CSFIn this study, we examined antemortem Elecsys-derived CSF biomarkers in relation to AD neuropathology assessed at autopsy in the same individuals. In preliminary analyses on a smaller subset of participants, we also analyzed antemortem levels of plasma p-tau181 and neurofilament light (NfL). Specifically, we first studied the diagnostic accuracy of the fluid biomarkers for distinguishing pathology-confirmed AD dementia cases from Aβ-PET-negative healthy controls and dementia cases without AD pathology at autopsy. We then assessed the specific associations of the different Aβ and tau biomarkers with distinct aspects of AD neuropathology, including established neuropathologic rating scales for regional extension of Aβ pathology , cortical density of diffuse and neuritic Aβ plaques (Consortium to Establish a Registry for Alzheimer's Disease [CERAD] score), and regional extension of neurofibrillary tangle tau pathology (Braak stages). We derived pathology-specific biomarker cutoffs that best separated individuals with absent to low levels from those with intermediate to high levels of the respective AD neuropathologic correlate. Finally, we assessed the sensitivity of the biomarkers for the presence of common non-AD pathologies at autopsy, including cerebral amyloid angiopathy (CAA), Lewy body (LB) pathology, and limbic TAR DNA-binding protein 43 (TDP-43) pathology.Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The ADNI is a public-private partnership that was launched in 2003 with the primary goal of testing whether neuroimaging and other biological markers can be used to track disease progression in AD. The ADNI website provides up-to-date information.Data collection and sharing were approved by the Institutional Review Board of each institution participating in ADNI. All participants provided written informed consent in accordance with the Declaration of Helsinki and its later amendments.doi.org/10.5061/dryad.n2z34tmwr). Participants were recruited between 2005 and 2013 and were followed up to autopsy between 2008 and 2017. Thirty-five participants were diagnosed with AD dementia, 6 with mild cognitive impairment, and 4 as cognitively normal at their last clinical evaluation  according to standard diagnostic criteria used in the ADNI study. A subsample of 26 participants  also had available plasma measurements that were used for a head-to-head comparison of CSF and plasma biomarkers. Average time difference between CSF and plasma sampling was 1.2  years in this subsample.In the present study, we used data from the subsample of ADNI participants who had been followed up to autopsy for standardized neuropathologic examinations . From this ADNI autopsy cohort, we identified 45 participants who had available antemortem CSF measurements, with an average time difference between lumbar puncture and death of 2.9  years  at the central laboratory of the ADNI Neuropathology Core at the Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO (directed by Dr. John C. Morris), which provides uniform neuropathologic assessments of deceased ADNI participants.26 Following the NIA-AA guidelines, Thal phases (0–5) and Braak stages (0–6) were converted to A and B scores, so that all neuropathologic rating scales (A–D) are scored on a common semiquantitative 4-point scale from absent (0) to low (1), intermediate (2), and high (3). The A-B-C scores were further collapsed into a 4-point scale ADNC composite score according to NIA-AA neuropathologic criteria, in which scores ≥2 correspond to a pathologic diagnosis of AD.27 Thus, ADNC composite scores were used to classify patients with a clinical diagnosis of AD dementia (n = 35) into pathology-confirmed AD dementia  and non-AD dementia  groups. Primary neuropathologic diagnoses in the non-AD dementia group included LB disease (n = 4), hippocampal sclerosis (n = 2), argyrophylic grain disease (n = 1), and frontotemporal lobar degeneration with TDP-43 inclusions (n = 1). Although CERAD scores for density of diffuse plaques (D) are not used for calculating the ADNC composite score, they were included in pathology-specific analyses to allow assessment of biomarker-specific associations with neuritic vs diffuse Aβ plaques. Neuritic plaques are considered pathologically advanced forms of Aβ plaques and can be distinguished from diffuse plaques by the presence of dystrophic neurites, which typically also exhibit immunoreactivity for phosphorylated tau.28The principal neuropathologic outcome measures of the present study were focused on established rating scales for different aspects of AD neuropathologic change (ADNC), including Thal phases of regional distribution of Aβ plaques (A), Braak stages of tau neurofibrillary tangle pathology (B), and CERAD scores for density of neuritic (C) and diffuse (D) plaques.29 and assessment of TDP-43 pathology followed a regional evaluation of TDP-43–immunoreactive inclusions in the spinal cord, amygdala, hippocampus, entorhinal cortex/inferior temporal gyrus, and frontal neocortex.30 For the purpose of the present study, all neuropathologic assessment scales/scores of non-AD pathologies were dichotomized into 0 = absent and 1 = present categories.In addition to AD-specific neuropathology, we assessed common comorbid non-AD pathologies, including CAA, LB, and TDP-43 pathology. Presence of CAA was assessed in parenchymal and leptomeningeal vessels and scored on a semiquantitative 4-point scale based on global brain area involvement (absent to widespread). Evidence of LB pathology was assessed according to modified McKeith criteria,More detailed information on the implementation and operational definitions of the different neuropathologic rating scales is provided in the coding guidebook of the National Alzheimer Coordinating Center Neuropathology Data Form.1-42, total tau (t-tau), and p-tau181 with the fully automated Roche Elecsys electrochemiluminescence immunoassays on a cobas e601 instrument  according to the kit manufacturer's instructions. The lower and upper technical limits for the biomarkers are 200 to 1,700 pg/mL for Aβ1-42, 80 to 1,300 pg/mL for t-tau, and 8 to 120 pg/mL for p-tau181.Available antemortem CSF samples were analyzed for peptide levels of Aβ1-42 values beyond the upper technical limit, which are provided on the basis of an extrapolation of the calibration curve. However, note that the use of these values is restricted to exploratory research purposes, and they should not be used for clinical decision-making.In the present study, we also included Aβ31 and analyzed at the Clinical Neurochemistry Laboratory, University of Gothenburg, Mölndal, Sweden. Plasma p-tau181 concentration was measured with a novel assay developed in-house on a single molecule array HD-X  instrument, as described previously.14Blood samples were collected and processed according to the ADNI protocol32 Plasma NfL also was measured using the single molecule array platform as previously described.34For comparison, we also included plasma NfL as a biomarker for general neurodegeneration, which is not specific for AD pathology.U tests to study the difference in biomarker levels between patients with pathology-confirmed AD dementia (ADNC ≥2), Aβ-PET–negative control participants, and patients with a clinical diagnosis of AD dementia but without neuropathologic evidence of AD pathology . The accuracy with which the biomarkers could discriminate between these groups was tested using the area under the curve (AUC) in receiver operating characteristic (ROC) curve analysis, and optimal biomarker cutoffs for group separation were derived from the value that maximizes the Youden index (sensitivity + specificity − 1).In a first analysis, we used Mann-Whitney 3 these association analyses were carried out across pooled diagnostic groups to increase pathologic variance in the sample. Associations between fluid biomarkers and neuropathologic measures were examined with 2 complementary analyses. First, Spearman partial correlations, adjusted for the time interval between biomarker collection and death, were calculated for the association between each fluid biomarker and the different semiquantitative neuropathologic rating scales. Second, the ability of the biomarkers to detect intermediate to high degrees of the different ADNCs, as well as the presence of non-AD pathologies, was quantified with ROC curve analysis as described above. Similar to the ADNC composite score, the 4-point semiquantitative rating scales (A–D) were dichotomized into high and low categories for this analysis according to a distinction of intermediate/high (2/3) vs absent/low (0/1) degrees of pathology.In a second set of analyses, we studied pathology-specific associations of the different biomarkers with distinct aspects of ADNC. Given that biomarkers are supposed to reflect specific pathologic processes regardless of their potential clinical consequences,p < 0.05.All analyses were conducted separately for the full sample with available CSF data (n = 45) and the subsample of 26 participants who additionally had plasma measurements. Statistical significance threshold was set at Data used in this study have been made publicly available by the ADNI in the Laboratory of Neuro Imaging database.Demographic, clinical, and neuropathologic characteristics of the analyzed sample are summarized in p < 0.001).Overall, the different neuropathologic rating scales were highly interrelated, specifically A and D scores (Spearman ρ = 0.92) as well as B and C scores (ρ = 0.94), whereas the associations between these neuropathologic categories were weaker . About half of the sample (49%) had evidence of LB pathology, and 40% had evidence of TDP-43 pathology, but neither was associated with any AD neuropathology score .With regard to non-AD pathologies, 31% of all cases exhibited intermediate to high levels of CAA, which were associated with AD neuropathology scores, most notably A scores    and Aβ-PET–negative healthy controls  . Optimal7–0.96]) .p < 0.001, AUC 0.91 [0.86–0.96], optimal cutoff 19.5 pg/mL) and from non-AD dementia cases  but not from non-AD dementia cases .In the subsample with available blood plasma measurements, plasma p-tau181 levels showed a similarly pronounced group difference and high discriminative accuracy for distinguishing those with pathology-confirmed AD (n = 14) from Aβ-PET–negative controls (1-42 were strongest with diffuse plaque scores (D) and Thal phase (A), whereas those for t-tau and p-tau181 were strongest with neuritic plaques (C) and Braak stage (B). However, for all neuropathologic scores, the strongest correlations were observed for the t-tau/Aβ1-42 and p-tau181/Aβ1-42 ratios.The distribution of biomarker values across the different AD neuropathologic rating scales is displayed in 1-42 levels , yielding an optimal cutoff of 1,097 pg/mL for both analyses. High and low degrees of Braak stage (B) and neuritic plaque scores (C) were best differentiated by p-tau181 levels , yielding an optimal cutoff of 19.1 pg/mL for both analyses. The t-tau cutoff that best differentiated between high and low Braak stage (B) was 229 pg/mL, and the same optimal cutoff was found for neuritic plaques (C), although lower cutoffs of 221 and 210 pg/mL yielded identical Youden indices in this ROC analysis. For all neuropathologic rating scales, high and low degrees of pathology were best differentiated by the t-tau/Aβ1-42 and p-tau181/Aβ1-42 ratios (AUC 0.95–0.98), for which cutoffs of 0.27 for t-tau/Aβ1-42 and 0.016 for p-tau181/Aβ1-42 yielded the best separation for Thal phases (A) and diffuse plaques (D), whereas higher cutoffs of 0.42 for t-tau/Aβ1-42 and 0.041 for p-tau181/Aβ1-42 yielded the best separation for Braak stages (B) and neuritic plaques (C).Correspondingly, ROC analyses indicated relatively high accuracy for all individual Elecsys CSF biomarkers to differentiate between high and low degrees of the different ADNC scores . High an1-42 levels (AUC 0.84 [0.73–0.96]) and with the t-tau/Aβ1-42 (AUC 0.88 [0.77–0.98]) and p-tau181/Aβ1-42 (AUC 0.88 [0.78–0.98]) ratios, but not with t-tau or p-tau181 levels individually  and neuritic plaque scores (C) , with corresponding AUC values of 0.71 [0.44–0.98] and 0.75 [0.52–0.98] , respectively  .The primary objective of this study was to study the accuracy of antemortem Elecsys-derived CSF biomarkers to detect AD neuropathology as assessed by neuropathologic examination at autopsy. Our findings provide Class II evidence that the fully automated Elecsys-derived CSF t-tau and p-tau181 measurements, as well as their ratios with AβIn this study, we examined the association of Elecsys-derived CSF biomarkers for AD pathology and plasma measures of p-tau181 and NfL with neuropathologic changes at autopsy. Our findings demonstrate that Elecsys CSF biomarkers separated pathology-confirmed AD dementia cases from healthy controls and non-AD dementia cases with very high discriminative accuracy in vivo. In pathology-specific analyses, the individual Elecsys CSF Aβ and tau biomarkers showed strongest associations with the different AD neuropathologic measures that most closely reflect their pathologic target. Preliminary analysis of plasma p-tau181 in a smaller subset demonstrated comparable group separation accuracy and similar, albeit weaker, pathology-specific associations as CSF p-tau181. Taken together, our findings demonstrate the high neuropathologic validity and diagnostic accuracy of Elecsys CSF biomarkers and the potential of plasma p-tau181 as a cost-effective and scalable in vivo measure of AD pathology.5 However, validation studies for the fully automated Elecsys CSF assays have so far covered only the concordance with Aβ-PET measures or clinical diagnostic and prognostic variables,7-23 leaving the neuropathologic validity of these automated biomarker measurements unclear. Here, we provide evidence of the very high diagnostic performance of Elecsys CSF biomarkers for discriminating between individuals with pathology-confirmed AD dementia and healthy controls and those with non-AD dementia. Notably, the diagnostic accuracy of the Elecsys-derived biomarkers was similar to or even higher than previously reported results for nonautomated CSF assays , suggesting that this automatization did not result in lowered performance. Similar to previous findings on the diagnostic accuracy of individual CSF biomarkers, we found that CSF Aβ1-42 discriminated better between those with AD dementia and Aβ-PET–negative controls than CSF tau biomarkers,19 whereas CSF tau biomarkers discriminated better between AD and non-AD dementia cases than CSF Aβ1-42.36 The low CSF Aβ1-42 levels in the non-AD dementia group may partly be explained by comorbid Aβ pathology  but also may be affected by other pathologic or physiologic factors known to influence CSF Aβ1-42 levels.37 In both diagnostic contexts, the discriminative accuracy could be slightly improved with the use of the CSF tau-to-Aβ1-42 ratios.Fully automated CSF biomarker assays have recently been developed to satisfy the unmet need for laboratory- and batch-independent absolute CSF measures that will enable the use of universal biomarker cutoffs in both research and clinical settings.1-42 vs Thal phase and diffuse plaques, and CSF p-tau181 vs Braak stage and neuritic plaques). These results are congruent with results from a previous study examining pathology-specific associations of CSF biomarkers measured by standard nonautomated assays in which pathologic measures of Aβ load were best correlated with CSF Aβ1-42 levels and pathologic measures of neurofibrillary tangle load were best correlated with CSF p-tau181 levels.20 However, in that study, the best neuropathologic correlate of both CSF biomarkers was CERAD neuritic plaque density. It also must be noted that CSF t-tau levels may be influenced by neurodegenerative processes such as neuronal death and axonal loss,1-3 which have not been assessed in the present study. Overall, the performance measures  for the pathology-specific associations in that previous study were very similar to the ones observed here for the Elecsys CSF biomarkers, and the highest performance for pathology detection was also observed for the tau-to-Aβ1-42 ratios. Regarding non-ADNCs, we found that none of the Elecsys CSF biomarkers were associated with the presence of TDP-43 or LB pathology, but CSF Aβ1-42 levels were lower in cases with CAA. While this can be expected on the basis of the pathologic substrate of CAA and has been reported previously for a nonautomated CSF Aβ1-42 assay,18 the association between CSF Aβ1-42 levels and CAA pathology may also partly be explained by the high coprevalence of CAA and Aβ plaque pathology. Disentangling the Aβ pathology specificity of CSF Aβ1-42 levels would require larger and pathologically more heterogeneous study samples. Summarized, our results indicate high pathologic specificity of Elecsys CSF biomarkers for the different aspects of AD neuropathology and point to CAA as a potential confounder for the in vivo assessment of Aβ plaque pathology using CSF Aβ1-42 levels.Another key feature of our study was the evaluation of the relative sensitivity of Elecsys CSF biomarkers for different aspects of AD neuropathology. We found that although all Elecsys CSF biomarkers were strongly associated with the different ADNC scores, these associations were generally strongest between each biomarker and its respective target pathology . In comparison, optimal cutoffs for describing Aβ-PET positivity have been reported to range from 977 to 1,100 pg/mL for Aβ1-42, 213 to 242 pg/mL for t-tau, and 19 to 21 pg/mL for p-tau181.7-9 The strong agreement between our neuropathology analysis and these in vivo biomarker studies may be explained by the excellent accuracy of Aβ-PET for the detection of Aβ pathology,24 further supporting the generalizability of Elecsys CSF cutoffs across different research settings. ROC analyses for separating patients with pathology-confirmed AD dementia from Aβ-PET–negative healthy controls in our study yielded very similar t-tau (211 pg/mL) and p-tau181 (19 pg/mL) cutoffs compared to the pathology-specific cutoffs but indicated a considerably lower Aβ1-42 cutoff of 838 pg/mL (and thus higher cutoffs for the tau-to-Aβ1-42 ratios). This difference in the CSF Aβ1-42 cutoff can be expected because pathologic confirmation of AD requires the presence of both Aβ and tau pathologies and therefore implies more advanced disease stages that show lower average CSF Aβ1-42 levels.9While CSF biomarker estimates from different assays are largely in agreement and highly correlated,39 both plasma p-tau181 and NfL demonstrated high accuracy for separating those with pathology-confirmed AD from healthy controls, but only p-tau181 demonstrated high accuracy in separating pathology-confirmed AD cases from non-AD dementia cases. The direct head-to-head comparison with CSF in our current study further indicated that the diagnostic accuracy of plasma p-tau181 was comparable to that of CSF p-tau181 in this differential diagnosis context. We also extended the existing neuropathologic studies on plasma p-tau181 measurements22 by investigating the specific neuropathologic correlates of this biomarker. Our analysis indicated a pathologic specificity of plasma p-tau181 for Braak tau stage and neuritic plaque scores similar to that of CSF p-tau181, although these associations were notably weaker, suggesting superior performance of Elecsys CSF biomarkers in this context.In preliminary findings from a smaller subsample analysis, we further compared the performance of Elecsys CSF biomarkers in the assessment of AD neuropathology with that of a novel plasma p-tau181 biomarker and with that of plasma NfL as a non–disease-specific neural injury marker. In line with recent neuropathologic studies of plasma p-tau181 and NfL biomarkers,doi.org/10.5061/dryad.n2z34tmwr). In addition, individuals with low levels of ADNC and non-AD dementia cases were underrepresented in our study; the sensitivity of the examined CSF and plasma biomarkers for early ADNC and their utility for differential dementia diagnosis thus remain to be established in more diverse cohorts. Cutoffs derived from small-sample analyses should be interpreted with caution. However, we are encouraged by the similarity between our cutoff values and those derived from larger studies using Aβ-PET or clinical outcomes as validation standards. Unfortunately, the CSF Aβ1-42/Aβ1-40 ratio, which has been proposed to compensate for individual differences in physiologic Aβ production,37 could not be assessed in our study. Moreover, the combination of plasma p-tau181 and Aβ markers may increase the correspondence with neuropathologic measures similar to the CSF p-tau181/Aβ1-42 ratio,12 but no measures of plasma Aβ were available for this study sample.Our study does have limitations. First, although relatively large for a combined antemortem CSF and postmortem neuropathology examination, the sample size of our study was still limited, particularly for the head-to-head comparison between CSF and plasma biomarkers. Moreover, the ADNI cohort represents a rather selective research cohort that may not reflect the general population, and the focus on autopsied individuals in this cohort introduces an additional selection bias, which is reflected in an older age, higher prevalence of men, and higher prevalence of an AD dementia diagnosis in our study sample (see supplementary Figure S1; data available from Dryad: Our neuropathologic association study demonstrates high neuropathologic validity of Elecsys-derived CSF biomarkers of AD and further provides pathology-derived concentration cutoffs for this standardized analysis platform, which will support harmonization and interpretation of biomarker findings across different laboratories and clinical settings. In a smaller subset, our findings for plasma p-tau181 indicate similar, although weaker, pathology-specific associations with neuritic plaques and Braak tau stages as for CSF p-tau181. Its accuracy in discriminating between diagnostic groups adds strong support for the use of this easily accessible and scalable biomarker as a screening tool, particularly for the differential diagnosis of dementia. The performance of both Elecsys CSF and plasma p-tau181 measures as biomarkers of early-stage AD neuropathology remains to be investigated in larger and pathologically more diverse autopsy cohorts with available antemortem bodily fluid samples.


DCD heart transplant has not been routinely used. We describe a low-cost, reproducible method for DCD heart procurement using NRP allowing for distant procurement with cold static storage.See Commentary on page 116.Donation after circulatory death (DCD) has been used outside of the United States to expand the cardiac donor pool with good results. Currently, recovery methods include the use of the Organ Care System  or normothermic regional perfusion (NRP).The institutional review board or equivalent ethics committee at UW did not approve this study, as it falls outside the scope of necessary approval. Patient written consent for the publication of the study was not received, as this is retrospective analysis of deceased individuals.Donor selection and premortem management are outside the scope of this review. Depending on hospital policies, life-sustaining treatments are withdrawn from the donor in either the intensive care unit or the operating room. If the donor dies within 30 minutes from agonal (defined as oxygen saturation less than 70% and blood pressure less than 50 systolic) a mandatory hands-off period is undertaken to prevent autoresuscitation. The donor is declared dead by cardiorespiratory examination performed by a physician. The procurement may now begin.Our portable VA-ECMO NRP circuit consists of a Biomedicus 560 Centrifugal Pump (Medtronic), Affinity Fusion oxygenation system with cardiotomy venous reservoir (Medtronic), and Affinity CP centrifugal pump head (Medtronic). Two quarter-inch tubing lines are connected from the sterile field to the cardiotomy reservoir to serve as field suction. Field and venous drainage are augmented as needed using vacuum assist. The prime volume consists of 1 L of PlasmaLyte  with normothermia maintained using a Micro-Temp LT portable heater cooler  is introduced. Vacuum is then applied to the VA-ECMO NRP circuit to assist with cardiac decompression. A silk tie is passed around the insertion point of the cannula including atrial tissue for security and to prevent air locking.The heart is retracted left ward by the assistant and the aortic arch dissection is carried out sharply. Once the brachiocephalic vessels are identified, the innominate artery and left carotid artery are clamped with straight vascular clamps to exclude the cerebral circulation.Following this, the adventitia is cleared from the ascending aorta, and with an 11 blade knife a stab incision is made for the aortic cannula. A Medtronic 20Fr aortic cannula is then introduced and connected in a wet-to-wet fashion to the arterial limb of the VA-ECMO NRP circuit. Clamps are released and the donor is placed on NRP. PROLENE purse-string sutures (Ethicon) are then placed around the aortic and venous cannulae and secured with rummell tourniquet.Once the donor has been successfully placed on NRP support, flow is titrated to maintain a cardiac index of 2 or greater. A Bentley needle is inserted directly into the ascending aorta to function as a pressure measurement line and a delivery system for cold cardioplegia. The patient is then reintubated with low tidal volume ventilation to prevent elevating the pulmonary vascular resistance secondary to atelectatic lungs. Vasopressors are titrated for a mean arterial pressure goal of greater than 60 mm Hg and managed per the organ-procurement organization or anesthesia staff.We maintain NRP perfusion for 45 minutes. During this time, the chest and abdominal teams perform standard procurement dissection. After 45 minutes of support, the donor is weaned gradually off of NRP and the heart is visually assessed for function by a skilled attending cardiac surgeon . We remaProcurement of the heart and additional donor organs for transplantation is then undertaken in the standard fashion. The heart is evaluated and packaged on the back table and returned to the home institution via cold static storage.Since the inception of our DCD NRP program, we have procured and subsequently transplanted 10 hearts via the protocol described in this manuscript. There has only been one donor organ that was placed on NRP, observed for approximately 45 minutes, and was deemed unsuitable for full procurement and subsequent transplantation. During this procurement process, we kept the heart on NRP until the abdominal procurement team was ready to clamp and flush to continue to preserve the abdominal organs. We have not procured a heart using NRP onto an OCS; all of our transplants have been stored with cold static storage following recovery.A manuscript has been submitted regarding our initial outcomes using the aforementioned protocol and process. In short, the short-term outcomes have been found to be noninferior when compared with our institutional experience with brain dead donors as well as our experience in the TransMedics OCS consortium evaluating the outcomes of DCD hearts procured and maintained on OCS.The UW technique for DCD-NRP heart transplantation with cold static storage is portable, reproducible, and low-cost, allowing for expansion of DCD cardiac transplantation even at distant donor locations .Figure 2


Inflammatory changes are among the key markers of Alzheimer's disease (AD) related pathological changes. Pro-inflammatory analytes have been related to cognitive decline while others have been related to attenuating neuronal death. Among them, changes in cerebrospinal fluid (CSF) levels of soluble triggering receptor expressed on myeloid cells 2 (sTREM2) and soluble tumor necrosis factor receptor 2 (sTNFR2) have been described as impacting favorable clinical outcomes in AD. We therefore evaluate the effect of CSF sTREM2 and sTNFR2 when taken together on AD biomarkers and longitudinal clinical decline to understand their relative role on impacting AD clinical biomarkers and subsequent clinical outcomes. This longitudinal observational cohort study included 168 amyloid-positive (A+) and p-tau-positive (T+) participants with mild cognitive impairment (MCI) or AD dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with 109 of them having concomitant CSF sTREM2 and sTNFR2 data and 48 A+ T+ participants with MCI from a tertiary memory clinic cohort. An exploratory analysis was performed using data from 86 cognitively normal (CN) participants from ADNI with 72 of them having concomitant CSF AD biomarkers and CSF sTREM2 and sTNFR2 data. General linear models were used to evaluate the effect of sTREM2 and sTNFR2 levels on baseline CSF Aβ42, t-tau, and p-tau, and a linear mixed-effects model was used to assess longitudinal cognitive change after controlling for well-known covariates. Among ADNI A+ T+ MCI and AD dementia participants, CSF sTNFR2 had a stronger association, than CSF sTREM2, with CSF t-tau and p-tau. This was replicated among A+ T+ MCI participants from the memory clinic cohort. On the contrary, among A+ T+ CN participants, CSF sTREM2 explained significant variance in CSF t-tau and p-tau, while CSF sTNFR2 did not. When the effects of CSF sTNFR2 and t-tau on longitudinal cognitive change were taken into account, higher CSF sTREM2 predicted slower cognitive decline in A+ T+ AD dementia participants and faster decline in A+ T+ CN participants. Our results show that given the dynamic changes in sTREM2 and sTNFR2, the clinical impact of these distinct inflammation related biomarkers in tracking AD temporal progression across disease stages are likely to differ. TREM2) has been reported to increase the risk of AD development by 2–3-fold  have noted multiple susceptibility loci for late-onset AD related to the innate immune system  CSF levels also relate to favorable clinical outcomes in AD  research cohort to test whether CSF sTREM2 levels correlate with sTNFR2 among MCI and dementia subjects classified as AD, aggregated Aβ (A+) and aggregated tau (T+), according to the National Institute on Aging and Alzheimer's Association (NIA-AA) AT(N) framework . Briefly, eligible participants were aged 55–90 years, had an informant able to provide an independent evaluation of functioning, and spoke either English or Spanish. Participants had completed at least 6 years of education . For clinical staging, the categories of CN, MCI, and AD dementia were used  met the A+ T+ criteria at baseline and had data on CSF sTREM2 and CSF sTNFR2 . The CSF multiplex data used in this analysis were cleaned and quality controlled based on methodology described in the statistical analysis of the Biomarkers Consortium data primerhttps://ida.loni.usc.edu.The CSF sTREM2 assay used in ADNI is based on the Meso Scale Diagnostics platform and has been described previously   who were recruited from a specialized memory clinic at Cleveland Clinic . Recruitment details have been described previously  dispensed into 96-well plates for TaqMan  allelic discrimination detection of single nucleotide polymorphisms that discriminate the APOE alleles . Polymerase chain reaction (PCR) was performed using a 9700 Gene Amp PCR system  and an end-point read in a 7500 Real-Time PCR system (Applied Biosystems).In these participants, the diagnosis of MCI-AD was confirmed by the presence of CSF Aβ42 and p-tau levels consistent with a diagnosis of AD as the primary etiology; the diagnosis was also confirmed by two neurologists  using published criteria (A+ T+) . Again following the ATN criteria, amyloid deposition (A+) was defined as an abnormal value of CSF Aβ1–42, and tau pathology (T+) was defined as an abnormal value of CSF p-tau181  with concomitant data on CSF sTREM2 and CSF sTNFR were included in the exploratory analysis   and AD biomarkers   and 86 c n = 57) .P-values were calculated for sTREM2, sTNFR2, and AD biomarkers. All tests were two-tailed, with the significance level set at 0.05. Sensitivity analyses were completed to assess the robustness of the effects, and collinearity between sTNFR2 and sTREM2 was assessed for the dependent variables t-tau, p-tau, and Aβ42. IBM SPSS Statistics for Windows, version 22.0 , and R Core Team RStudio (version 1.2.5042) were used for all analyses.A log (base 2) transformation allowed Pearson correlations to be fit for exploratory univariate analyses for all analytes, and the levels described are therefore dimensionless. Normality of biomarkers was evaluated using Shapiro-Wilk tests and graphical methods. Pearson estimates of correlation and APOEε4 status. Effect size was calculated using partial η2. F-test for lack-of-fit and residual plots were used to assess the model linearity and fit.To evaluate the effect of sTREM2 and sTNFR2 individually, multivariate general linear models were used to assess the effect of baseline CSF sTREM2 or sTNFR2 on CSF t-tau, p-tau, and Aβ42 levels (dependent variable) after controlling for well-known covariates of age, sex, education years, and APOEε4 status. The interaction between CSF sTREM2 and sTNFR2 on the AD biomarkers was also assessed for significance. Effect size was calculated using partial η2. F-test for lack-of-fit and residual plots were used to assess the model linearity and fit.To evaluate the effect of sTREM2 and sTNFR2 together, multivariate general linear models were used to assess the effect of baseline CSF sTREM2 plus sTNFR2 on CSF t-tau, p-tau, and Aβ42 levels (dependent variable) after controlling for well-known covariates of age, sex, education years, and APOEε4 status, and CSF Aβ42 were controlled for in each analysis. In addition, 95% confidence intervals (CIs) and Benjamini-Hochberg adjusted false discovery rate (FDR) P-values were calculated. Higher order interactions between sTREM2 and sTNFR2 together on longitudinal clinical outcomes were not assessed given challenges in interpretation. A sensitivity analysis was next conducted with and without the covariates and using p-tau instead of t-tau (given the concern for collinearly with both CSF t-tau and p-tau in the model) to evaluate the reliability of these results. Additionally Model 3 (without sTNFR2) results were corroborated in a sensitivity analysis among a larger number of ADNI participants with sTREM2 data alone . Covariates of age, sex, years of education, http://adni.loni.usc.edu/.The ADNI data analyzed are available in the ADNI repository, APOEε4 status, in addition to biomarker variables and baseline cognitive scores. Between A+T+ CN, MCI and dementia groups in ADNI, only CSF Aβ levels differed between them  but not CSF t-tau, p-tau, sTREM2 and sTNFR2 analytes (Demographic details of participants from the ADNI cohort (A+ T+) and the memory clinic replication cohort are presented in analytes .Among the MCI and AD dementia A+ T+ participants in the ADNI cohort, univariate analysis demonstrated that sTNFR2 and sTREM2 were significantly correlated with each other and with CSF t-tau and p-tau but not with Aβ42. This significant positive correlation between sTNFR2 and sTREM2 was replicated in the memory clinic participants with MCI, but only the sTNFR2 positive correlation with CSF t-tau and p-tau met the significance threshold .For ADNI MCI A+ T+ participants, both sTNFR2 and sTREM2 significantly predicted CSF p-tau and t-tau levels but not Aβ42 level (Model 1). The effect sizes were higher for sTNFR2 than for sTREM2. In Model 2, only sTNFR2 significantly predicted CSF p-tau and t-tau levels , Table 3Among participants in the replication memory clinic cohort, sTNFR2 (but not sTREM2) significantly predicted CSF p-tau and t-tau levels but not CSF Aβ42 level (Model 1). In Model 2, only sTNFR2 significantly predicted CSF p-tau and t-tau levels , Table 5In ADNI MCI A+ T+ participants, neither CSF sTREM2 nor sTNFR2 levels predicted future cognitive decline on CDR-SB when taking into account CSF p-tau or t-tau levels , Table 6P = 0.006, FDR = 0.048) . On further evaluating the robustness of this effect among a larger number of participants with sTREM2 and AD biomarkers alone, the significance and directionality of the results were again corroborated  , Table 7oborated .p < 0.0001). In the A– T– subgroup, sTNFR2 and sTREM2 were modestly correlated with each other  and each analyte was significantly related to CSF t-tau . In the A+ T+, A+ T–, and A– T+ subgroups, sTNFR2 and sTREM2 were not significantly correlated with each other. Only sTREM2 was correlated with CSF t-tau and p-tau in the A+ T+ subgroup, whereas only sTNFR2 was significantly correlated with CSF t-tau and p-tau in the A- T+ subgroup . In Model 2, sTREM2 again significantly predicted CSF p-tau and t-tau levels . sTREM2 Among A+ T– CN participants, neither analyte significantly predicted CSF p-tau and t-tau levels .Among A– T+ CN participants, sTNFR2 predicted t-tau and p-tau levels (Model 1). In Model 2, sTNFR2 significantly predicted CSF t-tau and Aβ42 levels .Among A– T– CN participants alone, the interaction of sTNFR2 and sTREM2 was significant on t-tau and p-tau levels (Model 1) .Among all CN participants combined, neither sTNFR2 nor sTREM2 predicted longitudinal cognitive change after accounting for CSF AD biomarkers (data not presented).P = 0.023, FDR = 0.092)  . In a se= 0.092) .Among A– T+, A+ T– and A– T– CN participants, neither sTNFR2 nor sTREM2 predicted longitudinal cognitive change after accounting for CSF AD biomarkers after FDR correction –10.42 and high total-tau or p-tau levels  or MCI (both cohorts). Among the above participants, sTNFR2 rather than sTREM2 explained most of the variance in relation to CSF t-tau and p-tau, whereas sTREM2 rather than sTNFR2 explained most of the variance in the same biomarkers among A+ T+ CN individuals (ADNI). These results are consistent with previous reports that demonstrated a positive correlation between CSF sTREM2 and t-tau and p-tau in participants with MCI  is higher in the preclinical stage of AD (A+ T+ CN) than in the A+ T+ MCI or dementia stages. Consistent with this, higher CSF sTREM2 levels that relate to higher CSF t-tau and p-tau levels at the preclinical AD stage was associated with greater cognitive decline, unlike in the dementia stage, in which higher CSF sTREM2 levels were associated with slower cognitive decline . These rTaken together our results suggest that there is a temporal window that should be considered for future therapeutic options targeting sTREM2- and sTNFR2-related inflammatory pathways and for the use of CSF sTREM2 in combination with other CSF AD and inflammatory biomarkers in evaluating its clinical significance. The temporal changes in CSF sTREM2 across different AD stages in this study parallels what has been described previously  appears to be a transition state in which the relationship noted between sTREM2, sTNFR2 and CSF t-tau or p-tau in all other stages of AD appears to be reversed, suggesting that in this stage, sTREM2 explains more of the variance of CSF t-tau and p-tau than does sTNFR2. This is consistent with prior results among preclinical AD with low AβThe statistical interaction noted between sTNFR2 and sTREM2 among CN A-T- participants shows higher levels of both sTNFR2 and sTREM2 together impact t-tau and p-tau levels more than we would expect if they acted independently, this appears to parallel the reports from animal studies where TNFR2 activation levels were related to transcriptional regulation of TREM2  in the replication cohort, the findings from this group could not be used to corroborate the effects of these analytes longitudinally from ADNI. These findings should also be corroborated in a cohort with different recruitment goals than ADNI, as the ADNI cohort is predominantly White with a high education attainment. We did not screen participants for possible TREM2 mutations, as the likelihood of these mutations is low  can be found at: The studies involving human participants were reviewed and approved by Cleveland Clinic. The patients/participants provided their written informed consent to participate in this study.JP obtained funding, design and conceptualized study, analyzed the data, interpreted the data, and drafted the manuscript for intellectual content. MK analyzed the data and revised the manuscript for intellectual content. JB design of study, interpreted the data, and revised the manuscript for intellectual content. JL interpreted the data and revised the manuscript for intellectual content. LB organized the data, interpreted the data, and revised the manuscript for intellectual content. All authors read and approved the final manuscript.JP received research funding from the National Institutes of Health, Alzheimer's Association, and Keep Memory Alive Foundation. JL has received consulting fees from Acadia, Aptnyx, Biogen, Eisai, GE Healthcare, Sanofi, and Takeda and grant support from the Alzheimer's Association, Alzheimer's Drug Discovery Foundation, Biogen, Department of Defense, GE Healthcare, Genzyme/Sanofi, Lewy Body Dementia Association, Michael J. Fox Foundation, and National Institute of Health NIA, NINDS. The remaining 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.


Capra pyrenaica, also known as Iberian ibex, Spanish ibex, and Spanish wild goat) underwent strong genetic bottlenecks during the 19th and 20th centuries due to overhunting and habitat destruction. From the 1970s to 1990s, augmentation translocations were frequently carried out to restock Iberian wild goat populations (very often with hunting purposes), but they were not systematically planned or recorded. On the other hand, recent data suggest the occurrence of hybridization events between Iberian wild goats and domestic goats (Capra hircus). Augmentation translocations and interspecific hybridization might have contributed to increase the diversity of Iberian wild goats. With the aim of investigating this issue, we have genotyped 118 Iberian wild goats from Tortosa‐Beceite, Sierra Nevada, Muela de Cortes, Gredos, Batuecas, and Ordesa and Monte Perdido by using the Goat SNP50 BeadChip (Illumina). The analysis of genotypic data indicated that Iberian wild goat populations are strongly differentiated and display low diversity. Only three Iberian wild goats out from 118 show genomic signatures of mixed ancestry, a result consistent with a scenario in which past augmentation translocations have had a limited impact on the diversity of Iberian wild goats. Besides, we have detected eight Iberian wild goats from Tortosa‐Beceite with signs of domestic goat introgression. Although rare, hybridization with domestic goats could become a potential threat to the genetic integrity of Iberian wild goats; hence, measures should be taken to avoid the presence of uncontrolled herds of domestic or feral goats in mountainous areas inhabited by this iconic wild ungulate.Iberian wild goats ( Habitat destruction and fragmentation combined with overhunting, climate change, and the introduction of invasive animals and plants have caused severe reductions in the genetic diversity and fitness of wild species, leading, in some cases, to their extinction Fahrig, . Human aHybridization between wild animals and livestock herds, which is largely unintentional, can also increase the genetic diversity of wild species, by introducing completely new alleles and genotypes, at the expense of decreasing adaptive potential due to outbreeding depression and behavioral changes, for example, reduced predator and human avoidance  is a wild goat ungulate native to the Iberian Peninsula which inhabits mountainous and rocky areas and feeds on shrubs, bushes, and grasses , C. p. victoriae , C. p. lusitanica , and C. p. pyrenaica , which became extinct two decades ago  and habitat loss and fragmentation  and domestic goats have been also described  and interspecific (hybridization between wild and domestic goats) gene flow on the diversity of Iberian wild goats by genotyping 118 individuals with a SNP assay.22.1th and 20th centuries but, as shown in Table In this work, we have investigated three CPH populations , two CPV populations (Gredos and Batuecas) and one CPP individual (Ordesa and Monte Perdido). All these Iberian wild goat populations underwent strong bottlenecks during the 192.2N = 43, 2010–2019), Muela de Cortes , and Sierra Nevada . Finally, one muscle sample from one of the last CPP representatives was collected in the location of Ordesa and Monte Perdido in 1996, before the extinction of this subspecies. Genomic DNA was isolated from blood samples as previously reported .Following the instructions of the manufacturer, we genotyped with the Goat SNP50 BeadChip from Illumina  and those with a minimum allele frequency (MAF) lower than 0.01 (‐maf 0.01) were filtered out. Markers with an individual missingness rate with more than 50% missing genotypes SNPs (–mind 0.5) and SNP with a missingness across samples greater than 1% (–geno 0.01) were also removed. After applying these filtering criteria, 21,621 SNPs were retained for genetic analyses.Preprocessing and filtering of data were carried out with the PLINK v.1.7 software  from Northern Spain (Bermeya and Blanca de Rasquera) and Southern Spain  typed with the Goat SNP50 BeadChip (Illumina) by Manunza et al. .2.4The majority of the 21,621 SNPs which passed the filtering criteria only segregated in eight Iberian wild goats from Tortosa‐Beceite, probably because of their introgression by domestic goats (see Section 2.5N = 118); (2) only Iberian wild goat populations (N = 118) with a data set of 894 SNPs, that is, 1001 SNPs minus the SNPs with missing values in the CPP sample . The reason for doing this is that MDS analyses tend to "locate" samples close to the center when missingness is high, so we wanted to test whether this circumstance could affect our results; (3) Iberian wild goat and domestic goat populations ; (4) eight hybrid Iberian wild goats from Tortosa‐Beceite and 50 domestic goats . MDS plots were built in R software by using the ggplot2 package  and expected (eH) heterozygosities, as well as the inbreeding coefficient Fhat2, were calculated by using the PLINK v.1.7 software  with FROH  because it is not defined as a probability but as an excess of homozygosity‐based inbreeding estimate  using the VCFtools software  between pairs of samples was estimated with the PI‐HAT coefficient, which describes the probability of sharing 0, 1, or 2 alleles IBD by pairs of individuals from the same homogeneous random‐mating population . A cross‐validation fold at 5% and a block bootstrap with 2000 iterations were used to calculate SE for admixture proportions. Confidence intervals for admixture proportions were inferred with Equation We used the Admixture software  and f3.In the Admixture analysis, eight individuals from Tortosa‐Beceite showed genomic signatures of introgression by domestic goats. We used the qp3pop program, included in the ADMIXTOOLS software package  ranged between 0.94 and 0.99, with an average of 0.98 ± 0.04. The only exception was the CPP DNA extracted from a muscle sample, which was considerably degraded and displayed a call rate of 0.86. In Figure 3.2N = 110) of Iberian wild goats. As expected, the MDS plot based on the information provided by these 1001 SNPs showed no signs of tight aggregation of Iberian wild goats in a single location  and expected (eH) heterozygosities were not substantially different in the five sampled Iberian wild goat populations  and Batuecas (Fhat2 = 0.539) populations, while in the Muela de Cortes population the magnitude of the Fhat2 coefficient was 20%–28% lower (Fhat2 = 0.442). The values of the Fhat2 coefficient in the Tortosa‐Beceite population were notably different depending on whether the eight hybrid individuals were included (Fhat2 = 0.516) or not (Fhat2 = 0.593) in the calculation  was much higher than among Spanish domestic goat breeds (FST < 0.072), with the only exception of the Gredos and Batuecas populations which had a weak genetic differentiation (FST = 0.035). The magnitude of the genetic differentiation did not correlate well with the assignment of populations to the CPH or CPV subspecies. For instance, the FST coefficient between the Sierra Nevada and Tortosa‐Beceite populations (FST = 0.379), which belong to the same CPH subspecies, was similar to FST coefficients measured between CPH and CPV populations. In addition, genetic differentiation among Spanish domestic goat and non‐hybrid Iberian wild goat was higher (FST = 0.337) than between Spanish domestic goat and the eight putative hybrid Iberian wild goats (FST = 0.183). The FST coefficient between the non‐hybrid Iberian wild goat populations and the eight Tortosa‐Beceite hybrids was 0.122.As shown in Table vs Batuecas comparison), indicating the absence of relatedness. In contrast, when these pairwise comparisons were made at the within‐population level , to investigate the diversity of Iberian wild goats. The call rates obtained with the Goat SNP50 BeadChip (Illumina) were consistent with previous estimates obtained by Miller et al. , who repoH and eH were twofold higher in domestic goats when compared to Alpine ibexes or Iberian wild goats, a result fully consistent with ours. Moreover, Grossen et al.  than those measured among domestic goat populations (FST < 0.072), and the latter were similar to those reported by Manunza et al. (The classification of Iberian wild goats in four subspecies proposed by Cabrera , 1914 raa et al.  for the a et al. .FST = 0.035, Table Overall, these results indicated that the classification of Cabrera , 1914 isIn the MDS analyses shown in Figure 4.3As pointed out by Acevedo and Cassinello , IberianOne of the main goals of the current work was to infer whether past restocking translocation processes have left genomic signatures that can be identified in current Iberian wild goat populations, as well as to ascertain the impact of restocking/repopulation on the within‐population genetic diversity. In a previous study based on a panel of 30 microsatellites (Angelone‐Alasaad et al., Many factors may explain why augmentation translocations left a scarce genomic footprint on the genomes of Iberian wild goats. For instance, chronic stress produced by the capture, handling, transport, captivity, and release of wild animals to a new location might result in substantially reduced reproductive success and increased mortality (Dickens et al., 4.4We detected eight Iberian wild goats from Tortosa‐Beceite with genomic signatures of domestic goat introgression. The f3 test agreed with the results of the Admixture analysis by showing that domestic goat introgression was significant Figure . The absDRB alleles that segregates in Alpine ibexes was identical to another one described in domestic goats. When the National Game Reserve of Tortosa‐Beceite was created in 1966, there was an estimated population of 200 Iberian wild goats. Although domestic goats were less abundant than domestic sheep, the presence of both domestic and feral goats combined with the low number of Iberian wild goats (Viñas‐Borrell et al., Angelone et al.  detectedAccording to our data, the introgression of Iberian wild goats by domestic goats does not seem to be widespread, probably because the interbreeding of these two species in the wild is a rare event, and moreover, some degree of reproductive incompatibility may exist (Herrero, Fernández‐Arberas, Prada, & García‐Serrano, The authors declare that they have no competing interests.Supplementary MaterialClick here for additional data file.


Urinary hippuric acid (uHA) is one of the biomonitoring parameters of toxic organic exposure, such as toluene. Repeated exposure to a low concentration of toluene may lead to chronic effects such as central nervous system damage. In the preliminary study, toluene was found in the batik industry's working area in Yogyakarta, Indonesia. This study aims to assess the health condition of batik workers to toluene exposure based on the concentration of uHA. There were 52 respondents divided into 2 groups: the batik workers as the exposed group (30 respondents) and the non-batik workers as the control group (22 respondents). The urine sample was taken from batik workers at the end of the shift, and uHA was measured using spectrophotometry. The uHA value was corrected with urinary creatinine. The results showed that the average uHA concentration of batik workers was higher than that of the control group. The result also showed that workers with more than 2 years working period, writing workers, and stamping workers give an Odds Ratio (OR) of 6.43, 6.75, and 9.00 respectively on having a higher concentration of uHA. Workers with toluene exposure symptoms were also having a higher concentration of uHA than workers without any symptoms. Hippuric acid, Batik industry, Toluene exposure, Biomarker, Batik wax. It is not only as a product but also as a symbol of Indonesian activities . Its comThe primary material needed for making batik is batik wax, mainly made from paraffin. During all the processes, the batik wax is heated at a certain temperature. The paraffin has a particular viscosity and could be applied easily to develop an excellent stroke . BecauseBesides the clinical assessment, the other parameter that can be used in health risk assessment is determining the exposure effect on the biochemical changes. Biomarkers are biological molecules found in organ tissues, blood and other body fluids that are signs of normal or abnormal body processes that indicate the condition of a disease. Biomarkers are used to see signs or the body's response to exposure to a pollutant substance . The widBatik workers mostly work in the indoor area to increase the exposure risk as a toluene concentration indoor is much higher than in the outdoor area , 18, 19.Studies on health risk assessment on batik workers in Indonesia are mainly on the effect that has been developed into disease symptoms. More evidence is required regarding toluene exposure and its correlation with worker's health on biochemical changes level. This study aimed to describe batik workers' health conditions based on the toluene exposure symptoms, determine and evaluate uHA concentration on batik workers, also determine the risk factor of having a high level of hippuric acid. This study result can be used as a screening and preventive action of batik workers' health effects.2A cross-sectional epidemiological study was conducted from August to October 2020 in three different batik industries in Kulon Progo, Special Region of Yogyakarta, Indonesia. The Ethics Committee has approved this research of Padjajaran University, Bandung, Indonesia.2.1A total of 52 respondents were divided into 2 groups: the exposed and control group. The exposed group's inclusion criteria were agreed to participate and signed informed consent, batik workers who work in the production area, have been working for more than 3 months, and 18 years older. Meanwhile, the control group is a resident and an administration staff in the batik industry. Respondents exposed to toluene outside working hours, having liver disease, and consuming medication that might affect toluene metabolism were excluded from this study.2.2The questionnaire was done by interviewing each respondent face-to-face before urine sampling. The questionnaire consists of five main parts: individual information, working history, medical history , lifestyle , health and safety environment (HSE), and toluene exposure symptoms, both acute and chronic symptoms. For the control group, the working history and HSE part were excluded.2.3Toluene exposure was measured by collecting inhaled air using a personal sampler pump and charcoal sorbent tube . The sampling duration was 3 hours long in the first period (09.00–12.00) or the second period (13.00–16.00) depends on the worker's activities on the sampling day. The toluene concentration and inhaled air characterization then measured using Gas Chromatography-Mass Spectrometry (Shimadzu GCMS-QP2010S) with Rtx-5 column .2.4The urine sample was taken by grab sampling at the end of the shift using a 50 mL polystyrene bottle with a minimum volume was 15 ml. The sample was then stored and transported at 4 °C to the laboratory without any additional preservatives and should be tested within 5 days after sampling.2.5Urinary hippuric acid was measured using UV-Vis Spectrophotometry based on the standard methods of NIOSH 8300 Issue 2 ,28,29. T2.6Descriptive analysis was used to analyze respondent information and urinary hippuric acid concentration profile. Data normality was determined using the Shapiro-Wilk test. The comparison test between the exposed and control groups was done using the non-parametric statistic method Mann-Whitney, Kruskal-Wallis, and Chi-Square test, depending on the number of variables and types of data. Correlation analysis between urinary hippuric acid concentration and the numerical variable was done using Spearman correlation rank. The Odds ratio of each risk factor was determined using binary logistic regression analysis.2.7The ethical clearance research was conducted closely between the parties involved in the research. The two-way agreement was obtained by verbal communication and signed a handwritten agreement. The Ethics Committee has approved this research of Padjajaran University, Bandung, Indonesia with No: 353/UN6.KEP/EC/2020.33.1A total of 30 respondents in the exposed group are dominated by age ranging 18–39 years old, while 22 respondents in the control group are dominated by 40–60 years old. Both groups are mainly non-smoker. Most of the exposed groups are light caffeine consumers (<3 glasses), while the control group is equal between light and heavy consumers. The caffeine consumption categories were made based on the study that reported a significant increase in uHA on heavy drinkers , 12, 30.3.2The exposed respondents are from the washing (43.33%), batik writing (40.00%), and batik stamping (16.67%) process . The sam3.3The mean value of uHA in the exposed and control group are 420.91 and 387.99 mg/g creatinine, respectively . For allNevertheless, in this study, both groups have higher uHA mean and median concentration than background value without the toluene exposure and benzoic acid intake 180 mg/g . This reThe uHA value distribution on the exposed group also is on the higher side with more than 200 up to 1000 mg/g creatinine compared to the control group that is clustered on the 200–700 mg/g creatinine . The incWe found an extreme value of uHA concentration on the control group with 842 mg/g creatinine. There are no unusual behaviors nor working histories on this respondent that could lead to be elevation of uHA. This respondent has a medical history with diabetic disease and takes medication routinely, but the medication does not alter the hippuric acid secretion. There should be a confounding factor affecting this result that could not be shown on the questionnaire result such as benzoic acid intake mentioned above.In recent years, ACGIH suggests other metabolites to be used as a biomonitoring compound of toluene exposure, the ortho-cresol . Ortho-cEven so, based on the uHA concentration result which is difficult to specify the exact sources of uHA secretion due to the confounding factors in the consumption behavior, especially on the control group, other methods should be considered for further analysis. Whether using a specific biomarker such as urinary o-cresol and toluene or restrict the uHA sources intake of the respondents on the sampling day.3.4Many factors have been associated with uHA concentration on humans. Individual factor such as gender, showing that adult female tends to produce uHA higher than males with the mean value respectively 200 mg/g creatinine and 160 mg/g creatinine . The resWorking period is the only variable that has a significant difference . Workers with more than 2 years of experience are having a significant uHA concentration higher than workers with less than 2 years of experience . When weThe working period is related to repeated exposure and accumulation of toluene, which will be affecting CNS disease symptoms indicated by the higher level of excreted uHA. Based on the review by Filley 2004), neuropsychological symptoms caused by toluene exposure could be detected as early as 2 years after initial exposure, which corresponds with findings in this current study . Compari, neuropsTo determine the magnitude of probabilities on each risk factor on having a higher concentration of uHA, an Odds Ratio (OR) was calculated using binary logistic regression analysis. Female (OR 2.531), overweight based on BMI (OR 2.333), smoker (OR 1.389), and heavy caffeine consumer (OR 1.692) are factors that increase the probability of having a high level of uHA. But in this study, the elevation is statistically insignificant . Working process and working period are the risk factors that have a significant increase in OR value. The writing process (OR 6.750) and workers with more than 2 years working period (OR 6.429) have a probability of having a higher level of uHA . Stamping workers also having a higher probability with OR value of 9.000 but this group is statistically significant in different significance levels  .Table 5OThe difference in process and materials used on writing and stamping workers suggested being a reason for a high concentration of uHA. Both working processes using batik wax that can generate toluene to the working area. In the working process, the batik wax was heated continuously throughout the working time, and the source of heat was near to the worker's body. The quantity of the usage of batik wax is also suggested as one of the factors. The stamping process uses stamping tools and a heating pan with a bigger surface area than on the writing process. The quantity of the fume generated and exposed to the workers might be higher in the stamping process.3.5The interviews regarding toluene exposure symptoms showed that most of the workers were having either acute or chronic symptoms. The highest percentage of toluene exposure symptoms experienced by batik workers are headache (50%) and insomnia (50%), followed by tiredness (40%), difficulty to concentrate (30%), nose irritation (27%), and loss of appetite (20%). Other symptoms such as nausea, eye irritation, and loss of smell were reported from less than 20% of workers.Comparison of the impact of toluene exposure and uHA concentration showed that workers experiencing fatigue, insomnia, and loss of smell had higher mean uHA concentrations. Meanwhile, in acute toluene exposure assessment, the increasing uHA mean concentration was varied between workers with and without symptoms . The ass3.6The uHA result showed that batik workers have a higher concentration on uHA than in the control group. It is also calculated that the working process and working period are the risk factor that significantly increases uHA in batik workers. To measure the level of toluene exposure, inhaled air sample was taken from each respondent, and toluene concentration was measured. In this study, the toluene measurement showing that the toluene content is in a very low concentration so that it could not be detected. The GC chromatogram showed a peak around the toluene retention area, but the intensity is very low, and the MS shows no significant result.4Batik workers have a high percentage of experiencing both acute and chronic toluene exposure symptoms. Workers with toluene exposure symptoms have a higher uHA concentration than workers without any symptoms. Toluene exposure monitored by uHA concentration showed that workers who have been working for more than 2 years are having a higher uHA concentration and probability 6.429 times higher on having a higher level of uHA. Workers who work using batik wax also have a high probability, 6.750 times and 9.000 times higher on having a higher level of uHA. The management of these risk factors should be considered in order to decrease the health risk on batik workers caused by occupational exposure.Katharina Oginawati: Conceived and designed the experiments; Performed the experiments.Annisa Artsani Hanif Anka: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data.Septian Hadi Susetyo: Contributed reagents, materials, analysis tools or data; Wrote the paper.Sri Awalia Febriana, Ikeu Tanziha, Cita Rosita Sigit Prakoeswa: Contributed reagents, materials, analysis tools or data.Kementerian Riset Teknologi Dan Pendidikan Tinggi Republik Indonesia, Riset Kolaborasi Indonesia (RKI) program.This work was supported by Data will be made available on request.The authors declare no conflict of interest.No additional information is available for this paper.


A strong agreement was observed between both devices for mean cadence (ICC > 0.87) and PO values (ICC > 0.81) recorded in essentially all conditions and for peak cadence (ICC > 0.98) and peak PO (ICC > 0.99) during all-out efforts. The coefficient of variation for PO values was consistently lower than 3%. In conclusion, the FAD pedal-based power meter can be considered an overall valid system to record PO and cadence during cycling, although it might present a small bias compared with power meters placed on other locations such as SRM.Cycling power meters enable monitoring external loads and performance changes. We aimed to determine the concurrent validity of the novel Favero Assioma Duo (FAD) pedal power meter compared with the crank-based SRM system (considered as gold standard). Thirty-three well-trained male cyclists were assessed at different power output (PO) levels , pedaling cadences (75–100 rpm) and cycling positions (seating and standing) to compare the FAD device vs. SRM. No significant differences were found between devices for cadence nor for PO during all-out efforts ( A large number of cycling power meters have been developed over the last 20 years  ,2. TheseThe SRM crank  is widely considered as the gold standard power meter (±1% accuracy) ,6,7,8. OThe rationale for locating the power meter in the pedals is that the PO of the athlete can be measured directly in the rider–bike interface, rather than in the point at which PO is transferred to the road (rear-hub-based system) , which dThe novel Favero Assioma Duo (FAD) pedal power meter bases its technology on using eight strain gauges placed around the axle to measure the slight deflections on the pedal spindle through the entire pedal stroke, as well as the two-dimensional force vectors . In addiDue to the widely spread use of pedal power meters, their potential advantage over other power meters, and particularly the growing popularity of the FAD power meter, the aim of the present study was to determine the concurrent validity of the FAD power meter under laboratory conditions when compared with SRM. We hypothesized that the FAD device would record similar PO values and cadence when compared with a scientifically validated system .We conducted a descriptive cross-sectional study. Participants’ recruitment and data collection took place between October and December 2020. During a period of 4 weeks, each participant performed the tests in the same laboratory  under standardized conditions (a temperature of 20.0 ± 1.1 °C and a humidity of 27.1 ± 1.6%). The study was conducted according to the tenets of the Declaration of Helsinki and was approved by the Investigation Ethics Commission of the European University of Madrid (CI-PI/20/165). Written informed consent was obtained from all participants prior to participation and after having the procedures explained in verbal and written form.In total, 33 well-trained male cyclists participated in the study . All participants had trained for 14.1 ± 3.0 h per week for a minimum of twelve months before the study. Participants were asked to avoid strenuous exercise, caffeine and alcohol for at least 24 h prior to testing sessions. Although an a priori sample size calculation was not performed, the sample size used was deemed appropriate based on the number of participants used in previous similar studies [A FAD power meter  was compared against an SRM crank-based power meter (gold standard method), revised and calibrated following manufacturer’s instructions  . The FAD−1) at six submaximal workloads  of 75 s duration. A metronome was used during this block to facilitate the cyclist’s adjustment to the required cadence [The validity of the FAD was assessed in the laboratory using protocols derived from those used in previous studies ,22. We c cadence . After tPO and cadence data of the three initials blocks were collected for a minimum of 60 s. The initial 10 s and last 5 s from each data recording were discarded to allow sufficient time for the cyclists to stabilize and maintain each new load ,24.Data are presented as mean ± SD. The relationship and level of agreement between systems was analyzed with Pearson’s correlation coefficients (r), intra-class correlation coefficients (ICC), and typical errors of measurement (TEM), with all measures expressed together with 95% confidence interval (CI). r-values of 0.1, 0.3, 0.5, 0.7, and 0.9 were considered small, moderate, strong, very strong and extremely strong, respectively . ICC valp < 0.05 for PO by measurement system interactions, mean bias 3–8 W), with no significant differences were found during all-out efforts (p > 0.05)   . Strong- = 0.66) , Table 1 = 0.66) .−1, −1.78 W at 85 rev·min−1 and −2.41 W at 100 rev·min−1)  a–c. A hiv·min−1) d,e. The v·min−1) f. There v·min−1) .The CV% for mean PO values was lower than 1.84% in block one, two and three, 2.89% in block four, and 1.49% for peak PO during the sprints.p > 0.05) was found for any of the conditions . Extremely strong r-values and ICCs were found between the peak cadence in sprints .The CV% for mean cadence was lower than 0.45% in block one, two and three, 1.10% in block four, and 0.83% for peak cadence during the sprints.The aim of the present study was to assess the validity of the FAD pedal power meter using a laboratory-based exercise protocol. The results of the study indicate that the FAD power meter system provides overall valid data for the measures of PO and cadence across a wide range of intensities. To our knowledge, this is the first study to assess the validity of this new power meter against the gold standard SRM device.p > 0.05), although significant but small differences were found for efforts at lower PO values (100–500 W). Particularly, we detected a small bias  or <8 W in block three (~2%)) between the SRM and FAD for the mean PO data, with slightly higher values observed for FAD. However, this small bias is in line with the manufacturers’ instructions for calibration of other pedal-based power meters  and the inner biological variability of the participants while pedaling. This resulted in a lower reliability when pedaling at very low intensities  but higher reliability at higher intensities . However, similar CVs were found between FAD and the gold standard SRM, and the overall CV (the comparison between FAD and SRM) values were low (<3%). Finally, we found an overall strong correlation between FAD and SRM for all PO values except for 300 W at 100 rpm (r = 0.69). This might have been caused by the small variations among subjects when pedaling at ~300 W , which hinders observing strong correlations at that specific PO, and indeed when attending at the whole range of PO values the correlation between both devices was strong (r > 0.87).In summary, the present findings overall support the concurrent validity of the FAD pedal power meter compared with SRM, although the former can result in slightly higher PO values (3–8 W on average) that might be potentially due to the measurement location . Therefore, the PO values registered between these devices should not be used interchangeably. The novel FAD power meter might offer some advantages over other power meters as it measures power in the direct zone of application , is cheaper than other power meters, can be easily interchanged between bikes and can be used to assess the PO of each leg separately.The FAD pedal power meter can be considered an overall valid device to record PO and cadence in different conditions, presenting an overall good agreement (ICC > ~0.80) and low albeit significant bias  compared to the PO values registered by the gold standard SRM device.