Showing papers by "University of Memphis published in 2018"

Ratiometric optical nanoprobes enable accurate molecular detection and imaging

Abstract: Exploring and understanding biological and pathological changes are of great significance for early diagnosis and therapy of diseases. Optical sensing and imaging approaches have experienced major progress in this field. Particularly, an emergence of various functional optical nanoprobes has provided enhanced sensitivity, specificity, targeting ability, as well as multiplexing and multimodal capabilities due to improvements in their intrinsic physicochemical and optical properties. However, one of the biggest challenges of conventional optical nanoprobes is their absolute intensity-dependent signal readout, which causes inaccurate sensing and imaging results due to the presence of various analyte-independent factors that can cause fluctuations in their absolute signal intensity. Ratiometric measurements provide built-in self-calibration for signal correction, enabling more sensitive and reliable detection. Optimizing nanoprobe designs with ratiometric strategies can surmount many of the limitations encountered by traditional optical nanoprobes. This review first elaborates upon existing optical nanoprobes that exploit ratiometric measurements for improved sensing and imaging, including fluorescence, surface enhanced Raman scattering (SERS), and photoacoustic nanoprobes. Next, a thorough discussion is provided on design strategies for these nanoprobes, and their potential biomedical applications for targeting specific biomolecule populations (e.g. cancer biomarkers and small molecules with physiological relevance), for imaging the tumor microenvironment (e.g. pH, reactive oxygen species, hypoxia, enzyme and metal ions), as well as for intraoperative image guidance of tumor-resection procedures.

From hype to reality: data science enabling personalized medicine

Abstract: Personalized, precision, P4, or stratified medicine is understood as a medical approach in which patients are stratified based on their disease subtype, risk, prognosis, or treatment response using specialized diagnostic tests. The key idea is to base medical decisions on individual patient characteristics, including molecular and behavioral biomarkers, rather than on population averages. Personalized medicine is deeply connected to and dependent on data science, specifically machine learning (often named Artificial Intelligence in the mainstream media). While during recent years there has been a lot of enthusiasm about the potential of ‘big data’ and machine learning-based solutions, there exist only few examples that impact current clinical practice. The lack of impact on clinical practice can largely be attributed to insufficient performance of predictive models, difficulties to interpret complex model predictions, and lack of validation via prospective clinical trials that demonstrate a clear benefit compared to the standard of care. In this paper, we review the potential of state-of-the-art data science approaches for personalized medicine, discuss open challenges, and highlight directions that may help to overcome them in the future. There is a need for an interdisciplinary effort, including data scientists, physicians, patient advocates, regulatory agencies, and health insurance organizations. Partially unrealistic expectations and concerns about data science-based solutions need to be better managed. In parallel, computational methods must advance more to provide direct benefit to clinical practice.

Surveying the forest: A meta-analysis, moderator investigation, and future-oriented discussion of the antecedents of voluntary employee turnover

Abstract: Recent narrative reviews (e.g., Hom, Mitchell, Lee, and Griffeth, 2012; Hom, Lee, Shaw, and Hausknecht, 2017) advise that it is timely to assess the progress made in research on voluntary employee turnover so as to guide future work. To provide this assessment, we employed a three-step approach. First, we conducted a comprehensive meta-analysis of turnover predictors, updating existing effect sizes and examining multiple new antecedents. Second, guided by theory, we developed and tested a set of substantive moderators, considering factors that might exacerbate or mitigate zero-order meta-analytic effects. Third, we examined the holistic pattern of results in order to highlight the most pressing needs for future turnover research. The results of Step 1 reveal multiple newer predictors and updated effect sizes of more traditional predictors, which have received substantially greater study. The results of Step 2 provide insight into the context-dependent nature of many antecedent–turnover relationships. In Step 3, our discussion takes a bird's-eye view of the turnover “forest” and considers the theoretical and practical implications of the results. We offer several research recommendations that break from the traditional turnover paradigm, as a means of guiding future study.

To co-produce or not to co-produce

Abstract: Researchers, stakeholders and funding organizations have embraced co-production of knowledge to solve sustainability problems. Research focusing on the practice of co-production can help us understand what works in what contexts and how to avoid potentially undesirable outcomes.

Language Experience in the Second Year of Life and Language Outcomes in Late Childhood

Abstract: OBJECTIVES: Quantity of talk and interaction in the home during early childhood is correlated with socioeconomic status (SES) and can be used to predict early language and cognitive outcomes We tested the effectiveness of automated early language environment estimates for children 2 to 36 months old to predict cognitive and language skills 10 years later and examined effects for specific developmental age periods METHODS: Daylong audio recordings for 146 infants and toddlers were completed monthly for 6 months, and the total number of daily adult words and adult-child conversational turnswere automatically estimated with Language Environment Analysis software Follow-up evaluations at 9 to 14 years of age included language and cognitive testing Language exposure for 3 age groups was assessed: 2 to 17 months, 18 to 24 months, and ≥25 months Pearson correlations and multiple linear regression analyses were conducted RESULTS: Conversational turn counts at 18 to 24 months of age accounted for 14% to 27% of the variance in IQ, verbal comprehension, and receptive and/or expressive vocabulary scores 10 years later after controlling for SES Adult word counts between 18 and 24 months were correlated with language outcomes but were considerably weakened after controlling for SES CONCLUSIONS: These data support the hypothesis that early talk and interaction, particularly during the relatively narrow developmental window of 18 to 24 months of age, can be used to predict school-age language and cognitive outcomes With these findings, we underscore the need for effective early intervention programs that support parents in creating an optimal early language learning environment in the home

HealthDep: An Efficient and Secure Deduplication Scheme for Cloud-Assisted eHealth Systems

Abstract: In this paper, we analyze the inherent characteristic of electronic medical records (EMRs) from actual electronic health (eHealth) systems, where we found that first, multiple patients would generate large amounts of duplicate EMRs and second, cross-patient duplicate EMRs would be generated numerously only in the case that the patients consult doctors in the same department. We then propose the first efficient and secure encrypted EMRs deduplication scheme for cloud-assisted eHealth systems (HealthDep). With the integration of our analysis results, HealthDep allows the cloud server to efficiently perform the EMRs deduplication, and enables the cloud server to reduce storage costs by more than 65% while ensuring the confidentiality of EMRs. Security analysis shows that HealthDep provides a stronger security guarantee than Marforio et al. 's scheme (NDSS 2014) and Bellare et al. 's scheme (USENIX Security 2013). Algorithm implementation and performance analysis demonstrate the feasibility and high efficiency of HealthDep.

Molecular Detection and Analysis of Exosomes Using Surface-Enhanced Raman Scattering Gold Nanorods and a Miniaturized Device.

Abstract: Exosomes are a potential source of cancer biomarkers. Probing tumor-derived exosomes can offer a potential non-invasive way to diagnose cancer, assess cancer progression, and monitor treatment responses. Novel molecular methods would facilitate exosome analysis and accelerate basic and clinical exosome research. Methods: A standard gold-coated glass microscopy slide was used to develop a miniaturized affinity-based device to capture exosomes in a target-specific manner with the assistance of low-cost 3-D printing technology. Gold nanorods coated with QSY21 Raman reporters were used as the label agent to quantitatively detect the target proteins based on surface enhanced Raman scattering spectroscopy. The expressions of several surface protein markers on exosomes from conditioned culture media of breast cancer cells and from HER2-positive breast cancer patients were quantitatively measured. The data was statistically analyzed and compared with healthy controls. Results: A miniaturized 17 × 5 Au array device with 2-mm well size was fabricated to capture exosomes in a target-specific manner and detect the target proteins on exosomes with surface enhanced Raman scattering gold nanorods. This assay can specifically detect exosomes with a limit of detection of 2×106 exosomes/mL and analyze over 80 purified samples on a single device within 2 h. Using the assay, we have showed that exosomes derived from MDA-MB-231, MDA-MB-468, and SKBR3 breast cancer cells give distinct protein profiles compared to exosomes derived from MCF12A normal breast cells. We have also showed that exosomes in the plasma from HER2-positive breast cancer patients exhibit significantly (P ≤ 0.01) higher level of HER2 and EpCAM than those from healthy donors. Conclusion: We have developed a simple, inexpensive, highly efficient, and portable Raman exosome assay for detection and protein profiling of exosomes. Using the assay and model exosomes from breast cancer cells, we have showed that exosomes exhibit diagnostic surface protein markers, reflecting the protein profile of their donor cells. Through proof-of-concept studies, we have identified HER2 and EpCAM biomarkers on exosomes in plasma from HER2-positive breast cancer patients, suggesting the diagnostic potential of these markers for breast cancer diagnostics. This assay would accelerate exosome research and pave a way to the development of novel cancer liquid biopsy for cancer detection and monitoring.

Advancing the Science of Collaborative Problem Solving

Abstract: Collaborative problem solving (CPS) has been receiving increasing international attention because much of the complex work in the modern world is performed by teams. However, systematic education a...

A Suite of Exercises for Verifying Dynamic Earthquake Rupture Codes

Abstract: We describe a set of benchmark exercises that are designed to test if computer codes that simulate dynamic earthquake rupture are working as intended. These types of computer codes are often used to understand how earthquakes operate, and they produce simulation results that include earthquake size, amounts of fault slip, and the patterns of ground shaking and crustal deformation. The benchmark exercises examine a range of features that scientists incorporate in their dynamic earthquake rupture simulations. These include implementations of simple or complex fault geometry, off‐fault rock response to an earthquake, stress conditions, and a variety of formulations for fault friction. Many of the benchmarks were designed to investigate scientific problems at the forefronts of earthquake physics and strong ground motions research. The exercises are freely available on our website for use by the scientific community.

Bactericidal Effects of Silver Nanoparticles on Lactobacilli and the Underlying Mechanism.

Abstract: While the antibacterial properties of silver nanoparticles (AgNPs) have been demonstrated across a spectrum of bacterial pathogens, the effects of AgNPs on the beneficial bacteria are less clear. To address this issue, we compared the antibacterial activity of AgNPs against two beneficial lactobacilli (Lactobacillus delbrueckii subsp. bulgaricus and Lactobacillus casei) and two common opportunistic pathogens (Escherichia coli and Staphylococcus aureus). Our results demonstrate that those lactobacilli are highly susceptible to AgNPs, while the opportunistic pathogens are not. Acidic environment caused by the lactobacilli is associated with the bactericidal effects of AgNPs. Our mechanistic study suggests that the acidic growth environment of lactobacilli promotes AgNP dissolution and hydroxyl radical (•OH) overproduction. Furthermore, increases in silver ions (Ag+) and •OH deplete the glutathione pool inside the cell, which is associated with the increase in cellular reactive oxygen species (ROS). High lev...

Observed rapid bedrock uplift in Amundsen Sea Embayment promotes ice-sheet stability

Abstract: The marine portion of the West Antarctic Ice Sheet (WAIS) in the Amundsen Sea Embayment (ASE) accounts for one-fourth of the cryospheric contribution to global sea-level rise and is vulnerable to catastrophic collapse. The bedrock response to ice mass loss, glacial isostatic adjustment (GIA), was thought to occur on a time scale of 10,000 years. We used new GPS measurements, which show a rapid (41 millimeters per year) uplift of the ASE, to estimate the viscosity of the mantle underneath. We found a much lower viscosity (4 × 10 18 pascal-second) than global average, and this shortens the GIA response time scale to decades up to a century. Our finding requires an upward revision of ice mass loss from gravity data of 10% and increases the potential stability of the WAIS against catastrophic collapse.

mTOR signaling regulates central and peripheral circadian clock function.

Abstract: The circadian clock coordinates physiology and metabolism. mTOR (mammalian/mechanistic target of rapamycin) is a major intracellular sensor that integrates nutrient and energy status to regulate protein synthesis, metabolism, and cell growth. Previous studies have identified a key role for mTOR in regulating photic entrainment and synchrony of the central circadian clock in the suprachiasmatic nucleus (SCN). Given that mTOR activities exhibit robust circadian oscillations in a variety of tissues and cells including the SCN, here we continued to investigate the role of mTOR in orchestrating autonomous clock functions in central and peripheral circadian oscillators. Using a combination of genetic and pharmacological approaches we show that mTOR regulates intrinsic clock properties including period and amplitude. In peripheral clock models of hepatocytes and adipocytes, mTOR inhibition lengthens period and dampens amplitude, whereas mTOR activation shortens period and augments amplitude. Constitutive activation of mTOR in Tsc2–/–fibroblasts elevates levels of core clock proteins, including CRY1, BMAL1 and CLOCK. Serum stimulation induces CRY1 upregulation in fibroblasts in an mTOR-dependent but Bmal1- and Period-independent manner. Consistent with results from cellular clock models, mTOR perturbation also regulates period and amplitude in the ex vivo SCN and liver clocks. Further, mTOR heterozygous mice show lengthened circadian period of locomotor activity in both constant darkness and constant light. Together, these results support a significant role for mTOR in circadian timekeeping and in linking metabolic states to circadian clock functions.

Predicting the adoption of connected autonomous vehicles: A new approach based on the theory of diffusion of innovations

Abstract: On the grounds that individuals heavily rely on the information that they receive from their peers when evaluating adoption of a radical innovation, this paper proposes a new approach to forecast long-term adoption of connected autonomous vehicles (CAVs). The concept of resistance is employed to explain why individuals typically tend to defer the adoption of an innovation. We assume that there exists a social network among individuals through which they communicate based on certain frequencies. In addition, individuals can be subject to media advertisement based on certain frequencies. An individual’s perceptions are dynamic and change over time as the individual is exposed to advertisement and communicates with satisfied and dissatisfied adopters. We also explicitly allow willingness-to-pay (WTP) to change as a result of peer-to-peer communication. An individual decides to adopt when (i) there is a need for a new vehicles; (ii) his/her WTP is greater than CAV price; and (iii) his/her overall impression about CAVs reaches a cutoff value. Applicability of the proposed approach is shown using a survey of employees of the University of Memphis. Our results show that the automobile fleet will be near homogenous in about 2050 only if CAV prices decrease at an annual rate of 15% or 20%. We find that a 6-month pre-introduction marketing campaign may have no significant impact on adoption trend. Marketing is shown to ignite CAV diffusion but its effect is capped. CAV market share will be close to 100% only if all adopters are satisfied with their purchases; therefore, the probability that an individual becomes a satisfied adopter plays an important role in the trend of adoption. The effect of the latter probability is more pronounced as time goes by and is also more prominent when CAV price reduces at greater rates. Some caveats may be inserted when considering the study results as the findings are subject to sample bias and data limitations.

Active inference, enactivism and the hermeneutics of social cognition.

Abstract: We distinguish between three philosophical views on the neuroscience of predictive models: predictive coding (associated with internal Bayesian models and prediction error minimization), predictive processing (associated with radical connectionism and ‘simple’ embodiment) and predictive engagement (associated with enactivist approaches to cognition). We examine the concept of active inference under each model and then ask how this concept informs discussions of social cognition. In this context we consider Frith and Friston’s proposal for a neural hermeneutics, and we explore the alternative model of enactivist hermeneutics.

How do we model learning at scale?: A systematic review of research on MOOCs

Abstract: Despite a surge of empirical work on student participation in online learning environments, the causal links between the learning-related factors and processes with the desired learning outcomes remain unexplored. This study presents a systematic literature review of approaches to model learning in Massive Open Online Courses offering an analysis of learning-related constructs used in the prediction and measurement of student engagement and learning outcome. Based on our literature review, we identify current gaps in the research, including a lack of solid frameworks to explain learning in open online setting. Finally, we put forward a novel framework suitable for open online contexts based on a well-established model of student engagement. Our model is intended to guide future work studying the association between contextual factors (i.e., demographic, classroom, and individual needs), student engagement (i.e., academic, behavioral, cognitive, and affective engagement metrics), and learning outcomes (i.e...

The effects of a mobile gamification app on elementary students’ Spanish achievement and self-efficacy

Abstract: A quasi-experimental, pretest-posttest, non-equivalent control group design was used to examine the effect of a mobile gamification application on third and fourth grade students’ Spanish language ...

A Review on Melt-Pool Characteristics in Laser Welding of Metals

Abstract: Laser welding of metals involves with formation of a melt-pool and subsequent rapid solidification, resulting in alteration of properties and the microstructure of the welded metal. Understanding and predicting relationships between laser welding process parameters, such as laser speed and welding power, and melt-pool characteristics have been the subjects of many studies in literature because this knowledge is critical to controlling and improving laser welding. Recent advances in metal additive manufacturing processes have renewed interest in the melt-pool studies because in many of these processes, part fabrication involves small moving melt-pools. The present work is a critical review of the literature on experimental and modeling studies on laser welding, with the focus being on the influence of process parameters on geometry, thermodynamics, fluid dynamics, microstructure, and porosity characteristics of the melt-pool. These data may inform future experimental laser welding studies and may be used for verification and validation of results obtained in future melt-pool modeling studies.

Querying in Internet of Things with Privacy Preserving: Challenges, Solutions and Opportunities

Abstract: IoT is envisioned as the next stage of the information revolution, enabling various daily applications and providing better service by conducting a deep fusion with cloud and fog computing. As the key mission of most IoT applications, data management, especially the fundamental function-data query, has long been plagued by severe security and privacy problems. Most query service providers, including the big ones (e.g., Google, Facebook, Amazon, and so on) are suffering from intensive attacks launched by insiders or outsiders. As a consequence, processing various queries in IoT without compromising the data and query privacy is an urgent and challenging issue. In this article, we propose a thing-fog-cloud architecture for secure query processing based on well studied classical paradigms. Following with a description of crucial technical challenges in terms of functionality, privacy and efficiency assurance, we survey the latest milestone-like approaches, and provide an insight into the advantages and limitations of each scheme. Based on the recent advances, we also discuss future research opportunities to motivate efforts to develop practical private query protocols in IoT.

Intelligent Tutoring Systems

Abstract: Intelligent tutoring systems (ITS) are computer learning environments that help students master knowledge and skills by implementing intelligent algorithms that adapt to students at a fine-grained level and that instantiate complex principles of learning. An ITS normally works with one student at a time because students differ on many dimensions and the goal is to be sensitive to the idiosyncrasies of individual learners. ITS have been developed for mathematics and other computationally well-formed topics as well as knowledge domains that have a verbal foundation. Reviews and quantitative meta-analyses confirm that ITS technologies frequently improve learning over reading text and traditional teacher-directed classroom teaching. This chapter describes affordances that are frequently incorporated in most applications. Some affordances are routinely incorporate in ITS (active student learning, interactivity, adaptivity, and feedback) whereas others are frequently but not always included (choice, non-linear access to topics, linked representations, and open-ended learner input). The Generalized Intelligent Framework for Tutoring (GIFT) is a framework that articulates the frequent practices, pedagogical and technical standards, and computational architectures for developing ITS; the goal of the GIFT initiative is to scale up ITS development for schools, the military, industry, and the public. The chapter also identifies major challenges in building ITS and some of their limitations.

Testing the Predictive Validity of the Healthy Eating Index-2015 in the Multiethnic Cohort: Is the Score Associated with a Reduced Risk of All-Cause and Cause-Specific Mortality?

Abstract: The Healthy Eating Index-2015 (HEI-2015) was created to assess conformance of dietary intake with the Dietary Guidelines for Americans (DGA) 2015-2020. We assessed the association between the HEI-2015 and mortality from all-cause, cardiovascular disease (CVD), and cancer in the Multiethnic Cohort (MEC). White, African American, Native Hawaiian, Japanese American, and Latino adults (n > 215,000) from Hawaii and California completed a quantitative food-frequency questionnaire at study enrollment. HEI-2015 scores were divided into quintiles for men and women. Radar graphs were used to demonstrate how dietary components contributed to HEI-2015 scores. Mortality was documented over 17-22 years of follow-up. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed using Cox proportional hazards models. High HEI-2015 scores were inversely associated with risk of mortality from all-cause, CVD, and cancer for men and women (p-trend <0.0001 for all models). For men, the HRs (CIs) for all-cause, CVD, and cancer comparing the highest to the lowest quintile were 0.79 (0.76, 0.82), 0.76 (0.71, 0.82), and 0.80 (0.75, 0.87), respectively. For women, the HRs were 0.79 (0.76, 0.82), 0.75 (0.70, 0.81), and 0.84 (0.78, 0.91), respectively. These results, in a multiethnic population, demonstrate that following a diet aligned with the DGAs 2015-2020 recommendations is associated with lower risk of mortality from all-cause, CVD, and cancer.

A Secure Link State Routing Protocol for NDN

Abstract: The Named-data Link State Routing protocol (NLSR) is a protocol for intra-domain routing in Named Data Networking (NDN). It is an application level protocol similar to many IP routing protocols, but NLSR uses NDN’s interest/data packets to disseminate routing updates, directly benefiting from NDN’s built-in data authenticity. The NLSR design, which was first developed in 2013 and deployed on the NDN test bed in August 2014, has undergone significant changes. Following an application-driven design approach, NLSR’s development helped drive the development of the trust/security functionality of NDN libraries as well as a number of features in NDN’s forwarding daemon and ChronoSync. In this paper, we describe the current design and implementation of NLSR, with emphasis on those features that differentiate it from an IP-based link state routing protocol: 1) naming: a hierarchical naming scheme for routers, keys, and routing updates; 2) security: a hierarchical trust model for routing within a single administrative domain; 3) routing information dissemination: using ChronoSync to disseminate routing updates; and 4) multipath routing: a simple way to calculate and rank multiple forwarding options. Although NLSR is designed in the context of a single domain, its design patterns may offer a useful reference for future development of inter-domain routing protocols.

Cohort Profile: Pregnancy And Childhood Epigenetics (PACE) Consortium

Abstract: Author(s): Felix, Janine F; Joubert, Bonnie R; Baccarelli, Andrea A; Sharp, Gemma C; Almqvist, Catarina; Annesi-Maesano, Isabella; Arshad, Hasan; Baiz, Nour; Bakermans-Kranenburg, Marian J; Bakulski, Kelly M; Binder, Elisabeth B; Bouchard, Luigi; Breton, Carrie V; Brunekreef, Bert; Brunst, Kelly J; Burchard, Esteban G; Bustamante, Mariona; Chatzi, Leda; Cheng Munthe-Kaas, Monica; Corpeleijn, Eva; Czamara, Darina; Dabelea, Dana; Davey Smith, George; De Boever, Patrick; Duijts, Liesbeth; Dwyer, Terence; Eng, Celeste; Eskenazi, Brenda; Everson, Todd M; Falahi, Fahimeh; Fallin, M Daniele; Farchi, Sara; Fernandez, Mariana F; Gao, Lu; Gaunt, Tom R; Ghantous, Akram; Gillman, Matthew W; Gonseth, Semira; Grote, Veit; Gruzieva, Olena; Haberg, Siri E; Herceg, Zdenko; Hivert, Marie-France; Holland, Nina; Holloway, John W; Hoyo, Cathrine; Hu, Donglei; Huang, Rae-Chi; Huen, Karen; Jarvelin, Marjo-Riitta; Jima, Dereje D; Just, Allan C; Karagas, Margaret R; Karlsson, Robert; Karmaus, Wilfried; Kechris, Katerina J; Kere, Juha; Kogevinas, Manolis; Koletzko, Berthold; Koppelman, Gerard H; Kupers, Leanne K; Ladd-Acosta, Christine; Lahti, Jari; Lambrechts, Nathalie; Langie, Sabine AS; Lie, Rolv T; Liu, Andrew H; Magnus, Maria C; Magnus, Per; Maguire, Rachel L; Marsit, Carmen J; McArdle, Wendy; Melen, Erik; Melton, Phillip; Murphy, Susan K; Nawrot, Tim S; Nistico, Lorenza; Nohr, Ellen A; Nordlund, Bjorn; Nystad, Wenche; Oh, Sam S; Oken, Emily; Page, Christian M; Perron, Patrice; Pershagen, Goran

Honey-Based Templates in Wound Healing and Tissue Engineering.

Abstract: Over the past few decades, there has been a resurgence in the clinical use of honey as a topical wound treatment. A plethora of in vitro and in vivo evidence supports this resurgence, demonstrating that honey debrides wounds, kills bacteria, penetrates biofilm, lowers wound pH, reduces chronic inflammation, and promotes fibroblast infiltration, among other beneficial qualities. Given these results, it is clear that honey has a potential role in the field of tissue engineering and regeneration. Researchers have incorporated honey into tissue engineering templates, including electrospun meshes, cryogels, and hydrogels, with varying degrees of success. This review details the current state of the field, including challenges which have yet to be overcome, and makes recommendations for the direction of future research in order to develop effective tissue regeneration therapies.

The rate of telomere loss is related to maximum lifespan in birds

Abstract: Telomeres are highly conserved regions of DNA that protect the ends of linear chromosomes. The loss of telomeres can signal an irreversible change to a cell's state, including cellular senescence. Senescent cells no longer divide and can damage nearby healthy cells, thus potentially placing them at the crossroads of cancer and ageing. While the epidemiology, cellular and molecular biology of telomeres are well studied, a newer field exploring telomere biology in the context of ecology and evolution is just emerging. With work to date focusing on how telomere shortening relates to individual mortality, less is known about how telomeres relate to ageing rates across species. Here, we investigated telomere length in cross-sectional samples from 19 bird species to determine how rates of telomere loss relate to interspecific variation in maximum lifespan. We found that bird species with longer lifespans lose fewer telomeric repeats each year compared with species with shorter lifespans. In addition, phylogenetic analysis revealed that the rate of telomere loss is evolutionarily conserved within bird families. This suggests that the physiological causes of telomere shortening, or the ability to maintain telomeres, are features that may be responsible for, or co-evolved with, different lifespans observed across species.This article is part of the theme issue 'Understanding diversity in telomere dynamics'.