Age Estimation Research Articles

Holocene evolution of the buried tidal sand body in the North Jiangsu Plain of China revealed by luminescence dating

In the northern Jiangsu coastal zone of China, the buried tidal sand body (BTSB) is suggested to share a similar origin with the offshore radial sand ridge system in the southwestern Yellow Sea. However, its chronological framework remains inadequately understood. This study conducted optically stimulated luminescence (OSL) dating of both silt- and sand-sized quartz on core LDC from the southwestern end of the BTSB. Together with data from the previously studied core XYK closer to the current coastline, this study aims to clarify the chronology of the BTSB and refine its evolution history. The results indicate that in both cores, sand-sized quartz provides more reliable age estimates than silt-sized quartz for the sandy sediment layers. Additionally, the discrepancy between ages derived from the single-grain central age model and the minimum age model is smaller within the top 11 m of the core, which was deposited over the last 0.9 ka. This period corresponds well with the southern migration of the Yellow River and its sediment discharge into the Yellow Sea from 1128 to 1855 CE. It suggests that distinct sediment sources from the Yellow and Yangtze Rivers may account for the observed differences in OSL characteristics. The OSL ages reveal significant temporal variations in sedimentation rates during the Holocene, with the most rapid deposition occurring between 1.2–0.4 ka and 10–8 ka in core LDC, and between 2–1 ka in core XYK. Together with dating results from the central part of the BTSB, it reveals complex spatiotemporal variations in sediment accumulation and emphasizes the need for detailed sediment sampling and dating to fully elucidate the evolutionary history of the coastal plain.

Comparative Analysis of Dental Age Estimation: A Systematic Review and Meta-analysis Assessing Gender-Specific Accuracy of the Demirjian and Nolla Methods Across Different Age Groups

Comparative Analysis of Dental Age Estimation: A Systematic Review and Meta-analysis Assessing Gender-Specific Accuracy of the Demirjian and Nolla Methods Across Different Age Groups

Perceived age estimation from facial image and demographic data in young and middle-aged South Korean adults

Biological age is an indicator of whether an individual is experiencing rapid, slowing, or normal aging. Perceived age is highly correlated with biological age, which reflects health appraisal and is often used as a clinical marker of aging. Perceived age has been reported as an important indicator of biological age and general health status, not only in older adult populations but also in young and middle-aged adults. However, there is a lack of objective methods for quantifying perceived age in these younger age groups. Thus, this study aimed to propose a novel perceived age estimation algorithm to meet the need for an objective method to predict perceived age. This cross-sectional study included 609 healthy men and 1388 healthy women (29.02–57.91 years, average 44.4 years) from 2017 to 2019 using data from the Korean Medicine Daejeon Citizen Cohort Study. The proposed algorithm comprised two steps. First, the initial predicted perceived age was estimated from facial images using a convolutional neural network (CNN) ensemble model. Then, the final perceived age was estimated using regression from the chronological age, sex, BMI, and initial predicted perceived age obtained in the first step. Better performance results were obtained by model averaging and model stacking generated from various basic regression models. The averaging models of Lasso, XGBoost, and CatBoost showed a mean absolute error of 2.2944, indicating that this algorithm can be used as a screening method for general health status in the population.

Age estimation based on sternebral fusion in a sample of Egyptian population using three-dimensional computed tomography scanning

ObjectivesAge estimation is a critical medico-legal issue in forensic medicine and sternebral fusion is recently supposed to be a helpful tool. Multidetector computed tomography (MDCT) scanning could provide three-dimensional (3D) imaging of the sternebral fusion. This study aimed to develop age estimation models based on the sternebral fusion state using MDCT scanning in a sample of Egyptians. Material and MethodsThe study included thoracic MDCT images of 261 Egyptians. The stage of sternebral fusion was evaluated in the 3D reconstructed images generated using Vitrea® software. Fusion between sternebrae 1&2, sternebrae 2&3, and sternebrae 3&4 were staged as non-fusion, partial fusion, and complete fusion. Scores 1, 2, and 3 were given to the three stages, respectively and their sum was the total sternebral fusion score. ResultsSignificant positive correlations were observed between all sternebral fusions and the participants’ chronological age. Stages of sternebral fusion significantly contributed to age estimation using simple and multiple linear regression models (P < 0.001 for each). Using calibration curves, the total sternebral fusion score and the multivariate models had the best performance to predict the chronological age. At cut-off > 6, total sternebral fusion score was an excellent predictor for the age of 18 with areas under the curve = 0.943 and 0.952, in females and males respectively. ConclusionThe developed models based on sternebral fusion stages can be used for forensic age estimation in the studied Egyptian sample. A total sternebral fusion score > 6 efficiently distinguished those aged 18 years.

Prevalence and incidence of multiple sclerosis in the Netherlands

BackgroundThe rising prevalence estimates of multiple sclerosis (MS) globally underscore the imperative for up-to-date epidemiological data specific to the Netherlands. MethodsData from two Dutch healthcare databases (Nivel Primary Care Database and Vektis Database) comprising both general practices and hospital electronic health records in 2019 were combined to assess age- and sex-standardized MS prevalence and incidence estimates. Differences in prevalence estimates based on latitude and between primary versus secondary care records were examined. ResultsThe age and sex-standardized prevalence estimate was 210.4 per 100,000 inhabitants. Incidence estimate of MS was 7.1 per 100,000 person-years within the year 2019. One-third of the MS cohort from primary care records was not documented in the hospital database over two consecutive years. Prevalence estimates were higher in northern areas versus southern areas (respectively 240.6 versus 208.3 per 100,000 inhabitants). ConclusionAligning results from different global regions, prevalence estimates of MS in the Netherlands have increased significantly over the last decennia, while incidence estimates are stable. The discrepancy between MS records within the primary and secondary care setting could indicate that a substantial proportion of Dutch patients with MS are not under specialized neurological care.

Zoomies: A Tool to Infer Stellar Age from Vertical Action in Gaia Data

Stellar age measurements are fundamental to understanding a wide range of astronomical processes, including Galactic dynamics, stellar evolution, and planetary system formation. However, extracting age information from main-sequence stars is complicated, with techniques often relying on age proxies in the absence of direct measurements. The Gaia data releases have enabled detailed studies of the dynamical properties of stars within the Milky Way, offering new opportunities to understand the relationship between stellar age and dynamics. In this study, we leverage high-precision astrometric data from Gaia DR3 to construct a stellar age prediction model based only on stellar dynamical properties, namely the vertical action. We calibrate two distinct, hierarchical stellar age–vertical action relations, first employing asteroseismic ages for red-giant-branch stars, then isochrone ages for main-sequence turn-off stars. We describe a framework called zoomies based on this calibration, by which we can infer ages for any star given its vertical action. This tool is open-source and intended for community use. We compare dynamical age estimates from zoomies with age measurements from open clusters and asteroseismology. We use zoomies to generate and compare dynamical age estimates for stars from the Kepler, K2, and TESS exoplanet transit surveys. While dynamical age relations are associated with large uncertainty, they are generally mass independent and depend on homogeneously measured astrometric data. These age predictions are uniquely useful for large-scale demographic investigations, especially in disentangling the relationship between planet occurrence, metallicity, and age for low-mass stars.

Field validation of post-mortem interval estimation based on insect development. Part 2: Pre-appearance interval, expert evidence selection and accuracy baseline data

This is the second part of the results from the field experiment aimed at validating PMI estimation based on insect evidence. First, we investigated the accuracy gains of PMI after supplementing age estimates with PAI. Second, we compared the impact on PMI of various ways, in which an expert selects insect evidence for the estimation. Third, we provided baseline data regarding the accuracy of PMI as estimated using different methods, insect species and life stages. Insects were sampled from nine pig carcasses exposed in a forest habitat, one carcass every one or two months, with 8–11 samples taken from each carcass using standard techniques. It was found that insect age alone clearly underestimates the true PMI across insect species and life stages. When age estimates were supplemented with PAI, the estimated PMI became generally significantly closer to the true PMI. Averaging PMI across multiple different pieces of evidence yielded more accurate estimates than using single evidence. The best single evidence method tested in this study, i.e. the use of the oldest evidence from the latest colonizing species, yielded the average PMI errors of about 22 % or 25 % (depending on the type of PAI used). For the best multiple evidence method, i.e. averaging PMI for late life stages of early colonizing species and early life stages of late colonizing species, these errors were about 13 % and 16 %. PMI ranges derived using 30 % error rate covered a true PMI in 95 % of cases but only for the best multiple evidence methods. These results demonstrate that the compound entomological method for estimating PMI (including age and PAI estimates), when applied to mock human death cases, is satisfactorily accurate. Moreover, the present findings highlight the importance of PAI and the great benefits of using multiple insect evidence to estimate PMI.

OMEGACat. IV. Constraining the Ages of Omega Centauri Subgiant Branch Stars with HST and MUSE

We present age estimates for over 8100 subgiant branch (SGB) stars in Omega Centauri (ω Cen) to study its star formation history. Our large data set, which combines multi-wavelength Hubble Space Telescope photometry with MUSE metallicities, provides an unprecedented opportunity to measure individual stellar ages. We do this by fitting each star’s photometry and metallicity with theoretical isochrones that are embedded with an empirical [C + N + O]–[Fe/H] relation specific to ω Cen. The bulk of the stars have ages between 13 and 10 Gyr, with the mean stellar age being 12.08 ± 0.01 Gyr and the median age uncertainty being 0.68 Gyr. From these ages we construct the most complete age–metallicity relation for ω Cen to date. We find that the mean age of stars decreases with increasing metallicity and find two distinct streams in the age–metallicity plane, hinting at different star formation pathways. We derive an intrinsic spread in the ages of 0.75 ± 0.01 Gyr for the whole cluster, with the age spread showing a clear increase with metallicity. We verify the robustness of our age estimations by varying isochrone parameters and constraining our systematics. We find the C + N + O relation to be the most critical consideration for constraining the age–metallicity relation. We also present an SGB chromosome map with age information. In the future these stellar ages could be combined with chemical abundances to study age differences in subpopulations and uncover the chemical evolution history of this massive nuclear star cluster.

Metabolic Status Modulates Global and Local Brain Age Estimates in Overweight and Obese Adults

BackgroundAs people live longer, maintaining brain health becomes essential for extending healthspan and preserving independence. Brain degeneration and cognitive decline are major contributors to disability. This study investigates how metabolic health influences brain-age-gap-estimate (brainAGE), which measures the difference between neuroimaging-predicted brain age and chronological age. MethodsK-means clustering was applied to fasting metabolic markers including insulin, glucose, leptin, cortisol, triglycerides, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol, steady-state-plasma glucose and of body mass index of 114 physically and cognitively healthy adults. The Homeostatic Model Assessment for Insulin Resistance served as a reference. T1-weighted brain MRIs were used to calculate voxel-level and global (G-brainAGE). Longitudinal data were available for 53 participants over a 3-year interval. ResultsK-mean clustering divided the sample into two groups: those with favorable (N=56) and suboptimal metabolic health (N=58). The suboptimal group showed signs of insulin resistance and dyslipidemia (PFDR<0.05) and had older G-brainAGE and L-brainAGE, with deviations most prominent in cerebellar, ventromedial prefrontal, and medial temporal regions (PFWE<0.05). Longitudinal analysis revealed group differences but no significant time or interaction effects on brainAGE measures. ConclusionsSuboptimal metabolic status is linked to accelerated brain aging, particularly in brain regions rich in insulin receptors. These findings highlight the importance of metabolic health in maintaining brain function and suggest that promoting metabolic well-being may help extend healthspan.

Accuracy of fetal kidney length and transcerebellar diameter in assessment of gestational age in normal and growth restricted fetuses

Background: Accurate monitoring of fetal gestational age is one of the most critical components of prenatal care. Aim: This study intends to determine the accuracy of fetal gestational age estimation using mean fetal kidney length and transcerebellar diameter and comparing their efficacy with other biometric measurements in normal and growth restricted fetuses. Subjects and Methods: Our prospective study was conducted on 251 pregnant women seeking for routine ultrasound examination during the second half of pregnancy at Al-Hussein and Al-Zaharaa university hospitals starting from November 2021 till November 2022 and the following fetal biometric parameters were measured transabdominally during each ultrasound examination including the transcerebellar diameter (TCD), fetal kidney length (FKL), biparietal diameter (BPD), head circumferences (HC), abdominal circumferences (AC) and femur length (FL). Results: The FKL and TCD in the present study correlated well with the assigned GA. The relationship of fetal kidney growth and TCD with GA is statistically significant. The present study hence validates the recommendation that FKL and TCD can be used as an important sonographic parameter for accurate prediction of fetal gestation age especially in IUGR fetuses. Conclusion: Fetal kidney length and TCD are accurate parameters for assessment of gestational age in 2nd half of normal pregnancy. In addition, fetal kidney length and TCD are highly accurate for detection of gestation age in IUGR suspected pregnancies.

Testing the Phenomenological Interacting Dark Energy Model with Gamma-Ray Bursts and Pantheon+ type Ia Supernovae

In this paper, we utilize recent observational data from gamma-ray bursts (GRBs) and Pantheon+ supernovae Ia (SNe Ia) samples to explore the interacting dark energy (IDE) model in a phenomenological scenario. Results from GRBs alone, SNe Ia and GRBs+SNe Ia indicate that the energy is transferred from dark energy to dark matter and the coincidence problem is alleviated. The value of H 0 from GRBs+SNe Ia in the IDE scenario shows agreement with the SH0ES measurement. Considering the age estimate of the quasar APM 08279+5255 at z = 3.91, we find that the phenomenological IDE scenario can predict a cosmic age greater than that of the ΛCDM model, thus the cosmic age problem can be alleviated.

Dual-Stream Enhanced Deep Network for Transmission Near-Infrared Dorsal Hand Vein Age Estimation with Attention Mechanisms

Dorsal hand vein recognition, with unique stable and reliable advantages, has attracted considerable attention from numerous researchers. In this case, the dorsal hand vein images captured by the means of transmission infrared imaging are clearer than those collected by other infrared methods, enabling it to be more suitable for the biometric applications. However, less attention is paid to individual age estimation based on dorsal hand veins. To this end, this paper proposes an efficient dorsal hand vein age estimation model using a deep neural network with attention mechanisms. Specifically, a convolutional neural network (CNN) is developed to extract the expressive features for age estimation. Simultaneously, another deep residual network is leveraged to strengthen the representation ability on subtle dorsal vein textures. Moreover, variable activation functions and pooling layers are integrated into the respective streams to enhance the nonlinearity modeling of the dual-stream model. Finally, a dynamic attention mechanism module is embedded into the dual-stream network to achieve multi-modal collaborative enhancement, guiding the model to concentrate on salient age-specific features. To evaluate the performance of dorsal hand vein age estimation, this work collects dorsal hand vein images using the transmission near-infrared spectrum from 300 individuals across various age groups. The experimental results show that the dual-stream enhanced network with the attention mechanism significantly improves the accuracy of dorsal hand vein age estimation in comparison with other deep learning approaches, indicating the potential of using near-infrared dorsal hand vein imaging and deep learning technology for efficient human age estimation.

Fetal Growth Restriction: A Pragmatic Approach.

An accurate diagnosis of fetal growth restriction relies on a precise estimation of gestational age based on a carefully obtained history as well as early ultrasound, since a difference of just a few days can lead to a significant error. There is a continuum of risk for adverse outcome that depends on the certainty of dates and presence or absence of comorbidities, in addition to the estimated fetal weight percentile and the umbilical artery waveform. The results of several studies, most notably the TRUFFLE trial, demonstrate that optimal management of fetal growth restriction with an abnormal umbilical artery waveform requires daily electronic fetal heart rate monitoring, and this monitoring does not require computerized interpretation. The role of ductus venosus waveform, biophysical profile, and middle cerebral artery waveform is less clear, and the results of these three modalities should be interpreted with caution.

Quick-reference criteria for identifying multivariate cognitive change in older adults with mild cognitive impairment and dementia: An ADNI study.

To establish quick-reference criteria regarding the frequency of statistically rare changes in seven neuropsychological measures administered to older adults. Data from 935 older adults examined over a two-year interval were obtained from the Alzheimer's Disease Neuroimaging Initiative. The sample included 401 cognitively normal older adults whose scores were used to determine the natural distribution of change scores for seven cognitive measures and to set change score thresholds corresponding to the 5th percentile. The number of test scores that exceeded these thresholds were counted for the cognitively normal group, as well as 381 individuals with mild cognitive impairment (MCI) and 153 individuals with dementia. Regression analyses examined whether the number of change scores predicted diagnostic group membership beyond demographic covariates. Only 4.2% of cognitively normal participants obtained two or more change scores that fell below the 5th percentile of change scores, compared to 10.6% of the stable MCI participants and 38.6% of those who converted to dementia. After adjusting for age, gender, race/ethnicity, and premorbid estimates, the number of change scores below the 5th percentile significantly predicted diagnostic group membership. It was uncommon for older adults to have two or more change scores fall below the 5th percentile thresholds in a seven-test battery. Higher change counts may identify those showing atypical cognitive decline.

Proteomic Markers of Aging and Longevity: A Systematic Review

This article provides a systematic review of research conducted on the proteomic composition of blood as part of a complex biological age estimation. We performed a comprehensive analysis of 17 publicly available datasets and compiled an integral list of proteins. These proteins were sorted based on their detection probability using mass spectrometry in human plasma. We propose this list as a basis for creating a panel of peptides and quantifying the content of selected proteins in the format of a proteomic aging clock. The selected proteins are especially notable for their roles in inflammatory processes and lipid metabolism. Our findings suggest, for the first time, that proteins associated with systemic disorders, including those approved by the FDA for clinical use, could serve as potential markers of aging.

The Who’s, What’s, and “Y”s: Y Sex Chromosome Loss and Methylation for Analysis in Male Aging and Mortality and Forensic Science Applications

The Y chromosome plays a crucial role in understanding the overall landscape of male health. Incorporating the Y chromosome into genomic and epigenomic research may elucidate the male-specific mechanisms behind aging and the pathogenesis of certain conditions, both acute and chronic. Present epigenetic research focuses on the effects of modifications like methylation on autosomal chromosomes. However, little research has been conducted to further these investigations in sex chromosomes, especially the Y chromosome. Epigenetic analyses can identify age-associated CpG sites that may offer potential biomarkers for age estimation and disease risk assessment, among others. This review emphasizes interdisciplinary efforts that have been made in the construction of an assembly and the application of “epigenetic clocks” to the Y chromosome. The studies reviewed here examined the effects of aging on genes such as NLGN4Y, DDX3Y, and TBL1Y, and on male-specific health disparities and disease etiologies, as well as the potential for the use of these genes to assess the diagnostic and age algorithmic potential of Y-specific genes.

Estimation of physiological aging based on routine clinical biomarkers: a prospective cohort study in elderly Chinese and the UK Biobank

BackgroundChronological age (CA) does not reflect individual variation in the aging process. However, existing biological age predictors are mostly based on European populations and overlook the widespread nonlinear effects of clinical biomarkers.MethodsUsing data from the prospective Dongfeng-Tongji (DFTJ) cohort of elderly Chinese, we propose a physiological aging index (PAI) based on 36 routine clinical biomarkers to measure aging progress. We first determined the optimal level of each biomarker by restricted cubic spline Cox models. For biomarkers with a U-shaped relationship with mortality, we derived new variables to model their distinct effects below and above the optimal levels. We defined PAI as a weighted sum of variables predictive of mortality selected by a LASSO Cox model. To measure aging acceleration, we defined ΔPAI as the residual of PAI after regressing on CA. We evaluated the predictive value of ΔPAI on cardiovascular diseases (CVD) in the DFTJ cohort, as well as nine major chronic diseases in the UK Biobank (UKB).ResultsIn the DFTJ training set (n = 12,769, median follow-up: 10.38 years), we identified 25 biomarkers with significant nonlinear associations with mortality, of which 11 showed insignificant linear associations. By incorporating nonlinear effects, we selected CA and 17 clinical biomarkers to calculate PAI. In the DFTJ testing set (n = 15,904, 5.87 years), PAI predict mortality with a concordance index (C-index) of 0.816 (95% confidence interval, [0.796, 0.837]), better than CA (C-index = 0.771 [0.755, 0.788]) and PhenoAge (0.799 [0.784, 0.814]). ΔPAI was predictive of incident CVD and its subtypes, independent of traditional risk factors. In the external validation set of UKB (n = 296,931, 12.80 years), PAI achieved a C-index of 0.749 (0.746, 0.752) to predict mortality, remaining better than CA (0.706 [0.702, 0.709]) and PhenoAge (0.743 [0.739, 0.746]). In both DFTJ and UKB, PAI calibrated better than PhenoAge when comparing the predicted and observed survival probabilities. Furthermore, ΔPAI outperformed any single biomarker to predict incident risks of eight age-related chronic diseases.ConclusionsOur results highlight the potential of PAI and ΔPAI as integrative biomarkers to evaluate aging acceleration and facilitate the development of targeted intervention strategies for healthy aging.

Technical variability across the 450K, EPICv1, and EPICv2 DNA methylation arrays: lessons learned for clinical and longitudinal studies

DNA methylation (DNAm) is the most commonly measured epigenetic mechanism in human populations, with most studies using Illumina arrays to assess DNAm levels. In 2023, Illumina updated their DNAm arrays to the EPIC version 2 (EPICv2), building on prior iterations, namely the EPIC version 1 (EPICv1) and 450K arrays. Whether DNAm measurements are stable across these three generations of arrays has yet not been investigated, limiting the ability of researchers—especially those with longitudinal data—to compare and replicate results across arrays. Here, we present results from a study of 30 child participants (15 male; 15 female) from the Drakenstein Child Health Study, who had DNAm measured on all three of the latest arrays: 450K, EPICv1, and EPICv2. Using these data, we created an annotation of probe quality across arrays, which includes the intraclass correlations, interquartile ranges, correlations, and array bias (i.e., the extent to which DNAm levels were explained by array type) of all CpGs. We also present results from an analysis of sex differences, where we found that CpGs with lower replicability across arrays had higher array-based variance, suggesting this variance metric help guide replication efforts. We also showed that epigenetic age estimates across arrays were more stable when using the principal component versions of epigenetic clocks. Ultimately, this collection of results provides a framework for investigating the replicability and longitudinal stability of epigenetic changes across multiple versions of Illumina DNAm arrays.

Comparison of accuracy of different dental age estimation methods in Finnish and Turkish populations.

The aims of this study were to assess the accuracy of Cameriere's and Demirjian's methods in Finnish children, and compare the findings with those of the Turkish children according to dental age. Dental panoramic tomography (DPT) of children (482 Finnish, 423 Turkish) aged between 5 and 15 years were evaluated. Comparison of mean difference between estimated and chronological age was evaluated. The difference between two means was analysed using paired t-test at 95% confidence interval (CI). Pearson correlation coefficients were used to estimate the correlation between chronological and estimated ages. Results: Demirjian's method resulted in overestimation in all age groups except for 8-year-old girls. Dental age, however, was found to be underestimated with Cameriere's method in all age groups but 6-year-old girls and boys. In Northern Finnish children, Demirjian's method was more suitable for boys while Cameriere's method led to better estimation in girls. When comparing Finnish and Turkish children, differences between dental ages and chronological ages differed significantly in 10-year-old boys and 8-year-old girls with both methods. Conclusion: Dental age of Turkish children seems higher than that of Finnish children. There is a significant difference between chronological and dental ages in both populations assessed by both methods.

Ecological analysis of the structure and dendrometric characteristics of the population of Juniperus thurifera: a vulnerable species

ABSTRACT Juniperus thurifera was selected for this study due to its crucial ecological role in high mountain ecosystems and the increasing threats it faces, such as habitat degradation and regeneration challenges. The analysis of stand structure by altitude shows that the distribution of individuals and stem count vary with elevation, highlighting the species’ adaptability to mountainous conditions. Altitudinal degradation significantly impacts seed production, with a positive correlation (r = 0.65) between stem and fruit numbers in females. J. thurifera also plays a vital role in soil retention, as indicated by the positive correlation (r = 0.511) between ground projection and soil thickness, emphasizing its importance in slope stabilization and erosion prevention. Sexual dimorphism reveals dendrometric differences between males and females, affecting regeneration and reproduction. Age estimation based on circumference shows the predominance of aging, non-reproductive trees, threatening future regeneration. Principal component analysis (PCA) further refines recommendations by revealing complex relationships between dendrometric characteristics and environmental factors, providing precise guidelines for J. thurifera conservation.