Chronological Age Research Articles

The implications of frailty in older adults with epilepsy.

Older adults constitute a large proportion of people with epilepsy (PWE) due to the changing demographics worldwide and epilepsy's natural history. Aging-related pathophysiological changes lower the tolerance and increase our vulnerability to stressors, which manifests as frailty. Frailty is closely associated with adverse health outcomes. This narrative review examines the interplay between frailty and epilepsy, especially in older adults, emphasizing its clinical implications, including its role in managing PWE. Mechanistically, frailty develops through complex interactions among molecular and cellular damage, including genomic instability, mitochondrial dysfunction, and hormonal changes. These contribute to systemic muscle mass, bone density, and organ function decline. The concept of frailty has evolved from a primarily physical syndrome to include social, psychological, and cognitive dimensions. The "phenotypic frailty" model, which focuses on physical performance, and the "deficit accumulation" model, which quantifies health deficits, provide frameworks for understanding and assessing frailty. PWE are potentially more prone to developing frailty due to a higher prevalence of risk factors predisposing to frailty. These include, but are not limited to, polypharmacy, higher comorbidity, low exercise level, social isolation, low vitamin D, and osteoporosis. We lack commercial biomarkers to measure frailty but can diagnose it using self- or healthcare provider-administered frailty scales. Recent attempts to develop a PWE-specific frailty scale are promising. Unlike chronological age, frailty is reversible, so its management using multidisciplinary care teams should be strongly considered. Frailty can affect antiseizure medication (ASM) tolerance secondary to its impact on pharmacokinetics and pharmacodynamics. While frailty's effect on seizure control efficacy of ASM is poorly understood, its undoubted association with overall poor outcomes, including epilepsy surgery, behooves us to consider its presence and implication while treating older PWE. Incorporation of frailty measures in future research is essential to improve our understanding of frailty's role in PWE health. PLAIN LANGUAGE SUMMARY: Frailty is the declining state of the human body. People with epilepsy are more prone to it. It should be factored into their management.

Exploring the potential of epigenetic clocks in aging research

The process of aging is a notable risk factor for numerous age-related illnesses. Hence, a reliable technique for evaluating biological age or the pace of aging is crucial for understanding the aging process and its influence on the progression of disease. Epigenetic alterations are recognized as a prominent biomarker of aging, and epigenetic clocks formulated on this basis have been shown to provide precise estimations of chronological age. Extensive research has validated the effectiveness of epigenetic clocks in determining aging rates, identifying risk factors for aging, evaluating the impact of anti-aging interventions, and predicting the emergence of age-related diseases. This review provides a detailed overview of the theoretical principles underlying the development of epigenetic clocks and their utility in aging research. Furthermore, it explores the existing obstacles and possibilities linked to epigenetic clocks and proposes potential avenues for future studies in this field.

Uncertainty quantification in epigenetic clocks via conformalized quantile regression.

DNA methylation (DNAm) is a chemical modification of DNA that can be influenced by various factors, including age, environment, and lifestyle. An epigenetic clock is a predictive tool that measures biological age based on DNAm levels. It can provide insights into an individual's biological age, which may differ from their chronological age. This difference, known as the epigenetic age acceleration, may indicate the state of one's health and risk for age-related diseases. Moreover, epigenetic clocks are used in studies of aging to assess the effectiveness of anti-aging interventions and to understand the underlying mechanisms of aging and disease. Various epigenetic clocks have been developed using samples from different populations, tissues, and cell types, typically by training high-dimensional linear regression models with an elastic net penalty. While these models can predict mean biological age with high precision, there is a lack of uncertainty quantification which is important for interpreting the precision of age estimations and for clinical decision-making. To understand the distribution of a biological age clock beyond its mean, we propose a general pipeline for training epigenetic clocks, based on an integration of high-dimensional quantile regression and conformal prediction, to effectively reveal population heterogeneity and construct prediction intervals. Our approach produces adaptive prediction intervals not only achieving nominal coverage but also accounting for the inherent variability across individuals. By using the data collected from 728 blood samples in 11 DNAm datasets from children, we find that our quantile regression-based prediction intervals are narrower than those derived from conventional mean regression-based epigenetic clocks. This observation demonstrates an improved statistical efficiency over the existing pipeline for training epigenetic clocks. In addition, the resulting intervals have a synchronized varying pattern to age acceleration, effectively revealing cellular evolutionary heterogeneity in age patterns in different developmental stages during individual childhoods and adolescent cohort. Our findings suggest that conformalized high-dimensional quantile regression can produce valid prediction intervals and uncover underlying population heterogeneity. Although our methodology focuses on the distribution of aging in children, it is applicable to a broader range of populations to improve understanding of epigenetic age beyond the mean. This inference-based toolbox could provide valuable insights for future applications of epigenetic interventions for age-related diseases.

A comprehensive map of the aging blood methylome in humans

BackgroundDuring aging, the human methylome undergoes both differential and variable shifts, accompanied by increased entropy. The distinction between variably methylated positions (VMPs) and differentially methylated positions (DMPs), their contribution to epigenetic age, and the role of cell type heterogeneity remain unclear.ResultsWe conduct a comprehensive analysis of > 32,000 human blood methylomes from 56 datasets (age range = 6–101 years). We find a significant proportion of the blood methylome that is differentially methylated with age (48% DMPs; FDR < 0.005) and variably methylated with age (37% VMPs; FDR < 0.005), with considerable overlap between the two groups (59% of DMPs are VMPs). Bivalent and Polycomb regions become increasingly methylated and divergent between individuals, while quiescent regions lose methylation more uniformly. Both chronological and biological clocks, but not pace-of-aging clocks, show a strong enrichment for CpGs undergoing both mean and variance changes during aging. The accumulation of DMPs shifting towards a methylation fraction of 50% drives the increase in entropy, smoothening the epigenetic landscape. However, approximately a quarter of DMPs exhibit anti-entropic effects, opposing this direction of change. While changes in cell type composition minimally affect DMPs, VMPs and entropy measurements are moderately sensitive to such alterations.ConclusionThis study represents the largest investigation to date of genome-wide DNA methylation changes and aging in a single tissue, providing valuable insights into primary molecular changes relevant to chronological and biological aging.

Artificial intelligence estimated electrocardiographic age as a recurrence predictor after atrial fibrillation catheter ablation

The application of artificial intelligence (AI) algorithms to 12-lead electrocardiogram (ECG) provides promising age prediction models. We explored whether the gap between the pre-procedural AI-ECG age and chronological age can predict atrial fibrillation (AF) recurrence after catheter ablation. We validated a pre-trained residual network-based model for age prediction on four multinational datasets. Then we estimated AI-ECG age using a pre-procedural sinus rhythm ECG among individuals on anti-arrhythmic drugs who underwent de-novo AF catheter ablation from two independent AF ablation cohorts. We categorized the AI-ECG age gap based on the mean absolute error of the AI-ECG age gap obtained from four model validation datasets; aged-ECG (≥10 years) and normal ECG age (<10 years) groups. In the two AF ablation cohorts, aged-ECG was associated with a significantly increased risk of AF recurrence compared to the normal ECG age group. These associations were independent of chronological age or left atrial diameter. In summary, a pre-procedural AI-ECG age has a prognostic value for AF recurrence after catheter ablation.

Gene Age Gap Estimate (GAGE) for major depressive disorder: a penalized biological age model using gene expression.

Recent associations between Major Depressive Disorder (MDD) and measures of premature aging suggest accelerated biological aging as a potential biomarker for MDD susceptibility or MDD as a risk factor for age-related diseases. Statistical and machine learning regression models of biological age have been trained on various sources of high dimensional data to predict chronological age. Residuals or "gaps" between the predicted biological age and chronological age have been used for statistical inference, such as testing whether an increased age gap is associated with a given disease state. Recently, a gene expression-based model of biological age showed a higher age gap for individuals with MDD compared to healthy controls (HC). In the current study, we propose a machine learning approach that simplifies gene selection by using a least absolute shrinkage and selection operator (LASSO) penalty to construct an expression-based Gene Age Gap Estimate (GAGE) model. We construct the LASSO-GAGE (L-GAGE) model in an RNA-Seq study of 78 unmedicated individuals with MDD and 79 HC and then test for accelerated biological aging in MDD. When testing L-GAGE association with MDD, we account for factors such as sex and chronological age to mitigate regression to the mean effects. The L-GAGE shows higher biological aging in MDD subjects than HC, but the elevation is not statistically significant. However, when we dichotomize chronological age, the interaction between MDD status and age is significant in L-GAGE model. This effect remains statistically significant even after adjusting for chronological age and sex. We find cytomegalovirus (CMV) serostatus is associated with elevated L-GAGE. We also investigate feature selection methods Random Forest and nearest neighbor projected distance regression (NPDR) to characterize age related genes, and we find functional enrichment of infectious disease and SARS-COV pathways.

Frailty in Persons with Down Syndrome: Results from the REVIVIS Study

ObjectivesTo determine frailty prevalence and identify possible nonclinical factors associated with this condition in community-dwelling individuals with Down syndrome (DS). DesignCross-sectional analysis of the registry study REVIVIS, a single-center, prospective study on the geriatric management of persons with DS. Setting and ParticipantsIndividuals with DS (n = 139) referred to a geriatric clinic. MethodsFrailty was assessed through a 38-item Frailty Index (FI). A multivariable linear regression model was performed to assess the relationship between frailty and different variables of interest: age, number of prescribed drugs, and employment status (unemployed vs employed). ResultsAmong 139 subjects (54.5% male), mean (SD) aged 42.9 (6.9) years, the median (interquartile range) FI was 0.24 (0.16-0.30) with 60 participants (43.2%) classified as frail. The number of prescribed medications was associated with higher FI levels (P < .001), whereas being employed was associated with lower FI levels (P < .001) compared with being unemployed. No association was found between chronological age and FI. Conclusions and ImplicationsOur findings suggest that chronological age is insufficient to encompass the complexity of a subject with DS, underscoring the importance of a standardized evaluation of the FI among this population. Access to geriatric care might become an important opportunity for people with DS, a population characterized by high vulnerability (or frailty).

Active longevity and aging: dissecting the impacts of physical and sedentary behaviors on longevity and age acceleration.

To examine the associations of physical activity (PA) and sedentary behavior (SB) with longevity and age acceleration (AA) using observational and Mendelian randomization (MR) studies, and quantify the mediating effects of lipids. In Guangzhou Biobank Cohort Study (GBCS), PA and SB were assessed by the Chinese Version of the International Physical Activity Questionnaire. Longevity was defined as participants whose age at follow-up or at death was at or above the 90th age percentile. AA was defined as the residual resulting from a linear model that regressed phenotypic age against chronological age. Linear regression and Poisson regression with robust error variance were used to assess the associations of total and specific PA in different intensities, and SB with AA and longevity, yielding βs or relative risks (RRs) and 95% confidence intervals (CIs). Two-sample MR was conducted to examine the causal effects. Mediation analysis was used to assess the mediating effects of lipids. Of 20,924 participants aged 50 + years in GBCS, during an average follow-up of 15.0years, compared with low PA, moderate and high PA were associated with higher likelihood of longevity (RR (95% CI): 1.56 (1.16, 2.11), 1.66 (1.24, 2.21), respectively), and also cross-sectionally associated with lower AA (β (95% CI): -1.43 (-2.41, -0.45), -2.09 (-3.06, -1.11) years, respectively). Higher levels of moderate PA (MPA) were associated with higher likelihood of longevity and lower AA, whereas vigorous PA (VPA) showed opposite effects. The association of PA with longevity observed in GBCS was mediated by low-density lipoprotein cholesterol (LDL-C) by 8.23% (95% CI: 3.58-39.61%), while the association with AA was mediated through LDL-C, triglycerides and total cholesterol by 5.13% (3.94-7.30%), 7.81% (5.98-11.17%), and 3.37% (2.59-4.80%), respectively. Additionally, in two-sample MR, SB was positively associated with AA (β (95% CI): 1.02 (0.67, 1.36) years). PA showed protective effects on longevity and AA, with the effects being partly mediated through lipids. Conversely, SB had a detrimental impact on AA. MPA was associated with higher likelihood of longevity and reduced AA, whereas VPA showed adverse effects. Our findings reinforce the recommendation of "sit less and move more" to promote healthy longevity, and highlight the potential risks associated with VPA in the elderly.

The association of psychological and trauma-related factors with biological and facial aging acceleration: evidence from the UK Biobank

BackgroundPsychological and trauma-related factors are associated with many diseases and mortality. However, a comprehensive assessment of the association between psycho-trauma exposures and aging acceleration is currently lacking.MethodsUsing data from 332,359 UK Biobank participants, we calculated biological aging acceleration, indexed by the presence of leukocyte telomere length (LTL) deviation (i.e., the difference between genetically determined and observed LTL > 0). The acceleration of facial aging (i.e., looking older than the chronological age) was assessed using a self-report question. Then, we estimated the associations of each psycho-trauma factor with biological and facial aging acceleration, using logistic regression models adjusted for multiple important covariates. Furthermore, restricted to 99,180 participants with complete psychological and trauma-related data, we identified clusters of individuals with distinct psycho-trauma patterns using the latent class analysis method and assessed their associations with aging acceleration using similar models.ResultsWe observed most of the studied psycho-trauma factors were associated with biological and facial aging acceleration. Compared to the “Absence of trauma and psychopathology” cluster, the “adverse childhood experiences (ACEs) with psychopathology” cluster showed strong associations with those aging measurements (odds ratio [OR] = 1.13 [1.05 − 1.23] for biological and 1.52 [1.18 − 1.95] for facial aging acceleration), while no such association was observed for the “ACEs without psychopathology” cluster (1.04 [0.99 − 1.09] and 1.02 [0.84 − 1.24].ConclusionsOur study demonstrated significant associations of psycho-trauma factors with both biological and facial aging acceleration. The differential aging consequences observed among ACEs exposed individuals with and without psychopathology prompt interventions aimed to improve individuals’ psychological resilience to prevent aging acceleration.

A Comparison of Two Methods of Dental Age Estimation in a Population of Saudi Children and Adolescents.

This study aimed to compare and evaluate the accuracy of the Demirjian (DE) and the London Atlas (LAE) dental age estimation methods in a Saudi population sample. This retrospective cross-sectional study used digital radiographs from electronic health records in three different dental institutes. In total, 357 male and 354 female (ages 5-15 years) digital orthopantomograms were selected for age estimation. The mean difference between the chronological age (CA) and age estimation method among males and females was 0.03 ± 0.34 and 0.00 ± 0.34, respectively, for LAE and 0.55 ± 0.84 and 0.76 ± 0.51, respectively, for DE. The mean difference between the LAE and DE methods among males and females was 0.52 ± 0.89 and -0.76 ± 0.57, respectively. No statistically significant difference between CA and LAE was found in either males (p = 0.079) or females (p = 0.872). A statistically significant difference was found between CA and DE in both genders (p < 0.001). A statistically significant difference was found between the LAE and DE groups (p < 0.001) in both genders. An overestimation of dental age was observed with DE compared with that in CA. LAE showed higher accuracy than CA, with no clinically significant difference. Although the difference between the LAE and DE methods was insignificant, the LAE method proved to be more accurate.

Medication Adherence and Health Outcomes: A Public Health Perspective

Medicine is a two-edged sword: while it can treat a patient's illness, when applied carelessly, it also has the potential to do more harm than good. Ensuring that patients receive appropriate medication for their clinical condition at the appropriate time, by the appropriate channel, and in the appropriate doses should be the top priority for any healthcare system. Polypharmacy can be helpful because numerous morbidities are common, but it can also have unintended harmful effects. The co-morbidity-polypharmacy score uses the patient's physiological age rather than their chronological age to predict how their therapy will turn out. Any departure from the medication's intended therapeutic impact may be regarded as a drug-related issue. The purpose of this study was to examine the effects of clinical pharmacist interventions on drug-related issues in prescriptions for polypharmacy as well as the cost-benefit analysis of clinical pharmacy services. The particular goals were to recognise and address drug-related issues, find out how well health care providers received clinical pharmacist interventions, analyse the cost-benefit of clinical pharmacy services, and create and suggest a clinical pharmacists intervention form to standardise and record drug-related issues.

Artificial intelligence age prediction using electrocardiogram data: Exploring biological age differences

BackgroundBiological age can be predicted using artificial intelligence (AI) trained on electrocardiograms (ECGs), which is prognostic for mortality and cardiovascular events. ObjectiveWe developed an AI model to predict age from an ECG and compared baseline characteristics to identify determinants of advanced biological age. MethodsAn AI model was trained on ECGs from cardiology inpatients aged 20–90 years. AI analysis used a convolutional neural network with data divided in an 80:20 ratio (development/internal validation), with external validation undertaken using data from the UK Biobank. Performance and subgroup comparison measures included correlation, difference, and mean absolute difference. ResultsA total of 63,246 patients with 353,704 total ECGs were included. In internal validation, the correlation coefficient was 0.72, with a mean absolute difference between chronological age and AI-predicted age of 9.1 years. The same model performed similarly in external validation. In patients aged 20–29 years, AI-ECG biological age was greater than chronological age by a mean of 14.3 ± 0.2 years. In patients aged 80–89 years, biological age was lower by a mean of 10.5 ± 0.1 years. Women were biologically younger than men by a mean of 10.7 months (P = .023), and patients with a single ECG were biologically 1.0 years younger than those with multiple ECGs (P < .0001). ConclusionThere are significant between-group differences in AI-ECG biological age for patient subgroups. Biological age was greater than chronological age in young hospitalized patients and lower than chronological age in older hospitalized patients. Women and patients with a single ECG recorded were biologically younger than men and patients with multiple recorded ECGs.

Biological Age, Chronological Age, and Survival in Pulmonary Fibrosis: A Causal Mediation Analysis.

Rationale: Accelerated biological aging has been implicated in the development of interstitial lung disease (ILD) and other diseases of aging but remains poorly understood. Objectives: To identify plasma proteins that mediate the relationship between chronological age and survival association in patients with ILD. Methods: Causal mediation analysis was performed to identify plasma proteins that mediated the chronological age-survival relationship in an idiopathic pulmonary fibrosis discovery cohort. Proteins mediating this relationship after adjustment for false discovery were advanced for testing in an independent ILD validation cohort and explored in a chronic obstructive pulmonary disease cohort. A proteomic-based measure of biological age was constructed and survival analysis performed, assessing the impact of biological age and peripheral blood telomere length on the chronological age-survival relationship. Measurements and Main Results: Twenty-two proteins mediated the chronological age-survival relationship after adjustment for false discovery in the idiopathic pulmonary fibrosis discovery cohort (n = 874), with 19 remaining significant mediators of this relationship in the ILD validation cohort (n = 983) and one mediating this relationship in the chronic obstructive pulmonary disease cohort. Latent transforming growth factor-β binding protein 2 and ectodysplasin A2 receptor showed the strongest mediation across cohorts. A proteomic measure of biological age completely attenuated the chronological age-survival association and better discriminated survival than chronological age. Results were robust to adjustment for peripheral blood telomere length, which did not mediate the chronological age-survival relationship. Conclusions: Molecular measures of aging completely mediate the relationship between chronological age and survival, suggesting that chronological age has no direct effect on ILD survival.

The relative age effect in selection of ab initio pilots–Revisiting Gladwell's famous claims

A relative age effect (RAE) has been found in education and sports, with students born earlier in the school year attaining higher levels of success. This was brought into public consciousness through Malcom Gladwell's Outliers: The Story of Success. However, the effect has not been thoroughly examined in other contexts. Thus, with regards to the context dependency of the RAE, and the specificity of which abilities it affects, there are unknowns. The aim of the present study was to scrutinize the tests in use in commercial aviation and explore whether there is a bias based on birthdate in competitive selection procedures assessing operational and cognitive abilities, outside of traditional education. Potential suboptimal selection has implications for flight safety. Associations were studied between relative age and test scores (of cognitive ability, manual spatial ability, and multitasking ability), as well as acceptance for higher education in commercial aviation in Sweden, in 1113 ab initio candidates. Relative age neither had a significant correlation with any of the six performance scores, nor with an aggregated factor score (r = −0.009, p = 0.791), nor predicted flight-school admission (b = 0.036, p = 0.210). Chronological age was associated with manual spatial ability, yet neither correlated with aggregate score nor with admission. The results may be an indication of the RAE having faded in early adulthood, and/or that indirect exposure of education does not benefit candidates in operational tests in early adulthood. Thus, neither relative age nor chronological age seemed to bias the results. For the effects of RAE to persist– or occur in operational abilities– competition between candidates in selection and subsequent relevant exposure (e.g., training/schooling), may be needed. Overall cognitive ability is likely more predictive of success when variance in specific enhancing exposure is limited.

Correlation of Clivus Length and Angle with Chronological Age, Gender, Sagittal Growth Pattern of the Jaws, and Skeletal Maturation Using Lateral Cephalometry.

Determination of remaining growth potential of patients is the most important factor in orthodontic treatment. This study aimed to assess the correlation of clivus length and angle with age, gender, sagittal growth pattern of the jaws, and skeletal maturation using lateral cephalometry. This cross-sectional study was conducted on 390 lateral cephalograms (Vatech, paX-i3D Green, South Korea) of patients aged 6 to 25 years. The patients were assigned to three groups of skeletal class I, II, III (n=130) with equal gender distribution. The clivus length and angle, Welcher angle, maxillary and mandibular effective length, sella turcica to Nasion (SN), and the angles between SN and point A (SNA), between SN and point B (SNB), and between NA and NB (ANB )were measured. Correlations of variables with age and gender, and cervical vertebral maturation stage (CVMS) were analyzed using the Pearson and Spearman's correlation tests, independent t-test, and one-way ANOVA at 0.05 level of significance. Clivus length had a significant correlation with SNA (r= 0.103, p= 0.042), SNB (r= 0.108, p= 0.033), maxillary (r= 0.547, p< 0.001) and mandibular (r= 0.589, p< 0.001) effective lengths, SN length (r= 0.586, p< 0.001), and CVMS (r= 0.697, p< 0.001). Clivus angle had a significant correlation with SNA (r= 0.105, p= 0.039), SNB (r= 0.155, p= 0.002), maxillary (r= 0.507, p< 0.001) and mandibular (r= 0.596, p= 0.001) effective lengths, SN length (r= 0.566, p< 0.001), and CVMS (r= 0.699, p< 0.001). The mean clivus length (p= 0.006) and angle (p= 0.002) were significantly higher in males, and had a significant correlation with age (r= 0.636 and r= 0.718, p< 0.001). The mean clivus length and angle were not significantly different in class I, II, III (p> 0.05). All parameters were greater in males, and increased with age (except Welcher angle). Clivus length and angle had significant correlations with position of both jaws but not with sagittal relationship.

Valgus-Related Elbow Pathology is not Associated with Decreased Baumann’s Angle: A Case-Control Study

BackgroundPrevious studies have demonstrated that varus alignment of the elbow has been associated with lateral condylar fractures. However, for other pediatric and adolescent elbow pathologies, the influence of upper extremity alignment has not been investigated. This study aimed to compare elbow alignment (quantified using Baumann’s angle) among patients with medial epicondyle humeral fractures and capitellum osteochondritis dissecans (OCD) and age- and sex-matched control patients. MethodsPediatric and adolescent patients (ages 5-18, inclusive) treated at a tertiary care hospital for medial epicondyle fractures (MEFx) and capitellum OCD lesions from January 2016 and October 2023 were retrospectively reviewed. Patients aged 5-18 with anteroposterior (AP) elbow radiographs demonstrating no elbow pathology were included as controls. Patients were matched 1:1:1 based on sex and chronologic age within 2 years and placed into cohorts by injury. Baumann’s angle was compared across groups using one-way ANOVA after data normality was established via Shapiro Wilk tests. Linear regression was used to assess whether fracture displacement in millimeters (in the medial epicondyle fracture group) or OCD lesion size (in the capitellum OCD group) correlated with Baumann’s angle. Two-tailed significance threshold was set as p≤0.05. Results72 matched patients were included (24 MEFx, 24 OCD, 24 controls). Mean age of the overall sample was 13.8±1.9 years, with 79% male. Mean Baumann’s angle was 75.7±5.9 degrees in MEFx, 71.7±7.9 degrees in OCD, and 74.1±5.2 degrees in controls (p=0.181). There was no association between fracture displacement and Baumann’s angle in the MEFx group (p=0.75), and there was no association between OCD lesion size and Baumann’s angle in the OCD group (p=0.31). ConclusionsThere was no difference in Baumann’s angle among pediatric and adolescent patients with MEFx, capitellum OCD lesions, and age and sex-matched controls. These findings suggest that static distal humerus alignment does not increase the risk for these injuries. Future studies should seek to evaluate dynamic alignment and its influence on these pathologies. Level of EvidenceIII

Bone age estimation with HS-optimized Resnet and Yolo for child growth disorder

Bone Age Assessment (BAA) plays a significant part in assessing skeletal maturity for preventing different types of skeletal disorders in the human body. Predicting BAA helps clinicians make decisions about the patient’s biological maturity. An increase or decrease in bone age (BA) causes serious issues for pediatricians who need advanced equipment for BA consistency with the chronological age. Recent techniques fail to accurately estimate the region over interest (ROI) of hand-wrist images to predict BA under low time complexity accurately. Hence, this article brings novel deep learning (DL) techniques to assess the BA to overcome child growth disorders accurately. The proposed methodology undergoes three major stages: pre-processing, ROI detection, and BA detection. In the pre-processing stage, contrast-limited fuzzy adaptive histogram equalization (CLFAHE) is done to maintain the originality of the hand image. The size of the image is also increased by using data augmentation. After pre-processing, the required hand bone region with ROI detection approaches you only live once version 3 (YOLOv3). At the final stage, the BA is predicted using the residual network-152 (ResNet152) technique. Finally, the weight updation takes place in the ResNet152 model using harmony search (HS) optimization techniques. The dataset used in this research is collected from the RSNA bone age dataset. The performance measures such as mean absolute error (MAE), root mean square error (RMSE), and root mean squared percentage error (RMSPE) are analyzed and compared with other existing measures. In an experimental scenario, the MAE of 2.59, RMSE of 2.97, and RMSPE of 0.35 for the male gender is obtained.

Curcumin Inhibits TORC1 and Prolongs the Lifespan of Cells with Mitochondrial Dysfunction.

Aging is an inevitable biological process that contributes to the onset of age-related diseases, often as a result of mitochondrial dysfunction. Understanding the mechanisms behind aging is crucial for developing therapeutic interventions. This study investigates the effects of curcumin on postmitotic cellular lifespan (PoMiCL) during chronological aging in yeast, a widely used model for human postmitotic cellular aging. Our findings reveal that curcumin significantly prolongs the PoMiCL of wildtype yeast cells, with the most pronounced effects observed at lower concentrations, indicating a hormetic response. Importantly, curcumin also extends the lifespan of postmitotic cells with mitochondrial deficiencies, although the hormetic effect is absent in these defective cells. Mechanistically, curcumin inhibits TORC1 activity, enhances ATP levels, and induces oxidative stress. These results suggest that curcumin has the potential to modulate aging and offer therapeutic insights into age-related diseases, highlighting the importance of context in its effects.

Investigating Task Persistence in Preschool Children With Developmental Language Disorder.

The present study was designed to investigate persistence in preschool children with developmental language disorder (DLD) compared to similar-age peers with typical language (TL) on tasks designed to be moderately challenging, yet equivalent in difficulty for both groups. Sixteen preschool-age children with DLD were matched to 16 children with TL based on chronological age, biological sex, and maternal education. The children completed two play-based tasks that were designed to elicit some success but impossible to complete. Task persistence was measured by the total time spent attempting to complete each unachievable task. Despite equivalent task difficulty for both groups, the children with DLD exhibited less persistence than the TL group. This reduced persistence behavior on the part of the DLD group was a generalized and not a task-specific response. Despite experiencing the same degree of success on moderately challenging play-based tasks, the children in the DLD group exhibited reduced task persistence relative to the TL group. Potential implications for reduced persistence for children with DLD are discussed.

Glycemic control contributes to the neuroprotective effects of Mediterranean and green-Mediterranean diets on brain age: the DIRECT PLUS brain-magnetic resonance imaging randomized controlled trial

BackgroundWe recently reported that Mediterranean (MED) and green-MED diets significantly attenuated age-related brain atrophy by ∼50% within 18 mo. ObjectiveThe objective of this study was to explore the contribution of specific diet-induced parameters to brain-volume deviation from chronologic age. MethodsA post hoc analysis of the 18-mo DIRECT PLUS trial, where participants were randomly assigned to the following groups: 1) healthy dietary guidelines, 2) MED diet, or 3) green-MED diet, high in polyphenols, and low in red meat. Both MED groups consumed 28 g walnuts/d (+440 mg/d polyphenols). The green-MED group further consumed green tea (3–4 cups/d) and Mankai green shake (Wolffia globosa aquatic plant) (+800 mg/d polyphenols). We collected blood samples through the intervention and followed brain structure volumes by magnetic resonance imaging (MRI). We used hippocampal occupancy (HOC) score (hippocampal and inferior lateral-ventricle volumes ratio) as a neurodegeneration marker and brain-age proxy. We applied multivariate linear regression models. ResultsOf 284 participants [88% male; age = 51.1 y; body mass index = 31.2 kg/m2; hemoglobin A1c (HbA1c) = 5.48%; APOE-ε4 genotype = 15.7%], 224 completed the trial with eligible whole-brain MRIs. Individuals with higher HOC deviations (i.e., younger brain age) presented lower body weight [r = –0.204; 95% confidence interval (CI): –0.298, –0.101], waist circumference (r = –0.207; 95% CI: –0.310, –0.103), diastolic (r = –0.186; 95% CI: –0.304, –0.072), systolic blood pressure (r = –0.189; 95% CI: –0.308, –0.061), insulin (r = –0.099; 95% CI: –0.194, –0.004), and HbA1c (r = –0.164; 95% CI: –0.337, –0.006) levels. After 18 mo, greater changes in HOC deviations (i.e., brain-age decline attenuation) were independently associated with improved HbA1c (β = –0.254; 95% CI: –0.392, –0.117), HOMA-IR (β = –0.200; 95% CI: –0.346, –0.055), fasting glucose (β = –0.155; 95% CI: –0.293, –0.016), and c-reactive protein (β = –0.153; 95% CI: –0.296, –0.010). Improvement in diabetes status was associated with greater HOC deviation changes than either no change in diabetes status (0.010; 95% CI: 0.002, 0.019) or with an unfavorable change (0.012; 95% CI: 0.002, 0.023). A decline in HbA1c was further associated with greater deviation changes in the thalamus, caudate nucleus, and cerebellum (P < 0.05). Greater consumption of Mankai and green tea (green-MED diet components) were associated with greater HOC deviation changes beyond weight loss. ConclusionsGlycemic control contributes to the neuroprotective effects of the MED and green-MED diets on brain age. Polyphenols-rich diet components as Mankai and green tea may contribute to a more youthful brain age.This trial was registered at clinicaltrials.gov at clinicaltrials.gov as NCT03020186.