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We describe a framework that addresses concern that the rate of change in any aging biomarker displays a trivial inverse relation with maximum lifespan. We apply this framework to methylation data from the Mammalian Methylation Consortium. We study the relationship of lifespan with the average rate of change in methylation (AROCM) from two datasets: one with 90 dog breeds and the other with 125 mammalian species. After examining 54 chromatin states, we conclude three key findings: First, a reciprocal relationship exists between the AROCM in bivalent promoter regions and maximum mammalian lifespan: AROCM ∝ 1/MaxLifespan. Second, the correlation between average methylation and age bears no relation to maximum lifespan, Cor(Methyl,Age) ⊥ MaxLifespan. Third, the rate of methylation change in young animals is related to that in old animals: Young animals' AROCM ∝ Old AROCM. These findings critically hinge on the chromatin context, as different results emerge in other chromatin contexts.

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Introduction: There is limited research examining factors impacting MOUD retention in rural settings, especially within the context of the COVID-19 pandemic. Using electronic health records data collected as part of a NIDA Clinical Trials Network study (CTN-0102), this study explored how the onset of the COVID-19 pandemic may have impacted MOUD retention in a sample of 563 rural primary care patients. Methods: Cox regression model was applied to examine if COVID-19 was related to treatment retention, controlling for demographics, clinic, insurance type, and other diagnoses. The independent variable was the number of days between the patient's first MOUD prescription date during the pre-COVID observation period (10/1/2019-3/13/2020) and the start of the COVID-19 pandemic. The dependent variable was retention on MOUD, defined as the time from the first MOUD prescription documented during the pre-COVID observation period to the first break in consecutive MOUD prescriptions (right censored at 180 days). Results: The findings demonstrated that there was a reduced risk of a prescription break for every 10-day increase in the time from the first documented MOUD prescription to the onset of the COVID-19 pandemic (HR = 0.96, 95 % CI = 0.92-0.99; p = 0.011). Conclusions: While the data did not include complete treatment histories to determine who was new to MOUD treatment, the findings suggest that patients whose first documented MOUD prescription in the dataset was closer to the onset of the pandemic had a greater likelihood of experiencing retention challenges. This underscores the importance for clinics to establish comprehensive contingency plans for future emergencies to ensure uninterrupted MOUD treatment and support, particularly for individuals in the early stabilization phase of their recovery.

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By analyzing 15,000 samples from 348 mammalian species, we derive DNA methylation (DNAm) predictors of maximum life span (R = 0.89), gestation time (R = 0.96), and age at sexual maturity (R = 0.85). Our maximum life-span predictor indicates a potential innate longevity advantage for females over males in 17 mammalian species including humans. The DNAm maximum life-span predictions are not affected by caloric restriction or partial reprogramming. Genetic disruptions in the somatotropic axis such as growth hormone receptors have an impact on DNAm maximum life span only in select tissues. Cancer mortality rates show no correlation with our epigenetic estimates of life-history traits. The DNAm maximum life-span predictor does not detect variation in life span between individuals of the same species, such as between the breeds of dogs. Maximum life span is determined in part by an epigenetic signature that is an intrinsic species property and is distinct from the signatures that relate to individual mortality risk.

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BACKGROUND: Whether individuals with gestational diabetes mellitus (GDM) had an increased risk of hypertension remains unclear. We conducted a systematic literature review and meta-analysis to examine the association between GDM and hypertension and performed a quantitative bias analysis to quantify the impact of uncontrolled confounding due to antenatal psychological stress. METHODS: We searched databases (PUBMED, EMBASE, and Web of Science) through 2022/11. Eligible studies were cohort studies that reported the association of GDM with hypertension. We assessed the risk of bias using the Newcastle-Ottawa Scale for cohort studies. We pooled adjusted risk ratios with 95% CIs using a random effects model. We performed the quantitative bias analysis using the bias formula. RESULTS: We included 15 cohort studies, with a total of 3 959 520 (GDM, 175 378; non-GDM, 3 784 142) individuals. During the follow-up of 2 to 20 years, 106 560 cases of hypertension were reported. We found that GDM was associated with a higher risk of hypertension (pooled risk ratio, 1.78 [95% CI, 1.47, 2.17]). The risk ratio was lower among cohorts assessing incident (1.58 [95% CI, 1.29, 1.95]) than prevalent hypertension (2.60 [95% CI, 2.40, 2.83]). However, other subgroup analyses showed no differences. The quantitative bias analysis revealed that if the uncontrolled confounder of antenatal psychological stress was additionally adjusted, the positive association between GDM and hypertension would attenuate slightly (≤18%) but remains positive. CONCLUSIONS: Limitations of this study included residual confounding and discrepancies in GDM and hypertension ascertainments. Our findings indicate that GDM is positively associated with hypertension after the index pregnancy.

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OBJECTIVES: Factors associated with treatment retention on medications for opioid use disorder (MOUD) in rural settings are poorly understood. This study examines associations between social determinants of health (SDoH) and MOUD retention among patients with opioid use disorder (OUD) in rural primary care settings. METHODS: We analyzed patient electronic health records from 6 rural clinics. Participants (N = 575) were adult patients with OUD and had any prescription for MOUD from October 2019 to April 2020. MOUD retention was measured by MOUD days and continuity defined as continuous 180 MOUD days with no more than a 7-day gap. Mixed-effect regressions assessed associations between the outcomes and SDoH (Medicaid insurance, social deprivation index [SDI], driving time from home to the clinic), telehealth use, and other covariates. RESULTS: Mean patient MOUD days were 127 days (SD = 50.7 days). Living in more disadvantaged areas (based on SDI) (adjusted relative risk [aRR]: 0.98; 95% confidence interval [CI], 0.98-0.99) and having more than an hour (compared with an hour or less) driving time from home to clinic (aRR: 0.95; 95% CI, 0.93-0.97) were associated with fewer MOUD days. Using telehealth was associated with more MOUD days (aRR: 1.23; 95% CI, 1.21-1.26). In this cohort, 21.7% of the participants were retained on MOUD for at least 180 days. SDoH and use of telehealth were not associated with having continuity of MOUD. CONCLUSIONS: Addressing SDoH (eg, SDI) and providing telehealth (eg, improvements in public transportation, internet access) may improve MOUD days in rural settings.

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AIMS: With the two-step gestational diabetes mellitus (GDM) screening approach, hyperglycemic subtypes can be identified. We aimed to investigate racial/ethnic differences in the prevalence of hyperglycemic subtypes and to examine the associations between these subtypes and adverse pregnancy outcomes. METHODS: In this retrospective cohort, 11,405 pregnancies were screened using the two-step approach. Hyperglycemic subtypes included: pregnancy-impaired glucose intolerance-I (PIGT-I), PIGT-II, GDM-I (abnormal post-load glucose only), and GDM-II (abnormal fasting & post-load glucose). Modified Poisson regressions with robust error variance were used to estimate age-adjusted prevalence ratios (PR) of hyperglycemic subtypes and multivariable-adjusted risk ratios (RR) of adverse pregnancy outcomes. RESULTS: The prevalence of hyperglycemic subtypes was higher in Asians (PIGT-I: 1.51 [95% confidence interval 1.35-1.69]; PIGT-II: 2.18 [1.78-2.68]; GDM-I: 2.55 [2.10-3.10]; GDM-II: 1.55 [1.08-2.21]) and Hispanics (PIGT-I: 1.32 [1.16-1.50]; PIGT-II: 2.07 [1.67-2.57]; GDM-I: 1.69 [1.35-2.13]; GDM-II: 2.68 [1.93-3.71]) than non-Hispanic Whites (NHW). Despite low GDM prevalence, Japanese and Koreans had higher PIGT prevalence than NHW. PIGT-II was positively associated with hypertensive disorders of pregnancy (1.19 [1.02-1.38]), large-for-gestational age (1.73 [1.37-2.18]), and preterm birth (PB, 1.33 [1.05-1.68]). PIGT-I (1.23 [1.04-1.45]) and GDM-I (1.56 [0.87-1.71]) were positively related to PB. CONCLUSIONS: The prevalence of hyperglycemic subtypes varies by race/ethnicity and they have distinct health implications.

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Purpose: To evaluate and compare the effectiveness of nearest neighbor (NN)- and variational autoencoder (VAE)-smoothing algorithms to reduce variability and enhance the performance of glaucoma visual field (VF) progression models. Design: Longitudinal cohort study. Subjects: 7150 eyes (4232 patients), with ≥ 5 years of follow-up and ≥ 6 visits. Methods: Vsual field thresholds were smoothed with the NN and VAE algorithms. The mean total deviation (mTD) and VF index rates, pointwise linear regression (PLR), permutation of PLR (PoPLR), and the glaucoma rate index were applied to the unsmoothed and smoothed data. Main Outcome Measures: The proportion of progressing eyes and the conversion to progression were compared between the smoothed and unsmoothed data. A simulation series of noiseless VFs with various patterns of glaucoma damage was used to evaluate the specificity of the smoothing models. Results: The mean values of age and follow-up time were 62.8 (standard deviation: 12.6) years and 10.4 (standard deviation: 4.7) years, respectively. The proportion of progression was significantly higher for the NN and VAE smoothed data compared with the unsmoothed data. VF progression occurred significantly earlier with both smoothed data compared with unsmoothed data based on mTD rates, PLR, and PoPLR methods. The ability to detect the progressing eyes was similar for the unsmoothed and smoothed data in the simulation data. Conclusions: Smoothing VF data with NN and VAE algorithms improves the signal-to-noise ratio for detection of change, results in earlier detection of VF progression, and could help monitor glaucoma progression more effectively in the clinical setting. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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BACKGROUND: Previous studies examined the associations of gestational diabetes mellitus with autism spectrum disorder and attention deficit hyperactivity disorder. However, the associations between gestational diabetes mellitus and other neurodevelopmental disorders, such as the common speech/language disorder and developmental coordination disorder, are rarely studied, and whether the associations vary by race/ethnicity remains unknown. OBJECTIVE: This study aimed to examine the associations of gestational diabetes mellitus with individual neurodevelopmental disorders in young offspring, and to investigate whether the associations vary by race/ethnicity. STUDY DESIGN: This retrospective cohort study (Glucose in Relation to Women and Babies' Health [GrownB]) included 14,480 mother-offspring pairs in a large medical center in the United States from March 1, 2013 to August 31, 2021. We ascertained gestational diabetes mellitus using the validated ICD (International Classification of Diseases) codes (ICD-9: 648.8x; ICD-10: O24.4x), and identified neurodevelopmental disorders (speech/language disorder, developmental coordination disorder, autism spectrum disorder, and other neurodevelopmental disorders [attention deficit hyperactivity disorder, behavioral disorder, intellectual disability, and learning difficulty]) and their combinations using validated algorithms. We compared the hazard of neurodevelopmental disorders during the entire follow-up period between offspring born to mothers with and without gestational diabetes mellitus using multivariable Cox regression models. RESULTS: Among all mothers, 19.9% were Asian, 21.8% were Hispanic, 41.0% were non-Hispanic White, and 17.3% were of other/unknown race/ethnicity. During the median follow-up of 3.5 years (range, 1.0-6.3 years) after birth, 8.7% of offspring developed at least 1 neurodevelopmental disorder. Gestational diabetes mellitus was associated with a higher risk of speech/language disorder (adjusted hazard ratio, 1.59 [95% confidence interval, 1.07-2.35]), developmental coordination disorder (2.36 [1.37-4.04]), autism spectrum disorder (3.16 [1.36-7.37]), other neurodevelopmental disorders (3.12 [1.51-6.47]), any neurodevelopmental disorder (1.86 [1.36-2.53]), the combination of speech/language disorder and autism spectrum disorder (3.79 [1.35-10.61]), and the combination of speech/language disorder and developmental coordination disorder (4.22 [1.69-10.51]) among offspring born to non-Hispanic White mothers. No associations between gestational diabetes mellitus and any neurodevelopmental disorders or their combinations were observed among offspring born to mothers of other racial/ethnic groups. CONCLUSION: We observed an elevated risk of neurodevelopmental disorders among young offspring born to non-Hispanic White mothers with gestational diabetes mellitus, but not among other racial/ethnic groups.

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Using DNA methylation profiles (n = 15,456) from 348 mammalian species, we constructed phyloepigenetic trees that bear marked similarities to traditional phylogenetic ones. Using unsupervised clustering across all samples, we identified 55 distinct cytosine modules, of which 30 are related to traits such as maximum life span, adult weight, age, sex, and human mortality risk. Maximum life span is associated with methylation levels in HOXL subclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species.

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With the availability of high dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients' survival, along with proper statistical inference. Censored quantile regression has emerged as a powerful tool for detecting heterogeneous effects of covariates on survival outcomes. To our knowledge, there is little work available to draw inference on the effects of high dimensional predictors for censored quantile regression. This paper proposes a novel procedure to draw inference on all predictors within the framework of global censored quantile regression, which investigates covariate-response associations over an interval of quantile levels, instead of a few discrete values. The proposed estimator combines a sequence of low dimensional model estimates that are based on multi-sample splittings and variable selection. We show that, under some regularity conditions, the estimator is consistent and asymptotically follows a Gaussian process indexed by the quantile level. Simulation studies indicate that our procedure can properly quantify the uncertainty of the estimates in high dimensional settings. We apply our method to analyze the heterogeneous effects of SNPs residing in lung cancer pathways on patients' survival, using the Boston Lung Cancer Survivor Cohort, a cancer epidemiology study on the molecular mechanism of lung cancer.

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Age determination of wild animals, including pinnipeds, is critical for accurate population assessment and management. For most pinnipeds, current age estimation methodologies utilize tooth or bone sectioning which makes antemortem estimations problematic. We leveraged recent advances in the development of epigenetic age estimators (epigenetic clocks) to develop highly accurate pinniped epigenetic clocks. For clock development, we applied the mammalian methylation array to profile 37,492 cytosine-guanine sites (CpGs) across highly conserved stretches of DNA in blood and skin samples (n = 171) from primarily three pinniped species representing the three phylogenetic families: Otariidae, Phocidae and Odobenidae. We built an elastic net model with Leave-One-Out-Cross Validation (LOOCV) and one with a Leave-One-Species-Out-Cross-Validation (LOSOCV). After identifying the top 30 CpGs, the LOOCV produced a highly correlated (r = 0.95) and accurate (median absolute error = 1.7 years) age estimation clock. The LOSOCV elastic net results indicated that blood and skin clock (r = 0.84) and blood (r = 0.88) pinniped clocks could predict age of animals from pinniped species not used for clock development to within 3.6 and 4.4 years, respectively. These epigenetic clocks provide an improved and relatively non-invasive tool to determine age in skin or blood samples from all pinniped species.

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PURPOSE: The use of telemedicine (TM) has accelerated in recent years, yet research on the implementation and effectiveness of TM-delivered medication treatment for opioid use disorder (MOUD) has been limited. This study investigated the feasibility of implementing a care coordination model involving MOUD delivered via an external TM provider for the purpose of expanding access to MOUD for patients in rural settings. METHODS: The study tested a care coordination model in 6 rural primary care sites by establishing referral and coordination between the clinic and a TM company for MOUD. The intervention spanned approximately 6 months from July/August 2020 to January 2021, coinciding with the peak of the COVID-19 pandemic. Each clinic tracked patients with OUD in a registry during the intervention period. A pre-/post-intervention design (N = 6) was used to assess the clinic-level outcome as patient-days on MOUD based on patient electronic health records. FINDINGS: All clinics implemented critical components of the intervention, with an overall TM referral rate of 11.7% among patients in the registry. Five of the 6 sites showed an increase in patient-days on MOUD during the intervention period compared to the 6-month period before the intervention (mean increase per 1,000 patients: 132 days, P = .08, Cohen's d = 0.55). The largest increases occurred in clinics that lacked MOUD capacity or had a greater number of patients initiating MOUD during the intervention period. CONCLUSIONS: To expand access to MOUD in rural settings, the care coordination model is most effective when implemented in clinics that have negligible or limited MOUD capacity.

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INTRODUCTION: Methamphetamine (MA) is increasingly available in the United States and manufactured with increasing potency. Although psychosis is a known harm related to MA use, we know little about the clinical outcomes and prognosis of individuals who use MA and experience psychosis. Some evidence exists that psychosis among people who use methamphetamine leads to a high utilization of emergency and acute inpatient services, but the extent of this use is unclear. METHODS: Using an electronic health record (EHR) database, this study assessed acute care visits of individuals receiving diagnostic codes of the following disorders: methamphetamine use disorder with undifferentiated psychosis (MUDp), schizophrenia (MUDs) and no history of psychosis (MUD) in addition to individuals without MUD diagnosis but with diagnoses of either undifferentiated psychosis (Psy) or schizophrenia (Scz) from 2006 to 2019. The study explored potential clinical risk factors associated with rate of acute care visits. RESULTS: Receiving diagnoses of psychotic disorders and MUD were both associated with high rates of acute care utilization. The incidence rate ratio (IRR) was highest in the MUDp group 6.30 (95% CI: 5.73, 6.93) followed by the MUDs group 4.03 (95% CI: 3.87, 4.20), the Psy group 3.77 (95% CI: 3.45, 4.11), the Scz group 3.11 (95% CI: 2.99, 3.23), and the MUD group 2.17 (95% CI: 2.09, 2.25). Receiving another SUD diagnosis was identified as a risk factor for acute care visits in the MUDp group, and mood and anxiety disorder diagnoses were a risk factor in the MUDs group. CONCLUSIONS: In a general health care system, individuals receiving diagnoses of MUD and co-occurring psychotic disorders were observed to have particularly high rates of acute care service utilization, suggesting a high degree of disease burden and the need for development of targeted treatment interventions with both MUD and psychosis.

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Epigenetic approaches for estimating the age of living organisms are revolutionizing studies of long-lived species. Molecular biomarkers that allow age estimates from small tissue biopsies promise to enhance studies of long-lived whales, addressing a fundamental and challenging parameter in wildlife management. DNA methylation (DNAm) can affect gene expression, and strong correlations between DNAm patterns and age have been documented in humans and nonhuman vertebrates and used to construct "epigenetic clocks". We present several epigenetic clocks for skin samples from two of the longest-lived cetaceans, killer whales and bowhead whales. Applying the mammalian methylation array to genomic DNA from skin samples we validate four different clocks with median errors of 2.3-3.7 years. These epigenetic clocks demonstrate the validity of using cytosine methylation data to estimate the age of long-lived cetaceans and have broad applications supporting the conservation and management of long-lived cetaceans using genomic DNA from remote tissue biopsies.

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Claims surrounding exceptional longevity are sometimes disputed or dismissed for lack of credible evidence. Here, we present three DNA methylation-based age estimators (epigenetic clocks) for verifying age claims of centenarians. The three centenarian clocks were developed based on n = 7039 blood and saliva samples from individuals older than 40, including n = 184 samples from centenarians, 122 samples from semi-supercentenarians (aged 105 +), and 25 samples from supercentenarians (aged 110 +). The oldest individual was 115 years old. Our most accurate centenarian clock resulted from applying a neural network model to a training set composed of individuals older than 40. An epigenome-wide association study of age in different age groups revealed that age effects in young individuals (age < 40) are correlated (r = 0.55) with age effects in old individuals (age > 90). We present a chromatin state analysis of age effects in centenarians. The centenarian clocks are expected to be useful for validating claims surrounding exceptional old age.

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BACKGROUND AND AIMS: Metabolomic profiling is a systematic approach to identifying biomarkers for dietary patterns. Yet, metabolomic markers for dietary patterns in pregnant individuals have not been investigated. The aim of this study was to identify plasma metabolomic markers and metabolite panels that are associated with the Mediterranean diet in pregnant individuals. METHODS: This is a prospective study of 186 pregnant individuals who had both dietary intake and metabolomic profiles measured from the Fetal Growth Studies-Singletons cohort. Dietary intakes during the peri-conception/1st trimester and the second trimester were accessed at 8-13 and 16-22 weeks of gestation, respectively. Adherence to the Mediterranean diet was measured by the alternate Mediterranean Diet (aMED) score. Fasting plasma samples were collected at 16-22 weeks and untargeted metabolomics profiling was performed using the mass spectrometry-based platforms. Metabolites individually or jointly associated with aMED scores were identified using linear regression and least absolute shrinkage and selection operator (LASSO) regression models with adjustment for potential confounders, respectively. RESULTS: Among 459 annotated metabolites, 64 and 41 were individually associated with the aMED scores of the diet during the peri-conception/1st trimester and during the second trimester, respectively. Fourteen metabolites were associated with the Mediterranean diet in both time windows. Most Mediterranean diet-related metabolites were lipids (e.g., acylcarnitine, cholesteryl esters (CEs), linoleic acid, long-chain triglycerides (TGs), and phosphatidylcholines (PCs), amino acids, and sugar alcohols. LASSO regressions also identified a 10 metabolite-panel that were jointly associated with aMED score of the diet during the peri-conception/1st trimester (AUC: 0.74; 95% CI: 0.57, 0.91) and a 3 metabolites-panel in the 2nd trimester (AUC: 0.68; 95% CI: 0.50, 0.86). CONCLUSION: We identified plasma metabolomic markers for the Mediterranean diet among pregnant individuals. Some of them have also been reported in previous studies among non-pregnant populations, whereas others are novel. The results from our study warrant replication in pregnant individuals by future studies. CLINICAL TRIAL REGISTRATION NUMBER: This study was registered at ClinicalTrials.gov.

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Purpose: To report an image analysis pipeline, DDLSNet, consisting of a rim segmentation (RimNet) branch and a disc size classification (DiscNet) branch to automate estimation of the disc damage likelihood scale (DDLS). Design: Retrospective observational. Participants: RimNet and DiscNet were developed with 1208 and 11 536 optic disc photographs (ODPs), respectively. DDLSNet performance was evaluated on 120 ODPs from the RimNet test set, for which the DDLS scores were graded by clinicians. Reproducibility was evaluated on a group of 781 eyes, each with 2 ODPs taken within 4 years apart. Methods: Disc damage likelihood scale calculation requires estimation of optic disc size, provided by DiscNet (VGG19 network), and the minimum rim-to-disc ratio (mRDR) or absent rim width (ARW), provided by RimNet (InceptionV3/LinkNet segmentation model). To build RimNet's dataset, glaucoma specialists marked optic disc rim and cup boundaries on ODPs. The "ground truth" mRDR or ARW was calculated. For DiscNet's dataset, corresponding OCT images provided "ground truth" disc size. Optic disc photographs were split into 80/10/10 for training, validation, and testing, respectively, for RimNet and DiscNet. DDLSNet estimation was tested against manual grading of DDLS by clinicians with the average score used as "ground truth." Reproducibility of DDLSNet grading was evaluated by repeating DDLS estimation on a dataset of nonprogressing paired ODPs taken at separate times. Main Outcome Measures: The main outcome measure was a weighted kappa score between clinicians and the DDLSNet pipeline with agreement defined as ± 1 DDLS score difference. Results: RimNet achieved an mRDR mean absolute error (MAE) of 0.04 (± 0.03) and an ARW MAE of 48.9 (± 35.9) degrees when compared to clinician segmentations. DiscNet achieved 73% (95% confidence interval [CI]: 70%, 75%) classification accuracy. DDLSNet achieved an average weighted kappa agreement of 0.54 (95% CI: 0.40, 0.68) compared to clinicians. Average interclinician agreement was 0.52 (95% CI: 0.49, 0.56). Reproducibility testing demonstrated that 96% of ODP pairs had a difference of ≤ 1 DDLS score. Conclusions: DDLSNet achieved moderate agreement with clinicians for DDLS grading. This novel approach illustrates the feasibility of automated ODP grading for assessing glaucoma severity. Further improvements may be achieved by increasing the number of incomplete rims sample size, expanding the hyperparameter search, and increasing the agreement of clinicians grading ODPs.

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Knowledge of an animal's chronological age is crucial for understanding and predicting population demographics, survival and reproduction, but accurate age determination for many wild animals remains challenging. Previous methods to estimate age require invasive procedures, such as tooth extraction to analyse growth layers, which are difficult to carry out with large, mobile animals such as cetaceans. However, recent advances in epigenetic methods have opened new avenues for precise age determination. These 'epigenetic clocks' present a less invasive alternative and can provide age estimates with unprecedented accuracy. Here, we present a species-specific epigenetic clock based on skin tissue samples for a population of Indo-Pacific bottlenose dolphins (Tursiops aduncus) in Shark Bay, Western Australia. We measured methylation levels at 37,492 cytosine-guanine sites (CpG sites) in 165 samples using the mammalian methylation array. Chronological age estimates with an accuracy of ±1 year were available for 68 animals as part of a long-term behavioral study of this population. Using these samples with known age, we built an elastic net model with Leave-One-Out-Cross-Validation, which retained 43 CpG sites, providing an r = 0.86 and median absolute age error (MAE) = 2.1 years (5% of maximum age). This model was more accurate for our data than the previously published methylation clock based on skin samples of common bottlenose dolphins (T. truncatus: r = 0.83, MAE = 2.2) and the multi-species odontocete methylation clock (r = 0.68, MAE = 6.8), highlighting that species-specific clocks can have superior performance over those of multi-species assemblages. We further developed an epigenetic sex estimator, predicting sex with 100% accuracy. As age and sex are critical parameters for the study of animal populations, this clock and sex estimator will provide a useful tool for extracting life history information from skin samples rather than long-term observational data for free-ranging Indo-Pacific bottlenose dolphins worldwide.

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Strengthening the infrastructure of public health systems around trauma-informed principles is crucial to addressing the needs of traumatized children in the child welfare system. In fact, many local and state initiatives have focused on large-scale evaluation studies to determine the value of training direct service staff on trauma foundations. Less yet is known about the benefits of training leaders on trauma foundations, which is crucial given their unique influence on implementation decisions. The current study evaluates a trauma training delivered to leadership-level stakeholders through a large-scale training initiative for the Los Angeles County Department of Children and Family Services. Findings indicated that leaders improved in trauma knowledge from baseline to post-training and reported changes in their professional wellbeing and leadership approach after the reflective training component. The leadership trauma program may have positive downstream implications for direct service staff, organizational culture, and child and family outcomes.

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Purpose: Accurate neural rim measurement based on optic disc imaging is important to glaucoma severity grading and often performed by trained glaucoma specialists. We aim to improve upon existing automated tools by building a fully automated system (RimNet) for direct rim identification in glaucomatous eyes and measurement of the minimum rim-to-disc ratio (mRDR) in intact rims, the angle of absent rim width (ARW) in incomplete rims, and the rim-to-disc-area ratio (RDAR) with the goal of optic disc damage grading. Design: Retrospective cross sectional study. Participants: One thousand and twenty-eight optic disc photographs with evidence of glaucomatous optic nerve damage from 1021 eyes of 903 patients with any form of primary glaucoma were included. The mean age was 63.7 (± 14.9) yrs. The average mean deviation of visual fields was -8.03 (± 8.59). Methods: The images were required to be of adequate quality, have signs of glaucomatous damage, and be free of significant concurrent pathology as independently determined by glaucoma specialists. Rim and optic cup masks for each image were manually delineated by glaucoma specialists. The database was randomly split into 80/10/10 for training, validation, and testing, respectively. RimNet consists of a deep learning rim and cup segmentation model, a computer vision mRDR measurement tool for intact rims, and an ARW measurement tool for incomplete rims. The mRDR is calculated at the thinnest rim section while ARW is calculated in regions of total rim loss. The RDAR was also calculated. Evaluation on the Drishti-GS dataset provided external validation (Sivaswamy 2015). Main Outcome Measures: Median Absolute Error (MAE) between glaucoma specialists and RimNet for mRDR and ARW. Results: On the test set, RimNet achieved a mRDR MAE of 0.03 (0.05), ARW MAE of 31 (89)°, and an RDAR MAE of 0.09 (0.10). On the Drishti-GS dataset, an mRDR MAE of 0.03 (0.04) and an mRDAR MAE of 0.09 (0.10) was observed. Conclusions: RimNet demonstrated acceptably accurate rim segmentation and mRDR and ARW measurements. The fully automated algorithm presented here would be a valuable component in an automated mRDR-based glaucoma grading system. Further improvements could be made by improving identification and segmentation performance on incomplete rims and expanding the number and variety of glaucomatous training images.