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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.

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, Cohens 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.

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.

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  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.

PurposeTo 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).DesignRetrospective observational.ParticipantsRimNet 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.MethodsDisc 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 measuresThe main outcome measure was a weighted kappa score between clinicians and the DDLSNet pipeline with agreement defined as ± 1 DDLS score difference.ResultsRimNet 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.ConclusionsDDLSNet 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.

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.

PurposeAccurate 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.DesignRetrospective cross sectional study.ParticipantsOne 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).MethodsThe 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 measuresMedian Absolute Error (MAE) between glaucoma specialists and RimNet for mRDR and ARW.ResultsOn 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.ConclusionsRimNet 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.

Background and aimsMetabolomic 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.MethodsThis 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.ResultsAmong 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).ConclusionWe 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 numberThis study was registered at ClinicalTrials.gov.

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.

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.

Knowledge of an animals 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.

BACKGROUND: Circulating individual SFAs in pregnant females are critical for maternal and fetal health. However, research on identifying their modifiable factors is limited. OBJECTIVES: We aimed to examine the associations of total physical activity (PA) and types of PA with circulating individual SFAs during pregnancy in a multiracial/multiethnic cohort of pregnant females in the United States. METHODS: The study included participants in a nested case-control study (n = 321) from the Eunice Kennedy Shriver NICHD Fetal Growth Studies-Singleton Cohort. Sampling weights were applied, so the results represented the entire Fetal Growth Cohort. Plasma phospholipid SFAs were measured at 4 visits [10-14 (visit 1), 15-26 (visit 2), 23-31 (visit 3), and 33-39 (visit 4) weeks of gestation] throughout pregnancy. PA of the previous year at visit 1 and since the previous visit at the subsequent visits was assessed using the validated Pregnancy PA Questionnaire. Time-specific and longitudinal associations were examined using multivariable linear and generalized estimating equation models. RESULTS: Total PA (metabolic equivalent of task-h/wk) was positively associated with circulating heptadecanoic acid (17:0) at visit 1 (β × 103: 0.07; 95% CI: 0.02, 0.11) and pentadecanoic acid (15:0) at visit 3 (β × 103: 0.09; 95% CI: 0.03, 0.14) independent of sociodemographic, reproductive, pregnancy, and dietary factors. Across the 4 visits, the positive associations with total PA were consistent for pentadecanoic acid (β × 103: 0.06; 95% CI: 0.02, 0.10) and heptadecanoic acid (β × 103: 0.10; 95% CI: 0.06, 0.14). Out of the 4 PA types (i.e., sports/exercise, household/caregiving, transportation, and occupational PA) considered, the magnitude of positive associations was the largest for sports/exercise PA. CONCLUSIONS: Our findings suggest that maternal PA is positively associated with circulating pentadecanoic and heptadecanoic acids. The findings warrant confirmation by future studies.This trial was registered at clinicaltrials.gov as NCT00912132.

BACKGROUND: Physical activity (PA) during pregnancy influences women and offsprings health via fatty acids metabolism. However, studies on associations of PA with plasma monounsaturated fatty acids (MUFAs) across pregnancy are sparse. Thus, our study aimed to examine associations of PA with individual plasma phospholipid MUFAs throughout pregnancy in a prospective and longitudinal study in the United States (US). MATERIALS AND METHODS: The study included 318 pregnant women from the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies-Singletons cohort. PA was measured four times: PA reported at 10-14 gestational weeks (GWs) representing PA in the past year, and at 15-26 GWs, 23-31 GWs, and 33-39 GWs representing PA since the last visit. Plasma phospholipid MUFAs were measured at the same four visits as the measurement of PA. Associations between moderate-to-vigorous PA (MVPA) and the total MUFAs and seven individual plasma phospholipid MUFAs (i.e., palmitoleic acid, 18:1n6-9 trans, 18:1n6c, cis-vaccenic acid, oleic acid, eicosenoic acid, and nervonic acid) were assessed at each visit using multivariable linear regression models adjusting for confounders. RESULTS: MVPA (hours/week) reported at 15-26 GWs representing MVPA since the last visit was positively associated with total MUFAs (% of total fatty acids) [adjusted β*102 (standard error (SE)*102) = 10.41 (3.19), P = 0.001] at 15-26 GWs. For individual MUFAs, MVPA reported at 15-26 GWs representing MVPA since the last visit was positively associated with oleic acid [adjusted β*102 (SE*102) = 8.56 (2.65), P = 0.001] and eicosenoic acid [adjusted β*102 (SE*102) = 0.55 (0.20), P = 0.01] at 15-26 GWs. MVPA reported at 23-31 GWs representing MVPA since the last visit was positively associated with palmitoleic acid [adjusted β*102 (SE*102) = 2.24 (0.64), P = 0.001] at 23-31 GWs. MVPA reported at 10-14 GWs and 33-39 GWs was not associated with total or individual MUFAs. CONCLUSION: We found novel positive associations of MVPA with individual MUFAs, such as oleic acid, eicosenoic acid, and palmitoleic acid, during middle-to-late pregnancy. These findings suggest that MVPA represents a potentially modifiable factor for plasma individual MUFA levels during pregnancy.

AimsTo investigate whether reduction in opioid use differs when treated by either buprenorphine-naloxone (BUP) or methadone (MET) among adults with comorbid opioid use disorder (OUD) and mental disorders.Design, setting and participantsIn a randomized controlled trial, adults with OUD were randomized to 24 weeks of either BUP or MET treatment and were followed up in 3-yearly assessments. The present secondary analyses were based on 597 participants who completed all assessments.MeasurementsThe outcome measure was the number of days of using opioids per month during the follow-up period. The Mini-International Neuropsychiatric Interview (MINI) was used to classify participants into three groups: life-time mood disorder (n = 302), life-time mental disorder other than mood disorder (n = 114) and no mental disorder (n = 181). Medication treatment (BUP, MET, no treatment) during the follow-up period was a time-varying predictor.FindingsBased on zero-inflated Poisson (ZIP) mixed regression analysis, it was found that relative to no treatment, opioid use during the follow-up was significantly reduced by BUP [odds ratio (OR) = 0.12, 95% confidence interval (CI) = 0.07-0.21 for any use; risk ratio (RR) = 0.77, 95% CI =0.66-0.89 for days of use] and by MET [OR = 0.33, 95% CI = 0.25-0.45 for any use; RR = 0.78, 95% CI = 0.72-0.84 for days of use]. Relative to MET, BUP was associated with a lower likelihood of any opioid use among participants with mood disorders (OR = 0.52, 95% CI = 0.36-0.74) and for participants without mental disorder (OR = 0.37, 95% CI = 0.21-0.66) and fewer number of days using opioids (RR = 0.37, 95% CI = 0.25-0.56) among participants with other mental disorders.ConclusionsAmong adults with comorbid opioid use disorder and mental disorders, treatment with buprenorphine-naloxone produced greater reductions in opioid use than treatment with methadone.

ObjectivesBoth COVID-19 deaths and opioid overdose deaths continue to increase in the United States. Little is known about the characteristics of counties with high rates of mortality for both.MethodsWe analyzed county-level data on COVID-19 mortality from January 1 to May 31, 2020, and on opioid overdose mortality during 2014-2018. The outcome variable, "high-risk county" was a binary indicator of high mortality rates (above 75% quartile) for both COVID-19 and opioid overdose. We conducted geospatial logistic regression models separately for urban and rural counties to identify social determinants of health associated with being a high-risk county.ResultsAfter adjusting for other covariates, the overall mortality rate of COVID-19 is higher in counties with larger population size and a higher proportion of racial/ethnic minorities, although counties with high rates of opioid overdose mortality have lower proportions of racial/ethnic minorities, a higher proportion of females, and are more economically disadvantaged. Significant predictors of rural counties with high mortality rates for both COVID-19 and opioid overdose include higher proportions of Blacks (Adjusted odds ratio [aOR], 1.04; 95%CI, 1.01-1.07), American Indians and Alaska Natives (aOR, 1.07; 95%CI, 1.02-1.13), and two or more races (aOR, 1.34; 95%CI, 1.13-1.60). Additional predictors for high-risk urban counties include population density (aOR, 1.12; 95%CI, 1.04-1.22) and higher unemployment rates during the COVID-19 pandemic (aOR, 1.23; 95%CI, 1.07-1.41).ConclusionsRural counties with high proportions of racial/ethnic minorities and urban counties with high unemployment rates are at high mortality risk for COVID-19 and opioid overdose.

The development of a precise blood or skin tissue DNA Epigenetic Aging Clock for Odontocete (OEAC) would solve current age estimation inaccuracies for wild odontocetes. Therefore, we determined genome-wide DNA methylation profiles using a custom array (HorvathMammalMethyl40) across skin and blood samples (n = 446) from known age animals representing nine odontocete species within 4 phylogenetic families to identify age associated CG dinucleotides (CpGs). The top CpGs were used to create a cross-validated OEAC clock which was highly correlated for individuals (r = 0.94) and for unique species (median r = 0.93). Finally, we applied the OEAC for estimating the age and sex of 22 wild Norwegian killer whales. DNA methylation patterns of age associated CpGs are highly conserved across odontocetes. These similarities allowed us to develop an odontocete epigenetic aging clock (OEAC) which can be used for species conservation efforts by provide a mechanism for estimating the age of free ranging odontocetes from either blood or skin samples.

DNA methylation data facilitate the development of accurate molecular estimators of chronological age or epigenetic clocks. We present a robust epigenetic clock for the beluga whale, Delphinapterus leucas, developed for an endangered population in Cook Inlet, Alaska, USA. We used a custom methylation array to measure methylation levels at 37,491 cytosine-guanine sites (CpGs) from skin samples of dead whales (n = 67) whose chronological ages were estimated based on tooth growth layer groups. Using these calibration data, a penalized regression model selected 23 CpGs, providing an R 2 = 0.92 for the training data; and an R 2 = 0.74 and median absolute age error = 2.9 years for the leave one out cross-validation. We applied the epigenetic clock to an independent dataset of 38 skin samples collected with a biopsy dart from living whales between 2016 and 2018. Age estimates ranged from 11 to 27 years. We also report sex correlations in CpG data and describe an approach of identifying the sex of an animal using DNA methylation. The epigenetic estimators of age and sex presented here have broad applications for conservation and management of Cook Inlet beluga whales and potentially other cetaceans.

The focus of modern biomedical studies has gradually shifted to explanation and estimation of joint effects of high dimensional predictors on disease risks. Quantifying uncertainty in these estimates may provide valuable insight into prevention strategies or treatment decisions for both patients and physicians. High dimensional inference, including confidence intervals and hypothesis testing, has sparked much interest. While much work has been done in the linear regression setting, there is lack of literature on inference for high dimensional generalized linear models. We propose a novel and computationally feasible method, which accommodates a variety of outcome types, including normal, binomial, and Poisson data. We use a splitting and smoothing approach, which splits samples into two parts, performs variable selection using one part and conducts partial regression with the other part. Averaging the estimates over multiple random splits, we obtain the smoothed estimates, which are numerically stable. We show that the estimates are consistent, asymptotically normal, and construct confidence intervals with proper coverage probabilities for all predictors. We examine the finite sample performance of our method by comparing it with the existing methods and applying it to analyze a lung cancer cohort study.

Maternal plasma phospholipid polyunsaturated fatty acids (PUFAs) play critical roles in maternal health and fetal development. Beyond dietary factors, maternal moderate-to-vigorous physical activity (MVPA) has been linked to multiple health benefits for both the mother and offspring, but studies investigating the influence of maternal MVPA on maternal PUFA profile are scarce. The objective of present study was to examine the time-specific and prospective associations of MVPA with plasma PUFA profile among pregnant women. This study included 321 participants from the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singletons cohort. Maternal plasma phospholipid PUFAs and MPVA were measured at four visits during pregnancy (10-14, 15-26, 23-31, and 33-39 gestational weeks (GW)). Associations of maternal MVPA with individual plasma PUFAs and desaturase activity were examined using generalized linear models. Maternal MVPA was associated inversely with plasma phospholipid linoleic acid, gamma-linolenic acid, and Δ6-desaturase in late pregnancy (23-31 or 33-39 GW), independent of maternal age, race, education, parity, pre-pregnancy body mass index, and dietary factors. Findings from this longitudinal study indicate that maternal habitual MVPA may play a role on PUFAs metabolism, particular by alerting plasma n-6 subclass and desaturase activity in late pregnancy. These associations are novel and merit confirmation in future studies.

Direct far-field visualization and characterization of surface plasmon polaritons (SPPs) are of great importance for fundamental studies and technological applications. To probe the evanescently confined plasmon fields, one usually requires advanced near-field techniques, which is typically not applicable for real-time, high-throughput detecting or mapping of SPPs in complicated environments. Here, we report the utilization of rare-earth-doped nanoparticles to quantitatively upconvert invisible, evanescently confined SPPs into visible photoluminescence emissions for direct far-field visualization of SPPs in a complicated environment. The observed interference fringes between the SPPs and the coherent incident light at the metal surface provide a quantitative measurement of the SPP wavelength and the SPP propagating length and the local dielectric environments. It thus creates a new signaling pathway to sensitively transduce the local dielectric environment change into interference periodicity variation, enabling a new design of directly measurable, spectrometer-free optical rulers for rapid, ultrasensitive label-free detection of various biomolecules, including streptavidin and prostate-specific antigen, down to the femtomolar level.

Stochastic clocks represent a class of time change methods for incorporating trading activity into continuous-time financial models, with the ability to deal with typical asymmetrical and tail risks in financial returns. In this paper we propose a significant improvement of stochastic clocks for the same objective but without decreasing the number of trades or changing the trading intensity. Our methodology targets any Lévy subordinator, or more generally any process of nonnegative independent increments, and is based on various choices of regulating kernels motivated from repeated averaging. By way of a hyperparameter linked to the degree of regulation, arbitrarily large skewness and excess kurtosis of returns can be easily achieved. Generic-time Laplace transforms, characterizing triplets, and cumulants of the regulated clocks and subsequent mixed models are analyzed, serving purposes ranging from statistical estimation and option price calibration to simulation techniques. Under specified jump–diffusion processes and tempered stable processes, a robust moment-based estimation procedure with profile likelihood is developed and a comprehensive empirical study involving S&P500 and Bitcoin daily returns is conducted to demonstrate a series of desirable effects of the proposed methods. [ABSTRACT FROM AUTHOR]

Broadband tunability is a central theme in contemporary nanophotonics and metamaterials research. Combining metamaterials with phase change media offers a promising approach to achieve such tunability, which requires a comprehensive investigation of the electromagnetic responses of novel materials at subwavelength scales. In this work, we demonstrate an innovative way to tailor band-selective electromagnetic responses at the surface of a heavy fermion compound, samarium sulfide (SmS). By utilizing the intrinsic, pressure sensitive, and multi-band electron responses of SmS, we create a proof-of-principle heavy fermion metamaterial, which is fabricated and characterized using scanning near-field microscopes with

We investigated phonon-polaritons in hexagonal boron nitride - a naturally hyperbolic van der Waals material - by means of the scattering-type scanning near-field optical microscopy. Real-space nanoimages we have obtained detail how the polaritons are launched when the light incident on a thin hexagonal boron nitride slab is scattered by various intrinsic and extrinsic inhomogeneities, including sample edges, metallic nanodisks deposited on its top surface, random defects, and surface impurities. The scanned tip of the near-field microscope is itself a polariton launcher whose efficiency proves to be superior to all the other types of polariton launchers we studied. Our work may inform future development of polaritonic nanodevices as well as fundamental studies of collective modes in van der Waals materials.