Magnetic-susceptibility-dependent ratiometric probes for enhancing quantitative MRI.

In magnetic resonance imaging (MRI), quantitative measurements of analytes are hindered by difficulties in distinguishing the MRI signals of activation of the probe by the analyte from those of the accumulation of the intact probe. Here we show that imaging sensitivity and quantitation can be enhanced by ratiometric MRI probes with a high relaxivity-ratio change (more than 2.5-fold at 7 T) via magnetic-susceptibility-dependent magnetic resonance tuning.

BIVARIATE FUNCTIONAL PATTERNS OF LIFETIME MEDICARE COSTS AMONG ESRD PATIENTS.

In this work we study the lifetime Medicare spending patterns of patients with end-stage renal disease (ESRD). We extract the information of patients who started their ESRD services in 2007-2011 from the United States Renal Data System (USRDS). Patients are partitioned into three groups based on their kidney transplant status: 1-unwaitlisted and never transplanted, 2-waitlisted but never transplanted, and 3-waitlisted and then transplanted.

Responsive Magnetic Particle Imaging Tracer: Overcoming "Always-On" Limitation, Eliminating Interference, and Ensuring Safety in Adaptive Therapy.

Magnetic particle imaging (MPI) has emerged as a novel technology utilizing superparamagnetic nanoparticles as tracers, essential for disease diagnosis and treatment guidance in preclinical animal models. Unlike other modalities, MPI provides high sensitivity, deep tissue penetration, and no signal attenuation. However, existing MPI tracers suffer from "always-on" signals, which complicate organ-specific imaging and hinder accuracy.

Kernel Estimation of Bivariate Time-varying Coefficient Model for Longitudinal Data with Terminal Event.

We propose a nonparametric bivariate time-varying coefficient model for longitudinal measurements with the occurrence of a terminal event that is subject to right censoring. The time-varying coefficients capture the longitudinal trajectories of covariate effects along with both the followup time and the residual lifetime. The proposed model extends the parametric conditional approach given terminal event time in recent literature, and thus avoids potential model misspecification.

Conditional Distribution Function Estimation Using Neural Networks for Censored and Uncensored Data.

Most work in neural networks focuses on estimating the conditional mean of a continuous response variable given a set of covariates. In this article, we consider estimating the conditional distribution function using neural networks for both censored and uncensored data. The algorithm is built upon the data structure particularly constructed for the Cox regression with time-dependent covariates.

Debiased lasso for stratified Cox models with application to the national kidney transplant data.

The Scientific Registry of Transplant Recipients (SRTR) system has become a rich resource for understanding the complex mechanisms of graft failure after kidney transplant, a crucial step for allocating organs effectively and implementing appropriate care. As transplant centers that treated patients might strongly confound graft failures, Cox models stratified by centers can eliminate their confounding effects. Also, since recipient age is a proven non-modifiable risk factor, a common practice is to fit models separately by recipient age groups.

Group vs Individual Prenatal Care and Gestational Diabetes Outcomes: A Secondary Analysis of a Randomized Clinical Trial.

Importance: The impact of group-based prenatal care (GPNC) model in the US on the risk of gestational diabetes (GD) and related adverse obstetric outcomes is unknown.

Objective: To determine the effects of the GPNC model on risk of GD, its progression, and related adverse obstetric outcomes.

Design, Setting, And Participants: This is a single-site, parallel-group, randomized clinical trial conducted between February 2016 and March 2020 at a large health care system in Greenville, South Carolina.

Statistical Inference for Cox Proportional Hazards Models with a Diverging Number of Covariates.

For statistical inference on regression models with a diverging number of covariates, the existing literature typically makes sparsity assumptions on the inverse of the Fisher information matrix. Such assumptions, however, are often violated under Cox proportion hazards models, leading to biased estimates with under-coverage confidence intervals. We propose a modified debiased lasso method, which solves a series of quadratic programming problems to approximate the inverse information matrix without posing sparse matrix assumptions.

Zinc-Carnosine Metallodrug Network as Dual Metabolism Inhibitor Overcoming Metabolic Reprogramming for Efficient Cancer Therapy.

The targeting of tumor metabolism as a novel strategy for cancer therapy has attracted tremendous attention. Herein, we develop a dual metabolism inhibitor, Zn-carnosine metallodrug network nanoparticles (Zn-Car MNs), which exhibits good Cu-depletion and Cu-responsive drug release, causing potent inhibition of both OXPHOS and glycolysis. Notably, Zn-Car MNs can decrease the activity of cytochrome c oxidase and the content of NAD, so as to reduce ATP production in cancer cells.

Posterior white matter hyperintensities are associated with reduced medial temporal lobe subregional integrity and long-term memory in older adults.

White matter hyperintensities are a marker of small vessel cerebrovascular disease that are strongly related to cognition in older adults. Similarly, medial temporal lobe atrophy is well-documented in aging and Alzheimer's disease and is associated with memory decline. Here, we assessed the relationship between lobar white matter hyperintensities, medial temporal lobe subregional volumes, and hippocampal memory in older adults.

Examination of Medication Use Patterns by Age Group, Comorbidity, and Month in COVID-19 Positive Patients in a Large Statewide Health System During the Pandemic in 2020.

Understanding medication use patterns for patients with COVID-19 will provide needed insight into the evolution of COVID-19 treatment over the course of the SARS-CoV-2 pandemic and aid clinical management considerations. To systematically determine most frequently used medications among COVID-19 patients overall and by hospitalization status. Secondary objective was use measurement of medications considered potential therapeutic options.

Debiased lasso for generalized linear models with a diverging number of covariates.

Modeling and drawing inference on the joint associations between single-nucleotide polymorphisms and a disease has sparked interest in genome-wide associations studies. In the motivating Boston Lung Cancer Survival Cohort (BLCSC) data, the presence of a large number of single nucleotide polymorphisms of interest, though smaller than the sample size, challenges inference on their joint associations with the disease outcome. In similar settings, we find that neither the debiased lasso approach (van de Geer et al.

Symptoms of obstructive sleep apnea are associated with less frequent exercise and worse subjective cognitive function across adulthood.

Study Objectives: To determine whether subjective measures of exercise and sleep are associated with cognitive complaints and whether exercise effects are mediated by sleep.

Methods: This study analyzed questionnaire data from adults (18-89) enrolled in a recruitment registry. The Cognitive Function Instrument (CFI) assessed cognitive complaints.

A Structured Brain-wide and Genome-wide Association Study Using ADNI PET Images.

A multi-stage variable selection method is introduced for detecting association signals in structured brain-wide and genome-wide association studies (brain-GWAS). Compared to conventional single-voxel-to-single-SNP approaches, our approach is more efficient and powerful in selecting the important signals by integrating anatomic and gene grouping structures in the brain and the genome, respectively. It avoids large number of multiple comparisons while effectively controls the false discoveries.

Medication Use Patterns in Hospitalized Patients With COVID-19 in California During the Pandemic.

This cohort study examines trends in medication use among patients hospitalized for COVID-19–related treatment in a large US university health care system from the start of stay-at-home orders in March 2020 throughout the rest of the year.

Ratiometric Semiconducting Polymer Nanoparticle for Reliable Photoacoustic Imaging of Pneumonia-Induced Vulnerable Atherosclerotic Plaque in Vivo.

Acute pneumonia can greatly increase the vulnerable risk of atherosclerotic plaque and contribute to the mortality of cardiovascular disease. To accurately assess the rupture risk caused by acute pneumonia, we developed a novel kind of ratiometric semiconducting polymer nanoparticle (RSPN) for photoacoustic imaging of vulnerable plaque in apolipoprotein E-deficient mice complicated with pneumonia. Specifically, RSPN can react with O and exhibit the enhanced photoacoustic signals at about 690 nm, while 800 nm is regarded as an internal photoacoustic reference.

Retention of Alzheimer Disease Research Participants.

Introduction: Participant retention is important to maintaining statistical power, minimizing bias, and preventing scientific error in Alzheimer disease and related dementias research.

Methods: We surveyed representative investigators from NIH-funded Alzheimer's Disease Research Centers (ADRC), querying their use of retention tactics across 12 strategies. We compared survey results to data from the National Alzheimer's Coordinating Center for each center.

Morphometric changes at the craniocervical junction during childhood.

Objective: Current understanding of how the pediatric craniocervical junction develops remains incomplete. Measurements of anatomical relationships at the craniocervical junction can influence clinical and surgical decision-making. The purpose of this analysis was to quantitatively define clinically relevant craniocervical junction measurements in a population of children with CT scans that show normal anatomy.

Age at Onset of Metabolic Syndrome Among Women With and Without Polycystic Ovary Syndrome-Like Status.

Context: Women with polycystic ovary syndrome (PCOS) have a higher prevalence of metabolic syndrome (MetS), but whether they develop MetS earlier than women without PCOS is unknown. Understanding the impact of PCOS on the timing of MetS onset is important for screening and clinical care in this population.

Design: Women with PCOS-like status (PCOSp) were identified from participants of the Michigan Bone Health and Metabolism Study based upon history of irregular menstrual cycles, high free-androgen index, and high levels of antimüllerian hormone.

Optimizing Electronic Release of Imaging Results through an Online Patient Portal.

Purpose To determine an optimal embargo period preceding release of radiologic test results to an online patient portal. Materials and Methods This prospective discrete choice conjoint survey with modified orthogonal design was administered to patients by trained interviewers at four outpatient sites and two institutions from December 2016 to February 2018. Three preferences for receiving imaging results associated with a possible or known cancer diagnosis were evaluated: delay in receipt of results (1, 3, or 14 days), method of receipt (online portal, physician's office, or phone), and condition of receipt (before, at the same time as, or after health care provider).

Proportional cross-ratio model.

Cross-ratio is an important local measure of the strength of dependence among correlated failure times. If a covariate is available, it may be of scientific interest to understand how the cross-ratio varies with the covariate as well as time components. Motivated by the Tremin study, where the dependence between age at a marker event reflecting early lengthening of menstrual cycles and age at menopause may be affected by age at menarche, we propose a proportional cross-ratio model through a baseline cross-ratio function and a multiplicative covariate effect.

Distinguishing acute from chronic aortic dissections using CT imaging features.

The aim was to compare computed tomography (CT) features in acute and chronic aortic dissections (AADs and CADs) and determine if a certain combination of imaging features was reliably predictive of the acute versus chronic nature of disease in individual patients. Consecutive patients with aortic dissection and a chest CT scan were identified, and 120 CT scans corresponding to 105 patients were reviewed for a variety of imaging features. Statistical tests assessed for differences in the frequency of these features.