Faculty Bibliography

INTRODUCTION/BACKGROUND:Despite longstanding status as a public health priority, preterm birth rates continue to be higher among non-Hispanic Black women compared with other racial and ethnic groups. A growing body of literature highlights the site of care as a key factor in pregnancy outcomes. Although research shows that many individuals do not receive guideline-based prenatal care, little is known about site-level variation in the use of recommended prenatal services and its potential relationship with Black-White preterm birth disparities. METHODS:In this cross-sectional cohort study, we analyzed variation in site-level use of 4 key prenatal services: tetanus, diphtheria, and pertussis (Tdap) vaccination, [per the CDC website] and screening for bacteriuria, diabetes, and group Beta streptococcus, using administrative data from New York State Medicaid and the American Community Survey. We used multivariable logistic regressions to estimate the odds of attending a low-use site (mean <2 services per patient) by race and ethnicity, controlling for age, high-poverty residential address, and low prenatal care attendance. We performed Fairlie decomposition analyses to quantify the contribution of individual and site-level factors to the observed difference in preterm birth rates among Black and White non-Hispanic women. RESULTS:Site-level use of recommended prenatal services ranged from an average of 1 to 3.6 services per patient. Non-Hispanic Black women had more than twice the odds (adjusted odds ratio, 2.42; 95% CI, 2.32-2.52) of attending a low-use site compared with non-Hispanic White women. Among factors in the decomposition analysis, site-level screening for bacteriuria and diabetes accounted for the highest proportion of the explained variance in the observed preterm birth rates for non-Hispanic Black (10.7%) and non-Hispanic White (6.7%) women. DISCUSSION/CONCLUSIONS:Results from this research support immediate improvement in guideline-based prenatal care to narrow the gap in preterm birth for non-Hispanic Black women. Research is needed to identify and correct site-level barriers to recommended prenatal services.

Xylose constitutes the second major sugar fraction of the plant-derived lignocellulosic biomass, which is the most abundantly available and renewable feedstock for microbial fermentations. Hence, comprehensive utilization of xylose is crucial from the perspective of sustainable development of bio-based products, such as fuels, fine chemicals, and high-value compounds. Due to several inherent advantages, various species and strains of yeast are employed to produce these biomolecules. With the advancement of genetic engineering in yeast, lignocellulosic biomass has begun to be commercialized for producing various bioproducts required in the food, fuel, pharmaceutical, chemical, and cosmetics industries. The increasing demands of these bioproducts worldwide lead to a necessity of utilizing xylose efficiently for yeast fermentation strategies together with/replacing glucose for more economic sustainability. However, yeast fermentation processes mostly employ glucose; hence, our understanding of xylose utilization by yeast has not been as scrupulous as it should have been. There has been a remarkable increase in the number of studies conducted on xylose utilization and metabolism in yeasts in the past decade. Our objective in this chapter is to highlight the key advancements and novel approaches in this area and to integrate our understanding of xylose metabolism in yeasts, which can help culminate into commercializing strategies in the future for the development of important bioproducts.

OBJECTIVE:Postpartum hemorrhage (PPH) is the leading cause of maternal morbidity and mortality worldwide. This case study aims to assess current PPH at our study site hospital, identify strategies to enhance management based on audit findings, and pilot test the feasibility and acceptability of these strategies. METHODS:A criteria-based audit (CBA) was conducted at La Maternidad Renee Klang Viuda Guzman Hospital in Santiago, Dominican Republic from November 2021 to September 2022. The audit assessed current practice through surveys of 59 healthcare workers and a retrospective review of 10 PPH cases, using eight evidence-based criteria. Audit findings informed the development of a PPH toolkit, protocol, and simulation-based training program (SBT). The toolkit's impact was evaluated through surveys, and SBT effectiveness was assess through post-training feedback from participants. RESULTS:The baseline audit revealed 25% compliance with evidence-based criteria. Key gaps included maternal risk assessment, provider training, and protocol use. Targeted strategies, including a PPH toolkit, protocol and SBT, were implemented. Of the 13 toolkit users, 92% felt it improved timely management. Post-SBT surveys showed that participants rated the training highly, with significant improvements in communication, teamwork, and self-reported competence in PPH management. CONCLUSION/CONCLUSIONS:CBAs are effective in identifying care barriers in middle-income settings. The PPH toolkit and SBT were well received and improved both technical and non-technical skills, offering a scalable model for improving PPH management in low-resource settings.

Platform trials are multi-arm designs that simultaneously evaluate multiple treatments for a single disease within the same overall trial structure. Unlike traditional randomized controlled trials, they allow treatment arms to enter and exit the trial at distinct times while maintaining a control arm throughout. This control arm comprises both concurrent controls, where participants are randomized concurrently to either the treatment or control arm, and non-concurrent controls, who enter the trial when the treatment arm under study is unavailable. While flexible, platform trials introduce the challenge of using non-concurrent controls, raising questions about estimating treatment effects. Specifically, which estimands should be targeted? Under what assumptions can these estimands be identified and estimated? Are there any efficiency gains? In this article, we discuss issues related to the identification and estimation assumptions of common choices of estimand. We conclude that the most robust strategy to increase efficiency without imposing unwarranted assumptions is to target the concurrent average treatment effect (cATE), the ATE among only concurrent units, using a covariate-adjusted doubly robust estimator. Our studies suggest that, for the purpose of obtaining efficiency gains, collecting important prognostic variables is more important than relying on non-concurrent controls. We also discuss the perils of targeting ATE due to an untestable extrapolation assumption that will often be invalid. We provide simulations illustrating our points and an application to the ACTT platform trial, resulting in a 20% improvement in precision compared to the naive estimator that ignores non-concurrent controls and prognostic variables.

High-dimensional multiplexed imaging can reveal the spatial organization of tumour tissues at the molecular level. However, owing to the scale and information complexity of the imaging data, it is challenging to discover and thoroughly characterize the heterogeneity of tumour microenvironments. Here we show that self-supervised representation learning on data from imaging mass cytometry can be leveraged to distinguish morphological differences in tumour microenvironments and to precisely characterize distinct microenvironment signatures. We used self-supervised masked image modelling to train a vision transformer that directly takes high-dimensional multiplexed mass-cytometry images. In contrast with traditional spatial analyses relying on cellular segmentation, the vision transformer is segmentation-free, uses pixel-level information, and retains information on the local morphology and biomarker distribution. By applying the vision transformer to a lung-tumour dataset, we identified and validated a monocytic signature that is associated with poor prognosis.

Individuals with heritable thoracic aortic disease (HTAD) face a high risk of deadly aortic dissections, but genetic testing identifies causative variants in only a minority of cases. We explored the contribution of non-canonical splice variants (NCVAS) to thoracic aortic disease (TAD) using SpliceAI and sequencing data from diverse cohorts, including 551 early-onset sporadic dissection cases and 437 HTAD probands with exome sequencing, 57 HTAD pedigrees with whole genome sequencing, and select sporadic cases with clinical panel testing. NCVAS were identified in syndromic HTAD genes such as FBN1, SMAD3, and COL3A1, including intronic variants in FBN1 in two Marfan syndrome (MFS) families. Validation in the Penn Medicine BioBank and UK Biobank showed enrichment of NCVAS in HTAD-associated genes among dissections. These findings suggest NCVAS are an underrecognized contributor to TAD, particularly in sporadic dissection and unsolved MFS cases, highlighting the potential of advanced splice prediction tools in genetic diagnostics.

BACKGROUND:In clinical settings, counseling patients on physical activity starts by assessing patients' current physical activity levels. Self-report measures of PA are generally easy to administer; however, they may be too long to be convenient and are known to correlate poorly with objective measures of physical activity. OBJECTIVE:To assess the concurrent validity of a self-report three-question physical activity vital sign with objective Fitbit step counts and the distance walked during a 6-min walk test. METHODS:This pilot study tested a best practice advisory embedded in the Epic electronic health record, which was designed to prompt providers in a preventive cardiology clinic to counsel patients reporting low levels of physical activity . Patients were invited to participate in the remote patient monitoring phase to assess the change in their physical activity by wearing a Fitbit for 12 weeks and completing a 6-min walk test at baseline and 12 weeks. This analysis used the cross-sectional data collected in this phase. Pearson correlations were conducted between self-reported physical activity, Fitbit step counts, and the distance walked during the 6-min walk-a measure associated with current physical activity levels. Kappa coefficients were calculated to assess agreement between the self-reported physical activity and step counts. RESULTS:Participants who enrolled in the Fitbit monitoring were approximately 50% female, with the majority identified as White non-Hispanic adults. Their most common cardiovascular risk factor was hypertension. The self-reported physical activity vital signs were significantly associated with step counts at baseline and 12 weeks but were not associated with the distance during the 6-min walk test. However, the distance walked was significantly associated with step counts at baseline and 12 weeks. The Kappa results demonstrate a poor level of agreement between two categories (meeting or not meeting current physical activity guidelines) of self-report physical activity vitals and the objective Fitbit step counts. DISCUSSION/CONCLUSIONS:There were moderate correlations between the self-reported physical activity vital signs and the Fitbit step counts, but there was lack of agreement when they were categorized. Further validation of this physical activity vital sign is warranted.

The mechanisms behind comorbid symptoms of depression in persons with epilepsy (PWE) remain largely unknown. Our study aimed to learn whether seizures moderate fluctuations in depressive symptoms in PWE when controlling for preictal symptoms of depression. We enrolled 57 adult PWE admitted to the New York University (NYU) Langone Epilepsy Monitoring Unit (EMU) from 2021 to 2024. Thirty-seven participants had a seizure. Twenty of the admitted patients did not have seizures during the admission period and therefore served as controls. All participants were seizure free for > 7 days prior to participation. Upon admission, all participants completed the Montgomery-Asberg Depression Rating Scale (MADRS) to evaluate baseline mood. The MADRS was repeated acutely (4-24 h post seizure or admission) and subacutely (2-7 days post seizure or discharge) for both groups. Linear regression models revealed that individuals with higher baseline MADRS scores (indicating higher depressive symptoms) experienced worse mood acutely post-seizure, while lower baseline MADRS scores were associated with acute mood improvement (R² = 0.59, p < 0.001). Experiencing a seizure was not associated with subacute mood outcomes, which were instead driven by acute mood state (R² = 0.56, p < 0.001). In conclusion, we found that seizures exacerbate pre-ictal depressive symptoms and that post-ictal depressive symptoms persist up to 7 days after seizure resolution. This study may provide evidence for a bidirectional relationship and demonstrate a vicious cycle between depression and epilepsy.