Summary of Work Report: Equity-Methods Curriculum TA

In Spring 2021, the Department of Epidemiology at UNC Chapel Hill created a first of its kind position - the "Equity-Methods Curriculum TA." The primary goal of the Equity-Methods Curriculum TA was to identify opportunities to strategically layer and integrate concepts of health equity and anti-racism into the existing material students experience as they advance through the core methods curriculum. This report summarizes the work completed by Rae Anne M. Martinez between May 2021-May 2022, during the inaugural year of the position. Additional context on the thematic and logistical structure of the Department of Epidemiology's core methods curriculum, prior changes (2017-2021), original scope of work, and approach is also provided. This report has been edited for external sharing and distribution. A more detailed version of this report was provided to Department of Epidemiology leadership on April 18th, 2022. The current revised version was created in November 2022. Questions regarding this report and the on-going work can be directed to the Director of Graduate Studies Committee (GSC), currently Dr. Brian Pence ([email protected])

Screening for Sugarcane Root Phenes Reveals That Reducing Tillering Does Not Lead to an Increased Root Mass Fraction

Sugarcane root systems are poorly studied and understood due to the perennial nature, tall stature, and the long cropping cycle. Whilst some field studies gave insights into sugarcane root traits, there is no detailed description of root and root system traits available. The objectives of our work were to establish a baseline of sugarcane root trait values that will serve for future studies, and to characterize the degree of root system resilience when restricting tiller number. We first conducted an initial screening for root trait diversity on a collection of twenty cultivars representative of sugarcane breeding from 1930 to now. Then we investigated the effect of reduced tillering, via manual de-tillering, on the plant root and root system traits of five varieties grown under optimal conditions in a glasshouse for 1700°Cd. In addition to establishing baseline means and variation for sugarcane root trait values that could serve as a reference for crop models, we demonstrated that the sugarcane root mass fraction was extremely resilient to drastic reduction in tiller number. Restricted plants were effectively maintaining their root system configuration (opening angle) by dramatically increasing the number of nodal roots produced per tiller as well as maximizing total root length by increasing the specific root length. Using this knowledge of sugarcane root traits in combination with the specific agronomic constraints for sugarcane will now underpin the development of a root system ideotype for sugarcane to enable targeted root trait selection for improving crop productivity

Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019.

BackgroundAs of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak.MethodsFor short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts.ResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone.ConclusionsOur projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges

The air–liquid interface model

The airway epithelium lining the airways is in first contact with the inhaled environment, which contains allergens, gaseous pollutants, particulates, and pathogenic microorganisms. It forms an ion- and size-selective barrier between the inhaled environment and the underlying tissue by the formation of intercellular tight junctions and adhesion junctions. Additionally, the airway epithelium plays an important role in innate immune defense, expressing receptors that recognize molecular patterns from pathogenic microbes, parasites, fungi, and allergens and danger signals from damaged cells, directing proinflammatory processes. Chronic lung diseases, such as asthma and chronic obstructive pulmonary disease, involve changes in airway epithelial function. For valuable insights into these changes, in vitro models should closely recapitulate human airway epithelial composition, three-dimensional structure, and function as an immunological barrier. The goal of this chapter is to review the literature on the use of air–liquid interface cultures to model the lung epithelium in health and disease.</p

Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018.

As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration

Effects of exemestane and letrozole therapy on plasma concentrations of estrogens in a randomized trial of postmenopausal women with breast cancer

PURPOSE: Inter-individual differences in estrogen concentrations during treatment with aromatase inhibitors (AIs) may contribute to therapeutic response and toxicity. The aim of this study was to determine plasma concentrations of estradiol (E2), estrone (E1), and estrone sulfate (E1S) in a large cohort of AI-treated breast cancer patients. METHODS: In a randomized, multicenter trial of postmenopausal women with early-stage breast cancer starting treatment with letrozole (n = 241) or exemestane (n = 228), plasma estrogen concentrations at baseline and after 3 months were quantitated using a sensitive mass spectrometry-based assay. Concentrations and suppression below the lower limit of quantification (LLOQ) were compared between estrogens and between drugs. RESULTS: The ranges of baseline estrogen concentrations were <LLOQ-361 pg/mL for E2, <LLOQ-190 pg/mL for E1, and 8.3-4060 pg/mL for E1S. For E2, the frequency of suppression below the LLOQ was not statistically significantly different between AIs (exemestane: 89.0%, letrozole: 86.9%, p = 0.51). However, patients on letrozole were more likely to achieve suppression below the LLOQ of both E1 (exemestane: 80.1%, letrozole: 90.1%, p = 0.005) and E1S (exemestane: 17.4%, letrozole: 54.9%, p = 4.34e-15). After 3 months of AI therapy, the ranges of estrogen concentrations were <LLOQ-63.8 pg/mL, <LLOQ-36.7 pg/mL, and <LLOQ-1090 pg/mL for E2, E1, and E1S, respectively. During treatment, 16 patients had an increased concentration compared to the baseline concentration of at least one estrogen. CONCLUSIONS: Letrozole had greater suppression of plasma E1 and E1S than exemestane, though the response was highly variable among patients. Additional research is required to examine the clinical relevance of differential estrogen suppression

Targeting mitochondrial 18 kDa translocator protein (TSPO) regulates macrophage cholesterol efflux and lipid phenotype

Abstract The aim of the present study was to establish mitochondrial cholesterol trafficking 18 kDa translocator protein (TSPO) as a potential therapeutic target, capable of increasing macrophage cholesterol efflux to (apo)lipoprotein acceptors. Expression and activity of TSPO in human (THP-1) macrophages were manipulated genetically and by the use of selective TSPO ligands

QTLs for shelf life in lettuce co-locate with those for leaf biophysical properties but not with those for leaf developmental traits

Developmental and biophysical leaf characteristics that influence post-harvest shelf life in lettuce, an important leafy crop, have been examined. The traits were studied using 60 informative F9 recombinant inbed lines (RILs) derived from a cross between cultivated lettuce (Lactuca sativa cv. Salinas) and wild lettuce (L. serriola acc. UC96US23). Quantitative trait loci (QTLs) for shelf life co-located most closely with those for leaf biophysical properties such as plasticity, elasticity, and breakstrength, suggesting that these are appropriate targets for molecular breeding for improved shelf life. Significant correlations were found between shelf life and leaf size, leaf weight, leaf chlorophyll content, leaf stomatal index, and epidermal cell number per leaf, indicating that these pre-harvest leaf development traits confer post-harvest properties. By studying the population in two contrasting environments in northern and southern Europe, the genotype by environment interaction effects of the QTLs relevant to leaf development and shelf life were assessed. In total, 107 QTLs, distributed on all nine linkage groups, were detected from the 29 traits. Only five QTLs were common in both environments. Several areas where many QTLs co-located (hotspots) on the genome were identified, with relatively little overlap between developmental hotspots and those relating to shelf life. However, QTLs for leaf biophysical properties (breakstrength, plasticity, and elasticity) and cell area correlated well with shelf life, confirming that the ideal ideotype lettuce should have small cells with strong cell walls. The identification of QTLs for leaf development, strength, and longevity will lead to a better understanding of processability at a genetic and cellular level, and allow the improvement of salad leaf quality through marker-assisted breeding

Resource Packet for "Clear communication of race and ethnicity for public health: best practices & common failings"

This work was created as a resource packet for attendees of the Interdisciplinary Association for Population Health Science (IAPHS)'s pre-conference workshop "Clear communication of race and ethnicity for public health: Best practices & common failings." The pre-conference workshop was held virtually on September 23rd, 2021 and facilitated by the author team

Revised timeline and distribution of the earliest diverged human maternal lineages in southern Africa

The oldest extant human maternal lineages include mitochondrial haplogroups L0d and L0k found in the southern African click-speaking forager peoples broadly classified as Khoesan. Profiling these early mitochondrial lineages allows for better understanding of modern human evolution. In this study, we profile 77 new early-diverged complete mitochondrial genomes and sub-classify another 105 L0d/L0k individuals from southern Africa. We use this data to refine basal phylogenetic divergence, coalescence times and Khoesan prehistory. Our results confirm L0d as the earliest diverged lineage (∼172 kya, 95%CI: 149-199 kya), followed by L0k (∼159 kya, 95%CI: 136-183 kya) and a new lineage we name L0g (∼94 kya, 95%CI: 72-116 kya). We identify two new L0d1 subclades we name L0d1d and L0d1c4/L0d1e, and estimate L0d2 and L0d1 divergence at ∼93 kya (95%CI:76-112 kya). We concur the earliest emerging L0d1’2 sublineage L0d1b (∼49 kya, 95%CI:37-58 kya) is widely distributed across southern Africa. Concomitantly, we find the most recent sublineage L0d2a (∼17 kya, 95%CI:10-27 kya) to be equally common. While we agree that lineages L0d1c and L0k1a are restricted to contemporary inland Khoesan populations, our observed predominance of L0d2a and L0d1a in non-Khoesan populations suggests a once independent coastal Khoesan prehistory. The distribution of early-diverged human maternal lineages within contemporary southern Africans suggests a rich history of human existence prior to any archaeological evidence of migration into the region. For the first time, we provide a genetic-based evidence for significant modern human evolution in southern Africa at the time of the Last Glacial Maximum at between ∼21-17 kya, coinciding with the emergence of major lineages L0d1a, L0d2b, L0d2d and L0d2a