Monitoring emerging pathogens using negative nucleic acid test results from endemic pathogens in pig populations: Application to porcine enteric coronaviruses.

This study evaluated the use of endemic enteric coronaviruses polymerase chain reaction (PCR)-negative testing results as an alternative approach to detect the emergence of animal health threats with similar clinical diseases presentation. This retrospective study, conducted in the United States, used PCR-negative testing results from porcine samples tested at six veterinary diagnostic laboratories. As a proof of concept, the database was first searched for transmissible gastroenteritis virus (TGEV) negative submissions between January 1st, 2010, through April 29th, 2013, when the first porcine epidemic diarrhea virus (PEDV) case was diagnosed. Secondly, TGEV- and PEDV-negative submissions were used to detect the porcine delta coronavirus (PDCoV) emergence in 2014. Lastly, encountered best detection algorithms were implemented to prospectively monitor the 2023 enteric coronavirus-negative submissions. Time series (weekly TGEV-negative counts) and Seasonal Autoregressive-Integrated Moving-Average (SARIMA) were used to control for outliers, trends, and seasonality. The SARIMA's fitted and residuals were then subjected to anomaly detection algorithms (EARS, EWMA, CUSUM, Farrington) to identify alarms, defined as weeks of higher TGEV-negativity than what was predicted by models preceding the PEDV emergence. The best-performing detection algorithms had the lowest false alarms (number of alarms detected during the baseline) and highest time to detect (number of weeks between the first alarm and PEDV emergence). The best-performing detection algorithms were CUSUM, EWMA, and Farrington flexible using SARIMA fitted values, having a lower false alarm rate and identified alarms 4 to 17 weeks before PEDV and PDCoV emergences. No alarms were identified in the 2023 enteric negative testing results. The negative-based monitoring system functioned in the case of PEDV propagating epidemic and in the presence of a concurrent propagating epidemic with the PDCoV emergence. It demonstrated its applicability as an additional tool for diagnostic data monitoring of emergent pathogens having similar clinical disease as the monitored endemic pathogens.

Early Surgical Excision of Necrotic Tissue Following Unintentional Dermal Injection of Extended-Release Buprenorphine.

INTRODUCTION: Extended-release subcutaneous buprenorphine is an increasingly common treatment for opioid use disorder. Serious adverse events are rare and may be poorly understood. This report describes an early surgical intervention to address tissue necrosis resulting from misplaced subcutaneous buprenorphine injection. We review identifying characteristics that distinguish the necrotic reaction from other adverse effects of subcutaneous buprenorphine and offer guidance to continue treatment with subcutaneous buprenorphine. CASE REPORT: A 33-year-old patient returned to clinic within an hour of his buprenorphine injection, reporting pain and skin changes unlike his previous injections. Non blanching erythema consistent with early necrosis was evident, and the patient was referred for surgical removal of his buprenorphine depot. The patient had uncomplicated healing of the surgical site and was provided sublingual buprenorphine before returning to continue treatment with subcutaneous buprenorphine. DISCUSSION: Although skin necrosis is known to be a rare complication of subcutaneous buprenorphine injection, early surgical excision to limit injury has not been described. Signs and symptoms of skin necrosis must be better understood to facilitate early intervention and continued treatment. CONCLUSIONS: This case affirms that a patient may continue treatment with subcutaneous buprenorphine despite suffering skin necrosis and demonstrates the value of early surgical intervention after superficial placement of extended-release buprenorphine.

Assessing and attenuating the impact of selection bias on spatial cluster detection studies.

Spatial cluster analyses are commonly used in epidemiologic studies of case-control data to detect whether certain areas in a study region have an excess of disease risk. Case-control studies are susceptible to potential biases including selection bias, which can result from non-participation of eligible subjects in the study. However, there has been no systematic evaluation of the effects of non-participation on the findings of spatial cluster analyses. In this paper, we perform a simulation study assessing the effect of non-participation on spatial cluster analysis using the local spatial scan statistic under a variety of scenarios that vary the location and rates of study non-participation and the presence and intensity of a zone of elevated risk for disease for simulated case-control studies. We find that geographic areas of lower participation among controls than cases can greatly inflate false-positive rates for identification of artificial spatial clusters. Additionally, we find that even modest non-participation outside of a true zone of elevated risk can decrease spatial power to identify the true zone. We propose a spatial algorithm to correct for potentially spatially structured non-participation that compares the spatial distributions of the observed sample and underlying population. We demonstrate its ability to markedly decrease false positive rates in the absence of elevated risk and resist decreasing spatial sensitivity to detect true zones of elevated risk. We apply our method to a case-control study of non-Hodgkin lymphoma. Our findings suggest that greater attention should be paid to the potential effects of non-participation in spatial cluster studies.

Smoking is not associated with wound complications in augmented urethroplasty: a NSQIP analysis.

OBJECTIVE: To investigate if predictors of wound complications differed between patients undergoing excision and primary anastomosis urethroplasty (EPA) and augmented urethroplasty. METHODS: The National Surgical Quality Improvement Program database from 2006 to 2018 was queried for male patients undergoing urethroplasty. Thirty-day wound complications were identified and categorized (superficial/deep/organ-space surgical site infections and dehiscence). Multivariable logistic regression was performed to determine risk factors associated with wound complications. Smoking history was defined as current smoker within the past year. RESULTS: Urethroplasty was performed in 2251 males, with 25.46% (n = 573) using a flap or graft. There was no significant difference in wound complications for patients undergoing augmented urethroplasty (n = 17, 2.97%) or EPA (n = 45, 2.68%) (p = 0.9). The augmented group had a higher BMI, longer operative time, and longer length of stay. On multivariable logistic regression, risk factors associated with wound complications for patients undergoing EPA were diabetes (OR 2.56, p = 0.03) and smoking (OR 2.32, p = 0.02). However, these factors were not associated with wound complications in patients undergoing augmented urethroplasty. CONCLUSIONS: Smoking and diabetes were associated with increased wound complications for men undergoing EPA, but not in patients undergoing augmented urethroplasty. Patients with comorbidities associated with worse wound healing may be more likely to have a wound complication when undergoing EPA.

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model.

Mixture analysis is an emerging statistical tool in epidemiological research that seeks to estimate the health effects associated with mixtures of several exposures. This approach acknowledges that individuals experience many simultaneous exposures and it can estimate the relative importance of components in the mixture. Health effects due to mixtures may vary over space driven by to political, demographic, environmental, or other differences. In such cases, estimating a global mixture effect without accounting for spatial variation would induce bias in effect estimates and potentially lower statistical power. To date, no methods have been developed to estimate spatially varying chemical mixture effects. We developed a Bayesian spatially varying mixture model that estimates spatially varying mixture effects and the importance weights of components in the mixture, while adjusting for covariates. We demonstrate the efficacy of the model through a simulation study that varies the number of mixtures (one and two) and spatial pattern (global, one-dimensional, radial) and magnitude of mixture effects, showing that the model is able to accurately reproduce the spatial pattern of mixture effects across a diverse set of scenarios. Finally, we apply our model to a multi-center case-control study of non-Hodgkin lymphoma (NHL) in Detroit, Iowa, Los Angeles, and Seattle. We identify significant spatially varying positive and inverse associations with NHL for two mixtures of pesticides in Iowa and do not find strong spatial effects at the other three centers. In conclusion, the Bayesian spatially varying mixture model represents a novel method for modeling spatial variation in mixture effects.

Analysis of the spatial distribution of amyotrophic lateral sclerosis in Virginia.

Objective: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that is usually fatal. Environmental exposures have been posited in the etiology of ALS, but few studies have modeled the spatial risk of ALS over large geographic areas. In this paper, our goal was to analyze the spatial distribution of ALS in Virginia and identify any areas with significantly elevated risk using Virginia ALS Association administrative data. Methods: We used Bayesian hierarchical spatial regression models to estimate the relative risk for ALS in Virginia census tracts, adjusting for several covariates posited to be associated with the disease. We used an intrinsic conditional autoregressive prior to allow for spatial correlation in the risk estimates and stabilize estimates over space. Results: Considerable variation in ALS risk existed across Virginia, with greater relative risk found in the central and western parts of the state. We identified significantly elevated relative risk in a number of census tracts. In particular, Henrico, Albemarle, and Botetourt counties all contained at least four census tracts with significantly elevated risk. Conclusions: We identified several areas with significantly elevated ALS risk across Virginia census tracts. These results can inform future studies of potential environmental triggers for the disease, whose etiology is still being understood.

Modeling historic neighborhood deprivation and non-Hodgkin lymphoma risk.

Many studies have identified associations between neighborhood deprivation and disease, emphasizing the importance of social determinants of health. However, when studying diseases with long latency periods such as cancers, considering the timing of exposures for deprivation becomes more important. In this study, we estimated the associations between neighborhood deprivation indices at several time points and risk of non-Hodgkin lymphoma (NHL) in a population-based case-control study at four study centers - Detroit, Iowa, Los Angeles County, and Seattle (1998-2000). We used the Bayesian index regression model and residential histories to estimate neighborhood deprivation index effects in crude models and adjusted for four chemical mixtures measured in house dust and individual-level covariates. We found that neighborhood deprivation in 1980, approximately twenty years before study entry, provided better model fit than did neighborhood deprivation at 1990 and 2000. We identified several statistically significant associations between neighborhood deprivation in 1980 and NHL risk in Iowa and among long-term (20+ years) residents of Detroit. The most important variables in these indices were median gross rent as a percentage of household income in Iowa and percent of single-parent households with at least one child and median household income in Detroit. Associations remained statistically significant after adjustment for individual-level covariates and chemical mixtures, providing evidence for historic neighborhood deprivation as a risk factor for NHL and motivating future research to uncover the specific carcinogens driving these associations in deprived areas.

Adjuvant chemotherapy non-adherence, patient-centered communication, and patient-level factors in elderly breast and colon cancer patients.

BACKGROUND: We examined patient-level factors (patient characteristics, disease and treatment factors, and patient experience), patient-centered communication (PCCM), and non-adherence to adjuvant chemotherapy (AC) guidelines among breast and colon cancer patients to inform AC adherence promotion and improve clinical outcomes. METHODS: Descriptive statistics for patient-level factors, PCCM, and AC non-adherence (primary non-adherence, non-persistence at 3 and 6 months) were obtained. Multiple logistic regression models were used to estimate AC non-adherence after accounting for the identified patient-level factors. RESULTS: The majority of the sample (n = 577) were White (87%), breast cancer patients (87%), and reported PCCM (provider communication score ≥ 90%, 73%, provider communication score = 100%, 58%). All three levels of AC nonadherence were significantly higher in breast cancer patients (69%, 81%, and 89% for primary non-adherence, and non-persistence at 3 and 6 months, respectively) than colon cancer patients (43%, 46%, and 62%, respectively). Male sex, survey assistance, and low/average ratings of a personal doctor, specialist, and healthcare were associated with lower PCCM. Older age, breast cancer diagnosis, and diagnosis group following 2007-2009 increased the likelihood of all three levels of AC non-adherence. Comorbidities and PCCM-90 were exclusively associated with non-persistence at 3 months. CONCLUSIONS: Adjuvant chemotherapy non-adherence varied by cancer diagnosis and treatment factors. The relationship between PCCM and AC non-adherence differed by level of PCCM, time period, and the presence of comorbidities. AC guideline adherence, communication, and value-concordant treatment should be assessed and compared simultaneously to improve our understanding of their interrelationships.

A Contemporary Analysis of Combat-related Urological Injuries: Data From the Department of Defense Trauma Registry.

PURPOSE: There has been little to no literature published on combat-related genitourinary injuries beyond 2013. With the goal of enhancing medical readiness prior to deployment and making recommendations to improve the long-term rehabilitation of service members as they become civilians, we sought to describe the incidence of combat-related genitourinary injuries and interventions from January 1, 2007, to March 17, 2020. MATERIALS AND METHODS: We conducted a retrospective analysis of the Department of Defense Trauma Registry, which is a prospectively maintained database, for the time between 2007 and 2020. We used predefined search criteria to primarily identify any casualties that arrived at a military treatment facility with urological-based injuries. RESULTS: The registry contained 25,897 adult casualties, of which 7.2% sustained urological injuries. The median age was 25. Explosive injuries (64%) and firearms (27%) predominated. The median injury severity score was 18 (IQR 10-29). Most patients survived until hospital discharge (94%). The most frequently injured organs were the scrotum (60%), testes (53%), penis (30%), and kidneys (30%). Massive transfusion protocols were activated in 35% of all patients who sustained a urological injury and accounted for 28% of all protocols between 2007 and 2020. CONCLUSIONS: The incidence of genitourinary trauma persistently increased for both military and civilian personnel as the U.S. remained actively engaged in major military conflicts during this period. Patients with genitourinary trauma in this data set were often associated with high injury severity scores and required an increased number of immediate and long-term resources for survival and rehabilitation.

Adjuvant Therapy for Renal Cell Carcinoma: End Points, Outcomes, and Risk Assessments.

PURPOSE: Targeted tyrosine kinase inhibitors (TKIs) and immune-checkpoint inhibitors (ICIs) revolutionized the treatment of metastatic renal cell carcinoma (RCC). Efforts to translate these therapies into the adjuvant setting for local and locoregional RCC have been pursued over the past decade. We sought to provide an updated review of the literature regarding adjuvant therapy in RCC, as well as an analysis of patient characteristics that may portend the most favorable responses. MATERIALS AND METHODS: Using PubMed, Google Scholar, and Wiley Online Library, we reviewed articles between 2000 and 2022. Search terms included "tyrosine kinase inhibitors," "adjuvant," "immunotherapy," and "renal cell carcinoma." The articles included were original and published in English. Information on clinical trials was collected from ClinicalTrials.gov, accessed in June 2022. RESULTS: Landmark trials investigating adjuvant vascular endothelial growth factor (VEGF) inhibitors produced conflicting results, with only a single trial of sunitinib (S-TRAC) resulting in US Food and Drug Administration-approval on the basis of a slightly prolonged progression-free survival (PFS). Subsequent meta-analyses failed to show a benefit for adjuvant VEGF inhibitors. Several trials evaluating ICIs are currently ongoing, with pembrolizumab (KEYNOTE-564) earning US Food and Drug Administration-approval for a prolonged PFS, although overall survival data are not yet mature. Preliminary results from other adjuvant ICI trials have been conflicting. CONCLUSION: There remains a lack of clear benefit for the use of adjuvant VEGF inhibitors in local and locoregional RCC. Adjuvant ICI investigations are ongoing, with promising results from KEYNOTE-564. It remains to be seen if PFS is an adequate surrogate end point for overall survival. Selection of patients at greatest risk for recurrence, and identification of those at greatest risk of rare but serious adverse events, may improve outcomes.

Neighborhood Deprivation, Indoor Chemical Concentrations, and Spatial Risk for Childhood Leukemia.

Leukemia is the most common childhood cancer in industrialized countries, and the increasing incidence trends in the US suggest that environmental exposures play a role in its etiology. Neighborhood socioeconomic status (SES) has been found to be associated with many health outcomes, including childhood leukemia. In this paper, we used a Bayesian index model approach to estimate a neighborhood deprivation index (NDI) in the analysis of childhood leukemia in a population-based case-control study (diagnosed 1999 to 2006) in northern and central California, with direct indoor measurements of many chemicals for 277 cases and 306 controls <8 years of age. We considered spatial random effects in the Bayesian index model approach to identify any areas of significantly elevated risk not explained by neighborhood deprivation or individual covariates, and assessed if groups of indoor chemicals would explain any elevated spatial risk areas. Due to not all eligible cases and controls participating in the study, we conducted a simulation study to add non-participants to evaluate the impact of potential selection bias when estimating NDI effects and spatial risk. The results in the crude model showed an odds ratio (OR) of 1.06 and 95% credible interval (CI) of (0.98, 1.15) for a one unit increase in the NDI, but the association became slightly inverse when adjusting for individual level covariates in the observed data (OR = 0.97 and 95% CI: 0.87, 1.07), as well as when using simulated data (average OR = 0.98 and 95% CI: 0.91, 1.05). We found a significant spatial risk of childhood leukemia after adjusting for NDI and individual-level covariates in two counties, but the area of elevated risk was partly explained by selection bias in simulation studies that included more participating controls in areas of lower SES. The area of elevated risk was explained when including chemicals measured inside the home, and insecticides and herbicides had greater effects for the risk area than the overall study. In summary, the consideration of exposures and variables at different levels from multiple sources, as well as potential selection bias, are important for explaining the observed spatial areas of elevated risk and effect estimates.

Modeling historic environmental pollutant exposures and non-Hodgkin lymphoma risk.

Environmental exposures to chemicals are suspected risk factors for non-Hodgkin lymphoma (NHL), but few studies have assessed historic environmental risk factors. In this study, we estimated the associations between NHL and 1) historic environmental pollutant emissions from the Risk Screening Environmental Indicators (RSEI) model, which uses a database from the Environmental Protection Agency of toxic release emissions to air, water, and land, and 2) chemical mixtures measured in house dust (groups of PCBs, PAHs, and two mixtures of pesticides) for study participants enrolled in the NCI-SEER population-based case-control study (1998-2000) at four SEER centers - Detroit, Iowa, Los Angeles County, and Seattle. We assigned 11 years of annual temporally-varying historic environmental exposure scores by intersecting residential locations from participants' residential histories with a fine grid from the RSEI model and by performing inverse distance weighting between facilities releasing specific carcinogenic chemicals and residential locations for spatially-precise exposure assignments. We used Bayesian index low-rank kriging multiple membership models to identify important lag times for RSEI scores, cumulative effects of RSEI scores, and specific carcinogenic chemical releases into the environment. We found a significant positive association between RSEI scores and NHL at the maximum time lag of 11 years (OR = 1.17, 95% CI (1.06, 1.32)) and a significant cumulative RSEI score effect (OR = 1.30, 95% CI (1.02, 1.84)) for long-term residents in Detroit, where benzene and trichloroethylene were the most important chemicals driving this association. Additionally, we identified significant inverse associations for two study centers and time lags that did not persist in cumulative exposure models. Large weights for dichloromethane and pentachlorophenol in models of cumulative exposure also support evidence for their association with NHL risk. These results underscore the importance of considering historic and cumulative environmental exposures and using residential histories for diseases with long latency periods such as NHL.

The effect of TRV027 on coagulation in COVID-19: A pilot randomized, placebo-controlled trial.

COVID-19 causes significant thrombosis and coagulopathy, with elevated D-dimer a predictor of adverse outcome. The precise mechanism of this coagulopathy remains unclear; one hypothesis is that loss of angiotensin-converting enzyme 2 activity during viral endocytosis leads to pro-inflammatory angiotensin-II accumulation, loss of angiotensin-1-7 and subsequent vascular endothelial activation. We undertook a double-blind randomized, placebo-controlled experimental medicine study to assess the effect of TRV027, a synthetic angiotensin-1-7 analogue on D-dimer in 30 patients admitted to hospital with COVID-19. The study showed a similar rate of adverse events in TRV027 and control groups. There was a numerical decrease in D-dimer in the TRV027 group and increase in D-dimer in the placebo group; however, this did not reach statistical significance (P = .15). A Bayesian analysis demonstrated that there was a 92% probability that this change represented a true drug effect.

Male Genitourinary Injuries in Combat - A Review of United States and British Forces in Afghanistan and Iraq: 2001-2013.

As we look to the current conflict in Ukraine, our service members deploy to periphery Northern Atlantic Treaty Organization countries. At the same time, we see an increase in high-kinetic wounding patterns in the United States. We look to the important underrepresented topic of urologic trauma in combat casualties to prepare for the wounds of modern warfare. Genitourinary wounds are increasingly frequent and affect both military and civilian casualties; civilian urologists and deployed surgeons require proficiency in treating these wounds. We present this review of urologic trauma in Afghanistan and Iraq to inform considerations for urologic surgeons and first responders.

Pleiotropic genetic architecture and novel loci for C-reactive protein levels.

C-reactive protein is involved in a plethora of pathophysiological conditions. Many genetic loci associated with C-reactive protein are annotated to lipid and glucose metabolism genes supporting common biological pathways between inflammation and metabolic traits. To identify novel pleiotropic loci, we perform multi-trait analysis of genome-wide association studies on C-reactive protein levels along with cardiometabolic traits, followed by a series of in silico analyses including colocalization, phenome-wide association studies and Mendelian randomization. We find 41 novel loci and 19 gene sets associated with C-reactive protein with various pleiotropic effects. Additionally, 41 variants colocalize between C-reactive protein and cardiometabolic risk factors and 12 of them display unexpected discordant effects between the shared traits which are translated into discordant associations with clinical outcomes in subsequent phenome-wide association studies. Our findings provide insights into shared mechanisms underlying inflammation and lipid metabolism, representing potential preventive and therapeutic targets.

Does Time to Adjuvant Chemotherapy after Radical Cystectomy Affect Survival in Muscle Invasive Bladder Cancer? A Systematic Review.

(1) Purpose: To assess the survival benefit for different times to adjuvant chemotherapy after a radical cystectomy. (2) Materials and Methods: We systematically searched PubMed®, Cochrane Central®, Scopus®, and Web of Science® library databases for original articles that looked at timing to adjuvant chemotherapy after radical cystectomy. Primary endpoints were five-year survival, progression free survival, and overall survival. Available multivariable hazard ratios and corresponding 95% CIs were included in the qualitative analysis. The risk of bias was completed for nonrandomized studies. (3) Results: Using PRISMA guidelines, our electronic search resulted in a total of 1862 records. After a detailed review, we selected four studies that addressed the impact of the timing of adjuvant chemotherapy for patients who underwent radical cystectomy. (4) Conclusion: A survival benefit was seen with an earlier administration of adjuvant chemotherapy, albeit a benefit persists for delayed chemotherapy post-radical cystectomy. A safe and ethical approach at this time would be to administer adjuvant chemotherapy as early in the postoperative period as possible, given the known survival benefit of such therapy (9-11% absolute survival benefit at five years).

Estimating mixture effects and cumulative spatial risk over time simultaneously using a Bayesian index low-rank kriging multiple membership model.

The exposome is an ideal in public health research that posits that individuals experience risk for adverse health outcomes from a wide variety of sources over their lifecourse. There have been increases in data collection in the various components of the exposome, but novel statistical methods are needed that capture multiple dimensions of risk at once. We introduce a Bayesian index low-rank kriging (LRK) multiple membership model (MMM) to simultaneously estimate the health effects of one or more groups of exposures, the relative importance of exposure components, and cumulative spatial risk over time using residential histories. The model employs an MMM to consider all residential locations for subjects weighted by duration and LRK to increase computational efficiency. We demonstrate the performance of the Bayesian index LRK-MMM through a simulation study, showing that the model accurately and consistently estimates the health effects of one or several group indices and has high power to identify a region of elevated spatial risk due to unmeasured environmental exposures. Finally, we apply our model to data from a multicenter case-control study of non-Hodgkin lymphoma (NHL), finding a significant positive association between one index of pesticides and risk for NHL in Iowa. Additionally, we find an area of significantly elevated spatial risk for NHL in Los Angeles. In conclusion, our Bayesian index LRK-MMM represents a step forward toward bringing the ideals of the exposome into practice for environmental risk analyzes.

Interfacing With the Electronic Health Record (EHR): A Comparative Review of Modes of Documentation.

Electronic health records (EHRs) have provided physicians with a systematic framework for collecting patient data, organizing notes from the healthcare team, and managing the daily workflow in the modern era of healthcare. Despite these advantages, EHRs have proven to be problematic for clinicians. The burdensome regulations requiring increased documentation with the EHR paradigm have led to inefficiencies from data-entry requirements forcing physicians to spend an inordinate amount of time on it, affecting the time available for direct patient care as well as leading to professional burnout. As a result, new modalities such as speech recognition, medical scribes, pre-made EHR templates, and digital scribes [a form of artificial intelligence (AI) based on ambient speech recognition] are increasingly being used to reduce charting time and increase the time available for patient care. The purpose of our review is to provide an up-to-date review of the literature on these modalities including their benefits and shortcomings, to help physicians and other medical professionals choose the best methods to document their patient-care encounters efficiently and effectively.

Monoclonal Autoantibody Against a Cryptic Epitope on Tissue-Adherent Low-Density Lipoprotein for Molecular Imaging in Atherosclerosis.

BACKGROUND: Antibody-based constructs for molecular imaging and therapeutic delivery provide promising opportunities for the diagnosis and treatment of atherosclerosis. OBJECTIVES: The authors aimed to generate and characterize immunoglobulin (Ig)G monoclonal autoantibodies in atherosclerosis for targeting of novel molecular determinants. METHODS: The authors created hybridomas from an unimmunized low-density lipoprotein (LDL) receptor-deficient (Ldlr-/-) mouse and selected an IgG2b isotype autoantibody, LO9, for further characterization. RESULTS: LO9 reacted well with native LDL bound to immobilized matrix components and less well to oxidized LDL. LO9 binding to immobilized native LDL was not neutralized by fluid-phase native LDL, indicating an adhesion-dependent epitope. The authors localized the epitope to a 20 amino-acid peptide sequence (P5) in the globular amino-terminus of apolipoprotein B. LO9 reacted with antigen in mouse atherosclerosis and in both human stable and ruptured coronary atherosclerosis. Furthermore, in vivo near-infrared fluorescence molecular tomographic imaging, and ex vivo confocal microscopy showed that intravenously injected LO9 localized beneath endothelium of the aortic arch in Ldlr-/- mice, in the vicinity of macrophages. CONCLUSIONS: The authors believe LO9 is the first example of an IgG autoantibody that reacts with a native LDL epitope revealed by adherence to tissue matrix. Antibodies against adherent native LDL have potential as molecular targeting agents for imaging of and therapeutic delivery to atherosclerosis.

Tobacco Retail Outlets, Neighborhood Deprivation and the Risk of Prenatal Smoke Exposure.

INTRODUCTION: Smoking and smoke exposure among pregnant women remain persistent public health issues. Recent estimates suggest that approximately one out of four nonsmokers have measurable levels of cotinine, a marker indicating regular exposure to secondhand smoke. Epidemiological research has attempted to pinpoint individual-level and neighborhood-level factors for smoking during pregnancy. However, most of these studies have relied upon self-reported measures of smoking. AIMS AND METHODS: To more accurately assess smoke exposure resulting from both smoking and secondhand exposure in mothers during pregnancy, we used Bayesian regression models to estimate the association of cotinine levels with tobacco retail outlet (TRO) exposure and a neighborhood deprivation index (NDI) in six counties in North Carolina centered on Durham County. RESULTS: Results showed a significant positive association between TRO exposure (ß = 0.008, 95% credible interval (CI) = [0.003, 0.013]) and log cotinine after adjusting for individual covariates (eg, age, race/ethnicity, education, marital status). TRO exposure was not significant after including the NDI, which was significantly associated with log cotinine (ß = 0.143, 95% CI = [0.030, 0.267]). However, in a low cotinine stratum (indicating secondhand smoke exposure), TRO exposure was significantly associated with log cotinine (ß = 0.005, 95% CI = [0.001, 0.009]), while in a high cotinine stratum (indicating active smoking), the NDI was significantly associated with log cotinine (ß = 0.176, 95% CI = [0.005, 0.372]). CONCLUSIONS: In summary, our findings add to the evidence that contextual factors are important for active smoking during pregnancy. IMPLICATIONS: In this study, we found several significant associations that suggest a more nuanced understanding of the potential influence of environmental- and individual-level factors for levels of prenatal smoke exposure. Results suggested a significant positive association between TRO exposure and cotinine levels, after adjusting for the individual factors such as race, education, and marital status. Individually, NDI was similarly positively associated with cotinine levels as well. However, when combining TRO exposure alongside NDI in the same model, TROs were no longer significantly associated with overall cotinine levels.