Type 3 secretion system induced leukotriene B4 synthesis by leukocytes is actively inhibited by Yersinia pestis to evade early immune recognition.

Subverting the host immune response to inhibit inflammation is a key virulence strategy of Yersinia pestis. The inflammatory cascade is tightly controlled via the sequential action of lipid and protein mediators of inflammation. Because delayed inflammation is essential for Y. pestis to cause lethal infection, defining the Y. pestis mechanisms to manipulate the inflammatory cascade is necessary to understand this pathogen's virulence. While previous studies have established that Y. pestis actively inhibits the expression of host proteins that mediate inflammation, there is currently a gap in our understanding of the inflammatory lipid mediator response during plague. Here we used the murine model to define the kinetics of the synthesis of leukotriene B4 (LTB4), a pro-inflammatory lipid chemoattractant and immune cell activator, within the lungs during pneumonic plague. Furthermore, we demonstrated that exogenous administration of LTB4 prior to infection limited bacterial proliferation, suggesting that the absence of LTB4 synthesis during plague contributes to Y. pestis immune evasion. Using primary leukocytes from mice and humans further revealed that Y. pestis actively inhibits the synthesis of LTB4. Finally, using Y. pestis mutants in the Ysc type 3 secretion system (T3SS) and Yersinia outer protein (Yop) effectors, we demonstrate that leukocytes recognize the T3SS to initiate the rapid synthesis of LTB4. However, several Yop effectors secreted through the T3SS effectively inhibit this host response. Together, these data demonstrate that Y. pestis actively inhibits the synthesis of the inflammatory lipid LTB4 contributing to the delay in the inflammatory cascade required for rapid recruitment of leukocytes to sites of infection.

Disparities Associated with Decision to Undergo Oncologic Surgery: A Prospective Mixed-Methods Analysis.

BACKGROUND: Underrepresented minority patients with surgical malignancies experience disparities in outcomes. The impact of provider-based factors, including communication, trust, and cultural competency, on outcomes is not well understood. This study examines modifiable provider-based barriers to care experienced by patients with surgical malignancies. METHODS: A parallel, prospective, mixed-methods study enrolled patients with lung or gastrointestinal malignancies undergoing surgical consultation. Surveys assessed patients' social needs and patient-physician relationship. Semi-structured interviews ascertained patient experiences and were iteratively analyzed, identifying key themes. RESULTS: The cohort included 24 patients (age 62 years; 63% White and 38% Black/African American). The most common cancers were lung (n = 18, 75%) and gastroesophageal (n = 3, 13%). Survey results indicated that food insecurity (n = 5, 21%), lack of reliable transportation (n = 4, 17%), and housing instability (n = 2, 8%) were common. Lack of trust in their physician (n = 3, 13%) and their physician's treatment recommendation (n = 3, 13%) were identified. Patients reported a lack of empathy (n = 3, 13%), lack of cultural competence (n = 3, 13%), and inadequate communication (n = 2, 8%) from physicians. Qualitative analysis identified five major themes regarding the decision to undergo surgery: communication, trust, health literacy, patient fears, and decision-making strategies. Five patients (21%) declined the recommended surgery and were more likely Black (100% vs. 21%), lower income (100% vs. 16%), and reported poor patient-physician relationship (40% vs. 5%; all p < 0.05). CONCLUSIONS: Factors associated with declining recommended cancer surgery were underrepresented minority race and poor patient-physician relationships. Interventions are needed to improve these barriers to care and racial disparities.

Chronic arsenic exposure induces malignant transformation of human HaCaT cells through both deterministic and stochastic changes in transcriptome expression.

Biological processes are inherently stochastic, i.e., are partially driven by hard to predict random probabilistic processes. Carcinogenesis is driven both by stochastic and deterministic (predictable non-random) changes. However, very few studies systematically examine the contribution of stochastic events leading to cancer development. In differential gene expression studies, the established data analysis paradigms incentivize expression changes that are uniformly different across the experimental versus control groups, introducing preferential inclusion of deterministic changes at the expense of stochastic processes that might also play a crucial role in the process of carcinogenesis. In this study, we applied simple computational techniques to quantify: (i) The impact of chronic arsenic (iAs) exposure as well as passaging time on stochastic gene expression and (ii) Which genes were expressed deterministically and which were expressed stochastically at each of the three stages of cancer development. Using biological coefficient of variation as an empirical measure of stochasticity we demonstrate that chronic iAs exposure consistently suppressed passaging related stochastic gene expression at multiple time points tested, selecting for a homogenous cell population that undergo transformation. Employing multiple balanced removal of outlier data, we show that chronic iAs exposure induced deterministic and stochastic changes in the expression of unique set of genes, that populate largely unique biological pathways. Together, our data unequivocally demonstrate that both deterministic and stochastic changes in transcriptome-wide expression are critical in driving biological processes, pathways and networks towards clonal selection, carcinogenesis, and tumor heterogeneity.

Increased expression of phosphodiesterase 4 in activated hepatic stellate cells promotes cytoskeleton remodeling and cell migration.

Activation and transdifferentiation of hepatic stellate cells (HSC) into migratory myofibroblasts is a key process in liver fibrogenesis. Cell migration requires an active remodeling of the cytoskeleton, which is a tightly regulated process coordinated by Rho-specific guanine nucleotide exchange factors (GEFs) and the Rho family of small GTPases. Rho-associated kinase (ROCK) promotes assembly of focal adhesions and actin stress fibers by regulating cytoskeleton organization. GEF exchange protein directly activated by cAMP 1 (EPAC1) has been implicated in modulating TGFß1 and Rho signaling; however, its role in HSC migration has never been examined. The aim of this study was to evaluate the role of cAMP-degrading phosphodiesterase 4 (PDE4) enzymes in regulating EPAC1 signaling, HSC migration, and fibrogenesis. We show that PDE4 protein expression is increased in activated HSCs expressing alpha smooth muscle actin and active myosin light chain (MLC) in fibrotic tissues of human nonalcoholic steatohepatitis cirrhosis livers and mouse livers exposed to carbon tetrachloride. In human livers, TGFß1 levels were highly correlated with PDE4 expression. TGFß1 treatment of LX2 HSCs decreased levels of cAMP and EPAC1 and increased PDE4D expression. PDE4 specific inhibitor, rolipram, and an EPAC-specific agonist decreased TGFß1-mediated cell migration in vitro. In vivo, targeted delivery of rolipram to the liver prevented fibrogenesis and collagen deposition and decreased the expression of several fibrosis-related genes, and HSC activation. Proteomic analysis of mouse liver tissues identified the regulation of actin cytoskeleton by the kinase effectors of Rho GTPases as a major pathway impacted by rolipram. Western blot analyses confirmed that PDE4 inhibition decreased active MLC and endothelin 1 levels, key proteins involved in cytoskeleton remodeling and contractility. The current study, for the first time, demonstrates that PDE4 enzymes are expressed in hepatic myofibroblasts and promote cytoskeleton remodeling and HSC migration. © 2023 The Pathological Society of Great Britain and Ireland.

Associations between residential volatile organic compound exposures and liver injury markers: The role of biological sex and race.

While occupational exposures to volatile organic compounds (VOCs) have been linked to steatohepatitis and liver cancer in industrial workers, recent findings have also positively correlated low-dose, residential VOC exposures with liver injury markers. VOC sources are numerous; factors including biological make up (sex), socio-cultural constructs (gender, race) and lifestyle (smoking) can influence both VOC exposure levels and disease outcomes. Therefore, the current study's objective is to investigate how sex and race influence associations between residential VOC exposures and liver injury markers particularly in smokers vs. nonsmokers. Subjects (n = 663) were recruited from residential neighborhoods; informed consent was obtained. Exposure biomarkers included 16 urinary VOC metabolites. Serological disease biomarkers included liver enzymes, direct bilirubin, and hepatocyte death markers (cytokeratin K18). Pearson correlations and generalized linear models were conducted. Models were adjusted for common liver-related confounders and interaction terms. The study population constituted approximately 60% females (n = 401) and 40% males (n = 262), and a higher percent of males were smokers and/or frequent drinkers. Both sexes had a higher percent of White (75% females, 82% males) vs. Black individuals. Positive associations were identified for metabolites of acrolein, acrylamide, acrylonitrile, butadiene, crotonaldehyde, and styrene with alkaline phosphatase (ALP), a biomarker for cholestatic injury; and for the benzene metabolite with bilirubin; only in females. These associations were retained in female smokers. Similar associations were also observed between these metabolites and ALP only in White individuals (n = 514). In Black individuals (n = 114), the styrene metabolite was positively associated with aspartate transaminase. Interaction models indicated that positive associations for acrylamide/crotonaldehyde metabolites with ALP in females were dose-dependent. Most VOC associations with K18 markers were negative in this residential population. Overall, the findings demonstrated that biological sex, race, and smoking status influence VOC effects on liver injury and underscored the role of biological-social-lifestyle factor(s) interactions when addressing air pollution-related health disparities.

Exposure to Volatile Organic Compounds Is Associated with Hypertension in Black Adults: The Jackson Heart Study.

BACKGROUND: The prevalence of hypertension is higher among Black adults than among White and Hispanic adults. Nevertheless, reasons underlying the higher rates of hypertension in the Black population remain unclear but may relate to exposure to environmental chemicals such as volatile organic compounds (VOCs). METHODS: We evaluated the associations of blood pressure (BP) and hypertension with VOC exposure in non-smokers and smokers in a subgroup of the Jackson Heart Study (JHS), consisting of 778 never smokers and 416 age- and sex-matched current smokers. We measured urinary metabolites of 17 VOCs by mass spectrometry. RESULTS: After adjusting for covariates, we found that amoong non-smokers, metabolites of acrolein and crotonaldehyde were associated with a 1.6 mm Hg (95%CI: 0.4, 2.7; p = 0.007) and a 0.8 mm Hg (95%CI: 0.01, 1.6; p = 0.049) higher systolic BP, and the styrene metabolite was associated with a 0.4 mm Hg (95%CI: 0.09, 0.8, p = 0.02) higher diastolic BP. Current smokers had 2.8 mm Hg (95% CI 0.5, 5.1) higher systolic BP. They were at higher risk of hypertension (relative risk = 1.2; 95% CI, 1.1, 1.4), and had higher urinary levels of several VOC metabolites. Individuals who smoke had higher levels of the urinary metabolites of acrolein, 1,3-butadiene, and crotonaldehyde and were associated with higher systolic BP. The associations were stronger among participants who were <60 years of age and male. Using Bayesian kernel machine regression to assess the effects of multiple VOC exposures, we found that the relationship between VOCs and hypertension among non-smokers was driven primarily by acrolein and styrene in non-smokers, and crotonaldehyde in smokers. CONCLUSIONS: Hypertension in Black individuals may be attributed, in part, to VOC exposure from the environment or tobacco smoke.

Lung cancer metabolomic data from tumor core biopsies enables risk-score calculation for progression-free and overall survival.

INTRODUCTION: Metabolomics has emerged as a powerful method to provide insight into cancer progression, including separating patients into low- and high-risk groups for overall (OS) and progression-free survival (PFS). However, survival prediction based mainly on metabolites obtained from biofluids remains elusive. OBJECTIVES: This proof-of-concept study evaluates metabolites as biomarkers obtained directly from tumor core biopsies along with covariates age, sex, pathological stage at diagnosis (I/II vs. III/VI), histological subtype, and treatment vs. no treatment to risk stratify lung cancer patients in terms of OS and PFS. METHODS: Tumor core biopsy samples obtained during routine lung cancer patient care at the University of Louisville Hospital and Norton Hospital were evaluated with high-resolution 2DLC-MS/MS, and the data were analyzed by Kaplan-Meier survival analysis and Cox proportional hazards regression. A linear equation was developed to stratify patients into low and high risk groups based on log-transformed intensities of key metabolites. Sparse partial least squares discriminant analysis (SPLS-DA) was performed to predict OS and PFS events. RESULTS: Univariable Cox proportional hazards regression model coefficients divided by the standard errors were used as weight coefficients multiplied by log-transformed metabolite intensity, then summed to generate a risk score for each patient. Risk scores based on 10 metabolites for OS and 5 metabolites for PFS were significant predictors of survival. Risk scores were validated with SPLS-DA classification model (AUROC 0.868 for OS and AUROC 0.755 for PFS, when combined with covariates). CONCLUSION: Metabolomic analysis of lung tumor core biopsies has the potential to differentiate patients into low- and high-risk groups based on OS and PFS events and probability.

Environmental exposure to volatile organic compounds is associated with endothelial injury.

OBJECTIVE: Volatile organic compounds (VOCs) are airborne toxicants abundant in outdoor and indoor air. High levels of VOCs are also present at various Superfund and other hazardous waste sites; however, little is known about the cardiovascular effects of VOCs. We hypothesized that ambient exposure to VOCs exacerbate cardiovascular disease (CVD) risk by depleting circulating angiogenic cells (CACs). APPROACH AND RESULTS: In this cross-sectional study, we recruited 603 participants with low-to-high CVD risk and measured 15 subpopulations of CACs by flow cytometry and 16 urinary metabolites of 12 VOCs by LC/MS/MS. Associations between CAC and VOC metabolite levels were examined using generalized linear models in the total sample, and separately in non-smokers. In single pollutant models, metabolites of ethylbenzene/styrene and xylene, were negatively associated with CAC levels in both the total sample, and in non-smokers. The metabolite of acrylonitrile was negatively associated with CD45dim/CD146+/CD34+/AC133+ cells and CD45+/CD146+/AC133+, and the toluene metabolite with AC133+ cells. In analysis of non-smokers (n = 375), multipollutant models showed a negative association with metabolites of ethylbenzene/styrene, benzene, and xylene with CD45dim/CD146+/CD34+ cells, independent of other VOC metabolite levels. Cumulative VOC risk score showed a strong negative association with CD45dim/CD146+/CD34+ cells, suggesting that total VOC exposure has a cumulative effect on pro-angiogenic cells. We found a non-linear relationship for benzene, which showed an increase in CAC levels at low, but depletion at higher levels of exposure. Sex and race, hypertension, and diabetes significantly modified VOC associated CAC depletion. CONCLUSION: Low-level ambient exposure to VOCs is associated with CAC depletion, which could compromise endothelial repair and angiogenesis, and exacerbate CVD risk.

Increased Expression of Long Non-coding RNA H19 is Associated With Colon Cancer Recurrence.

BACKGROUND: Colon cancer is a leading cause of cancer-related death. Long non-coding (Lnc) RNAs are critical mediators of tumor biology. H19 is a well-characterized lncRNA involved in p53 regulation and cancer progression. A specific colon cancer data set was utilized to determine if tumor H19 expression is associated with recurrence-free and overall survival. METHODS: Clinical patient data from The Cancer Genome Atlas colon adenocarcinoma data set was downloaded using FirebrowseR and normalized H19 expression from the associated RNA-seq data set downloaded using cBioportal. Univariable and multivariable Cox proportional regression analyses were used to identify an association between H19 expression in colon cancer tissue and recurrence-free, and overall survival. RESULTS: Three hundred eight patients were studied. Median age was 68 years (interquartile range: 58-77 years) and 156 patients (51%) were men. Increased H19 expression was associated with KRAS mutation status (P= 0.016). There was no difference in overall survival between the low and high H19 expression groups (log rank = 0.481); however, increased H19 expression was associated with reduced recurrence-free survival (Log-Rank = 0.012). On multivariable regression analysis, increased H19 expression (Hazard ratio  = 1.83, 95%CI: 1.02-3.27, P= 0.042), and stage III or IV disease (Hazard ratio  = 2.39, 95%CI: 1.34-4.27, P= 0.003) were risk factors for reduced recurrence-free survival. CONCLUSIONS: Colon cancer H19 expression is associated with advanced stage of tumor disease and is a significant risk factor for reduced recurrence-free survival. Tumor expression of H19 may have potential for both prognostic and therapeutic uses in the future.

Applications of Bayesian shrinkage prior models in clinical research with categorical responses.

BACKGROUND: Prediction and classification algorithms are commonly used in clinical research for identifying patients susceptible to clinical conditions such as diabetes, colon cancer, and Alzheimer's disease. Developing accurate prediction and classification methods benefits personalized medicine. Building an excellent predictive model involves selecting the features that are most significantly associated with the outcome. These features can include several biological and demographic characteristics, such as genomic biomarkers and health history. Such variable selection becomes challenging when the number of potential predictors is large. Bayesian shrinkage models have emerged as popular and flexible methods of variable selection in regression settings. This work discusses variable selection with three shrinkage priors and illustrates its application to clinical data such as Pima Indians Diabetes, Colon cancer, ADNI, and OASIS Alzheimer's real-world data. METHODS: A unified Bayesian hierarchical framework that implements and compares shrinkage priors in binary and multinomial logistic regression models is presented. The key feature is the representation of the likelihood by a Polya-Gamma data augmentation, which admits a natural integration with a family of shrinkage priors, specifically focusing on Horseshoe, Dirichlet Laplace, and Double Pareto priors. Extensive simulation studies are conducted to assess the performances under different data dimensions and parameter settings. Measures of accuracy, AUC, brier score, L1 error, cross-entropy, and ROC surface plots are used as evaluation criteria comparing the priors with frequentist methods as Lasso, Elastic-Net, and Ridge regression. RESULTS: All three priors can be used for robust prediction on significant metrics, irrespective of their categorical response model choices. Simulation studies could achieve the mean prediction accuracy of 91.6% (95% CI: 88.5, 94.7) and 76.5% (95% CI: 69.3, 83.8) for logistic regression and multinomial logistic models, respectively. The model can identify significant variables for disease risk prediction and is computationally efficient. CONCLUSIONS: The models are robust enough to conduct both variable selection and prediction because of their high shrinkage properties and applicability to a broad range of classification problems.

SwarnSeq: An improved statistical approach for differential expression analysis of single-cell RNA-seq data.

Single-cell RNA sequencing (scRNA-seq) is a powerful technology that is capable of generating gene expression data at the resolution of individual cell. The scRNA-seq data is characterized by the presence of dropout events, which severely bias the results if they remain unaddressed. There are limited Differential Expression (DE) approaches which consider the biological processes, which lead to dropout events, in the modeling process. So, we develop, SwarnSeq, an improved method for DE, and other downstream analysis that considers the molecular capture process in scRNA-seq data modeling. The performance of the proposed method is benchmarked with 11 existing methods on 10 different real scRNA-seq datasets under three comparison settings. We demonstrate that SwarnSeq method has improved performance over the 11 existing methods. This improvement is consistently observed across several public scRNA-seq datasets generated using different scRNA-seq protocols. The external spike-ins data can be used in the SwarnSeq method to enhance its performance. AVAILABILITY AND IMPLEMENTATION: The method is implemented as a publicly available R package available at https://github.com/sam-uofl/SwarnSeq.

Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model.

An unprecedented outbreak of the novel coronavirus (COVID-19) in the form of peculiar pneumonia has spread globally since its first case in Wuhan province, China, in December 2019. Soon after, the infected cases and mortality increased rapidly. The future of the pandemic's progress was uncertain, and thus, predicting it became crucial for public health researchers. These predictions help the effective allocation of health-care resources, stockpiling, and help in strategic planning for clinicians, government authorities, and public health policymakers after understanding the extent of the effect. The main objective of this paper is to develop a hybrid forecasting model that can generate real-time out-of-sample forecasts of COVID-19 outbreaks for five profoundly affected countries, namely the USA, Brazil, India, the UK, and Canada. A novel hybrid approach based on the Theta method and autoregressive neural network (ARNN) model, named Theta-ARNN (TARNN) model, is developed. Daily new cases of COVID-19 are nonlinear, non-stationary, and volatile; thus, a single specific model cannot be ideal for future prediction of the pandemic. However, the newly introduced hybrid forecasting model with an acceptable prediction error rate can help healthcare and government for effective planning and resource allocation. The proposed method outperforms traditional univariate and hybrid forecasting models for the test datasets on an average.

Differential Expression Analysis of Single-Cell RNA-Seq Data: Current Statistical Approaches and Outstanding Challenges.

With the advent of single-cell RNA-sequencing (scRNA-seq), it is possible to measure the expression dynamics of genes at the single-cell level. Through scRNA-seq, a huge amount of expression data for several thousand(s) of genes over million(s) of cells are generated in a single experiment. Differential expression analysis is the primary downstream analysis of such data to identify gene markers for cell type detection and also provide inputs to other secondary analyses. Many statistical approaches for differential expression analysis have been reported in the literature. Therefore, we critically discuss the underlying statistical principles of the approaches and distinctly divide them into six major classes, i.e., generalized linear, generalized additive, Hurdle, mixture models, two-class parametric, and non-parametric approaches. We also succinctly discuss the limitations that are specific to each class of approaches, and how they are addressed by other subsequent classes of approach. A number of challenges are identified in this study that must be addressed to develop the next class of innovative approaches. Furthermore, we also emphasize the methodological challenges involved in differential expression analysis of scRNA-seq data that researchers must address to draw maximum benefit from this recent single-cell technology. This study will serve as a guide to genome researchers and experimental biologists to objectively select options for their analysis.

Residential proximity to greenness mitigates the hemodynamic effects of ambient air pollution.

Residential proximity to greenness is associated with a lower risk of cardiovascular disease (CVD) and all-cause mortality. However, it is unclear whether the beneficial effects of greenness are linked to a reduction in the effects of ambient air pollutants. We measured arterial stiffness in 73 participants with moderate to high CVD risk. Average levels of ambient PM2.5 and ozone were calculated from local monitoring stations. Residential greenness was estimated using satellite-derived normalized difference vegetation index (NDVI) for a 200-m and 1-km radius around each participant's home. Participants were 51% female, average age of 52 yr, and 79% had diagnosed hypertension. In multiple linear regression models, residential NDVI was negatively associated with augmentation index (-3.8% per 0.1 NDVI). Ambient levels of PM2.5 [per interquartile range (IQR) of 6.9 µg/m3] were positively associated with augmentation pressure (3.1 mmHg), pulse pressure (5.9 mmHg), and aortic systolic pressure (8.1 mmHg). Ozone (per IQR of 0.03 ppm) was positively associated with augmentation index (5.5%), augmentation pressure (3.1 mmHg), and aortic systolic pressure (10 mmHg). In areas of low greenness, both PM2.5 and ozone were positively associated with pulse pressure. Additionally, ozone was positively associated with augmentation pressure and systolic blood pressure. However, in areas of high greenness, there was no significant association between indices of arterial stiffness with either PM2.5 or ozone. Residential proximity to greenness is associated with lower values of arterial stiffness. Residential greenness may mitigate the adverse effects of PM2.5 and ozone on arterial stiffness.NEW & NOTEWORTHY Previous studies have linked proximity to green spaces with lower cardiovascular disease risk. However, the mechanisms underlying the salutary effects of green areas are not known. In our study of participants at risk of cardiovascular disease, we found that arterial stiffness was positively associated with short-term exposure to PM2.5, PM10, and ozone and inversely associated with greenness. The association between pollution and arterial stiffness was attenuated in areas of high greenness, suggesting that living green neighborhoods can lessen the adverse cardiovascular effects of air pollution.

P027 Brain Fog in Patients With Inflammatory Bowel Disease, and Association With Use of Probiotics.

BACKGROUND: Brain fog has been minimally studied in patients with inflammatory bowel disease (IBD). IBD patients frequently consume probiotics, whether sanctioned by a physician or not. However, probiotic consumption in itself has been shown to increase the incidence of brain fog. We aimed to study the association between brain fog in IBD patients with or without probiotic use. METHODS: We conducted a cross-sectional study among patients visiting a busy IBD clinic. Patients aged >18 with a biopsy-proven diagnosis of inflammatory bowel disease, without pre-existing psychiatric illness or current use of opioid medications were included. They were divided into 2 groups: those using probiotics and those who did not. Patients were given a questionnaire that included details about symptoms of brain fog. Groups were analyzed by chi-square test for differences in baseline demographics, and Mann Whitney U test to compare outcomes between groups. A p-value < 0.05 was considered statistically significant. RESULTS: Of the 66 patients included (mean age 44±2 years), 35 (53%) were female and 59 (89.4%) were Caucasian. Among these patients, 31.8% (n = 21) took probiotics as dietary supplements with the majority (67%, n = 14) taking probiotics for over a year. Overall, there was a trend for an association between probiotic use and brain fog in all patients (p = 0.080) but no statistical significance was attained. However, brain fog was significantly associated with probiotic use among Caucasian patients (p = 0.044). Furthermore, there was a statistically significant association between brain fog and male patients using probiotics (p = 0.004). Duration of probiotic use was also associated with brain fog (p = 0.038). CONCLUSION: Consumption of probiotics was independently associated with brain fog in men, as well as Caucasian patients with IBD respectively. Given the high prevalence of probiotic use in IBD patients, prospective studies are warranted to examine the causal relationship between probiotics and IBD-associated brain fog to guide prescription of probiotic supplements for IBD.

A Phase II Trial of Once Weekly Hypofractionated Breast Irradiation for Early Stage Breast Cancer.

PURPOSE: To report an interim analysis of a phase II trial of once weekly, hypofractionated breast irradiation (WH-WBI) following breast conserving surgery (BCS). METHODS: Patients had stage 0-II breast cancer treated with breast BCS with negative margins. WH-WBI was 28.5 or 30Gy delivered to the whole breast using tangential beams with no elective coverage of lymph nodes. The primary endpoint was ipsilateral breast tumor recurrence (IBTR). Secondary endpoints were distant disease-free survival (DDFS), recurrence free survival (RFS), overall survival (OS), adverse events and cosmesis. RESULTS: From 2011 to 2015, 158 patients received WH-WBI. Median follow up was 4.4 years (range 0.2-8.1). Stage distribution was DCIS 22%; invasive pN0 68%; invasive pN1 10%. 80 patients received 30 Gy and 78 received 28.5 Gy with median follow up times of 5.6 and 3.7 years, respectively. There were 5 IBTR events, all in the 30 Gy group. The 5- and 7- year risks of IBRT for all patients were 2.2% (95% CI 0.6-5.8) and 6.0% (95% CI 1.1-17.2), respectively. The 7-year rates of DDFS, RFS, and OS were 96.3%, 91.5% and 89.8%, respectively. Improvement in IBTR-free time was seen in DCIS, lobular histology, low grade tumors, Her2 negative tumors and 28.5 Gy dose (all p < 0.0001). CONCLUSIONS: Disease-specific outcomes after WH-WBI are favorable and parallel those seen with conventional radiation techniques for stage 0-II breast cancer.

Decreased Tumoral Expression of Colon-Specific Water Channel Aquaporin 8 Is Associated With Reduced Overall Survival in Colon Adenocarcinoma.

BACKGROUND: Colon cancer survival is dependent on metastatic potential and treatment. Large RNA-sequencing data sets may assist in identifying colon cancer-specific biomarkers to improve patient outcomes. OBJECTIVE: This study aimed to identify a highly specific biomarker for overall survival in colon adenocarcinoma by using an RNA-sequencing data set. DESIGN: Raw RNA-sequencing and clinical data for patients with colon adenocarcinoma (n = 271) were downloaded from The Cancer Genome Atlas. A binomial regression model was used to calculate differential RNA expression between paired colon cancer and normal epithelium samples (n = 40). Highly differentially expressed RNAs were examined. SETTINGS: This study was conducted at the University of Louisville using data acquired by The Cancer Genome Atlas. PATIENTS: Patients from US accredited cancer centers between 1998 and 2013 were analyzed. MAIN OUTCOME MEASURES: The primary outcome measures were recurrence-free and overall survival. RESULTS: The median age was 66 years (147/271 men, 180/271 White patients). Thirty RNAs were differentially expressed in colon adenocarcinoma compared with paired normal epithelium, using a log-fold change cutoff of ±6. Using median expression as a cutoff, 4 RNAs were associated with worse overall survival: decreased ZG16 (log-rank = 0.023), aquaporin 8 (log-rank = 0.023), and SLC26A3 (log-rank = 0.098), and increased COL1A1 (log-rank = 0.105). On multivariable analysis, low aquaporin 8 expression (HR, 1.748; 95% CI, 1.016-3.008; p = 0.044) was a risk factor for worse overall survival. Our final aquaporin 8 model had an area under the curve of 0.85 for overall survival. On subgroup analysis, low aquaporin 8 was associated with worse overall survival in patients with high microsatellite instability and in patients with stage II disease. Low aquaporin 8 expression was associated with KRAS and BRAF mutations. Aquaporin 8 immunohistochemistry was optimized for clinical application. LIMITATIONS: This was a retrospective study. CONCLUSION: Aquaporin 8 is a water channel selectively expressed in normal colon tissue. Low aquaporin 8 expression is a risk factor for worse overall survival in patients who have colon cancer. Aquaporin 8 measurement may have a role as a colon-specific prognostic biomarker and help in patient risk stratification for increased surveillance. See Video Abstract at http://links.lww.com/DCR/B603. LA DISMINUCIN DE LA EXPRESIN TUMORAL DE LA ACUAPORINA DEL CANAL DE AGUA ESPECFICO DEL COLON SE ASOCIA CON UNA REDUCCIN DE LA SUPERVIVENCIA GENERAL EN EL ADENOCARCINOMA DE COLON: ANTECEDENTES:La supervivencia del cáncer de colon depende del potencial metastásico y del tratamiento. Grandes conjuntos de datos de secuenciación de ARN pueden ayudar a identificar biomarcadores específicos del cáncer de colon para mejorar los resultados de los pacientes.OBJETIVO:Identificar un biomarcador altamente específico para la supervivencia general en el adenocarcinoma de colon utilizando un conjunto de datos de secuenciación de ARN.DISEÑO:La secuenciación de ARN sin procesar y los datos clínicos para pacientes con adenocarcinoma de colon (n = 271) se descargaron de The Cancer Genome Atlas. Se utilizó un modelo de regresión binomial para calcular la expresión diferencial de ARN entre muestras de cáncer de colon emparejadas y muestras de epitelio normal (n = 40). Se examinaron los ARN expresados de forma altamente diferencial.ENTORNO CLINICO:Este estudio se realizó en la Universidad de Louisville utilizando datos adquiridos por The Cancer Genome Atlas.PACIENTES:Se analizaron pacientes de centros oncológicos acreditados en Estados Unidos entre 1998-2013.PRINCIPALES MEDIDAS DE VALORACION:Las principales medidas de valoración fueron la supervivencia general y libre de recurrencia.RESULTADOS:La mediana de edad fue de 66 años (147/271 hombres, 180/271 caucásicos). Treinta ARN se expresaron diferencialmente en el adenocarcinoma de colon en comparación con el epitelio normal emparejado, utilizando un límite de cambio logarítmico de ± 6. Utilizando la expresión mediana como punto de corte, cuatro ARN se asociaron con una peor supervivencia general: disminución de ZG16 (rango logarítmico = 0,023), acuaporina8 (rango logarítmico = 0,023) y SLC26A3 (rango logarítmico = 0,098) y aumento de COL1A1 (log -rango = 0,105). En el análisis multivariable, la baja expresión de acuaporina8 (HR = 1,748, IC del 95%: 1,016-3,008, p = 0,044) fue un factor de riesgo para una peor supervivencia global. Nuestro modelo de aquaporin8 final tuvo un AUC de 0,85 para la supervivencia global. En el análisis de subgrupos, la acuaporina8 baja se asoció con una peor supervivencia general en pacientes con MSI-H y en pacientes en estadio II. La baja expresión de acuaporina8 se asoció con mutaciones de KRAS y BRAF. La inmunohistoquímica de aquaporina8 se optimizó para su aplicación clínica.LIMITACIONES:Este fue un estudio retrospectivo.CONCLUSIÓN:La acuaporina8 es un canal de agua expresado selectivamente en el tejido normal del colon. La baja expresión de AQP8 es un factor de riesgo de peor supervivencia global en pacientes con cáncer de colon. La medición de aquaporina8 puede tener un papel como un biomarcador de pronóstico específico del colon y ayudar en la estratificación del riesgo del paciente para una mayor vigilancia. Consulte Video Resumen en http://links.lww.com/DCR/B603.

Exposure to volatile organic compounds - acrolein, 1,3-butadiene, and crotonaldehyde - is associated with vascular dysfunction.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of mortality worldwide. Exposure to air pollution, specifically particulate matter of diameter ≤2.5 µm (PM2.5), is a well-established risk factor for CVD. However, the contribution of gaseous pollutant exposure to CVD risk is less clear. OBJECTIVE: To examine the vascular effects of exposure to individual volatile organic compounds (VOCs) and mixtures of VOCs. METHODS: We measured urinary metabolites of acrolein (CEMA and 3HPMA), 1,3-butadiene (DHBMA and MHBMA3), and crotonaldehyde (HPMMA) in 346 nonsmokers with varying levels of CVD risk. On the day of enrollment, we measured blood pressure (BP), reactive hyperemia index (RHI - a measure of endothelial function), and urinary levels of catecholamines and their metabolites. We used generalized linear models for evaluating the association between individual VOC metabolites and BP, RHI, and catecholamines, and we used Bayesian Kernel Machine Regression (BKMR) to assess exposure to VOC metabolite mixtures and BP. RESULTS: We found that the levels of 3HPMA were positively associated with systolic BP (0.98 mmHg per interquartile range (IQR) of 3HPMA; CI: 0.06, 1.91; P = 0.04). Stratified analysis revealed an increased association with systolic BP in Black participants despite lower levels of urinary 3HPMA. This association was independent of PM2.5 exposure and BP medications. BKMR analysis confirmed that 3HPMA was the major metabolite associated with higher BP in the presence of other metabolites. We also found that 3HPMA and DHBMA were associated with decreased endothelial function. For each IQR of 3HPMA or DHBMA, there was a -4.4% (CI: -7.2, -0.0; P = 0.03) and a -3.9% (CI: -9.4, -0.0; P = 0.04) difference in RHI, respectively. Although in the entire cohort the levels of several urinary VOC metabolites were weakly associated with urinary catecholamines and their metabolites, in Black participants, DHBMA levels showed strong associations with urinary norepinephrine and normetanephrine levels. DISCUSSION: Exposure to acrolein and 1,3-butadiene is associated with endothelial dysfunction and may contribute to elevated risk of hypertension in participants with increased sympathetic tone, particularly in Black individuals.

Dynamic alteration in miRNA and mRNA expression profiles at different stages of chronic arsenic exposure-induced carcinogenesis in a human cell culture model of skin cancer.

Chronic arsenic exposure causes skin cancer, although the underlying molecular mechanisms are not well defined. Altered microRNA and mRNA expression likely play a pivotal role in carcinogenesis. Changes in genome-wide differential expression of miRNA and mRNA at 3 strategic time points upon chronic sodium arsenite (As3+) exposure were investigated in a well-validated HaCaT cell line model of arsenic-induced cutaneous squamous cell carcinoma (cSCC). Quadruplicate independent HaCaT cell cultures were exposed to 0 or 100 nM As3+ for up to 28-weeks (wk). Cell growth was monitored throughout the course of exposure and epithelial-mesenchymal transition (EMT) was examined employing immunoblot. Differentially expressed miRNA and mRNA profiles were generated at 7, 19, and 28-wk by RNA-seq, followed by identification of differentially expressed mRNA targets of differentially expressed miRNAs through expression pairing at each time point. Pathway analyses were performed for total differentially expressed mRNAs and for the miRNA targeted mRNAs at each time point. RNA-seq predictions were validated by immunoblot of selected target proteins. While the As3+-exposed cells grew slower initially, growth was equal to that of unexposed cells by 19-wk (transformation initiation), and exposed cells subsequently grew faster than passage-matched unexposed cells. As3+-exposed cells had undergone EMT at 28-wk. Pathway analyses demonstrate dysregulation of carcinogenesis-related pathways and networks in a complex coordinated manner at each time point. Immunoblot data largely corroborate RNA-seq predictions in the endoplasmic reticulum stress (ER stress) pathway. This study provides a detailed molecular picture of changes occurring during the arsenic-induced transformation of human keratinocytes.