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INTRODUCTION Although humans are capable of enduring critically low levels of oxygen, many hypoxaemic patients die despite aggressive therapies. Mimicking the physiological hyperventilation necessary to survive extreme hypoxic conditions could minimize the derangements caused by acute hypoxic-hypoxia. The objective of this study was to measure the haemodynamic-biochemical response to artificially induced hyperventilation in hypoxic rats. MATERIAL AND METHODS Twenty-four deeply anaesthetized and mechanically ventilated rats were allocated to 3 groups: control (n = 5, FiO2 = 1); hypoxic spontaneously hyperventilating (n = 10, FiO2 = 0.08); and hypoxic artificially induced hyperventilation (n = 9, targeting PaCO2 = 10 mm Hg, FiO2 = 0.08). We compared the spontaneously and artificially hyperventilating groups. P-values < 0.01 were considered statistically significant. Mean arterial pressure (MAP) and serum chemistry were measured for 180 minutes. RESULTS The control group remained stable throughout the experiment. The hypoxic groups developed profound hypotension after the decrease in FiO2. However, the artificially induced hyperventilated rats recovered their MAP to levels higher than the spontaneously hyperventilating group (117.1 ± 17.2 vs. 68.1 ± 16.0, P = 0.0048). In regard to the biochemical derangements, even though the serum lactate and PaO2 were not different among the hypoxic groups, the artificially hyperventilated group achieved significantly higher SaO2 (94.3 ± 3.6 vs. 58.6 ± 9.6, P = 0.005), pH (7.87 ± 0.04 vs. 7.50 ± 0.13, P = 0.005), and CaO2 (17.7 ± 2.6 vs. 10.2 ± 1.3, P = 0.005) at 180 minutes. CONCLUSIONS Artificially induced hyperventilation led to the correction of arterial oxygen content, severe serum chemistry, and haemodynamic derangements. These findings may represent a novel rescue manoeuvre and serve as a bridge to a permanent form of support, but should be further studied before being translated to the clinical setting.

Background: Three national career development programs (CDPs)—Early and Mid-Career Programs sponsored by the Association of American Medical Colleges and the Hedwig van Ameringen Executive Leadership in Academic Medicine sponsored by Drexel University—seek to expand gender diversity in faculty and institutional leadership of academic medical centers. Over 20 years of success and continued need are evident in the sustained interest and investment of individuals and institutions. However, their impact on promotion in academic rank remains unknown. The purpose of the study is to compare promotion rates of women CDP participants and other faculty of similar institutional environment and initial career stage. Methods: The study examined retrospective cohorts of 2,719 CDP participants, 12,865 nonparticipant women, and 26,810 men, from the same institutions, with the same degrees, and first years of appointment in rank. Rates of promotion to Associate and Full Professor ranks in respective cohorts of Assistant and of Associate Professors were compared using Kaplan-Meier survival curves and log-rank tests, and logistic regression adjusting for other predictors of academic success. Results: In adjusted analyses, participants were more likely than men and non-participant women to be promoted to Associate Professor and as likely as men and more likely than non-participant women to be promoted to Full Professor within 10 years. Within 5 years, CDP participants were more likely than nonparticipant women to be promoted to Associate Professor and as likely as to be promoted to Full Professor; in the same interval, participants were promoted to both higher ranks at the same rates as men. For both intervals, nonparticipant women were significantly less likely than men to be promoted to either rank. Conclusions: The higher rates of promotion for women participating in national CDPs support the effectiveness of these programs in building capacity for academic medicine.

In this article, we develop a Bayesian hierarchical mixture regression model for studying the association between a multivariate response, measured as counts on a set of features, and a set of covariates. We have available RNA-Seq and DNA methylation data measured on breast cancer patients at different stages of the disease. We account for the heterogeneity and over-dispersion of count data (here, RNA-Seq data) by considering a mixture of negative binomial distributions and incorporate the covariates (here, methylation data) into the model via a linear modeling construction on the mean components. Our modeling construction includes several innovative characteristics. First, it employs selection techniques that allow the identification of a small subset of features that best discriminate the samples while simultaneously selecting a set of covariates associated to each feature. Second, it incorporates known dependencies into the feature selection process via the use of Markov random field (MRF) priors. On simulated data, we show how incorporating existing information via the prior model can improve the accuracy of feature selection. In the analysis of RNA-Seq and DNA methylation data on breast cancer, we incorporate knowledge on relationships among genes via a gene-gene network, which we extract from the KEGG database. Our data analysis identifies genes which are discriminatory of cancer stages and simultaneously selects significant associations between those genes and DNA methylation sites. A biological interpretation of our findings reveals several biomarkers that can help understanding the effect of DNA methylation on gene expression transcription across cancer stages.

The simultaneous testing of multiple hypotheses is common to the analysis of high-dimensional data sets. The two-group model, first proposed by Efron, identifies significant comparisons by allocating observations to a mixture of an empirical null and an alternative distribution. In the Bayesian nonparametrics literature, many approaches have suggested using mixtures of Dirichlet Processes in the two-group model framework. Here, we investigate employing mixtures of two-parameter Poisson-Dirichlet Processes instead, and show how they provide a more flexible and effective tool for large-scale hypothesis testing. Our model further employs nonlocal prior densities to allow separation between the two mixture components. We obtain a closed-form expression for the exchangeable partition probability function of the two-group model, which leads to a straightforward Markov Chain Monte Carlo implementation. We compare the performance of our method for large-scale inference in a simulation study and illustrate its use on both a prostate cancer data set and a case-control microbiome study of the gastrointestinal tracts in children from underdeveloped countries who have been recently diagnosed with moderate-to-severediarrhea.

Electroencephalography (EEG) is a noninvasive neuroimaging modality that captures electrical brain activity many times per second. We seek to estimate power spectra from EEG data that ware gathered for 557 adolescent twin pairs through the Minnesota Twin Family Study (MTFS). Typically, spectral analysis methods treat time series from each subject separately, and independent spectral densities are fit to each time series. Since the EEG data were collected on twins, it is reasonable to assume that the time series have similar underlying characteristics, so borrowing information across subjects can significantly improve estimation. We propose a Nested Bernstein Dirichlet prior model to estimate the power spectrum of the EEG signal for each subject by smoothing periodograms within and across subjects while requiring minimal user input to tuning parameters. Furthermore, we leverage the MTFS twin study design to estimate the heritability of EEG power spectra with the hopes of establishing new endophenotypes. Through simulation studies designed to mimic the MTFS, we show our method out-performs a set of other popular methods.

Atherosclerosis represents one of the main risk factors for the development of cardiovascular diseases. Their etiologies have been studied in recent years in order to better define therapeutic targets for intervention and to identify diagnostic methods. Two different subtypes of macrophages, M1 and M2, have been described in physiological conditions. They can also be found in the atherosclerotic process, where they both have opposite roles in disease progression. Perivascular brown adipose tissue is also involved in inflammation and endothelial damage. In this work, we provide insights into the protective role of melatonin in the atherosclerotic process by morphological and 18F-FDG-PET/CT analyses. In particular, we examined the effects of melatonin on pathways that are linked to atherosclerosis development. We showed that melatonin, by suppressing M1 activity, reduced inflammation and directed macrophage polarization toward the M2 macrophage subtype. Moreover, melatonin preserved the activity of perivascular brown adipose tissue. In addition, 18F-FDG uptake is very high in mice treated with melatonin, confirming that other factors may alter 18F-FDG distribution. In conclusion, we showed that melatonin affects inflammatory pathways that have been linked to atherosclerosis, assessed the relationships of the 18F-FDG PET/CT parameters with macrophage markers and the production of their cytokines, which that have been defined by morphological evaluations.

The objectives of the study are (1) to distinguish lipoma (L) from atypical lipomatous tumor (ALT) using MRI qualitative features, (2) to assess the value of contrast enhancement, and (3) to evaluate the reproducibility and confidence level of radiological readings. Patients with pathologically proven L or ALT, who underwent MRI within 3 months from surgical excision were included in this retrospective multicenter international study. Two radiologists independently reviewed MRI centrally. Impressions were recorded as L or ALT. A third radiologist was consulted for discordant readings. The two radiologists re-read all non-contrast sequences; impression was recorded; then post-contrast images were reviewed and any changes were recorded. A total of 246 patients (135 females; median age, 59 years) were included. ALT was histopathologically confirmed in 70/246 patients. In multivariable analysis, in addition to the lesion size, deep location, proximal lower limb lesions, demonstrating incomplete fat suppression, or increased architectural complexity were the independent predictive features of ALT; but not the contrast enhancement. Post-contrast MRI changed the impression in a total of 5 studies (3 for R1 and 4 for R2; 2 studies are common); all of them were incorrectly changed from Ls to ALTs. Overall, inter-reader kappa agreement was 0.42 (95% CI 0.39–0.56). Discordance between the two readers was statistically significant for both pathologically proven L (p

Background and Objectives As a measure of nicotine dependence among adolescent smokers, the modified Fagerstrom Tolerance Questionnaire (mFTQ; seven items), has been successfully used in the United States (USA). Nonetheless, the validity and reliability of mFTQ at the international level is still needed. The current study is the first to test the validity and reliability of mFTQ in four countries: Thailand, Spain, the USA, and Russia. Methods In a cross-sectional survey, mFTQ, risk factors of nicotine dependence, and sociodemographic characteristics were assessed. Risk factors included age of first cigarette, frequency of alcohol use, frequency of marijuana use, and number of cigarettes smoked yesterday. Salivary cotinine was also obtained in Thailand and Spain. Results For all four countries, mFTQ exhibited a single factor structure, as supported by previous work in the USA. For all studied countries except Thailand, mFTQ presented acceptable internal reliability. Overall, risk factors of nicotine dependence have predicted mFTQ scores across countries. Frequency of alcohol use in the USA and frequency of marijuana use in Thailand and Spain were not associated with mFTQ scores. Discussion and Conclusions mFTQ is a single-factor measure of nicotine dependence that shows acceptable internal consistency and validity across countries. Further work can advance the scale and tailor it to different cultures. Scientific Significance mFTQ can be a clinically practical international measure of nicotine dependence. This study provides initial support for the utility of the mFTQ among Thai, Spanish, American, and Russian adolescents. Further research is needed to test and advance mFTQ across cultures. (Am J Addict 2017;XX:1–8)

While some individuals can defy the lure of temptation, many others find appetizing food irresistible. The goal of this study was to investigate the neuropsychological mechanisms that increase individuals' vulnerability to cue‐induced eating. Using ERPs, a direct measure of brain activity, we showed that individuals with larger late positive potentials in response to food‐related cues than to erotic images are more susceptible to cue‐induced eating and, in the presence of a palatable food option, eat more than twice as much as individuals with the opposite brain reactivity profile. By highlighting the presence of individual brain reactivity profiles associated with susceptibility to cue‐induced eating, these findings contribute to the understanding of the neurobiological basis of vulnerability to obesity., Our findings contribute to the understanding of the biological bases underlying individual differences in vulnerability to cue‐induced eating, and they represent a step toward identifying new targets for personalized weight control interventions.

© 2016 SAGE Publications. Opening and charting in the incorrect patient electronic record presents a patient safety issue. The authors investigated the prevalence of reported errors and whether efforts utilizing the anesthesia time-out and barcoding have decreased the incidence of errors in opening and charting in the patient electronic medical record in the perioperative environment. The authors queried the database for all surgeries and procedures requiring anesthesia from January 2009 to September 2012. Of the 115,760 records of anesthesia procedures identified, there were 57 instances of incorrect record opening and charting during the study period. A decreasing trend was observed for all sites combined (p < 0.0001) and at the off-site locations (p = 0.0032). All locations and the off-site locations demonstrated a statistically significant decreasing pattern of errors over time. Barcoding and the anesthesia time-out may play an important role in decreasing errors in incorrect patient record opening in the perioperative environment.

PURPOSE: The recovery pace of absolute lymphocyte count (ALC) is prognostic after hematopoietic stem cell transplantation (SCT). Previous studies have evaluated a wide range of ALC cutoffs and time points to predict outcomes. We aimed to determine the optimal ALC measure for outcome prediction after SCT from bone marrow grafts (BMT). METHODS: 518 patients who underwent BMT for acute leukemia or myelodysplastic syndrome between 1999 and 2010 were divided into training and test sets to assess the prognostic values of ALC on days 30, 60, 90, 120, 180, as well as, the first post-transplant day on which a patient achieved ALC of 100, 200, 300, 400, 500, and 1000/μL. RESULTS: In the training set, the best predictor of overall survival (OS), relapse-free survival (RFS), and non-relapse mortality (NRM) was ALC on day 60. In the whole patient cohort, multivariable analyses demonstrated significantly better OS, RFS, NRM, and lower incidence of graft-versus-host disease among patients with ALC >300/μL on day 60, both including and excluding patients who had developed graft-versus-host disease prior to day 60. Among the patient-, disease-, and transplant-related factors assessed, only busulfan-based conditioning was significantly associated with higher ALC counts on day 60 in both cohorts. CONCLUSION: The optimal ALC cutoff to predict outcomes after BMT is ALC of 300/μL on day 60 post-transplant.

BACKGROUND Previous studies have not evaluated the prevalence and specific risk factors for the development of left ventricular (LV) thrombus in patients with severely reduced left ventricular dysfunction due to chemotherapy-related cardiomyopathy. We sought to evaluate the prevalence and potential markers of LV thrombus in this patient population. METHODS From January 2009 to December 2013, patients with chemotherapy-related severe LV dysfunction (LV ejection fraction [LVEF] ≤ 30%) identified from MD Anderson Cancer Center database were reviewed. Patient characteristics and echocardiographic parameters were analyzed to determine potential risk factors for LV thrombus. RESULTS A total of 121 patients met inclusion criteria (age 54.8 ± 15.2 years; female 63.6%; LVEF 26.3 ± 4%). LV thrombus was present in 9 patients (7.4%). Patients with LV thrombus have significantly lower LVEF compared to those without (18.7 ± 3.8% vs 26.9 ± 3.4%, P

While some individuals can defy the lure of temptation, many others find appetizing food irresistible. The goal of this study was to investigate the neuropsychological mechanisms that increase individuals' vulnerability to cue-induced eating. Using ERPs, a direct measure of brain activity, we showed that individuals with larger late positive potentials in response to food-related cues than to erotic images are more susceptible to cue-induced eating and, in the presence of a palatable food option, eat more than twice as much as individuals with the opposite brain reactivity profile. By highlighting the presence of individual brain reactivity profiles associated with susceptibility to cue-induced eating, these findings contribute to the understanding of the neurobiological basis of vulnerability to obesity.

Many commonly used statistical methods for data analysis or clinical trial design rely on incorrect assumptions, or assume an over-simplified framework that ignores important information. Such statistical practices may lead to incorrect conclusions about treatment effects, or clinical trial designs that are impractical or that do not accurately reflect the investigator’s goals. Bayesian nonparametric (BNP) models and methods are a very flexible new class of statistical tools that can overcome such limitations. This is because BNP models can accurately approximate any distribution or function, and can accommodate a broad range of statistical problems, including density estimation, regression, survival analysis, graphical modeling, neural networks, classification, clustering, population models, forecasting and prediction, spatio-temporal models, and causal inference. This paper describes three illustrative applications of BNP methods, including a randomized clinical trial to compare treatments for intraoperative air leaks after pulmonary resection, estimating survival time with different multi-stage chemotherapy regimes for acute leukemia, and evaluating joint effects of targeted treatment and an intermediate biological outcome on progression-free survival time in prostate cancer.

Background The Human Microbiome has been variously associated with the immune-regulatory mechanisms involved in the prevention or development of many non-infectious human diseases such as autoimmunity, allergy and cancer. Integrative approaches which aim at associating the composition of the human microbiome with other available information, such as clinical covariates and environmental predictors, are paramount to develop a more complete understanding of the role of microbiome in disease development. Results In this manuscript, we propose a Bayesian Dirichlet-Multinomial regression model which uses spike-and-slab priors for the selection of significant associations between a set of available covariates and taxa from a microbiome abundance table. The approach allows straightforward incorporation of the covariates through a log-linear regression parametrization of the parameters of the Dirichlet-Multinomial likelihood. Inference is conducted through a Markov Chain Monte Carlo algorithm, and selection of the significant covariates is based upon the assessment of posterior probabilities of inclusions and the thresholding of the Bayesian false discovery rate. We design a simulation study to evaluate the performance of the proposed method, and then apply our model on a publicly available dataset obtained from the Human Microbiome Project which associates taxa abundances with KEGG orthology pathways. The method is implemented in specifically developed R code, which has been made publicly available. Conclusions Our method compares favorably in simulations to several recently proposed approaches for similarly structured data, in terms of increased accuracy and reduced false positive as well as false negative rates. In the application to the data from the Human Microbiome Project, a close evaluation of the biological significance of our findings confirms existing associations in the literature. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1516-0) contains supplementary material, which is available to authorized users.

© 2017 Elsevier Inc. Purpose Long-term survival of women with advanced-stage ovarian cancer is relatively rare. Little is known about quality of life (QOL) and survivorship concerns of these women. Here, we describe QOL of women with advanced-stage ovarian cancer surviving for 8.5 years or longer and compare women with 0–1 recurrence to those with multiple recurrences. Methods Participants (n = 56) recruited from 5 academic medical centers and the Ovarian Cancer Research Fund Alliance completed surveys regarding QOL (FACT-O), mood (CESD), social support (SPS), physical activity (IPAQ-SF), diet, and clinical characteristics. Median survival was 14.0 years (range 8.8–33.3). Results QOL and psychological adjustment of long-term survivors was relatively good, with mean FACT-G scores (multiple recurrences: 80.81 ± 13.95; 0–1 recurrence: 89.05 ± 10.80) above norms for healthy community samples (80.1 ± 18.1). Survivors with multiple recurrences reported more compromised QOL in domains of physical and emotional well-being (p

To identify unique echocardiographic features that could be used to reliably predict LVEF recovery upon resolution of sinus tachycardia in patients with cancer.Sinus tachycardia may be a manifestation of underlying cardiomyopathy or can lead to a reversible form of dilated cardiomyopathy known as tachycardia-mediated cardiomyopathy. While distinguishing the two can be challenging, predicting recovery regardless of cause can be of significant clinical importance in the cancer population.Results of echocardiograms performed were collected. Patients with a repeat echocardiogram within 6 months of the initial echocardiogram were included. Patients with structural heart disease, acute coronary syndrome, sepsis, and pericardial disease were excluded. A comparison between baseline echocardiogram and subsequent echocardiogram was made to determine whether specific echocardiographic parameters predicted LVEF recovery. Two groups of patients were defined at the outset of the study. The recovered group was comprised of patients with reduced LVEF in the setting of sinus tachycardia and normal LVEF with resolution of tachycardia to normal sinus rhythm (NSR). The unrecovered group was comprised of subjects with low LVEF in the setting of both sinus tachycardia and NSR.A total of 40 patients were included in the study. LVEF in the recovered group (n=18) was 42.8% with sinus tachycardia and increased to 58.3% with NSR. Average LVEF in the unrecovered group (n=22) was 35.1% with tachycardia and improved to 38.5% with NSR. Medial TDI (E') was significantly greater in the recovered group with both tachycardia (7.95 cm/s versus 4.56 cm/s, P.001) and NSR (8.11 cm/s versus 5.13 cm/s, P.001). Similarly, lateral TDI (E') was significantly greater in the recovered group than in the unrecovered group during tachycardia (8.97 cm/s versus 5.13 cm/s, P.001) and NSR (9.05 cm/s versus 5.13 cm/s, P.001). Multivariable logistic regression analysis showed that medial TDI6.5 cm/s (OR=30.9, P=.001) and lateral TDI7.8 cm/s (OR=52.5, P=.002) are positively associated with the probability of LVEF recovery.In conclusion, TDI (medial E'6.5 cm/s; lateral E'7.8 cm/s) appears to predict LVEF recovery in patients with sinus tachycardia upon resolution of the tachycardia in patients with cancer.

© Mary Ann Liebert, Inc. 2016. Background: For more than two decades, national career development programs (CDPs) have addressed underrepresentation of women faculty in academic medicine through career and leadership curricula. We evaluated CDP participation impact on retention. Methods: We used Association of American Medical Colleges data to compare 3268 women attending CDPs from 1988 to 2008 with 17,834 women and 40,319 men nonparticipant faculty similar to CDP participants in degree, academic rank, first year of appointment in rank, and home institution. Measuring from first year in rank to departure from last position held or December 2009 (study end date), we used Kaplan-Meier curves; Cox survival analysis adjusted for age, degree, tenure, and department; and 10-year rates to compare retention. Results: CDP participants were significantly less likely to leave academic medicine than their peers for up to 8 years after appointment as Assistant and Associate Professors. Full Professor participants were significantly less likely to leave than non-CDP women. Men left less often than non-CDP women at every rank. Participants attending more than one CDP left less often than those attending one, but results varied by rank. Patterns of switching institutions after 10 years varied by rank; CDP participants switched significantly less often than men at Assistant and Associate Professor levels and significantly less often than non-CDP women among Assistant Professors. Full Professors switched at equal rates. Conclusion: National CDPs appear to offer retention advantage to women faculty, with implications for faculty performance and capacity building within academic medicine. Intervals of retention advantage for CDP participants suggest vulnerable periods for intervention.

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations.

Patients with cancer undergoing head and neck reconstruction can experience significant distress from alterations in appearance and bodily functioning. We sought to delineate salient dimensions of body image concerns in this patient population preparing for reconstructive surgery.Participants completed self-report questionnaires evaluating numerous aspects of body image. We used Bayesian factor analysis modeling methods to identify latent factors emerging from the data.We identified 2 latent factors: appearance distress and functional difficulties. The highest level of preoperative body image concerns were related to distress about appearance changes and its perceived social consequences. Appearance distress items displayed greater variability compared with functional difficulties.Appearance and functional changes to body image are important areas of concern for patients with head and neck cancer as they prepare for reconstructive surgery. Knowledge regarding specific body image issues can be used to guide psychosocial assessments and intervention to enhance patient care. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1035-1042, 2016.

The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks in a wide spectrum of biological systems. © 2016 Trevino et al.

Atypical femoral fractures (AFFs) are rare adverse events attributed to bisphosphonate (BP) use. Few cases of AFF in cancer have been described; the aim of this study is to identify the incidence and risk factors for AFF in a large cancer center. This retrospective study was conducted at the MD Anderson Cancer Center. The incidence rate of AFF among BP users was calculated from January 1, 2004 through December 31, 2013. The control group (n = 51) included 2 or 3 patients on BPs matched for age (≤1 year) and gender. Logistic regression analysis was used to assess the relationship between clinical characteristics and AFF. Twenty-three AFF cases were identified radiographically among 10,587 BP users, the total BP exposure was 53,789 months (4482 years), and the incidence of AFF in BP users was 0.05 cases per 100,000 person-years. Meanwhile, among 300,553 patients who did not receive BPs there were 2 cases of AFF as compared with the 23 cases noted above. The odds ratio (OR) of having AFF in BP users was 355.58 times higher (95% CI, 84.1 to 1501.4, p 0.0001) than the risk in non-BP users. The OR of having AFF in alendronate users was 5.54 times greater (OR 5.54 [95% CI, 1.60 to 19.112, p = 0.007]) than the odds of having AFF among other BP users. Patients who were on zoledronic acid (ZOL) had smaller odds of developing AFF compared with other BP users in this matched case control sample. AFFs are rare, serious adverse events that occur in patients with cancer who receive BP therapy. Patients with cancer who receive BPs for prior osteoporosis therapy or for metastatic cancer are at higher risk of AFF. © 2016 American Society for Bone and Mineral Research.

The process of cancer-related breast reconstruction is typically multi-staged and can take months to years to complete, yet few studies have examined patient psychosocial well-being during the reconstruction process. We investigated the effects of reconstruction timing and reconstruction stage on body image and quality of life at specific time points during the breast reconstruction process.In this cross-sectional study, 216 patients were grouped into four reconstructive stages: pre-reconstruction, completed stage 1, completed stage 2, and final stages. Multiple regression analyses examined the roles of reconstruction timing (immediate vs delayed reconstruction) and reconstruction stage as well as their interaction in predicting body image and quality of life, controlling for patient age, BMI, type of reconstruction, chemotherapy, radiation therapy, and major complication(s).A difference in pattern of body image was observed across the reconstructive stages, with those receiving delayed reconstruction showing significant decrease in body image dissatisfaction compared with those with immediate reconstruction. At pre-reconstruction, patients awaiting delayed reconstruction reported significantly lower social well-being compared with those awaiting immediate reconstruction. Reconstruction stage predicted emotional well-being, with higher emotional well-being observed in those who had commenced reconstruction.Timing and stage of reconstruction are important to consider when examining psychosocial outcomes of breast cancer patients undergoing reconstruction. Those waiting to initiate delayed reconstruction appear at particular risk for body image, emotional, and social distress. Our findings have implications for delivery of psychosocial treatment to maximize body image and quality of life of patients undergoing cancer-related breast reconstruction.Copyright © 2015 John WileySons, Ltd.

Mesoderm Inducer in Xenopus Like1 (MIXL1), a paired-type homeobox transcription factor induced by TGF-β family of ligands is required for early embryonic specification of mesoderm and endoderm. Retrovirally transduced Mixl1 is reported to induce acute myelogenous leukemia (AML) with a high penetrance. But the mechanistic underpinnings of MIXL1 mediated leukemogenesis are unknown. Here, we establish the protooncogene c-REL to be a transcriptional target of MIXL1 by genome wide chromatin immune precipitation. Accordingly, expression of c-REL and its downstream targets BCL2L1 and BCL2A2 are elevated in MIXL1 expressing cells. Notably, MIXL1 regulates c-REL through a zinc finger binding motif, potentially by a MIXL1-Zinc finger protein transcriptional complex. Furthermore, MIXL1 expression is detected in the cancer genome atlas (TCGA) AML samples in a pattern mutually exclusive from that of HOXA9, CDX2 and HLX suggesting the existence of a core, yet distinct HOX transcriptional program. Finally, we demonstrate MIXL1 to be induced by BMP4 and not TGF-β in primary human hematopoietic stem and progenitor cells. Consequently, MIXL1 expressing AML cells are preferentially sensitive to the BMPR1 kinase inhibitor LDN-193189. These findings support the existence of a novel MIXL1-c REL mediated survival axis in AML that can be targeted by BMPR1 inhibitors. (MIXL1- human gene, Mixl1- mouse ortholog, MIXL1- protein).

© 2014 © 2014 Taylor & Francis. Increasing attention is being given to developing quantitative measures of facial expression. This study used quantitative facial expression analysis to examine associations between smiling intensity and psychosocial functioning in patients with head and neck cancer (HNC). Smiling intensity of 95 HNC patients was measured using 48 quantitative measures calculated from facial photographs with and without a smile. We computed a composite smiling intensity score for each patient representing the degree of similarity to healthy controls. A lower composite score indicates that the person is less expressive, on average, than healthy controls. Patients also completed self-report measures assessing domains of body image and quality of life (QOL). Spearman rank correlations were computed to examine relationships between composite scores and psychosocial functioning. Composite scores were significantly correlated with multiple measures of body image and QOL. Specifically, decreased smiling intensity was associated with feelings of dissatisfaction with ones body, perceived negative social impact of body image, increased use of avoidance as a body image-coping strategy, reduced functional well-being, and greater head and neck cancer-specific issues. To the best of our knowledge, this is the first study to demonstrate associations between an objectively quantified facial expression (i.e. smiling) and psychosocial functioning. Most previous studies have measured facial expression qualitatively. These findings indicate that smiling intensity may serve as an important clinical indicator of psychosocial well-being and warrants further clinical investigation.

Transcriptional enhancers are genomic sequences bound by transcription factors that act together with basal transcriptional machinery to regulate gene transcription. Several high-throughput methods have generated large datasets of tissue-specific enhancer sequences with putative roles in developmental processes. However, few enhancers have been deleted from the genome to determine their roles in development. To understand the roles of two enhancers active in the mouse embryonic limb bud we deleted them from the genome. Although the genes regulated by these enhancers are unknown, they were selected because they were identified in a screen for putative limb bud-specific enhancers associated with p300, an acetyltransferase that participates in protein complexes that promote active transcription, and because the orthologous human enhancers (H1442 and H280) drive distinct lacZ expression patterns in limb buds of embryonic day (E) 11.5 transgenic mice. We show that the orthologous mouse sequences, M280 and M1442, regulate dynamic expression in the developing limb. Although significant transcriptional differences in enhancer-proximal genes in embryonic limb buds accompany the deletion of M280 and M1442 no gross limb malformations during embryonic development were observed, demonstrating that M280 and M1442 are not required for mouse limb development. However, M280 is required for the development and/or maintenance of body size; M280 mice are significantly smaller than controls. M280 also harbors an “ultraconserved” sequence that is identical between human, rat, and mouse. This is the first report of a phenotype resulting from the deletion of an ultraconserved element. These studies highlight the importance of determining enhancer regulatory function by experiments that manipulate them in situ and suggest that some of an enhancer's regulatory capacities may be developmentally tolerated rather than developmentally required.

BACKGROUND: The fatality rate for general aviation, 82 times that of air carriers and even higher for those involving aeromedical transportation, has not declined over time. Although noncommercial (private) pilots are increasingly seeking the instrument rating (IFR), which offers safety advantages, there is a paucity of research on causes of fatal crashes for this aviator subset. METHODS: The NTSB accident database was queried for general aviation fatal accidents involving private pilots. Exact two sample proportions, linear regression model outcomes (log-odds), and Poisson rate ratio tests were used for statistical analysis. RESULTS: The fatal accident rate for flights in instrument conditions decreased 55% over 10 yr (2002-2011) although an increased fatality rate was evident for pilots > 65 yr of age. Instrument approach deficiency (lAD), spatial disorientation/failure to maintain control (SD/FMC), and failure to maintain obstacle/terrain clearance (FMOTC) were common causes of fatal accidents in reduced visibility. However a > 55% decline in fatal accidents due to IAD was evident over the decade. Under visual conditions, engine/air-frame malfunction, aerodynamic stall, and FMOTC represented frequent causes. Of these, FMOTC showed a statistically significant decline over 10 yr. Comparing day and night operations, fatal crashes attributed to FMOTC and IAD were more frequent at night. CONCLUSION: For the IFR-rated private pilot, our study argues for an emphasis on training and currency in SD/FMC and aerodynamic stall recovery. Likewise training to remedy IAD, the frequent cause of fatal night accidents, and flying by instrument flight rules to assure obstacle/terrain clearance should be encouraged for pilots undertaking such operations. Language: en

In this paper we present a novel wavelet-based Bayesian nonparametric regression model for the analysis of functional magnetic resonance imaging (fMRI) data. Our goal is to provide a joint analytical framework that allows to detect regions of the brain which exhibit neuronal activity in response to a stimulus and, simultaneously, infer the association, or clustering, of spatially remote voxels that exhibit fMRI time series with similar characteristics. We start by modeling the data with an hemodynamic response function (HRF) with a voxel-dependent shape parameter. We detect regions of the brain activated in response to a given stimulus by using mixture priors with a spike at zero on the coefficients of the regression model. We account for the complex spatial correlation structure of the brain by using a Markov Random Field (MRF) prior on the parameters guiding the selection of the activated voxels, therefore capturing correlation among nearby voxels. In order to infer association of the voxel time courses, we assume correlated errors, in particular long memory, and exploit the whitening properties of discrete wavelet transforms. Furthermore, we achieve clustering of the voxels by imposing a Dirichlet Process (DP) prior on the parameters of the long memory process. For inference, we use Markov Chain Monte Carlo (MCMC) sampling techniques that combine Metropolis- Hastings schemes employed in Bayesian variable selection with sampling algorithms for nonparametric DP models. We explore the performance of the proposed model on simulated data, with both block- and event-related design, and on real fMRI data.

Instrument certification (IFR) enhances a pilot's skills in precisely controlling the aircraft and requires a higher level of standards in maintaining heading and altitude compared with the less stringent private pilot certificate. However, there have been no prior studies to compare fatal accident causes for airmen with, and without, this rating, The NTSB accident database was queried for general aviation fatal accidents for private pilots with, and without IFR certification. Exact Poisson tests were used to calculate whether two rate parameters were equal (ratio of 1), normalized to the number of IFR-rated pilots and flight hours in the given time period. Proportion tests were used to determine whether there were significant differences in fatal accident causes between IFR-certified and non-certified pilots. A logistic regression for log-odds success was used in determining the trend and effect of age on fatal accident rates. IFR certification was associated with a reduced risk of accidents due to failure to maintain obstacle/terrain clearance and spatial disorientation for day and night operations respectively. In contrast, the likelihood of fatal accident due to equipment malfunction during day operations was higher for IFR-certified pilots. The fatal accident rate decreased over the last decade for IFR-certified but not for non-IFR-certified private pilots. However, the overall accident rate for IFR-certified private pilots was more than double that of the cohort lacking this certification. Finally, we found a trend for an increased fatality rate with advancing age for both group of pilots. Our findings informs on where training and/or technology should be focused. Both training for aerodynamic stalls, which causes over a quarter of all fatal accidents, should be intensified for both IFR-certified and non-certified private pilots. Similarly, adherence to minimum safe altitudes for both groups of pilots should be encouraged toward reducing the fatal accidents rate due to failure to maintain obstacle/terrain clearance. For night operations, the high percentage of accidents due to spatial disorientation for non-IFR certified airmen suggests that additional training be required for such operations or such flights carry restrictions for this subset of pilots.

Background: Weight gain, insulin-like growth factor-I (IGF-I) levels, and excess exogenous steroid hormone use are putative cancer risk factors, yet their interconnected pathways have not been fully characterized. This cross-sectional study investigated the relationship between plasma IGF-I levels and weight gain according to body mass index (BMI), leptin levels, and exogenous estrogen use among postmenopausal women. Methods: This study included 794 postmenopausal women who enrolled in an ancillary study of the Women's Health Initiative Observational Study between February 1995 and July 1998. The relationship between IGF-I levels and weight gain was analyzed using ordinal logistic regression. We used the molar ratio of IGF-I to IGF binding protein-3 (IGF-I/IGFBP-3) or circulating IGF-I levels adjusting for IGFBP-3 as a proxy of bioavailable IGF-I. The plasma concentrations were expressed as quartiles. Results: Among the obese group, women in the third quartile (Q3) of IGF-I and highest quartile of IGF-I/IGFBP-3 were less likely to gain weight (>3% from baseline) than were women in the first quartiles (Q1). Among the normal-weight group, women in Q2 and Q3 of IGF-I/IGFBP-3 were 70% less likely than those in Q1 to gain weight. Among current estrogen users, Q3 of IGF-I/IGFBP-3 had 0.5 times the odds of gaining weight than Q1. Conclusions: Bioavailable IGF-I levels were inversely related to weight gain overall. Impact: Although weight gain was not consistent with increases in IGF-I levels among postmenopausal women in this report, avoidance of weight gain as a strategy to reduce cancer risk may be recommended. Cancer Epidemiol Biomarkers Prev; 23(3); 534–44. ©2013 AACR.

To evaluate bone marrow changes on knee magnetic resonance imaging (MRI) in patients with 3- to 6-week-long period of unloading. MRI knee examinations were performed in 30 patients (14 men, 16 women; aged 20–53 years) at baseline and 5–10 weeks after immobilisation of the ipsilateral lower extremity; subsets of patients were examined at additional time-points. Ten volunteers (4 men, 6 women; aged 20–50 years) were studied as control cohort at two time-points. Bone marrow signal abnormalities were analysed according to: (1) severity, (2) signal alteration relative to hyaline cartilage, (3) morphology, (4) increased vascularity in the knee joint and (5) T1-signal alteration. Spearman’s rank correlation test (SRC) and Kendall’s tau (KT) were used to compare individual scores. All 30 patients presented abnormal bone marrow findings after unloading, which reached a peak at 10–25 weeks (P

Body image is a critical issue for cancer patients undergoing reconstructive surgery, as they can experience disfigurement and functional impairment. Distress related to appearance changes can lead to various psychosocial difficulties, and patients are often reluctant to discuss these issues with their healthcare team. Our goals were to design and evaluate a screening tool to aid providers in identifying patients who may benefit from referral for specialized psychosocial care to treat body image concerns.We designed a brief four-item instrument and administered it at a single time point to cancer patients who were undergoing reconstructive treatment. We used simple and multinomial regression models to evaluate whether survey responses, demographic, or clinical variables predicted interest and enrollment in counseling.Over 95% of the sample (n = 248) endorsed some concerns, preoccupation, or avoidance because of appearance changes. Approximately one-third of patients were interested in obtaining counseling or additional information to assist with body image distress. Each survey item significantly predicted interest and enrollment in counseling. Concern about future appearance changes was the single best predictor of counseling enrollment. Sex, age, and cancer type were not predictive of counseling interest or enrollment.We present initial data supporting use of the Body Image Screener for Cancer Reconstruction. Our findings suggest benefits of administering this tool to patients presenting for reconstructive surgery. It is argued that screening and treatment for body image distress should be provided to this patient population at the earliest possible time point.

The clinical and biological effects of metabolic alterations in cancer are not fully understood.In high-grade serous ovarian cancer (HGSOC) samples (n = 101), over 170 metabolites were profiled and compared with normal ovarian tissues (n = 15). To determine NAT8L gene expression across different cancer types, we analyzed the RNA expression of cancer types using RNASeqV2 data available from the open access The Cancer Genome Atlas (TCGA) website (http://www.cbioportal.org/public-portal/). Using NAT8L siRNA, molecular techniques and histological analysis, we determined cancer cell viability, proliferation, apoptosis, and tumor growth in in vitro and in vivo (n = 6-10 mice/group) settings. Data were analyzed with the Student's t test and Kaplan-Meier analysis. Statistical tests were two-sided.Patients with high levels of tumoral NAA and its biosynthetic enzyme, aspartate N-acetyltransferase (NAT8L), had worse overall survival than patients with low levels of NAA and NAT8L. The overall survival duration of patients with higher-than-median NAA levels (3.6 years) was lower than that of patients with lower-than-median NAA levels (5.1 years, P = .03). High NAT8L gene expression in other cancers (melanoma, renal cell, breast, colon, and uterine cancers) was associated with worse overall survival. NAT8L silencing reduced cancer cell viability (HEYA8: control siRNA 90.61% ± 2.53, NAT8L siRNA 39.43% ± 3.00, P.001; A2780: control siRNA 90.59% ± 2.53, NAT8L siRNA 7.44% ± 1.71, P.001) and proliferation (HEYA8: control siRNA 74.83% ± 0.92, NAT8L siRNA 55.70% ± 1.54, P.001; A2780: control siRNA 50.17% ± 4.13, NAT8L siRNA 26.52% ± 3.70, P.001), which was rescued by addition of NAA. In orthotopic mouse models (ovarian cancer and melanoma), NAT8L silencing reduced tumor growth statistically significantly (A2780: control siRNA 0.52 g ± 0.15, NAT8L siRNA 0.08 g ± 0.17, P.001; HEYA8: control siRNA 0.79 g ± 0.42, NAT8L siRNA 0.24 g ± 0.18, P = .008, A375-SM: control siRNA 0.55 g ± 0.22, NAT8L siRNA 0.21 g ± 0.17 g, P = .001). NAT8L silencing downregulated the anti-apoptotic pathway, which was mediated through FOXM1.These findings indicate that the NAA pathway has a prominent role in promoting tumor growth and represents a valuable target for anticancer therapy.Altered energy metabolism is a hallmark of cancer (1). Proliferating cancer cells have much greater metabolic requirements than nonproliferating differentiated cells (2,3). Moreover, altered cancer metabolism elevates unique metabolic intermediates, which can promote cancer survival and progression (4,5). Furthermore, emerging evidence suggests that proliferating cancer cells exploit alternative metabolic pathways to meet their high demand for energy and to accumulate biomass (6-8).

The risk of endoscopic interventions in thrombocytopenia has received little attention in the medical literature.The aim of this study was to assess the safety of endoscopic interventions including evaluation of GI bleeding (GIB) in patients with thrombocytopenia.Retrospective study, tertiary oncology center.Review of consecutive endoscopies with preprocedure platelet counts (PCs) of 75 × 10(3)/μL or lower.Risk of bleeding with routine endoscopic interventions and transfusion requirement after evaluation of GIB.A total of 617 (351 upper, 266 lower [90 colonoscopies]) endoscopies were performed in 395 patients. Forceps-biopsy specimens were obtained in 398 endoscopies (mean ± standard deviation [SD] PC: 38.21 ± 11.7 × 10(3)/μL) and 45 polypectomies were performed in 17 endoscopies (mean ± SD PC: 39.65 ± 8.53 × 10(3)/μL). The risk of bleeding was 1.5% (6 of 398 endoscopies) at the biopsy site and 4% (2 of 45 polypectomies) at the polypectomy site. Active GIB (mean ± SD PC: 32.85 ± 4.0 × 10(3)/μL) was observed in 68 (11% of 617) endoscopies and intervention (mean ± SD PC: 33.68 ± 4.6 × 10(3)/μL) was performed in 41 procedures. Together, angiodysplasias and ulcers were the most common etiology (51.2% of 41). Hemostasis was achieved in 39 (95.1% of 41) procedures. Comparison of blood transfusions ± 3 days of successful therapy showed a 52% reduction (P .001). By multivariate analysis, a higher aggregate blood transfusion 3 days preceding endoscopy (odds ratio 1.32; 95% confidence interval, 1.16-1.50; P .001) predicted endoscopic findings of active GIB.Retrospective design, single center.In the largest endoscopic experience reported in thrombocytopenic patients (Common Terminology Criteria for Adverse Events grade 3 or lower), bleeding caused by standard forceps biopsy and polypectomy (≤10 mm) was minor and easily controlled. Endoscopic therapy for GIB is safe and significantly reduces the packed red blood cell requirement and should be considered in patients with thrombocytopenia in the setting of an appropriate transfusion strategy.

Background Understanding longitudinal variability of the microbiome in ill patients is critical to moving microbiome-based measurements and therapeutics into clinical practice. However, the vast majority of data regarding microbiome stability are derived from healthy subjects. Herein, we sought to determine intra-patient temporal microbiota variability, the factors driving such variability, and its clinical impact in an extensive longitudinal cohort of hospitalized cancer patients during chemotherapy. Methods The stool (n = 365) and oral (n = 483) samples of 59 patients with acute myeloid leukemia (AML) undergoing induction chemotherapy (IC) were sampled from initiation of chemotherapy until neutrophil recovery. Microbiome characterization was performed via analysis of 16S rRNA gene sequencing. Temporal variability was determined using coefficients of variation (CV) of the Shannon diversity index (SDI) and unweighted and weighted UniFrac distances per patient, per site. Measurements of intra-patient temporal variability and patient stability categories were analyzed for their correlations with genera abundances. Groups of patients were analyzed to determine if patients with adverse outcomes had significantly different levels of microbiome temporal variability. Potential clinical drivers of microbiome temporal instability were determined using multivariable regression analyses. Results Our cohort evidenced a high degree of intra-patient temporal instability of stool and oral microbial diversity based on SDI CV. We identified statistically significant differences in the relative abundance of multiple taxa amongst individuals with different levels of microbiota temporal stability. Increased intra-patient temporal variability of the oral SDI was correlated with increased risk of infection during IC (P = 0.02), and higher stool SDI CVs were correlated with increased risk of infection 90 days post-IC (P = 0.04). Total days on antibiotics was significantly associated with increased temporal variability of both oral microbial diversity (P = 0.03) and community structure (P = 0.002). Conclusions These data quantify the longitudinal variability of the oral and gut microbiota in AML patients, show that increased variability was correlated with adverse clinical outcomes, and offer the possibility of using stabilizing taxa as a method of focused microbiome repletion. Furthermore, these results support the importance of longitudinal microbiome sampling and analyses, rather than one time measurements, in research and future clinical practice. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0409-1) contains supplementary material, which is available to authorized users.