Corrigendum: Machine Learning and Feature Selection Methods for Disease Classification With Application to Lung Cancer Screening Image Data.

[This corrects the article DOI: 10.3389/fonc.2019.01393.].

A Winding Road to Peace Building: Longitudinal Outcomes of a Peace Intervention for Survivors and Génocidaires of the 1994 Genocide Against the Tutsi in Rwanda.

This longitudinal study examined outcomes of a local peace-building intervention that applied principles of intergroup contact to promote reconciliation between génocidaires and survivors whom they have directly harmed during the 1994 Genocide Against the Tutsi in Rwanda. Individual interviews were conducted with 46 génocidaires and 45 survivors whom they have directly harmed during the genocide at 7-time points over the course of their 22-month participation in three programmatic activities (workshops, cell groups, and cooperative cow raising). One thousand bootstrapped samples generated to measure changes in outcomes indicated that survivors and génocidaires regarded themselves and those who directly impacted them during the genocide more positively after 22 months. Although both survivors and génocidaires experienced significant decline in trauma symptomatology after 22 months, they responded to programmatic activities differently. Cell group interactions sustained some positive outcomes (génocidaires perceived forgiveness by others) after the workshops and further improved others (génocidaires self-forgiveness). Survivors who participated in cell groups and raised cows with génocidaires demonstrated further willingness to reconcile compared to survivors who participated in cell groups alone. Our findings empirically support the benefits of promoting different forms of intergroup interactions long after a period of intense violence and highlight the importance of considering how the trajectories of outcomes can inform program and theory development. HIGHLIGHTS: Survivors and génocidaires in Rwanda benefited from a local intergroup contact intervention (CI). However, génocidaires and survivors they directly harmed benefited differently over 22-months. Preparing survivors and génocidaires with skills to participate in communal life is critical for CI. Highlighting both CI outcomes and trajectories are essential for program and theory development.

Machine Learning and Feature Selection Methods for Disease Classification With Application to Lung Cancer Screening Image Data.

As awareness of the habits and risks associated with lung cancer has increased, so has the interest in promoting and improving upon lung cancer screening procedures. Recent research demonstrates the benefits of lung cancer screening; the National Lung Screening Trial (NLST) found as its primary result that preventative screening significantly decreases the death rate for patients battling lung cancer. However, it was also noted that the false positive rate was very high (>94%).In this work, we investigated the ability of various machine learning classifiers to accurately predict lung cancer nodule status while also considering the associated false positive rate. We utilized 416 quantitative imaging biomarkers taken from CT scans of lung nodules from 200 patients, where the nodules had been verified as cancerous or benign. These imaging biomarkers were created from both nodule and parenchymal tissue. A variety of linear, nonlinear, and ensemble predictive classifying models, along with several feature selection methods, were used to classify the binary outcome of malignant or benign status. Elastic net and support vector machine, combined with either a linear combination or correlation feature selection method, were some of the best-performing classifiers (average cross-validation AUC near 0.72 for these models), while random forest and bagged trees were the worst performing classifiers (AUC near 0.60). For the best performing models, the false positive rate was near 30%, notably lower than that reported in the NLST.The use of radiomic biomarkers with machine learning methods are a promising diagnostic tool for tumor classification. The have the potential to provide good classification and simultaneously reduce the false positive rate.

Understanding HIV Transmission and Illness Stigma: A Relationship Revisited in Rural Rwanda.

Integrating an understanding of HIV transmission with structural-behavioral prevention approaches remains a priority in low prevalence rural regions in Africa. Many national indicators use categorical survey responses which do not capture the cultural nuances of HIV transmission knowledge that potentially reify stigmatizing treatment of persons living with HIV (PL-HIV). We examined the relationship between quantitative and qualitative measures of HIV knowledge and four forms of stigma (individual attitudes, felt normative, social distance, and stigma perceived by PLHIV) among 200 rural residents in Rwanda. Forty-two percent qualitatively reported concurrent accurate and partial knowledge of HIV transmission. Being more knowledgeable about HIV transmission was associated with less desire for social distancing from PLHIV. Our findings highlight the continued importance of reinforcing an accurate understanding of HIV transmission and correcting misinformation by drawing on quantitative and qualitative assessments of HIV knowledge as critical arms of HIV stigma reduction programs in low prevalence rural regions.

THE STRUCTURE AND SEASONALITY OF BAYLISASCARIS PROCYONIS POPULATIONS IN RACCOONS (PROCYON LOTOR).

Baylisascaris procyonis , the raccoon ( Procyon lotor ) ascarid, is a common roundworm parasite of raccoons that is also a well-recognized zoonotic pathogen, and a cause for conservation concern. The transmission dynamics of B. procyonis differ with host population attributes, season, and landscape. We examined how the parasite's population attributes change with season, parasite population structure, and host demographics. We examined 1,050 raccoon gastrointestinal tracts collected from 1996 to 2012. Of the 1,050 raccoons necropsied, 382 (36%) were infected with at least one B. procyonis (x¯=15.8 [95% confidence interval=13.39-18.26]; median=7; range 1-199 worms/host), and populations were overdispersed. There was a seasonal change in prevalence with a peak in October/November. Worm burdens decreased approximately 28% per month from January to June and increased approximately 31% per month from June to December. The sex structure of B. procyonis populations was female-biased (56% female). Host demographics did not impact parasite population attributes. This study provides evidence that B. procyonis populations exhibit a yearly cycle of loss and recruitment that may impact the transmission dynamics of the parasite.

Poverty indicators and mental health functioning among adults living with HIV in Delhi, India.

Poor mental health functioning among persons living with HIV (PLHIV) has gained considerable attention particularly in low-income countries that disproportionately carry the global HIV/AIDS burden. Fewer studies, however, have examined the relationship between poverty indicators and mental health among PHLIV in India. Based on this cross-sectional study of 196 HIV-seropositive adults who received medical services at Shalom AIDS Project in Delhi, India, structural equation modeling and mediation analysis were employed to estimate the associations between poverty indices (household asset index, food security, unemployment, water treatment, sanitation), HIV-health factors (illness in the past 3 months, co-morbid medical conditions), and psychological distress. In the final model, ownership of fewer household assets was associated with higher levels of food insecurity, which in turn was associated with higher psychological distress. Also, the household asset index, food insecurity, and unemployment had a larger effect on psychological distress than new opportunistic infections. These findings build on increasing evidence that support concerted efforts to design, evaluate, and refine HIV mental health interventions that are mainstreamed with livelihood programming in high poverty regions in India.

Factors associated with high rates of antiretroviral medication adherence among youth living with perinatal HIV in Thailand.

Antiretroviral medication adherence behaviour among Thai youth with perinatal HIV in Thailand has received growing attention. However, few studies have examined individual predictors of antiretroviral adherence using multiple self-reports. A convenience sample of 89 Thai youth (interquartile range 14-16 years) with perinatal HIV at three paediatric programmes in Chiang Mai completed a structured questionnaire and reported their antiretroviral adherence in the past one, seven and 30 days using count-based recall and a visual analog scale. Mean self-reported adherence rates ranged from 83.5% (past 30 days) to 99.8% (yesterday) of the time. One-inflated beta regression models were used to examine the associations between antiretroviral adherence outcomes, treatment self-efficacy, depression, anxiety, social support and beliefs/attitudes about medications. Higher percentage of medications taken in the past 30 days was independently associated with higher treatment self-efficacy and fewer symptoms of depression. Adherence monitoring would benefit from focal assessment of youth depression and perceived capacity to follow their antiretroviral regimen.

Influences of stigma and HIV transmission knowledge on member support for faith-placed HIV initiatives in Chinese immigrant Buddhist and protestant religious institutions in New York City.

Ethnic religious institutions in the United States are uniquely positioned to influence HIV programming within Asian immigrant communities at large. This article examines how knowledge of HIV transmission and stigma potentially influenced attendees' support for their institutions' involvement in HIV programs. Quantitative questionnaires were individually administered to 400 Chinese attendees of Protestant churches and 402 attendees of Buddhist temples in New York City. Mediational analyses indicated that HIV stigma significantly mediated the direct effects of HIV transmission knowledge on attendees' support of their institution's involvement in HIV education (bias corrected and accelerated [BCa] 95% confidence interval [CI], 0.004 to 0.051), HIV care (BCa 95% CI, 0.019 to 0.078), and stigma reduction initiatives (BCa 95% CI, 0.013 to 0.070), while controlling for religious affiliation, age, gender, and education. To mobilize Chinese churches and temples to engage in HIV programming, it remains important to support educational programs on HIV transmission that specifically help to mitigate stigma toward persons living with HIV.

Karl Pearson and eugenics: personal opinions and scientific rigor.

The influence of personal opinions and biases on scientific conclusions is a threat to the advancement of knowledge. Expertise and experience does not render one immune to this temptation. In this work, one of the founding fathers of statistics, Karl Pearson, is used as an illustration of how even the most talented among us can produce misleading results when inferences are made without caution or reference to potential bias and other analysis limitations. A study performed by Pearson on British Jewish schoolchildren is examined in light of ethical and professional statistical practice. The methodology used and inferences made by Pearson and his coauthor are sometimes questionable and offer insight into how Pearson's support of eugenics and his own British nationalism could have potentially influenced his often careless and far-fetched inferences. A short background into Pearson's work and beliefs is provided, along with an in-depth examination of the authors' overall experimental design and statistical practices. In addition, portions of the study regarding intelligence and tuberculosis are discussed in more detail, along with historical reactions to their work.

Key properties of D-optimal designs for event-related functional MRI experiments with application to nonlinear models.

To properly formulate functional magnetic resonance imaging (fMRI) experiments with complex mental activity, it is advantageous to permit great flexibility in the statistical components of the design of these studies. The length of an experiment, the placement of various stimuli and the modeling approach used all affect the ability to detect mental activity. Major advances in understanding the implications of various designs of fMRI experiments have taken place over the last decade. Nevertheless, new and increasingly difficult issues relating to the modeling of hemodynamic responses and the detection of activated brain regions continue to arise because of the increasing complexity of the experiments. In this article, the D-optimality criterion is used in conjunction with a genetic algorithm to create probability-based design generators for the selection of designs in event-related fMRI experiments where the hemodynamic response function is modeled with a function that is nonlinear in the parameters. The designs produced by these generators are shown to perform well compared with locally D-optimal designs and provide insight into optimal design characteristics that investigators can utilize in the selection of interstimulus intervals. Designs with these characteristics are shown to be applicable to fMRI studies involving one or two stimulus types. The designs are also shown to be robust with respect to misspecification of an AR(1) error autocorrelation and compare favorably with a maximin procedure.