Exploring Relations between Teachers’ Beliefs, Instructional Practices, and Students’ Beliefs in Statistics

We examined the epistemic climate of statistics classrooms across two different classrooms by measuring teachers’ espoused beliefs about teaching statistics and observing their teaching practices. We then explored whether students’ beliefs became more aligned with the epistemic climate of the classroom over time. Post-secondary students’ beliefs were measured at the beginning and end of the semester. To measure the epistemic climate, teachers completed self-reports of their beliefs about teaching and learning, and participated in two semi-structured interviews at the beginning and end of the semester. Moreover, several classroom observations were conducted over the course of the semester. Analyses of the data revealed that for one group of students in one class, their beliefs were well aligned with the classroom climate and remained stable over time whereas for the other group of students, their beliefs shifted over time to align with the classroom climate

Maternal Malaria and Gravidity Interact to Modify Infant Susceptibility to Malaria

BACKGROUND: In endemic areas, placental malaria due to Plasmodium falciparum is most frequent and severe in first-time mothers, and increases the risk of infant mortality in their offspring. Placental malaria may increase the susceptibility of infants to malaria parasitemia, but evidence for this effect is inconclusive. METHODS AND FINDINGS: During 2002–2004, we monitored parasitemia in 453 infants, including 69 who were born to mothers with placental malaria, in a region of northeastern Tanzania where malaria transmission is intense. We used a Cox proportional hazards model to evaluate the time from birth to first parasitemia, and a generalized estimating equations logistic regression model to evaluate risk of any parasitemia throughout the first year of life. Compared with infants whose mothers did not have placental malaria at delivery (“PM-negative”), offspring of mothers with placental malaria at delivery (“PM-positive”) were 41% more likely to experience their first parasitemia at a younger age (adjusted hazard ratio [AHR] = 1.41, 95% confidence interval [CI] 1.01–1.99). The odds of parasitemia throughout infancy were strongly modified by the interaction between placental malaria and gravidity (p for interaction = 0.008, Type 3 likelihood ratio test). Offspring of PM-negative primigravidae had lower odds of parasitemia during infancy (adjusted odds ratio [AOR] = 0.67, 95% CI 0.50–0.91) than offspring of PM-negative multigravidae, and offspring of PM-positive primigravidae had the lowest odds (AOR = 0.21, 95% CI 0.09–0.47). In contrast, offspring of PM-positive multigravidae had significantly higher odds of parasitemia (AOR = 1.59, 95% CI 1.16–2.17). CONCLUSION: Although parasitemia is more frequent in primigravid than multigravid women, the converse is true in their offspring, especially in offspring of PM-positive women. While placental malaria is known to increase mortality risk for first-born infants, it surprisingly reduced their risk of parasitemia in this study. Placental malaria of multigravidae, on the other hand, is a strong risk factor for parasitemia during infancy, and therefore preventive antimalarial chemotherapy administered to multigravid women close to term may reduce the frequency of parasitemia in their offspring

Analysis Method and Experimental Conditions Affect Computed Circadian Phase from Melatonin Data

Accurate determination of circadian phase is necessary for research and clinical purposes because of the influence of the master circadian pacemaker on multiple physiologic functions. Melatonin is presently the most accurate marker of the activity of the human circadian pacemaker. Current methods of analyzing the plasma melatonin rhythm can be grouped into three categories: curve-fitting, threshold-based and physiologically-based linear differential equations. To determine which method provides the most accurate assessment of circadian phase, we compared the ability to fit the data and the variability of phase estimates for seventeen different markers of melatonin phase derived from these methodological categories. We used data from three experimental conditions under which circadian rhythms - and therefore calculated melatonin phase - were expected to remain constant or progress uniformly. Melatonin profiles from older subjects and subjects with lower melatonin amplitude were less likely to be fit by all analysis methods. When circadian drift over multiple study days was algebraically removed, there were no significant differences between analysis methods of melatonin onsets (P = 0.57), but there were significant differences between those of melatonin offsets (P<0.0001). For a subset of phase assessment methods, we also examined the effects of data loss on variability of phase estimates by systematically removing data in 2-hour segments. Data loss near onset of melatonin secretion differentially affected phase estimates from the methods, with some methods incorrectly assigning phases too early while other methods assigning phases too late; missing data at other times did not affect analyses of the melatonin profile. We conclude that melatonin data set characteristics, including amplitude and completeness of data collection, differentially affect the results depending on the melatonin analysis method used

The androgen receptor CAG repeat polymorphism and modification of breast cancer risk in BRCA1 and BRCA2 mutation carriers.

INTRODUCTION: The androgen receptor (AR) gene exon 1 CAG repeat polymorphism encodes a string of 9-32 glutamines. Women with germline BRCA1 mutations who carry at least one AR allele with 28 or more repeats have been reported to have an earlier age at onset of breast cancer. METHODS: A total of 604 living female Australian and British BRCA1 and/or BRCA2 mutation carriers from 376 families were genotyped for the AR CAG repeat polymorphism. The association between AR genotype and disease risk was assessed using Cox regression. AR genotype was analyzed as a dichotomous covariate using cut-points previously reported to be associated with increased risk among BRCA1 mutation carriers, and as a continuous variable considering smaller allele, larger allele and average allele size. RESULTS: There was no evidence that the AR CAG repeat polymorphism modified disease risk in the 376 BRCA1 or 219 BRCA2 mutation carriers screened successfully. The rate ratio associated with possession of at least one allele with 28 or more CAG repeats was 0.74 (95% confidence interval 0.42-1.29; P = 0.3) for BRCA1 carriers, and 1.12 (95% confidence interval 0.55-2.25; P = 0.8) for BRCA2 carriers. CONCLUSION: The AR exon 1 CAG repeat polymorphism does not appear to have an effect on breast cancer risk in BRCA1 or BRCA2 mutation carriers

Rating general practitioner consultation performance in cancer care: Does the specialty of assessors matter? A simulated patient study

Background: Patients treated for prostate cancer may present to general practitioners (GPs) for treatment follow up, but may be reticent to have their consultations recorded. Therefore the use of simulated patients allows practitioner consultations to be rated. The aim of this study was to determine whether the speciality of the assessor has an impact on how GP consultation performance is rated. Methods: Six pairs of scenarios were developed for professional actors in two series of consultations by GPs. The scenarios included: chronic radiation proctitis, Prostate Specific Antigen (PSA) ‘bounce’, recurrence of cancer, urethral stricture, erectile dysfunction and depression or anxiety. Participating GPs were furnished with the patient’s past medical history, current medication, prostate cancer details and treatment, details of physical examinations. Consultations were video recorded and assessed for quality by two sets of assessors- a team of two GPs and two Radiation Oncologists deploying the Leicester Assessment Package (LAP). LAP scores by the GPs and Radiation Oncologists were compared. Results: Eight GPs participated. In Series 1 the range of LAP scores by GP assessors was 61%-80%, and 67%-86% for Radiation Oncologist assessors. The range for GP LAP scores in Series 2 was 51%- 82%, and 56%-89% for Radiation Oncologist assessors. Within GP assessor correlations for LAP scores were 0.31 and 0.87 in Series 1 and 2 respectively. Within Radiation Oncologist assessor correlations were 0.50 and 0.72 in Series 1 and 2 respectively. Radiation Oncologist and GP assessor scores were significantly different for 4 doctors and for some scenarios. Anticipatory care was the only domain where GPs scored participants higher than Radiation Oncologist assessors. Conclusion: The assessment of GP consultation performance is not consistent across assessors from different disciplines even when they deploy the same assessment tool

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment