CBCRisk-Black: a personalized contralateral breast cancer risk prediction model for black women.

Purpose: Black breast cancer (BC) survivors have a higher risk of developing contralateral breast cancer (CBC) than Whites. Existing CBC risk prediction tools are developed based on mostly White women. To address this racial disparity, it is crucial to develop tools tailored for Black women to help them inform about their actual risk of CBC.

Joint risk prediction for hazardous use of alcohol, cannabis, and tobacco among adolescents: A preliminary study using statistical and machine learning.

For some, substance use during adolescence may be a stepping stone on the way to substance use disorders in adulthood. Risk prediction models may help identify adolescent users at elevated risk for hazardous substance use. This preliminary analysis used cross-sectional data (n = 270, ages 13-18) from the baseline dataset of a randomized controlled trial intervening with adolescent alcohol and/or cannabis use.

A preliminary risk prediction model for cannabis use disorder.

The ongoing trend toward legalization of cannabis for medicinal/recreational purposes is expected to increase the prevalence of cannabis use disorder (CUD). Thus, it is imperative to be able to predict the quantitative risk of developing CUD for a cannabis user based on their personal risk factors. Yet no such model currently exists.

A Bayesian Hierarchical Framework for Pathway Analysis in Genome-Wide Association Studies.

Background: Pathway analysis allows joint consideration of multiple SNPs belonging to multiple genes, which in turn belong to a biologically defined pathway. This type of analysis is usually more powerful than single-SNP analyses for detecting joint effects of variants in a pathway.

Methods: We develop a Bayesian hierarchical model by fully modeling the 3-level hierarchy, namely, SNP-gene-pathway that is naturally inherent in the structure of the pathways, unlike the currently used ad hoc ways of combining such information.

A segmented measurement error model for modeling and analysis of method comparison data.

Method comparison studies are concerned with estimating relationship between two clinical measurement methods. The methods often exhibit a structural change in the relationship over the measurement range. Ignoring this change would lead to an inaccurate estimate of the relationship.

A Bayesian latent variable approach to aggregation of partial and top-ranked lists in genomic studies.

In genomic research, it is becoming increasingly popular to perform meta-analysis, the practice of combining results from multiple studies that target a common essential biological problem. Rank aggregation, a robust meta-analytic approach, consolidates such studies at the rank level. There exists extensive research on this topic, and various methods have been developed in the past.

Effect of exogenous melatonin and different photoperiods on oxidative status and antioxidant enzyme activity in Chhotanagpuri ewe.

Aim: The present study was conducted to evaluate the effect of exogenous melatonin under different photoperiods on oxidative status in Chhotanagpuri ewe.

Materials And Methods: A total of 42 non-pregnant, non-lactating Chhotanagpuri ewe, having body weight ranging between 14.11±0.

Dose-dependent effect of mammographic breast density on the risk of contralateral breast cancer.

Purpose: Increased mammographic breast density is a significant risk factor for breast cancer. It is not clear if it is also a risk factor for the development of contralateral breast cancer.

Methods: The data were obtained from Breast Cancer Surveillance Consortium and included women diagnosed with invasive breast cancer or ductal carcinoma in situ between ages 18 and 88 and years 1995 and 2009.

Semiparametric modeling and analysis of longitudinal method comparison data.

Studies comparing two or more methods of measuring a continuous variable are routinely conducted in biomedical disciplines with the primary goal of measuring agreement between the methods. Often, the data are collected by following a cohort of subjects over a period of time. This gives rise to longitudinal method comparison data where there is one observation trajectory for each method on every subject.

A model for individualized risk prediction of contralateral breast cancer.

Purpose: Patients diagnosed with invasive breast cancer (BC) or ductal carcinoma in situ are increasingly choosing to undergo contralateral prophylactic mastectomy (CPM) to reduce their risk of contralateral BC (CBC). This is a particularly disturbing trend as a large proportion of these CPMs are believed to be medically unnecessary. Many BC patients tend to substantially overestimate their CBC risk.

Effect of temperature variation on hormonal concentration at various gestation stages in black Bengal goat.

Aim: The present study was conducted to evaluate the effect of risingtemperature on the metabolic as well as the reproductive performance of the black Bengal goat.

Materials And Methods: A total 27 numbers of non-pregnant black Bengal goats of the same parity comprised the experimental animals. The selected goats were randomly assigned to 3 groups of 9 each, maintaining uniformity in body weight (average 14-18 kg).

Tolerance bands for functional data.

Often the object of inference in biomedical applications is a range that brackets a given fraction of individual observations in a population. A classical estimate of this range for univariate measurements is a "tolerance interval." This article develops its natural extension for functional measurements, a "tolerance band," and proposes a methodology for constructing its pointwise and simultaneous versions that incorporates both sparse and dense functional data.

Characterization of Cement Particles Found in Peri-implantitis-Affected Human Biopsy Specimens.

Purpose: Peri-implantitis is a disease characterized by soft tissue inflammation and continued loss of supporting bone, which can result in implant failure. Peri-implantitis is a multifactorial disease, and one of its triggering factors may be the presence of excess cement in the soft tissues surrounding an implant. This descriptive study evaluated the composition of foreign particles from 36 human biopsy specimens with 19 specimens selected for analysis.

A heteroscedastic measurement error model for method comparison data with replicate measurements.

Measurement error models offer a flexible framework for modeling data collected in studies comparing methods of quantitative measurement. These models generally make two simplifying assumptions: (i) the measurements are homoscedastic, and (ii) the unobservable true values of the methods are linearly related. One or both of these assumptions may be violated in practice.

Measuring agreement in method comparison studies with heteroscedastic measurements.

We propose a methodology for evaluation of agreement between two methods of measuring a continuous variable whose variability changes with magnitude. This problem routinely arises in method comparison studies that are common in health-related disciplines. Assuming replicated measurements, we first model the data using a heteroscedastic mixed-effects model, wherein a suitably defined true measurement serves as the variance covariate.

-statistics for Repeated Measurements Data With Application to Trimmed Means, Quantiles and Tolerance Intervals.

The -statistics form an important class of estimators in nonparametric statistics. Its members include trimmed means and sample quantiles and functions thereof. This article is devoted to theory and applications of -statistics for repeated measurements data, wherein the measurements on the same subject are dependent and the measurements from different subjects are independent.

Breastfed infants metabolize perchlorate.

Bifidobacteria are the dominant intestinal bacteria in breastfed infants. It is known that they can reduce nitrate. Although no direct experiments have been conducted until now, inferred pathways for Bifidobacterium bifidum include perchlorate reduction via perchlorate reductase.

Krüppel-like Factor 4 activates HBG gene expression in primary erythroid cells.

The SP1/Krüppel-like Factor (SP1/KLF) family of transcription factors plays a role in diverse cellular processes, including proliferation, differentiation and control of gene transcription. The discovery of KLF1 (EKLF), a key regulator of HBB (β-globin) gene expression, expanded our understanding of the role of KLFs in erythropoiesis. In this study, we investigated a mechanism of HBG (γ-globin) regulation by KLF4.

Early dysregulation of the mitochondrial proteome in a mouse model of Alzheimer's disease.

Mitochondrial structural and functional alterations appear to play to an important role in the pathogenesis of Alzheimer's disease (AD). In the present study, we used a quantitative comparative proteomic profiling approach to analyze changes in the mitochondrial proteome in AD. A triple transgenic mouse model of AD (3xTg-AD) which harbors mutations in three human transgenes, APP(Swe), PS1(M146V) and Tau(P301L), was used in these experiments.

A unified approach for nonparametric evaluation of agreement in method comparison studies.

We present a nonparametric methodology for evaluation of agreement between multiple methods of measurement of a continuous variable. Our approach is unified in that it can deal with any scalar measure of agreement currently available in the literature, and can incorporate repeated and unreplicated measurements, and balanced as well as unbalanced designs. Our key idea is to treat an agreement measure as a functional of the joint cumulative distribution function of the measurements from multiple methods.

In vivo pharmaco-proteomic analysis of hydroxyurea induced changes in the sickle red blood cell membrane proteome.

Hydroxyurea (HU) is an effective drug for the treatment of sickle cell disease (SCD). The main clinical benefit of HU is thought to derive from its capacity to increase fetal hemoglobin (HbF) production. However, other effects leading to clinical benefit, such as improved blood rheology, have been suggested.

Monocyte protein signatures of disease severity in sickle cell anemia.

Using two-dimensional difference gel electrophoresis (2D DIGE) we have analyzed monocytes derived from 10 sickle cell disease patients (5 males and 5 females ages 12-18) to generate hypotheses regarding signature proteins that appear most positively and negatively correlated with vasoocclusive event rate. Signature proteins have been identified by tandem mass spectrometry. Based on the limited number of samples analyzed, the most negatively correlated proteins related to crises rate were transketolase and coronin in the membrane fraction and heat shock 70 kDa protein cognate 4, and adenylate kinase isoenzyme 2, mitochondrial found in the cytosolic fraction.

Pharmaco-proteomic study of hydroxyurea-induced modifications in the sickle red blood cell membrane proteome.

Hydroxyurea (HU) is an effective oral drug for the management of homozygous sickle cell anemia (SS) in part because it increases fetal hemoglobin (HbF) levels within sickle red blood cells (RBCs) and thus reduces sickling. However, results from the Multicenter Study of HU suggested that clinical symptoms often improved before a significant increase in HbF levels occurred. This indicated that HU may be acting through the modification of additional cellular mechanisms that are yet to be identified.

A Bayesian approach for sample size determination in method comparison studies.

Studies involving two methods for measuring a continuous response are regularly conducted in health sciences to evaluate agreement of a method with itself and agreement between methods. Notwithstanding their wide usage, the design of such studies, in particular, the sample size determination, has not been addressed in the literature when the goal is the simultaneous evaluation of intra- and inter-method agreement. We fill this need by developing a simulation-based Bayesian methodology for determining sample sizes in a hierarchical model framework.

A tolerance interval approach for assessment of agreement with left censored data.

We describe a tolerance interval approach for assessing agreement in method comparison data that may be left censored. We model the data using a mixed model and discuss a Bayesian and a frequentist methodology for inference. A simulation study suggests that the Bayesian approach with noninformative priors provides a good alternative to the frequentist one for moderate sample sizes as the latter tends to be liberal.