SEPARATION OF EPIDERMAL LAYERS OF THE NEWBORN RAT

A method is presented for the separation of epidermal strata by the successive elimination of either the basal or basal and spinous cells with 0.24 M NH4Cl at pH 9.5. Histologic evidence suggests that the residual epidermal strata obtained after incubation of the skin with NH4Cl are reproducible; hence, this technique circumvents loss of granular layer histidine-rich protein inherent with trypsin separation and provides an effective procedure for biochemical analysis of arginine-rich and lysine-rich proteins in the various differentiating epidermal cells

Differences in the perceived impact of sleep deprivation among surgical and non-surgical residents

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72096/1/j.1365-2923.2007.02963.x.pd

EM-mosaic detects mosaic point mutations that contribute to congenital heart disease.

BackgroundThe contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined.MethodsWe developed a new computational method, EM-mosaic (Expectation-Maximization-based detection of mosaicism), to analyze mosaicism in exome sequences derived primarily from blood DNA of 2530 CHD proband-parent trios. To optimize this method, we measured mosaic detection power as a function of sequencing depth. In parallel, we analyzed our cohort using MosaicHunter, a Bayesian genotyping algorithm-based mosaic detection tool, and compared the two methods. The accuracy of these mosaic variant detection algorithms was assessed using an independent resequencing method. We then applied both methods to detect mosaicism in cardiac tissue-derived exome sequences of 66 participants for which matched blood and heart tissue was available.ResultsEM-mosaic detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The estimated true frequency of mosaic variants above 10% mosaicism was 0.14/person in blood and 0.21/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction.ConclusionsWe estimate that ~ 1% of CHD probands have a mosaic variant detectable in blood that could contribute to cardiac malformations, particularly those damaging variants with relatively higher allele fraction. Although blood is a readily available DNA source, cardiac tissues analyzed contributed ~ 5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses

Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects.

Genetic variants are the primary driver of congenital heart disease (CHD) pathogenesis. However, our ability to identify causative variants is limited. To identify causal CHD genes that are associated with specific molecular functions, the study used prior knowledge to filter de novo variants from 2,881 probands with sporadic severe CHD. This approach enabled the authors to identify an association between left ventricular outflow tract obstruction lesions and genes associated with the WAVE2 complex and regulation of small GTPase-mediated signal transduction. Using CRISPR zebrafish knockdowns, the study confirmed that WAVE2 complex proteins brk1, nckap1, and wasf2 and the regulators of small GTPase signaling cul3a and racgap1 are critical to cardiac development

Epidemiologic Evaluation of Measurement Data in the Presence of Detection Limits

Quantitative measurements of environmental factors greatly improve the quality of epidemiologic studies but can pose challenges because of the presence of upper or lower detection limits or interfering compounds, which do not allow for precise measured values. We consider the regression of an environmental measurement (dependent variable) on several covariates (independent variables). Various strategies are commonly employed to impute values for interval-measured data, including assignment of one-half the detection limit to nondetected values or of “fill-in” values randomly selected from an appropriate distribution. On the basis of a limited simulation study, we found that the former approach can be biased unless the percentage of measurements below detection limits is small (5–10%). The fill-in approach generally produces unbiased parameter estimates but may produce biased variance estimates and thereby distort inference when 30% or more of the data are below detection limits. Truncated data methods (e.g., Tobit regression) and multiple imputation offer two unbiased approaches for analyzing measurement data with detection limits. If interest resides solely on regression parameters, then Tobit regression can be used. If individualized values for measurements below detection limits are needed for additional analysis, such as relative risk regression or graphical display, then multiple imputation produces unbiased estimates and nominal confidence intervals unless the proportion of missing data is extreme. We illustrate various approaches using measurements of pesticide residues in carpet dust in control subjects from a case–control study of non-Hodgkin lymphoma

Automated Phase Mapping with AgileFD and its Application to Light Absorber Discovery in the V-Mn-Nb Oxide System

Rapid construction of phase diagrams is a central tenet of combinatorial materials science with accelerated materials discovery efforts often hampered by challenges in interpreting combinatorial x-ray diffraction datasets, which we address by developing AgileFD, an artificial intelligence algorithm that enables rapid phase mapping from a combinatorial library of x-ray diffraction patterns. AgileFD models alloying-based peak shifting through a novel expansion of convolutional nonnegative matrix factorization, which not only improves the identification of constituent phases but also maps their concentration and lattice parameter as a function of composition. By incorporating Gibbs’ phase rule into the algorithm, physically meaningful phase maps are obtained with unsupervised operation, and more refined solutions are attained by injecting expert knowledge of the system. The algorithm is demonstrated through investigation of the V-Mn-Nb oxide system where decomposition of eight oxide phases, including two with substantial alloying, provides the first phase map for this pseudo-ternary system. This phase map enables interpretation of high-throughput band gap data, leading to the discovery of new solar light absorbers and the alloying-based tuning of the direct-allowed band-gap energy of MnV2O6. The open-source family of AgileFD algorithms can be implemented into a broad range of high throughput workflows to accelerate materials discovery

Hormonal Correlates and Predictors of Nutritional Recovery in Malnourished African Children.

Background: Malnourished children show variable growth responses to nutritional rehabilitation. We aimed to investigate whether these differences could be explained by variations in growth and energy-regulating hormones. Methods: Quasi-experimental study: Children aged 6-24 months in rural Gambia were recruited to controls if weight-for-height z-score (WHZ) > -2 (n = 22), moderate acute malnutrition if WHZ  -3 (n = 18) or severe acute malnutrition if WHZ < -3 (n = 20). Plasma hormone and salivary CRP levels were determined by ELISA. Results: In univariable analyses, increases in weight-for-age z-score (WAZ) in malnourished children were positively correlated with insulin (F-ratio 7.8, p = 0.006), C-peptide (F-ratio 12.2, p < 0.001) and cortisol (F-ratio 5.0, p = 0.03). In multivariable analysis, only baseline C-peptide (F-ratio 7.6, p = 0.009) predicted the changes in WAZ over 28 days of interventions. Conclusion: In rural Gambian, malnourished children, although it cannot be used in isolation, baseline C-peptide was a predictor of future response to rehabilitation

Human Leukocyte Antigen Class I and II Alleles and Overall Survival in Diffuse Large B-Cell Lymphoma and Follicular Lymphoma

Genetic variation in the 6p21 chromosomal region, including human leukocyte antigen (HLA) genes and tumor necrosis factor (TNF), has been linked to both etiology and clinical outcomes of lymphomas. We estimated the effects of HLA class I (A, B, and C), class II DRB1 alleles, and the ancestral haplotype (AH) 8.1 (HLAA*01-B*08-DRB1*03-TNF-308A) on overall survival (OS) among patients with diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) in a population-based study of non-Hodgkin lymphoma. During a median followup of 89 months, 31% (52 of 166) DLBCL and 28% (46 of 165) FL patients died. Using multivariate Cox regression models, we observed statistically significant associations between genetic variants and survival: HLA-Cw*07:01 was associated with poorer OS among DLBCL patients (Hazard ratio [HR] = 1.76, 95% confidence interval [CI] = 1.01–3.05); HLA-A*01:01 was associated with poorer OS (HR = 2.23, 95% CI = 1.24–4.01), and HLA-DRB1*13 (HR = 0.12, 95% CI = 0.02–0.90) and HLA-B Bw4 (HR = 0.36, 95% CI = 0.20–0.63) with better OS among FL patients. These results support a role for HLA in the prognosis of DLBCL and FL and represent a promising class of prognostic factors that warrants further evaluation

Development of candidate rotavirus vaccines derived from neonatal strains in India

The need for a rotavirus vaccine in India is based on the enormous burden associated with the &lt;100,000 deaths due to rotavirus diarrhea that occur annually among Indian children. Two rotavirus strains identified during nosocomial outbreaks of rotavirus infection in New Delhi and Bangalore, India, more than a decade ago are being developed as live oral vaccines. Infected newborns had no symptoms, shed virus for up to 2 weeks after infection, mounted a robust immune response, and demonstrated protection against severe rotavirus diarrhea after reinfection. The 2 strains are naturally occurring bovine-human reassortants. The New Delhi strain, 116E, is characterized as having a P[11],G9 genotype, and the Bangalore strain, I321, is characterized as having a P[11],G10 genotype. The strains have been prepared as pilot lots for clinical trials to be conducted in New Delhi. This unique project, which is developing a new rotavirus vaccine in India with the use of Indian strains, an Indian manufacturer, and an Indian clinical development program, aims to expedite introduction of rotavirus vaccines in India