Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

Background: Neuroblastoma (NB) is the most common extracranial solid tumor found in children. The frequent gain/loss of many chromosome bands in tumor cells and absence of mutations found at diagnosis suggests that NB is a copy number-driven cancer. Despite the previous work, a systematic analysis that investigates the relationship between such frequent gain/loss of chromosome bands and patient prognosis has yet to be implemented. Methods: First, we analyzed two NB CNV datasets to select chromosomal bands with a high frequency of gain or loss. Second, we applied a computational approach to infer sample-specific CNVs for each chromosomal band selected in step 1 based on gene expression data. Third, we applied univariate Cox proportional hazards models to examine the association between the resulting inferred copy number values (iCNVs) and patient survival. Finally, we applied multivariate Cox proportional hazards models to select chromosomal bands that remained significantly associated with prognosis after adjusting for critical clinical variables, including age, stage, gender, and MYCN amplification status. Results: Here, we used a computational method to infer the copy number variations (CNVs) of sample-specific chromosome bands from NB patient gene expression profiles. The resulting inferred CNVs (iCNVs) were highly correlated with the experimentally determined CNVs, demonstrating CNVs can be accurately inferred from gene expression profiles. Using this iCNV metric, we identified 58 frequent gain/loss chromosome bands that were significantly associated with patient survival. Furthermore, we found that 7 chromosome bands were still significantly associated with patient survival even when clinical factors, such as MYCN status, were considered. Particularly, we found that the chromosome band chr11p14 has high potential as a novel candidate cytogenetic biomarker for clinical use. Conclusion: Our analysis resulted in a comprehensive list of prognostic chromosome bands supported by strong statistical evidence. In particular, the chr11p14 gain event provided additional prognostic value in addition to well-established clinical factors, including MYCN status, and thereby represents a novel candidate cytogenetic biomarker with high clinical potential. Additionally, this computational framework could be readily extended to other cancer types, such as leukemia

Comparative Analysis of Mutant Huntingtin Binding Partners in Yeast Species.

Huntington\u27s disease is caused by the pathological expansion of a polyglutamine (polyQ) stretch in Huntingtin (Htt), but the molecular mechanisms by which polyQ expansion in Htt causes toxicity in selective neuronal populations remain poorly understood. Interestingly, heterologous expression of expanded polyQ Htt is toxic in Saccharomyces cerevisiae cells, but has no effect in Schizosaccharomyces pombe, a related yeast species possessing very few endogenous polyQ or Q/N-rich proteins. Here, we used a comprehensive and unbiased mass spectrometric approach to identify proteins that bind Htt in a length-dependent manner in both species. Analysis of the expanded polyQ-associated proteins reveals marked enrichment of proteins that are localized to and play functional roles in nucleoli and mitochondria in S. cerevisiae, but not in S. pombe. Moreover, expanded polyQ Htt appears to interact preferentially with endogenous polyQ and Q/N-rich proteins, which are rare in S. pombe, as well as proteins containing coiled-coil motifs in S. cerevisiae. Taken together, these results suggest that polyQ expansion of Htt may cause cellular toxicity in S. cerevisiae by sequestering endogenous polyQ and Q/N-rich proteins, particularly within nucleoli and mitochondria

A General Pattern-Based Design Optimization for Asymmetric Spoke-Type Interior PM Machines

A novel asymmetric spoke-type interior permanent magnet (AS-IPM) machine is proposed in this paper. It utilizes the magnetic-field-shifting (MFS) effect to improve the torque performance, which achieves a high utilization ratio of both permanent magnet (PM) torque and reluctance torque. In addition, a general pattern of rotor topologies is proposed to represent all possible machine structures. Various rotor structures can be obtained by changing the design parameters of the general pattern. A non-dominated sorting genetic algorithm II (NSGA-II) is adopted to automatically search for optimal rotor configurations. With the aid of the optimization program, an asymmetric spoke-type rotor structure with improved performance is obtained. To showcase the advantages of the proposed machine, the electromagnetic performance is compared between a conventional spoke-type interior permanent magnet (S-IPM) machine and a proposed AS-IPM machine. The finite-element simulation results show that the optimal design of the AS-IPM performs a 7.7% higher output torque ripple due to the MFS effect while the total PM volume remains the same. Meanwhile, the torque ripple of the proposed structure is significantly reduced by 82.1%

The steroid hormone estriol (E3) regulates epigenetic programming of fetal mouse brain and reproductive tract.

peer reviewed[en] BACKGROUND: Estriol (E3) is a steroid hormone formed only during pregnancy in primates including humans. Although E3 is synthesized at large amounts through a complex pathway involving the fetus and placenta, it is not required for the maintenance of pregnancy and has classically been considered virtually inactive due to associated very weak canonical estrogen signaling. However, estrogen exposure during pregnancy may have an effect on organs both within and outside the reproductive system, and compounds with binding affinity for estrogen receptors weaker than E3 have been found to impact reproductive organs and the brain. Here, we explore potential effects of E3 on fetal development using mouse as a model system. RESULTS: We administered E3 to pregnant mice, exposing the fetus to E3. Adult females exposed to E3 in utero (E3-mice) had increased fertility and superior pregnancy outcomes. Female and male E3-mice showed decreased anxiety and increased exploratory behavior. The expression levels and DNA methylation patterns of multiple genes in the uteri and brains of E3-mice were distinct from controls. E3 promoted complexing of estrogen receptors with several DNA/histone modifiers and their binding to target genes. E3 functions by driving epigenetic change, mediated through epigenetic modifier interactions with estrogen receptors rather than through canonical nuclear transcriptional activation. CONCLUSIONS: We identify an unexpected functional role for E3 in fetal reproductive system and brain. We further identify a novel mechanism of estrogen action, through recruitment of epigenetic modifiers to estrogen receptors and their target genes, which is not correlated with the traditional view of estrogen potency

Modeling and Identification of the Rate-Dependent Hysteresis of Piezoelectric Actuator Using a Modified Prandtl-Ishlinskii Model

Piezoelectric actuator (PEA) is an ideal microscale and nanoscale actuator because of its ultra-precision positioning resolution. However, the inherent hysteretic nonlinearity significantly degrades the PEA’s accuracy. The measured hysteresis of PEA exhibits strong rate-dependence and saturation phenomena, increasing the difficulty in the hysteresis modeling and identification. In this paper, a modified Prandtl-Ishlinskii (PI) hysteresis model is proposed. The weights of the backlash operators are updated according to the input rates so as to account for the rate-dependence property. Subsequently, the saturation property is realized by cascading a polynomial operator with only odd powers. In order to improve the efficiency of the parameter identification, a special control input consisting of a superimposition of multiple sinusoidal signals is utilized. Because the input rate of such a control input covers a wide range, all the parameters of the hysteresis model can be identified through only one set of experimental data, and no additional curve-fitting is required. The effectiveness of the hysteresis modeling and identification methodology is verified on a PEA-driven flexure mechanism. Experimental results show that the modeling accuracy is on the same order of the noise level of the overall system

Estimating the Daily NO₂ Concentration with High Spatial Resolution in the Beijing–Tianjin–Hebei Region Using an Ensemble Learning Model

Nitrogen dioxide (NO2) is an important pollutant related to human activities, which has short-term and long-term effects on human health. An ensemble learning model was constructed and applied to estimate daily NO2 concentrations in the Beijing–Tianjin–Hebei region between 2010 and 2016. A variety of predictive variables included satellite-based troposphere NO2 vertical column concentration, meteorology, elevation, gross domestic product (GDP), population, land-use variables, and road network. The ensemble learning model achieved two things: a 0.01° × 0.01° grid resolution and the estimation of historical data for the years 2010–2013. The ensemble model showed good performance, whereby the R2 of tenfold cross-validation was 0.72 and the R2 of test validation was 0.71. Meteorological hysteretic effects were incorporated into the model, where the one-day lagged boundary layer height contributed the most. The annual NO2 estimation showed little change from 2010 to 2016. The seasonal NO2 estimation from highest to lowest occurred in winter, autumn, spring, and summer. In the annual maps and seasonal maps, the NO2 estimations in the northwest region were lower than those in the southeast region, and there was a heavily polluted band in the south of the Taihang Mountains. In coastal areas, the annual NO2 estimations were higher than the NO2 monitored values. The drawback of the model is underestimation at high values and overestimation at low values. This study indicates that the ensemble learning model has excellent performance in the simulation of NO2 with high spatial and temporal resolution. Furthermore, the research framework in this study can be a generally applied for drawing implications for other regions, especially for other cities in China

Fabrication of Cell-Laden Hydrogel Fibers with Controllable Diameters

Cell-laden hydrogel fibers are widely used as the fundamental building blocks to fabricate more complex functional three-dimensional (3D) structures that could mimic biological tissues. The control on the diameter of the hydrogel fibers is important so as to precisely construct structures in the above 3D bio-fabrication. In this paper, a pneumatic-actuated micro-extrusion system is developed to produce hydrogel fibers based on the crosslinking behavior of sodium alginate with calcium ions. Excellent uniformity has been obtained in the diameters of the fabricated hydrogel fibers as a proportional-integral-derivative (PID) control algorithm is applied on the driving pressure control. More importantly, a linear relationship has been obtained between the diameter of hydrogel fiber and the driving pressure. With the help of the identified linear model, we can precisely control the diameter of the hydrogel fiber via the control of the driving pressure. The differences between the measured and designed diameters are within ±2.5%. Finally, the influence of the calcium ions on the viability of the encapsulated cells is also investigated by immersing the cell-laden hydrogel fibers into the CaCl2 bath for different periods of time. LIVE/DEAD assays show that there is little difference among the cell viabilities in each sample. Therefore, the calcium ions utilized in the fabrication process have no impact on the cells encapsulated in the hydrogel fiber. Experimental results also show that the cell viability is 83 ± 2% for each sample after 24 h of culturing