Quantile regression in partially linear varying coefficient models

Semiparametric models are often considered for analyzing longitudinal data for a good balance between flexibility and parsimony. In this paper, we study a class of marginal partially linear quantile models with possibly varying coefficients. The functional coefficients are estimated by basis function approximations. The estimation procedure is easy to implement, and it requires no specification of the error distributions. The asymptotic properties of the proposed estimators are established for the varying coefficients as well as for the constant coefficients. We develop rank score tests for hypotheses on the coefficients, including the hypotheses on the constancy of a subset of the varying coefficients. Hypothesis testing of this type is theoretically challenging, as the dimensions of the parameter spaces under both the null and the alternative hypotheses are growing with the sample size. We assess the finite sample performance of the proposed method by Monte Carlo simulation studies, and demonstrate its value by the analysis of an AIDS data set, where the modeling of quantiles provides more comprehensive information than the usual least squares approach.Comment: Published in at http://dx.doi.org/10.1214/09-AOS695 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

LiDAR-Guided Cross-Attention Fusion for Hyperspectral Band Selection and Image Classification

The fusion of hyperspectral and light detection and range (LiDAR) data has been an active research topic. Existing fusion methods have ignored the high-dimensionality and redundancy challenges in hyperspectral images (HSIs), despite that band selection methods have been intensively studied for HSI processing. This article addresses this significant gap by introducing a cross-attention mechanism from the transformer architecture for the selection of HSI bands guided by LiDAR data. LiDAR provides high-resolution vertical structural information, which can be useful in distinguishing different types of land cover that may have similar spectral signatures but different structural profiles. In our approach, the LiDAR data are used as the “query” to search and identify the “key” from the HSI to choose the most pertinent bands for LiDAR. This method ensures that the selected HSI bands drastically reduce redundancy and computational requirements while working optimally with the LiDAR data. Extensive experiments have been undertaken on three paired HSI and LiDAR datasets: Houston 2013, Trento, and MUUFL. The results highlight the superiority of the cross-attention mechanism, underlining the enhanced classification accuracy of the identified HSI bands when fused with the LiDAR features. The results also show that the use of fewer bands combined with LiDAR surpasses the performance of state-of-the-art fusion models

Identification of H3K4me1-associated proteins at mammalian enhancers.

Enhancers act to regulate cell-type-specific gene expression by facilitating the transcription of target genes. In mammalian cells, active or primed enhancers are commonly marked by monomethylation of histone H3 at lysine 4 (H3K4me1) in a cell-type-specific manner. Whether and how this histone modification regulates enhancer-dependent transcription programs in mammals is unclear. In this study, we conducted SILAC mass spectrometry experiments with mononucleosomes and identified multiple H3K4me1-associated proteins, including many involved in chromatin remodeling. We demonstrate that H3K4me1 augments association of the chromatin-remodeling complex BAF to enhancers in vivo and that, in vitro, H3K4me1-marked nucleosomes are more efficiently remodeled by the BAF complex. Crystal structures of the BAF component BAF45C indicate that monomethylation, but not trimethylation, is accommodated by BAF45C's H3K4-binding site. Our results suggest that H3K4me1 has an active role at enhancers by facilitating binding of the BAF complex and possibly other chromatin regulators

Micromachined Electrodes for High Density Neural Stimulation Systems

Abstract-High-resolution retinal prosthetic systems require high-density stimulation electrodes to restore the vision of blind patients suffering from retinitis pigmentosa and macular degeneration. Micromachining the surface of electrodes to obtain high aspect ratio features can tremendously increase the effective area of the electrode. A unique process has been developed to obtain high aspect ratio structures by plating on the sidewall of recently developed and insufficiently rinsed resist. A quadrupling of the effective area of the electrode surface has been achieved with modest micromachining and should translate into a similar improvement in visual resolution

A Multi-Scale Approach to Study Biochemical and Biophysical Aspects of Resveratrol on Diesel Exhaust Particle-Human Primary Lung Cell Interaction

Diesel exhaust particles (DEPs) are major air pollutants that lead to numerous human disorders, especially pulmonary diseases, partly through the induction of oxidative stress. Resveratrol is a polyphenol that ameliorates the production of reactive oxygen species (ROS) and delays aging-related processes. Herein we studied the cytoprotective effect of resveratrol on DEP-exposed human lung cells in a factorial experimental design. This work investigates biophysical features including cellular compositions and biomechanical properties, which were measured at the single-cell level using confocal Raman microspectroscopy (RM) and atomic force microscopy (AFM), respectively. Principal component analysis (PCA), hierarchical cluster analysis (HCA) and partial least square regression (PLS) analysis were applied to analyze Raman spectra with and without resveratrol protection. The health status of individual cells could be effectively predicted using an index derived from characteristic Raman spectral peak (e.g., 1006 cm−1) based on PLS model. AFM measurements indicated that cellular adhesion force was greatly reduced, while Young’s modulus was highly elevated in resveratrol treated DEP-exposed cells. Anti-oxidant resveratrol reduced DEP-induced ROS production and suppressed releases of several cytokines and chemokines. These findings suggest resveratrol may enhance resistance of human lung cells (e.g., SAEC) to air pollutants (e.g. DEPs)

Adaptive restraint design for a diverse population through machine learning

ObjectiveUsing population-based simulations and machine-learning algorithms to develop an adaptive restraint system that accounts for occupant anthropometry variations to further enhance safety balance throughout the whole population.MethodsTwo thousand MADYMO full frontal impact crash simulations at 35 mph using two validated vehicle/restraint models representing a sedan and an SUV along with a parametric occupant model were conducted based on the maximal projection design of experiments, which considers varying occupant covariates (sex, stature, and body mass index) and vehicle restraint design variables (three for airbag, three for safety belt, and one for knee bolster). A Gaussian-process-based surrogate model was trained to rapidly predict occupant injury risks and the associated uncertainties. An optimization framework was formulated to seek the optimal adaptive restraint design policy that minimizes the population injury risk across a wide range of occupant sizes and shapes while maintaining a low difference in injury risks among different occupant subgroups. The effectiveness of the proposed method was tested by comparing the population-wise injury risks under the adaptive design policy and the traditional state-of-the-art design.ResultsCompared to the traditional state-of-the-art design for midsize males, the optimal design policy shows the potential to further reduce the joint injury risk (combining head, chest, and lower extremity injury risks) among the whole population in the sedan and SUV models. Specifically, the two subgroups of vulnerable occupants including tall obese males and short obese females had higher reductions in injury risks.ConclusionsThis study lays out a method to adaptively adjust vehicle restraint systems to improve safety balance. This is the first study where population-based crash simulations and machine-learning methods are used to optimize adaptive restraint designs for a diverse population. Nevertheless, this study shows the high injury risks associated with obese and female occupants, which can be mitigated via restraint adaptability

Revisiting Modes of energy generation in sulfate reducing bacteria

Sulfate reducing bacteria (SRB) play an important role in global sulfur and carbon cycling through their ability to completely mineralize organic matter while respiring sulfate to hydrogen sulfide. They are ubiquitous in anaerobic environments and have the ability to reduce toxic metals like Cr(VI) and U(VI). While SRB have been studied for over three decades, bioenergetic modes of this group of microbes are poorly understood. Desulfovibrio vulgaris strain Hildenborough (DvH) has served as a model SRB over the last decade with the accumulation of transcriptomic, proteomic and metabolic data under a wide variety of stressors. To further investigate the three hypothesized modes of energy generation in this anaerobe we conducted a systematic study involving multiple electron donor and acceptor combinations for growth. DvH was grown at 37oC in a defined medium with (a) lactate + thiosulfate, (b) lactate + sulfite (c) lactate + sulfate, (d) pyruvate + sulfate, (e) H2 + acetate + sulfate, (f) formate + acetate + sulfate, g) formate + sulfate and (h) pyruvate fermentation. Cells were harvested at mid-log phase of growth for all conditions for transcriptomics, when the optical density at 600nm was in the range 0.42-0.5. Initial results indicate that cells grown on lactate do not appear to significantly differentiate their gene expression profiles when presented with different electron acceptors. These profiles however differ significantly from those observed during growth with other electron donors such as H2 and formate, as well as during fermentative growth. Together the gene expression changes in the presence of different electron donors provide insights into the ability of DvH to differentially reduce metals such as Cr(VI). Here we present revised modes of energy generation in DvH in light of this new transcriptomic evidence

Tumor and serum DNA methylation in women receiving preoperative chemotherapy with or without vorinostat in TBCRC008

BACKGROUND: Methylated gene markers have shown promise in predicting breast cancer outcomes and treatment response. We evaluated whether baseline and changes in tissue and serum methylation levels would predict pathological complete response (pCR) in patients with HER2-negative early breast cancer undergoing preoperative chemotherapy. METHODS: The TBCRC008 trial investigated pCR following 12 weeks of preoperative carboplatin and albumin-bound paclitaxel + vorinostat/placebo (n = 62). We measured methylation of a 10-gene panel by quantitative multiplex methylation-specific polymerase chain reaction and expressed results as cumulative methylation index (CMI). We evaluated association between CMI level [baseline, day 15 (D15), and change] and pCR using univariate and multivariable logistic regression models controlling for treatment and hormone receptor (HR) status, and performed exploratory subgroup analyses. RESULTS: In univariate analysis, one log unit increase in tissue CMI levels at D15 was associated with 40% lower chance of obtaining pCR (odds ratio, OR 0.60, 95% CI 0.37-0.97; p = 0.037). Subgroup analyses suggested a significant association between tissue D15 CMI levels and pCR in vorinostat-treated [OR 0.44 (0.20, 0.93), p = 0.03], but not placebo-treated patients. CONCLUSION: In this study investigating the predictive roles of tissue and serum CMI levels in patients with early breast cancer for the first time, we demonstrate that high D15 tissue CMI levels may predict poor response. Larger studies and improved analytical procedures to detect methylated gene markers in early stage breast cancer are needed. TBCRC008 is registered on ClinicalTrials.gov (NCT00616967)

Occupational Exposure to Aerosolized Brevetoxins during Florida Red Tide Events: Effects on a Healthy Worker Population

Karenia brevis (formerly Gymnodinium breve) is a marine dinoflagellate responsible for red tides that form in the Gulf of Mexico. K. brevis produces brevetoxins, the potent toxins that cause neurotoxic shellfish poisoning. There is also limited information describing human health effects from environmental exposures to brevetoxins. Our objective was to examine the impact of inhaling aerosolized brevetoxins during red tide events on self-reported symptoms and pulmonary function. We recruited a group of 28 healthy lifeguards who are occupationally exposed to red tide toxins during their daily work-related activities. They performed spirometry tests and reported symptoms before and after their 8-hr shifts during a time when there was no red tide (unexposed period) and again when there was a red tide (exposed period). We also examined how mild exercise affected the reported symptoms and spirometry tests during unexposed and exposed periods with a subgroup of the same lifeguards. Environmental sampling (K. brevis cell concentrations in seawater and brevetoxin concentrations in seawater and air) was used to confirm unexposed/exposed status. Compared with unexposed periods, the group of lifeguards reported more upper respiratory symptoms during the exposed periods. We did not observe any impact of exposure to aerosolized brevetoxins, with or without mild exercise, on pulmonary function