Microarray missing data imputation based on a set theoretic framework and biological knowledge

Gene expressions measured using microarrays usually suffer from the missing value problem. However, in many data analysis methods, a complete data matrix is required. Although existing missing value imputation algorithms have shown good performance to deal with missing values, they also have their limitations. For example, some algorithms have good performance only when strong local correlation exists in data while some provide the best estimate when data is dominated by global structure. In addition, these algorithms do not take into account any biological constraint in their imputation. In this paper, we propose a set theoretic framework based on projection onto convex sets (POCS) for missing data imputation. POCS allows us to incorporate different types of a priori knowledge about missing values into the estimation process. The main idea of POCS is to formulate every piece of prior knowledge into a corresponding convex set and then use a convergence-guaranteed iterative procedure to obtain a solution in the intersection of all these sets. In this work, we design several convex sets, taking into consideration the biological characteristic of the data: the first set mainly exploit the local correlation structure among genes in microarray data, while the second set captures the global correlation structure among arrays. The third set (actually a series of sets) exploits the biological phenomenon of synchronization loss in microarray experiments. In cyclic systems, synchronization loss is a common phenomenon and we construct a series of sets based on this phenomenon for our POCS imputation algorithm. Experiments show that our algorithm can achieve a significant reduction of error compared to the KNNimpute, SVDimpute and LSimpute methods

Shape Memory and Superelastic Ceramics at Small Scales

Shape memory materials are a class of smart materials able to convert heat into mechanical strain (or strain into heat) by virtue of a martensitic phase transformation. Some brittle materials such as intermetallics and ceramics exhibit a martensitic transformation but fail by cracking at low strains and after only a few applied strain cycles. Here we show that such failure can be suppressed in normally brittle martensitic ceramics by providing a fine-scale structure with few crystal grains. Such oligocrystalline structures reduce internal mismatch stresses during the martensitic transformation and lead to robust shape memory ceramics that are capable of many superelastic cycles up to large strains; here we describe samples cycled as many as 50 times and samples that can withstand strains over 7%. Shape memory ceramics with these properties represent a new class of actuators or smart materials with a set of properties that include high energy output, high energy damping, and high-temperature usage.Project Agreement (9011102294)Project Agreement (9011102296

Statistical Spectral Characteristics of Three-Dimensional Winds in the Mesopause Region Revealed by the Andes Lidar

By analyzing data recorded at the Andes Lidar Observatory in Cerro Pachon, Chile (30.3°S, 70.7°W) from May 2014 to July 2019, we investigated the fundamental features of three-dimensional wind and temperature spectra. The vertical wavenumber spectral amplitudes of horizontal winds show obvious seasonal variations that are closely related to the seasonal variations in the source and background winds. The wavenumber spectral slopes of the horizontal winds are systematically less negative than −3, with mean values of −1.96 and −2.18 for zonal and meridional winds, respectively. The zonal and meridional wind frequency spectra have mean slopes of −1.37 and −1.56, respectively; these values are slightly less negative than −5/3. Moreover, the frequency spectral amplitudes show different seasonal variations from those of the wavenumber spectra, possibly because they correspond to different GW spectral components. The vertical wind has obviously different spectral features than the horizontal winds. The vertical wind spectra are notably shallower than the horizontal wind spectra, with mean slopes of −0.82 and −0.91 for the wavenumber and frequency spectra, respectively, departing evidently from those expected under linear instability theory (LIT). Although the vertical wind spectrum is almost always separable, the horizontal wind spectra are separable only at high frequencies. As the frequency increased, the horizontal wind wavenumber spectra become shallower and depart from the spectral slope expected under LIT, likely because high-frequency GWs are not completely saturated. In general, our results do not support LIT

Synthesis of deuterium‐labelled amlexanox and its metabolic stability against mouse, rat, and human microsomes

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149374/1/jlcr3716_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149374/2/jlcr3716.pd

Modeling the impact of wild harvest on plant-disperser mutualisms: Plant and disperser co-harvest model

Across the tropics, millions of rural families rely on non-timber forest products for protein, subsistence, and other financial or cultural uses. Often, communities exploit biotically dispersed trees and their mammalian or avian seed disperser. Empirical findings have indicated that many plant and animal resources are overexploited, presenting challenges for biodiversity conservation and sustainable rural livelihoods. However, there has been limited research investigating the impacts of harvest that targets both seed dispersers and zoochoric trees. We formulated a discrete-time model for interacting seed dispersers and plants under harvest. We found that the more dependent species will dictate the sustainable threshold level of harvest, and that higher levels of dependence could drive the species pair to local extinction. We illustrated the application of sensitivity analysis to our modeling framework in order to facilitate future analyses and applications using this approach

Preparation of Mouse Monoclonal Antibody for RB1CC1 and Its Clinical Application

RB1-inducible coiled-coil 1 (RB1CC1; also known as FIP200) plays important roles in several biological pathways such as cell proliferation and autophagy. Evaluation of RB1CC1 expression can provide useful clinical information on various cancers and neurodegenerative diseases. In order to realize the clinical applications, it is necessary to establish a stable supply of antibody and reproducible procedures for the laboratory examinations. In the present study, we have generated mouse monoclonal antibodies for RB1CC1, and four kinds of antibodies (N1-8, N1-216, N3-2, and N3-42) were found to be optimal for clinical applications such as ELISA and immunoblots and work as well as the pre-existing polyclonal antibodies. N1-8 monoclonal antibody provided the best recognition of RB1CC1 in the clinico-pathological examination of formalin-fixed paraffin-embedded tissues. These monoclonal antibodies will help to generate new opportunities in scientific examinations in biology and clinical medicine

Genetically Determined Plasma Lipid Levels and Risk of Diabetic Retinopathy: A Mendelian Randomization Study.

Results from observational studies examining dyslipidemia as a risk factor for diabetic retinopathy (DR) have been inconsistent. We evaluated the causal relationship between plasma lipids and DR using a Mendelian randomization approach. We pooled genome-wide association studies summary statistics from 18 studies for two DR phenotypes: any DR (N = 2,969 case and 4,096 control subjects) and severe DR (N = 1,277 case and 3,980 control subjects). Previously identified lipid-associated single nucleotide polymorphisms served as instrumental variables. Meta-analysis to combine the Mendelian randomization estimates from different cohorts was conducted. There was no statistically significant change in odds ratios of having any DR or severe DR for any of the lipid fractions in the primary analysis that used single nucleotide polymorphisms that did not have a pleiotropic effect on another lipid fraction. Similarly, there was no significant association in the Caucasian and Chinese subgroup analyses. This study did not show evidence of a causal role of the four lipid fractions on DR. However, the study had limited power to detect odds ratios less than 1.23 per SD in genetically induced increase in plasma lipid levels, thus we cannot exclude that causal relationships with more modest effect sizes exist