Whole-Brain Evaluation of Cortical Microconnectomes

The brain is an organ that functions as a network of many elements connected in a nonuniform manner. In the brain, the neocortex is evolutionarily newest and is thought to be primarily responsible for the high intelligence of mammals. In the mature mammalian brain, all cortical regions are expected to have some degree of homology, but have some variations of local circuits to achieve specific functions performed by individual regions. However, few cellular-level studies have examined how the networks within different cortical regions differ. This study aimed to find rules for systematic changes of connectivity (microconnectomes) across 16 different cortical region groups. We also observed unknown trends in basic parameters in vitro such as firing rate and layer thickness across brain regions. Results revealed that the frontal group shows unique characteristics such as dense active neurons, thick cortex, and strong connections with deeper layers. This suggests the frontal side of the cortex is inherently capable of driving, even in isolation and that frontal nodes provide the driving force generating a global pattern of spontaneous synchronous activity, such as the default mode network. This finding provides a new hypothesis explaining why disruption in the frontal region causes a large impact on mental health.

Mesoscale Process Modeling of a Thick Pultruded Composite with Variability in Fiber Volume Fraction

Pultruded fiber-reinforced polymer composites are susceptible to microstructural nonuniformity such as variability in fiber volume fraction (Vf), which can have a profound effect on process-induced residual stress. Until now, this effect of non-uniform Vf distribution has been hardly addressed in the process models. In the present study, we characterized the Vf distribution and accompanying nonuniformity in a unidirectional fiber-reinforced pultruded profile using optical light microscopy. The identified nonuniformity in Vf was subsequently implemented in a mesoscale thermal-chemical-mechanical process model, developed explicitly for the pultrusion process. In our process model, the constitutive material behavior was defined locally with respect to the corresponding fiber volume fraction value in different-sized representative volume elements. The effect of nonuniformity on the temperature and cure degree evolution, and residual stress was analyzed in depth. The results show that the nonuniformity in fiber volume fraction across the cross-section increased the absolute magnitude of the predicted residual stress, leading to a more scattered residual stress distribution. The observed Vf gradient promotes tensile residual stress at the core and compressive residual stress at the outer regions. Consequently, it is concluded that it is essential to take the effects of nonuniformity in fiber distribution into account for residual stress estimations, and the proposed numerical framework was found to be an efficient tool to study this aspect.

Modelling RNA-Seq data with a zero-inflated mixture Poisson linear model

RNA sequencing (RNA-Seq) has been frequently used in genomic studies and has generated a vast amount of data. The RNA-Seq data are composed of two parts: (a) a sequence of nucleotides of the genome; and (b) a corresponding sequence of counts, standing for the number of short reads whose mapped positions start at each position of the genome. One common feature of these count data is that they are typically nonuniform; recent studies have revealed that the nonuniformity is partially owing to a systematic bias resulted from the sequencing preference. Existing works in the literature model the nonuniformity with a single component Poisson linear model that incorporates the effects of the sequencing preference. However, we observe consistently that the short reads mapped to a gene may have a mixture structure and can be zero-inflated. A single component model may not suffice to model the complexity of such data. In this paper, we propose a zero-inflated mixture Poisson linear model for the RNA-Seq count data and derive a fast expectation-maximisation-based algorithm for estimating the unknown parameters. Numerical studies are conducted to illustrate the effectiveness of our method.

Nonuniformity in ligaments is a structural strategy for optimizing functionality

Ligaments serve as compliant connectors between hard tissues. In that role, they function under various load regimes and directions. The 3D structure of ligaments is considered to form as a uniform entity that changes due to function. The periodontal ligament (PDL) connects the tooth to the bone and sustains different types of loads in various directions. Using the PDL as a model, employing a fabricated motorized setup in a microCT, we demonstrate that the fibrous network structure within the PDL is not uniform, even before the tooth becomes functional. Utilizing morphological automated segmentation methods, directionality analysis, as well as second harmonic generation imaging, we find high correlation between blood vessel distribution and fiber density. We also show a structural feature in a form of a dense collar around the neck of the tooth as well as a preferred direction of the fibrous network. Finally, we show that the PDL develops as a nonuniform structure, with an architecture designed to sustain specific types of load in designated areas. Based on these findings, we propose that ligaments in general should be regarded as nonuniform entities, structured already at developmental stages for optimal functioning under variable load regimes.

Robust Approach for Nonuniformity Correction in Infrared Focal Plane Array

In this paper, we propose a new scene-based nonuniformity correction technique for infrared focal plane arrays. Our work is based on the use of two well-known scene-based methods, namely, adaptive and interframe registration-based exploiting pure translation motion model between frames. The two approaches have their benefits and drawbacks, which make them extremely effective in certain conditions and not adapted for others. Following on that, we developed a method robust to various conditions, which may slow or affect the correction process by elaborating a decision criterion that adapts the process to the most effective technique to ensure fast and reliable correction. In addition to that, problems such as bad pixels and ghosting artifacts are also dealt with to enhance the overall quality of the correction. The performance of the proposed technique is investigated and compared to the two state-of-the-art techniques cited above.

Hot regions of noninterfering crossovers coexist with a nonuniformly interfering pathway in Arabidopsis thaliana

In most organisms that have been studied, crossovers formed during meiosis exhibit interference: nearby crossovers are rare. Here we provide an in-depth study of crossover interference in Arabidopsis thaliana, examining crossovers genome-wide in >1500 backcrosses for both male and female meiosis. This unique data set allows us to take a two-pathway modeling approach based on superposing a fraction p of noninterfering crossovers and a fraction (1 - p) of interfering crossovers generated using the gamma model characterized by its interference strength nu. Within this framework, we fit the two-pathway model to the data and compare crossover interference strength between chromosomes and then along chromosomes. We find that the interfering pathway has markedly higher interference strength nu in female than in male meiosis and also that male meiosis has a higher proportion p of noninterfering crossovers. Furthermore, we test for possible intrachromosomal variations of nu and p. Our conclusion is that there are clear differences between left and right arms as well as between central and peripheral regions. Finally, statistical tests unveil a genome-wide picture of small-scale heterogeneities, pointing to the existence of hot regions in the genome where crossovers form preferentially without interference.