Responsible Genes for Neuronal Migration in the Chromosome 17p13.3: Beyond Pafah1b1(Lis1), Crk and Ywhae(14-3-3ε)

The 17p13.3 chromosome region is often deleted or duplicated in humans, resulting in severe neurodevelopmental disorders such as Miller–Dieker syndrome (MDS) and 17p13.3 duplication syndrome. Lissencephaly can also be caused by gene mutations or deletions of a small piece of the 17p13.3 region, including a single gene or a few genes. PAFAH1B1 gene, coding for LIS1 protein, is a responsible gene for lissencephaly and MDS and regulates neuronal migration by controlling microtubules (MTs) and cargo transport along MTs via dynein. CRK is a downstream regulator of the reelin signaling pathways and regulates neuronal migration. YWHAE, coding for 14-3-3ε, is also responsible for MDS and regulates neuronal migration by binding to LIS1-interacting protein, NDEL1. Although these three proteins are known to be responsible for neuronal migration defects in MDS, there are 23 other genes in the MDS critical region on chromosome 17p13.3, and little is known about their functions in neurodevelopment, especially in neuronal migration. This review will summarize the recent progress on the functions of LIS1, CRK, and 14-3-3ε and describe the recent findings of other molecules in the MDS critical regions in neuronal migration.

Haplotype-resolved inversion landscape reveals hotspots of mutational recurrence associated with genomic disorders

Unlike copy number variants (CNVs), inversions remain an underexplored genetic variation class. By integrating multiple genomic technologies, we discover 729 inversions in 41 human genomes. Approximately 85% of inversions <2 kbp form by twin-priming during L1-retrotransposition; 80% of the larger inversions are balanced and affect twice as many base pairs as CNVs. Balanced inversions show an excess of common variants, and 72% are flanked by segmental duplications (SDs) or mobile elements. Since this suggests recurrence due to non-allelic homologous recombination, we developed complementary approaches to identify recurrent inversion formation. We describe 40 recurrent inversions encompassing 0.6% of the genome, showing inversion rates up to 2.7*10-4 per locus and generation. Recurrent inversions exhibit a sex-chromosomal bias, and significantly co-localize to the critical regions of genomic disorders. We propose that inversion recurrence results in an elevated number of heterozygous carriers and structural SD diversity, which increases mutability in the population and predisposes to disease-causing CNVs.

Adversarial Attack for Uncertainty Estimation: Identifying Critical Regions in Neural Networks

We propose a novel method to capture data points near decision boundary in neural network that are often referred to a specific type of uncertainty. In our approach, we sought to perform uncertainty estimation based on the idea of adversarial attack method. In this paper, uncertainty estimates are derived from the input perturbations, unlike previous studies that provide perturbations on the model's parameters as in Bayesian approach. We are able to produce uncertainty with couple of perturbations on the inputs. Interestingly, we apply the proposed method to datasets derived from blockchain. We compare the performance of model uncertainty with the most recent uncertainty methods. We show that the proposed method has revealed a significant outperformance over other methods and provided less risk to capture model uncertainty in machine learning.

Numerical Study to Assess the Structural Behavior of the Bajrakli Mosque (Western Kosovo)

Cultural heritage is one of most significant concerns in modern societies carrying different social and historical values. Among the stock of cultural heritage, historical monuments are one of the greatest contributors to the values in many aspects. Due to several factors, such structures have gone through changes causing structural deficiencies. The aim of this study is to provide a clear insight of the cause and impacts of structural deficiencies through visual inspections and computational methods. As a representative model, Bajrakli Mosque located in western of Kosovo is selected as a case study. During visual inspections, some cracks are found along the structural elements of the mosque. A possible cause of the structural cracks may be the stress concentration through the regions of the structure. In order to provide a better understanding, two different loadings are considered to examine the structural behavior of the mosque. The first loading covers the analysis due to gravity loads, whereas the second one defines the dynamic loading due to ground shakings defined by the earthquake spectrum using finite element analysis in SAP2000. By means of these analyses, the performance of the building is examined. As a result, important data are obtained for identifying the critical regions of the structure. The maximum displacement of the structure is found to be 7.1 mm and 8.0 mm in combination of self-weight and earthquake load in X and Y direction, respectively. Moreover, the regions showing highest values of stress concentration are found through the small domes, through the openings of main dome and connections with arches, and around the openings of the walls.

Using CFD modelling to study hydraulic flow over labyrinth weirs

Compound labyrinth weir is a new type of labyrinth weirs that consider a good applicable choice for increasing the capacity of discharge. The flow over a compound labyrinth weirs is a complex problem because the flow behavior is three-dimension. The present study aims to simulate the flow over the compound labyrinth weir into the critical regions that can not be observed when using an experimental test. The computational fluid dynamics (CFD) programme was utilised to implement a sensitive analysis for this purpose and different flow conditions. The MAPE and RMSE indices were utilised to verify the CFD results with experimental work. The statistics indices of the maximum error ME, RMSE and MAPE were 4.7%, 0.033 and 3.9 respectively. Therefore, the findings showed that there is a good matching between the experimental and CFD results. The CFD results demonstrated that the hydraulics behaviour of the compound labyrinth weir was similar to the oblique and linear weirs in high discharges. The results also confirmed that air cavities and bubbles existed behind the nappe flow in addition to the negative pressure that may occur beneath the nappe when the flow is aerated. Furthermore, the flow was divided into two parts and most streamlines were concentrated over the notches. Moreover, the flow velocity passing through the notches was bigger than the flow velocity over the high crest of the compound labyrinth weir.

Two-Branch Attention Learning for Fine-Grained Class Incremental Learning

As a long-standing research area, class incremental learning (CIL) aims to effectively learn a unified classifier along with the growth of the number of classes. Due to the small inter-class variances and large intra-class variances, fine-grained visual categorization (FGVC) as a challenging visual task has not attracted enough attention in CIL. Therefore, the localization of critical regions specialized for fine-grained object recognition plays a crucial role in FGVC. Additionally, it is important to learn fine-grained features from critical regions in fine-grained CIL for the recognition of new object classes. This paper designs a network architecture named two-branch attention learning network (TBAL-Net) for fine-grained CIL. TBAL-Net can localize critical regions and learn fine-grained feature representation by a lightweight attention module. An effective training framework is proposed for fine-grained CIL by integrating TBAL-Net into an effective CIL process. This framework is tested on three popular fine-grained object datasets, including CUB-200-2011, FGVC-Aircraft, and Stanford-Car. The comparative experimental results demonstrate that the proposed framework can achieve the state-of-the-art performance on the three fine-grained object datasets.

Network-driven anomalous transport is a fundamental component of brain microvascular dysfunction

Blood microcirculation supplies neurons with oxygen and nutrients, and contributes to clearing their neurotoxic waste, through a dense capillary network connected to larger tree-like vessels. This complex microvascular architecture results in highly heterogeneous blood flow and travel time distributions, whose origin and consequences on brain pathophysiology are poorly understood. Here, we analyze highly-resolved intracortical blood flow and transport simulations to establish the physical laws governing the macroscopic transport properties in the brain micro-circulation. We show that network-driven anomalous transport leads to the emergence of critical regions, whether hypoxic or with high concentrations of amyloid-β, a waste product centrally involved in Alzheimer’s Disease. We develop a Continuous-Time Random Walk theory capturing these dynamics and predicting that such critical regions appear much earlier than anticipated by current empirical models under mild hypoperfusion. These findings provide a framework for understanding and modelling the impact of microvascular dysfunction in brain diseases, including Alzheimer’s Disease.

Modeling the marine chromium cycle: new constraints on global-scale processes

Chromium (Cr) and its isotopes hold great promise as a tracer of past oxygenation and marine biological activity due to the contrasted chemical properties of its two main oxidation states, Cr(III) and Cr(VI), and the associated isotope fractionation during redox transformations. However, to date the marine Cr cycle remains poorly constrained due to insufficient knowledge about sources and sinks and the influence of biological activity on redox reactions. We therefore implemented the two oxidation states of Cr in the Bern3D Earth system model of intermediate complexity in order to gain an improved understanding on the mechanisms that modulate the spatial distribution of Cr in the ocean. Due to the computational efficiency of the Bern3D model we are able to explore and constrain the range of a wide array of parameters. Our model simulates vertical, meridional, and inter-basin Cr concentration gradients in good agreement with observations. We find a mean ocean residence time of Cr between 5 and 8 kyr and a benthic flux, emanating from sediment surfaces, of 0.1–0.2 nmol cm−2 yr−1, both in the range of previous estimates. We further explore the origin of regional model–data mismatches through a number of sensitivity experiments. These indicate that the benthic Cr flux may be substantially lower in the Arctic than elsewhere. In addition, we find that a refined representation of oxygen minimum zones and their potential to reduce Cr yield Cr(III) concentrations and Cr removal rates in these regions in much improved agreement with observational data. Yet, further research is required to better understand the processes that govern these critical regions for Cr cycling.