Structure and Function of the ABCD1 Variant Database: 20 Years, 940 Pathogenic Variants, and 3400 Cases of Adrenoleukodystrophy

The progressive neurometabolic disorder X-linked adrenoleukodystrophy (ALD) is caused by pathogenic variants in the ABCD1 gene, which encodes the peroxisomal ATP-binding transporter for very-long-chain fatty acids. The clinical spectrum of ALD includes adrenal insufficiency, myelopathy, and/or leukodystrophy. A complicating factor in disease management is the absence of a genotype–phenotype correlation in ALD. Since 1999, most ABCD1 (likely) pathogenic and benign variants have been reported in the ABCD1 Variant Database. In 2017, following the expansion of ALD newborn screening, the database was rebuilt. To add an additional level of confidence with respect to pathogenicity, for each variant, it now also reports the number of cases identified and, where available, experimental data supporting the pathogenicity of the variant. The website also provides information on a number of ALD-related topics in several languages. Here, we provide an updated analysis of the known variants in ABCD1. The order of pathogenic variant frequency, overall clustering of disease-causing variants in exons 1–2 (transmembrane domain spanning region) and 6–9 (ATP-binding domain), and the most commonly reported pathogenic variant p.Gln472Argfs*83 in exon 5 are consistent with the initial reports of the mutation database. Novel insights include nonrandom clustering of high-density missense variant hotspots within exons 1, 2, 6, 8, and 9. Perhaps more importantly, we illustrate the importance of collaboration and utility of the database as a scientific, clinical, and ALD-community-wide resource.

Molecular and Clinical Implications of Variant Repeats in Myotonic Dystrophy Type 1

Myotonic dystrophy type 1 (DM1) is one of the most variable monogenic diseases at phenotypic, genetic, and epigenetic level. The disease is multi-systemic with the age at onset ranging from birth to late age. The underlying mutation is an unstable expansion of CTG repeats in the DMPK gene, varying in size from 50 to >1000 repeats. Generally, large expansions are associated with an earlier age at onset. Additionally, the most severe, congenital DM1 form is typically associated with local DNA methylation. Genetic variability of DM1 mutation is further increased by its structural variations due to presence of other repeats (e.g., CCG, CTC, CAG). These variant repeats or repeat interruptions seem to confer an additional level of epigenetic variability since local DNA methylation is frequently associated with variant CCG repeats independently of the expansion size. The effect of repeat interruptions on DM1 molecular pathogenesis is not investigated enough. Studies on patients indicate their stabilizing effect on DMPK expansions because no congenital cases were described in patients with repeat interruptions, and the age at onset is frequently later than expected. Here, we review the clinical relevance of repeat interruptions in DM1 and genetic and epigenetic characteristics of interrupted DMPK expansions based on patient studies.

Balanced Leadership Case Study

This case study discusses the application of balanced leadership in Transport for New South Wales in Australia (Transport). It reports on three aspects of balanced leadership in Transport: how decisions are made regarding projects and programs; how leadership shifts between the vertical leader (project or program manager) and horizontal leader (subject matter experts in teams); and elements of socio-cognitive space that support the transition between vertical and horizontal leadership. The predominant methodology used to deliver programs in Transport was found to be agile, and all the programs delivered from the unit where the interviewees were located were aimed at supporting the creation of value from big data. The unit managing programs in this organization was not fully involved in implementing projects in the programs, creating an additional level of leadership where some tasks were also undertaken by project team members in a vendor’s organization.

Hybrid Optimization-Based Robust Watermarking Using Denoising Convolutional Neural Network

Colour images have been widely used in many aspects of life; however, copyright violation issues related to these images motivate research efforts. This paper aims to develop an enhanced watermarking algorithm for producing a watermarked image using hybrid optimisation with high imperceptibility and robustness. The algorithm is based on spatial and transform domains and begins by embedding multiple secret marks into cover media using an optimal scaling factor. The multi-type mark contributes an additional level of authenticity to the proposed algorithm. Furthermore, the marked image is encrypted using an improved encryption scheme, and the denoising convolutional neural network (DnCNN) is employed to enhance the robustness of the proposed algorithm. The results reveal that the proposed watermarking algorithm yields low computational overhead, excellent watermark capacity, imperceptibility, and robustness to common filtering attacks. Moreover, the comparison shows that the proposed algorithm outperforms other competing methods.

Colliding Identities During COVID-19: Identifying and Addressing the Challenges of Being an Academic Mother During a Global Pandemic

Academic workloads require a careful balance of teaching, research, supervision, and administrative responsibilities. Being an academic parent adds an additional level of responsibility to this, which has traditionally been successfully managed with organisation, careful planning and support. For many academic parents the Covid-19 pandemic disrupted this carefully curated balance, forcing them to work from home while also dealing with the loss of childcare and the requirement to provide homeschooling. The pre-existing gender disparity in childcare and housework was exacerbated by lockdown, with a disproportionate impact on academic mothers who were often forced to take on additional childcare and housework responsibilities, alongside remote schooling. The gender disparity further affected job stability, with women losing a greater number of paid working hours during the pandemic and having greater employment instability. This article reflects upon the impact of gender disparity in academic parents during the Covid-19 pandemic, and considers potential barriers to productivity and progression, including the role of interruptions, delivering sensitive materials in a workspace shared with children and technological challenges.

Determinants of Household Energy Choice for Cooking in Northern Sudan: A Multinomial Logit Estimation

Traditional biomass utilization is connected with negative environmental and human health impacts. However, its transition to cleaner cooking fuels is still low where the household’s fuels preferences play an important role in the process. To examine the factors that influence the household’s cooking fuel choice in Northern Sudan, a multinomial logit model (MNL) was used to analyze data collected from Kassala state in two selected districts, New Halfa and Nahr Atabara. The findings show that the most utilized fuels are still firewood and charcoal, which are used by 63.4% of all respondents. The results also revealed that socioeconomic factors have an impact on household fuel choice, where one additional unit of credit access may boost the possibility of choosing LPG by 22.7%. Furthermore, one additional level of education would reduce 5.4% of charcoal users while simultaneously raising 10% of current liquefied petroleum gas (LPG) users. Therefore, the study suggests initiating mobilization and training programs to raise awareness and encourage the usage of cleaner fuels. This study will provide policymakers with information on household cooking energy utilization while designing and developing policies related to energy. It will also contribute to the expanding body of literature concerning the transition to clean cooking fuels from traditional biomass.

Strain-Specific Liver Metabolite Profiles in Medaka

The relationship between genetic variation and phenotypic traits is often poorly understood since specific genotypes do not always easily translate into associated phenotypes, especially for complex disorders. The genetic background has been shown to affect metabolic pathways and thus contribute to variations in the metabolome. Here, we tested the suitability of NMR metabolomics for comparative analysis of fish lines as a first step towards phenotype-genotype association studies. The Japanese rice fish, medaka (Oryzias latipes), is a widely used genetic vertebrate model with several isogenic inbred laboratory strains. We used liver extracts of medaka iCab and HO5 strains as a paradigm to test the feasibility of distinguishing the metabolome of two different inbred strains. Fifteen metabolites could be detected in uni- and multivariate analyses that showed strain-specific levels. Differences could be assigned to specific metabolic pathways. Our results show that NMR spectroscopy is a suitable method to detect variance of the metabolome caused by subtle genetic differences. Thus, it has the potential to address genotype–phenotype associations in medaka, providing an additional level of phenotypic analysis.

Region-aggregated attention CNN for disease detection in fruit images

Background Diseases and pests have a profound effect on a yearly harvest and productivity in agriculture. A precise and accurate detection of the diseases and pests could facilitate timely treatment and management of the diseases and pests and lessen the resultant loss in economy and health. Herein, we propose an improved design of the disease detection system for plant images. Methods Built upon the two-stage framework of object detection neural networks such as Mask R-CNN, the proposed network involves three types of extensions, including the addition of additional level of feature pyramids to improve the exploration and proposal of candidate regions, the aggregation of feature maps from all levels of feature pyramids per candidate region to fully exploit the information from feature pyramids, and the introduction of a squeeze-and-excitation block to the construction of feature pyramids and the aggregated feature maps to improve the representation of feature maps. Results The proposed network was evaluated using 74 images of infected apple fruits. In 3-fold cross-validation, the proposed network achieved averaged precision (AP) of 72.26, AP at 0.5 threshold of 88.51 and AP at 0.75 threshold of 82.30. In the comparative experiments, the proposed network outperformed the other competing networks. The utility of the three extensions was also demonstrated in comparison to Mask R-CNN. Conclusions The experimental results suggest that the proposed network could identify and localize the symptom of the disease with high accuracy, leading to an early diagnosis and treatment of the disease, and thus holding the potential for improving crop yield and quality.

Is Sentinel Lymph Node Biopsy for Breast Cancer with Cytology-Proven Axillary Metastasis Safe? A Prospective Single-Arm Study

The purpose of this study was to evaluate pathologic lymph node metastasis in breast cancer with cytology-proven axillary metastasis. This study was designed prospectively. We performed axillary lymph node dissections (ALND) after lymphatic mapping by near-infrared (NIR) fluorescence imaging with Indocyanine Green (ICG). We evaluated 72 breast cancer patients with cytology-proven axillary metastasis by curative surgery at the Samsung Medical Center between May of 2016 and December of 2017. Among the 72 patients with cytology-proven axillary metastasis, 14 of 39 patients (35.9%) with one or two sentinel lymph nodes containing metastases were metastasized to post-sentinel lymph node. Thirteen of fourteen patients had additional non-sentinel lymph node metastases, seven of thirteen patients also had additional level II lymph node metastases, and one patient had only one additional level II lymph node metastasis. Of T1 or T2 stage patients, 10 of 33 patients (30.3%) with one or two sentinel lymph nodes containing metastases were metastasized to post-sentinel lymph node. Even in patients without SLN metastasis, 50% of the patients had at least three LN metastases, and 40% in the T1 or T2 stage patients. Sentinel lymph node biopsy without ALND might be not safe for patients with cytology-proven axillary metastasis.