Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Toward Sustainable Environmental Quality : Priority Research Questions for Asia

Environmental and human health challenges are pronounced in Asia, an exceptionally diverse and complex region where influences of global megatrends are extensive and numerous stresses to environmental quality exist. Identifying priorities necessary to engage grand challenges can be facilitated through horizon scanning exercises, and to this end we identified and examined 23 priority research questions needed to advance toward more sustainable environmental quality in Asia, as part of the Global Horizon Scanning Project. Advances in environmental toxicology, environmental chemistry, biological monitoring, and risk-assessment methodologies are necessary to address the adverse impacts of environmental stressors on ecosystem services and biodiversity, with Asia being home to numerous biodiversity hotspots. Intersections of the food–energy–water nexus are profound in Asia; innovative and aggressive technologies are necessary to provide clean water, ensure food safety, and stimulate energy efficiency, while improving ecological integrity and addressing legacy and emerging threats to public health and the environment, particularly with increased aquaculture production. Asia is the largest chemical-producing continent globally. Accordingly, sustainable and green chemistry and engineering present decided opportunities to stimulate innovation and realize a number of the United Nations Sustainable Development Goals. Engaging the priority research questions identified herein will require transdisciplinary coordination through existing and nontraditional partnerships within and among countries and sectors. Answering these questions will not be easy but is necessary to achieve more sustainable environmental quality in Asia. Environ Toxicol Chem 2020;39:1485–1505

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Graphene Nanoplatelet Exoskeleton on Polyurethane Foam to Produce Flame‐Retardant, Piezoresistive, and Electromagnetic Interference Shielding Surfaces

Abstract Polyurethane foam (PUF)’s porous structure, light weight, flexibility, and low‐cost properties make it useful in various cutting‐edge technologies. However, time‐consuming, costly, and complicated surface modification methods severely hinder its commercial applications. Herein, an ultrafast, simple, and cost‐effective surface modification method based on the evaporation of a low boiling point solvent to prepare a multifunctional graphene nanoplatelet (GNP)‐decorated PUF (GNP@PUF) is proposed. Due to the passive heat barrier of GNP sheets, the resulting sponge exhibits excellent flame retardancy by reducing the critical fire retardancy metrics, that is, peak heat release rate, total heat release, and total smoke release by 72%, 50%, and 81%, respectively. In addition, GNP@PUF can function as a piezoresistive sensor and electromagnetic interference (EMI)‐shielding material. As a piezoresistive sensor, it exhibits a wide‐compressive pressure (2.4–112 kPa)/strain (5–70%) range and ultra‐fast response/relaxation time (48/35 ms), wide‐stretching strain (5–100%) range, and it can detect minute human motions by being attached to different parts of the human body. Meanwhile, the composite foam displays good absorption‐dominant EMI shielding performance (≈38 dB), possibly due to conductive dissipation and multiple reflections/scattering of EM waves inside the 3D conductive graphene network. This study provides a simple coating technique for developing multifunctional lightweight foam materials

Chiral aromatase and dual aromatase steroid sulfatase inhibitors from the letrozole template: synthesis, absolute configuration and In vitro activity

To explore aromatase inhibition and to broaden the structural diversity of dual aromatase-sulfatase inhibitors (DASIs), we introduced the steroid sulfatase (STS) inhibitory pharmacophore to letrozole. Letrozole derivatives were prepared bearing bis-sulfamates or mono-sulfamates with or without adjacent substituents. The most potent of the achiral and racemic aromatase inhibitor was 40 (IC50 ) 3.0 nM). Its phenolic precursor 39 was separated by chiral HPLC, and the absolute configuration of each enantiomer was determined using vibrational and electronic circular dichroism in tandem with calculations of the predicted spectra. Of the two enantiomers, (R)-phenol (39a) was the most potent aromatase inhibitor (IC50 ) 0.6 nM, comparable to letrozole), whereas the (S)-sulfamate, (40b) inhibited STS most potently (IC50 ) 553 nM). These results suggest that a new structural class of DASI for potential treatment of hormone-dependent breast cancer has been identified, and this is the first report of STS inhibition by an enantiopure nonsteroidal compound