High Speed Visible Light Communication Using Blue GaN Laser Diodes

GaN-based laser diodes have been developed over the last 20 years making them desirable for many security and defence applications, in particular, free space laser communications. Unlike their LED counterparts, laser diodes are not limited by their carrier lifetime which makes them attractive for high speed communication, whether in free space, through fiber or underwater. Gigabit data transmission can be achieved in free space by modulating the visible light from the laser with a pseudo-random bit sequence (PRBS), with recent results approaching 5 Gbit/s error free data transmission. By exploiting the low-loss in the blue part of the spectrum through water, data transmission experiments have also been conducted to show rates of 2.5 Gbit/s underwater. Different water types have been tested to monitor the effect of scattering and to see how this affects the overall transmission rate and distance. This is of great interest for communication with unmanned underwater vehicles (UUV) as the current method using acoustics is much slower and vulnerable to interception. These types of laser diodes can typically reach 50-100 mW of power which increases the length at which the data can be transmitted. This distance could be further improved by making use of high power laser arrays. Highly uniform GaN substrates with low defectivity allow individually addressable laser bars to be fabricated. This could ultimately increase optical power levels to 4 W for a 20-emitter array. Overall, the development of GaN laser diodes will play an important part in free space optical communications and will be vital in the advancement of security and defence applications

Identifying the Irritability Dimension of ODD: Application of a Modified Bifactor Model Across Five Large Community Samples of Children

The importance of irritability, as measured among the symptoms of oppositional defiant disorder (ODD), has dramatically come to the fore in recent years. New diagnostic categories rely on the distinct clinical utility of irritability, and models of psychopathology suggest it plays a key role in explaining developmental pathways within and between disorders into adulthood. However, only a few studies have tested multidimensional models of ODD, and the results have been conflicting. Further, consensus has not been reached regarding which symptoms best identify irritability. The present analyses use 5 large community data sets with 5 different measures of parent-reported ODD, comprising 16,280 youth in total, to help resolve these questions. Across the samples, ages ranged from 5 to 18, and included both boys and girls. Confirmatory factor analyses demonstrated that a modified bifactor model showed the best fit in each data set. The structure of the model included 2 correlated specific factors (irritability and oppositional behavior) in addition to a general ODD factor. In 4 models, the best fit was obtained using the items “being touchy,” “angry,” and “often losing temper” as indicators of irritability. Given the structure of the models and the generally high correlation between the specific dimensions, the results suggest that irritability may not be sufficiently distinct from oppositional behavior to support an entirely independent diagnosis. Rather, irritability may be better understood as a dimension of psychopathology that can be distinguished within ODD, and which may be related to particular forms of psychopathology apart from ODD

Unified concepts for understanding and modelling turnover of dissolved organic matter from freshwaters to the ocean: the UniDOM model

The transport of dissolved organic matter (DOM) across the land-ocean-aquatic continuum (LOAC), from freshwater to the ocean, is an important yet poorly understood component of the global carbon budget. Exploring and quantifying this flux is a significant challenge given the complexities of DOM cycling across these contrasting environments. We developed a new model, UniDOM, that unifies concepts, state variables and parameterisations of DOM turnover across the LOAC. Terrigenous DOM is divided into two pools, T1 (strongly-UV-absorbing) and T2 (non- or weakly-UV-absorbing), that exhibit contrasting responses to microbial consumption, photooxidation and flocculation. Data are presented to show that these pools are amenable to routine measurement based on specific UV absorbance (SUVA). In addition, an autochtonous DOM pool is defined to account for aquatic DOM production. A novel aspect of UniDOM is that rates of photooxidation and microbial turnover are parameterised as an inverse function of DOM age. Model results, which indicate that ~5% of the DOM originating in streams may penetrate into the open ocean, are sensitive to this parameterisation, as well as rates assigned to turnover of freshly produced DOM. The predicted contribution of flocculation to DOM turnover is remarkably low, although a mechanistic representation of this process in UniDOM was considered unachievable because of the complexities involved. Our work highlights the need for ongoing research into the mechanistic understanding and rates of photooxidation, microbial consumption and flocculation of DOM across the different environments of the LOAC, along with the development of models based on unified concepts and parameterisations

Antibiotic-induced accumulation of lipid II synergizes with antimicrobial fatty acids to eradicate bacterial populations

Antibiotic tolerance and antibiotic resistance are the two major obstacles to the efficient and reliable treatment of bacterial infections. Identifying antibiotic adjuvants that sensitize resistant and tolerant bacteria to antibiotic killing may lead to the development of superior treatments with improved outcomes. Vancomycin, a lipid II inhibitor, is a frontline antibiotic for treating methicillin-resistant Staphylococcus aureus and other Gram-positive bacterial infections. However, vancomycin use has led to the increasing prevalence of bacterial strains with reduced susceptibility to vancomycin. Here, we show that unsaturated fatty acids act as potent vancomycin adjuvants to rapidly kill a range of Gram-positive bacteria, including vancomycin-tolerant and resistant populations. The synergistic bactericidal activity relies on the accumulation of membrane-bound cell wall intermediates that generate large fluid patches in the membrane leading to protein delocalization, aberrant septal formation, and loss of membrane integrity. Our findings provide a natural therapeutic option that enhances vancomycin activity against difficult-to-treat pathogens, and the underlying mechanism may be further exploited to develop antimicrobials that target recalcitrant infection

Age at symptom onset and death and disease duration in genetic frontotemporal dementia : an international retrospective cohort study

Background: Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. Methods: In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. Findings: Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49\ub75 years (SD 10\ub70; onset) and 58\ub75 years (11\ub73; death) in the MAPT group, 58\ub72 years (9\ub78; onset) and 65\ub73 years (10\ub79; death) in the C9orf72 group, and 61\ub73 years (8\ub78; onset) and 68\ub78 years (9\ub77; death) in the GRN group. Mean disease duration was 6\ub74 years (SD 4\ub79) in the C9orf72 group, 7\ub71 years (3\ub79) in the GRN group, and 9\ub73 years (6\ub74) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0\ub745 between individual and parental age at onset, r=0\ub763 between individual and mean family age at onset, r=0\ub758 between individual and parental age at death, and r=0\ub769 between individual and mean family age at death) than in either the C9orf72 group (r=0\ub732 individual and parental age at onset, r=0\ub736 individual and mean family age at onset, r=0\ub738 individual and parental age at death, and r=0\ub740 individual and mean family age at death) or the GRN group (r=0\ub722 individual and parental age at onset, r=0\ub718 individual and mean family age at onset, r=0\ub722 individual and parental age at death, and r=0\ub732 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35\u201362, for age at onset; 61%, 47\u201373, for age at death), and even more by family membership (66%, 56\u201375, for age at onset; 74%, 65\u201382, for age at death). In the GRN group, only 2% (0\u201310) of the variability of age at onset and 9% (3\u201321) of that of age of death was explained by the specific mutation, whereas 14% (9\u201322) of the variability of age at onset and 20% (12\u201330) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11\u201326) of the variability of age at onset and 19% (12\u201329) of that of age at death. Interpretation: Our study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates. Funding: UK Medical Research Council, National Institute for Health Research, and Alzheimer's Society

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

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of SARS-CoV-2 genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three available genomic nomenclature systems for SARS-CoV-2 to all sequence data from the WHO European Region available during the COVID-19 pandemic until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation. We provide a comparison of the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2.Peer reviewe

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