Clouds, shadows, or twilight? Mayfly nymphs recognise the difference

1. We examined the relative changes in light intensity that initiate night-time locomotor activity changes in nymphs of the mayfly, Stenonema modestum (Heptageniidae). Tests were carried out in a laboratory stream to examine the hypothesis that nymphs increase their locomotion in response to the large and sustained reductions in relative light intensity that take place during twilight but not to short-term daytime light fluctuations or a minimum light intensity threshold. Ambient light intensity was reduced over a range of values representative of evening twilight. Light was reduced over the same range of intensities either continuously or in discrete intervals while at the same time nymph activity on unglazed tile substrata was video recorded. 2. Nymphs increased their locomotor activity during darkness in response to large, sustained relative light decreases, but not in response to short-term, interrupted periods of light decrease. Nymphs did not recognise darkness unless an adequate light stimulus, such as large and sustained relative decrease in light intensity, had taken place. 3. We show that nymphs perceive light change over time and respond only after a lengthy period of accumulation of light stimulus. The response is much lengthier than reported for other aquatic organisms and is highly adaptive to heterogeneous stream environments

Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Compound heterozygous variants in NBAS as a cause of atypical osteogenesis imperfecta

Background Osteogenesis imperfecta (OI), the commonest inherited bone fragility disorder, affects 1 in 15,000 live births resulting in frequent fractures and reduced mobility, with significant impact on quality of life. Early diagnosis is important, as therapeutic advances can lead to improved clinical outcome and patient benefit. Report Whole exome sequencing in patients with OI identified, in two patients with a multi-system phenotype, compound heterozygous variants in NBAS (neuroblastoma amplified sequence). Patient 1: NBAS c.5741G > A p.(Arg1914His); c.3010C > T p.(Arg1004*) in a 10-year old boy with significant short stature, bone fragility requiring treatment with bisphosphonates, developmental delay and immunodeficiency. Patient 2: NBAS c.5741G > A p.(Arg1914His); c.2032C > T p.(Gln678*) in a 5-year old boy with similar presenting features, bone fragility, mild developmental delay, abnormal liver function tests and immunodeficiency. Discussion Homozygous missense NBAS variants cause SOPH syndrome (short stature; optic atrophy; Pelger-Huet anomaly), the same missense variant was found in our patients on one allele and a nonsense variant in the other allele. Recent literature suggests a multi-system phenotype. In this study, patient fibroblasts have shown reduced collagen expression, compared to control cells and RNAseq studies, in bone cells show that NBAS is expressed in osteoblasts and osteocytes of rodents and primates. These findings provide proof-of-concept that NBAS mutations have mechanistic effects in bone, and that NBAS variants are a novel cause of bone fragility, which is distinguishable from ‘Classical’ OI. Conclusions Here we report on variants in NBAS, as a cause of bone fragility in humans, and expand the phenotypic spectrum associated with NBAS. We explore the mechanism underlying NBAS and the striking skeletal phenotype in our patients

A deep dive into the ecology of Gamay (Botany Bay, Australia): current knowledge and future priorities for this highly modified coastal waterway

Context: Gamay is a coastal waterway of immense social, cultural and ecological value. Since European settlement, it has become a hub for industrialisation and human modification. There is growing desire for ecosystem-level management of urban waterways, but such efforts are often challenged by a lack of integrated knowledge. Aim and methods: We systematically reviewed published literature and traditional ecological knowledge (TEK), and consulted scientists to produce a review of Gamay that synthesises published knowledge of Gamay’s aquatic ecosystem to identify knowledge gaps and future research opportunities. Key results: We found 577 published resources on Gamay, of which over 70% focused on ecology. Intertidal rocky shores were the most studied habitat, focusing on invertebrate communities. Few studies considered multiple habitats or taxa. Studies investigating cumulative human impacts, long-term trends and habitat connectivity are lacking, and the broader ecological role of artificial substrate as habitat in Gamay is poorly understood. TEK of Gamay remains a significant knowledge gap. Habitat restoration has shown promising results and could provide opportunities to improve affected habitats in the future. Conclusion and implications: This review highlights the extensive amount of knowledge that exists for Gamay, but also identifies key gaps that need to be filled for effective management

A function-based typology for Earth’s ecosystems

As the United Nations develops a post-2020 global biodiversity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of ‘living in harmony with nature’1,2. Advancing dual imperatives to conserve biodiversity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management3. Ecosystems vary in their biota4, service provision5 and relative exposure to risks6, yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This hampers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth’s ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global biodiversity framework

Are biological systems poised at criticality?

Many of life's most fascinating phenomena emerge from interactions among many elements--many amino acids determine the structure of a single protein, many genes determine the fate of a cell, many neurons are involved in shaping our thoughts and memories. Physicists have long hoped that these collective behaviors could be described using the ideas and methods of statistical mechanics. In the past few years, new, larger scale experiments have made it possible to construct statistical mechanics models of biological systems directly from real data. We review the surprising successes of this "inverse" approach, using examples form families of proteins, networks of neurons, and flocks of birds. Remarkably, in all these cases the models that emerge from the data are poised at a very special point in their parameter space--a critical point. This suggests there may be some deeper theoretical principle behind the behavior of these diverse systems.Comment: 21 page