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One of the most common symbiotic relationships is between various species of algae and fungi, or between cyanobacteria (commonly known as blue-green algae though it's not algae) and fungi. These paired species take the form of lichens. The term symbiosis was first used in the 19th century to describe the lichen relationship, which was thought to be highly unusual. Since then, we've discovered symbiosis is the norm, rather than the exception. In fact, it has shaped the evolution of most life on Earth. Symbiosis is almost everywhere we look Lichens are diverse. They grow on tree trunks, on roof tiles and on ancient rocks. The symbiosis of two different species allows both to survive in environments they might not be able to colonize otherwise. The fungus provides a suitable environment for its partnering species of algae or cyanbacteria to grow—it might otherwise be too exposed or dry, for example. In return, the fungus gets to share some of the carbohydrates produced by photosynthesis.

Species living closely together in symbiosis is far older and way more common than you might think

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A collaborative research team from NIMS and Tokyo University of Science has successfully developed an artificial intelligence (AI) device that executes brain-like information processing through few-molecule reservoir computing. This innovation utilizes the molecular vibrations of a select number of organic molecules. By applying this device for the blood glucose level prediction in patients with diabetes, it has significantly outperformed existing AI devices in terms of prediction accuracy.

High-precision blood glucose level prediction achieved by few-molecule reservoir computing

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Molecule-based reservoir computing (RC) is promising for achieving low power consumption neuromorphic computing, although the information-processing capability of small numbers of molecules is not clear. Here, we report a few- and single-molecule RC that uses the molecular vibration dynamics in the para-mercaptobenzoic acid (pMBA) detected by surface-enhanced Raman scattering (SERS) with tungsten oxide nanorod/silver nanoparticles. The Raman signals of the pMBA molecules, adsorbed at the SERS active site of the nanorod, were reversibly perturbated by the application of voltage-induced local pH changes near the molecules, and then used to perform time-series analysis tasks. Despite the small number of molecules used, our system achieved good performance, including >95% accuracy in various nonlinear waveform transformations, 94.3% accuracy in solving a second-order nonlinear dynamic system, and a prediction error of 25.0 milligrams per deciliter in a 15-minute-ahead blood glucose level prediction. Our work provides a concept of few-molecular computing with practical computation capabilities.

Few- and single-molecule reservoir computing experimentally demonstrated with surface-enhanced Raman scattering and ion gating | Science Advances

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A collaborative research team from NIMS and Tokyo University of Science has successfully developed an artificial intelligence (AI) device that executes brain-like information processing through few-molecule reservoir computing. This innovation utilizes the molecular vibrations of a select number of organic molecules. By applying this device for the blood glucose level prediction in patients with diabetes, it has significantly outperformed existing AI devices in terms of prediction accuracy.

High-precision blood glucose level prediction achieved by few-molecule reservoir computing

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The unusually high temperatures have caused disruption to education and agriculture across the Asian region. Bangladesh was also forced to close all schools this week after temperatures soared to between 40C and 42C in some areas. About 33 million children in Bangladesh were affected, according to the charity Save the Children. “Leaders need to act now to urgently reduce warming temperatures, as well as factoring children – particularly those affected by poverty, inequality and discrimination – into decision making and climate finance,” said Shumon Sengupta, Country Director Bangladesh, Save the Children International. Thousands of people in Bangladesh have gathered in mosques and rural fields, praying for relief from the heat.

Wave of exceptionally hot weather scorches south and south-east Asia | South and central Asia | The Guardian

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RNA expression of retroviral element RNLTR12-int is crucial for myelination • RNLTR12-int binds to SOX10 to regulate Mbp expression • RNLTR12-int-like sequences (RetroMyelin) were identified in all jawed vertebrates • Convergent evolution likely led to RetroMyelin acquisition, adapted for myelination Summary Myelin, the insulating sheath that surrounds neuronal axons, is produced by oligodendrocytes in the central nervous system (CNS). This evolutionary innovation, which first appears in jawed vertebrates, enabled rapid transmission of nerve impulses, more complex brains, and greater morphological diversity. Here, we report that RNA-level expression of RNLTR12-int, a retrotransposon of retroviral origin, is essential for myelination. We show that RNLTR12-int-encoded RNA binds to the transcription factor SOX10 to regulate transcription of myelin basic protein (Mbp, the major constituent of myelin) in rodents. RNLTR12-int-like sequences (which we name RetroMyelin) are found in all jawed vertebrates, and we further demonstrate their function in regulating myelination in two different vertebrate classes (zebrafish and frogs). Our study therefore suggests that retroviral endogenization played a prominent role in the emergence of vertebrate myelin.

A retroviral link to vertebrate myelination through retrotransposon-RNA-mediated control of myelin gene expression: Cell

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This paper introduces novel attack primitives that enable adversaries to leak (read) and manipulate (write) the path history register (PHR) and the prediction history tables (PHTs) of the conditional branch predictor in high-performance CPUs. These primitives enable two new classes of attacks: first, it can recover the entire control flow history of a victim program by exploiting read primitives, as demonstrated by a practical secret-image recovery based on capturing the entire control flow of libjpeg routines. Second, it can launch extremely high-resolution transient attacks by exploiting write primitives. We demonstrate this with a key recovery attack against AES based on extracting intermediate values.

Pathfinder: High-Resolution Control-Flow Attacks Exploiting the Conditional Branch Predictor | Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3

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the current study leverages the large-scale dataset from the UK Biobank and employs data-driven approaches to identify naturally developed dietary patterns and their associations with cognitive function, mental health, blood and metabolic biomarkers, brain imaging and genomics. Specifically, we first utilized food-liking data from the UK Biobank participants and applied principal component analysis (PCA) and hierarchical clustering techniques to develop subtypes of food-liking. Subsequently, through one-way analysis of covariance (ANCOVA), we assessed differences in various brain health domains among these subtypes, including mental health, cognitive functions, blood and metabolism biomarkers, and brain magnetic resonance imaging (MRI) traits. We also examined differences among these subtypes by analyzing longitudinal data on mental disorders via Cox proportional hazards models. Third, structural equation models (SEMs) were employed to explore the relationships between dietary patterns and different aspects of brain health. Fourth, genome-wide association analysis (GWAS) and gene expression and enrichment analysis were conducted to investigate the genetic underpinnings of distinct subtypes of food-liking and potential biological pathways. This study pioneeringly represents the large-scale exploration of food preferences and their comprehensive associations with brain health. By exploring these intricate connections, our research lays the groundwork for further investigations and potential interventions that can significantly impact human health on a global scale, underscoring the importance of understanding the intricate relationship between diet and brain health.

Associations of dietary patterns with brain health from behavioral, neuroimaging, biochemical and genetic analyses | Nature Mental Health

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The dietary choices of a large sample of 181,990 participants from the UK Biobank were analyzed against and a range of physical evaluations, including cognitive function, blood metabolic biomarkers, brain imaging, and genetics—unveiling new insights into the relationship between nutrition and overall well-being. The food preferences of each participant were collected via an online questionnaire, which the team categorized into 10 groups (such as alcohol, fruits and meats). A type of AI called machine learning helped the researchers analyze the large dataset. A balanced diet was associated with better mental health, superior cognitive functions and even higher amounts of gray matter in the brain—linked to intelligence—compared with those with a less varied diet.

Research shows 'profound' link between dietary choices and brain health

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Real systems showing regime shifts, such as ecosystems, are often composed of many dynamical elements interacting on a network. Various early warning signals have been proposed for anticipating regime shifts from observed data. However, it is unclear how one should combine early warning signals from different nodes for better performance. Based on theory of stochastic differential equations, we propose a method to optimize the node set from which to construct an early warning signal. The proposed method takes into account that uncertainty as well as the magnitude of the signal affects its predictive performance, that a large magnitude or small uncertainty of the signal in one situation does not imply the signal’s high performance, and that combining early warning signals from different nodes is often but not always beneficial. The method performs well particularly when different nodes are subjected to different amounts of dynamical noise and stress.

Anticipating regime shifts by mixing early warning signals from different nodes | Nature Communications

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Cicadas comprise a diverse family of over 3,000 insect species found globally, with the majority of their lives spent underground in a larval state. They emerge as adults to transform and mate, with some species appearing annually and others, known as periodical cicadas, synchronizing their emergence every 13 or 17 years. Mathematicians have long been intrigued by the question of why periodical cicadas follow prime number cycles, despite the lack of a clear evolutionary explanation. This year's event involves the 13-year Brood XIX, currently emerging in the Carolinas, followed by the 17-year Brood XIII in the Midwest. There could be a small area of overlap in central Illinois.

Cicada-palooza! Billions of bugs to blanket America

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we performed ultra-deep metagenomic sequencing on 351 fecal samples from the Hadza hunter-gatherers of Tanzania and comparative populations in Nepal and California. We recovered 91,662 genomes of bacteria, archaea, bacteriophages, and eukaryotes, 44% of which are absent from existing unified datasets. We identified 124 gut-resident species vanishing in industrialized populations and highlighted distinct aspects of the Hadza gut microbiome related to in situ replication rates, signatures of selection, and strain sharing. Industrialized gut microbes were found to be enriched in genes associated with oxidative stress, possibly a result of microbiome adaptation to inflammatory processes. This unparalleled view of the Hadza gut microbiome provides a valuable resource, expands our understanding of microbes capable of colonizing the human gut, and clarifies the extensive perturbation induced by the industrialized lifestyle.

Ultra-deep sequencing of Hadza hunter-gatherers recovers vanishing gut microbes: Cell

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There are 10-100 trillion microbes that reside in our gastrointestinal tract, representing thousands of species. The gut microbiota is a control center for multiple aspects of our biology including our immune status, metabolism, and neurobiology. Many of the metabolic activities and developmental signals that the microbiota deploys are complementary to our own, affirming that humans are composite organisms consisting of microbial and human parts. Microbiota composition varies considerably between individuals, and factors like variation in host genotype and diet impact the community. Changes in our microbial communities differentially influence aspects of host biology (e.g., immune function) and likely explain aspects of variation within and between human populations (e.g., predisposition to disease). The plasticity of the microbiota suggests that it may be a viable therapeutic target, and necessitates the pursuit of a fundamental understanding of how extrinsic and intrinsic factors alter its composition, function, and interaction with the host.

The Sonnenburg Lab - Research

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prevent arms transfers that risk facilitating or otherwise contributing to violations of human rights or international humanitarian law;

National Security Memorandum on Safeguards and Accountability With Respect to Transferred Defense Articles and Defense Services | The White House

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Prior to completion of the human genome sequencing project, some predicted that we would find ~100,000 genes. For many, feelings of surprise and perhaps humility were associated with the announcement that our genome only contains ~20,000 protein-coding genes, a number not greatly different from that of the fruit fly. However, by expanding our view of ourselves, we can see that the number 100,000 is likely an underestimate. The microbes that live inside and on us (the microbiota) outnumber our somatic and germ cells by an estimated 10-fold. The collective genomes of our microbial symbionts (the microbiome) provide us with traits we have not had to evolve on our own1. If we consider ourselves to be a composite of microbial and human species, our genetic landscape a summation of the genes embedded in our human genome and microbiome, and our metabolic features a coalescence of human and microbial traits, the self-portrait that emerges is one of a ‘human supraorganism’. Thus, understanding the range of human genetic and physiologic diversity means that we must characterize our microbiome and the factors that influence the distribution and evolution of our microbial partners.

The human microbiome project: exploring the microbial part of ourselves in a changing world - PMC

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The microbial cells that colonize the human body, including in mucosal and skin environments, are at least as abundant as our somatic cells1, and certainly contain far more genes than our human genome (Box 1). An estimated 500–1000 species of bacteria exist in the human body at any one time2, although the number of unique genotypes (sub-species) could be orders of magnitude greater than this

Current understanding of the human microbiome - PMC

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“the surface area of our digestive system is about a hundred times greater than the area of our skin”

Gut by Giulia Endere review – a celebration of our most under-rated organ | Health, mind and body books | The Guardian