Lifeboat Foundation

Anatomical decision-making by cellular collectives: Bioelectrical pattern memories, regeneration, and synthetic living organisms.

A key question for basic biology and regenerative medicine concerns the way in which evolution exploits physics toward adaptive form and function. While genomes specify the molecular hardware of cells, what algorithms enable cellular collectives to reliably build specific, complex, target morphologies? Our lab studies the way in which all cells, not just neurons, communicate as electrical networks that enable scaling of single-cell properties into collective intelligences that solve problems in anatomical feature space. By learning to read, interpret, and write bioelectrical information in vivo, we have identified some novel controls of growth and form that enable incredible plasticity and robustness in anatomical homeostasis. In this talk, I will describe the fundamental knowledge gaps with respect to anatomical plasticity and pattern control beyond emergence, and discuss our efforts to understand large-scale morphological control circuits. I will show examples in embryogenesis, regeneration, cancer, and synthetic living machines. I will also discuss the implications of this work for not only regenerative medicine, but also for fundamental understanding of the origin of bodyplans and the relationship between genomes and functional anatomy.

How do our bodies know what to become?

There are no instructions in our genes that code for the exact 3D structure of our bodies. There’s no tiny human contained in our DNA. So, what powers the transformation of the first cell in the embryo to a full-blown organism?

Continue reading “#14 Michael Levin — Our Body is a Collection of Intelligent Organisms” »

Scientists have found an extremely subtle twist in the genetics of aging cells, one that seems to make them increasingly less functional as time goes on.

R esearchers from Northwestern University have revealed animals like mice, rats, killifish, and even humans show a gradual imbalance of long and short genes in virtually every cell in their body as they age.

The discovery suggests there aren’t specific genes that control the aging process. Instead, old age seems to be governed by systems-level changes with complex effects. And this can impact thousands of different genes and their respective proteins.

Fluid intelligence refers to the ability to solve challenging novel problems when prior learning or accumulated experience are of limited use. ¹ Fluid intelligence ranks amongst the most important features of cognition, correlates with many cognitive abilities (e.g. memory), ² and predicts educational and professional success, ³ social mobility, ⁴ health ⁵ and longevity. ⁶ It is thought to be a key mental capacity involved in ‘active thinking’, ⁷ fluid intelligence declines dramatically in various types of dementia ⁸ and reflects the degree of executive impairment in older patients with frontal involvement. ⁹ Despite the importance of fluid intelligence in defining human behaviour, it remains contentious whether this is a single or a cluster of cognitive abilities and the nature of its relationship with the brain. ¹⁰

Fluid intelligence is traditionally measured with tests of novel problem-solving with non-verbal material that minimize dependence on prior knowledge. Such tests are known to have strong fluid intelligence correlations in large-scale factor analyses. ^{11, 12} Raven’s Advanced Progressive Matrices ¹³ (APM), a test widely adopted in clinical practice and research, ¹⁴ contains multiple choice visual analogy problems of increasing difficulty. Each problem presents an incomplete matrix of geometric figures with a multiple choice of options for the missing figure. Less commonly, verbal tests of fluid intelligence such as Part 1 of the Alice Heim 4 (AH4-1) ¹⁵ are adopted. The Wechsler Adult Intelligence Scale (WAIS) ¹⁶ has also been used to estimate fluid intelligence by averaging performance on a diverse range of subtests. However, several subtests (e.g. vocabulary) emphasize knowledge, disproportionately weighting measures of ‘crystallized’ intelligence, ^{17, 18} whilst others (e.g. picture completion) have rather low fluid intelligence correlations. ¹⁹ Hence, it has been argued that tests such as the APM are the most suitable for a theoretically-based investigation of changes in fluid intelligence after brain injury. ^{20, 21}

Proposals regarding the neural substrates of fluid intelligence have suggested close links with frontal and parietal functions. For example, Duncan and colleagues ²² have argued that a network of mainly frontal and parietal areas, termed the ‘multiple-demand network’ (MD), is ‘the seat’ of fluid intelligence. The highly influential parieto-frontal integration theory (P-FIT), based largely on neuroimaging studies of healthy subjects, posits that structural symbolism and abstraction emerge from sensory inputs to parietal cortex, with hypothesis generation and problem solving arising from interactions with frontal cortex. Once the best solution is identified, the anterior cingulate is engaged in response selection and inhibition of alternatives. ^{23, 24} Despite its name, P-FIT also posits occipital and temporal involvement, implying widely distributed substrates of fluid intelligence.

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//Although lipomatosis is very common and increases with age, scientists have previously devoted little discussion and research to it. Scientists at Uppsala University have just published a study that offers significant insights into the causes of human lymph node function decline with aging and the effects on immune system performance.

Scientists carefully examined more than 200 lymph nodes to show that lipomatosis starts in the medulla, which is the center of the lymph node. They also provided evidence connecting lipomatosis to converting lymph node supporting cells (fibroblasts) into adipocytes (fat cells). They also demonstrate that fibroblast subtypes in the medulla are more likely to develop into adipocytes.\.

The study is a first step toward understanding why lipomatosis occur.

Framing the process of ageing more as a treatable condition, rather than an inevitable consequence of life, could allow people to live longer, thanks to emerging biotechnologies and a greater emphasis on healthy living.

TMCs are responsible for all aspects of data generation from tissue collection and analysis to data integration and interpretation. We anticipate that TMCs will acquire and integrate imaging and omics data to benchmark, standardize and validate SnC maps at single-cell resolution for their assigned tissues. The TDA sites are responsible for development of innovative, new approaches and tools necessary to deeply phenotype SnCs in human tissues and model systems. Examples include multi-omics characterization of the 4D nucleome in SnCs, high-throughput quantification of telomere-associated foci, and in vivo detection of SnCs via positron emission tomography imaging. Once developed, these new technologies are expected to be applied broadly and collaboratively across multiple tissues by the TMCs. The CODCC will collect, store and curate all data and metadata generated by the TMCs and TDA sites. The CODCC is responsible for generating the computational models, and final atlas products as well as the tools to visualize and disseminate the data as a resource for the broad scientific community.

It is expected that SenNet will interface with other cell mapping programs such as Human Bimolecular Atlas Program (HuBMAP), Human Cell Atlas (HCA) and the Kidney Precision Medicine Project (KPMP). HuBMAP is an NIH Common Fund Initiative to develop the resources and framework to map the 30 trillion cells that make up the human body using protein identifiers of cell lineage. HCA is using single-cell and spatial transcriptomics to create cell reference maps defining the position, function and characteristics of all cells in the human body. The KPMP is an initiative of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) aimed at using state-of-the-art and emerging technologies to characterize renal biopsies from participants with acute kidney injury or chronic kidney disease to enable personalized approaches to their treatment.

Transhuman brains are the melding of hyper-advanced electronics and super-artificial intelligence (AI) with neurobiological tissue. The goal is not only to repair injury and mitigate disease, but also to enhance brain capacity and boost mental function. What is the big vision, the end goal — how far can transhuman brains go? What does it mean for individual consciousness and personal identity? Is virtual immortality possible? What are the ethics, the morality, of transhuman brains? What are the dangers?

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Continue reading “Max Tegmark — Transhuman Brains?” »