Lifeboat Foundation

The current understanding of the biology of aging is largely based on research aimed at identifying factors that influence lifespan. However, lifespan as a sole proxy measure of aging has limitations because it can be influenced by specific pathologies (not generalized physiological deterioration in old age). Hence, there is a great need to discuss and design experimental approaches that are well-suited for studies targeting the biology of aging, rather than the biology of specific pathologies that restrict the lifespan of a given species. For this purpose, we here review various perspectives on aging, discuss agreement and disagreement among researchers on the definition of aging, and show that while slightly different aspects are emphasized, a widely accepted feature, shared across many definitions, is that aging is accompanied by phenotypic changes that occur in a population over the course of an average lifespan. We then discuss experimental approaches that are in line with these considerations, including multidimensional analytical frameworks as well as designs that facilitate the proper assessment of intervention effects on aging rate. The proposed framework can guide discovery approaches to aging mechanisms in all key model organisms (e.g., mouse, fish models, D. melanogaster, C. elegans) as well as in humans.

Keywords: Aging; experimental design; lifespan; models; phenotypes.

Copyright © 2023 Elsevier B.V. All rights reserved.

The fascinating collective behaviors of biological systems have inspired extensive studies on shape assembly of robot swarms^6,7,8,9. One class of strategies widely studied in the literature are based on goal assignment in either centralized or distributed ways^10,11,12. Once a swarm of robots are assigned unique goal locations in a desired shape, the consequent task is simply to plan collision-free trajectories for the robots to reach their goal locations¹⁰ or conduct distributed formation control based on locally sensed information^6,13,14. It is notable that centralized goal assignment is inefficient to support large-scale swarms since the computational complexity increases rapidly as the number of robots increases^15,16. Moreover, when robots fail to function normally, additional algorithms for fault-tolerant detection and goal re-assignment are required to handle such situations¹⁷. As a comparison, distributed goal assignment can support large-scale swarms by decomposing the centralized assignment into multiple local ones^11,12. It also exhibits better robustness to robot faults. However, since distributed goal assignments are based on locally sensed information, conflicts among local assignments are inevitable and must be resolved by sophisticated algorithms such as local task swapping^11,12.

Another class of strategies for shape assembly that have also attracted extensive research attention are free of goal assignment^18,19,20,21. For instance, the method proposed in ref. ¹⁸ can assemble complex shapes using thousands of homogeneous robots. An interesting feature of this method is that it does not rely on external global positioning systems. Instead, it establishes a local positioning system based on a small number of pre-localized seed robots. As a consequence of the local positioning system, the proposed edge-following control method requires that only the robots on the edge of a swarm can move while those inside must stay stationary. The method in ref. ¹⁹ can generate swarm shapes spontaneously from a reaction-diffusion network similar to embryogenesis in nature. However, this method is not able to generate user-specified shapes precisely. The method in ref. ²¹ can aggregate robots on the frontier of shapes based on saliency detection. The user-defined shape is specified by a digital light projector. An interesting feature of this method is that it does not require centralized edge detectors. Instead, edge detection is realized in a distributed manner by fusing the beliefs of a robot with its neighbors. However, since the robots cannot self-localize themselves relative to the desired shape, they make use of random walks to search for the edges, which would lead to random trajectories. Another class of methods that do not require goal assignment is based on artificial potential fields^22,23,24,25. One limitation of this class of methods is that robots may easily get trapped in local minima, making it difficult to assemble nonconvex complex shapes.

Here, we propose a strategy for shape assembly of robot swarms based on the idea of mean-shift exploration: when a robot is surrounded by neighboring robots and unoccupied locations, it would actively give up its current location by exploring the highest density of nearby unoccupied locations in the desired shape. This idea does not rely on goal assignment. It is realized by adapting the mean-shift algorithm^26,27,28, which is an optimization technique widely used in machine learning for locating the maxima of a density function. Moreover, a distributed negotiation mechanism is designed to allow robots to negotiate the final desired shape with their neighbors in a distributed manner. This negotiation mechanism enables the swarm to maneuver while maintaining a desired shape based on a small number of informed robots. The proposed strategy empowers robot swarms to assemble nonconvex complex shapes with strong adaptability and high efficiency, as verified by numerical simulation results and real-world experiments with swarms of 50 ground robots. The strategy can be adapted to generate interesting behaviors including shape regeneration, cooperative cargo transportation, and complex environment exploration.

More apologism for aging and death.

Chinese scientists have devised a technique to coat everyday materials like paper and plastic with liquid metal, potentially creating “smart devices.” The method, which involves adjusting pressure rather than using a binding material, successfully enables the liquid metal to adhere to surfaces, a previously challenging task due to high surface tension.

Everyday materials such as paper and plastic could be transformed into electronic “smart devices” by using a simple new method to apply liquid metal to surfaces, according to scientists in Beijing, China. The study, published June 9 in the journal Cell Reports.

<em>Cell Reports</em> is a peer-reviewed scientific journal that published research papers that report new biological insight across a broad range of disciplines within the life sciences. Established in 2012, it is the first open access journal published by Cell Press, an imprint of Elsevier.

The characteristics of the “egress complex” found in termite mounds can be replicated to enhance the optimize interior climate of buildings.

Of the approximately 2,000 recognized termite species.

A species is a group of living organisms that share a set of common characteristics and are able to breed and produce fertile offspring. The concept of a species is important in biology as it is used to classify and organize the diversity of life. There are different ways to define a species, but the most widely accepted one is the biological species concept, which defines a species as a group of organisms that can interbreed and produce viable offspring in nature. This definition is widely used in evolutionary biology and ecology to identify and classify living organisms.

Enter Kim’s class, 2.74 (Bio-Inspired Robotics).

According to Kim, researchers need to understand this cognitive bias, this tendency toward anthropomorphism, in order to even begin developing robots that can help humans with their physical movements. While Kim’s research interest is in building robots that could help people, such as the elderly in an aging population with fewer young people to perform services, such advancement is not even possible without understanding biology, biomechanics, and how much we don’t understand about our own everyday movements.

“One big thing students should learn in this class is not necessarily to understand how we move our body but the fact that we don’t understand how we move,” Kim says. “One of our ultimate goals in robotics is to develop robots that help elderly people by mimicking how we use our arms and legs, but if you don’t realize how little we know about how we move, we cannot even start tackling this problem.”

As biological singularity genes grow so will leisure activities grow and blossom. Even now tricking is a show of the real human potential in movement. Just shows us that the future is much brighter everyday with new activities that push the human potential and humans will have even greater heights of human abilities when the biological singularity genes can make us soar to new abilities.

Sixteen of the best tricking athletes came to Atlanta and battled head to head for the winning title.

Continue reading “Freestyle Tricking Battle | Red Bull Throwdown 2014” »

Inspired by biological fractals, a team of researchers affiliated with multiple institutions in China has developed a new pore structure for a membrane used to separate uranium from seawater. In their paper published in the journal Nature Sustainability, the group describes their pore structure and how well it worked when tested. Alexander Wiechert and Sotira Yiacoumi with the Georgia Institute of Technology and Costas Tsouris with Oak Ridge National Laboratory, have published a News & Views piece on the work done by the team in China and the work that is left to do before the membrane can be commercialized.

In the 1950s, scientists realized that the world’s oceans held the potential for supplying the uranium needed to produce atomic weapons and electrical power. But it took another 30 years before a viable means of extracting uranium was developed. A team of researchers in Japan developed an amidoxime-grafted adsorbent that appeared able to do the job, but only in a limited way. In this new effort, the researchers have expanded on the work by the Japanese team to create a membrane for use in filtering uranium from seawater.

The membrane created by the team in China is based on a hierarchical pore structure that was modeled on fractals found in nature. Seawater containing uranium enters the outer portion of the membrane through macropores. The molecules in the water then migrate into a branching matrix of smaller channels. From there, they are carried to a microporous inner portion of the membrane where the uranium is absorbed by an amidoxime-grafted adsorbent. Testing showed it capable of extracting 9 mg g⁻¹ from a sample of seawater over four weeks.

Year 2021 😀 😍

The COVID-19 pandemic has reached direct and indirect medical and social consequences with a subset of patients who rapidly worsen and die from severe-critical manifestations. As a result, there is still an urgent need to identify prognostic biomarkers and effective therapeutic approaches. Severe-critical manifestations of COVID-19 are caused by a dysregulated immune response. Immune checkpoint molecules such as Programmed death-1 (PD-1) and its ligand programmed death-ligand 1 (PD-L1) play an important role in regulating the host immune response and several lines of evidence underly the role of PD-1 modulation in COVID-19. Here, by analyzing blood sample collection from both hospitalized COVID-19 patients and healthy donors, as well as levels of PD-L1 RNA expression in a variety of model systems of SARS-CoV-2, including in vitro tissue cultures, ex-vivo infections of primary epithelial cells and biological samples obtained from tissue biopsies and blood sample collection of COVID-19 and healthy individuals, we demonstrate that serum levels of PD-L1 have a prognostic role in COVID-19 patients and that PD-L1 dysregulation is associated to COVID-19 pathogenesis. Specifically, PD-L1 upregulation is induced by SARS-CoV-2 in infected epithelial cells and is dysregulated in several types of immune cells of COVID-19 patients including monocytes, neutrophils, gamma delta T cells and CD4+ T cells. These results have clinical significance since highlighted the potential role of PD-1/PD-L1 axis in COVID-19, suggest a prognostic role of PD-L1 and provide a further rationale to implement novel clinical studies in COVID-19 patients with PD-1/PD-L1 inhibitors.

COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) holds the world in thrall since early March 2020. COVID-19 manifests a spectrum of signs and symptoms from mild illness to acute pneumonia. Unfortunately, a considerable percentage of patients rapidly worse to acute respiratory distress syndrome (ARDS) requiring intensive care (1, 2).

Continue reading “PD-L1 Dysregulation in COVID-19 Patients” »