Category Archives: Biology

Biology

Beyond Nature’s Limits: Ethical Dilemmas in the Age of Synthetic Biology – Medium

Synthetic biology, a relatively new interdisciplinary field that combines engineering, biology, and chemistry, is revolutionizing the way we design and produce biological systems. Its an exciting and rapidly evolving area of research, with potential applications ranging from medicine and agriculture to energy production and materials science. As 2030 year olds who are digitally savvy and intellectually curious, you may have heard about synthetic biology but arent entirely clear on what it is or how it could impact your lives. In this article, we will explore the rise of synthetic biology, its applications, and the ethical implications that come with this revolutionary technology.

Synthetic biology can be defined as the design and construction of new biological parts, devices, and systems not found in nature. Using a combination of molecular biology techniques and engineering principles, synthetic biologists create functional DNA sequences or genetic circuits to program living cells to perform specific tasks. These engineered cells can then be used for various applications, such as producing medicines, biofuels, or even creating new organisms with novel characteristics.

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Beyond Nature's Limits: Ethical Dilemmas in the Age of Synthetic Biology - Medium

Biology

Biological Research And Self-driving Labs In Deep Space Supported By Artificial Intelligence – Astrobiology – Astrobiology News

Sickbay Aboard Starship Enterprise Star Trek Strange New Worlds / Paramount

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life.

Multi-hierarchical levels of space biological research and data. Space biology research seeks to characterize the effects of spaceflight on living systems across hierarchical biological levels. Our current understanding of the biological responses to spaceflight incorporates multiple types of evidence at the cellular, tissue, and whole organism level. q-bio.OT

To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges.

Self-driving labs are automated experimental platforms with AI closed-loop control for knowledge gain and experimental design. In spaceflown research programs, implementation of self-driving labs will aid comprehensive characterization of the effects of spaceflight on living systems, ultimately feeding research findings into applications such as in situ analytics, Earth-based open science research programs, and precision astronaut health systems. q-bio.OT

In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space.

Deep space biological and biomedical data collection and transfer. The diagram shows the data and information flow in which a cloud-based data management environment serves as the nexus between space-based data and research and Earth-based researchers and analysts, enabling Open Science access to data and analytics and facilitating preparation of AI-ready datasets. q-bio.OT

Comments: 28 pages, 4 figures Subjects: Other Quantitative Biology (q-bio.OT); Machine Learning (cs.LG) Cite as: arXiv:2112.12582 [q-bio.OT] (or arXiv:2112.12582v1 [q-bio.OT] for this version) https://doi.org/10.48550/arXiv.2112.12582 Focus to learn more Submission history From: Lauren Sanders [v1] Wed, 22 Dec 2021 05:18:26 UTC (4,520 KB) https://arxiv.org/abs/2112.12582 (full article) Astrobiology, space biology, space life science,

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Biological Research And Self-driving Labs In Deep Space Supported By Artificial Intelligence - Astrobiology - Astrobiology News

Biology

Surprising behavior in one of the least studied mammals in the world – EurekAlert

image:

Bairds beaked whale, The Commander Islands

Credit: Olga Filatova, University of Southern Denmark

Some animals live in such remote and inaccessible regions of the globe that it is nearly impossible to study them in their natural habitats. Beaked whales, of which 24 species have been found so far, are among them: They live far from land and in deep oceanic waters, where they search for food at depths of 500 meters and more.

The record holder for the deepest dive by a mammal is a Cuvier's beaked whale, which in 2014 was measured to dive at least 2992 meters. A beaked whale also holds the mammalian record for the longest dive; 222 minutes.

Now, the world gets a new and surprising insight into the world of distant beaked whales through a scientific study of a population of Baird's beaked whales. The population has unexpectedly been found near the coast and in shallower waters than previously observed.

The study is led by whale biologists Olga Filatova and Ivan Fedutin from the University of Southern Denmark/Fjord&Blt, and it ispublished in the journal Animal Behaviour.

Filatova and Fedutin have many years of whale studies in the northern Pacific behind them, and it was during an expedition to the Commander Islands in 2008 that they first saw a group of Baird's beaked whales near the coast.

"We were there to look for killer whales and humpback whales, so we just noted that we had seen a group of Baird's beaked whales and didn't do much about it. But we also saw them in the following years, and after five years, we suspected that it was a stable community frequently visiting the same area. We saw them every year until 2020, when Covid 19 prevented us from going back to the Commander Islands," explains Olga Filatova,a whale expert and postdoc at Department of Biology and SDU Climate Cluster, University of Southern Denmark.

The studied population of Baird's beaked whales came close to the coast - within four km from land, and they were observed in shallow water; less than 300 meters.

"It is uncharacteristic for this species," says Olga Filatova, who also points out that the population likely has adapted to this particular habitat and thus deviates from the established perception that all beaked whales roam far out at sea and in deep waters.

"It means that you cannot expect all individuals within a specific species to behave the same way. This makes it difficult to plan species protection - in this case, for example, you cannot plan based on the assumption that beaked whales only live far out in deep sea. We have shown that they can also live in shallow and coastal waters. There may be other different habitats that we are not aware of yet," says Olga Filatova.

There are many examples of individuals from the same whale species not behaving the same. In the whale world, it is common to find groups of the same species living in different places, eating different prey, communicating differently, and not liking to mingle with fellow species in other groups.

Some killer whale groups only hunt marine mammals like seals and porpoises, others only herring. Some humpback whales migrate between the tropics and the Arctic, others are residents in certain areas. Some sperm whale groups develop their own dialects for internal communication and do not like to communicate with others outside the group.

According to Olga Filatova, social learning is at play when groups develop preferences for, for example, habitats and prey.

There are many forms of social learning in the animal world. Imitation is the most complex form; the animal sees what others do and understands the motivation and reasoning behind it. Then there is "local enhancement," where an animal sees another animal heading to a specific place, follows, and learns that the place has value. This has been observed in many animals, including fish.

Olga Filatova believes that the population of Baird's beaked whales at the Commander Islands learns through "local enhancement": They see that some peers go to the shallow water near the coast, follow, and discover that it is a good place, probably because there are many fish.

"It becomes a cultural tradition, and it is the first time a cultural tradition has been observed among beaked whales," she says.

Other examples of cultural traditions in whales include when they develop specific hunting traditions: some slap their tails to stun fish, some generate waves to wash seals off ice floes, some chase fish onto the beach.

The researchers observed a total of 186 individuals of the Baird's beaked whale species at the Commander Islands from 2008-2019. 107 were only observed once and thus assessed to be transient whales. 79 individuals were spotted for more than one year and were thus assessed to be residents.

61 of the transient whales were seen interacting with the residents, and seven of them were seen in shallow water.

"The transients are not as familiar with local conditions as the residents, and therefore, they usually seek food at the depths that are normal for their species. But we actually observed some transients in the shallow area. These were individuals who had some form of social contact with the residents. It must be in that contact that they learned about the shallow water and its advantages," says Olga Filatova.

It is unclear how many Baird's beaked whales exist in the world.

The study was supported by Rufford Small Grants, Whale and Dolphin Conservation, Animal Welfare Institut and Russian Fund for Fundamental Research.Olga Filatova's research is also supported by Human Frontier Science Program.

Beaked whalesWe know 24 species of beaked whales, which belong to the toothed whales. Some are known only from strandings and skull finds, and photos of them are generally rare. Baird's beaked whale is the largest of the beaked whales, reaching a length of up to 10 meters. The female is slightly larger than the male. Both females and males have a characteristic underbite with two pairs of teeth in the lower jaw.

Observational study

Animals

Unusual use of shallow habitats may be evidence of a cultural tradition in Baird's beaked whales

22-Jan-2024

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Surprising behavior in one of the least studied mammals in the world - EurekAlert

Biology

Exploring the Role of Non-Protein Ubiquitination in Cellular Biology – Medriva

Ubiquitination, a process fundamental to cellular biology, has traditionally been associated with protein regulation. However, recent research has expanded its scope to non-protein biomolecules, diving into a whole new realm of biological complexity. This article delves into the concept of non-lysine ubiquitination and its extension to biomolecules other than proteins, exploring the challenges, potential, and significance of this emerging field.

Ubiquitination, the process of attaching ubiquitin protein to biomolecules, is well-known for regulating protein degradation, localization, and activity. Recently, scientists have discovered that ubiquitination can also occur on non-protein molecules such as bacterial lipopolysaccharides, phosphatidylethanolamine, saccharides, and ADP-ribose. This has opened up new avenues of study, but has also presented unique difficulties in terms of quantification and detection.

E3 ligases, the enzymes that facilitate the transfer of ubiquitin to the target molecule, play a critical role in non-proteinaceous ubiquitination. Understanding the biological functions of these ligases can be complex, mainly due to the vast variety and specificity of E3 ligases. Nevertheless, their study is crucial for unravelling the intricacies of non-protein ubiquitination.

Proteasomes, cellular complexes that break down proteins, have been found to interact with ubiquitinated molecules. Research has shown that proteasomes can catalyze peptide splicing of full-length proteins, producing a variety of peptides with regulatory activities in cells. On the other hand, proteasome inhibitors (PIs) have demonstrated the potential to target the 26S proteasome in hematologic malignancies, prevent the degradation of tumor suppressor proteins, and inhibit the NF B signaling pathway. However, the resistance to these inhibitors remains a significant limitation.

Ubiquitinations role extends beyond normal cellular function and into disease pathology. For instance, Central Congenital Hypoventilation Syndrome (CCHS), a rare and life-threatening condition, has been linked to the ubiquitin transfer system. Expansion mutations of the poly-alanine tract in PHOX2B have been found to disrupt proper ubiquitin transfer to neural proteins, leading to cell death and triggering CCHS.

Despite the challenges in studying non-proteinaceous ubiquitination, the potential for groundbreaking discoveries and therapeutic development is immense. Antioxidant activity of protein-derived peptides, for example, has shown promise in disease prevention, management, and treatment, hinting at the diverse applications of ubiquitination knowledge. To fully realize this potential, interdisciplinary collaboration is needed, along with the development of novel methods for research in this field.

In conclusion, non-protein ubiquitination is a complex and promising field of study that can revolutionize our understanding of cellular biology and disease mechanisms. By overcoming the challenges associated with studying this process, we can unlock new therapeutic avenues and contribute to a deeper understanding of lifes intricate processes.

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Exploring the Role of Non-Protein Ubiquitination in Cellular Biology - Medriva

Biology

Lost Loves: USU Neuroscientists Learn About Grief From Widowed Coyotes – Utah State University

Utah State University Honors student Rachel Tong says that prior to working in a neuroscience lab, she gave little thought to the source of her emotions.

Like everyone, I sometimes feel sad, mad or happy, says Tong, a human biology and communications studies major with minors in chemistry and psychology. But I never thought about what was actually happening inside my brain that was driving these responses and feelings.

With faculty mentor Sara Freeman, assistant professor in USUs Department of Biology, Tong is delving into brains not human brains, but the brains of another socially monogamous mammal: the coyote.

It surprises many people to learn coyotes are a socially monogamous species, as are all wild canid species studied to date, Freeman says. This makes coyotes a valuable subject of study.

Female coyotes rely on their mates to help with each litter. The survival of their offspring has much more chance for success with the cooperation of both parents. Biologists whove studied the canids report coyotes generally mate for life and only seek a new partner if a mate dies.

Freeman and her students study adult male-female pairs of coyotes (Canis latrans) housed in the USDA APHIS National Wildlife Research Center Predator Ecology and Behavior Project Field Station in Millville, Utah, along with the brains of deceased coyotes.

Tong, a recipient of a USU College of Science Minigrant in 2023 and a USU Undergraduate Research and Creative Opportunities (URCO) grant for spring 2024, is studying brains from female coyotes that died from natural causes, including some that had live mates and some that lost their mates prior to death.

Her research focuses on a neuropeptide produced in both human and canid brains called corticotropin-releasing factor, or CRF.

CRF plays a major role in both human and coyote behaviors following stress and anxiety, Tong says. In response to stress, including grief, CRF causes the brains stress system, known as the hypothalamic-pituitary-adrenal axis, to release cortisol into the bloodstream. Cortisol is a stress hormone that regulates many body processes, and mobilizes the bodys response to stressful or threatening stimuli.

With her study, Tong is exploring where CRF receptors in the brain are located and if the amounts of these receptors change in the brains of female coyotes that experienced social loss.

To do this, Tong carefully slices 20-micron sections of brain tissue, using an instrument called a cryostat, for microscopic analysis. Its a skill shes conscientiously honed since joining Freemans lab in fall 2021.

Each section is about the width of a human hair, she says.

Tong examines the intricately branching, folding regions of each brain section and, using digital densitometry tools that help to visualize the densest areas of receptor expression, she can identify the location of CRF receptors.

Its fascinating and Im excited to see if we see significant differences in the brains of paired coyotes versus the widowed coyotes, she says.

An aspiring physician, Tongs research efforts are now competing with her preparations for taking the MCAT a step toward applying to medical schools. The Undergraduate Research Fellow has shadowed a pediatrician and an emergency medicine physician.

I was impressed not only by their knowledge and skills, but also by how they dealt with different cases and established strong patient-provider communications and relationships, she says.

Since working in Freemans lab, Tong has developed an affinity for neuroscience, which is enhanced by her campus efforts to foster social well-being among her fellow students. She serves as the College of Science student representative for the USU Honors Student Advisory Board, which includes working with her peers to foster access and inclusion, along with student success and retention.

Tong is also president of the Biology Undergraduate Student Association, and serves on USUs International Student Council and with the universitys Asian Student Association. She also volunteers with the iHelp Foundation, the ReadingBud program at Adams Elementary School and at the English Language Center of Cache Valley.

Helping fellow students feel included, giving encouragement to children struggling to read and sharing experiences with people adapting to a new culture as I did, when I arrived in the United States are all ways of helping people feel a sense of belonging and community, says Tong, who is from Singapore. Its been interesting and beneficial to me to interact with different age groups and with people from different cultures. Coming out of a global pandemic, we all need to establish supportive social bonds to be healthy both mentally and physically.

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Lost Loves: USU Neuroscientists Learn About Grief From Widowed Coyotes - Utah State University

Biology

Unraveling the Complexities of Multiple Sclerosis: A New Approach to Understanding Chronic Diseases – Medriva

Unraveling the Complexities of Multiple Sclerosis

An international study led by the Department of Medicine and Life Sciences (MELIS) at Pompeu Fabra University has developed a cutting-edge computational biology tool that offers an integrated vision of multiple sclerosis (MS). This study used multi-level network analysis in a groundbreaking method that simultaneously analyzes data from genes to the whole organism. The tool has been developed with the potential to revolutionize the understanding and management of complex diseases such as MS and various forms of dementia.

This innovative tool is based on the analysis of multiomic data, brain and retinal images, and clinical data of 328 patients with MS and 90 healthy individuals. Multiomic data include genomic, phosphoproteomic, and cytomic data, providing a comprehensive perspective of the disease at various biological levels. The analysis offers valuable insights into the complexity of chronic diseases, revealing correlations and interactions that were previously elusive.

Notably, the tool has revealed a significant correlation between the protein MK03, T cell count, retinal nerve fiber thickness, and the timed gait test. These findings offer a comprehensive understanding of the interplay between proteins, cells, tissues, and behavior in MS. The identification of such correlations and their potential impact on disability and disease progression could lead to future strategies for personalized MS therapeutics.

The potential of this tool extends beyond MS. The method used for multi-level network analysis could be applied to study other complex diseases such as Alzheimers and other types of dementia. By providing an integrated view of these diseases, the tool could help identify essential biomarkers, inform treatment strategies, and contribute to the development of personalized medicine.

The researchers emphasize the significance of understanding the relationships between biological elements in building a coherent picture of complex diseases. This integrated approach is a big leap in medical research, bridging the gap between molecular, cellular, and phenotypic scales. The tools ability to link genomics, proteomics, cytomics, imaging, and clinical data underlines the importance of considering all these factors in the study of complex diseases.

This study represents a major advancement in our understanding and management of complex diseases like MS. The computational biology tool developed provides an integrated vision of these diseases, opening new avenues for research and therapeutic intervention. As the study continues, it is hoped that this tool could provide new insights, improve diagnosis, and contribute to the development of personalized medicine for chronic diseases.

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Unraveling the Complexities of Multiple Sclerosis: A New Approach to Understanding Chronic Diseases - Medriva

Biology

Synthetic biology aims to tackle disease and give cells superpowers – Science News Explores

activate: (in biology) To turn on, as with a gene or chemical reaction.

amino acids: Simple molecules that occur naturally in plant and animal tissues and that are the basic building blocks of proteins.

antenna: (plural: antennae or antennas) In biology: Either of a pair of long, thin sensory appendages on the heads of insects, crustaceans and some other arthropods. (in physics) Devices for picking up (receiving) electromagnetic energy.

artery: Part of the bodys circulation system. There are several. Each is amajor tuberunning between the heart and blood vessels that will move blood to all parts of the body.

behavior: The way something, often a person or other organism, acts towards others, or conducts itself.

biology: The study of living things. The scientists who study them are known as biologists.

blood vessel: A tubular structure that carries blood through the tissues and organs.

cancer: Any of more than 100 different diseases, each characterized by the rapid, uncontrolled growth of abnormal cells. The development and growth of cancers, also known as malignancies, can lead to tumors, pain and death.

carbon: A chemical element that is the physical basis of all life on Earth. It can self-bond, chemically, to form an enormous number of chemically, biologically and commercially important molecules.

carbon nanotube: A nanoscale, tube-shaped material, made from carbon that conducts heat and electricity well.

cardiologist: A doctor that specializes in the branch of medicine dealing with functions and diseases of the heart.

cell: (in biology) The smallest structural and functional unit of an organism. Typically too small to see with the unaided eye, it consists of a watery fluid surrounded by a membrane or wall. Depending on their size, animals are made of anywhere from thousands to trillions of cells.

cell membrane: A structure that separates the inside of a cell from what is outside of it. Some particles are permitted to pass through the membrane.

chain reaction: An event that once started continues to keep itself going. Its a term frequently used to describe atomic fission in a nuclear power plant. By packing enough fuel closely enough together, neutrons released by fissioning atoms bombard neighboring atoms, inducing them to fission. This sets up a self-sustaining process.

chemical: A substance formed from two or more atoms that unite (bond) in a fixed proportion and structure. For example, water is a chemical made when two hydrogen atoms bond to one oxygen atom. Its chemical formula is H2O. Chemical also can be an adjective to describe properties of materials that are the result of various reactions between different compounds.

chemical signal: A message made up of molecules that get sent from one place to another. Bacteria and some animals use these signals to communicate.

chemistry: The field of science that deals with the composition, structure and properties of substances and how they interact.

cholesterol: A fatty material in animals that forms a part of cell walls. In vertebrate animals, it travels through the blood in little vessels known as lipoproteins. Excessive levels in the blood can signal risks to blood vessels and heart.

clot: (in medicine) A collection of blood cells (platelets) and chemicals that collect in a small region, stopping the flow of blood.

conductive: Able to carry an electric current.

contract: To activate muscle by allowing filaments in the muscle cells to connect. The muscle becomes more rigid as a result.

current: (in electricity) The flow of electricity or the amount of charge moving through some material over a particular period of time.

defense: (in biology) A natural protective action taken or chemical response that occurs when a species confronts predators or agents that might harm it. (adj. defensive)

DNA: (short for deoxyribonucleic acid) A long, double-stranded and spiral-shaped molecule inside most living cells that carries genetic instructions. It is built on a backbone of phosphorus, oxygen, and carbon atoms. In all living things, from plants and animals to microbes, these instructions tell cells which molecules to make.

electricity: A flow of charge, usually from the movement of negatively charged particles, called electrons.

electrode: A device that conducts electricity and is used to make contact with non-metal part of an electrical circuit, or that contacts something through which an electrical signal moves. (in electronics)Part of a semiconductor device (such as a transistor) that either releases or collects electronsor holes, or that can controltheir movement.

engineer: A person who uses science and math to solve problems. As a verb, to engineer means to design a device, material or process that will solve some problem or unmet need.

generation: A group of individuals (in any species) born at about the same time or that are regarded as a single group. Your parents belong to one generation of your family, for example, and your grandparents to another. Similarly, you and everyone within a few years of your age across the planet are referred to as belonging to a particular generation of humans.

germ: Any one-celled microorganism, such as a bacterium orfungal species, or a virus particle. Some germs cause disease. Others can promote the health of more complex organisms, including birds and mammals. The health effects of most germs, however, remain unknown.

immune: (adj.) Having to do with immunity. (v.) Able to ward off a particular infection.

immune system: The collection of cells and their responses that help the body fight off infections and deal with foreign substances that may provoke allergies.

implant: A device manufactured to replace a missing biological structure, to support a damaged biological structure, or to enhance an existing biological structure. Examples include artificial hips, knees and teeth; pacemakers; and the insulin pumps used to treat diabetes.Or some device installed surgically into an animals body to collect information on the individual (such as its temperature, blood pressure or activity cycle).

infectious: An adjective that describes a type of microbe or virus that can be transmitted to people, animals or other living things.

limb: (in physiology) An arm or leg. (in botany) A large structural part of a tree that branches out from the trunk.

link: A connection between two people or things.

magnetic field: An area of influence created by certain materials, called magnets, or by the movement of electric charges.

membrane: A barrier which blocks the passage (or flow through) of some materials depending on their size or other features. Membranes are an integral part of filtration systems. Many serve that same function as the outer covering of cells or organs of a body.

molecule: An electrically neutral group of atoms that represents the smallest possible amount of a chemical compound. Molecules can be made of single types of atoms or of different types. For example, the oxygen in the air is made of two oxygen atoms (O2), but water is made of two hydrogen atoms and one oxygen atom (H2O).

muscle: A type of tissue used to produce movement by contracting its cells, known as muscle fibers. Muscle is rich in protein, which is why predatory species seek prey containing lots of this tissue.

nanoparticle: A small particle with dimensions measured in billionths of a meter.

nerve: A long, delicate fiberthat transmits signalsacross the body of an animal. An animals backbone contains many nerves, some of which control the movement of its legs or fins, and some of which convey sensations such as hot, cold or pain.

network: A group of interconnected people or things. (v.) The act of connecting with other people who work in a given area or do similar thing (such as artists, business leaders or medical-support groups), often by going to gatherings where such people would be expected, and then chatting them up. (n. networking)

novel: Something that is clever or unusual and new, as in never seen before.

organ: (in biology) Various parts of an organism that perform one or more particular functions. For instance, an ovary is an organ that makes eggs, the brain is an organ that makes sense of nerve signals and a plants roots are organs that take in nutrients and moisture.

organism: Any living thing, from elephants and plants to bacteria and other types of single-celled life.

particle: A minute amount of something.

pH: A measure of a solutions acidity or alkalinity. A pH of 7 is perfectly neutral. Acids have a pH lower than 7; the farther from 7, the stronger the acid. Alkaline solutions, called bases, have a pH higher than 7; again, the farther above 7, the stronger the base.

plaque: An accumulation of materials in the body from the fluids that move through an area or bathe it. They can be minerals, proteins or other substances that collect as deposits. (in heart disease) Fatty deposits that accumulate in vessels as a result of a disease known as atherosclerosis. This plaque is made up of fat, cholesteroland other substances carried by the blood. Eventually these deposits will harden and narrow the internal openings of the arteries. This reduces the flow of oxygen and blood to organs throughout body.

podcast: A digital audio or video series that can be downloaded from the Internet to your computer or smartphone. Some podcasts also are shows that are broadcast on radio, television or other media.

pore: A tiny hole in a surface. On the skin, substances such as oil, water and sweat pass through these openings.

prosthetic: Adjective that refers to a prosthesis.

protein: A compound made from one or more long chains of amino acids. Proteins are an essential part of all living organisms. They form the basis of living cells, muscle and tissues; they also do the work inside of cells. Antibodies, hemoglobin and enzymes are all examples of proteins. Medicines frequently work by latching onto proteins.

retinitis pigmentosa: Also known as RP, this incurable family of genetic eye diseases causes cells in the retina light-sensitive tissue at the back of the eyeball to fail. Problems emerge in childhood. Most patients eventually go blind.

rhodopsin: A pigment molecule bound to the light-sensing protein opsin. Rhodopsins are found in red cells of the eye. They are extremely sensitive to light, but cannot sense color.

risk: The chance or mathematical likelihood that some bad thing might happen. For instance, exposure to radiation poses a risk of cancer. Or the hazard or peril itself. (For instance: Among cancer risks that the people faced were radiation and drinking water tainted with arsenic.)

science fiction: A field of literary or filmed stories that take place against a backdrop of fantasy, usually based on speculations about how science and engineering will direct developments in the distant future. The plots in many of these stories focus on space travel, exaggerated changes attributed to evolution or life in (or on) alien worlds.

strategy: A thoughtful and clever plan for achieving some difficult or challenging goal.

synthetic: An adjective that describes something that did not arise naturally, but was instead created by people. Many synthetic materialshave been developed to stand in for natural materials, such as synthetic rubber, synthetic diamond or a synthetic hormone. Some may even have a chemical makeup and structure identical to the original.

synthetic biology: A research field in which scientists work on developing custom life forms in the lab. Because they make synthetic organisms, scientists who work in this field are known as synthetic biologists.

system: A network of parts that together work to achieve some function. For instance, the blood, vessels and heart are primary components of the human body's circulatory system. Similarly, trains, platforms, tracks, roadway signals and overpasses are among the potential components of a nation's railway system. System can even be applied to the processes or ideas that are part of some method or ordered set of procedures for getting a task done.

technology: The application of scientific knowledge for practical purposes, especially in industry or the devices, processes and systems that result from those efforts.

tissue: Made of cells, it is any of the distinct types of materials that make up animals, plants or fungi. Cells within a tissue work as a unit to perform a particular function in living organisms. Different organs of the human body, for instance, often are made from many different types of tissues.

wave: A disturbance or variation that travels through space and matter in a regular, oscillating fashion.

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Synthetic biology aims to tackle disease and give cells superpowers - Science News Explores

Biology

Ecological determinants of Cope’s rule and its inverse | Communications Biology – Nature.com

We determine phylogenies using a process-based community-evolution model that describes changes in two adaptive traits, body size and ecological niche. Body size is a key functional trait with well-documented ecological implication (e.g.,ref.48), and adaptation of this trait alone enables the emergence of trophically structured communities44,46 (see also the reviewin ref.63). The similarity in ecological niche plays a fundamental complementary role in scaling species interactions, with interaction strengths naturally being maximized among individuals occupying the same niche. Accounting for this second trait in our model is a critical prerequisite for more complex processes of evolutionary diversification and, therefore, for the emergence of richer and more realistic community structures64. Below, we explain how these two traits jointly determine demographic dynamics and how gradual adaptive change over evolutionary time creates complex trophically structured ecological communities, complete with their specific phylogenetic histories.

We consider communities comprising (N) heterotrophic species designated by the indices (i=1,ldots ,N) that are interacting among each other and with one basal autotrophic resource designated by the index (i=0). The communitys species richness (N) is changing dynamically, through processes of extinction and speciation, as detailed below. Each species (i) is characterized by its population density ({x}_{i}) and two adaptive traits describing the average body size ({s}_{i}) and ecological niche ({n}_{i}) of its individuals. FollowingBrnnstrmet al.44, we express ({s}_{i}) in nondimensional logarithmic form as ({r}_{i}={{{{mathrm{ln}}}}}({s}_{i}/{s}_{0})), where ({s}_{0}) is the size of the basal autotrophic resource. While population densities and body sizes are necessarily non-negative, niche traits can take non-negative and negative values. We fix the otherwise arbitrary origin of the niche traits by assuming ({n}_{0}=0) for the basal autotrophic resource without loss of generality(.) All model parameters are shown in Table1 together with their default values.

The demographic dynamics of the (N) heterotrophic species (i=1,ldots ,N) and of the one basal autotrophic resource (i=0) are described by LotkaVolterra equations,

$$overbrace{frac{,{dot{x}}_{i}}{{x}_{i}}}^{{{{{{rm{Growth}}}}}}}= -overbrace{,d({r}_{i}),}^{{{{{{rm{Intrinsic}}}}}},{{{{{rm{mortality}}}}}}}+overbrace{mathop{sum }limits_{j=0}^{N}beta P({n}_{i},{n}_{j})p({r}_{i},{r}_{j})lambda exp ({r}_{j}-{r}_{i}){x}_{j}}^{{{{{{rm{Gains}}}}}},{{{{{rm{from}}}}}},{{{{{rm{predation}}}}}}}\ -overbrace{mathop{sum }limits_{j=1}^{N}beta P({n}_{j},{n}_{i})p({r}_{j},{r}_{i}){x}_{j}}^{{{{{{rm{Losses}}}}}},{{{{{rm{from}}}}}},{{{{{rm{predation}}}}}}}-overbrace{mathop{sum }limits_{j=1}^{N}alpha C({n}_{i},{n}_{j})c({r}_{i},{r}_{j}){x}_{j}}^{{{{{{rm{Losses}}}}}},{{{{{rm{from}}}}}},{{{{{rm{competition}}}}}}}$$

(1a)

and

$$overbrace{frac{,{dot{x}}_{0}}{{x}_{0}}}^{{{{{{rm{Growth}}}}}}}=+overbrace{,{g}_{0},}^{{{{{{rm{Intrinsic}}}}}},{{{{{rm{growth}}}}}}}-overbrace{mathop{sum }limits_{j=1}^{N}beta p({r}_{j},0)P({n}_{j},0){x}_{j}}^{{{{{{rm{Losses}}}}}},{{{{{rm{from}}}}}},{{{{{rm{predation}}}}}}}-overbrace{{x}_{0}/{K}_{0}}^{{{{{{rm{Losses}}}}}},{{{{{rm{from}}}}}},{{{{{rm{competition}}}}}}},$$

(1b)

where ({dot{x}}_{i}) denotes the rate at which the population density ({x}_{i}) changes. The terms on the right-hand side of Eq. (1a) are the per-capita rates of, for the heterotrophic species, intrinsic mortality, gains from predation, losses from predation, and losses from interference competition, respectively. Similarly, the terms on the right-hand side of Eq. (1b) are the per-capita rates of, for the basal autotrophic resource, intrinsic growth, losses from predation, and losses from competition, respectively. Gains can be realized through increased fecundity, reduced mortality, or a mixture of both, and, likewise, losses can be realized through reduced fecundity, increased mortality, or a mixture of both.

We consider a species to be extant as long as its population density exceeds the threshold (epsilon); conversely, if and when a species population density falls below this threshold, it is considered extinct and is removed from the community. The parameter (epsilon) can thus be interpreted as a measure of extinction risk resulting from sensitivity to demographic and environmental stochasticity.

The rate of intrinsic mortality and the intensities of predation and interference competition depend on the two adaptive traits. To reflect the energetic advantages of a larger body size over a smaller one, the intrinsic mortality rate is assumed to decline allometrically with the body size ({s}_{i}), and thus exponentially with the logarithmic body size ({r}_{i}), according to an exponent (q), whose value is suggested by Peters48 to equal ~0.25,

$$dleft({r}_{i}right)={d}_{0}{left({s}_{i}/{s}_{0}right)}^{-q}={d}_{0}exp (-q{r}_{i}).$$

(2a)

The intensities of predation and interference competition between individuals of two species (i) and (j) occupying the same niche, ({n}_{i}={n}_{j},) are determined by the ratio of their body sizes ({s}_{i}), and thus by the difference of their logarithmic body sizes ({r}_{i}). A predator of species (i) and logarithmic body size ({r}_{i}) forages on a prey of species (j) and logarithmic body size ({r}_{j}) at an intensity that is assumed to be maximized when their logarithmic body sizes differ by a value (mu) that is optimal for predation,

$$p({r}_{i},{r}_{j})=exp left(-tfrac{1}{2}{({r}_{i}-{r}_{j}-mu )}^{2}/{sigma }_{{{{{{rm{p}}}}}}}^{2}-tfrac{1}{4}{({r}_{i}-{r}_{j})}^{4}/{gamma }_{{{{{{rm{p}}}}}}}^{4}right).$$

(2b)

Similarly the intensity of interference competition between individuals of two species (i) and (j) occupying the same niche and having logarithmic body sizes ({r}_{i}) and ({r}_{j}) is assumed to be symmetrical and maximal for individuals of equal body size,

$$c({r}_{i},{r}_{j})=exp left(-tfrac{1}{2}{({r}_{i}-{r}_{j})}^{2}/{sigma }_{{{{{{rm{c}}}}}}}^{2}-tfrac{1}{4}{({r}_{i}-{r}_{j})}^{4}/{gamma }_{{{{{{rm{c}}}}}}}^{4}right).$$

(2c)

The intensities of predation and interference competition, respectively, between individuals of two species (i) and (j) occupying different niches, ({n}_{i}, ne , {n}_{j}), are reduced by factors described by functions that decline with increasing niche separation,

$$P({n}_{i},{n}_{j})=exp left(-tfrac{1}{2}{({n}_{i}-{n}_{j})}^{2}/{sigma }_{{{{{rm{P}}}}}}^{2}-tfrac{1}{4}{({n}_{i}-{n}_{j})}^{4}/{gamma }_{{{{{rm{P}}}}}}^{4}right)$$

(2d)

and

$$C({n}_{i},{n}_{j})=exp left(-tfrac{1}{2}{({n}_{i}-{n}_{j})}^{2}/{sigma }_{{{{{rm{C}}}}}}^{2}-tfrac{1}{4}{({n}_{i}-{n}_{j})}^{4}/{gamma }_{{{{{rm{C}}}}}}^{4}right).$$

(2e)

To ensure our results are robust when the functions above deviate from Gaussian shapes, we allow platykurtic functions in Eqs. (2c)(2e): specifically, the parameters ({gamma }_{{{{{rm{p}}}}}}), ({gamma }_{{{{{rm{c}}}}}}), ({gamma }_{{{{{rm{P}}}}}}), and ({gamma }_{{{{{rm{C}}}}}}) scale the quartic terms in the exponents above and hence the extent to which those functions are platykurtic, i.e., deviate from Gaussian shapes in the direction of more box-like shapes. Even slight degrees of platykurtosis are known to overcome the historically often overlooked structural instability caused by purely Gaussian functions in models of trait-mediated competition and thereby suffice to enable the ecologically and evolutionarily stable coexistence of phenotypically differentiated discrete species (e.g., refs. 65,66).

In summary, the combined effects of body size and ecological niche on predation and interference competition are given by the products (p({r}_{i},{r}_{j})P({n}_{i},{n}_{j})) and (c({r}_{i},{r}_{j})C({n}_{i},{n}_{j})), respectively, as shown in Eqs. (1).

The evolutionary dynamics of the adaptive traits are determined by the corresponding selection pressures (e.g., refs. 44,45). Writing (F({N;}{x}_{0},ldots ,{x}_{N};{s}_{0},ldots ,{s}_{N};{n}_{0},ldots ,{n}_{N})) for the right-hand side of Eq. (1a), we define the invasion fitness of an initially rare population with trait values ({s}^{{prime} }) and ({n{{hbox{'}}}}) in a community comprising the autotropic basal resource and (N) resident heterotrophic species with population densities ({x}_{0},ldots ,{x}_{N}) and trait values ({s}_{0},ldots ,{s}_{N}) and ({n}_{0},ldots ,{n}_{N}) as

$$f(N{{{{{rm{;}}}}}}x,s,n{{{{{rm{;}}}}}}{s}^{{prime}},{n}^{{prime}} )=mathop{{{{{mathrm{lim}}}}}}limits_{{x}^{{prime} }to 0+}Fleft(N+1{{{{{rm{;}}}}}}{x}_{0},ldots ,{x}_{N},{x}^{{prime} }{{{{{rm{;}}}}}}{s}_{0},ldots ,{s}_{N},{s}^{{prime} }{{{{{rm{;}}}}}}{n}_{0},ldots ,{n}_{N},{n}^{{prime} }right),$$

(3a)

where (x=({x}_{0},ldots ,{x}_{N})), (s=({s}_{0},ldots ,{s}_{N})), and (n=({n}_{0},ldots ,{n}_{N})).

We solve the (N+1) demographic equations in Eqs. (1) alongside (2N) evolutionary equations, one for each trait in each species,

$${dot{s}}_{i}={varepsilon }_{{{{{{rm{s}}}}}}}{left.frac{partial fleft(N{{{{{rm{;}}}}}}x,s,n{{{{{rm{;}}}}}}s^{prime} ,n^{prime} right)}{partial s^{prime} }right|}_{{s}^{{prime} }={s}_{i},{n}^{{prime} }={n}_{i}}$$

(3b)

and

$${dot{n}}_{i}={varepsilon }_{{{{{{rm{n}}}}}}}{left.frac{partial fleft(N{{{{{rm{;}}}}}}x,s,n{{{{{rm{;}}}}}}s^{prime} ,n^{prime} right)}{partial n^{prime} }right|}_{{s}^{{prime} }={s}_{i},{n}^{{prime} }={n}_{i}},$$

(3c)

where ({varepsilon }_{{{{{{rm{s}}}}}}}) and ({varepsilon }_{{{{{{rm{n}}}}}}}) scale the rates of evolutionary change. We assume ({varepsilon }_{{{{{{rm{s}}}}}}}) and ({varepsilon }_{{{{{{rm{n}}}}}}}) to be so small that body sizes and ecological niches are evolving slowly relative to the demographics dynamics.

Evolution of the adaptive traits under directional selection proceeds according to Eqs. (3) until a local fitness minimum is encountered in one or more of the heterotrophic species and selection thus turns disruptive. Specifically, we test whether the magnitudes of the selection pressures, i.e., of the derivatives in Eqs. (3b) and (3c), fall below a prescribed threshold for both adaptive traits. If and when the underlying extremum in a species invasion-fitness landscape given by Eq. (3a) happens to be a minimum, the species is replaced with two species with trait values shifted a fixed distance toward either side of the fitness minimum along the direction of steepest increase (i.e., highest curvature) of invasion fitness, in a process intended to mimic ecological speciation67,68.

Further information on research design is available in theNature Portfolio Reporting Summary linked to this article.

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Ecological determinants of Cope's rule and its inverse | Communications Biology - Nature.com

Biology

New Evolution Theory Explains Why Animals Shrink Over Time – SciTechDaily

A recent study uncovers the factors influencing animal size changes over time, identifying three evolutionary patterns based on competition and environmental pressures, providing clarity on the inconsistencies in fossil records. Credit: SciTechDaily.com

New research reveals key factors behind the changing sizes of certain animals over time, challenging traditional evolutionary theories with its findings on species size variations.

The mystery behind why Alaskan horses, cryptodiran turtles, and island lizards shrunk over time may have been solved in a new study.

The new theoretical research proposes that animal size over time depends on two key ecological factors: the intensity of direct competition for resources between species, and the risk of extinction from the environment.

Using computer models simulating evolution, the study, published today (Thursday, January 18) in the journal Communications Biology, identifies why some species gradually get smaller, as indicated by fossil records.

Dr. Shovonlal Roy, an ecosystem modeler from the University of Reading who led the research, said: Just like how we try to adapt to hot or cold weather depending on where we live, our research shows animal size can get bigger or smaller over long periods depending on the habitat or environment.

In places and times where theres lots of competition between different species for food and shelter, animal sizes often get smaller as the species spread out and adapt to the distribution of resources and competitors. For example, small horses that lived in Alaska during the Ice Age rapidly shrank due to changes in the climate and vegetation.

Where direct competition is less, sizes tend to get bigger, even though being really big and few in number can make animals more vulnerable to dying out such as what happened with the dinosaurs.

Changes in ecological factors help explain why fossil records shows such confusing mixes of size evolution patterns, with some lineages shrinking over time and others growing.

The research team carried out their study by challenging the contradictions fossil evidence posed to Copes rule. Copes rule refers to the tendency for certain animal groups to evolve larger body sizes over thousands and millions of years. The rule is named after Edward Cope, a 19th-century paleontologist who was credited to have first noticed this pattern in the fossil record. For example, early horse ancestors were small dog-sized animals that increased in size over evolutionary time, ultimately producing the modern horse.

However, fossil evidence shows remarkably conflicting trends, with increased size in some groups but decreased size in others.

Using computer models simulating evolution, the study identified three distinct patterns of body-size change emerging under different conditions:

Reference: Ecological determinants of Copes rule and its inverse 18 January 2024, Communications Biology. DOI: 10.1038/s42003-023-05375-z

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New Evolution Theory Explains Why Animals Shrink Over Time - SciTechDaily