Friday, January 27, 2023

Study offers new insight on what ancient noses smelled

Scientists compare humans' extinct genetic relatives to present-day people

Peer-Reviewed Publication

UNIVERSITY OF ALASKA FAIRBANKS

Neanderthal woman 

IMAGE: A RECONSTRUCTION OF A NEANDERTHAL WOMAN view more 

CREDIT: <A HREF="HTTPS://COMMONS.WIKIMEDIA.ORG/WIKI/FILE:RECONSTRUCTION_OF_NEANDERTHAL_WOMAN.JPG">BACON CPH</A>, <A HREF="HTTPS://CREATIVECOMMONS.ORG/LICENSES/BY/2.5">CC BY 2.5</A>, VIA WIKIMEDIA COMMONS

It sounds a little like Stone Age standup: A Denisovan and a human walk past a bees’ nest heavy with honeycomb. What happens next?

According to a study led by University of Alaska Fairbanks biological anthropologist Kara C. Hoover and Universite Paris-Saclay biochemist Claire de March, the Denisovan, with the species’ greater sensitivity to sweet smells, may have immediately homed in on the scent and beat the human to a high-energy meal.

"This research has allowed us to draw some larger conclusions about the sense of smell in our closest genetic relatives and understand the role that smell played in adapting to new environments and foods during our migrations out of Africa,” said Hoover, a professor in the Department of Anthropology at UAF.

A paper on the research, recently published in iScience, was written by collaborators from UAF, Duke University, Universite Paris-Saclay, Tokyo University of Agriculture and Technology, and the University of Manchester. The study investigated whether humans share a sense of smell with their now-extinct Denisovan and Neanderthal cousins, who left Africa about 750,000 years ago. Contemporary humans left Africa about 65,000 years ago.

To recreate the noses of our extinct genetic relatives and compare them to those of present-day people, the research team used publicly available genome sequences from multiple Neanderthals, one Denisovan and one ancient human. They used data from the 1000 Genomes project to represent modern humans.

They then compared 30 olfactory receptor genes from each group. The team found that 11 of the receptors had some novel mutations present only in extinct lineages. In the largest study of its kind to date, the team created laboratory versions of those 11 olfactory receptors and then exposed them to hundreds of odors at different concentrations. 

When the receptors detected an odor, they literally lit up. The speed and brightness of the luminescence told the scientists whether, how soon and to what degree each “nose” could smell the odors. While the receptors could detect the same things as modern humans, they differed in sensitivity to many of the odors.

“We literally reproduced an event that hadn’t happened since the extinction of Denisova and Neanderthal 30,000 years ago: an extinct odorant receptor responding to an odor in cells on a lab bench,” de March said. “This took us closer to understanding how Neanderthal and Denisova perceived and interacted with their olfactory environment.”

Neanderthals, who lived in Eurasia between 430,000 and 40,000 years ago, had the poorest sense of smell. For example, the Neanderthal from the Chagyrskaya Cave couldn’t detect the sex steroid androstadienone, which smells something like sweat and urine. That may have been useful, Hoover said, given that they were trapped in close quarters in caves during glacial maximums, when the ice sheets from the poles expanded southward and made many areas uninhabitable.

Denisovans have left behind less physical evidence than Neanderthals. They are known mostly from modern-day Siberia, where remains in the Denisova Cave were dated to between 76,200 and 51,600 years ago. Denisovans were generally more sensitive to odors than humans and much more sensitive than Neanderthals. They were most responsive to sweet and spicy smells like honey, vanilla, cloves and herbs. That trait could have helped them find high-calorie food.

Present-day humans fell somewhere in the middle.

“This is the most exciting research I have ever been involved in,” said co-author Matthew Cobb from the University of Manchester. “It shows how we can use genetics to peer back into the sensory world of our long-lost relatives, giving us insight into how they will have perceived their environment and, perhaps, how they were able to survive.”

In many species, olfactory receptors have been linked to their ecological and dietary needs.

"Each species must evolve olfactory receptors to maximize their fitness for finding food," said co-author Hiroaki Matsunami in a Duke University news release. "In humans, it's more complicated because we eat a lot of things. We're not really specialized."

Smell is integral to the human story, Hoover said. “Such a strongly overlapping olfactory repertoire suggests that our generalist approach to smelling has enabled us to find new foods when migrating to new places — not just us but our cousins who left Africa much earlier than us!”

 

Astral alchemy

Researchers at Osaka University participate in a particle accelerator experiment that creates an exotic, highly unstable particle and measures its mass, which may help explain the interior of ultra-dense neutron stars

Peer-Reviewed Publication

OSAKA UNIVERSITY

Fig. 1 

IMAGE: THE EXOTIC BARYON CALLED Λ(1405) AND A SCHEMATIC ILLUSTRATION OF THE EVOLUTION OF MATTER view more 

CREDIT: HIROYUKI NOUMI

Osaka, Japan – The Standard Model of particle physics tells us that most particles we observe are made up of combinations of just six types of fundamental entities called quarks. However, there are still many mysteries, one of which is an exotic, but very short-lived, Lambda resonance known as Λ(1405). For a long time, it was thought to be a particular excited state of three quarks—up, down, and strange—and understanding its internal structure may help us learn more about the extremely dense matter that exists in neutron stars.

Now, investigators from Osaka University were part of a team that succeeded in synthesizing Λ(1405) for the first time by combining a K- meson and a proton and determining its complex mass (mass and width). The K meson is a negatively charged particle containing a strange quark and an up antiquark. The much more familiar proton that makes up the matter that we are used to has two up quarks and a down quark. The researchers showed that Λ(1405) is best thought of as a temporary bound state of the K- meson and the proton, as opposed to a three-quark excited state.

In a study published recently in Physics Letters B, the group describe the experiment they carried out at the J-PARC accelerator. K mesons were shot at a deuterium target, each of which had one proton and one neutron. In a successful reaction, a K meson kicked out the neutron, and then merged with the proton to produce the desired Λ(1405). “The formation of a bound state of a K- meson and a proton was only possible because the neutron carried away some of the energy,” says an author of the study, Kentaro Inoue One of the aspects that had been perplexing scientists about Λ(1405) was its very light overall mass, even though it contains a strange quark, which is nearly 40 times as heavy as an up quark. During the experiment, the team of researchers was able to successfully measure the complex mass of Λ(1405) by observing the behavior of the decay products.

“We expect that progress in this type of research can lead to a more accurate description of ultra-high-density matter that exists in the core of a neutron star.” says Shingo Kawasaki, another study author. This work implies that Λ(1405) is an unusual state consisting of four quarks and one antiquark, making a total of 5 quarks, and does not fit the conventional classification in which particles have either three quarks or one quark and one antiquark. This research may lead to a better understanding of the early formation of the Universe, shortly after the Big Bang, as well as what happens when matter is subject to pressures and densities well beyond what we see under normal conditions.

###

The article, “Pole position of Λ(1405) measured in d(K,n)πΣ reactions,” was published in Physics Letters B at DOI: https://doi.org/10.1016/j.physletb.2022.137637.

The current work was performed by an international research collaboration, E31, involving scientists from Research Center for Nuclear Physics (RCNP), Osaka University together with RIKEN, KEK, JAEA, J-PARC, Tohoku University, INFN (Italy), SMI (Austria) and others.

  

Schematic illustration of the reaction used to synthesize Λ(1405) by fusing a K- (green circle) with a proton (dark blue circle), which takes place inside a deuteron nucleus

CREDIT

Hiroyuki Noumi

Fig. 3 (IMAGE)

OSAKA UNIVERSITY


Research representives:

Prof. Hiroyuki Noumi, RCNP, Osaka University/IPNS, KEK

Dr. Fuminori Sakuma, RIKEN Cluster for Pioneering Research, RIKEN

Dr. Tadashi Hashimoto, Advanced Science Research Center, JAEA

Prof. Hiroaki Ohnish, Research Center for Electron Photon Science, Tohoku University

Prof. Catalina Curceanu, Laboratori Nazionali di Frascati, INFN

Prof. Johannes Zmeskal, Stefan-Mayer-Institut für subatomare Physik

About Osaka University

Osaka University was founded in 1931 as one of the seven imperial universities of Japan and is now one of Japan's leading comprehensive universities with a broad disciplinary spectrum. This strength is coupled with a singular drive for innovation that extends throughout the scientific process, from fundamental research to the creation of applied technology with positive economic impacts. Its commitment to innovation has been recognized in Japan and around the world, being named Japan's most innovative university in 2015 (Reuters 2015 Top 100) and one of the most innovative institutions in the world in 2017 (Innovative Universities and the Nature Index Innovation 2017). Now, Osaka University is leveraging its role as a Designated National University Corporation selected by the Ministry of Education, Culture, Sports, Science and Technology to contribute to innovation for human welfare, sustainable development of society, and social transformation.

Website: https://resou.osaka-u.ac.jp/e

Conservation Research: Sustaining flamingo populations – size matters

Flocking flamingos in groups of 50 or more may be one key to encouraging successful reproduction

Peer-Reviewed Publication

SPECIES360

Flamingo study results infographic 

IMAGE: FLAMINGO STUDY RESULTS INFOGRAPHIC view more 

CREDIT: DR. ANDREW MOONEY

Flocking flamingos in groups of 50 or more may be one key to encouraging successful reproduction, according to a study published this month in Zoo Biology. Researchers used global data shared by zoos and aquariums to study reproductive success and factors such as climate, flock numbers, and an equal sex ratio in four species of flamingo in 540 ex situpopulations worldwide. The zoos and aquariums curate data on groups of flamingos using the Zoological Information Management System (ZIMS) provided by the nonprofit Species360.

The open-access paper in Zoo Biology looks at strategies for encouraging reproductive success in ex situ populations of flamingos, or flamingos living in zoological institutions like wildlife refuges, zoos, and aquariums. Population managers across the national and regional zoo and aquarium associations as well as other organizations, can use this information to provide guidelines for protecting and sustaining flamingo populations.

The Conservation Science Alliance (CSA),and University of Southern Denmark data analysts and population management scholars, collaborated with lead researcher Dr. Andrew Mooney, Conservation and Research Officer at Dublin Zoo, and former Ph.D. student of the CSA, who graduated from Trinity College Dublin, to complete the study.

Applying modern analytics to ZIMS data, the team found that, to encourage reproduction and sustain populations, ex situ flamingo flocks should be as large as 50 –100 individuals and consist of an even sex ratio. Additionally, adding new individuals to a flock can sometimes seemingly spice things up and increase reproductive success, while climatic variables play a limited role.

Dr. Johanna Stärk, study co-author and researcher with University of Southern Denmark and the Species360 Conservation Science Alliance, said: “High quality data collected by Species360 members worldwide is critical for improving our understanding of what animals under human care need. At the Species360 Conservation Science Alliance, we aim to transform ZIMS data into real-world recommendations by working in close collaboration with researchers and species experts. This study is an excellent example of such a successful collaboration that could lead to more sustainable population management and improve global conservation efforts for flamingos.”

Describing the approach, lead researcher Dr. Andrew Mooney says:

“We utilized current and historic zoological records from Species360 member institutions to investigate how flock size and structure influence reproductive success in captive flamingos. We combined demographic data with high resolution global climatic data within the same statistical modeling framework to gain a more complete view of the determinants of reproductive success in captive flamingo populations, while also revealing temporal trends in institutional flock sizes.”

Dr. Mooney continues, “This has been seen first-hand at Dublin Zoo, where we have found that adding new birds to our Chilean flamingo flock stimulated reproduction in the subsequent year, while rainfall had little impact."

For more information, read the full study: onlinelibrary.wiley.com/doi/full/10.1002/zoo.21753

Red algae-derived metal-polysaccharide shows promise for anti-microbial applications because of its long and dense spikes

Peer-Reviewed Publication

BEN-GURION UNIVERSITY OF THE NEGEV

BEER-SHEVA, Israel, January 26, 2023 – Antibiotic resistant bacteria are becoming more and more of a concern as traditional sources of anti-microbial treatments become less effective. Therefore, researchers at Ben-Gurion University of the Negev are looking farther afield for promising compounds to treat wounds and infections.

Prof. Shoshana (Mails) Arad and Prof. Ariel Kushmaro, Prof. Levi A. Gheber and PhD. student Nofar Yehuda joined a metal and a polysaccharide together and discovered the new compound worked well against bacteria and fungus (Candida albicans) because of the longer and denser spikes on its surface that poked holes in the membrane and killed off the bacteria and the fungus.

"A polysaccharide is a carbohydrate with linked sugar molecules and by adding a metal (Cu), we were able to create an effective new material," according to the researchers.

Their findings were published recently in the peer-reviewed journal Marine Drugs as the new compound is derived from marine red microalga Porphyridium sp.

Commercialization of these new compounds could come sooner rather than later.

"In light of the increased resistance to antibiotic and antifungal agents, there is a growing need for the development of new and improved treatments. BGN Technologies holds a patent application ready for licensing in the field," say BGN's Galit Mazooz-Perlmuter and Anat Shperberg Avni. BGN Technologies is Ben-Gurion University's technology transfer company.

The research was conducted by Prof. Shoshana (Mails) Arad, Prof. Kushmaro and PhD. student Nofar Yehuda, as well as Prof. Levi A. Gheber. Prof. Shoshana (Mails) Arad is from the Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Prof. Kushmaro is a member of the Goldman-Sonnenfeldt School of Sustainability and Climate Change and the Avram and Stella Goldstein-Goren Department of Biotechnology Engineering. Prof. Gheber is a member of the same department as well as The Ilse Katz Institute for Nanoscale Science and Technology.

RaiBo - a versatile robo-dog runs through the sandy beach at 3 meters/sec

Peer-Reviewed Publication

THE KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY (KAIST)

Photo 1 

IMAGE: PHOTO 1. RAI LAB TEAM WITH PROFESSOR HWANGBO IN THE MIDDLE OF THE BACK ROW. view more 

CREDIT: KAIST ROBOTICS & ARTIFICIAL INTELLIGENCE LAB.

KAIST (President Kwang Hyung Lee) announced on the 25th that a research team led by Professor Jemin Hwangbo of the Department of Mechanical Engineering developed a quadrupedal robot control technology that can walk robustly with agility even in deformable terrain such as sandy beach.

< Photo. RAI Lab Team with Professor Hwangbo in the middle of the back row. >

Professor Hwangbo's research team developed a technology to model the force received by a walking robot on the ground made of granular materials such as sand and simulate it via a quadrupedal robot. Also, the team worked on an artificial neural network structure which is suitable in making real-time decisions needed in adapting to various types of ground without prior information while walking at the same time and applied it on to reinforcement learning. The trained neural network controller is expected to expand the scope of application of quadrupedal walking robots by proving its robustness in changing terrain, such as the ability to move in high-speed even on a sandy beach and walk and turn on soft grounds like an air mattress without losing balance.

This research, with Ph.D. Student Soo-Young Choi of KAIST Department of Mechanical Engineering as the first author, was published in January in the Science Robotics. (Paper title: Learning quadrupedal locomotion on deformable terrain).

Reinforcement learning is an AI learning method used to create a machine that collects data on the results of various actions in an arbitrary situation and utilizes that set of data to perform a task. Because the amount of data required for reinforcement learning is so vast, a method of collecting data through simulations that approximates physical phenomena in the real environment is widely used.

In particular, learning-based controllers in the field of walking robots have been applied to real environments after learning through data collected in simulations to successfully perform walking controls in various terrains.

However, since the performance of the learning-based controller rapidly decreases when the actual environment has any discrepancy from the learned simulation environment, it is important to implement an environment similar to the real one in the data collection stage. Therefore, in order to create a learning-based controller that can maintain balance in a deforming terrain, the simulator must provide a similar contact experience.

The research team defined a contact model that predicted the force generated upon contact from the motion dynamics of a walking body based on a ground reaction force model that considered the additional mass effect of granular media defined in previous studies.

Furthermore, by calculating the force generated from one or several contacts at each time step, the deforming terrain was efficiently simulated.

The research team also introduced an artificial neural network structure that implicitly predicts ground characteristics by using a recurrent neural network that analyzes time-series data from the robot's sensors.

The learned controller was mounted on the robot 'RaiBo', which was built hands-on by the research team to show high-speed walking of up to 3.03 m/s on a sandy beach where the robot's feet were completely submerged in the sand. Even when applied to harder grounds, such as grassy fields, and a running track, it was able to run stably by adapting to the characteristics of the ground without any additional programming or revision to the controlling algorithm.

In addition, it rotated with stability at 1.54 rad/s (approximately 90° per second) on an air mattress and demonstrated its quick adaptability even in the situation in which the terrain suddenly turned soft.

The research team demonstrated the importance of providing a suitable contact experience during the learning process by comparison with a controller that assumed the ground to be rigid, and proved that the proposed recurrent neural network modifies the controller's walking method according to the ground properties.

The simulation and learning methodology developed by the research team is expected to contribute to robots performing practical tasks as it expands the range of terrains that various walking robots can operate on.

The first author, Suyoung Choi, said, “It has been shown that providing a learning-based controller with a close contact experience with real deforming ground is essential for application to deforming terrain.” He went on to add that “The proposed controller can be used without prior information on the terrain, so it can be applied to various robot walking studies.”

This research was carried out with the support of the Samsung Research Funding & Incubation Center of Samsung Electronics.

< Figure 1. Adaptability of the proposed controller to various ground environments. The controller learned from a wide range of randomized granular media simulations showed adaptability to various natural and artificial terrains, and demonstrated high-speed walking ability and energy efficiency. >

  

Figure 1. Adaptability of the proposed controller to various ground environments. The controller learned from a wide range of randomized granular media simulations showed adaptability to various natural and artificial terrains, and demonstrated high-speed walking ability and energy efficiency.

CREDIT

KAIST Robotics & Artificial Intelligence Lab.

< Figure 2. Contact model definition for simulation of granular substrates. The research team used a model that considered the additional mass effect for the vertical force and a Coulomb friction model for the horizontal direction while approximating the contact with the granular medium as occurring at a point. Furthermore, a model that simulates the ground resistance that can occur on the side of the foot was introduced and used for simulation. >

Photo 2. RaiBo in a beach run

CREDIT

KAIST Robotics & Artificial Intelligence Lab.

Figure 2. Contact model definition. (A) The terrain model predicts a vertical component of a ground reaction force based on the intruder’s penetration depth and velocity. The calculation involves the developing granular cone beneath the intruder, as Aguilar et al. (27) proposed. (B) The surface contact between the intruder and the adjacent substrates is approximated as a point contact at the deepest point. The bulk tangential force from the substrates is assumed to be Coulomb friction. (C) The horizontal stroke resistive force model is introduced to simulate the reaction from the substrates when the intruder moves horizontally in the substrates. The force is computed based on the travel distance dHSR and the current penetration depth zt.

CREDIT

KAIST Robotics & Artificial Intelligence Lab.

Artificial intelligence for soil health

Grant and Award Announcement

AARHUS UNIVERSITY

Soils are under pressure from current farming practices, and the challenges are only increasing with the growing demand for food production. Threats to soil health include loss of organic matter, loss of biodiversity, soil compaction from large machinery and, not least, loss of soil itself due to erosion.

"We are at a crossroad; we need to do something if we are to preserve European and global soil resources. It is a paradox that on the one hand soil is part of the solution to reduce greenhouse gas emissions, and at the same time 60-70% of Europe's soil is not doing well. It is therefore imperative that we have better monitoring of soil quality," says Professor Mogens H. Greve from the Department of Agroecology.

Ambitious climate goals cannot be achieved without increased focus on soil

Similar to the ambitious Danish climate targets, the European Commission has set several concrete goals to prevent further soil degradation and to combat climate change. The targets include zero emissions and the planting 3 billion trees by 2030.

"By 2028, all land managers should have access to verified data on CO2 emissions and removals. In addition, the ambition is for agriculture to have an increased focus on carbon storage and thereby contribute to meeting the 2030 target of a reduction in climate impact of 310 million tonnes CO2eq for the entire soil sector in the EU," explains Mogens H. Greve.

To succeed in improving soil health across Europe and meet the ambitious targets, methods are needed to measure and assess progress towards healthier soils. This is where the Horizon Europe project AI4SoilHealth comes into play. The aim is to support the EU's Soil Health & Food Mission to achieve the goals set out in the EU Soil Strategy 2030.

"We will develop and maintain a digital infrastructure with free access across Europe. The aim is that the infrastructure will be used to assess and continuously monitor soil health in relation to its management," says Professor Lis W. de Jonge, also from the Department of Agroecology at Aarhus University.

Artificial intelligence rhymes with soil 

The kind of artificial intelligence the researchers will be working with includes software and big data solutions that can improve and automate decision-making systems. Artificial intelligence can be used for many things in soil science. Soil analysis, remote sensing, and soil mapping are just a few examples.

"In this project, we will use artificial intelligence more systematically to assess soil datasets and measurements, so that we can build an automated data-driven decision support system for European soils. We propose to develop an indicator framework that can provide new and untapped opportunities for monitoring soil properties. AI4SoilHealth will use a pan-European soil monitoring system called LUCAS along with remote sensing and soil observations to improve soil health," says Lis W. de Jonge.

The expectation is that AI4SoilHealth will create:

  • a method to calculate a soil health index
  • a toolbox for rapid soil health assessment
  • AI4SoilHealth data for the whole of Europe
  • Soil health monitoring 
  • An AI4SoilHealth app

"Our goal with AI4SoilHealth is to create an effective soil health certification system that can be used by farmers, landowners and not least policy makers in the context of the new Green Deal for Europe," says Mogens H. Greve.

More about the project

CollaboratorsAarhus University, OpenGeoHub Foundation, UK Center for Ecology and Hydrology, Soil Association, Planet Labs, IIASA, Institute of Geo-Hydroinformatics at TUHH, University of Zagreb, Stockholm University, Aalborg University, Thünen Institue of Climate-Smart Agriculture, Universitá degli studi Roma Tre, NEIKER, University of Aberdeen, Max Planck Institute of Biogeochemistry, Basel University, ETH Zurich, Bern University for Applied Sciences, Aristotle University of Thessaloniki, Natural Resources Institute Finland (Luke), INRAE, Sorbonne University, ISINNOVA, Institute for Soil Sciences at ATK, MultiOne, Digit Soil and Sustinn
FundingHORIZON-MISS-2021-SOIL-02-02-02 – HORIZON-RIA
Amount granted13.789.328 EUR
Project periodJanuary 2023 – December 2026
Read moreYou can read more about AI4SoilHealth here
ContactProfessor Mogens H. Greve, Department of Agroecology, Aarhus University. Tel.: +45 20726734 or mail greve@agro.au.dk