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Genetic tracing at the Huanan Seafood market further supports COVID animal origins

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Genetic tracing at the Huanan Seafood market further supports COVID animal origins


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Credit: CC0 Public Domain

A new international collaborative study provides a list of the wildlife species present at the market from which SARS-CoV-2, the virus responsible for the COVID-19 pandemic, most likely arose in late 2019. The study is based on a new analysis of metatranscriptomic data released by the Chinese Center for Disease Control and Prevention (CDC).

The data come from more than 800 samples collected in and around the Huanan Seafood Wholesale market beginning on January 1, 2020, and from viral genomes reported from early COVID-19 patients. The research appears September 19 in the journal Cell.

“This is one of the most important datasets that exists on the origin of the COVID-19 pandemic,” says co-corresponding author Florence Débarre of the French National Center for Scientific Research (CNRS). “We’re extremely grateful that the data exist and were shared.”

“This paper adds another layer to the accumulating evidence that all points to the same scenario: that infected animals were introduced into the market in mid- to late November 2019, which sparked the pandemic,” says co-corresponding author Kristian Andersen of Scripps Research.

“We have analyzed, in new and rigorous ways, the vitally important data that the Chinese CDC team collected,” says co-corresponding author Michael Worobey of the University of Arizona. “This is an authoritative analysis of that data and how it fits in with the rest of the huge body of evidence we have about how the pandemic started.”

On January 1, 2020, after the animals were removed and just hours after the market was closed, investigators from the Chinese CDC went to the market to collect samples. They swabbed the floors, walls, and other surfaces of the stalls; they came back days later to focus on surfaces in stalls selling wildlife, such as a cage and carts used to move animals, and then also collected samples from the drains and sewers.

They performed metatranscriptomic sequencing of the samples, a technique aiming to obtain all RNA sequences (and which can pick up DNA as well) from all organisms present in the samples—viruses, bacteria, plants, animals, humans. The Chinese CDC team, led by Liu Jun, published their data and results in 2023 in the journal Nature.

However, the article left unresolved the exact identities of the animal species found in the data that could represent plausible intermediate hosts. The Chinese CDC shared their sequencing data on public and open repositories.

According to the latest analysis of the data being published in Cell, SARS-CoV-2 was present in some of the same stalls as wildlife sold at the market—including raccoon dogs (small fox-like animals with markings similar to raccoons) and civet cats (small carnivorous mammals related to mongooses and hyenas).

In some cases, genetic material from the SARS-CoV-2 virus and these animals was even found on the same swabs. The exact animal species were identified by genotyping their mitochondrial genomes in the samples.

“Many of the key animal species had been cleared out before the Chinese CDC teams arrived, so we can’t have direct proof that the animals were infected,” Débarre says. “We are seeing the DNA and RNA ghosts of these animals in the environmental samples, and some are in stalls where SARS-CoV-2 was found too. This is what you would expect under a scenario in which there were infected animals in the market.”

“These are the same sorts of animals that we know facilitated the original SARS coronavirus jumping into humans in 2002,” Worobey adds. “This is the most risky thing we can do—take wild animals that are teeming with viruses and then play with fire by bringing them into contact with humans living in the heart of big cities, whose population densities make it easy for these viruses to take hold.”

The international team also performed evolutionary analysis of the earliest viral genomes reported in the pandemic, including these environmental sequences, and inferred the most likely progenitor genotypes of the virus that infected humans and led to the COVID-19 pandemic.

The results imply that there were very few, if any, humans infected prior to the market outbreak. This is consistent with spillovers from animals to humans within the market. There may also have been spillovers of limited impact in the immediate upstream animal trade.

“In this paper, we show that the sequences linked to the market are consistent with a market emergence,” Débarre says. “The main diversity of SARS-CoV-2 was in the market from the very beginning.”

The new study landed on a short list of animal species in the wet market found co-occurring or close to viral samples that could represent the most likely intermediate hosts for SARS-CoV-2. The common raccoon dog, a species susceptible to SARS-CoV-2 and that carried SARS-CoV in 2003, was found to be the most genetically abundant animal in the samples from market wildlife stalls.

Genetic material from masked palm civets, which were also associated with the earlier outbreak of SARS-CoV, was also found in a stall with SARS-CoV-2 RNA. Other species such as the Hoary bamboo rat and Malayan porcupines were also found to be present in SARS-CoV-2-positive samples, as well as a multitude of other species.

While the data cannot prove whether one or more of these animals may have been infected, the team’s analyses provide a clear list of the species that most plausibly could have carried the virus and genetic information that could be used to help trace where they originated.

The investigators stress the importance of understanding the origins of the COVID-19 pandemic, especially in light of other recent spillovers, such as the spread of avian flu viruses in cattle in the United States. “There has been a lot of disinformation and misinformation about where SARS-CoV-2 originated,” Worobey says.

“The reason it’s so important to find out is that this affects national security and public health, not just in the United States but around the world. And the truth is, since the pandemic started more than four years ago, although there has been an increased focus on lab safety, not much has been done to decrease the chance of a zoonotic scenario like this happening again.”

More information:
Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic, Cell (2024). DOI: 10.1016/j.cell.2024.08.010. www.cell.com/cell/fulltext/S0092-8674(24)00901-2

Citation:
Genetic tracing at the Huanan Seafood market further supports COVID animal origins (2024, September 19)
retrieved 19 September 2024
from https://phys.org/news/2024-09-genetic-huanan-seafood-covid-animal.html

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COVID-19 job losses impacted early withdrawal from retirement accounts: Study

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COVID-19 job losses impacted early withdrawal from retirement accounts: Study


savings
Credit: Unsplash/CC0 Public Domain

Having a robust emergency savings fund could help people weather financial shocks, such as job loss during the COVID-19 pandemic, finds a new study from the Brown School at Washington University in St. Louis.

“We found that for individuals who lost jobs, those with at least three months’ worth of emergency savings were significantly less likely to tap into their retirement savings early,” said Haotian Zheng, a Ph.D. candidate and lead author of an article published this month in the Journal of Consumer Affairs.

“Ultimately, this study emphasizes the importance of emergency savings in helping workers stay financially resilient during crises,” Zheng said. “Building and maintaining a sufficient emergency savings can help people protect their long-term financial security by reducing the need for premature withdrawals from retirement accounts during periods of unexpected income loss.”

Researchers, including Stephen Roll, an assistant professor at the Brown School, surveyed 2,923 respondents; 60% of the baseline data were collected in April 2020, during which the unemployment rate peaked at 14.4%.

Twenty percent of those in the sample experienced a job loss, and 10% were forced to withdraw money from their retirement savings.

Overall, the study points out the need for workers to plan ahead financially, Zheng said.

“This study suggests that in the event of another pandemic or large-scale economic disruption, workers without sufficient emergency savings and/or financial knowledge could be at a higher risk of making less desirable financial decisions, such as withdrawing from retirement accounts prematurely,” he said.

Employers’ role

Businesses and organizations can play a role in helping their workers prepare for future hardship, the researchers said.

“Employers could offer structured emergency savings programs, automatic payroll deductions or matching contributions to make it easier for workers to accumulate savings,” Roll said.

“By supporting these savings efforts, employers can help safeguard their employees’ financial well-being, which in turn fosters a more secure workforce, ultimately benefiting both the individuals and the organization.”

Employment is one of the most important institutions in determining financial security, particularly during times of crisis.

“Given that personal savings rates are often low, relying solely on individual efforts to save for emergencies may not be sufficient or ideal,” Zheng said. “Institutional efforts, such as employer-driven initiatives, are likely to be more effective in helping workers build the necessary financial buffer.”

More information:
Haotian Zheng et al, Job loss during COVID‐19 on early retirement withdrawals: A moderated‐mediation analysis, Journal of Consumer Affairs (2024). DOI: 10.1111/joca.12598

Citation:
COVID-19 job losses impacted early withdrawal from retirement accounts: Study (2024, September 19)
retrieved 19 September 2024
from https://phys.org/news/2024-09-covid-job-losses-impacted-early.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.





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Aversion to inequality drives support for redistribution policies, study finds

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Aversion to inequality drives support for redistribution policies, study finds


Aversion to inequality drives support for redistribution policies
Association between inequality aversion and support for redistribution. Panels A and B show the effect of advantageous inequality aversion. Panels C and D indicate the effects of disadvantageous inequality aversion. Credit: Proceedings of the National Academy of Sciences (2024). DOI: 10.1073/pnas.2401445121

As income inequality widens, debates around redistribution policies are heating up. New research from the Universities of Zurich, Lille and Copenhagen reveals that support for these policies stems not only from individuals’ financial situations but also from an inherent aversion to inequality.

This finding, published in an article in the Proceedings of the National Academy of Sciences, offers valuable insights into predicting public support for future redistribution policies.

Traditional economic theories assume that individuals only care about their own income when it comes to supporting redistribution policies. However, an international team of researchers from the University of Zurich (UZH), the University of Lille and the University of Copenhagen now challenges this view.

The results of their study show that people’s preferences towards inequality per se play a major role. “By taking into account how much people dislike inequality, we can better predict who will support policies aimed at reducing the income gap,” says Ernst Fehr, corresponding author and director of the UBS Center for Economics in Society at the Department of Economics at UZH.

Attitudes towards inequality vary

People’s aversion to inequality comes in two forms: While some dislike being worse off than others, known as “disadvantageous inequality aversion,” others dislike the existence of poorer individuals, termed “advantageous inequality aversion.” These attitudes vary widely among people, and the understanding of how these preferences shape political support for redistribution policies remains limited.

In the study involving roughly 9,000 Danish participants aged 20 to 64, the researchers measured individuals’ aversion to inequality with a behavioral experiment.

They then linked the results to individuals’ support for politically enforced income redistribution, i.e., policies that reduce income differences, and for charitable giving through documented real-life charitable donations that reveal their private redistribution preferences.

Inequality aversion influences support for redistribution

“Our empirical results show that people who have a stronger dislike of both advantageous and disadvantageous inequality are more likely to support political redistribution,” says Fehr.

However, when it comes to charitable giving, those with a stronger dislike of advantageous inequality are more generous while those with a stronger aversion for disadvantageous inequality are less generous.

“Our findings support the theory of inequality aversion which suggests that many people dislike inequality per se, and that this dislike has important economic and political consequences—both at the societal and the personal level,” Ernst Fehr concludes.

More information:
Thomas F. Epper et al, Inequality aversion predicts support for public and private redistribution, Proceedings of the National Academy of Sciences (2024). DOI: 10.1073/pnas.2401445121

Citation:
Aversion to inequality drives support for redistribution policies, study finds (2024, September 19)
retrieved 19 September 2024
from https://phys.org/news/2024-09-aversion-inequality-redistribution-policies.html

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part may be reproduced without the written permission. The content is provided for information purposes only.





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How plants carry environmental clues across generations

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How plants carry environmental clues across generations


The memory in seeds—how plants carry environmental clues across generations
Cyclic Manhattan plots of P values for phenotypic plasticity through the whole Arabidopsis genome (composed of five chromosomes represented by distinct colors) calculated by coFunMap. Credit: Horticulture Research (2024). DOI: 10.1093/hr/uhae172

Phenotypic plasticity enables plants to adjust their physical traits in response to environmental variations, playing a vital role in their survival and adaptability. While past research has primarily focused on how these traits manifest within a single generation, the genetic basis of transgenerational inheritance remains largely unexplored. Addressing this gap is essential to fully understand how plants transmit adaptive traits from one generation to the next.

New research on phenotypic plasticity conducted by teams from Beijing Forestry University and Tsinghua University, was published on June 25, 2024, in Horticulture Research.

Utilizing a nested experimental design, the study explored how maternal light conditions influence the phenotypic traits of Arabidopsis thaliana offspring. By integrating ecological and computational methods, the researchers identified critical genetic regions associated with transgenerational phenotypic plasticity, providing fresh insights into plant adaptation mechanisms.

The study implemented a reciprocal experimental design, cultivating recombinant inbred lines (RILs) of Arabidopsis under high- and low-light conditions. Offspring were then grown in both matching and contrasting light environments. This setup allowed researchers to assess the influence of maternal conditions on traits such as leaf number and to understand how these traits are inherited across generations.

The findings revealed that the genetic framework of phenotypic plasticity evolves between generations and is significantly impacted by maternal environmental experiences. Specific Quantitative Trait Loci (QTLs) linked to phenotypic plasticity were identified, varying with light conditions and generational context. The study underscored a complex interplay between genetic and epigenetic factors that drive these adaptive responses.

Dr. Rongling Wu, the study’s senior author, stated, “Our research provides a detailed view of how plants inherit adaptive traits across generations through both genetic and non-genetic pathways. Recognizing the complex interactions between maternal environments and offspring traits could pave the way for enhancing plant resilience in the face of climate change.”

This research offers critical insights into plant adaptation strategies, which are invaluable for agriculture and environmental conservation. Understanding the genetic and epigenetic foundations of phenotypic plasticity can help breeders and scientists predict plant responses to future environmental challenges, guiding the development of more resilient crops.

The study also enriches our understanding of evolutionary biology, revealing how organisms manage environmental variability across generations.

More information:
Jincan Che et al, A nested reciprocal experimental design to map the genetic architecture of transgenerational phenotypic plasticity, Horticulture Research (2024). DOI: 10.1093/hr/uhae172

Citation:
The memory in seeds: How plants carry environmental clues across generations (2024, September 19)
retrieved 19 September 2024
from https://phys.org/news/2024-09-memory-seeds-environmental-clues-generations.html

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part may be reproduced without the written permission. The content is provided for information purposes only.





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The relationship between emotions and economic decision-making differ across countries, multi-national analysis finds

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The relationship between emotions and economic decision-making differ across countries, multi-national analysis finds


The relationship between emotions and economic decision-making could differ across countries
Cross-country variation in the relationship between positive mood and patience (a) or positive mood and risk taking (b). Credit: Nature Human Behaviour, 2024. DOI: https://doi.org/10.1038/s41562-024-01927-3)

When making economic decisions, humans can be driven by various factors, including their goals and emotions. Past studies have hypothesized that emotions play a crucial role in economic decisions, particularly those that involve risk or trade-offs between immediate and future benefits.

Researchers at Stanford Graduate School of Business, Stanford University and University of Chicago Booth School of Business recently set out to investigate the relationship between emotions and economic choices in greater depth by analyzing a large multi-national dataset.

Their findings, published in Nature Human Behaviour, unveiled distinct patterns in the extent to which emotions predict economic decisions across several countries worldwide.

“In 2019, we encountered a new dataset that measured how individuals make financial decisions around the globe,” Samuel Pertl, co-author of the paper, told Phys.org. “We were fascinated by this dataset, and as we delved deeper, we discovered an additional layer of information that the original research team had not explored: participants’ emotional experiences.

“This aspect intrigued us because most prior research on the influence of emotions on decision-making has been conducted in a few highly developed countries, primarily the U.S. With nationally representative samples from 74 countries, we saw an opportunity to test whether the relationship between emotions and economic decision-making replicates and generalizes on a global scale.”

Some theorists previously proposed that the link between emotions and economic choices could be universal and thus exhibits similar patterns across different countries. The key objective of the recent study by Pertl and his colleagues was to test this hypothesis, by analyzing data from the Gallup World Poll and Global Preferences Survey, two large-scale surveys spanning a total of 74 countries.

“To examine how emotions influence economic decision-making, we employed two different approaches,” explained Pertl. “There are already many existing studies examining how incidental emotions influence individuals’ intertemporal or risky decisions. As a first step, we summarized these studies through a meta-analysis, which pools together existing findings and summarizes them into an average relationship.”

The meta-analysis carried out by the researchers unveiled that most past studies were conducted with non-representative samples, typically from a few Western countries.

The relationship between emotions and economic decision-making could differ across countries
Predictors of cross-country differences in the relationship between positive mood and patience (a and b) or positive mood and risk taking (c and d). Credit: Nature Human Behaviour, 2024. DOI: https://doi.org/10.1038/s41562-024-01927-3

This encouraged them to carry out a global analysis, leveraging large multi-national datasets. Collectively, Pertl and his colleagues analyzed the survey responses of 77,242 individuals residing in 74 countries.

“Each respondent was asked about their emotional experiences—specifically, whether they experienced happiness, enjoyment, sadness, worry, anger, stress or pain during most of the previous day, with each emotion measured separately,” said Pertl.

“The dataset also captured how individuals made economic decisions, such as choosing between a smaller immediate reward versus a larger future reward (intertemporal decision), or between a certain smaller reward versus an uncertain larger reward (risky decision).”

Using statistical methods, the researchers looked at whether emotions predicted the economic decisions of survey respondents, controlling for various factors, including demographics, language differences and geographical location. To determine whether the link between emotions and economic decision-making was in fact universal, they compared the patterns they observed across different countries.

“I believe the most notable finding from our paper is that there is substantial and systematic cross-country variation in whether and how emotions predict economic decision-making,” said Pertl. “For example, it has been proposed that being in a positive mood leads to greater patience (i.e., individuals are more willing to wait for a delayed reward).

“However, our analyses suggest that this relationship is far from universal. We found that while being in a positive mood was associated with greater patience in 53 countries, it was linked to greater impatience in 21 countries.”

Interestingly, Pertl and his colleagues also found that the cross-country differences in the relationships between emotions and economic decision-making can be explained. Specifically, they found that emotions were stronger predictors of economic decisions in more economically developed countries (measured using the Human Development Index) and in more individualistic countries (measured using Hofstede’s Individualism Index).

“Our findings underscore the need for more diverse samples when studying fundamental questions about decision-making,” added Pertl. “While I am now exploring questions in a different research area, my co-authors are still working on several projects related to how emotions influence decision-making.”

More information:
Samuel M. Pertl et al, A multinational analysis of how emotions relate to economic decisions regarding time or risk, Nature Human Behaviour (2024). DOI: 10.1038/s41562-024-01927-3

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Citation:
The relationship between emotions and economic decision-making differ across countries, multi-national analysis finds (2024, September 19)
retrieved 19 September 2024
from https://phys.org/news/2024-09-relationship-emotions-economic-decision-differ.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.





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