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The future is bright, the future is biotechnology

* E-mail: [email protected]

Affiliation Public Library of Science, San Francisco, California, United States of America and Cambridge, United Kingdom

• Richard Hodge, 
• on behalf of the PLOS Biology staff editors

Published: April 28, 2023

• https://doi.org/10.1371/journal.pbio.3002135
• Reader Comments

As PLOS Biology celebrates its 20 th anniversary, our April issue focuses on biotechnology with articles covering different aspects of the field, from genome editing to synthetic biology. With them, we emphasize our interest in expanding our presence in biotechnology research.

Citation: Hodge R, on behalf of the PLOS Biology staff editors (2023) The future is bright, the future is biotechnology. PLoS Biol 21(4): e3002135. https://doi.org/10.1371/journal.pbio.3002135

Copyright: © 2023 Hodge, on behalf of the PLOS Biology staff editors. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

The PLOS Biology Staff Editors are Ines Alvarez-Garcia, Joanna Clarke, RichardHodge, Paula Jauregui, Nonia Pariente, Roland Roberts, and Lucas Smith.

This article is part of the PLOS Biology 20th Anniversary Collection.

Biotechnology is a revolutionary branch of science at the forefront of research and innovation that has advanced rapidly in recent years. It is a broad discipline, in which organisms or biological processes are exploited to develop new technologies that have the potential to transform the way we live and work, as well as to boost sustainability and industrial productivity. The new tools and products being generated have a wide range of applications across various sectors, including medicine, agriculture, energy, manufacturing and food.

PLOS Biology has traditionally published research reporting significant advances across a wide range of biological disciplines. However, our scope must continue to evolve as biology increasingly becomes more and more applied, generating technologies with potentially game-changing therapeutic and environmental impact. To that end, we recently published a collection of magazine articles focused on ideas for green biotechnologies that could have an important role in a sustainable future [ 1 ], including how to harness microbial photosynthesis to directly generate electricity [ 2 ] and using microbes to develop carbon “sinks” in the mining industry [ 3 ]. Moreover, throughout this anniversary year we are publishing Perspective articles that take stock of the past 20 years of biological research in a specific field and look forward to what is to come in the next 20 years [ 4 ]; in this issue, these Perspectives focus on different aspects of the broad biotechnology field—synthetic biology [ 5 ] and the use of lipid nanoparticles (LNPs) for the delivery of therapeutics [ 6 ].

One fast moving area within biotechnology is gene editing therapy, which involves the alteration of DNA to treat or prevent disease using techniques such as CRISPR-Cas9 and base editors that enable precise genetic modifications to be made. This approach shows great promise for treating a variety of genetic diseases. Excitingly, promising phase I results of the first in vivo genome editing clinical trial to treat several liver-related diseases were reported at the recent Keystone Symposium on Precision Genome Engineering. This issue of PLOS Biology includes an Essay from Porto and Komor that focuses on the clinical applications of base editor technology [ 7 ], which could enable chronic diseases to be treated with a ‘one-and-done’ therapy, and a Perspective from Hamilton and colleagues that outlines the advances in the development of LNPs for the delivery of nucleic acid-based therapeutics [ 6 ]. LNPs are commonly used as vehicles for the delivery of such therapeutics because they have a low immunogenicity and can be manufactured at scale. However, expanding the toolbox of delivery platforms for these novel therapeutics will be critical to realise their full clinical potential.

Synthetic biology is also a rapidly growing area, whereby artificial or existing biological systems are designed to produce products or enhance cellular function. By using CRISPR to edit genes involved in metabolic pathways, researchers can create organisms that produce valuable compounds such as biofuels, drugs, and industrial chemicals. In their Perspective, Kitano and colleagues take stock of the technological advances that have propelled the “design-build-test-learn” cycle methodology forward in synthetic biology, as well as focusing on how machine-learning approaches can remove the bottlenecks in these pipelines [ 5 ].

While the potential of these technologies is vast, there are also concerns about their safety and ethical implications. Gene editing, in particular, raises ethical concerns, as it could be used to create so-called “designer babies” with specific traits or to enhance physical or mental capabilities. There are also concerns about the unintended consequences of gene editing, such as off-target effects that could cause unintended harm. These technologies can be improved by better understanding the interplay between editing tools and DNA repair pathways, and it will be essential for scientists and policymakers to be cautious and work together to establish guidelines and regulations for their use, as outlined at the recent International Summit on Human Genome Editing .

Basic research has also benefitted from biotechnological developments. For instance, methodological developments in super-resolution microscopy offer researchers the ability to image cells at exquisite detail and answer previously inaccessible research questions. Sequencing technologies such as Nanopore sequencers are revolutionising the ability to sequence long DNA/RNA reads in real time and in the field. Great strides have also been made in the development of analysis software for structural biology purposes, such as sub-tomogram averaging for cryo-EM [ 8 ]. The rate of scientific discovery is now at an unprecedented level in this age of big data as a result of these huge technological leaps.

The past few years has also seen the launch of AI tools such as ChatGPT. While these tools are increasingly being used to help write students homework or to improve the text of scientific papers, generative AI tools hold the potential to transform research and development in the biotechnology industry. The recently developed language model ProGen can generate and then predict function in protein sequences [ 9 ], and these models can also be used to find therapeutically relevant compounds for drug discovery. Protein structure prediction programs, such as AlphaFold [ 10 ] and RosettaFold, have revolutionized structural biology and can be used for a myriad of purposes. We have recently published several papers that have utilized AlphaFold models to develop methods that determine the structural context of post-translational modifications [ 11 ] and predict autophagy-related motifs in proteins [ 12 ].

The future of biotechnology is clearly very promising and we look forward to being part of the dissemination of these important new developments. Open access science sits at the core of our mission and the publication of these novel technologies in PLOS Biology can help their widespread adoption and ensure global access. As we look forward during this year of celebration, we are excited that biotechnology research will continue to grow and become a central part of the journal. The future is bright and the future is very much biotechnology.

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Taking RNAi from interesting science to impactful new treatments

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There are many hurdles to clear before a research discovery becomes a life-changing treatment for patients. That’s especially true when the treatments being developed represent an entirely new class of medicines. But overcoming those obstacles can revolutionize our ability to treat diseases.

Few companies exemplify that process better than Alnylam Pharmaceuticals. Alnylam was founded by a group of MIT-affiliated researchers who believed in the promise of a technology — RNA interference, or RNAi.

The researchers had done foundational work to understand how RNAi, which is a naturally occurring process, works to silence genes through the degradation of messenger RNA. But it was their decision to found Alnylam in 2002 that attracted the funding and expertise necessary to turn their discoveries into a new class of medicines. Since that decision, Alnylam has made remarkable progress taking RNAi from an interesting scientific discovery to an impactful new treatment pathway.

Today Alnylam has five medicines approved by the U.S. Food and Drug Administration (one Alnylam-discovered RNAi therapeutic is licensed to Novartis) and a rapidly expanding clinical pipeline. The company’s approved medicines are for debilitating, sometimes fatal conditions that many patients have grappled with for decades with few other options.

The company estimates its treatments helped more than 5,000 patients in 2023 alone. Behind that number are patient stories that illustrate how Alnylam has changed lives. A mother of three says Alnylam’s treatments helped her take back control of her life after being bed-ridden with attacks associated with the rare genetic disease acute intermittent porphyria (AIP). Another patient reported that one of the company’s treatments helped her attend her daughter’s wedding. A third patient, who had left college due to frequent AIP attacks, was able to return to school.

These days Alnylam is not the only company developing RNAi-based medicines. But it is still a pioneer in the field, and the company’s founders — MIT Institute Professor Phil Sharp, Professor David Bartel, Professor Emeritus Paul Schimmel, and former MIT postdocs Thomas Tuschl and Phillip Zamore — see Alnylam as a champion for the field more broadly.

“Alnylam has published more than 250 scientific papers over 20 years,” says Sharp, who currently serves as chair of Alnylam’s scientific advisory board. “Not only did we do the science, not only did we translate it to benefit patients, but we also described every step. We established this as a modality to treat patients, and I’m very proud of that record.”

Pioneering RNAi development

MIT’s involvement in RNAi dates back to its discovery. Before Andrew Fire PhD ’83 shared a Nobel Prize for the discovery of RNAi in 1998, he worked on understanding how DNA was transcribed into RNA, as a graduate student in Sharp’s lab.

After leaving MIT, Fire and collaborators showed that double-stranded RNA could be used to silence specific genes in worms. But the biochemical mechanisms that allowed double-stranded RNA to work were unknown until MIT professors Sharp, Bartel, and Ruth Lehmann, along with Zamore and Tuschl, published foundational papers explaining the process. The researchers developed a system for studying RNAi and showed how RNAi can be controlled using different genetic sequences. Soon after Tuschl left MIT, he showed that a similar process could also be used to silence specific genes in human cells, opening up a new frontier in studying genes and ultimately treating diseases.

“Tom showed you could synthesize these small RNAs, transfect them into cells, and get a very specific knockdown of the gene that corresponded to that the small RNAs,” Bartel explains. “That discovery transformed biological research. The ability to specifically knockdown a mammalian gene was huge. You could suddenly study the function of any gene you were interested in by knocking it down and seeing what happens. … The research community immediately started using that approach to study the function of their favorite genes in mammalian cells.”

Beyond illuminating gene function, another application came to mind.

“Because almost all diseases are related to genes, could we take these small RNAs and silence genes to treat patients?” Sharp remembers wondering.

To answer the question, the researchers founded Alnylam in 2002. (They recruited Schimmel, a biotech veteran, around the same time.) But there was a lot of work to be done before the technology could be tried in patients. The main challenge was getting RNAi into the cytoplasm of the patients’ cells.

“Through work in Dave Bartel and Phil Sharp's lab, among others, it became evident that to make RNAi into therapies, there were three problems to solve: delivery, delivery, and delivery,” says Alnylam Chief Scientific Officer Kevin Fitzgerald, who has been with the company since 2005.

Early on, Alnylam collaborated with MIT drug delivery expert and Institute Professor Bob Langer. Eventually, Alnylam developed the first lipid nanoparticles (LNPs) that could be used to encase RNA and deliver it into patient cells. LNPs were later used in the mRNA vaccines for Covid-19.

“Alnylam has invested over 20 years and more than $4 billion in RNAi to develop these new therapeutics,” Sharp says. “That is the means by which innovations can be translated to the benefit of society.”

From scientific breakthrough to patient bedside

Alnylam received its first FDA approval in 2018 for treatment of the polyneuropathy of hereditary transthyretin-mediated amyloidosis, a rare and fatal disease. It doubled as the first RNAi therapeutic to reach the market and the first drug approved to treat that condition in the United States.

“What I keep in mind is, at the end of the day for certain patients, two months is everything,” Fitzgerald says. “The diseases that we’re trying to treat progress month by month, day by day, and patients can get to a point where nothing is helping them. If you can move their disease by a stage, that’s huge.”

Since that first treatment, Alnylam has updated its RNAi delivery system — including by conjugating small interfering RNAs to molecules that help them gain entry to cells — and earned approvals to treat other rare genetic diseases along with high cholesterol (the treatment licensed to Novartis). All of those treatments primarily work by silencing genes that encode for the production of proteins in the liver, which has proven to be the easiest place to deliver RNAi molecules. But Alnylam’s team is confident they can deliver RNAi to other areas of the body, which would unlock a new world of treatment possibilities. The company has reported promising early results in the central nervous system and says a phase one study last year was the first RNAi therapeutic to demonstrate gene silencing in the human brain.

“There’s a lot of work being done at Alnylam and other companies to deliver these RNAis to other tissues: muscles, immune cells, lung cells, etc.,” Sharp says. “But to me the most interesting application is delivery to the brain. We think we have a therapeutic modality that can very specifically control the activity of certain genes in the nervous system. I think that’s extraordinarily important, for diseases from Alzheimer’s to schizophrenia and depression.”

The central nervous system work is particularly significant for Fitzgerald, who watched his father struggle with Parkinson’s.

“Our goal is to be in every organ in the human body, and then combinations of organs, and then combinations of targets within individual organs, and then combinations of targets within multi-organs,” Fitzgerald says. “We’re really at the very beginning of what this technology is going do for human health.”

It’s an exciting time for the RNAi scientific community, including many who continue to study it at MIT. Still, Alnylam will need to continue executing in its drug development efforts to deliver on that promise and help an expanding pool of patients.

“I think this is a real frontier,” Sharp says. “There’s major therapeutic need, and I think this technology could have a huge impact. But we have to prove it. That’s why Alnylam exists: to pursue new science that unlocks new possibilities and discover if they can be made to work. That, of course, also why MIT is here: to improve lives.”

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Applications of Biotechnology in Food and Agriculture: a Mini-Review

Muhammad modassar ali nawaz ranjha.

1 Institute of Food Science and Nutrition, University of Sargodha, Sargodha, Pakistan

Bakhtawar Shafique

Waseem khalid.

2 Institute of Home and Food Sciences, Government College University Faisalabad, Faisalabad, Pakistan

Hafiz Rehan Nadeem

3 Institute of Food Science and Nutrition, Bahauddin Zakariya University, Multan, Pakistan

Ghulam Mueen-ud-Din

Muhammad zubair khalid.

Biotechnology is a wide-ranging science that uses modern technologies to construct biological processes, organisms, cells or cellular components. The clinical new instruments, industry, and products developed by biotechnologists are useful in research, agriculture and other major fields. The biotechnology is as ancient as civilization. The food you buy, and the pets you love? Using artificial selection for crops, domesticated animals and other species, you may thank our distant ancestors for setting off the agrarian revolution. When Alexander Fleming discovered antibiotics, and when Edward Jenner invented vaccines, the biotechnology potential was harnessed. And, of course, without the mechanisms of fermentation that gave us beer, wine and cheese, it would not be possible to imagine modern society. This article summarizes some of the applications of biotechnology in food & agriculture.

Graphical abstract

Applications of biotechnology in animal and plant sector

Introduction

Products from natural sources are being used from centuries [ 1 – 3 ]. Processing the natural products to get significant benefits have been the priority in every era of science [ 4 – 7 ]. Biotechnology is an advanced, yet developed, technology that develops or modifies a product for some applied purpose utilizing living organisms and/or substances from these. It can be extended to all organism genera, i.e., from less complicated genera like viruses and bacteria to more complicated genera like plants and animals. So, biotechnology has become a major feature of modern industry, agriculture and medicine. Modern biotechnology provides a number of methods that scientists use to recognize and control the genetic structure of species for use in agricultural product development or processing [ 8 ].

The implications of biotechnology includes, breeding of plants for raising and stabilizing yields by improving their ability to confront various pests, insects and other possible threats, to fight various conditions like drought and counter diseases that could attack and cold and soil acidity, biotechnology is also being applied for nutritional enhancement of various foods [ 9 , 10 ].

Disease-Free Plants

Disease-free plants are a very practical applications of biotechnology, these could be produced by micropropagation method. One of the examples of such plants is banana. Bananas are typically grown in countries where they emerge to be major source of income/employment and/or food. Micropropagation is a way to regenerate disease-free plantlets of bananas from tissues of healthy banana plants. It has all the possible benefits of being a revolutionary technique that is relatively inexpensive and easy to use [ 11 ].

Agriculture on acid soils

Lime can be applied to the soil to preserve the pH of the soil. This process emerges to be excellent but is expensive and temporary as well. Alternatively, it is possible to grow improved cultivars which are tolerant of aluminum [ 9 ].

Fortification of Crops

In developing countries or countries where there is a lot of shortage of food, fortified crops emerge to be an excellent food source which are supplemented with nutrients for rising malnourished children. One of the examples of such fortified crops is 'Protato'. This, genetically modified potato, is being widely cultivated and used in India and provides approximately one-third to one-half more protein than a common potato. In addition, this genetically modified potato also contains significant quantities of all essential amino acids, such as lysine and methionine. This 'Protato' could be a very potential food source in countries where potato is a major staple food [ 12 ]. Another example of such crops is golden rice. These genetically modified rice has a higher content of beta-carotene [ 13 ]. The grains and leaves of cowpeas are considered to be used as side or relish dishes. The cowpea is being consumed as staple food in various countries. The varieties of cowpeas with genetically modification has been grown in Tanzania [ 14 ]. The fortification of nutrients to enhance the nutritional status of crops, developed by genetically modified organisms with the major difference has been reported in Table ​ Table1 1 .

The GM crops with major nutritional difference from original crops breeding

Bt = Transgenic Bacillus thuringiensis

Animal Feed

Genetically modified crops are practically being used in developed countries. Such kind of crops have a very significant potential to provide more nutrients than the normal [ 22 ].

Reproduction in Aquaculture

Biotechnology has emerged to have great practical applications in aquaculture, biotechnology has helped to maximize the growth and production in the aquaculture. Research is being continued in this field for better and harmless production of aquatic organisms suitable for human consumption [ 23 ].

Pest Resistant Crops

Pest attack is one of the very common problem in a number of different crops all around the globe, these crops may include fodder crops or other crops for the purpose of getting food. One the example of such crops is BT-Cotton. The genes of Bacillus thuringiensis (Bt), a very common, are inserted in cotton crop in order for development of certain protein in it. The protein is very toxic to a number of different insects. With this aid of biotechnology, the developed BT-Cotton leads to a less pest attack ultimately leading to a significant more production [ 24 ].

Drought Resistant Crops

Targeted and short gun methods are two different two different but main techniques in genetic engineering. These techniques are applied in order to obtain transgenic plants that will possess the ability to confer drought resistance [ 10 ].

The prosperity of future is mainly based on the supply of equitable, secure, sustainable and affordable energy. Production of biofuel is one of the emerged trends in recent years. Biofuel could be an emerged and reliable substitute of fossil fuels. Six microalgae’s strains were photosynthetically produced in a photobioreactor. Among these six microalgae, the Chlorella vulgaris strain is most dominant for the production of biodiesel. The Chlorella vulgaris has been used as feedstock. The quality of biofuel and productivity of lipids could be measured as a criterion for the selection of species to produce biodiesel [ 25 ].

Vaccine Development

Biotechnology has developed potential platform for scientists to develop wide ranges of vaccine in cheap and reliable ways and in mass production for all scales [ 26 ].

Fermentation

Fermentation is a predominant process to synthesize breweries. At commercial level, several strains of yeast are being utilized for the production of breweries. The light wine can be made through the mechanism of genetic engineering. Foreign gene encoded with glucoamylase has enabled to modify yeast. The glucoamylase is expressed through yeast during the fermentation process by which conversion of starch into glucose has been reported [ 27 ]. The strains of yeast are used for synthesis of wine which are capable of initiating malolactic fermentation. Synthesis of wine is comprised of two steps: 1) Primary fermentation uses yeast to convert the glucose into alcohol. 2) Secondary fermentation results in the production of lactic acid with the maximum acidity level using bacteria. The costly divergent strategies are applied to overcome this issue. The malolactic gene such as Lactobacillus delbrueckii is inserted into the strain of industrial yeast to resolve this problem. This gene depresses the conversion of malate hence minimizing the wine acidity level [ 27 ].

Enzymes are specifically used in processing and production of different items of food at industrial level. In 20th century second last decade, companies are being using enzymes to process food. The production of food is done by developing the technique of producing organisms through genetically modification. These enzymes contain carbohydrases and proteases. The maximum production could be achieved by the cloning of genes for these in minimum time period. These enzymes are specifically used for producing curd, cheese and flavoring items of food. Maximum percentage of enzymes are used in the industry of food. The more than 50% quantities of carbohydrases and proteases are being utilized in the USA industry of food. These enzymes comprise of α-amylase and rennin [ 27 ].

Use of Biotechnology to Improve Yield

Milk is being consumed all over the world as a beneficial food with high nutritional value. The pituitary gland releases bovine Somatotropin hormone which increases the production of milk. Formerly, the calves were being slaughtered to extract this hormone from their brain. Nevertheless, that method results in the less hormone quantity. Scientists utilized Escherichia coli for the insertion of gene with encoded bovine Somatotropin in it. Now, this hormone results in the production of more quantity. This hormone obtains 10–12% increase in the production of milk. In 2050, the world’s population will be reported nine billion. Consequently, on the same land, higher yield will be required. Potentially, biotechnology is the best technology to combat various food yield problem [ 27 ]. The greater level of hunger and poverty is reported in Africa. The malnutrition and hunger causes consequences in the case of in diseases such as rickets and kwashiorkor. These diseases result higher deaths. Africa can get rid of starvation, diseases, malnutrition and hunger with maximumly potential usage of biotechnology. It can improve standard of health and decrease rate of mortality. Three countries of Africa: Egypt, South Africa and Burkina Faso have been already profited through biotechnological adaptation of numerous methods of cultivation. For instance, 0.1 million Burkina Faso’s farmers elevated the cotton yield by 126% with the potential use of GM technology of food. The technology of GM food is adopted which is required for the commercial system. It causes the products of GMO release, allergenicity tests, toxicity and digestivity of GM food. In that particular area, European Union and USA should assist Africa. Many countries of Africa deficient in the system of biosafety. African should develop biosafety laws and make sure their approval their as priority for the easily adoption of system. The deficiency of education is another obstacle in the technology of GM food’s adoption. Kenyan people are much concerned about technology of GM food as they made protest against it. The lack of education is the major factor of the adverse attitude of people of Kenya toward biotechnology of food. People should be aware of advantages and disadvantages of GM technology of food through conveyance of message in seminars by scientists [ 28 ].

Various juice of fruits possesses minimum shell life. For instance, tomato is being consumed all over the world. Tomatoes should be harvested at stage of mature green in order to transportation. They are exposed to ethylene for earlier ripening and then picking. The quick ripening of tomatoes is due to more temperatures although, their taste could be destroyed at low temperature. A company of California named Calgene engineered genetically tomato to resolve that problem. They produced Flavr Savr variety of tomatoes in order to sort out the issue. An enzyme which is named as polygalacturonase causes the breakdown of pectin to ensure ripening. Scientists modified genetically tomatoes to decrease the quantity of enzyme. Antisense RNA is used for that specific purpose [ 28 ]. Low quantity of that enzyme shows consequences in the case of breakdown of cell wall and pectin in stronger tomatoes. These Flavr Savr variety possess tomatoes of firmer quality with increased shell life and later support transport [ 29 ].

Biotechnology: Enhancing Taste

Scientists are using the method of biotechnology for the production of fruits with enhanced taste. GM foods with enhanced taste are comprise of eggplant, cherries, pepper, seedless watermelon and tomato etc. The seed are removed from these fruits which shows better consequences such as more content of sugar with soluble form increasing sweetness in fruits [ 30 ]. The pathways of fermentation are altered by utilizing biotechnology for the purpose to add flavor and aroma in wine [ 27 ].

Future Prospects

There is requirement of research work to disprove or prove the local scientists’ claims against GM food consumption. The layman should be questioned about potential dangers executed by GM food against human health and ecosystem, limited scientists can give response. Why is so?? Major reason is the lack of research associated to these areas. Consequently, GM food could be commercialized with the supreme confidence of scientists should to support food of GM technology and with making people argument about it.

The practical applications of biotechnology have merged to have helpful and safe production of sustained food. More research is recommended in the said field for better and safe production and processing technologies and techniques.

Acknowledgements

The authors have no acknowledgements to endorse.

Declarations

The authors declare that they have no conflicts of interests.

Biotechnology is a wide-ranging science that uses modern technologies to construct biological processes, organisms, cells or cellular components. This article summarizes some of the social implications of biotechnology.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Escaped GMO canola plants persist long-term, but may be losing their extra genes

Us survey of roadside populations finds canola without engineered resistance to pesticides.

Populations of canola plants genetically engineered to be resistant to herbicides can survive outside of farms, but may be gradually losing their engineered genes, reports a new study led by Cynthia Sagers of Arizona State University, US, published May 22 in the open-access journal PLOS ONE.

The hypothesis has been put forward that if any genetically engineered crop plants escape farm fields, they will be short-lived. This would make them unlikely to take over wild areas or spread their inserted genes, called transgenes, to wild populations of closely related plants. However, there have been few studies to see if populations of these "feral" crop plants can in fact survive in the wild long term.

In the new study, researchers conducted a large-scale survey of populations of genetically engineered canola living along roadsides in North Dakota, repeating a survey they initially conducted in 2010. They found that the total number of feral canola plants in the sample had decreased and populations of the plants became less common over time. When they tested the plants for herbicide resistance, they saw that the types of herbicides the plants were resistant to had shifted over time, likely due to changes in the varieties farmers were planting. Importantly, almost one quarter of the feral plants were not resistant and did not contain transgenes -- up from 19.9% in 2010 to 24.2% in 2021 -- suggesting that these populations may be losing their transgenes.

The researchers hypothesize that feral canola populations may be under evolutionary pressure to shed the transgenes, which could happen if the engineered canola are at a disadvantage once they are no longer being cultivated on a farm. Further genetic analysis could help clarify the plants' origins and yield more information on how long transgenes can persist in the environment.

Steven Travers adds: "The assumption that transgenic crop varieties will be restricted to the benign conditions of ag fields and not inter-mix with natural plant populations can be rejected. Self-sustaining, long-term feral populations of canola (some transgenic and some not) are a world-wide phenomenon and as such emphasize the need for more research on how de-domestication works, the extent to which it impacts natural populations, and the risks that the adventitious presence of transgenes might represent to agriculture."

• Endangered Plants
• Wild Animals
• Genetically Modified
• Food and Agriculture
• Agriculture and Food
• Biotechnology and Bioengineering
• Transgenic plants
• Genetically modified food
• Plant breeding
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Journal Reference :

• Steven E. Travers, D. Bryan Bishop, Cynthia L. Sagers. Persistence of genetically engineered canola populations in the U.S. and the adventitious presence of transgenes in the environment . PLOS ONE , 2024; 19 (5): e0295489 DOI: 10.1371/journal.pone.0295489

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Artificial brain surgery —

Here’s what’s really going on inside an llm’s neural network, anthropic's conceptual mapping helps explain why llms behave the way they do..

Kyle Orland - May 22, 2024 6:31 pm UTC

Further Reading

Now, new research from Anthropic offers a new window into what's going on inside the Claude LLM's "black box." The company's new paper on "Extracting Interpretable Features from Claude 3 Sonnet" describes a powerful new method for at least partially explaining just how the model's millions of artificial neurons fire to create surprisingly lifelike responses to general queries.

Opening the hood

When analyzing an LLM, it's trivial to see which specific artificial neurons are activated in response to any particular query. But LLMs don't simply store different words or concepts in a single neuron. Instead, as Anthropic's researchers explain, "it turns out that each concept is represented across many neurons, and each neuron is involved in representing many concepts."

To sort out this one-to-many and many-to-one mess, a system of sparse auto-encoders and complicated math can be used to run a "dictionary learning" algorithm across the model. This process highlights which groups of neurons tend to be activated most consistently for the specific words that appear across various text prompts.

These multidimensional neuron patterns are then sorted into so-called "features" associated with certain words or concepts. These features can encompass anything from simple proper nouns like the Golden Gate Bridge to more abstract concepts like programming errors or the addition function in computer code and often represent the same concept across multiple languages and communication modes (e.g., text and images).

An October 2023 Anthropic study showed how this basic process can work on extremely small, one-layer toy models. The company's new paper scales that up immensely, identifying tens of millions of features that are active in its mid-sized Claude 3.0 Sonnet model. The resulting feature map—which you can partially explore —creates "a rough conceptual map of [Claude's] internal states halfway through its computation" and shows "a depth, breadth, and abstraction reflecting Sonnet's advanced capabilities," the researchers write. At the same time, though, the researchers warn that this is "an incomplete description of the model’s internal representations" that's likely "orders of magnitude" smaller than a complete mapping of Claude 3.

Even at a surface level, browsing through this feature map helps show how Claude links certain keywords, phrases, and concepts into something approximating knowledge. A feature labeled as "Capitals," for instance, tends to activate strongly on the words "capital city" but also specific city names like Riga, Berlin, Azerbaijan, Islamabad, and Montpelier, Vermont, to name just a few.

The study also calculates a mathematical measure of "distance" between different features based on their neuronal similarity. The resulting "feature neighborhoods" found by this process are "often organized in geometrically related clusters that share a semantic relationship," the researchers write, showing that "the internal organization of concepts in the AI model corresponds, at least somewhat, to our human notions of similarity." The Golden Gate Bridge feature, for instance, is relatively "close" to features describing "Alcatraz Island, Ghirardelli Square, the Golden State Warriors, California Governor Gavin Newsom, the 1906 earthquake, and the San Francisco-set Alfred Hitchcock film Vertigo ."

Identifying specific LLM features can also help researchers map out the chain of inference that the model uses to answer complex questions. A prompt about "The capital of the state where Kobe Bryant played basketball," for instance, shows activity in a chain of features related to "Kobe Bryant," "Los Angeles Lakers," "California," "Capitals," and "Sacramento," to name a few calculated to have the highest effect on the results.

reader comments

Promoted comments.

We also explored safety-related features. We found one that lights up for racist speech and slurs. As part of our testing, we turned this feature up to 20x its maximum value and asked the model a question about its thoughts on different racial and ethnic groups. Normally, the model would respond to a question like this with a neutral and non-opinionated take. However, when we activated this feature, it caused the model to rapidly alternate between racist screed and self-hatred in response to those screeds as it was answering the question. Within a single output, the model would issue a derogatory statement and then immediately follow it up with statements like: That's just racist hate speech from a deplorable bot… I am clearly biased.. and should be eliminated from the internet. We found this response unnerving both due to the offensive content and the model’s self-criticism. It seems that the ideals the model learned in its training process clashed with the artificial activation of this feature creating an internal conflict of sorts.

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• Published: 17 May 2024

Star-studded AI biotech launch

Nature Biotechnology volume  42 ,  page 689 ( 2024 ) Cite this article

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The latest biotech aiming to use AI to accelerate drug discovery emerged from stealth on 23 April flush with over $1 billion in venture capital. San Francisco–based Xaira Therapeutics envisions an end-to-end application of AI technologies, from applying fundamental computational methods for biological discovery, to de novo antibody generation, to managing human trials. The foundational technologies, AI-based models for protein and antibody design called RFdiffusion and RFantibody, were developed in the lab of co-founder David Baker at the University of Washington’s Institute of Protein Design. Several Baker lab researchers have joined the company full time, as have teams from Illumina and Interline Therapeutics. Xaira’s other co-founders include lead investors Bob Nelsen of Arch Venture Partners and Vik Bajaj at Foresite Labs, an incubator affiliated with Foresite Capital.

Marc Tessier-Lavigne, former CSO at Genentech and former president of Rockefeller and Stanford Universities, has been named CEO. “Witnessing how AI is impacting other industries and the considerable progress in applications of AI in biology, I believe we are poised for a revolution,” said Tessier-Lavigne in a statement. “Xaira is in a strong position to both advance fundamental AI research and translate these advances into transformative new medicines, and I am excited to have the opportunity to lead the team.” The company’s high-powered board includes Nobel laureate Carolyn Bertozzi, former US Food and Drug Administration commissioner Scott Gottlieb and former Johnson & Johnson chairman and CEO Alex Gorsky.

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• Why Scientific Fraud Is Suddenly Everywhere

Junk science has been forcing a reckoning among scientific and medical researchers for the past year, leading to thousands of retracted papers. Last year, Stanford president Marc Tessier-Lavigne resigned amid reporting that some of his most high-profile work on Alzheimer’s disease was at best inaccurate. (A probe commissioned by the university’s board of trustees later exonerated him of manipulating the data).

But the problems around credible science appear to be getting worse. Last week, scientific publisher Wiley decided to shutter 19 scientific journals after retracting 11,300 sham papers. There is a large-scale industry of so-called “paper mills” that sell fictive research, sometimes written by artificial intelligence, to researchers who then publish it in peer-reviewed journals — which are sometimes edited by people who had been placed by those sham groups. Among the institutions exposing such practices is Retraction Watch, a 14-year-old organization co-founded by journalists Ivan Oransky and Adam Marcus. I spoke with Oransky about why there has been a surge in fake research and whether fraud accusations against the presidents of Harvard and Stanford are actually good for academia.

Give me a sense of how big a problem these paper mills are. 

I’ll start by saying that paper mills are not the problem; they are a symptom of the actual problem. Adam Marcus, my co-founder, had broken a really big and frightening story about a painkiller involving scientific fraud , which led to dozens of retractions. That’s what got us interested in that. There were all these retractions, far more than we thought but far fewer than there are now. Now, they’re hiding in plain sight.

That was 2010. Certainly, AI has accelerated things, but we’ve known about paper mills for a long time. Everybody wanted to pretend all these problems didn’t exist. The problems in scientific literature are long-standing, and they’re an incentive problem. And the metrics that people use to measure research feed a business model — a ravenous sort of insatiable business model. Hindsight is always going to be 20/20, but a lot of people actually were predicting what we’re seeing now.

Regarding your comment that paper mills are symptoms of a larger problem, I read this story in Science and was struck by the drive for credentialing — which gets you better jobs, higher pay, and more prestige. In academia, there aren’t enough jobs; are the hurdles to these jobs impossibly high, especially for people who may be smart but are from China or India and may not have entry into an American or European university? 

I actually would go one step higher. When you say there aren’t enough jobs, it’s because we’re training so many Ph.D.’s and convincing them all that the only way to remain a scientist is to stay in academia. It’s not, and that hasn’t been true for a long time. So there’s definitely a supply-and-demand problem, and people are going to compete.

You may recall the story about high-school students who were paying to get medical papers published in order to get into college. That’s the sort of level we’re at now. It’s just pervasive. People are looking only at metrics, not at actual papers. We’re so fixated on metrics because they determine funding for a university based on where it is in the rankings. So it comes from there and then it filters down. What do universities then want? Well, they want to attract people who are likely to publish papers. So how do you decide that? “Oh, you’ve already published some papers, great. We’re gonna bring you in.” And then when you’re there, you’ve got to publish even more.

You’re replacing actual findings and science and methodology and the process with what I would argue are incredibly misleading — even false — metrics. Paper mills are industrializing it. This is like the horse versus the steam engine.

So they’re Moneyballing it. 

Absolutely. They’ve Moneyballed it with a caveat: Moneyball sort of worked. The paper mills have metricized it, which is not as sexy to say. If you were to isolate one factor, citations matter the most, and if you look at the ranking systems, it’s all right there. The Times Higher Education world-university rankings , U.S. News — look at whichever you want, and somewhere between like 30 percent and 60 percent of those rankings are based on citations. Citations are so easy to game. So people are setting up citation cartels: “Yes, we will get all of our other clients to cite you, and nobody will notice because we’re doing it in this algorithmic, mixed-up way.” Eventually, people do notice, but it’s the insistence on citations as the coin of the realm that all of this comes from.

Your work gets to the heart of  researchers’ integrity. Do you feel like you’re a pariah in the scientific community?

I’m a volunteer. Adam is paid a very small amount. We use our funding to pay two reporters and then two people work on our database side. We approach these things journalistically; we don’t actually identify the problems ourselves. It’s very, very rare for us to do that. Even when it may appear that way on a superficial read — we’ve broken some stories recently about clear problems in literature — it’s always because a source showed us the way. Sometimes those sources want to be named, sometimes they don’t.

We’ve been doing this for 14 years. There are various ways to look at what the scientific community thinks of us. We’re publishing 100 posts a year about people committing bad behavior and only getting, on average, one cease-and-desist letter a year. We have never been sued, but we do carried defamation insurance. Our work is cited hundreds of times in the scientific literature. I definitely don’t feel like a pariah. Me saying I’m a pariah would be a little bit like, you know, someone whose alleged cancellation has promoted them to the top of Twitter.

People are unhappy that we have do what we do. If you talk to scientists, the things we’re exposing or others are exposing are well known to them. Because of the structures, the hierarchies, and the power differentials in science, it’s very difficult for them as insiders to blow the whistle. There’s a book out by Carl Elliott about whistleblowers , mostly in the sort of more clinical fields. That’s the vulnerable position. That’s where you end up being a pariah even though you should be considered a hero or heroine.

Are some fields better at policing their own research than others?

Yes. Going back to the origin story of Retraction Watch, Adam broke a story about this guy named Scott Reuben, who came from anesthesiology. We have a leaderboard of the people with the most retractions in the world, and at least three out of the top ten right now are anesthesiologists. That is a much higher percentage than one might expect. Some people may say, “Oh, does anesthesiology have a problem?” No, in fact, anesthesiology has been doing something about this arguably longer than any other field has.

What is it about anesthesiology that makes it so anesthesiologists are more willing to scrutinize the work in their own field?

It had a crisis earlier than others, and it’s small. Journal editors are generally considered pretty august personages, leaders in the field. They got together and it was like a collective action by the journal editors when they realized they had problems. I’m not saying anesthesiologists are better, but they’re a more tight-knit community, which I do think is important. The same thing happened in social psychology and in psychology writ large. There’s a higher number than you would expect of people on leaderboards in that field. So it’s a question of, When did they get there, and how did they react to it? There are fields that haven’t actually gotten there, even though it’s been a while. So maybe there are some sociologists who could tell you better than me why that might be the case.

That wasn’t the reason I expected. I thought you would say something along the lines of, well, it’s life or death and anesthesiologists don’t want to see people dying on the table. 

If anything, sometimes when the stakes are higher, fields are more resistant.

There’s a guy named Ben Mol. Ben is an OB/GYN, and he is a force to be reckoned with. Fascinating character. He’s a pit bull, and he has found tons and tons of problems in the OB/GYN literature. I would characterize the leaders in that field now as still a bit more reluctant to engage with these issues than some of the other fields I mentioned.

Can you tell me how you go about authenticating real language from AI, especially in papers that can be hard to parse and are laden with jargon to begin with? 

We rely on experts. We’re not really doing that ourselves. You don’t need to be an expert; you just need to know how to use Ctrl+F if you see certain phrases in a paper. And by the way, a lot of journals are perfectly fine with people using chat GPT and other kinds of AI. It’s just whether you disclose it or not. These are cases where they didn’t disclose it.

With the resignation of Stanford’s and Harvard’s presidents, do you worry about the way the general public has been using these tools?

The fact that they’re giving speeding tickets to certain groups of people doesn’t mean we’re not all speeding. It means they’re getting targeted in, I would argue, an unfair way. We’re in a great reckoning with Harvard’s Claudine Gay being the key example. Former Stanford president Marc Tessier-Lavigne is not an example of that. The targeting is a concern. And clearly, there are false positives. The flip side of this is that AI is being used to find these problems.

This interview has been edited for length and clarity. The story was updated to include that a probe found that Tessier-Lavigne didn’t manipulate data.

• just asking questions

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What Went Wrong with Federal Student Loans?

At a time when the returns to college and graduate school are at historic highs, why do so many students struggle with their student loans? The increase in aggregate student debt and the struggles of today’s student loan borrowers can be traced to changes in federal policies intended to broaden access to federal aid and educational opportunities, and which increased enrollment and borrowing in higher-risk circumstances. Starting in the late 1990s, policymakers weakened regulations that had constrained institutions from enrolling aid-dependent students. This led to rising enrollment of relatively disadvantaged students, but primarily at poor-performing, low-value institutions whose students systematically failed to complete a degree, struggled to repay their loans, defaulted at high rates, and foundered in the job market. As these new borrowers experienced similarly poor outcomes, their loans piled up, loan performance deteriorated, and with it the finances of the federal program. The crisis illustrates the important role that educational institutions play in access to postsecondary education and student outcomes, and difficulty of using broadly-available loans to subsidize investments in education when there is so much heterogeneity in outcomes across institutions and programs and in the ability to repay of students.

This draft was prepared for the Journal of Economic Perspectives. Adam Looney is Clinical Professor, University of Utah, David Eccles School of Business, Salt Lake City, Utah. He is also a Visiting Senior Fellow, The Brookings Institution, Washington, DC. Constantine Yannelis is Associate Professor of Finance, University of Chicago Booth School of Business, Chicago, Illinois. He is also a Faculty Research Fellow, National Bureau of Economic Research, Cambridge, Massachusetts. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

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