In findings recently published in Environmental Research Letters, the team reported that the level of corn crop decline would vary, depending on the scale of the conflict. A regional nuclear war, which would send about 5.5 tons of soot into the atmosphere, could reduce world-wide annual corn production by 7%. A large-scale global war, injecting 165 tons of soot into the atmosphere, could lead to an 80% drop in annual corn yields. In all, the study simulated six nuclear war scenarios with varying soot injections.

Because of the crop’s global significance, the researchers chose to model corn’s collapse in a nuclear winter to represent the expected fate of agriculture overall, according to study first author Yuning Shi, associate research professor in Penn State’s Department of Plant Science. He noted that an 80% drop in global crop production would have catastrophic consequences, leading to a widespread global food crisis. Even a 7% drop in global crop production would have a severe impact on the global food system and economy, likely resulting in increased food insecurity and hunger.

The simulations were possible thanks to the Cycles agroecosystem model, created a few years ago by scientists in Penn State’s College of Agricultural Sciences, including lead developer Armen Kemanian, professor of production systems and modeling and corresponding author on this study. Using high-performance computing and considering atmospheric conditions, Cycles enables large-scale, high-resolution, multi-year simulations of crop growth by meticulously tracking the carbon and nitrogen cycles within the soil-plant-atmosphere system.

“We simulated corn production in 38,572 locations under the six nuclear war scenarios of increasing severity — with soot injections ranging from 5 to 165 tons,” Shi said. “This investigation advances our understanding of global agricultural resilience and adaptation in response to catastrophic climatic disruptions.”

In addition to considering the effects of massive amounts of soot in the atmosphere, the researchers modeled the increase in UV-B radiation — a type of ultraviolet radiation that can lead to DNA damage, oxidative stress and reduced photosynthesis in plants — that would reach Earth’s surface in a nuclear winter that could further limit agriculture.

Shi said he believes that this was the first study to estimate the extent of UV-B radiation damage to agriculture after nuclear explosions, which the researchers predicted would peak six to eight years after a global war. They estimated this could further cut corn production by an additional 7%, for a total worst-case scenario of an 87% drop in corn production.

Ozone high in Earth’s atmosphere effectively absorbs the bulk of UV radiation the planet receives from the sun, but nuclear war would dismantle this ability, Shi explained.

“The blast and fireball of atomic explosions produce nitrogen oxides in the stratosphere,” he said. “The presence of both nitrogen oxides and heating from absorptive soot could rapidly destroy ozone, increasing UV-B radiation levels at the Earth’s surface. This would damage plant tissue and further limit global food production.”

While the predictions point to potentially catastrophic drops in the production of corn varieties currently grown, Shi said, switching to crop varieties that can grow under cooler conditions in shorter growing seasons could boost global crop production by 10% compared to no adaptation. However, seed availability for these crops could become a serious problem — a “bottleneck to adaptation,” the researchers said.

Their proposed solution is to prepare “agricultural resilience kits” ahead of any nuclear disaster, containing region- and climate-specific seeds for crop varieties that can grow under cooler conditions with shorter growing seasons to survive lower temperatures.

“These kits would help sustain food production during the unstable years following a nuclear war, while supply chains and infrastructure recover,” Kemanian said. “The agricultural resilience kits concept can be expanded to other disasters — when catastrophes of these magnitude strike, resilience is of the essence.”

Shi noted that while proactive, internationally coordinated planning for such kits is unlikely, simply increasing awareness could help lead to better preparedness. “If we want to survive, we must be prepared, even for unthinkable consequences,” he said.

Kemanian said he sees value in the research beyond human-caused calamity.

“Recall that catastrophes of this nature can happen not just because of nuclear war, but due to, for example, violent volcanic eruptions,” he said. “One may think that studies of this nature are just navel gazing, but they force us to realize the fragility of the biosphere — the totality of all living things and how they interact with one another and the environment.”

Contributing to the research at Penn State were Felipe Montes, associate research professor of cropping systems modeling; Francesco Di Gioia, associate professor of vegetable crop science; and Charles Anderson, professor of biology and principal investigator of the project funding this work; as well as Charles Bardeen, with the Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, Colorado; and Yolanda Gil, Deborah Khider and Varun Ratnakar, all with the Information Sciences Institute, University of Southern California.

This research was supported by Open Philanthropy, the Defense Advanced Research Projects Agency, the U.S. Department of Agriculture National Institute of Food and Agriculture, the U.S. National Science Foundation and the Future of Life Institute.

Despite the growing popularity of bio-based plastics, plastic pollution remains one of the world’s most pressing environmental issues. According to the OECD’s Global Plastics Outlook (2022), about 353 million metric tons of plastic waste were produced globally in 2019, with nearly 1.7 million metric tons flowing directly into aquatic ecosystems. Much of this waste becomes trapped in large rotating ocean currents, known as gyres, forming the infamous “garbage patches” found in the Pacific, Atlantic, and Indian Oceans.

To tackle this, researchers have been searching for plastics that can be degraded more reliably in deep-sea environments. One promising candidate is poly(d-lactate-co-3-hydroxybutyrate) or LAHB, a lactate-based polyester biosynthesized using engineered Escherichia coli. So far, LAHB has shown strong potential as a biodegradable polymer that breaks down in river water and shallow seawater.

Now, in a study made available online on July 1, 2025, and published in Volume 240 of the journal Polymer Degradation and Stability on October 1, 2025, researchers from Japan have shown for the first time that LAHB can also get biodegraded under deep-sea conditions, where low temperatures, high pressure, and too limited nutrients make breakdown of plastic extremely difficult. The study was led by Professor Seiichi Taguchi at the Institute for Aqua Regeneration, Shinshu University, Japan, together with Dr. Shun’ichi Ishii from the Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Japan and Professor Ken-ichi Kasuya from Gunma University Center for Food Science and Wellness, Japan.

“Our study demonstrates for the first time that LAHB, a microbial lactate-based polyester, undergoes active biodegradation and complete mineralization even on the deep-sea floor, where conventional PLA remains completely non-degradable,” explains Prof. Taguchi.

The research team submerged two types of LAHB films — one containing about 6% lactic acid (P6LAHB) and another with 13% lactic acid (P13LAHB) — alongside a conventional PLA film for comparison. The samples were submerged at a depth of 855 meters near Hatsushima Island, where deep-sea conditions, cold temperatures (3.6 °C), high salinity, and low dissolved oxygen levels make it hard for microbes to degrade plastic.

After 7 and 13 months of immersion, the LAHB films revealed clear signs of biodegradation under deep-sea conditions. The P13LAHB film lost 30.9% of its weight after 7 months and over 82% after 13 months. The P6LAHB film showed similar trends. By contrast, the PLA film showed no measurable weight loss or visible degradation during the same period, underscoring its resistance to microbial degradation. The surfaces of the LAHB films had developed cracks and were covered by biofilms made up of oval- and rod-shaped microbes, indicating that deep-sea microorganisms were colonizing and decomposing the LAHB plastic. The PLA film, however, remained completely free of biofilm.

To understand how the plastic decomposes, the researchers analyzed the plastisphere, the microbial community that formed on the plastic’s surface. They found that different microbial groups played distinct roles. Dominant Gammaproteobacterial genera, including Colwellia, Pseudoteredinibacter, Agarilytica, and UBA7957, produced specialized enzymes known as extracellular poly[3-hydroxybutyrate (3HB)] depolymerases. These enzymes break down long polymer chains into smaller fragments like dimers and trimers. Certain species, such as UBA7959, also produce oligomer hydrolases (like PhaZ2) that further cleave these fragments, splitting 3HB-3HB or 3HB-LA dimers into their monomers.

Once the polymers are broken down into these simpler building blocks, other microbes, including various Alpha-proteobacteria and Desulfobacterota, continue the process by consuming the monomers like 3HB and lactate. Working together, these microbial communities ultimately convert the plastic into carbon dioxide, water, and other harmless compounds that ideally return to the marine ecosystem.

The findings of this study fill a critical gap in our understanding of how bio-based plastics degrade in remote marine environments. Its proven biodegradability makes it a promising option for creating safer, more biodegradable materials.

“This research addresses one of the most critical limitations of current bioplastics — their lack of biodegradability in marine environments. By showing that LAHB can decompose and mineralize even in deep-sea conditions, the study provides a pathway for safer alternatives to conventional plastics and supports the transition to a circular bioeconomy,” says Prof. Taguchi.

This dramatically shortens the process of finding effective molecules for cancer treatment from years to a few weeks.

“We are essentially creating a new set of eyes for the immune system. Current methods for individual cancer treatment are based on finding so-called T-cell receptors in the immune system of a patient or donor that can be used for treatment. This is a very time-consuming and challenging process. Our platform designs molecular keys to target cancer cells using the AI platform, and it does so at incredible speed, so that a new lead molecule can be ready within 4-6 weeks,” says Associate Professor at the Technical University of Denmark (DTU) and last author of the study Timothy P. Jenkins.

Targeted missiles against cancer

The AI platform, developed by a team from DTU and the American Scripps Research Institute, aims to solve a major challenge in cancer immunotherapy by demonstrating how scientists can generate target treatments for tumor cells and avoid damaging healthy tissue.

Normally, T cells naturally identify cancer cells by recognizing specific protein fragments, known as peptides, presented on the cell surface by molecules called pMHCs.It is a slow and challenging process to utilize this knowledge for therapy, often because the variation in the body’s own T-cell receptors makes it challenging to create a personalized treatment.

Boosting the body’s immune system

In the study, the researchers tested the strength of the AI platform on a well-known cancer target, NY-ESO-1, which is found in a wide range of cancers. The team succeeded in designing a minibinder that bound tightly to the NY-ESO-1 pMHC molecules. When the designed protein was inserted into T cells, it created a unique new cell product named ‘IMPAC-T’ cells by the researchers, which effectively guided the T cells to kill cancer cells in laboratory experiments.

“It was incredibly exciting to take these minibinders, which were created entirely on a computer, and see them work so effectively in the laboratory,” says postdoc Kristoffer Haurum Johansen, co-author of the study and researcher at DTU.

The researchers also applied the pipeline to design binders for a cancer target identified in a metastatic melanoma patient, successfully generating binders for this target as well. This documented that the method also can be used for tailored immunotherapy against novel cancer targets.

Screening of treatments

A crucial step in the researchers’ innovation was the development of a ‘virtual safety check’. The team used AI to screen their designed minibinders and assess them in relation to pMHC molecules found on healthy cells. This method enabled them to filter out minibinders that could cause dangerous side effects before any experiments were carried out.

“Precision in cancer treatment is crucial. By predicting and ruling out cross-reactions already in the design phase, we were able to reduce the risk associated with the designed proteins and increase the likelihood of designing a safe and effective therapy,” says DTU professor and co-author of the study Sine Reker Hadrup.

Five years to treatment

Timothy Patrick Jenkins expects that it will take up to five years before the new method is ready for initial clinical trials in humans. Once the method is ready, the treatment process will resemble current cancer treatments using genetically modified T cells, known as CAR-T cells, which are currently used to treat lymphoma and leukemia.Patients will first have blood drawn at the hospital, similar to a routine blood test. Their immune cells will then be extracted from this blood sample and modified in the laboratory to carry the AI-designed minibinders. These enhanced immune cells are returned to the patient, where they act like targeted missiles, precisely finding and eliminating cancer cells in the body.

Amit Roy-Chowdhury, a professor of electrical and computer engineering, and doctoral candidate Rohit Kundu, both from UCR’s Marlan and Rosemary Bourns College of Engineering, teamed up with Google scientists to develop an artificial intelligence model that detects video tampering — even when manipulations go far beyond face swaps and altered speech. (Roy-Chowdhury is also the co-director of the UC Riverside Artificial Intelligence Research and Education (RAISE) Institute, a new interdisciplinary research center at UCR.)

Their new system, called the Universal Network for Identifying Tampered and synthEtic videos (UNITE), detects forgeries by examining not just faces but full video frames, including backgrounds and motion patterns. This analysis makes it one of the first tools capable of identifying synthetic or doctored videos that do not rely on facial content.

“Deepfakes have evolved,” Kundu said. “They’re not just about face swaps anymore. People are now creating entirely fake videos — from faces to backgrounds — using powerful generative models. Our system is built to catch all of that.”

UNITE’s development comes as text-to-video and image-to-video generation have become widely available online. These AI platforms enable virtually anyone to fabricate highly convincing videos, posing serious risks to individuals, institutions, and democracy itself.

“It’s scary how accessible these tools have become,” Kundu said. “Anyone with moderate skills can bypass safety filters and generate realistic videos of public figures saying things they never said.”

Kundu explained that earlier deepfake detectors focused almost entirely on face cues.

“If there’s no face in the frame, many detectors simply don’t work,” he said. “But disinformation can come in many forms. Altering a scene’s background can distort the truth just as easily.”

To address this, UNITE uses a transformer-based deep learning model to analyze video clips. It detects subtle spatial and temporal inconsistencies — cues often missed by previous systems. The model draws on a foundational AI framework known as SigLIP, which extracts features not bound to a specific person or object. A novel training method, dubbed “attention-diversity loss,” prompts the system to monitor multiple visual regions in each frame, preventing it from focusing solely on faces.

The result is a universal detector capable of flagging a range of forgeries — from simple facial swaps to complex, fully synthetic videos generated without any real footage.

“It’s one model that handles all these scenarios,” Kundu said. “That’s what makes it universal.”

The researchers presented their findings at the high ranking 2025 Conference on Computer Vision and Pattern Recognition (CVPR) in Nashville, Tenn. Titled “Towards a Universal Synthetic Video Detector: From Face or Background Manipulations to Fully AI-Generated Content,” their paper, led by Kundu, outlines UNITE’s architecture and training methodology. Co-authors include Google researchers Hao Xiong, Vishal Mohanty, and Athula Balachandra. Co-sponsored by the IEEE Computer Society and the Computer Vision Foundation, CVPR is among the highest-impact scientific publication venues in the world.

The collaboration with Google, where Kundu interned, provided access to expansive datasets and computing resources needed to train the model on a broad range of synthetic content, including videos generated from text or still images — formats that often stump existing detectors.

Though still in development, UNITE could soon play a vital role in defending against video disinformation. Potential users include social media platforms, fact-checkers, and newsrooms working to prevent manipulated videos from going viral.

“People deserve to know whether what they’re seeing is real,” Kundu said. “And as AI gets better at faking reality, we have to get better at revealing the truth.”