Canada – Page 2 – Relatix Bio

July 14, 2026

Protein Design’s AI Revolution: Inside David Baker’s “Communal Brain”

“I have this idea of a communal brain.” David Baker, PhD, told me as I sat in his office at the University of Washington (UW) surrounded by colorful and complex figurines of protein structures. It was the one-year anniversary of his Nobel Prize in Chemistry win.

Just outside his doors, a lab of more than 100 researchers was united by the shared ambition to design proteins from scratch (or de novo) for powerful applications across pharmaceuticals, vaccines, biosensors, and more. This “communal brain” housed at the UW Institute for Protein Design (IPD), where Baker led as director, was hard at work developing deep learning methods that could achieve atomic precision.

A small protein composed of 100 amino acids had an astronomical 20¹⁰⁰ possible sequences. Yet, only a vanishingly tiny fraction could fold into stable, functional structures. Misplacing a residue by an angstrom could mean the difference between a drug binding tightly to its target or complete failure.

For the antibody drug market worth hundreds of billions of dollars, Nathaniel Bennett, PhD, former postdoctoral researcher in the Baker lab, says AI-guided antibody design that bypasses the need for time-consuming experimental screens has long been a “holy grail” for a breadth of indications, including cancer and autoimmune disease.

Last November, Bennett and colleagues published a Nature paper demonstrating that full length de novo antibodies could bind user-specified epitopes. AI models could now construct antibody loops, the key region involved in binding that has been historically challenging to design due to its flexible nature.

Despite this technological leap, AI-designed proteins that were manufacturable, remained stable in the body, and avoided unwanted side effects, were still a step away. The gap fueled an industry debate over whether generating de novo medicines was even possible.

When I asked Baker to separate the hype from reality, he didn’t hesitate.

“The reality is that we can now design proteins on a computer,” Baker explained in our video interview. “The hype is that for therapeutics, there’s a lot more than the basic activity of a protein binding or catalyzing a reaction. Whether de novo proteins will revolutionize medicine will require improving our understanding of the biology.”

Nobel guests

Bennett is continuing molecular design research as a co-founder at Xaira Therapeutics. The AI-focused biotech launched in 2024 with over $1 billion in total funding and a star-studded leadership team, including Baker, as a scientific advisor, and Marc Tessier-Lavigne, PhD, former president of Stanford and CSO of Genentech, as CEO. Carolyn Bertozzi, PhD, Nobel laureate in chemistry, Scott Gottlieb, MD, former FDA head, and Alex Gorsky, former CEO of Johnson & Johnson, are among the board of directors.

Xaira is among a staggering list of biotech companies that Baker has co-founded over the past three decades.

“Science all becomes obsolete quickly because the field’s moving!” Baker told me. “The people that you mentor are more important than any science you do. They all go on and do great things.”

2024 Nobel Week was a testament to Baker’s scientific reach. Nearly 200 current and former members of his lab gathered in the Grand Hôtel in Stockholm to celebrate the newly named laureate, who was among a cohort of renowned AI experts who swept the awards ceremony.

Baker shared the Nobel Prize in Chemistry with Google DeepMind duo, CEO Demis Hassabis, PhD, and then-senior research scientist, John Jumper, PhD, whose AI model, AlphaFold, solved the protein structure prediction problem and has become one of the most widely adopted computational tools for drug discovery.

Meanwhile, the Nobel Prize in Physics was jointly awarded to Geoffrey Hinton, PhD, professor emeritus at University of Toronto, and John Hopfield, PhD, professor emeritus at Princeton University, for foundational discoveries that enabled machine learning with neural networks.

Together, the prizes represented a pivotal moment. AI was no longer confined to computer science but had become a transformative force across disciplines, earning recognition as a breakthrough deemed to confer the “greatest benefit to humankind.”

Back at the IPD, Baker’s research group spanned multiple floors. Yet, he knew everyone’s name, where they sat, and moved easily between conversations, bringing together researchers whose expertise might unlock a new direction. In the weeks after receiving the historic Nobel call, Baker chose to remain fully present for his team, implementing a strict “no travel rule,” despite the avalanche of invitations and media attention that accompanied the prize.

“David’s really good at forcing you to break the ice with people,” said Seth Woodbury, a graduate student who is designing metallohydrolases, enzymes that cleave some of the strongest bonds in biology for sustainability applications, including degrading pollutants. “Once you talk to your colleagues at happy hour, it’s not so scary to go ask them a question.”

Woody Ahern, graduate student and co-author of the metallohydrolase Nature paper, adds that Baker has a “very reasonable disdain for hierarchy.”

“Anyone can speak up in meetings. Anyone can question the work. It breeds this culture of staying focused on what matters in an interdisciplinary way,” said Ahern.

When Ria Sonigra was applying to graduate schools in the U.S., every option felt equally far from her home in India. She recalled sending Baker a cold email with questions about the lab. He quickly replied and offered to connect her with another international student who could help her navigate the application process. Today, Sonigra is an IPD graduate student, designing programmable nanopores for molecular sensing and sequencing.

“People outside the lab may think that David can’t pay attention to everyone, which is not true,” Sonigra said. “He knows your project and what he expects of you before the next meeting, even if he has a hundred trainees.”

At one point, Baker waved me over with a smile. “You’re missing chocolate hour!” he said, inviting me to one of many small weekly rituals that embodied the collaborative culture he had built.

Lowest energy search

At GEN’s inaugural virtual event, The State of AI in Drug Discovery, I asked Baker for his initial reactions to winning the Nobel.

“My group was not the first to do protein design,” he said humbly.

The field’s early innings trace back to 1988, when William DeGrado, PhD, demonstrated that sequences not found in nature could achieve stable 3D folds. The work challenged the long-held belief that functional proteins could only arise through evolution.

Steps toward computational design came a decade later, when for the first time, an in silico predicted protein was experimentally validated to adopt a target structure. The work was published in a Science study led by Steve Mayo, PhD.

Baker, alongside then-postdoctoral researcher, Brian Kuhlman, PhD, went a step further in 2003, expanding the design scope to include flexible backbones that represented entirely new folds, making it possible to not only modify natural proteins, but to create new ones from scratch.

“The prize was given because protein design has so much promise now, and that reflects the work of the whole community,” Baker continued.

Today, Degrado, Mayo, and Kuhlman are continuing to advance structural biology as prominent faculty members across University of California, San Francisco (UCSF), California Institute for Technology, and University of North Carolina (UNC) Chapel Hill, respectively.

Top7 was the first protein created on a computer with a custom amino acid sequence that folds into a never-before-seen structure. When viewed at an angle, the transparent partition allows the two forms to become superimposed, illustrating the beauty of uniting sequence and structure. [UW Institute for Protein Design]

Decades before OpenAI co-founder, Andrej Karpathy, coined the term “vibe coding,” Baker’s team was writing a program in FORTRAN. Named Rosetta, the molecular modeling suite simulated proteins atom-by-atom based on biophysical properties, from hydrogen bonds to backbone torsion angles. By calculating free energy, Rosetta could estimate which sequences were most likely to achieve a desired structure: the lower the energy, the more stable the predicted fold.

Yet, a protein’s energy landscape is rugged, with countless local minima among an astronomical number of conformations. Success was rare. Researchers were searching for a single grain of sand across the desert.

Still, “Rosetta was impressive,” said Sierin Lim, PhD, an associate professor at Nanyang Technological University, who is among a group of researchers engineering self-assembling nanoscale containers, known as protein cages, for applications across drug discovery, imaging, and materials science. She recalled watching molecules move on her screen in Singapore in the early 2000s. At the time, Rosetta was the only program that could model proteins.

Over the next twenty years, Baker adamantly pushed Rosetta to be openly available, inviting collaborators to not only use the software, but to improve it.

PyRosetta, a user-friendly Python-based implementation developed by Johns Hopkins University researchers led by Jeffrey Gray, PhD, broadened Rosetta’s access for structural biologists without a strong computational background. Meanwhile, progress in generating high affinity and selective ligand binders and epitope scaffolds for vaccine development were bringing computational proteins closer to real-world medicines.

What started as a single lab project grew into the Rosetta Commons, an international collaboration spanning more than 100 laboratories.

“It was a great move making Rosetta open, seeing what it can do now,” Lim said.

CASP14

Then came a seminal 2017 report titled simply, “Attention Is All You Need.”

Researchers from Google introduced the transformer, a neural network architecture that enabled machines to analyze entire sequences at once. By using a “self-attention” mechanism, AI models could now uncover patterns across massive datasets at unprecedented scale. Soon, large language models (LLMs) trained on internet-scale text could not only understand, but converse in eloquent dialogue with humans.

The generative AI era had begun.

While the rest of the world was captivated by chatbots, structural biologists were sitting on a treasure trove of biological data pristine for machine learning.

For over fifty years, researchers had painstakingly deposited hundreds of thousands of experimentally determined structures in the Protein Data Bank (PDB) for public use. This molecular atlas now offered AI a window into the rules of biology.

In 2020, Baker received a phone call from one of the organizers of the Critical Assessment of protein Structure Prediction (CASP) competition, the biannual experiment that assesses the field’s latest state-of-the-art models.

“The first thing he said was, ’David somebody has done amazingly well this year, and it isn’t you!’” Baker recalled during his Nobel banquet speech. “That was how I first learned about the work of Demis and John.”

Instead of relying on human-defined biophysical rules, AlphaFold quickly learned decades of biochemistry from the PDB, uncovering the hidden instructions governing an amino acid sequence to fold into its 3D shape. At CASP14, the model remarkably predicted structures that were indistinguishable from real-world proteins. Months of laboratory work turned into a computational task completed in minutes.

Hassabis was quick to translate the breakthrough into medicine, taking the helm of DeepMind’s drug discovery spinout, Isomorphic Labs, as CEO a year later.

Today, the company’s IsoDD (Isomorphic Labs Drug Design Engine) platform, expands the druggable landscape by probing previously inaccessible biology, including predicting induced-fit interactions, where proteins change shape upon ligand binding, and identifying hidden binding pockets for drug targeting.

Isomorphic was betting, not on single therapeutic assets, but on a general discovery engine applicable across any disease area. That vision has since secured major pharma partnerships with Novartis, Eli Lilly, and Johnson & Johnson.

“I’ve always believed the No.1 application of AI should be to improve human health,” wrote Hassabis on LinkedIn when announcing Isomorphic’s whopping $2.1 billion funding raise in May.

Diffusion evolution

Concurrently, Baker’s team began applying deep learning to de novo design, drawing inspiration from AI’s emerging ability to generate realistic images. These diffusion models could operate on atomic coordinates and create entirely new protein backbones. Designs were conditioned for desired structural and functional constraints, opening the door to programmable biology.

When Baker’s team presented de novo design model, RFdiffusion (RoseTTAFold diffusion), in Nature in 2023, Mohammed AlQuraishi, PhD, assistant professor of systems biology at Columbia University, described the advance as “a really big deal.”

‘‘Prior to the ‘diffusion evolution’, the success rates were probably on the order of 1 to 10,000, if you’re lucky,’’ AlQuraishi told me shortly after RFdiffusion’s publication. ‘‘With diffusion models, the success rates are closer to the single percentages when you get into the laboratory. It’s a huge magnitude improvement of what it used to be.”

Donald Hilvert, PhD, professor emeritus at ETH Zurich, met Baker twenty years ago while working on enzyme design with Defense Advanced Research Projects Agency (DARPA). Traditional Rosetta methods would carve out binding pockets in existing proteins and install a new catalytic apparatus.

“But the activities were not very good,” Hilvert recalled. Designing catalysis, where success depended on precisely positioning chemical groups to stabilize fleeting transition states, proved far more difficult than engineering a stable protein fold. Rosetta struggled to achieve that level of accuracy, prompting much of the field, including Baker, to turn attention elsewhere.

“Two years ago, David called me and said, ‘Why don’t you come and visit? All these new AI-driven techniques are really changing the game!’” Hilvert told me.

Hilvert has spent the past two summers at the IPD, collaborating with Woodbury, Ahern, and IPD postdoctoral researcher, Donghyo Kim, PhD, to design metallohydrolases using RFdiffusion. He “hardly knew how to turn on a computer,” yet was reading Python scripts and generating his first computational designs within weeks. To his amazement, experiments quickly yielded five or six promising hits.

“There is this common purpose of people helping one another,” Hilvert said. “David sets the tone from the top.”

Application generalist

As I walked through the halls of the IPD, I saw the extraordinary reach of protein design applications firsthand. Desks were intermingled across fields. The proximity was deliberate for ideas to travel as far as possible.

Florence Hardy, PhD, is a postdoctoral researcher tackling a new enzyme design project for global health applications, including streamlining the manufacturing process for therapeutics.

“I always say that I can only think in a ten angstrom sphere at a time,” she chuckled. “That’s just as big as the active site.”

“Most medicines focus on inhibitors,” Xinru Wang, PhD, explained when describing her postdoctoral research developing insulin agonists, or binders that lead to activation, to address metabolic disease. In contrast to blocking activity, “turning on” a signaling complex required precise structural tuning that was a natural fit for the IPD’s expertise.

Last November, Wang and colleagues published a study in Molecular Cell, demonstrating that de novo designed insulin receptor (IR) agonists could extend glucose-lowering effects. The findings offered a therapeutic alternative to escalating insulin doses, which is a known contributor to resistance. Notably, these engineered agonists avoided triggering cancer proliferation that is often associated with excessive insulin activation. Wang is currently an assistant professor at Northeastern University.

Tabitha Tcheau designs DNA binding proteins inducible with small molecules that can recognize novel pathogens and trigger the plant immune system. The highlight of her project, she says, is the ability to span interdisciplinary subgroups, from conformational dynamics, small molecules, and nucleic acids.

“One thing that blew me away here is that people are extremely supportive,” Tcheau told me. “Everyone you ask is super eager to help.”

Enisha Sehgal is among a team of researchers designing sequence specific DNA binding proteins that can power programmable transcription factors, targeted gene regulation, and new genome engineering tools.

“Being in this lab allows you to be a specialist in protein design, but a generalist in all the applications,” Sehgal said. “You get answers faster. You can iterate faster. Science moves faster.”

Visiting researcher and machine learning scientist, Kieran Didi, reiterates how the IPD’s interdisciplinary team enables rapid experimental validation of models. “I’m not going to spend two months in this fantasy world of computational benchmarks,” he said. “In the next week, I know if the model is actually working. Someone will quickly put it to the reality test.”

Postdoctoral researcher and chemist, Declan Evans, PhD, concurs and sees himself as the Alpha tester.

“I can go straight to the developer and say, ‘this is not how computational chemists would use this software,’” Evans said. “You can see changes being made in real time.”

Back in Baker’s office, he told me about his regular weekend escape to the mountains, one of the benefits of living in Seattle. Skiing and hiking were activities he valued highly. When asked to contribute an item to the Nobel Prize Museum, Baker chose a broken ski pole as a symbol that progress often comes through overcoming setbacks.

“But I don’t think people get ideas on top of mountains,” Baker tempered. “If you’re going to be a [principal investigator], you have to really like mentoring. For me, it’s super fun!”

Baker’s most enduring creation may not be any single protein, but rather the network he built—the diverse, inviting, and interconnected communal brain.

The post Protein Design’s AI Revolution: Inside David Baker’s “Communal Brain” appeared first on GEN – Genetic Engineering and Biotechnology News.

July 10, 2026

Brain Scans Reveal Dopamine Damage in Long COVID, Pointing to New Treatments

New brain imaging research has provided the strongest evidence to date that long COVID is associated with injury to the brain’s dopamine system, offering a potential biological explanation for persistent symptoms such as fatigue, slowed movement, lack of motivation, and memory problems.

The study, published in eBioMedicine by researchers at the Centre for Addiction and Mental Health in Canada, used positron emission tomography (PET) imaging to examine dopamine-releasing neurons in people with long COVID. The findings suggest that reduced dopamine nerve terminal density in key brain regions may underlie many of the neurological symptoms experienced by patients and identify a potential therapeutic target for future treatments.

Long COVID is estimated to affect approximately nine million adults in the United States and about 5% of the global population, making it one of the most common chronic conditions to emerge from the COVID-19 pandemic. The condition is characterized by symptoms that persist for at least three months after the initial SARS-CoV-2 infection and commonly includes fatigue, brain fog, memory impairment, and mood changes. Despite its prevalence, there are currently no evidence-based treatments, largely because the biological mechanisms driving these symptoms remain poorly understood.

To investigate whether the brain’s dopamine system is involved, the researchers used PET imaging to measure a well-established marker of dopamine neuron integrity in individuals with long COVID and healthy control participants.

Compared with healthy volunteers, participants with long COVID had significantly lower levels of the dopamine neuron marker throughout the striatum, a brain region that plays a central role in motivation, movement, learning, and cognition. The reduced signal indicates a loss of dopamine nerve terminal density, providing direct evidence that dopamine-releasing neurons are injured in long COVID.

The imaging findings also closely matched patients’ clinical symptoms. Lower dopamine markers in the ventral striatum were associated with greater loss of motivation, reductions in the dorsal putamen correlated with slower movement, and lower marker levels in the caudate were linked to poorer memory performance. The pattern suggests that damage within specific regions of the dopamine system may contribute to distinct neurological symptoms experienced by people with long COVID.

The findings build on the research group’s earlier work demonstrating elevated inflammation in the brains of people with long COVID, particularly in regions rich in dopamine-producing neurons. Because inflammation is known to damage dopamine neurons in other neurological disorders, the new study provides direct evidence that this inflammatory process may be accompanied by measurable injury to the brain’s dopamine system. The close relationship between dopamine neuron loss and symptom severity further strengthens the case that dopamine dysfunction plays a central role in the condition.

The study also shifts attention beyond inflammation alone and suggests that long COVID should be considered, at least in part, a disorder affecting the brain’s dopamine system. That conclusion has important therapeutic implications because several medications already approved for other neurological disorders increase dopamine availability or enhance dopamine signaling. The researchers suggest that repurposing dopamine precursors or drugs that inhibit dopamine metabolism could represent a promising strategy for treating persistent cognitive and neurological symptoms associated with long COVID.

The findings also provide biological evidence supporting the experiences of people living with long COVID, many of whom have struggled for years with debilitating symptoms despite the absence of clear diagnostic markers. By demonstrating measurable injury to dopamine-releasing neurons, the study offers objective evidence that persistent neurological symptoms have a biological basis.

Building on these results, the investigators plan to launch a clinical trial in collaboration with University Health Network to evaluate whether therapies that improve dopamine function can reduce fatigue, improve motivation, and enhance memory in people with long COVID. If successful, the trial could pave the way for one of the first mechanism-based treatment approaches for the condition.

The post Brain Scans Reveal Dopamine Damage in Long COVID, Pointing to New Treatments appeared first on Inside Precision Medicine.

July 9, 2026

Ag Genomics Begins to Bear Fruit

Agrigenomics is, to use an analogy, spring looking toward summer. Wielding modern genomics tools fine-tuned to agriculture, along with AI-driven insights from field technologies and satellites in low Earth orbit, traditional agriculture is transitioning to precision farming and the bounty it brings. Insights are compressing 30 years of field trials into a single growing season and enabling growers to express specific traits without introducing foreign genes and without hit-and-miss Mendelian hybridization.

This intensive application of science starts with comprehensive soil analyses and extends, not only to the major row crops, but also to such lesser-studied areas as fruits and forestry.

It’s all about the soil

Nate Kelly
CEO, Miraterra

Healthy, productive crops all need a good growing environment. “Soil is the most complex, beautiful system on the planet,” Nate Kelly, CEO, Miraterra, points out. Yet, “The soil measurement system in place today is quite archaic,” with manual systems and complex chemistries.

Miraterra’s lead technology is the Digitizer. With shifted-excitement Raman difference spectroscopy as its core, it also employs lasers and advanced signal processing to remove the noise that previously made Raman spectroscopy untenable for soil samples. Robust modeling transforms those data into a molecular fingerprint of soil to 30 ppm, with significantly enhanced resolution anticipated. The Digitizer shortens analysis time from hours to minutes, and makes toxic chemical analysis unnecessary. “Today, we measure texture, organic matter, and carbon and—soon—nutrients,” Kelly says.

After acquiring Trace Genomics and its large soil microbiology data set last year, the company can identify approximately 400,000 different biological components of soil, “things like nitrogen fixers, phosphorus solubilizers, pathogens, and nematodes,” Kelly says.

Miraterra Fill Tray. Healthy crops begin with deep knowledge of soil’s chemistry, biology, and structure. [Miraterra]

As its capabilities increase, Miraterra plans to measure soil chemistry, texture, and biological content. It already accesses public data, satellite imaging, and LiDAR to develop reports, such as nutrient flow, on plots as small as 10 square meters. By adding AI to identify patterns predictive of pest infestations and disease prevalence, he says the company expects to correlate soil health with plant conditions and pathogens.

“Soil is too complex [chemically and biologically] to stick a simple probe in the ground and try to get a reading,” Kelly says. “My aspiration is to cut the cost [of soil analysis] by about 90%, to democratize measurement,” Kelly says. “That means turning a $40 analysis into one that costs less than $5.”

CRISPR: Beyond corn and soy

CRISPR technology is being applied to agrigenomics with the same revolutionary results it created for medicine. As the basis of Pairwise’s Fulcrum Platform, it is expanding agrigenomics well beyond the major crops of corn and soybeans.

Fulcrum technology produced the world’s first seedless blackberry—now in field trials—and a more compact blackberry plant that is commercialized in the Americas. With this compact Fontana blackberry, “Growers can plant more blackberry plants per acre, which helps them be more efficient and produce more yield,” Ryan Bartlett, PhD, CTO, says. A thornless blackberry plant is on the horizon.

The goal is to “make growers more sustainable and efficient, and to give consumers the opportunity to consume more healthy things, like blackberries,” Bartlett says. Fast, precision editing will also help plant breeders quickly adjust to climate change.

Fulcrum features plant-specific CRISPR editing that fine-tunes gene expression rather than simply turning genes on or off. The platform includes additional gene editing tools, enzymes, and trait libraries to help breeders design and test changes and quickly advance specific phenotypes into field trials.

Bartlett calls this “traditional breeding on an accelerated basis.” With Fulcrum, these new blackberries were produced in about three years. Using traditional Mendelian breeding would have taken 10 to 40 years.

Pairwise genomic tools — Genomics tools coupled with advanced analytics enable growers to plant more per acre. [Pairwise]

The speed comes from genome editing that generates the desired phenotype in one cycle, eliminating the need for generations of crosses to develop the features growers want.

Pairwise is also working with “additional permanent crops like cherries,” Bartlett says. “There haven’t been a lot of advancements in the past 50 years.” That may soon change, as Pairwise is working with Sun World to develop a pitless cherry.

New opportunities

“Accelerating timelines and lowering the cost of crop improvement [will] unlock expansive opportunities in agriculture, new species, new geographics, and new traits,” Brad Zamft, PhD, CEO and co-founder of Heritable Agriculture, says.

Heritable focuses on breeding indoor vegetables and forestry, although it also develops fruits and row crops with strategic partners. “The majority of the unmet need comes from placing existing plants in the right places and determining what crosses would make them better,” Zamft says.

Brad Zamft takes pictures in a field — Brad Zamft, PhD
CEO, Heritable Agriculture

Consider strawberries. “We think we’re going to bring a new strawberry variety to the market—start to finish—within four years. The status quo is around a decade.” Heritable can identify desired traits, determine the genes involved, and validate them in growing plants within 18 months, versus 3 to 12 years using traditional methods. Currently, Heritable is adapting genetics from Consorzio Italiano Vivaisti’s (CIV’s) strawberries to grow indoors in Canada.

To speed the process, Heritable uses digital field trials and an AI engine developed in-house specifically for agrigenomics. Potential applications are global. “We have scalable integration of weather and soil to 10-meter resolution anywhere in the world,” Zamft says.

Increasingly accurate correlations of genes to phenotypes shorten the development timeline, Zamft adds. For example, three of the top eight genes Heritable’s team discovered for flowering time in corn proved causative, and three of three in a flavor project for leafy greens. In contrast, he cited a literature analysis that reported that out of 1,671 unique genes that were field-tested across multiple traits, only 22 were identified as validated leads.

To produce and commercialize these innovations, Heritable relies on an alliance of partners in which each partner brings vital strengths to the endeavor, from genomics through production, distribution, and sales. The company also engages in trait development with seed developers and growers, and recently launched a software-as-a-service platform to enable users to predict plant performance under multiple variables.

The company is also active in commercial forestry, using AI to help breeders make placement and breeding decisions that could shorten the breeding cycle by more than half.

Gene editing = no GMOs

Verinomics built its foundation on plant genomics, computational biology, and trait mapping to enable breakthroughs in multiple crops. Most recently, it developed Nonpareil+, a self-pollinating Nonpareil almond variety that may increase per-acre productivity by 30%.

That anticipated productivity gain is directly tied to self-pollination. Because the Nonpareil variety—which is the dominant commercial almond variety in California—is self-incompatible, it requires cross-pollination. That, in turn, requires planting alternating rows of other almond varieties as pollinators and then renting beehives (at about $400 per acre) to pollinate the orchard.

“There’s no way to create a self-compatible Nonpareil using conventional breeding,” Stephen Dellaporta, PhD, founder of Verinomics and professor at Yale University, points out. Therefore, using Verinomics’ Genesis gene editing platform, “we identified the self-incompatibility gene and edited it to a self-compatible gene.” The resultant Nonpareil+ is genetically identical to the Nonpareil except that it is self-pollinating.

Growers are beginning to plant it this year, with the expectation of reducing or eliminating the need for multi-variety almond orchards and bee hives. If it works as expected, growers can harvest all the trees at once, rather than needing separate harvests for multiple varieties.

Almonds aren’t the only crop on Dellaporta’s mind. Back in the lab, “we just completed 60 whole genome sequences, assemblies, and annotations,” he says. The company works with partners to address concerns in multiple crops, making adaptations without introducing foreign DNA.

The bacterial disease known as citrus greening is an example. It’s killed millions of acres of citrus trees, according to the U.S. Department of Agriculture. “There’s no known resistance within the domesticated citrus germplasm,” Dellaporta says. Crossing a wild-type, resistant citrus with a domesticated citrus would take decades to produce a resistant, domesticated citrus, he points out. “Gene editing may create a modification to allow the plant to be resistant without losing varietal identity.”

Precision farming can bring incredible benefits to agrigenomics, just as precision genomics is doing for medicine. As agrigenomics begins to bear fruit, developers can look forward to a genomics-fueled bounty very, very soon.

The post Ag Genomics Begins to Bear Fruit appeared first on GEN – Genetic Engineering and Biotechnology News.

July 9, 2026

Altered brain entropy and functional connectivity patterns in peritoneal dialysis patients

ObjectiveTo explore abnormal changes in brain entropy (BEN) and resting-state functional connectivity (RSFC) in peritoneal dialysis (PD) patients and their associations with cognitive impairment (CI).MethodsFifty-three PD patients and 49 age-, gender-, and education-matched healthy controls (HCs) were enrolled. Resting-state functional magnetic resonance imaging (rs-fMRI) was performed to calculate BEN and RSFC. Neuropsychological assessments and clinical indicator collection were conducted. PD patients were divided into mild cognitive impairment (MCI) and non-cognitive impairment (NCI) groups using Montreal Cognitive Assessment (MoCA) scores. Correlation analyses were performed between BEN/RSFC values and neuropsychological/clinical indicators.ResultsPD patients exhibited significantly poorer performance in multiple cognitive scales than HCs (all p < 0.001). Compared with HCs, PD patients had decreased BEN in the right middle occipital gyrus and left caudate nucleus, and increased BEN in the left middle temporal gyrus and right fusiform gyrus. Reduced RSFC was found between the right middle occipital gyrus and the right fusiform gyrus, right middle frontal gyrus, and right precuneus in PD patients. BEN and RSFC values were correlated with emotional scale scores, cognitive scale subscores, and clinical indicators (e.g., glycosylated hemoglobin, transferrin saturation).ConclusionPatients with end-stage kidney disease undergoing peritoneal dialysis present abnormal brain entropy and functional connectivity patterns. These alterations are associated with systemic metabolic disorders, long-term dialysis treatment, and cognitive/emotional impairment.

July 9, 2026

Local field potentials for target localization in centromedian deep brain stimulation for epilepsy

ObjectiveTo evaluate whether local field potential (LFP) spectral profiles can serve as a candidate “spectral fingerprint” for physiological confirmation of centromedian-parafascicular (CM–Pf) targeting during thalamic deep brain stimulation (DBS) for drug resistant epilepsy (DRE).MethodsThis is a retrospective study of 10 patients (20 leads) who underwent CM-DBS implantation for DRE at a single tertiary center. Postoperative CT and preoperative MRI were co-registered, normalized to the Montreal Neurological Institute (MNI) space, and reconstructed using Lead-DBS software to anatomically localize contacts. BrainSense™ Survey recordings were obtained at least 3 weeks post-implant during routine programming. LFP frequency content was analyzed, and prominent peaks were identified and classified into canonical frequency bands (theta, alpha, beta). These spectral profiles were then mapped to MRI-based anatomical localizations, and statistical tests were applied to assess associations between peak patterns, contact localizations and thalamic subregions.ResultsContacts were distributed as follows: 50 in the CM, 16 in the Parafascicular (Pf), 15 in the Centrolateral, 8 in the Mediodorsal, and 7 in the Ventrolateral (VL) nuclei. Of the 10 representative spectral localizations confined to the CM/CM-Pf region, 8 (80%) displayed a distinct dual-peak spectral profile with peaks in the theta/low alpha (5.5–9 Hz) and high beta (20–30 Hz) bands (mean frequencies: 7.63 Hz and 21.02 Hz, Fisher’s exact test, p < 0.001). Single-peak profiles showed no significant association with specific nuclei (p = 0.871). Contacts overlapping other thalamic nuclei more frequently exhibited narrow 10–15 Hz peaks (p = 0.005) or triple-peak profiles (p = 0.02), suggesting mixed structural contributions.ConclusionA dual- band candidate spectral pattern consisting of theta/low alpha and high beta peaks was associated with the CM-Pf region in this cohort. This finding provides early evidence supporting the feasibility of incorporating passive LFP recordings as a physiologic marker of target engagement. Future work to prospectively compare bipolar survey-based localization with monopolar recording strategies could enable development of a state-based, physiologically informed spectral atlas to refine CM-Pf targeting in thalamic neuromodulation for DRE.

July 8, 2026

High-Fat Diet Works with Gut Microbes to Benefit Cancer Treatment

A high-fat diet can result in better outcomes from cancer immunotherapy by improving the balance of microbes in the gut, early research shows.

The findings reveal how diet shapes immune states and how altering it could improve cancer treatment outcomes.

The study, reported in Nature, revealed that an obesogenic diet improved response to immune checkpoint inhibitors, with this occurring outside its impact on bodyweight or metabolism.

Instead, the benefits were linked with the creation of a favorable microbial ecosystem, which worked synergistically with the diet.

The results offer a potential explanation for the obesity paradox in cancer treatment, in which high body mass index is associated with improved immunotherapy responses to several types of cancer.

“Prolonged obesogenic diets are associated with well-established health risks and are not proposed as long-term interventions for patients with cancer,” caution researcher Lysanne Desharnais, PhD, from McGill University in Montreal, Canada, and colleagues.

“Rather, our work highlights the therapeutic potential of short-term dietary modulation, and of specific bacteria or microbial-derived metabolites, to create an optimal host ecosystem for immunotherapy responses.”

Previous research has indicated that the gut microbiota regulates immunotherapy responses, with diet shaping both the microbial and metabolic states that influence immune function.

Gut dysbiosis is a hallmark feature of obesity that links diet, the microbiome and health risk factors. Yet paradoxically, studies have shown that high BMI is associated with improved ICI responses for several types of cancer.

To investigate further, Desharnais and colleagues examined the impact of 12 mouse diets to designed to reflect variation in the human diet and also studied the impact of fecal microbiota transplants (FMTs).

In addition to traditional low fat, high fat, and Western diets, they used diverse ingredients as sources of protein, carbohydrates, fat and fiber to mimic Mediterranean, Japanese, vegan, American and ketogenic diets.

The team found that the efficacy of immune checkpoint inhibitors was dependent on the diet-gut axis rather than metabolic dysfunction, creating a favorable host ecosystem for therapy.

Lactobacillus johnsonii was as one of several key gut species associated with response against programmed cell death protein (PD-1), a protein found on T immune cells that helps keep immune responses in check.

Nonetheless, the researchers reported, “FMT, monocolonization, and diet switch experiments demonstrated that diet was more influential than microbiota composition alone, with maximal benefits observed when favorable bacteria were paired with favorable diets, due to synergistic metabolic remodeling.”

Obesogenic diets were not uniformly beneficial.

For example, the Mediterranean diet—high in fat from olive oil—retained a microbiota resembling lean, metabolically healthy mice, including low Lactobacillus, and remained insensitive to immune checkpoint inhibitors.

Conversely, a diet high in the soluble plant fiber inulin was lean and responsive to immune checkpoint inhibitors, yet had a distinct microbial composition characterized by low Lactobacillus and high Bifidobacteria.

Aromatic amino acid metabolites mediated the efficacy of immune checkpoint inhibitors. Tyrosine-derived phenylpropionate metabolism was a key pathway leading to production of desaminotyrosine and related metabolites, which enhanced T cell effector function.

There were also beneficial rises in indole-containing tryptophan metabolites, including indole-3-lactic acid, although this was not specifically dependent on Lactobacillus.

The researchers concluded: “Together, our findings identify diet–microbiome synergy as a mechanistic basis for the obesity paradox in cancer immunotherapy and a tractable target for improving therapeutic responses across diverse patient populations.”

The post High-Fat Diet Works with Gut Microbes to Benefit Cancer Treatment appeared first on Inside Precision Medicine.

July 8, 2026

Millions of People in Canada Are Finding AI-Enabled Support for Mental Health Effective Amid Ongoing Questions Around Trust.

(OTTAWA) July 8, 2026 — New polling shows approximately six million people in Canada used AI-enabled tools for mental health support in the past year and most find them effective. Today, the Mental Health Commission of Canada (the Commission), in partnership with Mental Health Research Canada (MHRC) and Pollara Strategic Insights, releases the first nationally representative data on how people in Canada engage with digitally supported mental health tools, including AI and virtual care, across every province and demographic.

Quick Facts:

1 in 7 people in Canada used AI mental health tools in the past year
Three out of four who used AI and virtual mental health services found them effective for their well-being
Only 14 % trust AI tools, just 2% trust them completely
40 % of AI users said they were more likely to seek professional care
Nearly half (45%) who accessed mental health care did so virtually, in whole or in part

WHY IT MATTERS

People in Canada are turning to AI as a convenient way to access mental health support. AI-enabled tools may offer greater convenience and accessibility. Among those surveyed, AI is being used because it is:

Free or low-cost; 46% of AI users cite this as the reason they use it during a time when financial stress is itself a cause for anxiety.
Always available; 44% of AI users cite 24/7 access.
Immediate and convenient; it can be used from anywhere without travelling or waiting for an appointment. For someone in rural Canada, it saves time and travel costs.
Seemingly private; 39 % of AI service users cite private, anonymous support as a reason for use, while privacy and data protection remain key public concerns.

AI is most used for general well-being (42%), companionship (36%), and mild-to-moderate stress (36%), and 40% of AI users said they were more likely to seek professional care.

WHO IS USING IT AND HOW MUCH DO THEY TRUST IT?

Use is higher among people in Canada under 35 (27%; 29% among men aged 25–34), newcomers to Canada (28%), racialized people in Canada (23%), and 2SLGBTQI+ communities (20%), populations that may experience greater barriers to traditional care.

Overall, trust remains low, particularly for AI-enabled tools, where only 2% of people in Canada trust them completely. People in Canada over 55 show the lowest adoption and trust.

VIRTUAL CARE: EFFECTIVE AND MORE TRUSTED BUT FALLS SHORT OF IN-PERSON SERVICES

45% of people in Canada who used mental health services in the past year did so virtually, with 75% reporting positive outcomes. However, nearly 1 in 3 prefer a hybrid model that combines virtual and in-person services. The data signals what people in Canada need: well-designed tools for safer digital mental health care that they can trust.

THE COMMISSION OFFERS GUIDANCE FOR THE DIGITAL MENTAL HEALTH ERA

The Commission is Canada’s trusted resource for safe digital mental health — assessing apps and tools, setting evidence-based standards, and leading the national conversation on guidance for AI in mental health and substance use health care.

As virtual services and AI-enabled tools continue to expand rapidly across the mental health landscape, there is a growing need for evidence-based insight into how people in Canada engage with, understand, and perceive them. The Commission partnered with MHRC to leverage their ongoing national polling initiative and provide timely insights into usage, attitudes, and concerns related to e-mental health and AI.

The polling is clear: people in Canada want to close the gap between availability and trust. The Commission is working with the Canadian Centre on Substance Use and Addiction and collaborators, provincial governments, technology developers, and health system partners to establish guidance for AI.

“Six million people in Canada have already used AI for mental health support and most found it convenient and effective for their well-being. It is critical that AI is safe and equitable to increase public trust and reduce harms.” – Lili-Anna Pereša, President and Chief Executive Officer, Mental Health Commission of Canada

“The people turning to digitally-supported mental health tools are often those facing some of the greatest barriers to care. Making sure these tools are safe, effective, evidence-based and human-centred is a matter of equity. Ongoing research is essential to understanding where they help and where safeguards are needed.”– Akela Peoples, Chief Executive Officer, Mental Health Research Canada

About Mental Health Commission of Canada
As an independent, not-for-profit with charitable status, the Commission collaborates with leading experts and organizations nationally and internationally, including with people with lived and living experience, to develop national guidelines, standards and strategies, promote innovation and best practices, reduce stigma, increase mental health literacy, and support all levels of government to improve mental health outcomes for everyone living in Canada.  The Commission is Canada’s trusted resource for digital mental health best practices with the e-Mental Health Strategy for Canada, app assessment, e-modules for e-mental health implementation, and AI guidance for mental health and substance use health.

About Mental Health Research Canada
As an independent national charity, MHRC works hard to enable a future where mental health in Canada is transformed using evidence, data and stakeholder engagement. We unite researchers, communities, and people with lived experience to bridge gaps in care through national population polling, rapid data reporting, and partnerships that inform policy to improve outcomes. Learn more at www.mhrc.ca

About the Polling
Conducted by Pollara Strategic Insights in partnership with Mental Health Research Canada and the Mental Health Commission of Canada, this national poll (n=3,519) is the first representative data on AI use for mental health in Canada. Full findings: https://mentalhealthcommission.ca/AI-polling-report

About the Funding
The views in this report solely represent the views of the Mental Health Commission of Canada. Production of this report is made possible through financial contribution from Health Canada.

Media Contact
Heather Bakken, Pendulum Group
email: heather@pendulumgroup.ca
cell: 613-406-5432

The post Millions of People in Canada Are Finding AI-Enabled Support for Mental Health Effective Amid Ongoing Questions Around Trust. appeared first on Mental Health Commission of Canada.

July 7, 2026

KLK1 Expands Possibilities to Restore Vascular Health

Knowing that the protein tissue kallikrein-1 (KLK1) is effective in treating ischemic diseases is one thing. Manufacturing it as a recombinant protein has been quite another. So, when DiaMedica Therapeutics cracked the manufacturing aspect, it was well on its way toward commercializing KLK1 therapeutics.

The manufacturing breakthrough came when researchers realized that protein activity (which is essential for therapeutic benefit) was linked to certain glycosylation patterns. DiaMedica engineered the molecule to reflect those glycosylations and also made two changes to the amino acid sequence to improve manufacturability. “Then we partnered with Catalent,” Rick Pauls, president and CEO, says. “We are using its GPEx^® technology with CHO cells,” which produces more cells within the same timeframe and thus lowers manufacturing costs.

Tenacity in action

This happened neither easily nor quickly. To understand the measure of this achievement, we need to look at DiaMedica’s history.

KLK1 came to DiaMedica’s attention because of liver research. “A liver physiologist cut the vagus nerve [which regulates liver metabolism] and discovered that the rats, effectively, became diabetic,” Pauls recounts. “We hypothesized that when a healthy person consumed a meal, the liver releases something that acts as an insulin sensitizer. We did some basic work and identified KLK1 as that insulin sensitizer.”

The company was founded in 2004 to develop a KLK1 therapeutic for complications related to Type II diabetes. Those trials failed. “It’s a long story,” says Pauls, that left the company “pretty close to bankrupt.”

DiaMedica, though, was tenacious. “We knew there was a human urine form of this protein that had been used for a few decades in Asia to treat acute ischemic stroke, and a porcine form treating hypertension for decades as well,” Pauls recalls. DiaMedica had the protein and the manufacturing know-how to produce active, recombinant proteins, and—with KLK1 levels low in stroke patients—a reason to pivot.

Ischemic stroke and preeclampsia

Its lead compound, DM199 (rinvecalinase alfa), is enrolling patients in Phase II/III trials for acute ischemic stroke. Called the ReMEDy2 trial, the company anticipates an interim readout near year’s end. Additionally, Phase I and II studies for preeclampsia and Phase II studies for fetal growth restriction are underway.

“This is protein restoration,” Pauls says. It targets ischemic stroke patients who have missed the three-to-four-hour post-stroke treatment window for tissue plasminogen activator (tPA) therapeutics or mechanical thrombectomy. Those patients constitute approximately 80% of acute ischemic strokes today, so “there is a huge unmet medical need,” Pauls says.

DM199 works by restoring normal levels of the KLK1 protein. KLK1, in turn, is thought to enhance the production of nitric oxide, prostacyclin, and endothelium-derived hyperpolarizing factor. Pouring through their own preclinical and clinical results, the DiaMedica team noticed that DM199 consistently enhanced blood circulation and lowered blood pressure.

That realization drove the team to also target preeclampsia, a hypertensive disease of pregnancy that Pauls says may be the company’s most exciting application for investors.

Unlike approved blood pressure therapeutics, DM199 does not cross the placental barrier, a critical safety feature that protects the fetus. After examining early clinical data, DiaMedica scientists also realized that increasing blood flow to the placenta could target the root cause of the disease and perhaps gain another few weeks of crucial time in utero for the fetus.

“Today, there are no approved treatments. Mothers are given labetalol and nifedipine to control blood pressure and to extend the baby’s time in utero for only a few days.” Results are less than ideal, and the consequences can be severe.

Pauls says, “Some 40% of babies born before 28 weeks could have long-term disabilities, and 10 to 15% will have problems with eyesight for life. There’s been a real lack of drugs in development because developers are worried about harming the baby.”

An investigator-led Phase II clinical trial is enrolling. Later this year, the company plans to initiate its own Phase II study focused on early-onset preeclampsia after recently receiving regulatory clearance to start the study in Canada.

If the molecule eventually is approved for preeclampsia, DM199 seems poised to become, perhaps, the first approved treatment that offers the potential to extend gestational days and possibly address a root cause of preeclampsia.

Leveraging the pivot

Unlike many biopharmaceutical companies, DiaMedica has been able to bypass some of the usual first steps by leveraging existing studies on KLK1, as well as existing clinical data for stroke and preeclampsia.

That allows researchers to focus on humans without the translational issues inherent in animal studies. It also helps the company identify the human subgroups most likely to benefit from these treatments and the most appropriate dosing regimen early. “Having that clinical data helps de-risk our program and gives a better possibility of success,” Pauls says, because, as he points out, “Animals are not the same as people.”

Once the company pivoted to its current indications six or seven years ago, the challenge shifted from getting and manufacturing the active form of the protein to selecting the best indications and assembling the right team members.

“In the early days, maybe we didn’t have the right level of experience with limited capital,” he admits. Today, “we’ve been able to bring people on board who have brought drugs to market.”

Readouts due in 2027

Currently, the company is focused tightly on its clinical trials. The next step for DiaMedica is to get readouts from many of those, with five readouts on various aspects of the programs expected between now and the end of 2027. Each of those readouts will report on about 30 patients and will be factors in the design of a subsequent pivotal trial.

Additionally, an interim analysis of the first 200 patients in its acute ischemic stroke trial is expected by the end of the year, Pauls says. “If we see a drug effect that’s comparable to our Phase II trial or the data with the urine form (of KLK1) from China—which treats close to a million patients per year—we’ll be looking at completing enrollment the following quarter for stroke and then for preeclampsia. DiaMedica is dedicated to offering second chances to acute ischemic stroke patients and others who haven’t had them before, all while pivoting to new opportunities itself. Now, as trials advance, Pauls says, “I think this should be a straightforward path.”

The post KLK1 Expands Possibilities to Restore Vascular Health appeared first on GEN – Genetic Engineering and Biotechnology News.

July 7, 2026

Biomanufacturing in Space to Be Key Topic at ISSCR 2026

Scientists from the Cedars-Sinai Board of Governors Regenerative Medicine Institute, including investigators from the Cedars-Sinai Biomanufacturing Center, say they will share groundbreaking discoveries and discuss new frontiers in research at ISSCR 2026. The annual meeting of the International Society for Stem Cell Research will take in Montreal from July 8–11.

The Cedars-Sinai Center for Space Medicine Research has taken a special interest in biomanufacturing in space. It studies how microgravity aboard the International Space Station and other space platforms can be used to manufacture higher-quality biomedical products.

Researchers investigate the production of stem cells, organoids, engineered tissues, exosomes, and biopharmaceuticals, taking advantage of the reduced effects of gravity on cell growth and three-dimensional tissue formation.

The center collaborates with NASA, commercial space companies, and biotechnology partners to determine whether space-based manufacturing can yield therapies with improved quality, consistency, and function. Its long-term goal is to translate discoveries made in space into scalable manufacturing methods that advance regenerative medicine, drug development, and personalized healthcare on Earth.

At the upcoming ISSCR 2026 meeting, Arun Sharma, PhD, director of the Center for Space Medicine Research, will participate in a session co-sponsored by Cedars-Sinai on regenerative medicine in low Earth orbit. The focus of Sharma’s talk is accelerating development of organoid-based disease modeling and stem cell therapies due to increased access to microgravity, as well as in-space biomanufacturing.

Avinash Srivastava, PhD, a biomedical scientist in the Cedars-Sinai Biomanufacturing Center, is presenting information on the center’s proprietary integrated induced pluripotent stem cell biomanufacturing platform. The platform integrates standardized manufacturing with advanced bioprocessing to facilitate the scalable production of high-quality engineered cell therapies.

Dhruv Sareen, PhD, associate professor of Biomedical Sciences and founding director of the Cedars-Sinai Biomanufacturing Center, is presenting research on the integration of an in situ seed plating system into the center’s manufacturing workflow to streamline production of complex induced pluripotent stem cell lines for clinical-grade and research use.

The post Biomanufacturing in Space to Be Key Topic at ISSCR 2026 appeared first on GEN – Genetic Engineering and Biotechnology News.

July 2, 2026

Experiences With Technology Among Adults Aging With HIV Engaged in an Online Community–Based Exercise Intervention Study: Longitudinal Qualitative Descriptive Study and Secondary Data Analysis

Background: As individuals with HIV live longer, many now face the health consequences of aging and multimorbidity, known as disability. Exercise can mitigate disability; however, engagement in exercise among adults living with HIV varies. Technology-based interventions, such as telerehabilitation, may help mitigate geographical, financial, and time barriers to community-based exercise (CBE). However, little is known about the experiences with technology uptake and usage among adults living with HIV. Understanding these experiences is essential to inform the design of inclusive, accessible, and sustainable online interventions. Objective: This study aimed to describe experiences with technology uptake and usage among adults aging with HIV participating in a 6-month online CBE intervention and explore how these experiences changed over time, from baseline to postintervention. Methods: We conducted a longitudinal qualitative descriptive study and secondary analysis using interview data from adults living with HIV who were engaged in a CBE intervention study in Toronto, Canada. Participants engaged in a 6-month online CBE intervention consisting of thrice-weekly exercise supervised biweekly through online personal coaching sessions, weekly group exercise classes, and monthly self-management education sessions (via Zoom). The technology used included Zoom software and a webcam, as well as the Sweat for Good YMCA app and the YMCA Virtuagym website; participants wore a wireless physical activity monitor (Fitbit Inspire 2) throughout. Participants completed interviews at baseline and postintervention. We conducted a group-based content analysis of interview transcripts, focusing on digital access, setup, usage, and perceptions of technology. Questionnaire data describing digital literacy and access to technology provided additional context to the interview data. Results: Eleven participants completed at least one interview. We analyzed 19 interview transcripts from 11 participants (women: n=6, 55%; men: n=5, 45%; median age 52, IQR 45-60 y). Experiences with technology uptake and usage among adults aging with HIV were characterized by four components: (1) preparations for technology (technology setup), (2) interactions with technology (preferences for different types of technology, preferences for mode of delivery, and ease of usage), (3) facilitators and satisfaction with technology (facilitators to technology uptake and usage and satisfaction with technology), and (4) challenges and frustrations with technology (barriers to technology uptake and usage and frustrations with technology). Experiences with technology across participants were influenced by intrinsic contextual factors (prior exposure to technology) and extrinsic contextual factors (COVID-19 pandemic and technological and social support). Conclusions: Experiences with technology among adults aging with HIV engaging in an online CBE intervention varied from increasing ease of use to increasingly burdensome over time. Results highlight the need to incorporate personal preferences and ongoing technological support when implementing online CBE with adults aging with HIV.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/0a8d6a5175ae1cbe3aafc0c9c2827f3c" />