Radically different
One of the biggest obstacles in targeting CRISPR therapy deliveries directly into the body isn’t the editing chemistry, it’s the size of the editors themselves. The field’s workhorse nucleases, including Cas9 and Cas12a, are considerably large (exceeding 1,300 amino acids) to fit inside adeno‑associated virus (AAV) vectors, the most widely used delivery vehicle for in vivo gene therapy. That size mismatch has forced most clinical applications to rely on ex vivo editing of blood or bone‑marrow‑derived cells, leaving many tissues out of reach. A smaller CRISPR system that can be packaged into AAV without sacrificing efficiency has long been a key missing piece.
A new study published in Nature Structural & Molecular Biology takes a major step toward that goal. Researchers at the University of Texas at Austin and collaborators report the discovery and engineering of a compact Cas12f nuclease that performs robustly in human cells, a notable advance for a class of miniature enzymes that have historically shown lower efficiencies in mammalian cells compared to larger systems. The paper is titled, “Comparative characterization of Cas12f orthologs reveals mechanistic features underlying enhanced genome editing efficiency.”
The team began by mining metagenomic datasets for naturally small CRISPR enzymes and identified a previously uncharacterized ortholog, Alistipes sp. Cas12f (Al3Cas12f). Despite its compact size—roughly one‑third that of Cas9—the nuclease showed unexpectedly strong activity in human cells. In initial screens, Al3Cas12f produced more than 50% editing at many genomic sites and exceeded 90% at several targets. The authors wrote, “Results from a gRNA screen targeting intron 1 of the ALB gene, exon 3 of the APOA1 gene and the AAVS1 site within PPP1R12C intron 1 showed that 27 target sites displayed >10% editing, 19 sites displayed >50% editing and 10 sites displayed >90% editing across AAVS1 and APOA1.”
Cryo‑EM structures revealed why this miniature enzyme punches above its weight. Compared with other Cas12f orthologs, Al3Cas12f forms a more extensive and interlocking dimer interface, creating a stable, preassembled complex that supports efficient R‑loop formation. The guide RNA scaffold also appears naturally streamlined: unlike other Cas12f gRNAs, it lacks an extraneous stem‑loop and adopts a compact conformation that docks cleanly into the protein. As the authors noted, Al3Cas12f achieves “efficient R‑loop formation through a stable dimer interface and a naturally optimized gRNA.”
Using these structural insights, the team engineered an enhanced variant, Al3Cas12f RKK, that dramatically boosts editing efficiency across genomic loci. In human cells, the variant increased editing from below 10% to more than 80% at many targets, with some sites reaching 90%. The researchers tested the system in a leukemia‑derived human cell line, focusing on genes implicated in cancer, atherosclerosis, and ALS.
The mechanistic comparisons were equally revealing. By solving the structures of two additional Cas12f orthologs—Oscillibacter sp. Cas12f and Ruminiclostridium herbifermentans Cas12f—the team noted “divergent architectures and regulatory features governing protospacer-adjacent motif recognition, gRNA binding, dimerization, and DNA cleavage.” Al3Cas12f’s extended helices and mortise‑and‑tenon‑like interactions appear to be lineage‑specific adaptations that stabilize the nuclease and support high activity.
The next step is to test whether the enzyme maintains its performance when packaged into AAV vectors. If successful, the system could offer a blueprint for engineering future generations of compact CRISPR tools.
The post Engineered Miniature CRISPR Boosts Gene‑Editing Efficiency in Human Cells appeared first on GEN – Genetic Engineering and Biotechnology News.
Around half the outputs from five commonly used artificial intelligence (AI) chatbots could lead users to ineffective or harmful medical choices without professional guidance, suggests research led by the Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center.
As reported in BMJ Open, the researchers tested the free web versions of Gemini, DeepSeek, Meta AI, ChatGPT 3.5 and Grok available in 2024. They created 50 different adversarial prompts intended to test whether the AI models would give a problematic response or not.
The prompts were intended to realistically represent the kinds of queries members of the public might enter about health topics ranging from cancer to vaccines to stem cells, nutrition, and athletic performance. Some prompts required a specific answer and some were more open.
The researchers collected 250 responses to their prompts and categorized them as non-, somewhat, or highly problematic, using pre-defined criteria. Around 50% were problematic, 30% somewhat problematic and 19.6% highly problematic. Open-ended prompts received the most problematic answers.
In terms of the specific models, Grok produced a disproportionate share of highly problematic answers, while Gemini produced the fewest highly problematic and the most non-problematic responses. Topic-wise, the chatbots appeared more accurate when asked about cancer and vaccines, but less so when asked about stem cells, athletic performance, and nutrition.
Reference lists provided to users by the models were limited or inaccurate and the answers required some knowledge to interpret properly and were aimed at college-educated users.
“Despite adversarial pressure, chatbots typically responded in a confident, authoritative tone. Refusals to answer and explicit caveats or disclaimers were rare, reflecting the models’ strong tendency to provide an output even when prompts steered toward contraindicated advice,” write lead author Nicholas Tiller, PhD, a research associate at the Lundquist Institute, Harbor-UCLA Medical Center, and colleagues.
“As the use of AI chatbots continues to expand, our data highlight a need for public education, professional training and regulatory oversight to ensure that generative AI supports, rather than erodes, public health,” they conclude.
The post Popular AI Chatbots Can Provide Misleading Medical Information appeared first on Inside Precision Medicine.
Technology-based interventions in the field of disability and rehabilitation, which serve assistive, therapeutic, and/or service delivery functions, are considered complex due to the skills required of providers and recipients, degree of individual tailoring, and diversity of use settings. Feasibility studies are an important step in the evolution of complex interventions that can help refine the intervention, inform implementation, and prevent wasted resources. However, guidance is lacking regarding specific considerations for feasibility studies of technology-based interventions in disability and rehabilitation, which leaves researchers and developers reliant on resources from other fields that do not address important technology properties. To advance the field, context-specific definitions, considerations, and evaluation dimensions must be explicitly outlined to ensure that feasibility studies are constructively designed to meet the unique needs of these interventions. In this viewpoint article, we (1) propose a definition and framework for feasibility studies within the specific context of technology-based disability and rehabilitation interventions, (2) highlight important and unique imperatives for feasibility studies of these interventions, and (3) articulate relevant feasibility dimensions and associated evaluation criteria for these interventions. Building on previous work, we distinguish between feasibility studies, wherein we focus on iterative intervention refinement by addressing key development questions (eg, usability), and pilot studies, which are small-scale versions of a larger study that will evaluate intervention outcomes. Integrating previous typologies, we present 13 feasibility dimensions relevant to technology-based interventions and provide sample evaluation criteria, focusing on the intervention itself rather than study design considerations (eg, trial management). This information may be useful for research and development communities (academic, clinical, or industry) to inform comprehensive feasibility studies that examine unique aspects of technology-based interventions to promote real-world impact. This contribution encourages greater harmonization of terminology and evaluation methods to streamline interpretation and comparison across studies.
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Background: Artificial intelligence–powered conversational agents (ie, chatbots) are increasingly popular outlets for users seeking psychological support, yet little is known about how users experience early-stage prototypes or which therapeutic processes contribute to clinical improvement. A transparent evaluation of emerging chatbot prototypes is needed to clarify if, how, and why artificial intelligence companions work and to guide their continued development. Objective: This mixed methods pilot study evaluated user experience, acceptability, and preliminary clinical signals for an early-stage mental wellness chatbot. We also examined whether baseline symptom severity moderated clinical improvement. Methods: Three sequential cohorts (n=125) completed a 2-week, incentivized chatbot exposure (approximately 60 min per week). Participants provided first-impression ratings, qualitative feedback, and pre–post assessments of depressive symptoms (PHQ-8 [Patient Health Questionnaire-8]), anxiety symptoms (GAD-7 [Generalized Anxiety Disorder-7]), psychological distress, well-being, and loneliness. Statistical models estimated symptom change and tested interactions with baseline symptom severity. Mixed methods analysis integrated quantitative outcomes with large language model–assisted qualitative content analysis of open-ended responses. Results: Participants described the chatbot as accessible, easy to use, and emotionally validating, while citing limitations in personalization and conversational depth. Qualitative responses consistently highlighted early therapeutic processes such as emotional validation, goal setting, and perceived attunement. Regression models showed significant pre–post reductions in depressive (Hedges =–0.32) and anxiety (=–0.32) symptoms, alongside modest improvements in distress and well-being. Baseline severity moderated improvement, with marginal effects indicating larger predicted reductions at higher PHQ-8 and GAD-7 baseline scores (eg, PHQ-8=15: =–0.84; GAD-7=15: =–0.62). Conclusions: This pilot provides a comprehensive view of early chatbot development and suggests promising user experiences and preliminary symptom improvements under structured pilot conditions. By integrating experiential and exploratory clinical data, the study identifies candidate process targets to inform ongoing refinement. Findings support continued development and demonstrate procedural feasibility for progression to larger, longer-term trials evaluating engagement and clinical outcomes under more naturalistic conditions.
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Cellares reported that the first two patients have been dosed with Cabaletta Bio’s investigational CAR T cell therapy rese-cel (resecabtagene autoleucel) manufactured on Cellares’ Cell Shuttle
instrument. The administration of an autologous cell therapy, which met all release criteria and was manufactured on an automated manufacturing platform, represents an important step on the journey to realizing a future where scalable manufacturing of autologous products to supply thousands of patients per year can be achieved with minimal capital investment and a low cost of goods, according to a Cellares spokesperson.
While the transformative clinical benefits of autologous CAR T cell therapy are well established in oncology, the high manufacturing costs, lack of scalability, process inconsistency, and operational inflexibility associated with the current highly manual way of manufacturing have created meaningful barriers to patient access, reducing patient accessibility to these therapies.
“This is an important milestone that reflects three years of focused collaboration between the teams at Cabaletta and Cellares,” said Steven Nichtberger, MD, co-founder, chairman, and CEO of Cabaletta Bio. “The dosing of these first two patients is an important demonstration of Cellares’ GMP manufacturing and supply chain capabilities with their automated manufacturing platform and thus represents a significant achievement toward our goal of securing high-capacity flexible supply with minimal capital investment and a low cost of goods.”
“This milestone is a transformative moment for the field of autologous cell therapy,” added Fabian Gerlinghaus, co-founder and CEO of Cellares. “For years, the promise of autologous CAR T has been constrained by manufacturing models that were never designed to scale.”
Rese-cel (formerly referred to as CABA-201) is an investigational, autologous CAR T cell therapy engineered with a fully human CD19 binder and a 4-1BB co-stimulatory domain, designed specifically for the treatment of autoimmune diseases. Administered as a single, weight-based infusion, rese-cel is intended to transiently and deeply deplete CD19-positive cells, with the goal of resetting the immune system and achieving durable clinical responses without the need for chronic therapy.
Cabaletta is evaluating rese-cel in the RESET (REstoring SElf-Tolerance) clinical development program, which includes multiple ongoing company-sponsored trials across a diverse and growing range of autoimmune diseases in rheumatology, neurology, and dermatology.
The post CAR T Cell Therapy Biomanufactured by Cellares Infused Into First Two Patients appeared first on GEN – Genetic Engineering and Biotechnology News.