Researchers used artificial intelligence to design functional CRISPR enzymes not seen in nature.
Category: biotech/medical – Page 78
New research clears the way to healing lung diseases
Pulmonary fibrosis is a deadly disease in which scar tissue grows in the lungs, making breathing more difficult. Approximately 2,170 Australians are diagnosed annually with idiopathic pulmonary fibrosis (IPF), a form of the disease with no known cause and very few treatments.
“In pulmonary fibrosis, the normal wound-healing process in the body goes wrong. Instead of repairing damaged tissue, it starts to produce scar tissue in the lungs,” said Associate Professor Gang Liu from the University of Technology Sydney (UTS) School of Life Sciences.
“People with idiopathic pulmonary fibrosis have a very short survival time, usually only two to five years from diagnosis. Only two drugs are approved to treat it, and neither can reverse the scarring and cure the disease.”
Feasibility evaluation of tumor treating fields for brainstem gliomas
Tumor treating fields (TTFields) are FDA-approved for supratentorial glioblastoma, but feasibility in infratentorial tumors remains poorly defined. This simulation study evaluated TTFields dose in brainstem gliomas using patient-specific modeling with scalp-only transducer arrays.
MRI and CT imaging from seven patients with brainstem gliomas were used for TTFields planning with MAXPOINT® (Novocure, Switzerland). Clinical target volume (CTV) was defined as enhancing tumor on T1 post-contrast MRI (Gross tumor volume, GTV) plus a 3 mm peritumoral expansion. The platform optimized scalp-only array layouts, and finite element calculations generated maps of local minimum field intensity (LMiFI, V/cm) and local minimum power density (LMiPD, mW/cm³). Values were compared against a standard, unplanned layout using one-sided paired t-tests, with LMiFI ≥ 1.0 V/cm as a therapeutic reference.
MAXPOINT-optimized layouts achieved significantly higher LMiFI than the standard layout across all regions (all p ≤ 0.019). GTV median LMiFI was 1.1 vs. 1.0 V/cm (p = 0.019). CTV median LMiFI was 1.1 vs. 1.0 V/cm (p = 0.002). Brainstem median LMiFI was 1.3 vs. 1.1 V/cm (p = 0.002). Posterior fossa showed the largest difference: median LMiFI 1.5 vs. 1.2 V/cm (p 0.001). All optimized LMiFI values met or exceeded the therapeutic reference. LMiPD was also significantly higher with MAXPOINT® across all regions (all p ≤ 0.006).
Finding the RNA aptamer in the haystack that could improve treatment for Parkinson’s
Synucleinopathies are a group of neurodegenerative disorders that include serious conditions such as Parkinson’s disease and dementia with Lewy bodies. There are currently no cures for these disorders, and treatment is limited to mitigating symptoms. Recently, antibody-based therapies have attracted considerable attention, but alternative approaches are still necessary.
Therapy development for synucleinopathies tends to target the alpha-synuclein protein, αSyn, the abnormal aggregation of which is a hallmark of these diseases. However, targeting this protein using conventional drug discovery strategies is stymied by the molecule’s lack of a stable three-dimensional structure, which promotes aggregation.
Interested in understanding how abnormal protein aggregation drives neurodegeneration, a team of researchers at Kyoto University had an idea that was both scientifically intriguing and therapeutically promising: Could RNA aptamers—often described as “chemical antibodies”—directly recognize αSyn’s disordered regions and suppress pathological aggregation?
Gene therapy restores key fragile X traits in preclinical study
A gene therapy designed to replace the missing protein that causes fragile X syndrome restored several disease-relevant traits in a mouse model, according to a new study published in Gene Therapy.
Fragile X syndrome is the most common inherited form of intellectual disability and a leading single-gene condition associated with autism. There is no cure, and current care focuses on managing symptoms such as anxiety, sensory sensitivity, hyperactivity, developmental seizures and learning challenges.
The study, led by investigators at Cincinnati Children’s and collaborators at Forge Biologics, tested adeno-associated viral vectors carrying human FMR1, the gene silenced in fragile X syndrome. After testing several candidates, the team found an approach that produced the FMRP protein in key brain regions and improved multiple phenotypes in Fmr1 knockout mice.
Ovaries may take on job in immune system after their tenure as reproductive organs
For most women, the body begins to change dramatically in their 40s or 50s. This transition, known as menopause, is defined as 12 consecutive months without a menstrual period, marking the end of the reproductive years. While researchers are aware of the functions the ovaries perform during active reproductive years, what happens to the organ after menopause is largely a mystery.
A recent study in Molecular Human Reproduction investigated what happens to the ovary in mice after it stops producing eggs, a period known as the post-reproductive stage, similar to menopause in humans.
Researchers found that even after the ovary can no longer support reproduction, it doesn’t simply become inactive. Instead, aging ovaries undergo remarkable changes, producing a different set of signaling molecules from those of younger ovaries.
Dendrites may be key to learning and memory, study suggests
Branchlike structures called dendrites that extend from neurons appear to make their own computations independent of the cell body, helping individual brain cells store memories of the past, respond to the present and anticipate the future, a study led by UT Southwestern Medical Center researchers suggests.
The findings, published in Science, represent a paradigm shift in current models of how learning and memory take place.
“This shifts our entire perspective. Rather than acting as simple switches, neurons behave more like sophisticated processors with internal divisions of labor, dramatically increasing the brain’s computational capacity,” said Attila Losonczy, M.D., Ph.D., professor at the Peter O’Donnell Jr. Brain Institute of Neuroscience and director of the Program in Memory Longevity (PML) at UT Southwestern.
Autonomous biomedical research with an artificial intelligence agent
Biomedical research is increasingly constrained by repetitive, fragmented workflows that slow discovery. We introduce Biomni, a general-purpose biomedical artificial intelligence agent that autonomously executes diverse research tasks. To map the biomedical action space, Biomni’s action-discovery agent mines tools, databases, and protocols from thousands of publications across 25 domains, building a unified agentic environment. Its general-purpose architecture integrates large language model reasoning with retrieval-augmented planning and code-based execution, dynamically composing workflows without predefined templates. Systematic benchmarking shows strong generalization across heterogeneous tasks—causal gene prioritization, drug repurposing, rare-disease diagnosis, microbiome analysis, and molecular cloning—without task-specific tuning.