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Mitochondrial fission helps immune cells kill bacteria and could counter resistance
Alternative therapies that aid the body’s immune system to fight bacteria have shown promise in addressing the global threat of antibiotic resistance. University of Queensland researchers have found when under attack, the body’s immune cells activate a cellular process called mitochondrial fission to kill invading bacteria. Their study is published in the journal Science Immunology.
Dr. James Curson, from UQ’s Institute for Molecular Bioscience, said mitochondrial fission was a critical process in which mitochondria within cells split into smaller units to support the body’s response to stresses, including infections.
“Some bacteria have evolved strategies to stop activation of the mitochondrial fission process—allowing the invading pathogens to survive, and the infection to persist,” Dr. Curson said.
Gene Therapy for Parkinson’s Disease Associated with GBA1 Mutations
Abeliovich et al. make a compelling case for the promise of using gene therapy to treat Parkinson’s disease (PD) patients who possess mutations in the GBA1 gene. People interested in the clinical-translational side of biomedicine should definitely check this out!
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Dyno Therapeutics Launches Two New AAV Capsids and AI Platform for Rare Disease Therapeutic Development at the 2026 American Society of Gene & Cell Therapy (ASGCT) Annual Meeting
Dyno continues to develop impressive new AAV capsids with their AI-guided design approach!
About Dyno Therapeutics.
Dyno Therapeutics is on a mission to build high-performance genetic technologies that transform patients’ lives. Dyno applies AI to build technologies for gene delivery and sequence design that advance “Genetic Agency” — an individual’s ability to take action at the genetic level to live a healthier life — through safe, effective and widely accessible genetic treatments. With frontier AI models and high-throughput in vivo experimentation, Dyno designs optimized AAV delivery vectors that solve gene delivery challenges across a wide range of therapeutic applications including eye, muscle and CNS. Dyno partners across industries to ensure these life-transforming technologies can help as many patients as possible, including through strategic collaborations with leading gene therapy developers Astellas and Roche and with technology companies including NVIDIA. Dyno’s AI-designed capsids are available for direct licensing and through the Dyno Frontiers Network. Visit www.dynotx.com for more information.
‘Dyno Therapeutics’, ‘dyno’, the Dyno logo, and mountain logo are registered trademarks of Dyno Therapeutics, Inc. All rights reserved.
Law of the iterated logarithm
Where “log” is the natural logarithm, “lim sup” denotes the limit superior, and “a.s.” stands for “almost surely”. [ 3 ] [ 4 ]
Another statement given by A. N. Kolmogorov in 1929 [ 2 ] is as follows.
Roles of lysosomal small-molecule transporters in metabolism and signaling
Small-molecule transporters of the lysosomal membrane export lysosomal catabolites for reuse in cell metabolism.
These transporters often show substrate promiscuity and, conversely, a given metabolite is often exported through distinct transport routes and sometimes in different states (e.g., single amino acids versus dipeptides).
Some lysosomal transporters import metabolites into the lumen. The combination of importers and exporters can create small-molecule shuttles across the lysosomal membrane, which regulate the lumen state.
Some lysosomal transporters participate in intracellular signaling cascades. sciencenewshighlights ScienceMission https://sciencemission.com/lysosomal-small-molecule-transporters
Lysosomes degrade damaged or unwanted cell/tissue components and recycle their building blocks through small-molecule transporters of the lysosomal membrane. They also act as signaling hubs that sense and signal internal cues, such as amino acids, to coordinate cell responses. Recently, the activity of several lysosomal metabolite transporters has been elucidated, bringing new insights into lysosomal functions. Cell biological and structural studies of lysosomal transporters have also highlighted their roles in recruiting signaling complexes to lysosomes and delineated how their substrates gate such hybrid transporter/receptor, or ‘transceptor’, function.
Quobly Toolbox Explores Quantum Phase Estimation Pipeline With Tensor Networks
An international collaboration between a French quantum startup and a major Taiwanese electronics manufacturer has yielded a new open-source tool for exploring a critical area of quantum computing. Quobly and Taiwan’s Hon Hai Research Institute, the R&D arm of Foxconn, jointly released a numerical toolbox dedicated to the Quantum Phase Estimation (QPE) algorithm, described as a cornerstone of fault-tolerant quantum computing with major applications in quantum chemistry and materials science. While QPE’s theoretical benefits are understood, simulating its practical resource needs has proven difficult; the toolbox aims to bridge this gap by allowing researchers to explore implementations and their implications. The tool focuses on practical, interpretable numerical experiments, enabling full circuit executions for up to 20 qubits and circuits ranging from 1,000 to 100,000 gates on standard laptops.
Quantum Phase Estimation Toolbox for Molecular Systems
While the theoretical underpinnings of QPE are well established, simulating its practical demands has proven a significant hurdle, limiting exploration beyond simplified models. The toolbox addresses this gap by offering a platform for practical, interpretable numerical experiments, allowing scientists to investigate QPE implementations without requiring access to full-scale quantum hardware, which is currently unavailable. Built upon advanced tensor network techniques and the open-source quimb library, the toolbox facilitates the preparation of initial states using DMRG and matrix product states, and allows encoding of molecular Hamiltonians into quantum circuits through methods like trotterization and qubitization. Researchers can directly compare standard QPE with the single-ancilla Robust Phase Estimation (RPE) method, analyzing circuit depth, gate counts, and potential error sources.