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Category: biotech/medical – Page 5

How a broken DNA repair tool accelerates aging

Although DNA is tightly packed and protected within the cell nucleus, it is constantly threatened by damage from normal metabolic processes or external stressors such as radiation or chemical substances. To counteract this, cells rely on an elaborate network of repair mechanisms. When these systems fail, DNA damage can accumulate, impair cellular function, and contribute to cancer, aging, and degenerative diseases.

One particularly severe form of DNA damage are the so-called DNA–protein crosslinks (DPCs), in which proteins become attached to DNA. DPCs can arise from alcohol consumption, exposure to substances such as formaldehyde or other aldehydes, or from errors made by enzymes involved in DNA replication and repair. Because DPCs can cause serious errors during cell division by stalling DNA replication, DNA–protein crosslinks pose a serious threat to genome integrity.

The enzyme SPRTN removes DPCs by cleaving the DNA-protein crosslinks. SPRTN malfunctions, for example as a result of mutations, may predispose individuals to developing bone deformities and liver cancer in their teenage years. This rare genetic disorder is known as Ruijs-Aalfs syndrome. Its underlying mechanism remains poorly understood, and there are no specific therapies.

Scientists teach microorganisms to build molecules with light

Researchers are continually looking for new ways to hack the cellular machinery of microbes like yeast and bacteria to make products that are useful for humans and society. In a new proof-of-concept study, a team from the Carl R. Woese Institute for Genomic Biology showed they can expand the biosynthetic capabilities of these microbes by using light to help access new types of chemical transformations.

The paper, published in Nature Catalysis, demonstrates how the bacteria Escherichia coli can be engineered to produce these new molecules in vivo, using light-driven enzymatic reactions. This framework sets the foundation for future development in the emerging field of photobiocatalysis.

“Photobiocatalysis is basically light-activated catalysis by enzymes. Without light, the target enzyme cannot catalyze a reaction. When light is added, the target enzyme will be activated,” said Huimin Zhao (BSD leader/CAMBERS/CGD/MMG), Steven L. Miller Chair of Chemical and Biomolecular Engineering. “We have published many papers showing that it is possible to combine photocatalysis with enzyme catalysis to create a new class of photoenzymes. These artificial photoenzymes can catalyze selective reactions that cannot be achieved by natural enzymes and are also very difficult, or sometimes even not possible, with chemical catalysis.”

Immunoglobulin G’s overlooked hinge turns out to be a structural control hub

The lower hinge of immunoglobulin G (IgG), an overlooked part of the antibody, acts as a structural and functional control hub, according to a study by researchers at Science Tokyo. Deleting a single amino acid in this region transforms a full-length antibody into a stable half-IgG1 molecule with altered immune activity.

The findings provide a blueprint for engineering next-generation antibody therapies with precisely tailored immune effects for treating diseases such as cancer and autoimmune diseases.

Antibodies are Y-shaped proteins that help the immune system recognize and eliminate foreign threats such as bacteria and viruses. The dominant antibody in the bloodstream is immunoglobulin G (IgG), which accounts for about 75% of circulating antibodies. Its structure is divided into two main functional units connected by a flexible hinge that must work together seamlessly.

Taming Tumor Chaos: Researchers Uncover Key to Improving Glioblastoma Treatment

A groundbreaking study from Brown University Health researchers has identified a crucial factor that may help improve treatment for glioblastoma, one of the most aggressive and common forms of adult brain cancer. The findings, published November 10 in Cell Reports, reveal how differences among cells within a single tumor influence the cancer’s response to chemotherapy, and introduce a promising new therapy designed to tip the odds in the patients’ favor.

Glioblastoma is notoriously difficult to treat. One of the key reasons is that no two cells within the tumor behave exactly alike. Even inside one tumor, some cells may respond to treatment while others resist it, allowing the cancer to persist and grow. For decades, scientists have known that tumors are composed of diverse cells, but the biological forces driving these differences, and their impact on treatment, have remained elusive.

“Traditionally, researchers have focused on the overall behavior of a tumor by studying the average response across all the individual cells, using differences between the cells to interpret the average,” said senior author Clark Chen, MD, PhD, professor and director of the brain tumor program, department of neurosurgery at Brown University Health. “Our study fundamentally flipped that approach. Rather than focusing on the average response, we focused on the differences between individual cells within the same tumor, and what we found could change how we treat glioblastoma.”

Teaching NeuroImage: Miliary Perivascular Space Enhancement in Sepsis-Associated Posterior Reversible Encephalopathy Syndrome

Plants display a wide range of life spans and aging rates. Although dynamic changes to DNA methylation are a hallmark of aging in mammals, it is unclear whether similar molecular signatures reflect rates of aging and organism life span in plants. In this work, we show that the short-lived model plant Arabidopsis thaliana exhibits a loss of epigenetic integrity during aging, which causes DNA methylation decay and the expression of transposable elements. We show that the rate of epigenetic aging can be manipulated by extending or curtailing life span and that shoot apical meristems are protected from these epigenetic changes. We demonstrate that a program of transcriptional repression suppresses DNA methylation maintenance pathways during aging and that mutants of this program display a complete absence of epigenetic decay while physical aging remains unaffected.

AI tool predicts six-month risks for cancer patients after heart attack

Cancer patients who suffer a heart attack face a dangerous mix of risks, which makes their clinical treatment particularly challenging. As a result, patients with cancer have been systematically excluded from many clinical trials and available risk scores. Until now, doctors had no standard tool to guide treatment in this vulnerable group.

An international team led by researchers from the University of Zurich (UZH) has now developed the first risk prediction model designed specifically for cancer patients who have had a heart attack. The study, published in The Lancet, analyzed more than one million heart attack patients in England, Sweden and Switzerland, including over 47,000 with cancer.

Overall, the results show that cancer patients have a strikingly poor prognosis: nearly one in three died within six months, while around one in 14 suffered a major bleed and one in six experienced another heart attack, stroke or cardiovascular death.

Antithrombotic Treatment for Stroke Prevention in Cervical Artery Dissection: The STOP-CAD Study

This was a multicenter international retrospective observational study (63 sites from 16 countries; Figure S1) that included patients presenting to an acute care hospital and diagnosed with CAD without concomitant major trauma. We identified adult patients aged ≥18 years with CAD based on International Classification of Diseases, Ninth Revision codes (443.21 and 443.24),8,9 International Classification of Diseases, Tenth Revision codes (I77.71, I77.74, and I77.75),10 or from institutional registries. These codes have been used or validated in prior studies.8–10

The patients’ vascular neuroimaging studies were reviewed by site principal investigators, and only those with clinical suspicion for CAD and imaging confirmation were included. Imaging confirmation required the presence of at least one of the following imaging features: crescent-shaped hyperintensity in the vessel wall indicating an intramural hematoma; a double lumen sign; the presence of a dissecting pseudoaneurysm, intimal flap, or vessel irregularity; or flame-shaped or tapering stenosis or occlusion of the artery at a typical dissection site and without evidence of atherosclerotic changes. Imaging reports, when available, were reviewed by neurologists at the lead site to confirm a dissection diagnosis.

We excluded patients with incidental chronic dissection, those with major head or neck trauma within the previous 4 weeks (eg, causing skull or cervical fractures or hemorrhage), those with a dissecting aneurysm causing primary subarachnoid hemorrhage, and those with iatrogenic dissection.

Measuring metabolic flux in brain cancer patients with AI based digital twin

The study, published in Cell Metabolism, builds on previous research showing that some gliomas can be slowed down through the patient’s diet. If a patient isn’t consuming certain protein building blocks, called amino acids, then some tumors are unable to grow. However, other tumors can produce these amino acids for themselves, and can continue growing anyway. Until now, there was no easy way to tell which patients would benefit from dietary restrictions.

The digital twin’s ability to map metabolic activity in tumors also helped determine whether a drug that prevents tumors from producing a building block for replicating and repairing DNA would work, as some cells can obtain that molecule from their environments.

To overcome challenges in mapping tumor metabolism inside the brain, the team developed a computer-based “digital twin” that can predict how an individual patient’s brain tumor will react to each treatment.

“Typically, metabolic measurements during surgeries to remove tumors can’t provide a clear picture of tumor metabolism—surgeons can’t observe how metabolism varies with time, and labs are limited to studying tissues after surgery. By integrating limited patient data into a model based on fundamental biology, chemistry and physics, we overcame these obstacles,” said a co-corresponding author of the study.

The digital twin uses patient data obtained through blood draws, metabolic measurements of the tumor tissue and the tumor’s genetic profile. The digital twin then calculates the speed at which the cancer cells consume and process nutrients, known as metabolic flux.

“This is the first time a machine learning and AI-based approach has been used to measure metabolic flux directly in patient tumors,” said a co-first author of the study.

The researchers built a type of deep learning model called a convolutional neural network and trained it on synthetic patient data, generated based on known biology and chemistry and constrained by measurements from eight patients with glioma who were infused with labeled glucose during surgery. By comparing their computer models with different data from six of those patients, they found the digital twins could predict metabolic activity with high accuracy. In experiments conducted on mice, the team confirmed that the diet only slowed tumor growth in mice that the digital twin had identified as good candidates for the treatment.

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