A patch made of stem cells from donor placentas has been used to treat fetuses in the womb with a severe form of spina bifida as part of a world-first trial. The novel approach seems to have reversed a brain complication associated with the congenital condition at least as effectively as the go-to treatment, but is expected to enable more children to walk over the long term.
The mother of one of the babies, who is now 4 years old, says she expected that her son Toby would require a wheelchair when he was diagnosed with the condition in the womb. “But Toby is healthy [and] has hit all of his milestones – he’s walking, running and jumping – and has no problems with bladder control, which is rare for people with the condition,” she says.
Spina bifida – which affects about 1 in every 2,800 births in the US every year – occurs when a baby’s spine and spinal cord do not fully develop in the womb. In the most severe form of the condition, called myelomeningocele, the spinal cord and its surrounding tissue protrude out of a gap in the vertebrae, which often impairs mobility and bowel and bladder control. The cause of spina bifida is unknown, but folic acid deficiency during pregnancy raises the risk.
One of the standard treatments involves surgery in the womb that tucks the spinal cord and the surrounding tissue back into the vertebrae, before sewing up the skin to form a tight seal. “But many children still end up unable to walk and there’s [usually] no improvement in bowel or bladder control,” says Diana Farmer at the University of California, Davis.
This led Farmer and her colleagues to wonder if the addition of stem cells could help by promoting the growth and repair of spinal tissue. To find out, they recruited six pregnant women carrying fetuses with myelomeningocele.
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SAN FRANCISCO/SINGAPORE — DeepSeek, the Chinese artificial intelligence lab whose low-cost model rattled global markets last year, has not shown US chipmakers its upcoming flagship model for performance optimization, two sources familiar with the matter said, breaking from standard industry practice ahead of a major model update.
Instead, the lab, which is expected to launch its next major update, V4, granted early access to domestic suppliers, including Huawei Technologies, the sources said.
AI developers typically share pre-release versions of major models with leading chipmakers such as Nvidia and Advanced Micro Devices to ensure their software performs efficiently on widely used hardware. DeepSeek has previously worked closely with Nvidia’s technical staff.
Adult sleep GWAS-derived polygenic scores demonstrated comparable associations with corresponding sleep phenotypes in Adolescents, suggesting genetic influences on sleep persist across developmental stages.
Question Do genetic variants that are associated with adult sleep/circadian phenotypes influence sleep phenotypes in adolescents?
Findings In a population-based birth cohort study (N = 3903), genetic influences on all adult sleep phenotypes (sleep duration, insomnia, daytime sleepiness, napping, and chronotype as indexed by polygenic scores derived from adult genome-wide association studies) were associated with their corresponding sleep/circadian phenotypes in adolescents aged 15 years.
Meaning Genetic variants identified in adult genome-wide association studies may also be relevant to a variety of sleep phenotypes in adolescence, suggesting that these variants index sleep phenotypes during a key developmental stage in which sleep disturbances typically emerge.
In contrast, traditional deep learning methods in the medical domain have long been constrained by scarce annotations data, weak cross-modal semantic correlation, and insufficient generalization capabilities. FMs can effectively alleviate these issues by extracting semantic representations from large-scale unlabeled data, reducing dependence on expert annotations, and enhancing cross-modal understanding and transferability [7]. This provides technical support to address challenges such as long-tail distributions, data scarcity, and modality imbalance, thereby promoting a shift in medical decision-making from experience-driven to data-driven approaches.
Unlike traditional specialist models such as nnU-Net [8], which are typically designed for a single modality and specific tasks, FMs emphasize modality unification and task generalization, enabling cross-domain transfer and knowledge sharing. With mechanisms such as prompt engineering and PEFT, these models support few-shot and even zero-shot transfer (ZST). For example, Med-PaLM [9] is based on a unified medical pretraining model, which can generate structured pathology reports and perform lesion localization from medical images. It effectively overcomes the limitations of traditional methods that require separate architectures for different tasks, significantly improving modeling efficiency and system integration. Driven by such unified model architecture, medical AI systems are evolving toward greater generality and reusability.
Despite these advancements, the unique characteristics of the medical domain pose multiple challenges to the application of FMs. On one hand, medical data are highly heterogeneous, with pronounced differences in resolution, contrast, and noise distribution across imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound [10]. This limits the ability of traditional single-modality pretraining strategies to achieve effective cross-domain knowledge integration. On the other hand, clinical applications demand higher standards for model performance. Clinical decision-making relies on interpretable diagnostic evidence, yet pretraining models often behave as “black boxes”, limiting their clinical traceability [11]. In addition, the long-tail distribution of rare diseases poses fairness challenges for model generalization [12].
Gene therapy has been successfully used to treat a number of diseases, including immune deficiencies, hereditary blindness, hemophilia and, recently, Huntington’s disease, a fatal neurological disorder.
An advance reported in the journal Neuron adds to the technique’s growing track record of evidence supporting the view that it could unlock powerful, personalized therapies: researchers found that released markers of activity (RMAs) ⎯ engineered proteins designed to cross the blood-brain barrier and persist in the blood for hours at a time, providing a reliable and noninvasive way to get information about gene expression in the brain ⎯ work just as well in monkeys as they do in mice.
Alongside precision, RMA technology is also capacious and adaptable: Different serum markers can be designed to track multiple genes across different brain regions. ScienceMission sciencenewshighlights.
Hematopoietic stem cell transplant (HPSCT), sometimes referred to as bone marrow transplant, involves administering healthy hematopoietic stem cells to patients with dysfunctional or depleted bone marrow. There are several types of HPSCT in clinical use, and transplanted cells may be obtained from several sources. This procedure has several benefits and may be used to treat malignant and non-malignant conditions. It helps to augment bone marrow function. In addition, depending on the disease being treated, it may allow for the destruction of malignant tumor cells. It can also generate functional cells that replace dysfunctional ones in cases like immune deficiency syndromes, hemoglobinopathies, and other diseases. Survival rates after HPSCT are increasing, but morbidity due to complications of the procedure continues. This activity reviews the indications for HPSCT, the different options by which to obtain donor cells, including the advantages and disadvantages of each, and the acute and chronic complications of the procedure. Additionally, it highlights the role of the interprofessional team in managing patients who undergo HPSCT to improve patient outcomes and decrease procedure-associated morbidities.
Objectives:
Describe the malignant and non-malignant indications for hematopoietic stem cell transplants.
Immorta Bio just doubled the lifespan of mice using a first-in-class senolytic immunotherapy called SenoVax combined with personalized stem cells from their StemCellRevivify platform. In this deep dive, I break down exactly how it works, why it matters, and what it means for the future of human aging.
SenoVax is a vaccine that trains your immune system to hunt down and destroy senescent cells — the \.
This study investigated the associations between neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, and systemic immune-inflammation index with progression of CSVD.
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Cancer development results from the selection of cells with mutation(s) that provide survival and proliferative advantages. Normal barriers to proliferation are overcome as clones adapt to an ever changing hostile microenvironment, where low oxygen tension, low glucose levels, and an acidic extracellular pH (all of which increase genetic instability) are found. The hypoxia inducible factors, HIF-1 and HIF-2, are upregulated in response to these conditions. This could occur by constitutive activation of PI3K signaling or inactivating mutations in, for example, the von Hippel–Lindau tumor suppressor, VHL [35-37], which normally deacetylates HIF-1α, leading to HIF-1α polyubiquitination and proteasomal degradation [38]. HIFs trans activate genes mediating proliferation, angiogenesis, intermediate metabolism (glycolysis) and pH regulation, which promote tumor development [39].
HIF-1α stimulates production of growth factors, such as transforming growth factor β (TGF-β), insulin-like growth factor 2, interleukin-6 (IL-6), interleukin-8, macrophage migration inhibitory factor (MIF), and growth factor receptors, such as the epidermal growth factor receptor (EGFR), resulting in continuous proliferative signaling. In the hypoxic environment, constitutive activation of these signaling pathways (e.g., Ras [1] and PI3K [2]) stabilizes HIF-1 and may result in “oncogene addiction” that persists through the transition from adenoma to carcinoma. In the case of PI3K, constitutive activation may result from the appearance of mutations in tumor suppressor genes (e.g., the phosphatase and tensin homolog [PTEN]), from activating mutations in the PI3K complex itself, or from aberrant signaling in receptor tyrosine kinases [40].