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Not long to go now: After more than nine months on the International Space Station, two astronauts are a step closer to returning home following the launch of a crew swap mission on Friday.

A Falcon 9 rocket with a Crew Dragon fixed to its top blasted off from the Kennedy Space Center in Florida at 7:03 pm (2303 GMT), carrying a four-member team bound for the orbital outpost.

“We celebrate the countless individuals all over the world that have made this journey possible,” said astronaut Nichole Ayers, the designated pilot of the Crew-10 mission, just before launch.

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Most cells in the body send out little messengers called extracellular vesicles that carry proteins, lipids, and other bioactive molecules to other cells, playing an important role in intercellular communication. But healthy cells are not the only ones that rely on extracellular vesicles. Cancer cells do, too. Small extracellular vesicles that are shed from tumor cells contribute to how cancer spreads to healthy tissue.

These small messengers could be a key to developing new cancer-fighting drugs and therapies, but it has been unclear how exactly the recipient cells absorb the extracellular vesicles and their cargo. Recent research used state-of-the-art imaging to observe the uptake of tumor-derived small extracellular vesicles by target cells. The results were published in Nature Communications on March 12, 2025.

“In recent years, extracellular vesicles have attracted attention as a carrier of intercellular signaling. However, the mechanism of their internalization by target cells has not been well understood. We wanted to elucidate the pathway and mechanism of internalization of extracellular vesicles by target cells,” said Kenichi G. N. Suzuki, a professor at the Institute for Glyco-core Research at Gifu University in Gifu and a chief at the Division of Advanced Bioimaging, National Cancer Center Research Institute in Tokyo, Japan.

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Does autoimmunity underlie minimal change disease?

Tobias B. Huber, Nicola M. Tomas & team report a direct pathogenic role of anti-nephrin autoantibodies in the development of podocytopathy with a minimal change disease phenotype:

The electron microscopy image shows moderate podocyte foot process effacement (without electron-dense deposits) in the anti-nephrin rabbit.

Address correspondence to: Tobias B. Huber or Nicola M. Tomas, III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, D-20246 Hamburg, Germany. Phone: 49.40.7410.53908; Email: [email protected] (TBH); [email protected] (NMT).

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A novel cortical biomarker can accurately distinguish high and low pain-sensitive individuals and may predict the transition from acute to chronic pain.

Importance Biomarkers would greatly assist decision-making in the diagnosis, prevention, and treatment of chronic pain.

Objective To undertake analytical validation of a sensorimotor cortical biomarker signature for pain consisting of 2 measures: sensorimotor peak alpha frequency (PAF) and corticomotor excitability (CME).

Design, Setting, and Participants This cohort study at a single center (Neuroscience Research Australia) recruited participants from November 2020 to October 2022 through notices placed online and at universities across Australia. Participants were healthy adults aged 18 to 44 years with no history of chronic pain or a neurological or psychiatric condition. Participants experienced a model of prolonged temporomandibular pain with outcomes collected over 30 days. Electroencephalography to assess PAF and transcranial magnetic stimulation (TMS) to assess CME were recorded on days 0, 2, and 5. Pain was assessed twice daily from days 1 through 30.

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What excites you the most about the potential of quantum computers?

💡 Future Business Tech explores AI, emerging technologies, and future technologies.

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This video explores the future of quantum computing. Related terms: ai, future business tech, future technology, future tech, future business technologies, future technologies, quantum computing, etc.

ℹ️ Some links are affiliate links. They cost you nothing extra but help support the channel so I can create more videos like this.

#technology #quantumcomputing

Continue reading “The Future Of Quantum Computing: 10 Bold Predictions” | >

Molecular Nutrition In Health, Well-Being & Longevity — Dr. Courtney Millar, Ph.D. — Marcus Institute For Aging Research, Hebrew SeniorLife / Harvard Medical School

Dr. Courtney Millar, Ph.D. (https://www.marcusinstituteforaging.org/who-we-are/profiles/courtney-millar-phd) is an Assistant Scientist at the Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, and Instructor in Medicine, Harvard Medical School and Beth Israel Deaconess Medical Center.

Dr. Millar is a research scientist devoted to improving health and well-being of older adults through dietary interventions and her current research aims to test the ability of anti-inflammatory dietary strategies that promote both physical and emotional well-being in older adults.

Dr. Millar received her PhD in molecular nutrition at the University of Connecticut, where she developed a deep understanding of the relationship between dietary bioactive components and metabolic disease.

Dr. Millar’s post-doctoral fellowship focused on training related to conducting both nutritional epidemiological analyses and clinical interventions.

Continue reading “Dr. Courtney Millar — Marcus Inst. For Aging Research — Molecular Nutrition In Health & Well-Being” | >

In today’s AI news, OpenAI and Google are pushing the US government to allow their AI models to train on copyrighted material. Both companies outlined their stances in proposals published this week, with OpenAI arguing that applying fair use protections to AI “is a matter of national security.” The proposals come in response to a request from the White House, which asked for input on Trump’s AI Action Plan.

In other advancements, one of the bigger players in automation has scooped up a startup in the space in hopes of taking a bigger piece of that market. UiPath, as part of a quarterly result report last night that spelled tougher times ahead, also delivered what it hopes might prove a silver lining. It said it had acquired, a startup founded originally in Manchester, England.

S most advanced features are now available to free users. You And, the restrictive and inconsistent licensing of so-called ‘open’ AI models is creating significant uncertainty, particularly for commercial adoption, Nick Vidal, head of community at the Open Source Initiative, told TechCrunch. While these models are marketed as open, the actual terms impose various legal and practical hurdles that deter businesses from integrating them into their products or services.

S Kate Rooney sits down with Garry Tan, Y Combination president and CEO, at the accelerator On Inside the Code, Ankit Kumar, Sesame, and Anjney Midha, a16z on the Future of Voice AI. What goes into building a truly natural-sounding AI voice? Sesame’s cofounder and CTO, Ankit Kumar, joins a16z’s Anjney Midha for a deep dive into the research and engineering behind their voice technology.

Then, Nate B. Jones explains how AI is making intelligence cheaper, but software strategies built on user lock-in are failing. Historically, SaaS companies relied on retaining users by making it difficult to switch. However, as AI lowers the cost of building and refactoring, users move between tools more freely. The real challenge now is data interoperability—data remains siloed, making AI-generated content and workflows hard to integrate.

We close out with, AI is getting expensive…but it doesn’t have to be. NetworkChuck found a way to access all the major AI models– ChatGPT, Claude, Gemini, even Grok – without paying for multiple expensive subscriptions. Not only does he get unlimited access to the newest models, but he also has better security, more privacy, and a ton of features… this might be the best way to use AI.

Thats all for today, but AI is moving fast — subscribe and follow for more Neural News.

Continue reading “Eurocell transforms inventory management process by deploying Peak’s AI capabilities” | >

Convolutional neural networks (CNNs) were inspired by the organization of the primate visual system, and in turn have become effective models of the visual cortex, allowing for accurate predictions of neural stimulus responses. While training CNNs on brain-relevant object-recognition tasks may be an important pre-requisite to predict brain activity, the CNN’s brain-like architecture alone may already allow for accurate prediction of neural activity. Here, we evaluated the performance of both task-optimized and brain-optimized convolutional neural networks (CNNs) in predicting neural responses across visual cortex, and performed systematic architectural manipulations and comparisons between trained and untrained feature extractors to reveal key structural components influencing model performance. For human and monkey area V1, random-weight CNNs employing the ReLU activation function, combined with either average or max pooling, significantly outperformed other activation functions. Random-weight CNNs matched their trained counterparts in predicting V1 responses. The extent to which V1 responses can be predicted correlated strongly with the neural network’s complexity, which reflects the non-linearity of neural activation functions and pooling operations. However, this correlation between encoding performance and complexity was significantly weaker for higher visual areas that are classically associated with object recognition, such as monkey IT. To test whether this difference between visual areas reflects functional differences, we trained neural network models on both texture discrimination and object recognition tasks. Consistent with our hypothesis, model complexity correlated more strongly with performance on texture discrimination than object recognition. Our findings indicate that random-weight CNNs with sufficient model complexity allow for comparable prediction of V1 activity as trained CNNs, while higher visual areas require precise weight configurations acquired through training via gradient descent.

The authors have declared no competing interest.

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A 69-year-old man with metastatic prostate adenocarcinoma, treated with chemotherapy 3 years ago, presented with pancytopenia (white blood cells, 3.1 × 109/L; hemoglobin, 11.1 g/L; platelets, 47 × 109/L). A bone marrow aspirate revealed increased blasts with folded nuclei, deeply basophilic cytoplasm, prominent nucleoli, perinuclear hofs, and occasional salmon-colored cytoplasmic granules without Auer rods (panel A, Giemsa stain, original magnification ×1000, lens objective 100×). The blasts were positive for CD34, CD13, CD19, CD25 (partial), CD33, CD38 (decreased), CD45 (dim), CD64 (partial), CD79a (dim), CD117, CD123, HLA-DR (bright), and myeloperoxidase and negative for CD7, CD10, CD14, CD20, CD22, CD36, CD56, cytoplasmic IgM and terminal deoxynucleotidyl transferase (panel B). Next-generation sequencing detected a DNMT3A mutation (F794del, variant allelic frequency 2%), likely representing bystander clonal hematopoiesis. Cytogenetic analysis revealed an abnormal karyotype (46,XY,+1,der(1;15)(q10;q10), t(16;21)(q24;q22)[20]) (panel C). Result of dual-color fusion fluorescence in situ hybridization (FISH) was negative for RUNX1::RUNX1T1. Nevertheless, 23% of the cells exhibited 3 copies of RUNX1, suggesting RUNX1 rearrangement with another partner (panel D); RUNX1 rearrangement was confirmed by FISH using a break-apart probe (panel E). Optical genome mapping confirmed the presence of RUNX1::CBFA2T3 (panel F). Acute myeloid leukemia (AML) with RUNX1::CBFA2T3 is a rare AML with characteristic morphologic and immunophenotypic features that overlap with AML with RUNX1::RUNX1T1. This case highlights the morphologic and immunophenotypic similarities between these AML subtypes and raises awareness of this rare entity.

Wei J. Wang, Sanam Loghavi; Acute myeloid leukemia with RUNX1:: CBFA2T3 fusion. Blood 2025; 145 (11): 1226. doi: https://doi.org/10.1182/blood.2024027698

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Over the course of their lives, humans and other animals typically learn to avoid situations and stimuli that are dangerous or are perceived as threatening. Past neuroscience studies have gathered evidence suggesting that the medial prefrontal cortex (mPFC), a brain region that plays a key role in learning and decision-making, also contributes to these learned threat responses.

Researchers at the University of California Los Angeles (UCLA) recently carried out a study aimed at better understanding how the gradual strengthening of neural connections during the brain’s development influences changes in the threat responses of mice.

Their findings, published in Nature Neuroscience, revealed that there are critical transitions during that alter how the mPFC interacts with the nucleus accumbens (NAc) and basolateral amygdala (BLA), two brain regions involved in threat-based and emotional learning.

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