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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.

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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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Recent advances in the field of materials science have opened new possibilities for the fabrication of bioelectronics, devices designed to be worn or implanted in the human body. Bioelectronics can help to track or support the function of organs, tissues and cells, which can contribute to the prevention and treatment of various diseases.

A promising material for the fabrication of bioelectronics is PEDOT: PSS, a polymer known for its , flexibility and compatibility with biological tissues. Despite its advantageous properties, PEDOT: PSS is known to gradually dissolve in biological fluids, a limitation that has so far been counteracted using chemical compounds and processes.

Researchers at Stanford University, the University of Cambridge and Rice University recently uncovered an easier and potentially safer strategy to stabilize this bio-compatible polymer using heat. Their proposed thermal treatment, outlined in the journal Advanced Materials, was found to make PEDOT: PSS films stable in water without the need for any chemical additives.

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A team of researchers from the University of Ottawa has made significant strides in understanding the ionization of atoms and molecules, a fundamental process in physics that has implications for various fields including X-ray generation and plasma physics.

The research, titled “Orbital angular momentum control of strong-field in atoms and molecules,” is published in Nature Communications.

Think about atoms—the building blocks of everything around us. Sometimes, they lose their electrons and become charged particles (that’s ionization). It happens in lightning, in plasma TVs, and even in the . Until now, scientists thought they could only control this process in limited ways.

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Astrophysicists have once again enriched our knowledge of the cosmos with a new discovery: two small planets orbiting TOI-1453. Located at around 250 light years from Earth in the Draco constellation, this star is part of a binary system (a pair of stars orbiting each other) and is slightly cooler and smaller than our sun. This discovery, published in the journal Astronomy & Astrophysics, paves the way for future atmospheric studies to better understand these types of planets.

Around this star are two planets, a super-Earth and a sub-Neptune. These are types of planets that are absent from our own solar system, but paradoxically constitute the most common classes of planet in the Milky Way. This discovery sheds light on a planetary configuration that could provide valuable clues to the formation and evolution of planets.

Using data from NASA’s Transiting Exoplanet Survey Satellite (TESS) and the HARPS-N high-resolution spectrograph, the researchers were able to identify TOI-1453 b and TOI-1453 c, the two exoplanets orbiting TOI-1453.

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Temperature is a critical variable that influences countless biological processes at the cellular level. However, precisely measuring temperatures within living cells remains challenging. Conventional temperature measurement techniques often lack the spatial resolution needed to detect subtle temperature variations in complex microscopic environments. Additionally, many existing molecular thermometers have significant limitations in terms of their sensitivity, resolution, and applicable targets, highlighting the need for innovative approaches and versatile tools.

Against this backdrop, a research team led by Associate Professor Gen-ichi Konishi from the Institute of Science Tokyo, Japan, has developed a molecular thermometer using a novel solvatochromic fluorescent dye. Their findings, published online in the Journal of the American Chemical Society on March 5, 2025, demonstrate that this new compound enables high-precision temperature measurements through changes in fluorescence properties.

The researchers designed a series of donor−π–acceptor (D−π–A) fluorophores based on a π-extended fluorene structure. These molecules are specially engineered to change their fluorescence properties in response to their surrounding environment’s polarity. When the temperature increases, the polarity of the solvent slightly decreases, which causes these dyes to emit light at different wavelengths and intensities.

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Biomolecular condensates are shifting blobs in our cells that organize cellular matter. They are distinct molecular communities made of DNA, RNA and proteins that “condense” molecules to key locations, yet they frequently defy description. Partly this is because they are so small, they cannot be measured using traditional microscopes.

“These blobs were once described as being ‘liquid-like’ because some of them were observed to kiss, fuse, drip and flow like raindrops on windshields,” said Rohit Pappu, Gene K. Beare Distinguished Professor of biomedical engineering the McKelvey School of Engineering at Washington University in St. Louis.

However, while the blobs may look like raindrops, computations have suggested otherwise. The molecular organization within condensates is more like that of a network that rearranges on different timescales, giving condensates more of a shifting, silly putty-like character.

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