Fine-tuning petal senescence is crucial for the manipulation of flower longevity and genetic improvement. Yang et al. propose a TgFbox1-TgNAC2-TgWIN1 regulatory cascade that integrates ABA and ethylene signaling pathways with cuticular wax biosynthesis to govern petal senescence in a developmentally stage-dependent manner.
In a paradigm-breaking study, researchers have discovered a novel way the immune system, specifically Tcells, attack their target cells, reshaping long-held assumptions in immunology and demonstrating direct implications for the field of cancer immunology and bone marrow transplantation. The team consists of Dr. Pavan Reddy, director of the Dan L Duncan Comprehensive Cancer Center at Baylor College of Medicine (BCM) and his team, in collaboration with Drs. Arul Chinnaiyan, S P Hicks Endowed Professor of Pathology, and Marcin Cieslik, assistant professor of pathology, both from University of Michigan Rogel Cancer Center. The study is published in Nature Immunology.
Rewriting the rules of T cell biology The immune system relies on molecules called major histocompatibility complexes (MHC) to detect external “threats” to the body, including from cancerous or foreign (allogeneic) cells. Historically, MHC class I molecules were believed to present signals only to CD8+ T cells (“killer” T cells), while MHC II activated CD4+ T cells (“helper” T cells). This division of MHC class roles guided decades of immunology and cancer research.
In an example of collaborative work, Reddy’s graduate students Emma Lauder and Meng-Chih Wu from BCM and Chinnaiyan and Cieslik’s student Mahnoor Gondal, from University of Michigan, worked with colleagues on various components of the work that spanned several years. The work challenges this foundational MHC class-restricted dichotomy and reveals a previously unrecognized role for the class I pathway in CD4+ T cell–mediated immune defense.
Malignant tumors are sneaky. They tend to fly under the immune system’s radar because, unlike invaders such as viruses or bacteria, cancer cells arise from normal cells, so they bear many of the same familiar molecules on their surface.
Once tumors are established, they become even more adept at hiding out from the immune system. They might cloak themselves in proteins to block immune cells from entering them or undergo genetic changes to further reduce the chance that disease-fighting cells will notice anything is amiss.
【】 Full article: (Authored by Yu Bai and Fei Meng, from University of Shanghai for Science and Technology, China.)
Engineering load signals support durability analysis because they reflect real service conditions. Long-duration load histories are essential for fatigue-life prediction and reliability assessment. However, long-term field measurements are often costly and difficult to obtain. Therefore, extending short measurements into representative long histories is practically important. This study proposes a frequency-consistent diffusion_model (FCDM) for long-horizon extrapolation of non-stationary bearing load signals under turning conditions. load_extrapolation.
This study proposes a frequency-consistent diffusion model (FCDM) for long-horizon extrapolation of non-stationary bearing load signals. Condition tokens and spectral-consistency constraints are introduced to preserve spectral and fatigue-related characteristics during tenfold extrapolation. The generated signals are evaluated using PSD, band-energy proportion, Range-Mean distribution, and unit pseudo-damage. Compared with DDPM, FCDM better preserves dominant frequencies, harmonic structure, and band-energy allocation. The dominant frequency error is 1.02%, and the mean harmonic error is 0.52%. FCDM also shows smaller band-energy allocation errors across all frequency bands. In addition, it reproduces the bimodal clustering pattern in the Range-Mean distribution more accurately. The unit pseudo-damage is 1.0978 for FCDM and 1.1280 for DDPM. These results indicate that FCDM improves spectral fidelity and fatigue-related consistency in long-sequence load extrapolation.
Great article. I should note that it actually has nothing to do with slow and boring research — it’s about the importance of scientists practicing good communication and public engagement to facilitate fundraising from non-governmental sources.
As federal research funding shrinks, scientists are looking to other sources of support. Can they learn to sell their work without selling out?
Since the middle of the twentieth century, the National Institutes of Health and the National Science Foundation have embodied an imperfect social contract: Federal agencies would fund basic research at scale, and in return, that research would serve the public good through medical advances, technological progress, and economic growth.
For scientists, this system created a reliable pathway: Do good work, write strong grants, and federal agencies would keep your lab running. It was never a perfectly fair system, but it was predictable enough that you could build a life around it. If your work was solid and your grants were strong, the system would fund you.
The first topic of discussion at the 2025 Maintainers Summit has been in the air for a while: what role — if any — should machine-learning-based tools have in the kernel development process? While there has been a fair amount of controversy around these tools, and concerns remain, it seems that the kernel community, or at least its high-level maintainership, is comfortable with these tools becoming a significant part of the development process.
Sasha Levin began the discussion by pointing to a summary he had sent to the mailing lists a few days before. There is some consensus, he said, that human accountability for patches is critical, and that use of a large language model in the creation of a patch does not change that. Purely machine-generated patches, without human involvement, are not welcome. Maintainers must retain the authority to accept or reject machine-generated contributions as they see fit. And, he said, there is agreement that the use of tools should be disclosed in some manner.
But, he asked the group: is there agreement in general that these tools are, in the end, just more tools? Steve Rostedt said that LLM-generated code may bring legal concerns that other tools do not raise, but Greg Kroah-Hartman answered that the current developers certificate of origin (“Signed-off-by”) process should cover the legal side of things. Rostedt agreed that the submitter is ultimately on the hook for the code they contribute, but he wondered about the possibility of some court ruling that a given model violates copyright years after the kernel had accepted code it generated. That would create the need for a significant cleanup effort.
A new study shows that the overexpression of somatostatin (SST), a neuropeptide produced in neurons and acting mostly on microglia, lowers inflammation and amyloid β burden, improving cognitive abilities in a mouse model of Alzheimer’s. Drugs affecting this pathway are already available [1].
The unusual suspect
In Alzheimer’s disease, many signaling pathways in the brain become dysregulated. Since going after the main hallmarks of the disease (amyloid β and tau protein accumulation) has only yielded modest results so far, scientists are exploring various secondary targets whose levels correlate with the disease.
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