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A recent study published in the journal Aging by Julia Michalkiewicz, Tung D. Nguyen, and Monica Y. Lee from the University of Illinois at Chicago College of Medicine underscores the essential role of the protein Nucleoporin93 (Nup93) in preserving blood vessel health during aging. The authors discuss emerging research that identifies Nup93 as a potential therapeutic target for preventing or mitigating aging-related conditions such as heart disease and stroke.

Cardiovascular diseases remain the leading causes of death worldwide, with aging identified as a major risk factor. Vascular health declines as endothelial cells (EC)—the protective lining of blood vessels—lose their functionality with age. This deterioration leads to inflammation, arterial stiffening, and reduced blood flow, significantly increasing the risk of life-threatening diseases. The authors underscore the urgent need to uncover the molecular mechanisms driving these changes.

The size and strength of the momentum bandgap improve as the quality factor of the metasurface increases. Figure 3f shows that metasurfaces with a higher Q-factor provide wider momentum bandgaps for surface waves with larger amplification rates, assuming the same modulation function. In comparison, the metasurface discussed in Fig. 3b–e has a quality factor of Q = 2.44. Moreover, for sufficiently large Q-factors (Q ≥ 9.75), a second momentum bandgap opens inside the light cone, that is, for propagating waves. The size of the second bandgap grows with the quality factor of the metasurface because resonances with longer lifetimes suffer from smaller radiation losses and require weaker modulation to maintain the same amplification rate. When the quality factor takes sufficiently large values, the two bandgaps merge and the metasurface can amplify incident waves with all possible momenta k _{∣ ∣} (see Fig. 3f).

We place a dipole emitter above the metasurface to demonstrate this infinite momentum bandgap (see Fig. 3g). The dipole radiation includes a wide spectrum of momenta, as shown in the upper panel of the figure. Once the temporal modulation of the metasurface is on, waves with all different momenta are amplified and radiated in the specular and retro-directions with respect to the source; see the lower panel in Fig. 3g. This leads to interesting possibilities such as amplified emission and lasing of light from a radiation source⁶. In contrast to the idea suggested in ref. ⁶, due to the substantially enhanced bandgap, it is possible here to amplify emission with a large and, in principle, tunable spectrum of wavenumbers. This provides opportunities for beam shaping of the amplified signal and for creating perfect lenses³¹. Indeed, the evanescent wave content of the source radiation can be reconstructed effectively thanks to the amplification of the wide range of k _{∣ ∣}. In Supplementary Section 5, we demonstrate that evanescent and propagating wave components of the radiating dipole are amplified by the metasurface in reflection and transmission regimes.

To provide a feasible optical realization of the resonant PTC, we consider a penetrable metasurface surrounded by air and consisting of dielectric nanospheres that are made of a material with a time-varying permittivity (see Fig. 4a). Each nanosphere effectively behaves as an LC resonator as it supports Mie resonances³². For simplicity, we initially ignore material dispersion. The permittivity associated with each nanosphere reads \(\varepsilon (t)=1+{\chi }_{0}[1+m\cos ({\omega }_{{\rm{m}}}t)]\). Varying the permittivity in time modulates the Mie resonance frequencies of the nanospheres (see Fig. 2b). In the following, we rely on the T-matrix method to study the optical response from such a metasurface³³ (see Methods and Supplementary Section 6 for details).

Neuroscientific research on human behavior and cognition has methodologically moved from unimodal explanatory approaches to machine learning-based predictive modeling (1). This implies a shift from standard approaches testing for associations between behavior and single neurobiological variables within one sample (unimodal explanatory research) to the identification of relationships between behavior and multiple neurobiological variables to forecast behavior of unseen individuals across samples (multimodal predictive research) (2). Modern machine learning techniques can learn such general relations in neural data (2, 3) and have consequently become increasingly prominent also in research on fundamental psychological constructs like intelligence (4).

Intelligence captures the general cognitive ability level of an individual person and predicts crucial life outcomes, such as academic achievement, health, and longevity (5, 6). Multiple psychometrical theories about the underlying conceptual structure of intelligence have been proposed. For example, Spearman (7) noticed that a person’s performance on different cognitive tasks is positively correlated and suggested that this “positive manifold” results from an underlying common factor—general intelligence (g). A decomposition of the g-factor into fluid (gF) and crystallized (gC) components was later proposed by Cattell (8, 9). While fluid intelligence is assumed to mainly consist of inductive and deductive reasoning abilities that are rather independent of prior knowledge and cultural influences, crystallized intelligence reflects the ability to apply acquired knowledge and thus depends on experience and culture (10).

Neurobiological correlates of intelligence differences were identified in brain structure (11) and brain function (12). However, rather than disclose a single “intelligence brain region”, meta-analyses and systematic reviews suggest the involvement of a distributed brain network (13–15), thus paving the way for proposals of whole-brain structural and functional connectivity (FC) underlying intelligence (16, 17). While the great majority of such studies used an explanatory approach, recently, an increasing number of machine learning-based techniques were developed and applied to predict intelligence from brain features (4, 18, 19). Although intrinsic FC measured during the (task-free) resting state has enabled robust prediction of intelligence (19), prediction performance can be boosted by measuring connectivity during task performance (18, 20).

The Call is still open on senescence in brain aging and Alzheimers disease!

Submit your paper today! 📩

Understanding Senescence in Brain Aging and Alzheimer’s Disease

Guest Editors Drs. Julie Andersen and Darren Baker, Associate Editor Dr. Anna Csiszar and Editor-in-Chief Dr. Zoltan Ungvari, and the editorial team of GeroScience (Journal of the American Aging Association; 2018 Impact Factor: 6.44) invite submission of original research articles, opinion papers and review articles related to research focused on understanding the role of senescence in brain aging and in Alzheimer’s disease. Senescent cells accumulate in aging and pathological conditions associated with accelerated aging. While earlier investigations focused on cellular senescence in tissues and cells outside of the brain (e.g. adipose tissue, dermal fibroblasts, cells of the cardiovascular system), more recent studies started to explore the role of senescent cells in age-related decline of brain function and the pathogenesis of neurodegenerative disease and vascular cognitive impairment. This call-for-papers is aimed at providing a platform for the dissemination of critical novel ideas related to the functional and physiological consequences of senescence in diverse brain cell types (e.g., oligodendrocytes, pericytes, astrocytes, endothelial cells, microglia, neural stem cells), with the ultimate goal to identify novel targets for treatment and prevention Alzheimer’s disease, Parkinson’s disease and vascular cognitive impairment. We welcome manuscripts focusing on senescent-cell-targeting mouse models, the role of paracrine senescence, senescence pathways in terminally differentiated neurons, the pleiotropic effects of systemic senescence, the role of senescence in neuroinflammation and the protective effects of senolytic therapies. We are especially interested in manuscripts exploring the causal role of molecular mechanisms of aging in induction of cellular senescence as well as links between lifestyle (e.g., diet, exercise, smoking), medical treatments (e.g. cancer treatments), exposure environmental toxicants and cellular senescence in the brain. We encourage submission of manuscripts on developing innovative strategies to identify and target senescent cells for prevention/treatment of age-related diseases of the brain. Authors are also encouraged to submit manuscripts focusing on translational aspects of senescence research.

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- is focusing on the role of molecular mechanisms of aging in the pathogenesis of cardiovascular diseases, COVID19, hypertension, obesity and vascularhomeostasis. ‘ + Read more in the comments and submit📧 at the link⬇

Cell Biology of Vascular Aging.

Guest Editors: Prof. Zoltan Arany, Prof. Jalees Rehman and Prof. Gabor Csanyi.

Deputy Editor Dr. Stefano Tarantini and Editor-in-Chief Dr. Zoltan Ungvari, and the editorial team of GeroScience (Official Journal of the American Aging Association, published by Springer) invite submission of original research articles, opinion papers and review articles related to research focused on understanding the mechanisms involved in vascular aging, the factors promoting accelerated aging in vascular cells and the role of vascular cells in the pathogenesis of age-related diseases. This call-for-papers is aimed at providing a platform for the dissemination of critical novel ideas related to the mechanisms of vascular aging as well as mechanisms related to key phenotypes of vascular aging including.

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Aging gracefully comes naturally to these creatures, which can live for hundreds, and sometimes even thousands, of years.

A longevity expert thinks that those who are currently in their 40s may have more than a 50% likelihood of not dying from aging-related causes.

If you looked at two snapshots of the same maple tree taken in July and December, you’d see a dramatic change from summer’s full green crown to winter’s bare branches. What those two photos don’t show you, however, is how the change occurred—gradually or all at once? In truth, deciduous trees tend to hold out for an environmental signal—a change in light or temperature—and then shed all their leaves within just a week or two.

When it comes to aging, we may be more like these trees than we realized.

According to new work from Rockefeller’s Laboratory of Single-Cell Genomics and Population Dynamics, mammals follow a similar aging trajectory at the cellular level. As described in a new paper in Science, lab head Junyue Cao and his colleagues used single-cell sequencing to simultaneously scan more than 21 million cells from every major mouse organ across five stages of life. This enormous collection is now the world’s largest cellular atlas within a single study.