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Perturbative and numerical study of nonlinear relativistic effects in weak lensing
Item type: Journal Article
Magi M.; Lepori F.; Adamek J. (2026)
The standard weak lensing formalism assumes that the lensing map relating the observed image of a source to its intrinsic shape depends only on the deflection angle. We show that this description is incomplete beyond linear perturbation theory, even when only scalar perturbations are present at first order. Using the Jacobi map formalism, we derive expressions for the rotation field, shear B-modes, and their angular power spectra at second order in relativistic perturbation theory. In the standard formalism, rotation and shear B-modes share the same spectrum, however, this degeneracy is broken once the parallel transport of the Sachs basis is consistently taken into account. We quantify this correction numerically, finding a difference of about 5% on large angular scales ℓ ∼ 5 for sources at redshift zs = 0.5. We also investigate frame-dragging effects, which are usually neglected in weak lensing. We present the first analytical derivation of the corresponding impact on the angular power spectrum of shear B-modes and show that it becomes the dominant contribution on scales ℓ ≲ 10. While both Sachs-basis rotation and frame dragging significantly affect shear B-modes on large scales, their contribution to the observed ellipticity B-mode angular power spectrum is at the percent level relative to the total ellipticity B-mode signal, making these nonlinear relativistic corrections challenging to detect in practice. Our results are supported by relativistic simulations of weak lensing observables, including the first numerical study of frame dragging in the power spectra of the lensing convergence and cosmic shear.
Lymph Node Lymphatic PD-L1 Regulates Tumor-Infiltrating T Cells in Immune Checkpoint-Sensitive Melanoma
Item type: Journal Article
Reynaud E.; Belherazem S.; Hemanna S.; et al. (2026)
Lymph node (LN)-resident lymphatic endothelial cells (LEC) form the interphase between the lymphatic sinus lumen and the LN cortex. Beyond their role in leukocyte trafficking, LECs shape immune responses as they scavenge and cross-present exogenous antigens from the afferent lymph and constitutively express immune-regulatory proteins such as PD-L1. However, it remains unclear which immune cell types and activation states are sensitive to LN lymphatic PD-L1, and whether lymphatic PD-L1 expression is relevant for immune checkpoint blockade (ICB) sensitivity in patients with cancer. To dissect the contribution of LN lymphatic PD-L1 to tumor immunity and ICB outcomes in melanoma, we utilized a conditional lymphatic PD-L1-knockout mouse model in combination with syngeneic melanoma models varying in ICB sensitivity. Although lymphatic PD-L1 deletion did not alter primary tumor growth, progression, or the overall immune landscape within tumor-draining LNs, it modulated the intratumoral immune composition in ICB-sensitive but not in ICB-resistant melanoma. Specifically, lymphatic PD-L1 deletion resulted in an increased frequency of proliferating PD-1+ CD8+ T cells and a reduction in PD-1+ Th1 T cells. Together, our findings reveal that lymphatic PD-L1 plays a context-dependent role in shaping antitumor T cell responses, particularly in ICB-sensitive disease. SIGNIFICANCE: The authors expand the concept of immune checkpoint regulation beyond immune cells in the tumor microenvironment, demonstrating how lymphatic endothelial PD-L1 in melanoma-draining LNs regulates tumor-infiltrating T cells in immune checkpoint-sensitive melanoma.
Roadmap on sustainable soft robotics by additive manufacturing
Item type: Review Article
Qi Q.; Wang Z.; Qiu Z.; et al. (2026)
Technology disposal poses increasing pressure on the environment, society and economy. Scientists and engineers are seeking sustainable alternative solutions to meet these challenges, for example, through the development of sustainable soft robotics. Compared to conventional robotics, sustainable soft robotics can degrade into nothing at the end of their functional lives, leaving zero footprint in their surrounding environment. This is of paramount importance, especially in the push toward the ubiquity of robotic technology through advanced design and manufacturing techniques. Additive manufacturing (AM) describes the creation of 3D objects through the consecutive addition of material layers, enabling the fast prototyping of complex structures and devices, thereby reducing the financial and temporal cost in advanced robot development. The marriage of smart materials and AM can significantly promote the advancement of sustainable soft robotics technologies. In this roadmap, leading experts overview the status and development of sustainable soft robotics and provide insights into the exciting challenges and potential opportunities of sustainable actuators and sensors, AM technologies, functional materials, and robotic components across a wide range of application fields. This roadmap also serves as a vital compass for experts and enthusiasts in the field of sustainable soft robotics.
Beyond Muscle Quantity: Rethinking Sarcopenia as a Disorder of Brain-Muscle Communication?
Item type: Journal Article
Gennaro F.; Casolo A.; de Bruin E.D. (2026)
Sarcopenia is classically defined by age-related loss of muscle mass, strength, and function, yet strength and functional decline consistently outpace the loss of muscle tissue itself, a mismatch that a purely muscle-centered model cannot fully explain. Mounting evidence therefore hints towards neurogenic contributors to sarcopenia. In this concept study, we propose reframing sarcopenia as a disorder of brain-muscle communication, integrating a framework across three complementary levels of neuromuscular organization: i) corticospinal connectivity, ii) motor-unit behavior, and iii) muscle synergies, introducing the concept that each level is individually informative but insufficient alone to capture the neural contribution to sarcopenia-related muscle weakness. We further argue that conventional static and single-task assessments may underestimate this neural component, and that combining them with dynamic and ecologically valid dual-task paradigms could reveal compensatory motor control reorganization. Moreover, we propose a self-reinforcing loop in which selective fasttwitch fiber loss and impaired neural drive interact to amplify functional decline over time. If validated, multimodal neurophysiological profiling could help identify individual neural phenotypes and inform personalized resistance and motor-cognitive training. The evidence remains cross-sectional and hypothesis-generating: the key emerging tool is unvalidated in sarcopenia, and etiological heterogeneity across sarcopenia subtypes is unaddressed.
Does higher-resolution climate forcing improve impact model performance?
Item type: Other Journal Item
Malle J.T.; Reyer C.P.O.; Amitai Y.; et al. (2026)
Climate-impact assessments increasingly use high-resolution climate forcing, often assuming that finer spatial detail improves impact projections. Yet this assumption has rarely been tested systematically across impact sectors, regions, and forcing variables. Here we use coordinated simulations from 16 impact models participating in the Inter-Sectoral Impact Model Intercomparison Project to evaluate how increasing forcing resolution from 60 km to 10 km, 3 km, and 1 km affects both climate-input accuracy and impact-model performance. We find that most gains occur when moving from 60 km to 10 km resolution. Further refinement to 3 km and 1 km yields smaller and less consistent benefits, and in some cases degrades performance. Improvements are strongest for temperature-sensitive models and in topographically complex regions, where finer forcing better captures spatial gradients. By contrast, precipitation-driven models and low-relief regions show weaker and less systematic gains. These results challenge the expectation that ever-finer climate forcing necessarily improves impact modelling. Instead, the value of resolution depends on the forcing variable, sector, region, and process representation of the impact model. Benchmarking resolution choices against impact-model performance, rather than climate-input accuracy alone, is therefore essential for designing efficient and decision-relevant climate-impact assessments.