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by Anubhav Dhar, Sucheta Dey, Sanjana Mullick, Nishant Kumar Suman, Maxime C. van Zwam, Nishaant Kumar Palani Balaji, Angana Ghosh, Deepak Nair, Koen van den Dries, Sudarshan Gadadhar, Saravanan Palani Expansion microscopy (ExM) has revolutionized super-resolution imaging in cell biology due to its simple and inexpensive workflow. The use of ExM has revealed several novel insights into the nanoscale architectures of cellular protein complexes, especially the microtubule cytoskeleton in model and non-model systems. Despite tremendous progress in expansion microscopy protocols that preserve cellular ultrastructure (U-ExM), compatible probes for imaging actin isoforms with U-ExM are still lacking and have hindered the study of diverse actin isoforms and networks across model systems. Here, we use IntAct, an internally tagged actin that incorporates into cellular actin networks, to develop and optimize U-ExM for diverse actin structures in yeast, mammalian cells, and primary neurons. Using ALFA-tagged IntAct variants, we achieve robust visualization of actin patches, cables, and rings in yeast, as well as diverse actin architectures including the cortex, stress fibers, filopodia, and lamellipodia in mammalian cells at improved resolution. In primary hippocampal neurons, IntAct efficiently labels actin throughout the soma and neuronal projections, revealing strong enrichment at dendritic spines and synaptic boutons. Notably, we observe a periodic organization of F-actin along axons consistent with the membrane-associated periodic cytoskeleton, thereby resolving the periodic, sub-diffraction actin ring organization. We also detect transient nuclear actin filaments using IntAct-U-ExM underscoring the advantages offered by our approach to image understudied actin structures. Overall, we demonstrate the effectiveness of IntAct-U-ExM for performing super-resolution imaging of various actin structures in an isoform-specific manner and highlight the potential of IntAct to study the nanoscale organization of diverse actin cytoskeletal networks across species.

The common marmoset (Callithrix jacchus) is an important non-human primate model in neuroscience and biomedical research. However, existing 3D resources for this species have mainly focused on brain atlases or keypoint-based pose estimation, and reusable data resources that jointly describe the body surface, fur, articulated structure, and experimental environment remain limited. Here, we present a multimodal dataset designed to reconstruct body-environment interactions of common marmosets in three dimensions. The dataset includes a whole-body surface mesh derived from computed tomography (CT) images, fur representations based on photographic references, a rigged 3D model for pose-driven animation, synchronized behavioral videos from three individuals recorded for approximately 90 hours from eight view-points, 2D and 3D keypoint estimation data, 3D models of the experimental environment constructed from blueprint information, and rendered pseudo-egocentric views generated by integrating pose estimation results with the 3D body and environment models. Technical validation assessed the geometric agreement between the CT-derived mesh and the surface model, the accuracy of 2D and 3D keypoint estimation, the dimensional accuracy of the environment model, and the structural similarity between real and rendered images. This dataset provides a foundation for treating marmoset natural behavior not only as point trajectories but also as a three-dimensional phenomenon involving body shape and its spatial relationship with the environment, thereby enabling applications in behavioral analysis, visualization, synthetic-data generation, and future digital-twin studies.

Temporal psychological well-being (subjective well-being, future confidence and life satisfaction) is an important indicator of the level of mental health and well-being. During adolescence, the dynamic development of their psychological well-being is more susceptible to multiple factors. However, the trends and multidimensional influences on adolescents’ temporal psychological well-being, as well as their co-development with the relationship between interpersonal relationships and temporal psychological well-being, are not known. Therefore, 568 adolescents (Mage ± SD = 17.41 ± 1.14) aged 16 to 19 years were selected for this study using longitudinal data from the 2018, 2020, and 2022 China Family Panel Studies (CFPS). Analyses were conducted using the latent growth curve model (LGCM). It was found that adolescents’ subjective well-being, future confidence, and life satisfaction showed a significant linear decline. Health status, academic pressure, and parent–child relationships were significantly associated with the initial level and developmental trajectory of temporal psychological well-being. In addition, we observed co-development patterns between interpersonal relationships and adolescents’ temporal psychological well-being, such that parallel changes in interpersonal relationships coincided with changes in well-being over time, and vice versa. This study reveals the dynamic patterns of changes in adolescents’ temporal psychological well-being and their co-development with relationships, providing empirical evidence for targeted interventions.

by Olav N. L. Aga, Sabrina J. Moyo, Joel Manyahi, Upendo Kibwana, Iren H. Löhr, Nina Langeland, Bjørn Blomberg, Iain G. Johnston Antimicrobial resistance (AMR) is a substantial and growing global health burden. Understanding, and predicting, its evolution in specific pathogens will help responses across scales from individual patient cases to large-scale policy. Here, we use global data on AMR features, predicted from 47k Klebsiella pneumoniae genomes, with hypercubic transition path sampling to infer the evolutionary pathways by which AMR features in K. pneumoniae (KpAMR) are acquired across 102 countries, territories, and areas. We identify “globally consistent” evolutionary behaviors that hold across countries, and “globally divergent” behaviors including carbapenem and fluoroquinolone resistance that vary across countries. We show how these divergent dynamics covary both with public health superregion and drug use policy, and reveal competing evolutionary pathways within and between countries. Using newly sequenced data across several decades from sub-Saharan Africa, we show that this inferred global roadmap of KpAMR evolution successfully predicts prospective evolutionary dynamics. Together, we hope that the ability to characterize and predict evolutionary dynamics of AMR acquisition, connected to socio-economic and drug policy predictors, will help strengthen our understanding of AMR evolution worldwide.