Browse Articles

Neural representation of cytokines by vagal sensory neurons

Abstract The nervous system coordinates with the immune system to detect and respond to harmful stimuli. Inflammation is a universal response to injury and infection that involves the release of cytokines. While it is known that information about cytokines is transmitted from the body to the brain, how the nervous system encodes specific cytokines in the form of neural activity is not well understood. Using in vivo calcium imaging, we show that vagal sensory neurons within the nodose ganglia exhibit distinct real-time neuronal responses to inflammatory cytokines. Some neurons respond selectively to individual cytokines, while others encode multiple cytokines with distinct activity patterns. In male mice with induced colitis, inflammation increased the baseline activity of these neurons but decreased responsiveness to specific cytokines, reflecting altered neural excitability. Transcriptomic analysis of vagal ganglia from colitis mice revealed downregulation of cytokine signaling pathways, while neuronal activity pathways were upregulated. Thus, nodose ganglia neurons perform real-time encoding of cytokines at the first neural station in a body-brain axis, providing a new framework for studying the dynamic nature of neuroimmune communication.

FG-4592 combined with PRP significantly accelerates the healing of refractory diabetic wounds by upregulating HIF-1α

Long-distance coherent quantum communications in deployed telecom networks

Norway set to scrap mandatory language training for foreign postdocs and PhD students

Experimental determination of giant polarization in wurtzite III-nitride semiconductors

The relationship between the ratio of triglyceride to high-density lipoprotein cholesterol and left ventricular hypertrophy in Chinese hypertension adults

Comparative characterization of human accelerated regions in neurons

Human V4 size predicts crowding distance

Self-determination, motivation and burnout among residents in Lebanon

Regulating Na content and Mn defects in birnessite for high-voltage aqueous sodium-ion batteries

Exploring hypoxia driven subtypes of pulmonary arterial hypertension through transcriptomics single cell sequencing and machine learning

A hypothalamic circuit underlying the dynamic control of social homeostasis

Abstract Social grouping increases survival in many species, including humans 1,2 . By contrast, social isolation generates an aversive state (‘loneliness’) that motivates social seeking and heightens social interaction upon reunion 3–5 . The observed rebound in social interaction triggered by isolation suggests a homeostatic process underlying the control of social need, similar to physiological drives such as hunger, thirst or sleep 3,6 . In this study, we assessed social responses in several mouse strains, among which FVB/NJ mice emerged as highly, and C57BL/6J mice as moderately, sensitive to social isolation. Using both strains, we uncovered two previously uncharacterized neuronal populations in the hypothalamic preoptic nucleus that are activated during either social isolation or social rebound and orchestrate the behaviour display of social need and social satiety, respectively. We identified direct connectivity between these two populations and with brain areas associated with social behaviour, emotional state, reward and physiological needs and showed that mice require touch to assess the presence of others and fulfil their social need. These data show a brain-wide neural system underlying social homeostasis and provide significant mechanistic insights into the nature and function of circuits controlling instinctive social need and for the understanding of healthy and diseased brain states associated with social context.

Local mapping of the nanoscale viscoelastic properties of fluid membranes by AFM nanorheology

Abstract Biological membranes are intrinsically dynamic entities that continually adapt their biophysical properties and molecular organisation to support cellular function. Current microscopy techniques can derive high-resolution structural information of labelled molecules but quantifying the associated viscoelastic behaviour with nanometre precision remains challenging. Here, we develop an approach based on atomic force microscopy in conjunction with fast nano-actuators to map the viscoelastic response of unlabelled supported membranes with nanometre spatial resolution. On fluid membranes, we show that the method can quantify local variations in the molecular mobility of the lipids and derive a diffusion coefficient. We confirm our experimental approach with molecular dynamics simulations, also highlighting the role played by the water at the interface with the membrane on the measurement. Probing ternary model bilayers reveals spatial correlations in the local diffusion over distances of ≈20 nm within liquid disordered domains. This lateral correlation is enhanced in native bovine lens membranes, where the inclusion of protein-rich domains induces four-fold variations in the diffusion coefficient across < 100 nm of the fluid regions, consistent with biological function. Our findings suggest that diffusion is highly localised in fluid biomembranes.

Modification of photocatalytic activity and antibacterial properties of Mn2O3 by Zn ions doping

Abstract This study focuses on the fabrication of zinc-doped manganese oxide (Mn2O3) nanoparticles (NPs) to unleash their potential as high-performance photocatalysts. Zn-doped Mn2O3 nanoparticles (NPs) were prepared via a precipitation method, with fine adjustment of Zn content (3%, 5%, and 10%). The structural evolution from cubic Mn2O3 to tetragonal ZnMn2O4 was confirmed by X-ray diffraction (XRD). Energy dispersive X-ray (EDX) analysis confirmed the smooth Zn incorporation, while transmission electron microscopy (TEM) and FESEM revealed the transformative effect of Zn on the particle size and shape. Optical characterizations showed impressive results:UV-Vis DRS revealed a significant reduction in the band gap from 2.26 eV to 1.89 eV, enhancing light absorption. Meanwhile, the photoluminescence (PL) spectra showed vibrant emission peaks at 425, 466, 563, and 623 nm, with the intensity increasing along with the zinc content. The optical prowess of these nanoparticles was validated by the nearly complete degradation of methyl green (MG) dye under visible light. Also, Zn-doped Mn2O3 samples were evaluated against harmful pathogens such as S. aureus, E. faecalis, K. pneumoniae, P. aeruginosa, E. coli, and C. albicans.

Three ways to cool Earth by pulling carbon from the sky

Quantifying the trade-offs between renewable energy visibility and system costs

Abstract Visual landscape impacts on scenic and populated places are among significant factors affecting local acceptance of large-scale renewable energy projects. Through the combination of large-scale reverse viewshed and techno-economic energy system analyses, we assess their potential impacts for nationwide energy systems. In our case study of Germany, moderate consideration of visual impact by placing renewables out of sight of the most scenic and densely populated areas does not have a significant impact on future energy system costs and design. In contrast, in scenarios assuming high sensitivity to visual impacts, annual energy system costs would increase by up to 38% in 2045. The energy system’s resilience would also be compromised due to the increasing reliance on green hydrogen imports and the uncertain mass adoption of rooftop photovoltaics. Our analytical framework facilitates careful planning that considers the visual impact of renewable energy infrastructure, thus enabling socially acceptable deployment while understanding the implications for system costs and transformation pathways.

A novel knockout mouse model to assess the impact of one-copy loss of Hnrnpk in CD4 + T cells in chronically inflamed skin as a prelude to CTCL

Fluctuation-driven topological Hall effect in room-temperature itinerant helimagnet Fe3Ga4

Evaluating the impact of disability support services on healthcare utilization in individuals with disabilities and hypertension in Korea

Abstract People with disabilities often face heightened barriers to accessing healthcare services, resulting in unmet medical needs and increased prevalence of chronic conditions such as hypertension. In response, the Korean government expanded the Personal Assistance Service (PAS) program to enhance healthcare accessibility and support daily living needs for individuals with disabilities. This study aims to evaluate the impact of the PAS program expansion on healthcare utilization, specifically focusing on hospital visits for hypertension management among people with severe disabilities. We used sample cohort data from the National Health Insurance System. The difference-in-differences approach was used to estimate differences in hospital utilization between the treatment and control groups before and after the intervention period. The expansion of PAS program was associated with an increase in hypertension total visits increase of 0.128. Specifically, the number of outpatient visits increased by 0.132. The increase in hospital visits was more pronounced in unclassified disability types. Seasonal variations and higher Charlson Comorbidity Index (CCI) scores were positively associated with increased hospital visits. The results reveal that expanding enrollment in programs for people with disabilities was linked to an increase in outpatient visits among people with severe disabilities. This study is noteworthy because the expansion of services could potentially help bridge health disparities.

An interpretable approach to estimate the self-motion in fish-like robots using mode decomposition analysis

Abstract The artificial lateral line system, composed of velocity and pressure sensors, is the sensing system for fish-like robots by mimicking the lateral line system of aquatic organisms. However, accurately estimating the self-motion of the fish-like robot remains challenging due to the complex flow field generated by its movement. In this study, we employ the mode decomposition method to estimate the motion states based on artificial lateral lines for the fish-like robot. We find that primary decomposed modes are strongly correlated with the velocity components and can be interpreted through Lighthill’s theoretical pressure model. Moreover, our decomposition analysis indicates the redundancy of the sensor array design, which is verified by further synthetic analysis and explained by flow visualization. Finally, we demonstrate the generalizability of our method by accurately estimating the self-states of the fish-like robot under varying oscillation parameters, analyzing three-dimensional pressure data from the computational fluid dynamics simulations of boxfish (Ostracion cubicus) and eel-like (Anguilla anguilla) models, and robustly estimating the self-velocity in complex flows with vortices caused by a neighboring robot. Our interpretable and generalizable data-driven pipeline could be beneficial in generating hydrodynamic sensing hypotheses in biofluids and enhancing artificial-lateral-line-based perception in autonomous underwater robotics.