Reassortment between different influenza strains occurs when they co-infect the same host cell. The emergence of a reassortant virus depends on both its intrinsic fitness and extrinsic factors, including preexisting humoral immunity. The generation of pandemic strains, such as H2N2 and H3N2, and zoonotic influenza A viruses, such as H5N6, H5N8, and H7N9, in birds is suggested to be the result of extensive selection by preexisting antibodies. To further explore the role of humoral immunity in reassortment, we generated two divergent fluorescent protein-expressing viruses and used strain-specific and cross-reactive monoclonal antibodies (mAbs) to assess the impact of cross-immunity on reassortment. Our results indicate that all mAbs altered the genotypic diversity and significantly reduced the release of progeny virions in co-infected cells both in vitro and in vivo. Moreover, antibody transfer studies in mice revealed protection from challenge with divergent pathogenicity profiles. Notably, selection driven by a strain-specific mAb depended on its neutralizing specificity, whereas the selection driven by broadly reactive mAbs was independent of neutralization specificity. Our findings demonstrate that preexisting neutralizing antibodies shape reassortment and that strain-specific neutralizing antibodies promote antigenic shift during co-infection, which is not the case for broadly cross-reactive antibodies that recognize influenza viruses from different subtypes.
A zoonotic Babesia species previously referred to as Babesia sp. MO1 is formally described and named here as Babesia hegotelforum sp. nov. This taxon is distinct from Babesia divergens based on genome-wide sequence divergence, phylogenetic placement, host associations, and clinical presentation. The parasite infects erythrocytes of humans, and eastern cottontail rabbits (Sylvilagus floridanus), and is transmitted by Ixodes dentatus. The holotype consists of a Giemsa-stained thin blood smear and cryopreserved infected erythrocytes from the cloned isolate BML-Bh-B12 at ≤10 passages in continuous in vitro culture. Paratype material includes five additional clones (BML-Bh-H1, BML-Bh-F12, BML-Bh-H6, BML-Bh-A3, and BML-Bh-F1) derived from BEI Resources strain NR-50441, along with the original mixed isolate NR-50441. This species description meets the requirements of the International Code of Zoological Nomenclature and establishes Babesia hegotelforum sp. nov. as a distinct species of clinical and epidemiological significance in North America.
BACKGROUND: Machine learning methods employing neuroimaging data are useful for monitoring the activation of neural representations. Specifically, they can be used to discern the brain networks engaged in processing specific categories of items. This approach has been employed on neuroimaging data, including functional magnetic resonance imaging data and electroencephalography (EEG) data. NEW METHOD: Here, we present a task and an analytical pipeline for investigating category representations using EEG. Participants (N = 30) viewed a series of images and words of objects belonging to five categories (Animals, Tools, Food, Scenes, and Vehicles) and responded when items from the same category were presented consecutively. RESULTS: We trained support vector machines on EEG data within participants and found that both image trials and word trials yielded significant category classification accuracy, with image trials achieving higher accuracy than word trials. When comparing categories in a pair-wise fashion, all pairs were statistically distinguishable for image trials, whereas only one pair was distinguishable for word trials. Parietal and left temporal electrodes contributed more to image classification than frontal and right temporal electrodes. Category-specific activity patterns also generalized across participants for image trials. COMPARISON WITH EXISTING METHODS: Our data and analytic pipeline yielded high classification accuracies, primarily for image trials, providing support for the utility of EEG data for neural decoding. CONCLUSIONS: These methods can be instrumental for exploring the activation and reactivation of neural representations at the category level during wakefulness and, potentially, during offline states.
We build upon Haueis and Colaço's account in two ways. First, we argue that the backgrounding of metabolism was a pragmatic response to a data granularity problem faced by traditional cognitive modelers. Then, we suggest that equivalence demonstrations offer a promising pathway for incrementally introducing metabolic considerations into extant modeling practice.
Bumble bees are essential pollinators that have an annual eusocial lifestyle where new cohorts of queens establish colonies each season. The early stages of colony establishment are critical for colony success and are heavily impacted by how readily queens activate their ovaries and initiate egg laying at the start of the season. Understanding the social and nesting factors that influence queen reproduction may provide key insights into early colony establishment. Here, we examine how social conditions and nest cavity size affect the onset of egg laying in early nesting Bombus impatiens queens. In the first experiment, queens were assigned to a social condition where they were placed into nesting boxes that either completely restricted contact with nestmates (and were smaller in size) or allowed direct physical contact and then housed either alone or with nestmates (males or workers). We found that contact with either workers or males accelerated egg laying in queens relative to being housed alone. Unexpectedly, queens housed in the restricted cages, regardless of whether alone or with nestmates, also initiated egg laying earlier. This led us to a second experiment, where we examined ovarian activation and hemolymph juvenile hormone (JH-III) concentrations in early queens housed in different nesting cavity sizes. Here, we found that smaller nest cavity sizes lead to a greater degree of ovarian activation in gynes (young, unmated queens), but juvenile hormone concentrations did not differ. Our findings demonstrate that both social conditions and nest cavity size influence reproductive timing in queens in early-stage bumble bee colonies.
While cancer remains the leading cause of occupational death among firefighters, cancer mitigation efforts are not always successful. This study examines how health practices become durable behavioral changes within the professional field of California firefighters. Drawing on 48 in-depth interviews, we examine how health uptake has been successful in a field where resistance would be expected based on the entrenched tradition and masculine culture. Integrating Bourdieu's framework with Fundamental Cause Theory, we show that cultural, symbolic, and social capital must be reconfigured concurrently to transform the entrenched habitus and enhance cancer mitigation. Specifically, acquiring new knowledge on cancer risks, reclassifying clean gear as a new symbol of professionalism, and solidifying the new knowledge and symbol through cohesive social networks can facilitate habitus transformation and produce sustained behavioral changes in cancer mitigation. Our research enriches both theoretical perspectives and extends medical sociology's understanding of how to overcome sociocultural barriers to pro-health actions.
Characterizing the high-energy radiation environments of stars plays a critical role in determining which systems’ planets are capable of retaining atmospheres and sustaining habitable conditions. X-ray through UV radiation drives atmospheric photochemistry, heating, and escape, making accurate characterization of stellar high-energy emission essential for both interpreting future exoplanet observations and identifying the most promising targets for life detection. We construct panchromatic spectral energy distributions (SEDs) spanning the X-ray through radio for 12 nearby low-mass and Sun-like stars with directly imageable habitable zones that are prioritized targets for the Habitable Worlds Observatory (HWO) and Extremely Large Telescopes (ELTs). These SEDs are generated using forward stellar atmosphere models guided and constrained by available archival X-ray and UV observations. We find that many stars in this sample exhibit elevated high-energy radiation environments relative to the modern Sun, with habitable zone X-ray and extreme UV (XUV) fluxes frequently exceeding solar values by 1–2 orders of magnitude. The elevated emission likely reflects a combination of sample selection effects, differences in stellar age and rotation, and intrinsic magnetic variability, with multiepoch observations demonstrating that variability alone can significantly alter inferred radiation environments. These results highlight high-energy radiation as an important discriminator in identifying the most promising habitable planet hosts and demonstrate the need for expanded X-ray and UV observations to complete the stellar characterization necessary for HWO target prioritization.
The habitable zone (HZ) is a fundamental concept used to guide our search for temperate exoplanets with stable surface liquid water that would sustain remotely detectable biosignatures. So far, most advanced 3D climate studies and prospective spectral simulations of HZ planets have focused on inner HZ planets that receive stellar radiation similar to Earth’s and would consequently maintain relatively low (e.g., hundreds of parts per million) atmospheric CO2. Here, we present a systematic investigation of outer HZ (OHZ) planets, which require high CO2 for habitability, using the 3D Generic Planetary Climate Model (PCM). Our 3D climate results are compared with previous 1D predictions that show strong agreement between models. Simulated spectra of the modeled planets indicate that high overlying CO2 levels affect remote signatures of habitability. We also determine substantial spectral differences that would distinguish habitable versus nonhabitable high-CO2 worlds with future direct-imaging observations for solar analogs and with transmission and emission spectroscopy for M dwarfs. Our results demonstrate that 3D models that include CO2 condensation are necessary to understand the potential planetary habitability and spectral impacts of clouds on terrestrial worlds in the OHZ.
How do people emotionally imagine political others and the competing sovereignty claims they represent, and how are these imaginaries tied to different visions of the collective “us”? Drawing on 93 interviews with Chinese college students in China and the United States between 2019 and 2021, this study examines how Chinese youth’s visions of China’s future organize their emotional responses to Hong Kong and Taiwan. We develop a typology along two dimensions: visions of China’s future (stronger versus freer) and the perceived significance of Hong Kong and Taiwan for that future. A stronger-China vision paired with high perceived significance produces nationalist defensiveness , which frames sovereignty in terms of national dignity, security, and the unfinished project of national strengthening. A freer-China vision paired with high perceived significance yields admiration and identification with democratic freedoms. Among students who attach less significance to Hong Kong and Taiwan or regard them as given, a stronger-China vision often appears as apathy , whereas a freer-China vision more often generates envy or ambivalence . These orientations are further informed by social positions, out-group interaction, and access to alternative information, which can either reinforce existing visions of “us” or unsettle perceptions of “them.” By foregrounding the interplay between imagined futures of “us” and emotional evaluations of “them,” this study shows how sovereignty debates are mediated through everyday emotions and national imaginaries, bridging research on state narratives and public opinion on territorial sovereignty.
This Letter presents a combination of searches for Higgs boson pair ( ) production performed by the ATLAS and CMS Collaborations using proton-proton collision datasets recorded at during the Large Hadron Collider Run 2, corresponding to integrated luminosities ranging between 126 and . The upper limit at the 95% confidence level on the total signal strength, defined as the ratio of the measured cross section to the standard model (SM) prediction, corresponds to 2.5, with an expected value of 1.7 (2.8) assuming the absence (presence) of the SM signal. The strength of the signal is measured to be relative to the SM prediction. The observed significance is found to be 1.1 standard deviations whereas 1.3 are expected for the SM signal. Constraints are set on the Higgs boson trilinear self-coupling and on the couplings of two Higgs bosons to two vector bosons, both normalized to the SM predictions and denoted as and , respectively. The observed individual constraints at the 95% confidence level are and , while the expected constraints assuming the presence of the SM signal are and .
