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Multi-antigen DNA vaccine targeting non-structural proteins confers robust T Cell-mediated protection against Zika virus
No full textZika virus (ZIKV) vaccine development has been hindered by the risk of antibody-dependent enhancement (ADE), particularly in dengue-endemic regions, where sub-neutralizing antibodies can exacerbate disease severity. T cell-based vaccines targeting non-structural (NS) antigens represent a safer alternative that bypasses this risk. Using immunocompetent BALB/c mice, we performed highresolution in vivo mapping of ZIKV specific CD8⁺ and CD4⁺ T cell responses following ZIKVPRVABC59 infection, identifying high avidity, polyfunctional memory T cells targeting conserved NS1, NS3 and NS4 proteins. Guided by these data, we developed DNA vaccines encoding full-length NS3 and NS4 and evaluated their efficacy against ZIKV infection alone or combined with a validated construct encoding secreted NS1 (p-tpaNS1). NS3 and NS4 vaccination elicited robust cytotoxic and IFN-γ producing T cell responses, while co-administration with p-tpaNS1 significantly reduced peak serum viremia achieving earlier and stronger viral control. Although NS1 alone conferred strong protection, the multi-antigen formulation demonstrated additive benefits. This T cell-based vaccine approach, targeting conserved NS proteins, offers a scalable, thermostable platform with potential for safe deployment in childbearing women and resource-limited regions. Given NS protein conservation and cross-reactivity across flaviviruses, it also provides a promising foundation for next-generation panflavivirus vaccine development, although this remains to be directly tested.Ryan Santos, Zelalem A. Mekonnen, Arthur Eng Lip Yeow, Dawn M.Whelan, Zahraa Al-Delfi, Nicholas S. Eyre, Michael R. Beard, Dan H. Barouch, David H. O, Connor, Makutiro G. Masavuli, Branka Grubor-Bau
Networked competitive bivirus SIS spread with higher order interactions
No full textThe paper studies the simultaneous spread of two competing viruses over a network of population nodes with higher-order interactions (HOI), using a continuous-time time-invariant competitive bivirus networked susceptible–infected–susceptible (SIS) system. In this paper, by HOI, we mean interactions among group sizes of no more than three nodes. The first key contribution is to establish several important general properties for generic systems. Namely, there are a finite number of equilibria, each equilibrium is nondegenerate, and the system is a strongly monotone dynamical system. Put together, we establish that for almost all initial conditions, the system will converge to a stable equilibrium (of which there may be many). We then turn our focus to characterizing the existence and stability of the equilibria of this system, which are (i) the disease-free equilibrium (DFE), (ii) single-virus endemic equilibria, and (iii) coexistence equilibria (where both viruses are present). We present a range of conditions on the existence or nonexistence of various equilibria. Two key features underpin our results: First, we substantially relax the connectivity conditions of the network relative to existing literature. More specifically, for securing several important general properties for generic systems, we do not require strong connectivity of the standard pairwise interaction graph. Second, we identify dynamical phenomena, including multiple stable equilibria, which are known to be impossible without HOI. The latter illustrates the novel insights that are obtained by including HOI into models of epidemic spread. Finally, we illustrate our results using a real-world large-scale network.Sebin Gracy, Brian D.O. Anderson, Mengbin Ye, César A. Urib
FloodTransformer: Efficient real-time high-resolution flood forecasting
No full textFlood forecasting is crucial for disaster planning and risk management, yet conventional hydrodynamicbased approaches are often slow in response and computationally intensive. We present a hybrid framework leveraging traditional hydrodynamic modelling with a novel AI model to enable accurate, real-time, and highresolution flood prediction. To address the computational challenges of large-scale, dense flood prediction, we develop an efficient flood prediction model, FloodTransformer, which possesses three key novelties: variablesize cell embedding, tokenised time-sequence encoding, and physics-informed multi-task optimisation. These components effectively capture complex spatiotemporal dependencies, allowing accurate sequential predictions in a single run. Comprehensive evaluations on both simulated and historical flood events demonstrate FloodTransformer’s excellent accuracy and efficiency: NSE 0.9445, KGE 0.9759 for water-depth prediction, and IoU 0.8180, F1 0.8997 for inundation classification, outperforming all comparative models. With 3s inference enabling multiple horizons in one pass, FloodTransformer offers a robust and practical solution for operational flood risk management.Zhanzhong Gu, Jiachen Kang, Wenzheng Jin, Feifei Tong, Jay Guo, Wenjing Ji
Rigid models for 2-gerbes I: Chern–Simons geometry
No full textOnlinePublMotivated by the problem of constructing explicit geometric string structures, we give a rigid model for bundle 2-gerbes, and define connective structures thereon. This model is designed to make explicit calculations easier in applications to physics. To compare to the existing definition, we give a functorial construction of a bundle 2-gerbe as in the literature from our rigid model, including with connections. As an example we prove that the Chern–Simons bundle 2-gerbe from the literature, with its connective structure, can be rigidified—it arises, up to isomorphism in the strongest possible sense, from a rigid bundle 2-gerbe with connective structure via this construction. Further, our rigid version of 2-gerbe trivialisation (with connections) gives rise to trivialisations (with connections) of bundle 2-gerbes in the usual sense, and as such can be used to describe geometric string structures. The preprint of this article is available as arXiv:2209.05521.David Michael Roberts, Raymond F. Vozz
Learning label-specific features for multi-dimensional classification
No full textLink to a related website: https://orcid.org/0000-0003-2843-5738, ORCID profile - Liu, LinIn multi-dimensional classification (MDC), instances are associated with multiple class variables that are assumed in the output space, and each class variable corresponds to one heterogeneous class space and characterizes the objects’ semantics from one dimension. Learning from MDC examples poses challenges due to the heterogeneity of class spaces, since the outputs from different class spaces are not directly comparable. Moreover, existing approaches often use identical data representation for all labels in a class, which may lead to suboptimal results as each label might be determined by its own specific characteristics. Critically, the inherent incomparability of raw heterogeneous labels prevents existing methods from effectively capturing label correlations, which are essential for guiding feature learning. In this paper, we propose a novel algorithm named LEAD, i.e., learning Label-spEcific feAtures for multi-Dimensional classification. LEAD first resolves label heterogeneity by transforming the original output space into a unified encoded label space through one-hot label encoding. This critical alignment enables explicit extraction of label correlations from the encoded space. To enhance the reliability of the estimation of label correlations, LEAD then leverages feature-space manifold structures via locally linear embedding, propagating labeling information across similar instances to counteract sparsity. Finally, LEAD jointly learns label-specific feature representations and constructs the classifier through sparse learning while incorporating label correlations. Experimental comparisons on fifteen datasets demonstrate that our proposed method outperforms state-of-the-art multi-dimensional classification methods
Synergistic Effects of Lime–Organic Amendment Interactions in Acidic Soils
No full textCalcitic lime (CaCO₃) is commonly used to ameliorate soil acidity, but its effectiveness is limited by slow solubility. This study aims to evaluate interactive effects of lime (90% calcite, 6% quartz) and organic amendments on lime dissolution and soil acidity neutralisation. The experiment utilised various organic amendments with the following differing decomposability: (i) readily decomposable faba bean straw, and (ii) more resistant blended poultry litter, biochar, and compost, with average organic carbon mineralisation indices (OCMI) of 29%, 6%, 4%, and 6%, respectively. The lime–faba bean straw combination produced the highest partial pressure of CO₂ (pCO₂) (1398 μatm) compared to lime alone (375 μatm). The net average increase in dissolved inorganic carbon (DIC) due to the synergistic interaction between lime and organic amendments ranged from +0.3 mg L⁻¹ for the lime–blended poultry litter treatment to +1.9 mg L⁻¹ for the lime–compost combination, representing a 2- to 5-fold increase. The dissolved organic carbon (DOC) content in lime–organic amendment mixes also increased by 29%–36% compared to organic amendments alone. The pCO₂/DIC ratio decreased when lime was combined with organic materials compared to when it was applied alone, indicating more efficient conversion of respired CO₂ to H₂CO₃* (* indicates this comprises both dissolved CO₂ and carbonic acid, H₂CO₃). A lower DIC/carbonate alkalinity (DIC/CarbAlk) ratio and a positive calcite saturation index (SIC) in the combined treatments further confirmed the increased generation of HCO₃− and CO₃²−, reducing acidity. The co-application of lime and organic amendments also mobilised Ca²⁺ while reducing potential Al3+ bioavailability and phytotoxicity. These beneficial synergies highlight the potential for improved acid soil remediation strategies using combined lime–organic matter amendments.Birhanu Iticha, Rob Fitzpatrick, Petra Marschner, Luke M. Mosle
Long-term survival gains after allogeneic hematopoietic stem cell transplant are driven by reductions in non-relapse mortality: A 35-Year Statewide Australian cohort study
No full textOnlinePublBackground Allogeneic hematopoietic stem cell transplant (alloHSCT) has evolved substantially in recent decades, expanding patient access via widespread adoption of increased age limits, alternate mismatched donors, reduced intensity conditioning, and novel graft versus host disease (GVHD) prophylaxis strategies. However, real-world outcomes reflective of these changes remain underreported. Study Design We performed a retrospective population-based analysis of all consecutive adult alloHSCT within South Australia from 1990–2023 (N=864). Patients were grouped by decade to evaluate temporal changes in practice and outcomes. Results Median age at transplant increased from 41 years in the 1990s to 54 years in the 2020s, with patients aged ≥60 years now comprising >40% of recipients. Donor utilization shifted markedly, with matched related donors declining (90% to 25%) in favor of matched unrelated (10% to 51%) and haploidentical donors (0% to 16%). Conditioning intensity transitioned from predominantly myeloablative (68% to 21%) to reduced intensity regimens (32% to 71%). Despite treating an older and more comorbid population, outcomes improved steadily: 3-year overall survival increased from 41% in the 1990s to 58% in the 2020s (P=0.0005), progression-free survival from 37% to 49% (P=0.01), and non-relapse mortality declined from 55% to 25% (P<0.0001). Relapse rates remained static at approximately 26–31% since 2000, with disease status at transplant the strongest predictor of recurrence. GVHD incidence peaked in the 2010s but declined in the 2020s, coinciding with wider adoption of post-transplant cyclophosphamide. Conclusion In conclusion, alloHSCT outcomes have improved markedly over 35 years, with survival gains predominantly driven by reductions in non-relapse mortality. Relapse remains the dominant barrier to cure, underscoring the need for novel strategies to augment disease control.Alia Cibich, Gauri Wechalekar, Naranie Shanmuganathan, Deepak Singhal, Ashanka Beligaswatte, Rebecca Wayte, Phil Selby, Susan Branford, David Yeung, Peter Bardy, Devendra Hiwas
Association of acetabular implants with sensitive radiographic surveillance on revision rates: a study based on 5 hip arthroplasty registries
No full textBACKGROUND AND PURPOSE: National joint arthroplasty registries are the gold standard for monitoring long-term acetabular implant survivorship. Sensitive radiographic surveillance (SRS) has been recommended as a complementary surveillance approach, but no study has investigated whether implants introduced with no sensitive radiographic surveillance (NSRS) are associated with higher revision rates. Therefore, we investigated whether acetabular implants with NSRS are associated with higher revision rates than those with SRS. METHODS: Acetabular implants with SRS were defined as those with published evidence of stability measurements assessed using either radiostereometric analysis or "Ein Bild Röntgen Analyse." Evidence of SRS of acetabular implant designs was sourced from 2 literature reviews. A mixed-effects model was used to pool and compare the revision rate of acetabular implants with SRS and NSRS at 5 and 10 years from 5 arthroplasty registries. RESULTS: There were 29 unique acetabular implant designs with SRS and 86 designs with NSRS that had matching 5- and 10-year revision rates. At 5 years, there was a mean difference of 0.8% (95% confidence interval [CI] 0.5-1.1) in mean all-cause revision rates favoring implants with SRS. Mean all-cause revision rates at 10 years for acetabular implants with SRS and NSRS were 5.2% (CI 4.9-5.5) and 7.4% (CI 7.0-7.9) respectively, with a mean difference of 1.8% (CI 1.2-2.3) favoring implants with SRS. CONCLUSION: Acetabular implants with NSRS were associated with 1.8% higher pooled revision rates than those with SRS at 10 years, which represents a relative increase in acetabular revision burden of approximately 36%.Chan Hee CHO, John M ABRAHAMS, Deepti K SHARMA, Lucian B SOLOMON, Christopher J WALL, Bart G PIJLS, and Stuart A CALLAR
The role of polyvinyl chloride in achieving circularity in the built environment: A comprehensive review
No full textThe world is struggling with the enormous challenge of managing Plastic Waste (PW), which is over 400 million tonnes (Mt) annually and is the world’s largest and most rapidly accumulating waste stream. Polyvinyl chloride (PVC), a versatile synthetic polymer, is the third most sold commodity plastic used in various industries. To promote sustainable development and implement the Circular Economy (CE) concepts, reuse, recycling, and remanufacturing have become priorities for PVC circularity. This research study examines the current trends in PVC circularity and gaps for future research directions in connecting Waste Management (WM) to achieve CE practices. Hence, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was undertaken, and two databases, namely Scopus and Web of Science, were used. The findings from the systematic literature review show that PVC circularity research has advanced significantly in recent years, with an emphasis on chemical and mechanical recycling as well as the creation of novel methods to improve material recovery and lower toxicity. However, gaps remain in circularity-directed research and in exploring efficient recycling processes for PVC waste. Addressing these challenges will require concerted efforts to improve stakeholder collaboration, build better communication channels, and invest in infrastructure supporting circular practices. By strengthening these areas, the PVC can make significant progress toward enhancing circularity, reducing environmental impact, and contributing to broader sustainability goals. The findings suggest prioritising effective recycling methods, material flow analysis, and policy frameworks to facilitate PVC’s transition to a CE, consequently minimising environmental impact and resource dependency.Nirusika Rajenthiran, Jian Zuo, Daniel Oteng, Navodana Rodrig
When education fails: narcissism, uniqueness, and need for closure in conspiracy beliefs and misinformation
No full textEducation is typically protective against epistemically unwarranted beliefs; however, recent research shows that these effects are conditional. Across two studies (N = 354; N = 306), this article examines factors that moderate the relationship between education and belief accuracy across conspiracy and misinformation contexts. In Study One, narcissistic grandiosity and the need for uniqueness offset negative effects of education on conspiracy mentality. Similarly, in Study Two, narcissism, and less consistently need for cognitive closure, offset the negative effects of education on generic conspiracy beliefs and susceptibility to misinformation.
Across both studies, the benefits of education disappeared at just one standard deviation above the mean on these traits. Other factors, including dichotomous thinking, trust and social dominance orientation, were associated with conspiracy beliefs but did not interact with education, showing consistent effects across all education levels. These findings suggest that education and reasoning may be made redundant by psychological needs for certainty, distinctiveness, and superiority – a process cautiously termed ‘epistemic-social motivated reasoning’. This framework describes how education-related abilities can be redirected towards underlying psychological and social needs rather than accuracy. Implications and future directions for research are discussed