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Pluriversal literacies: perspectives and practices for sustainable and anticolonial futures
Get PDFThis chapter is about literacies including, but exceeding, language-based literacies. In the language and educational sciences, literacy has become synonymous with reading and writing the written word. However, human based language is only one of many sign systems that mediate our world and all life on this planet. We argue that relating to, and communicating in this world, equitably and sustainably, requires far more literacies than that of the written word
Low circulating miR-190a-5p predicts progression of chronic kidney disease
Get PDFMicroRNAs may act as diagnostic and prognostic biomarkers of chronic kidney disease and are functionally important in disease pathogenesis. To identify novel microRNA biomarkers, we performed small RNA-sequencing on plasma from individuals with type 2 diabetes, with and without chronic kidney disease. MiR-190a-5p abundance was significantly lower in the circulation of type 2 diabetic patients with reduced function compared to those with normal kidney function. In an independent cohort of patients with chronic kidney disease of diverse aetiology, miR-190a-5p abundance predicted disease progression in individuals with no or moderate albuminuria ( < 300 mg/mmol). miR-190a-5p expression in kidney biopsy tissue correlated with the level of miR-190a-5p in the circulation and with estimated glomerular filtration rate, tubular mass and negatively with histological fibrosis. Administration of a miR-190a-5p mimic in a murine ischaemia-reperfusion injury model in male mice reduced tubular injury and fibrosis and increased expression of genes associated with tubular health. Our analyses suggest that miR-190a-5p is a biomarker of tubular cell health, low circulating levels may predict chronic kidney disease progression independent of existing risk factors and strategies to preserve miR-190a-5p may be an effective treatment for restoring tubular cell health following kidney injury
Special episode focussing on inclusivity and assessment for quantitative disciplines. With Nic Labrosse and Errol Rivera. Interview by Eilidh Soussi
No full textIn the summer, Eilidh Soussi met with Nic Labrosse and Errol Rivera to discuss a special project Errol and Nic have been working on for the past couple of years. In this episode they introduce the project, with a view to more detailed discussions over the months to come.
Listen, enjoy and any questions do get in touch on the SoTL Teams channel
Towards A New Era of Geo-Foundation Models: Expert-Guided Multimodal Alignment and Geospatial Context Awareness
Get PDFFoundation Models (FMs) have demonstrated significant potential for geospatial analysis. As geospatial big data (e.g., geo-tagged text and images) continues to grow, FMs have evolved into geospatial foundation models (GeoFMs), the FMs with the capability of geospatial reasoning. However, two critical tasks remain challenging: (1) how to align various geospatial modalities for model training, and (2) how to enhance FMs' geospatial context awareness. To fill these gaps, this work develops CLIP4Geo, a unified GeoFM that integrates satellite imagery, LiDAR point clouds, geo-tagged points of interest (POIs), and textual description into a shared representation space. Specifically, to empower the model with geospatial intelligence, we design a Geospatial Expert Knowledge System, which tailors both textual and visual information and encodes them into shared geospatial embeddings. Furthermore, we propose a novel Geospatial Context Awareness Transformer to guide the cross-attention mechanism, which leverages geospatial context position embedding to effectively capture spatial dependencies across modalities. We also introduce CityVerse, a large-scale, spatially aligned, and multimodal benchmark dataset covering diverse urban regions in the U.S. and China, supporting a range of geospatial downstream tasks (e.g., zero-shot classification, semantic segmentation / localization, and cross-modality retrieval and generation). Extensive experiments demonstrate that CLIP4Geo consistently outperforms state-of-the-art FM baselines, highlighting the importance of expert-guided multimodal alignment and geospatial context embeddings. Our work provides a scalable framework and comprehensive benchmark to facilitate the future development of GeoFMs for various geospatial applications
Anthracycline dose, myocardial injury, and change in left ventricular function in the Cardiac CARE trial
Get PDFBackground:
Anthracycline-induced toxicity contributes to long-term cardiovascular morbidity in cancer survivors. Cardiac troponin is recommended for risk stratification and diagnosis, but the relationship between troponin concentrations—particularly those measured using high-sensitivity assays—and subsequent cardiac dysfunction remains unclear.
Objectives:
The authors sought to examine associations between high-sensitivity cardiac troponin I (hs-cTnI), cumulative anthracycline dose, number of treatment cycles, and changes in left ventricular (LV) function.
Methods:
The Cardiac CARE trial was a prospective, multicenter, randomized, open-label, blinded-endpoint study of cardioprotective therapy in patients with elevated baseline hs-cTnI undergoing high-dose anthracycline chemotherapy. Hs-cTnI was measured before each chemotherapy cycle and at 2, 4, and 6 months after treatment. LV function was assessed by cardiac magnetic resonance at baseline and 6 months post-chemotherapy.
Results:
Of the 175 participants (mean age 52 ± 11 years; 86.5% women), 171 received ≥3 anthracycline cycles. The median cumulative epirubicin-equivalent dose was 600 mg/m2 (Q1-Q3: 513-660 mg/m2). Peak hs-cTnI concentrations were observed 2 months after chemotherapy (median 14.0 ng/L [Q1-Q3: 9.0-30.5 ng/L]) and statistically correlated with the number of treatment cycles, but not with cumulative dose. No participants developed an LV ejection fraction (LVEF) <50%, although 24 of 171 patients (14.0%) experienced a decline in LVEF >10%. Hs-cTnI showed a weak correlation with LVEF change and was predictive of global longitudinal strain by cardiac magnetic resonance.
Conclusions:
Hs-cTnI levels were not associated with cumulative anthracycline dose and were only weakly associated with LVEF decline at 6 months. These findings suggest that mild myocardial injury, as reflected by hs-cTnI elevation, may not reliably predict subsequent cardiac dysfunction following anthracycline chemotherapy
Leveraging Depth and Language for Open-Vocabulary Domain-Generalized Semantic Segmentation
Get PDFOpen-Vocabulary semantic segmentation (OVSS) and domain generalization in semantic segmentation (DGSS) highlight a subtle complementarity that motivates Open-Vocabulary Domain-Generalized Semantic Segmentation (OV-DGSS). OV-DGSS aims to generate pixel-level masks for unseen categories while maintaining robustness across unseen domains, a critical capability for real-world scenarios such as autonomous driving in adverse conditions. We introduce Vireo, a novel single-stage framework for OV-DGSS that unifies the strengths of OVSS and DGSS for the first time. Vireo builds upon the frozen Visual Foundation Models (VFMs) and incorporates scene geometry via Depth VFMs to extract domain-invariant structural features. To bridge the gap between visual and textual modalities under domain shift, we propose three key components: (1) GeoText Query, which align geometric features with language cues and progressively refine VFM encoder representations; (2) Coarse Mask Prior Embedding (CMPE) for enhancing gradient flow for faster convergence and stronger textual influence; and (3) the Domain-Open-Vocabulary Vector Embedding Head (DOV-VEH), which fuses refined structural and semantic features for robust prediction. Comprehensive evaluation on these components demonstrates the effectiveness of our designs. Our proposed Vireo achieves the state-of-the-art performance and surpasses existing methods by a large margin in both domain generalization and open-vocabulary recognition, offering a unified and scalable solution for robust visual understanding in diverse and dynamic environments
Preface: the organisation of irresponsibility? COVID-19 and the governance of state-society relations in Europe
No full textNo abstract available
The influence of learning orientation on corporate sustainability: serial mediation of supply chain practices
Get PDFBased on the theory of organizational learning, supply chain practice view, and stakeholder theory, this paper presents an empirical analysis of the influence of learning orientation on corporate sustainability through supply chain relationships and supply chain agility. A learning orientation strengthens supply chain practices, potentially extending its impact beyond mere business transactions to enhance sustainability through knowledge transfer. Empirical results reveal the relationships among the constructs and serial mediation of supply chain relationship and supply chain agility. The empirical data were collected from organizations in the United Arab Emirates. The structural equation modeling approach is applied to validate the models in the study. Mediation analysis was performed to better understand the organizational and supply chain phenomenon. In addition, this study provides empirical support for serial mediation, with supply chain relationships and supply chain agility mediating the relationship between learning orientation and corporate sustainability. The study draws managers' attention to the importance of learning orientation as well as supply chain relationship and supply chain agility post-COVID-19. The findings may guide firms toward designing their sustainable supply chain strategies under organizational learning. This paper contributes to the sustainable supply chain management literature
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