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    Exploring geographic differences in IgE response through network and manifold analyses
    (Elsevier Inc. on behalf of the American Academy of Allergy, Asthma & Immunology, 2026-01-01) Cucco A; Pearce N; Simpson A; Pembrey L; Mpairwe H; Figueiredo CA; Cooper PJ; Douwes J; Brooks C; Adcock IM; Kermani NZ; Roberts GDM; Murray CS; Custovic A; Fontanella S; WASP Study Group; STELAR/UNICORN Consortium; U-BIOPRED Consortium
    Background: Component-resolved diagnostics allow detailed assessment of IgE sensitization to multiple allergenic molecules (component-specific IgEs, or c-sIgEs) and may be useful for asthma diagnosis. However, to effectively use component-resolved diagnostics across diverse settings, it is crucial to account for geographic differences. Objective: We investigated spatial determinants of c-sIgE networks to facilitate development of diagnostic algorithms applicable globally. Methods: We used multiplex component-resolved diagnostics array to measure c-sIgE to 112 proteins in an international collaboration of several studies: WASP (World Asthma Phenotypes; United Kingdom, New Zealand, Brazil, Ecuador, and Uganda), U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes; 7 European countries), and MAAS (Manchester Asthma and Allergy Study, a UK population-based birth cohort). Hierarchical clustering on low-dimensional representation of co-occurrence networks ascertained sensitization and c-sigE clusters across populations. Cross-country comparisons focused on a common subset of 18 c-sIgEs. We investigated sensitization networks across regions in relation to asthma severity. Results: Sensitization profiles shared similarities across regions. For 18 c-sIgEs shared across study populations, the response structure enabled differentiation between different geographic areas and study designs, revealing 3 clusters: (1) Uganda, Ecuador, and Brazil, (2) U-BIOPRED children and adults, and (3) New Zealand, United Kingdom, and MAAS. Spectral clustering identified differences between clusters. We observed constant, almost parallel shifts between severe and nonsevere asthma in each country. Conclusions: Patterns of c-sIgE response reflect geographic location and study design. However, despite geographic differences in c-sIgE networks, there is a remarkably consistent shift between networks of subjects with nonsevere and severe asthma.
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    Transgender healthcare, telehealth, venture capital and community
    (Intellect, 2023-07-31) Easterbrook-Smith G
    Accessing reliable and competent gender-affirming medical care is often difficult for transgender people. FOLX is a telehealth and pharmaceutical delivery start-up which launched in late 2020, primarily offering gender-affirming hormone therapy for a monthly fee. FOLX’s marketing makes extensive use of social media and online influencers, and the company frequently highlights a goal of being created ‘by and for’ transgender people. This article examines FOLX’s deployment of narratives of community, collectivity, unmet need and commercial opportunity, examining the company’s website, social media posts and media coverage and interviews with the founder. Ultimately, it argues that while the core business offering of FOLX meets a need for a marginalized and underserved population, their deployment of narratives about community support should be regarded with some scepticism. These narratives appear in some cases to co-opt community values of collectivity, mutual aid and support for the benefit of venture capital firms.
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    Love what you do (and it'll become increasingly difficult to agitate for workplace rights): Sex, work, and rejecting the empowerment discourse
    (Taylor and Francis Group on behalf of Routledge, 2022-09-02) Easterbrook-Smith G; Rees E
    Taking as its point of inquiry movements in sex work activism which frame sex work as work, this chapter considers the implications of a resistance to discourses of ‘empowerment’. An ‘empowerment’ discourse gained prominence through the late 1990s and 2000s as a means to justify sex work as legitimate and deserving of respect. However, this discourse has been weaponised against sex workers who experience exploitation, or other poor working conditions. Resisting the insistence that sex work must be pleasurable in order to be real work is implicitly a resistance to neoliberal and particularly postfeminist pressures to display an appropriate affective engagement in one’s work. Rather than a politics which aims for incremental acceptance for those already closest to inclusion, it demands that the work be taken seriously regardless of how, where, and by whom it is carried out. Speaking to the interplay of themes about the personal and political, this chapter argues that in this context a refusal to engage with discussions of pleasure may, counterintuitively, sometimes be subversive.
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    CSMSA: Cross-Space Multiscale Adaptive Link Prediction for ceRNA-Mediated Multimolecular Disease Regulatory Networks
    (Association for Computing Machinery, 2025-12-10) Long J; Li J; Qu G; Liu K; Liu B
    Regulatory interactions associated with diseases are pivotal for elucidating the molecular mechanisms that drive disease progression and promoting precision medicine. Nevertheless, existing research algorithms often overlook the potential dynamic synergistic-competitive mechanisms between different ceRNA regulatory networks and lack cross-space learning capabilities across multiple heterogeneous graph structures, making it difficult to comprehensively capture the multidimensional molecular regulatory biological mechanisms in disease data with different structural densities. Therefore, we propose the cross-space multiscale adaptive learning framework (CSMSA) that integrates a heterogeneous five-layer ceRNA regulatory network and introduces an adaptive cross-space learning mechanism to dynamically capture complementary and specific interactions and effectively learn the intrinsic biological regulatory mechanisms. Moreover, the CSMSA framework employs a multi-scale feature fusion strategy that hierarchically learns node embeddings by integrating local structural information and global topological features from heterogeneous graphs to enhance predictive performance and robustness across complex datasets of varying sizes. Comprehensive evaluations on three independent datasets show that CSMSA surpasses existing methods in the multimolecular disease prediction task (Max AUC = 0.9880, Max AUPR = 0.9829), thereby providing a reliable new paradigm for probing disease regulatory links.
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    Smart Glasses for CVI: Co-Designing Extended Reality Solutions to Support Environmental Perception by People with Cerebral Visual Impairment
    (Association for Computing Machinery, 2025-10-22) Gamage B; Mcdowell N; Kovacic D; Holloway L; Do TT; Lowery AJ; Price N; Marriott K; Kane S; Shinohara K
    Cerebral Visual Impairment (CVI) is the set to be the leading cause of vision impairment, yet remains underrepresented in assistive technology research. Unlike ocular conditions, CVI affects higher-order visual processing - impacting object recognition, facial perception, and attention in complex environments. This paper presents a co-design study with two adults with CVI investigating how smart glasses, i.e. head-mounted extended reality displays, can support understanding and interaction with the immediate environment. Guided by the Double Diamond design framework, we conducted a two-week diary study, two ideation workshops, and ten iterative development sessions using the Apple Vision Pro. Our findings demonstrate that smart glasses can meaningfully address key challenges in locating objects, reading text, recognising people, engaging in conversations, and managing sensory stress. With the rapid advancement of smart glasses and increasing recognition of CVI as a distinct form of vision impairment, this research addresses a timely and under-explored intersection of technology and need.
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    Vulnerability of marine megafauna to global at-sea anthropogenic threats
    (Wiley Periodicals LLC on behalf of Society for Conservation Biology, 2025-11-14) VanCompernolle M; Morris J; Calich HJ; Rodríguez JP; Marley SA; Pearce JR; Abrahms B; Abrantes K; Afonso AS; Aguilar A; Agyekumhene A; Akamatsu T; Åkesson S; Alawa NG; Alfaro-Shigueto J; Anderson RC; Anker-Nilssen T; Arata JA; Araujo G; Arostegui MC; Arrizabalaga H; Arrowsmith LM; Auger-Méthé M; Avila IC; Bailleul F; Barker J; Barlow DR; Barnett A; Barrios-Garrido H; Baylis AMM; Bearzi G; Bejder L; Belda EJ; Benson SR; Berumen ML; Bestley S; Bezerra NPA; Blaison AV; Boehme L; Bograd SJ; Abimbola BD; Bond ME; Borrell A; Bouchet PJ; Boveng P; Braulik G; Braun CD; Brodie S; Bugoni L; Bustamante C; Campana SE; Cárdenas-Alayza S; Carmichael RH; Carroll G; Carter MID; Ceia FR; Cerchio S; Ferreira LC; Chambault P; Chapple TK; Charvet P; Chavez EJ; Chevallier D; Chiaradia A; Chilvers BL; Cimino MA; Clark BL; Clarke CR; Clay TA; Cloyed CS; Cochran JEM; Collins T; Cortes E; Cuevas E; Curnick DJ; Dann P; de Bruyn PJN; de Vos A; Derville S; Dias MP; Diaz-Lopez B; Dodge KL; Dove ADM; Doyle TK; Drymon JM; Dudgeon CL; Dutton PH; Ellenberg U; Elwen SH; Emmerson L; Eniang EA; Espinoza M; Esteban N; Mul E; Fadely BS; Fayet AL; Feare C; Ferguson SH; Feyrer LJ; Finucci B; Florko KRN; Fontes J; Fortuna CM; Fossette S; Fouda L; Frere E; Fuentes MMPB; Gallagher AJ; Borboroglu PG; Garrigue C; Gauffier P; Gennari E; Genov T; Germanov ES; Giménez J; Godfrey MH; Godley BJ; Goldsworthy SD; Gollock M; González Carman V; Gownaris NJ; Grecian WJ; Guzman HM; Hamann M; Hammerschlag N; Hansen ES; Harris MP; Hastie G; Haulsee DE; Hazen EL; Heide-Jørgensen MP; Hieb EE; Higdon JW; Hindell MA; Hinke JT; Hoenner X; Hofmeyr GJG; Holmes BJ; Hoyt E; Huckstadt LA; Hussey NE; Huveneers C; Irvine LG; Jabado RW; Jacoby DMP; Jaeger A; Jagielski PM; Jessopp M; Jewell OJD; Jiménez Alvarado D; Jordan LKB; Jorgensen SJ; Kahn B; Karamanlidis AA; Kato A; Keith-Diagne LW; Kiani MS; Kiszka JJ; Kock AA; Kopf RK; Kuhn C; Kyne PM; Laidre KL; Lana FO; Lander ME; Le Corre M; Lee OA; Leeney RH; Levengood AL; Levenson JJ; Libertelli M; Liu K-M; Lopez Mendilaharsu M; Loveridge A; Lowe CG; Lynch HJ; Macena BCL; Mackay AI
    Marine megafauna species are affected by a wide range of anthropogenic threats. To evaluate the risk of such threats, species’ vulnerability to each threat must first be determined. We build on the existing threats classification scheme and ranking system of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species by assessing the vulnerability of 256 marine megafauna species to 23 at-sea threats. The threats we considered included individual fishing gear types, climate-change-related subthreats not previously assessed, and threats associated with coastal impacts and maritime disturbances. Our ratings resulted in 70 species having high vulnerability (v > 0.778 out of 1) to at least 1 threat, primarily drifting longlines, temperature extremes, or fixed gear. These 3 threats were also considered to have the most severe effects (i.e., steepest population declines). Overall, temperature extremes and plastics and other solid waste were rated as affecting the largest proportion of populations. Penguins, pinnipeds, and polar bears had the highest vulnerability to temperature extremes. Bony fishes had the highest vulnerability to drifting longlines and plastics and other solid waste; pelagic cetaceans to 4 maritime disturbance threats; elasmobranchs to 5 fishing threats; and flying birds to drifting longlines and 2 maritime disturbance threats. Sirenians and turtles had the highest vulnerability to at least one threat from all 4 categories. Despite not necessarily having severe effects for most taxonomic groups, temperature extremes were rated among the top threats for all taxa except bony fishes. The vulnerability scores we provide are an important first step in estimating the risk of threats to marine megafauna. Importantly, they help differentiate scope from severity, which is key to identifying threats that should be prioritized for mitigation.
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    MIC: Medical Image Classification Using Chest X-ray (COVID-19 & Pneumonia) Dataset with the Help of CNN and Customized CNN
    (Association for Computing Machinery, 2025-06-06) Fahad N; Ahmed R; Jahan F; Jamal Sadib R; Morol MK; Jubair MAA
    The COVID-19 pandemic has had a detrimental impact on the health and welfare of the world's population. An important strategy in the fight against COVID-19 is the effective screening of infected patients, with one of the primary screening methods involving radiological imaging with the use of chest X-rays. Which is why this study introduces a customized convolutional neural network (CCNN) for medical image classification. This study used a dataset of 6432 images named Chest X-ray (COVID-19 & Pneumonia), and images were preprocessed using techniques, including resizing, normalizing, and augmentation, to improve model training and performance. The proposed CCNN was compared with a convolutional neural network (CNN) and other models that used the same dataset. This research found that the Convolutional Neural Network (CCNN) achieved 95.62% validation accuracy and 0.1270 validation loss. This outperformed earlier models and studies using the same dataset. This result indicates that our models learn effectively from training data and adapt efficiently to new, unseen data. In essence, the current CCNN model achieves better medical image classification performance, which is why this CCNN model efficiently classifies medical images. Future research may extend the model's application to other medical imaging datasets and develop real-time offline medical image classification websites or apps.
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    Developing a serious game for indoor air quality and mold prevention education in residential buildings
    (Emerald Publishing Limited, 2025-10-21) Baghaei Daemei A; Feng Z; Paes D
    Purpose This study explores the development and prototyping of a serious game aimed at teaching individuals how to prevent mold growth in homes. Design/methodology/approach The development process involved several steps including identifying learning objectives based on Bloom’s Taxonomy, establishing educational content through literature review, designing game mechanics followed by Octalysis, designing the game’s narrative and storyline, developing the prototype using Storyline 360, verifying the educational content via interview and home visit, and refining it through the verification outcomes. Findings Key findings highlighted the most mold-prone areas in the kitchen, bedroom, and bathroom, the main factors contributing to mold growth: moisture, cold surfaces, nutrients, and spores. Also, the study recommends maintaining indoor temperatures between 20–24°C and humidity levels between 40–60% to prevent mold and keep moisture levels in check. Practical mold prevention strategies were identified and integrated into the game. The game incorporates a variety of mechanics, including narrative, points, progress bars, quest lists, step-by-step tutorials, level-ups, milestone unlocks, instant feedback, avatars, mentorship, visual storytelling, and progress loss. The preliminary assessment of a within-subject experiment (pre-test vs post-test) on 60 participants demonstrated that knowledge was improved after the intervention. Practical implications The game offers an innovative tool for a healthy built environment to educate the general public on mold risks and prevention strategies. Social implications By promoting healthy housing practices and awareness of indoor environmental quality, the game has the potential to improve respiratory health outcomes and reduce health disparities in vulnerable populations in the built environment. Originality/value This study represents the first attempt to design, develop, and verify a serious game specifically focused on mold prevention in residential buildings, integrating verified real-world data, expert insights, and user-centered design principles.
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    Integrated multi-omic and symptom clustering reveals lower-gastrointestinal disorders of gut-brain interaction heterogeneity
    (Taylor and Francis Group, 2026-12-31) Dowrick JM; Roy NC; Carco C; James SC; Heenan PE; Frampton CMA; Fraser K; Young W; Cooney J; Trower T; Keenan JI; McNabb WC; Mullaney JA; Bayer SB; Talley NJ; Gearry RB; Angeli-Gordon TR
    Rome IV disorders of gut-brain interaction (DGBI) subtypes are known to be unstable and demonstrate high rates of non-treatment response, likely indicating patient heterogeneity. Cluster analysis, a type of unsupervised machine learning, can identify homogeneous sub-populations. Independent cluster analyses of symptom and biological data have highlighted its value in predicting patient outcomes. Integrated clustering of symptom and biological data may provide a unique multimodal perspective that better captures the complexity of DGBI. Here, integrated symptom and multi-omic cluster analysis was performed on a cohort of healthy controls and patients with lower-gastrointestinal tract DGBI. Cluster stability was assessed by considering how frequently pairs of participants appeared in the same cluster between different bootstrapped datasets. Functional enrichment analysis was performed on the biological signatures of stable DGBI-predominant clusters, implicating disrupted ammonia handling and metabolism as possible pathophysiologies present in a subset of patients with DGBI. Integrated clustering revealed subtypes that were not apparent using a singular modality, suggesting a symptom-only classification is prone to capturing heterogeneous sub-populations.
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    Air-liquid interface biofilm formation of pseudomonads and the impact of traditional clean-in-place on biofilm removal
    (Elsevier Ltd, 2026-02-28) Muthuraman S; Palmer J; Flint S
    Pseudomonads are common psychrotrophic spoilage bacteria associated with dairy, poultry, and meat processing environments. They can multiply at low temperatures, 4–7 °C, producing thermostable spoilage enzymes. Pseudomonads form strong biofilms by producing higher EPS (Extracellular polymeric substances) at low temperatures. This study focused on the biofilm formation of pseudomonads at the air-liquid interface and their EPS removal. Two strong biofilm-forming isolates, (Pseudomonas lundensis) 3SM and (Pseudomonas cedrina) 20SM were allowed to form biofilms on stainless steel coupons in a CDC reactor under a continuous flow of nutrients at 4 °C over a week. The cell counts reached approximately 7.5 log CFU/cm2. The biofilms formed at the air-liquid interface showed more visible biofilms, polysaccharides, and higher cell counts than those submerged in liquid. Cleaning the biofilms using 1 % NaOH at 70 °C resulted in viable bacterial cells below the detection limit. However, residual material termed biofilm “footprints” was present after cleaning and were analysed with SEM and FTIR. The SEM observations showed tightly packed robust biofilm cells before cleaning. Coupons treated with 55 °C water showed an upper layer of degraded cells. After treatment with 70 °C NaOH, organic material was still visible under SEM. Based on the FTIR observations, the EPS extracted from the control and treated coupons showed that the amount of biomolecules reduced after cleaning with NaOH, but the footprints still existed. The biofilm footprints led to the early appearance of biofilms at the air-liquid interface compared to new coupons exposed to strong biofilm-forming isolates. Cleaning with caustic can eliminate the cells, but the EPS from biofilms of pseudomonads is not completely removed, resulting in a possibility of regrowth when the new inoculum is introduced.