Search Results (743)

Background: Severe involutional lower eyelid ectropion with complete eyelid eversion represents an advanced stage of eyelid malposition in which long-standing involutional changes may be accompanied by secondary structural remodeling of the posterior lamella. Although conventional surgical techniques are generally effective in mild to moderate cases, the management of end-stage involutional ectropion remains challenging. Methods: This retrospective single-center case series included nine patients treated for severe involutional lower eyelid ectropion with complete eyelid eversion between January 2024 and December 2025. Surgical treatment consisted of horizontal eyelid tightening, with adjunctive procedures performed according to intraoperative findings. Lower eyelid retractors were managed by reattachment, tightening, or complete release based on intraoperative clinical judgment when marked fibrosis, shortening, and persistent inferior traction were identified. Clinical outcomes were analyzed descriptively. Results: Complete lower eyelid retractor release was performed in three patients during primary surgery and two during revision surgery. The remaining patients underwent retractor tightening or reattachment. During a mean follow-up of 10.5 months, recurrent ectropion occurred in five of six patients treated with retractor tightening or reattachment. No recurrence was observed after complete retractor release, either as a primary or revision procedure. Revision surgery including complete retractor release restored a stable eyelid position in all reoperated patients during the available follow-up period. Conclusions: Complete lower eyelid retractor release was associated with favorable anatomical outcomes in this small retrospective case series of selected patients with intraoperative evidence of marked retractor fibrosis or shortening. These findings are descriptive and hypothesis-generating and should be interpreted within the limitations of the study. Full article

Background/Objectives: Total ankle arthroplasty (TAA) is increasingly used to treat end-stage ankle arthritis, but comprehensive cross-registry data on revision patterns remain limited. This study describes indications, causes, and patient risk factors for revisions using three national registries. Methods: Aggregate data were extracted from the UK National Joint Registry (NJR; 22nd Annual Report 2025; n = 11,321), the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR; 2025 Ankle Supplementary Report; n = 5379), and the Swedish Ankle Registry (SwedAnkle; Annual Report 2024; n = 1852; survival estimates from a published sub-cohort, n = 1226). Metrics were compared descriptively without inferential pooling. Results: Across registries, 18,552 primary TAAs were identified. Ten-year cumulative per cent revision (CPR) was 9.54% (95% confidence interval [CI], 8.75–10.39) in the NJR, 13.5% (95% CI, 12.1–15.1) in the AOANJRR osteoarthritis sub-cohort, and approximately 26% (author-derived from Kaplan–Meier curves; see Methods) in SwedAnkle (1993 onwards implants). Aseptic loosening was the predominant cause of revision in all three registries; the rank of subsequent causes differed between registries (infection was second in the NJR and AOANJRR; in SwedAnkle, infection ranked below insert wear/breakage at 11.5%). AOANJRR Cox analysis identified younger age (hazard ratios (HRs), 2.00 for <55 vs. ≥75 years; 95% CI, 1.30–3.07; p = 0.001), earlier surgical era (HR, 1.91 for pre-2015 vs. 2015–2024; 95% CI, 1.53–2.38; p < 0.001), and obesity (HR, 1.52 for body mass index (BMI) ≥ 30; 95% CI, 1.06–2.19; p = 0.023) as significant independent predictors in AOANJRR Cox proportional hazards models (osteoarthritis sub-cohort for age, sex, BMI and ASA; all-diagnoses primary cohort for surgical era). Sex and American Society of Anesthesiologists (ASA) scores were not significant. Conclusions: Aseptic loosening was the predominant cause of revision in all three registries. The rank of subsequent causes differed: in the NJR and AOANJRR, infection was the second most frequent cause; in SwedAnkle, infection ranked below insert wear/breakage. Younger age, obesity, and earlier surgical era were independent predictors of revision in AOANJRR Cox proportional hazards models. The post-2015 era was associated with approximately 48% lower revision hazard; this association cannot be interpreted causally, as the independent contributions of implant design, surgical technique, patient selection, and other secular changes cannot be isolated from registry data. These findings may inform preoperative counselling, implant selection, and registry harmonisation efforts. Full article

Background: The Martini and Melamed criteria for diagnosing multiple primary lung cancers (MPLCs) have remained in use for half a century despite substantial changes in lung cancer epidemiology, risk factors, imaging technologies, and treatment approaches. Correspondingly, the landscape of MPLC has likely changed, necessitating revisions to their diagnostic guidelines. Research Question: What are the clinicopathologic profiles of modern-day MPLC patients, and can these features be used to identify a subset of patients classified as MPLC that may warrant additional investigation as intrapulmonary metastasis (IPM)? Study Design and Methods: We conducted a retrospective cohort study using electronic medical record data from patients who underwent multiple lung cancer resections at Mount Sinai Hospital. Patient demographics, tumor characteristics, and surgical treatments were compared with those reported in the original Martini and Melamed series. We then proposed a reclassification framework incorporating a CT-based assessment of synchronous versus metachronous tumors and contemporary clinicopathologic features documented in imaging and pathology reports. Results: Ninety-one patients underwent successive lung cancer resections. Among first nodules treated with surgical resection, 46% exhibited pathologic features suggestive of metastasis within the lung, including visceral pleural invasion (18%), vascular invasion (24%), lymphatic invasion (36%), and/or lymph node positivity (3%). In contrast, among second nodules (second temporal surgery), 45% demonstrated ground-glass opacity (GGO) supportive of a diagnosis of MPLC. Using the original criteria, 83 patients (91%) were classified as having MPLC; this proportion decreased to 53 patients (58%) under the reclassification criteria. Regardless of the criteria applied, contemporary MPLCs were more likely to occur in older patients, women, those with adenocarcinoma histology, and treated with sublobar resections compared with MPLCs described in the Martini and Melamed era. Conclusions: MPLCs are increasingly recognized, and their clinical presentation has changed substantially over time. Modern imaging and pathologic assessment may be useful tools for diagnosing MPLCs, but this requires future validation. This has important implications for staging and treatment decision-making, as patients may be undertreated by not being offered multimodal treatments or over-treated with systemic therapy when surgery alone may be sufficient. Full article

Background/Objectives: Total knee arthroplasty (TKA) relieves pain and restores function for most patients with end-stage knee disease; yet, a clinically important minority are left with persistent pain, stiffness or both despite well-fixed, well-aligned implants. These “hidden failures” are poorly captured by implant survivorship but drive disability, dissatisfaction and disproportionate cost—stiff knees incur roughly 1.5–7.5 times the two-year treatment costs of non-stiff knees. This review integrates three usually separate studies within one phenotype-based framework. Methods: A structured comprehensive narrative review and thematic synthesis was undertaken; PubMed/MEDLINE, Web of Science and Google Scholar were searched between 30 October 2025 and 1 May 2026, identifying 467 records, of which 239 met the eligibility criteria and informed the synthesis. Results: Clinically meaningful chronic pain affects roughly 10–30% of recipients and stiffness approximately 1–7%, with high-impact chronic pain persisting in about one-in-five and neuropathic features in a third to a half of those affected. Contemporary dissatisfaction estimates appear closer to 7–14% than the historical “one-in-five” paradigm, with persistent pain and stiffness the dominant drivers of residual dissatisfaction. Symptoms arise from interacting mechanical, fibrotic, infective, neuropathic, central and psychosocial mechanisms. Six practical phenotypes are proposed—pain-dominant with preserved motion, stiffness-dominant, combined stiff-and-painful, neuropathic-dominant, centrally sensitized, and arthrofibrosis with true mechanical block—and diagnosis, prevention and management are organized around them, spanning risk stratification, surgical technique, manipulation under anesthesia (mean gains ~30–47°, ~6% failure), arthrolysis, revision and multidisciplinary pain care. Conclusions: Chronic pain and stiffness are the quiet arithmetic of arthroplasty success—rare on the survivorship curve, common in the clinic. Matching treatment to phenotype and reserving the operating theater for a knee with a mechanical fault to fix rather than a nervous system to calm, offers the clearest path from a technically successful operation to a genuinely successful recovery. Full article

Understanding individual growth is essential for assessing exploitation status and supporting sustainable fishery management. For the southern Brazilian stock of the mullet Mugil liza, previous growth estimates were based on whole otolith readings and included few young individuals, potentially influencing growth parameter estimation and stock assessment outputs. In this study, daily otolith microincrements of juveniles were validated using oxytetracycline (OTC) marking and combined with age–length data from a previous study to evaluate the effect of incorporating validated juvenile ages into von Bertalanffy growth function estimates. The updated model yielded a 15% smaller asymptotic length (564 mm), a 47% higher growth coefficient (0.28 yr⁻¹), and a theoretical age at zero length closer to biologically plausible values (t0 = −0.11). Revised growth parameters were incorporated into an age-structured production model (ASPM). Although temporal trends in spawning biomass and fishing mortality remained similar, substantial differences were observed in biomass scale and biological reference points. These findings highlight the sensitivity of stock assessment outputs to growth parameterization and the importance of adequately representing early life stages in growth models. Full article

Vibration-based sensing systems for deployed industrial fault diagnosis often face incremental fault classes, changing degradation stages, and limited permission to retain historical sensor streams. Static fault classifiers are therefore insufficient for online maintenance settings in which a model must learn new sensor-observed states while preserving previous diagnostic knowledge under a bounded memory budget. This paper proposes ASBR-CL, an adaptive stage-aware balanced replay framework for continual fault diagnosis under a fixed exemplar-memory budget. ASBR-CL combines dataset-adaptive exemplar memory, balanced replay between current data and retained exemplars, and a conditional validation checkpoint module that is enabled only when it improves balanced stage recognition. Experiments on SEU-enhanced92, the 92-dimensional feature construction for SEU, and XJTU-bearing23, the 23-dimensional feature construction for XJTU-SY, compare ASBR-CL with DGGN/MFF same-backbone continual-learning baselines and XJTU imbalance-aware variants under five random seeds and $K=100$ training exemplars. On SEU, the selected ASBR-CL setting reports $97.49\pm 1.18$ Average Accuracy, $90.37\pm 4.53$ Final Accuracy, $90.37\pm 4.53$ Macro Recall, and $11.50\pm 5.25$ Average Forgetting. On XJTU, the conservative ASBR-CL-BoundedVal-K100 setting is not a universal Final Accuracy winner: DGGN-ER reaches a slightly higher Final Accuracy ($89.52\pm 2.68$ versus $89.05\pm 2.48$). The ASBR-CL evidence instead lies in balanced recognition and retention, with Macro Recall $75.00\pm 2.00$, Macro-F1 $67.66\pm 3.83$, and Average Forgetting $20.39\pm 4.89$, compared with DGGN-ER at $63.94\pm 7.50$, $55.48\pm 12.82$, and $41.11\pm 13.61$. Additional validation-resource, RMS-derived stage-definition, and imbalance-aware baseline analyses show that the revised XJTU claim should be framed as more stable Macro Recall, Macro-F1, and forgetting control under memory-limited continual diagnosis, not as superiority on every accuracy metric. Full article

Background: Postoperative haemorrhage (POH) is a rare but potentially life-threatening complication of thyroid surgery, with an incidence of 0.6–4%. Early identification of patients at increased risk is critical to guide perioperative management, especially in the context of evolving surgical practices and increasing demand for outpatient procedures. Methods: We conducted an explorative, retrospective, single-centre case–control study using a prospectively documented quality assurance dataset including 9158 thyroidectomies (2012–2019). POH requiring revision (n = 104) were compared to matched controls (n = 416; 1:4 ratio), matched by age, sex, type of procedure (uni- vs. bilateral), and year of surgery. Univariate analysis (Chi-square and t-test) was used to identify possible associations between candidate risk factors and POH. To supplement classical univariate statistics, we applied a Random Forest machine learning model to assess the relative importance of 25 potential variables derived from the clinical dataset based on previous literature. It was also planned to use the results to develop a proposal for a quantitative risk score, system, assigning weights to each factor (3, 1, or 0 points) depending on their relative importance for predicting POH. Patients were subsequently categorized into risk classes (low, intermediate, high) based on total point scores and reclassified. Results: High-impact risk factors confirmed in univariate analysis and Random Forest modelling included reoperative thyroidectomy, smoking, relevant comorbidities, medical treatment for hyperthyroidism and advanced age and were weighted with 3 points. Moderately associated variables such as regular alcohol consumption, Graves’ disease, hyperthyroid state at surgery, duration of the procedure and thyroid weight were weighted 1 point. Factors with negligible predictive value (e.g., BMI, gender, ASA classification) were assigned 0 points. The average score among patients without haemorrhage was 5.21, whereas the average score among patients with haemorrhage was 7.61. Within the matched study cohort, patients with POH accumulated higher risk scores than controls, suggesting potential discriminatory capacity. These findings formed the basis for the development of an exploratory three-stage ‘traffic light’ risk stratification model that requires external validation. Conclusions: A simple, interpretable point-based scoring system derived from a large matched case–control cohort identified key predictors of postoperative hemorrhage (POH) after thyroid surgery and enabled risk stratification within the study population. By combining conventional statistical methods with machine-learning approaches, the score may support individualized perioperative monitoring, surgical planning, and institutional resource allocation. However, because the model was developed using a 1:4 matched case–control design, it should be considered an exploratory risk stratification tool rather than a fully validated prediction model, and it does not directly estimate absolute POH risk or population incidence. External and prospective validation in large, representative multicentre cohorts (e.g., StuDoQ, HEDOS) is ongoing and will be required to establish calibration, generalizability, and clinical utility. Full article

3D concrete printing (3DCP) is an emerging modern method of construction with potential to improve construction efficiency, reduce labour requirements, and support the delivery of sustainable housing. In Ireland, its recent adoption coincides with increasing policy emphasis on modern methods of construction and the introduction of stricter European requirements for assessing the climate impact of buildings. The recast Energy Performance of Buildings Directive (EPBD) introduces progressive requirements for the calculation and reporting of whole-life Global Warming Potential (GWP) for new buildings, creating a need for Life Cycle Assessment (LCA) methodologies aligned with current regulatory requirements and capable of capturing the specific characteristics of emerging construction technologies. This paper reviews the applicability of the EPBD, EN 15978, EN 15804, Level(s), and relevant Irish methodologies to 3DCP buildings. It also examines existing LCA studies on 3DCP and evaluates their methodological scope, system boundaries, functional units, data sources, and alignment with current regulatory requirements. The review shows that most existing 3DCP LCA studies remain focused on materials, components, or limited life-cycle stages, with cradle-to-gate assessments being particularly common. Consequently, many published studies do not fully align with the whole-building, cradle-to-grave assessment framework introduced under the revised EPBD.. The review also identifies a lack of LCA methodologies specifically tailored to 3DCP buildings, particularly in relation to printable material design, construction-process energy consumption, material efficiency, reinforcement strategy, durability, maintenance, and end-of-life scenarios. These gaps limit the comparability and regulatory relevance of current sustainability assessments. The paper concludes that EPBD-compliant whole-life carbon assessments of complete 3DCP buildings are urgently needed, alongside the development of 3DCP-specific methodological guidance and data to support reliable environmental benchmarking and wider adoption of the technology in Ireland and Europe. Full article

Geopolitical instability is increasingly affecting the development and deployment of artificial intelligence (AI) infrastructure by disrupting energy systems, semiconductor supply chains, and digital infrastructure networks. While existing research has explored geopolitical risk, digital sovereignty, and AI governance, little attention has been paid to understanding how geopolitical factors are integrated into the valuation and strategic allocation of AI infrastructure. This theory-building study introduces the concept of geopolitical repricing, defined as the process through which firms, investors, governments, and infrastructure operators revise their assessment of the economic value, risk profile, and strategic importance of AI infrastructure in response to geopolitical instability. Drawing on literature on geopolitical risk, AI infrastructure, digital sovereignty, geo-economics, and investment under uncertainty, the paper develops a four-stage analytical framework that links geopolitical shocks, transmission channels, revaluation, and strategic reallocation. The framework identifies three interconnected transmission channels: energy volatility, supply-chain disruption, and infrastructure vulnerability, and explains how their cumulative effects may influence valuation judgments, investment criteria, and infrastructure allocation decisions. The study further proposes a set of theoretically derived propositions and operational indicators to guide future empirical research. The paper contributes to the emerging political economy of AI by providing a conceptual explanation of how geopolitical instability may shape infrastructure valuation beyond the immediate effects of disruption. It lays the groundwork for future research on the connections between geopolitical factors, infrastructure strategies, and AI development. Full article

Data has become a strategic production factor, but the institutional logic underlying data’s tradability, priceability, and governability remains insufficiently theorized. In response, this study develops a coevolutionary framework that connects conventional factor market theory with digital political economy, platform theory, and comparative institutional analysis. This study adopts a conceptual–analytical research design, integrating three research methods: theory synthesis, comparative institutional analysis, and policy-process interpretation. Through theoretical synthesis, institutional comparison, and policy-process interpretation, it analyzes the conditions under which data circulation becomes feasible, lawful, and economically sustainable. In addition, by combining transaction data, exchange listings, property rights registrations, network indicators, and regional policy variations, it formulates testable propositions and an empirical agenda. The study finds that data factor markets do not emerge automatically with digitalization; their formation requires three mutually reinforcing conditions: technologically reducing search, verification, privacy protection, and contract enforcement costs; institutionally realizing a modular definition of rights and establishing compliance boundaries; and market demand from firms, public agencies, and research organizations generating use-case-specific value. Meanwhile, this study revises the three-stage model of market evolution as a contingent and testable pathway—from administrative pilot allocation, through hybrid state–market professionalization, to ecosystem-based cross-domain circulation. It also clarifies a closed-loop dynamic mechanism consisting of external shocks, internal strategic feedback, and adaptive governance, which jointly shapes market boundaries, pricing rules, and competition patterns. Full article

(1) Background: ASD diagnostic and screening instruments were historically developed on predominantly male samples, raising concerns about their differential validity across sexes. (2) Objective: This meta-analysis quantified the magnitude of gender bias in ASD diagnostic and screening tools and examined its consistency across instruments, age groups, and clinical contexts. (3) Method: A systematic search was conducted in APA PsycINFO, ERIC, Dialnet, and PsicoDoc (2015–2025) following PRISMA 2020 guidelines. Fourteen empirical studies were included (N = 55 to ~3,000,000). Effect sizes were computed as Fisher r-to-z transformed coefficients and pooled using a random-effects model. Heterogeneity was assessed via Cochran’s Q and I²; methodological quality was assessed via the CRF-QS. (4) Results: The pooled effect size was $\hat{\mathrm{\mu }}$ = 0.29 (95% CI: 0.11–0.47, z = 3.11, p = 0.001), indicating systematic bias favoring detection of externalizing, prototypically male profiles. Substantial heterogeneity was observed (I² = 99.93%, Q(13) = 11,417.61, p < 0.001, τ² = 0.11), with a prediction interval of −0.40 to 0.97. Funnel plot asymmetry suggested possible publication bias (p = 0.01). (5) Conclusions: ASD diagnostic instruments systematically underperform in identifying female presentations of autism. Bias operates across screening and formal evaluation stages, is not corrected by specialist assessment, and is associated with diagnostic delay and increased psychopathological burden. Revision of diagnostic tools and clinical training is urgently warranted. Full article

Recent advances in large language models (LLMs) have improved abstractive text summarization, yet their benefits remain limited for low-resource and morphologically rich languages such as Kazakh. This study investigates the adaptation of the instruction-tuned Gemma-3-4B-it (Google LLC, Mountain View, CA, USA) model for Kazakh news summarization. We propose a two-stage training pipeline combining domain-adaptive pretraining (DAPT) on an unlabeled Kazakh news corpus with parameter-efficient supervised fine-tuning (SFT) using LoRA on summarization datasets. We also examine an inference-time self-correction step in which the model revises its initial summaries to improve consistency and reduce factual errors. Experiments are conducted on Kazakh news data, including a translated version of XSum and corpora collected from BAQ and TengriNews. We compare the baseline, SFT-only, DAPT-only, and DAPT + SFT configurations, with and without self-correction. Evaluation is performed using ROUGE, BERTScore, chrF++, human assessment, and qualitative linguistic analysis. The results show that DAPT combined with SFT achieves the strongest overall performance, while self-correction further improves automatic scores in the DAPT + SFT setting. However, human evaluation indicates that metric gains do not always correspond to higher factual faithfulness or informativeness. These findings highlight the need for domain adaptation and careful evaluation when applying LLMs to Kazakh summarization. Full article

This study develops a digital tactile graphic learning framework based on Korean cultural heritage images to support potential concept learning of students with visual impairments and examines its educational appropriateness through expert validation. The lack of standardized tactile graphic guidelines in visual-centric educational environments imposes considerable burden on teachers, who must restructure content individually. Using a design-based research (DBR) methodology grounded in the Universal Design for Learning (UDL) framework, this study constructed a dataset of 200 cultural heritage images from elementary textbooks across four categories—architecture, artifacts, cultural symbols, and traditional objects—and restructured them through illustration simplification, initial tactile graphic conversion (informed by braille production principles), and two expert revision cycles. Ninety educationally applicable items were finalized for second-stage validation, and five tactile graphic design guidelines were derived. A panel of 15 experts evaluated the materials using a 5-point Likert scale and Content Validity Index (CVI) analysis. The overall mean was M = 4.69 (SD = 0.51), with the final 15-item instrument yielding an overall S-CVI/Ave of 0.99 (initial 0.98 across the original 16 items, refined after removal of one underperforming item per standard CVI practice); the practical usability domain reached S-CVI/Ave = 1.00, indicating full expert agreement. The study contributes a cultural heritage image dataset, a systematic image restructuring procedure, UDL-based design guidelines, iteratively refined and expert-validated CVI evaluation criteria, and a prototype TUI-based tactile learning environment configuration. Full article

Periprosthetic joint infection (PJI) remains a major clinical challenge after total joint arthroplasty because of its association with prolonged antimicrobial therapy, repeated surgery, implant failure, functional disability, and substantial socioeconomic burden. Current strategies, including systemic antibiotics, debridement with implant retention, staged revision, and antibiotic-loaded cement spacers, remain indispensable but are limited by mature biofilm tolerance, protected microbial reservoirs, insufficient local drug penetration, persistent inflammation, and compromised periprosthetic bone repair. Increasing evidence indicates that PJI is not merely bacterial colonization of an implant surface, but a dynamic prosthetic interface disorder involving biofilm persistence, immune dysregulation, inflammatory osteolysis, and failed osseointegration. This review summarizes recent advances in anti-infective prosthetic interface design, emphasizing the transition from passive antibacterial coatings toward multifunctional immuno-antibacterial osseointegrative systems. The pathogenic basis of PJI is first discussed, including conditioning film formation, bacterial adhesion, biofilm maturation, protected reservoirs, immune evasion, and osteolysis. Current clinical management limitations are then evaluated, followed by emerging biomaterial strategies, including anti-adhesive and contact-killing surfaces, active antimicrobial coatings, mature biofilm disruption, biological antibiofilm therapies, smart infection-responsive delivery systems, and osteoimmunomodulatory interfaces. Particular attention is given to balancing early antibacterial activity with cytocompatibility, immune resolution, angiogenesis, mechanical durability, and long-term osseointegration. Finally, key translational barriers are highlighted, including load-bearing and tribological constraints, insufficiently standardized mature biofilm and animal models, limited clinical evidence for advanced smart materials, manufacturing reproducibility, sterilization compatibility, regulatory complexity, and application-specific clinical readiness. Future anti-PJI interfaces should evolve beyond unidirectional bacterial killing toward stage-specific systems integrating biofilm control, immune restoration, vascularized bone regeneration, and durable mechanical performance. Full article

Chronic limb-threatening ischemia (CLTI) in patients with no conventional targets for revascularization presents a formidable challenge in limb salvage. Deep venous arterialization (DVA) is an emerging endovascular approach that redirects arterial blood flow into the venous system to perfuse the ischemic foot. Despite early promising results, appropriate wound management of the ischemic foot following a DVA procedure has been described in the literature, albeit infrequently and with limited standardization. Here, we present a case of an 85-year-old male with multiple comorbidities, including peripheral artery disease and a prior right above-knee amputation (AKA), who underwent a successful left-sided DVA following an open transmetatarsal amputation (TMA) for infection. A staged wound care approach with guillotine amputation, delayed revision and skin grafting ultimately preserved his only remaining limb and allowed for ambulation. This case underscores the potential of DVA as a limb-saving option in complex “no-option” patients when paired with multidisciplinary care and tailored wound management. Full article