Search Results (2,408)

Background/Objectives: The clinical management of uterine fibroids in the context of infertility is characterized by significant heterogeneity. The aim of our study was to record the participants’ views and clinical practices regarding minimally invasive, fertility-sparing management of fibroids, focusing on fertility outcomes. Methods: An online survey was distributed to members of the European Society of Gynecology (ESG), using a questionnaire comprising 27 questions. Questions 1 to 5 related to the participants’ background, while questions 6 to 27 related to the clinical management of fibroids. Results: A total of 98 participants completed the survey, of whom 83% (n = 82) practiced in European countries and 43% (n = 42) had completed specialist training in minimally invasive gynecological surgery. For FIGO 0–II fibroids, hysteroscopic removal was recommended by 94% (n = 92) of participants, although only 27% (n = 26) would do so in all cases, irrespective of the size and submucosal proportion. Anti-adhesion agents were used at least occasionally after the hysteroscopic removal of FIGO 0–II fibroids by 51% (n = 50) of participants. A clinically significant fibroid size was recognized by 57% (n = 56) of participants for FIGO III fibroids and by 51% (n = 50) for FIGO IV fibroids. The opinion was almost evenly divided on whether the distance between an intramural, non-cavity-distorting fibroid and the junctional zone affected the decision for removal: 49% (n = 48) considered that it did not, whereas 51% (n = 50) considered that it did, citing variable cut-off values. Most participants favored minimal-access approaches over laparotomy, whereas the use of robot-assisted laparoscopy was limited. Conclusions: Our results confirm the significant variation in clinical practice associated with fibroid management and underline the need for standardized care, based on high-quality evidence. Full article

Rapid, low-cost ethanol quantification is vital for beverage quality control, biofuel production, and pharmaceutical applications, yet current approaches are costly, reagent- or label-dependent, or rely on spectroscopy with substantial sample preparation. We introduce a purely cell-based, label-free biosensor that exploits temperature-gradient-induced spontaneous detachment of Saccharomyces cerevisiae from a chip surface. The readout is the detachment half-time, t_d50, derived from time-resolved changes in interfacial thermal resistance, R_th, at the solid–liquid interface. Cells were pre-exposed to ethanol (0–70% v/v) and the detachment kinetics monitored using the heat transfer method (HTM). Under these conditions, cells display a pronounced non-monotonic t_d50 response with a peak around 20% v/v ethanol. Overall, the t_d50 rises from ~45 min (0% ethanol) to ≳10 h (20%) and then decreases, with no detachment at 60% and beyond. Critically, cell quality gates the detachment window. Fresh yeast responds up to ~50%, whereas aged yeast ceases to detach above ~8%, demonstrating a dual-function assay. Complementary measurements show that ethanol decreases surface tension monotonically, as expected, while optical/SEM imaging reveals aggregation above the detachment window. Requiring only a heater and a temperature probe, this platform offers a compact and low-cost strategy for ethanol sensing. Its applicability in a complex matrix is further demonstrated using whiskey diluted to selected alcohol concentrations, which produced responses consistent with the ethanol calibration trend. Potentially, it also offers a thermal assay for real-time monitoring of microbial cell quality across biotechnology and bioengineering applications. Considering ethanol as a proxy for drugs, the strategy may also support label-free drug screening on cells. At a fundamental level, the non-monotonic effect of ethanol, and especially the sharp maximum at 20%, remains unresolved and invites further studies. Full article

Background: Inborn errors of metabolism (IEMs) represent a diverse group of genetic disorders affecting biochemical pathways. Despite advances in diagnostic technologies, comprehensive understanding of their historical evolution, classification systems, and diagnostic approaches remains fragmented. Objectives: This systematic review and meta-analysis aimed to synthesize evidence on the historical development, classification frameworks, and diagnostic modalities for IEMs, diagnostic accuracy, and prevalence estimates, providing a comprehensive resource for clinicians and researchers. Methods: Following PRISMA 2020 guidelines, we conducted a systematic search of seven electronic databases (PubMed/MEDLINE, Embase, Scopus, Web of Science, Google Scholar, SciSpace and ArXiv) from January 2000 to March 2026. Studies addressing historical perspectives, classification systems, or diagnostic approaches for IEMs were included. Two independent reviewers performed screening, data extraction, and quality assessment. Meta-analyses were conducted using random-effects models for diagnostic accuracy and prevalence estimates. Results: From 1342 identified records, 54 studies met the inclusion criteria, encompassing 8,234,567 individuals across 35 countries. Historical analysis revealed 16 major milestones from Garrod’s 1902 “chemical individuality” concept to the current AI-powered diagnostics. Four major classification systems were identified: pathophysiological (intoxication, energy deficiency, complex molecule disorders), biochemical pathway (amino acid, organic acid, urea cycle, carbohydrate, fatty acid oxidation, mitochondrial, peroxisomal, lysosomal disorders), organelle-based, and the integrated Society for the Study of Inborn Errors of Metabolism (SSIEM) nosology. Meta-analysis demonstrated high diagnostic performance of tandem mass spectrometry (MS/MS) with a pooled sensitivity of 99.1% (95% CI: 98.6–99.5) and specificity of 99.8% (95% CI: 99.7–99.9%). The pooled global prevalence of IEMs was 50.9 per 100,000 live births (95% CI 45.2–56.8). Next-generation sequencing achieved a diagnostic yield of 42.8% (95% CI: 38.2–47.5%) in suspected cases. Emerging AI-powered diagnostic tools demonstrated high discrimination performance with area under the curve (AUC) values exceeding 0.95 for specific IEM, though external validation remains limited. Newborn screening expanded from single-disease to comprehensive panels detecting over 50 disorders. Conclusions: This comprehensive review demonstrates that IEMs have evolved from rare curiosities to systematically diagnosable conditions through technological advances. Integration of metabolomics, genomics, proteomics and artificial intelligence promises further diagnostic improvements. Standardized classification systems and evidence-based diagnostic algorithms are essential for optimal patient care. Future directions include artificial intelligence-enhanced diagnostics, expanded screening, and personalized medicine approaches. Full article

Small ruminant production in Kosovo is predominantly extensive, and biosecurity practices remain poorly characterized. The emergence of Peste des Petits Ruminants (PPR) in Europe (beginning in 2024) and the first confirmed case in Kosovo (July 2025) highlight the urgent need for baseline biosecurity data to inform disease control. A cross-sectional pilot study was conducted on 63 small ruminant farms (53 meat-producing, 10 dairy-producing) across seven municipalities in Kosovo between September 2025 and February 2026. Biosecurity practices were assessed using the Biocheck.UGent™ questionnaire during direct on-farm visits. External (Ext) biosecurity scores (preventing pathogen introduction) were higher (p < 0.0001) than internal (Int) scores (limiting spread within farms). For external biosecurity, the highest scores were observed for purchase and reproduction (Ext A), intermediate scores existed for feed and water (Ext C) and visitors and farm workers (Ext D), and the lowest scores were found for transport and carcass removal (Ext B) and infrastructure (Ext E). For internal biosecurity, the highest scores were observed for lamb/kid management (Int H) and dairy management (Int I), followed by the management of adult animals (Int J); work organization (Int K) and reproduction management (Int G) formed an intermediate-low cluster, whereas disease management (Int F) scored the lowest. Benchmarking against the Biocheck.UGent™ worldwide database (predominantly intensive systems, thus not directly comparable) indicated that internal biosecurity and overall biosecurity levels were lower than the benchmark, while external biosecurity was comparable for some components. Given the convenience sample (36.4% response rate), findings are exploratory and are not directly generalizable. Larger herd size was positively correlated with external (ρ = 0.54, p < 0.0001), internal (ρ = 0.35, p = 0.005), and overall (ρ = 0.57, p < 0.0001) biosecurity scores. This first empirical biosecurity assessment of small ruminant farms in Kosovo reveals critical gaps in transport hygiene, disease management, and reproductive management pathways that enable PPR spread and perpetuate endemic zoonoses. The positive association between herd size and biosecurity may indicate structural barriers and/or knowledge gaps for small farms. Current biosecurity tools, designed for intensive systems, require adaptation for extensive production systems. These findings provide a baseline for targeted interventions, policy development, and validation of context-appropriate biosecurity instruments in Kosovo and similar extensive systems globally. Full article

Orthographic depth varies across alphabetic writing systems and plays a central role in spelling acquisition. In immersion education, a second language (L2) is used as a language of instruction for part of the curriculum, such that learners are primarily confronted with its writing system during the initial stages of literacy development. This early exposure may shape the spelling strategies subsequently deployed in the first language (L1), which also corresponds to the dominant language of the surrounding community. This article provides a structured review of key mechanisms involved in spelling acquisition, orthographic depth, and cross-linguistic influence in bilingual and immersion contexts. On this basis, it proposes a conceptual and predictive framework specifying how the orthographic depth of the instructional language modulates spelling strategies and spelling error profiles in L1. Focusing on French-speaking pupils enrolled in immersion programmes with L2s characterised by either predominantly phonemic or opaque orthographies, the framework integrates strategy-based models of orthographic development. The model distinguishes phonological, lexical, and morphographic components of orthographic knowledge and predicts that immersion in phonemic-dominant orthographies favours phonographic dominance and regularisation patterns, whereas immersion in opaque orthographies promotes greater reliance on lexical–orthographic strategies, resulting in distinct and systematic spelling error profiles in French. Full article

Iron is essential for life, but its safe use by the body depends on it being kept within tightly controlled compartments. When this compartmentalisation is disrupted—through haemolysis, saturation of scavenger proteins, or dysregulation of the hepcidin–ferroportin axis—damaging iron species accumulate in the circulation and within vascular cells, with potentially serious consequences for endothelial function. This review explores the mechanisms by which iron dysregulation compromises vascular endothelial cell biology across a range of disease states, including haemolytic anaemias, atherosclerosis, cerebrovascular disease, extracorporeal circulatory support, and iatrogenic iron loading. Common pathological themes emerge: depletion of nitric oxide bioavailability, oxidative stress, endothelial activation, and in chronic settings, vascular remodelling. The review subsequently focuses in depth on the pulmonary vasculature, where dysregulated iron compartmentalisation has emerged as a key contributor to the pathogenesis of pulmonary hypertension. Here, iron-driven mitochondrial dysfunction, smooth muscle cell proliferation, and iron-dependent lipid peroxidation via ferroptosis are discussed as mechanistic drivers of pulmonary vascular remodelling. The therapeutic implications of targeting iron handling in pulmonary hypertension are considered, including modulation of the hepcidin–ferroportin axis. Together, the evidence presented highlights disordered iron compartmentalisation as a unifying pathological thread across vascular disease and a compelling target for intervention. Full article

Forests of Lualaba Province (DR Congo) form a compositionally complex mosaic of dry dense forest, gallery forest, and Miombo woodland. Yet, categorical land-cover maps impose discrete boundaries on these inherently continuous vegetation gradients, systematically discarding subpixel compositional information critical for forest monitoring and carbon accounting. The magnitude of this information loss at the landscape scale, however, remains largely unquantified. In this study, we train a Multi-Output Neural Network (MONN) using Sentinel-2 spectral and textural predictors (2025) to estimate the proportional cover of three forest types across the province. Model performance is benchmarked against a normalised Random Forest (RF) using spatial block cross-validation. Categorical information loss is quantified pixel-wise using two complementary metrics, dominant class proportion and Shannon compositional entropy, alongside a derived interpretive quantity, categorical information loss. The MONN slightly outperformed RF (R² = 0.648 vs. 0.630; RMSE = 0.224 vs. 0.229), yet the results reveal a fundamentally heterogeneous landscape structure. The mean dominant-class proportion was only 56.2%, indicating that categorical maps discard, on average, 43.8% of compositional information per pixel. Only 7.9% of forested pixels exceeded the 75% dominance threshold, while Shannon entropy reached 74.1% of its theoretical maximum, indicating that forest types coexist in near-equal proportions across most pixels. This renders categorical attribution structurally inadequate for most of the forested landscape. Across 92.1% of forested pixels, no single forest type achieved clear dominance. These results show that compositional mixing is the dominant structural condition of the landscape, and that compositional mapping is essential for representing tropical forest structure in heterogeneous drylands. By formally quantifying categorical information loss at the landscape scale, this study shows that continuous compositional mapping converts this structural ambiguity into a spatially explicit ecological signal, with direct implications for monitoring vegetation dynamics and biodiversity, suggesting a structural source of error in carbon stock estimation in tropical dry forests that warrants empirical validation. Full article

Digital twin (DT) technology is attracting increasing interest as a potentially valuable tool for the future of agriculture. By offering a dynamic virtual representation of real agricultural systems, it opens up new possibilities for real-time monitoring, simulation, and decision support. In principle, such approaches could improve predictive capacity, optimize resource use, and support more responsive management strategies. However, agriculture cannot be treated as an engineered system, and this is where important challenges emerge. Agroecosystems are living, context-dependent, and inherently variable, shaped by diverse processes that remain only partly observable and often difficult to model. This makes their representation and prediction considerably more complex than in many industrial applications. In this review, we critically examine the conceptual foundations, architectural frameworks, and current applications of agricultural digital twins (ADTs), while also identifying key scientific and practical constraints that continue to limit their development. Particular attention is given to two recurring issues: the assumption that increasing data availability necessarily improves prediction, and the persistent gap between observable variables and the underlying biological and ecological processes that govern system behaviour. Drawing on conceptual figures and comparative analyses, we highlight important research gaps and argue for a shift in perspective. Rather than pursuing increasingly precise predictions, there is a need to develop digital twins that explicitly account for uncertainty and support more resilient forms of decision-making. In this context, the value of ADTs may lie less in predictive accuracy alone, and more in their ability to help decision-makers navigate complexity, variability, and change. Full article

Metamaterials with tailored structural architectures enable negative thermal expansion through geometric mechanisms that counteract constituent-level positive expansion. This study evaluates the thermomechanical performance and structural limits of polymer and hybrid NTE lattices. We systematically classify the dominant kinematic mechanisms, including bimetallic bending, rotational squares, and re-entrant honeycombs, and quantify the inherent trade-offs between effective thermal contraction, structural stiffness, and mass efficiency. The analysis demonstrates that reliance on idealized linear–elastic and rigid-lever models leads to significant predictive discrepancies when evaluating the physical response of polymeric and hybrid prototypes. We establish that these deviations are fundamentally governed by localized stress singularities at multi-material interfaces and the profound thermoviscoelastic softening of polymers as they approach the glass transition temperature ($T_g$). We conclude that accurate prediction of the cyclic lifespan and dimensional stability of these systems requires a transition to coupled multiphysics frameworks. Specifically, integrating temperature-dependent cohesive zone modeling and time–temperature superposition principles is essential for capturing interfacial delamination and thermal ratcheting in high-performance polymeric NTE metamaterials. Full article

Pediatric acute myeloid leukemia (pedAML) is a childhood malignancy with relapse rates of approximately 30%. CD68, a macrophage marker involved in phagocytosis and macrophage recruitment, may contribute to AML biology. We analyzed CD68 expression using the TARGET database and performed survival analyses, mRNA/protein profiling, and functional assays in AML cell lines, pedAML samples, and cord blood samples. High CD68 transcript levels correlated with KMT2A-rearrangements and inversion 16. Survival analysis showed that high CD68 predicted worse event-free survival, though not independently in a multivariate analysis. Flow cytometry confirmed higher CD68 expression in 7/8 pedAML samples compared to cord blood samples. Functionally, CD68 knockdown reduced proliferation and increased drug sensitivity, while overexpression promoted growth and resistance. Gene set enrichment analysis (GSEA) indicated enrichment of MAPK signaling, AP-1–mediated stress response, and epithelial–mesenchymal transition (EMT)/migration-associated pathways in CD68-high models. Together, these findings suggest that CD68 contributes to a pro-tumorigenic and stress-adaptive phenotype in pedAML and may represent a biologically relevant therapeutic target. Full article

Background: Creatine deficiency syndromes (CDS) are rare neurometabolic disorders caused by defects in creatine biosynthesis (AGAT and GAMT deficiencies) or creatine transport (SLC6A8 deficiency). Early biochemical recognition is crucial for timely treatment of AGAT and GAMT deficiencies and for improving neurodevelopmental outcomes. In Morocco, expanding the liquid chromatography-tandem mass spectrometry (LC-MS/MS) biomarker panel for inherited metabolic disorders is a priority to strengthen diagnostic capacity and reduce diagnostic delay. Methods: We developed and validated a rapid LC-MS/MS method for the simultaneous quantification of creatine (Cr), guanidinoacetate (GAA), and creatinine (Crn) in plasma and urine using isotopically labelled internal standards and a standardized sample preparation procedure. Analytical performance, including linearity, precision, accuracy, sensitivity, matrix effects, carryover, inter-sample contamination, stability, and measurement uncertainty, was assessed in accordance with ISO 15189:2022 requirements. Results: The assay showed excellent linearity across the analytical range (r² > 0.99), with robust intra- and inter-day precision (CV < 10%). Limits of detection (LOD) were 0.05 µmol/L for Cr and 0.03 µmol/L for GAA in urine, and 0.05 µmol/L for Cr and GAA in plasma. The total run time was 1.1 min per sample, supporting high-throughput implementation. Method performance was further supported by satisfactory results in ERNDIM external quality assessment schemes. Preliminary internal reference ranges and expanded measurement uncertainty were calculated from the available anonymized dataset. Conclusions: This rapid LC-MS/MS method enables the measurement of key CDS biomarkers and contributes to expanding the LC-MS/MS biomarker panel for inherited metabolic disorders in Morocco. Full article

Accurately quantifying aboveground biomass (AGB) in tropical forest enrichment plantations remains challenging, particularly in managed regenerating stands where tree crown architecture, size structure, and species composition differ from the datasets used to calibrate classical allometric equations. Here, we assess whether AGB in tropical forest enrichment plantations can be estimated more accurately by combining tree-specific woody volume reconstructed from mobile laser scanning (MLS) with an explicit foliar-biomass component. We combined destructive measurements from 83 trees with high-resolution MLS point clouds to quantify biomass components, calibrate leaf-mass models, and assess the contribution of foliage to total AGB. Stems accounted for most of the biomass (65%), whereas leaves contributed only 3% on average. Among the models tested, Model 3, which included DBH, projected crown area, and wood density, showed the best performance (R² = 54.4%; RMSE = 2.43 kg). The main gain relative to regional (−20.4%) and pantropical (−25.6%) allometric equations came from the use of MLS-derived woody volume combined with species wood density, whereas the inclusion of predicted leaf biomass provided a moderate additional correction to the remaining bias. These results highlight the importance of canopy structure for biomass estimation in enrichment plantations and managed regenerating stands and support the use of LiDAR data as a robust alternative for AGB assessment in this context. Full article

The conversion of agro-industrial co-products and unsold organic plant-based residues into black soldier fly (BSF; Hermetia illucens (L. 1758)) proteins was assessed for use in organic post-weaning piglet diets in Belgium. A total of 72 crossbred female piglets (Landrace × Pietrain) were enrolled in a 5-week feeding trial. Experimental diets consisted of a common energy core (81.2% of the feed) and a protein core (18.8%) composed of organic soybean meal, pea meal, and potato protein, partially replaced by defatted BSF meal at inclusion levels of 15%, 25%, and 35%. All diets were formulated to be isoenergetic and isonitrogenous, with standardized ileal digestibility values for lysine, methionine, threonine, and tryptophan held constant. Incorporating 15% defatted BSF meal can substitute conventional organic protein sources without compromising growth performance in post-weaning piglets. However, economic modelling based on a cumulative feed conversion ratio expressed on a dry matter (DM) basis showed that break-even prices for organic BSF meal remained well below the price of the control protein nucleus (€1039·t⁻¹, excluding VAT), indicating that economic parity could not be achieved at typical market prices under the observed feed efficiency. Full article

Heat stress (HS) alters rumen function and may compromise fermentation efficiency in dairy cows. This in vitro study evaluated the effects of six additives—betaine, sodium bicarbonate, bentonite clay, protected fat, Saccharomyces cerevisiae yeast, and Melissa officinalis (lemon balm)—on ruminal fermentation under increasing incubation temperatures (39.0 °C, 40.5 °C, 41.5 °C). This study was designed as an initial in vitro screening approach aimed at evaluating additive resilience under a conservative, worst-case thermal challenge. The highest incubation temperature (41.5 °C) was not used to reproduce the exact physiological rumen environment but rather served to identify additives capable of maintaining fermentation when exposed to extreme conditions that may occur during severe heat load. These results therefore constitute a preliminary step before in vivo validation under realistic HS scenarios. Fermentation was assessed after 24 h by measuring gas production, pH, redox potential, volatile fatty acids (VFAs), and ammonia (NH₃) and performing protozoa counts. Temperature alone produced limited effects in the control, with numerical increases in gas, acetate, total VFAs, and NH₃ at 41.5 °C. Betaine and yeast maintained overall stable fermentation across all temperatures, preserving gas production, pH, redox potential, and VFA profiles. Sodium bicarbonate increased the pH but reduced gas production. Lemon balm enhanced VFAs and propionate at 39.0 °C but showed reduced activity at high temperature. Protected fat and bentonite clay resulted in lower gas production with minimal influence on other parameters. The protozoa counts were not affected by temperature and showed statistically detectable differences among additives. Overall, betaine and yeast exhibited the highest thermal stability and appear to be suitable candidates for inclusion in feeding strategies aimed at supporting rumen fermentation during periods of HS. Full article

Remote sensing of crop diseases has traditionally focused on detecting visible symptoms, often limiting intervention to advanced stages of epidemic development. This study investigates whether high-resolution unmanned aerial vehicles (UAV)-based red–green–blue (RGB) imagery can reveal earlier physiological destabilization preceding visible symptoms of wheat stripe rust and wheat leaf rust. UAV imagery was acquired at four winter wheat-growing sites in Luxembourg during the 2018/2019 season. Temporal dynamics of green–red spectral slopes were analyzed and compared with ground-based disease severity observations to identify potential pre-symptomatic spectral signals. A consistent flattening of the green–red spectral slope was detected prior to a rapid increase in visually assessed severity for both diseases. However, the length of this pre-symptomatic window varied between the two diseases: it lasted 7 to 14 days for wheat stripe rust and 5 to 10 days for wheat leaf rust. Likewise, the reduction in spectral slope magnitude was slightly greater for wheat stripe rust (65–80%) than for wheat leaf rust (60–75%), indicating that the temporal lead time and intensity of the spectral response were disease-dependent. During the pre-symptomatic phase, the spectral dynamics reflected latent physiological changes rather than visible disease severity. Strong correlations emerged only after the epidemic transition. These findings demonstrate that UAV-based RGB imagery could capture a distinct pre-symptomatic phase of stripe rust and leaf rust epidemics in winter wheat. Interpreting RGB spectral dynamics as early-warning indicators rather than merely as static severity proxies can guide proactive disease monitoring and precision agriculture. Full article