Search Results (16,290)

Automated AI-assisted colony counting may improve standardization in digital microbiology, but performance can be affected by colony density, culture medium, colony morphology, adhesion, and plate artifacts. We evaluated the Starry-300 AI colony counting system using 382 standardized pure culture bacterial and yeast plates across four agar media. AI-assisted counts were compared with a three-reader median ImageJ-assisted manual comparator derived from independent counts by experienced technologists. The AI workflow showed close agreement with the manual consensus comparator across a broad colony density range. Overall, 360/382 plates (94.24%) were within ±10 CFU and 377/382 plates (98.69%) were within ±30 CFU of the manual median count. Error-based and agreement analyses showed a mean absolute error of 3.19 CFU/plate; both the intraclass correlation coefficient and Lin’s concordance correlation coefficient were0.99. AI software analysis required approximately 5–15 s/plate, although this did not include plate handling, correction, or reporting. These findings support the analytical feasibility of reviewable AI-assisted colony enumeration under controlled pure culture conditions. Further validation using primary clinical specimens, mixed cultures, near-threshold samples, and external sites is required before broad clinical implementation. Full article

Colloidal gold dietary supplements intended for oral consumption are increasingly marketed as nano-enabled products, yet their physicochemical characteristics and biological effects remain insufficiently documented. In this study, commercially available colloidal gold supplements produced and marketed in Romania (30, 55, and 110 mg/L) were investigated to determine their classification as nanomaterials and to assess their preliminary biological effects in the context of oral exposure. Transmission electron microscopy revealed a narrow particle size distribution (4–11 nm), while SAED and EDX confirmed the presence of metallic gold nanoparticles. UV-VIS spectroscopy showed the characteristic surface plasmon resonance, supported by comparison with citrate-stabilized reference AuNPs (5–20 nm). DLS and zeta potential measurements indicated stable electrostatically stabilized colloids. According to the current EU definition, the number-based size distribution supports classification as nanomaterials. Manufacturer-recommended daily intakes were compared with doses reported in the literature using HED conversion to contextualize oral exposure. In vitro assays showed no pronounced acute cytotoxic or antitumoral effects on HCT-8 cells and no inhibitory effects on selected LAB. However, increased cytotoxicity was observed in HEK293 cells exposed to the dietary supplement formulation compared with the corresponding standard AuNP formulation. These results underscore the importance of considering cell-specific responses when evaluating the safety of nano-enabled dietary supplements and support the need for long-term toxicological studies. Full article

Pancreatic cancer is among the most aggressive malignancies, and late diagnosis remains a key challenge. For a systematic review of pancreatic cancer diagnosis and prognosis, Scopus and Web of Science databases were used for the period from 2016 to 2026. The search query included the following keywords and their combinations: pancreatic cancer, diagnosis, early detection, prognosis, biomarkers, metabolomic profiling, CA19-9, microbiome, metagenomic changes, circulating tumor DNA, genomic analysis. Inclusion criteria included only articles published in English. Exclusion criteria included case reports and studies that did not examine pancreatic cancer. Our analysis demonstrates that integrating multi-omics data, particularly combining traditional CA19-9 with circulating tumor DNA (ctDNA) and metabolomic profiles (lipids, amino acids, carbohydrates), significantly improves diagnostic accuracy. Microbiome composition and genomic alterations further refine risk stratification and prognostic assessment. The synergistic use of these biomarkers may facilitate the development of screening, early diagnosis, risk stratification, and treatment optimization. However, the introduction of new diagnostic approaches into clinical practice requires additional verification, standardization and prospective clinical studies. Full article

Background/Objectives: Poly(lactic-co-glycolic acid) (PLGA) microparticles are widely used for sustained drug delivery, yet the release behavior reported in the literature remains difficult to predict across studies. It was hypothesized that this limitation reflects insufficient information content in commonly reported formulation variables rather than model inadequacy. Methods: A curated dataset of 321 PLGA microparticle formulations from 113 publications comprising 89 drugs and 4913 release observations was analyzed. Early time release was parameterized using Korsmeyer–Peppas descriptors (n, K), and burst release was quantified as the 24 h cumulative release. Machine learning models were evaluated using formulation-grouped cross-validation, applicability-domain analysis, and leave-one-study-out validation to assess cross-laboratory transportability. Results: Under formulation-grouped validation, predictability was limited (stacked ensemble: $R^2=0.156$ for n, $R^2=0.169$ for K, burst $R^2=0.100$). Leave-one-study-out validation yielded negative pooled $R^2$ values for all targets ($-0.061$, $-0.040$, and $-0.180$, respectively), indicating failure to generalize across laboratories. Applicability-domain filtering did not materially improve performance, supporting the interpretation that prediction is limited by missing or inconsistently reported variables rather than covariate extrapolation alone. Conclusions: These results reveal an information-limited regime in PLGA release prediction in which the literature covariates enable only weak formulation-level prediction under grouped validation and cannot support transferable models. Minimum reporting priorities are therefore proposed, including standardized characterization of polymer molecular weight, end-group chemistry, quantitative emulsification and solvent-removal parameters, and microstructural or porosity measurements, to enable reproducible formulation screening. Full article

Background: Myelomeningocele (MMC) is a severe neural tube defect resulting from primary neurulation failure. Despite advanced multidisciplinary paradigms, long-term morbidity remains substantial. Population-based longitudinal data from small European cohorts are scarce. This study evaluates long-term clinical and functional outcomes within a complete national cohort in Slovenia. Methods: A retrospective cohort study was conducted on all children born with MMC in Slovenia between 2007 and 2023. Patients were managed via a centralized, standardized multidisciplinary program. Phenotypic severity was stratified by anatomical lesion levels, and outcomes were assessed using standardized functional measures. Results: Over an 18-year period, 32 children were treated (prevalence: ~1 per 10,000 live births; mean follow-up: 13.2 years). All underwent anatomical closure within 24 h of birth. Hydrocephalus developed in 71.8% (n = 23), with 65.6% requiring ventriculoperitoneal shunting. Independent ambulation was achieved by 28.1%, while 46.8% were wheelchair-dependent and paraplegic. Neurogenic bladder dysfunction occurred in 87.5%. Subgroup analysis demonstrated that thoracolumbar lesions were significantly associated with lower ambulation rates and higher shunt dependency compared to lumbosacral lesions (p < 0.05). Long-term survival was 96.9%. Conclusions: This study represents the first comprehensive national analysis of myelomeningocele outcomes in Slovenia. Despite the relatively small number of patients, complete national coverage and centralized multidisciplinary management provide a unique overview of long-term outcomes. The findings demonstrate that outcomes achieved within the Slovenian healthcare system are comparable to those reported internationally, thereby establishing an important national benchmark for future evaluation of preventive measures and evolving treatment strategies. Full article

Advanced oxidation processes (AOPs) are widely applied to degrade recalcitrant organic contaminants in municipal effluents, industrial wastewaters, and water-reuse streams. Their deployment, however, remains constrained by matrix scavenging, high energy or reagent demand, catalyst/electrode ageing, and the possible formation of toxic transformation products. Artificial intelligence and machine learning (AI/ML) have been proposed as tools for prediction, optimization, catalyst discovery, mechanism inference, and process control, but high accuracy on curated laboratory datasets is often confused with actionable knowledge for real treatment systems. This narrative review evaluates AI/ML-enabled AOPs through an evidence-to-deployment framework built on three principles: real wastewater is treated as the primary inference domain; mechanistic claims are graded according to convergent evidence; and AI/ML contributions are linked to explicit decisions rather than to model accuracy alone. We argue that progress depends less on black-box complexity than on standardized reporting, benchmark matrices, curated datasets, uncertainty-aware validation, and pilot-scale demonstrations that satisfy contaminant removal, energy efficiency, byproduct safety, and operational constraints simultaneously. A six-gate decision framework and a targeted research agenda are proposed to guide future studies toward deployment-grade evidence. Full article

Lichen planus (LP) is a chronic T-cell-mediated interface dermatitis. Genital involvement is frequently refractory to topical corticosteroids and calcineurin inhibitors and may lead to fibrosis, architectural distortion, and substantial impairment in quality of life. We report the case of a 39-year-old male with a 15-year history of biopsy-confirmed genital LP unresponsive to high-potency topical corticosteroids and tacrolimus 0.1%, who received topical Rosa damascena stem cell-derived exosomes (RSCEs) at biweekly sessions for four months. Each session combined 2 mL of in-office application with superficial microneedling in hyperkeratotic areas, followed by 3 mL of the same-day home application. No concomitant topical corticosteroid or calcineurin inhibitor was used during the treatment period. Paired pre- and post-treatment 4 mm punch biopsies were obtained from the same anatomical region, processed using identical protocols, stained with hematoxylin and eosin, and reviewed by a board-certified dermatopathologist. After four months, we observed clinical resolution of pruritus and fissuring, progressive desquamation of hyperkeratotic plaques, and improved tissue elasticity. The post-treatment biopsy showed reduced hyperkeratosis and hypergranulosis, attenuation of the band-like lymphohistiocytic infiltrate, partial restoration of the dermoepidermal interface, and reduced basal vacuolar degeneration relative to baseline. No dysplastic changes or treatment-related adverse events were observed. These observations are based on a single uncontrolled case and cannot establish causality, isolate the contribution of microneedling, or demonstrate disease modification beyond the descriptive level. Histological assessment was qualitative; no semi-quantitative or immunohistochemical analysis was performed. The exosome preparation was used as a standardized commercial product and was not independently characterized in our laboratory. The findings are intended solely as hypothesis-generating. Independent characterization of the exosome preparation, immunohistochemical and ideally transcriptomic profiling of paired tissue, and prospective controlled studies are required before any therapeutic claim can be supported. Full article

Accurate, automated delineation of adult diffuse gliomas from multi-parametric magnetic resonance imaging (mpMRI) is central to quantitative neuro-oncology. Volumetric 3D networks dominate the BraTS leaderboard but require expensive GPUs, long training cycles, and provide diminishing returns relative to their compute budget. Slice-wise 2D models, by contrast, discard inter-slice context that is informative for thin tumor rims and small enhancing foci. We introduce GDNet, a 2.5D multimodal MRI segmentation framework for adult glioma evaluated on the BraTS 2024 cohort. GDNet consumes a stack of three adjacent axial slices from the four standard BraTS modalities (T1, T1ce, T2, FLAIR) as a 12-channel input to a compact U-shaped encoder–decoder with Group Normalization and predicts whole tumor (WT), tumor core (TC), and enhancing tumor (ET) masks for the central slice. The training pipeline pairs the 2.5D backbone with: (i) Exponential Moving Average (EMA) of model weights with decay 0.999, (ii) mixed tumor-aware slice sampling (p_tumor = 0.50), (iii) a compound Cross-Entropy + Soft-Dice loss, and (iv) AdamW with warm-up plus cosine annealing under Automatic Mixed Precision. We performed a systematic, step-by-step ablation covering a 2D baseline, EMA + mixed sampling, tumor-centered crop fine-tuning, a GDNet-inspired architectural integration, a region-aware loss, 3-slice and 5-slice 2.5D inputs, and connected-component post-processing, and we report multi-seed results to quantify reproducibility. On the held-out BraTS 2024 test partition, the final 3-slice 2.5D GDNet achieved positive-only Dice scores of 0.791 ± 0.000 (WT), 0.736 ± 0.003 (TC), 0.654 ± 0.004 (ET), and a mean foreground positive-only Dice of 0.820 ± 0.000 across seeds; the all-slice mean foreground Dice exceeded 0.927 ± 0.000. Validation positive-only scores were 0.805 ± 0.002 (WT), 0.757 ± 0.004 (TC), 0.683 ± 0.009 (ET). The inter-seed standard deviation was small for every region (≤0.01 Dice points), indicating low inter-seed variance across the two seeds evaluated; with only two seeds, we regard this as preliminary evidence of training stability rather than a strong reproducibility claim. The ablation isolated EMA + mixed tumor sampling and the 2.5D context window as the dominant sources of improvement; notably, a GDNet-style architectural integration with a region-aware loss did not outperform the simpler 2.5D U-Net on positive-only WT/TC/ET, and light post-processing improved only all-slice Dice. A failure-mode audit found that the residual catastrophic predictions are concentrated on a small minority of diffuse, infiltrative tumors with mass effect. Conclusions: Carefully engineered training strategies, tumor-aware sampling, EMA stabilization, and a modest 2.5D context window recover a substantial fraction of the accuracy of much heavier 3D networks at a fraction of the compute, are reproducible across seeds, and outperform a heavier GDNet-inspired architectural variant on the same data. GDNet is therefore a practical and, pending external validation, potentially clinically deployable framework for multimodal glioma segmentation on workstation-class GPU hardware. Full article

Background: Vesicoureteral reflux (VUR) is a common pediatric urologic disorder associated with recurrent febrile urinary tract infections, renal scarring, hypertension, and potential long-term renal morbidity. Postoperative outcomes after ureteral reimplantation may be influenced by reflux grade, reflux etiology, bladder function, renal status, operative technique, surgeon experience, and follow-up intensity. However, real-world evidence from low- and middle-income healthcare settings remains limited, particularly for surgically treated children with high-grade VUR. Objective: To describe postoperative outcomes after ureteral reimplantation in children with Grade III–V VUR and to explore the association of VUR grade and surgical approach with reflux resolution, recurrence, and reintervention in a surgically selected pediatric cohort. Methods: We conducted a retrospective cohort study at a tertiary pediatric referral center in Ecuador. The study included 90 children aged 0 to 15 years with Grade III–V VUR confirmed by voiding cystourethrography who underwent open or laparoscopic ureteral reimplantation between January 2019 and January 2024. Demographic, clinical, imaging, and surgical variables were extracted from medical records. Postoperative outcomes included reflux resolution, recurrence, and reintervention. Logistic regression models were used as exploratory analyses only. Because the cohort included only operated patients, treatment allocation was nonrandomized, event numbers were limited, and several relevant prognostic variables were incompletely documented, adjusted estimates were interpreted cautiously and were not used to infer causality. Results: Overall reflux resolution was achieved in 68 of 90 patients (75.6%), recurrence occurred in 12 patients (13.3%), and reintervention was required in 8 patients (8.9%). Resolution rates were similar after open and laparoscopic surgery (44/59, 74.6% vs. 24/31, 77.4%; p = 0.766). Recurrence was numerically lower after laparoscopic than open reimplantation, but the difference was not statistically significant (2/31, 6.5% vs. 10/59, 16.9%; p = 0.164). Reintervention rates were also similar between groups (3/31, 9.7% vs. 5/59, 8.5%; p = 0.849). In exploratory multivariable analysis, Grade V VUR was associated with lower odds of reflux resolution (OR, 0.06; 95% CI, 0.01–0.40; p = 0.003) and higher odds of recurrence (OR, 16.69; 95% CI, 1.88–148.32; p = 0.012) compared with Grade III VUR. Surgical approach was not independently associated with resolution, recurrence, or reintervention. The small Grade V subgroup, the limited number of recurrence and reintervention events, and the wide confidence intervals indicate substantial statistical imprecision. Conclusions: In this surgically treated pediatric cohort from a tertiary referral center in Ecuador, ureteral reimplantation was associated with reflux resolution in approximately three-quarters of patients. Higher reflux grade, particularly Grade V disease, was associated with less favorable postoperative outcomes in exploratory analyses, but these findings should not be interpreted as causal or definitive because of the small subgroup size, limited event numbers, selection bias, and incomplete documentation of reflux etiology, bladder dysfunction, renal scarring, renal function, surgeon experience, and follow-up duration. Open and laparoscopic approaches showed comparable resolution and reintervention rates, while the lower recurrence observed after laparoscopy did not reach statistical significance. Future prospective studies should standardize outcome definitions, distinguish imaging-confirmed from clinically documented resolution, report follow-up duration, and account for reflux etiology, bladder function, renal status, surgical experience, and healthcare access. Full article

Background: Chronic stress contributes to mental and physical disorders, including burnout, anxiety, and depression. While self-report assessments remain valuable, they are inherently subjective and may be insensitive to short-term psychophysiological fluctuations. Remote photoplethysmography (rPPG) enables non-contact extraction of cardiovascular signals from facial videos and has increasingly been explored for stress-related monitoring through heart rate and heart rate variability features. Objective: This preliminary study aimed to assess the feasibility, usability, and preliminary construct validity of a mobile rPPG-based application for psychophysiological stress monitoring in daily life by examining usability, stress index distributions, and associations with self-reported psychological distress. Methods: A total of 252 participants from the general population and university students completed standardized facial video acquisition using a smartphone-based rPPG application and self-report questionnaires. The app extracted pulse wave signals, computed cardiovascular features related to heart rate and pulse rate variability, and integrated them into three indices: Stress Level, Stress Recovery, and Stress Response. Correlation and regression analyses examined associations with psychological distress. Results: The three indices showed substantial inter-individual variability. Stress Level was significantly associated with anxiety (r = 0.13, p = 0.036), depressive symptoms (r = 0.13, p = 0.047), and General Emotional Distress (r = 0.17, p = 0.006). In regression analysis, Stress Level emerged as the only significant independent correlate of General Emotional Distress (β = 0.21, p = 0.017). Younger participants and women showed higher Stress Level scores. Conclusions: The present findings should therefore be interpreted as preliminary and exploratory evidence of construct validity, suggesting that the app-derived indices may capture individual differences in stress-related physiological activation in everyday contexts. Currently, the observed associations were weak, the model explained limited variance, and the results do not demonstrate clinical validity, diagnostic utility, or predictive accuracy. Looking ahead, further longitudinal studies, repeated rPPG assessments, correction-aware analyses, and validation against reference physiological measures are needed before these indices can be considered suitable for clinical or preventive use. Full article

A new family of fourth-order accurate time integration schemes is developed by introducing two complex time sub-steps into the classical Newmark family of second-order algorithms. These sub-steps consist of a pair of complex conjugate numbers, enabling the triangularization of a complex-valued effective stiffness matrix. The proposed formulation can be easily implemented in existing codes with only minor modifications to the standard Newmark algorithm. The solution is composed of both real (physical) and imaginary components. The real component provides fourth-order accuracy even in the presence of external loads and physical damping, while the imaginary component offers additional insight into the distribution of numerical errors, an original feature not previously reported for implicit formulations. Compared to the classical Newmark method with a time-step size four times smaller, the proposed scheme exhibits significantly lower numerical dissipation and dispersion errors. Furthermore, the sub-step procedure extends the critical time step of conditionally stable members of the Newmark family by a factor of $\sqrt{3}$. The numerical analysis performed in the proposed time integration method, along with the results obtained for dynamic structural problems, including a complex three-dimensional (3D) application, clearly demonstrate that the method outperforms both Fung’s fourth-order complex scheme and the classical Newmark approach in terms of accuracy. Full article

Breast cancer is the most commonly diagnosed cancer in women, with early detection playing a critical role in clinical outcomes. Mammography remains the standard screening modality, producing X-ray images used to assess mammographic density, a key indicator of the proportion of fibroglandular tissue within the breast. The Breast Imaging-Reporting and Data System (BI-RADS) classification system is widely used to report density across four qualitative categories. High density can obscure malignancies and is independently associated with elevated breast cancer risk. Manual interpretation of mammographic density is prone to subjectivity and inter-observer variability, and supervised learning-based estimation methods trained on subjective labels may reflect this inherent subjectivity. This work proposes an unsupervised framework for quantitative breast density estimation that requires no labeled data in its core pipeline. Expert labels are used exclusively to calibrate post hoc discretization thresholds for binary classification, enabling comparison with supervised methods in the literature. The main contributions include: (i) an adaptive Region of Interest (ROI) extraction algorithm, (ii) a Convolutional Neural Network (CNN) based unsupervised segmentation pipeline tuned for mammographic density separation, (iii) a novel confidence metric for identifying unreliable segmentation outputs, (iv) a label correction mechanism for low-confidence cases, and (v) a confidence-filtered majority voting scheme for per-patient classification. The framework is evaluated on two public datasets, namely DDSM and INbreast, with segmentation performance yielding Silhouette scores exceeding 0.92. Agreement with expert labels reaches 71.43% and 79.28% for DDSM and INbreast, respectively. Image-level clustering quality assessment confirms effective unsupervised labeling, with Silhouette scores averaging 0.57 for DDSM and 0.50 for INbreast. The proposed framework provides a practical and non-subjective model for quantitative breast density estimation, with potential utility as a decision-support tool for radiologists that can be considered in clinical practice after further investigation. Full article

The use of European Sustainability Reporting Standards (ESRS) under the Corporate Sustainability Reporting Directive (CSRD) represents a major change in corporate sustainability reporting, particularly through the formalisation of the double materiality principle. Despite its regulatory relevance, empirical evidence on how organisations disclose double materiality remains limited, especially during the first reporting cycle. This study provides early empirical indicative evidence on the application of double materiality in disclosure following the initial ESRS reporting. It examines how leading European water-sector companies and environmental service providers with urban water activities integrated this approach into their 2024 sustainability disclosures. A mixed-methods design is applied, combining qualitative content analysis with descriptive quantitative checks of sustainability, ESG, and integrated reports. The disclosed material topics are assessed against the ESRS thematic framework. The findings indicate a strong convergence on the key environmental issues reported, notably climate change, water management, and circular economy-disclosed practices, including companies not yet fully subject to ESRS requirements. In contrast, social and governance disclosures suggest greater heterogeneity. Overall, the results suggest that broader material coverage does not necessarily imply higher information quality, as this reflects the breadth of disclosure rather than its quality, reinforcing double materiality as a sector-driven prioritisation mechanism. Full article

Fragrance allergens are widely used in cosmetics and personal care products to make them more attractive to consumers. However, their presence has raised increasing concerns due to their potential to induce allergic contact dermatitis and other adverse health effects. As a result, regulatory authorities have progressively strengthened labelling requirements and restrictions for fragrance allergens in cosmetics, creating new analytical and compliance challenges for both industry and regulatory laboratories. In this context, the development of sensitive, selective, and reliable analytical methodologies has become essential for the identification and quantification of these compounds in complex cosmetic matrices. This review provides a comprehensive overview of analytical methodologies reported between 2015 and 2025 for the determination of fragrance allergens in cosmetic matrices, with a focus on sample preparation. Conventional extraction methodologies are critically discussed together with advanced, miniaturized and microextraction approaches. The advantages, limitations, and applicability for routine quality control and regulatory compliance are critically discussed. Chromatographic developments, including the use of multidimensional approaches, are assessed. Recent regulatory updates are examined, and the challenges related to allergen labelling, low-level detection, matrix complexity, standardization, and harmonization of analytical protocols are also addressed. Finally, future perspectives on innovative analytical tools, and green analytical chemistry approaches are highlighted. Full article

Background: Glioblastoma (used to be called glioblastoma multiforme—GBM) is the most common and aggressive brain tumor, having the lowest overall survival rate. Initial focal neurological deficits are primarily attributable to surrounding edema; however, as tumor invasion progresses, these deficits become more pronounced and permanent. The standard treatment for newly diagnosed glioblastoma is represented by cytoreductive neurosurgery followed by the Stupp Protocol. Postoperative recovery of the patient with glioblastoma is a long-term process that should include, for overall more acceptable outcomes, neurorehabilitation. This review aims to bring together evidence from neuro-oncology, neurosurgery, and neurorehabilitation in order to better understand the factors associated with recovery, functional status, and quality of life (QoL) after glioblastoma surgery. Our work also aimed to update the related knowledge base and to attempt to optimize the related protocols in patients with operated cerebral glioblastoma. Methods: For these purposes, we conducted a systematic literature review to assess the current state of research referring to the above-mentioned topic. We have used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA—widely recognized internationally) methodology. We used, in this respect, specific keyword combinations/“syntaxes” for searching literature in the domain, in four international databases. Results: Following PRISMA screening, 14 studies met the predefined eligibility criteria. Additional manual reference screening and complementary searches identified further relevant publications, resulting in a total of 22 included articles. Together, the reviewed work addressed a diverse range of topics relevant to postoperative glioblastoma management, including the potential role of multidisciplinary rehabilitation, cognitive interventions, neuromodulation approaches, and functional assessment strategies in improving postoperative outcomes and QoL in glioblastoma patients, while emphasizing that this interdisciplinary domain warrants more extended approaches. Discussion and Conclusions: Despite the relatively limited and largely exploratory available information, neurorehabilitation may contribute to improved functional outcomes and QoL in patients with glioblastoma. Full article