Beyond SMN1 mutation: environmental predispositions and epigenetic contributors to phenotypic variability and disease severity in spinal muscular atrophy.

Comparing the Readability and Usability of Patient Education Materials Generated by Different Large Language Models: ChatGPT, Copilot, and Gemini.

Geochemical assessment of potentially toxic elements in river sediments from a highly contaminated mining area - Cavnic, Romania.

A synergistic dual-endopeptidase platform for high-yield, homogeneous F(ab')2 production from polyclonal equine immunoglobulins for therapeutic applications.

Cystoscopy is a crucial diagnostic tool in urology for the detection and evaluation of bladder lesions. However, its diagnostic accuracy (ACC) is highly dependent on the operator's experience, which can lead to significant interobserver variability. To address these challenges, this study develops and evaluates two deep learning-based systems for automated cystoscopic image analysis. These systems aim to enhance diagnostic efficiency in clinical settings. We collected 9362 bladder tumor, cystitis, and postoperative scar images from 2056 examinations for the dataset. We used this dataset to build two deep learning models, one for classifying bladder diseases and the other for locating bladder tumor lesions. We used multiple deep learning model architectures, including convolutional neural networks, Vision Transformer models, and Vision Mamba, to build the models and selected the one with the highest performance. The two deep learning models constructed in this study both demonstrate relatively good capabilities. The common bladder lesion classification model demonstrated high performance, with an area under the curve of 0.872, whereas the bladder tumor segmentation model achieved a Dice similarity coefficient of 0.821 with accurate tumor margin delineation. Both models showed strong generalizability, with the classification model covering most initial diagnostic scenarios. Our findings indicate that artificial intelligence (AI)-powered cystoscopic analysis significantly enhances both diagnostic ACC and efficiency, aiding clinicians in identifying subtle or complex lesions. This study demonstrates the practicality of deep learning models in real-world clinical applications, laying the groundwork for future AI-driven innovations in urologic diagnostics.

To summarize current approaches to isolation precautions and infection prevention and control (IPC) practices in immunocompromised hosts, including patients with hematologic malignancies, those receiving cellular therapies, and transplant recipients, with attention to variability in evidence and practice. Standard and transmission-based precautions remain foundational but often require adaptation for immunocompromised populations due to increased infection severity, prolonged pathogen shedding, and heightened transmissibility. Protective environments, including HEPA (high-efficiency particulate air) filtration and positive pressure rooms, may be of benefit for the highest risk populations but are resource-intensive and inconsistently applied. Emerging data support strategies such as universal masking to reduce respiratory viral infections (RVIs) and tailored transmission-based precautions. The role of multidrug-resistant organism (MDRO) screening and isolation continues to evolve, with mixed evidence and reconsideration of prior practices. Enhanced environmental cleaning and no-touch disinfection technologies hold potential but lack consistent outcome data. Several long-standing practices, including the neutropenic diet, are increasingly being re-evaluated. IPC in immunocompromised patients is complex and multifaceted, with limited high-quality evidence guiding practice resulting in significant practice variability. A shift toward individualized, risk-adapted strategies - balancing risk mitigation, resource utilization, and patient-centered care - will ultimately optimize outcomes.

Application of the prompt γ-ray spectroscopy in the boron neutron capture therapy of pets.

Flexible cystoscopy is one of the most frequently performed diagnostic procedures in urology. Despite its routine nature, significant variability exists in how it is performed across institutions and countries, reflecting a lack of procedural standardization. Metric-based approaches have been effectively used in other surgical domains to characterize and objectively assess performance, but no such framework has previously been established for cystoscopy. The aim of the current study is to develop and achieve expert consensus on performance metrics for flexible cystoscopy through a modified Delphi consensus. The study followed a validated methodological framework of metric-based performance analysis previously applied to an image-guided procedure. The study consisted of two phases: (1) procedure characterization and metrics development and (2) face and content validation through an in-person modified Delphi panel of 13 urologists, held at ORSI Academy (Melle, Belgium) on September 25, 2025. The preliminary metrics, comprising six procedural phases, 24 steps, 24 errors, and 16 critical errors (CEs), were developed through literature review, video analysis, and expert discussion. During the Delphi meeting, 14 international experts (urologists and one behavioral scientist) reviewed, discussed, and refined each metric element until ≥80% agreement was achieved. Consensus was unanimous (100%) for all procedural components. After editing, the final metrics include six phases, 24 steps, 25 errors, and 16 CEs. Beyond metric modifications and language refinements, discussions addressed the role of antibiotic prophylaxis, preprocedural urine cultures, patient positioning, and irrigation control. This Delphi consensus represents the first international, structured effort to define standardized, performance-based metrics for flexible cystoscopy. The resulting metrics provide an objective, reproducible framework for describing optimal and suboptimal performance and will serve as the foundation for future validation, educational implementation, and quality assurance initiatives in endourology.

Accurate measurements of lead using isotope dilution calibration curve method with the accounting for natural isotopic variations.

Metrology of rare earths and other elements in waste fluorescent lamp powder - A methodological comparison.

A rapid GC-MS method for the simultaneous determination of bupropion and hydroxybupropion in plasma using SALLME and microwave-assisted derivatization.

Rapid quantitative urinary chloride sensing with conductivity correction for cardiac patient management.

Clinically meaningful thresholds in patient-reported outcome measures (PROMs) for arthroscopic meniscal surgery: A systematic review with narrative synthesis.

The natural protection offered by saltmarsh and mangrove wetlands is increasingly recognised and there is widespread interest in understanding this phenomenon to assist nature-based coastal interventions. Roughness plays a fundamental role in shallow-water hydrodynamic process and hence is a critical parameter for simulating flow over coastal vegetation and the resulting dynamics of surge and wave attenuation. This study provides a comprehensive review of our understanding of the Manning’s coefficient (T/L 1/3 ) in saltmarsh and mangroves. The literature was screened using a rigorous selection procedure to identify studies relevant to saltmarsh and mangrove hydrodynamics and bed roughness. Considering all the numerical, laboratory and field studies that used Manning’s coefficient in saltmarsh and mangrove ecosystems, 36 papers were identified and assessed. The results indicate an interquartile range of Manning’s coefficient (s/m 1/3 ) from 0.04 to 0.08 for saltmarshes and 0.10 to 0.14 for mangroves, providing indicative ‘global’ estimates for these two coastal wetland types. Geographic location, tidal range and temperature showed no statistical relationship, supporting the use of global indicative values. However, statistical testing reveals that the Manning’s coefficient for saltmarshes and mangroves do show significant cross-shore variability with increasing values from the seaward to landward direction. This should be considered and further assessed, especially in more detailed studies. Hence, this analysis provides an indicative ‘global’ constant estimate of Manning’s coefficient for saltmarshes and mangroves, as well as suggestions for more systematic future research on wetland roughness. • A global review of Manning’s number in saltmarsh and mangrove wetlands is presented. • Global assessment of supporting nature based solutions restoring coastal wetlands • Indicative Manning’s values: 0.04–0.08 for saltmarsh and 0.10–0.14 for mangroves. • No statistical link found between Manning’s number and location, tide or temperature. • Cross-shore variability of roughness is significant and needs further investigation.

Rhinoplasty can achieve both aesthetic and functional improvements by altering the internal and external structures of the nose. Given the complex anatomy and significant individual variability of the nasal structure, rhinoplasty requires high precision. 3D printing technology, with its advantages of personalization and rapid prototyping, is increasingly being applied in the field of nasal reconstruction. This technology allows for the creation of three-dimensional models from patient imaging data, enhancing preoperative planning and simulation, enabling custom prosthetic design, and providing intraoperative guidance. Additionally, it aids in postoperative evaluation and care, while providing preoperative training models for surgeons. Clinical applications demonstrate that 3D printing can shorten surgical time, reduce complications, and improve patient satisfaction. However, 3D printing still faces several challenges, including insufficient imaging accuracy, high costs, and technical limitations in bioprinting. Future advancements are needed in imaging and modeling technologies, the development of advanced biomaterials, and cost reduction to further enhance and expand the application of 3D printing in rhinoplasty.

Appendiceal cancer (AC) is a rare malignancy that often presents at advanced stages with significant histological variability influencing clinical outcomes. Precise genomic profiling is essential for accurate diagnosis and personalized patient management. This study interrogated DNA from appendiceal tumor tissue, buffy coat cells, and the cell-free DNA component of plasma using a 523-gene panel for comprehensive genomic profiling (CGP) to identify cancer-related genetic mutations in tumor and blood, evaluate tumor mutation burden, and determine genetic markers associated with histologic grade. A total of 73 patients provided blood samples comprising cell-free DNA (cfDNA) and germline buffy coat cells (bcDNA) for analysis compared with tumor tissues available from 56 of these patients. Concordance of mutations between matched tumor tissue and plasma samples (n = 51) was assessed and tumor-specific and germline variants were classified using OncoKB™ clinical criteria to delineate oncogenic and therapeutically actionable variants [level 1 mutations with U.S. Food and Drug Administration (FDA)-approved therapy]. Additionally, cfDNA concentrations were tested for association with clinical and pathologic features and oncologic outcome including disease-specific (DSS) and progression-free (PFS) survival. Circulating tumor DNA (ctDNA) from plasma cell-free DNA demonstrated high concordance with tumor genomic profiling, reaching 98.4% concordance [median, interquartile range (IQR) 13.5, 21.5] overall and 85.7% (IQR 64.6, 100) for therapeutically actionable level 1 mutations. Prevalent appendiceal tumor-specific mutations included KRAS proto-oncogene, GTPase (KRAS) (41%), GNAS complex locus (GNAS) (30%), tumor protein p53 (TP53) (30%), and SMAD family member 4 (SMAD4) (29%). Tumor-specific TP53, SMAD4, and spectrin alpha, erythrocytic 1 (SPTA1) mutations strongly correlated with intermediate and high-grade histology, whereas GNAS mutations predominated in low-grade tumors. Germline analysis identified coding mutations shared among this patient cohort in notch receptor 4 (NOTCH4) (55%) and BRCA1 associated RING domain 1 (BARD1) (48%) genes, with zinc finger homeobox 3 (ZFHX3) (29%) and adhesion G protein-coupled receptor A2 (ADGRA2), DNA polymerase epsilon (POLE), and transcription factor 3 (TCF3) mutations (all = 23%) specifically enriched in intermediate and high-grade AC. Both histological grade and cfDNA stratified by concentration tertiles independently predicted progression-free and disease-specific survival. Plasma samples exhibited consistently lower variant allele frequencies than solid tumors, limiting sensitivity for discovery of novel mutations exclusively from plasma. This study supports integrating comprehensive ctDNA assays into standard diagnostic and treatment pathways for AC using large gene panels. TP53, SMAD4, SPTA1, and GNAS mutations serve as prospective tumor-specific molecular classifiers for histological grade, while germline variants in NOTCH4 and BARD1 may further influence disease biology, with ZFHX3, ADGRA2, POLE, and TCF3 affecting grade stratification. Overall cfDNA concentration may serve as a potential prognostic biomarker in AC.

Artificial intelligence and machine learning in smart vaginal formulation development.

Bonellia viridis is a benthic echiurid commonly associated with Mediterranean rocky substrates, yet its distribution patterns and environmental drivers remain poorly understood. This study investigates its spatial patterns along the Ligurian coast (NW Mediterranean Sea) using standardised video ROV surveys conducted over the last decade (2015-2025) at multiple sites between 20 and 100 m depth, characterised by coralligenous and rocky reefs under diverse environmental conditions. Results revealed significant spatial variability, with average abundance increasing from east to west and a clear preference for depths less than 50 m. Multivariate analyses highlighted the key roles of substrate slope, bottom type and biocoverage in shaping the echiurid distribution patterns, while sediment cover showed no significant effect. A multiple linear regression confirmed that most environmental variables significantly contributed to species abundance. At the broad spatial scale, species abundance was negatively correlated with rainfall regime and positively correlated with the Population Equivalent (PE) of the coastal towns facing the sites where transects were conducted. This suggests that B. viridis may benefit from increased nutrient availability associated with urban runoff, untreated sewage, and harbour operations—common features along the highly urbanised western Ligurian coast. Seasonal comparisons indicated higher abundances in spring and autumn, likely driven by an enrichment in organic matter associated with increased primary production. These findings provide new insights into the ecological requirements of B. viridis and suggest its potential role as a bioindicator species for monitoring benthic habitat conditions in Mediterranean coastal ecosystems. • Bonellia viridis distribution was assessed in the Ligurian Sea by ROV surveys. • Hard bottom features shape B. viridis distribution in coralligenous habitats. • Echiurans may decline with rainfall-driven inorganic sediment increase. • B . viridis may benefit from from nutrients increased by urbanization and runoff. • Seasonal shifts in abundance suggest link with food availability and biological cycle.

Babesia gibsoni in Brazil: First multilocus molecular characterization in a domestic dog with clinical, hematological and morphological data.

Anemia results from imbalanced hemoglobin or red blood cell production and clearance. Hemolytic anemia, caused by premature red blood cell removal, can be intravascular (in blood) or extravascular (erythrophagocytosis). Hemolysis is common in Sickle Cell Disease (SCD) and Beta-Thalassemia anemia (β-thalassemia), the most prevalent inherited hemolytic anemias. Hemolysis severity is primarily assessed by measuring indirect serum biomarkers such as lactate dehydrogenase, released by cytolysis, bilirubin and haptoglobin. However, these markers do not directly indicate either the cause or the primary site of hemolysis. We introduced a novel plasma heme assay that quantifies all heme-related species in plasma, including hemoglobin, methemoglobin, heme, and hemopexin. Our findings revealed a more profound intravascular red blood cell destruction in SCD compared to β-thalassemia as demonstrated by higher values of plasma hemoglobin, respectively 6.20 and 2.52 μM (p < 0.001), with significant inter-individual variability. In contrast, β-thalassemia patients exhibited higher plasma heme values (11.00 μM vs. 1.51 μM; p < 0.0001) reflecting a probable mixed origin (dyserythropoiesis and hemolysis). Plasma hemopexin was negatively correlated with plasma heme in all patients. Plasma heme exceeded hemopexin scavenging capability in 72% of β-thalassemia and 36% of SCD patients. In β-thalassemia, plasma heme levels were significantly higher in transfusion-dependent compared to non-transfusion-dependent patients, indicating that excess heme reflects clinical severity. In SCD, elevated concentration of excess heme was associated with a significant increased risk of mortality compared to LDH or reticulocytes%. This novel spectral assay offered significant benefits for diagnosis, treatment, and patient management.