Search Results (450)

Background: Fractures of the distal humerus (DHFs) represent challenging intra-articular injuries that are often followed by postoperative complications, most notably ulnar neuropathy. There is still debate regarding the best method of handling the ulnar nerve during open reduction and internal fixation (ORIF). Objective: The primary objective was to evaluate the incidence of postoperative ulnar neuropathy (UN) in patients who underwent open reduction and internal fixation (ORIF) for DHFs, comparing anterior transposition (AT) with in situ decompression (ISD) of the ulnar nerve. Additionally, we investigated the influence of AT on individuals presenting with preoperative UN. Methods: A retrospective review was conducted on 68 patients (26 females and 42 males; mean age: 46.3 years) who underwent ORIF for intra-articular DHF between 2018 and 2022. Patients were divided into two groups: anterior transposition (n = 14) and in situ decompression (n = 54). Ulnar neuropathy was evaluated using the modified McGowan classification, and radiographic outcomes were assessed with AO/OTA fracture classification. Results: Sixty-eight patients (26F/42M) were included. The mean age was 46.3 years (20–77 years) and the mean follow-up time was 53 months (36–76 months). The postoperative UN incidence was 30.8% (21/68). Neuropathy was significantly higher in the transposition group compared to in situ decompression (57.1% vs. 24%; p = 0.012). Olecranon osteotomy (36.3% vs. 20%; p = 0.042) and parallel plate configuration (33.3% vs. 12.5%; p = 0.037) were also associated with increased neuropathy risk. Among patients with preoperative ulnar neuropathy (n = 12), functional recovery was more favorable with transposition, where 71% experienced full resolution compared to 60% in the in situ group. Conclusions: Routine anterior transposition of the ulnar nerve during ORIF for DHF is associated with an increased risk of postoperative neuropathy and should be avoided in patients without preoperative symptoms. However, transposition appears beneficial in patients with pre-existing ulnar neuropathy. Surgeons should individualize ulnar nerve management to balance surgical risks and neurological outcomes. Full article

Background/Objectives: This article aims to investigate the multifaceted effects of alcohol on neurophysiopathological development from gestational stages through adult life and the consequent dynamic-relational challenges in individuals with Fetal Alcohol Spectrum Disorder (FASD). FASD, resulting from prenatal alcohol exposure (PAE), is characterized by a range of neurological, cognitive, behavioral, and sometimes physical impairments. This article explores how alcohol and its toxic metabolites cross the placenta, inducing direct cellular toxicity and epigenetic alterations that disrupt critical neurodevelopmental processes such as neurogenesis and brain circuit formation. Clinically, individuals with FASD exhibit diverse deficits in executive functioning, learning, memory, social skills, and sensory-motor abilities, leading to significant lifelong disabilities. A central focus is the application of the World Health Organization’s International Classification of Functioning, Disability and Health (ICF) criteria to comprehensively frame these disabilities. The ICF’s biopsychosocial model allows for a multidimensional assessment of impairments in body functions and structures, limitations in activities, and restrictions in participation, while also considering the crucial role of environmental factors. Methods: PubMed and Semantic Scholar databases were searched for relevant papers published in English. Results: This article highlights the utility of the ICF in creating individualized functioning profiles to guide interventions and support services, addressing the limitations of traditional assessment methods. Conclusions: While the ICF framework offers a robust approach for understanding and managing FASD, further research is essential to develop and validate FASD-specific ICF-based assessment tools to enhance support and social participation for affected individuals. Full article

Background/Objectives: Feeding and swallowing difficulties are common in young children with cerebral palsy (CP), yet no validated tool has been available in Korea for those under 3 years. The Mini-Eating and Drinking Ability Classification System (Mini-EDACS) was designed for children aged 18–36 months. This study aimed to translate the Mini-EDACS into Korean and evaluate its reliability and validity. Methods: Translation followed international guidelines, including forward–backward translation and Delphi consensus with experts in pediatric dysphagia. Forty-eight children with CP (mean age 27.1 ± 5.0 months) were assessed. Caregivers and speech–language pathologists (SLPs) independently rated Mini-EDACS and assistance levels. Inter-rater reliability was examined using Cohen’s κ. Construct validity was tested by Spearman’s correlations with the Gross Motor Function Classification System (GMFCS), Mini-MACS, the Communication Function Classification System (CFCS), the Visual Function Classification System (VFCS), and the Functional Oral Intake Scale for Children (FOIS-C). Results: Agreement between caregivers and SLPs was excellent (κ = 0.90; weighted κ = 0.98). Assistance-level ratings also showed almost perfect concordance (κ = 0.97). Mini-EDACS correlated strongly with FOIS-C (ρ = −0.86, p < 0.001) and with assistance levels (ρ = 0.81, p < 0.001). Moderate-to-strong positive correlations were observed with GMFCS (ρ = 0.56), Mini-MACS (ρ = 0.64), CFCS (ρ = 0.61), and VFCS (ρ = 0.61), supporting construct validity. Conclusions: The Korean Mini-EDACS is a reliable and valid tool for classifying eating and drinking abilities in children with CP under 3 years. It enables standardized communication between caregivers and clinicians, complements existing functional classification systems, and may facilitate earlier identification and intervention for feeding difficulties. Full article

Background: Muscle health is an emerging concept linked to physical performance and functional independence. However, the term lacks a standardized definition and is often used as a broad muscle-related outcome descriptor. Clinical communication and research would benefit from a conceptual model of muscle health grounded in an established framework. Methods: We conducted systematic search and narrative synthesis to identify multifactorial measurement approaches explicitly described under ‘muscle health’. PubMed and CINAHL were searched for clinical and randomized controlled trials published in the past 5 years (final search: March 2025) that used the term “muscle health.” Studies were reviewed for explicit definitions of “muscle health,” and all identified outcomes (e.g., strength, mass) and measurement tools (e.g., grip strength, ultrasound) were synthesized. This review was retrospectively registered (INPLASY202580069). Results: Of the 65 clinical or randomized controlled trials that met inclusion criteria, 29 provided an operational definition of ‘muscle health’, while 36 inferred measurements without a clear definition. The identified measurements spanned four primary categories, with body composition/muscle mass being the most common (92.3%), followed by muscle performance (78.5%), physical function (63.1%), and tissue composition (30.8%). Most studies included more than one muscle health metric (93.9%). Common assessment methods included DXA (44.6%), grip strength (64.6%), and gait speed (27.7%). Conclusions: While there are common measurement approaches, the definition of muscle health varies widely in the cited works. The framework of the International Classification of Functioning, Disability and Health, was used to identify domains aligned with muscle health components of muscle morphology/morphometry (e.g., mass and composition), functional status (performance-based tasks), and physical capacity (muscle performance). This framework provides a structured basis for evaluating muscle health in research and clinical practice. Consistent use of these domains could enhance assessment and support efforts to standardize testing and interpretation across settings. Full article

Insights into the state of individual cells within a living organism are essential for identifying diseases and abnormalities. The internal state of a cell is reflected in its morphological features and changes in the localization of intracellular molecules. Using this information, it is possible to infer the state of the cells with high precision. In recent years, technological advancements and improvements in instrument specifications have made large-scale analyses, such as single-cell analysis, more widely accessible. Among these technologies, imaging flow cytometry (IFC) is a high-throughput imaging platform that can simultaneously acquire information from flow cytometry (FCM) and cellular images. While conventional FCM can only obtain fluorescence intensity information corresponding to each detector, IFC can acquire multidimensional information, including cellular morphology and the spatial arrangement of proteins, nucleic acids, and organelles for each imaging channel. This enables the discrimination of cell types and states based on the localization of proteins and organelles, which is difficult to assess accurately using conventional FCM. Because IFC can acquire a large number of single-cell morphological images in a short time, it is well suited for automated classification using machine learning. Furthermore, commercial instruments that combine integrated imaging and cell sorting capabilities have recently become available, enabling the sorting of cells based on their image information. In this review, we specifically highlight practical applications of IFC in four representative areas: cell cycle analysis, protein localization analysis, immunological synapse formation, and the detection of leukemic cells. In addition, particular emphasis is placed on applications that directly contribute to elucidating molecular mechanisms, thereby distinguishing this review from previous general overviews of IFC. IFC enables the estimation of cell cycle phases from large numbers of acquired cellular images using machine learning, thereby allowing more precise cell cycle analysis. Moreover, IFC has been applied to investigate intracellular survival and differentiation signals triggered by external stimuli, to monitor DNA damage responses such as γH2AX foci formation, and more recently, to detect immune synapse formation among interacting cells within large populations and to analyze these interactions at the molecular level. In hematological malignancies, IFC combined with fluorescence in situ hybridization (FISH) enables high-throughput detection of chromosomal abnormalities, such as BCR-ABL1 translocations. These advances demonstrate that IFC provides not only morphological and functional insights but also clinically relevant genomic information at the single-cell level. By summarizing these unique applications, this review aims to complement existing publications and provide researchers with practical insights into how IFC can be implemented in both basic and translational research. Full article

Surface water resources are under growing pressure from urbanization, industrial activity, and agriculture, making effective monitoring essential for safeguarding ecological integrity and human use. Conventional monitoring methods, which rely on manual sampling and rigid Water Quality Index (WQI) categories, often provide delayed feedback and oversimplify conditions near classification thresholds, limiting their usefulness for timely management. To overcome these shortcomings, we have developed an interactive fuzzy logic-based water quality monitoring interface or dashboard that integrates the WQI developed by Malaysia’s Department of Environment with the National Water Quality Standards (NWQS) Class I–V framework. The interface combines conventional WQI computation with advanced visualization tools such as dynamic gauges, parameter tables, fuzzy membership graphs, scatter plots, heatmaps, and bar charts. Then, triangular membership functions map six key parameters to NWQS classes, providing smoother and more nuanced interpretation compared to rigid thresholds. In addition to that, the dashboard enables clearer communication of trends, supports timely decision-making, and demonstrates adaptability for broader applications since it is implemented on the Replit platform. Finally, evaluation results show that the fuzzy interface improves interpretability by resolving ambiguities in over 15% of cases near class boundaries and facilitates faster assessment of pollution trends compared to conventional reporting. Thus, these contributions highlight the necessity and value of the research on advancing Malaysia’s national water quality monitoring and providing a scalable framework for international contexts. Full article

Phaeozem, which is recognized as one of the world’s most fertile soils, derives much of its productivity from soil organic matter (SOM). Because SOM strongly influences fertility, soil structure, and ecological functions, it is the SOM content that must be rapidly and accurately determined to ensure sustainable soil management. Traditional chemical methods are reliable but time-consuming and labor-intensive, which makes them inadequate for large-scale applications. Hyperspectral reflectance, which is highly sensitive to SOM variations, provides a non-destructive alternative for rapid SOM grading. This study proposes an ensemble learning strategy model based on phaeozem hyperspectral reference data for the rapid grading and detection of SOM content. First, the SOM content of the collected phaeozem samples was determined using the potassium dichromate volumetric method. Next, hyperspectral reflectance data of the phaeozem were collected using a hyperspectral imaging sensor, with a wavelength range of 400–1000 nm. Furthermore, stacking models were constructed by modifying the internal structure, with five classifiers (MLP, SVC, DTree, XGBoost, kNN) as the L1 layer. Then, global optimization was performed using the simulated annealing algorithm. Through comparative analysis, the LSVM-stacking model demonstrated the highest accuracy and generalization capabilities. The results demonstrated that the LSVM-stacking model not only achieved the highest overall accuracy (0.9488 on the independent test set) but also improved the classification accuracy of “Category 1” samples to 1.0. Compared with other models, this framework significantly improved generalization ability and robustness. It is therefore evident that combining hyperspectral reflectance with improved stacking strategies provides a novel and effective approach for the rapid grading and detection of SOM in phaeozem. Full article

Background and Objectives: Tibial tuberosity avulsion fractures are rare injuries in pediatric athletes, with limited data on the potential role of an elevated body mass index (BMI) as a risk factor. Previous studies have primarily focused on age, sex, and sport type, but the association between BMI and these injuries remains underexplored. Tibial tuberosity avulsion fractures are rare injuries predominantly affecting adolescent boys during sports activities involving strong quadriceps contractions. This pilot study aimed to analyze the epidemiological and anthropometric characteristics of patients with these fractures, including the distribution of injury mechanisms and the fracture types, to test whether the prevalence of overweight/obesity among cases exceeded national population benchmarks, and to describe the associated clinical outcomes. Materials and Methods: A retrospective analysis was conducted on medical records and radiographs of patients under the age of 18 treated between 2017 and 2024. The data collected included demographic and anthropometric characteristics, injury mechanisms, fracture classification, treatment methods, complications, and outcomes. The patients were categorized as normal weight (<85th percentile) or overweight/obese (≥85th percentile). The primary outcome was whether the prevalence of overweight/obesity among the cases exceeded national pediatric benchmarks. Formal sample size and power analyses were performed to guide future research. Results: Twenty-one patients met the inclusion criteria, with a mean age of 13.7 years; 95.2% were male. Soccer was the most common injury mechanism (52.4%), followed by athletics and running. The predominant fracture type was Ogden IVb (38.1%). Overweight/obesity was present in 52.4% of the patients, significantly higher than the national benchmarks. An open reduction and internal fixation was performed in 90.5% of the cases, with a mean follow-up of 14.6 months (range: 6–36). Complications occurred in 14.3% overall, all within the overweight/obese group (27.3%). Conclusions: This pilot retrospective study suggests a potential link between an elevated BMI and tibial tuberosity avulsion fractures, with overweight/obesity being significantly more prevalent in affected patients than in the general pediatric population. These exploratory findings warrant confirmation in larger, adequately powered studies, and emphasize the importance of weight management and tailored sports activities as potential preventive strategies. An early diagnosis, timely surgical intervention, and adequate rehabilitation are critical for achieving optimal functional recovery. Full article

Although giant viruses have introduced new perspectives on the definition and evolution of viruses and are increasingly recognized for their significant biological roles within marine ecosystems, systematic evaluations of development trends and scientific contributions in this research field remain limited. This study conducted a bibliometric analysis of the global academic literature on marine giant viruses (MGVs), focusing on nucleocytoplasmic large DNA viruses (NCLDVs), from 1996 to 2024. Using the Web of Science Core Collection, 1544 publications related to giant viruses were identified. After filtering using marine-related keywords and manual review, 300 studies specifically addressing marine giant viruses were selected for the final analysis. This study comprehensively examined the structural characteristics and evolutionary trends in this field by analyzing annual publication productivity, citation patterns, contributions by countries and institutions, author collaboration networks, and keyword co-occurrence patterns. The results show that research on MGVs has steadily increased since the mid-2000s, with a notable surge after 2018 driven by advancements in metagenomics, next-generation sequencing technologies, and global ocean exploration initiatives. The United States and France have taken leading positions in terms of research productivity and impact, with key institutions such as the CNRS (Centre National de la Recherche Scientifique) and Aix-Marseille Université playing central roles. A multipolar network of international collaborations between countries and institutions has been formed. Research topics have evolved from an early focus on virus classification and genome analysis to more diverse themes, including interactions with marine microbiota, viral ecological functions, infection dynamics, virophage research, and metagenome-based ecosystem-level studies. This study provides an overview of the chronological and structural evolution of the marine giant virus research field by systematically presenting key research themes and collaborative networks. The results provide a valuable foundation for determining future academic directions and planning strategic research initiatives. Furthermore, it is expected to facilitate interdisciplinary research in marine biology, environmental science, systems biology, and artificial intelligence-based functional predictions. Full article

Structural analysis of glycosphingolipids provides novel insights into organismal classification and reveals conserved functional roles that transcend taxonomic boundaries. To elucidate the structural characteristics of acidic glycosphingolipids (AGLs) in the adductor muscle of the Japanese giant scallop (Patinopecten yessoensis), AGLs were isolated and purified by column chromatography using anion exchange resin and silica gel. Structural characterization was performed using mass spectrometry, proton nuclear magnetic resonance spectroscopy, and immunological techniques. The sugar chain structure was identified as GlcA4Meβ1-4(GalNAc3Meα1-3)Fucα1-4GlcNAcβ1-2Manα1-3Manβ1-4Glcβ1-Cer, consistent with the mollu-series core reported for mollusks. In addition to uronic acid, the structure was distinguished by internal fucose and methylated sugars, features commonly found in bivalves. The presence of xylose in the sugar chains of AGLs was also suggested. In contrast, the ceramide moiety was composed primarily of fatty acids C16:0 and C18:0 and the long-chain base d16:1. This chemical structure provides valuable insights into the biological classification of P. yessoensis and the mollu-series glycolipids containing fucose and methylated sugars, which may serve as bioactive components shared across species in the phylum Mollusca and class Bivalvia. Full article

Background/Objectives: Cerebral palsy (CP) is the most common cause of motor disability in childhood and is frequently associated with cognitive impairments that limit autonomy and participation. While motor function is a known predictor of functional outcomes, the specific contribution of cognitive domains within the International Classification of Functioning, Disability and Health (ICF) framework remains unexplored. This systematic review examines the relationship between cognitive domains and the ICF components of Activities and Participation, and Environmental Factors in people with CP. Methods: Following PRISMA guidelines, a systematic search was conducted across six databases (PubMed, PsycINFO, CENTRAL, CINAHL, ERIC, and WOS) for studies published between 2002 and 2025. Eligible studies included participants with CP (n = 3056) and analyzed associations between cognitive functions and ICF domains using standardized tools and statistical methods. Risk of bias was evaluated using the Oxford Centre for Evidence-Based Medicine criteria. Results: Forty-four studies met inclusion criteria, involving mostly children and adolescents with spastic CP and mild to moderate motor impairment. General intellectual functioning, language, and visual perception were the most studied domains, showing consistent associations with ICF chapters such as Learning and applying knowledge, Communication, and Mobility. Although fewer studies examined Environmental Factors, relevant associations emerged with support systems, attitudes, and services. Heterogeneity in assessment methods and participant profiles was observed, and adult representation was limited. Conclusions: Cognitive functioning is significantly associated with multiple ICF domains in CP. Environmental Factors remain insufficiently addressed. Further research should consider CP heterogeneity and promote standardized assessments to support ICF-based intervention planning. Full article

Generative models, particularly autoencoders, often function as black boxes, making it challenging for non-expert users to effectively control the generation process and understand how inputs affect outputs. Existing methods for improving interpretability and control frequently require specific model training regimes or labeled data, limiting their applicability. This work introduces a novel approach to enhance the controllability and explainability of generative models, specifically tested on autoencoders with entangled latent spaces. We propose using a semi-supervised contrastive learning setup to learn steering vectors. These vectors, when added to an input’s latent representation, effectively manipulate specific attributes in the generated output without conditional training of the model or attribute classifiers, thus being applicable to pretrained models and avoiding compound classification errors. Furthermore, we leverage these learned steering vectors to interpret and explain the decoding process of a target attribute, allowing for efficient exploration of feature dimension interactions and the construction of an interpretable plot of the generative process, while lowering scalability limitations of perturbation-based Explainable AI (XAI) methods by reducing the search space. Our method provides an efficient pathway to controllable generation, offers an interpretable result of the model’s internal mechanisms, and relates the interpretations to human-understandable explanation questions. Full article

Background and Objectives: Quality of life is significantly impacted by patients’ diagnosis perceptions, and self-assessment of quality of life is increasingly used in medicine. With this study, we aim to provide an overview of the differences in self-assessed quality of life among patients in different diagnostic categories in otorhinolaryngology, focusing on physical health, physical pain, and social and emotional well-being. We hypothesize that these differences are substantial and can further improve patient care. Methods: The research was carried out from 1 May to 30 June 2024 with 127 otorhinolaryngology patients scheduled for a follow-up appointment at an otorhinolaryngology clinic. The 36-Item Short Form Health Survey, adequately completed by 114 patients, was used to determine the differences in self-reported quality of life between patients with different otorhinolaryngological diagnoses, classified by the International Classification of Diseases. Results: The results showed significant differences in the self-assessed quality of life for patients with different otorhinolaryngology diagnoses. Patients with oncological diagnoses had lower scores for emotional (p ≤ 0.001) and social functioning (p ≤ 0.038) compared with patients with other diagnoses but scored similarly to patients with chronic inflammation of the nose and patients with impaired communication due to ear or voice diseases. Conclusions: Self-assessment of quality of life is significantly different across diagnostic categories in otorhinolaryngology. These findings underscore the necessity of tailoring healthcare communication strategies to the specific needs of individual patients, addressing not only their physical but also emotional well-being. Full article

The integration of nanotechnology into drug repurposing strategies is redefining the development landscape for diagnostic, therapeutic, and theranostic agents. In radiopharmacy, nanoplatforms are increasingly being explored to enhance or extend the use of existing radiopharmaceuticals, complementing earlier applications in other biomedical fields. Many of these nanoplatforms evolve into multifunctional systems by incorporating additional imaging modalities (e.g., MRI, fluorescence) or non-radioactive therapies (e.g., photodynamic therapy, chemotherapy). These hybrid constructs often emerge from the reformulation, repositioning, or revival of previously approved or abandoned compounds, generating entities with novel pharmacological, pharmacokinetic, and biodistribution profiles. However, their translational potential faces significant regulatory hurdles. Existing frameworks—typically designed for single-modality drugs or devices—struggle to accommodate the combined complexity of nanoengineering, radioactive components, and integrated functionalities. This review examines how these systems challenge current norms in classification, safety assessment, preclinical modeling, and regulatory coordination. It also addresses emerging concerns around digital adjuncts such as AI-assisted dosimetry and software-based therapy planning. Finally, the article outlines international initiatives aimed at closing regulatory gaps and provides future directions for building harmonized, risk-adapted frameworks that support innovation while ensuring safety and efficacy. Full article

Background/Objectives: Femoral neck and proximal femur fractures in the elderly can result from low-energy trauma due to osteoporotic changes and contribute significantly to increased morbidity and mortality. Despite various treatment options, closed reduction and internal fixation (CRIF) with intramedullary nails has become the predominant approach. While a minimally invasive approach reduces complications and speeds recovery, this outcome is not always feasible in practice. The primary surgical goal remains achieving a stable and precise fracture reduction, favoring CRIF when possible. Our study aims to evaluate the clinical, radiological, and functional outcomes of patients operated on using the Wide-Awake Local Anesthesia No Tourniquet (WALANT) technique. Methods: Patients who underwent surgery for intertrochanteric femur fractures between June 2019 and June 2021 were analyzed. Patients who were between 75 and 90 years old and had undergone surgery with a proximal femoral nail (PFN) were included in the study. Patients were excluded if they required general anesthesia, if an acceptable reduction could not be achieved with the PFN, if they did not attend the last follow-up examination, or if the follow-up period was <4 years. Patients were functionally assessed using the Harris hip score at the 6th month and at the last follow-up and using the visual analog scale at the surgery, at the 4th hour after surgery, and at the time of discharge. For radiological assessment, the classification of reduction quality and the measurement of the tip–apex distance were used. Results: Forty patients (22F/18M) were included in the study. Their mean age was 83.0 ± 2.9 years. The mean time from trauma to surgery was 6.8 ± 2.3 h. Patients were mobilized on average 1.53 ± 0.8 h after surgery, and the mean hospitalization time was 27.4 ± 8.1 h. No statistically significant decrease in hemoglobin value was observed before or after surgery (p = 0.476). The Harris hip score was 73.3 ± 3.2 at the 6th month postoperatively and 74.9 ± 2.5 at the last follow-up (p = 0.296). The reduction quality was found to be poor in only two patients. Conclusions: The WALANT technique’s promising results in terms of pain management, blood loss control, and early mobilization show that it is a viable alternative to conventional anesthesia methods in geriatric hip fractures. Full article