Search Results (8,810)

Conservative management of rotator cuff disorders remains challenging, with no comprehensive, evidence-based framework integrating diagnosis, prognosis, rehabilitation, and biological therapies. Existing recommendations usually address isolated components of care, leading to inconsistent treatment strategies. This article proposes a global, pragmatic protocol for the non-surgical management of rotator cuff lesions, from initial assessment to long-term follow-up. Drawing on clinical expertise supported by recent literature, we outline a stepwise approach that begins with a comprehensive diagnostic process that combines history, clinical examination, and targeted imaging. Based on lesion type, associated shoulder or neurogenic conditions, and patient profile, rotator cuff disorders are stratified into three prognostic categories under conservative care: good, borderline, and poor prognosis, highlighting factors that require treatment adaptation or early surgical consideration. Rehabilitation objectives are structured around four domains: (1) inflammation and pain control, (2) mobility and scapular kinematics, (3) strengthening and motor control with tendon-sparing strategies, and (4) preservation or restoration of anatomy. For each prognostic category, we define a monitoring plan integrating clinical reassessment, ultrasound follow-up, and functional milestones, including return-to-play criteria for athletes. This comprehensive narrative review demonstrates that precise diagnosis and individualized rehabilitation can optimize medical follow-up, active strengthening, and complementary or regenerative therapies. Aligning therapeutic decisions with prognostic and functional goals allows clinicians to optimize patient satisfaction and recovery, providing a clear, evidence-informed roadmap for conservative management of rotator cuff disorders. Full article

Introduction: Nursing informatics aims to improve patient care through rapid access to patient data, systematic assessment, a reduction in clinical errors, evidence-based practice, cost-effectiveness, and improved patient outcomes and safety. Background: Despite being the largest workforce in healthcare, nurses are not being adequately prepared to use nursing informatics, and this has been attributed to poor digital literacy, limited professional development, and a lack of undergraduate informatics education. Objectives: This scoping review aims to review contemporary published literature on the benefits, barriers, and enablers for embedding nursing informatics into undergraduate nursing education with a focus on the Australian healthcare context. Methods: A scoping review was conducted using the PRISMA-ScR checklist and the JBI Manual for evidence synthesis in adherence with an a priori scoping review protocol. A comprehensive search of JBI, Cochrane, CINAHL, Ovid, ProQuest, PubMed, and Scopus databases was performed. Two reviewers independently screened the results via Covidence, with discrepancies resolved via a third reviewer. Results: Two searches were conducted for this scoping review. In the first search, a total of 3227 articles were identified through database searches, with an additional 76 articles identified through bibliographic and grey literature searches. Following duplicate removal and screening, 46 articles met the inclusion criteria. In the second search, a total of 1555 articles were identified, and after duplicate removal and screening, 16 articles met the inclusion criteria. Duplicate removal during the second search round included those articles identified in the first search. The combined searches resulted in a total of 62 sources for this review. Conclusions: Despite the early adoption of nursing informatics in Australia in the 1980s, barriers remain to effective nursing informatics engagement and proficiency, including a lack of understanding of nursing informatics, limited infrastructure and resources, inadequate digital literacy of students and faculty, and the evolving nature of nursing informatics. Definitions of nursing informatics and associated fields, development of university faculty competency, access to digital health technologies, competency standards, digital literacy of the student cohort, faculty digital proficiency, and leadership from professional nursing bodies are all viewed as integral foundations for the development of student competency in nursing informatics. Full article

Background: Streptococcus pneumoniae (Spn) is a leading bacterial pathogen responsible for severe invasive diseases, including meningitis, sepsis, and pneumonia. Current pneumococcal vaccines, which are all based on capsular polysaccharide antigens, provide limited protection and are further compromised by post-vaccination serotype replacement. Pneumococcal surface protein A (PspA), a highly conserved virulence factor expressed across diverse serotypes, has emerged as a promising candidate antigen for novel protein-based vaccines. However, progress in this field has been hindered by the absence of standardized in vitro functional antibody assays. Methods: This study established a robust functional antibody detection method for PspA-based protein vaccines by modifying the conventional multiplex opsonophagocytic killing assay (MOPA), originally designed for polysaccharide-based vaccines. Using polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) typing, a target strain panel was selected and developed to include representative strains from PspA Family 1-Clade 2 and Family 2-Clades 3 and 4. The MOPA protocol was optimized by extending the phagocytic reaction time to enhance sensitivity. Specificity was confirmed through recombinant PspA competitive inhibition assays. Results: The assay demonstrated high linearity (R² ≥ 0.98) between opsonophagocytic index (OI) and serum dilution, along with acceptable repeatability (CV ≤ 30%) and intermediate precision (CV ≤ 50%). Both preclinical and clinical serum samples exhibited potent bactericidal activity against diverse PspA families, independent of capsule type. Conclusion: This study provided a standardized framework to support the development and regulatory assessment of protein-based pneumococcal vaccines. Full article

Pancreatic β-cell replacement represents a promising therapeutic avenue for insulin-dependent diabetes, yet clinical translation has been limited by donor scarcity, immune rejection, and incomplete engraftment. Three-dimensional (3D) pancreatic organoids derived from human pluripotent stem cells (hPSCs) or primary tissue offer a scalable and physiologically relevant platform, recapitulating native islet architecture, paracrine interactions, and glucose-responsive insulin secretion. Recent advances in differentiation protocols, vascularization strategies, and immune-protective approaches—including encapsulation and hypoimmunogenic engineering—have enhanced β-cell maturation, survival, and functional performance in vitro and in vivo. Despite these developments, challenges remain in achieving fully mature β-cells, durable graft function, and scalable, reproducible production that is suitable for clinical use. This review highlights the promise of pancreatic organoid engineering, emphasizing strategies to optimize β-cell maturation, vascular integration, and immune protection, and outlines key future directions to advance organoid-based β-cell replacement toward safe, effective, and personalized diabetes therapies. Full article

Background/Objectives: Anastomotic leakage (AL) is a major complication of colorectal surgery. Despite multiple identified risk factors, no single strategy has proven fully effective in preventing AL. This single-arm pilot study aims to evaluate the feasibility, safety, and adherence of a multimodal colorectal anastomosis assessment protocol (CASPI) in patients undergoing surgery for colorectal cancer. Methods: This prospective descriptive interventional single-arm pilot study included patients diagnosed with colorectal cancer who underwent surgical resection. The CASPI protocol consists of five steps: (1) indocyanine green (ICG) perfusion assessment, (2) doughnut integrity checking, (3) air leak testing, (4) intraoperative flexible endoscopy, and (5) postoperative flexible sigmoidoscopy. Results: A total of 34 patients were included. The median age was 63.5 years, and the median BMI was 27.7 kg/m². Twenty-seven patients had rectal tumors, and 66.7% received neoadjuvant therapy. Adherence to the protocol was 100% intraoperatively and 88.2% postoperatively. Adequate perfusion by ICG was confirmed in 94.1% of cases; intact anastomotic doughnuts were obtained in all procedures. Intraoperative endoscopy showed Grade 1 mucosa in 76.5% of patients and Grade 2 in 23.5%. No complications related to the CASPI protocol were observed. Stoma closure was performed in all patients with temporary ileostomy. Conclusions: Implementation of the CASPI protocol in colorectal surgery demonstrated excellent feasibility, high adherence, and strong safety. These findings support its further evaluation in larger, controlled studies designed to assess clinical effectiveness in the incidence of anastomotic complications. Full article

Prader–Willi (PWS) and Angelman (AS) syndromes were the first examples in humans with errors in genomic imprinting, usually from de novo 15q11-q13 deletions of different parent origin (paternal in PWS and maternal in AS). Dozens of genes and transcripts are found in the 15q11-q13 region, and may play a role in PWS, specifically paternally expressed SNURF-SNRPN and MAGEL2 genes, while AS is due to the maternally expressed UBE3A gene. These three causative genes, including their encoding proteins, were targeted. This review article summarizes and illustrates the current understanding and cause of both PWS and AS using strategies to include the literature sources of key words and searchable web-based programs with databases for integrated gene and protein interactions, biological processes, and molecular mechanisms available for the two imprinting disorders. The SNURF-SNRPN gene is key in developing complex spliceosomal snRNP assemblies required for mRNA processing, cellular events, splicing, and binding required for detailed protein production and variation, neurodevelopment, immunodeficiency, and cell migration. The MAGEL2 gene is involved with the regulation of retrograde transport and promotion of endosomal assembly, oxytocin and reproduction, as well as circadian rhythm, transcriptional activity control, and appetite. The UBE3A gene encodes a key enzyme for the ubiquitin protein degradation system, apoptosis, tumor suppression, cell adhesion, and targeting proteins for degradation, autophagy, signaling pathways, and circadian rhythm. PWS is characterized early with infantile hypotonia, a poor suck, and failure to thrive with hypogenitalism/hypogonadism. Later, growth and other hormone deficiencies, developmental delays, and behavioral problems are noted with hyperphagia and morbid obesity, if not externally controlled. AS is characterized by seizures, lack of speech, severe learning disabilities, inappropriate laughter, and ataxia. This review captures the clinical presentation, natural history, causes with genetics, mechanisms, and description of established laboratory testing for genetic confirmation of each disorder. Three separate searchable web-based programs and databases that included information from the updated literature and other sources were used to identify and examine integrated genetic findings with predicted gene and protein interactions, molecular mechanisms and functions, biological processes, pathways, and gene-disease associations for candidate or causative genes per disorder. The natural history, review of pathophysiology, clinical presentation, genetics, and genetic-phenotypic findings were described along with computational biology, molecular mechanisms, genetic testing approaches, and status for each disorder, management and treatment options, clinical trial experiences, and future strategies. Conclusions and limitations were discussed to improve understanding, clinical care, genetics, diagnostic protocols, therapeutic agents, and genetic counseling for those with these genomic imprinting disorders. Full article

Artificial intelligence (AI) has shown promising performance in brain tumor diagnosis and prognosis; however, most reported advances remain difficult to translate into clinical practice due to limited interpretability, inconsistent evaluation protocols, and weak generalization across datasets and institutions. In this work, we present a critical synthesis of recent brain tumor AI studies (2020–2025) guided by two novel conceptual tools: a unified diagnostic-prognostic framework and a triadic evaluation model emphasizing interpretability, computational efficiency, and generalizability as core dimensions of clinical readiness. Following PRISMA 2020 guidelines, we screened and analyzed over 100 peer-reviewed studies. A structured analysis of reported metrics reveals systematic trends and trade-offs—for instance, between model accuracy and inference latency—rather than providing a direct performance benchmark. This synthesis exposes critical gaps in current evaluation practices, particularly the under-reporting of interpretability validation, deployment-level efficiency, and external generalization. By integrating conceptual structuring with evidence-driven analysis, this work provides a framework for more clinically grounded development and evaluation of AI systems in neuro-oncology. Full article

Background and Objectives: Sternocleidomastoid (SCM) dysfunction is commonly implicated in several musculoskeletal conditions. Accordingly, shear-wave elastography has been used to characterize SCM stiffness in asymptomatic and clinical cohorts. However, the only reproducibility study available reported limited reliability, so clinical interpretations should be made with caution. Therefore, this study revisits key methodological aspects of that protocol to assess intra-examiner reliability and includes two examiners with different levels of expertise to evaluate inter-examiner reliability. Materials and Methods: A longitudinal observational study was conducted, recruiting twenty-five asymptomatic participants. Two examiners with different experience levels participated in this study after following structured training. For each side, images were obtained in immediate succession in the sequence experienced–novice–experienced–novice (with side order randomized), using an ROI spanning full muscle thickness, stabilizing approximately 10 s before freezing to record Young’s modulus and shear-wave speed. Results: Inter-examiner agreement was good–excellent: single-measurement ICCs were 0.77–0.86, improving to 0.79–0.87 when averaging two trials, which also reduced the standard error of measurement (SEM) and minimal detectable changes (MDCs). Between-examiner mean differences were small and nonsignificant (p ≥ 0.068). Intra-examiner reliability was excellent (ICC ≈ 0.93–0.94) with small absolute errors. Precision was high (SEM ~5–6 kPa; 0.22 m/s), and MDCs were ~15–16 kPa and ~0.60 m/s, with no trial-to-trial bias (all p ≥ 0.311). Conclusions: The revised protocol showed excellent intra-examiner repeatability and good–excellent inter-examiner reliability with minimal bias. Averaging two acquisitions improved precision, while a single operator optimized longitudinal stability. Full article

In this work, we evaluate the efficiency of a DNA purification protocol from gynecological samples using locally synthesized Fe₃O₄@SiO₂ magnetic microparticles and a low-cost, guanidinium thiocyanate (GITC)-free lysis buffer. The microparticles were characterized by SEM, EDS, FTIR, and magnetic measurements, confirming the formation of compact silica-coated aggregates with suitable magnetic responsiveness for rapid and complete capture. Using this material in combination with a simple, GITC-free lysis buffer, we achieved DNA extraction yields comparable to those obtained with standard methods based on chaotropic salts. The purified DNA showed high compatibility with molecular assays for the detection of Chlamydia trachomatis, Ureaplasma urealyticum, Mycoplasma hominis, and human papilloma virus. Clinical validation demonstrated excellent diagnostic performance, with only a few discrepancies observed in samples near the detection threshold of qPCR, a limitation shared with commercial kits. Overall, the method represents a low-cost, safe, and sustainable alternative for routine clinical and epidemiological applications, compared to methods based on chaotropic salt buffers. Furthermore, it reduces reliance on imported commercial consumables and minimizes the handling of hazardous reagents. Full article

Background/Objectives: Obesity is a multifactorial condition and a major public health challenge. Conventional treatment centers on caloric restriction, which is often unsustainable and may cause stigma and psychoemotional harm. This study aimed to describe the methodology and assess the effects of a multicomponent nutritional intervention not focused on caloric restriction on psychoemotional outcomes. Women were selected as the target population because of the higher prevalence of obesity-related psychoemotional distress, body dissatisfaction, and weight-related stigma in this group, as well as their greater vulnerability to the psychosocial impacts of weight-focused interventions. Methods: This randomised, parallel, open-label trial included 89 obese women from primary care in Viçosa, Brazil. The participants were allocated into three groups: Group 1 (Control), which received a personalised hypocaloric diet (from 500 to 1000 kcal/day); Group 2 (NutrirCom (NutrirCom is a multicomponent, person-centred nutritional intervention protocol that is not focused on caloric restriction, conceived by a group of researchers at the Federal University of Viçosa for the care of women with obesity in Primary Health Care. It integrates nutritional, psychoemotional, behavioural, and social strategies, with an emphasis on promoting eating autonomy, mental health, and quality of life through a humanised, integrated, and sustainable approach, aiming to enhance the effectiveness of health care delivery and clinical practice)), which received 10 individual NutrirCom-based sessions; and Group 3 (NutrirCom + Social Support), which combined individual NutrirCom sessions with monthly group meetings for social support. Randomisation was stratified by body mass index via Excel^® with concealed allocation. The six-month intervention assessed changes in stress, anxiety, depression, and self-compassion, along with anthropometric and metabolic markers. Results: All groups presented reductions in waist circumference, fasting glucose, and total body fat, with increased lean mass. Anxiety remained unchanged in Group 1 but decreased significantly in Groups 2 (p = 0.002) and 3 (p = 0.005). Only Group 2 showed a significant reduction in depression symptoms (p = 0.023). Self-compassion improved significantly in groups 2 and 3. Conclusions: NutrirCom is a low-cost, scalable, and human-centered intervention that integrates emotional, social, and nutritional aspects of care. This approach shows promise as a sustainable strategy for obesity treatment in primary health care. Registration: Brazilian Registry of Clinical Trials (ReBEC) (no. RBR-87wb8x5). Full article

Over the past decades, remarkable progress in multimodal therapy has significantly improved survival outcomes for children with cancer. Yet, considerable variability in treatment response and toxicity persists, often driven by underlying genetic differences that affect the pharmacokinetics and pharmacodynamics of anticancer drugs. Pharmacogenomics, the study of genetic determinants of drug response, offers a powerful approach to personalize pediatric cancer therapy by optimizing efficacy while minimizing adverse effects. This review synthesizes current evidence on key pharmacogenetic variants influencing the response to major classes of antineoplastic agents used in children, including thiopurines, methotrexate, anthracyclines, alkylating agents, vinca alkaloids, and platinum compounds. Established gene–drug associations such as TPMT, NUDT15, DPYD, SLC28A3, and RARG are discussed alongside emerging biomarkers identified through genome-wide and multi-omics studies. The review also examines the major challenges that impede clinical implementation, including infrastructural limitations, cost constraints, population-specific variability, and ethical considerations. Furthermore, it highlights how integrative multi-omics, systems pharmacology, and artificial intelligence may accelerate the translation of pharmacogenomic data into clinical decision-making. The integration of pharmacogenomic testing into pediatric oncology protocols has the potential to transform cancer care by improving drug safety, enhancing treatment precision, and paving the way toward ethically grounded, personalized therapy for children. Full article

Knee osteoarthritis (KOA) is a leading cause of disability in older adults, characterized by persistent pain and reduced physical function. Beyond localized joint pathology, many individuals with knee osteoarthritis experience multisite pain and live with multiple comorbidities, reflecting a heterogeneous and multifactorial pain condition. Prognostic models based primarily on biomedical variables have shown limited ability to explain long-term outcomes, partly due to insufficient integration of pain chronicity, comorbidity count and psychosocial determinants such as treatment expectations and pain self-efficacy. While exercise and education are commonly recommended as primary non-surgical treatments, people often respond to them very differently. This study protocol describes a secondary longitudinal observational analysis of data from the EPIPHA-KNEE two-arm, multicentre randomized controlled trial. The primary outcomes will be knee OA pain intensity and physical function, assessed using the Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire at baseline, 3, 6 and 12 months. Baseline prognostic factors will include pain duration, pain distribution, comorbidity count and patient expectations, including treatment expectations and pain self-efficacy. Linear mixed-effects models will be used to examine longitudinal associations between these predictors and pain and function trajectories, with particular emphasis on predictor-by-time interactions to characterize differential patterns of change over time. The planned analyses aim to improve understanding of how clinical characteristics and expectancy-related factors jointly shape 12-month pain and physical function trajectories in older adults with knee osteoarthritis receiving education and exercise-based care, thereby informing prognostic stratification within non-surgical management. Full article

The exponential growth of multimodal orthopedic data, ranging from longitudinal Electronic Health Records to high-resolution musculoskeletal imaging, has rendered manual analysis insufficient. This has established Large Language Models (LLMs) as algorithmically necessary for managing healthcare complexity. However, their deployment in high-stakes surgical environments presents a fundamental algorithmic paradox: while generic foundation models possess vast reasoning capabilities, they often lack the precise, protocol-driven domain knowledge required for safe orthopedic decision support. This review provides a structured synthesis of the emerging algorithmic frameworks required to build modern clinical AI assistants. We deconstruct current methodologies into their core components: large-language-model adaptation, multimodal data fusion, and standardized data interoperability pipelines. Rather than proposing a single proprietary architecture, we analyze how recent literature connects specific algorithmic choices such as the trade-offs between full fine-tuning and Low-Rank Adaptation to their computational costs and factual reliability. Furthermore, we examine the theoretical architectures required for ‘agentic’ capabilities, where AI systems integrate outputs from deep convolutional neural networks and biosensors. The review concludes by outlining the unresolved challenges in algorithmic bias, security, and interoperability that must be addressed to transition these technologies from research prototypes to scalable clinical solutions. Full article

Maintaining cardiovascular stability during anesthesia is essential, yet the routine use of atropine to prevent vagally induced low heart rate may impose additional stress on the heart. This randomized, controlled, observer-blinded, clinical study aimed to evaluate whether ondansetron, a selective 5-HT₃ receptor antagonist, could serve as an alternative anesthetic adjuvant to modulate autonomic activity while maintaining cardiovascular stability in dogs. A total of 66 female dogs, with a mean age of 1.5 years and a mean weight of 16–18 kg ASA I, undergoing elective surgery were assigned to three study groups to receive atropine, ondansetron, or no autonomic-modulating drug. Heart rate, arterial pressure, respiratory rate, and NT-proBNP were recorded before, during, and after anesthesia. Dogs treated with ondansetron maintained stable cardiovascular values throughout the procedure, with no episodes of low heart rate or excessive increases in heart rate. In contrast, atropine induced marked and sustained elevation in heart rate and higher arterial pressures. Concentrations of the cardiac biomarker NT-proBNP increased significantly 48 h after surgery in the atropine group but remained unchanged in the ondansetron group, indicating the absence of additional myocardial stress. These findings suggest that ondansetron may help preserve autonomic balance during anesthesia while minimizing myocardial stress. Ondansetron could represent a useful component of multimodal anesthetic protocols, particularly in dogs in which excessive cardiac stimulation should be avoided. Full article

Neuromuscular diseases are biologically diverse, clinically heterogeneous, and often difficult to diagnose and treat, highlighting the need for computational tools that can help resolve overlapping phenotypes and support timely, mechanism-informed interventions. This narrative review synthesizes recent advances in artificial intelligence (AI) and machine learning applied to neuromuscular diseases across diagnosis, outcome modeling, biomarker development, and therapeutics. AI-based approaches may assist clinical and genetic diagnosis from phenotypic data; however, early phenotype-driven tools have seen limited clinician adoption due to modest accuracy, usability challenges, and poor workflow integration. Electrophysiological studies remain central to diagnosing neuromuscular diseases, and AI shows promise for accurate classification of electrophysiological signals. Predictive models for disease outcome and progression—particularly in amyotrophic lateral sclerosis—are under active investigation, but most remain at an early stage of development and are not yet ready for routine clinical use. Digital biomarkers derived from imaging, gait, voice, and wearable sensors are emerging, with MRI-based quantification of muscle fat replacement representing the most mature and widely accepted application to date. Efforts to apply AI to therapeutic discovery, including drug repurposing and optimization of gene-based therapies, are ongoing but have thus far yielded limited clinical translation. Persistent barriers to broader adoption include disease rarity, data scarcity, heterogeneous acquisition protocols, inconsistent terminology, limited external validation, insufficient model explainability, and lack of seamless integration into clinical workflows. Addressing these challenges is essential to moving AI tools from the laboratory into clinical practice. We conclude with a practical checklist of considerations intended to guide the development and adoption of AI tools in neuromuscular disease care. Full article