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Ex vivo human skin models are valuable tools in skin research due to their physiological relevance. Traditionally, standard cultivation is performed in a cell culture incubator with a defined temperature of 37 °C and a specific atmosphere enriched with CO 2 to ensure media stability. Maintaining the model under these specific conditions limits its flexibility in assessing exposures to which the skin is exposed to in daily life, for example changes in atmospheric compositions. In this study we demonstrated that the foreskin-derived skin model can be successfully cultured at room temperature outside a CO 2 incubator using a CO 2 -independent, serum-free media. Over a cultivation period of three days, the integrity of the tissue and the preservation of immune cells is well maintained, indicating the model’s stability and resilience under the given conditions. Exposing our Medical University of Graz – human Organotypic Skin Explant Culture (MUG-hOSEC) model to cytotoxic and inflammatory stimuli results in responses analyzable within the supernatant. Besides the common analysis of released proteins upon treatment, such as cytokines and enzymes, we have included extracellular vesicle to obtain a more comprehensive picture of cell communication.

Artificial intelligence (AI) is increasingly applied in medical imaging, yet its ability to predict biological sex from pediatric radiographs remains unclear. This study investigates the performance of convolutional neural network (CNN) models in sex classification using a large dataset of pediatric trauma imaging and compares results with human raters. Radiographs from computed and digital radiography systems were processed to normalize grayscale and enhance contrast. The EfficientNet family of CNN models (B0–B7) was trained on this dataset, with attention to balancing the test set by age, sex, and fracture visibility. A subset of 1,000 images was independently assessed by human raters for comparison. AI models achieved a mean precision of 0.731 ± 0.035, recall of 0.718 ± 0.110, accuracy of 0.722 ± 0.032, and F1-score of 0.724 ± 0.050 across all network variants. Performance improved with age, peaking in the 13–18 group. Pelvic X-rays achieved the highest classification metrics. Human raters showed significantly lower agreement. AI can classify biological sex from pediatric radiographs with high accuracy, surpassing human performance. Results vary by age and body region, supporting the potential for AI-assisted imaging in pediatric clinical practice.

Accurate differentiation between skull fractures and sutures is challenging in young children. Traditional diagnostic modalities like computed tomography involve ionizing radiation, while sonography is safer but demands expertise. This study explores the application of artificial intelligence (AI) to improve diagnostic accuracy in this context. A retrospective study utilized sonographic images of 86 children (mean age: 8.5 months) presenting with suspected skull fractures was performed. The AI approach included binary classification and object localization, with tenfold cross-validation applied to 385 images. The study compared AI performance against nine raters with varying expertise, with and without AI assistance. EfficientNet demonstrated superior classification metrics, with the B6 variant achieving the highest F1 score (0.841) and PR AUC (0.913). YOLOv11 models underperformed compared to EfficientNet in detecting fractures and sutures. Raters significantly benefited from AI-assisted diagnostics, with F1 scores improving from 0.749 (unassisted) to 0.833 (assisted). AI models consistently outperformed unassisted human raters. This study presents the first AI model differentiating skull fractures from sutures on pediatric sonographic images, highlighting AI’s potential to enhance diagnostic accuracy. Future efforts should focus on expanding datasets, validating AI models on independent cohorts, and exploring dynamic sonographic data to improve the diagnostic impact.

To evaluate and compare surface doses of a cone beam computed tomography (CBCT) and a multidetector computed tomography (MDCT) device in pediatric ankle and wrist phantoms. Thermoluminescent dosimeters (TLD) were used to measure and compare surface doses between CBCT and MDCT in a left ankle and a right wrist pediatric phantom. In both modalities adapted pediatric dose protocols were utilized to achieve realistic imaging conditions. All measurements were repeated three times to prove test-retest reliability. Additionally, objective and subjective image quality parameters were assessed. Average surface doses were 3.8 ±2.1 mGy for the ankle, and 2.2 ±1.3 mGy for the wrist in CBCT. The corresponding surface doses in optimized MDCT were 4.5 ±1.3 mGy for the ankle, and 3.4 ±0.7 mGy for the wrist. Overall, mean surface dose was significantly lower in CBCT (3.0 ±1.9 mGy vs. 3.9 ±1.2 mGy, p<0.001). Subjectively rated general image quality was not significantly different between the study protocols (p = 0.421), whereas objectively measured image quality parameters were in favor of CBCT (p<0.001). Adapted extremity CBCT imaging protocols have the potential to fall below optimized pediatric ankle and wrist MDCT doses at comparable image qualities. These possible dose savings warrant further development and research in pediatric extremity CBCT applications.

Background: Advancements in artificial intelligence (AI) and machine learning (ML) are set to revolutionize healthcare, particularly in fields like endoscopic surgery that heavily rely on digital imaging. However, to effectively integrate these technologies and drive future innovations, pediatric surgeons need specialized AI/ML skills. This survey evaluated the current level of readiness and educational needs regarding AI/ML among members of the European Society of Pediatric Endoscopic Surgeons (ESPES). Methods: A structured survey was distributed via LimeSurvey to ESPES members via email before and during the 2024 Annual Conference. Responses were collected over four weeks with voluntary, anonymous participation. Quantitative data were analyzed using descriptive statistics. Results: A total of 125 responses were received. Two-thirds (65%) of respondents rated their AI/ML understanding as basic, with only 6% reporting advanced knowledge. Most respondents (86%) had no formal AI/ML training. Some respondents (31%) used AI/ML tools in their practice, mainly for diagnostic imaging, surgical planning, and predictive analytics; 42% of the respondents used these tools weekly. The majority (95%) expressed interest in further AI/ML training, preferring online courses, workshops, and hands-on sessions. Concerns about AI/ML in pediatric surgery were high (85%), especially regarding data bias (98%). Half of respondents (51%) expect AI/ML to play a significant role in advancing robotic surgery, oncology, and minimally invasive techniques. A strong majority (84%) felt that the ESPES should lead AI education in pediatric surgery. Conclusions: This survey presents the ESPES with a unique opportunity to develop a competency map of its membership’s AI/ML skills and develop targeted educational programs, thus positioning the society to take the lead in AI education and the advancement of AI solutions in pediatric endosurgery.

Gut hyperpermeability can be caused by either apoptosis of the intestinal epithelium or altered status, permeability or porosity of tight junctions. This project aims to elucidate these mechanisms in the early phase of sepsis. Eighteen male wild type mice were randomized to two groups. All mice received one single gavage of fluorescein isothiocyanate (FITC) dextran 30 min before intervention. One group (n = 10) underwent cecal ligation and puncture to induce sepsis. The other group (n = 8) was sham operated. Septic animals exhibited significantly increased permeability for FITC 8 h post-operatively. Significantly increased serum interleukin-6, tumor-necrosis-factor-alpha and interleukin-1-beta confirmed sepsis. Septic animals showed significant bowel wall inflammation of ileum and colon samples. PCR revealed significantly increased expression of claudin-2 and decreased expressions of claudin-4, tight-junction-protein-1 and occludin-1 resembling increased permeability of tight junctions. However, these alterations could not be confirmed at the protein level. Light microscopy revealed significant dilatation of intercellular spaces at the basal sections of intestinal epithelial cells (IEC) in septic animals confirmed by increased intercellular spaces at the level of tight junctions and adherens junctions in electron microscopy (TEM). In small angle X-ray scattering no increase in number or size of nanopores could be shown in the bowel wall. HOECHST staining and PCR of ileum samples for apoptosis markers proofed no relevant differences in intestinal epithelial cell apoptosis between the groups. Intestinal hyperpermeability in septic animals was most likely caused by alterations of the intercellular contacts and not by apoptosis or increased size/number of nanopores of intestinal epithelial cells in this murine model of early sepsis.

Purpose The aim of our systematic work was to investigate an artificial intelligence-based prediction of relevant internal injuries of the paediatric knee joint based on initial radiographs and to develop a corresponding AI model. Methods We queried the hospital information systems of two independent sites for pediatric and adolescent patients up to the age of 19 years with a history of recent trauma, who had undergone a radiograph at ap and lateral projections and Magnetic Resonance Imaging (MRI) of the same knee joint within 48 hours. After exclusion of patients due to postoperative situations, tumorous or infectious diseases, missing and invalid radiographs, 873 patients with 1746 total images were included. Each model was assessed for precision, recall, accuracy and the F1 score, revealing variation between model versions in performance metrics. Results The averaged performance across all EfficientNet models achieved a precision of 0.7340, recall of 0.7181, accuracy of 0.7131, and 0.7260. The best per- forming model, EfficientNet-B5, achieved an average precision of 0.7445, recall for 0.7890, and accuracy for 0.7450, respectively. The heat maps revealed significant concentrations of pathologies detected by AI primarily in the femoral and tibial condyles. AI also identified fractures and microtrabecular fractures, suggesting their effectiveness in identifying relevant injuries on (pediatric) knee radiograph.

Cancer therapy is often associated with severe side effects such as drug induced weight loss, also known as chemotherapy-induced cachexia. The aim of this study was to investigate the effects of a multispecies probiotic (OMNi-BiOTiC® 10 AAD) in a chemotherapy mouse model. A total of 24 male BALB/c mice were gavage-fed with the probiotic formulation or water, once a day for 3 weeks. In the third week, the mice received intraperitoneal cyclophosphamide. At euthanasia, the organs were dissected, and serum was sampled for cytokine analysis. Tight junction components, myosin light chain kinase, mucins, and apoptosis markers were detected in the ileum and colon using histological analyses and qRT-PCR. Lipolysis was analyzed by enzymatic activity assay, Western blotting analyses, and qRT-PCR in WAT. The fecal microbiome was measured with 16S-rRNA gene sequencing from stool samples, and fecal volatile organic compounds analysis was performed using gas chromatography/mass spectrometry. The probiotic-fed mice exhibited significantly less body weight loss and adipose tissue wasting associated with a reduced CGI58 mediated lipolysis. They showed significantly fewer pro-inflammatory cytokines and lower gut permeability compared to animals fed without the probiotic. The colons of the probiotic-fed animals showed lower inflammation scores and less goblet cell loss. qRT-PCR revealed no differences in regards to tight junction components, mucins, or apoptosis markers. No differences in microbiome alpha diversity, but differences in beta diversity, were observed between the treatment groups. Taxonomic analysis showed that the probiotic group had a lower relative abundance of Odoribacter and Ruminococcus-UCG014 and a higher abundance of Desulfovibrio. VOC analysis yielded no significant differences. The results of this study indicate that oral administration of the multispecies probiotic OMNi-BiOTiC® 10 AAD could mitigate cyclophosphamide-induced chemotherapy side effects.

Proton pump inhibitors (PPIs) are the standard therapy for gastroesophageal reflux disease. In adults, PPI treatment is associated with infections (CDI). In contrast to adults the microbiome of infants develops from sterility at birth toward an adult-like profile in the first years of life. The effect of PPIs on this developing microbiome has never been studied. The aim of the present study was to determine the effect of oral PPIs on the fecal microbiome in infants with gastroesophageal reflux disease (GERD). In this prospective longitudinal study 12 infants with proven GERD received oral PPIs for a mean period of 18 weeks (range 8-44). Stool samples were collected before (\"before PPI\") and 4 weeks after initiation of PPI therapy (\"on PPI\"). A third sample was obtained 4 weeks after PPI discontinuation (\"after PPI\"). The fecal microbiome was determined by NGS based 16S rDNA sequencing. This trial was registered with clinicaltrials.gov (NCT02359604). In a comparison of \"before PPI\" and \"on PPI\" neither α- nor β-diversity changed significantly. On the genus level, however, the relative abundances showed a decrease of and and an increase of . After PPI therapy there was a significant increase of α- and β-diversity. Additionally, the relative abundances of the phyla Firmicutes, Bacteroidetes, and Proteobacteria were significantly changed and correlated to patients' age and the introduction of solid foods. PPI treatment has only minor effects on the fecal microbiome. After discontinuation of PPI treatment the fecal microbiome correlated to patients' age and nutrition.

The aim of this study was to assess whether adolescents following anorectal malformation repair have a decreased cardiorespiratory performance capacity and impaired motor skills. All eligible children treated for ARMs between 2000 and 2014 were invited to participate in a prospective study consisting of a clinical examination, evaluation of Bowel function and Quality of Life, spirometry, spiroergometry and assessment of the motor activity. The results were compared to a healthy age- and sex-matched control group. There was no statistically significant difference in height, weight, BMI, muscle mass or body fat percentage between the study and the control group. Nine out of 18 patients (50%) had an excellent functional outcome with a normal Bowel Function Score. Spirometry revealed no significant differences between ARM patients and controls, four patients showed a ventilation disorder. Spiroergometry revealed a significantly lower relative performance capacity and the overall rating of the motor activity test showed significantly decreased grades in ARM patients. ARM patients were affected by an impaired cardiopulmonary function and decreased motor abilities. Long-term examinations consisting of routine locomotor function evaluation and spiroergometry are advisable to detect impaired cardiopulmonary function and to prevent a progression of associated complications and related impaired quality of life.