Purpose: Literature reviews outline minimally invasive approaches for abdominal diastasis in patients without skin excess. However, few surgeons are trained in endoscopic rectus sheath plication, and no simulated training programs exist for this method. This study aimed to develop and validate a synthetic simulation model for the training of skills in this approach under the Messick validity framework.
Methods: A cross-sectional study was carried out to assess the participants' previous level of laparoscopic/endoscopic skills by a questionnaire. Participants performed an endoscopic plication on the model and their performance was evaluated by one blinded observer using the global rating scale OSATS and a procedure specific checklist (PSC) scale. A 5-level Likert survey was applied to 5 experts and 4 plastic surgeons to assess Face and Content validity.
Results: Fifteen non-experts and 5 experts in abdominal wall endoscopic surgery were recruited. A median OSATS score [25 (range 24-25) vs 14 (range 5-22); p < 0.05 of maximum 25 points] and a median PSC score [11 (range 10-11) vs 8 (range 3-10); p < 0.05 of maximum 11 points] was significantly higher for experts compared with nonexperts. All experts agreed or strongly agreed that the model simulates a real scenario of endoscopic plication of the rectus sheath.
Conclusion: Our simulation model met all validation criteria outlined in the Messick framework, demonstrating its ability to differentiate between experts and non-experts based on their baseline endoscopic surgical skills. This model stands as a valuable tool for evaluating skills in endoscopic rectus sheath plication.
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http://dx.doi.org/10.1007/s10029-024-03059-z | DOI Listing |
Alzheimers Dement
December 2024
University of Pennsylvania, Philadelphia, PA, USA.
Background: Structural and functional heterogeneity in the brains of patients with Alzheimer's disease (AD) leads to diagnostic and prognostic uncertainty and confounds clinical treatment planning. Normative modelling, where individual-level deviations in brain measures from a reference sample are computed to infer personalized effects of disease, allows parsing of disease heterogeneity. In this study, GAN based normative modelling technique quantifies individual level neuroanatomical abnormality thereby facilitating measurement of personalized disease related effects in AD patients.
View Article and Find Full Text PDFACS Catal
January 2025
Institute of Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog-Weg, 1, 8093 Zurich, Switzerland.
Buchwald-Hartwig (BH) aminations are crucial for synthesizing arylamine motifs in numerous bioactive molecules and fine chemicals. While homogeneous palladium complexes can be effective catalysts, their high costs and environmental impact motivate the search for alternative approaches. Heterogeneous palladium single-atom catalysts (SAC) offer promising recoverable alternatives in C-C cross-couplings.
View Article and Find Full Text PDFNPJ Syst Biol Appl
January 2025
Center for Interdisciplinary Digital Sciences (CIDS), Department Information Services and High-Performance Computing (ZIH), Dresden University of Technology, 01062, Dresden, Germany.
Predicting the biological behavior and time to recurrence (TTR) of high-grade diffuse gliomas (HGG) after maximum safe neurosurgical resection and combined radiation and chemotherapy plays a pivotal role in planning clinical follow-up, selecting potentially necessary second-line treatment and improving the quality of life for patients diagnosed with a malignant brain tumor. The current standard-of-care (SoC) for HGG includes follow-up neuroradiological imaging to detect recurrence as early as possible and relies on several clinical, neuropathological, and radiological prognostic factors, which have limited accuracy in predicting TTR. In this study, using an in-silico analysis, we aim to improve predictive power for TTR by considering the role of (i) prognostically relevant information available through diagnostics used in the current SoC, (ii) advanced image-based information not currently part of the standard diagnostic workup, such as tumor-normal tissue interface (edge) features and quantitative data specific to biopsy positions within the tumor, and (iii) information on tumor-associated macrophages.
View Article and Find Full Text PDFSynth Syst Biotechnol
December 2024
Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
, a widely utilized model organism, has seen continuous updates to its genome-scale metabolic model (GEM) to enhance the prediction performance for metabolic engineering and systems biology. This study presents an auxotrophy-based curation of the yeast GEM, enabling facile upgrades to yeast GEMs in future endeavors. We illustrated that the curation bolstered the predictive capability of the yeast GEM particularly in predicting auxotrophs without compromising accuracy in other simulations, and thus could be an effective manner for GEM refinement.
View Article and Find Full Text PDFMethods Mol Biol
January 2025
Department of Biotechnology, College of Natural and Applied Science, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia.
While traditional assay methods face challenges in detecting specific proteins, aptamers, known for their high specificity and affinity, are emerging as a valuable biomarker detection tool. Aurora kinase A (AURKA) plays a role in cell division and influences stem cell reprogramming. In this study, an in silico approach method was conducted for a random ssDNA aptamer sequence selection and its binding with AURKA.
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