Tissue Stromal Vascular Fraction Improves Early Scar Healing:A Prospective Randomized Multicenter Clinical Trial

Background Wound healing and scar formation depends on a plethora of factors. Given the impact of abnormal scar formation, interventions aimed to improve scar formation would be most advantageous. The tissue stromal vascular fraction (tSVF) of adipose tissue is composed of a heterogenous mixture of cells embedded in extracellular matrix. It contains growth factors and cytokines involved in wound-healing processes, eg, parenchymal proliferation, inflammation, angiogenesis, and matrix remodeling.Objectives The aim of this study was to investigate the hypothesis that tSVF reduces postsurgical scar formation.Methods This prospective, double-blind, placebo-controlled, randomized trial was conducted between 2016 and 2020. Forty mammoplasty patients were enrolled and followed for 1 year. At the end of the mammoplasty procedure, all patients received tSVF in the lateral 5 cm of the horizontal scar of 1 breast and a placebo injection in the contralateral breast to serve as an intrapatient control. Primary outcome was scar quality measure by the Patient and Observer Scar Assessment Scale (POSAS). Secondary outcomes were obtained from photographic evaluation and histologic analysis of scar tissue samples.Results Thirty-four of 40 patients completed follow-up. At 6 months postoperation, injection of tSVF had significantly improved postoperative scar appearance as assessed by the POSAS questionnaire. No difference was observed at 12 months postoperation. No improvement was seen based on the evaluation of photographs and histologic analysis of postoperative scars between both groups.Conclusions Injection of tSVF resulted in improved wound healing and reduced scar formation at 6 months postoperation, without any noticeable advantageous effects seen at 12 months.</p

A Systematic Evaluation of Cost-Saving Dosing Regimens for Therapeutic Antibodies and Antibody-Drug Conjugates for the Treatment of Lung Cancer

Background: Expensive novel anticancer drugs put a serious strain on healthcare budgets, and the associated drug expenses limit access to life-saving treatments worldwide. Objective: We aimed to develop alternative dosing regimens to reduce drug expenses. Methods: We developed alternative dosing regimens for the following monoclonal antibodies used for the treatment of lung cancer: amivantamab, atezolizumab, bevacizumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, and ramucirumab; and for the antibody-drug conjugate trastuzumab deruxtecan. The alternative dosing regimens were developed by means of modeling and simulation based on the population pharmacokinetic models developed by the license holders. They were based on weight bands and the administration of complete vials to limit drug wastage. The resulting dosing regimens were developed to comply with criteria used by regulatory authorities for in silico dose development. Results: We found that alternative dosing regimens could result in cost savings that range from 11 to 28%, and lead to equivalent pharmacokinetic exposure with no relevant increases in variability in exposure. Conclusions: Dosing regimens based on weight bands and the use of complete vials to reduce drug wastage result in less expenses while maintaining equivalent exposure. The level of evidence of our proposal is the same as accepted by regulatory authorities for the approval of alternative dosing regimens of other monoclonal antibodies in oncology. The proposed alternative dosing regimens can, therefore, be directly implemented in clinical practice.</p

Rank–rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures

Comparing independent high-throughput gene-expression experiments can generate hypotheses about which gene-expression programs are shared between particular biological processes. Current techniques to compare expression profiles typically involve choosing a fixed differential expression threshold to summarize results, potentially reducing sensitivity to small but concordant changes. We present a threshold-free algorithm called Rank–rank Hypergeometric Overlap (RRHO). This algorithm steps through two gene lists ranked by the degree of differential expression observed in two profiling experiments, successively measuring the statistical significance of the number of overlapping genes. The output is a graphical map that shows the strength, pattern and bounds of correlation between two expression profiles. To demonstrate RRHO sensitivity and dynamic range, we identified shared expression networks in cancer microarray profiles driving tumor progression, stem cell properties and response to targeted kinase inhibition. We demonstrate how RRHO can be used to determine which model system or drug treatment best reflects a particular biological or disease response. The threshold-free and graphical aspects of RRHO complement other rank-based approaches such as Gene Set Enrichment Analysis (GSEA), for which RRHO is a 2D analog. Rank–rank overlap analysis is a sensitive, robust and web-accessible method for detecting and visualizing overlap trends between two complete, continuous gene-expression profiles. A web-based implementation of RRHO can be accessed at http://systems.crump.ucla.edu/rankrank/

Colonia Apollinaris Augusta emerita Raurica : Katalog einer Ausstellung zur Geschichte der Ausgrabungen in Augst

Bei den im Katalog vorgestellten 211 Objektnummern handelt es sich um Handschriften und Druckwerke, die sich auf Augusta Raurica beziehen. Die Texte wurden ursprünglich nicht für einen Katalog zusammengestellt und redigiert, sondern als eine wohl ausführliche, doch nur vorübergehende Vitrinenbeschriftung