Giant Mesenteric Lipoma As an Unusual Cause of Abdominal Pain: A Case Report and a Review of the Literature

We report a rare case of giant mesenteric lipoma presenting with colicky abdominal pain. A 29-yr-old woman underwent laparoscopic resection for a giant mesenteric lipoma causing compression of the ileal loop. The resected ileal segment was encased by a giant fatty tissue, and normal mucosal fold patterns of the resected ileum were effaced by the mass. Microscopically, the mass was characterized by homogenous mature adipose tissue without cellular atypia, which was compatible with the diagnosis of a mesenteric lipoma. Despite the benign nature of this tumor, total excision with or without the affected intestinal loop should be considered if intestinal symptoms such as abdominal pain are present

RAFT dispersion polymerization : a method to tune the morphology of thymine-containing self-assemblies

YesThe synthesis and self-assembly of thymine-containing polymers were performed using RAFT dispersion polymerization. A combination of microscopy and scattering techniques was used to analyze the resultant complex morphologies. The primary observation from this study is that the obtained aggregates induced during the polymerization were well-defined despite the constituent copolymers possessing broad dispersities. Moreover, a variety of parameters, including the choice of polymerization solvent, the degree of polymerization of both blocks and the presence of an adenine-containing mediator, were observed to affect the resultant size and shape of the assembly.University of Warwick, National Science Foundation (U.S.) (NSF), Engineering and Physical Sciences Research Council (EPSRC

Institutional investors and corporate governance

We provide a comprehensive overview of the role of institutional investors in corporate governance with three main components. First, we establish new stylized facts documenting the evolution and importance of institutional ownership. Second, we provide a detailed characterization of key aspects of the legal and regulatory setting within which institutional investors govern portfolio firms. Third, we synthesize the evolving response of the recent theoretical and empirical academic literature in finance to the emergence of institutional investors in corporate governance. We highlight how the defining aspect of institutional investors – the fact that they are financial intermediaries – differentiates them in their governance role from standard principal blockholders. Further, not all institutional investors are identical, and we pay close attention to heterogeneity amongst institutional investors as blockholders

Use of complementary nucleobase-containing synthetic polymers to prepare complex self-assembled morphologies in water

YesAmphiphilic nucleobase-containing block copolymers with poly(oligo(ethylene glycol) methyl ether methacrylate) as the hydrophilic block and nucleobase-containing blocks as the hydrophobic segments were successfully synthesized using RAFT polymerization and then self-assembled via solvent switch in aqueous solutions. Effects of the common solvent on the resultant morphologies of the adenine (A) and thymine (T) homopolymers, and A/T copolymer blocks and blends were investigated. These studies highlighted that depending on the identity of the common solvent, DMF or DMSO, spherical micelles or bicontinuous micelles were obtained. We propose that this is due to the presence of A–T interactions playing a key role in the morphology and stability of the resultant nanoparticles, which resulted in a distinct system compared to individual adenine or thymine polymers. Finally, the effects of annealing on the self-assemblies were explored. It was found that annealing could lead to better-defined spherical micelles and induce a morphology transition from bicontinuous micelles to onion-like vesicles, which was considered to occur due to a structural rearrangement of complementary nucleobase interactions resulting from the annealing process.European Research Council (ERC), University of Warwick, Engineering and Physical Sciences Research Council (EPSRC), National Science Foundation (U.S.) (NSF

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

Machine Learning Model for Lymph Node Metastasis Prediction in Breast Cancer Using Random Forest Algorithm and Mitochondrial Metabolism Hub Genes

Breast cancer metastasis can have a fatal outcome, with the prediction of metastasis being critical for establishing effective treatment strategies. RNA-sequencing (RNA-seq) is a good tool for identifying genes that promote and support metastasis development. The hub gene analysis method is a bioinformatics method that can effectively analyze RNA sequencing results. This can be used to specify the set of genes most relevant to the function of the cell involved in metastasis. Herein, a new machine learning model based on RNA-seq data using the random forest algorithm and hub genes to estimate the accuracy of breast cancer metastasis prediction. Single-cell breast cancer samples (56 metastatic and 38 non-metastatic samples) were obtained from the Gene Expression Omnibus database, and the Weighted Gene Correlation Network Analysis package was used for the selection of gene modules and hub genes (function in mitochondrial metabolism). A machine learning prediction model using the hub gene set was devised and its accuracy was evaluated. A prediction model comprising 54-functional-gene modules and the hub gene set (NDUFA9, NDUFB5, and NDUFB3) showed an accuracy of 0.769 ± 0.02, 0.782 ± 0.012, and 0.945 ± 0.016, respectively. The test accuracy of the hub gene set was over 93% and that of the prediction model with random forest and hub genes was over 91%. A breast cancer metastasis dataset from The Cancer Genome Atlas was used for external validation, showing an accuracy of over 91%. The hub gene assay can be used to predict breast cancer metastasis by machine learning