Publications by authors named "A Immanuel"

Article Synopsis
  • This study evaluates the effectiveness of Robot-assisted minimally invasive esophagectomy (RAMIE) for treating esophageal cancer at various centers globally, aiming to pinpoint areas for enhancement in surgical outcomes.
  • Over three time periods (2016-2023), data from 28 centers was analyzed, revealing improvements in textbook outcome rates, lymph node yields, and decreased hospital stays, particularly with McKeown procedures.
  • The results showed varying success rates in surgical outcomes and complications, with a noteworthy decrease in anastomotic leakage rates and hospital stays over time, highlighting advancements in surgical techniques.
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Levan is a fructan polymer with many industrial applications such as the formulation of hydrogels, drug delivery, and wound healing, among others. To this end, metabolic systems engineering is a valuable method to improve the yield of a specific metabolite in a wide range of bacterial and eukaryotic organisms. In this study, we report a systems biology approach integrating genomics data for the model, wherein the metabolic pathway for levan biosynthesis is unpacked.

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Article Synopsis
  • Minimally invasive total gastrectomy (MITG) is an important surgical approach for treating gastric cancer, but there is currently no consensus on the best techniques for key processes like lymphadenectomy and anastomosis creation.
  • An international panel of expert surgeons participated in a study using the Delphi method, which involved multiple rounds of voting to establish consensus on the technical steps of MITG, resulting in 41 key statements after three rounds.
  • The consensus findings, showing high internal consistency, aim to improve surgical quality and outcomes for patients undergoing MITG by providing standardized techniques based on expert agreement.
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DARPP-32 is a key regulator of protein-phosphatase-1 (PP-1) and protein kinase A (PKA), with its function dependent upon its phosphorylation state. We previously identified DKK1 and GRB7 as genes with linked expression using Artificial Neural Network (ANN) analysis; here, we determine protein expression in a large cohort of early-stage breast cancer patients. Low levels of DARPP-32 Threonine-34 phosphorylation and DKK1 expression were significantly associated with poor patient prognosis, while low levels of GRB7 expression were linked to better survival outcomes.

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