Laparoscopic Toupet-Sleeve gastrectomy in morbid obese patients with preoperative gastro-esophageal reflux: a 4-year follow-up cohort study.

Aim: To assess the 4-year outcomes after Toupet-Sleeve (TS) gastrectomy in morbid obese patients with concomitant preoperative gastro-esophageal reflux disease (GERD).

Material And Methods: The study group consisted of 19 consecutive patients operated on between August 2017 and February 2019. There were 5 men and 14 women with a mean body mass index (BMI) of 43 ± 5 kg/m and a mean age of 42 ± 15 years.

Short-course subcutaneous treatment with PQ Grass strongly improves symptom and medication scores in grass allergy.

Background: A modified grass allergen subcutaneous immunotherapy (SCIT) product with MicroCrystalline Tyrosine and monophosphoryl lipid-A as an adjuvant system (Grass MATA MPL [PQ Grass]) is being developed as short-course treatment of grass-pollen allergic rhinitis (SAR) and/or rhinoconjunctivitis. We sought to evaluate the combined symptom and medication score (CSMS) of the optimized cumulative dose of 27,600 standardized units (SU) PQ Grass in a field setting prior to embarking on a pivotal Phase III trial.

Methods: In this exploratory, randomized, double-blind, placebo-controlled trial subjects were enrolled across 14 sites (Germany and the United States of America).

A machine learning-based multiscale model to predict bone formation in scaffolds.

Computational modeling methods combined with non-invasive imaging technologies have exhibited great potential and unique opportunities to model new bone formation in scaffold tissue engineering, offering an effective alternate and viable complement to laborious and time-consuming in vivo studies. However, existing numerical approaches are still highly demanding computationally in such multiscale problems. To tackle this challenge, we propose a machine learning (ML)-based approach to predict bone ingrowth outcomes in bulk tissue scaffolds.