Key steps in exposure techniques for robotic total mesorectal excision (TME).

Aim: The use of robotic surgery is increasing significantly. Specific training is fundamental to achieve high quality and better oncological outcomes. This work defines key exposure techniques in robotic total mesorectal excision (TME).

Effectiveness of the modified Seldinger technique for peripheral central catheter in newborns: a randomized clinical trial.

Objectives: to evaluate the effectiveness of peripheral central catheterization by comparing the modified Seldinger technique and the conventional technique in critically ill newborns.

Methods: randomized unmasked clinical trial conducted in a public children's hospital. Participation of 111 newborns with randomized allocation, 56 in the control group (conventional technique) and 55 in the experimental group (modified Seldinger).

Current landscape of clinical use of ex vivo expanded natural killer cells for cancer therapy.

Natural Killer cells are immune leukocytes required for responses against tumor cells and virus-infected cells. In the last decade, natural killer cells have emerged as promising tools in cancer therapy, and clinical studies on patients treated with natural killer cells have revealed increased rates of disease-free survival. In this article, we review results from the major clinical trials that have used natural killer cells for cancer treatment, including their global distribution.

A New Severe Congenital Neutropenia Syndrome Associated with Autosomal Recessive COPZ1 Mutations.

We have identified a new inherited bone marrow (BM) failure syndrome with severe congenital neutropenia (CN) caused by autosomal recessive mutations in the coatomer protein complex I (COPI) subunit zeta 1 (COPZ1) gene. A stop-codon COPZ1 mutation and a missense mutation were found in three patients from two unrelated families. While two affected siblings with a stop-codon COPZ1 mutation suffered from congenital neutropenia (CN) that involves other hematological lineages, and non-hematological tissues, the patient with a missense COPZ1 mutation had isolated neutropenia.

Modeling and predicting caffeine contamination in surface waters using artificial intelligence and standard statistical methods.

Caffeine, considered an emerging contaminant, serves as an indicator of anthropic influence on water resources. This research employs various modeling techniques, including Artificial Neural Networks (ANN), Random Forest (RF), and more, along with hybrid and ensemble methods, to predict caffeine concentrations (in regression and classification scenarios) using readily available water quality parameters. The results indicate Ensemble-RF as the most effective method for estimating caffeine concentrations, while classification scenarios highlight Ensemble-RF, ANN, and Ensemble-ANN as promising methodologies for predicting contamination levels.