Deep-learning-based semantic segmentation of autonomic nerves from laparoscopic images of colorectal surgery: an experimental pilot study.

Background: The preservation of autonomic nerves is the most important factor in maintaining genitourinary function in colorectal surgery; however, these nerves are not clearly recognisable, and their identification is strongly affected by the surgical ability. Therefore, this study aimed to develop a deep learning model for the semantic segmentation of autonomic nerves during laparoscopic colorectal surgery and to experimentally verify the model through intraoperative use and pathological examination.

Materials And Methods: The annotation data set comprised videos of laparoscopic colorectal surgery.

Development and Validation of a Model for Laparoscopic Colorectal Surgical Instrument Recognition Using Convolutional Neural Network-Based Instance Segmentation and Videos of Laparoscopic Procedures.

Importance: Deep learning-based automatic surgical instrument recognition is an indispensable technology for surgical research and development. However, pixel-level recognition with high accuracy is required to make it suitable for surgical automation.

Objective: To develop a deep learning model that can simultaneously recognize 8 types of surgical instruments frequently used in laparoscopic colorectal operations and evaluate its recognition performance.

Novel complex class 1 integron bearing an ISCR1 element in an Escherichia coli isolate carrying the blaCTX-M-14 gene.

This work identifies an ISCR1-related bla(CTX-M-14) gene, which has never been reported before, from a clinical isolate of Escherichia coli. The bla(CTX-M-14) gene was preceded by an ISCR1 element that was followed by a class 1 integron containing three different insert gene cassettes, i.e.

Genetic and biochemical characterization of GES-5, an extended-spectrum class A beta-lactamase from Klebsiella pneumoniae.

The present study was conducted to characterize a new class 1 integron containing the blaGES-5 gene cassette in Klebsiella pneumoniae clinical isolate CHAK36 and measure the kinetic parameters of GES-5 beta-lactamase. Long-range polymerase chain reactions (PCRs) and sequence analysis were performed to identify and analyze the blaGES-5 gene cassette-containing integrons. Kinetic parameters were determined from purified GES-5.

Detection of extended-spectrum beta-lactamases by using boronic acid as an AmpC beta-lactamase inhibitor in clinical isolates of Klebsiella spp. and Escherichia coli.

We evaluated highly sensitive methods using boronic acid (BA) to detect extended-spectrum beta-lactamase (ESBL) production. A total of 182 clinical isolates of Klebsiella spp. (n = 118) and Escherichia coli (n = 64) were analyzed: 62 harbored only ESBLs, 80 harbored both ESBLs and plasmid-mediated AmpC beta-lactamases (pAmpCs), and 40 harbored only pAmpCs.

Emergence of CTX-M-12 extended-spectrum beta-lactamase-producing Escherichia coli in Korea.

Objectives: To characterize CTX-M-12 extended-spectrum beta-lactamase (ESBL) produced by clinical Escherichia coli isolates and to investigate its genetic environment.

Methods: Antimicrobial susceptibilities were determined by disc diffusion and agar dilution methods, and the double-disc synergy test was carried out. Detection of genes encoding class A beta-lactamases was performed by PCR amplification, and the genetic environments of the bla(CTX-M-12) genes were investigated by PCR and sequencing of the regions surrounding the genes.