An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen\u27s self-organizing feature map, learning vector quantization, and a back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system

An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen\u27s self-organizing feature map, learning vector quantization, and a back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system

Image directed lymph node sampling for lung cancer staging

http://deepblue.lib.umich.edu/bitstream/2027.42/117374/1/40644_2014_Article_102.pd

Minimally invasive transhiatal esophagectomy

While traditionally performed through an open approach, the role of minimally invasive technologies has evolved in its application to esophageal resection. Esophagectomy is associated with significant morbidity, which has led to interest in developing minimally invasive esophagectomy (e.g., laparoscopic/thoracoscopic approaches) to address this issue. As a result, the role of minimally invasive approaches for esophageal resection has evolved, with a growing body of literature describing these techniques. Minimally invasive approaches have been applied to transhiatal esophagectomy, with application of both laparoscopic and robotic-assisted techniques. Although minimally invasive esophagectomy approaches are well-described in the literature for esophageal malignancies, the efficacy of robotic-assisted esophagectomy is not as well established. Since the initial reports of this application, the adoption of this technology for esophagectomy has continued to expand. As the role for robotic techniques has expanded across esophageal resection approaches, a more defined application to minimally invasive transhiatal esophagectomy (MI-THE) has developed. Our group has sought to adapt laparoscopic and robotic techniques to the transhiatal approach for both malignant and end-stage benign esophageal disease. With growing MI-THE experience, operative technique has been further refined. This report describes the operative technique and best practices for robotic-assisted transhiatal esophagectomy with cervical esophagogastric anastomosis, including preoperative preparation, operative technique, postoperative care, and perioperative outcomes

Characterizing isoform switching events in esophageal adenocarcinoma

Isoform switching events with predicted functional consequences are common in many cancers, but characterization of switching events in esophageal adenocarcinoma (EAC) is lacking. Next-generation sequencing was used to detect levels of RNA transcripts and identify specific isoforms in treatment- naïve esophageal tissues ranging from premalignant Barrett’s esophagus (BE), BE with low- or high-grade dysplasia (BE.LGD, BE.HGD), and EAC. Samples were stratified by histopathology and TP53 mutation status, identifying significant isoform switching events with predicted functional consequences. Comparing BE.LGD with BE.HGD, a histopathology linked to cancer progression, isoform switching events were identified in 75 genes including KRAS, RNF128, and WRAP53. Stratification based on TP53 status increased the number of significant isoform switches to 135, suggesting switching events affect cellular functions based on TP53 mutation and tissue histopathology. Analysis of isoforms agnostic, exclusive, and shared with mutant TP53 revealed unique signatures including demethylation, lipid and retinoic acid metabolism, and glucuronidation, respectively. Nearly half of isoform switching events were identified without significant gene-level expression changes. Importantly, two TP53-interacting isoforms, RNF128 and WRAP53, were significantly linked to patient survival. Thus, analysis of isoform switching events may provide new insight for the identification of prognostic markers and inform new potential therapeutic targets for EAC

Characterizing isoform switching events in esophageal adenocarcinoma

Isoform switching events with predicted functional consequences are common in many cancers, but characterization of switching events in esophageal adenocarcinoma (EAC) is lacking. Next-generation sequencing was used to detect levels of RNA transcripts and identify specific isoforms in treatment- naïve esophageal tissues ranging from premalignant Barrett’s esophagus (BE), BE with low- or high-grade dysplasia (BE.LGD, BE.HGD), and EAC. Samples were stratified by histopathology and TP53 mutation status, identifying significant isoform switching events with predicted functional consequences. Comparing BE.LGD with BE.HGD, a histopathology linked to cancer progression, isoform switching events were identified in 75 genes including KRAS, RNF128, and WRAP53. Stratification based on TP53 status increased the number of significant isoform switches to 135, suggesting switching events affect cellular functions based on TP53 mutation and tissue histopathology. Analysis of isoforms agnostic, exclusive, and shared with mutant TP53 revealed unique signatures including demethylation, lipid and retinoic acid metabolism, and glucuronidation, respectively. Nearly half of isoform switching events were identified without significant gene-level expression changes. Importantly, two TP53-interacting isoforms, RNF128 and WRAP53, were significantly linked to patient survival. Thus, analysis of isoform switching events may provide new insight for the identification of prognostic markers and inform new potential therapeutic targets for EAC

Exome and whole genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity

The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. With a five-year survival rate of 15%, identification of new therapeutic targets for EAC is greatly important. We analyze the mutation spectra from whole exome sequencing of 149 EAC tumors/normal pairs, 15 of which have also been subjected to whole genome sequencing. We identify a mutational signature defined by a high prevalence of A to C transversions at AA dinucleotides. Statistical analysis of exome data identified significantly mutated 26 genes. Of these genes, four (TP53, CDKN2A, SMAD4, and PIK3CA) have been previously implicated in EAC. The novel significantly mutated genes include chromatin modifying factors and candidate contributors: SPG20, TLR4, ELMO1, and DOCK2. Functional analyses of EAC-derived mutations in ELMO1 reveal increased cellular invasion. Therefore, we suggest a new hypothesis about the potential activation of the RAC1 pathway to be a contributor to EAC tumorigenesis