Bioinformatic Identification of TP53 Gene Mutation Hotspots in Colorectal Cancer.

Mutations and inactivation of the TP53 gene are frequently observed in various types of malignancies. Precise knowledge of the genetic structure and detection of mutation hotspots are crucial, as these indicate a high probability of developing cancer. The aim of our study was to perform the bioinformatic detection of mutation hotspots in the TP53 gene in patients diagnosed with malignant colon neoplasms using self-developed software (version 1). We compared TP53 gene sequences from 50 healthy individuals with those from 50 patients diagnosed with colorectal carcinoma. Of the 50 samples from cancer patients, the most frequent mutations were observed in exons 5 and 8 (12 mutations per exon) and gene sequences of 12 samples, which differed from those of the 50 samples from healthy individuals. Based on our results, the distribution of mutations in the TP53 gene structure was not even across different exons. By comparing the gene sequences of healthy individuals with those of colon cancer samples, we conclude that structural changes occurring in similar gene regions are not associated with increases in susceptibility to malignancies in every case, namely, that the pathological mechanism is multifactorial.

Motorway Measurement Campaign to Support R&D Activities in the Field of Automated Driving Technologies.

A spectacular measurement campaign was carried out on a real-world motorway stretch of Hungary with the participation of international industrial and academic partners. The measurement resulted in vehicle based and infrastructure based sensor data that will be extremely useful for future automotive R&D activities due to the available ground truth for static and dynamic content. The aim of the measurement campaign was twofold. On the one hand, road geometry was mapped with high precision in order to build Ultra High Definition (UHD) map of the test road. On the other hand, the vehicles-equipped with differential Global Navigation Satellite Systems (GNSS) for ground truth localization-carried out special test scenarios while collecting detailed data using different sensors. All of the test runs were recorded by both vehicles and infrastructure. The paper also showcases application examples to demonstrate the viability of the collected data having access to the ground truth labeling. This data set may support a large variety of solutions, for the test and validation of different kinds of approaches and techniques. As a complementary task, the available 5G network was monitored and tested under different radio conditions to investigate the latency results for different measurement scenarios. A part of the measured data has been shared openly, such that interested automotive and academic parties may use it for their own purposes.

Bowel elastography - a pilot study for developing an elastographic scoring system to evaluate disease activity in pediatric Crohn's disease.

UNLABELLED: The diagnosis and monitoring of Crohn's disease (CD) represents a diagnosis challenge in which imaging plays an important role. AIM: In the present paper we aim to demonstrate the role of sonoelastography (SE), performed in addition to hydrosonography (HS), in the evaluation of CD in children and to propose a scoring system for the appreciation of disease activity. MATERIAL AND METHOD: All the patients included into the study were diagnosed with CD and had underwent HS and SE as part of the imaging evaluation. In selected cases magnetic resonance enterography (MRE) was also performed. SE aspects were classified into three types, each corresponding to a specific bowel wall pattern: normal or remission (type A), inflammation (type B) and fibrosis (type C); this classification represents the basis of the scoring system. For the purpose of statistical analysis each evaluated bowel segment became an individual case. RESULTS: Forty eight bowel segments were evaluated by SE: 21 type A, 20 type B and 7 type C. Statistically significant correlations were found between the intestinal wall HS changes, presence of complications, activity markers and the SE score. The HS assessment of the periintestinal area correlated only partially with SE score, while certain SE scores also proved to be predictors for the presence of complications or for increased values of the disease activity markers. CONCLUSIONS: SE, along with HS, represents a reliable investigation in the correct diagnosis and monitoring of pediatric patients with CD and the SE scoring system may be introduced as a method for the assessment of disease activity.

Diagnostic accuracy of controlled attenuation parameter measured by transient elastography for the non-invasive assessment of liver steatosis: a prospective study.

BACKGROUND AND AIMS: A novel non-invasive tool based on the evaluation of ultrasound attenuation using transient elastography (TE) has been developed, called controlled attenuation parameter (CAP). We aim to establish the histopathological parameters that significantly influence CAP, the cutoff values and their performance in predicting each steatosis grade on a group of biopsied patients with chronic liver diseases (CLD) from Romania. METHODS: We prospectively analyzed 201 consecutive CLD patients who underwent CAP measurements using TE. Steatosis, liver fibrosis and necroinflammatory activity were staged and graded during the pathological analysis of bioptic specimens. Univariate and multivariate regression analyses were applied to identify the variables correlated with CAP values. The diagnostic performance of CAP for steatosis prediction was assessed using an AUC analysis. RESULTS: Among the histopathological factors correlating with CAP, the multivariate analysis found steatosis as the only factor independently influencing CAP values (p < 0.001). Maximal diagnostic accuracy (DA) was obtained for the prediction of ≥ 34-66% (S2) fatty load and of 67-100% (S3) fatty load (82.06%, respectively 81.59%) while, for the prediction of ≥ 11-33% (S1) fatty load, DA reached only 76.11%. The negative predictive value for the exclusion of ≥ S2 and S3 was 93.5% and 98.7%, respectively. AUCs calculated between each two steatosis grades were: 0.772 (S0 vs S1), 0.874 (S0 vs S2), 0.904 (S0 vs S3), 0.659 (S1 vs S2), 0.777 (S1 vs S3), and 0.665 (S2 vs S3). CONCLUSION: Steatosis is the only histopathological factor independently influencing CAP. Maximal DA could be obtained for the prediction of ≥ S2 and S3 (82.06% and 81.59%), while for the prediction of S1, the accuracy reached only 76.11%.