presentation of real-life data and compatibility with the data of the studies to daily life.

Although tumors located in the right colon have been considered to be worse in terms of progression-free and overall survival in clinical trials, the results of this study showed that in daily practice, there was no difference between left and right colon localized tumors in progression-free and overall survival. Further, in k-ras wild-type colon cancers, tumor localization predicts the treatment response. This study is important with the presentation of real-life data and compatibility with the data of the studies to daily life.

For years e‑bike (Pedelec) sales have been steadily increasing. Therefore, the incidence of e‑bike-related injuries and deaths has been growing. check details Due to clinical experience, emergency personnel are suspecting that e‑bikers might be injured more severely compared to conventional bicyclists suffering from an accident. This topic has not yet been analyzed for Germany.

Analysis of injury severity and mortality following e‑bike and conventional bicycle accidents in alevelI trauma center in Germany.

Data of patients treated after abicycle accident at the accident and emergency department as well as the clinic for traumatology and orthopedics of the Evangelical Hospital (Evangelisches Krankenhaus) Oldenburg were gathered from 1 March 2017 to 1 March 2019.

In this study 59electric bicycle users (e-bikers) and 164 conventional cyclists were included. The average age of e‑bikers was 62 years compared to 48 years in the group of conventional cyclists. Comorbidities were significantly more frequent in the e‑bike gntional cyclists. Due to older age and comorbidity they form a sensitive trauma subgroup. Based on demographics, an increase of old age, more frail cyclists and a growing incidence of serious e‑bike accidents is to be expected. Preventive measures, such as helmet usage and riding lessons should be introduced, especially in e‑bikers. E‑bikers in the emergency department should be examined and treated with special care and aggressive diagnostics. A low threshold for an initial interdisciplinary assessment (shock room management) is advised.

Clinically significant pancreatic fistula (POPF) has been established as a well-known risk factor for late and severe postpancreatectomy hemorrhage after pancreaticoduodenectomy (PD) (postpancreatectomy pancreatic fistula-associated hemorrhage [PPFH]). Our aim was to assess whether contrast-enhanced CT scan after PD is an effective tool for early prediction of PPFH.

From a prospectively acquired database, all consecutive patients who underwent PD between January 2013 and May 2019 were identified; within this database, all patients who were evaluated, for clinical suspicion of POPF, with at least one contrast-enhanced CT scan examination, were enrolled in this retrospective study. The selected CT findings included perianastomotic fluid collections and air bubbles; pancreaticojejunostomy (PJ) was analyzed in terms of dehiscence and defect.

One hundred seventy-eight out of 953 PD patients (18.7%) suffered from clinically significant POPF; after exclusions, 166 patients were enrolled. Among this subset, 33 and see” approach, to a more proactive one that relies on early anticipation and timely prevention.

• Postpancreatectomy hemorrhage (PPH) is a dramatic, clinically unpredictable occurrence. • After pancreaticoduodenectomy (PD), early identification of posterior pancreaticojejunostomy defect, perianastomotic air bubbles, and retroperitoneal fluid collections enables effective PPH risk stratification by means of a practical CT-based 4-point scoring system. • CT scan after PD allows a paradigm shift in the management PPH, from a conventional “wait and see” approach, to a more proactive one that relies on early anticipation and timely prevention.

The aim of this study was to determine the invasiveness of ground-glass nodules (GGNs) using a 3D multi-task deep learning network.

We propose a novel architecture based on 3D multi-task learning to determine the invasiveness of GGNs. In total, 770 patients with 909 GGNs who underwent lung CT scans were enrolled. The patients were divided into the training (n = 626) and test sets (n = 144). In the test set, invasiveness was classified using deep learning into three categories atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive pulmonary adenocarcinoma (IA). Furthermore, binary classifications (AAH/AIS/MIA vs. IA) were made by two thoracic radiologists and compared with the deep learning results.

In the three-category classification task, the sensitivity, specificity, and accuracy were 65.41%, 82.21%, and 64.9%, respectively. In the binary classification task, the sensitivity, specificity, accuracy, and area under the ROC curve (Avasiveness of GGNs. • The proposed network includes a classification and segmentation branch to learn global and regional features, respectively. • The multi-task model could assist doctors in selecting patients with invasive lesions who need surgery and choosing appropriate surgical methods.An electrochemical sensor capable of quantitative determination of caspase-3 activities was developed. A thiolated peptide whose sequence contained a caspase-3 cleaved site and a cell penetration sequence was preimmobilized onto an electrode. The quantification of caspase-3 was accomplished after cell penetration and the subsequent adsorption of silver nanoparticles (AgNPs). The oxidation current of AgNPs was found to be inversely proportional to the concentration of caspase-3 between 0.02 and 0.2 U/mL. A detection limit of 0.02 U/mL for caspase-3 was achieved due to the large number of positively charged AgNPs adsorbed onto the negatively charged cells. The proof of concept was demonstrated by monitoring the cleavage of surface-confined peptide substrates by caspase-3 in cell lysates. The current sensor could be extended to detect cells by replacing the surface-confined peptide with aptamers that recognize cells. Thus, the use of a cell as a matrix for AgNPs shows excellent potential for constructing electrochemical sensors and provides a useful alternative for sensor development in the future.