Our protocol enabled qualitative and quantitative analyses of CBN in samples of a bottom sediment core’ having been obtained from a small lake in Northern India, where intense local retting of hemp was suggested in the past. The analyses showed a maximum CBN content in pollen zone 4 covering a depth range of 262-209 cm, dating from approximately 480 BCE to 1050 CE. These findings correlate with existing records of Cannabis-type pollen. Thus, the method we propose is a helpful tool to track ancient hemp retting activities. Graphical Abstract.Considering that Quist et al. first described the acute idiopathic scrotal edema (AISE) already in 1956, there are not many studies published in literature concerning the etiology, the development, and the progress of the disease since then. According to the literature the incidence of AISE is about 20%. Although it is an important differential diagnosis for acute scrotum, it remains extensively unknown. Therefore, AISE should be kept in mind by urologists, pediatric surgeons and pediatricians to avoid needless surgery or antibiotic therapy.BACKGROUND Surgical disciplines are fighting with a critical and escalating shortage of recruits. Potential young professionals belong to the Generation Y, a generation that is constantly challenging senior consultants and human resources departments. The aim of this study was the analysis of various measures of personnel acquisition with respect to motivating factors of young medical students. MATERIAL AND METHODS A survey was carried out among students of the first and ninth semesters of a medical faculty on individual motivating factors, aspiration for medical specialist training and professional experience gained in surgery. RESULTS Results from 179 out of 269 medical students were available for analysis (66.5% response rate). The interest in a specialist training in surgery was high in the first semester of medical school (21%) but dropped noticeably up to the ninth semester (13%, p = 0.23). Medical students in the ninth semester, who favored professional advancement and appreciation over flexible working hours showed a significantly higher interest in a specialist training in surgery (p = 0.022). Surgical experience gained was valued with an average grade of 2+ (1 = best, 6 = worst). CONCLUSION The high fundamental interest in a surgical residency during the beginning of medical studies is a competitive advantage of surgical disciplines; however, the diverse recruiting efforts are mainly aimed at later stages of studies. Timely hands-on courses in the core working area of surgery, the operating theatre, have proven to be particularly successful for the long-term acquisition and retention of junior doctors.BACKGROUND Long-term drug users regularly present with deep inguinal vascular-associated abscesses due to continued drug injections utilizing superficial veins. selleck compound The treatment of these complications continues to be a major medical challenge. So far no uniform treatment regimens have been described in the literature. OBJECTIVE What are the treatment strategies and outcomes of injection-associated inguinal perivascular abscesses in drug addicts? MATERIAL AND METHODS All drug users treated at the Augsburg University Hospital in the period between 1 January 2004 and 31 May 2019 were retrospectively reviewed and compared with the currently available literature. RESULTS In this study 37 cases (male = 25, female = 12) could be included in the data collection after implementation of the inclusion criteria. The median age in the investigated patient population was 34.3 years. The 30-day mortality was 2.7% (1/37). The amputation rate was 2.8%. In the investigated collective 13 patients had arterial involvement, in 5 cases a ligature of arteries was primarily used and in another 5 cases a reconstruction using an autologous conduit graft was primarily performed. In another 3 cases an obturator bypass (1/3) was placed and a patch plasty (2/3). The patency rate after arterial reconstruction was 87.5% with a mean follow-up of 421 days. The overall complication rate was 51.4%. CONCLUSION For vascular involvement an approach appropriate for the situation is meaningful. In addition to the elimination of complicated septic venous thromboses, the correction of arterial hemorrhages using autologous reconstruction measures seems promising.New digital technologies will also gain in importance in vascular surgery. There is a wide field of potential applications. Simulation-based training of endovascular procedures can lead to improvement in procedure-specific parameters and reduce fluoroscopy and procedural times. The use of intraoperative image-guided navigation and robotics also enables a reduction of the radiation dose. Artificial intelligence can be used for risk stratification and individualization of treatment approaches. Health apps can be used to improve the follow-up care of patients.PURPOSE Volumetric assessment of meningiomas represents a valuable tool for treatment planning and evaluation of tumor growth as it enables a more precise assessment of tumor size than conventional diameter methods. This study established a dedicated meningioma deep learning model based on routine magnetic resonance imaging (MRI) data and evaluated its performance for automated tumor segmentation. METHODS The MRI datasets included T1-weighted/T2-weighted, T1-weighted contrast-enhanced (T1CE) and FLAIR of 126 patients with intracranial meningiomas (grade I 97, grade II 29). For automated segmentation, an established deep learning model architecture (3D deep convolutional neural network, DeepMedic, BioMedIA) operating on all four MR sequences was used. Segmentation included the following two components (i) contrast-enhancing tumor volume in T1CE and (ii) total lesion volume (union of lesion volume in T1CE and FLAIR, including solid tumor parts and surrounding edema). Preprocessing of imaging data included registration, skull stripping, resampling, and normalization. After training of the deep learning model using manual segmentations by 2 independent readers from 70 patients (training group), the algorithm was evaluated on 56 patients (validation group) by comparing automated to ground truth manual segmentations, which were performed by 2 experienced readers in consensus. RESULTS Of the 56 meningiomas in the validation group 55 were detected by the deep learning model. In these patients the comparison of the deep learning model and manual segmentations revealed average dice coefficients of 0.91 ± 0.08 for contrast-enhancing tumor volume and 0.82 ± 0.12 for total lesion volume. In the training group, interreader variabilities of the 2 manual readers were 0.92 ± 0.07 for contrast-enhancing tumor and 0.88 ± 0.05 for total lesion volume. CONCLUSION Deep learning-based automated segmentation yielded high segmentation accuracy, comparable to manual interreader variability.