Contemporary update of cancer control after radical prostatectomy in the UK

Despite a significant increase of the number of radical prostatectomies (RPs) to treat organ-confined prostate cancer, there is very limited documentation of its oncological outcome in the UK. Pathological stage distribution and changes of outcome have not been audited on a consistent basis. We present the results of a multicentre review of postoperative predictive variables and prostatic-specific antigen (PSA) recurrence after RP for clinically organ-confined disease. In all, 854 patient's notes were audited for staging parameters and follow-up data obtained. Patients with neoadjuvant and adjuvant treatment as well as patients with incomplete data and follow-up were excluded. Median follow-up was 52 months for the remaining 705 patients. The median PSA was 10 ng ml−1. A large migration towards lower PSA and stage was seen. This translated into improved PSA survival rates. Overall Kaplan–Meier PSA recurrence-free survival probability at 1, 3, 5 and 8 years was 0.83, 0.69, 0.60 and 0.48, respectively. The 5-year PSA recurrence-free survival probability for PSA ranges 20 ng ml−1 was 0.82, 0.73, 0.59 and 0.20, respectively (log rank, P<0.0001). PSA recurrence-free survival probabilities for pathological Gleason grade 2–4, 5 and 6, 7 and 8–10 at 5 years were 0.84, 0.66, 0.55 and 0.21, respectively (log rank, P<0.0001). Similarly, 5-year PSA recurrence-free survival probabilities for pathological stages T2a, T2b, T3a, T3b and T4 were 0.82, 0.78, 0.48, 0.23 and 0.12, respectively (log rank, P=0.0012). Oncological outcome after RP has improved over time in the UK. PSA recurrence-free survival estimates are less optimistic compared to quoted survival figures in the literature. Survival figures based on pathological stage and Gleason grade may serve to counsel patients postoperatively and to stratify patients better for adjuvant treatment

Leadership of highly creative people in highly creative fields: A historiometric study of scientific leaders

In recent years there has been a marked increase in the study of the influence of leadership on creativity, and the effects of this relationship on organizational performance. While a number of explanations have been broached with regard to the positive effects of leadership on creativity, many of these studies propose different, and often contradictory, methods for leaders to achieve these positive effects on creativity within their organizations and work groups. Additionally, little work has been done examining the effects of leadership on highly creative people in fields requiring creativity. The purpose of this study is to examine two existing leadership theories with regard to their viability as models to explain creative performance of eminent scientists. Eminent scientists represent a population of leaders of highly creative individuals in a field that values the production of innovative ideas and products as a marker of performance. Ninety-three excerpts from the biographies of scientists were content coded for leader behaviors and performance criteria. The results of this analysis indicate that a model based on strategic planning and product championing may serve to explain the positive effects of leadership on creativity in a highly creative population

Development of a commercially feasible method of producting dehydrated berries and cherries

The end of the European phase of the war lessens somewhat the demands on the military for food in one theater of operations. The successful prosecution of the Pacific phase of the war and the needs of the liberated peoples of the world, plus the civilian requirements of the allied nations, make imperative increased rather than reduced food production. The problems of adequate shipping space and tremendous transport distances accentuate more than ever the need tor dehydrated foods. Thus the dehydration of cherries and berries, especially in the Pacific Northwest, remains important as an industry. The figures on the production of sweet and red sour cherries, as well as berries of various types, show that the western states, and especially Oregon and Washington, can grow the raw products for a greatly expanded dehydration industry

EXPLORING THE TEST-RETEST RELIABILITY OF MARKERLESS MOTION CAPTURE FOR OUTDOOR WALKING

BACKGROUND: Markerless motion capture is a rapidly advancing technology and has been tested indoors and proven reliable. However, there are no studies that have tested a portable markerless motion capture system outdoors and out of the lab setting. The purpose of this study is to determine test-retest reliability of knee kinematics using a portable markerless motion capture system during a walking test in healthy adults. METHODS: Twenty-one participants (6M, 15F, age=23.11 ± 1.89 years, height = 167.17 ± 7.89 cm, mass = 69.85 ± 23.11 kg) performed two walking tests each separated by a minimum of five days. Participants were instructed to walk at their comfortable walking pace, which was recorded at the beginning of their trials. Eight trials were recorded within 5% of their recorded walking pace. Videos were recorded using 8 video cameras (OptiTrack Prime Color, Corvallis, OR. Natural Point Inc.) at 60hz. After collection, video data was exported and reduced in a markerless motion capture software (Theia3D, Kingston, Ontario). The maximum and minimum knee flexion and extension and knee abduction and adduction angles during the first 50% of stance phase were collected for data analysis. Test-retest reliability was calculated with intraclass correlation coefficients (ICCs) between testing time 1 and time 2. Reliability was interpreted as excellent (\u3e0.90), good (0.90-0.75), moderate (0.75-0.50), and poor (\u3c0.50). Precision was calculated with the standard error of measurement (SEM). RESULTS: ICC and SEM demonstrated good reliability and precision for peak knee flexion (ICC=0.859 (0.722,0.931), SEM=1.84). Reliability and precision were moderate for knee extension (ICC=0.732 (0.506, 0.864), SEM=1.23). Reliability was moderate for knee abduction (ICC=0.547 (0.547,0.757), SEM=1.47) and knee adduction (ICC=0.576 (0.273, 0.775), SEM=1.62). CONCLUSION: Our results suggest that sagittal plane movements like knee extension and flexion demonstrate good to moderate reliability, however, they can still improve. Movements in the frontal plane are less reliable than the sagittal plane. Possible solutions to improve reliability would include more cameras or positioning in a different pattern enabling a better view of the knee joint. Artificial Intelligence (AI) may need improvements, and future research should continue to investigate reliability and precision as improvements are made

Improving Generalizability of PET DL Algorithms: List-Mode Reconstructions Improve DOTATATE PET Hepatic Lesion Detection Performance

Deep learning (DL) algorithms used for DOTATATE PET lesion detection typically require large, well-annotated training datasets. These are difficult to obtain due to low incidence of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and the high cost of manual annotation. Furthermore, networks trained and tested with data acquired from site specific PET/CT instrumentation, acquisition and processing protocols have reduced performance when tested with offsite data. This lack of generalizability requires even larger, more diverse training datasets. The objective of this study is to investigate the feasibility of improving DL algorithm performance by better matching the background noise in training datasets to higher noise, out-of-domain testing datasets. 68Ga-DOTATATE PET/CT datasets were obtained from two scanners: Scanner1, a state-of-the-art digital PET/CT (GE DMI PET/CT; n = 83 subjects), and Scanner2, an older-generation analog PET/CT (GE STE; n = 123 subjects). Set1, the data set from Scanner1, was reconstructed with standard clinical parameters (5 min; Q.Clear) and list-mode reconstructions (VPFXS 2, 3, 4, and 5-min). Set2, data from Scanner2 representing out-of-domain clinical scans, used standard iterative reconstruction (5 min; OSEM). A deep neural network was trained with each dataset: Network1 for Scanner1 and Network2 for Scanner2. DL performance (Network1) was tested with out-of-domain test data (Set2). To evaluate the effect of training sample size, we tested DL model performance using a fraction (25%, 50% and 75%) of Set1 for training. Scanner1, list-mode 2-min reconstructed data demonstrated the most similar noise level compared that of Set2, resulting in the best performance (F1 = 0.713). This was not significantly different compared to the highest performance, upper-bound limit using in-domain training for Network2 (F1 = 0.755; p-value = 0.103). Regarding sample size, the F1 score significantly increased from 25% training data (F1 = 0.478) to 100% training data (F1 = 0.713; p &lt; 0.001). List-mode data from modern PET scanners can be reconstructed to better match the noise properties of older scanners. Using existing data and their associated annotations dramatically reduces the cost and effort in generating these datasets and significantly improves the performance of existing DL algorithms. List-mode reconstructions can provide an efficient, low-cost method to improve DL algorithm generalizability