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Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology—from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle. © 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.

Contains fulltext : 251550.pdf (Publisher’s version ) (Open Access), BACKGROUND: Robotic surgery may improve surgical performance during minimally invasive pancreatoduodenectomy as compared to 3D- and 2D-laparoscopy but comparative studies are lacking. This study assessed the impact of robotic surgery versus 3D- and 2D-laparoscopy on surgical performance and operative time using a standardized biotissue model for pancreatico- and hepatico-jejunostomy using pooled data from two randomized controlled crossover trials (RCTs). METHODS: Pooled analysis of data from two RCTs with 60 participants (36 surgeons, 24 residents) from 11 countries (December 2017-July 2019) was conducted. Each included participant completed two pancreatico- and two hepatico-jejunostomies in biotissue using 3D-robotic surgery, 3D-laparoscopy, or 2D-laparoscopy. Primary outcomes were the objective structured assessment of technical skills (OSATS: 12-60) rating, scored by observers blinded for 3D/2D and the operative time required to complete both anastomoses. Sensitivity analysis excluded participants with excess experience compared to others. RESULTS: A total of 220 anastomoses were completed (robotic 80, 3D-laparoscopy 70, 2D-laparoscopy 70). Participants in the robotic group had less surgical experience [median 1 (0-2) versus 6 years (4-12), p < 0.001], as compared to the laparoscopic group. Robotic surgery resulted in higher OSATS ratings (50, 43, 39 points, p = .021 and p < .001) and shorter operative time (56.5, 65.0, 81.5 min, p = .055 and p < .001), as compared to 3D- and 2D-laparoscopy, respectively, which remained in the sensitivity analysis. CONCLUSION: In a pooled analysis of two RCTs in a biotissue model, robotic surgery resulted in better surgical performance scores and shorter operative time for biotissue pancreatic and biliary anastomoses, as compared to 3D- and 2D-laparoscopy.

Item does not contain fulltext, BACKGROUND: We tested the added value of 3D-vision on procedure time and surgical performance during robotic pancreatoduodenectomy anastomoses in biotissue. Robotic surgery has the advantage of articulating instruments and 3D-vision. Consensus is lacking on the added value of 3D-vision during laparoscopic surgery. Given the improved dexterity with robotic surgery, the added value of 3D-vision may be even less with robotic surgery. METHODS: In this experimental randomized controlled cross-over trial, 20 surgeons and surgical residents from 5 countries performed robotic pancreaticojejunostomy and hepaticojejunostomy anastomoses in a biotissue organ model using the da Vinci® system and were randomized to start with either 3D- or 2D-vision. Primary endpoint was the time required to complete both anastomoses. Secondary endpoint was the objective structured assessment of technical skill (OSATS; range 12-60) rating; scored by two observers blinded to 3D/2D. RESULTS: Robotic 3D-vision reduced the combined operative time from 78.1 to 57.3 min (24.6% reduction, p < 0.001; 20.8 min reduction, 95% confidence intervals 12.8-28.8 min). This reduction was consistent for both anastomoses and between surgeons and residents, p < 0.001. Robotic 3D-vision improved OSATS performance by 6.1 points (20.8% improvement, p = 0.003) compared to 2D (39.4 to 45.1 points, ± 5.5). CONCLUSION: 3D-vision has a considerable added value during robotic pancreatoduodenectomy anastomoses in biotissue in both time reduction and improved surgical performance as compared to 2D-vision.

Background: Few studies have investigated the learning curves of minimally invasive donor nephrectomy (MIDN) using the cumulative sum (CUSUM) analysis. In addition, no study has compared the learning curves of the different surgical MIDN techniques in one cohort study using the CUSUM

Background: Growing evidence for the advantages of robotic pancreatoduodenectomy (RPD) has been demonstrated internationally. However, there has been no structured training program for RPD in Japan. Herein, we present the surgical training model of RPD and a standardized protocol for surgical technique. Methods: The surgical training model and surgical technique were standardized in order to implement RPD safely, based on the Dutch training system collaborated with the University of Pittsburgh Medical Center. Results: The surgical training model included various trainings such as basic robotic training, simulation training, biotissue training, and a surgical video review. Furthermore, a standardized protocol on the surgical technique was established to understand the tips, tricks, and pitfalls of RPD. Conclusions: Safe implementation of RPD can be achieved through the completion of a structured training program and learning surgical technique. A nationwide structured training system should be developed to implement the program safely in Japan.