Vascular Endothelial Growth Factor (VEGF)-B Blockade with CSL346 in Diabetic Kidney Disease: A Phase 2A Randomized Controlled Trial.

BACKGROUND: Increased vascular endothelial growth factor B (VEGF-B) expression in patients with diabetic kidney disease (DKD) is associated with increased lipid deposition in glomerular podocytes. Reducing VEGF-B activity in animal models of DKD using an anti-VEGF-B antibody improved histological evidence of glomerular injury and reduced albuminuria; effects attributed to prevention of ectopic lipid deposition in the kidney. CSL346 is a novel humanized monoclonal antibody that binds VEGF-B with high affinity. Targeting VEGF-B in patients with type 2 diabetes mellitus may improve DKD progression markers. METHODS: An international, randomized, double-blind, placebo-controlled, phase 2a study (NCT04419467) assessed CSL346 (8 mg/kg or 16 mg/kg subcutaneously every 4 weeks for 12 weeks) in participants with type 2 diabetes mellitus and a urinary albumin-to-creatinine ratio (UACR) ≥150 mg/g (17.0 mg/mmol), and eGFR >20 mL/min/1.73m2. Efficacy, safety/tolerability, pharmacokinetics, and pharmacodynamics of CSL346 were evaluated. The primary analysis compared the change from baseline in log-transformed UACR between the two CSL346 dose groups combined versus placebo at Week 16. RESULTS: In total, 114 participants were randomized. CSL346 did not significantly reduce UACR compared with placebo at Week 16 (combined CSL346 group difference from placebo 95% confidence interval]: 4.0% [-14.7, 26.8]). Furthermore, no effect was seen in participant subgroups (degree of kidney impairment or sodium-glucose cotransporter 2 [SGLT2] inhibitor use) or on urinary biomarkers reflecting proximal tubular injury. CSL346 was generally well tolerated; however, diastolic blood pressure was significantly higher with CSL346 16 mg/kg versus placebo from Week 2 onwards, with differences ranging from +3.8 to +5.3 mmHg (P = 0.002 at Week 16). CONCLUSIONS: CSL346 did not reduce UACR compared with placebo at 16 weeks in participants with type 2 diabetes mellitus and DKD, and was associated with an increase in diastolic blood pressure.

Fruit Volume and Leaf-Area Determination of Cabbage by a Neural-Network-Based Instance Segmentation for Different Growth Stages.

Fruit volume and leaf area are important indicators to draw conclusions about the growth condition of the plant. However, the current methods of manual measuring morphological plant properties, such as fruit volume and leaf area, are time consuming and mainly destructive. In this research, an image-based approach for the non-destructive determination of fruit volume and for the total leaf area over three growth stages for cabbage (brassica oleracea) is presented. For this purpose, a mask-region-based convolutional neural network (Mask R-CNN) based on a Resnet-101 backbone was trained to segment the cabbage fruit from the leaves and assign it to the corresponding plant. Combining the segmentation results with depth information through a structure-from-motion approach, the leaf length of single leaves, as well as the fruit volume of individual plants, can be calculated. The results indicated that even with a single RGB camera, the developed methods provided a mean accuracy of fruit volume of 87% and a mean accuracy of total leaf area of 90.9%, over three growth stages on an individual plant level.

Mechanical chest compression devices in the helicopter emergency medical service in Switzerland.

BACKGROUND: Over the past years, several emergency medical service providers have introduced mechanical chest compression devices (MCDs) in their protocols for cardiopulmonary resuscitation (CPR). Especially in helicopter emergency medical systems (HEMS), which have limitations regarding loading weight and space and typically operate in rural and remote areas, whether MCDs have benefits for patients is still unknown. The aim of this study was to evaluate the use of MCDs in a large Swiss HEMS system. MATERIALS AND METHODS: We conducted a retrospective observational study of all HEMS missions of Swiss Air rescue Rega between January 2014 and June 2016 with the use of an MCD (Autopulse®). Details of MCD use and patient outcome are reported from the medical operation journals and the hospitals' discharge letters. RESULTS: MCDs were used in 626 HEMS missions, and 590 patients (94%) could be included. 478 (81%) were primary missions and 112 (19%) were interhospital transfers. Forty-nine of the patients in primary missions were loaded under ongoing CPR with MCDs. Of the patients loaded after return of spontaneous circulation (ROSC), 20 (7%) experienced a second CA during the flight. In interhospital transfers, 102 (91%) only needed standby use of the MCD. Five (5%) patients were loaded into the helicopter with ongoing CPR. Five (5%) patients went into CA during flight and the MCD had to be activated. A shockable cardiac arrhythmia was the only factor significantly associated with better survival in resuscitation missions using MCD (OR 0.176, 95% confidence interval 0.084 to 0.372, p < 0.001). CONCLUSION: We conclude that equipping HEMS with MCDs may be beneficial, with non-trauma patients potentially benefitting more than trauma patients.

Correction: Vázquez-Arellano, M., et al. 3-D Imaging Systems for Agricultural Applications-A Review. Sensors 2016, 16, 618.

The authors wish to make the following corrections to Table 1 of the title paper [1]: the working environment of the PlantEye platform should be changed from "Greenhouse" to "Open field, Greenhouse" and the shadowing device of the Scanalyzer platform should be changed from "'√" to "x". [...].

3-D Imaging Systems for Agricultural Applications-A Review.

Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture.