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The point spread function (PSF) of a microscope describes the image of a point emitter. Knowing the accurate PSF model is essential for various imaging tasks, including single-molecule localization, aberration correction and deconvolution. Here we present universal inverse modeling of point spread functions (uiPSF), a toolbox to infer accurate PSF models from microscopy data, using either image stacks of fluorescent beads or directly images of blinking fluorophores, the raw data in single-molecule localization microscopy (SMLM). Our modular framework is applicable to a variety of microscope modalities and the PSF model incorporates system- or sample-specific characteristics, for example, the bead size, field- and depth- dependent aberrations, and transformations among channels. We demonstrate its application in single or multiple channels or large field-of-view SMLM systems, 4Pi-SMLM, and lattice light-sheet microscopes using either bead data or single-molecule blinking data., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Introduction: Esophagectomy is the mainstay of esophageal cancer treatment, but anastomotic insufficiency related morbidity and mortality remain challenging for patient outcome. Therefore, the objective of this work was to optimize anastomotic technique and gastric conduit perfusion with hyperspectral imaging (HSI) for total minimally invasive esophagectomy (MIE) with linear stapled anastomosis., Material and Methods: A live porcine model (n = 58) for MIE was used with gastric conduit formation and simulation of linear stapled side-to-side esophagogastrostomy. Four main experimental groups differed in stapling length (3 vs. 6 cm) and simulation of anastomotic position on the conduit (cranial vs. caudal). Tissue oxygenation around the anastomotic simulation site was evaluated using HSI and was validated with histopathology., Results: The tissue oxygenation (ΔStO 2 ) after the anastomotic simulation remained constant only for the short stapler in caudal position (-0.4 ± 4.4%, n.s.) while it was impaired markedly in the other groups (short-cranial: -15.6 ± 11.5%, p = 0.0002; long-cranial: -20.4 ± 7.6%, p = 0.0126; long-caudal: -16.1 ± 9.4%, p < 0.0001). Tissue samples from avascular stomach as measured by HSI showed correspondent eosinophilic pre-necrotic changes in 35.7 ± 9.7% of the surface area., Conclusion: Tissue oxygenation at the site of anastomotic simulation of the gastric conduit during MIE is influenced by stapling technique. Optimal oxygenation was achieved with a short stapler (3 cm) and sufficient distance of the simulated anastomosis to the cranial end of the gastric conduit. HSI tissue deoxygenation corresponded to histopathologic necrotic tissue changes. The experimental model with HSI and ML allow for systematic optimization of gastric conduit perfusion and anastomotic technique while clinical translation will have to be proven., Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interest for the submission of the manuscript “Optimization of anastomotic technique and gastric conduit perfusion with hyperspectral imaging and machine learning in an experimental model for minimally invasive esophagectomy”., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: As human failure has been shown to be one primary cause for post-operative death, surgical training is of the utmost socioeconomic importance. In this context, the concept of surgical telestration has been introduced to enable experienced surgeons to efficiently and effectively mentor trainees in an intuitive way. While previous approaches to telestration have concentrated on overlaying drawings on surgical videos, we explore the augmented reality (AR) visualization of surgical hands to imitate the direct interaction with the situs., Methods: We present a real-time hand tracking pipeline specifically designed for the application of surgical telestration. It comprises three modules, dedicated to (1) the coarse localization of the expert's hand and the subsequent (2) segmentation of the hand for AR visualization in the field of view of the trainee and (3) regression of keypoints making up the hand's skeleton. The semantic representation is obtained to offer the ability for structured reporting of the motions performed as part of the teaching., Results: According to a comprehensive validation based on a large data set comprising more than 14,000 annotated images with varying application-relevant conditions, our algorithm enables real-time hand tracking and is sufficiently accurate for the task of surgical telestration. In a retrospective validation study, a mean detection accuracy of 98%, a mean keypoint regression accuracy of 10.0 px and a mean Dice Similarity Coefficient of 0.95 were achieved. In a prospective validation study, it showed uncompromised performance when the sensor, operator or gesture varied., Conclusion: Due to its high accuracy and fast inference time, our neural network-based approach to hand tracking is well suited for an AR approach to surgical telestration. Future work should be directed to evaluating the clinical value of the approach., (© 2022. The Author(s).)

This experiment evaluated the effects of feeding whole cottonseed (WC) and/or calcium salts of fatty acids (CSFA) on dry matter intake (DMI), performance, and carcass characteristics of Bos indicus animals receiving a high-concentrate diet during the finishing phase. On day 0, 96 Nellore bulls were blocked according to initial shrunk body weight (BW; 302 ± 26.7 kg) into group pens (four animals/pen) and, within blocks, pens were randomly assigned to receive: 1) 15% of WC and 2% of CSFA (dry matter [DM] basis) of palm, cottonseed, and soybean oil (15WC; n = 6); 2) 10% of WC and 3% of CSFA (DM basis) of palm, cottonseed, and soybean oil (10WC; n = 6); 3) 5% of WC and 4% of CSFA (DM basis) of palm, cottonseed, and soybean oil (5WC; n = 6); and 4) 0% of WC and 5% of CSFA (DM basis) of palm, cottonseed, and soybean oil (0WC; n = 6). Diets were formulated to be isocaloric, isonitrogenous, and isolipidic. Experimental period lasted 108 d; DMI was evaluated daily, whereas blood samples and carcass measurements were obtained on days 0, 55, and 108 of the study. Upon slaughter on day 109, steaks were collected for determination of the chemical and fatty acid (FA) profile of the meat. No treatment effects ( P ≥ 0.35) were observed on DMI, performance, average daily gain (ADG), carcass ultrasound measurements, and chemical variables of the steak. Nonetheless, including WC into the diets decreased C12:0, C16:0, C16:1 trans -9, C17:0, C18:0, C18:1 cis-9, C18:2 cis -9, cis -12, C18:3 cis -9, cis -12, cis -15, saturated, and unsaturated FA intake ( P < 0.01). Moreover, adding WC increased DMI fluctuation and feed efficiency (FE; P = 0.03) but decreased marbling ( P ≤ 0.03). A treatment × day interaction was observed ( P < 0.01) for serum leptin concentration, as 10WC animals had greater leptin concentration on day 103 vs. other treatments ( P < 0.01). Regarding steak FA profile, WC addition into the diet increased C18:2 cis -7, trans- 9 and C18:3 cis -9, cis -12, cis -15 ( P < 0.001), whereas saturated FA was quadratically affected ( P = 0.02) and unsaturated FA was reduced for 15WC ( P < 0.04). In summary, increasing levels of CSFA into isolipidic finishing diets containing WC did not negatively impact feedlot performance but reduced FE and increased marbling scores of B. indicus bulls, demonstrating its feasibility as a technology to improve carcass traits of low-marbling animals., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Single-molecule localization microscopy (SMLM) has had remarkable success in imaging cellular structures with nanometer resolution, but standard analysis algorithms require sparse emitters, which limits imaging speed and labeling density. Here, we overcome this major limitation using deep learning. We developed DECODE (deep context dependent), a computational tool that can localize single emitters at high density in three dimensions with highest accuracy for a large range of imaging modalities and conditions. In a public software benchmark competition, it outperformed all other fitters on 12 out of 12 datasets when comparing both detection accuracy and localization error, often by a substantial margin. DECODE allowed us to acquire fast dynamic live-cell SMLM data with reduced light exposure and to image microtubules at ultra-high labeling density. Packaged for simple installation and use, DECODE will enable many laboratories to reduce imaging times and increase localization density in SMLM., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: The YouTube channel "TiHoVideos" was created by the University of Veterinary Medicine Hannover, Foundation (TiHo) to enable easy, public access to the university's instructional videos as an additional support for learning clinical skills. Video production is expensive and time-consuming. To be able to optimize video production and aligning content to student needs we wanted to know if and how our students use these videos., Results: Results show that the participating students primarily prepared for learning stations in the Clinical Skills Lab (CSL) by watching TiHoVideos at home on tablets or laptops and then concentrated at the CSL on learning the practical skills hands on. The videos available on TiHoVideos are rated as being a "very helpful" educational tool when preparing for CSL learning stations., Conclusions: Instructional videos represent an unquestionably suitable medium to aid veterinary students learn practical skills and a contribution to animal welfare by reducing the use of live animals in undergraduate veterinary education. The university's production of educational video material proves to be worth the effort because the videos are being used, appreciated and well-rated by TiHo students for their learning experience.

Purpose: We report on the development of the open-source cross-platform radiation treatment planning toolkit matRad and its comparison against validated treatment planning systems. The toolkit enables three-dimensional intensity-modulated radiation therapy treatment planning for photons, scanned protons and scanned carbon ions., Methods: matRad is entirely written in Matlab and is freely available online. It re-implements well-established algorithms employing a modular and sequential software design to model the entire treatment planning workflow. It comprises core functionalities to import DICOM data, to calculate and optimize dose as well as a graphical user interface for visualization. matRad dose calculation algorithms (for carbon ions this also includes the computation of the relative biological effect) are compared against dose calculation results originating from clinically approved treatment planning systems., Results: We observe three-dimensional γ-analysis pass rates ≥ 99.67% for all three radiation modalities utilizing a distance to agreement of 2 mm and a dose difference criterion of 2%. The computational efficiency of matRad is evaluated in a treatment planning study considering three different treatment scenarios for every radiation modality. For photons, we measure total run times of 145 s-1260 s for dose calculation and fluence optimization combined considering 4-72 beam orientations and 2608-13597 beamlets. For charged particles, we measure total run times of 63 s-993 s for dose calculation and fluence optimization combined considering 9963-45574 pencil beams. Using a CT and dose grid resolution of 0.3 cm 3 requires a memory consumption of 1.59 GB-9.07 GB and 0.29 GB-17.94 GB for photons and charged particles, respectively., Conclusion: The dosimetric accuracy, computational performance and open-source character of matRad encourages a future application of matRad for both educational and research purposes., (© 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)