SurgT challenge: Benchmark of soft-tissue trackers for robotic surgery.

This paper introduces the "SurgT: Surgical Tracking" challenge which was organized in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022). There were two purposes for the creation of this challenge: (1) the establishment of the first standardized benchmark for the research community to assess soft-tissue trackers; and (2) to encourage the development of unsupervised deep learning methods, given the lack of annotated data in surgery. A dataset of 157 stereo endoscopic videos from 20 clinical cases, along with stereo camera calibration parameters, have been provided. Participants were assigned the task of developing algorithms to track the movement of soft tissues, represented by bounding boxes, in stereo endoscopic videos. At the end of the challenge, the developed methods were assessed on a previously hidden test subset. This assessment uses benchmarking metrics that were purposely developed for this challenge, to verify the efficacy of unsupervised deep learning algorithms in tracking soft-tissue. The metric used for ranking the methods was the Expected Average Overlap (EAO) score, which measures the average overlap between a tracker's and the ground truth bounding boxes. Coming first in the challenge was the deep learning submission by ICVS-2Ai with a superior EAO score of 0.617. This method employs ARFlow to estimate unsupervised dense optical flow from cropped images, using photometric and regularization losses. Second, Jmees with an EAO of 0.583, uses deep learning for surgical tool segmentation on top of a non-deep learning baseline method: CSRT. CSRT by itself scores a similar EAO of 0.563. The results from this challenge show that currently, non-deep learning methods are still competitive. The dataset and benchmarking tool created for this challenge have been made publicly available at https://surgt.grand-challenge.org/. This challenge is expected to contribute to the development of autonomous robotic surgery and other digital surgical technologies.

Visual tracking of viral infection dynamics reveals the synergistic interactions between cucumber mosaic virus and broad bean wilt virus 2.

Cucumber mosaic virus (CMV) is one of the most prevalent plant viruses in the world, and causes severe damage to various crops. CMV has been studied as a model RNA virus to better understand viral replication, gene functions, evolution, virion structure, and pathogenicity. However, CMV infection and movement dynamics remain unexplored due to the lack of a stable recombinant virus tagged with a reporter gene. In this study, we generated a CMV infectious cDNA construct tagged with a variant of the flavin-binding LOV photoreceptor (iLOV). The iLOV gene was stably maintained in the CMV genome after more than four weeks of three serial passages between plants. Using the iLOV-tagged recombinant CMV, we visualized CMV infection and movement dynamics in living plants in a time course manner. We also examined whether CMV infection dynamics is influenced by co-infection with broad bean wilt virus 2 (BBWV2). Our results revealed that no spatial interference occurred between CMV and BBWV2. Specifically, BBWV2 facilitated the cell-to-cell movement of CMV in the upper young leaves. In addition, the BBWV2 accumulation level increased after co-infection with CMV.

A biomimetic compound eye lens for photocurrent enhancement at low temperatures.

In this study, an artificial compound eye lens (ACEL) was fabricated using a laser cutting machine and polyvinyl alcohol (PVA) solution. A laser cutter was used to punch micro-sized holes (500 µm diameter-the smallest possible diameter) into an acrylic plate; this punched plate was then placed on the aqueous PVA solution, and the water was evaporated. The plate was used as the mold to obtain a polydimethylsiloxane (PDMS) micro lens array film, which was fixed to a dome-shaped three-dimensional-printed mold for further PDMS curing, and a hemispherical compound eye lens was obtained. Using a gallium nitride (GaN) photodetector, a light detection experiment was performed with the ACEL, bare lens, and no lens by irradiating light at various angles under low temperatures. The photodetector with the ACEL generated a high photocurrent under several conditions. In particular, when the light was irradiated at 0° and below -20 °C, the photocurrent of the GaN sensor with the ACEL increased by 61% and 81% compared with the photocurrent of the GaN sensor with the bare lens and without a lens, respectively. In this study, a sensor for detecting light with ACEL was demonstrated in low-temperature environments, such as indoor refrigerated storages and external conditions in Antarctica and Arctic.

Newly emerged resistance-breaking variants of cucumber mosaic virus represent ongoing host-interactive evolution of an RNA virus.

Understanding the evolutionary history of a virus and the mechanisms influencing the direction of its evolution is essential for the development of more durable strategies to control the virus in crop fields. While the deployment of host resistance in crops is the most efficient means to control various viruses, host resistance itself can act as strong selective pressure and thus play a critical role in the evolution of virus virulence. Cucumber mosaic virus (CMV), a plant RNA virus with high evolutionary capacity, has caused endemic disease in various crops worldwide, including pepper (Capsicum annuum L.), because of frequent emergence of resistance-breaking variants. In this study, we examined the molecular and evolutionary characteristics of recently emerged, resistance-breaking CMV variants infecting pepper. Our population genetics analysis revealed that the high divergence capacity of CMV RNA1 might have played an essential role in the host-interactive evolution of CMV and in shaping the CMV population structure in pepper. We also demonstrated that nonsynonymous mutations in RNA1 encoding the 1a protein enabled CMV to overcome the deployed resistance in pepper. Our findings suggest that resistance-driven selective pressures on RNA1 might have contributed in shaping the unique evolutionary pattern of CMV in pepper. Therefore, deployment of a single resistance gene may reduce resistance durability against CMV and more integrated approaches are warranted for successful control of CMV in pepper.