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The endosymbiotic origin of plastids from cyanobacteria gave eukaryotes photosynthetic capabilities and launched the diversification of countless forms of algae. These primary plastids are found in members of the eukaryotic supergroup Archaeplastida. All known archaeplastids still retain some form of primary plastids, which are widely assumed to have a single origin. Here, we use single-cell genomics from natural samples combined with phylogenomics to infer the evolutionary origin of the phylum Picozoa, a globally distributed but seemingly rare group of marine microbial heterotrophic eukaryotes. Strikingly, the analysis of 43 single-cell genomes shows that Picozoa belong to Archaeplastida, specifically related to red algae and the phagotrophic rhodelphids. These picozoan genomes support the hypothesis that Picozoa lack a plastid, and further reveal no evidence of an early cryptic endosymbiosis with cyanobacteria. These findings change our understanding of plastid evolution as they either represent the first complete plastid loss in a free-living taxon, or indicate that red algae and rhodelphids obtained their plastids independently of other archaeplastids. The origin of primary plastids in an ancestor of Archaeplastida gave eukaryotes photosynthetic capabilities. This study used single-cell genomics and phylogenomics to infer the evolutionary origin of the plastid-lacking phylum Picozoa, a group of marine microbial heterotrophic eukaryotes, showing that they belong to the Archaeplastida and changing our understanding of plastid evolution.

Most simultaneous localization and mapping (SLAM) systems assume that SLAM is conducted in a static environment. When SLAM is used in dynamic environments, the accuracy of each part of the SLAM system is adversely affected. We term this problem as dynamic SLAM. In this study, we propose solutions for three main problems in dynamic SLAM: camera tracking, three-dimensional map reconstruction, and loop closure detection. We propose to employ geometry-based method, deep learning-based method, and the combination of them for object segmentation. Using the information from segmentation to generate the mask, we filter the keypoints that lead to errors in visual odometry and features extracted by the CNN from dynamic areas to improve the performance of loop closure detection. Then, we validate our proposed loop closure detection method using the precision-recall curve and also confirm the framework’s performance using multiple datasets. The absolute trajectory error and relative pose error are used as metrics to evaluate the accuracy of the proposed SLAM framework in comparison with state-of-the-art methods. The findings of this study can potentially improve the robustness of SLAM technology in situations where mobile robots work together with humans, while the object-based point cloud byproduct has potential for other robotics tasks.

ABSTRACT Introduction This study evaluates the readability of online patient education materials (OPEMs) across otolaryngology subspecialties, hospital characteristics, and national otolaryngology organizations, while assessing AI alternatives. Methods Hospitals from the US News Best ENT list were queried for OPEMs describing a chosen surgery per subspecialty; the American Academy of Otolaryngology—Head and Neck Surgery (AAO), American Laryngological Association (ALA), Ear, Nose, and Throat United Kingdom (ENTUK), and the Canadian Society of Otolaryngology—Head and Neck Surgery (CSOHNS) were similarly queried. Google was queried for the top 10 links from hospitals per procedure. Ownership (private/public), presence of respective otolaryngology fellowships, region, and median household income (zip code) were collected. Readability was assessed using seven indices and averaged: Automated Readability Index (ARI), Flesch Reading Ease Score (FRES), Flesch–Kincaid Grade Level (FKGL), Gunning Fog Readability (GFR), Simple Measure of Gobbledygook (SMOG), Coleman–Liau Readability Index (CLRI), and Linsear Write Readability Formula (LWRF). AI‐generated materials from ChatGPT were compared for readability, accuracy, content, and tone. Analyses were conducted between subspecialties, against national organizations, NIH standard, and across demographic variables. Results Across 144 hospitals, OPEMs exceeded NIH readability standards, averaging at an 8th–12th grade level across subspecialties. In rhinology, facial plastics, and sleep medicine, hospital OPEMs had higher readability scores than ENTUK's materials (11.4 vs. 9.1, 10.4 vs. 7.2, 11.5 vs. 9.2, respectively; all p < 0.05), but lower than AAO (p = 0.005). ChatGPT‐generated materials averaged a 6.8‐grade level, demonstrating improved readability, especially with specialized prompting, compared to all hospital and organization OPEMs. Conclusion OPEMs from all sources exceed the NIH readability standard. ENTUK serves as a benchmark for accessible language, while ChatGPT demonstrates the feasibility of producing more readable content. Otolaryngologists might consider using ChatGPT to generate patient‐friendly materials, with caution, and advocate for national‐level improvements in patient education readability. This study evaluates the readability of online patient education materials (OPEMs) across otolaryngology subspecialties and organizations, finding that most materials exceed NIH reading level guidelines. The study also demonstrates that ChatGPT‐generated content offers improved readability, while international organizations like ENT UK provide significantly more accessible materials compared to US‐based groups such as the AAO.

Cells maintain the specific lipid composition of distinct organelles by vesicular transport as well as non-vesicular lipid trafficking via lipid transport proteins. Oxysterol-binding proteins (OSBPs) are a family of lipid transport proteins that transfer lipids at various membrane contact sites (MCSs). OSBPs have been extensively investigated in human and yeast cells where 12 have been identified in Homo sapiens and 7 in Saccharomyces cerevisiae. The evolutionary relationship between these well-characterized OSBPs is still unclear. By reconstructing phylogenies of eukaryote OSBPs, we show that the ancestral Saccharomycotina had four OSBPs, the ancestral fungus had five OSBPs, and the ancestral animal had six OSBPs, whereas the shared ancestor of animals and fungi as well as the ancestral eukaryote had only three OSBPs. Our analyses identified three undescribed ancient OSBP orthologues, one fungal OSBP (Osh8) lost in the lineage leading to yeast, one animal OSBP (ORP12) lost in the lineage leading to vertebrates, and one eukaryotic OSBP (OshEu) lost in both the animal and fungal lineages.

The endosymbiotic origin of plastids from cyanobacteria gave eukaryotes photosynthetic capabilities and launched the diversification of countless forms of algae. These primary plastids are found in members of the eukaryotic supergroup Archaeplastida. All known archaeplastids still retain some form of primary plastids, which are widely assumed to have a single origin. Here, we used single-cell genomics from natural samples combined with phylogenomics to infer the evolutionary origin of the phylum Picozoa, a globally distributed but seemingly rare group of marine microbial heterotrophic eukaryotes. Strikingly, the analysis of single-cell genomes shows that Picozoa belong to Archaeplastida, specifically related to red algae and the phagotrophic rhodelphids. These picozoan genomes support the hypothesis that Picozoa lack a plastid, and further reveal no evidence of an early cryptic endosymbiosis with cyanobacteria. These findings change our understanding of plastid evolution as they either represent the first complete plastid loss in a free-living taxon, or indicate that red algae and rhodelphids obtained their plastids independently of other archaeplastids. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://doi.org/10.6084/m9.figshare.c.5388176 * https://github.com/maxemil/picozoa-scripts

For safe and reliable deployment of any robot controller on the real hardware platform, it is generally a necessary practice to comprehensively assess the performance of the controller with the specific robot in a realistic simulation environment beforehand. While there exist several software solutions that can provide the core physics engine for this purpose, it is often a cumbersome and error-prone effort to interface the simulation environment with the robot controller being evaluated. The controller may have a complex structure consisting of multiple states and transitions within a finite-state machine (FSM), and may even require input through a GUI. In this work, we present mc-mujoco -- an open-source software framework that forms an interface between the MuJoCo physics simulator and the mc-rtc robot control framework. We provide implementation details and describe the process for adding support for essentially any new robot. We also demonstrate and publish a sample FSM controller for bipedal locomotion and stable grasping of a rigid object by the HRP-5P humanoid robot in MuJoCo. The code and usage instructions for mc-mujoco, the developed robot modules, and the FSM controller are available online.

In immersive humanoid robot teleoperation, there are three main shortcomings that can alter the transparency of the visual feedback: the lag between the motion of the operator's and robot's head due to network communication delays or slow robot joint motion. This latency could cause a noticeable delay in the visual feedback, which jeopardizes the embodiment quality, can cause dizziness, and affects the interactivity resulting in operator frequent motion pauses for the visual feedback to settle; (ii) the mismatch between the camera's and the headset's field-of-views (FOV), the former having generally a lower FOV; and (iii) a mismatch between human's and robot's range of motions of the neck, the latter being also generally lower. In order to leverage these drawbacks, we developed a decoupled viewpoint control solution for a humanoid platform which allows visual feedback with low-latency and artificially increases the camera's FOV range to match that of the operator's headset. Our novel solution uses SLAM technology to enhance the visual feedback from a reconstructed mesh, complementing the areas that are not covered by the visual feedback from the robot. The visual feedback is presented as a point cloud in real-time to the operator. As a result, the operator is fed with real-time vision from the robot's head orientation by observing the pose of the point cloud. Balancing this kind of awareness and immersion is important in virtual reality based teleoperation, considering the safety and robustness of the control system. An experiment shows the effectiveness of our solution.

The recent characterization of the polysaccharide composition of papillae deposited at the barley cell wall during infection by the powdery mildew pathogen, Blumeria graminis f. sp. hordei (Bgh), has provided new targets for the generation of enhanced disease resistance. The role of callose in papilla-based penetration resistance of crop species is largely unknown because the genes involved in the observed callose accumulation have not been identified unequivocally. We have employed both comparative and functional genomics approaches to identify the functional orthologue of AtGsl5 in the barley genome. HvGsl6 (the barley glucan synthase-like gene), which has the highest sequence identity to AtGsl5, is the only Bgh-induced gene among the HvGsls examined in this study. Through double-stranded RNA interference (dsRNAi)-mediated silencing of HvGsl6, we have shown that the down-regulation of HvGsl6 is associated with a lower accumulation of papillary and wound callose and a higher susceptibility to penetration of the papillae by Bgh, compared with control lines. The results indicate that the HvGsl6 gene is a functional orthologue of AtGsl5 and is involved in papillary callose accumulation in barley. The increased susceptibility of HvGsl6 dsRNAi transgenic lines to infection indicates that callose positively contributes to the barley fungal penetration resistance mechanism.

Background Genome-wide association studies do not always replicate well across populations, limiting the generalizability of polygenic risk scores (PRS). Despite higher incidence and mortality rates of prostate cancer in men of African descent, much of what is known about cancer genetics comes from populations of European descent. To understand how well genetic predictions perform in different populations, we evaluated test characteristics of PRS from three previous studies using data from the UK Biobank and a novel dataset of 1298 prostate cancer cases and 1333 controls from Ghana, Nigeria, Senegal, and South Africa. Results Allele frequency differences cause predicted risks of prostate cancer to vary across populations. However, natural selection is not the primary driver of these differences. Comparing continental datasets, we find that polygenic predictions of case vs. control status are more effective for European individuals (AUC 0.608–0.707, OR 2.37–5.71) than for African individuals (AUC 0.502–0.585, OR 0.95–2.01). Furthermore, PRS that leverage information from African Americans yield modest AUC and odds ratio improvements for sub-Saharan African individuals. These improvements were larger for West Africans than for South Africans. Finally, we find that existing PRS are largely unable to predict whether African individuals develop aggressive forms of prostate cancer, as specified by higher tumor stages or Gleason scores. Conclusions Genetic predictions of prostate cancer perform poorly if the study sample does not match the ancestry of the original GWAS. PRS built from European GWAS may be inadequate for application in non-European populations and perpetuate existing health disparities.

Immune-mediated anti-tumoral responses, elicited by oncolytic viruses and augmented with checkpoint inhibition, may be an effective treatment approach for glioblastoma. Here in this multicenter phase 1/2 study we evaluated the combination of intratumoral delivery of oncolytic virus DNX-2401 followed by intravenous anti-PD-1 antibody pembrolizumab in recurrent glioblastoma, first in a dose-escalation and then in a dose-expansion phase, in 49 patients. The primary endpoints were overall safety and objective response rate. The primary safety endpoint was met, whereas the primary efficacy endpoint was not met. There were no dose-limiting toxicities, and full dose combined treatment was well tolerated. The objective response rate was 10.4% (90% confidence interval (CI) 4.2–20.7%), which was not statistically greater than the prespecified control rate of 5%. The secondary endpoint of overall survival at 12 months was 52.7% (95% CI 40.1–69.2%), which was statistically greater than the prespecified control rate of 20%. Median overall survival was 12.5 months (10.7–13.5 months). Objective responses led to longer survival (hazard ratio 0.20, 95% CI 0.05–0.87). A total of 56.2% (95% CI 41.1–70.5%) of patients had a clinical benefit defined as stable disease or better. Three patients completed treatment with durable responses and remain alive at 45, 48 and 60 months. Exploratory mutational, gene-expression and immunophenotypic analyses revealed that the balance between immune cell infiltration and expression of checkpoint inhibitors may potentially inform on response to treatment and mechanisms of resistance. Overall, the combination of intratumoral DNX-2401 followed by pembrolizumab was safe with notable survival benefit in select patients (ClinicalTrials.gov registration: NCT02798406). A safety and efficacy trial of a single intratumoral dose of the oncolytic adenovirus DNX-2401 followed by intravenous anti-PD-1 pembrolizumab in patients with recurrent glioblastoma shows an encouraging clinical benefit rate and 12 months overall survival.