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Abstract Background While evidence of hyperprogressive disease (HPD) continues to grow, the lack of a consensual definition obscures a proper characterization of HPD incidence. We examined how HPD incidence varies by the tumor type or the type of definition used. Methods We searched PubMed, Embase, the Cochrane Library of Systematic Reviews, and Web of Science from database inception to June 21, 2022. Observational studies reporting HPD incidence, in patients diagnosed with solid malignant tumors and treated with immune checkpoint inhibitors (ICI), were included. Random‐effects meta‐analyses were performed, and all statistical tests were 2‐sided. Results HPD incidence was 12.4% (95% CI 10.2%–15.0%) with evidence of heterogeneity (Q = 119.32, p 50). Conclusions The incidence of immunotherapy‐related HPD may vary across tumor types and definitions used, supporting the argument for a uniform and improved method of HPD evaluation for informed clinical decision‐making.

Abstract Rhodopsin is a prototypical G protein-coupled receptor (GPCR) critical for vertebrate vision. Research on GPCR signaling states has been facilitated using llama-derived nanobodies (Nbs), some of which bind to the intracellular surface to allosterically modulate the receptor. Extracellularly binding allosteric nanobodies have also been investigated, but the structural basis for their activity has not been resolved to date. Here, we report a library of Nbs that bind to the extracellular surface of rhodopsin and allosterically modulate the thermodynamics of its activation process. Crystal structures of Nb2 in complex with native rhodopsin reveal a mechanism of allosteric modulation involving extracellular loop 2 and native glycans. Nb2 binding suppresses Schiff base deprotonation and hydrolysis and prevents intracellular outward movement of helices five and six – a universal activation event for GPCRs. Nb2 also mitigates protein misfolding in a disease-associated mutant rhodopsin. Our data show the power of nanobodies to modulate the photoactivation of rhodopsin and potentially serve as therapeutic agents for disease-associated rhodopsin misfolding.

ABSTRACT The recrudescence of Toxoplasma cysts is the cause of clinical disease in the immunocompromised. Although Toxoplasma has been a useful parasite model for decades because it is relatively easy to genetically modify and culture, attempts to generate and study the recrudescence of tissue cysts have come up short with cell culture-adapted strains generating low numbers of tissue cysts in vivo. Taking advantage of a new ex vivo model of Toxoplasma recrudescence that uses a Type II ME49 strain unadapted to cell culture, we determined the cell biology, gene expression, and host cell dependency that define bradyzoite-cyst reactivation. Bradyzoite infection of fibroblasts and astrocytes produced sequential tachyzoite growth stages with pre-programmed kinetics; thus, an initial fast-growing stage was followed by a slow-growing replicating form. In vivo infections demonstrated that only fast growth tachyzoites, and not parasites post-growth shift, led to successful parasite dissemination to the brain and peripheral organs. In astrocytes, cells that reside in the central nervous system (CNS), bradyzoites initiated an additional recrudescent pathway involving brady-brady replication, which is a pathway not observed in fibroblasts. To investigate the molecular basis of growth and cell-dependent reactivation pathways, single-cell mRNA sequencing was performed on recrudescing parasites, revealing distinct gene signatures of these parasite populations and confirming multifunctionality of the original ex vivo bradyzoite population. This revised model of Toxoplasma recrudescence uncovers previously unknown complexity in the clinically important bradyzoite stage of the parasite, which opens the door to further study these novel developmental features of the Toxoplasma intermediate life cycle. IMPORTANCE The classical depiction of the Toxoplasma lifecycle is bradyzoite excystation conversion to tachyzoites, cell lysis, and immune control, followed by the reestablishment of bradyzoites and cysts. In contrast, we show that tachyzoite growth slows independent of the host immune response at a predictable time point following excystation. Furthermore, we demonstrate a host cell-dependent pathway of continuous amplification of the cyst-forming bradyzoite population. The developmental plasticity of the excysted bradyzoites further underlines the critical role the cyst plays in the flexibility of the lifecycle of this ubiquitous parasite. This revised model of Toxoplasma recrudescence uncovers previously unknown complexity in the clinically important bradyzoite stage of the parasite, which opens the door to further study these novel developmental features of the Toxoplasma intermediate life cycle.

Cushing’s syndrome (CS), secondary to paraneoplastic syndrome, is more commonly seen in small cell lung cancer but never before reported in epidermal growth factor receptor-mutated adenocarcinoma of the lung. Here, we present a case of a patient whose symptoms of hypokalemia, hypertension, and progressive abnormal glucose levels led to further workup that revealed adrenocorticotropic hormone-dependent hypercortisolism. Her cortisol levels dropped after 1 month of osilodrostat treatment, while lung cancer was treated with osimertinib. The use of osilodrostat in paraneoplastic CS has been previously reported in only 3 patients.

In Earth observation, multimodal data fusion is an intuitive strategy to break the limitation of individual data. Complementary physical contents of data sources allow comprehensive and precise information retrieval. With current satellite missions, such as ESA Copernicus programme, various data will be accessible at an affordable cost. Future applications will have many options for data sources. Such a privilege can be beneficial only if algorithms are ready to work with various data sources. However, current data fusion studies mostly focus on the fusion of two data sources. There are two reasons; first, different combinations of data sources face different scientific challenges. For example, the fusion of synthetic aperture radar (SAR) data and optical images needs to handle the geometric difference, while the fusion of hyperspectral and multispectral images deals with different resolutions on spatial and spectral domains. Second, nowadays, it is still both financially and labour expensive to acquire multiple data sources for the same region at the same time. In this paper, we provide the community with a benchmark multimodal data set, MDAS, for the city of Augsburg, Germany. MDAS includes synthetic aperture radar data, multispectral image, hyperspectral image, digital surface model (DSM), and geographic information system (GIS) data. All these data are collected on the same date, 7 May 2018. MDAS is a new benchmark data set that provides researchers rich options on data selections. In this paper, we run experiments for three typical remote sensing applications, namely, resolution enhancement, spectral unmixing, and land cover classification, on MDAS data set. Our experiments demonstrate the performance of representative state-of-the-art algorithms whose outcomes can serve as baselines for further studies. The dataset is publicly available at https://doi.org/10.14459/2022mp1657312 (Hu et al., 2022a) and the code (including the pre-trained models) at https://doi.org/10.5281/zenodo.7428215 (Hu et al., 2022b).

Summary: In daylight, demand for visual chromophore (11-cis-retinal) exceeds supply by the classical visual cycle. This shortfall is compensated, in part, by the retinal G-protein-coupled receptor (RGR) photoisomerase, which is expressed in both the retinal pigment epithelium (RPE) and in Müller cells. The relative contributions of these two cellular pools of RGR to the maintenance of photoreceptor light responses are not known. Here, we use a cell-specific gene reactivation approach to elucidate the kinetics of RGR-mediated recovery of photoreceptor responses following light exposure. Electroretinographic measurements in mice with RGR expression limited to either cell type reveal that the RPE and a specialized subset of Müller glia contribute both to scotopic and photopic function. We demonstrate that 11-cis-retinal formed through photoisomerization is rapidly hydrolyzed, consistent with its role in a rapid visual pigment regeneration process. Our study shows that RGR provides a pan-retinal sink for all-trans-retinal released under sustained light conditions and supports rapid chromophore regeneration through the photic visual cycle.

IntroductionDirofilariasis, including heartworm disease, is a major emergent veterinary parasitic infection and a human zoonosis. Currently, experimental infections of cats and dogs are used in veterinary heartworm preclinical drug research.MethodsAs a refined alternative in vivo heartworm preventative drug screen, we assessed lymphopenic mouse strains with ablation of the interleukin-2/7 common gamma chain (γc) as susceptible to the larval development phase of Dirofilaria immitis.ResultsNon-obese diabetic (NOD) severe combined immunodeficiency (SCID)γc−/− (NSG and NXG) and recombination-activating gene (RAG)2−/−γc−/− mouse strains yielded viable D. immitis larvae at 2–4 weeks post-infection, including the use of different batches of D. immitis infectious larvae, different D. immitis isolates, and at different laboratories. Mice did not display any clinical signs associated with infection for up to 4 weeks. Developing larvae were found in subcutaneous and muscle fascia tissues, which is the natural site of this stage of heartworm in dogs. Compared with in vitro-propagated larvae at day 14, in vivo-derived larvae had completed the L4 molt, were significantly larger, and contained expanded Wolbachia endobacteria titres. We established an ex vivo L4 paralytic screening system whereby assays with moxidectin or levamisole highlighted discrepancies in relative drug sensitivities in comparison with in vitro-reared L4 D. immitis. We demonstrated effective depletion of Wolbachia by 70%−90% in D. immitis L4 following 2- to 7-day oral in vivo exposures of NSG- or NXG-infected mice with doxycycline or the rapid-acting investigational drug, AWZ1066S. We validated NSG and NXG D. immitis mouse models as a filaricide screen by in vivo treatments with single injections of moxidectin, which mediated a 60%−88% reduction in L4 larvae at 14–28 days.DiscussionFuture adoption of these mouse models will benefit end-user laboratories conducting research and development of novel heartworm preventatives via increased access, rapid turnaround, and reduced costs and may simultaneously decrease the need for experimental cat or dog use.

A long-standing goal of spinal cord injury research is to develop effective repair strategies, which can restore motor and sensory functions to near-normal levels. Recent advances in clinical management of spinal cord injury have significantly improved the prognosis, survival rate and quality of life in patients with spinal cord injury. In addition, a significant progress in basic science research has unraveled the underlying cellular and molecular events of spinal cord injury. Such efforts enabled the development of pharmacologic agents, biomaterials and stem-cell based therapy. Despite these efforts, there is still no standard care to regenerate axons or restore function of silent axons in the injured spinal cord. These challenges led to an increased focus on another therapeutic approach, namely neuromodulation. In multiple animal models of spinal cord injury, epidural electrical stimulation of the spinal cord has demonstrated a recovery of motor function. Emerging evidence regarding the efficacy of epidural electrical stimulation has further expanded the potential of epidural electrical stimulation for treating patients with spinal cord injury. However, most clinical studies were conducted on a very small number of patients with a wide range of spinal cord injury. Thus, subsequent studies are essential to evaluate the therapeutic potential of epidural electrical stimulation for spinal cord injury and to optimize stimulation parameters. Here, we discuss cellular and molecular events that continue to damage the injured spinal cord and impede neurological recovery following spinal cord injury. We also discuss and summarize the animal and human studies that evaluated epidural electrical stimulation in spinal cord injury.

In recent years, hyperspectral imaging, also known as imaging spectroscopy, has been paid an increasing interest in geoscience and remote sensing community. Hyperspectral imagery is characterized by very rich spectral information, which enables us to recognize the materials of interest lying on the surface of the Earth more easier. We have to admit, however, that high spectral dimension inevitably brings some drawbacks, such as expensive data storage and transmission, information redundancy, etc. Therefore, to reduce the spectral dimensionality effectively and learn more discriminative spectral low-dimensional embedding, in this paper we propose a novel hyperspectral embedding approach by simultaneously considering spatial and spectral information, called spatial-spectral manifold embedding (SSME). Beyond the pixel-wise spectral embedding approaches, SSME models the spatial and spectral information jointly in a patch-based fashion. SSME not only learns the spectral embedding by using the adjacency matrix obtained by similarity measurement between spectral signatures, but also models the spatial neighbours of a target pixel in hyperspectral scene by sharing the same weights (or edges) in the process of learning embedding. Classification is explored as a potential strategy to quantitatively evaluate the performance of learned embedding representations. Classification is explored as a potential application for quantitatively evaluating the performance of these hyperspectral embedding algorithms. Extensive experiments conducted on the widely-used hyperspectral datasets demonstrate the superiority and effectiveness of the proposed SSME as compared to several state-of-the-art embedding methods.

Abstract Transparency in reporting is essential to scientific progress. No report should be considered complete without a full account of uncertainties, including those due to natural variation and measurement and model error and those incurred by handling problematic data, such as outliers. We randomly selected 132 papers published in 2019 from a list of 100 scientific journals to characterize the current state of uncertainty reporting in ecosystem studies. Each paper was evaluated for the extent to which it reported measures of uncertainty in any of four topic areas common to ecosystem studies: vegetation, soils, precipitation, and surface water. We found that most papers reported a minority of the uncertainty sources we deemed relevant. Papers on surface water reported the highest fraction of uncertainty sources (averaging 47% ± 5%), followed by soils (45% ± 4%), vegetation (32% ± 4%), and precipitation (21% ± 8%). A greater fraction of relevant uncertainty sources were reported when the topics were the primary focus of the paper (44% ± 3%) than when they were not (32% ± 4%). Sampling error—the uncertainty in replicate measurements—was the source most commonly reported in studies of vegetation (84%), soil mass (56%), and surface water (76% of papers). The source of measurement error most often reported was chemical analysis, with 41% of papers on surface water and 75% of papers on precipitation reporting this source, if applicable. In contrast, only 1 of 12 papers reporting chemistry of vegetation provided information on analytical uncertainty. Fewer papers reported what methods were used for handling missing or unusable data and observations below detection limits, but it was difficult to judge whether these sources were relevant if they were not mentioned. Finally, we found that a minority of the papers made all (21%) or some (an additional 21%) of their data available in online repositories, after correcting for a failure rate of 13% of the links. Clearly, there is room for improving the completeness and transparency of scientific reporting in ecosystem studies.

In this paper, we propose a framework for obtaining semantic labels of LiDAR point clouds and refining the classification results by combining a deep neural network with a graph-structured smoothing technique. In general, the goal of the semantic scene analysis is to assign a semantic label to each point in the point cloud. Although various related researches have been reported, due to the complexity of urban areas, the semantic labeling of point clouds in urban areas is still a challenging task. In this paper, we address the issues of how to effectively extract features from each point and its local surrounding and how to refine the initial soft labels by considering contextual information in the spatial domain. Specifically, we improve the effectiveness of classification of point cloud in two aspects. Firstly, instead of utilizing handcrafted features as input for classification and refinement, the local context of a point is embedded into deep dimensional space and classified via a deep neural network (PointNet++), and simultaneously soft labels are obtained as initial results for next refinement. Secondly, the initial label probability set is improved by taking the context both in the spatial domain into consideration by constructing a graph structure, and the final labels are optimized by a graph cuts algorithm. To evaluate the performance of our proposed framework, experiments are conducted on a mobile laser scanning (MLS) point cloud dataset. We demonstrate that our approach can achieve higher accuracy in comparison to several commonly-used state-of-the-art baselines. The overall accuracy of our proposed method on TUM dataset can reach 85.38% for labeling eight semantic classes.

MXenes are an emerging family of 2D transition metal carbides and nitrides and have already shown potential in various applications. However, up to now, studies on the field emission application of MXenes are scarce. In this study, the field emitters based on the Ti _3 C _2 T _x (MXene) flakes were prepared by facile solution process and the effect of different plasmas (H _2 , Ar, O _2 ) on the field emission properties of Ti _3 C _2 T _x films was investigated. The plasma treated Ti _3 C _2 T _x films showed significantly better field emission properties than that of as-deposited Ti _3 C _2 T _x films. Compared to the Ar and O _2 plasma treated Ti _3 C _2 T _x films, the H _2 plasma treated Ti _3 C _2 T _x films displayed lower turn-on field (8.5 V/ μ m) and larger maximum current density (1222 μ A cm ^−2 ). The H _2 plasma treated Ti _3 C _2 T _x films also showed good emission stability. These results suggested the potential of the H _2 plasma treated Ti _3 C _2 T _x films as electron source of vacuum electronic devices.

A new approach to more accurately monitor and evaluate transboundary particulate matter (PM) pollution is introduced based on aerosol optical products from Korea's Geostationary Ocean Color Imager (GOCI). The area studied is Northeast Asia (including eastern parts of China, the Korean peninsula and Japan), where GOCI has been monitoring since June 2010. The hourly multi-spectral aerosol optical data that were retrieved from GOCI sensor onboard geostationary satellite COMS (Communication, Ocean, and Meteorology Satellite) through the Yonsei aerosol retrieval algorithm were first presented and used in this study. The GOCI-retrieved aerosol optical data are integrated with estimated aerosol distributions from US EPA Models-3/CMAQ (Community Multi-scale Air Quality) v4.5.1 model simulations via data assimilation technique, thereby making the aerosol data spatially continuous and available even for cloud contamination cells. The assimilated aerosol optical data are utilized to provide quantitative estimates of transboundary PM pollution from China to the Korean peninsula and Japan. For the period of 1 April to 31 May, 2011 this analysis yields estimates that AOD as a proxy for PM2.5 or PM10 during long-range transport events increased by 117–265% compared to background average AOD (aerosol optical depth) at the four AERONET sites in Korea, and average AOD increases of 121% were found when averaged over the entire Korean peninsula. This paper demonstrates that the use of multi-spectral AOD retrievals from geostationary satellites can improve estimates of transboundary PM pollution. Such data will become more widely available later this decade when new sensors such as the GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI-2 are scheduled to be launched.