Biomimetic cell stimulation with a graphene oxide antigen-presenting platform for developing T cell-based therapies.

Chimeric antigen receptor (CAR)-engineered T cells represent a front-line therapy for cancers. However, the current CAR T cell manufacturing protocols do not adequately reproduce immunological synapse formation. Here, in response to this limitation, we have developed a flexible graphene oxide antigen-presenting platform (GO-APP) that anchors antibodies onto graphene oxide. By decorating anti-CD3 (αCD3) and anti-CD28 (αCD28) on graphene oxide (GO-APP3/28), we achieved remarkable T cell proliferation. In vitro interactions between GO-APP3/28 and T cells closely mimic the in vivo immunological synapses between antigen-presenting cells and T cells. This immunological synapse mimicry shows a high capacity for stimulating T cell proliferation while preserving their multifunctionality and high potency. Meanwhile, it enhances CAR gene-engineering efficiency, yielding a more than fivefold increase in CAR T cell production compared with the standard protocol. Notably, GO-APP3/28 stimulated appropriate autocrine interleukin-2 (IL-2) in T cells and overcame the in vitro reliance on external IL-2 supplementation, offering an opportunity to culture T cell-based products independent of IL-2 supplementation.

Biomimetic-Structured Cobalt Nanocatalyst Suppresses Aortic Dissection Progression by Catalytic Antioxidation.

As one of the most lethal cardiovascular diseases, aortic dissection (AD) is initiated by overexpression of reactive oxygen species (ROS) in the aorta that damages the vascular structure and finally leads to massive hemorrhage and sudden death. Current drugs used in clinics for AD treatment fail to efficiently scavenge ROS to a large extent, presenting undesirable therapeutic effect. In this work, a nanocatalytic antioxidation concept has been proposed to elevate the therapeutic efficacy of AD by constructing a cobalt nanocatalyst with a biomimetic structure that can scavenge pathological ROS in an efficient and sustainable manner. Theoretical calculations demonstrate that the antioxidation reaction is catalyzed by the redox transition between hydroxocobalt(III) and oxo-hydroxocobalt(V) accompanied by inner-sphere proton-coupled two-electron transfer, forming a nonassociated activation catalytic cycle. The efficient antioxidation action of the biomimetic nanocatalyst in the AD region effectively alleviates oxidative stress, which further modulates the aortic inflammatory microenvironment by promoting phenotype transition of macrophages. Consequently, vascular smooth muscle cells are also protected from inflammation in the meantime, suppressing AD progression. This study provides a nanocatalytic antioxidation approach for the efficient treatment of AD and other cardiovascular diseases.

A Dual-Targeting, Multi-Faceted Biocompatible Nanodrug Optimizes the Microenvironment to Ameliorate Abdominal Aortic Aneurysm.

Abdominal aortic aneurysm (AAA) is a highly lethal cardiovascular disease that currently lacks effective pharmacological treatment given the complex pathophysiology of the disease. Here, single-cell RNA-sequencing data from patients with AAA and a mouse model are analyzed, which reveals pivotal pathological changes, including the M1-like polarization of macrophages and the loss of contractile function in smooth muscle cells (SMCs). Both cell types express the integrin αvß3, allowing for their dual targeting with a single rationally designed molecule. To this end, a biocompatible nanodrug, which is termed EVMS@R-HNC, that consists of the multifunctional drug everolimus (EVMS) encapsulated by the hepatitis B virus core protein modifies to contain the RGD sequence to specifically bind to integrin αvß3 is designed. Both in vitro and in vivo results show that EVMS@R-HNC can target macrophages as well as SMCs. Upon binding of the nanodrug, the EVMS is released intracellularly where it exhibits multiple functions, including inhibiting M1 macrophage polarization, thereby suppressing the self-propagating inflammatory cascade and immune microenvironment imbalance, while preserving the normal contractile function of SMCs. Collectively, these results suggest that EVMS@R-HNC presents a highly promising therapeutic approach for the management of AAA.

Oropharyngeal cancer and human papillomavirus: a visualization based on bibliometric analysis and topic modeling.

Objectives: The incidence of oropharyngeal cancer (OPC) is increasing. This study used bibliometric analysis and topic modeling to explore the research trends and advancements in this disease over the past 10 years, providing valuable insights to guide future investigations. Methods: 7,355 English articles from 2013 to 2022 were retrieved from the Web of Science Core Collection for bibliometric analysis. Topic modeling was applied to 1,681 articles from high-impact journals, followed by an assessment of topic significance ranking (TSR). Medical Subject Headings (MeSH) terms were extracted using R and Python, followed by an analysis of the terms associated with each topic and on an annual basis. Additionally, genes were extracted and the number of genes appearing each year and the newly emerged genes were counted. Results: The bibliometric analysis suggested that the United States and several European countries hold pivotal positions in research. Current research is focused on refining treatments, staging and stratification. Topic modeling revealed 12 topics, emphasizing human papillomavirus (HPV) and side effect reduction. MeSH analysis revealed a growing emphasis on prognosis and quality of life. No new MeSH terms emerged after 2018, suggesting that the existing terms have covered most of the core concepts within the field of oropharyngeal cancers. Gene analysis identified TP53 and EGFR as the most extensively studied genes, with no novel genes discovered after 2019. However, CD69 and CXCL9 emerged as new genes of interest in 2019, reflecting recent research trends and directions. Conclusion: HPV-positive oropharyngeal cancer research, particularly treatment de-escalation, has gained significant attention. However, there are still challenges in diagnosis and treatment that need to be addressed. In the future, more research will focus on this issue, indicating that this field still holds potential as a research hotspot.

Generation of allogeneic CAR-NKT cells from hematopoietic stem and progenitor cells using a clinically guided culture method.

Cancer immunotherapy with autologous chimeric antigen receptor (CAR) T cells faces challenges in manufacturing and patient selection that could be avoided by using 'off-the-shelf' products, such as allogeneic CAR natural killer T (AlloCAR-NKT) cells. Previously, we reported a system for differentiating human hematopoietic stem and progenitor cells into AlloCAR-NKT cells, but the use of three-dimensional culture and xenogeneic feeders precluded its clinical application. Here we describe a clinically guided method to differentiate and expand IL-15-enhanced AlloCAR-NKT cells with high yield and purity. We generated AlloCAR-NKT cells targeting seven cancers and, in a multiple myeloma model, demonstrated their antitumor efficacy, expansion and persistence. The cells also selectively depleted immunosuppressive cells in the tumor microenviroment and antagonized tumor immune evasion via triple targeting of CAR, TCR and NK receptors. They exhibited a stable hypoimmunogenic phenotype associated with epigenetic and signaling regulation and did not induce detectable graft versus host disease or cytokine release syndrome. These properties of AlloCAR-NKT cells support their potential for clinical translation.

Sex-based outcomes after thoracic endovascular aortic repair: A systematic review and meta-analysis.

OBJECTIVE: As it remains unclear whether there are sex-based differences in clinical outcomes after thoracic endovascular aortic repair (TEVAR), this meta-analysis aimed to evaluate differences in early outcomes and overall survival between female and male patients who underwent TEVAR. METHODS: The PubMed, Embase, Web of Science, and Cochrane Central databases were searched for eligible studies published through June 10, 2023, that reported sex-based differences in clinical outcomes after TEVAR. The primary outcome was operative mortality; second outcomes included stroke, spinal cord ischemia, acute kidney injury, hospital length of stay, and overall survival. Patient characteristics, operative data, and early outcomes were aggregated using the random-effects model, presenting pooled risk ratio (RR) or standardized mean difference along with their corresponding 95% confidence intervals (CIs). Overall survival was assessed by reconstructing individual patient data to generate sex-specific pooled Kaplan-Meier curves. This study was registered in PROSPERO (CRD42023426069). RESULTS: Of the 1785 studies retrieved, 14 studies met all eligibility criteria, encompassing a total of 17,374 patients, comprising 5026 female and 12,348 male patients. Female patients were older, had a smaller maximum aortic diameter, had lower rates of smoking and coronary artery disease, and had higher rates of anemia. Intraoperatively, female patients were more likely to use iliac conduits and require blood transfusions. There were no sex-based differences in operative mortality (RR: 1.12, 95% CI: 0.90-1.40; P = .309), stroke (RR: 1.14, 95% CI: 0.95-1.38; P = .165), spinal cord ischemia (RR: 1.33, 95% CI: 0.83-2.14; P = .234), acute kidney injury (RR: 0.78, 95% CI: 0.52-1.17; P = .228), and hospital length of stay (standardized mean difference: 0.09, 95% CI: -0.03 to 0.20; P = .141). Pooled Kaplan-Meier estimates showed a worse overall survival in female patients compared with male patients (87.2% vs 89.8% at 2 years, log-rank P = .001). CONCLUSIONS: Among patients treated by TEVAR, female sex was not associated with increased risk of operative mortality or major morbidity. However, female patients exhibited a lower overall survival after TEVAR compared with male patients.

Shaping high-performance wearable robots for human motor and sensory reconstruction and enhancement.

Most wearable robots such as exoskeletons and prostheses can operate with dexterity, while wearers do not perceive them as part of their bodies. In this perspective, we contend that integrating environmental, physiological, and physical information through multi-modal fusion, incorporating human-in-the-loop control, utilizing neuromuscular interface, employing flexible electronics, and acquiring and processing human-robot information with biomechatronic chips, should all be leveraged towards building the next generation of wearable robots. These technologies could improve the embodiment of wearable robots. With optimizations in mechanical structure and clinical training, the next generation of wearable robots should better facilitate human motor and sensory reconstruction and enhancement.

Distributed Formation Control of Multi-Robot Systems with Path Navigation via Complex Laplacian.

This paper focuses on the formation control of multi-robot systems with leader-follower network structure in directed topology to guide a system composed of multiple mobile robot agents to achieve global path navigation with a desired formation. A distributed linear formation control strategy based on the complex Laplacian matrix is employed, which enables the robot agents to converge into a similar formation of the desired formation, and the size and orientation of the formation are determined by the positions of two leaders. Additionally, in order to ensure that all robot agents in the formation move at a common velocity, the distributed control approach also includes a velocity consensus component. Based on the realization of similar formation control of a multi-robot system, the path navigation algorithm is combined with it to realize the global navigation of the system as a whole. Furthermore, a controller enabling the scalability of the formation size is introduced to enhance the overall maneuverability of the system in specific scenarios like narrow corridors. The simulation results demonstrate the feasibility of the proposed approach.

PB-LNet: a model for predicting pathological subtypes of pulmonary nodules on CT images.

OBJECTIVE: To investigate the correlation between CT imaging features and pathological subtypes of pulmonary nodules and construct a prediction model using deep learning. METHODS: We collected information of patients with pulmonary nodules treated by surgery and the reference standard for diagnosis was post-operative pathology. After using elastic distortion for data augmentation, the CT images were divided into a training set, a validation set and a test set in a ratio of 6:2:2. We used PB-LNet to analyze the nodules in pre-operative CT and predict their pathological subtypes. Accuracy was used as the model evaluation index and Class Activation Map was applied to interpreting the results. Comparative experiments with other models were carried out to achieve the best results. Finally, images from the test set without data augmentation were analyzed to judge the clinical utility. RESULTS: Four hundred seventy-seven patients were included and the nodules were divided into six groups: benign lesions, precursor glandular lesions, minimally invasive adenocarcinoma, invasive adenocarcinoma Grade 1, Grade 2 and Grade 3. The accuracy of the test set was 0.84. Class Activation Map confirmed that PB-LNet classified the nodules mainly based on the lungs in CT images, which is in line with the actual situation in clinical practice. In comparative experiments, PB-LNet obtained the highest accuracy. Finally, 96 images from the test set without data augmentation were analyzed and the accuracy was 0.89. CONCLUSIONS: In classifying CT images of lung nodules into six categories based on pathological subtypes, PB-LNet demonstrates satisfactory accuracy without the need of delineating nodules, while the results are interpretable. A high level of accuracy was also obtained when validating on real data, therefore demonstrates its usefulness in clinical practice.