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Combination radiotherapy (RT) and αPD-L1 therapy has potential to enhance local and distant (abscopal) tumor control, however, clinical results in humans have been variable. Using murine melanoma models, we found RT + αPD-L1 increases intra-tumor progenitor CD8+ PD-1+ TCF-1+ T cells. This increase depends on trafficking of the PD-1+ TCF-1+ cells from the tumor-draining lymph node (TdLN) to the tumor. RT alone promotes the expansion and differentiation of the TdLN derived PD-1+ TCF-1+ cells into TIM-3+ GZMB+ TCF-1- effector-like cells in the tumor with further enhancement after the addition of αPD-L1. In the TdLN, combination therapy enriches for a novel PD-1+ TCF-1+ TOX- LY6A+ subset with expression of a type I interferon and migratory signature. This subset is able to traffic to the tumor and differentiate into TIM-3+ TCF-1- cells. Finally, we found that ablation of the PD-1+ TCF-1+ T cell population attenuates the enhanced tumor control observed with combination RT + αPD-L1. These results suggest that abscopal response failures may be secondary to impaired stimulation of TdLN CD8+ PD-1 + TCF-1+ T cells or an inability of PD-1+ TCF-1+ cells in the TdLN to traffic to the tumor. Combination radiotherapy (RT) + αPD-L1 enhances tumor control via a tumor-draining lymph node (TdLN)-derived CD8+ PD-1+ TCF-1+ T cells. RT + αPD-L1 induces a novel LY6A+ subset in the TdLN that migrates to the tumor and differentiates into effectors.

A proper scene representation is central to the pursuit of spatial intelligence where agents can robustly reconstruct and efficiently understand 3D scenes. A scene representation is either metric, such as landmark maps in 3D reconstruction, 3D bounding boxes in object detection, or voxel grids in occupancy prediction, or topological, such as pose graphs with loop closures in SLAM or visibility graphs in SfM. In this work, we propose to build Multiview Scene Graphs (MSG) from unposed images, representing a scene topologically with interconnected place and object nodes. The task of building MSG is challenging for existing representation learning methods since it needs to jointly address both visual place recognition, object detection, and object association from images with limited fields of view and potentially large viewpoint changes. To evaluate any method tackling this task, we developed an MSG dataset and annotation based on a public 3D dataset. We also propose an evaluation metric based on the intersection-over-union score of MSG edges. Moreover, we develop a novel baseline method built on mainstream pretrained vision models, combining visual place recognition and object association into one Transformer decoder architecture. Experiments demonstrate that our method has superior performance compared to existing relevant baselines.

Tumor synthesis enables the creation of artificial tumors in medical images, facilitating the training of AI models for tumor detection and segmentation. However, success in tumor synthesis hinges on creating visually realistic tumors that are generalizable across multiple organs and, furthermore, the resulting AI models being capable of detecting real tumors in images sourced from different domains (e.g., hospitals). This paper made a progressive stride toward generalizable tumor synthesis by leveraging a critical observation: early-stage tumors (< 2cm) tend to have similar imaging characteristics in computed tomography (CT), whether they originate in the liver, pancreas, or kidneys. We have ascertained that generative AI models, e.g., Diffusion Models, can create realistic tumors generalized to a range of organs even when trained on a limited number of tumor examples from only one organ. Moreover, we have shown that AI models trained on these synthetic tumors can be generalized to detect and segment real tumors from CT volumes, encompassing a broad spectrum of patient demographics, imaging protocols, and healthcare facilities.

Despite the demonstrated editing capacity in the latent space of a pretrained GAN model, inverting real-world images is stuck in a dilemma that the reconstruction cannot be faithful to the original input. The main reason for this is that the distributions between training and real-world data are misaligned, and because of that, it is unstable of GAN inversion for real image editing. In this paper, we propose a novel GAN prior based editing framework to tackle the out-of-domain inversion problem with a composition-decomposition paradigm. In particular, during the phase of composition, we introduce a differential activation module for detecting semantic changes from a global perspective, ıe, the relative gap between the features of edited and unedited images. With the aid of the generated Diff-CAM mask, a coarse reconstruction can intuitively be composited by the paired original and edited images. In this way, the attribute-irrelevant regions can be survived in almost whole, while the quality of such an intermediate result is still limited by an unavoidable ghosting effect. Consequently, in the decomposition phase, we further present a GAN prior based deghosting network for separating the final fine edited image from the coarse reconstruction. Extensive experiments exhibit superiorities over the state-of-the-art methods, in terms of qualitative and quantitative evaluations. The robustness and flexibility of our method is also validated on both scenarios of single attribute and multi-attribute manipulations.

The electrolytic capacitor-less PMSM drive system presents complex nonlinear characteristics. Since electrolytic capacitor-less systems exhibit low inertia due to the absence of energy storage components, traditional controllers struggle to achieve the dynamic optimization of phase and amplitude margins, resulting in power transmission mismatches that trigger DC bus voltage surges. This severely limits the dynamic response capability and reliable operation of the system across full operating conditions, leading to an insufficient wide-speed-range performance and disturbance rejection. This study investigates the stable operation mechanism under intermittent working conditions by analyzing DC bus voltage transient characteristics. It optimizes control parameters for stable intermittent operations and establishes a neural network-based adaptive controller model. By modeling the correlation between hardware parameters and control parameters in drive systems under frequent start–stop conditions, this research achieves dynamic controllability of the controller during intermittent operations. This approach enhances the computational accuracy of the drive system control model, ultimately improving system-wide operational reliability and adaptability. Experimental validation confirms the effectiveness of this approach, showing significant reliability improvements in capacitor-less variable-frequency speed-control systems. Key innovations include: (1) BP neural network integration for dynamic parameter optimization, (2) impulse voltage suppression through adaptive control matching, and (3) enhanced transient response via machine learning-enhanced speed regulation. The test results demonstrate a 63% reduction in bus voltage fluctuations and 35% improvement in load transition responses compared to conventional PID-based systems, proving the strategy’s practical viability for industrial drive applications.

Pathological retinal neovascularization (RNV) is one of the leading causes of blindness worldwide; however, its underlying mechanism remains unclear. Here, we found that the expression of endothelial protein C receptor ( Epcr ) was increased during RNV, and its ligand was elevated in the serum or vitreous body of patients with proliferative diabetic retinopathy. Deleting endothelial Epcr or using an EPCR-neutralizing antibody ameliorated pathological retinal angiogenesis. EPCR promoted endothelial heme catabolism and carbon monoxide release through heme oxygenase 1 (HO-1). Inhibition of heme catabolism by deleting endothelial Ho-1 or using an HO-1 inhibitor suppressed pathological angiogenesis in retinopathy. Conversely, supplementation with carbon monoxide rescued the angiogenic defects after endothelial Epcr or Ho-1 deletion. Our results identified EPCR-dependent endothelial heme catabolism as an important contributor to pathological angiogenesis, which may serve as a potential target for treating vasoproliferative retinopathy. Pathological retinal neovascularization (RNV) is a major cause of blindness. Here, the authors show that endothelial protein C receptor (EPCR) promotes RNV through carbon monoxide derived from heme catabolism, and blocking EPCR offers therapeutic potential for the treating RNV.

Background Pathological retinal angiogenesis resulting from a variety of ocular diseases including oxygen induced retinopathy, diabetic retinopathy and ocular vein occlusion, is one of the major reasons for vision loss, yet the therapeutic option is limited. Multiple nanoparticles have been reported to alleviate angiogenic retinopathy. However, the adverse effect cannot be ignored due to the relatively large scale. Graphene quantum dots (GQDs) have shown potential in drug delivery and have been proved biocompatible. In this study, Graphene quantum dots are extensively investigated for their application in angiogenic retinopathy therapy. Results We showed that GQDs were biocompatible nanomaterials in vitro and in vivo. The nanoparticles have a dose-dependent inhibitory effect on proliferation, migration, tube formation and sprouting of human umbilical vein endothelial cells (HUVECs). Further data show that GQDs could inhibit pathological retinal neovascularization in an oxygen-induced retinopathy (OIR) model. The data of RNA sequencing suggested that periostin is involved in this process. GQDs inhibit the expression of periostin via STAT3, and further regulated cell cycle-related protein levels through ERK pathway. The signaling pathway was conformed in vivo using OIR mouse model. Conclusions The present study indicated that GQDs could be a biocompatible anti-angiogenic nanomedicine in the treatment of pathological retinal neovascularization via disrupting periostin/ERK pathway and subsequent cell cycle. Graphical Abstract

Shanxi-aged vinegar, a traditional Chinese grain-fermented food that is rich in polyphenols, has been shown to have therapeutic effects on a variety of diseases. However, there has been no comprehensive evaluation of the anti-inflammatory activity of polyphenols extracted from Shanxi-aged vinegar (SAVEP) to date. The anti-inflammatory activities of SAVEP, both in RAW 264.7 macrophages and mice, were extensively investigated for the potential application of SAVEP as a novel anti-inflammatory agent. In order to confirm the notion that polyphenols could improve inflammatory symptoms, SAVEP was firstly detected by gas chromatography mass spectrometry (GC-MS). In total, 19 polyphenols were detected, including 12 phenolic acids. The study further investigated the protective effect of SAVEP on lipopolysaccharide-induced inflammation in RAW264.7 macrophages and ICR mice. The results showed that compared with those of the model group, SAVEP could remarkably recover the inflammation of macrophage RAW264.7 and ICR mice. SAVEP can normalise the expression of related proteins via the suppression of MAPK/NF-κB pathway activation, inhibiting the expression of iNOS and COX-2 proteins, and consequently the production of inflammatory factors, thus alleviating inflammatory stress. These results suggest that SAVEP may have a potential function against inflammation.

Excessive glucocorticoid (GC) action is linked to various metabolic disorders. Recent findings suggest that disrupting skeletal GC signaling prevents bone loss and alleviates metabolic disorders in high-fat diet (HFD)-fed obese mice, underpinning the neglected contribution of skeletal GC action to obesity and related bone loss. Here, we show that the elevated expression of 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1), the enzyme driving local GC activation, and GC signaling in osteoblasts, are associated with bone loss and obesity in HFD-fed male mice. Osteoblast-specific 11β-HSD1 knockout male mice exhibit resistance to HFD-induced bone loss and metabolic disorders. Mechanistically, elevated 11β-HSD1 restrains glucose uptake and osteogenic activity in osteoblast. Pharmacologically inhibiting osteoblastic 11β-HSD1 by using bone-targeted 11β-HSD1 inhibitor markedly promotes bone formation, ameliorates glucose handling and mitigated obesity in HFD-fed male mice. Taken together, our study demonstrates that osteoblastic 11β-HSD1 directly contributes to HFD-induced bone loss, glucose handling impairment and obesity. Excessive glucocorticoid (GC) action is linked to various metabolic disorders. Here the authors show that elevated expression of 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1), the enzyme driving local bone GC activation, is associated with bone loss and obesity mice.

Glucose metabolism, the major source of energy, plays a crucial role in physiological cell function and the maintenance of homeostasis. Glucose acts as the predominant source of metabolic fuel in the generation of ATP and is involved in biosynthesis and epigenetics. Thus, glucose metabolism maintains a key role in cell function, homeostasis, energy generation, biosynthesis and epigenetics. An increasing number of studies have revealed that glucose metabolism is intricately involved in angiogenesis, with the disruption of angiogenesis contributing to several vascular diseases. Ocular vascular diseases are common ophthalmological disorders, and the prevalence of these disorders is increasing annually. Ocular vascular diseases largely occur from abnormal congenital development or acquired disturbances to the vasculature. Thus, identifying the process of occurrence and development of physiological and pathological angiogenesis is of utmost importance, and this involves understanding the inseparable role of intercellular communications between vascular cells. Although vascular endothelial growth factor (VEGF) is a well-recognized therapeutic target for the management of ocular vascular diseases, VEGF-based therapy fails to achieve the desired therapeutic effects in several cases, partly due to drug resistance and non-compliance. In the present review, current knowledge on the processes and roles of glucose metabolism in governing both physiological and pathological ocular angiogenesis are summarized, highlighting vascular glucose metabolism as a promising strategy for maintaining or restoring the physiological functions of the vasculature, thus potentially ameliorating ocular vascular diseases.