IL-17 can promote tumor growth through an IL-6–Stat3 signaling pathway

Although the Th17 subset and its signature cytokine, interleukin (IL)-17A (IL-17), are implicated in certain autoimmune diseases, their role in cancer remains to be further explored. IL-17 has been shown to be elevated in several types of cancer, but how it might contribute to tumor growth is still unclear. We show that growth of B16 melanoma and MB49 bladder carcinoma is reduced in IL-17−/− mice but drastically accelerated in IFN-γ−/− mice, contributed to by elevated intratumoral IL-17, indicating a role of IL-17 in promoting tumor growth. Adoptive transfer studies and analysis of the tumor microenvironment suggest that CD4+ T cells are the predominant source of IL-17. Enhancement of tumor growth by IL-17 involves direct effects on tumor cells and tumor-associated stromal cells, which bear IL-17 receptors. IL-17 induces IL-6 production, which in turn activates oncogenic signal transducer and activator of transcription (Stat) 3, up-regulating prosurvival and proangiogenic genes. The Th17 response can thus promote tumor growth, in part via an IL-6–Stat3 pathway

State of the Art in Dense Monocular Non-Rigid 3D Reconstruction

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular2D image observations is a long-standing and actively researched area ofcomputer vision and graphics. It is an ill-posed inverse problem,since--without additional prior assumptions--it permits infinitely manysolutions leading to accurate projection to the input 2D images. Non-rigidreconstruction is a foundational building block for downstream applicationslike robotics, AR/VR, or visual content creation. The key advantage of usingmonocular cameras is their omnipresence and availability to the end users aswell as their ease of use compared to more sophisticated camera set-ups such asstereo or multi-view systems. This survey focuses on state-of-the-art methodsfor dense non-rigid 3D reconstruction of various deformable objects andcomposite scenes from monocular videos or sets of monocular views. It reviewsthe fundamentals of 3D reconstruction and deformation modeling from 2D imageobservations. We then start from general methods--that handle arbitrary scenesand make only a few prior assumptions--and proceed towards techniques makingstronger assumptions about the observed objects and types of deformations (e.g.human faces, bodies, hands, and animals). A significant part of this STAR isalso devoted to classification and a high-level comparison of the methods, aswell as an overview of the datasets for training and evaluation of thediscussed techniques. We conclude by discussing open challenges in the fieldand the social aspects associated with the usage of the reviewed methods.<br

Cutting-edge advances in modeling the blood–brain barrier and tools for its reversible permeabilization for enhanced drug delivery into the brain

The bloodâ brain barrier (BBB) is a sophisticated structure whose full functionality is required for maintaining the executive functions of the central nervous system (CNS). Tight control of transport across the barrier means that most drugs, particularly large size, which includes powerful biologicals, cannot reach their targets in the brain. Notwithstanding the remarkable advances in characterizing the cellular nature of the BBB and consequences of BBB dysfunction in pathology (brain metastasis, neurological diseases), it remains challenging to deliver drugs to the CNS. Herein, we outline the basic architecture and key molecular constituents of the BBB. In addition, we review the current status of approaches that are being explored to temporarily open the BBB in order to allow accumulation of therapeutics in the CNS. Undoubtedly, the major concern in field is whether it is possible to open the BBB in a meaningful way without causing negative consequences. In this context, we have also listed few other important key considerations that can improve our understanding about the dynamics of the BBB.The authors, DCF, RLR and JMO, would like to thank the funds under the project 2IQBIONEURO (reference: 0624_2IQBIONEURO_6_E) co-funded by INTERREG (Atlantic (Atlantic program or 622 V-A Spain-Portugal) and European fund for Regional Development (FEDER).Open Access funding enabled and organized by Projekt DEAL

{3D} Morphable Face Models -- Past, Present and Future

In this paper, we provide a detailed survey of 3D Morphable Face Models over the 20 years since they were first proposed. The challenges in building and applying these models, namely capture, modeling, image formation, and image analysis, are still active research topics, and we review the state-of-the-art in each of these areas. We also look ahead, identifying unsolved challenges, proposing directions for future research and highlighting the broad range of current and future applications

IL-23 suppresses innate immune response independently of IL-17A during carcinogenesis and metastasis

IL-23 is an important molecular driver of Th17 cells and has strong tumor-promoting proinflammatory activity postulated to occur via adaptive immunity. Conversely, more recently it has been reported that IL-17A elicits a protective inflammation that promotes the activation of tumor-specific CD8(+) T cells. Here we show the much broader impact of IL-23 in antagonizing antitumor immune responses primarily mediated by innate immunity. Furthermore, the majority of this impact was independent of IL-17A, which did not appear critical for many host responses to tumor initiation or metastases. IL-23-deficient mice were resistant to experimental tumor metastases in three models where host NK cells controlled disease. Immunotherapy with IL-2 was more effective in mice lacking IL-23, and again the protection afforded was NK cell mediated and independent of IL-17A. Further investigation revealed that loss of IL-23 promoted perforin and IFN-gamma antitumor effector function in both metastasis models examined. IL-23-deficiency also strikingly protected mice from tumor formation in two distinct mouse models of carcinogenesis where the dependence on host IL-12p40 and IL-17A was quite different. Notably, in the 3'-methylcholanthrene (MCA) induction of fibrosarcoma model, this protection was completely lost in the absence of NK cells. Overall, these data indicate the general role that IL-23 plays in suppressing natural or cytokine-induced innate immunity, promoting tumor development and metastases independently of IL-17A

Regulation of Tumor Immune Surveillance and Tumor Immune Subversion by TGF-β

Transforming growth factor-β (TGF-β) is a highly pleiotropic cytokine playing pivotal roles in immune regulation. TGF-β facilitates tumor cell survival and metastasis by targeting multiple cellular components. Focusing on its immunosuppressive functions, TGF-β antagonists have been employed for cancer treatment to enhance tumor immunity. TGF-β antagonists exert anti-tumor effects through #1 activating effector cells such as NK cells and cytotoxic CD8+ T cells (CTLs), #2 inhibiting regulatory/suppressor cell populations, #3 making tumor cells visible to immune cells, #4 inhibiting the production of tumor growth factors. This review focuses on the effect of TGF-β on T cells, which are differentiated into effector T cells or newly identified tumor-supporting T cells

An algorithm to compare two‐dimensional footwear outsole images using maximum cliques and speeded‐up robust feature

Footwear examiners are tasked with comparing an outsole impression (Q) left at a crime scene with an impression (K) from a database or from the suspect\u27s shoe. We propose a method for comparing two shoe outsole impressions that relies on robust features (speeded‐up robust feature; SURF) on each impression and aligns them using a maximum clique (MC). After alignment, an algorithm we denote MC‐COMP is used to extract additional features that are then combined into a univariate similarity score using a random forest (RF). We use a database of shoe outsole impressions that includes images from two models of athletic shoes that were purchased new and then worn by study participants for about 6 months. The shoes share class characteristics such as outsole pattern and size, and thus the comparison is challenging. We find that the RF implemented on SURF outperforms other methods recently proposed in the literature in terms of classification precision. In more realistic scenarios where crime scene impressions may be degraded and smudged, the algorithm we propose—denoted MC‐COMP‐SURF—shows the best classification performance by detecting unique features better than other methods. The algorithm can be implemented with the R‐package shoeprintr

Occlusion-aware 3D Morphable Models and an Illumination Prior for Face Image Analysis

Faces in natural images are often occluded by a variety of objects. We propose a fully automated, probabilistic and occlusion-aware 3D morphable face model adaptation framework following an analysis-by-synthesis setup. The key idea is to segment the image into regions explained by separate models. Our framework includes a 3D morphable face model, a prototype-based beard model and a simple model for occlusions and background regions. The segmentation and all the model parameters have to be inferred from the single target image. Face model adaptation and segmentation are solved jointly using an expectation-maximization-like procedure. During the E-step, we update the segmentation and in the M-step the face model parameters are updated. For face model adaptation we apply a stochastic sampling strategy based on the Metropolis-Hastings algorithm. For segmentation, we apply loopy belief propagation for inference in a Markov random field. Illumination estimation is critical for occlusion handling. Our combined segmentation and model adaptation needs a proper initialization of the illumination parameters. We propose a RANSAC-based robust illumination estimation technique. By applying this method to a large face image database we obtain a first empirical distribution of real-world illumination conditions. The obtained empirical distribution is made publicly available and can be used as prior in probabilistic frameworks, for regularization or to synthesize data for deep learning methods

First-in-class, first-in-human phase I results of targeted agents: Highlights of the 2008 American Society of Clinical Oncology meeting

This review summarizes phase I trial results of 11 drugs presented at the American Society of Clinical Oncology meeting held in Chicago IL from May 30 to June 3rd 2008: BMS-663513, CT-322, CVX-045, GDC-0449, GRN163L, LY2181308, PF-00562271, RAV12, RTA 402, XL765, and the survivin vaccine