Biomarkers on the basis of tumor-infiltrating lymphocytes (TIL) are potentially valuable in predicting the effectiveness of immune checkpoint inhibitors (ICI). However, clinical application remains ...challenging because of methodologic limitations and laborious process involved in spatial analysis of TIL distribution in whole-slide images (WSI).
We have developed an artificial intelligence (AI)-powered WSI analyzer of TIL in the tumor microenvironment that can define three immune phenotypes (IPs): inflamed, immune-excluded, and immune-desert. These IPs were correlated with tumor response to ICI and survival in two independent cohorts of patients with advanced non-small-cell lung cancer (NSCLC).
Inflamed IP correlated with enrichment in local immune cytolytic activity, higher response rate, and prolonged progression-free survival compared with patients with immune-excluded or immune-desert phenotypes. At the WSI level, there was significant positive correlation between tumor proportion score (TPS) as determined by the AI model and control TPS analyzed by pathologists (
< .001). Overall, 44.0% of tumors were inflamed, 37.1% were immune-excluded, and 18.9% were immune-desert. Incidence of inflamed IP in patients with programmed death ligand-1 TPS at < 1%, 1%-49%, and ≥ 50% was 31.7%, 42.5%, and 56.8%, respectively. Median progression-free survival and overall survival were, respectively, 4.1 months and 24.8 months with inflamed IP, 2.2 months and 14.0 months with immune-excluded IP, and 2.4 months and 10.6 months with immune-desert IP.
The AI-powered spatial analysis of TIL correlated with tumor response and progression-free survival of ICI in advanced NSCLC. This is potentially a supplementary biomarker to TPS as determined by a pathologist.
Recent research studies on outlier detection have focused on examining the nearest neighbor structure of a data object to measure its outlierness degree. This leads to two weaknesses: the size of ...nearest neighborhood, which should be predetermined, greatly affects the final detection results, and the outlierness scores produced by existing methods are not sufficiently diverse to allow precise ranking of outliers. To overcome these problems, in this research paper, a novel outlier detection method involving an iterative random sampling procedure is proposed. The proposed method is inspired by the simple notion that outlying objects are less easily selected than inlying objects in blind random sampling, and therefore, more inlierness scores are given to selected objects. We develop a new measure called the observability factor (OF) by utilizing this idea. In order to offer a heuristic guideline to determine the best size of nearest neighborhood, we additionally propose using the entropy of OF scores. An intensive numerical evaluation based on various synthetic and real-world datasets shows the superiority and effectiveness of the proposed method.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
In this article, we propose a novel model-parallel learning method, called local critic training , which trains neural networks using additional modules called local critic networks . The main ...network is divided into several layer groups, and each layer group is updated through error gradients estimated by the corresponding local critic network. We show that the proposed approach successfully decouples the update process of the layer groups for both convolutional neural networks (CNNs) and recurrent neural networks (RNNs). In addition, we demonstrate that the proposed method is guaranteed to converge to a critical point. We also show that trained networks by the proposed method can be used for structural optimization. Experimental results show that our method achieves satisfactory performance, reduces training time greatly, and decreases memory consumption per machine. Code is available at https://github.com/hjdw2/Local-critic-training .
Assessing image aesthetics is a challenging computer vision task. One reason is that aesthetic preference is highly subjective and may vary significantly among people for certain images. Thus, it is ...important to properly model and quantify such subjectivity, but there has not been much effort to resolve this issue. In this paper, we propose a novel probabilistic framework that can model and quantify subjective aesthetic preference based on the subjective logic. In this framework, the rating distribution is modeled as a beta distribution, from which the probabilities of being definitely pleasing, being definitely unpleasing, and being uncertain can be obtained. We use the probability of being uncertain to define an intuitive metric of subjectivity. Furthermore, we present a method to learn deep neural networks for prediction of image aesthetics, which is shown to be effective in improving the performance of subjectivity prediction via experiments.
Cellular lipid metabolism has been linked to immune responses; however, the precise mechanisms by which de novo fatty acid synthesis can regulate inflammatory responses remain unclear. The NLRP3 ...inflammasome serves as a platform for caspase-1-dependent maturation and secretion of proinflammatory cytokines. Here, we demonstrated that the mitochondrial uncoupling protein-2 (UCP2) regulates NLRP3-mediated caspase-1 activation through the stimulation of lipid synthesis in macrophages. UCP2-deficient mice displayed improved survival in a mouse model of polymicrobial sepsis. Moreover, UCP2 expression was increased in human sepsis. Consistently, UCP2-deficient mice displayed impaired lipid synthesis and decreased production of IL-1β and IL-18 in response to LPS challenge. In macrophages, UCP2 deficiency suppressed NLRP3-mediated caspase-1 activation and NLRP3 expression associated with inhibition of lipid synthesis. In UCP2-deficient macrophages, inhibition of lipid synthesis resulted from the downregulation of fatty acid synthase (FASN), a key regulator of fatty acid synthesis. FASN inhibition by shRNA and treatment with the chemical inhibitors C75 and cerulenin suppressed NLRP3-mediated caspase-1 activation and inhibited NLRP3 and pro-IL-1β gene expression in macrophages. In conclusion, our results suggest that UCP2 regulates the NLRP3 inflammasome by inducing the lipid synthesis pathway in macrophages. These results identify UCP2 as a potential therapeutic target in inflammatory diseases such as sepsis.
Background and Purpose
Kazinol U is a prenylated flavan isolated from an extract of Broussonetia kazinoki Sieb (Moraceae). Kazinol U has shown cytoprotective effects against cytokine‐induced ...apoptotic cell death and induces AMP kinase (AMPK) activation through LKB1 activation. However, kazinol U has not been tested as a regulator of melanogenesis, although bark extract of B. kazinoki has been used as a cosmetic ingredient for skin conditioning.
Experimental Approach
We cultured mouse, human melanoma cells and normal human melanocytes to demonstrate anti‐melanogenic effects of kazinol U. A tyrosinase activity assay, Western blot, RT‐qPCR and a luciferase reporter gene assay were performed to determine the anti‐melanogenic mechanisms of kazinol U. We confirmed its effect on melanogenesis in vivo using zebrafish.
Key Results
Kazinol U inhibited the expression and activity of tyrosinase, the rate‐limiting enzyme in melanogenesis, and reduced tyrosinase expression and activity in response to cAMP‐inducing agents. Kazinol U reduced the expression of other melanogenic enzymes, such as tyrosinase‐related protein (Tyrp) 1 and Tyrp2, and down‐regulated microphthalmia‐associated transcription factor (MITF), the master regulator of the tyrosinase gene family. Moreover, kazinol U induced phosphorylation of AMPK and MAPK proteins, which are MITF inhibitors. It also exhibited anti‐melanogenic effects in zebrafish, a recently developed in vivo model.
Conclusions and Implications
Our findings suggest that kazinol U reduces melanogenesis via its inhibitory effect on MITF and its downstream target genes, tyrosinase, Tyrp1 and Tyrp2. This work may provide a basis for the application of kazinol U for the treatment of hyperpigmentation skin disorders.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
Arteriovenous malformation (AVM) is characterized by high-flow blood vessels connecting arteries and veins without capillaries. This disease shows increased angiogenesis and a pathophysiological ...hypoxic environment in proximal tissues. Here, we analyzed the effects of hypoxia on angiogenesis in the endothelial cells (ECs) of AVM and normal tissues. ECs from human normal and AVM tissues were evaluated using immunocytochemistry with CD31. In vitro tube formation under hypoxia was tested in both ECs using Matrigel. The relative expression of angiogenesis-related genes was measured using real-time PCR. Under normoxia, CD31 was significantly higher in AVM ECs (79.23 ± 0.65%) than in normal ECs (74.15 ± 0.70%). Similar results were observed under hypoxia in AVM ECs (63.85 ± 1.84%) and normal ECs (60.52 ± 0.51%). In the tube formation test under normoxic and hypoxic conditions, the junction count and total vessel length were significantly greater in AVM ECs than normal ECs. Under both normoxia and hypoxia, the angiogenesis-related gene FSTL1 showed a significantly higher expression in AVM ECs than in normal ECs. Under hypoxia, CSPG4 expression was significantly lower in AVM ECs than in normal ECs. Accordingly, the angiogenic effect was increased in AVM ECs compared with that in normal ECs. These results provide a basic knowledge for an AVM treatment strategy.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Microphthalmia-associated transcription factor (MITF), a basic helix-loop-helix leucine zipper transcription factor (bHLH-Zip), has been identified as a melanocyte-specific transcription factor and ...plays a critical role in melanocyte survival, differentiation, function, proliferation and pigmentation. Although numerous studies have explained the roles of MITF in melanocytes and in melanoma development, the function of MITF in the hematopoietic or immune system-beyond its function in melanin-producing cells-is not yet fully understood. However, there is convincing and increasing evidence suggesting that MITF may play multiple important roles in immune-related cells. Therefore, this review is focused on recent advances in elucidating novel functions of MITF in cancer progression and immune responses to cancer. In particular, we highlight the role of MITF as a central modulator in the regulation of immune responses, as elucidated in recent studies.
Background
Venous malformations (VMs) are distinguished from lymphatic malformations (LMs) when specific diagnostic skin lesions are present. In the deep type, this is difficult by clinico‐radiologic ...evaluation alone. We aimed to investigate the usefulness of lymphatic vessel endothelial cell (LEC) markers for the differential diagnosis of the deep VMs and LMs.
Methods
A retrospective study was conducted based on the medical records of patients with VMs and LMs who underwent biopsy with both D2‐40 and PROX‐1 immunohistochemistry. We compared the initial clinico‐radiological diagnosis with the final pathological diagnosis and identified which ones showed a difference.
Results
From 261 patients who had VMs and LMs, 111 remained after the exclusion of those who showed definite surface diagnostic features. After pathological diagnosis with the expressions of D2‐40 and PROX‐1, 38 of 111 (34.2%) patients' final diagnoses were changed. Among these 38 cases, diagnosis was not changed by D2‐40 positivity alone, but changed by PROX‐1 positivity alone (52.6%) or by both (47.4%). The diagnostic changes were more frequent in the deep category (43.7%) than in the superficial category.
Conclusions
Identifying the expression of D2‐40, and especially PROX‐1, in the differential diagnosis of VMs and LMs may provide important treatment guidelines and understanding their natural course.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Since outlier detection is applicable to various fields such as the financial, telecommunications, medical, and commercial industries, its importance is radically increasing. Receiving such great ...attention has led to the development of many detection methods, most of which pertain to either the distance-based approach or the density-based approach. However, each approach has intrinsic weaknesses. The former hardly detects local outliers, while the latter has the low density patterns problem. To overcome these weaknesses, we proposed a new detection method that introduces the instability factor of a data point by utilizing the concept of the center of gravity. The proposed method can be flexibly used for both local and global detection of outliers by controlling its parameter. In addition, it offers the instability plot containing useful information about the number and size of clusters in data. Numerical experiments based on artificial and real datasets show the effectiveness of the proposed method.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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