Imbalanced data classification is a prevalent challenge in real-world applications. While a conventional sphere-based classification algorithm, random sphere cover (RSC), evenly constructs a set of ...spheres for two classes in balanced data using a parameter for the minimum sphere size, it struggles with constructing minority spheres in class-imbalanced data. Although RSC can be combined with existing oversampling methods, this approach requires additional hyperparameters, and its effectiveness decreases as the minority size decreases. To overcome these issues, we propose a novel approach that employs the area under the receiver operating characteristic curve (AUC) to construct and expand spheres for minority class. This parameter-free sphere classifier considers both the majority and minority classes simultaneously. We conducted a thorough experiment on both synthetic and 50 real datasets, which revealed that our proposed method outperformed existing various oversampling techniques with the lowest training time.
•A novel sphere-based algorithm for imbalanced data classification was proposed.•The proposed method was designed to maximize AUC of a trained classifier.•No hyperparameters need to be set for the proposed method.•The proposed method can effectively train a classifier for severely imbalanced data.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The present review summarizes the recent progresses in the synthesis of 2-pyrones and the application to the synthesis of marine natural products. Especially, much attention was placed on the ...transition metal catalyzed synthetic methodologies in this review.
This paper presents a novel end-to-end oversampling-classification approach, which we refer to as imbalanced data-classifying generative adversarial network (ImbGAN), for imbalanced data ...classification. ImbGAN has a classifier-embedded structure within a GAN and consists of five components: (1) generator, (2) discriminator, (3) classifier, (4) storage for misclassified minority class data, and (5) storage for artificial minority class data. By iterative interaction with the embedded classifier, the first two components generate artificial minority class instances that are similar to minority class instances misclassified by the classifier. Therefore, these three networks are iteratively and simultaneously trained. The misclassified and artificial minority class instances are stored in the fourth and fifth components, respectively. These two components are also updated as iterations proceed. Our method obtains the final classification model from a single learning process, while most artificial data generation methods for imbalanced data classification go through an additional process for training classifiers after artificial data generation. Numerical experiments based on tabular, image, and text datasets confirm that the proposed method outperforms well-known synthetic sampling methods.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Although transmission electron microscopy (TEM) may be one of the most efficient techniques available for studying the morphological characteristics of nanoparticles, analyzing them quantitatively in ...a statistical manner is exceedingly difficult. Herein, we report a method for mass-throughput analysis of the morphologies of nanoparticles by applying a genetic algorithm to an image analysis technique. The proposed method enables the analysis of over 150,000 nanoparticles with a high precision of 99.75% and a low false discovery rate of 0.25%. Furthermore, we clustered nanoparticles with similar morphological shapes into several groups for diverse statistical analyses. We determined that at least 1,500 nanoparticles are necessary to represent the total population of nanoparticles at a 95% credible interval. In addition, the number of TEM measurements and the average number of nanoparticles in each TEM image should be considered to ensure a satisfactory representation of nanoparticles using TEM images. Moreover, the statistical distribution of polydisperse nanoparticles plays a key role in accurately estimating their optical properties. We expect this method to become a powerful tool and aid in expanding nanoparticle-related research into the statistical domain for use in big data analysis.
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IJS, KILJ, NUK, PNG, UL, UM
This paper presents a modification of Quinlan's C4.5 algorithm for imbalanced data classification. While the C4.5 algorithm uses the difference in information entropy to determine the goodness of a ...split, the proposed method, which is named AUC4.5, examines the difference in the area under the ROC curve (AUC) of a split. It implies that our method attempts to maximize the AUC value of a trained decision tree in order to cope with class imbalance in data. An extensive experimental study was performed on 20 real datasets from the machine learning repository at the University of California at Irvine, Irvine. The proposed AUC4.5 algorithm showed better classification than both the standard and cost-sensitive C4.5 algorithms.
Lithium–oxygen (Li–O2) batteries have been intensively investigated in recent decades for their utilization in electric vehicles. The intrinsic challenges arising from O2 (electro)chemistry have ...been mitigated by developing various types of catalysts, porous electrode materials, and stable electrolyte solutions. At the next stage, we face the need to reform batteries by substituting pure O2 gas with air from Earth’s atmosphere. Thus, the key emerging challenges of Li–air batteries, which are related to the selective filtration of O2 gas from air and the suppression of undesired reactions with other constituents in air, such as N2, water vapor (H2O), and carbon dioxide (CO2), should be properly addressed. In this review, we discuss all key aspects for developing Li–air batteries that are optimized for operating in ambient air and highlight the crucial considerations and perspectives for future air-breathing batteries.
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Pembrolizumab, an inhibitor of programmed cell death 1 (PD-1), produced responses in 24% of patients with non–small-cell lung cancer, with a median overall survival of 16.2 months. The response rate ...increased to 45% if more than 50% of tumor cells expressed the PD-1 ligand.
Lung cancer is the leading cause of cancer-related death worldwide.
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Platinum-based chemotherapy, with or without maintenance therapy and subsequently followed by second-line cytotoxic chemotherapy, is standard treatment for most patients with advanced non–small-cell lung cancer, with a median survival of approximately 1 year.
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One hallmark of cancer is immune evasion, in which the immune system does not mount an effective antitumor response.
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Programmed cell death 1 (PD-1) is a negative costimulatory receptor expressed primarily on the surface of activated T cells.
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The binding of PD-1 to one of its ligands, PD-L1 or PD-L2, can inhibit a cytotoxic . . .
In CheckMate 227, nivolumab plus ipilimumab prolonged overall survival (OS) versus chemotherapy in patients with tumor programmed death-ligand 1 (PD-L1) greater than or equal to 1% (primary end ...point) or less than 1% (prespecified descriptive analysis). We report results with minimum 4 years' follow-up.
Adults with previously untreated stage IV or recurrent NSCLC were randomized (1:1:1) to nivolumab plus ipilimumab, nivolumab, or chemotherapy (PD-L1 ≥1%); or to nivolumab plus ipilimumab, nivolumab plus chemotherapy, or chemotherapy (PD-L1 <1%). Efficacy included OS and other measures. Safety included timing and management of immune-mediated adverse events (AEs). A post hoc analysis evaluated efficacy in patients who discontinued nivolumab plus ipilimumab due to treatment-related AEs (TRAEs).
After 54.8 months' median follow-up, OS remained longer with nivolumab plus ipilimumab versus chemotherapy in patients with PD-L1 greater than or equal to 1% (hazard ratio = 0.76; 95% confidence interval: 0.65–0.90) and PD-L1 less than 1% (0.64; 0.51–0.81); 4-year OS rate with nivolumab plus ipilimumab versus chemotherapy was 29% versus 18% (PD-L1 ≥1%); and 24% versus 10% (PD-L1 <1%). Benefits were observed in both squamous and nonsquamous histologies. In a descriptive analysis, efficacy was improved with nivolumab plus ipilimumab relative to nivolumab (PD-L1 ≥1%) and nivolumab plus chemotherapy (PD-L1 <1%). Safety was consistent with previous reports. The most common immune-mediated AE with nivolumab plus ipilimumab, nivolumab, and nivolumab plus chemotherapy was rash; most immune-mediated AEs (except endocrine events) occurred within 6 months from start of treatment and resolved within 3 months after, mainly with systemic corticosteroids. Patients who discontinued nivolumab plus ipilimumab due to TRAEs had long-term OS benefits, as seen in the all randomized population.
At more than 4 years' minimum follow-up, with all patients off immunotherapy treatment for at least 2 years, first-line nivolumab plus ipilimumab continued to demonstrate durable long-term efficacy in patients with advanced NSCLC. No new safety signals were identified. Immune-mediated AEs occurred early and resolved quickly with guideline-based management. Discontinuation of nivolumab plus ipilimumab due to TRAEs did not have a negative impact on the long-term benefits seen in all randomized patients.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Summary Background Atezolizumab is a humanised antiprogrammed death-ligand 1 (PD-L1) monoclonal antibody that inhibits PD-L1 and programmed death-1 (PD-1) and PD-L1 and B7-1 interactions, ...reinvigorating anticancer immunity. We assessed its efficacy and safety versus docetaxel in previously treated patients with non-small-cell lung cancer. Methods We did a randomised, open-label, phase 3 trial (OAK) in 194 academic or community oncology centres in 31 countries. We enrolled patients who had squamous or non-squamous non-small-cell lung cancer, were 18 years or older, had measurable disease per Response Evaluation Criteria in Solid Tumors, and had an Eastern Cooperative Oncology Group performance status of 0 or 1. Patients had received one to two previous cytotoxic chemotherapy regimens (one or more platinum based combination therapies) for stage IIIB or IV non-small-cell lung cancer. Patients with a history of autoimmune disease and those who had received previous treatments with docetaxel, CD137 agonists, anti-CTLA4, or therapies targeting the PD-L1 and PD-1 pathway were excluded. Patients were randomly assigned (1:1) to intravenously receive either atezolizumab 1200 mg or docetaxel 75 mg/m2 every 3 weeks by permuted block randomisation (block size of eight) via an interactive voice or web response system. Coprimary endpoints were overall survival in the intention-to-treat (ITT) and PD-L1-expression population TC1/2/3 or IC1/2/3 (≥1% PD-L1 on tumour cells or tumour-infiltrating immune cells). The primary efficacy analysis was done in the first 850 of 1225 enrolled patients. This study is registered with ClinicalTrials.gov , number NCT02008227. Findings Between March 11, 2014, and April 29, 2015, 1225 patients were recruited. In the primary population, 425 patients were randomly assigned to receive atezolizumab and 425 patients were assigned to receive docetaxel. Overall survival was significantly longer with atezolizumab in the ITT and PD-L1-expression populations. In the ITT population, overall survival was improved with atezolizumab compared with docetaxel (median overall survival was 13·8 months 95% CI 11·8–15·7 vs 9·6 months 8·6–11·2; hazard ratio HR 0·73 95% CI 0·62–0·87, p=0·0003). Overall survival in the TC1/2/3 or IC1/2/3 population was improved with atezolizumab (n=241) compared with docetaxel (n=222; median overall survival was 15·7 months 95% CI 12·6–18·0 with atezolizumab vs 10·3 months 8·8–12·0 with docetaxel; HR 0·74 95% CI 0·58–0·93; p=0·0102). Patients in the PD-L1 low or undetectable subgroup (TC0 and IC0) also had improved survival with atezolizumab (median overall survival 12·6 months vs 8·9 months; HR 0·75 95% CI 0·59–0·96). Overall survival improvement was similar in patients with squamous (HR 0·73 95% CI 0·54–0·98; n=112 in the atezolizumab group and n=110 in the docetaxel group) or non-squamous (0·73 0·60–0·89; n=313 and n=315) histology. Fewer patients had treatment-related grade 3 or 4 adverse events with atezolizumab (90 15% of 609 patients) versus docetaxel (247 43% of 578 patients). One treatment-related death from a respiratory tract infection was reported in the docetaxel group. Interpretation To our knowledge, OAK is the first randomised phase 3 study to report results of a PD-L1-targeted therapy, with atezolizumab treatment resulting in a clinically relevant improvement of overall survival versus docetaxel in previously treated non-small-cell lung cancer, regardless of PD-L1 expression or histology, with a favourable safety profile. Funding F. Hoffmann-La Roche Ltd, Genentech, Inc.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The mitochondria-associated membrane (MAM) has emerged as a cellular signaling hub regulating various cellular processes. However, its molecular components remain unclear owing to lack of reliable ...methods to purify the intact MAM proteome in a physiological context. Here, we introduce Contact-ID, a split-pair system of BioID with strong activity, for identification of the MAM proteome in live cells. Contact-ID specifically labeled proteins proximal to the contact sites of the endoplasmic reticulum (ER) and mitochondria, and thereby identified 115 MAM-specific proteins. The identified MAM proteins were largely annotated with the outer mitochondrial membrane (OMM) and ER membrane proteins with MAM-related functions: e.g., FKBP8, an OMM protein, facilitated MAM formation and local calcium transport at the MAM. Furthermore, the definitive identification of biotinylation sites revealed membrane topologies of 85 integral membrane proteins. Contact-ID revealed regulatory proteins for MAM formation and could be reliably utilized to profile the proteome at any organelle–membrane contact sites in live cells.
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