The objective of change-point detection is to discover abrupt property changes lying behind time-series data. In this paper, we present a novel statistical change-point detection algorithm based on ...non-parametric divergence estimation between time-series samples from two retrospective segments. Our method uses the relative Pearson divergence as a divergence measure, and it is accurately and efficiently estimated by a method of direct density-ratio estimation. Through experiments on artificial and real-world datasets including human-activity sensing, speech, and Twitter messages, we demonstrate the usefulness of the proposed method.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The goal of supervised feature selection is to find a subset of input features that are responsible for predicting output values. The least absolute shrinkage and selection operator (Lasso) allows ...computationally efficient feature selection based on linear dependency between input features and output values. In this letter, we consider a feature-wise kernelized Lasso for capturing nonlinear input-output dependency. We first show that with particular choices of kernel functions, nonredundant features with strong statistical dependence on output values can be found in terms of kernel-based independence measures such as the Hilbert-Schmidt independence criterion. We then show that the globally optimal solution can be efficiently computed; this makes the approach scalable to high-dimensional problems. The effectiveness of the proposed method is demonstrated through feature selection experiments for classification and regression with thousands of features.
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Background
Specific treatment strategies are sorely needed for scirrhous-type gastric cancer still, which has poor prognosis. Based on the promising results of our previous phase II study (JCOG0210), ...we initiated a phase III study to confirm the efficacy of neoadjuvant chemotherapy (NAC) in type 4 or large type 3 gastric cancer.
Methods
Patients aged 20–75 years without a macroscopic unresectable factor as confirmed via staging laparoscopy were randomly assigned to surgery followed by adjuvant chemotherapy with S-1 (Arm A) or NAC (S-1plus cisplatin) followed by D2 gastrectomy plus adjuvant chemotherapy with S-1 (Arm B). The primary endpoint was overall survival (OS).
Results
Between October 2005 and July 2013, 316 patients were enrolled, allocating 158 patients to each arm. In Arm B, in which NAC was completed in 88% of patients. Significant downstaging based on tumor depth, lymph node metastasis, and peritoneal cytology was observed using NAC. Excluding the initial 16 patients randomized before the first revision of the protocol, 149 and 151 patients in arms A and B, respectively, were included in the primary analysis. The 3-year OS rates were 62.4% 95% confidence interval (CI) 54.1–69.6 in Arm A and 60.9% (95% CI 52.7–68.2) in Arm B. The hazard ratio of Arm B against Arm A was 0.916 (95% CI 0.679–1.236).
Conclusions
For type 4 or large type 3 gastric cancer, NAC with S-1 plus cisplatin failed to demonstrate a survival benefit. D2 surgery followed by adjuvant chemotherapy remains the standard treatment.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The ability to rapidly assay morphological and intracellular molecular variations within large heterogeneous populations of cells is essential for understanding and exploiting cellular heterogeneity. ...Optofluidic time-stretch microscopy is a powerful method for meeting this goal, as it enables high-throughput imaging flow cytometry for large-scale single-cell analysis of various cell types ranging from human blood to algae, enabling a unique class of biological, medical, pharmaceutical, and green energy applications. Here, we describe how to perform high-throughput imaging flow cytometry by optofluidic time-stretch microscopy. Specifically, this protocol provides step-by-step instructions on how to build an optical time-stretch microscope and a cell-focusing microfluidic device for optofluidic time-stretch microscopy, use it for high-throughput single-cell image acquisition with sub-micrometer resolution at >10,000 cells per s, conduct image construction and enhancement, perform image analysis for large-scale single-cell analysis, and use computational tools such as compressive sensing and machine learning for handling the cellular 'big data'. Assuming all components are readily available, a research team of three to four members with an intermediate level of experience with optics, electronics, microfluidics, digital signal processing, and sample preparation can complete this protocol in a time frame of 1 month.
This letter reports a proof‐of‐concept experiment conducted on a novel application of the multi‐core fibre (MCF), where image reconstruction is based on a single‐pixel imaging (SPI) technique and the ...diffraction pattern emitted from an MCF. The technique is intended to reduce the size of the SPI system, the applications of which can now be extended with the help of this study.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Abstract
Motivation
Finding non-linear relationships between biomolecules and a biological outcome is computationally expensive and statistically challenging. Existing methods have important ...drawbacks, including among others lack of parsimony, non-convexity and computational overhead. Here we propose block HSIC Lasso, a non-linear feature selector that does not present the previous drawbacks.
Results
We compare block HSIC Lasso to other state-of-the-art feature selection techniques in both synthetic and real data, including experiments over three common types of genomic data: gene-expression microarrays, single-cell RNA sequencing and genome-wide association studies. In all cases, we observe that features selected by block HSIC Lasso retain more information about the underlying biology than those selected by other techniques. As a proof of concept, we applied block HSIC Lasso to a single-cell RNA sequencing experiment on mouse hippocampus. We discovered that many genes linked in the past to brain development and function are involved in the biological differences between the types of neurons.
Availability and implementation
Block HSIC Lasso is implemented in the Python 2/3 package pyHSICLasso, available on PyPI. Source code is available on GitHub (https://github.com/riken-aip/pyHSICLasso).
Supplementary information
Supplementary data are available at Bioinformatics online.
Background
Patients with peritoneal dissemination of gastric cancer have poor oral intake caused by malignant bowel obstruction (MBO). Palliative surgery has often been undertaken to improve quality ...of life (QOL), but few prospective studies on palliative surgery in this patient population have been published.
Patients and methods
We prospectively investigated the significance of palliative surgery using patient-reported QOL measures. Patients underwent palliative surgery by small intestine/colon resection or small intestine/colon bypass or ileostomy/colostomy for MBO. The primary endpoint was change in QOL assessed at baseline, 14 days, 1 month, and 3 months following palliative surgery using the Euro QoL Five Dimensions (EQ-5D™) questionnaire and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire gastric cancer module (QLQ-STO22). Secondary endpoints were postoperative improvement in oral intake and surgical complications.
Results
Between April 2013 and March 2018, 63 patients were enrolled from 14 institutions. The mean EQ-5D™ utility index baseline score of 0.6 remained consistent. Gastric-specific symptoms mostly showed statistically significant improvement from baseline. Forty-two patients (67%) were able to eat solid food 2 weeks after palliative surgery and 36 patients (57%) tolerated it for 3 months. The rate of overall morbidity of ≥ grade III according to the Clavien–Dindo classification was 16% (10 patients) and the 30-day postoperative mortality rate was 3.2% (2 patients).
Conclusions
In patients with MBO caused by peritoneal dissemination of gastric cancer, palliative surgery did not improve QOL while improving solid food intake, with an acceptable postoperative morbidity and mortality rate.
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Background
Preoperative chemotherapy with cisplatin plus S-1 (CS) followed by gastrectomy with D2 plus para-aortic lymph node (PAN) dissection is regarded as a standard treatment in Japan for ...advanced gastric cancer with bulky lymph node (BN) and/or PAN metastasis. In the JCOG1002, we added docetaxel to CS (DCS) to further improve long-term outcomes. However, the primary endpoint, clinical response rate (RR), did not reach the expected level (Ito et al. in Gastric Cancer 20:322–31, 2017). Herein, we report our long-term survival results.
Methods
Patients with BN and/or PAN metastasis received 2 or 3 cycles of DCS therapy (docetaxel at 40 mg/m
2
and cisplatin at 60 mg/m
2
on day 1 and S-1 at 80 mg/m
2
per day for 2 weeks, followed by a 2-week rest) followed by gastrectomy with D2 plus PAN dissection and postoperative S-1 for 1 year.
Results
Between July 2011 and May 2013, 53 patients were enrolled. Clinically, 17.0% had both PAN and BN metastasis, and the rest had either PAN (26.4%) or BN (56.6%) metastasis. Among all eligible patients, the 5-year overall survival was 54.9% (95% confidence interval 40.3–67.3%) at the last follow-up in May 2018. Among 44 eligible patients with R0 resection, the 5-year relapse-free survival was 47.7% (95% confidence interval 32.5–61.5%).
Conclusions
Adding docetaxel to CS in preoperative chemotherapy for extensive nodal metastasis improved neither short-term outcomes nor long-term survival. Preoperative chemotherapy with CS followed by D2 + PAN dissection and postoperative S-1 remains the standard of care for patients with extensive nodal metastasis.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
We propose a set of convex low-rank inducing norms for coupled matrices and tensors (hereafter referred to as coupled tensors), in which information is shared between the matrices and tensors through ...common modes. More specifically, we first propose a mixture of the overlapped trace norm and the latent norms with the matrix trace norm, and then, propose a completion model regularized using these norms to impute coupled tensors. A key advantage of the proposed norms is that they are convex and can be used to find a globally optimal solution, whereas existing methods for coupled learning are nonconvex. We also analyze the excess risk bounds of the completion model regularized using our proposed norms and show that they can exploit the low-rankness of coupled tensors, leading to better bounds compared to those obtained using uncoupled norms. Through synthetic and real-data experiments, we show that the proposed completion model compares favorably with existing ones.
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•We propose to recommend a publication venue to maximize the influence of a paper•We formulate venue recommendation through the lens of treatment effect estimation•We propose to a debiasing method to ...estimate the potential impact of a venue•We empirically investigate the effect of our proposed method
Choosing a publication venue for an academic paper is a crucial step in the research process. However, in many cases, decisions are based solely on the experience of researchers, which often leads to suboptimal results. Although there exist venue recommender systems for academic papers, they recommend venues where the paper is expected to be published. In this study, we aim to recommend publication venues from a different perspective. We estimate the number of citations a paper will receive if the paper is published in each venue and recommend the venue where the paper has the most potential impact. However, there are two challenges to this task. First, a paper is published in only one venue, and thus, we cannot observe the number of citations the paper would receive if the paper were published in another venue. Secondly, the contents of a paper and the publication venue are not statistically independent; that is, there exist selection biases in choosing publication venues. In this paper, we formulate the venue recommendation problem as a treatment effect estimation problem. We use a bias correction method to estimate the potential impact of choosing a publication venue effectively and to recommend venues based on the potential impact of papers in each venue. We highlight the effectiveness of our method using paper data from computer science conferences.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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