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Predicting drug response through tumor deconvolution by cancer cell lines

Patterns 2024年第4期5卷 100949页

作者： Hsu, Yu-Ching Chiu, Yu-Chiao Lu, Tzu-Pin Hsiao, Tzu-Hung Chen, Yidong Bioinformatics Program Taiwan International Graduate Program National Taiwan University Taipei115 Taiwan Bioinformatics Program Institute of Statistical Science Taiwan International Graduate Program Academia Sinica Taipei115 Taiwan Institute of Health Data Analytics and Statistics Department of Public Health College of Public Health National Taiwan University Taipei100 Taiwan Greehey Children's Cancer Research Institute University of Texas Health San Antonio San AntonioTX78229 United States Department of Medicine School of Medicine University of Pittsburgh PittsburghPA15261 United States UPMC Hillman Cancer Center University of Pittsburgh PittsburghPA15232 United States Department of Medical Research Taichung Veterans General Hospital Taichung40705 Taiwan Department of Population Health Sciences University of Texas Health San Antonio San AntonioTX78229 United States

Large-scale cancer drug sensitivity data have become available for a collection of cancer cell lines, but only limited drug response data from patients are available. Bridging the gap in pharmacogenomics knowledge between in vitro and in vivo datasets remains challenging. In this study, we trained a deep learning model, Scaden-CA, for deconvoluting tumor data into proportions of cancer-type-specific cell lines. Then, we developed a drug response prediction method using the deconvoluted proportions and the drug sensitivity data from cell lines. The Scaden-CA model showed excellent performance in terms of concordance correlation coefficients (>0.9 for model testing) and the correctly deconvoluted rate (>70% across most cancers) for model validation using Cancer Cell Line Encyclopedia (CCLE) bulk RNA data. We applied the model to tumors in The Cancer Genome Atlas (TCGA) dataset and examined associations between predicted cell viability and mutation status or gene expression levels to understand underlying mechanisms of potential value for drug repurposing. © 2024 The Authors

关键词： Tumors

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COVID-19 detection in computed tomography images with 2D and 3D approaches

arXiv

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arXiv 2021年

作者： Ali Ahmed, Sara Atito Can Yavuz, Mehmet Umut Sen, Mehmet Gulsen, Fatih Tutar, Onur Korkmazer, Bora Samancı, Cesur Şirolu, Sabri Hamid, Rauf Eryürekli, Ali Ergun Mammadov, Toghrul Yanikoglu, Berrin Sabanci University Istanbul34956 Turkey Urbanstat The Istanbul University-Cerrahpaşa Cerrahpaşa Faculty of Medicine Turkey The Computer Science and Engineering Program Sabanci University Istanbul34956 Turkey The Sabanci University Center of Excellence in Data Analytics

Detecting COVID-19 in computed tomography (CT) or radiography images has been proposed as a supplement to the definitive RT-PCR test. We present a deep learning ensemble for detecting COVID-19 infection, combining slice-based (2D) and volume-based (3D) approaches. The 2D system detects the infection on each CT slice independently, combining them to obtain the patient-level decision via different methods (averaging and long-short term memory networks). The 3D system takes the whole CT volume to arrive to the patient-level decision in one step. A new high resolution chest CT scan dataset, called the IST-C dataset, is also collected in this work. The proposed ensemble, called IST-CovNet, obtains 90.80% accuracy and 0.95 AUC score overall on the IST-C dataset in detecting COVID-19 among normal controls and other types of lung pathologies;and 93.69% accuracy and 0.99 AUC score on the publicly available MosMed dataset that consists of COVID-19 scans and normal controls only.. The system is deployed at Istanbul University Cerrahpaşa School of Medicine. Copyright © 2021, The Authors. All rights reserved.

关键词： Computerized tomography

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Robust shape estimation with false-positive contact detection

arXiv

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arXiv 2021年

作者： Shibata, Kazuki Miyano, Tatsuya Jimbo, Tomohiko Matsubara, Takamitsu Autonomous Distributed Cooperative Control Program Data Analytics Research-Domain Toyota Central RandD Labs. Inc. 41-1 Yokomichi Nagakute Aichi Japan Graduate School of Science and Technology Division of Information Science Nara Institute of Science and Technology Nara Japan

We propose a means of omni-directional contact detection using accelerometers instead of tactile sensors for object shape estimation using touch. Unlike tactile sensors, our contact-based detection method tends to induce a degree of uncertainty with false-positive contact data because the sensors may react not only to actual contact but also to the unstable behavior of the robot. Therefore, it is crucial to consider a robust shape estimation method capable of handling such false-positive contact data. To realize this, we introduce the concept of heteroscedasticity into the contact data and propose a robust shape estimation algorithm based on Gaussian process implicit surfaces (GPIS). We confirmed that our algorithm not only reduces shape estimation errors caused by false-positive contact data but also distinguishes false-positive contact data more clearly than the GPIS through simulations and actual experiments using a quadcopter. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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Evolution, Sympatric Speciation, and Risk Aversion

Evolution, Sympatric Speciation, and Risk Aversion

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Oluwatobi I. Ajagbe Dean Frederick Hougen Data Science and Analytics Program University of Oklahoma Norman Oklahoma USA School of Computer Science University of Oklahoma Norman Oklahoma USA

ISBN: (数字)9781728125473

ISBN: (纸本)9781728125480

Speciation is a crucial topic in the biological sciences. Knowledge of this process helps explain the diversity of life. In the computational realm, considerable efforts have been made to understand mechanisms and conditions that lead to speciation. Speciation has profound implications for artificial life, evolutionary computation, and evolutionary robotics, yet many aspects of it remain unexplored. Resource distribution is one of the key factors in natural selection, which is critical for sympatric speciation. Research on speciation typically assumes that there is a consistent supply of resources in each available niche. However, fluctuations in available resources might have strong impacts on the extent to which niches are occupied. Such fluctuations could be seen as analogous to risk in economics. Moreover, just as risk necessarily leads to risk aversion in reinforcement learning agents, so might fluctuations in resources lead to a phenomenon analogous to risk aversion in evolution. In this study, the effects of fluctuations in resource distribution are investigated in a simulated biological setting that has been established to favor sympatric speciation. We conclude that fluctuations in resource distribution lead to risk aversion in the process of evolution.

关键词： Birds Beak Statistics Sociology Evolution (biology) Standards Resource management

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Method for modelling the number of HIV and AIDS cases using least square spline Biresponse nonparametric negative binomial regression

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MethodsX 2025年 14卷 103336页

作者： Ramadan, Arip Chamidah, Nur Budiantara, I Nyoman Lestari, Budi Aydin, Dursun Doctoral Study Program of Mathematics and Natural Sciences Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Information System Study Program Department of Industrial and System Engineering Telkom University Surabaya Campus Surabaya 60231 Indonesia Department of Mathematics Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Research Group of Statistical Modeling in Life Science Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Statistics Department Faculty of Science and Data Analytics Sepuluh Nopember Institute of Technology Surabaya 60111 Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences The University of Jember Jember 68121 Indonesia Department of Statistics Faculty of Science Muğla Sıtkı Koçman University Muğla 48000 Turkey Research Scholar at Department of Mathematics University of Wisconsin Oshkosh Algoma Blvd Oshkosh 54901 WI United States

We propose a new statistical modeling method to analyze functional relationship between predictor variables and correlated response variables, and apply it for modeling the number of HIV and AIDS cases influenced by early-age marriages and contraceptive users. The proposed method is LS-Spline BNNBR that is a Biresponse Nonparametric Negative Binomial Regression (BNNBR) based on least squares spline (LS-Spline). To validate the proposed method, we compare it with classical method, namely Ordinary Least Square Biresponse Parametric Negative Binomial Regression (OLS-BPNBR). The results show that the LS-Spline BNNBR method provided deviance value of 7.542334 which is smaller than that of OLS-BPNBR method, namely 7.993935. Thus, the proposed method has better prediction fit than the classical method. • This study discusses new statistical modeling method for the number of HIV and AIDS cases influenced by early-age marriages and contraceptive users where the response variables are correlated with each other. • The model estimation results show that the number of HIV and AIDS cases in Indonesia will decrease if the early-age marriages percentage increases and the contraceptive users percentage decreases. • The results are useful to provide a scientific basis for making policies to control the number of HIV and AIDS cases in Indonesia. © 2025 The Authors

关键词： AIDS BLSSNNBR model Contraceptive user Early-age marriage HIV Least square spline

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Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport

arXiv

引用

arXiv 2021年

作者： Shibata, Kazuki Jimbo, Tomohiko Matsubara, Takamitsu Autonomous Distributed Cooperative Control Program Data Analytics Research-Domain Toyota Central R&D Labs. Inc. 41-1 Yokomichi Nagakute Aichi Japan Graduate School of Science and Technology Division of Information Science Nara Institute of Science and Technology Nara Japan

In this paper, we explore a multi-agent reinforcement learning approach to address the design problem of communication and control strategies for multi-agent cooperative transport. Typical end-to-end deep neural network policies may be insufficient for covering communication and control;these methods cannot decide the timing of communication and can only work with fixed-rate communications. Therefore, our framework exploits event-triggered architecture, namely, a feedback controller that computes the communication input and a triggering mechanism that determines when the input has to be updated again. Such event-triggered control policies are efficiently optimized using a multi-agent deep deterministic policy gradient. We confirmed that our approach could balance the transport performance and communication savings through numerical simulations. Copyright © 2021, The Authors. All rights reserved.

关键词： Multi agent systems

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Spin-tunable thermoelectric performance in monolayer chromium pnictides

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Physical Review Materials 2022年第6期6卷 064010-064010页

作者： Melania S. Muntini Edi Suprayoga Sasfan A. Wella Iim Fatimah Lila Yuwana Tosawat Seetawan Adam B. Cahaya Ahmad R. T. Nugraha Eddwi H. Hasdeo Department of Physics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya 60111 Indonesia Research Center for Quantum Physics National Research and Innovation Agency Tangerang Selatan 15314 Indonesia Center of Excellence on Alternative Energy Research and Development Institution Sakon Nakhon Rajabhat University Sakon Nakhon 47000 Thailand Program of Physics Faculty of Science and Technology Sakon Nakhon Rajabhat University Sakon Nakhon 47000 Thailand Department of Physics Faculty of Mathematics and Natural Sciences Universitas Indonesia Depok 16424 Indonesia Department of Physics and Materials Science University of Luxembourg L-1511 Luxembourg

Historically, finding two-dimensional (2D) magnets is well known to be a difficult task due to the instability against thermal spin fluctuations. Metals are also normally considered poor thermoelectric (TE) materials. Combining intrinsic magnetism in two dimensions with conducting properties, one may expect to get the worst for thermoelectrics. However, we will show this is not always the case. Here, we investigate the spin-dependent TE properties of monolayer chromium pnictides (CrX, where X=P, As, Sb, and Bi) using first-principles calculations of electron- and phonon-energy dispersion, along with the Boltzmann transport formalism under an energy-dependent relaxation time approximation. All the CrX monolayers are dynamically stable and they also exhibit half metallicity with ferromagnetic ordering. Using the spin-valve setup with an antiparallel spin configuration, the half metallicity and ferromagnetism in monolayer CrX enable the manipulation of spin degrees of freedom to tune the TE figure of merit (ZT). At an optimized chemical potential and operating temperature of 500 K, the maximum ZT values (≈0.22, 0.12, and 0.09) with the antiparallel spin-valve setup in CrAs, CrSb, and CrBi improve up to almost twice the original values (ZT≈0.12, 0.08, and 0.05) without the spin-valve configuration. Only in CrP, which is the lightest species and less spin polarized among CrX, the maximum ZT (≈0.34) without the spin-valve configuration is larger than that (≈0.19) with the spin-valve one. We also find that, at 500 K, all the CrX monolayers possess exceptional TE power factors of about 0.02–0.08 W/m K2, which could be one of the best values among 2D conductors.

关键词： First-principles calculations Thermopower Monolayer films Electronic structure

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Projected Time for the Elimination of Cervical Cancer Under Various Intervention Scenarios: Age-Period-Cohort Macrosimulation Study

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JMIR Public Health and Surveillance 2024年 10卷 e46360页

作者： Chen, Yi-Chu Chen, Yun-Yuan Su, Shih-Yung Jhuang, Jing-Rong Chiang, Chun-Ju Yang, Ya-Wen Lin, Li-Ju Wu, Chao-Chun Lee, Wen-Chung Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Head Office Taiwan Blood Services Foundation Taipei Taiwan Master Program in Statistics National Taiwan University Taipei Taiwan Institute of Statistical Science Academia Sinica Taipei Taiwan Taiwan Cancer Registry Taipei city Taiwan Health Promotion Administration Ministry of Health and Welfare Taipei Taiwan Institute of Health Data Analytics College of Public Health National Taiwan University Taipei Taiwan

BACKGROUND: The World Health Organization aims for the global elimination of cervical cancer, necessitating modeling studies to forecast long-term outcomes. OBJECTIVE: This paper introduces a macrosimulation framework using age-period-cohort modeling and population attributable fractions to predict the timeline for eliminating cervical cancer in Taiwan. METHODS: data for cervical cancer cases from 1997 to 2016 were obtained from the Taiwan Cancer Registry. Future incidence rates under the current approach and various intervention strategies, such as scaled-up screening (cytology based or human papillomavirus [HPV] based) and HPV vaccination, were projected. RESULTS: Our projections indicate that Taiwan could eliminate cervical cancer by 2050 with either 70% compliance in cytology-based or HPV-based screening or 90% HPV vaccination coverage. The years projected for elimination are 2047 and 2035 for cytology-based and HPV-based screening, respectively;2050 for vaccination alone;and 2038 and 2033 for combined screening and vaccination approaches. CONCLUSIONS: The age-period-cohort macrosimulation framework offers a valuable policy analysis tool for cervical cancer control. Our findings can inform strategies in other high-incidence countries, serving as a benchmark for global efforts to eliminate the disease. ©Yi-Chu Chen, Yun-Yuan Chen, Shih-Yung Su, Jing-Rong Jhuang, Chun-Ju Chiang, Ya-Wen Yang, Li-Ju Lin, Chao-Chun Wu, Wen-Chung Lee. Originally published in JMIR Public Health and Surveillance (https://***), 18.04.2024.

关键词： Age-period-cohort model Cancer screening Cervical cancer Cervical screening HPV Human papillomavirus Intervention Macrosimulation Population attributable fraction Public health intervention Women

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On the computational Bayesian survival spatial Dengue hemorrhagic fever (DHF) modelling with Fernandez–steel skew normal conditional autoregressive (FSSN CAR) frailty

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AIP Conference Proceedings 2023年第1期2536卷

作者： Dwi Rantini Nur Iriawan Irhamah Musofa Rusli Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Department of Statistics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya 60111 Indonesia Department of Internal Medicine Faculty of Medicine Universitas Airlangga Surabaya 60115 Indonesia

Generally, infectious disease data has a spatial effect, meaning that areas that are close together affect each other. One of the infectious diseases is dengue hemorrhagic fever (DHF). The recovery time of DHF patients is interesting to study. In this research, DHF data in eastern Surabaya was used. The recovery time of this DHF patient can be modeled using one of the statistical methods, namely survival analysis. This recovery time data follows the Weibull distribution. On the data indicated spatial effect, the conditional autoregressive (CAR) model can be used to express dependencies between adjacent areas. Spatial random effects in the survival model were modeled with Normal CAR, Double-Exponential (DE) CAR, and Fernandez-Steel skew Normal (FSSN) CAR. In this research, Cox regression was used and parameter estimation was performed using the Bayesian analysis with Hamiltonian Monte Carlo (HMC) algorithm using the Stan programming language. Based on the comparison of the Watanabe-Akaike information criterion (WAIC), the spatial random effects on the Weibull Cox regression model are best modeled with the FSSN CAR. This is because the FSSN CAR is able to capture error patterns both symmetrical and asymmetrical, not with Normal CAR and DE CAR which can only capture symmetrical error patterns. In this research, several variables that allegedly affect the recovery rate of DHF patients are given. Then, based on the best model, variables that significantly affect the patient's recovery rate are age, the high schools in last education, housewife in the type of occupation, stadium-II in severity level, fever days before entering the hospital, pulse, temperature, and leukocytes.

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Comparison of endoscopic third ventriculostomy versus cerebrospinal fluid shunt procedures for the treatment of pediatric hydrocephalus in Taiwan

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Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery 2024年第9期40卷 2883-2891页

作者： Shu-Mei Chen Li-Ying Chen Jiann-Her Lin Nicole Salazar Tu-Hsueh Yeh Wei-Lun Lo Tai-Ngar Lui Yi-Chen Hsieh Li-Nien Chien Department of Neurosurgery Taipei Medical University Hospital Taipei Medical University Taipei Taiwan. Department of Surgery School of Medicine Taipei Medical University Taipei Taiwan. Health Data Analytics and Statistics Center Office of Data Science Taipei Medical University Taipei Taiwan. Julius L. Chambers Biomedical/Biotechnology Institute and Department of Biological & Biomedical Sciences North Carolina Central University Durham NC USA. Department of Neurology Taipei Medical University Hospital Taipei Taipei Medical University Taipei Taiwan. Department of Neurology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan. Department of Neurosurgery Shuang Ho Hospital Taipei Medical University Taipei Taiwan. The PhD Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University 250 Wu-Hsing Street Taipei Taiwan. ychsieh@tmu.edu.tw. Institute of Health and Welfare Policy College of Medicine National Yang Ming Chiao Tung University No.155 Sec. 2 Linong St. Beitou District Taipei Taiwan. linien.chien@nycu.edu.tw. Graduate Institute of Data Science College of Management Taipei Medical University Taipei Taiwan. linien.chien@nycu.edu.tw.

PURPOSE:Pediatric hydrocephalus is the most common cause of surgically treatable neurological disease in children. Controversies exist whether endoscopic third ventriculostomy (ETV) or cerebrospinal fluid (CSF) shunt placement is the most appropriate treatment for pediatric hydrocephalus. This study aimed to compare the risk of re-operation and death between the two procedures. METHODS:We performed a retrospective population-based cohort study and included patients younger than 20-years-old who underwent CSF shunt or ETV for hydrocephalus from the Taiwan National Health Insurance Research database. RESULTS:A total of 3,555 pediatric patients from 2004 to 2017 were selected, including 2,340 (65.8%) patients that received CSF shunt placement and 1215 (34.2%) patients that underwent ETV. The incidence of all-cause death was 3.31 per 100 person-year for CSF shunt group and 2.52 per 100 person-year for ETV group, with an adjusted hazard ratio (HR) of 0.79 (95% confidence interval [CI] = 0.66-0.94, p = 0.009). The cumulative incidence competing risk for reoperation was 31.2% for the CSF shunt group and 26.4% for the ETV group, with an adjusted subdistribution HR of 0.82 (95% CI = 0.70-0.96, p = 0.015). Subgroup analysis showed that ETV was beneficial for hydrocephalus coexisting with brain or spinal tumor, central nervous system infection, and intracranial hemorrhage. CONCLUSION:Our data indicates ETV is a better operative procedure for pediatric hydrocephalus when advanced surgical techniques and instruments are available.

关键词： Cerebrospinal shunt Pediatric hydrocephalus Reoperation Third ventriculostomy

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