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Partial least squares regression and principal component analysis:similarity and differences between two popular variable reduction approaches

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General Psychiatry 2022年第1期35卷 67-71页

作者： Chenyu Liu Xinlian Zhang Tanya T Nguyen Jinyuan Liu Tsungchin Wu Ellen Lee Xin M Tu Division of Biostatistics and Bioinformatics Herbert Wertheim School of Public Health and Human Longevity ScienceUC San DiegoLa JollaCaliforniaUSA Department of Psychiatry Stein Institute for Research on AgingUC San DiegoLa JollaCaliforniaUSA

SUMMARY In many statistical applications,composite variables are constructed to reduce the number of variables and improve the performances of statistical analyses of these variables,especially when some of the variables are highly *** component analysis(PCA)and factor analysis(FA)are generally used for such *** the variables are used as explanatory or independent variables in linear regression analysis,partial least squares(PLS)regression is a better *** PCA and FA,PLS creates composite variables by also taking into account the response,or dependent variable,so that they have higher correlations with the response than composites from their PCA and FA *** this report,we provide an introduction to this useful approach and illustrate it with data from a real study.

关键词： composite composites component

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Regulation of translation elongation and integrated stress response in heat-shocked neurons

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Cell Reports 2025年第5期44卷

作者： Seluzicki, Caitlin M. Razavi-Mohseni, Milad Türker, Fulya Patel, Priyal Hua, Boyang Beer, Michael A. Goff, Loyal Margolis, Seth S. Department of Biological Chemistry The Johns Hopkins University School of Medicine Baltimore 21205 MD United States Department of Biomedical Engineering The Johns Hopkins University Baltimore 21205 MD United States Department of Molecular Biology and Genetics The Johns Hopkins University School of Medicine Baltimore 21205 MD United States Solomon H. Snyder Department of Neuroscience The Johns Hopkins University School of Medicine Baltimore 21205 MD United States Department of Oncology Division of Biostatistics and Bioinformatics Sidney Kimmel Comprehensive Cancer Center Baltimore 21205 MD United States McKusick-Nathans Department of Genetic Medicine Johns Hopkins University School of Medicine Baltimore 21205 MD United States Department of Molecular Biology and Genetics Bilkent University Ankara 06800 Turkey

Neurons deviate from a canonical heat shock response (HSR). Here, we revealed that neuronal adaptation to heat shock accompanies a brake on mRNA translation, slowed elongating ribosomes, phosphorylation of eukaryotic elongation factor-2 (p-eEF2), and suppressed the integrated stress response (ISR). Returning neurons to control temperature within 1 h of starting heat shock was necessary for survival and allowed for restored translation following dephosphorylation of eEF2. Subsequent to recovery, neurons briefly activated the ISR and were sensitive to the ISR inhibitor ISRIB, which enhanced protein synthesis and survival. Ribosome profiling and RNA sequencing (RNA-seq) identified newly synthesized and existing transcripts associated with ribosomes during heat shock. Preservation of these transcripts for translation during recovery was in part mediated by p-eEF2 and slowed ribosomes. Our work supports a neuronal heat shock model of a partially suspended state of translation poised for rapid reversal if recovery becomes an option and provides insight into regulation between the HSR and the ISR. © 2025 The Author(s)

关键词： CP: Molecular biology CP: Neuroscience eEF2 eIF2α elongation heat shock integrated stress response ISR neurons translation

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Development of Machine Learning Models for Predicting Radiation Dermatitis in Breast Cancer Patients Using Clinical Risk Factors, Patient-Reported Outcomes, and Serum Cytokine Biomarkers

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Clinical Breast Cancer 2025年

作者： Lin, Neil Abbas-Aghababazadeh, Farnoosh Su, Jie Wu, Alison J. Lin, Cherie Shi, Wei Xu, Wei Haibe-Kains, Benjamin Liu, Fei-Fei Kwan, Jennifer Y.Y. Institute of Medical Science Temerty Faculty of Medicine University of Toronto Toronto Canada Temerty Faculty of Medicine University of Toronto Toronto Canada Princess Margaret Bioinformatics and Computational Genomics Laboratory University Health Network Toronto Canada Biostatistics Division Princess Margaret Cancer Centre Toronto Canada Research Institute Princess Margaret Cancer Centre Toronto Canada Department of Computer Science University of Toronto Toronto Canada Ontario Institute for Cancer Research Toronto Canada Vector Institute for Artificial Intelligence Toronto Canada Department of Radiation Oncology Temerty Faculty of Medicine University of Toronto Toronto Canada Department of Medical Biophysics Temerty Faculty of Medicine University of Toronto Toronto Canada Radiation Medicine Program Princess Margaret Cancer Centre Toronto Canada

Background: Radiation dermatitis (RD) is a significant side effect of radiotherapy experienced by breast cancer patients. Severe symptoms include desquamation or ulceration of irradiated skin, which impacts quality of life and increases healthcare costs. Early identification of patients at risk for severe RD can facilitate preventive management and reduce severe symptoms. This study evaluated the utility of subjective and objective factors, such as patient-reported outcomes (PROs) and serum cytokines, for predicting RD in breast cancer patients. The performance of machine learning (ML) and logistic regression-based models were compared. Patients and Methods: Data from 147 breast cancer patients who underwent radiotherapy was analyzed to develop prognostic models. ML algorithms, including neural networks, random forest, XGBoost, and logistic regression, were employed to predict clinically significant Grade 2+ RD. Clinical factors, PROs, and cytokine biomarkers were incorporated into the risk models. Model performance was evaluated using nested cross-validation with separate loops for hyperparameter tuning and calculating performance metrics. Results: Feature selection identified 18 predictors of Grade 2+ RD including smoking, radiotherapy boost, reduced motivation, and the cytokines interleukin-4, interleukin-17, interleukin-1RA, interferon-gamma, and stromal cell-derived factor-1a. Incorporating these predictors, the XGBoost model achieved the highest performance with an area under the curve (AUC) of 0.780 (95% CI: 0.701-0.854). This was not significantly improved over the logistic regression model, which demonstrated an AUC of 0.714 (95% CI: 0.629-0.798). Conclusion: Clinical risk factors, PROs, and serum cytokine levels provide complementary prognostic information for predicting severe RD in breast cancer patients undergoing radiotherapy. ML and logistic regression models demonstrated comparable performance for predicting clinically significant RD with AUC>0.70. ©

关键词： Cancer survivorship Oncology Predictive modeling Radiotherapy Skin toxicity

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[RD] PRISM library: Patient registry item specifications and metadata for rare diseases

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Journal of Library Metadata 2010年第2-3期10卷 119-135页

作者： Richesson, Rachel Shereff, Denise Andrews, James Division of Bioinformatics and Biostatistics University of South Florida College of Medicine Tampa FL 33612 3650 Spectrum Boulevard Suite 100 United States School of Library and Information Science University of South Florida Tampa FL United States

Patient registries are important for understanding the causes and origins of rare diseases and estimating their impact;and they may prove critical to the development of new diagnostics and therapeutics. This paper introduces the [RD] PRISM resource (http://***), a project funded by the National Institutes of Health to develop a library of standardized question-and-answer sets to support rare disease research. The paper presents a project case-driven plan for creating a new registry using questions from an existing related registry, revising and expanding an existing registry, and showing interoperability of data collected from different registries and data sources. Each of the use cases involves the retrieval of indexed questions for reuse. Successful retrieval of questions can facilitate their reuse in registries, meaning new registries can be implemented more quickly, and the use of "standard" questions can be facilitated. The paper further discusses issues involved in encoding the sets with relevant data standards for interoperability and indexing encoded sets with metadata for optimal retrievability. © Taylor & Francis Group, LLC.

关键词： Metadata Patient registry Rare disease

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A robustified posterior for Bayesian inference on a large number of parallel effects

arXiv

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arXiv 2018年

作者： Liao, J.G. Berg, Arthur McMurry, Timothy L. Division of Biostatistics & Bioinformatics Pennsylvania State University HersheyPA17033 United States

Many modern experiments, such as microarray gene expression and genome-wide association studies, present the problem of estimating a large number of parallel effects. Bayesian inference is a popular approach for analyzing such data by modeling the large number of unknown parameters as random effects from a common prior distribution. However, misspecification of the prior distribution can lead to erroneous estimates of the random effects, especially for the largest and most interesting effects. This paper has two aims. First, we propose a robustified posterior distribution for a parametric Bayesian hierarchical model that can substantially reduce the impact of a misspecified prior. Second, we conduct a systematic comparison of the standard parametric posterior, the proposed robustified parametric posterior, and a nonparametric Bayesian posterior which uses a Dirichlet process mixture prior. The proposed robustifed posterior when combined with a flexible parametric prior can be a superior alternative to nonparametric Bayesian methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Random processes

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The Molecular Basis Underlying Phenotypic Divergences between Humans and Mice

The Molecular Basis Underlying Phenotypic Divergences betwee...

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2013第六届国际蛋白质和多肽大会

作者： Ben-Yang Liao Division of Biostatistics and Bioinformatics Institute of Population Health Sciences National Health Research Institutes

The relative importance of protein function change and gene regulatory change in phenotypic evolution is a contentious, yet central topic in biology, and the understanding of it has broad implications in biomedicine. This presentation is comprised of two parts: (i) the molecular basis underlying the change in gene essentiality, and (ii) the molecular basis underlying morphological and physiological divergences, between humans and mice. One-to-one orthologous genes of relatively closely related species are widely assumed to have similar functions and cause similar phenotypes when deleted from the genome. Although this assumption is the foundation of comparative genomics and the basis for the use of model organisms to study human biology and disease, its validity is known only from anecdotes rather than from systematic examination. Comparing documented phenotypes of null mutations in humans and mice, we find that >20% of human essential genes have nonessential mouse orthologs. These changes of gene essentiality appear to be associated with adaptive evolution at the protein-sequence, but not gene-expression, level. Proteins localized to the vacuole, a cellular compartment for waste management, are highly enriched among essentiality- changing genes. It is probable that the evolution of the prolonged life history in humans required enhanced waste management for proper cellular function until the time of reproduction, which rendered these vacuole proteins essential and generated selective pressures for their improvement. If our gene sample represents the entire genome, our results would mean frequent changes of phenotypic effects of one-to-one orthologous genes even between relatively closely related species, a possibility that should be considered in comparative genomic studies and in making cross-species inferences of gene function and phenotypic effect. Analyzing 5,199 mouse genes with recorded mutant phenotypes, we find that genes exclusively affecting morphological t

关键词： The Molecular Basis Underlying Phenotypic Divergences between Humans and Mice

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Intraoperative radiotherapy for early breast cancer and age: Clinical characteristics and outcomes

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American Journal of Surgery 2015年第4期210卷 624-628页

作者： Abbott, Andrea M. Dossett, Lesly A. Loftus, Loretta Sun, Weihong Fulp, William Sokol, Gerald H. Laronga, Christine Department of Breast Oncology Moffitt Cancer Center Tampa FL United States Division of Biostatistics and Bioinformatics Moffitt Cancer Center Tampa FL United States Uniformed Services University of the Health Sciences Bethesda MD United States

Background Eligibility criteria for intraoperative radiation therapy (IORT) for breast cancer are being established. Impact of age, one criterion, on short-term complications/outcomes was evaluated. Methods Institutional Review Board approved retrospective review of early-stage breast cancer patients undergoing breast conserving surgery and IORT from January 2011 to June 2013 were reviewed. Data collected were demographics, comorbidities, histopathology, intraoperative data, adjuvant treatment, and outcomes. Local recurrence (LR), re-excision rates, and complications were evaluated by age group using descriptive statistics. Results The total number of patients was 100 (43 patients <70, 57 patients 70). No significant differences existed between groups in tumor size, operative time, estrogen receptor status, nodal status, tumor grade, or margin excision. Wound infection rates were low for both groups (P =.21). Two LR occurred (both patients 70). Median follow-up time was 24 months. Conclusion IORT with its low rate of LR and wound complications may be a reasonable alternative to whole breast irradiation for early-stage breast cancer, regardless of age. © 2015 Elsevier Inc. All rights reserved.

关键词： Accelerated partial breast radiation Breast cancer Elderly Intraoperative radiation therapy Surgical outcomes

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A comparison of efficiencies between quasi-likelihood and pseudo-likelihood estimates in non-separable spatial-temporal binary data

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Journal of Statistical Planning and Inference 2009年第9期139卷 3310-3318页

作者： Lin, Pei-Sheng Lee, Hui-Yun Clayton, Murray Department of Mathematics National Chung Cheng University Min-Hsiung Chia-Yi 621 168 University Road Taiwan Division of Biostatistics and Bioinformatics National Health Research Institutes Taiwan Department of Statistics University of Wisconsin Madison United States

The goal of this paper is to compare the performance of two estimation approaches, the quasi-likelihood estimating equation and the pseudo-likelihood equation, against model mis-specification for non-separable binary data. This comparison, to the authors' knowledge, has not been done yet. In this paper, we first extend the quasi-likelihood work on spatial data to non-separable binary data. Some asymptotic properties of the quasi-likelihood estimate are also briefly discussed. We then use the techniques of a truncated Gaussian random field with a quasi-likelihood type model and a Gibbs sampler with a conditional model in the Markov random field to generate spatial-temporal binary data, respectively. For each simulated data set, both of the estimation methods are used to estimate parameters. Some discussion about the simulation results are also included. © 2009 Elsevier B.V. All rights reserved.

关键词： Estimating equation Markov random field Pseudo-likelihood function Quasi-likelihood estimate Spatial-temporal data

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Racial disparities in lung function by pulmonary function testing among lung transplant candidates and race-specific reference equations

JHLT Open

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JHLT Open 2025年 8卷 100252-100252页

作者： Daniel M. Guidot Mackenzie Wood Emily Poehlein Scott Palmer Lisa McElroy Geriatrics Research Education and Care Center Durham VA Medical Center Durham North Carolina Division of Pulmonary Allergy and Critical Care Duke University Medical Center Durham North Carolina Department of Biostatistics and Data Science Wake Forest School of Medicine Winston-Salem North Carolina Department of Biostatistics and Bioinformatics Duke University School of Medicine Durham North Carolina Duke Clinical Research Institute Duke University Medical Center Durham North Carolina Division of Abdominal Transplant Department of Surgery Duke University Medical Center Durham North Carolina Department of Population Health Sciences Duke University Medical Center Durham North Carolina

Non-White patients with interstitial lung disease (ILD) experience racial disparities in lung transplant waitlist mortality. Race-specific equations for spirometry may contribute by underestimating restriction severity in non-White candidates. We analyzed US lung transplant candidates to assess for disparities in forced vital capacity (FVC) at listing, comparing absolute and adjusted values using race-specific and race-neutral equations. We identified 17,457 adults with ILD listed May 4, 2005 to September 31, 2023. At listing, mean absolute FVC was higher for White patients (2.03 ± 0.80 liters) than Black patients (1.61 ± 0.67 liters) and Asian patients (1.49 ± 0.86 liters). Differences were attenuated after applying race-specific equations (White patients 50.0 ± 17.5%, Black patients 47.7 ± 17.9%, Asian patients 46.2 ± 24.2%). Compared with race-neutral equations, race-specific equations had higher odds of classifying FVC as severe (≤40%) requiring listing in White patients (OR 1.37, 95% CI 1.28–1.40) but lower odds in Black patients (OR 0.82, 95% CI 0.74–0.90). Using race-neutral equations might help improve racial disparities for lung transplant candidates with ILD.

关键词： BMI Body mass index CI Confidence interval cm Centimeter FVC Forced vital capacity GLI Global lung initiative IPF Idiopathic pulmonary fibrosis ILD Interstitial lung disease kg/m 2 Kilogram per meter squared L Liter OR Odds ratio Sep September STAR Standard Transplant Analysis Research UNOS United Network of Organ Sharing interstitial lung disease lung transplantation forced vital capacity race-specific reference equations racial disparity referral United Network for Organ Sharing

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Obstetric hemorrhage survey: Attitudes and practices of maternal-fetal medicine fellows

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Journal of Neonatal-Perinatal Medicine 2016年第2期9卷 133-137页

作者： Ahmadzia, H.K. Thomas, S.M. Murtha, A.P. Heine, R.P. Brancazio, L.R. Department of Obstetrics and Gynecology Division of Maternal Fetal Medicine Duke University Medical Center DUMC 3967 Durham 27710 NC United States Department of Biostatistics and Bioinformatics Duke University School of Medicine Durham NC United States

OBJECTIVE: To evaluate experiences related to obstetric hemorrhage and suspected abnormal placentation among first year maternal-fetal medicine fellows. STUDY DESIGN: A cross-sectional anonymous survey was administered at the Society for Maternal-Fetal Medicine fellow retreat in March 2013. Fellows were asked about management strategies that reflected both their individual and institutional practices. RESULTS: There was a 56 response rate (55/98). In cases of postpartum hemorrhage due to uterine atony, there was variable use of the uterine tamponade device. The median incremental time for balloon deflation was every 5 hours (IQR=2-12). Compared to the east coast, fellows from the west coast performed more hysterectomies (mean±SD;2.9±2.4 vs. 1.2±1.2, p=0.004). During a peripartum hysterectomy, 29 of fellows used a handheld cautery device such as Ligasure® or Gyrus®. Fifty-six percent responded that their institution never recommend planned delayed hysterectomies for abnormal placental implantation. CONCLUSION: There is wide variation in practice among first year maternal-fetal medicine fellows in management of peripartum hysterectomy and postpartum hemorrhage. © 2016 - IOS Press and the authors.

关键词： abnormal placentation maternal-fetal medicine Obstetric hemorrhage survey study

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