Estimating Treatment Effects and Identifying Optimal Treatment Regimes to Prolong Patient Survival.

Motivated by an observational prostate cancer recurrence study, we investigate the effect of treatment on survival outcome. For studies such as these, it is important to properly handle the confounding effects, especially from longitudinal covariates. In addition, baseline covariates may also reflect the heterogeneity of the population in responding to the treatment. It is possible to recognize these differences and customize the treatment strategy accordingly. In the first project, we formulate a generalized accelerated failure time (AFT) model to describe the treatment effect and the model includes a longitudinal covariate as a functional predictor, whose coefficient is a time-varying nonparametric function. We propose a spline-based sieve estimation for the time-varying coefficient of the functional predictor, and maximize the likelihood in the sieve space where we approximate the functional predictor and nonparametric coefficient using B-spline basis. Asymptotic properties of the proposed estimator are developed, and its performance is evaluated through simulation studies. We further consider the interaction between treatment and other covariates, and explore the heterogeneity of the treatment effect and approaches to personalize the treatment assignment to optimize the survival outcome. In the second project, using the causal inference framework, we consider the counterfactual outcome as if every patient follows a given treatment regimen and develop a method to identify the optimal dynamic treatment regime from observational longitudinal data. We propose to use Random Forest to model the regime adherence of each subject, and use inverse probability weights to adjust for non-adherence to obtain the regime specific survival distribution. We study the theoretical properties of the proposed estimators, and its finite sample performance through simulation and real data analysis. In the third project, we consider a more general class of candidate regimes through flexible models of the outcomes. We propose to use Random Survival Forest plus an inverse probability weighted bootstrap to estimate the causal outcome while marginalizing over the unavailable covariates. By comparing the restricted mean survival times, the optimal regime can be estimated for the target population. The performance of the proposed method is assessed through simulation studies.PhDBiostatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110404/1/jcshen_1.pd

Modeling Longitudinal Outcomes: A Contrast of Two Methods

journal articleBackground: Repeated measures analysis of variance (ANOVA) is frequently used to model longitudinal data but does not appropriately account for within-person correlations over time, does not explicitly model time, and cannot flexibly handle missing data. In contrast, mixed-effects regression addresses these limitations. In this commentary, we compare these two methods using openly available tools. Methods: We emulated a real developmental study of elite skiers, tracking national rankings from 2011 to 2018. We constructed unconditional models of time (establishing the "pattern" of change), conditional models (identifying factors that affect change over time) and contrasted these models against comparable repeated measures ANOVAs. Results: Mixed-effects regression allowed for linear and non-linear modeling of the skiers' longitudinal trajectories despite missing data. Missing data is still a concern in mixed-effects regression models, but in the present dataset missingness could be accounted for by skiers' ages, satisfying the missing at random assumption. Discussion: Although ANOVA and mixed-effects regression are both suitable for time-series data, their applications differ. ANOVA will be most parsimonious when the research question focuses on group-level mean differences at arbitrary time points. However, mixed-effects regression is more suitable where time is inherently important to the outcome, and where individual differences are of interest

DBMLoc: a Database of proteins with multiple subcellular localizations

<p>Abstract</p> <p>Background</p> <p>Subcellular localization information is one of the key features to protein function research. Locating to a specific subcellular compartment is essential for a protein to function efficiently. Proteins which have multiple localizations will provide more clues. This kind of proteins may take a high proportion, even more than 35%.</p> <p>Description</p> <p>We have developed a database of proteins with multiple subcellular localizations, designated DBMLoc. The initial release contains 10470 multiple subcellular localization-annotated entries. Annotations are collected from primary protein databases, specific subcellular localization databases and literature texts. All the protein entries are cross-referenced to GO annotations and SwissProt. Protein-protein interactions are also annotated. They are classified into 12 large subcellular localization categories based on GO hierarchical architecture and original annotations. Download, search and sequence BLAST tools are also available on the website.</p> <p>Conclusion</p> <p>DBMLoc is a protein database which collects proteins with more than one subcellular localization annotation. It is freely accessed at <url>http://www.bioinfo.tsinghua.edu.cn/DBMLoc/index.htm</url>.</p

Comparison of methods for estimating the effect of salvage therapy in prostate cancer when treatment is given by indication

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102122/1/sim5890.pd

Content, Composition, and Biosynthesis of Anthocyanin in Fragaria Species: A Review

Anthocyanins are responsible for fruit coloration and are beneficial to human health. The fruits of cultivated strawberry (Fragaria ×ananassa) varieties are colorful, a trait that attracts consumers. The fruits of wild Fragaria species, close relatives of the cultivated strawberry, vary in color. In this review, we describe the content and composition of anthocyanins in cultivated and wild strawberry varieties. We also explore the biosynthetic pathway of anthocyanins, including their transcriptional regulation mechanisms. Additionally, we discuss the effect of environmental factors on anthocyanin accumulation. This review will inform further studies toward developing anthocyanin-rich strawberries via environmental control and exogenous application of compounds

Evaluation of dual energy quantitative CT for determining the spatial distributions of red marrow and bone for dosimetry in internal emitter radiation therapy

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135113/1/mp0378.pd

Local bone metabolism balance regulation via double-adhesive hydrogel for fixing orthopedic implants

© 2021 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)The effective osteointegration of orthopedic implants is a key factor for the success of orthopedic surgery. However, local metabolic imbalance around implants under osteoporosis condition could jeopardize the fixation effect. Inspired by the bone structure and the composition around implants under osteoporosis condition, alendronate (A) was grafted onto methacryloyl hyaluronic acid (H) by activating the carboxyl group of methacryloyl hyaluronic acid to be bonded to inorganic calcium phosphate on trabecular bone, which is then integrated with aminated bioactive glass (AB) modified by oxidized dextran (O) for further adhesion to organic collagen on the trabecular bone. The hybrid hydrogel could be solidified on cancellous bone in situ under UV irradiation and exhibits dual adhesion to organic collagen and inorganic apatite, promoting osteointegration of orthopedic implants, resulting in firm stabilization of the implants in cancellous bone areas. In vitro, the hydrogel was evidenced to promote osteogenic differentiation of embryonic mouse osteoblast precursor cells (MC3T3-E1) as well as inhibit the receptor activator of nuclear factor-κ B ligand (RANKL)-induced osteoclast differentiation of macrophages, leading to the upregulation of osteogenic-related gene and protein expression. In a rat osteoporosis model, the bone-implant contact (BIC) of the hybrid hydrogel group increased by 2.77, which is directly linked to improved mechanical stability of the orthopedic implants. Overall, this organic-inorganic, dual-adhesive hydrogel could be a promising candidate for enhancing the stability of orthopedic implants under osteoporotic conditions.This work was supported by the National Key R&D Program of China (2020YFA0908200), National Natural Science Foundation of China (82120108017), Six talent peaks project in Jiangsu Province (WSW-018). This work was financed by Portuguese funds through FCT - Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Ensino Superior in the framework of the project “Institute for Research and Innovation in Health Sciences” UID/BIM/04293/2019.info:eu-repo/semantics/publishedVersio

DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function

Background The difference between an individual's chronological and DNA methylation predicted age (DNAmAge), termed DNAmAge acceleration (DNAmAA), can capture life-long environmental exposures and age-related physiological changes reflected in methylation status. Several studies have linked DNAmAA to morbidity and mortality, yet its relationship with kidney function has not been assessed. We evaluated the associations between seven DNAm aging and lifespan predictors (as well as GrimAge components) and five kidney traits (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [uACR], serum urate, microalbuminuria and chronic kidney disease [CKD]) in up to 9688 European, African American and Hispanic/Latino individuals from seven population-based studies. Results We identified 23 significant associations in our large trans-ethnic meta-analysis (p < 1.43E-03 and consistent direction of effect across studies). Age acceleration measured by the Extrinsic and PhenoAge estimators, as well as Zhang's 10-CpG epigenetic mortality risk score (MRS), were associated with all parameters of poor kidney health (lower eGFR, prevalent CKD, higher uACR, microalbuminuria and higher serum urate). Six of these associations were independently observed in European and African American populations. MRS in particular was consistently associated with eGFR (beta = - 0.12, 95% CI = [- 0.16, - 0.08] change in log-transformed eGFR per unit increase in MRS, p = 4.39E-08), prevalent CKD (odds ratio (OR) = 1.78 [1.47, 2.16], p = 2.71E-09) and higher serum urate levels (beta = 0.12 [0.07, 0.16], p = 2.08E-06). The first-generation clocks (Hannum, Horvath) and GrimAge showed different patterns of association with the kidney traits. Three of the DNAm-estimated components of GrimAge, namely adrenomedullin, plasminogen-activation inhibition 1 and pack years, were positively associated with higher uACR, serum urate and microalbuminuria. Conclusion DNAmAge acceleration and DNAm mortality predictors estimated in whole blood were associated with multiple kidney traits, including eGFR and CKD, in this multi-ethnic study. Epigenetic biomarkers which reflect the systemic effects of age-related mechanisms such as immunosenescence, inflammaging and oxidative stress may have important mechanistic or prognostic roles in kidney disease. Our study highlights new findings linking kidney disease to biological aging, and opportunities warranting future investigation into DNA methylation biomarkers for prognostic or risk stratification in kidney disease

DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function

Background The difference between an individual's chronological and DNA methylation predicted age (DNAmAge), termed DNAmAge acceleration (DNAmAA), can capture life-long environmental exposures and age-related physiological changes reflected in methylation status. Several studies have linked DNAmAA to morbidity and mortality, yet its relationship with kidney function has not been assessed. We evaluated the associations between seven DNAm aging and lifespan predictors (as well as GrimAge components) and five kidney traits (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [uACR], serum urate, microalbuminuria and chronic kidney disease [CKD]) in up to 9688 European, African American and Hispanic/Latino individuals from seven population-based studies. Results We identified 23 significant associations in our large trans-ethnic meta-analysis (p < 1.43E−03 and consistent direction of effect across studies). Age acceleration measured by the Extrinsic and PhenoAge estimators, as well as Zhang’s 10-CpG epigenetic mortality risk score (MRS), were associated with all parameters of poor kidney health (lower eGFR, prevalent CKD, higher uACR, microalbuminuria and higher serum urate). Six of these associations were independently observed in European and African American populations. MRS in particular was consistently associated with eGFR (β =  − 0.12, 95% CI = [− 0.16, − 0.08] change in log-transformed eGFR per unit increase in MRS, p = 4.39E−08), prevalent CKD (odds ratio (OR) = 1.78 [1.47, 2.16], p = 2.71E-09) and higher serum urate levels (β = 0.12 [0.07, 0.16], p = 2.08E−06). The “first-generation” clocks (Hannum, Horvath) and GrimAge showed different patterns of association with the kidney traits. Three of the DNAm-estimated components of GrimAge, namely adrenomedullin, plasminogen-activation inhibition 1 and pack years, were positively associated with higher uACR, serum urate and microalbuminuria. Conclusion DNAmAge acceleration and DNAm mortality predictors estimated in whole blood were associated with multiple kidney traits, including eGFR and CKD, in this multi-ethnic study. Epigenetic biomarkers which reflect the systemic effects of age-related mechanisms such as immunosenescence, inflammaging and oxidative stress may have important mechanistic or prognostic roles in kidney disease. Our study highlights new findings linking kidney disease to biological aging, and opportunities warranting future investigation into DNA methylation biomarkers for prognostic or risk stratification in kidney disease