106 research outputs found

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

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    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

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    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

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    <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

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

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    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

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

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    © 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

    Causal mechanisms and evolution processes of “block-burst” debris flow hazard chains in mountainous urban areas: a case study of Meilong gully in Danba county, Sichuan Province, China

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    The research interest in multi-hazard chains lies in the comprehension of how various hazards, such as debris flows, floods, and landslides, can interact and amplify one another, resulting in cascading or interconnected hazards. On 17 June 2020, at approximately 3:20 a.m., a debris flow occurred in Meilong gully (MLG), located in Banshanmen Town, Danba County, in southwest China’s Sichuan Province. The debris flow had a discharge volume of approximately 40 × 104 m3 and rushed out to block the Xiaojinchuan (XJC) river, subsequently forming a barrier lake. This event ultimately induced a hazard chain that included heavy rainfall, debris flow, landslides, the formation of a barrier lake, and an outburst flood. The impact of this chain resulted in the displacement of 48 households and affected 175 individuals. Furthermore, it led to the destruction of an 18 km section of National Highway G350, stretching from Xiaojin to Danba County, causing economic losses estimated at 65 million yuan. The objective of this study is to analyze the factors leading to the formation of this hazard chain, elucidate its triggering mechanisms, and provide insights for urban areas in the western mountainous region of Sichuan to prevent similar dam-break type debris flow hazard chains. The research findings, derived from field investigations, remote sensing imagery analysis, and parameter calculations, indicate that prior seismic disturbances and multiple dry-wet cycle events increased the volume of loose solid materials within the MLG watershed. Subsequently, heavy rainfall triggered the initiation of the debris flow in MLG. The cascading dam-break, resulting from three unstable slopes and boulders within the channel, amplified the scale of the hazard chain, leading to a significant amount of solid material rushing into the XJC river, thus creating a dam that constricted the river channel. With the intensification of river scouring, the reactivation and destabilization of the Aniangzhai (ANZ) paleolandslide occurred, ultimately leading to the breach of the dam and the formation of an outburst flood. The research comprehensively and profoundly reveals the causal mechanism of the MLG hazard chain, and proposes measures to disrupt the chain at various stages, which can aid in enhancing monitoring, early warning, forecasting systems, and identifying key directions for ecological environmental protection in urban areas within the western mountainous region of Sichuan. Additionally, it could also serve as a reference for mountainous urban areas such as the Tianshan, Alps, Rocky Mountains, and Andes, among others
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