Semiparametric proportional means model for marker data contingent on recurrent event

In many biomedical studies with recurrent events, some markers can only be measured when events happen. For example, medical cost attributed to hospitalization can only incur when patients are hospitalized. Such marker data are contingent on recurrent events. In this paper, we present a proportional means model for modelling the markers using the observed covariates contingent on the recurrent event. We also model the recurrent event via a marginal rate model. Estimating equations are constructed to derive the point estimators for the parameters in the proposed models. The estimators are shown to be asymptotically normal. Simulation studies are conducted to examine the finite-sample properties of the proposed estimators and the proposed method is applied to a data set from the Vitamin A Community Trial

The association between socioeconomic status and disability after stroke: Findings from the Adherence eValuation After Ischemic stroke Longitudinal (AVAIL) registry

Background Stroke is the leading cause of disability among adults in the United States. The association of patients’ pre-event socioeconomic status (SES) with post-stroke disability is not well understood. We examined the association of three indicators of SES—educational attainment, working status, and perceived adequacy of household income—with disability 3-months following an acute ischemic stroke. Methods We conducted retrospective analyses of a prospective cohort of 1965 ischemic stroke patients who survived to 3 months in the Adherence eValuation After Ischemic stroke – Longitudinal (AVAIL) study. Multivariable logistic regression was used to examine the relationship of level of education, pre-stroke work status, and perceived adequacy of household income with disability (defined as a modified Rankin Scale of 3–5 indicating activities of daily living limitations or constant care required). Results Overall, 58% of AVAIL stroke patients had a high school or less education, 61% were not working, and 27% perceived their household income as inadequate prior to their stroke. Thirty five percent of patients were disabled at 3-months. After adjusting for demographic and clinical factors, stroke survivors who were unemployed or homemakers, disabled and not-working, retired, less educated, or reported to have inadequate income prior to their stroke had a significantly higher odds of post-stroke disability. Conclusions In this cohort of stroke survivors, socioeconomic status was associated with disability following acute ischemic stroke. The results may have implications for public health and health service interventions targeting stroke survivors at risk of poor outcomes

Relationship of national institutes of health stroke scale to 30-day mortality in medicare beneficiaries with acute ischemic stroke.

BackgroundThe National Institutes of Health Stroke Scale (NIHSS), a well-validated tool for assessing initial stroke severity, has previously been shown to be associated with mortality in acute ischemic stroke. However, the relationship, optimal categorization, and risk discrimination with the NIHSS for predicting 30-day mortality among Medicare beneficiaries with acute ischemic stroke has not been well studied.Methods and resultsWe analyzed data from 33102 fee-for-service Medicare beneficiaries treated at 404 Get With The Guidelines-Stroke hospitals between April 2003 and December 2006 with NIHSS documented. The 30-day mortality rate by NIHSS as a continuous variable and by risk-tree determined or prespecified categories were analyzed, with discrimination of risk quantified by the c-statistic. In this cohort, mean age was 79.0 years and 58% were female. The median NIHSS score was 5 (25th to 75th percentile 2 to 12). There were 4496 deaths in the first 30 days (13.6%). There was a strong graded relation between increasing NIHSS score and higher 30-day mortality. The 30-day mortality rates for acute ischemic stroke by NIHSS categories were as follows: 0 to 7, 4.2%; 8 to 13, 13.9%; 14 to 21, 31.6%; 22 to 42, 53.5%. A model with NIHSS alone provided excellent discrimination whether included as a continuous variable (c-statistic 0.82 [0.81 to 0.83]), 4 categories (c-statistic 0.80 [0.79 to 0.80]), or 3 categories (c-statistic 0.79 [0.78 to 0.79]).ConclusionsThe NIHSS provides substantial prognostic information regarding 30-day mortality risk in Medicare beneficiaries with acute ischemic stroke. This index of stroke severity is a very strong discriminator of mortality risk, even in the absence of other clinical information, whether used as a continuous or categorical risk determinant. (J Am Heart Assoc. 2012;1:42-50.)

Biomechanical analysis of lower limbs during stand-to-sit tasks in patients with early-stage knee osteoarthritis

Background: Knee osteoarthritis (KOA) is a common degenerative disease among the older people that severely affects their daily life. Previous studies have confirmed that movement biomechanics are altered in patients with KOA during task performance. However, changes that occur in lower limb joints and muscles in the three planes during stand-to-sit (STS) tasks in patients with early-stage KOA are unclear.Method: Of the 36 participants recruited in this study, 24 (8 males and 16 females) and 12 (4 males and 8 females) were added to the KOA and control groups, respectively. The Nexus Vicon motion capture system along with Delsys wireless surface electromyography devices and plantar pressure measurement mat was used to record test data. A Visual 3D software was used to process the data and calculate the biomechanical and electromyographic parameters during STS tasks.Results: There was no significant difference in task duration between the two groups. Patients with KOA could perform a greater range of pelvic motion and smaller range of hip and knee joint motion with a lower maximum hip joint angular acceleration in the sagittal plane and greater knee and ankle joint motion in the coronal plane. There was no significant difference in the motion range in the horizontal plane. During the STS task, patients in the KOA group had a lower vertical ground reaction force (GRF) amplitude on the injured side but a higher integrated GRF on both sides than those in the control group. Moreover, patients with KOA demonstrated higher PERM and PABM of the lower limb joints and smaller knee PADM and ankle PEM. Additionally, maximum activation levels of GMed muscle, affected-side gluteus medius (GM), ST, rectus femoris (RF), and tibialis anterior (TA) muscles were lower in patients with KOA than in controls. Conversely, the activation level of biceps femoris (BF) was higher. Furthermore, the integral EMG values of GMed, GM, ST, VL, RF, vastus medialis VM, and TA muscles on the affected side were lower, except for the BF muscle, in patients with KOA.Conclusion: Compared with the participants in the control group, patients with early-stage KOA exhibited consistent changes in sEMG parameters and biomechanical alterations in the sagittal plane, as observed in previous studies. However, differences in parameters were observed in the coronal and transverse planes of these patients. The noninvasive analysis of the 3D parameters of the involved motion patterns may lead to the early detection of KOA

Transition measurement error models for longitudinal data.

We propose a new class of models, transition measurement error models, to model longitudinal data when covariates are measured with error. We study the asymptotic bias in the estimation when the measurement error is ignored. Such bias can be large. We propose three approaches for inference in transition measurement error models to account for the measurement error. These approaches include the structural modeling approach, the simulation-extrapolation (SIMEX) approach, and the semi-parametric estimation approach. When a structural model is correctly specified for the unobserved true covariate, the maximum likelihood estimates for the regression parameters in the transition models are derived via the Expectation-Maximization algorithm. When no knowledge is available about the distribution of the unobserved true covariate, both the SIMEX approach and the semiparametric estimation approach are proposed: the SIMEX approach is simulation-based and the semiparametric estimation approach is likelihood-based. We show that the estimators using the SIMEX approach are consistent and asymptotically normal with a known correct extrapolation function. To implement the semiparametric estimation approach, we construct the conditional score equations to give consistent estimators for the parameters in both linear transition model and logistic transition model. These estimators are also shown to be asymptotically normal. Specifically, we are able to obtain the most efficient estimator for linear transition models in the presence of validation data. All three approaches are applied to a longitudinal social support study for elderly women with heart disease.Ph.D.Biological SciencesBiostatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/123255/2/3068941.pd

Health Status-Based Predictive Maintenance Decision-Making via LSTM and Markov Decision Process

Maintenance decision-making is essential to achieve safe and reliable operation with high performance for equipment. To avoid unexpected shutdown and increase machine life as well as system efficiency, it is fundamental to design an effective maintenance decision-making scheme for equipment. In this paper, we propose a novel maintenance decision-making method for equipment based on Long Short-Term Memory (LSTM) and Markov decision process, which can provide specific maintenance strategies in different degradation stages of the system. Specifically, the LSTM model is firstly applied to predict the remaining service life of equipment to distinguish its health state quantitatively. Then, based on the bearing residual life prediction curve, the degradation process model is constructed, and the corresponding parameters of the model are identified. Finally, the bearing degradation curve is obtained by the degradation process model, based on which the Markov decision process model is constructed to provide accurate maintenance strategies for different health conditions of system. To demonstrate the effectiveness of the proposed method, an experimental study with the full life cycle data set of rolling bearings is carried out. The experimental results show that the proposed method can achieve efficient maintenance decisions for bearings under different health states, which provides a feasible solution for the maintenance of bearing systems

Molecular Analysis of 14-3-3 Genes in Citrus sinensis and Their Responses to Different Stresses

14-3-3 proteins (14-3-3s) are among the most important phosphorylated molecules playing crucial roles in regulating plant development and defense responses to environmental constraints. No report thus far has documented the gene family of 14-3-3s in Citrus sinensis and their roles in response to stresses. In this study, nine 14-3-3 genes, designated as CitGF14s (CitGF14a through CitGF14i) were identified from the latest C. sinensis genome. Phylogenetic analysis classified them into ε-like and non-ε groups, which were supported by gene structure analysis. The nine CitGF14s were located on five chromosomes, and none had duplication. Publicly available RNA-Seq raw data and microarray databases were mined for 14-3-3 expression profiles in different organs of citrus and in response to biotic and abiotic stresses. RT-qPCR was used for further examining spatial expression patterns of CitGF14s in citrus and their temporal expressions in one-year-old C. sinensis “Xuegan” plants after being exposed to different biotic and abiotic stresses. The nine CitGF14s were expressed in eight different organs with some isoforms displayed tissue-specific expression patterns. Six of the CitGF14s positively responded to citrus canker infection (Xanthomonas axonopodis pv. citri). The CitGF14s showed expressional divergence after phytohormone application and abiotic stress treatments, suggesting that 14-3-3 proteins are ubiquitous regulators in C. sinensis. Using the yeast two-hybrid assay, CitGF14a, b, c, d, g, and h were found to interact with CitGF14i proteins to form a heterodimer, while CitGF14i interacted with itself to form a homodimer. Further analysis of CitGF14s co-expression and potential interactors established a 14-3-3s protein interaction network. The established network identified 14-3-3 genes and several candidate clients which may play an important role in developmental regulation and stress responses in this important fruit crop. This is the first study of 14-3-3s in citrus, and the established network may help further investigation of the roles of 14-3-3s in response to abiotic and biotic constraints

Identification and Functional Analysis of the <i>C</i><i>gNAC043</i> Gene Involved in Lignin Synthesis from <i>Citrus</i><i>grandis</i> “San Hong”

Overaccumulation of lignin (a physiological disorder known as granulation) often occurs during fruit ripening and postharvest storage in pomelo (Citrus grandis). It causes an unpleasant fruit texture and taste. Previous studies have shown that lignin metabolism is closely associated with the process of juice sacs granulation. At present, the underlying transcriptional regulatory mechanisms remain unclear. In this study, we identified and isolated a candidate NAC transcription factor, CgNAC043, that is involved in the regulation of lignin biosynthesis in Citrus grandis, which has homologs in Arabidopsis and other plants. We used the fruit juice sacs of ‘San hong’ as the material, the staining for lignin with HCl−phloroglucinol of fruit juice sacs became dark red from the various developmental stages at 172 to 212 days post anthesis (DPA). The RT-qPCR was used to analyze the gene expression of CgNAC043 and its target gene CgMYB46 in fruit sacs, it was found that the expression trend of CgNAC043 was basically same as CgMYB46, which increased gradually and peaked at 212 DPA. The expression level of CgNAC043 in juice sacs obtained away from the core was the lowest, while those near the core and granulated area were highly expressed. The transcriptional activation activity of CgNAC043 and CgMYB46 was analyzed by a yeast two-hybrid system, with only CgNAC043 showing transcriptional activation activity in Y2H Gold yeast. A transformation vector, p1301- CgNAC043, was transformed into the mesocarp of ‘San hong’ by Agrobacterium-mediated transformation. Results showed that the expression of transcription factors CgMYB58 and CgMYB46 are all upregulated. Further experiments proved that CgNAC043 not only can directly trans-activate the promoter of CgMYB46 but also trans-activate the promoters for the lignin biosynthesis-related genes CgCCoAOMT and CgC3H by dual luciferase assay. We isolated the CgNAC043 gene in pomelo and found CgNAC043 regulates target genes conferring the regulation of juice sacs granulation