A finite mixture of normal distributions, in both mean and variance parameters, is a typical finite mixture in the location and scale families. Because the likelihood function is unbounded for any ...sample size, the ordinary maximum likelihood estimator is not consistent. Applying a penalty to the likelihood function to control the estimated component variances is thought to restore the optimal properties of the likelihood approach. Yet this proposal lacks practical guidelines, has not been indisputably justified, and has not been investigated in the most general setting. In this paper, we present a new and solid proof of consistency when the putative number of components is equal to, and when it is larger than, the true number of components. We also provide conditions on the required size of the penalty and study the invariance properties. The finite sample properties of the new estimator are also demonstrated through simulations and an example from genetics.
In cancer research, two-stage designs are usually used to assess the effect of a new agent in phase II clinical trials. Optimal two-stage designs with two co-primary endpoints have been proposed to ...assess the effects of new cancer treatments, such as cytostatic or molecularly targeted agents (MTAs), based on both response rate and early progression rate. Accurate estimation of response and early progression rates based on the data from the phase II trials conducted according to the optimal two-stage designs would be very useful for further testing of the agents in phase II trials. In this paper, we derive some estimation procedures, which include both standard and bias-corrected maximum likelihood estimates (MLE) and uniformly minimum variance unbiased estimate (UMVUE), for two binomial probabilities which are used to define the hypotheses for two co-primary endpoints tested in a two-stage phase II clinical trial. Simulation studies were performed to evaluate the performance of these procedures. These procedures are also applied to analyze the data from a phase II trial conducted by the Canadian Cancer Trials Group.
The leaf area index (LAI) is crucial for assessing and monitoring maize (Zea mays L.) vegetation status and photosynthetic ability. Predicting maize LAI by hyperspectral remote sensing technology is ...significant for managing agricultural production. In this study, three N rates (0, 120, and 240 kg N ha−1) and four drought stress treatments (60–70%, 45–55%, 30–40%, and 15–25% of field capacity), were imposed to provide the different environments for maize. The canopy spectral reflectance and LAI of maize were measured at the V6 and V12 stages. In this study, the main objectives were to investigate the performance of a new statistical method for monitoring LAI from canopy spectral reflectance. We used the canopy spectral reflectance to estimate the LAI and compared several methods of spectral analysis, including vegetation indices, wavelet functions, and the combination of continuous wavelet transform (CWT)–uninformative variable elimination (UVE)–partial least squares (PLS) (i.e., CWT–UVE–PLS), for spectral reflectance data analysis and model construction of maize LAI. Results showed that the model using the combination of db3–UVE–PLS achieved the best performance (with the highest coefficient of determination R2 and lowest RMSE for the calibration R2 = .979, RMSEC = .172 and validation R2 = .861, RMSEP = .533 datasets, respectively) in estimating the maize LAI. The CWT–UVE–PLS exhibited a considerable advantage in avoiding redundant or noise information interaction and achieving excellent correlations with maize LAI.
Core Ideas
The CWT‐UVE‐PLS method was developed to estimate maize leaf area index.
The vegetation indices and wavelet functions show a strong correlation with the leaf area index.
The CWT‐UVE‐PLS method achieves the best R2 and the lowest root mean square error.
The CWT‐UVE‐PLS method can overcome the underestimation problem and saturation effect.
The leaf area index can be accurately monitored with the CWT‐UVE‐PLS method.
Aging leads to structural and functional changes in the vasculature characterized by arterial endothelial dysfunction and stiffening of large elastic arteries and is a predominant risk factor for ...cardiovascular disease, the leading cause of morbidity and mortality in modern societies. Although exercise reduces the risk of many age-related diseases, including cardiovascular disease, the mechanisms underlying the beneficial effects of exercise on age-related endothelial function fully elucidated.
The present study explored the effects of exercise on the impaired endothelium-derived hyperpolarizing factor (EDHF)-mediated vasodilation in aged arteries and on the involvement of the transient receptor potential vanilloid 4 (TRPV4) channel and the small-conductance calcium-activated potassium (K
2.3) channel signaling in this process.
Male Sprague-Dawley rats aged 19-21 months were randomly assigned to a sedentary group or to an exercise group. Two-month-old rats were used as young controls.
We found that TRPV4 and K
2.3 isolated from primary cultured rat aortic endothelial cells pulled each other down in co-immunoprecipitation assays, indicating that the two channels could physically interact. Using ex vivo functional arterial tension assays, we found that EDHF-mediated relaxation induced by acetylcholine or by the TRPV4 activator GSK1016790A was markedly decreased in aged rats compared with that in young rats and was significantly inhibited by TRPV4 or K
2.3 blockers in both young and aged rats. However, exercise restored both the age-related and the TRPV4-mediated and K
2.3-mediated EDHF responses.
These results suggest an important role for the TRPV4-K
2.3 signaling undergirding the beneficial effect of exercise to ameliorate age-related arterial dysfunction.
Purpose
To estimate the radiobiological parameters of three popular NTCP models, which describe the dose–response relations of carotid blowout syndrome (CBOS) after stereotactic body radiotherapy ...(SBRT). To evaluate the goodness‐of‐fit and the correlation of those models with CBOS.
Methods
The study included 61 patients with inoperable locally recurrent head and neck cancer treated with SBRT using CyberKnife (Accuray, Sunnyvale, CA) at the Department of Radiation Oncology, Hacettepe University, Ankara, Turkey between June 2007 and March 2011. The dose‐volume histograms of the internal carotid were exported from the plans of all the patients. The follow‐up results regarding the end point of carotid blowout syndrome were collected retrospectively. Initially, univariable analyses (Wilcoxon rank‐sum or Chi‐square tests) and a multivariate logistic regression analysis were performed between the outcome data and a list of clinical and treatment factors to identify significant correlations. Additionally, the Lyman–Kutcher–Burman (LKB), Relative Seriality (RS), and Logit NTCP models were used to fit the clinical data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC), Akaike information criterion (AIC), and Odds Ratio methods.
Results
The clinical/treatment factors that were found to have a significant or close to significant correlations with acute CBOS were Age at the time of CK (P‐value = 0.03), Maximum carotid dose (P‐value = 0.06), and CK prescription dose (P‐value = 0.08). Using Dmax, physical DVH, and EQD2 Gy‐DVH as the dosimetric metrics in the NTCP models, the derived LKB model parameters were: (a) D50 = 45.8 Gy, m = 0.24, n = n/a; (b) D50 = 44.8 Gy, m = 0.28, n = 0.01; and (c) D50 = 115.8 Gy, m = 0.45, n = 0.01, respectively. The AUC values for the dosimetric metrics were 0.70, 0.68, and 0.61, respectively. The differences in AIC between the different models were less than 2 and ranged within ±0.9.
Conclusion
The maximum dose to the internal carotid less than 34 Gy appears to significantly reduce the risk for CBOS. Age at the time of CK, Maximum carotid dose, and CK prescription dose were also found to correlate with CBOS. The values of the parameters of three NTCP models were determined for this endpoint. A threshold of gEUD <34.5 Gy appears to be significantly associated with lower risks of CBOS.
Abstract
PURPOSE/OBJECTIVE(S)
The primary purpose of this study is to determine whether a machine learning approach can estimate survival in patients with brain metastases undergoing stereotactic ...radiosurgery or fractionated stereotactic radiotherapy (SRS/SRT). The secondary purpose is to identify covariates of importance.
MATERIALS/METHODS
Data were collected for 377 SRS/SRT treatments in 291 patients done between the years 2008-2021. If a patient was treated with more than one course of SRS/SRT within 30 days, they were counted only once. Twenty-five clinically-relevant variables were identified as covariates and the primary outcome of time from brain metastasis diagnoses to death was used to build a random survival forest model. Brain metastasis location was categorized as infratentorial, supratentorial, or both. An 80/20 split was used for training (n = 302) and test (n = 75) sets. Missing data points were imputed using a just-in-time adaptive tree approach. Minimal depth and variable importance (VIMP) approaches were used to identify prognostic factors. Model performance was assessed using time-dependent area under the receiver operating characteristics curve (tAUC).
RESULTS
Median survival time was 16 months. The most important variables according to minimal depth analysis (depth threshold 5.23) were Karnofsky Performance Status (KPS), extracranial status, age, insurance status, metastases volume, histology, number of metastases, and location. Error rate on the test set was 0.38. tAUC was found to increase continuously over time and at 6, 12, 24, and 36 months was 0.56, 0.63, 0.74, and 0.84 respectively.
CONCLUSION
An ensemble tree approach can provide good survival prediction for patients with brain metastases undergoing SRS/SRT. Model performance, as measured by tAUC, increases over time suggesting better predictive capability at longer time intervals. Future directions include collecting more data to increase model performance, comparing to other models, and validating with external data.
von Hippel-Lindau (VHL) is a critical tumor suppressor in clear cell renal cell carcinomas (ccRCCs). It is important to identify additional therapeutic targets in ccRCC downstream of VHL loss besides ...hypoxia-inducible factor 2α (HIF2α). By performing a genome-wide screen, we identified Scm-like with four malignant brain tumor domains 1 (SFMBT1) as a candidate pVHL target. SFMBT1 was considered to be a transcriptional repressor but its role in cancer remains unclear. ccRCC patients with VHL loss-of-function mutations displayed elevated SFMBT1 protein levels. SFMBT1 hydroxylation on Proline residue 651 by EglN1 mediated its ubiquitination and degradation governed by pVHL. Depletion of SFMBT1 abolished ccRCC cell proliferation in vitro and inhibited orthotopic tumor growth in vivo. Integrated analyses of ChIP-seq, RNA-seq, and patient prognosis identified sphingosine kinase 1 (SPHK1) as a key SFMBT1 target gene contributing to its oncogenic phenotype. Therefore, the pVHL-SFMBT1-SPHK1 axis serves as a potential therapeutic avenue for ccRCC.
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•A genome-wide screen identified SFMBT1 as a pVHL target•Potential Proline hydroxylation of SFMBT1 decreases its protein stability and is regulated by pVHL•SFMBT1 promotes ccRCC tumorigenesis and is upregulated in patients with ccRCC•SFMBT1 increases SPHK1 expression in ccRCC
The pVHL-SFMBT1-SPHK1 axis serves as a potential therapeutic avenue for ccRCC.
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