Weighting Based Approaches to Borrowing Historical Controls for Indirect comparison for Time-to-Event Data with a Cure Fraction

To use historical controls for indirect comparison with single-arm trials, the population difference between data sources should be adjusted to reduce confounding bias. The adjustment is more difficult for time-to-event data with a cure fraction. We propose different adjustment approaches based on pseudo observations and calibration weighting by entropy balancing. We show a simple way to obtain the pseudo observations for the cure rate and propose a simple weighted estimator based on them. Estimation of the survival function in presence of a cure fraction is also considered. Simulations are conducted to examine the proposed approaches. An application to a breast cancer study is presented

A Propensity-Score Integrated Approach to Bayesian Dynamic Power Prior Borrowing

Use of historical control data to augment a small internal control arm in a randomized control trial (RCT) can lead to significant improvement of the efficiency of the trial. It introduces the risk of potential bias, since the historical control population is often rather different from the RCT. Power prior approaches have been introduced to discount the historical data to mitigate the impact of the population difference. However, even with a Bayesian dynamic borrowing which can discount the historical data based on the outcome similarity of the two populations, a considerable population difference may still lead to a moderate bias. Hence, a robust adjustment for the population difference using approaches such as the inverse probability weighting or matching, can make the borrowing more efficient and robust. In this paper, we propose a novel approach integrating propensity score for the covariate adjustment and Bayesian dynamic borrowing using power prior. The proposed approach uses Bayesian bootstrap in combination with the empirical Bayes method utilizing quasi-likelihood for determining the power prior. The performance of our approach is examined by a simulation study. We apply the approach to two Acute Myeloid Leukemia (AML) studies for illustration

Probing the symmetry energy with isospin ratio from nucleons to fragments

Within the framework of ImQMD05, we study several isospin sensitive observables, such as DR(n/p) ratios, isospin transport ratio (isospin diffusion), yield ratios for LCPs between the projectile region and mid-rapidity region for the reaction systems Ni+Ni, Zn+Zn, Sn+Sn at low-intermediate energies. Our results show that those observables are sensitive to the density dependence of symmetry energy, and also depend on the cluster formation mechanism. By comparing these calculations to the data, the information of the symmetry energy and reaction mechanism is obtained.Comment: Talk given by Yingxun Zhang at the 11th International Conference on Nucleus-Nucleus Collisions (NN2012), San Antonio, Texas, USA, May 27-June 1, 2012. To appear in the NN2012 Proceedings in Journal of Physics: Conference Series (JPCS

An Object-Oriented Classification Method on High resolution Satellite Data

ABSTRACT：To traditional moderate or low resolution satellite data, the data processing or information detecting is only on a per-pixel basis because of the impacts to geometric accuracy of spatial resolution, Thereby only the spectral information is used for the classification. High spatial resolution sensors involves a general increase of spatial information and the accuracy of results may decrease on a per-pixel basis. In order to realise the full potential of the VHR image data, An object-oriented image analysis is implemented with the software eCognition. It is based on fuzzy logic, allows the integration of different object featrues, such as spectral values, shape and texture. In this paper we analysis an object-oriented classification method using QuickBird panchromatic and multispectral data on the test area of the PuDong New district of ShangHai.The analysis includes two parts: first dividing the image data into segments and then classifying the segments by means of fuzzy approach of nearest neighbour classifier

Cuproptosis/ferroptosis-related gene signature is correlated with immune infiltration and predict the prognosis for patients with breast cancer

Background: Breast invasive carcinoma (BRCA) is a malignant tumor with high morbidity and mortality, and the prognosis is still unsatisfactory. Both ferroptosis and cuproptosis are apoptosis-independent cell deaths caused by the imbalance of corresponding metal components in cells and can affect the proliferation rate of cancer cells. The aim in this study was to develop a prognostic model of cuproptosis/ferroptosis-related genes (CFRGs) to predict survival in BRCA patients.Methods: Transcriptomic and clinical data for breast cancer patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Cuproptosis and ferroptosis scores were determined for the BRCA samples from the TCGA cohort using Gene Set Variation Analysis (GSVA), followed by weighted gene coexpression network analysis (WGCNA) to screen out the CFRGs. The intersection of the differentially expressed genes grouped by high and low was determined using X-tile. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) were used in the TGCA cohort to identify the CFRG-related signature. In addition, the relationship between risk scores and immune infiltration levels was investigated using various algorithms, and model genes were analyzed in terms of single-cell sequencing. Finally, the expression of the signature genes was validated with quantitative real-time PCR (qRT‒PCR) and immunohistochemistry (IHC).Results: A total of 5 CFRGs (ANKRD52, HOXC10, KNOP1, SGPP1, TRIM45) were identified and were used to construct proportional hazards regression models. The high-risk groups in the training and validation sets had significantly worse survival rates. Tumor mutational burden (TMB) was positively correlated with the risk score. Conversely, Tumor Immune Dysfunction and Exclusion (TIDE) and tumor purity were inversely associated with risk scores. In addition, the infiltration degree of antitumor immune cells and the expression of immune checkpoints were lower in the high-risk group. In addition, risk scores and mTOR, Hif-1, ErbB, MAPK, PI3K/AKT, TGF-β and other pathway signals were correlated with progression.Conclusion: We can accurately predict the survival of patients through the constructed CFRG-related prognostic model. In addition, we can also predict patient immunotherapy and immune cell infiltration

Combining Multiple Algorithms for Road Network Tracking from Multiple Source Remotely Sensed Imagery: a Practical System and Performance Evaluation

In light of the increasing availability of commercial high-resolution imaging sensors, automatic interpretation tools are needed to extract road features. Currently, many approaches for road extraction are available, but it is acknowledged that there is no single method that would be successful in extracting all types of roads from any remotely sensed imagery. In this paper, a novel classification of roads is proposed, based on both the roads' geometrical, radiometric properties and the characteristics of the sensors. Subsequently, a general road tracking framework is proposed, and one or more suitable road trackers are designed or combined for each type of roads. Extensive experiments are performed to extract roads from aerial/satellite imagery, and the results show that a combination strategy can automatically extract more than 60% of the total roads from very high resolution imagery such as QuickBird and DMC images, with a time-saving of approximately 20%, and acceptable spatial accuracy. It is proven that a combination of multiple algorithms is more reliable, more efficient and more robust for extracting road networks from multiple-source remotely sensed imagery than the individual algorithms

Medicarpin induces G1 arrest and mitochondria-mediated intrinsic apoptotic pathway in bladder cancer cells

Bladder cancer (BC) is the tenth most commonly diagnosed cancer. High recurrence, chemoresistance, and low response rate hinder the effective treatment of BC. Hence, a novel therapeutic strategy in the clinical management of BC is urgently needed. Medicarpin (MED), an isoflavone from Dalbergia odorifera, can promote bone mass gain and kill tumor cells, but its anti-BC effect remains obscure. This study revealed that MED effectively inhibited the proliferation and arrested the cell cycle at the G1 phase of BC cell lines T24 and EJ-1 in vitro. In addition, MED could significantly suppress the tumor growth of BC cells in vivo. Mechanically, MED induced cell apoptosis by upregulating pro-apoptotic proteins BAK1, Bcl2-L-11, and caspase-3. Our data suggest that MED suppresses BC cell growth in vitro and in vivo via regulating mitochondria-mediated intrinsic apoptotic pathways, which can serve as a promising candidate for BC therapy

siRNAs compete with miRNAs for methylation by HEN1 in Arabidopsis

Plant microRNAs (miRNAs) and small interfering RNAs (siRNAs) bear a 2′-O-methyl group on the 3′-terminal nucleotide. This methyl group is post-synthetically added by the methyltransferase protein HEN1 and protects small RNAs from enzymatic activities that target the 3′-OH. A mutagenesis screen for suppressors of the partial loss-of-function hen1-2 allele in Arabidopsis identified second-site mutations that restore miRNA methylation. These mutations affect two subunits of the DNA-dependent RNA polymerase IV (Pol IV), which is essential for the biogenesis of 24 nt endogenous siRNAs. A mutation in RNA-dependent RNA polymerase 2, another essential gene for the biogenesis of endogenous 24-nt siRNAs, also rescued the defects in miRNA methylation of hen1-2, revealing a previously unsuspected, negative influence of siRNAs on HEN1-mediated miRNA methylation. In addition, our findings imply the existence of a negative modifier of HEN1 activity in the Columbia genetic background