A combination of the K-L and S-P approaches for treating acetabular posterior wall factures accompanied by femoral head fractures with open reduction and internal fixation.

Background: In clinical practice, acetabular posterior wall fracture combined with femoral head fracture is rare. However, with the increasing number of engineering and traffic accidents, such fractures, have increased significantly in recent years. This paper aims to explore the clinical efficiency of the Kocher-Langenbeck (K-L) and Smith-Petersen (S-P) combined approaches for open reduction and internal fixation (ORIF) of acetabular posterior wall fractures accompanied by femoral head fractures (Pipkin type IV fractures).

An adaptive gBOIN design with shrinkage boundaries for phase I dose-finding trials.

Background: With the emergence of molecularly targeted agents and immunotherapies, the landscape of phase I trials in oncology has been changed. Though these new therapeutic agents are very likely induce multiple low- or moderate-grade toxicities instead of DLT, most of the existing phase I trial designs account for the binary toxicity outcomes. Motivated by a pediatric phase I trial of solid tumor with a continuous outcome, we propose an adaptive generalized Bayesian optimal interval design with shrinkage boundaries, gBOINS, which can account for continuous, toxicity grades endpoints and regard the conventional binary endpoint as a special case.

Testing quantitative trait locus effects in genetic backcross studies with double recombination occurring.

Testing the existence of quantitative trait locus (QTL) effects is an important task in QTL mapping studies. In this paper, we assume the phenotype distributions from a location-scale distribution family, and consider to test the QTL effects in both location and scale in the backcross studies with double recombination occurring. Without equal scale assumption, the log-likelihood function is unbounded, which leads to the traditional likelihood ratio test being invalid.

Meta-Analyzing Multiple Omics Data With Robust Variable Selection.

High-throughput omics data are becoming more and more popular in various areas of science. Given that many publicly available datasets address the same questions, researchers have applied meta-analysis to synthesize multiple datasets to achieve more reliable results for model estimation and prediction. Due to the high dimensionality of omics data, it is also desirable to incorporate variable selection into meta-analysis.

Meta-analysis with zero-event studies: a comparative study with application to COVID-19 data.

Background: Meta-analysis is a statistical method to synthesize evidence from a number of independent studies, including those from clinical studies with binary outcomes. In practice, when there are zero events in one or both groups, it may cause statistical problems in the subsequent analysis.

Methods: In this paper, by considering the relative risk as the effect size, we conduct a comparative study that consists of four continuity correction methods and another state-of-the-art method without the continuity correction, namely the generalized linear mixed models (GLMMs).

Diagonal likelihood ratio test for equality of mean vectors in high-dimensional data.

We propose a likelihood ratio test framework for testing normal mean vectors in high-dimensional data under two common scenarios: the one-sample test and the two-sample test with equal covariance matrices. We derive the test statistics under the assumption that the covariance matrices follow a diagonal matrix structure. In comparison with the diagonal Hotelling's tests, our proposed test statistics display some interesting characteristics.

A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix.

Expression of a Codon-Optimized dsdA Gene in Tobacco Plastids and Rice Nucleus Confers D-Serine Tolerance.

D-serine is toxic to plants. D-serine ammonia lyase, which is encoded by the dsdA gene, can attenuate this toxicity with high specificity. In the present study, we explored the function of codon-optimized dsdA with tobacco plastids and rice nuclear transformation system.

Functional analysis of OsPGIP1 in rice sheath blight resistance.

As one of the most devastating diseases of rice, sheath blight causes severe rice yield loss. However, little progress has been made in rice breeding for sheath blight resistance. It has been reported that polygalacturonase inhibiting proteins can inhibit the degradation of the plant cell wall by polygalacturonases from pathogens.