Assessing differential gene expression with small sample sizes in oligonucleotide arrays using a mean-variance model

The identification of the genes that are differentially expressed in two-sample microarray experiments remains a difficult problem when the number of arrays is very small. We discuss the implications of using ordinary t-statistics and examine other commonly used variants. For oligonucleotide arrays with multiple probes per gene, we introduce a simple model relating the mean and variance of expression, possibly with gene-specific random effects. Parameter estimates from the model have natural shrinkage properties that guard against inappropriately small variance estimates, and the model is used to obtain a differential expression statistic. A limiting value to the positive false discovery rate (pFDR) for ordinary t-tests provides motivation for our use of the data structure to improve variance estimates. Our approach performs well compared to other proposed approaches in terms of the false discovery rate.     

非线性接触率和种群动力学对SI传染病模型的影响

本文研究了具有一般非线性接触率和易感类中具有Logistic增长的SI传染病模型的正不变集、平衡位置以及平衡位置的稳定性．     

Time-dependent cross ratio estimation for bivariate failure times

In the analysis of bivariate correlated failure time data, it is important to measure the strength of association among the correlated failure times. One commonly used measure is the cross ratio. Motivated by Cox's partial likelihood idea, we propose a novel parametric cross ratio estimator that is a flexible continuous function of both components of the bivariate survival times. We show that the proposed estimator is consistent and asymptotically normal. Its finite sample performance is examined using simulation studies, and it is applied to the Australian twin data.     

Roles of phospholipase D in phorbol myristate acetate‐stimulated neutrophil respiratory burst

The phorbol myristate acetate (PMA) stimulated nutrophil respiratory burst has been considered to simply involve the activation of protein kinase C (PKC). However, the PLD activity was also increased by 10‐fold in human neutrophils stimulated with 100 nM PMA. Unexpectedly, U73122, an inhibitor of phospholipase C, was found to significantly inhibit PMA‐stimulated respiratory burst in human neutrophils. U73122 at the concentrations, which were sufficient to inhibit the respiratory burst completely, caused partial inhibition of the PLD activity but no inhibition on PKC translocation and activation, suggesting that PLD activity is also required in PMA‐stimulated respiratory burst. Using 1‐butanol, a PLD substrate, to block phosphatidic acid (PA) generation, the PMA‐stimulated neutrophil respiratory burst was also partially inhibited, further indicating that PLD activation, possibly its hydrolytic product PA and diacylglycerol (DAG), is involved in PMA‐stimulated respiratory burst. Since GF109203X, an inhibitor of PKC that could completely inhibit the respiratory burst in PMA‐stimulated neutrophils, also caused certain suppression of PLD activation, it may suggest that PLD activation in PMA‐stimulated neutrophils might be, to some extent, PKC dependent. To further study whether PLD contributes to the PMA stimulated respiratory burst through itself or its hydrolytic product, 1,2‐dioctanoyl‐sn‐glycerol, an analogue of DAG , was used to prime cells at low concentration, and it reversed the inhibition of PMA‐stimulated respiratory burst by U73122. The results indicate that U73122 may act as an inhibitor of PLD, and PLD activation is required in PMA‐stimulated respiratory burst.     

Efficiency Boost in All-Small-Molecule Organic Solar Cells: Insights from the Re-Ordering Kinetics

Achieving high-performance in all-small-molecule organic solar cells (ASM-OSCs) significantly relies on precise nanoscale phase separation through domain size manipulation in the active layer. Nonetheless, for ASM-OSC systems, forging a clear connection between the tuning of domain size and the intricacies of phase separation proves to be a formidable challenge. This study investigates the intricate interplay between domain size adjustment and the creation of optimal phase separation morphology, crucial for ASM-OSCs’ performance. It is demonstrated that exceptional phase separation in ASM-OSCs’ active layer is achieved by meticulously controlling the continuity and uniformity of domains via re-packing process. A series of halogen-substituted solvents (Fluorobenzene, Chlorobenzene, Bromobenzene, and Iodobenzene) is adopted to tune the re-packing kinetics, the ASM-OSCs treated with CB exhibited an impressive 16.2% power conversion efficiency (PCE). The PCE enhancement can be attributed to the gradual crystallization process, promoting a smoothly interconnected and uniformly distributed domain size. This, in turn, leads to a favorable phase separation morphology, enhanced charge transfer, extended carrier lifetime, and consequently, reduced recombination of free charges. The findings emphasize the pivotal role of re-packing kinetics in achieving optimal phase separation in ASM-OSCs, offering valuable insights for designing high-performance ASM-OSCs fabrication strategies.     

AMPK regulates homeostasis of invasion and viability in trophoblasts by redirecting glucose metabolism: Implications for pre‐eclampsia

Pre‐eclampsia (PE) is deemed an ischemia‐induced metabolic disorder of the placenta due to defective invasion of trophoblasts during placentation; thus, the driving role of metabolism in PE pathogenesis is largely ignored. Since trophoblasts undergo substantial glycolysis, this study aimed to investigate its function and regulatory mechanism by AMPK in PE development. Metabolomics analysis of PE placentas was performed by gas chromatography–mass spectrometry (GC–MS). Trophoblast‐specific AMPKα1‐deficient mouse placentas were generated to assess morphology. A mouse PE model was established by Reduced Uterine Perfusion Pressure, and placental AMPK was modulated by nanoparticle‐delivered A769662. Trophoblast glucose uptake was measured by 2‐NBDG and 2‐deoxy‐d‐[³H] glucose uptake assays. Cellular metabolism was investigated by the Seahorse assay and GC–MS.PE complicated trophoblasts are associated with AMPK hyperactivation due not to energy deficiency. Thereafter, AMPK activation during placentation exacerbated PE manifestations but alleviated cell death in the placenta. AMPK activation in trophoblasts contributed to GLUT3 translocation and subsequent glucose metabolism, which were redirected into gluconeogenesis, resulting in deposition of glycogen and accumulation of phosphoenolpyruvate; the latter enhanced viability but compromised trophoblast invasion. However, ablation of AMPK in the mouse placenta resulted in decreased glycogen deposition and structural malformation. These data reveal a novel homeostasis between invasiveness and viability in trophoblasts, which is mechanistically relevant for switching between the ‘go’ and ‘grow’ cellular programs.

Pre‐eclampsia (PE) is associated with trophoblast AMPK hyperactivation, presumably due to LKB1 phosphorylation, and glucose uptake is consequently increased via trafficking of GLUT3 from the cytosol to the plasma membrane. Such translocation enhances glycolytic flux and redirects glucose metabolic intermediates into gluconeogenesis, resulting in PEP accumulation, which not only benefits cell survival but also suppresses invasion by repressing MMPs, and thus in turn modulates switching between the ‘go’ and ‘grow’ cellular programs.     

SCNVSim: somatic copy number variation and structure variation simulator

Background

Somatically acquired structure variations (SVs) and copy number variations (CNVs) can induce genetic changes that are directly related to tumor genesis. Somatic SV/CNV detection using next-generation sequencing (NGS) data still faces major challenges introduced by tumor sample characteristics, such as ploidy, heterogeneity, and purity. A simulated cancer genome with known SVs and CNVs can serve as a benchmark for evaluating the performance of existing somatic SV/CNV detection tools and developing new methods.

Results

SCNVSim is a tool for simulating somatic CNVs and structure variations SVs. Other than multiple types of SV and CNV events, the tool is capable of simulating important features related to tumor samples including aneuploidy, heterogeneity and purity.

Conclusions

SCNVSim generates the genomes of a cancer cell population with detailed information of copy number status, loss of heterozygosity (LOH), and event break points, which is essential for developing and evaluating somatic CNV and SV detection methods in cancer genomics studies.