Confidence intervals for the mean of diagnostic test charge data containing zeros

In this paper, we consider the problem of interval estimation for the mean of diagnostic test charges. Diagnostic test charge data may contain zero values, and the nonzero values can often be modeled by a log-normal distribution. Under such a model, we propose three different interval estimation procedures: a percentile-t bootstrap interval based on sufficient statistics and two likelihood-based confidence intervals. For theoretical properties, we show that the two likelihood-based one-sided confidence intervals are only first-order accurate and that the bootstrap-based one-sided confidence interval is second-order accurate. For two-sided confidence intervals, all three proposed methods are second-order accurate. A simulation study in finite-sample sizes suggests all three proposed intervals outperform a widely used minimum variance unbiased estimator (MVUE)-based interval except for the case of one-sided lower end-point intervals when the skewness is very small. Among the proposed one-sided intervals, the bootstrap interval has the best coverage accuracy. For the two-sided intervals, when the sample size is small, the bootstrap method still yields the best coverage accuracy unless the skewness is very small, in which case the bias-corrected ML method has the best accuracy. When the sample size is large, all three proposed intervals have similar coverage accuracy. Finally, we analyze with the proposed methods one real example assessing diagnostic test charges among older adults with depression.     

Further investigation on nuclear transplantation in different orders of teleost: the combination of the nucleus of Tilapia (Oreochromis nilotica) and the cytoplasm of Loach (Paramisgurnus dabryanus).

The nucleus of a blastula cell from Tilapia (Oreochromis nilotica, family Cichlidae, order Perciformes) was transplanted into an enucleated egg of Loach (Paramisgurnus dabryanus, family Cobitidae, order Cypriniformes). From among 3747 nucleo-cytoplasmic hybrid (NCH) eggs two NCH larval fish (0.05%) were obtained; one died on the 6th day and the other died on the 12th day after the operation. Morphological examinations showed that both NCH larval fish had developed normally with an opened mouth except they could not take food after complete utilization of their egg yolk on the 5th day of development. The possible mechanisms for obtaining such inter-order NCH larval fish are discussed. This is the first report indicating that inter-order NCH larval fish can be obtained in spite of their evolutionary divergence.     

Radiosynthesis and evaluation of a fluorine-18 labeled radioligand targeting vesicular acetylcholine transporter

Vesicular acetylcholine transporter (VAChT) is a reliable biomarker for assessing the loss of cholinergic neurons in the brain that is associated with cognitive impairment of patients. 5-Hydrotetralin compound (±)-5-OH-VAT is potent (K_i?=?4.64?±?0.32?nM) and selective for VAChT (>1800-fold and 398-fold for σ₁ and σ₂ receptor, respectively) with favorable hydrophilicity (LogD?=?1.78), while (?)-5-OH-VAT originally serves as the radiolabeling precursor of (?)-[¹⁸F]VAT, a promising VAChT radiotracer with a logD value of 2.56. To evaluate (?)-5-OH-[¹⁸F]VAT as a radiotracer for VAChT, we performed in vitro binding assay to determine the potency of the minus enantiomer (?)-5-OH-VAT and plus enantiomer (+)-5-OH-VAT, indicating that (?)-5-OH-VAT is a more potent VAChT enantiomer. Radiosynthesis of (?)-5-OH-[¹⁸F]VAT was explored using three strategies. (?)-5-OH-[¹⁸F]VAT was achieved with a good yield (24?±?6%) and high molar activity (～37?GBq/µmol, at the end of synthesis) using a microwave assisted two-step one-pot procedure that started with di-MOM protected nitro-containing precursor (?)-6. MicroPET studies in the brain of nonhuman primate (NHP) suggest that (?)-5-OH-[¹⁸F]VAT readily penetrated the blood brain barrier and specifically accumulated in the VAChT-enriched striatum with improved washout kinetics from striatum compared to [¹⁸F]VAT. Nevertheless, the lower target to non-target ratio may limit its use for in vivo measurement of the VAChT level in the brain.     

Personalized medicine and proteomics: lessons from non-small cell lung cancer

Personalized medicine allows the selection of treatments best suited to an individual patient and disease phenotype. To implement personalized medicine, effective tests predictive of response to treatment or susceptibility to adverse events are needed, and to develop a personalized medicine test, both high quality samples and reliable data are required. We review key features of state-of-the-art proteomic profiling and introduce further analytic developments to build a proteomic toolkit for use in personalized medicine approaches. The combination of novel analytical approaches in proteomic data generation, alignment and comparison permit translation of identified biomarkers into practical assays. We further propose an expanded statistical analysis to understand the sources of variability between individuals in terms of both protein expression and clinical variables and utilize this understanding in a predictive test.     

单面针的生物碱研究

自芸香科(Rutaceae)花椒属植物单面针(Zanthoxylum nitidum var. fastuosum How ex Huang)的根皮中分得五种已知生物碱:乙氧基白屈菜红碱(ethoxychelerythrine)(Ⅰ);氯化光花椒碱(nitidine chloride)(Ⅱ);去甲基白屈菜红碱(des-N-methychelerythrine)(Ⅲ);α—别隐品碱(α-allocryptopine)(Ⅳ);鹅掌揪宁(liriodenine)(Ⅴ).     

Critical contribution of immunoproteasomes in the induction of protective immunity against Trypanosoma cruzi in mice vaccinated with a plasmid encoding a CTL epitope fused to green fluorescence protein

Acquired immunity against infection with Trypanosoma cruzi is dependent on CD8(+)T cells. Here, to develop a vaccine strategy taking advantage of activated CD8(+)T cells, we constructed a DNA vaccine, designated pGFP-TSA1, encoding a fusion protein linking GFP to a single CTL epitope of TSA1, a leading candidate for vaccine against T. cruzi. C57BL/6 mice vaccinated with this plasmid showed suppressed parasitemia and prolonged survival. Vaccination with pGFP-TSA1 enhanced epitope-specific cytotoxicity and IFN-gamma secretion by CD8(+)T cells. Furthermore, the depletion of CD8(+)T cells prior to challenge infection with T. cruzi completely abolished this protection, indicating that CD8(+)T cells are the principal effector T cells involved. When mice deficient in the proteasome activator PA28alpha/beta or the immunoproteasome subunits LMP2 and LMP7 were used, the protective immunity against infection was profoundly attenuated. Our findings clearly demonstrate that vaccination with pGFP-TSA1 successfully induces protection dependent on CD8(+)T cell activation, in which immunoproteasomes play a crucial role. It is noteworthy to document that physical binding of the epitope and GFP is required for induction of this protection, since mice vaccinated with pTSA1-IRES-GFP failed to acquire resistance, probably because the epitope and GFP are separately expressed in the antigen-presenting cells.     

Improving of lipid productivity of the biodiesel promising green microalga <Emphasis Type="Italic">Chlorella pyrenoidosa</Emphasis> via low-energy ion implantation

High lipid content in microalgae is an essential parameter for adopting of microalgal biomass as a feedstock for biodiesel. Mutation is one approach to obtain desired algal strain with high lipid production. In this study, a mutant strain of Chlorella pyrenoidosa was isolated using 1.5?×?10¹⁵ ions cm^?2 s^?1 of N⁺ ion beam implantation technique, which has been widely used in mutagenesis of agricultural crops. N⁺ implantation slightly improved the growth of the mutant over the corresponding wild strain with significant increase in lipid content (32.4 % higher than the wild strain), which resulted in significant increase in lipid productivity by 35 %. In addition, ion implantation mutagenesis of C. pyrenoidosa resulted in 21.4 % decrease in total saturated fatty acids (SFAs) compared to the wild type, with a noticeable increase in polyunsaturated fatty acids (PUFAs). The increase in PUFAs was due mainly to stimulation of hexadecadienoic acid (C16:2) and octadecadienoic acid (C18:2) production. However, the SFA content of wild and mutant strains was 31.7 and 24.9 % of total fatty acids, respectively, highlighting the oxidative stability of biodiesel produced by both strains according to the European standards. Cultivation of C. pyrenoidosa mutant in selenite enrichment medium for five successive cultivation experiments showed insignificant changes in biomass productivity, lipid content, and lipid productivity alongside the study period, which confirms the genetic stability of the produced mutant. The present study confirmed the feasibility of generation of microalgae mutants with significant high lipid production using ion beam implantation.     

Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions

One key problem in computational neuroscience and neural engineering is the identification and modeling of functional connectivity in the brain using spike train data. To reduce model complexity, alleviate overfitting, and thus facilitate model interpretation, sparse representation and estimation of functional connectivity is needed. Sparsities include global sparsity, which captures the sparse connectivities between neurons, and local sparsity, which reflects the active temporal ranges of the input-output dynamical interactions. In this paper, we formulate a generalized functional additive model (GFAM) and develop the associated penalized likelihood estimation methods for such a modeling problem. A GFAM consists of a set of basis functions convolving the input signals, and a link function generating the firing probability of the output neuron from the summation of the convolutions weighted by the sought model coefficients. Model sparsities are achieved by using various penalized likelihood estimations and basis functions. Specifically, we introduce two variations of the GFAM using a global basis (e.g., Laguerre basis) and group LASSO estimation, and a local basis (e.g., B-spline basis) and group bridge estimation, respectively. We further develop an optimization method based on quadratic approximation of the likelihood function for the estimation of these models. Simulation and experimental results show that both group-LASSO-Laguerre and group-bridge-B-spline can capture faithfully the global sparsities, while the latter can replicate accurately and simultaneously both global and local sparsities. The sparse models outperform the full models estimated with the standard maximum likelihood method in out-of-sample predictions.