En-bloc transurethral resection vs. conventional transurethral resection for primary non-muscle invasive bladder cancer: A meta-analysis

INTRODUCTION

We performed a meta-analysis to evaluate the effect of en-bloc transurethral resection vs. conventional transurethral resection for primary non-muscle invasive bladder cancer.

METHODS

A systematic literature search up to January 2022 was done and 28 studies included 3714 primary non-muscle invasive bladder cancer subjects at the start of the study; 1870 of them were en-bloc transurethral resection, and 1844 were conventional transurethral resection for primary non-muscle invasive bladder cancer. We calculated the odds-ratio (OR) and mean-difference (MD) with 95% confidence-intervals (CIs) to evaluate the effect of en-bloc transurethral resection compared with conventional transurethral resection for primary non-muscle invasive bladder cancer by the dichotomous or continuous methods with random or fixed-effects models.

RESULTS

En-bloc transurethral resection had significantly lower twenty-four-month recurrence (OR: 0.63; 95%CI: 0.50-0.78; p < 0.001), catheterization-time (MD: -0.66; 95%CI: -1.02-[-0.29]; p < 0.001), length of hospital stay (MD: -0.95; 95%CI: -1.55-[-0.34]; p = 0.002), postoperative bladder irrigation duration (MD: -6.06; 95%CI: -9.45-[-2.67]; p < 0.001), obturator nerve reflex (OR: 0.08; 95%CI: 0.02-0.34; p = 0.03), and bladder perforation (OR: 0.14; 95%CI: 0.06-0.36: p < 0.001) and no significant difference in the 12-month-recurrence (OR: 0.79; 95%CI: 0.61-1.04; p = 0.09), the operation time (MD: 0.67; 95%CI: -1.92 to 3.25; p = 0.61), and urethral stricture (OR: 0.46; 95%CI: 0.14-1.47; p = 0.0.19) compared with conventional transurethral resection for primary non-muscle invasive bladder cancer subjects.

CONCLUSIONS

En-bloc transurethral resection had a significantly lower twenty-four-month recurrence, catheterization time, length of hospital stay, postoperative bladder irrigation duration, obturator nerve reflex, bladder perforation, and no significant difference in the twelve-month recurrence, operation time, and urethral stricture compared with conventional transurethral resection for primary non-muscle invasive bladder cancer subjects. Further studies are required.

Revealing the sensory impact of different levels and combinations of esters and volatile thiols in Chardonnay wines

The assessment of different aroma families on tropical fruit aroma perception is still not well understood. This study aimed to investigate the effect of esters and volatile thiols on tropical fruit aroma perception in white wines. Four levels of thiols (none, low, medium and high) and three levels of esters (none, low, medium) were added to a dearomatized white wine base in a full factorial design. Check-All-That-Apply (CATA) was used to determine the aroma descriptors that most differentiated the wines followed by Sensory Descriptive Analysis (SDA) to evaluate the intensity of those significant aroma attributes. More than 78% of the total variance was described in the first two dimensions when using Canonical Variate Analysis. Tropical fruit aromas were associated with wines containing different levels of esters and ester-thiol combinations. Volatile thiols alone imparted an earthy aroma and were grouped with the control wine. The different ester-thiol combinations altered the tropical fruit aroma quality in the wines from citrus to passionfruit, pineapple and guava. Understanding the cause of tropical fruit aroma allows for targeted processing to achieve the desired wine sensory quality.

Characterizing the extracellular matrix transcriptome of cervical, endometrial, and uterine cancers

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The matrisome plays a critical role in the progression of cancer, but the matrisomes of gynecological cancers have not been well characterized.

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We built an in silico analysis pipeline to analyze publicly available bulk RNA-seq datasets of cervical, endometrial, and uterine cancers.

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Using a machine learning approach, we identified genes and gene networks that held inferential significance for cancer stage and patient survival.

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Cervical, endometrial, and uterine cancers are highly distinct from one another and should be analyzed separately.

Increasingly, the matrisome, a set of proteins that form the core of the extracellular matrix (ECM) or are closely associated with it, has been demonstrated to play a key role in tumor progression. However, in the context of gynecological cancers, the matrisome has not been well characterized. A holistic, yet targeted, exploration of the tumor microenvironment is critical for better understanding the progression of gynecological cancers, identifying key biomarkers for cancer progression, establishing the role of gene expression in patient survival, and for assisting in the development of new targeted therapies. In this work, we explored the matrisome gene expression profiles of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), uterine corpus endometrial carcinoma (UCEC), and uterine carcinosarcoma (UCS) using publicly available RNA-seq data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) portal. We hypothesized that the matrisomal expression patterns of CESC, UCEC, and UCS would be highly distinct with respect to genes which are differentially expressed and hold inferential significance with respect to tumor progression, patient survival, or both. Through a combination of statistical and machine learning analysis techniques, we identified sets of genes and gene networks which characterized each of the gynecological cancer cohorts. Our findings demonstrate that the matrisome is critical for characterizing gynecological cancers and transcriptomic mechanisms of cancer progression and outcome. Furthermore, while the goal of pan-cancer transcriptional analyses is often to highlight the shared attributes of these cancer types, we demonstrate that they are highly distinct diseases which require separate analysis, modeling, and treatment approaches. In future studies, matrisome genes and gene ontology terms that were identified as holding inferential significance for cancer stage and patient survival can be evaluated as potential drug targets and incorporated into in vitro models of disease.

Effects of blood pathological changes before TAI on pregnancy of dairy cows with anestrus and estrus

ABSTRACT The objective of this study was to investigate the influence of plasma pathological changes before timed artificial insemination (TAI) on pregnancy of cows. The contents of estrogen (E2), progesterone (P4), glucose (Glu), selenium (Se), brain-derived neurotrophic factor (BDNF), and histamine (HIS) in plasma of 48 Holstein cows were measured before TAI. According to the estrus detection, the cows were divided into estrus (E) and anestrus (A) groups. After pregnancy testing at 28 d after TAI, two groups of E and A were divided into positive pregnancy of E group (EP+), negative pregnancy of E group (EP-), positive pregnancy of A group (AP+), and negative pregnancy of A group (AP-). The contents of E2, P4, Glu, Se, BDNF and hIS significantly differed among the four groups (P<0.01). The ROC analysis was used to determine the risk of negative pregnancy test (-) after TAI was increased when plasma E2 was less than 46.45 pmol/L in cows before TAI. The changes in E2, P4,hIS, Glu, and BDNF in the blood of natural estrus and natural anestrus cows affected the pregnancy after TAI. the level of E2 in plasma may be used to assess the risk of negative pregnancy after TAI.

[Retinal toxicity study of intravitreal ganciclovir in albino rabbit]

Objective: To elevated the retinal toxicity of intravitreal ganciclovir in albino rabbit eyes. Methods: Experimental study. Twenty-four New Zealand albino rabbits (forty-eight eyes) were divided into four groups by random. Three groups were prepared for ganciclovir experiment, named A, B, C. Each group received intravitreal injection ganciclovir dose at 400 μg/0.05 ml, 2 mg/0.05 ml and 5 mg/0.05 ml respectively. The other group named D served as a control accepted intravitreal injection 0.9% normal saline 0.1 ml. Before and after 1, 2 and 4 weeks, flicker full field electroretina gram (ERG) was recorded. After 1, 2 and 4 weeks light and electron microscopic tests were recorded for further toxicity study. Results: There was significant difference in amplitude of maximal combined response a wave in one week(χ(2)=8.319, P=0.04), and pairwise comparison the 5 mg group (140.50 μV) was significantly lower than the control group (165.00 μV) (χ(2)=-2.830, P=0.028). Maximal combined response b wave in four weeks(χ(2)=-10.626, P=0.014), and pairwise comparison the 5 mg group (261.50 μV) was significantly lower than the control group (398.00 μV) (χ(2)=-2.973, P=0.018). 30 Hz flicker response in one, two and four weeks(χ(2)=17.589, 8.225, 8.997, P=0.001, 0.042, 0.02), and pairwise comparison the 5 mg group (71.3μV, 106.00μV, 63.60μV) was significantly lower than the control group (118.50μV, 129.00μV, 116.50μV) (χ(2)=-4.142, -2.826, -2.713, P=0.000, 0.028, 0.040). There was no histologic retinal toxicity evidence of group 400 μg and control group observed by light microscopy in any stage of the study. Histologic changes of group 2 mg four week later, group 5 mg two and four week later include inner nuclear layer loose arranged, nuclear of ganglia were widened and outer plexiform layer stained less in four week later. By electron microscopic observation, the ultrastructure of retina changed to different degrees and became worse in each experimental group with significant mitochondrial swelling and hydropic changes were seen in the inner segments of photoreceptors, loosely arranged and disordered in the outer segment of photoreceptors four weeks later. Conclusions: The retinal function and morphology were normal in group 400 μg. Group 2 mg and 5 mg had retinal toxicity, and 5 mg was more severe. Therefore, the clinical application of ganciclovir in the treatment of acute retinal necrosis (ARN) should select the minimum effective dose to avoid the occurrence of retinal toxicity. (Chin J Ophthalmol, 2020, 56:279-285).

Model-Based Clustering with Measurement or Estimation Errors

Model-based clustering with finite mixture models has become a widely used clustering method. One of the recent implementations is MCLUST. When objects to be clustered are summary statistics, such as regression coefficient estimates, they are naturally associated with estimation errors, whose covariance matrices can often be calculated exactly or approximated using asymptotic theory. This article proposes an extension to Gaussian finite mixture modeling-called MCLUST-ME-that properly accounts for the estimation errors. More specifically, we assume that the distribution of each observation consists of an underlying true component distribution and an independent measurement error distribution. Under this assumption, each unique value of estimation error covariance corresponds to its own classification boundary, which consequently results in a different grouping from MCLUST. Through simulation and application to an RNA-Seq data set, we discovered that under certain circumstances, explicitly, modeling estimation errors, improves clustering performance or provides new insights into the data, compared with when errors are simply ignored, whereas the degree of improvement depends on factors such as the distribution of error covariance matrices.

[The relationship between optical coherence tomography performance and visual acuity of acute retinal necrosis]

Objective: To analyze the relationship between optical coherence tomography(OCT) performance and visual acuity of patients with acute retinal necrosis (ARN). Methods: Retrospective analysis was performed on the patients diagnosed with ARN at the ophthalmology department of Peking union hospital during October 2011 and May 2016. Fourteen patients (15 eyes), 9 males and 5 females, whose anterior and posterior inflammation disappeared and the retinal necrosis lesion in the fundus of the eye subsided were included. The mean age was (41.6±12.2) years. All patients underwent careful examinations including best corrected visual acuity (BCVA), slit-lamp microscope, indirect ophthalmoscope, color fundus picture, fundus fluorescein angiography (FFA) and OCT (results of their last consultations). Results: BCVA: 8 eyes were increased, 2 eyes were unchanged and 5 eyes were decreased at the last visit; light perception (LP) 1 eye, finger count (FC) 1 eye, 3 eyes of 0.01 to 0.1, 6 eyes of 0.15 to 0.25. The inflammatory reaction in the anterior segment of 14 eyes disappeared, while the inflammatory reaction of the remaining 1 eye was relieved. The fundus lesions of all 15 eyes disappeared. According to OCT results: five eyes (5/15) exhibited normal macula area, among the 5 eyes, 4 eyes are of 0.15 to 0.25 visual acuity, and 1 eye is of 0.5 visual acuity;macular epiretinal membrane is present in three eyes (3/15), of which the visual acuity is 0.02, 0.25 and 0.3 respectively macula edema is present in three eyes (3/15), among the 3 eyes, 1 eye (visual acuity of 0.01)showed thickening of neurosensory retina, cystoid change of fovea and several fluid dark areas, the other 2 eyes (visual acuity of 0.02 and 0.5 respectively) showed small diffuse fluid dark area in the neurosensory retina;atrophy of neurosensory retina and absence of IS/OS was found in four eyes (4/15), among the 4 eyes, the visual acuity of 3 is below 0.01, and the other 1 eye is of 0.08 visual acuity. Conclusions: The OCT performance of stationary phase of ARN tends to be positively correlated with the visual acuity of patients. The prognosis of visual acuity of the patients whose OCT results showed atrophy of neurosensory retina and absence of IS/OS is poor. (Chin J Ophthalmol, 2018, 54: 369-374).

[Research progress on the diagnosis and treatment of acute retinal necrosis]

Acute retinal necrosis is an uncommon but devastating and potentially blinding ophthalmopathy featured with unfavorable prognosis as the lesions tend to develop rapidly in a circumferential way in few days. Therefore timely diagnosis and early treatment are of great significance. The polymerase chain reaction test on intraocular fluid can improve specificity and sensitivity of the etiological detection for acute retinal necrosis. Etiology results included in the diagnostic criteria is favorable for etiological diagnosis. Current treatment for acute retinal necrosis is generally based on systemic antiviral therapy, and supported by hormone and antithrombotic drugs, while surgical treatment should be considered when the disease progresses. This article reviews the research progress on the diagnosis and treatment of acute retinal necrosis in an effort to improve the diagnosis and treatment performance of acute retinal necrosis. (Chin J Ophthalmol, 2018, 54: 306-311).

[Current research of sympathetic ophthalmia]

Sympathetic ophthalmia (SO) is a rare, bilateral, non-necrotizing, granulomatous uveitis that usually occurs after open ocular injury or intraocular surgery. The pathophysiology is not clearly understood, but generally SO is an immediate hypersensitivity mediated by T lymphocytes which are related to ocular tissue antigens. The main histopathological features are granulation tissues composed of lymphocytes, macrophages and multinucleated giant cells. The clinical manifestations are different from person to person, which might be mild or severe. Although it could be presented with anterior uveitis, intermediate uveitis and posterior uveitis, panuveitis is the most common sign. The ophthalmic examinations, such as fundus fluorescein angiography, optical coherence tomography and B-scan, could be used to observe the patients' conditions and monitor the therapeutic effect. The main treatment of SO is medical therapy with corticosteroids, immunomodulators and biomodulators. Topical drug administration, including intravitreal injection of triamcinolone acetonide and implantation of a fluocinolone acetonide implant, can be considered. There is controversy about whether enucleation or evisceration is more appropriate and when the procedure should be done. The prognosis of SO could be poor. SO is liable to deteriorate and may lead to blindness. This article reviews the etiology, mechanisms, histopathology, clinical characteristics, diagnosis and treatment of SO. (Chin J Ophthalmol, 2017, 53:778-782).

[The ocular manifestations of human immunodeficiency virus and syphilis coinfection]

Objective: To investigate the ocular manifestations of human immunodeficiency virus (HIV) and syphilis coinfection. Methods: A retrospective analysis of the ocular manifestations was carried out in 27 patients (54 eyes) diagnosed as syphilis and HIV coinfection by the Department of Infectious Medicine in Peking Union Medical College Hospital during the years of 2006-2017. The research included 26 males and 1 female, aging from 24 to 76 years old, with a mean age of 40.40±12.94 years old. Ocular anterior segments were examined with slit-lamp microscope. Fundus examinations were conducted with papillary dilation, fundus photography. Results: At the first visit, there were 2 eyes without light perception, 4 eyes with light perception, 1 eye with hand movement, 1 eye with finger counting, 2 eyes with 0.01-0.09 eyesight, 8 eyes with 0.1-0.2 eyesight, 12 eyes with 0.25-0.4 eyesight, 15 eyes with 0.5-0.9 eyesight, 9 eyes with 1.0-1.5 eyesight. Among the 27 patients (54 eyes) coinfected with HIV and syphilis, keratic precipitates were identified in 20 eyes, aqueous flare positive in 20 eyes, float positive in 15 eyes, and iris posterior synechias in 7 eyes. Nineteen eyes were diagnosed as syphilis uveitis, including 2 eyes with syphilis anterior uveitis and 17 eyes with syphilis panuveitis, among which, vitreous inflammatory opacity was observed in all 19 eyes, disk atrophy in 2 eyes, optic edema in 1 eye, vitreous hemorrhage in 1 eye, retinal detachment in 2 eyes, retinal hemorrhage and white vein in 1 eye. In addition, 8 eyes were diagnosed as HIV retinopathy, all manifested as cotton-wool spot. Among the 8 eyes, 4 were diagnosed as cytomegalovirus retinitis, 3 showed retinal yellow-white lesions, and 1 was in late phase which showed retinal pigmentation. The incidence of both HIV and syphilis coinfection patients and male homosexuality population increased. The most common ocular manifestation of HIV and syphilis coinfection was syphilis panuveitis. Six patients first visited the Department of Ophthalmology, and were then diagnosed as HIV and syphilis coinfection. Conclusions: The ocular manifestations of HIV and syphilis coinfection are diversified, which can be manifested as fundus necrotic lesions as well as anterior and posterior inflammatory. For HIV positive patients, syphilis serologic test should be routinely performed. The same, syphilis positive patients should be tested for HIV serum antibodies, in order to improve the diagnosis level of HIV/syphilis coinfection and give timely etiological treatment, which is of vital importance for saving visual acuity. (Chin J Ophthalmol, 2019, 55:267-272).

Searching for best lower dimensional visualization angles for high dimensional RNA-Seq data

The accumulation of RNA sequencing (RNA-Seq) gene expression data in recent years has resulted in large and complex data sets of high dimensions. Exploratory analysis, including data mining and visualization, reveals hidden patterns and potential outliers in such data, but is often challenged by the high dimensional nature of the data. The scatterplot matrix is a commonly used tool for visualizing multivariate data, and allows us to view multiple bivariate relationships simultaneously. However, the scatterplot matrix becomes less effective for high dimensional data because the number of bivariate displays increases quadratically with data dimensionality. In this study, we introduce a selection criterion for each bivariate scatterplot and design/implement an algorithm that automatically scan and rank all possible scatterplots, with the goal of identifying the plots in which separation between two pre-defined groups is maximized. By applying our method to a multi-experiment Arabidopsis RNA-Seq data set, we were able to successfully pinpoint the visualization angles where genes from two biological pathways are the most separated, as well as identify potential outliers.

[Application of optical coherence tomography angiography in ophthalmology]

Optical coherence tomography angiography (OCTA) is a new technology of angiography in recent years. It has advantages of the optical coherence tomography (OCT), moreover, it can hierarchically observe the vascular morphology of the retina and choroid. By using the pseudo-color, abnormal vascular structure can be distinguished from normal vascular structure of the retina. With the fusion of the OCTA image and the regular OCT image, the structure and blood flow information can be obtained at the same time. This technology provides another method of examination for clinical ophthalmology, especially for the diagnosis of retinal diseases. This review will analyze and summarize the operating principle of OCTA, its application in ophthalmology, as well as its advantages and limitations. (Chin J Ophthalmol, 2017, 53: 65-72).

Identifying stably expressed genes from multiple RNA-Seq data sets

We examined RNA-Seq data on 211 biological samples from 24 different Arabidopsis experiments carried out by different labs. We grouped the samples according to tissue types, and in each of the groups, we identified genes that are stably expressed across biological samples, treatment conditions, and experiments. We fit a Poisson log-linear mixed-effect model to the read counts for each gene and decomposed the total variance into between-sample, between-treatment and between-experiment variance components. Identifying stably expressed genes is useful for count normalization and differential expression analysis. The variance component analysis that we explore here is a first step towards understanding the sources and nature of the RNA-Seq count variation. When using a numerical measure to identify stably expressed genes, the outcome depends on multiple factors: the background sample set and the reference gene set used for count normalization, the technology used for measuring gene expression, and the specific numerical stability measure used. Since differential expression (DE) is measured by relative frequencies, we argue that DE is a relative concept. We advocate using an explicit reference gene set for count normalization to improve interpretability of DE results, and recommend using a common reference gene set when analyzing multiple RNA-Seq experiments to avoid potential inconsistent conclusions.

The spatial-temporal variations of water quality in controlling points of the main rivers flowing into the Miyun Reservoir from 1991 to 2011

Cluster analysis (CA), discriminant analysis (DA), and principal component analysis/factor analysis (PCA/FA) were used to analyze the interannual, seasonal, and spatial variations of water quality from 1991 to 2011 in controlling points (Xinzhuang Bridge, Daguan Bridge) of the main rivers (Chaohe River, Baihe River) flowing into the Miyun Reservoir. The results demonstrated that total nitrogen (TN) and total phosphorus (TP) exceeded China National Standard II for surface water separately 5.08 times and 1 time. CA showed that the water quality could be divided into three interannual (IA) groups: IAI (1991-1995, 1998), IAII (1996-1997, 1999-2000, 2002-2006), and IAIII (2001, 2007-2011) and two seasonal clusters: dry season 1 (December), dry season 2 (January-February), and non-dry season (March-November). At interannual scale, the higher concentration of SO4 (2-) from industrial activities, atmospheric sedimentation, and fertilizer use in IAIII accelerated dissolution of carbonate, which increased Ca(2+), Mg(2+), total hardness (T-Hard), and total alkalinity (T-Alk). The decreasing trend of CODMn contributed to the establishment of sewage treatment plants and water and soil conservation in the Miyun upstream. The changing trend of NO3 (-)-N indicated increasing non-point pollution load of IAII and effective non-point pollution controlling of IAIII. Only one parameter T in the seasonal scale verified improved non-point pollution controlling. The major pollution in two controlling points was NO3 (-)-N, T-Hard, TN, and other ion pollution (SO4 (2-), F(-), Ca(2+), Mg(2+), T-Hard, T-Alk). Higher concentration of NO3 (-)-N in Xinzhuang and CODMn in Daguan indicated different controlling measures, especially controlling agriculture intensification in Chaohe River to decrease N pollution and decreasing water and soil loss and cage culture in Baihe River to weaken organic pollution. Controlling SO4 (2-) from industrial activity, atmospheric sedimentation and fertilizer use in watershed can effectively control Ca(2+), Mg(2+), T-Hard, and T-Alk.

The level of residual dispersion variation and the power of differential expression tests for RNA-Seq data

RNA-Sequencing (RNA-Seq) has been widely adopted for quantifying gene expression changes in comparative transcriptome analysis. For detecting differentially expressed genes, a variety of statistical methods based on the negative binomial (NB) distribution have been proposed. These methods differ in the ways they handle the NB nuisance parameters (i.e., the dispersion parameters associated with each gene) to save power, such as by using a dispersion model to exploit an apparent relationship between the dispersion parameter and the NB mean. Presumably, dispersion models with fewer parameters will result in greater power if the models are correct, but will produce misleading conclusions if not. This paper investigates this power and robustness trade-off by assessing rates of identifying true differential expression using the various methods under realistic assumptions about NB dispersion parameters. Our results indicate that the relative performances of the different methods are closely related to the level of dispersion variation unexplained by the dispersion model. We propose a simple statistic to quantify the level of residual dispersion variation from a fitted dispersion model and show that the magnitude of this statistic gives hints about whether and how much we can gain statistical power by a dispersion-modeling approach.

Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data

This work is about assessing model adequacy for negative binomial (NB) regression, particularly (1) assessing the adequacy of the NB assumption, and (2) assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq) data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

Bovine hepatic differential gene expression in response to perennial ryegrass staggers

>‘Perennial ryegrass staggers’ is a neurological condition characterised by muscular tremors and ataxia in livestock that ingest the indole diterpene lolitrem B from endophyte-infected perennial ryegrass. While the neurotoxic mechanism of action of ryegrass staggers has been defined, little is known about metabolic and other molecular processes that lolitrem B may affect in livestock. The objective of this study was to characterise differential gene expression in the liver of animals fed lolitrem B-containing feed over an extended period of time. Eighteen steers were fed one of three rations (n=6/group) containing lolitrem B (247, 1,554 or 2,256 μg/kg (dry matter basis)) over 64 days in a double-blind study. Microarray and confirmatory qPCR were performed to evaluate the hepatic gene expression profile from biopsies taken on days 0 and 64. Widespread perturbation of gene expression was observed in all groups receiving lolitrem B, with a total of 152 differential genes identified (false discovery rate ≤0.05). This suggests that chronic exposure to lolitrem B, even at levels below the current threshold of toxicity (2,000 μg/kg lolitrem B), can perturb many genes, biological processes and pathways. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses indicated that many of these genes were categorised under lipid/steroid biosynthesis/metabolism and oxidation-reduction. Specifically, genes involved in the biosynthesis pathway of ceramide, a sphingolipid molecule (ACSS2, LASS6 and SCD) and changes in neurosignaling through alteration of nitric oxide synthase activity (ARG1 and GPX4) were up-regulated. Future work should focus on the overall balance between ceramide and its metabolites and antioxidants/oxidants in a variety of body matrices in animals with perennial ryegrass staggers, to determine how these compounds contribute to the overall etiology of this disease.

Single-gene negative binomial regression models for RNA-Seq data with higher-order asymptotic inference

We consider negative binomial (NB) regression models for RNA-Seq read counts and investigate an approach where such NB regression models are fitted to individual genes separately and, in particular, the NB dispersion parameter is estimated from each gene separately without assuming commonalities between genes. This single-gene approach contrasts with the more widely-used dispersion-modeling approach where the NB dispersion is modeled as a simple function of the mean or other measures of read abundance, and then estimated from a large number of genes combined. We show that through the use of higher-order asymptotic techniques, inferences with correct type I errors can be made about the regression coefficients in a single-gene NB regression model even when the dispersion is unknown and the sample size is small. The motivations for studying single-gene models include: 1) they provide a basis of reference for understanding and quantifying the power-robustness trade-offs of the dispersion-modeling approach; 2) they can also be potentially useful in practice if moderate sample sizes become available and diagnostic tools indicate potential problems with simple models of dispersion.

Family-based association test using normal approximation to gene dropping null distribution

We derive the analytical mean and variance of the score test statistic in gene-dropping simulations and approximate the null distribution of the test statistic by a normal distribution. We provide insights into the gene-dropping test by decomposing the test statistic into two components: the first component provides information about linkage, and the second component provides information about fine mapping under the linkage peak. We demonstrate our theoretical findings by applying the gene-dropping test to the simulated data set from Genetic Analysis Workshop 18 and comparing its performance with existing population and family-based association tests.

A comparative study of ripening among berries of the grape cluster reveals an altered transcriptional programme and enhanced ripening rate in delayed berries

Transcriptional studies in relation to fruit ripening generally aim to identify the transcriptional states associated with physiological ripening stages and the transcriptional changes between stages within the ripening programme. In non-climacteric fruits such as grape, all ripening-related genes involved in this programme have not been identified, mainly due to the lack of mutants for comparative transcriptomic studies. A feature in grape cluster ripening (Vitis vinifera cv. Pinot noir), where all berries do not initiate the ripening at the same time, was exploited to study their shifted ripening programmes in parallel. Berries that showed marked ripening state differences in a véraison-stage cluster (ripening onset) ultimately reached similar ripeness states toward maturity, indicating the flexibility of the ripening programme. The expression variance between these véraison-stage berry classes, where 11% of the genes were found to be differentially expressed, was reduced significantly toward maturity, resulting in the synchronization of their transcriptional states. Defined quantitative expression changes (transcriptional distances) not only existed between the véraison transitional stages, but also between the véraison to maturity stages, regardless of the berry class. It was observed that lagging berries complete their transcriptional programme in a shorter time through altered gene expressions and ripening-related hormone dynamics, and enhance the rate of physiological ripening progression. Finally, the reduction in expression variance of genes can identify new genes directly associated with ripening and also assess the relevance of gene activity to the phase of the ripening programme.

Activity of a group B oncolytic adenovirus (ColoAd1) in whole human blood

Intravenous (i.v.) delivery of therapeutic viruses to human patients exposes virus particles to the potentially neutralising environment of the human bloodstream, where many components of the innate and adaptive immune system provide a formidable barrier to virus infection of target cells. Here we assess the haemocompatibility of ColoAd1, an oncolytic adenovirus currently undergoing clinical assessment for treatment of disseminated cancer by i.v. delivery. Compared with the commonly used serotype Ad5, ColoAd1 (which has a capsid derived from Ad11p) showed only minor inhibition of oncolytic activity by pooled human serum or washed human blood cells, with the amount of ColoAd1 required to kill cancer cells in vitro (the IC50) increasing <10-fold. However, some virus-blood interactions are concentration- and context-dependent, requiring study in whole, undiluted, human blood. ColoAd1 showed <50-fold increases in the IC50 in whole blood from most donors, whereas the activity of Ad5 was ablated. Extrapolating these findings to the clinical situation indicates that ColoAd1 would 'breakthrough' neutralisation in some patients receiving as few as 10(10) ColoAd1 particles i.v., and in most patients receiving doses of 10(12) or above, well within the achievable dose range.

Electrolytic partitioning of uranium and plutonium based on a new type of electrolytic mixer-settler

The design of a new type of electroreduction mixer-settler for the partitioning of uranium and plutonium during the Purex process, which is featured with E-shaped cathodes and U-shaped anodes in settling chamber, is described and the operational results achieved using this equipment are presented. The results show that this new type of mixer-settler has excellent separation performances. The flow rate of organic feed solution is 3 mL/min and the flow ratio of feed solution (1BF) to aqueous back extraction stream (1BX) and to organic wash stream (1BS) is 4/1/1. For an organic feed of 84 g/L uranium and 1.40 ⁓ 2.64 g/L plutonium, both the separation factor of plutonium from uranium and that of uranium from plutonium are apparently higher than 104

Methylome reorganization during in vitro dedifferentiation and regeneration of Populus trichocarpa

BACKGROUND

Cytosine DNA methylation (5mC) is an epigenetic modification that is important to genome stability and regulation of gene expression. Perturbations of 5mC have been implicated as a cause of phenotypic variation among plants regenerated through in vitro culture systems. However, the pattern of change in 5mC and its functional role with respect to gene expression, are poorly understood at the genome scale. A fuller understanding of how 5mC changes during in vitro manipulation may aid the development of methods for reducing or amplifying the mutagenic and epigenetic effects of in vitro culture and plant transformation.

RESULTS

We investigated the in vitro methylome of the model tree species Populus trichocarpa in a system that mimics routine methods for regeneration and plant transformation in the genus Populus (poplar). Using methylated DNA immunoprecipitation followed by high-throughput sequencing (MeDIP-seq), we compared the methylomes of internode stem segments from micropropagated explants, dedifferentiated calli, and internodes from regenerated plants. We found that more than half (56%) of the methylated portion of the genome appeared to be differentially methylated among the three tissue types. Surprisingly, gene promoter methylation varied little among tissues, however, the percentage of body-methylated genes increased from 9% to 14% between explants and callus tissue, then decreased to 8% in regenerated internodes. Forty-five percent of differentially-methylated genes underwent transient methylation, becoming methylated in calli, and demethylated in regenerants. These genes were more frequent in chromosomal regions with higher gene density. Comparisons with an expression microarray dataset showed that genes methylated at both promoters and gene bodies had lower expression than genes that were unmethylated or only promoter-methylated in all three tissues. Four types of abundant transposable elements showed their highest levels of 5mC in regenerated internodes.

CONCLUSIONS

DNA methylation varies in a highly gene- and chromosome-differential manner during in vitro differentiation and regeneration. 5mC in redifferentiated tissues was not reset to that in original explants during the study period. Hypermethylation of gene bodies in dedifferentiated cells did not interfere with transcription, and may serve a protective role against activation of abundant transposable elements.

The genome of tolypocladium inflatum: evolution, organization, and expression of the cyclosporin biosynthetic gene cluster

The ascomycete fungus Tolypocladium inflatum, a pathogen of beetle larvae, is best known as the producer of the immunosuppressant drug cyclosporin. The draft genome of T. inflatum strain NRRL 8044 (ATCC 34921), the isolate from which cyclosporin was first isolated, is presented along with comparative analyses of the biosynthesis of cyclosporin and other secondary metabolites in T. inflatum and related taxa. Phylogenomic analyses reveal previously undetected and complex patterns of homology between the nonribosomal peptide synthetase (NRPS) that encodes for cyclosporin synthetase (simA) and those of other secondary metabolites with activities against insects (e.g., beauvericin, destruxins, etc.), and demonstrate the roles of module duplication and gene fusion in diversification of NRPSs. The secondary metabolite gene cluster responsible for cyclosporin biosynthesis is described. In addition to genes necessary for cyclosporin biosynthesis, it harbors a gene for a cyclophilin, which is a member of a family of immunophilins known to bind cyclosporin. Comparative analyses support a lineage specific origin of the cyclosporin gene cluster rather than horizontal gene transfer from bacteria or other fungi. RNA-Seq transcriptome analyses in a cyclosporin-inducing medium delineate the boundaries of the cyclosporin cluster and reveal high levels of expression of the gene cluster cyclophilin. In medium containing insect hemolymph, weaker but significant upregulation of several genes within the cyclosporin cluster, including the highly expressed cyclophilin gene, was observed. T. inflatum also represents the first reference draft genome of Ophiocordycipitaceae, a third family of insect pathogenic fungi within the fungal order Hypocreales, and supports parallel and qualitatively distinct radiations of insect pathogens. The T. inflatum genome provides additional insight into the evolution and biosynthesis of cyclosporin and lays a foundation for further investigations of the role of secondary metabolite gene clusters and their metabolites in fungal biology.

Higher order asymptotics for negative binomial regression inferences from RNA-sequencing data

RNA sequencing (RNA-Seq) is the current method of choice for characterizing transcriptomes and quantifying gene expression changes. This next generation sequencing-based method provides unprecedented depth and resolution. The negative binomial (NB) probability distribution has been shown to be a useful model for frequencies of mapped RNA-Seq reads and consequently provides a basis for statistical analysis of gene expression. Negative binomial exact tests are available for two-group comparisons but do not extend to negative binomial regression analysis, which is important for examining gene expression as a function of explanatory variables and for adjusted group comparisons accounting for other factors. We address the adequacy of available large-sample tests for the small sample sizes typically available from RNA-Seq studies and consider a higher-order asymptotic (HOA) adjustment to likelihood ratio tests. We demonstrate that 1) the HOA-adjusted likelihood ratio test is practically indistinguishable from the exact test in situations where the exact test is available, 2) the type I error of the HOA test matches the nominal specification in regression settings we examined via simulation, and 3) the power of the likelihood ratio test does not appear to be affected by the HOA adjustment. This work helps clarify the accuracy of the unadjusted likelihood ratio test and the degree of improvement available with the HOA adjustment. Furthermore, the HOA test may be preferable even when the exact test is available because it does not require ad hoc library size adjustments.

Length bias correction in gene ontology enrichment analysis using logistic regression

When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called “length bias”, will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

Effect of linkage disequilibrium on the identification of functional variants

We summarize the contributions of Group 9 of Genetic Analysis Workshop 17. This group addressed the problems of linkage disequilibrium and other longer range forms of allelic association when evaluating the effects of genotypes on phenotypes. Issues raised by long-range associations, whether a result of selection, stratification, possible technical errors, or chance, were less expected but proved to be important. Most contributors focused on regression methods of various types to illustrate problematic issues or to develop adaptations for dealing with high-density genotype assays. Study design was also considered, as was graphical modeling. Although no method emerged as uniformly successful, most succeeded in reducing false-positive results either by considering clusters of loci within genes or by applying smoothing metrics that required results from adjacent loci to be similar. Two unexpected results that questioned our assumptions of what is required to model linkage disequilibrium were observed. The first was that correlations between loci separated by large genetic distances can greatly inflate single-locus test statistics, and, whether the result of selection, stratification, possible technical errors, or chance, these correlations seem overabundant. The second unexpected result was that applying principal components analysis to genome-wide genotype data can apparently control not only for population structure but also for linkage disequilibrium.

Power of association tests in the presence of multiple causal variants

We show that the statistical power of a single single-nucleotide polymorphism (SNP) score test for genetic association reflects the cumulative effect of all causal SNPs that are correlated with the test SNP. Statistical significance of a score test can sometimes be explained by the collective effect of weak correlations between the test SNP and multiple causal SNPs. In a finite population, weak but significant correlations between the test SNP and the causal SNPs can arise by chance alone. As a consequence, when a single-SNP score test shows significance, the causal SNPs contributing to the power of the test are not necessarily located near the test SNP, nor do they have to be in linkage disequilibrium with the test SNP. These findings are confirmed with the Genetic Analysis Workshop 17 mini-exome data. The findings of this study highlight the often overlooked importance of long-range and weak linkage disequilibrium in genetic association studies.

GENE-counter: a computational pipeline for the analysis of RNA-Seq data for gene expression differences

GENE-counter is a complete Perl-based computational pipeline for analyzing RNA-Sequencing (RNA-Seq) data for differential gene expression. In addition to its use in studying transcriptomes of eukaryotic model organisms, GENE-counter is applicable for prokaryotes and non-model organisms without an available genome reference sequence. For alignments, GENE-counter is configured for CASHX, Bowtie, and BWA, but an end user can use any Sequence Alignment/Map (SAM)-compliant program of preference. To analyze data for differential gene expression, GENE-counter can be run with any one of three statistics packages that are based on variations of the negative binomial distribution. The default method is a new and simple statistical test we developed based on an over-parameterized version of the negative binomial distribution. GENE-counter also includes three different methods for assessing differentially expressed features for enriched gene ontology (GO) terms. Results are transparent and data are systematically stored in a MySQL relational database to facilitate additional analyses as well as quality assessment. We used next generation sequencing to generate a small-scale RNA-Seq dataset derived from the heavily studied defense response of Arabidopsis thaliana and used GENE-counter to process the data. Collectively, the support from analysis of microarrays as well as the observed and substantial overlap in results from each of the three statistics packages demonstrates that GENE-counter is well suited for handling the unique characteristics of small sample sizes and high variability in gene counts.

Contrasting identity-by-descent estimators, association studies, and linkage analyses using the Framingham Heart Study data

We explored the utility of population- and pedigree-based analyses using the Framingham Heart Study genome-wide 50 k single-nucleotide polymorphism marker data provided for Genetic Analysis Workshop 16. Our aims were: 1) to compare identity-by-descent sharing estimates from variable amounts of data; 2) to apply each of these estimates to a case-control association study designed to control for relatedness among samples; and 3) to contrast these results to those obtained using model-based and model-free linkage analysis methods.

Conditional tests for localizing trait genes

BACKGROUND/AIMS

With pedigree data, genetic linkage can be detected using inheritance vector tests, which explore the discrepancy between the posterior distribution of the inheritance vectors given observed trait values and the prior distribution of the inheritance vectors. In this paper, we propose conditional inheritance vector tests for linkage localization. These conditional tests can also be used to detect additional linkage signals in the presence of previously detected causal genes.

METHODS

For linkage localization, we propose to perform inheritance vector tests conditioning on the inheritance vectors at two positions bounding a test region. We can detect additional linkage signals by conducting a further conditional test in a region with no previously detected genes. We use randomized p values to extend the marginal and conditional tests when the inheritance vectors cannot be completely determined from genetic marker data.

RESULTS

We conduct simulation studies to compare and contrast the marginal and the conditional tests and to demonstrate that randomized p values can capture both the significance and the uncertainty in the test results.

CONCLUSIONS

The simulation results demonstrate that the proposed conditional tests provide useful localization information, and with informative marker data, the uncertainty in randomized marginal and conditional test results is small.

Exact trait-model-free tests for linkage detection in pedigrees

A number of trait-model-free tests have been proposed for linkage detection between a genomic region and a trait. These tests involve testing the dependence in segregation between a trait and marker alleles by assigning a score to every possible identity-by-descent configuration of the pedigree members without modeling the trait, and then averaging the scores over all such configurations compatible with the observed marker genotypes and genealogical relationship of the pedigree members. In this paper we propose a permutation test as an alternative to the existing exact trait-model-free tests for linkage detection. The proposed test is computationally efficient and is applicable on complex multigeneration pedigree structures. In this paper, we have compared the performance of the permutation test with two other exact trait-model-free tests for linkage detection on simulated datasets. We have demonstrated that the proposed permutation test is fully robust against mispecification of marker allele frequencies and has very good power for linkage detection. The permutation test is implemented in the program lm_ibdtests within the framework of MORGAN 2.8 (http://www.stat.washington.edu/thompson/Genepi/MORGAN/Morgan.shtml).

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus.