Differential expression analysis with global network adjustment

<p>Background: Large-scale chromosomal deletions or other non-specific perturbations of the transcriptome can alter the expression of hundreds or thousands of genes, and it is of biological interest to understand which genes are most profoundly affected. We present a method for predicting a gene’s expression as a function of other genes thereby accounting for the effect of transcriptional regulation that confounds the identification of genes differentially expressed relative to a regulatory network. The challenge in constructing such models is that the number of possible regulator transcripts within a global network is on the order of thousands, and the number of biological samples is typically on the order of 10. Nevertheless, there are large gene expression databases that can be used to construct networks that could be helpful in modeling transcriptional regulation in smaller experiments.</p> <p>Results: We demonstrate a type of penalized regression model that can be estimated from large gene expression databases, and then applied to smaller experiments. The ridge parameter is selected by minimizing the cross-validation error of the predictions in the independent out-sample. This tends to increase the model stability and leads to a much greater degree of parameter shrinkage, but the resulting biased estimation is mitigated by a second round of regression. Nevertheless, the proposed computationally efficient “over-shrinkage” method outperforms previously used LASSO-based techniques. In two independent datasets, we find that the median proportion of explained variability in expression is approximately 25%, and this results in a substantial increase in the signal-to-noise ratio allowing more powerful inferences on differential gene expression leading to biologically intuitive findings. We also show that a large proportion of gene dependencies are conditional on the biological state, which would be impossible with standard differential expression methods.</p> <p>Conclusions: By adjusting for the effects of the global network on individual genes, both the sensitivity and reliability of differential expression measures are greatly improved.</p&gt

High-throughput in vivo vertebrate screening

We demonstrate a high-throughput platform for cellular-resolution in vivo chemical and genetic screens on zebrafish larvae. The system automatically loads zebrafish from reservoirs or multiwell plates, and positions and rotates them for high-speed confocal imaging and laser manipulation of both superficial and deep organs within 19 s without damage. We performed small-scale test screening of retinal axon guidance mutants and neuronal regeneration assays in combination with femtosecond laser microsurgery.National Institutes of Health (U.S.) (Director’s Innovator Award 1-DP2-OD002989–01)David & Lucile Packard Foundation (Award in Science and Engineering)Alfred P. Sloan Foundation (Award)Broad Institute of MIT and Harvard (Sparc Grant)National Science Foundation (U.S.) (Fellowship)Foxconn (Sponsorship

When Do Stalled Stars Resume Spinning Down? Advancing Gyrochronology with Ruprecht 147

This is the final version. Available on open access from IOP Publishing via the DOI in this recordRecent measurements of rotation periods () in the benchmark open clusters Praesepe (670 Myr), NGC 6811 (1 Gyr), and NGC 752 (1.4 Gyr) demonstrate that, after converging onto a tight sequence of slowly rotating stars in mass-period space, stars temporarily stop spinning down. These data also show that the duration of this epoch of stalled spin-down increases toward lower masses. To determine when stalled stars resume spinning down, we use data from the K2 mission and the Palomar Transient Factory to measure for 58 dwarf members of the 2.7 Gyr old cluster Ruprecht 147, 39 of which satisfy our criteria designed to remove short-period or near-equal-mass binaries. Combined with the Kepler data for the approximately coeval cluster NGC 6819 (30 stars with M ∗ > 0.85, our new measurements more than double the number of ≈2.5 Gyr benchmark rotators and extend this sample down to ≈0.55. The slowly rotating sequence for this joint sample appears relatively flat (22 ± 2 days) compared to sequences for younger clusters. This sequence also intersects the Kepler intermediate-period gap, demonstrating that this gap was not created by a lull in star formation. We calculate the time at which stars resume spinning down and find that 0.55 stars remain stalled for at least 1.3 Gyr. To accurately age-date low-mass stars in the field, gyrochronology formulae must be modified to account for this stalling timescale. Empirically tuning a core-envelope coupling model with open cluster data can account for most of the apparent stalling effect. However, alternative explanations, e.g., a temporary reduction in the magnetic braking torque, cannot yet be ruled out.National Science Foundation (NSF)European Union Horizon 2020NASADunlap FellowshipDanish National Research FoundationPennsylvania State UniversityEberly College of Scienc

Conditionally Replicating Adenovirus Expressing TIMP2 Increases Survival in a Mouse Model of Disseminated Ovarian Cancer

Ovarian cancer remains difficult to treat mainly due to presentation of the disease at an advanced stage. Conditionally-replicating adenoviruses (CRAds) are promising anti-cancer agents that selectively kill the tumor cells. The present study evaluated the efficacy of a novel CRAd (Ad5/3-CXCR4-TIMP2) containing the CXCR4 promoter for selective viral replication in cancer cells together with TIMP2 as a therapeutic transgene, targeting the matrix metalloproteases (MMPs) in a murine orthotopic model of disseminated ovarian cancer. An orthotopic model of ovarian cancer was established in athymic nude mice by intraperitonal injection of the human ovarian cancer cell line, SKOV3-Luc, expressing luciferase. Upon confirmation of peritoneal dissemination of the cells by non-invasive imaging, mice were randomly divided into four treatment groups: PBS, Ad-ΔE1-TIMP2, Ad5/3-CXCR4, and Ad5/3-CXCR4-TIMP2. All mice were imaged weekly to monitor tumor growth and were sacrificed upon reaching any of the predefined endpoints, including high tumor burden and significant weight loss along with clinical evidence of pain and distress. Survival analysis was performed using the Log-rank test. The median survival for the PBS cohort was 33 days; for Ad-ΔE1-TIMP2, 39 days; for Ad5/3-CXCR4, 52.5 days; and for Ad5/3-CXCR4-TIMP2, 63 days. The TIMP2-armed CRAd delayed tumor growth and significantly increased survival when compared to the unarmed CRAd. This therapeutic effect was confirmed to be mediated through inhibition of MMP9. Results of the in vivo study support the translational potential of Ad5/3-CXCR4-TIMP2 for treatment of human patients with advanced ovarian cancer

Bioenergetics Failure and Oxidative Stress in Brain Stem Mediates Cardiovascular Collapse Associated with Fatal Methamphetamine Intoxication

Background: Whereas sudden death, most often associated with cardiovascular collapse, occurs in abusers of the psychostimulant methamphetamine (METH), the underlying mechanism is much less understood. The demonstration that successful resuscitation of an arrested heart depends on maintained functionality of the rostral ventrolateral medulla (RVLM), which is responsible for the maintenance of stable blood pressure, suggests that failure of brain stem cardiovascular regulation, rather than the heart, holds the key to cardiovascular collapse. We tested the hypothesis that cessation of brain stem cardiovascular regulation because of a loss of functionality in RVLM mediated by bioenergetics failure and oxidative stress underlies the cardiovascular collapse elicited by lethal doses of METH. Methodology/Principal Findings: Survival rate, cardiovascular responses and biochemical or morphological changes in RVLM induced by intravenous administration of METH in Sprague-Dawley rats were investigated. High doses of METH induced significant mortality within 20 min that paralleled concomitant the collapse of arterial pressure or heart rate and loss of functionality in RVLM. There were concurrent increases in the concentration of METH in serum and ventrolateral medulla, along with tissue anoxia, cessation of microvascular perfusion and necrotic cell death in RVLM. Furthermore, mitochondrial respiratory chain enzyme activity or electron transport capacity and ATP production in RVLM were reduced, and mitochondria-derived superoxide anion level was augmented. All those detrimental physiological and biochemica

The spine in Paget’s disease

Paget’s disease (PD) is a chronic metabolically active bone disease, characterized by a disturbance in bone modelling and remodelling due to an increase in osteoblastic and osteoclastic activity. The vertebra is the second most commonly affected site. This article reviews the various spinal pathomechanisms and osseous dynamics involved in producing the varied imaging appearances and their clinical relevance. Advanced imaging of osseous, articular and bone marrow manifestations of PD in all the vertebral components are presented. Pagetic changes often result in clinical symptoms including back pain, spinal stenosis and neural dysfunction. Various pathological complications due to PD involvement result in these clinical symptoms. Recognition of the imaging manifestations of spinal PD and the potential complications that cause the clinical symptoms enables accurate assessment of patients prior to appropriate management

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules