Novel single nucleotide polymorphism-based assay for genotyping Mycobacterium avium subsp. paratuberculosis

Typing of Mycobacterium avium subspecies paratuberculosis strains presents a challenge, since they are genetically monomorphic and traditional molecular techniques have limited discriminatory power. The recent advances and availability of whole-genome sequencing have extended possibilities for the characterization of Mycobacterium avium subspecies paratuberculosis, and whole-genome sequencing can provide a phylogenetic context to facilitate global epidemiology studies. In this study, we developed a single nucleotide polymorphism (SNP) assay based on PCR and restriction enzyme digestion or sequencing of the amplified product. The SNP analysis was performed using genome sequence data from 133 Mycobacterium avium subspecies paratuberculosis isolates with different genotypes from 8 different host species and 17 distinct geographic regions around the world. A total of 28,402 SNPs were identified among all of the isolates. The minimum number of SNPs required to distinguish between all of the 133 genomes was 93 and between only the type C isolates was 41. To reduce the number of SNPs and PCRs required, we adopted an approach based on sequential detection of SNPs and a decision tree. By the analysis of 14 SNPs Mycobacterium avium subspecies paratuberculosis isolates can be characterized within 14 phylogenetic groups with a higher discriminatory power than mycobacterial interspersed repetitive unit–variable number tandem repeat assay and other typing methods. Continuous updating of genome sequences is needed in order to better characterize new phylogenetic groups and SNP profiles. The novel SNP assay is a discriminative, simple, reproducible method and requires only basic laboratory equipment for the large-scale global typing of Mycobacterium avium subspecies paratuberculosis isolates

Medial prefrontal cortex circuit function during retrieval and extinction of associative learning under anesthesia

Associative learning is encoded under anesthesia and involves the medial prefrontal cortex (mPFC). Neuronal activity in mPFC increases in response to a conditioned stimulus (CS+) previously paired with an unconditioned stimulus (US) but not during presentation of an unpaired stimulus (CS-) in anesthetized animals. Studies in conscious animals have shown dissociable roles for different mPFC subregions in mediating various memory processes, with the prelimbic (PL) and infralimbic (IL) cortex involved in the retrieval and extinction of conditioned responding, respectively. Therefore PL and IL may also play different roles in mediating the retrieval and extinction of discrimination learning under anesthesia. Here we used in vivo electrophysiology to examine unit and local field potential (LFP) activity in PL and IL before and after auditory discrimination learning and during later retrieval and extinction testing in anesthetized rats. Animals received repeated presentations of two distinct sounds, one of which was paired with footshock (US). In separate control experiments animals received footshocks without sounds. After discrimination learning the paired (CS+) and unpaired (CS-) sounds were repeatedly presented alone. We found increased unit firing and LFP power in PL and, to a lesser extent, IL after discrimination learning but not after footshocks alone. After discrimination learning, unit firing and LFP power increased in PL and IL in response to presentation of the first CS+, compared to the first CS-. However, PL and IL activity increased during the last CS- presentation, such that activity during presentation of the last CS+ and CS- did not differ. These results confirm previous findings and extend them by showing that increased PL and IL activity result from encoding of the CS+/US association rather than US presentation. They also suggest that extinction may occur under anesthesia and might be represented at the neural level in PL and IL

Sex differences in learned fear expression and extinction involve altered gamma oscillations in medial prefrontal cortex

Sex differences in learned fear expression and extinction involve the medial prefrontal cortex (mPFC). We recently demonstrated that enhanced learned fear expression during auditory fear extinction and its recall is linked to persistent theta activation in the prelimbic (PL) but not infralimbic (IL) cortex of female rats. Emerging evidence indicates that gamma oscillations in mPFC are also implicated in the expression and extinction of learned fear. Therefore we re-examined our in vivo electrophysiology data and found that females showed persistent PL gamma activation during extinction and a failure of IL gamma activation during extinction recall. Altered prefrontal gamma oscillations thus accompany sex differences in learned fear expression and its extinction. These findings are relevant for understanding the neural basis of post-traumatic stress disorder, which is more prevalent in women and involves impaired extinction and mPFC dysfunction

Persistent prelimbic cortex activity contributes to enhanced learned fear expression in females

Anxiety disorders, such as post-traumatic stress, are more prevalent in women and are characterized by impaired inhibition of learned fear and medial prefrontal cortex (mPFC) dysfunction. Here we examined sex differences in fear extinction and mPFC activity in rats. Females showed more learned fear expression during extinction and its recall, but not fear conditioning. They also showed more spontaneous fear recovery and more contextual fear before extinction and its recall. Moreover, enhanced learned fear expression in females was associated with sustained prelimbic (PL) cortex activity. These results suggest that sex differences in learned fear expression may involve persistent PL activation

Ozone database in support of CMIP5 simulations: results and corresponding radiative forcing

A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC) and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM) simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009) with multimodel mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios) A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2) Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and GISSPUCCINI)and of the future by one CCM (CAM3.5). The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs). Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that total column ozone is overestimated in the southern polar latitudes during spring and tropospheric column ozone is slightly underestimated. Vertical profiles of tropospheric ozone are broadly consistent with ozonesondes and in-situ measurements, with some deviations in regions of biomass burning. The tropospheric ozone radiative forcing (RF) from the 1850s to the 2000s is 0.23Wm−2, lower than previous results. The lower value is mainly due to (i) a smaller increase in biomass burning emissions; (ii) a larger influence of stratospheric ozone depletion on upper tropospheric ozone at high southern latitudes; and possibly (iii) a larger influence of clouds (which act to reduce the net forcing) compared to previous radiative forcing calculations. Over the same period, decreases in stratospheric ozone, mainly at high latitudes, produce a RF of −0.08Wm−2, which is more negative than the central Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) value of −0.05Wm−2, but which is within the stated range of −0.15 to +0.05Wm−2. The more negative value is explained by the fact that the regression model simulates significant ozone depletion prior to 1979, in line with the increase in EESC and as confirmed by CCMs, while the AR4 assumed no change in stratospheric RF prior to 1979. A negative RF of similar magnitude persists into the future, although its location shifts from high latitudes to the tropics. This shift is due to increases in polar stratospheric ozone, but decreases in tropical lower stratospheric ozone, related to a strengthening of the Brewer-Dobson circulation, particularly through the latter half of the 21st century. Differences in trends in tropospheric ozone among the four RCPs are mainly driven by different methane concentrations, resulting in a range of tropospheric ozone RFs between 0.4 and 0.1Wm−2 by 2100. The ozone dataset described here has been released for the Coupled Model Intercomparison Project (CMIP5) model simulations in netCDF Climate and Forecast (CF) Metadata Convention at the PCMDI website (http://cmip-pcmdi.llnl.gov/)

A systematic review of methods to incorporate external evidence into trial-based survival extrapolations for health technology assessment

Background External evidence is commonly used to inform survival modeling for health technology assessment (HTA). While there are a range of methodological approaches that have been proposed, it is unclear which methods could be used and how they compare. Purpose This review aims to identify, describe, and categorize established methods to incorporate external evidence into survival extrapolation for HTA. Data Sources Embase, MEDLINE, EconLit, and Web of Science databases were searched to identify published methodological studies, supplemented by hand searching and citation tracking. Study Selection Eligible studies were required to present a novel extrapolation approach incorporating external evidence (i.e., data or information) within survival model estimation. Data Extraction Studies were classified according to how the external evidence was integrated as a part of model fitting. Information was extracted concerning the model-fitting process, key requirements, assumptions, software, application contexts, and presentation of comparisons with, or validation against, other methods. Data Synthesis Across 18 methods identified from 22 studies, themes included use of informative prior(s) (n = 5), piecewise (n = 7), and general population adjustment (n = 9), plus a variety of “other” (n = 8) approaches. Most methods were applied in cancer populations (n = 13). No studies compared or validated their method against another method that also incorporated external evidence. Limitations As only studies with a specific methodological objective were included, methods proposed as part of another study type (e.g., an economic evaluation) were excluded from this review. Conclusions Several methods were identified in this review, with common themes based on typical data sources and analytical approaches. Of note, no evidence was found comparing the identified methods to one another, and so an assessment of different methods would be a useful area for further research. Highlights This review aims to identify methods that have been used to incorporate external evidence into survival extrapolations, focusing on those that may be used to inform health technology assessment. We found a range of different approaches, including piecewise methods, Bayesian methods using informative priors, and general population adjustment methods, as well as a variety of “other” approaches. No studies attempted to compare the performance of alternative methods for incorporating external evidence with respect to the accuracy of survival predictions. Further research investigating this would be valuable

Chiral and Gluon Condensates at Finite Temperature

We investigate the thermal behaviour of gluon and chiral condensates within an effective Lagrangian of pseudoscalar mesons coupled to a scalar glueball. This Lagrangian mimics the scale and chiral symmetries of QCD. (Submitted to Z. Phys. C)Comment: 20 pages + 7 figures (uuencoded compressed postscript files), University of Regensburg preprint TPR-94-1

Exact two-particle eigenstates in partially reduced QED

We consider a reformulation of QED in which covariant Green functions are used to solve for the electromagnetic field in terms of the fermion fields. It is shown that exact few-fermion eigenstates of the resulting Hamiltonian can be obtained in the canonical equal-time formalism for the case where there are no free photons. These eigenstates lead to two- and three-body Dirac-like equations with electromagnetic interactions. Perturbative and some numerical solutions of the two-body equations are presented for positronium and muonium-like systems, for various strengths of the coupling.Comment: 33 pages, LaTex 2.09, 4 figures in EPS forma

Cloning and regional localization of the mouse faciogenital dysplasia ( Fgd1 ) gene

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47027/1/335_2004_Article_BF00352375.pd