Latitudinal Differences in the Hibernation Characteristics of Woodchucks (Marmota monax)

There is little information on the phenotypic flexibility of hibernation characteristics within species. To address this issue, we observed differences in hibernation characteristics of three free-ranging populations of woodchucks (Marmota monax) distributed along a latitudinal gradient from Maine to South Carolina. Data from free-ranging animals exhibited a direct relationship between latitude and length of the hibernation season. As expected, woodchucks in the northern latitudes hibernated longer than those in the southern latitudes. Also, the length of interbout arousals decreased with increase in latitude, whereas the length of torpor bouts and the number of arousals increased. Thus, we observed phenotypic plasticity in hibernation characteristics based primarily on latitudinal temperature differences in each population. Further analysis revealed a direct relationship between latitude and total time spent in torpor. Maine animals spent 68% more time in torpor than South Carolina animals. However, total time spent euthermic did not differ among the three populations. The cost-benefit hypothesis of hibernation may help to explain these results. It assumes that hibernators avoid the physiological stress of torpor by staying euthermic as much as possible. Woodchucks in each population maximized time spent euthermic, utilizing torpor only at the level needed to survive winter hibernation and to commence reproduction in the spring

Perturbations of a Universe Filled with Dust and Radiation

A first-order perturbation approach to $k=0$ Friedmann cosmologies filled with dust and radiation is developed. Adopting the coordinate gauge comoving with the perturbed matter, and neglecting the vorticity of the radiation, a pair of coupled equations is obtained for the trace $h$ of the metric perturbations and for the velocity potential $v$. A power series solution with upwards cutoff exists such that the leading terms for large values of the dimensionless time $\xi$ agree with the relatively growing terms of the dust solution of Sachs and Wolfe.Comment: 9 pp, typeset in late

The Counterpart Principle of Analogical Support by Structural Similarity

We propose and investigate an Analogy Principle in the context of Unary Inductive Logic based on a notion of support by structural similarity which is often employed to motivate scientific conjectures

Progesterone utility in the synthesis of steroidal heterocyclic compounds with antitumor activity

One–pot and efficient method for the synthesis of progesteronpyridine 5a-c, 6a-c and 7a,b and/or progesteronpyran derivatives 9a-c and 10a,b by condensation reaction of progesterone 1 with different aldehydes and active methylene compounds in the presence of ammonium acetate or piperidine.  New progesteronopyrimidine derivatives 12a-d and 13a, b were synthesized via interaction of progesterone 1 with urea or thiourea and/or guanidine reagents and aldehyde. Progesterone 1 was examined to synthesize heterocyclic compound 16 containing ?-Lactone chiral carbon via the reaction of hydrazone derivative 14 with phenyl isothiocyanate followed by boiling with chloroacetic acid in benzene. The biological activity of compounds 5a, 5b, 6b, 7a, 9b, 9c, 12a, 12c, and 13a were evaluated as growth inhibitors of the liver and the breast carcinoma human cell line (HEPG2 & MCF7). Compounds 13a, 12a and 7a showed a higher potency than the standard. Key Words: Progesterone, MCR’s (multicomponents reaction), (pyridine, pyran, pyrimidine, ?-Lactone) derivatives, HEPG2 & MCF7

Mutation analysis of HIF prolyl hydroxylases (PHD/EGLN) in individuals with features of phaeochromocytoma and renal cell carcinoma susceptibility

Germline mutations in the von Hippel–Lindau disease (VHL) and succinate dehydrogenase subunit B (SDHB) genes can cause inherited phaeochromocytoma and/or renal cell carcinoma(RCC). Dysregulation of the hypoxia-inducible factor (HIF) transcription factors has been linked to VHL and SDHB-related RCC; both HIF dysregulation and disordered function of a prolyl hydroxylase domain isoform 3 (PHD3/EGLN3)-related pathway of neuronal apoptosis have been linked to the development of phaeochromocytoma. The 2-oxoglutarate-dependent prolyl hydroxylase enzymes PHD1 (EGLN2), PHD2 (EGLN1) and PHD3 (EGLN3) have a key role in regulating the stability of HIF-a subunits (and hence expression of the HIF-a transcription factors). A germline PHD2 mutation has been reported in association with congenital erythrocytosis and recurrent extra-adrenal phaeochromocytoma. We undertook mutation analysis of PHD1, PHD2 and PHD3 in two cohorts of patients with features of inherited phaeochromocytoma (nZ82) and inherited RCC (nZ64) and no evidence of germline mutations in known susceptibility genes. No confirmed pathogenic mutations were detected suggesting that mutations in these genes are not a frequent cause of inherited phaeochromocytoma or RCC

Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer

BACKGROUND: Long intergenic non-coding RNAs (lncRNAs) represent an emerging and under-studied class of transcripts that play a significant role in human cancers. Due to the tissue- and cancer-specific expression patterns observed for many lncRNAs it is believed that they could serve as ideal diagnostic biomarkers. However, until each tumor type is examined more closely, many of these lncRNAs will remain elusive. RESULTS: Here we characterize the lncRNA landscape in lung cancer using publicly available transcriptome sequencing data from a cohort of 567 adenocarcinoma and squamous cell carcinoma tumors. Through this compendium we identify over 3,000 unannotated intergenic transcripts representing novel lncRNAs. Through comparison of both adenocarcinoma and squamous cell carcinomas with matched controls we discover 111 differentially expressed lncRNAs, which we term lung cancer-associated lncRNAs (LCALs). A pan-cancer analysis of 324 additional tumor and adjacent normal pairs enable us to identify a subset of lncRNAs that display enriched expression specific to lung cancer as well as a subset that appear to be broadly deregulated across human cancers. Integration of exome sequencing data reveals that expression levels of many LCALs have significant associations with the mutational status of key oncogenes in lung cancer. Functional validation, using both knockdown and overexpression, shows that the most differentially expressed lncRNA, LCAL1, plays a role in cellular proliferation. CONCLUSIONS: Our systematic characterization of publicly available transcriptome data provides the foundation for future efforts to understand the role of LCALs, develop novel biomarkers, and improve knowledge of lung tumor biology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0429-8) contains supplementary material, which is available to authorized users

Testing nonperturbative techniques in the scalar sector of the standard model

We discuss the current picture of the standard model's scalar sector at strong coupling. We compare the pattern observed in the scalar sector in perturbation theory up to two-loop with the nonperturbative solution obtained by a next-to-leading order 1/N expansion. In particular, we analyze two resonant Higgs scattering processes, ff -> H -> f'f' and ff -> H -> ZZ, WW. We describe the ingredients of the nonperturbative calculation, such as the tachyonic regularization, the higher order 1/N intermediate renormalization, and the numerical methods for evaluating the graphs. We discuss briefly the perspectives and usefulness of extending these nonperturbative methods to other theories

Maintenance hemodialysis patients have high cumulative radiation exposure

Hemodialysis is associated with an increased risk of neoplasms which may result, at least in part, from exposure to ionizing radiation associated with frequent radiographic procedures. In order to estimate the average radiation exposure of those on hemodialysis, we conducted a retrospective study of 100 patients in a university-based dialysis unit followed for a median of 3.4 years. The number and type of radiological procedures were obtained from a central radiology database, and the cumulative effective radiation dose was calculated using standardized, procedure-specific radiation levels. The median annual radiation dose was 6.9 millisieverts (mSv) per patient-year. However, 14 patients had an annual cumulative effective radiation dose over 20mSv, the upper averaged annual limit for occupational exposure. The median total cumulative effective radiation dose per patient over the study period was 21.7mSv, in which 13 patients had a total cumulative effective radiation dose over 75mSv, a value reported to be associated with a 7% increased risk of cancer-related mortality. Two-thirds of the total cumulative effective radiation dose was due to CT scanning. The average radiation exposure was significantly associated with the cause of end-stage renal disease, history of ischemic heart disease, transplant waitlist status, number of in-patient hospital days over follow-up, and death during the study period. These results highlight the substantial exposure to ionizing radiation in hemodialysis patients

Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment

We present a simulation-based study using deep convolutional neural networks (DCNNs) to identify neutrino interaction vertices in the MINERvA passive targets region, and illustrate the application of domain adversarial neural networks (DANNs) in this context. DANNs are designed to be trained in one domain (simulated data) but tested in a second domain (physics data) and utilize unlabeled data from the second domain so that during training only features which are unable to discriminate between the domains are promoted. MINERvA is a neutrino-nucleus scattering experiment using the NuMI beamline at Fermilab. $A$-dependent cross sections are an important part of the physics program, and these measurements require vertex finding in complicated events. To illustrate the impact of the DANN we used a modified set of simulation in place of physics data during the training of the DANN and then used the label of the modified simulation during the evaluation of the DANN. We find that deep learning based methods offer significant advantages over our prior track-based reconstruction for the task of vertex finding, and that DANNs are able to improve the performance of deep networks by leveraging available unlabeled data and by mitigating network performance degradation rooted in biases in the physics models used for training.Comment: 41 page