Inhibition of HeLa cell messenger RNA translation by 7-methylguanosine 5'-monophosphate

Translation of HeLa cell RNA containing poly(A) in a wheat germ cell-free system is markedly but incompletely inhibited by 7-methylguanosine 5'-monophosphate (m7G5'p). We have analyzed the translation products synthesized in the presence of different concentrations of m7G5'p and find that translation of all mRNAs is equally inhibited. To demonstrate the specificity of the inhibitor for RNAs with 5'-terminal m7G5' ppp... we show that specific translation products of satellite tobacco necrosis virus RNA, which does not have this 5' terminus, are synthesized in the presence of m7G5' p. Protein synthesis programmed by endogenous mRNA in a HeLa cell-free system is inhibited after a 10-min lag by m7G5' p. Other guanosine nucleotides without the 7-methyl group or with the phosphate in a different position are not inhibitor. We show that translation of all mRNAs is inhibited to a similar extent by m7G5'p in the HeLa cell-free system, by synthesizing 35S-labeled proteins in the presence of different inhibitory concentrations of this nucleotide and analyzing the translation products by electrophoresis and autoradiography. Translation of encephalomyocarditis virus RNA added to the HeLa cell-free system is not inhibited by m7"g5p; this viral RNA does not have this nucleotide at the 5' terminus. This indicates that m7G5'p specifically inhibits translation of mRNAs with the 5' terminus m7G5'ppp... and suggests that initiation of translation of picornavirus RNA may proceed via a mechanism different from that of cellular mRNAs.     

Elemental dissolution study of Pu-bearing borosilicate glasses

Single-pass flow-through tests were conducted to study the effects of self-radiation damage from alpha decay on dissolution kinetics of three radiation-aged Pu-bearing (1 mass% PuO₂) borosilicate glasses over a pH interval of 9–12 at 80–88 °C. The chemical compositions of the glasses were identical except the ²³⁹Pu/²³⁸Pu isotopic ratio, which was varied to yield accumulated doses of 1.3 × 10¹⁶, 2.9 × 10¹⁷ and 2.6 × 10¹⁸ -decays/g at the time of testing. Release of Al, B, Cs, Na, Si and U to solution increased with increasing pH, whereas Ca, Pu and Sr were invariant over the pH interval. Average dissolution rates, based on B release, were identical within experimental uncertainty for all three glass compositions and increased from 0.17 ± 0.07 at pH(23 °C) 9 to 10.6 ± 2.7 (g/(m² d¹)) at pH(23 °C) 12. Release rates of Pu were 10²- to 10⁵-fold slower compared to all other elements and were not affected by isotopic composition, self-radiation damage sustained by the glass, or pH. These data demonstrate that self-radiation damage does not affect glass dissolution rates, despite exposure to internal radiation doses for >20 years.     

Adoption of electronic options trading at the ISE

US brokerage firms have shown strong interest in a new alternative for trading of equity options since the 26 May 2000 launch of the International Securities Exchange (ISE), an all-electronic trading platform. Although the collective impact of these adoption decisions led to a successful launch and a formidable competitor to the four established options markets in the US, major brokerage firms differ widely in their usage and adoption rates.     

Mental health services for homeless mentally ill persons: Federal initiatives and current service trends.

Recent research suggests that approximately one third of the population of homeless single adults suffer from severe mental illnesses. Despite multiple health, mental health, and social welfare needs, this population is often unable to obtain necessary housing and community-based services. For this reason, since 1982, the National Institute of Mental Health (NIMH) has undertaken a number of federal initiatives to encourage research and assist states and localities in improving services focused on this vulnerable subgroup of the homeless population. This article describes the target population, NIMH research findings, and current mental health programs—with particular emphasis on two mental health programs established under the Stewart B. McKinney Homeless Assistance Act. Proposed future directions for federal research and evaluation efforts in this area are also discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Order vs. Disorder: Cholesterol and Omega-3 Phospholipids Determine Biomembrane Organization

Lipid structural diversity strongly affects biomembrane chemico-physical and structural properties in addition to membrane-associated events. At high concentrations, cholesterol increases membrane order and rigidity, while polyunsaturated lipids are reported to increase disorder and flexibility. How these different tendencies balance in composite bilayers is still controversial. In this study, electron paramagnetic resonance spectroscopy, small angle neutron scattering, and neutron reflectivity were used to investigate the structural properties of cholesterol-containing lipid bilayers in the fluid state with increasing amounts of polyunsaturated omega-3 lipids. Either the hybrid 1-stearoyl-2-docosahexaenoyl-sn-glycero-3-phosphocholine or the symmetric 1,2-docosahexaenoyl-sn-glycero-3-phosphocholine were added to the mixture of the naturally abundant 1-palmitoyl-2-oleyl-sn-glycero-3-phosphocholine and cholesterol. Our results indicate that the hybrid and the symmetric omega-3 phospholipids affect the microscopic organization of lipid bilayers differently. Cholesterol does not segregate from polyunsaturated phospholipids and, through interactions with them, is able to suppress the formation of non-lamellar structures induced by the symmetric polyunsaturated lipid. However, this order/disorder balance leads to a bilayer whose structural organization cannot be ascribed to either a liquid ordered or to a canonical liquid disordered phase, in that it displays a very loose packing of the intermediate segments of lipid chains.     

An Adaptive Role for DNA Double-Strand Breaks in Hippocampus-Dependent Learning and Memory

DNA double-strand breaks (DSBs), classified as the most harmful type of DNA damage based on the complexity of repair, lead to apoptosis or tumorigenesis. In aging, DNA damage increases and DNA repair decreases. This is exacerbated in disease, as post-mortem tissue from patients diagnosed with mild cognitive impairment (MCI) or Alzheimer’s disease (AD) show increased DSBs. A novel role for DSBs in immediate early gene (IEG) expression, learning, and memory has been suggested. Inducing neuronal activity leads to increases in DSBs and upregulation of IEGs, while increasing DSBs and inhibiting DSB repair impairs long-term memory and alters IEG expression. Consistent with this pattern, mice carrying dominant AD mutations have increased baseline DSBs, and impaired DSB repair is observed. These data suggest an adaptive role for DSBs in the central nervous system and dysregulation of DSBs and/or repair might drive age-related cognitive decline (ACD), MCI, and AD. In this review, we discuss the adaptive role of DSBs in hippocampus-dependent learning, memory, and IEG expression. We summarize IEGs, the history of DSBs, and DSBs in synaptic plasticity, aging, and AD. DSBs likely have adaptive functions in the brain, and even subtle alterations in their formation and repair could alter IEGs, learning, and memory.     

Protein–Protein Interaction Prediction for Targeted Protein Degradation

Protein–protein interactions (PPIs) play a fundamental role in various biological functions; thus, detecting PPI sites is essential for understanding diseases and developing new drugs. PPI prediction is of particular relevance for the development of drugs employing targeted protein degradation, as their efficacy relies on the formation of a stable ternary complex involving two proteins. However, experimental methods to detect PPI sites are both costly and time-intensive. In recent years, machine learning-based methods have been developed as screening tools. While they are computationally more efficient than traditional docking methods and thus allow rapid execution, these tools have so far primarily been based on sequence information, and they are therefore limited in their ability to address spatial requirements. In addition, they have to date not been applied to targeted protein degradation. Here, we present a new deep learning architecture based on the concept of graph representation learning that can predict interaction sites and interactions of proteins based on their surface representations. We demonstrate that our model reaches state-of-the-art performance using AUROC scores on the established MaSIF dataset. We furthermore introduce a new dataset with more diverse protein interactions and show that our model generalizes well to this new data. These generalization capabilities allow our model to predict the PPIs relevant for targeted protein degradation, which we show by demonstrating the high accuracy of our model for PPI prediction on the available ternary complex data. Our results suggest that PPI prediction models can be a valuable tool for screening protein pairs while developing new drugs for targeted protein degradation.