An efficient two-step strategy has been developed to access diversely functionalized benzylic sulfonamides. Execution of this strategy required the development of two reaction methods: the palladium-catalyzed cross-coupling of aryl halides with CH-acidic methanesulfonamides and a metathesis reaction between the resulting alpha-arylated sulfonamides and diverse amines. The broad scope of the cross-coupling process combined with a versatile sulfonamide metathesis constitutes an efficient strategy for the synthesis of various benzylic sulfonamides.

The first coupling of atmospheric pressure ionization methods, electrospray ionization (ESI) and desorption electrospray ionization (DESI), to a miniature hand-held mass spectrometer is reported. The instrument employs a rectilinear ion trap (RIT) mass analyzer and is battery-operated, hand-portable, and rugged (total system: 10 kg, 0.014 m(3), 75 W power consumption). The mass spectrometer was fitted with an atmospheric inlet, consisting of a 10 cm x 127 microm inner diameter stainless steel capillary tube which was used to introduce gas into the vacuum chamber at 13 mL/min. The operating pressure was 15 mTorr. Ions, generated by the atmospheric pressure ion source, were directed by the inlet along the axis of the ion trap, entering through an aperture in the dc-biased end plate, which was also operated as an ion gate. ESI and DESI sources were used to generate ions; ESI-MS analysis of an aqueous mixture of drugs yielded detection limits in the low parts-per-billion range. Signal response was linear over more than 3 orders of magnitude. Tandem mass spectrometry experiments were used to identify components of this mixture. ESI was also applied to the analysis of peptides and in this case multiply charged species were observed for compounds of molecular weight up to 1200 Da. Cocaine samples deposited or already present on different surfaces, including currency, were rapidly analyzed in situ by DESI. A geometry-independent version of the DESI ion source was also coupled to the miniature mass spectrometer. These results demonstrate that atmospheric pressure ionization can be implemented on simple portable mass spectrometry systems.

Methods for the selective and reproducible expression of genetically encoded tools in targeted subsets of cells are required to facilitate studies of neuronal development, connectivity, and function in living animals. In the absence of techniques for synthesizing promoters that target defined cell groups, current methods exploit the regulatory elements of endogenous genes to achieve specificity of transgene expression. However, single promoters often have expression patterns too broad to pinpoint the functional roles of specific neurons. In this review, we describe emerging combinatorial techniques that make transgene expression contingent not upon a single promoter, but upon two or more promoters. Although only a few such techniques are currently available, recent developments promise rapid growth in this area in the coming years.

The hippocampus is essential for episodic memory, which requires single-trial learning. Although long-term potentiation (LTP) of synaptic strength is a candidate mechanism for learning, it is typically induced by using repeated synaptic activation to produce precisely timed, high-frequency, or rhythmic firing. Here we show that hippocampal synapses potentiate robustly in response to strong activation by a single burst. The induction mechanism of this single-burst LTP requires activation of NMDA receptors, L-type voltage-gated calcium channels, and dendritic spikes. Thus, dendritic spikes are a critical trigger for a form of LTP that is consistent with the function of the hippocampus in episodic memory.

Spinocerebellar ataxia type-3 (SCA3) is among the most common dominantly inherited ataxias, and is one of nine devastating human neurodegenerative diseases caused by the expansion of a CAG repeat encoding glutamine within the gene. The polyglutamine domain confers toxicity on the protein Ataxin-3 leading to neuronal dysfunction and loss. Although modifiers of polyglutamine toxicity have been identified, little is known concerning how the modifiers function mechanistically to affect toxicity. To reveal insight into spinocerebellar ataxia type-3, we performed a genetic screen in Drosophila with pathogenic Ataxin-3-induced neurodegeneration and identified 25 modifiers defining 18 genes. Despite a variety of predicted molecular activities, biological analysis indicated that the modifiers affected protein misfolding. Detailed mechanistic studies revealed that some modifiers affected protein accumulation in a manner dependent on the proteasome, whereas others affected autophagy. Select modifiers of Ataxin-3 also affected tau, revealing common pathways between degeneration due to distinct human neurotoxic proteins. These findings provide new insight into molecular pathways of polyQ toxicity, defining novel targets for promoting neuronal survival in human neurodegenerative disease.

Physical traces underlying simple memories can be confined to a single group of cells in the brain. In the fly Drosophila melanogaster, the Kenyon cells of the mushroom bodies house traces for both appetitive and aversive odor memories. The adenylate cyclase protein, Rutabaga, has been shown to mediate both traces. Here, we show that, for appetitive learning, another group of cells can additionally accommodate a Rutabaga-dependent memory trace. Localized expression of rutabaga in either projection neurons, the first-order olfactory interneurons, or in Kenyon cells, the second-order interneurons, is sufficient for rescuing the mutant defect in appetitive short-term memory. Thus, appetitive learning may induce multiple memory traces in the first- and second-order olfactory interneurons using the same plasticity mechanism. In contrast, aversive odor memory of rutabaga is rescued selectively in the Kenyon cells, but not in the projection neurons. This difference in the organization of memory traces is consistent with the internal representation of reward and punishment.

Inducible and reversible perturbation of the activity of selected neurons in vivo is critical to understanding the dynamics of brain circuits. Several genetically encoded systems for rapid inducible neuronal silencing have been developed in the past few years offering an arsenal of tools for in vivo experiments. Some systems are based on ion-channels or pumps, others on G protein coupled receptors, and yet others on modified presynaptic proteins. Inducers range from light to small molecules to peptides. This diversity results in differences in the various parameters that may determine the applicability of each tool to a particular biological question. Although further development would be beneficial, the current silencing tool kit already provides the ability to make specific perturbations of circuit function in behaving animals.

We developed a series of statistical potentials to recognize the native protein from decoys, particularly when using only a reduced representation in which each side chain is treated as a single C(beta) atom. Beginning with a highly successful all-atom statistical potential, the Discrete Optimized Protein Energy function (DOPE), we considered the implications of including additional information in the all-atom statistical potential and subsequently reducing to the C(beta) representation. One of the potentials includes interaction energies conditional on backbone geometries. A second potential separates sequence local from sequence nonlocal interactions and introduces a novel reference state for the sequence local interactions. The resultant potentials perform better than the original DOPE statistical potential in decoy identification. Moreover, even upon passing to a reduced C(beta) representation, these statistical potentials outscore the original (all-atom) DOPE potential in identifying native states for sets of decoys. Interestingly, the backbone-dependent statistical potential is shown to retain nearly all of the information content of the all-atom representation in the C(beta) representation. In addition, these new statistical potentials are combined with existing potentials to model hydrogen bonding, torsion energies, and solvation energies to produce even better performing potentials. The ability of the C(beta) statistical potentials to accurately represent protein interactions bodes well for computational efficiency in protein folding calculations using reduced backbone representations, while the extensions to DOPE illustrate general principles for improving knowledge-based potentials.