The interaction-strength interpolation method for main-group chemistry: benchmarking, limitations, and perspectives

We have tested the original interaction-strength-interpolation (ISI) exchange-correlation functional for main group chemistry. The ISI functional is based on an interpolation between the weak and strong coupling limits and includes exact-exchange as well as the G\"orling-Levy second-order energy. We have analyzed in detail the basis-set dependence of the ISI functional, its dependence on the ground-state orbitals, and the influence of the size-consistency problem. We show and explain some of the expected limitations of the ISI functional (i.e. for atomization energies), but also unexpected results, such as the good performance for the interaction energy of dispersion-bonded complexes when the ISI correlation is used as a correction to Hartree-Fock.Comment: 20 pages, 20 figure

The Functional Characterization of the N-terminal Domains of TUT4

Cells have the ability to adapt in response to environmental stressors by regulating RNA stability. Terminal uridylyltransferases (TUTases) have emerged as essential enzymes in post-transcriptional regulation. TUTases catalyze the untemplated addition of uridine residues to the RNA 3’-end, which generally leads to RNA degradation. Human TUTase 4 (TUT4) regulates mRNA and miRNA stability by initiating the decay of RNA through the addition of a poly(U) tail. TUT4 encodes two catalytic regions. Previously, the C-terminal catalytic motif was thought to execute uridylation activity, while the N-terminal motif was thought to be catalytically inactive. I here demonstrate that while less active than its Cterminal counterpart, the N-terminal motif is indeed capable of post-transcriptional RNA editing and displays RNA substrate specificity. I further identified one of the three catalytic aspartates required for uridylation activity. This reveals a previously unknown catalytic function of the N-terminal catalytic domains with implications for its biological function

At 11 months, prosody still outranks statistics

English-learning 7.5-month-olds are heavily biased to perceive stressed syllables as word onsets. By 11 months, however, infants begin segmenting non-initially stressed words from speech.Using the same artificial language methodology as Johnson and Jusczyk (2001), we explored the possibility that the emergence of this ability is linked to a decreased reliance on prosodic cues to word boundaries accompanied by an increased reliance on syllable distribution cues. In a baseline study, where only statistical cues to word boundaries were present, infants exhibited a familiarity preference for statistical words. When conflicting stress cues were added to the speech stream, infants exhibited a familiarity preference for stress as opposed to statistical words. This was interpreted as evidence that 11-month-olds weight stress cues to word boundaries more heavily than statistical cues. Experiment 2 further investigated these results with a language containing convergent cues to word boundaries. The results of Experiment 2 were not conclusive. A third experiment using new stimuli and a different experimental design supported the conclusion that 11-month-olds rely more heavily on prosodic than statistical cues to word boundaries. We conclude that the emergence of the ability to segment non-initially stressed words from speech is not likely to be tied to an increased reliance on syllable distribution cues relative to stress cues, but instead may emerge due to an increased reliance on and integration of a broad array of segmentation cues

Infant word segmentation revisited: Edge alignment facilitates target extraction

In a landmark study, Jusczyk and Aslin (1995) demonstrated that English-learning infants are able to segment words from continuous speech at 7.5 months of age. In the current study, we explored the possibility that infants segment words from the edges of utterances more readily than the middle of utterances. The same procedure was used as in Jusczyk and Aslin (1995); however, our stimuli were controlled for target word location and infants were given a shorter familiarization time to avoid ceiling effects. Infants were familiarized to one word that always occurred at the edge of an utterance (sentence-initial position for half of the infants and sentence-final position for the other half) and one word that always occurred in sentence-medial position. Our results demonstrate that infants segment words from the edges of an utterance more readily than from the middle of an utterance. In addition, infants segment words from utterance-final position just as readily as they segment words from utterance-initial position. Possible explanations for these results, as well as their implications for current models of the development of word segmentation, are discussed

Rat Monoclonal Antibodies Specific for LST1 Proteins

The LST1 gene is located in the human MHC class III region and encodes transmembrane and soluble isoforms that have been suggested to play a role in the regulation of the immune response and are associated with inflammatory diseases such as rheumatoid arthritis. Here we describe the generation and characterization of the first monoclonal antibodies against LST1. Two hybridoma lines secreting monoclonal antibodies designated 7E2 and 8D12 were established. The 7E2 antibody detects recombinant and endogenous LST1 by Western blot analysis while 8D12 reacts with recombinant and endogenous LST1 in immunoprecipitation and flow cytometry procedures. The newly established antibodies were used to survey LST1 protein expression in human cell lines, which was found to be tightly regulated, allowing the expression of transmembrane isoforms but suppressing soluble isoforms

Complexity of Equivalence and Learning for Multiplicity Tree Automata

We consider the complexity of equivalence and learning for multiplicity tree automata, i.e., weighted tree automata over a field. We first show that the equivalence problem is logspace equivalent to polynomial identity testing, the complexity of which is a longstanding open problem. Secondly, we derive lower bounds on the number of queries needed to learn multiplicity tree automata in Angluin's exact learning model, over both arbitrary and fixed fields. Habrard and Oncina (2006) give an exact learning algorithm for multiplicity tree automata, in which the number of queries is proportional to the size of the target automaton and the size of a largest counterexample, represented as a tree, that is returned by the Teacher. However, the smallest tree-counterexample may be exponential in the size of the target automaton. Thus the above algorithm does not run in time polynomial in the size of the target automaton, and has query complexity exponential in the lower bound. Assuming a Teacher that returns minimal DAG representations of counterexamples, we give a new exact learning algorithm whose query complexity is quadratic in the target automaton size, almost matching the lower bound, and improving the best previously-known algorithm by an exponential factor

The Promise of Neuroprotective Agents in Parkinson’s Disease

Parkinson’s disease (PD) is characterized by loss of dopamine neurons in the substantia nigra of the brain. Since there are limited treatment options for PD, neuroprotective agents are currently being tested as a means to slow disease progression. Agents targeting oxidative stress, mitochondrial dysfunction, and inflammation are prime candidates for neuroprotection. This review identifies Rasagiline, Minocycline, and creatine, as the most promising neuroprotective agents for PD, and they are all currently in phase III trials. Other agents possessing protective characteristics in delaying PD include stimulants, vitamins, supplements, and other drugs. Additionally, combination therapies also show benefits in slowing PD progression. The identification of neuroprotective agents for PD provides us with therapeutic opportunities for modifying the course of disease progression and, perhaps, reducing the risk of onset when preclinical biomarkers become available

English-learning infants’ perception of word stress patterns

Adult speakers of different free stress languages (e.g., English, Spanish) differ both in their sensitivity to lexical stress and in their processing of suprasegmental and vowel quality cues to stress. In a head-turn preference experiment with a familiarization phase, both 8-month-old and 12-month-old English-learning infants discriminated between initial stress and final stress among lists of Spanish-spoken disyllabic nonwords that were segmentally varied (e.g. [ˈnila, ˈtuli] vs [luˈta, puˈki]). This is evidence that English-learning infants are sensitive to lexical stress patterns, instantiated primarily by suprasegmental cues, during the second half of the first year of life

Strictly correlated uniform electron droplets

We study the energetic properties of finite but internally homogeneous D-dimensional electron droplets in the strict-correlation limit. The indirect Coulomb interaction is found to increase as a function of the electron number, approaching the tighter forms of the Lieb-Oxford bound recently proposed by Rasanen et al. [Phys. Rev. Lett. 102, 206406 (2009)]. The bound is satisfied in three-, two-, and one-dimensional droplets, and in the latter case it is reached exactly - regardless of the type of interaction considered. Our results provide useful reference data for delocalized strongly correlated systems, and they can be used in the development and testing of exchange-correlation density functionals in the framework of density-functional theory

Developmental changes in infants’ ability to cope with dialect variation in word recognition

Toward the end of their first year of life, infants’ overly specified word representations are thought to give way to more abstract ones, which helps them to better cope with variation not relevant to word identity (e.g., voice and affect). This developmental change may help infants process the ambient language more efficiently, thus enabling rapid gains in vocabulary growth. One particular kind of variability that infants must accommodate is that of dialectal accent, because most children will encounter speakers from different regions and backgrounds. In this study, we explored developmental changes in infants’ ability to recognize words in continuous speech by familiarizing them with words spoken by a speaker of their own region (North Midland-American English) or a different region (Southern Ontario Canadian English), and testing them with passages spoken by a speaker of the opposite dialectal accent. Our results demonstrate that 12- but not 9-month-olds readily recognize words in the face of dialectal variation