Internal‐Rotation in Hydrogen Peroxide: The Far‐Infrared Spectrum and the Determination of the Hindering Potential

The torsional oscillation between the two OH groups of the hydrogen peroxide molecule is investigated through a study of the far‐infrared absorption spectrum of the molecule. A 1‐m‐focal‐length vacuum grating monochromator was used to scan the region from 15 to 700 cm−1 with an average resolution of 0.3 cm−1. The observed spectrum contains seven perpendicular‐type bands of which only the Q branches are resolved. The centers of the seven bands are at 11.43, 116.51, 198.57, 242.76, 370.70, 521.68, and 557.84 cm−1. These bands result from transitions between different states of the internal rotation and their identification makes it possible to construct the internal‐rotation energy level scheme through the first five excited states. Relative to the torsional ground state, these levels occur at 11.43, 254.2, 370.7, 569.3, and 775.9 cm−1.A theory of internal rotation in the hydrogen peroxide molecule is developed for use in the analysis of the far‐infrared spectra. In this theory, the Hamiltonian is constructed assuming all structural distances and angles fixed except the dihedral angle x defining the relative position of the two OH bars. By the use of a contact transformation the Hamiltonian is put in the form H (asymmetric top)+H(internal rotation) where the interaction between the internal and over‐all rotations arises through the x dependence of the inertial parameters of H(asymmetric top). It is assumed that the relative position of the two OH bars is governed by a potential‐energy function of the form V(x) = V1cosx+V2cos2x+V3cos3xV(x)=V1cosx+V2cos2x+V3cos3x. The internal‐rotation wave equation [αpx2+V(x)]M(x) = EM(x)[αpx2+V(x)]M(x)=EM(x) is solved numerically by an electronic‐computer and the potential function parameters V1=993 cm−1, V2=636 cm−1, and V3=44 cm−1 are chosen to fit the internal‐rotation energy‐level scheme. The trans and cis potential barrier heights are 386 and 2460 cm−1, respectively, and the potential‐function minima are located 111.5° from the cis configuration. Diagonalization of the matrix of the complete Hamiltonian to second order by the use of perturbation theory is sufficient to account for the observed Q‐branch shapes in the far infrared region.Two microwave frequencies observed by Massey and Bianco at 22 054.5 and 27 639.6 Mc/sec are identified from their Stark effects as the first excited‐state transitions J, K, n, τ=8, 6, 1, 1→7, 5, 1, 3 and J, K, n, τ=8, 5, 1, 3→9, 6, 1, 1, respectively, where the internal‐rotation quantum number n=1 denotes the first excited torsional state and where τ denotes trans symmetric (τ=1 and 2) or antisymmetric (τ=3 and 4) states. The form of the dipole moment operator is assumed to be μ0 cos(x/2) and μ0 is found to be 3.15 D in agreement with the value obtained from the torsional ground‐state transitions.Two J=0 microwave series observed by Massey, Beard, and Jen in a mixed sample of the deuterated species D2O2 and HOOD give confirmation of the potential function determined from the H2O2 analysis. The K=4→5 series is identified as the D2O2 first excited torsional state transition n=1→1, τ=4→2. The K=0→1 series is identified as the HOOD torsional ground‐state transition n=0→0, τ=4→2. Only very small changes in the trans barrier height are necessary to fit the constant terms of these series exactly. These changes, which are expected to arise from vibration‐internal rotation interactions, show a reasonable progression from H2O2 to D2O2: V (trans, HOOH) = 386 cm−1, V (trans, HOOD) = 381 cm−1 and V (trans, DOOD) = 378 cm−1.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71115/2/JCPSA6-42-6-1931-1.pd

Quantum Hamilton-Jacobi analysis of PT symmetric Hamiltonians

We apply the quantum Hamilton-Jacobi formalism, naturally defined in the complex domain, to a number of complex Hamiltonians, characterized by discrete parity and time reversal (PT) symmetries and obtain their eigenvalues and eigenfunctions. Examples of both quasi-exactly and exactly solvable potentials are analyzed and the subtle differences, in the singularity structures of their quantum momentum functions, are pointed out. The role of the PT symmetry in the complex domain is also illustrated.Comment: 11 page

Disruption of a structurally important extracellular element in the Glycine Receptor leads to decreased synaptic integration and signaling resulting in Severe Startle Disease

Functional impairments or trafficking defects of inhibitory glycine receptors (GlyRs) have been linked to human hyperekplexia/startle disease and autism spectrum disorders. We found that a lack of synaptic integration of GlyRs, together with disrupted receptor function, is responsible for a lethal startle phenotype in a novel spontaneous mouse mutant shaky, caused by a missense mutation, Q177K, located in the extracellular β8–β9 loop of the GlyR α1 subunit. Recently, structural data provided evidence that the flexibility of the β8–β9 loop is crucial for conformational transitions during opening and closing of the ion channel and represents a novel allosteric binding site in Cys-loop receptors. We identified the underlying neuropathological mechanisms in male and female shaky mice through a combination of protein biochemistry, immunocytochemistry, and both in vivo and in vitro electrophysiology. Increased expression of the mutant GlyR α1Q177K subunit in vivo was not sufficient to compensate for a decrease in synaptic integration of α1Q177Kβ GlyRs. The remaining synaptic heteromeric α1Q177Kβ GlyRs had decreased current amplitudes with significantly faster decay times. This functional disruption reveals an important role for the GlyR α1 subunit β8–β9 loop in initiating rearrangements within the extracellular–transmembrane GlyR interface and that this structural element is vital for inhibitory GlyR function, signaling, and synaptic clustering

Spinal Cord Infarction with Multiple Etiologic Factors

Spinal cord infarction is uncommon and usually presents with sudden onset of paralysis and sensory disturbances. A variety of causes are described, but rarely with multiple factors involved. We report a case of a 63-year-old man with a history of diabetes mellitus, hypertension, and osteoarthritis who presented with acute onset of chest pain, numbness, and weakness associated with episodic hypotension. He had incomplete tetraplegia and was areflexic without spasticity. Pain and temperature sensations were impaired below the C7 dermatome and absent below the T4 dermatome bilaterally. Proprioception and vibration sensations were diminished on the right below the C6 dermatome. Magnetic resonance imaging showed spinal cord infarction affecting C6–T3 segments, and severe cervical and lumbar spine degenerative changes. This case illustrates an unusual presenting symptom of spinal infarction, the need to identify multiple risk factors for spinal cord infarction, and the importance of optimal preventive therapy in patients at risk

Collocation analysis for UMLS knowledge-based word sense disambiguation

BACKGROUND: The effectiveness of knowledge-based word sense disambiguation (WSD) approaches depends in part on the information available in the reference knowledge resource. Off the shelf, these resources are not optimized for WSD and might lack terms to model the context properly. In addition, they might include noisy terms which contribute to false positives in the disambiguation results. METHODS: We analyzed some collocation types which could improve the performance of knowledge-based disambiguation methods. Collocations are obtained by extracting candidate collocations from MEDLINE and then assigning them to one of the senses of an ambiguous word. We performed this assignment either using semantic group profiles or a knowledge-based disambiguation method. In addition to collocations, we used second-order features from a previously implemented approach.Specifically, we measured the effect of these collocations in two knowledge-based WSD methods. The first method, AEC, uses the knowledge from the UMLS to collect examples from MEDLINE which are used to train a Naïve Bayes approach. The second method, MRD, builds a profile for each candidate sense based on the UMLS and compares the profile to the context of the ambiguous word.We have used two WSD test sets which contain disambiguation cases which are mapped to UMLS concepts. The first one, the NLM WSD set, was developed manually by several domain experts and contains words with high frequency occurrence in MEDLINE. The second one, the MSH WSD set, was developed automatically using the MeSH indexing in MEDLINE. It contains a larger set of words and covers a larger number of UMLS semantic types. RESULTS: The results indicate an improvement after the use of collocations, although the approaches have different performance depending on the data set. In the NLM WSD set, the improvement is larger for the MRD disambiguation method using second-order features. Assignment of collocations to a candidate sense based on UMLS semantic group profiles is more effective in the AEC method.In the MSH WSD set, the increment in performance is modest for all the methods. Collocations combined with the MRD disambiguation method have the best performance. The MRD disambiguation method and second-order features provide an insignificant change in performance. The AEC disambiguation method gives a modest improvement in performance. Assignment of collocations to a candidate sense based on knowledge-based methods has better performance. CONCLUSIONS: Collocations improve the performance of knowledge-based disambiguation methods, although results vary depending on the test set and method used. Generally, the AEC method is sensitive to query drift. Using AEC, just a few selected terms provide a large improvement in disambiguation performance. The MRD method handles noisy terms better but requires a larger set of terms to improve performance

Measurement of the Neutron Radius of 208Pb Through Parity-Violation in Electron Scattering

We report the first measurement of the parity-violating asymmetry A_PV in the elastic scattering of polarized electrons from 208Pb. A_PV is sensitive to the radius of the neutron distribution (Rn). The result A_PV = 0.656 \pm 0.060 (stat) \pm 0.014 (syst) ppm corresponds to a difference between the radii of the neutron and proton distributions Rn - Rp = 0.33 +0.16 -0.18 fm and provides the first electroweak observation of the neutron skin which is expected in a heavy, neutron-rich nucleus.Comment: 6 pages, 1 figur

Exploiting MeSH indexing in MEDLINE to generate a data set for word sense disambiguation

<p>Abstract</p> <p>Background</p> <p>Evaluation of Word Sense Disambiguation (WSD) methods in the biomedical domain is difficult because the available resources are either too small or too focused on specific types of entities (e.g. diseases or genes). We present a method that can be used to automatically develop a WSD test collection using the Unified Medical Language System (UMLS) Metathesaurus and the manual MeSH indexing of MEDLINE. We demonstrate the use of this method by developing such a data set, called MSH WSD.</p> <p>Methods</p> <p>In our method, the Metathesaurus is first screened to identify ambiguous terms whose possible senses consist of two or more MeSH headings. We then use each ambiguous term and its corresponding MeSH heading to extract MEDLINE citations where the term and only one of the MeSH headings co-occur. The term found in the MEDLINE citation is automatically assigned the UMLS CUI linked to the MeSH heading. Each instance has been assigned a UMLS Concept Unique Identifier (CUI). We compare the characteristics of the MSH WSD data set to the previously existing NLM WSD data set.</p> <p>Results</p> <p>The resulting MSH WSD data set consists of 106 ambiguous abbreviations, 88 ambiguous terms and 9 which are a combination of both, for a total of 203 ambiguous entities. For each ambiguous term/abbreviation, the data set contains a maximum of 100 instances per sense obtained from MEDLINE.</p> <p>We evaluated the reliability of the MSH WSD data set using existing knowledge-based methods and compared their performance to that of the results previously obtained by these algorithms on the pre-existing data set, NLM WSD. We show that the knowledge-based methods achieve different results but keep their relative performance except for the Journal Descriptor Indexing (JDI) method, whose performance is below the other methods.</p> <p>Conclusions</p> <p>The MSH WSD data set allows the evaluation of WSD algorithms in the biomedical domain. Compared to previously existing data sets, MSH WSD contains a larger number of biomedical terms/abbreviations and covers the largest set of UMLS Semantic Types. Furthermore, the MSH WSD data set has been generated automatically reusing already existing annotations and, therefore, can be regenerated from subsequent UMLS versions.</p