Drug Facilitated Sexual Assault: Detection and Stability of Benzodiazepines in Spiked Drinks Using Gas Chromatography-Mass Spectrometry

Benzodiazepines are detected in a significant number of drug facilitated sexual assaults (DFSA). Whilst blood and urine from the victim are routinely analysed, due to the delay in reporting DFSA cases and the short half lives of most of these drugs in blood and urine, drug detection in such samples is problematic. Consideration of the drinks involved and analysis for drugs may start to address this. Here we have reconstructed the ‘spiking’ of three benzodiazepines (diazepam, flunitrazepam and temazepam) into five drinks, an alcopop (flavoured alcoholic drink), a beer, a white wine, a spirit, and a fruit based non-alcoholic drink (J2O) chosen as representative of those drinks commonly used by women in 16–24 year old age group. Using a validated GC-MS method for the simultaneous detection of these drugs in the drinks we have studied the storage stability of the benzodiazepines under two different storage conditions, uncontrolled room temperature and refrigerator (4°C) over a 25 day period. All drugs could be detected in all beverages over this time period. Diazepam was found to be stable in all of the beverages, except the J2O, under both storage conditions. Flunitrazepam and temazepam were found not to be stable but were detectable (97% loss of temazepam and 39% loss of flunitrazepam from J2O). The recommendations from this study are that there should be a policy change and that drinks thought to be involved in DFSA cases should be collected and analysed wherever possible to support other evidence types

The GABA transporter 1 (SLC6A1): a novel candidate gene for anxiety disorders

Recent evidence suggests that the GABA transporter 1 (GAT-1; SLC6A1) plays a role in the pathophysiology and treatment of anxiety disorders. In order to understand the impact of genetic variation within SLC6A1 on pathological anxiety, we performed a case–control association study with anxiety disorder patients with and without syndromal panic attacks. Using the method of sequential addition of cases, we found that polymorphisms in the 5′ flanking region of SLC6A1 are highly associated with anxiety disorders when considering the severity of syndromal panic attacks as phenotype covariate. Analysing the effect size of the association, we observed a constant increase in the odds ratio for disease susceptibility with an increase in panic severity (OR ~ 2.5 in severely affected patients). Nominally significant association effects were observed considering the entire patient sample. These data indicate a high load of genetic variance within SLC6A1 on pathological anxiety and highlight GAT-1 as a promising target for treatment of anxiety disorders with panic symptoms

Comparison of quality of life after stereotactic body radiotherapy and surgery for early-stage prostate cancer

Background: As the long-term efficacy of stereotactic body radiation therapy (SBRT) becomes established and other prostate cancer treatment approaches are refined and improved, examination of quality of life (QOL) following prostate cancer treatment is critical in driving both patient and clinical treatment decisions. We present the first study to compare QOL after SBRT and radical prostatectomy, with QOL assessed at approximately the same times pre- and post-treatment and using the same validated QOL instrument. Methods: Patients with clinically localized prostate cancer were treated with either radical prostatectomy (n = 123 Spanish patients) or SBRT (n = 216 American patients). QOL was assessed using the Expanded Prostate Cancer Index Composite (EPIC) grouped into urinary, sexual, and bowel domains. For comparison purposes, SBRT EPIC data at baseline, 3 weeks, 5, 11, 24, and 36 months were compared to surgery data at baseline, 1, 6, 12, 24,and 36 months. Differences in patient characteristics between the two groups were assessed using Chi-squared tests for categorical variables and t-tests for continuous variables. Generalized estimating equation (GEE) models were constructed for each EPIC scale to account for correlation among repeated measures and used to assess the effect of treatment on QOL. Results: The largest differences in QOL occurred in the first 1-6 months after treatment, with larger declines following surgery in urinary and sexual QOL as compared to SBRT, and a larger decline in bowel QOL following SBRT as compared to surgery. Long-term urinary and sexual QOL declines remained clinically significantly lower for surgery patients but not for SBRT patients. Conclusions: Overall, these results may have implications for patient and physician clinical decision making which are often influenced by QOL. These differences in sexual, urinary and bowel QOL should be closely considered in selecting the right treatment, especially in evaluating the value of non-invasive treatments, such as SBRT

Detailed Regulatory Mechanism of the Interaction between ZO-1 PDZ2 and Connexin43 Revealed by MD Simulations

The gap junction protein connexin43 (Cx43) binds to the second PDZ domain of Zonula occludens-1 (ZO-1) through its C-terminal tail, mediating the regulation of gap junction plaque size and dynamics. Biochemical study demonstrated that the very C-terminal 12 residues of Cx43 are necessary and sufficient for ZO-1 PDZ2 binding and phosphorylation at residues Ser (-9) and Ser (-10) of the peptide can disrupt the association. However, only a crystal structure of ZO-1 PDZ2 in complex with a shorter 9 aa peptide of connexin43 was solved experimentally. Here, the interactions between ZO-1 PDZ2 and the short, long and phosphorylated Cx43 peptides were studied using molecular dynamics (MD) simulations and free energy calculation. The short peptide bound to PDZ2 exhibits large structural variations, while the extension of three upstream residues stabilizes the peptide conformation and enhanced the interaction. Phosphorylation at Ser(-9) significantly weakens the binding and results in conformational flexibility of the peptide. Glu210 of ZO-1 PDZ2 was found to be a key regulatory point in Cx43 binding and phosphorylation induced dissociation

Nanorings and rods interconnected by self-assembly mimicking an artificial network of neurons

[EN] Molecular electronics based on structures ordered as neural networks emerges as the next evolutionary milestone in the construction of nanodevices with unprecedented applications. However, the straightforward formation of geometrically defined and interconnected nanostructures is crucial for the production of electronic circuitry nanoequivalents. Here we report on the molecularly fine-tuned self-assembly of tetrakis-Schiff base compounds into nanosized rings interconnected by unusually large nanorods providing a set of connections that mimic a biological network of neurons. The networks are produced through self-assembly resulting from the molecular conformation and noncovalent intermolecular interactions. These features can be easily generated on flat surfaces and in a polymeric matrix by casting from solution under ambient conditions. The structures can be used to guide the position of electron-transporting agents such as carbon nanotubes on a surface or in a polymer matrix to create electrically conducting networks that can find direct use in constructing nanoelectronic circuits.The research leading to these results has received funding from ICIQ, ICREA, the Spanish Ministerio de Economia y Competitividad (MINECO) through project CTQ2011-27385 and the European Community Seventh Framework Program (FP7-PEOPLE-ITN-2008, CONTACT consortium) under grant agreement number 238363. We acknowledge E. C. Escudero-Adan, M. Martinez-Belmonte and E. Martin from the X-ray department of ICIQ for crystallographic analysis, and M. Moncusi, N. Argany, R. Marimon, M. Stefanova and L. Vojkuvka from the Servei de Recursos Cientifics i Tecnics from Universitat Rovira i Virgili (Tarragona, Spain).Escarcega-Bobadilla, MV.; Zelada-Guillen, GA.; Pyrlin, SV.; Wegrzyn, M.; Ramos, MMD.; Giménez Torres, E.; Stewart, A.... (2013). Nanorings and rods interconnected by self-assembly mimicking an artificial network of neurons. Nature Communications. 4:2648-2648. https://doi.org/10.1038/ncomms3648S264826484Champness, N. R. Making the right connections. Nat. Chem. 4, 149–150 (2012).Hopfield, J. J. & Tank, D. W. Computing with neural circuits: A model. Science 233, 625–633 (1986).Andres, P. R. et al. Self-assembly of a two-dimensional superlattice of molecularly linked metal clusters. Science 273, 1690–1693 (1996).Eichen, Y., Braun, E., Sivan, U. & Ben-Yoseph, G. Self-assembly of nanoelectronic components and circuits using biological templates. Acta Polym. 49, 663–670 (1998).Kawakami, T. et al. Possibilities of molecule-based spintronics of DNA wires, sheets, and related materials. Int. J. Quantum Chem. 105, 655–671 (2005).Kashtan, N., Itzkovitz, S., Milo, R. & Alon, U. Topological generalizations of network motifs. Phys. Rev. E 70, 031909 (2004).Grill, L. et al. Nano-architectures by covalent assembly of molecular building blocks. Nat. Nanotech. 2, 687–691 (2007).Lafferentz, L. et al. Controlling on-surface polymerization by hierarchical and substrate-directed growth. Nat. Chem. 4, 215–220 (2012).Alivisatos, A. P. et al. From molecules to materials: current trends and future directions. Adv. Mater. 10, 1297–1336 (1998).Pauling, L. The principles determining the structure of complex ionic crystals. J. Am. Chem. Soc. 51, 1010–1026 (1929).Damasceno, P. F., Engel, M. & Glotzer, S. C. Predictive self-assembly of polyhedra into complex structures. Science 337, 453–457 (2012).De Graaf, J. & Manna, L. A roadmap for the assembly of polyhedral particles. Science 337, 417–418 (2012).Percec, V. et al. Controlling polymer shape through the self-assembly of dendritic side-groups. Nature 391, 161–164 (1998).Stupp, S. I. et al. Supramolecular materials: self-organized nanostructures. Science 276, 384–389 (1997).Mann, S. The chemistry of form. Angew. Chem. Int. Ed. 39, 3392–3406 (2000).Sakakibara, K., Hill, J. P. & Ariga, K. Thin-film-based nanoarchitectures for soft matter: controlled assemblies into two-dimensional worlds. Small 7, 1288–1308 (2011).Huang, Z. et al. Pulsating tubules from noncovalent macrocycles. Science 337, 1521–1526 (2012).Ackermann, D., Jester, S.-S. & Famulok, M. Design strategy for DNA rotaxanes with a mechanically reinforced PX100 axle. Angew. Chem. Int. Ed. 27, 6771–6775 (2012).Marx, J. L. Microtubules: versatile organelles. Science 181, 1236–1237 (1973).Heus, H. A. & Pardi, A. Structural features that give rise to the unusual stability of RNA hairpins containing GNRA loops. Science 253, 191–194 (1991).Braun, E., Eichen, Y., Sivan, U. & Ben-Yoseph, G. DNA-templated assembly and electrode attachment of a conducting silver wire. Nature 391, 775–778 (1998).Zhang, S. Fabrication of novel biomaterials through molecular self-assembly. Nat. Biotechnol. 21, 1171–1178 (2003).Cai, X. et al. Integrated compact optical vortex beam emitters. Science 338, 363–365 (2012).Clark, A. W. & Cooper, J. M. Nanogap ring antennae as plasmonically coupled SERRS substrates. Small 7, 119–125 (2011).Armani, A. M., Kulkarni, R. P., Fraser, S. E., Flagan, R. C. & Vahala, K. J. Label-free, single-molecule detection with optical microcavities. Science 317, 783–787 (2007).Frischmann, P. D., Guieu, S., Tabeshi, R. & MacLachlan, M. J. Columnar organization of head-to-tail self-assembled Pt4 rings. J. Am. Chem. Soc. 132, 7668–7675 (2010).Frischmann, P. D. et al. Capsule formation, carboxylate exchange, and DFT exploration of cadmium cluster metallocavitands: highly dynamic supramolecules. J. Am. Chem. Soc. 132, 3893–3908 (2010).Akine, S., Hotate, S. & Nabeshima, T. A molecular leverage for helicity control and helix Inversion. J. Am. Chem. Soc. 133, 13868–13871 (2011).Salassa, G. et al. Extremely strong self-assembly of a bimetallic salen complex visualized at the single-molecule level. J. Am. Chem. Soc. 134, 7186–7192 (2012).Escárcega-Bobadilla, M. V., Salassa, G., Martínez Belmonte, M., Escudero-Adán, E. C. & Kleij, A. W. Versatile switching in substrate topicity: supramolecular chirality induction in di- and trinuclear host complexes. Chem. Eur. J. 18, 6805–6810 (2012).Frischmann, P. D., Jiang, J., Hui, J. K.-H., Grzybowski, J. J. & MacLachlan, M. J. Reversible—irreversible approach to Schiff base macrocycles. Access to isomeric macrocycles with multiple salphen pockets. Org. Lett. 10, 1255–1258 (2008).Glaser, T. Rational design of single-molecule magnets: a supramolecular approach. Chem. Commun. 47, 116–130 (2011).Lee, E. C. et al. Understanding of assembly phenomena by aromatic−aromatic interactions: benzene dimer and the substituted systems. J. Phys. Chem. A 111, 3446–3457 (2007).Grybowski, B. A., Wilmer, C. E., Kim, J., Browne, K. P. & Bishop, K. J. M. Self-assembly: from crystals to cells. Soft Matter. 5, 1110–1128 (2009).Martínez Belmonte, M. et al. Self-assembly of Zn(salphen) complexes: steric regulation, stability studies and crystallographic analysis revealing an unexpected dimeric 3,3′-t-Bu-substituted Zn(salphen) complex. Dalton Trans. 39, 4541–4550 (2010).Salassa, G., Castilla, A. M. & Kleij, A. W. Cooperative self-assembly of a macrocyclic Schiff base complex. Dalton Trans. 40, 5236–5243 (2011).Hormoz, S. & Brenner, M. P. Design principles for self-assembly with short-range interactions. Proc. Natl Acad. Sci. 108, 5193–5198 (2011).Biemans, H. A. M. et al. Hexakis porphyrinato benzenes. A new class of porphyrin arrays. J. Am. Chem. Soc. 120, 11054–11060 (1998).Lensen, M. C. et al. Aided self-assembly of porphyrin nanoaggregates into ring-shaped architectures. Chem. Eur. J. 10, 831–839 (2004).Martin, A., Buguin, A. & Brochard-Wyart, F. Dewetting nucleation centers at soft interfaces. Langmuir. 17, 6553–6559 (2001).Schenning, A. P. H. J., Benneker, F. B. G., Geurts, H. P. M., Liu, X. Y. & Nolte, R. J. M. Porphyrin wheels. J. Am. Chem. Soc. 118, 8549–8552 (1996).Deegan, R. D. et al. Capillary flow as the cause of ring strains from dried liquid drops. Nature 389, 827–829 (1997).Scriven, L. E. & Sternling, C. V. The Marangoni effects. Nature 187, 186–188 (1960).Cai, Y. & Newby, B. Z. Marangoni flow-induced self-assembly of hexagonal and stripe-like nanoparticle patterns. J. Am. Chem. Soc. 130, 6076–6077 (2008).Whitesides, G. M. & Grzybowski, B. Self-assembly at all scales. Science 295, 2418–2421 (2002).Mann, S. Self-assembly and transformation of hybrid nano-objects and nanostructures under equilibrium and non-equilibrium conditions. Nat. Mater. 8, 781–792 (2009).Gröschnel, A. H. et al. Precise hierarchical self-assembly of multicompartment micelles. Nat. Commun. 3, 710 (2012).Adam, M., Dogic, Z., Keller, S. L. & Fraden, S. Entropically driven microphase transitions in mixtures of colloidal rods and spheres. Nature 393, 349–352 (1998).Ohara, P. C., Heath, J. R. & Gelbart, W. M. Self-assembly of submicrometer rings of particles from solutions of nanoparticles. Angew. Chem. Int. Ed. 36, 1077–1080 (1997).Xu, J., Xia, J. & Lin, Z. Evaporation-induced self-assembly of nanoparticles from a sphere-on-flat geometry. Angew. Chem. Int. Ed. 46, 1860–1863 (2007).Yosef, G. & Rabani, E. Self-assembly of nanoparticles into rings: A lattice-gas model. J. Phys. Chem. B 110, 20965–20972 (2006).Khanal, B. P. & Zubarev, E. R. Rings of nanorods. Angew. Chem. Int. Ed. 46, 2195–2198 (2007).Wang, Z. et al. One-step, self-assembly, alignment, and patterning of organic semiconductor nanowires by controlled evaporation of confined microfluids. Angew. Chem. Int. Ed. 50, 2811–2815 (2011).Hong, S. W. et al. Directed self-assembly of gradient concentric carbon nanotube rings. Adv. Func. Mater. 18, 2114–2122 (2008).Palma, M. et al. Controlled formation of carbon nanotube junctions via linker-induced assembly in aqueous solution. J. Am. Chem. Soc. 135, 8440–8443 (2013).Horcas, I. et al. WSXM: A software for scanning probe microscopy and a tool for nanotechnology. Rev. Sci. Instrum. 78, 013705 (2007).Soler, J. M. et al. The SIESTA method for ab initio order-n materials simulation. J. Phys. Cond. Matter 14, 2745–2779 (2002).Haynes, P. D., Mostof, A. A., Skylaris, C. & Payne, M. C. ONETEP: Linear-scaling density-functional theory with plane-waves. J. Phys. Conf. Ser. 26, 143–148 (2006).Valiev, M. et al. NWCHEM: A comprehensive and scalable open-source solution for large scale molecular simulations. Comp. Phys. Commun. 181, 1477–1489 (2010).Plimpton, S. Fast parallel algorithms for short-range molecular dynamics. J. Comp. Phys. 117, 1–19 (1995)

Gender Differences in Associations of Glutamate Decarboxylase 1 Gene (GAD1) Variants with Panic Disorder

Background: Panic disorder is common (5% prevalence) and females are twice as likely to be affected as males. The heritable component of panic disorder is estimated at 48%. Glutamic acid dehydrogenase GAD1, the key enzyme for the synthesis of the inhibitory and anxiolytic neurotransmitter GABA, is supposed to influence various mental disorders, including mood and anxiety disorders. In a recent association study in depression, which is highly comorbid with panic disorder, GAD1 risk allele associations were restricted to females. Methodology/Principal Findings: Nineteen single nucleotide polymorphisms (SNPs) tagging the common variation in GAD1 were genotyped in two independent gender and age matched case-control samples (discovery sample n = 478; replication sample n = 584). Thirteen SNPs passed quality control and were examined for gender-specific enrichment of risk alleles associated with panic disorder by using logistic regression including a genotype×gender interaction term. The latter was found to be nominally significant for four SNPs (rs1978340, rs3762555, rs3749034, rs2241165) in the discovery sample; of note, the respective minor/risk alleles were associated with panic disorder only in females. These findings were not confirmed in the replication sample; however, the genotype×gender interaction of rs3749034 remained significant in the combined sample. Furthermore, this polymorphism showed a nominally significant association with the Agoraphobic Cognitions Questionnaire sum score. Conclusions/Significance: The present study represents the first systematic evaluation of gender-specific enrichment of risk alleles of the common SNP variation in the panic disorder candidate gene GAD1. Our tentative results provide a possible explanation for the higher susceptibility of females to panic disorder