Sleep disturbance and serum ferritin levels associate with high impulsivity and impulse control disorders in male Parkinson\u27s Disease patients

Impulse control disorders (ICDs) occur in a subset of Parkinson’s disease (PD) patients on dopaminergic medications however there are currently no reliable markers to identify patients at risk. Sleep disturbances are more common in patients with an ICD. Serum ferritin levels have been associated with PD disease stage and progression, but have not previously been associated with impulsivity levels. The objective of this study was to determine if serum ferritin levels and sleep disturbance are associated with high traits of impulsivity and ICD in a cohort of PD patients attending a movement disorders clinic. This study assessed impulsiveness in 87 PD patients using the Barratt Impulsiveness Scale. Severity of sleep disturbance was determined using the sleep-related items of the MDS-UPDRS. Serum ferritin, iron and transferrin levels were measured in patients, as well as 36 age-matched healthy controls. Serum ferritin levels were significantly elevated in male PD patients in the high impulsivity group compared to patients in the low (p=.022) and normal range groups (p=.024) and showed a linear increase across the three groups. Sleep disturbance also demonstrated a linear trend, which was most severe in the high impulsivity group (p=.030). A subgroup of 11 male PD patients who fulfilled the DSM-5 criteria for an ICD had significantly higher ferritin levels and more severe sleep disturbance when compared with the remaining male PD cohort. Serum ferritin levels and sleep disturbance severity are highlighted as potential markers for abnormal impulsivity and ICD in PD patients

Extended Timed Up and Go assessment as a clinical indicator of cognitive state in Parkinson\u27s disease

Objective: To evaluate a modified extended Timed Up and Go (extended-TUG) assessment against a panel of validated clinical assessments, as an indicator of Parkinson’s disease (PD) severity and cognitive impairment. Methods: Eighty-seven participants with idiopathic PD were sequentially recruited from a Movement Disorders Clinic. An extended-TUG assessment was employed which required participants to stand from a seated position, walk in a straight line for 7 metres, turn 180 degrees and then return to the start, in a seated position. The extended-TUG assessment duration was correlated to a panel of clinical assessments, including the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), Quality of Life (PDQ-39), Scales for Outcomes in Parkinson’s disease (SCOPA-Cog), revised Addenbrooke’s Cognitive Index (ACE-R) and Barratt’s Impulsivity Scale 11 (BIS-11). Results: Extended-TUG time was significantly correlated to MDS-UPDRS III score and to SCOPA-Cog, ACE-R (p\u3c0.001) and PDQ-39 scores (p\u3c0.01). Generalized linear models determined the extended-TUG to be a sole variable in predicting ACE-R or SCOPA-Cog scores. Patients in the fastest extended-TUG tertile were predicted to perform 8.3 and 13.4 points better in the SCOPA-Cog and ACE-R assessments, respectively, than the slowest group. Patients who exceeded the dementia cut-off scores with these instruments exhibited significantly longer extended-TUG times. Conclusions: Extended-TUG performance appears to be a useful indicator of cognition as well as motor function and quality of life in PD, and warrants further evaluation as a first line assessment tool to monitor disease severity and response to treatment. Poor extended-TUG performance may identify patients without overt cognitive impairment form whom cognitive assessment is needed

Pliocene-Pleistocene marine cyclothems, Wanganui Basin, New Zealand: a lithostratigraphic framework

The Rangitikei River valley between Mangaweka and Vinegar Hill and the surrounding Ohingaiti region in eastern Wanganui Basin contains a late Pliocene to early Pleistocene (c. 2.6-1.7 Ma), c. 1100 m thick, southward-dipping (4-9deg.), marine cyclothemic succession. Twenty sedimentary cycles occur within the succession, each of which contains coarse-grained (siliciclastic sandstone and coquina) and fine-grained (siliciclastic siltstone) units. Nineteen of the cycles are assigned to the Rangitikei Group (new). Six new formations are defined within the Rangitikei Group, and their distribution in the Ohingaiti region is represented in a new geologic map. The new formations are named: Mangarere, Tikapu, Makohine, Orangipongo, Mangaonoho, and Vinegar Hill. Each formation comprises one or more cyclothems and includes a previously described and named distinctive basal horizon. Discrete sandstones, siltstones, and coquinas within formations are assigned member status and correspond to systems tracts in sequence stratigraphic nomenclature. The members provide the link between the new formational lithostratigraphy and the sequence stratigraphy of the Rangitikei Group. Base of cycle coquina members accumulated during episodes of sediment starvation associated with stratigraphic condensation on an open marine shelf during sea-level transgressions. Siltstone members accumulated in mid-shelf environments (50-100 m water depth) during sea-level highstands, whereas the overlying sandstone members are ascribed to inner shelf and shoreface environments (0-50 m water depth) and accumulated during falling eustatic sea-level conditions. Repetitive changes in water depth of 50-100 m magnitude are consistent with a glacio-eustatic origin for the cyclothems, which correspond to an interval of Earth history when successive glaciations in the Northern Hemisphere are known to have occurred. Moreover, the chronology of the Rangitikei River section indicates that Rangitikei Group cyclothems accumulated during short duration, 41 ka cycles in continental ice volume attributed to the dominance of the Milankovitch obliquity orbital parameter. The Ohingaiti region has simple postdepositional structure. The late Pliocene formations dip generally to the SSW between 4deg. and 9deg.. Discernible discordances of c. 1deg. between successively younger formations are attributed to synsedimentary tilting of the shelf concomitant with migration of the tectonic hingeline southward into the basin. The outcrop distribution of the Rangitikei Group is strongly influenced by this regional tilt and also by three major northeast-southwest oriented, high-angle reverse faults (Rauoterangi, Pakihikura, and Rangitikei Faults)

‘We achieve the impossible’: discourses of freedom and escape at music festivals and free parties

In this article, we explore the notion of freedom as a form of governance within contemporary consumer culture in a sphere where ‘freedom’ appears as a key component: outdoor music-based leisure events, notably music festivals and free parties. ‘Freedom’ is commodified as central to the marketing of many music festivals, which now form a highly commercialised sector of the UK leisure industry, subject to various regulatory restrictions. Free parties, in contrast, are unlicensed, mostly illegal and far less commercialised leisure spaces. We present data from two related studies to investigate how participants at three major British outdoor music festivals and a small rural free party scene draw on discourses of freedom, escape and regulation. We argue that major music festivals operate as temporary bounded spheres of ‘licensed transgression’, in which an apparent lack of regulation operates as a form of governance. In contrast, free parties appear to ‘achieve the impossible’ by creating alternative (and illegal) spaces in which both freedom and regulation are constituted in different ways compared to music festival settings

Demographic and clinical predictors of trait impulsivity in Parkinson’s disease patients

Background: Impulsive behaviour has become increasingly recognised as a neuropsychiatric complication of Parkinson’s disease (PD). Thought to be a product of compromised cognitive control, the spectrum of impulsive behaviours in PD ranges from cognitive disinhibition to impulse control disorders (ICDs). Objective: At present, there are no indicators for trait impulsivity in PD. The objective of the current study was to identify demographic and clinical predictors of susceptibility to trait impulsivity in a cohort of PD patients. Methods: The current study assessed impulsivity using the Barratt Impulsiveness Scale 11 (BIS-11) in a cohort of 87 PD patients. General linear models (GLMs) were used to identify clinical and demographic variables predictive of heightened BIS-11 second-order attentional and nonplanning subscale scores. Results: Male gender, no history of smoking, postsecondary education, and heightened disease severity were predictive of increased BIS-11 attentional scores (p \u3c 0.05). Similarly, male gender, after secondary education, and disease severity were predictive of increased BIS-11 nonplanning scores (p \u3c 0.05). Contrary to previous reports, dopaminergic medication use was not a significant determinant of either BIS-11 subscale scores. Conclusions: Several demographic and clinical variables including male gender, no history of past smoking, after secondary education, and elevated disease severity are associated with impulsivity in PD

Elevated serum ceruloplasmin levels are associated with higher impulsivity in people with Parkinson’s Disease

Background. Heightened impulsivity has been reported in a subset of people with Parkinson’s disease (PwP) and is considered a risk factor for the development of impulse control disorders (ICDs). However, at present, there are no recognised biochemical markers of heightened impulsivity. Objectives. To determine if ceruloplasmin, a serum marker involved in the regulation of iron and copper homeostasis, is associated with trait impulsivity in PwP. Methods. The study measured serum ceruloplasmin and impulsivity using the Barratt Impulsiveness Scale (BIS-11) in an Australian cohort of 214 PwP. Multivariate general linear models (GLMs) were used to identify whether higher serum ceruloplasmin levels (>75th percentile) were significantly predictive of BIS-11 scores. Results. Serum ceruloplasmin was higher in females with PD (p<0.001) and associated with MDS-UPDRS III, Hoehn and Yahr, and ACE-R scores (p<0.05). When correcting for covariates, higher serum ceruloplasmin concentrations were associated with the 2nd order nonplanning impulsivity and with the 1st order self-control and cognitive complexity impulsivity domains. Conclusions. Higher serum ceruloplasmin levels are independently associated with heightened nonplanning impulsivity in PwP. Thus, serum ceruloplasmin levels may have clinical utility as a marker for heightened impulsivity in PD

THE ELEVENTH AND TWELFTH DATA RELEASES OF THE SLOAN DIGITAL SKY SURVEY: FINAL DATA FROM SDSS-III

Citation: Alam, S., Albareti, F. D., Prieto, C. A., Anders, F., Anderson, S. F., Anderton, T., . . . Zhu, G. T. (2015). THE ELEVENTH AND TWELFTH DATA RELEASES OF THE SLOAN DIGITAL SKY SURVEY: FINAL DATA FROM SDSS-III. Astrophysical Journal Supplement Series, 219(1), 27. doi:10.1088/0067-0049/219/1/12The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg(2) of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg(2) of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg(2); 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra.Additional Authors: Berlind, A. A.;Beutler, F.;Bhardwaj, V.;Bird, J. C.;Bizyaev, D.;Blake, C. H.;Blanton, M. R.;Blomqvist, M.;Bochanski, J. J.;Bolton, A. S.;Bovy, J.;Bradley, A. S.;Brandt, W. N.;Brauer, D. E.;Brinkmann, J.;Brown, P. J.;Brownstein, J. R.;Burden, A.;Burtin, E.;Busca, N. G.;Cai, Z.;Capozzi, D.;Rosell, A. C.;Carr, M. A.;Carrera, R.;Chambers, K. C.;Chaplin, W. J.;Chen, Y. C.;Chiappini, C.;Chojnowski, S. D.;Chuang, C. H.;Clerc, N.;Comparat, J.;Covey, K.;Croft, R. A. C.;Cuesta, A. J.;Cunha, K.;da Costa, L. N.;Da Rio, N.;Davenport, J. R. A.;Dawson, K. S.;De Lee, N.;Delubac, T.;Deshpande, R.;Dhital, S.;Dutra-Ferreira, L.;Dwelly, T.;Ealet, A.;Ebelke, G. L.;Edmondson, E. M.;Eisenstein, D. J.;Ellsworth, T.;Elsworth, Y.;Epstein, C. R.;Eracleous, M.;Escoffier, S.;Esposito, M.;Evans, M. L.;Fan, X. H.;Fernandez-Alvar, E.;Feuillet, D.;Ak, N. F.;Finley, H.;Finoguenov, A.;Flaherty, K.;Fleming, S. W.;Font-Ribera, A.;Foster, J.;Frinchaboy, P. M.;Galbraith-Frew, J. G.;Garcia, R. A.;Garcia-Hernandez, D. A.;Perez, A. E. G.;Gaulme, P.;Ge, J.;Genova-Santos, R.;Georgakakis, A.;Ghezzi, L.;Gillespie, B. A.;Girardi, L.;Goddard, D.;Gontcho, S. G. A.;Hernandez, J. I. G.;Grebel, E. K.;Green, P. J.;Grieb, J. N.;Grieves, N.;Gunn, J. E.;Guo, H.;Harding, P.;Hasselquist, S.;Hawley, S. L.;Hayden, M.;Hearty, F. R.;Hekker, S.;Ho, S.;Hogg, D. W.;Holley-Bockelmann, K.;Holtzman, J. A.;Honscheid, K.;Huber, D.;Huehnerhoff, J.;Ivans, II;Jiang, L. H.;Johnson, J. A.;Kinemuchi, K.;Kirkby, D.;Kitaura, F.;Klaene, M. A.;Knapp, G. R.;Kneib, J. P.;Koenig, X. P.;Lam, C. R.;Lan, T. W.;Lang, D. T.;Laurent, P.;Le Goff, J. M.;Leauthaud, A.;Lee, K. G.;Lee, Y. S.;Licquia, T. C.;Liu, J.;Long, D. C.;Lopez-Corredoira, M.;Lorenzo-Oliveira, D.;Lucatello, S.;Lundgren, B.;Lupton, R. H.;Mack, C. E.;Mahadevan, S.;Maia, M. A. G.;Majewski, S. R.;Malanushenko, E.;Malanushenko, V.;Manchado, A.;Manera, M.;Mao, Q. Q.;Maraston, C.;Marchwinski, R. C.;Margala, D.;Martell, S. L.;Martig, M.;Masters, K. L.;Mathur, S.;McBride, C. K.;McGehee, P. M.;McGreer, I. D.;McMahon, R. G.;Menard, B.;Menzel, M. L.;Merloni, A.;Meszaros, S.;Miller, A. A.;Miralda-Escude, J.;Miyatake, H.;Montero-Dorta, A. D.;More, S.;Morganson, E.;Morice-Atkinson, X.;Morrison, H. L.;Mosser, B.;Muna, D.;Myers, A. D.;Nandra, K.;Newman, J. A.;Neyrinck, M.;Nguyen, D. C.;Nichol, R. C.;Nidever, D. L.;Noterdaeme, P.;Nuza, S. E.;O'Connell, J. E.;O'Connell, R. W.;O'Connell, R.;Ogando, R. L. C.;Olmstead, M. D.;Oravetz, A. E.;Oravetz, D. J.;Osumi, K.;Owen, R.;Padgett, D. L.;Padmanabhan, N.;Paegert, M.;Palanque-Delabrouille, N.;Pan, K. K.;Parejko, J. K.;Paris, I.;Park, C.;Pattarakijwanich, P.;Pellejero-Ibanez, M.;Pepper, J.;Percival, W. J.;Perez-Fournon, I.;Perez-Rafols, I.;Petitjean, P.;Pieri, M. M.;Pinsonneault, M. H.;de Mello, G. F. P.;Prada, F.;Prakash, A.;Price-Whelan, A. M.;Protopapas, P.;Raddick, M. J.;Rahman, M.;Reid, B. A.;Rich, J.;Rix, H. W.;Robin, A. C.;Rockosi, C. M.;Rodrigues, T. S.;Rodriguez-Torres, S.;Roe, N. A.;Ross, A. J.;Ross, N. P.;Rossi, G.;Ruan, J. J.;Rubino-Martin, J. A.;Rykoff, E. S.;Salazar-Albornoz, S.;Salvato, M.;Samushia, L.;Sanchez, A. G.;Santiago, B.;Sayres, C.;Schiavon, R. P.;Schlegel, D. J.;Schmidt, S. J.;Schneider, D. P.;Schultheis, M.;Schwope, A. D.;Scoccola, C. G.;Scott, C.;Sellgren, K.;Seo, H. J.;Serenelli, A.;Shane, N.;Shen, Y.;Shetrone, M.;Shu, Y. P.;Aguirre, V. S.;Sivarani, T.;Skrutskie, M. F.;Slosar, A.;Smith, V. V.;Sobreira, F.;Souto, D.;Stassun, K. G.;Steinmetz, M.;Stello, D.;Strauss, M. A.;Streblyanska, A.;Suzuki, N.;Swanson, M. E. C.;Tan, J. C.;Tayar, J.;Terrien, R. C.;Thakar, A. R.;Thomas, D.;Thomas, N.;Thompson, B. A.;Tinker, J. L.;Tojeiro, R.;Troup, N. W.;Vargas-Magana, M.;Vazquez, J. A.;Verde, L.;Viel, M.;Vogt, N. P.;Wake, D. A.;Wang, J.;Weaver, B. A.;Weinberg, D. H.;Weiner, B. J.;White, M.;Wilson, J. C.;Wisniewski, J. P.;Wood-Vasey, W. M.;Yeche, C.;York, D. G.;Zakamska, N. L.;Zamora, O.;Zasowski, G.;Zehavi, I.;Zhao, G. B.;Zheng, Z.;Zhou, X.;Zhou, Z. M.;Zou, H.;Zhu, G. T

Understanding the unsteady pressure field inside combustion chambers of compression-ignited engines using a computational fluid dynamics approach

[EN] In this article, a numerical methodology for assessing combustion noise in compression ignition engines is described with the specific purpose of analysing the unsteady pressure field inside the combustion chamber. The numerical results show consistent agreement with experimental measurements in both the time and frequency domains. Nonetheless, an exhaustive analysis of the calculation convergence is needed to guarantee an independent solution. These results contribute to the understanding of in-cylinder unsteady processes, especially of those related to combustion chamber resonances, and their effects on the radiated noise levels. The method was applied to different combustion system configurations by modifying the spray angle of the injector, evidencing that controlling the ignition location through this design parameter, it is possible to decrease the combustion noise by minimizing the resonance contribution. Important efficiency losses were, however, observed due to the injector/bowl matching worsening which compromises the performance and emissions levels.The authors want to express their gratitude to CONVERGENT SCIENCE Inc. and Convergent Science GmbH for their kind support for performing the CFD calculations using CONVERGE software.Torregrosa, AJ.; Broatch, A.; Margot, X.; Gómez-Soriano, J. (2018). Understanding the unsteady pressure field inside combustion chambers of compression-ignited engines using a computational fluid dynamics approach. International Journal of Engine Research. 1-13. https://doi.org/10.1177/1468087418803030S113Benajes, J., Novella, R., De Lima, D., & Tribotté, P. (2014). Analysis of combustion concepts in a newly designed two-stroke high-speed direct injection compression ignition engine. International Journal of Engine Research, 16(1), 52-67. doi:10.1177/1468087414562867Costa, M., Bianchi, G. M., Forte, C., & Cazzoli, G. (2014). A Numerical Methodology for the Multi-objective Optimization of the DI Diesel Engine Combustion. Energy Procedia, 45, 711-720. doi:10.1016/j.egypro.2014.01.076Navid, A., Khalilarya, S., & Taghavifar, H. (2016). Comparing multi-objective non-evolutionary NLPQL and evolutionary genetic algorithm optimization of a DI diesel engine: DoE estimation and creating surrogate model. Energy Conversion and Management, 126, 385-399. doi:10.1016/j.enconman.2016.08.014Benajes, J., García, A., Pastor, J. M., & Monsalve-Serrano, J. (2016). Effects of piston bowl geometry on Reactivity Controlled Compression Ignition heat transfer and combustion losses at different engine loads. Energy, 98, 64-77. doi:10.1016/j.energy.2016.01.014Masterton, B., Heffner, H., & Ravizza, R. (1969). The Evolution of Human Hearing. The Journal of the Acoustical Society of America, 45(4), 966-985. doi:10.1121/1.1911574Strahle, W. C. (1978). Combustion noise. 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Combustion chamber resonances in direct injection automotive diesel engines: A numerical approach. International Journal of Engine Research, 5(1), 83-91. doi:10.1243/146808704772914264Broatch, A., Margot, X., Gil, A., & Christian Donayre, (José). (2007). Computational study of the sensitivity to ignition characteristics of the resonance in DI diesel engine combustion chambers. Engineering Computations, 24(1), 77-96. doi:10.1108/02644400710718583Eriksson, L. J. (1980). Higher order mode effects in circular ducts and expansion chambers. The Journal of the Acoustical Society of America, 68(2), 545-550. doi:10.1121/1.384768Broatch, A., Margot, X., Novella, R., & Gomez-Soriano, J. (2017). Impact of the injector design on the combustion noise of gasoline partially premixed combustion in a 2-stroke engine. Applied Thermal Engineering, 119, 530-540. doi:10.1016/j.applthermaleng.2017.03.081Tutak, W., & Jamrozik, A. (2016). Validation and optimization of the thermal cycle for a diesel engine by computational fluid dynamics modeling. Applied Mathematical Modelling, 40(13-14), 6293-6309. doi:10.1016/j.apm.2016.02.021Payri, F., Benajes, J., Margot, X., & Gil, A. (2004). CFD modeling of the in-cylinder flow in direct-injection Diesel engines. Computers & Fluids, 33(8), 995-1021. doi:10.1016/j.compfluid.2003.09.003Benajes, J., Novella, R., De Lima, D., & Thein, K. (2017). Impact of injection settings operating with the gasoline Partially Premixed Combustion concept in a 2-stroke HSDI compression ignition engine. Applied Energy, 193, 515-530. doi:10.1016/j.apenergy.2017.02.044Lesieur, M., Métais, O., & Comte, P. (2005). Large-Eddy Simulations of Turbulence. doi:10.1017/cbo9780511755507Pope, S. B. (2004). Ten questions concerning the large-eddy simulation of turbulent flows. New Journal of Physics, 6, 35-35. doi:10.1088/1367-2630/6/1/035Silva, C. F., Leyko, M., Nicoud, F., & Moreau, S. (2013). Assessment of combustion noise in a premixed swirled combustor via Large-Eddy Simulation. Computers & Fluids, 78, 1-9. doi:10.1016/j.compfluid.2010.09.034Jamrozik, A., Tutak, W., Kociszewski, A., & Sosnowski, M. (2013). Numerical simulation of two-stage combustion in SI engine with prechamber. Applied Mathematical Modelling, 37(5), 2961-2982. doi:10.1016/j.apm.2012.07.040Qin, W., Xie, M., Jia, M., Wang, T., & Liu, D. (2014). Large eddy simulation of in-cylinder turbulent flows in a DISI gasoline engine. Applied Mathematical Modelling, 38(24), 5967-5985. doi:10.1016/j.apm.2014.05.004Broatch, A., Margot, X., Novella, R., & Gomez-Soriano, J. (2016). Combustion noise analysis of partially premixed combustion concept using gasoline fuel in a 2-stroke engine. Energy, 107, 612-624. doi:10.1016/j.energy.2016.04.045Torregrosa, A. J., Broatch, A., Martín, J., & Monelletta, L. (2007). Combustion noise level assessment in direct injection Diesel engines by means of in-cylinder pressure components. Measurement Science and Technology, 18(7), 2131-2142. doi:10.1088/0957-0233/18/7/045Payri, F., Broatch, A., Margot, X., & Monelletta, L. (2008). Sound quality assessment of Diesel combustion noise using in-cylinder pressure components. Measurement Science and Technology, 20(1), 015107. doi:10.1088/0957-0233/20/1/015107Ihlenburg, F. (2003). The Medium-Frequency Range in Computational Acoustics: Practical and Numerical Aspects. Journal of Computational Acoustics, 11(02), 175-193. doi:10.1142/s0218396x03001900Lapuerta, M., Armas, O., & Hernández, J. J. (1999). Diagnosis of DI Diesel combustion from in-cylinder pressure signal by estimation of mean thermodynamic properties of the gas. Applied Thermal Engineering, 19(5), 513-529. doi:10.1016/s1359-4311(98)00075-1Payri, F., Olmeda, P., Martín, J., & García, A. (2011). 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Assessment of flamelet versus multi-zone combustion modeling approaches for stratified-charge compression ignition engines. International Journal of Engine Research, 17(3), 280-290. doi:10.1177/1468087415571006Torregrosa, A. J., Broatch, A., Gil, A., & Gomez-Soriano, J. (2018). Numerical approach for assessing combustion noise in compression-ignited Diesel engines. Applied Acoustics, 135, 91-100. doi:10.1016/j.apacoust.2018.02.006Torregrosa, A., Olmeda, P., Degraeuwe, B., & Reyes, M. (2006). A concise wall temperature model for DI Diesel engines. Applied Thermal Engineering, 26(11-12), 1320-1327. doi:10.1016/j.applthermaleng.2005.10.021Broatch, A., Javier Lopez, J., García-Tíscar, J., & Gomez-Soriano, J. (2018). Experimental Analysis of Cyclical Dispersion in Compression-Ignited Versus Spark-Ignited Engines and Its Significance for Combustion Noise Numerical Modeling. Journal of Engineering for Gas Turbines and Power, 140(10). doi:10.1115/1.4040287Molina, S., García, A., Pastor, J. 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Altered gut microbiome in Parkinson\u27s disease and the influence of lipopolysaccharide in a human α-synuclein over-expressing mouse model

The interaction between the gut microbiota and alpha-synuclein (αSyn) aggregation in Parkinson’s disease (PD) is receiving increasing attention. The objective of this study was to investigate gut microbiota, and effects of an inflammatory lipopolysaccharide (LPS) trigger in a human αSyn over-expressing mouse model of PD (Thy1-αSyn). Stool samples from patients with confirmed PD and Thy1-αSyn mice were analyzed using 16S ribosomal RNA sequencing. Compared to healthy controls, the relative abundance of mucin-degrading Verrucomicrobiae and LPS-producing Gammaproteobacteria were greater in PD patients. In mice, the abundance of Gammaproteobacteria was negligible in both Thy1-αSyn and wild-type (WT) animals, while Verrucomicrobiae were reduced in Thy1-αSyn mice. The effect of LPS on intestinal barrier function was investigated in vitro using intestinal epithelial (IEC-6) cells, and in vivo via administration of LPS in drinking water to Thy1-αSyn mice. Acute exposure to LPS in vitro resulted in a reduction and altered distribution of the tight junction markers ZO-1 and e-Cadherin around the cell membrane in IEC-6 cells, as shown by immunohistochemistry. LPS administration in Thy1-αSyn mice resulted in the emergence of early motor manifestations at 10 weeks, compared to untreated mice who were still asymptomatic at this age. This study reaffirms that an altered microbiome exists in patients with PD, and supports the notion of a proinflammatory gut microbiome environment as a trigger for PD pathogenesis