Although the Lesnoy eddy occurs frequently and is variable in its

Although the Lesnoy eddy occurs frequently and is variable in its location, form and size, it is not strictly attributed to any form of the coastline off the base of the Curonian Spit, where the coastline changes direction from W-E to a SW-NE. The Lesnoy eddy does not form an obvious vortex signature on satellite images, and although vortex-like structures (mostly in form of a hook) in this area can be identified on MODIS images, even if this is relatively rare. The stability of the Lesnoy eddy in time and its influence on coastal processes should be further investigated. The Lesnoy eddy as

well as sub-mesoscale eddies near the central part of the Curonian Spit have different properties and dimensions selleck kinase inhibitor in every ABT 199 case, and it is probable that the satellite imagery used here has only provided snapshots of the development of coastal eddies of different origins. The authors express their thanks to LUKOIL AB, which financed monitoring activities in the area of D6 Oil Field Marine Platform (Dr V. V. Sivkov – coordinator), the CODAR measurements off the northern shore of the Sambian Peninsula (carried out by V. V. Gorbatskiy, A. N. Babakov, E.S. Gurova over 2 years), and the meteorological measurements at platform

D6 (processed by Zh. I. Stont). Detailed analysis of meteorological conditions was possible only due to the kind input from Dr A. Lehmann, who shared the results of BSIOM model. The authors thank NASA for free open access to MODIS data, and ESA (via project C1P-3424, with personal thanks to A. Yu. Ivanov) for providing ASAR satellite imagery for this research. The preparation of this paper was

partly supported by grants No. 11-05-00674 and 12-05-90807-mol_rf_nr of the Russian Foundation for Basic Research. The authors are very grateful to the reviewers for their valuable comments, and to Dr Margaret Carlisle for the language corrections: their inputs improved the quality of the manuscript a lot. “
“Optical shallowness implies that the water-leaving Dichloromethane dehalogenase radiance Lwn of a basin depends both on the optical properties of the water body and on the light backscattered from its bed and/or from bottom sediments resuspended by bottom currents. The latter factors hamper the retrieval of chlorophyll from Lwn measured in shallow basins but they can be useful for the remote sensing of near-bottom water flows ( Karabashev et al. 2009). The thickness of the layer from which radiance originates equation(1) Zor(λ)=1/Kd(λ),Zorλ=1/Kdλ, where Kd(λ) is the coefficient of daylight attenuation in water at a wavelength λ ( Gordon & McCluney 1975). Kd at λ = 470 nm ranges from 0.02 m− 1 in oligotrophic waters to 1 m− 1 or higher in ultra-eutrophic ocean areas or inland seas. Hence, an optically shallow aquatic area can be as deep as 50 m.

A smaller study (N = 39) by the same group reported no difference

A smaller study (N = 39) by the same group reported no differences in patient survival, graft survival, or BPAR incidence between patients receiving SRL/standard TAC and those receiving SRL/reduced TAC (Table 1) [49]. However, 38% and 6% of patients on standard TAC were discontinued due to TAC nephrotoxicity and thrombotic microangiopathy, respectively. Several factors may have contributed to the apparent increased nephrotoxicity, including the study population (79% black), use of kidneys from deceased

donors, and high incidence of delayed graft function (59%). Two-year data compared similar regimens in 132 live donor renal allotransplant patients [50]. The efficacy outcomes were patient survival and graft

survival, BPAR incidence, and graft function. At 2 years, renal function Tacrolimus order was significantly improved with the TAC-free regimen (SRL/MMF), compared with find protocol the SRL/TAC-sparing regimen, as measured by serum creatinine level and calculated GFR (both p < 0.05; Table 1). In addition, the rate of acute rejection was numerically lower in the TAC-free group (13.5% vs 18.5%; p = ns). Three-year results from a long-term study (N = 150) comparing SRL/TAC, MMF/TAC, and SRL/CsA are also available [51]. At 3 years, patient survival, graft survival, and BPAR incidence did not differ significantly among the 3 groups (Table 1), although the latter showed a trend in favor of MMF/TAC (p = 0.07). Although renal function (as measured by creatinine) was acceptable in each of the 3 groups, the MMF/TAC group was statistically more favorable when compared with SRL/CsA at 12, 24, and 36 months

(p = 0.02, p = 0.05, Flucloronide and p = 0.04, respectively) and SRL/TAC at 24 months (p = 0.05). Rates of NODM by year 3 were lowest with MMF/TAC (11% vs 27–31% in other groups). Longer-term follow-up of the same study (median of 8 years) showed significant differences or trends with respect to the above endpoints that consistently favored MMF/TAC over the other regimens [52]. Viral infections and need for antilipid therapy were significantly lower with MMF/TAC versus the other regimens combined (p < 0.05), and the incidence of NODM was numerically lower with MMF/TAC (Table 1). Similar long-term findings were reported by Chhabra and colleagues [53]. In their study, 82 renal transplant recipients were followed for up to a mean of 8.5 years. MMF/TAC provided better efficacy and safety than SRL/TAC, with significant differences seen for graft survival and GFR (Table 1). In summary, results to date are derived mainly from single-center studies, and thus more robust data are needed to confirm the preliminary findings. Two small-scale studies compared reduced-dose TAC versus standard-dose TAC, when used in combination with SRL [47] and [49].

Flt-1 baseline level of CA1 and CA2 neurons occupied the intermed

Flt-1 baseline level of CA1 and CA2 neurons occupied the intermediary position relative to CA3 and DG; CA1 and CA2 neurons showed quite the same baseline distribution pattern of Flt-1. In all four regions the expression of Flt-1 at basal level was visibly higher in P14 rats than in 8–10 wks rats. In Panobinostat animals of both ages i.p.-injected with PNV there was immediate upregulation of the level of Flt-1 expression in all the four hippocampal regions studied. CA1 and DG were the regions with most dramatic rise of Flt-1 expression 1 h after injection: Flt-1 level of PNV-exposed rats was upregulated by 90% in CA1, 135% in DG whereas CA2 and CA3 just showed a trend for rising. Also, it is of interest to observe

that CA1 and DG neurons of animals of both ages displayed a similar time-course changes of the VEGF’s Flt-1 receptor density of pixels (compare Fig. 4A and D). Likewise, neurons of CA2 and CA3 in animals of both ages showed quite the same pattern of time-course changes in their immunolabeling (compare Fig. 4B and C). In animals of both ages, the neurons of CA2 were the least susceptible to change the expression of Flt-1 receptor (Fig. 4B). The two-way analysis of variance showed that there was interaction between time after PNV injection versus age of animals for CA3 and DG in relation to the expression of the receptor. The Flt-1 expression was

influenced by the two variables “time after envenoming” and “age of animals” in all the four regions scanned. To investigate a potential involvement of the vascular endothelial growth factor (VEGF) in the neurotoxic effects caused by P. nigriventer venom in the hippocampus, Oligomycin A manufacturer we analyzed whether the expression of VEGFR-1, also named Flt-1, was changed after i.p. administration of venom. Using immunohistochemistry for the Flt-1 it was possible to determine that neurons were the principal cells constitutively expressing the receptor and that anti-Flt-1 was immunodetected in the nucleus of neurons; by immunohistochemistry labeling the distribution

and expressional level of Flt-1 was demonstrated in all the four selected regions of the hippocampus: CA1, CA2, CA3 and DG. Nuclear location of Flt-1 has been found in the dorsal root Cyclin-dependent kinase 3 ganglion sensory neurons ( Dhondt et al., 2011), ventral root motor neurons ( Poesen et al., 2008), and lumbar motor neurons ( Islamov et al., 2004) and others. In hippocampus, Flt-1 mRNA is restricted to pyramidal neurons of CA regions and granular neurons of DG ( Choi et al., 2007). In all these regions the upregulation of Flt-1 has been associated with neuroprotective signals mediating VEGF effects in different injury conditions. Herein, the investigation was focused on hippocampus as one of the brain regions particularly targeted by PNV as has been shown by our laboratory (Le Sueur et al., 2003; Rapôso et al., 2007; da Cruz-Höfling et al., 2009). These previous studies have shown that the i.v.

Determining this coefficient required the well-known dependence R

Determining this coefficient required the well-known dependence Rrsλ~bbλaλ+bbλ

( Gordon & Morel 1983) and formula  (7) (derived in this work) describing the relationship between the light absorption coefficient a and the reflectance Rrs to be taken into consideration. It was additionally assumed that the scattering coefficient b is associated with the backscattering coefficient bb and the SPM concentration, the latter being highly correlated with ca Rrs(800 nm) (see Ficek et al. 2011). The relationship see more obtained is shown in Figure 9 and expressed by formula (8): equation(8) b440nm=15.59×Rrs800nm0.282×100.554logx2−1.380logx+0.161, where x = Rrs(490 nm)/Rrs(665 nm). Having established the empirical relationships between the absorption and scattering of light of particular wavelengths, we can determine approximate values of these selected inherent optical properties of Type I and III lake waters for any wavelength from the PAR range from measurements of remote reflectance spectra Rrs  (λ). We obtain the spectrum of the coefficient of light absorption by SPM by first determining the value of this coefficient for λ = 440 nm from equation (6)

and then using equation (3) and Table 3 to determine its value for other wavelengths. The spectrum of light absorption by CDOM is also determined in two stages. In the first stage we determine a  CDOM(440 nm) from equation (5); SAHA HDAC price then, using the relationship a  CDOM(λ) = a  CDOM(440 nm) exp[−S¯(λ−440nm)] we obtain the value of this coefficient Progesterone for waves of different lengths. The parameter S¯ appearing in this equation varies from 0.015 to 0.018 nm−1 and depends on the type of lake (see the caption to Figure 2). We obtain the total absorption spectrum by summing the coefficients of absorption by SPM ap(λ), dissolved substances aCDOM(λ) and the water itself aw(λ). Values of the last-mentioned component can be found in e.g. Woźniak & Dera (2007). We obtain the spectrum of the light scattering coefficient by first determining this factor for light of wavelength 440 nm,

and then its values for other wavelengths using equation (4). In these calculations we could also take the values for water molecules into account. But since scattering by water is negligible compared to that by SPM (see e.g. Haltrin 2006), it makes no significant difference to the final result of the calculations. The great complexity of the results presented in this work precludes the precise definition of the errors of measurements and analyses, even though we took the greatest care with the measurement procedures stated in the Introduction. These procedures and the measuring apparatus they require govern the accuracy of these studies, in which we estimated the measurement errors of different magnitudes to be from 3 to 10% and more, e.g. with respect to the remote sensing reflectance Rrs and the scattering coefficients.

In order to quantify PO4 production and removal in the individual

In order to quantify PO4 production and removal in the individual sub-layers (Table 1), a mass balance was applied describing the temporal change in the PO4 concentrations for each time interval and in each SL (Table 1) by vertical mixing with the neighbouring SL and by PO4 production/removal, QPO4 (eq. (1)). QPO4 thus includes all PO4 related processes in the water column and PO4 exchange at the sediment surface of the individual SL. equation(1) ΔPO4Δt=An−1Fn−1+AnFn+1Vn+QPO4,where n – SL number; The PO4 gradients were obtained Selleckchem Roscovitine from the difference

between the mean PO4 concentrations in neighbouring SLs and division by the distance between the centres of the corresponding SLs. On the basis of these experimentally derived quantities, eq. (1) enables QPO4 to be calculated, which represents the PO4 release by organic matter mineralization and the Fe-P dissolution/precipitation for each time interval and each SL. The accumulation of QPO4 over time (accQPO4) for each SL and for the entire basin below 150 m were determined by the successive addition of QPO4 values (Table 4). A rapid increase in accQPO4 in SL1 occurred

during the AZD6244 research buy first year of the stagnation. This is a consequence of the fact that the bottom water had already become anoxic during the first time interval of the stagnation period (Figure 3b) and that previously deposited Fe-P was redissolved by reduction of Fe3+ to Fe2+. In SL2 to SL3 the

accQPO4 increase occurred during later stages of the Sulfite dehydrogenase stagnation, coinciding with the upward migration of the redoxcline. The dependence of varying PO4 release rates on the redox conditions in the different SL is also reflected in the relationship between the accQPO4 and the accumulated carbon mineralization, accQCT (Figure 4). During the first phase of the stagnation, accQPO4 in SL1 and SL2 increased almost linearly with accQCT (Figures 4a, 4b). The slopes of the regression lines correspond to a C/P ratio of 40 and 45 respectively, and are thus far below the Redfield ratio of 106, which is assumed to characterize the organic matter composition. The decrease in the C/P ratio of the mineralization products may be due to the fact that the microbial decomposition of organic matter does not occur synchronously for the different elements and that organic P is the first to be mineralized. However, our observations refer to a time span of more than two years, and in the long term the elemental ratios of the mineralization products will correspond to the composition of the organic matter. Therefore, the low C/P ratios derived from the relationship between accQPO4 and accQCT during the early development of anoxic conditions in SL1 and SL2 are attributed to the dissolution of Fe-P.

russelii venom ( Fig  4B) The VAV assay will only detect bound a

russelii venom ( Fig. 4B). The VAV assay will only detect bound antivenom because the microplate is coated with an anti-snake venom antibody which binds the venom, and detection is with labelled anti-horse antibodies which bind equine antivenom (Fig. 1B). In vitro this provides

a measure of antivenom-venom binding for increasing concentrations of antivenom. The curve increases with increasing binding of antivenom (antibodies) to free venom until a point where increasing amounts of antivenom (antibodies) prevent the venom-antivenom complex binding to the microplate, because there are no longer any free antibody binding sites (epitopes) on the venom molecules ( Fig. 1B). The concentration of antivenom at which the VAV peak occurs is the concentration

at which every venom component, on average, must be attached to at least one antivenom molecule. This gives us a new measure SP600125 datasheet of antivenom efficacy. In addition, it provides an assay to measure bound venom in vivo and to determine if venom detected post-antivenom selleck chemical using the free venom assay is bound. At low concentrations of antivenom, the antivenom binds to the venom molecules in a one to one ratio to form VAV complexes. The VAV complex still has free binding sites on the venom molecule which allows further antivenom to bind with increasing concentrations to form V(AV)2, V(AV)3, … V(AV)n where n is the maximum number of antibody binding sites on a venom molecule. However, at least one binding site must remain free and exposed for the venom-antivenom complex to bind to the anti-snake venom antibodies on the microplate. In other words, V(AV)n cannot bind to the microplate ( Fig. 1B). This is the reason that initially as the antivenom concentration increases and the proportion of antivenom in the mixture increases, there is an increasing amount of VAV detected. The maximum or VAV

peak occurs when further binding of antivenom results in decreasing free antibody binding sites on venom molecules, resulting in decreasing binding to the microplate. Rather simplistically, the VAV peak is when there is on average of mainly V(AV)n − 1 in the antivenom/venom mixture and this means that there is at least one antivenom molecule is attached to each venom molecule. This is a rather simplistic description of what occurs the because venom consists of different toxins and each toxin is likely to have a different number of epitopes (antibody binding sites) depending on toxin size and antigenicity. In addition, antivenom is a polyclonal antibody mixture with antibodies to different toxins and different toxin epitopes with varying affinities. However, the stepwise formation of V(AV)k complexes (where 1 < k < n) applies to the behaviour of the whole population of venom (toxins) and antivenom molecules, regardless of the fact the venoms contain dozens of different proteins, each with several epitopes, and that the antivenoms are themselves polyclonal.

The Staudinger–Bertozzi ligation between an azide and a triarylph

The Staudinger–Bertozzi ligation between an azide and a triarylphosphine moiety ( Figure 1c) and alternatively the copper-catalysed [3 + 2] cycloaddition between an azide and an alkyne group [ 18] ( Figure 1a, also referred to as ‘click reaction’) are the most popular types of bioorthogonal reactions that can be used in vitro as well as in vivo because of their superior selectivity and biocompatibility [ 19]. Recently, copper-free click chemistry

has emerged that relies on strain-promoted cycloaddition making the reaction suitable for in vivo applications and work with highly sensitive protein learn more samples ( Figure 1b) [ 20]. In parallel, UAAs have been developed that can serve as reactant in a copper-free cycloaddition [ 21]. Plass et al. demonstrated that this approach leads to fluorescently labelled proteins suitable for single molecule studies [ 22•]. The Staudinger–Bertozzi ligation and cycloaddition can also be employed if the UAA carries the alkyne and the fluorophore is modified with the azide group, which is an attractive option because ERK inhibitor azides are often reduction-sensitive and labile during biochemical purification [ 23]. Many single molecule studies are designed to address the conformational flexibility of proteins in solution, or the structural organization either of

single proteins or protein complexes. Donor and acceptor probes for an intermolecular FRET system can be engineered into individual subunits that constitute a complex molecular Quisqualic acid machine or a heteromeric complex following standard coupling chemistries. In contrast, site-specific incorporation of donor and acceptor fluorophore in a single polypeptide is challenging and requires multiple unique coupling sites for differential labelling. A combination of the described coupling techniques often lead to successful dual labelling. For example, the N-terminus of a protein can be labelled via an amine-reactive group and a single cysteine with a thiol-reactive group.

Likewise, the modification of a single cysteine and an unnatural amino acid in a single protein chain is a sensible approach for an intramolecular site-specific labelling [23]. The incorporation of multiple [24] and two different UAAs [25] has been described, which opens the door for stochastic and site-specific labelling of proteins via the reactive side-chains of the UAAs. In some cases the site-specific positioning of the donor or acceptor probe is not mandatory to analyse the conformational flexibility or folding of a protein. Here, labelling via identical reactive moieties (e.g. 2 cysteines or 2 UAAs) is practicable [26]. Recently, advanced labelling strategies have been utilized to allow even triple-colour labelling within a single protein (stochastical labelling of two cysteines and one UAA) [27].

Different types of fat depots exhibit different properties, and t

Different types of fat depots exhibit different properties, and their anatomic location is an important risk factor for cardiovascular diseases, metabolic disorders, and other conditions [91]. The current evidence demonstrates biological and genetic differences between adipose tissues depending on their anatomic location. Specifically, the upper body/visceral fat distribution in obesity is closely associated with metabolic complications [87]. Intra-abdominal tissues are metabolically and functionally different from subcutaneous adipose tissue (SAT) and exhibit a higher

capillary density, sympathetic PFT�� mouse innervation and adrenergic receptor expression [55]. Intra-abdominal tissues release more free fatty acids, glycerol and endocrine hormones into the portal venous system and have direct access to the liver, whereas those derived from SAT are secreted into the systemic circulation [55] and [91]. In our

study, the circulating levels of HDL and VLDL were not significantly altered by the hypercaloric diet and/or chronic stress. The animals subjected to the hypercaloric diet model demonstrated an increase in LDL cholesterol and total cholesterol, similar to the findings in earlier studies using the cafeteria diet [8] and [51]. Studies in humans and animals subjected to chronic stress have been linked to increased levels of serum cholesterol [29] and [85], and the results of our six-week restraint stress Interleukin-2 receptor protocol confirms the association between stress and cholesterol. The high leptin levels found with the exposure to the high-calorie diet may be related to an increase in fatty tissues, especially visceral fat accumulation, because leptin is synthesized mainly in these tissues [19]. Adipose tissue secretes

signaling molecules that play a central role in weight regulation and metabolic function [108]. Leptin is an adipocyte hormone that signals the status of energy stores in the peripheral tissues to the brain [33], affecting feeding behavior and metabolism [50]. This peptide plays an important role in the regulation of food intake, energy consumption, glucose metabolism, the cardiovascular system, the immune system, and the secretion of insulin and the pituitary hormone [2]. In addition, growing evidence suggests that leptin may contribute to the development of cardiac dysfunction, and chronic hyperleptinemia may increase the risk of cardiac disorders [54]. The circulating leptin levels are proportional to the total amount of the adipose tissue mass, and leptin binds to receptors within specific hypothalamic nuclei to regulate energy balance by reducing appetite [114]. Leptin acts in association with other neuropeptides, such as NPY, which increases food consumption and decreases energy expenditure [3].

(11), one must use multi-solute osmometric data Alternatively, i

(11), one must use multi-solute osmometric data. Alternatively, it is possible to develop mixing rules to avoid this requirement. Thermodynamic mixing rules are theoretical relations that predict the values of

cross-coefficients using the values of individual solute coefficients. Elliott et al. [14] and [15] have proposed the following second and third order mixing rules for the molality- and mole fraction-based osmotic virial equations equation(12) Bij=Bii+Bjj2, equation(13) Cijk=(CiiiCjjjCkkk)1/3,Cijk=(CiiiCjjjCkkk)1/3, equation(14) Bij∗=Bii∗+Bjj∗2, equation(15) Cijk∗=(Ciii∗Cjjj∗Ckkk∗)1/3. Applying these mixing rules yields the molality- and mole fraction-based Elliott et al. multi-solute osmotic virial equations equation(16) π=∑i=2rmi+∑i=2r∑j=2r(Bii+Bjj)2mimj+∑i=2r∑j=2r∑k=2r(CiiiCjjjCkkk)1/3mimjmk+…, check details equation(17) π̃=∑i=2rxi+∑i=2r∑j=2r(Bii∗+Bjj∗)2xixj+∑i=2r∑j=2r∑k=2r(Ciii∗Cjjj∗Ckkk∗)1/3xixjxk+…,or, in the presence of electrolytes equation(18) π=∑i=2rkimi+∑i=2r∑j=2r(Bii+Bjj)2kimikjmj+∑i=2r∑j=2r∑k=2r(CiiiCjjjCkkk)1/3kimikjmjkkmk+…,

equation(19) π̃=∑i=2rki∗xi+∑i=2r∑j=2r(Bii∗+Bjj∗)2ki∗xikj∗xj+∑i=2r∑j=2r∑k=2r(Ciii∗Cjjj∗Ckkk∗)1/3ki∗xikj∗xjkk∗xk+…,where r is the number of solutes present. These equations have been found to provide accurate predictions of osmolality in a wide variety of non-ideal multi-solute solutions [3], [7], [14], [43], [54], [55] and [56]. It should, however, be noted that although Eqs. (16) (or (18)) and (17) (or (19)) are similar in form and were derived using similar methods, they were obtained Stem Cell Compound Library nmr using different Ureohydrolase starting assumptions (regarding concentration units i.e. Landau and Lifshitz solution theory versus regular solution theory). They are not equivalent, will not necessarily yield the same predictions for a given solution, and it is not possible to directly convert the coefficients of one to those of the other. That is, Eqs. (16) and (17) are effectively separate and distinct solution theories. The Kleinhans and Mazur

freezing point summation model is similar to the osmotic virial equation in that it also models the osmolality (or, in this case, freezing point depression directly) as being a polynomial function in terms of solute concentration [38]. For a binary aqueous solution containing a single solute i, this model represents the freezing point depression as [38] equation(20) ΔTm=Tmo-Tm=-(C1imi+C2imi2+C3imi3),where C1i, C2i, and C3i are empirical solute-specific coefficients. Like the osmotic virial coefficients, the coefficients in Eq. (20) can be obtained by fitting to single-solute solution osmometric data. For multi-solute solutions, Kleinhans and Mazur proposed summing the freezing point depression equations of all solutes present, i.e. [38] equation(21) ΔTm=Tmo-Tm=-∑i=2r(C1imi+C2imi2+C3imi3),where the number of solutes present is (r − 1).

After injection of AAV-hSNCA, a dose dependent level of expressio

After injection of AAV-hSNCA, a dose dependent level of expression of hSNCA-IR was observed in soma and fibers in ipsilateral SN and ventral tegmental area (VTA) and in fibers in ipsilateral striatum (ST) (Fig. 1a). A dose dependent significant loss of TH-IR neurons in these rats was also observed (Table S1). Reduced contralateral forelimb use was observed at the lowest dose (0.6×1010 vg) of AAV-hSNCA (Fig. 1b). When different ratios of mir30-SNCA were examined, hSNCA-IR was found to be reduced in rats that received GSK2118436 price the lowest dose of mir30-SNCA (1:3 ratio), although hSNCA expression was still detectable

in cell bodies in the SN and in fibers in both SN and ST. At the highest dose of mir30-SNCA (1:55 ratio), hSNCA-IR was not detected in Obeticholic Acid supplier ST and only rare hSNCA-IR cells or fibers were detected in the SN, although a diffuse background of hSNCA-IR was observed in the SN (Fig. 1a). A statistically significant protection from the AAV-hSNCA-induced deficit in contralateral forelimb use

was observed at a hSNCA to mir30-SNCA ratio of 1:55, but not at a ratio of 1:29 or 1:3 in this pilot study with n=3 (contra: F5,12=3.8, p=0.0275; ipsi: F5,12=6.2, p=0.0046; Fig. 1b). However, no significant differences in numbers of TH-IR neurons between control and injected SN at any ratio of AAV-hSNCA to AAV-mir30-SNCA were found ( Table S1). Because TH neuron counts do not differ between injected and control SN at any ratio of hSNCA to mir30-SNCA ( Table S1), the optimal ratio was determined by the efficiency of hSNCA-IR silencing and the protection against the deficit in forelimb motor behavior, which differs among hSNCA to mir30-SNCA ratios. Based on the results of this pilot study, the subsequent efficacy experiments were carried out using the 1:55 hSNCA to mir30-SNCA ratio. To confirm that rats in each treatment

group were transduced with the vectors to the same extent, DNA levels of hSNCA and turbo GFP (representing either mir30-SNCA or a control, non-silencing, Janus kinase (JAK) silencing vector containing a scrambled target sequence (NS)) were determined by quantitative real time QPCR at 10d (Fig. S2a and b) and 2 months (Fig. 2a) survival in the ventral midbrain. All groups received similar levels of hSNCA vector DNA (Fig. S2b and Fig. 2a). Groups injected with AAV-hSNCA and AAV-mir30-SNCA, or AAV-hSNCA and AAV-NS, received similar levels of silencing vector DNA, as measured by turbo GFP (Fig. S2a). hSNCA DNA also was detected in the ST of rats that received AAV-hSNCA alone, but not in ST from other treatment groups (Fig. S3). hSNCA expression levels were examined at the mRNA level in the ventral midbrain and ST at 10d (Fig. S2c) and 2 months (Fig. 2b and c) using qRT-PCR to confirm hSNCA expression and silencing.