It could allow the device possess an internal standard without th

It could allow the device possess an internal standard without the necessity to calibrate daily based on the SMBG reading.Figure 1.Illustration of the Sencil? system for glucose sensing. (a) Similarity of shape and size between Sencil? and human hair with attached follicle (white bar = 100 ��m). (b) Sensor components and relationships promotion info to tissue in vivo. (c) …Like most of the minimal and noninvasive designs for continuously in vivo glucose monitoring [12�C15], Sencil? measures glucose in the interstitial fluid (ISF) compartment of skin to estimate plasma glucose. Although the concentration of the plasma glucose is the clinical index in identifying and managing diabetes, the ISF glucose concentration has a closer correlation to the development of complications on the peripheral tissues through the regional cell-level activities [16].

The ISF glucose and plasma glucose are Inhibitors,Modulators,Libraries expected to have different steady-state concentrations Inhibitors,Modulators,Libraries and kinetic responses under conditions with all the physiological barriers [17,18], but the detection is the main objective due to its ease of use and safe accessibility. The estimation of plasma glucose from ISF glucose introduces discrepancy from the sensor detection Inhibitors,Modulators,Libraries and time delay of the concentration gradient between the blood pool and ISF through the capillary vessel wall. The concentration gradient between ISF and plasma can be approximated by the two-compartment model [17,19,20]. The main challenge of the detection accuracy is on the design to minimize the sensor delay and the establishment of a valid and efficient in vivo calibration [12,13,16,20,21].

The aim of this paper was to study the acute response of Sencil? for glucose detection in a clinical environment and address the follow questions: (1) how long does the sensor settled in tissue after implantation Inhibitors,Modulators,Libraries for short-term applications, and (2) how accurate is the measurement from acute response under in vitro calibration, and (3) how accurate is the acute response to estimate plasma glucose from the ISF detection? The information is crucial to establish foundation for further in vivo testing in elaborating the sensor accuracy of full working range through glucose clamp experiments, and chronic in vivo performance.2.?Experimental Section2.1. Canine SubjectsFour clinical healthy dogs scheduled for ovariohysterectomy were selected for the study.

All dogs had Entinostat a record of normal glycemia when admitted. Physical examination of each dog was performed cell assay by a board-certificated veterinary surgeon or veterinary resident to confirm the subject��s health. The hematological profile (WBC, RBC, Hb., Hct., MCV, MCH, MCHC, Thromob., Parasite) and bloodchemistry profile (AST/STOG, ALT/SGPT, LDH, CK, Alk. P��tase, Glucose, BUN, Creatinine, T. protein, Albumin, Calcium, Phosphorous) were verified within normal limits by Hitachi 7050 prior the induction of anesthesia.

The responsivity is defined as the ratio of the output voltage of

The responsivity is defined as the ratio of the output voltage of the sensor to the incident power. The authors designed a web-shaped top electrode sellectchem which not only improves the heat absorption but also the heat uniformity throughout the ZnO layer. The responsivity Inhibitors,Modulators,Libraries of the sensor may be improved by opening the windows so that the ZnO layer can come into direct contact with the heat source. On the other hand, the contact windows may reduce the top-electrode area and disperse the electrode and this electrode area reduction and dispersion may degrade the responsivity of the sensor. Thus, in the layout design of the top electrode, both the size of the ZnO layer contact window and the dispersion of the top electrodes must be considered. This work designs a web-type top electrode.

The outer regions of the web type possess large ZnO layer contact windows, whereas the inner regions possess dense Inhibitors,Modulators,Libraries top electrodes.Figure 1.The senor structures and dimensions in ��m.3.?Preparation of Inkjet SolutionsThe ZnO inkjet solution is prepared by the sol-gel method, as shown in Figure 2(a). It is synthesized by dissolving Inhibitors,Modulators,Libraries 0.4 mol of zinc acetate into 120 mL ethylene glycol and heating at 140 ��C for 30 min, which results in a transparent solution. However, the solution will settle after cooling at room temperature for about 30 minutes. Therefore 280 mL ethanol are add into the solution which is sonicated for 30 minutes until the sediment is completely dissolved in ethanol. Filtration of the solution affords a clear and homogeneous ZnO solution.

Its molal concentration is 1 M, its viscosity is 14 CPS, its surface tension is 30 dynes/cm, and its pH value is 6. The inkjet material of the top electrode layer is a commercial alcohol-based nano-silver ink provided by Cabot Conductive Ink (CCI-300). Inhibitors,Modulators,Libraries Its viscosity and surface tension at room temperature are about 11�C15 CPS and 30�C33 mN/m respectively, the silver solids loading is about 19�C21 wt%, and its density is about 19�C21 g/mL.Figure 2.(a) The preparation process of ZnO inkjet solution; (b) the fabrication process flow of the flexible pyroelectric sensor.4.?Fabrication ProcessThe overall process flow is shown in Figure 2(b) while the parameters are detailed in Table 1. Firstly, the flexible aluminum sheet is cleaned with ethanol and then blow-dried with nitrogen.

Then atmospheric Entinostat plasma is used to make the surface of the aluminum sheet more hydrophilic, to improve the adhesion of the ZnO solution on the aluminum sheet. The aluminum sheet is placed onto the stage of the plasma equipment. The plasma is sprayed by a nozzle whose orifice diameter is 4 mm. The orifice of the plasma spray nozzle is at a distance of 25 mm from the aluminum sheet. Figure 3 shows that the contact angle changes from 78.49�� to 18.67�� after the plasma modification.Figure 3.The contact angle of the aluminum sheet before and after method plasma modification.Table 1.

3 ?Results and DiscussionsThe narrow-band gap semiconducting poly

3.?Results and DiscussionsThe narrow-band gap semiconducting polymer, PCPDTBT (Scheme 1a), has broad band absorption at the wavelengths �� = 300�C950 nm, with a cutoff at �� �� 1,000 nm (Figure 1), high photoconductivity. quality control Good solar cell performance is obtained by blending it with PC70BM [12].Figure 1.Absorption spectra (left) of pristine PCPDTBT and PCPDTBT:PC70BM thin films, and EQE (right) from the device with the following structure: ITO/PEDOT:PSS/PCPDTBT:PC70BM/Al. The EQE was measured at zero bias.The photo-active layer in our PPDs comprises a phase separated blend of PCPDTBT and PC70BM. The two components form interpenetrating Inhibitors,Modulators,Libraries donor/acceptor networks in the bulk heretojunction (BHJ) structure.

Three different PPD architectures were investigated:PPD A: ITO/PEDOT:PSS/PCPDTBT: PC70BM/Al;PPD B: ITO/PEDOT:PSS/PCPDTBT: PC70BM/C60/Al Inhibitors,Modulators,Libraries andPPD C: ITO/PEDOT:PSS/PS-TPD-PFCB/PCPDTBT: PC70BM/C60/Al.These three device architectures are shown in Scheme 1b (the thickness of each layer is indicated). The energy level diagram in Scheme 1c shows the lowest unoccupied molecular orbital (LUMO) and the highest occupied molecular orbital (HOMO) of PCPDTBT, PC70BM, C60 and PS-TPD-PFCB. The workfunctions of PEDOT:PSS and Al are also shown in Scheme 1c. The difference between the LUMOs of PCPDTBT and PC70BM is ~0.8 eV, which ensures photoinduced charge transfer and charge separation in the PCPDTBT:PC70BM BHJ structure [14].The current-density voltage (J�CV) characteristics measured in the dark and under illumination (�� = 800 nm) with light intensity of 0.22 mW/cm2 are shown in Figure 2.

All PPDs (A, B and C) Inhibitors,Modulators,Libraries show good rectification ratios in the dark, 104 at ��1 V, indicating the formation of good diodes. The dark currents observed from PPD B are more than 2 orders of magnitude smaller than that from PPD A; the dark currents observed from PPD C are more than 10 times smaller than that from PPD B. These results indicate that the thin C60 and PS-TPD-PFCB buffer layers are important for minimizing the dark currents generated withinfrom the PCPDTBT:PCBM PC70BM BHJ structure.Figure 2.Current-density-voltage characteristics of polymer photodetectors measured in the dark (Jd) Inhibitors,Modulators,Libraries and under light (Jph); �� = 800nm with intensity of 0.

22 mW/cm2For PPDs A, B and C, the current density (J)�Cvoltage (V) relationship can AV-951 be described by the standard diode equation [15]:J=?J0exp[q(V+JRS)nKBT]?1?V+JRSRSE(1)whereJ0=A*T2exp(?EPFKBT)(2)and A* = 4��qm*KB2/h3, J0 is the saturation current density, q is the electron charge V is the voltage, selleck compound n is the ideality factor, KB is the Boltzman constant, T is the absolute temperature RS is the series resistance, RSH is the shunt resistance, m* is the effective electron mass, h is Planck��s constant, A* is Richardson��s constant and EPF is the energy difference between the HOMO of PCPDTBT and the LUMO of PC70BM (~0.6 eV).As described above, a high dark current is expected from PPD A because EPF (~0.6 eV) is relatively small.

The choice of a constant current source as the sensor bridge powe

The choice of a constant current source as the sensor bridge power supply was based on previous works that show a remarkable reduction in the temperature coefficient of the bridge sensitivity [15�C18].Figure 1.Variables definition in the Wheatstone bridge before compensation.If a current sensor is considered, its non-compensated output, vo,nc could be given by:vo,nc (t)=S(t)?i+vo,off(1)being somehow Inhibitors,Modulators,Libraries i the current to be sensed (measured in amps), vo,off the sensor output at zero input current (in mV), t the temperature (in ��C) and S(t), the sensor sensitivity (in mV/A). The output offset could not be considered if this has been compensated previously by calibration. As equation (1) shows, a change in temperature will produce a change in the sensor sensitivity generating an output sensor variation, but without any change in the current i to be measured.

Let S����SvB,nc be the sensor sensitivity normalized to bridge voltage, vB,nc. If the sensor bridge is driven by a constant current iB,nc the voltage drop across it will be:vB,nc (t)=iB,nc?RB (t)=no?iref?RB (t)(2)where RB is the equivalent bridge resistance. The constant current Inhibitors,Modulators,Libraries iB,nc in equation (2) is supplied by the GIC circuit and it is equal to the product of the constant no times the GIC input reference current iref, [13,14]. As a consequence, the non-compensated sensor bridge output vo,nc will be Inhibitors,Modulators,Libraries given by:vo,nc (t)=S��(t)?vB,nc (t)?i=S��(t)?iB,nc?RB (t)?i=S��(t)?no?iref?RB (t)?t(3)Equation (3) shows that the temperature drift of the sensor output will be provided by both normalized sensitivity and bridge equivalent resistance temperature dependences.

It is assumed that before Inhibitors,Modulators,Libraries compensation iref is a good reference current and it is not affected by the temperature.The main purpose of the compensation method is to place enough temperature dependence in iref to compensate the drift in vo,nc(t) caused by (t) and RB(t). As a result the compensated sensor output, vo,c(t) will have no temperature dependence:dvo,c (t)dt=0.(4)Figure 2 depicts how a practical GIC circuit supplies to the bridge sensor Anacetrapib a current iB proportional to a 100 ��A reference current iref. The gain factor no depends on GIC resistances R1 to R4, a proper replacement of one of them by a series association of a temperature sensor Rs(t) and a constant resistance R will lead to accomplish equation (4). The final objective of the compensation method will be to find a properly selected R resistance value.Figure 2.Driving the MR current sensor by a constant current source using a GIC circuit.

2 ?Related WorkIn-network aggregation query processing methods us

2.?Related WorkIn-network aggregation query processing methods used in sensor networks such as TAG [13] only send the aggregated results inside the sensor network so as to reduce the number of messages. It enables one to increase sensor network lifetime by reducing energy consumption. Some special aggregation quality control queries such as SUM, MIN and MAX, are more effective in saving energy since they only aggregate a single aggregation value instead of all possible data. Also, DCSs process queries in a sensor network, and only send query results to a server. However, skyline queries exclude values only when data are dominated by other data, so it is difficult to find complete query results without inspecting all the data. Therefore, to process skyline queries in sensor network, it is important to establish criteria to exclude unnecessary data from the results.
Several skyline query processing methods such as [8�C11] have been proposed. Most of them focus on designing filters to exclude as much unnecessary data as possible. Huang et al. [8] dealt with a constrained skyline query problem on MANETs by devising a single point filter-based evaluation algorithm that is easily extended to sensor networks. Xin et al. [10] proposed two filter-based algorithms. One is the single point filter-based algorithm TF and another is the grid filter-based algorithm GI. The TF algorithm chooses the point that dominates the maximum number of points as the filter, assuming that the data distribution density is given beforehand, while the GI algorithm exploits the grid partition of data space and generates a grid filter.
Liang et al. [9] proposed a new filter-based algorithm which consists of multiple rather than single points as the filter, whereby each sensor sends part of its Brefeldin_A local skyline points chosen by a greedy algorithm to its parent and the root broadcasts the received points as the global certificate obtained through in-network aggregation. The points that cannot pass through the certificate will be filtered out from transmission. Xin et al. [10] proposed a density function based skyline query processing algorithm. It assumes that the density function of data is known beforehand. However, in real applications it is hard to find out the density function beforehand. Chen et al. [11] proposed two algorithms for evaluating skyline queries are devised, which find the skyline points progressively. It partitions the dataset this research into disjoint subsets, followed by returning the skyline points through examining each subsequent subset progressively, using some found skyline points so far as a filter to filter out those unlikely skyline points in the currently processing subset from transmission.3.?Proposed Skyline Query Processing Method Based on DCS3.1.

4 2 Effect of Thickness of Silicon Membrane on CharacteristicsWh

4.2. Effect of Thickness of Silicon Membrane on CharacteristicsWhen the test environment temperature is 22 ��C, and relative humidity is 15% RH, calibration experiments of the nc-Si/c-Si heterojunction MOSFETs pressure sensor, which includes the nc-Si/c-Si heterojunction MOSFETs with L:W ratio 2:1 and square silicon membrane thickness 75 ��m and 45 ��m, respectively, are done using a Mensor PCS400 pressure calibration systems, HP34401A multimeter and BJ1790B power supply. The additional pressure range of the sensor with silicon membrane thickness 75 ��m, are from 0 to 160 kPa, the additional pressure range of the sensor with silicon membrane thickness 45 ��m, are from 0 to 20 kPa.When the supply voltage VDD is 1.0 V, 1.5 V and 3.
0 V, respectively, Figure 7 shows the input-output characteristic experimental curves of the pressure sensor with c
Digital surface models (DSMs) depict the elevation of surfaces visible from the sensor, such as building tops, tree tops, or unoccluded bare ground [1]. Today, specialists from a large range of disciplines are making use of such models. For example, in forest science DSMs are used to model the canopy surface of forests and analyse its vertical structure [2,3]. Thus, DSMs enable the 3D modelling of the forest canopy, which allows assessments of tree cover [4], estimation of crown structure [5], measurements of canopy heights [6,7] and the detection of canopy gaps [8], including the monitoring of these properties over time. For all the mentioned applications it is crucial to know the accuracy of the input data for the DSM generation as they influence the usability and reliability of the generated results.
In general the preferred data source option for digital surface modelling Brefeldin_A is a balance between the desired accuracy of the DSM, the costs involved in its creation and the availability of the input data [9]. Remotely sensed data are suitable for DSM generation [10�C12] and can be acquired on different platforms (e.g., satellite, airplane) [13]. There selleck Romidepsin are two main types of remote sensing: active systems such as laser or radar, and passive systems such as optical images. In the last two decades airborne laser scanning (ALS) has taken an upturn due to its operability [14]. In forest research airborne laser scanning is often the method of choice, because in forested areas the laser can penetrate to the ground [15]. Airborne laser scanning is costly, however, which limits repeated measurements for the monitoring of changes in the forest.

Historically, soil sampling has been a technique utilized for det

Historically, soil sampling has been a technique utilized for determining N rate recommendations. However, the reliability of soil N tests is often questionable due to the challenges associated with the dynamic nature of N in the soil, particularly selleck in the humid alluvial soils of Louisiana [4]. Therefore, crop yield monitoring has become an important aspect of many N management schemes. A common method of incorporating crop yield into N rate recommendations is through the use of yield goals, specifically in cereal crop production [5]. A yield goal is defined as yield per unit area we might expect to achieve given adequate growing conditions and it is determined by taking a recent five year average plus 30% to account for potentially above average growing conditions.
Johnson [6] and Schmitt [7] reported the importance of yield goal for N recommendations in winter wheat (Triticum aestivum) and corn (Zea mays), respectively. They indicated that 33 kg?N?ha?1 for every 1 Mg of wheat and 20 kg?N?ha?1 for every 1 Mg of corn would be required. However, setting yield goals at unrealistic levels can lead to under-or over-estimation of N rate recommendations. This is envisaged especially when N recommendations based on yield goals across large scale spatial variability do not take into account temporal variability, due to environmental growing conditions, nor within field spatial variability.Due to limitations associated with utilizing yield goals, research in other crops such as wheat and corn has focused on in-season crop monitoring as an approach to N management.
However, limited research is available for sugarcane production, particularly Louisiana sugarcane production. Additionally, research that is available has produced negative or inconclusive results [8,9]. Wiedenfeld [9] reported that chlorophyll meters were not a viable tool for predicting N recommendations for sugarcane grown in the Lower Rio Grande Valley. This lack of viability is partially due to the chlorophyll meter relying solely on plant tissue N concentrations and N accumulation in sugarcane occurred later in the season compared to when measurements were taken.Many plant indices based on canopy spectral reflectance have shown the ability to accurately estimate crop physiological properties, including plant biomass and crop yield [10�C12].
Brefeldin_A The NDVI value, which is a vegetative index that compares reflectance at the red and near infrared region, has also shown the ability to determine yield potential (YP) [13�C15]. Yield potential differs from yield goal because it is a function of the environmental conditions of the current growing season and is defined more info as achievable yield with no additional N fertilizer [11]. Teal [14] reported that there was a strong relationship between NDVI and grain yield in corn using an exponential model.

5 mL of 0 01 M HAuCl4?3H2O (Aldrich, St Louis, MO, USA), 0 5 mL

5 mL of 0.01 M HAuCl4?3H2O (Aldrich, St. Louis, MO, USA), 0.5 mL of 0.01 M trisodium citrate (WAKO Chemical, Osaka, Japan). The substrate sample was kept for 30 min in the solution to facilitate selleck chem Rucaparib gold ions adsorption onto the substrate surface and after that a 0.5 mL of ice-cold 0.1 M NaBH4 (WAKO Chemical) was then added to the solution to induce the formation of gold nanoseeds on the surface. The addition of NaBH4 into the solution changed the solution appearance from colorless to red, an indication of nanoseed formation. The substrate was further kept in the solution for another 1 h. After that, the sample was taken out, rinsed with pure water and dried with a flow of nitrogen gas. Using this approach, gold nanoseeds with sizes ranging from 2 to 5 nm could be obtained on the surface.
The nanoseeds on the substrate surface were then grown by immersing the substrate into a solution that contains 20 mL of 0.1 M CTAB (Amresco, Solon, OH, USA), 0.1 mL of 0.1 M ascorbic acid (WAKO Chemical) and 0.5 mL of 0.01 M HAuCl4?3H2O (Aldrich). A reddish color on the substrate may be observed within seconds after the substrate immersion into this solution indicating the formation of the gold nanoparticles. Gold nanoparticles with different size could be realized on the surface by varying the immersion time in the solution. Next, the substrate was removed and then rinsed thoroughly with a copious amount of pure water and dried with a stream of nitrogen gas. Finally, the sample was annealed at 200 ��C in air for 1 h to remove any organic residues on the surface.2.1.2.
Nanorod PreparationThe gold nanorods in solution were prepared following the technique developed by Nikoobakht and El-Sayed [31] with several modifications [32]. In this technique, two solutions were prepared for the growth of nanorods, namely seed solution and growth solution. Firstly, gold seed solution was prepared by adding 0.25 mL of 0.005 M HAuCl4?3H2O into 5 mL of 0.2 M CTAB and shaken for 1 min to mix the solution. Next, fresh
Ambient Intelligence (AmI) is a vision of smart environments that are reactive to people and able to make our actions safer, more efficient, more informed, more comfortable or simply more enticing. In this vision our environments will be embedded with different types of sensing systems, pervasive devices, and networks that can perceive and react to people [1].
Ambient Intelligence has been described by researchers in different Brefeldin_A ways, but two characteristics that an AmI system must possess are to be sensitive and responsive [2]. Through sensors, AmI systems gather kinase inhibitor Tubacin information about the environment, process that information in some manner and finally through actuators modify the environment in a form that will benefit users in the environment [3].A control system is a device or set of devices to manage, command, direct or regulate the behavior of other devices or systems [4].

y of inflamma tion and neutrophil elastase activity in the gastri

y of inflamma tion and neutrophil elastase activity in the gastric mucosa of H. pylori infected indi viduals and the bronchoalveolar lavage fluid of Pseudomonas infected subjects. Progranulin, also known as acrogranin, proepithelin and PC cell derived growth factor, is a 68 kDa glycopro tein secreted by many epithelial and immune cells. The full length protein is subsequently modified by lim ited proteolysis leading to the generation of 6 25 kDa fragments called granulins. Pathophysiologically, Progranulin has drawn a lot of attention in the last years since it has been identified that mutations of the corresponding granulin gene are causally linked to the development of frontotemporal dementia. Indivi duals with these mutations exhibit tau negative, but ubi quitin positive, inclusions in their brain that eventually cause frontotemporal dementia.

Both the precursor and the degraded forms med iate different cellular effects in a variety of pathophysio logical conditions such as inflammation, proliferation, carcinogenesis and wound healing. While Progranu lin acts as growth factor for epithelial cells, fibroblasts and neurons and has anti inflammatory properties, granulins drive inflammation leading to the infiltration of immune cells and induced cytokine expression. The conversion of Progranulin to granulins, which is the critical step in the regulation of the balance between both molecular forms, is controlled by SLPI that binds Progranulin and prevents degrada tion by elastase. The importance of this interaction for the wound healing was demonstrated at the SLPI deficient mice.

The lack of SLPI resulted in higher serine protease derived activities that were associated with impaired wound healing in these animals. The delayed wound healing was normalized after the addi tion of Progranulin providing evidence for the impor tance of the interaction between Progranulin and SLPI. We recently identified a marked down regulation of mucosal SLPI levels in H. pylori infected subjects. The role of SLPI for the balance between Progranulin and granulins and the high prevalence of mucosal inju ries in H. pylori infected subjects, prompted us to study the expression levels of Progranulin in context to that of SLPI in relation to H. pylori status. Considering the role of SLPI for regulating the activity of elastase, we hypothesized that the H.

pylori AV-951 induced reduc tion of SLPI would lead to a reduction of mucosal Progra nulin levels, since the higher elastase activities in the mucosa of H. pylori infected subjects would degrade the molecule into the granulin fragments. In addition, gastric epithelial cells were used as in vitro model to prove the proposed hypothesis. Methods Study design and H. pylori status The study protocol was conducted according to the declaration of Helsinki and approved by the ethics com new product mittee of the Otto von Guericke University as well as government authorities, all participants signed informed consent before entering the study. Detail

ntrifugation at 21,000 g for 10 minutes The cleared supernatant

ntrifugation at 21,000 g for 10 minutes. The cleared supernatant was incubated with 10 ug BORIS antibody coupled to dynabead protein A for 1 2 hours at 4 C. After extensive washes with buffer D, 0. 1 U ml of RNaseOut, 0. 02% NP 40 and 0. 25% Triton X 100 the bead protein complex was incubated with Dasatinib order 50 units of DNase 1 containing 100 units of RNase OUT for 5 minutes at 37 C. An equal volume of pro teinase K containing buffer was added and incubated for another 15 minutes at 37 C. RNA was extracted with standard phenol chloroform procedure and precip itated with 2 ul of glycogen. The RNA was used for either hybridization to Affyme trix U133 plus 2. 0 expression arrays or for RT qPCR verification of BORIS target transcripts. For array ana lysis, double stranded cDNA was synthesized from 1.

5 5 ug total RNA using the Affymetrix One cycle cDNA synthesis kit following the manufacturers instructions. Synthesis of Biotin labeled cRNA was per formed using the Affymetrix GeneChip IVT labeling kit followed by purification with the sample cleanup mod ule. Labeled cRNA was then fragmented and hybridized to Affymetrix GeneChip Human Genome U133Plus 2. 0 arrays overnight. Hybridisation and scanning was performed in house at Barts Cancer Institute. For RT qPCR analysis, RNA in the IP material was reverse transcribed to cDNA using superscript III following the manufacturers instructions. Quantitative real time PCR was performed on ABI7500 equipment using gene specific primer pairs and amplification condi tion of 2 min at 50 C, 10 min at 95 C, and then 40 cycles of 15 secs at 95 C and 45 secs at 60 C.

Total RNA was isolated using silica based spin column extraction kit follow ing the manufacturers protocol. Total RNA was treated with RNase free DNase1 to reduce genomic DNA contamination. RNA integrity was evaluated using the Agilent Bioanalyzer. Two micrograms of total RNA was reverse transcribed with SuperScriptase III using Oligo dT primers or random hexamers ac cording to the manufacturers protocol. Negative controls contained RNase free water substituted for re verse transcriptase. Recombinant BORIS purification The mammalian expression plasmid pM49 T4738 car ries BORIS with an N terminal HaloTag. Adherent HEK293T cells were transfected using Lipofectamine 2000 using standard methods. Cells were cultured for 48 h prior to harvest.

Media were aspirated and cells washed in cold PBS before removal GSK-3 by cell scraping. Cells were centrifuged at 2000 �� g for 5 min. The cell pellet containing over expressed HaloTag BORIS was stored at ?80 C overnight. The cell pellet was lysed in lysis buffer supplemented with BaculoGold protease inhibitor. HaloTag BORIS was purified as excellent validation per manufacturers protocol. The cell pellet was lysed on ice in 1 ml of lysis buffer per 2 �� 107 cells for 10 minutes, followed by 5 min pulse sonication using Diagenodes Bioruptor 3 min. Crude lysate was centrifuged at 10,000 �� g for 30 min. The resulting cleared lysate was mixed with 100 ml HaloLink re