e., Calyptogena soyoae) at 1,100 m depth off Hatsushima Island, in Sagami Bay (34��59.97��N, 139��13.69��E; central Japan). The video-camera was continuously new product acquiring images in a time-lapse mode (i.e., a frame each 4 s) under a constant source of illumination (i.e., six white-light lamps). Videos were stored on VH-S videotapes and their processing in relation to behavioural rhythms was never attempted before. We selected long lasting continuous 10 years-old footage for the technological challenge of performing automated video-image analysis on videos lacking digital standards. The footage was digitized and partitioned into frames at a rate equivalent to the frequency of video recording. Footage processing and video-image analysis were both carried out with MatLab 7.1.2.2.

Video-image AnalysisMotion detection procedure Inhibitors,Modulators,Libraries identified animals based on their displacement through consecutive frames [14-17]. In this process, the quality of extracted information depends upon several contingent factors typical of the deep-sea context [9]. Firstly, the detection of movement depends upon the rate of image acquisition in comparison to the speed of animals’ motion. Secondly, a source of continuous white illumination, gradually decreasing over the distance (i.e., within 3�C4 m) is always present during filming operations. This may impair animal detection depending on its positioning within the camera field. Thirdly, consistent water turbidity is often present (i.e., high-contrast organic debris as ��marine snow��), creating difficulties in the automated identification of moving animals.

Inhibitors,Modulators,Libraries Fourthly, different species possess different shapes that are also variables according to animal displacement within the camera filed.In spite of all these considerations, an automated video-image analysis protocol was developed according to two major steps: (1) animals’ motion detection, by means of image extraction; (2) animals’ recognition within different species categories, by multivariate morphometric techniques such as Fourier Descriptors (FD) and the Supervised Standard Inhibitors,Modulators,Libraries K-Nearest Neighbours (KNN) analyses. A flow chart specifying Inhibitors,Modulators,Libraries the different steps involved in the automated procedure is illustrated in Figure 1.Figure 1.Flow chart representing the different steps involved in the automated procedure.2.3.

Animals’ Motion DetectionAutomated video-image analysis for the tracking of movement was based on combined frame subtraction and a multiple filtering procedure (Figure 2).Figure 2.The consecutive stages of automated video-image analysis for the tracking of movement. Entinostat A frame is firstly subtracted by its consecutive (A). The image without sensible objects is used for background subtraction (B), which occurs within a region of interest …We applied a high throughput screening simple algorithm in order to subtract the current image for a background image of reference.

For further details of table 1 the mode assignment, we refer to the literature [11].The advantage of using these approximations, which deviate from the exact solutions only by an error of the order of ��?1, is simply that equations 1 comprise analytical functions that can be easily implemented into a fitting routine for simultaneous determination of the parameters ��, m, and R, while calculation of the exact solutions involves a tedious numerical procedure, Inhibitors,Modulators,Libraries incl. the multiple use of Bessel functions, whose application in a fitting algorithm is presently not feasible on a personal computer.For determination of the parameters, the spectra obtained were first fitted by means of Voigt profiles applying either linear or 4th order background correction.

We used Voigt profiles instead of Lorentzians Inhibitors,Modulators,Libraries to account for a potentially present small inhomogeneous broadening imposed by small deviations of the beads�� shape from sphericity [18]. In particular for larger beads with sizes of about 10 ��m it is important to fit all modes simultaneously including proper background correction, because Inhibitors,Modulators,Libraries some higher order modes with bandwidths of several nanometers [1] contribute to the background and have to be accounted for by use of additional Voigt profiles and occasionally by applying a non-linear background correction. Two examples of the peak fitting procedure are given in Figure 1 for illustration.Figure 1.Illustration of the fitting of Voigt profiles and linear background correction to the measured WGM spectra for determination of mode positions and bandwidths. (a) Spectrum of the R = 4.

9 ��m bead at a fluid index, nfl = 1.370. (b) Spectrum of the …With the measured mode positions, Inhibitors,Modulators,Libraries �ˡ�iTM and �ˡ�iTE, precisely determined, the free parameters of Equation 1, which are �� (or alternatively, ), m (or alternatively, ne), Brefeldin_A and R, can be fitted by minimizing the deviation between measured and calculated mode positions:��=��i,j|�ˡ�iTM?��iTM(q=1,?i,R,m)|+|�ˡ�jTM?��jTM(q=1,?j,R,m)|(2)The only ambiguity in applying Equation 2 is related to the classification of the measured modes into TM and TE modes. This issue, however, can be easily resolved by applying Equation 1 to some approximate values for the parameters ��, m, and R, which then shows that for polystyrene beads of few micrometers in diameter in an aqueous ambient, TM and TE modes of same mode number show up in the spectra as well-separated pairs with �ˡ�?TM<�ˡ�?TE, thus allowing an assignment by eye (cf.

, e.g., mode assignments in Figure 1). An initially chosen wrong assignment would further lead to an unsatisfying residual deviation �� within the relevant parameter range.On this basis, the free parameters were determined from the EPZ-5676 order experimental WGM spectra at a precision of three digits for bead radii and four digits for refractive indices. Mode numbers were obviously determined as integers.3.

The Au capacitance plates are fabricated directly onto the glass substrate to form the capacitor with the low-resistivity silicon resonator, of which the resistivity U0126 cost is between 0.001 ��?cm and 0.004 ��?cm.Figure 1.Structure of the MEMS torsional resonant magnetometer.The operation principle is illustrated in Figure 2. If a DC current I is introduced into the excitation coil and a magnetic flux-density Bx in x-direction is presented, for one turn of the excitation coil with length Lc in y-direction, the Lorentz forces perpendicular to the silicon plane are:FL=I?Lc?Bx(1)The Lorentz Inhibitors,Modulators,Libraries forces are generated on both sides of the resonator with opposite directions. Therefore the torque caused by the Lorentz forces is of the same direction, which twists the torsional beams.Figure 2.

Operation principle of the MEMS torsional resonant magnetometer.If a sinusoidal current shown in (2) passes through the excitation coil instead of a DC current, the silicon Inhibitors,Modulators,Libraries resonator will vibrate around the torsional beams due to the alternating directions of the Lorentz force FL in (3):i=I0 sin 2�� ft(2)FL=i?Lc?Bx=I0LcBx sin 2�� ft(3)When the frequency f of the current Inhibitors,Modulators,Libraries is equal to the resonant frequency of the silicon resonator, the vibration amplitude will dramatically increase due to the resonance and the high quality factor of the structure. Then this vibration amplitude will be converted into the differential change of the two sensing capacitances as shown indicated in Figure 2. Here, a capacitance detection circuit could be used to measure the capacitance change that reflects the value of the magnetic flux-density [3].

For the Lorentz Force Magnetometer, the input is the magnetic flux-density Bx in x-direction and the output is the capacitance change ��C. The transfer function can be expressed as in (4):��C=SM S�� SC Bx=?M?B??��?M??(��C)?��?Bx(4)Here, SM, S and SC respectively stand for the transfer function from the magnetic flux-density Inhibitors,Modulators,Libraries B to the excitation torque M, from the excitation torque M to the torsional angle , and from the torsional angle to Anacetrapib the capacitance change ��C. When the structural parameters of the resonant magnetometer are determined, it can be proved that SM, S and SC are approximately constant under small deflection condition [6]. Therefore, the capacitance change ��C has a linear relationship with the magnetic flux-density Bx.

meantime The output signal of the capacitance detection circuit can accurately represent the magnetic flux-density Bx in x-direction when the torsional angle of the resonator is in an appropriate range. For instance, when the resonator surface area S is 3,000 ��m �� 2,000 ��m and the capacitance plate distance d0 is 15 ��m, the linearity of the sensor can be within 1.0% when the rotation angle does not exceed 6 �� 10?4 rad.3.?Fabrication ProcessThe fabrication process of the prototype is based on the anodic bonding of low-resistivity silicon and a Pyrex glass substrate.

In this study, we have labeled L6 cells with IgG conjugated QDs in 4 ��C. The experimental time was reduced by using QD-IgG conjugates. The GLUT4-QD complex was located on PM and internalization of GLUT4 selleck chem inhibitor can be observed after this simplified labeling procedure. Coupled with Andor Revolution XD laser confocal microscope system, three dimensional trajectory of GLUT4 in live L6 cells can be observed clearly in real time.2.?Materials and Methods2.1. MaterialsAnti-c-myc monoclonal antibody 9E10 and Qdot 605 goat anti-mouse IgG conjugate were purchased from Invitrogen. L6-GLUT4myc Inhibitors,Modulators,Libraries cells were provided by Prof. Amira Klip, the Hospital for Sick Children (Toronto, Ontario, Canada). GLUT4-EGFP plasmid was provided by Prof. Tao Xu (Institute of Biophysics of the Chinese Academy of Sciences, Beijing, China).

Other chemicals were purchased from Invitrogen.2.2. Cell Inhibitors,Modulators,Libraries CultureL6-GLUT4myc myoblasts were cultured in ��-MEM supplemented with 10% fetal bovine serum and 1% antibiotic at 37 with 5% CO2.2.3. Labeling GLUT4myc Molecular with QDsL6-GLUT4myc cells were seeded in growth medium (��-MEM, 10% fetal bovine serum, and 1% antibiotic) at 30�C40% confluence the previous day. They were starved with depletion medium (��-MEM and Inhibitors,Modulators,Libraries 1% antibiotic) for 3 h at 37 ��C prior to experimentation to enhance the effect of insulin stimulation. Then, they were stimulated with 100 nM insulin at 37 ��C for 20 min. Later, they were blocked with 5% goat serum in ��-MEM containing 100 nM insulin for 10 min at 37 ��C and then incubated with anti-myc monoclonal antibody 9E10 (with an initial concentration of 0.

5 mg/mL, 1:100 diluted in ��-MEM) containing 100 nM insulin for 1 h at 37 ��C. Unbound antibody was aspirated away and the cover slips were washed three times with ice-cold ��-MEM containing 100 nM insulin at 4 ��C. Later, they were blocked with 5% goat serum in ��-MEM containing 100 nM Inhibitors,Modulators,Libraries insulin for 10 min at 4 ��C and incubated with Qdot 605 goat anti-mouse IgG conjugate Batimastat (with an initial concentration of 1 ��M, 1:50 diluted in ��-MEM) containing 100 nM insulin for 1 h at 4 ��C. Unbound Qdot-IgG was aspirated away and the cover slips were washed five times with ice-cold ��-MEM containing 100 nM insulin at 4 ��C. Finally, the cells were cultured in growth medium at 37 ��C for imaging. For control, two groups were prepared.

One group was stimulated with insulin and then incubated research use only with QD-IgG diluted in growth medium containing 100 nM insulin for 1 h at 4 ��C, the primary antibody 9E10 was omitted during the labeling procedure in this group. Another group was not stimulated with insulin and insulin was absent throughout the labeling procedure.2.4. Transfection with GLUT4-EGFPL6-GLUT4myc cells were seeded in growth medium (��-MEM, 10% fetal bovine serum, and 1% antibiotic) at 80% confluence prior to experimentation. For each chamber, 0.8 ��g GLUT4-EGFP plasmid was diluted into 50 ��L OMEM without fetal bovine serum.

The cluster head broadcasts its status to the other sensors in the network. Each sensor selleckbio node determines to which cluster it wants to belong by choosing the cluster head that requires the minimum communication energy. Once all the nodes are organized into clusters, each cluster head creates a schedule for the nodes in its cluster. This allows the radio components of each non-cluster-head node to be turned off at all times except during its transmit time, thus minimizing the energy dissipated in the individual sensors.2.2. Cooperative CommunicationThe physical phenomena monitored by sensor networks, e.g., forest temperature, water contamination, usually yield sensed data that are strongly correlated. Data aggregation is the tool by which the correlated data size can be significantly reduced depending on the correlation factor.
Figure 2 explains the cooperative communication where the sensors at cluster 1 send the information data to the cluster head os cluster 2. At the first step, the sensors at cluster 1 send the data to their cluster head. The cluster head then aggregates the data in the second step. After the aggregation, the cluster head send the aggregated data back to all the sensors in that cluster. This is the step three in cooperative communication. At this stage, all the sensors at cluster 1 have the same information data. At the fourth step, the sensors transmit the aggregated data to the cluster 2. After receiving the data at the receiving cluster, sensors at cluster 2 transmit the received data to their cluster head locally and complete the cooperative communication.
Figure 2.Cooperative communication.3.?Error Correction Codes in Wireless Sensor NetworkError control coding (ECC) introduces redundancy into an information sequence u of length k by the addition of extra parity bits. Several different types of ECC exist, but we may loosely categorize them into two divisions: (1) block codes, which are of a fixed length nC, with nC ? k parity bits, and are decoded into one block or codeword at a time; (2) convolutional codes, which, for a rate Batimastat k/nC code, input k bits and output nC bits at each time interval, but are decoded in a continuous stream of length L >> nC. Block codes include repetition codes, Hamming codes [17], Reed Solomon codes, and BCH codes [18].
Short block codes like Hamming codes can be decoded by syndrome decoding or maximum likelihood (ML) decoding by either decoding to the nearest codeword or decoding on a trelli
In many applications such as manufacturing, distribution logistics, access control, and healthcare, the ability to uniquely identify, real-time product track, useful handbook locate and monitor individual objects is indispensable for efficient business processes and inventory visibility. The use of radio-frequency identification (RFID) technology has simplified the process of identifying, tracking, locating and monitoring objects in many applications.

The dimensions of the treated crane rail are relatively small. In practice crane rails of much larger dimensions are encountered. The required measurement precisions are adequately higher. The proposed approach can therefore obviously be performed only if we can use a total station of the highest precision possible.2.2. Signalization of Detail Points����L�� Platform with PrismsA special platform (Figure 1) is used for the signalization of detail points. It consists of a holder and two precise prisms force-centered on it. The holder is made of an L-shaped 2 cm thick iron profile. It is 6.5 cm wide and its arms are 7 and 14 cm long. Adapters for precise prisms are attached at both outer surfaces. At the edge a circular level is fixed to the holder to ensure the horizontality of the platform.Figure 1.
��L�� platform for point signalization and its constants.The position of the characteristical point, representing the upper inner edge of the rail, can be derived from the measured positions of both precise prisms. Accurate dimensions of the platform need to be known, i.e., offset of both prisms from the edge of the rail.2.2.1. Calibration of the ��L�� Platform and Characteristic Point DeterminationEach setting of the platform onto a crane rail provides us with two prism center points. We want to represent each setting with one characteristical point. The position of a characteristic point is shown in Figure 1. The centers of measuring prisms are uniquely determinable. The centers of the prisms and the characteristic point lie in the common vertical plane.
The coordinate system is defined in such a way that it allows the computation of the characteristic point using the upper prism:[xKT1yKT1zKT1]=[x1?dx1y1z1?dz1](5)or using the side prism:[xKT2yKT2zKT2]=[x2?dx2y2z2?dz2].(6)Indexes 1 and 2 will hereafter represent the upper (5) and the side (6) prism, respectively. Two computation modes provide us the control and accuracy evaluation of the characteristical point. For such computation parameters, dx1, Anacetrapib dz1, dx2, dz2 defining the geometry of the
As one of the most promising strain and temperature sensors, the fiber Bragg grating (FBG) has attracted considerable attention due to its novel properties such as small size, fiber compatibility, immunity to electromagnetic interference, and multipoint sensing capability [1,2].
To implement a multiple FBG sensor network, various methods such as wavelength division multiple access (WDMA), time division multiple selleck chemicals Tofacitinib access (TDMA), and code division multiple access (CDMA) have been reported. The primary advantage of using an FBG as a sensor is that a large number of sensors can be integrated along a single fiber [3]. In the WDMA system, the maximum number of sensors is determined by the usable spectral bandwidth of the system and the wavelength shift of each sensor [4].

However, the calibration operated throughout these applications is often imprecise in relation to the scientific needs for colorimetric quantification [30]. selleckchem A colorimetric calibration is therefore often carried out by combining different polynomial algorithms, multivariate statistics, and neural networks approaches [20]. All of these procedures can successfully reduce the external noise to different extents, pointing out that both the camera settings and its sensor’s response to light play a crucial role for objective color quantification.In this context, the present study introduces a novel colorimetric calibration approach that aims to minimize the effects of the illuminants, camera characteristics and settings. Color image calibration was implemented according to a novel approach: the 3-dimensional sRGB Thin-Plate Spline interpolation (TPS-3D).
The calibration efficiency of this method was compared with the one obtained through the use of a widely used commercial software (i.e., ProfileMaker) as well as with that obtained by multivariate linear regression (Partial Least Squares).2.?Experimental SectionThe Drug_discovery images utilized in this study come from four markedly different operative field and laboratory contexts, in which different devices and lighting conditions occurred or were artificially created.2.1. Calibration/Validation Setup ExperimentIn order to explore the device variability and resolution, two different cameras were used: (i) a commercial high resolution compact Nikon Coolpix P6000, (13.5 real MP-CCD 4.
67�� sensor) with selleck inhibitor optical 4�� NIKKOR lens, providing TIFF 8 bit images (from NRG RAW format) with good macro features (manual white balance control, exposure and metering methods were enabled); (ii) aprofessional high resolution reflex Canon 30D (with a 8.2 real MP CMOS 1.6�� APS-C sensor) with a Canon 10�C22 mm f/3.5�C4.5 ens (used at 22 mm, equivalent to 35.2 mm on a full-frame sensor) providing TIFF 8 bit images (from CR2 RAW format). For both devices, white balance, metering method and exposure were manually defined, while ISO sensitivity was set to the minimum.For each sensor, three consecutive pictures were acquired under four different light conditions: (i) 200 watt Tungsten bulbs (5,000�� K) (T); (ii) 200 watt weakened Tungsten bulbs plus neon tubes plus environmental light (wTNE); (iii) neon tubes plus environmental light (NE); (iv) full sun (i.e., at midday; 6,500�� K) (S). Pictures for the color calibration setup have been taken with three inside altogether different color checkers: the GretagMacbeth ColorChecker SG 140 color-patches, the GretagMacbeth ColorChecker 24 color-patches and the IFRAO Standard ColorChecker 7 color-patches.2.2.

In comparison to classical input or output grating couplers, GMR optical biosensors differ distinctly from traditional sensors in their operational principle and functionality [4,5]. Gemcitabine FDA Wawro et al. presented a method using fiber optic sensor integrating dielectric diffraction gratings and thin films on optical fiber endfaces for biomedical sensing applications [6]. In2002, Cunningham et al. discussed the use of these resonant elements as biosensors, capable of resolving changes of 0.1 nm in a sample. They also make it possible to quickly measure a large number of molecular interactions taking place simultaneously upon a grating surface. Moreover, they can monitor reactions in real time [7�C10]. Furthermore, Cunningham et al. improved the sensitivity by changing the GMR structure [8].
The polarization of the incident light is a key factor in the sensitivity of this kind of optical biosensor. Magnusson et al. emphasized polarization-based parametric discrimination and presented that resonant sensors can be designed to support two or more leaky modes in the spectral band of interest [11]. Electric field distribution analysis (EFDA) can reveal the difference the Transverse Electric (TE) and Transverse Magnetic (TM) modes have on sensitivity. This article presents a comparison of sensitivity in the TE and TM modes using EFDA. It is found that sensitivity in the TM mode is three times that achieved in the TE mode.Magnusson and Lee introduced a phase modulation method [12,13], which is more complex than the amplitude modulation method, so the amplitude method is used in this article.
When molecules are attached to the surface, the reflected wavelength (color) is shifted due to a change in the optical path of light that is coupled into the grating. In this article, the appropriate parameters of a GMR biosensor structure are determined and the sensitivity of the different modes of incident light is shown. Then the sensitivity of the TE and TM modes of incident light is compared by the EFDA.2.?ModelThe structure of the GMR optical biosensor is shown in Figure 1. From top to bottom, the GMR optical biosensor includes a cover layer (air), a sample layer (biological samples, such as protein molecules), a grating layer, a waveguide layer, and a substrate layer (quartz glass).
Based on the theory of the optical waveguide, the effective Carfilzomib index of the i-th order diffracted wave should be in the range followed with Equation (1) in [14]:maxnc,ns��|��i/k0|=|ncsin��-i��/��|Ganetespib cancer �� = 500 nm, dw = 101 nm, dg = 120 nm.Here, nc and ns are the refractive index of the sample layer and the substrate, �� is the propagation constant, k0 is the wave number, �� is the incident angle, �� is the resonant wavelength, and �� is the period of the grating layer.

Other auction-based techniques have also been applied in [6]. Such thereby methods are likely to show similar performance to the most popular and efficient utilities approach.The utilities approach was introduced by Burgard et al. in [9]. The essence is to compute a distance cost towards each frontier and then update the utilities of neighboring frontiers according to greedy assignments of the teammates. This work has been enhanced by using machine learning such as clustering frontiers [11] and learning typical indoor environments [2,14] for more certain mapping and better goal point assignment. The best work in terms of efficient exploration and algorithm complexity reports an O(n2T) for greedy frontier allocation for n robots and T frontiers, and optimal allocation with up to O(T!(T?n)!), without considering any additional processing [1].
On the other hand, some works have focused on determining costs that try to minimize the uncertainty of the process. In [16] the idea is to keep the robots in line of sight so that they can help each other to accurately localize while each one navigates in a round-robin process. If robots tend to go out of range, then a rendezvous is scheduled. In [15], the goal is to assign targets that are estimated to reduce the odometry error. Balch and Arkin in [19] propose an anchored random exploration such that every robot remains inside communication range. Nevertheless, even when these works have similar results to the utilities technique and have the advantage of improving the overall accuracy of the map, they have the disadvantage of keeping the robots in close proximity, which can increase the exploration time by preventing the robots from efficiently spreading.
Other works include [8,24] in which they leverage the work in [9] by including communication limits in the cost Entinostat function and allocating frontiers within a bidding process. Also, in [17], an inside-communication technique demonstrates similar results to the work in [19]. Moreover, with the same rendezvous idea of [16], researchers propose in [18] a role-based technique for allowing robots to explore distant areas
Methane is the main component of coal mine gas and natural gas, and it is closely connected with the people’s daily activities and life. Since methane gas is inflammable and explosive, it is important to accurately detect the concentration of methane gas. Methane detectors may be classified into two categories based on their applications. One is mainly used to alarm for the explosion of methane. Since the low explosive level (LEL) concentration of methane is 5%, detectors for this purpose usually do not require a high Wortmannin side effects resolution or a very low detection limit. The other is focused on detecting very low concentrations of methane (ppm level).

, on the other hand, is found in at least three of the six eukaryo tic supergroups and was likely present in the LCEA. This suggests that selleck chemical the evolution of mART activity within the PARP gene family occurred before the full complement of crown groups had formed. In addition, the changes in the catalytic domain of the Clade 2 proteins also suggest that these proteins have altered enzymatic activities. Therefore, it is likely that mART activity and or loss of enzymatic activity has evolved at least twice from PARP activity and that mART activity in extant Clade 6 proteins represents an even earlier acquisition of this enzymatic activity. What functions do PARP like mART proteins play While no members of Clade 6 have been characterized, several members of Clade 3 have, all in mammalian sys tems.

PARP9 BAL1, PARP14 BAL2, and PARP15 BAL3 have been shown to interact with transcription factors and mediate transcriptional repression or activation. PARP13 ZCC2 ZAP has been shown to bind to viral RNA through its zinc fingers and promote degradation of the RNA by the exosome. PARP12 shares significant similarity to PARP13 and is thought to function similarly. PARP10 interacts with MYC and inhibits transformation, its overexpression leads to a loss of cell viability. To date, no clear consensus about the function of Clade 3 proteins can be formulated. True tankyrases are confined to animals Human tankyrase1 was originally identified as a telo meric protein interacting with TRF1, a negative regula tor of telomere length. It was shown to act as a PARP and automodify itself as well as TRF1.

A second human tankyrase, tankyrase2, was identified shortly after the initial discovery of tankyrase1. Human tankyrases can be found both in the nucleus, at the nuclear pore and centrosome, and in the cytoplasm associated with the Golgi or vesi cles or the plasma membrane. Since their initial discovery, the known functions of these proteins have expanded to include spindle assembly and vesicle trafficking, sister chromatid segrega tion, and regulation of the WNT pathway. Tankyrases have been identified in a number of animal species, including mouse. In this model organ ism, it appears tankyrase may not function in telomere length control, but its other functions are con served and its function is essential.

Consistent with functions outside of the telomere, a tankyrase is found in Drosophila melanogaster, Anacetrapib an organism with a highly divergent telomere consisting of transposons rather than the short repeats found in other eukaryotes. Our more phylogenetic tree places a number of proteins previously reported as tankyrases in Clade 1, rather than within Clade 4. These proteins do have a different domain structure than tankyrases, shar ing ankyrin repeats with tankyrases but having WGR and PRD domains rather than SAM motifs. It is likely that the Clade 1 ankyrin repeat proteins do not share functions with tankyrases. PME5 from C. elegans was reported as a tankyrase and has been function